diff --git a/SK_ring-relabelling-secondattempt.ipynb b/SK_ring-relabelling-secondattempt.ipynb index bfbe813..3d7219a 100644 --- a/SK_ring-relabelling-secondattempt.ipynb +++ b/SK_ring-relabelling-secondattempt.ipynb @@ -52,7 +52,7 @@ "outputs": [], "source": [ "import numpy as np\n", - "from scipy import linalg\n", + "from scipy import linalg, sparse\n", "from mpl_toolkits.mplot3d import Axes3D\n", "import matplotlib.pyplot as plt\n", "import cv2\n", @@ -402,138 +402,138 @@ "output_type": "stream", "text": [ "trying shift by -20 pmt columns\n", - "image 801 has reduced yaw error from 25.534564070251704 to -21.934994502088838\n", + "image 801 has reduced yaw error from 25.534564070251655 to -21.93499450208874\n", "trying shift by -16 pmt columns\n", - "image 801 has reduced yaw error from 25.534564070251704 to -11.638805107025306\n", + "image 801 has reduced yaw error from 25.534564070251655 to -11.638805107025407\n", "trying shift by -12 pmt columns\n", - "image 792 has reduced yaw error from 14.869267113523073 to -13.929434613176237\n", - "image 800 has reduced yaw error from 17.79011388762643 to -11.11299060962441\n", - "image 801 has reduced yaw error from 25.534564070251704 to -2.5828689006216994\n", - "image 901 has reduced yaw error from 16.88525102662485 to -11.61049137305415\n", + "image 792 has reduced yaw error from 14.869267113523073 to -13.929434613176287\n", + "image 800 has reduced yaw error from 17.79011388762643 to -11.112990609624687\n", + "image 801 has reduced yaw error from 25.534564070251655 to -2.5828689006212926\n", + "image 901 has reduced yaw error from 16.88525102662485 to -11.610491373054382\n", "trying shift by -8 pmt columns\n", - "image 788 has reduced yaw error from 15.564220899694183 to -6.457165387096472\n", - "image 791 has reduced yaw error from 12.548390511040258 to -6.089132751112064\n", - "image 792 has reduced yaw error from 14.869267113523073 to -5.089431404768282\n", - "image 793 has reduced yaw error from 12.03422669051545 to -6.681564332362487\n", - "image 794 has reduced yaw error from 14.07930665890146 to -5.240368375612933\n", - "image 795 has reduced yaw error from 12.728290912476995 to -6.441755830408477\n", - "image 796 has reduced yaw error from 14.466774585053194 to -4.549337492763155\n", - "image 797 has reduced yaw error from 11.759535955204232 to -7.209335153884957\n", - "image 798 has reduced yaw error from 18.798585444158483 to -11.902804694198567\n", - "image 799 has reduced yaw error from 14.576661098634967 to -5.195391742530237\n", - "image 800 has reduced yaw error from 17.79011388762643 to -1.3336718201144266\n", - "image 801 has reduced yaw error from 25.534564070251704 to 7.105197019874885\n", - "image 901 has reduced yaw error from 16.88525102662485 to -2.7235447288878456\n", - "image 902 has reduced yaw error from 12.268083204891818 to -6.168140158035983\n", - "image 903 has reduced yaw error from 12.935193475098343 to -7.86710412719839\n", + "image 788 has reduced yaw error from 15.564220899694183 to -6.457165387097693\n", + "image 791 has reduced yaw error from 12.548390511040258 to -6.089132751112268\n", + "image 792 has reduced yaw error from 14.869267113523073 to -5.089431404768028\n", + "image 793 has reduced yaw error from 12.03422669051545 to -6.681564332362334\n", + "image 794 has reduced yaw error from 14.07930665890146 to -5.240368375612831\n", + "image 795 has reduced yaw error from 12.728290912476995 to -6.441755830408375\n", + "image 796 has reduced yaw error from 14.466774585053194 to -4.54933749276285\n", + "image 797 has reduced yaw error from 11.759535955204232 to -7.209335153885261\n", + "image 798 has reduced yaw error from 18.798585444158483 to -11.902804694198823\n", + "image 799 has reduced yaw error from 14.576661098634967 to -5.195391742530618\n", + "image 800 has reduced yaw error from 17.79011388762643 to -1.3336718201145794\n", + "image 801 has reduced yaw error from 25.534564070251655 to 7.105197019874682\n", + "image 901 has reduced yaw error from 16.88525102662485 to -2.723544728887642\n", + "image 902 has reduced yaw error from 12.268083204891818 to -6.168140158035958\n", + "image 903 has reduced yaw error from 12.935193475098343 to -7.867104127198415\n", "trying shift by -4 pmt columns\n", - "image 761 has reduced yaw error from 9.30112544770821 to -0.35049228325057175\n", - "image 762 has reduced yaw error from 5.3375145732522755 to -3.8808238269710715\n", - "image 786 has reduced yaw error from 6.392813797382068 to -2.795172181506747\n", - "image 787 has reduced yaw error from 8.444697705952972 to -1.7768025015562394\n", - "image 788 has reduced yaw error from 15.564220899694183 to 2.9247321886789055\n", - "image 790 has reduced yaw error from 9.623939372048554 to 0.3375224599607775\n", - "image 791 has reduced yaw error from 12.548390511040258 to 3.246094160841288\n", - "image 792 has reduced yaw error from 14.869267113523073 to 5.332909106495658\n", - "image 793 has reduced yaw error from 12.03422669051545 to 1.9717774124038068\n", - "image 794 has reduced yaw error from 14.07930665890146 to 4.195452541882016\n", - "image 795 has reduced yaw error from 12.728290912476995 to -2.228829475686343\n", - "image 796 has reduced yaw error from 14.466774585053194 to 4.970430127682494\n", - "image 797 has reduced yaw error from 11.759535955204232 to 1.647307996142614\n", - "image 798 has reduced yaw error from 18.798585444158483 to -2.912578325286001\n", - "image 799 has reduced yaw error from 14.576661098634967 to 4.295629687400236\n", - "image 800 has reduced yaw error from 17.79011388762643 to 7.974090527465735\n", - "image 801 has reduced yaw error from 25.534564070251704 to 16.759710594154686\n", - "image 901 has reduced yaw error from 16.88525102662485 to 7.245055581358396\n", - "image 902 has reduced yaw error from 12.268083204891818 to 3.2155426509939313\n", - "image 903 has reduced yaw error from 12.935193475098343 to 1.6445283340622998\n", + "image 761 has reduced yaw error from 9.30112544770821 to -0.3504922832506481\n", + "image 762 has reduced yaw error from 5.3375145732522755 to -3.880823826971122\n", + "image 786 has reduced yaw error from 6.392813797382068 to -2.7951721815065436\n", + "image 787 has reduced yaw error from 8.444697705952972 to -1.776802501555934\n", + "image 788 has reduced yaw error from 15.564220899694183 to 2.924732188678855\n", + "image 790 has reduced yaw error from 9.623939372048554 to 0.33752245996072666\n", + "image 791 has reduced yaw error from 12.548390511040258 to 3.2460941608411353\n", + "image 792 has reduced yaw error from 14.869267113523073 to 5.33290910649576\n", + "image 793 has reduced yaw error from 12.03422669051545 to 1.971777412404163\n", + "image 794 has reduced yaw error from 14.07930665890146 to 4.1954525418822195\n", + "image 795 has reduced yaw error from 12.728290912476995 to -2.228829475686241\n", + "image 796 has reduced yaw error from 14.466774585053194 to 4.970430127682596\n", + "image 797 has reduced yaw error from 11.759535955204232 to 1.6473079961425123\n", + "image 798 has reduced yaw error from 18.798585444158483 to -2.912578325285187\n", + "image 799 has reduced yaw error from 14.576661098634967 to 4.295629687400338\n", + "image 800 has reduced yaw error from 17.79011388762643 to 7.97409052746543\n", + "image 801 has reduced yaw error from 25.534564070251655 to 16.759710594154534\n", + "image 901 has reduced yaw error from 16.88525102662485 to 7.245055581358599\n", + "image 902 has reduced yaw error from 12.268083204891818 to 3.215542650994237\n", + "image 903 has reduced yaw error from 12.935193475098343 to 1.6445283340621728\n", "trying shift by 0 pmt columns\n", - "image 755 has reduced yaw error from -0.8733408316600104 to -0.8113443500277746\n", - "image 756 has reduced yaw error from -2.206310049943644 to -2.1711641468427385\n", - "image 757 has reduced yaw error from -3.9486105703258785 to -3.8601596864757135\n", - "image 759 has reduced yaw error from 1.5448980440476894 to 1.5173562963412721\n", - "image 760 has reduced yaw error from -0.9048894730781343 to -0.7079178341951331\n", - "image 761 has reduced yaw error from 9.30112544770821 to 9.258495486193825\n", - "image 765 has reduced yaw error from 0.9720725289686496 to 0.9021502151679314\n", - "image 770 has reduced yaw error from -6.06865366148957 to -5.65677400006745\n", - "image 772 has reduced yaw error from 0.36406020614971357 to 0.2703696487224636\n", - "image 774 has reduced yaw error from -0.9957703639144924 to -0.8015841333587035\n", - "image 777 has reduced yaw error from -1.2359467482922037 to -1.0911778019043779\n", - "image 778 has reduced yaw error from 0.736533679267461 to 0.5446979258296363\n", - "image 779 has reduced yaw error from 2.9529519959647037 to 2.394660246786599\n", - "image 780 has reduced yaw error from -4.093534042396289 to -3.3750144318589443\n", + "image 755 has reduced yaw error from -0.8733408316599849 to -0.8113443500275965\n", + "image 756 has reduced yaw error from -2.206310049943644 to -2.171164146842535\n", + "image 757 has reduced yaw error from -3.9486105703258785 to -3.8601596864758916\n", + "image 759 has reduced yaw error from 1.5448980440476894 to 1.5173562963413738\n", + "image 760 has reduced yaw error from -0.9048894730781343 to -0.7079178341952094\n", + "image 761 has reduced yaw error from 9.30112544770821 to 9.258495486193977\n", + "image 765 has reduced yaw error from 0.9720725289686496 to 0.9021502151678296\n", + "image 770 has reduced yaw error from -6.06865366148957 to -5.656774000067678\n", + "image 772 has reduced yaw error from 0.36406020614971357 to 0.2703696487224127\n", + "image 774 has reduced yaw error from -0.9957703639144924 to -0.8015841333586526\n", + "image 777 has reduced yaw error from -1.2359467482922037 to -1.0911778019041742\n", + "image 778 has reduced yaw error from 0.736533679267461 to 0.544697925829509\n", + "image 779 has reduced yaw error from 2.9529519959647037 to 2.3946602467868536\n", + "image 780 has reduced yaw error from -4.093534042396289 to -3.3750144318588933\n", "image 783 has reduced yaw error from 3.718673297236211 to 1.3484422816264277\n", - "image 784 has reduced yaw error from -0.35249692348878453 to 0.16045257397332618\n", - "image 785 has reduced yaw error from 4.0119729660922285 to 3.852979706835748\n", - "image 788 has reduced yaw error from 15.564220899694183 to 14.14351986061233\n", - "image 793 has reduced yaw error from 12.03422669051545 to 11.873932229276773\n", - "image 795 has reduced yaw error from 12.728290912476995 to 12.666579828776431\n", - "image 797 has reduced yaw error from 11.759535955204232 to 11.706651656871612\n", - "image 798 has reduced yaw error from 18.798585444158483 to 5.939572169526795\n", - "image 799 has reduced yaw error from 14.576661098634967 to 13.975177638478932\n", - "image 901 has reduced yaw error from 16.88525102662485 to 16.75158533362732\n", - "image 903 has reduced yaw error from 12.935193475098343 to 11.57223984414676\n", + "image 784 has reduced yaw error from -0.35249692348878453 to 0.16045257397363152\n", + "image 785 has reduced yaw error from 4.0119729660922285 to 3.8529797068357987\n", + "image 788 has reduced yaw error from 15.564220899694183 to 14.143519860611821\n", + "image 793 has reduced yaw error from 12.03422669051545 to 11.873932229276875\n", + "image 795 has reduced yaw error from 12.728290912476995 to 12.666579828776788\n", + "image 797 has reduced yaw error from 11.759535955204232 to 11.706651656870898\n", + "image 798 has reduced yaw error from 18.798585444158483 to 5.939572169527304\n", + "image 799 has reduced yaw error from 14.576661098634967 to 13.97517763847878\n", + "image 901 has reduced yaw error from 16.88525102662485 to 16.75158533362722\n", + "image 903 has reduced yaw error from 12.935193475098343 to 11.572239844147118\n", "trying shift by 4 pmt columns\n", - "image 758 has reduced yaw error from -6.008549540172706 to 3.5824859202839403\n", + "image 758 has reduced yaw error from -6.008549540172706 to 3.5824859202842965\n", "image 768 has reduced yaw error from -5.3072449824569485 to 4.218475724871712\n", - "image 769 has reduced yaw error from -6.748155619138371 to -0.06053580951269085\n", - "image 770 has reduced yaw error from -6.06865366148957 to 3.820397274540782\n", - "image 771 has reduced yaw error from -5.963350067710753 to 2.7258821754416203\n", - "image 798 has reduced yaw error from 18.798585444158483 to 16.258825719054528\n", + "image 769 has reduced yaw error from -6.748155619138371 to -0.06053580951258908\n", + "image 770 has reduced yaw error from -6.06865366148957 to 3.820397274540833\n", + "image 771 has reduced yaw error from -5.963350067710753 to 2.7258821754412894\n", + "image 798 has reduced yaw error from 18.798585444158483 to 16.25882571905412\n", "trying shift by 8 pmt columns\n", "trying shift by 12 pmt columns\n", "trying shift by 16 pmt columns\n", "final shifts:\n", - "image 755: 0 from -0.8733408316600104 to -0.8113443500277746\n", - "image 756: 0 from -2.206310049943644 to -2.1711641468427385\n", - "image 757: 0 from -3.9486105703258785 to -3.8601596864757135\n", - "image 758: 4 from -6.008549540172706 to 3.5824859202839403\n", - "image 759: 0 from 1.5448980440476894 to 1.5173562963412721\n", - "image 760: 0 from -0.9048894730781343 to -0.7079178341951331\n", - "image 761: -4 from 9.30112544770821 to -0.35049228325057175\n", - "image 762: -4 from 5.3375145732522755 to -3.8808238269710715\n", + "image 755: 0 from -0.8733408316599849 to -0.8113443500275965\n", + "image 756: 0 from -2.206310049943644 to -2.171164146842535\n", + "image 757: 0 from -3.9486105703258785 to -3.8601596864758916\n", + "image 758: 4 from -6.008549540172706 to 3.5824859202842965\n", + "image 759: 0 from 1.5448980440476894 to 1.5173562963413738\n", + "image 760: 0 from -0.9048894730781343 to -0.7079178341952094\n", + "image 761: -4 from 9.30112544770821 to -0.3504922832506481\n", + "image 762: -4 from 5.3375145732522755 to -3.880823826971122\n", "image 763: 0 from 3.8499068523592404 to 3.8499068523592404\n", "image 764: 0 from 1.3533676148311151 to 1.3533676148311151\n", - "image 765: 0 from 0.9720725289686496 to 0.9021502151679314\n", + "image 765: 0 from 0.9720725289686496 to 0.9021502151678296\n", "image 766: 0 from -1.3300971262351167 to -1.3300971262351167\n", - "image 767: 0 from -2.2198435986523015 to -2.2198435986523015\n", + "image 767: 0 from -2.219843598652276 to -2.219843598652276\n", "image 768: 4 from -5.3072449824569485 to 4.218475724871712\n", - "image 769: 4 from -6.748155619138371 to -0.06053580951269085\n", - "image 770: 4 from -6.06865366148957 to 3.820397274540782\n", - "image 771: 4 from -5.963350067710753 to 2.7258821754416203\n", - "image 772: 0 from 0.36406020614971357 to 0.2703696487224636\n", + "image 769: 4 from -6.748155619138371 to -0.06053580951258908\n", + "image 770: 4 from -6.06865366148957 to 3.820397274540833\n", + "image 771: 4 from -5.963350067710753 to 2.7258821754412894\n", + "image 772: 0 from 0.36406020614971357 to 0.2703696487224127\n", "image 773: 0 from -0.05209309978998264 to -0.05209309978998264\n", - "image 774: 0 from -0.9957703639144924 to -0.8015841333587035\n", - "image 775: 0 from 1.2005478491241859 to 1.2005478491241859\n", + "image 774: 0 from -0.9957703639144924 to -0.8015841333586526\n", + "image 775: 0 from 1.2005478491241606 to 1.2005478491241606\n", "image 776: 0 from 0.0 to 0.0\n", - "image 777: 0 from -1.2359467482922037 to -1.0911778019043779\n", - "image 778: 0 from 0.736533679267461 to 0.5446979258296363\n", - "image 779: 0 from 2.9529519959647037 to 2.394660246786599\n", - "image 780: 0 from -4.093534042396289 to -3.3750144318589443\n", + "image 777: 0 from -1.2359467482922037 to -1.0911778019041742\n", + "image 778: 0 from 0.736533679267461 to 0.544697925829509\n", + "image 779: 0 from 2.9529519959647037 to 2.3946602467868536\n", + "image 780: 0 from -4.093534042396289 to -3.3750144318588933\n", "image 781: 0 from -1.5219803255064384 to -1.5219803255064384\n", "image 782: 0 from 2.0939359187515483 to 2.0939359187515483\n", "image 783: 0 from 3.718673297236211 to 1.3484422816264277\n", - "image 784: 0 from -0.35249692348878453 to 0.16045257397332618\n", - "image 785: 0 from 4.0119729660922285 to 3.852979706835748\n", - "image 786: -4 from 6.392813797382068 to -2.795172181506747\n", - "image 787: -4 from 8.444697705952972 to -1.7768025015562394\n", - "image 788: -4 from 15.564220899694183 to 2.9247321886789055\n", + "image 784: 0 from -0.35249692348878453 to 0.16045257397363152\n", + "image 785: 0 from 4.0119729660922285 to 3.8529797068357987\n", + "image 786: -4 from 6.392813797382068 to -2.7951721815065436\n", + "image 787: -4 from 8.444697705952972 to -1.776802501555934\n", + "image 788: -4 from 15.564220899694183 to 2.924732188678855\n", "image 789: 0 from -1.7575510813935526 to -1.7575510813935526\n", - "image 790: -4 from 9.623939372048554 to 0.3375224599607775\n", - "image 791: -4 from 12.548390511040258 to 3.246094160841288\n", - "image 792: -8 from 14.869267113523073 to -5.089431404768282\n", - "image 793: -4 from 12.03422669051545 to 1.9717774124038068\n", - "image 794: -4 from 14.07930665890146 to 4.195452541882016\n", - "image 795: -4 from 12.728290912476995 to -2.228829475686343\n", - "image 796: -8 from 14.466774585053194 to -4.549337492763155\n", - "image 797: -4 from 11.759535955204232 to 1.647307996142614\n", - "image 798: -4 from 18.798585444158483 to -2.912578325286001\n", - "image 799: -4 from 14.576661098634967 to 4.295629687400236\n", - "image 800: -8 from 17.79011388762643 to -1.3336718201144266\n", - "image 801: -12 from 25.534564070251704 to -2.5828689006216994\n", - "image 901: -8 from 16.88525102662485 to -2.7235447288878456\n", - "image 902: -4 from 12.268083204891818 to 3.2155426509939313\n", - "image 903: -4 from 12.935193475098343 to 1.6445283340622998\n", + "image 790: -4 from 9.623939372048554 to 0.33752245996072666\n", + "image 791: -4 from 12.548390511040258 to 3.2460941608411353\n", + "image 792: -8 from 14.869267113523073 to -5.089431404768028\n", + "image 793: -4 from 12.03422669051545 to 1.971777412404163\n", + "image 794: -4 from 14.07930665890146 to 4.1954525418822195\n", + "image 795: -4 from 12.728290912476995 to -2.228829475686241\n", + "image 796: -8 from 14.466774585053194 to -4.54933749276285\n", + "image 797: -4 from 11.759535955204232 to 1.6473079961425123\n", + "image 798: -4 from 18.798585444158483 to -2.912578325285187\n", + "image 799: -4 from 14.576661098634967 to 4.295629687400338\n", + "image 800: -8 from 17.79011388762643 to -1.3336718201145794\n", + "image 801: -12 from 25.534564070251655 to -2.5828689006212926\n", + "image 901: -8 from 16.88525102662485 to -2.723544728887642\n", + "image 902: -4 from 12.268083204891818 to 3.215542650994237\n", + "image 903: -4 from 12.935193475098343 to 1.6445283340621728\n", "image 904: 0 from 1.0654016218004685 to 1.0654016218004685\n" ] } @@ -565,7 +565,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 272, "metadata": {}, "outputs": [], "source": [ @@ -576,12 +576,16 @@ "\n", "new_image_feature_locations['796'] = shift_labels(image_feature_locations['796'], -4) # automated relabelling suggested -8\n", "\n", - "new_image_feature_locations['799'] = shift_labels(image_feature_locations['799'], -6) # automated relabelling suggested -4, image looks like off by half supermodule\n" + "new_image_feature_locations['799'] = shift_labels(image_feature_locations['799'], -6) # automated relabelling suggested -4, image looks like off by half supermodule\n", + "\n", + "\n", + "\n", + "new_image_feature_locations['758'] = shift_labels(image_feature_locations['758'], 4) # automated relabelling suggested 4\n" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 273, "metadata": {}, "outputs": [], "source": [ @@ -593,7 +597,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 274, "metadata": { "pycharm": { "is_executing": false, @@ -628,7 +632,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 249, "metadata": { "scrolled": false }, @@ -883,6 +887,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -1140,11 +1148,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -1154,7 +1165,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -1273,10 +1284,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -1284,18 +1295,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -1320,7 +1330,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -1330,6 +1340,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -1340,8 +1363,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -1594,7 +1623,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -1872,6 +1901,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -2129,11 +2162,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -2143,7 +2179,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -2262,10 +2298,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -2273,18 +2309,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -2309,7 +2344,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -2319,6 +2354,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -2329,8 +2377,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -2612,7 +2666,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 275, "metadata": {}, "outputs": [ { @@ -2638,7 +2692,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 276, "metadata": { "pycharm": { "is_executing": false @@ -2650,57 +2704,57 @@ "name": "stdout", "output_type": "stream", "text": [ - "image 0 reprojection errors: average:8.18390110876233 max: 24.940922334112226\n", - "image 1 reprojection errors: average:5.805743311708305 max: 22.544199450115567\n", - "image 2 reprojection errors: average:5.3932973825051 max: 17.746577796705097\n", - "image 3 reprojection errors: average:9.249812619087006 max: 25.373555736715026\n", - "image 4 reprojection errors: average:5.244403216477963 max: 26.30564049317777\n", - "image 5 reprojection errors: average:5.442937098672511 max: 16.872318415315487\n", - "image 6 reprojection errors: average:6.918473151842166 max: 32.00865423247106\n", - "image 7 reprojection errors: average:6.535620723727593 max: 16.060733950131045\n", - "image 8 reprojection errors: average:7.30100908490715 max: 27.14384362948084\n", - "image 9 reprojection errors: average:8.041999905102857 max: 34.83824420274272\n", - "image 10 reprojection errors: average:6.370255934425072 max: 20.10736496295024\n", - "image 11 reprojection errors: average:6.887148773826209 max: 17.42767041281086\n", - "image 12 reprojection errors: average:8.210569329964082 max: 26.585739470838494\n", - "image 13 reprojection errors: average:6.39000960408589 max: 21.94211596885494\n", - "image 14 reprojection errors: average:14.92900993644056 max: 30.31644632771952\n", - "image 15 reprojection errors: average:7.097952944178674 max: 22.56536442999593\n", - "image 16 reprojection errors: average:5.265234583168665 max: 17.417982326469886\n", - "image 17 reprojection errors: average:5.252303406542907 max: 14.665181214138517\n", - "image 18 reprojection errors: average:4.5200875154681555 max: 15.488591658253304\n", - "image 19 reprojection errors: average:3.8739597282077156 max: 9.085935192378928\n", - "image 20 reprojection errors: average:7.2513561632222805 max: 20.43400454194171\n", - "image 21 reprojection errors: average:8.541820698222 max: 27.833814655175075\n", - "image 22 reprojection errors: average:6.146747172907711 max: 15.61413459452357\n", - "image 23 reprojection errors: average:4.88815583046527 max: 9.838168750394386\n", - "image 24 reprojection errors: average:6.597261143243092 max: 19.43094723324123\n", - "image 25 reprojection errors: average:4.062229166866455 max: 9.577115766033314\n", - "image 26 reprojection errors: average:7.006709711877225 max: 17.976745856756295\n", - "image 27 reprojection errors: average:7.615443569136982 max: 36.58264882365775\n", - "image 28 reprojection errors: average:5.5658802495709825 max: 9.301873799033457\n", - "image 29 reprojection errors: average:5.9226348773873 max: 21.646447530851813\n", - "image 30 reprojection errors: average:6.447495264341781 max: 17.016725069353175\n", - "image 31 reprojection errors: average:6.536835698748838 max: 21.629916614670336\n", - "image 32 reprojection errors: average:5.538457374020163 max: 11.369721689674806\n", - "image 33 reprojection errors: average:10.562864979598398 max: 44.49949437981786\n", - "image 34 reprojection errors: average:9.906919655829332 max: 17.523899418061323\n", - "image 35 reprojection errors: average:10.383395341200721 max: 19.371239749071695\n", - "image 36 reprojection errors: average:10.90387585914992 max: 20.348652989508036\n", - "image 37 reprojection errors: average:8.979812978701283 max: 21.428894394790177\n", - "image 38 reprojection errors: average:12.82523134923746 max: 31.577812486117022\n", - "image 39 reprojection errors: average:6.15677626549432 max: 21.514457392846346\n", - "image 40 reprojection errors: average:31.72552517041376 max: 75.66715182174264\n", - "image 41 reprojection errors: average:9.038105751756841 max: 29.701301540679278\n", - "image 42 reprojection errors: average:2.9410401045486756 max: 6.641734089086367\n", - "image 43 reprojection errors: average:6.2533880951232135 max: 11.10074038258666\n", - "image 44 reprojection errors: average:4.920868359688668 max: 13.629635865637965\n", - "image 45 reprojection errors: average:5.087970321241018 max: 11.127710112224214\n", - "image 46 reprojection errors: average:4.214466769179211 max: 8.109655893746073\n", - "image 47 reprojection errors: average:6.392564533301369 max: 20.021508272517355\n", - "image 48 reprojection errors: average:5.787761900683224 max: 11.217884191587995\n", - "image 49 reprojection errors: average:4.880935428336551 max: 9.281954054415156\n", - "image 50 reprojection errors: average:5.893760543568564 max: 23.75724130874825\n" + "image 0 reprojection errors: average:8.18390110876375 max: 24.94092233411413\n", + "image 1 reprojection errors: average:5.8057433117079595 max: 22.54419945011449\n", + "image 2 reprojection errors: average:5.3932973825052315 max: 17.746577796702898\n", + "image 3 reprojection errors: average:9.249812619087974 max: 25.373555736717968\n", + "image 4 reprojection errors: average:5.244403216475949 max: 26.30564049317514\n", + "image 5 reprojection errors: average:5.442937098671642 max: 16.872318415314282\n", + "image 6 reprojection errors: average:6.91847315184272 max: 32.00865423247497\n", + "image 7 reprojection errors: average:6.535620723727753 max: 16.060733950136335\n", + "image 8 reprojection errors: average:7.301009084916339 max: 27.143843629499244\n", + "image 9 reprojection errors: average:8.041999905103376 max: 34.838244202745926\n", + "image 10 reprojection errors: average:6.37025593442635 max: 20.107364962952094\n", + "image 11 reprojection errors: average:6.887148773823956 max: 17.427670412805366\n", + "image 12 reprojection errors: average:8.210569329963937 max: 26.585739470833815\n", + "image 13 reprojection errors: average:6.39000960408542 max: 21.942115968856132\n", + "image 14 reprojection errors: average:14.929009936442187 max: 30.316446327719635\n", + "image 15 reprojection errors: average:7.097952944178554 max: 22.565364429994716\n", + "image 16 reprojection errors: average:5.2652345831695495 max: 17.417982326467932\n", + "image 17 reprojection errors: average:5.252303406543003 max: 14.665181214135375\n", + "image 18 reprojection errors: average:4.520087515467902 max: 15.48859165825143\n", + "image 19 reprojection errors: average:3.8739597282078924 max: 9.085935192382738\n", + "image 20 reprojection errors: average:7.251356163222619 max: 20.434004541942645\n", + "image 21 reprojection errors: average:8.541820698220842 max: 27.833814655174077\n", + "image 22 reprojection errors: average:6.146747172907995 max: 15.614134594523062\n", + "image 23 reprojection errors: average:4.88815583046578 max: 9.838168750390725\n", + "image 24 reprojection errors: average:6.59726114324304 max: 19.43094723324123\n", + "image 25 reprojection errors: average:4.062229166866377 max: 9.577115766031268\n", + "image 26 reprojection errors: average:7.0067097118768515 max: 17.976745856756665\n", + "image 27 reprojection errors: average:7.6154435691381686 max: 36.58264882365354\n", + "image 28 reprojection errors: average:5.565880249570669 max: 9.301873799042598\n", + "image 29 reprojection errors: average:5.922634877387619 max: 21.646447530853163\n", + "image 30 reprojection errors: average:6.447495264342218 max: 17.016725069346514\n", + "image 31 reprojection errors: average:6.536835698745158 max: 21.62991661467258\n", + "image 32 reprojection errors: average:5.5384573740207985 max: 11.369721689675746\n", + "image 33 reprojection errors: average:10.56286497960333 max: 44.49949437980213\n", + "image 34 reprojection errors: average:9.906919655833176 max: 17.523899418065618\n", + "image 35 reprojection errors: average:10.383395341199535 max: 19.37123974907046\n", + "image 36 reprojection errors: average:10.90387585914805 max: 20.34865298951052\n", + "image 37 reprojection errors: average:8.979812978701162 max: 21.428894394791442\n", + "image 38 reprojection errors: average:12.825231349234468 max: 31.577812486110894\n", + "image 39 reprojection errors: average:6.156776265494568 max: 21.514457392844474\n", + "image 40 reprojection errors: average:31.725525170418837 max: 75.66715182175243\n", + "image 41 reprojection errors: average:9.038105751755074 max: 29.70130154067451\n", + "image 42 reprojection errors: average:2.9410401045484855 max: 6.641734089083937\n", + "image 43 reprojection errors: average:6.253388095122778 max: 11.100740382590844\n", + "image 44 reprojection errors: average:4.920868359687841 max: 13.629635865639829\n", + "image 45 reprojection errors: average:5.087970321246291 max: 11.127710112231272\n", + "image 46 reprojection errors: average:4.214466769179164 max: 8.109655893746092\n", + "image 47 reprojection errors: average:6.392564533301612 max: 20.021508272525644\n", + "image 48 reprojection errors: average:5.787761900685547 max: 11.217884191590672\n", + "image 49 reprojection errors: average:4.88093542833702 max: 9.281954054413037\n", + "image 50 reprojection errors: average:5.893760543568262 max: 23.757241308739147\n" ] } ], @@ -2717,16 +2771,16 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 277, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "795 04721-00 40 75.66715182174264\n", - "795 04722-00 40 62.99503133115818\n", - "795 04722-00 40 62.99503133115818\n" + "795 04721-00 40 75.66715182175243\n", + "795 04722-00 40 62.99503133115899\n", + "795 04722-00 40 62.99503133115899\n" ] } ], @@ -2758,10 +2812,42 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 278, "metadata": { "scrolled": false }, + "outputs": [], + "source": [ + "images_to_plot = []#common_image_feature_locations.keys()# ['766', '767', '768', '769']\n", + "for test_image in images_to_plot:\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.stack(list(common_image_feature_locations[test_image].values()))\n", + " repro_coords = np.stack(list(reprojected_points[test_image].values()))\n", + " ax.scatter(coords[:,0], 3000-coords[:,1], marker='.', label='detected')\n", + " ax.scatter(repro_coords[:,0], 3000-repro_coords[:,1], marker='.', label='reprojected')\n", + " for t, f in common_image_feature_locations[test_image].items():\n", + " ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='k')\n", + "# for t, f in reprojected_points[fitter_pmts.index_image[test_image]].items():\n", + "# ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='gray')\n", + " ax.set_title(\"Image {}\".format(test_image))\n", + " ax.set_ylim(0, 3000)\n", + " ax.set_xlim(0, 4000)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()\n", + " plt.savefig(saveLocation+\"initial_estimate/image_plots/\"+test_image+\"-initial_estimate-plot\"+imageExtension)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot camera position estimates in 3D" + ] + }, + { + "cell_type": "code", + "execution_count": 256, + "metadata": {}, "outputs": [ { "data": { @@ -3013,6 +3099,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -3270,11 +3360,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -3284,7 +3377,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -3403,10 +3496,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -3414,18 +3507,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -3450,7 +3542,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -3460,6 +3552,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -3470,8 +3575,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -3724,7 +3835,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -3732,7 +3843,27 @@ }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "fig = plt.figure(figsize=(12,9))\n", + "pmt_array = np.stack(list(pmt_locations.values()))\n", + "feat_array = np.stack(list(pmt_locations.values()))\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(feat_array[:,0], feat_array[:,1], feat_array[:,2], marker='.', label=\"seed positions\", zorder=2)\n", + "for i, f in enumerate(pmt_locations.keys()):\n", + " ax.text(pmt_array[i,0], pmt_array[i,1], pmt_array[i,2], f[:5], size=4, zorder=4, color='k') \n", + "ax.scatter(camera_positions[:,0], camera_positions[:,1], camera_positions[:,2], marker='*', label=\"camera estimate\", zorder=1)\n", + "plt.legend(loc=0)\n", + "fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -3983,6 +4114,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -4240,11 +4375,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -4254,7 +4392,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -4373,10 +4511,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -4384,18 +4522,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -4420,7 +4557,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -4430,6 +4567,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -4440,8 +4590,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -4694,7 +4850,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -4702,7 +4858,27 @@ }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(9,9))\n", + "pmt_array = np.stack(list(pmt_locations.values()))\n", + "ax.scatter(pmt_array[:,0], pmt_array[:,1], marker='^', label=\"pmt (seed position)\")\n", + "ax.scatter(camera_positions[:,0], camera_positions[:,1], marker='*', label=\"camera estimate\", zorder=1)\n", + "for i, p in enumerate(camera_positions):\n", + " ax.text(p[0], p[1], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", + "ax.set_ylim((-1800,1800))\n", + "ax.set_xlim((-1800,1800))\n", + "plt.legend(loc=0)\n", + "fig.tight_layout()\n", + "fig.savefig(saveLocation+\"initial_estimate/initial_estimate-top\"+imageExtension)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -4953,6 +5129,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -5210,11 +5390,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -5224,7 +5407,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -5343,10 +5526,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -5354,18 +5537,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -5390,7 +5572,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -5400,6 +5582,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -5410,8 +5605,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -5664,7 +5865,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -5672,7 +5873,173 @@ }, "metadata": {}, "output_type": "display_data" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(16,6))\n", + "pmt_array = np.stack(list(pmt_locations.values()))\n", + "ax.scatter(np.arctan2(pmt_array[:,1],pmt_array[:,0]), pmt_array[:,2], marker='^', label=\"pmt (seed position)\")\n", + "ax.scatter(np.arctan2(camera_positions[:,1], camera_positions[:,0]), camera_positions[:,2], marker='*', label=\"camera estimate\", zorder=1)\n", + "for i, p in enumerate(camera_positions):\n", + " ax.text(np.arctan2(p[1],p[0]), p[2], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", + "ax.set_xlim((-np.pi-0.1,np.pi+0.1))\n", + "ax.set_ylim((0,500))\n", + "plt.legend(loc=0)\n", + "fig.tight_layout()\n", + "fig.savefig(saveLocation+\"initial_estimate/initial_estimate-barrel\"+imageExtension)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Perform bundle asjustment starting from seed geometry and estimated camera poses" + ] + }, + { + "cell_type": "code", + "execution_count": 281, + "metadata": { + "pycharm": { + "is_executing": false }, + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.6712e+04 1.63e+06 \n", + " 1 2 1.7117e+04 5.96e+04 5.83e+01 2.03e+04 \n", + " 2 3 1.5525e+04 1.59e+03 2.11e+01 1.20e+04 \n", + " 3 4 1.4842e+04 6.83e+02 6.60e+00 4.74e+03 \n", + " 4 5 1.4676e+04 1.66e+02 2.79e+00 4.96e+03 \n", + " 5 6 1.4595e+04 8.07e+01 1.39e+00 4.94e+03 \n", + " 6 7 1.4544e+04 5.17e+01 9.25e-01 4.04e+03 \n", + " 7 8 1.4497e+04 4.70e+01 9.88e-01 5.08e+03 \n", + " 8 9 1.4451e+04 4.55e+01 8.65e-01 4.25e+03 \n", + " 9 10 1.4407e+04 4.42e+01 9.54e-01 5.16e+03 \n", + " 10 11 1.4364e+04 4.31e+01 8.45e-01 4.32e+03 \n", + " 11 12 1.4322e+04 4.18e+01 9.24e-01 5.39e+03 \n", + " 12 13 1.4281e+04 4.09e+01 8.25e-01 4.64e+03 \n", + " 13 14 1.4242e+04 3.96e+01 8.91e-01 5.96e+03 \n", + " 14 15 1.4203e+04 3.89e+01 8.03e-01 5.27e+03 \n", + " 15 16 1.4165e+04 3.77e+01 8.60e-01 6.49e+03 \n", + " 16 17 1.4128e+04 3.68e+01 7.72e-01 6.44e+03 \n", + " 17 18 1.4092e+04 3.56e+01 8.12e-01 8.30e+03 \n", + " 18 19 1.4058e+04 3.44e+01 7.14e-01 8.74e+03 \n", + " 19 20 1.4027e+04 3.07e+01 6.63e-01 1.21e+04 \n", + " 20 21 1.4007e+04 2.01e+01 3.08e-01 1.07e+04 \n", + " 21 22 1.4004e+04 3.72e+00 7.68e-04 2.94e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 22, initial cost 7.6712e+04, final cost 1.4004e+04, first-order optimality 2.94e+01.\n", + "mean reprojection error: 3.0502375288380037\n", + "max reprojection error: 21.636539426893115\n" + ] + } + ], + "source": [ + "# camera_rotations, camera_translations, reco_locations, fitted_matrix, fitted_distortion = fitter_all.bundle_adjustment(\n", + "# camera_rotations, camera_translations, use_sparsity=True, max_error=5, fit_cam=True)\n", + "camera_rotations, camera_translations, reco_locations, opt = fitter_all.bundle_adjustment(camera_rotations, camera_translations, use_sparsity=True, return_opt=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 282, + "metadata": {}, + "outputs": [], + "source": [ + "J=opt.jac[:,fitter_all.nimages*6:].toarray()\n", + "U, s, Vh = linalg.svd(J, full_matrices=False)\n", + "tol = np.finfo(float).eps*s[0]*max(J.shape)\n", + "w = s > tol\n", + "cov = (Vh[w].T/s[w]**2) @ Vh[w] # robust covariance matrix\n", + "perr = np.sqrt(np.diag(cov)) # 1sigma uncertainty on fitted parameters\n", + "feature_location_errors = perr.reshape((-1, 3))" + ] + }, + { + "cell_type": "code", + "execution_count": 300, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "3522" + ] + }, + "execution_count": 300, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "opt.fun.size" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "2250" + ] + }, + "execution_count": 301, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "opt.x.size" + ] + }, + { + "cell_type": "code", + "execution_count": 304, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1944" + ] + }, + "execution_count": 304, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "perr.size" + ] + }, + { + "cell_type": "code", + "execution_count": 305, + "metadata": {}, + "outputs": [], + "source": [ + "chi2dof = np.sum(opt.fun**2)/(opt.fun.size - perr.size)\n", + "cov_scaled = cov*chi2dof\n", + "perr = np.sqrt(np.diag(cov_scaled)) # 1sigma uncertainty on fitted parameters\n", + "feature_location_errors = perr.reshape((-1, 3))" + ] + }, + { + "cell_type": "code", + "execution_count": 306, + "metadata": { + "scrolled": false + }, + "outputs": [ { "data": { "application/javascript": [ @@ -5923,6 +6290,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -6180,11 +6551,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -6194,7 +6568,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -6313,10 +6687,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -6324,18 +6698,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -6360,7 +6733,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -6370,6 +6743,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -6380,8 +6766,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -6634,7 +7026,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -6643,6 +7035,50 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'Number of features')" + ] + }, + "execution_count": 306, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "ax.hist(feature_location_errors.flatten(), bins=20, histtype=\"step\")\n", + "ax.set_xlabel(\"Fitter error on feature position [cm]\", fontsize=15)\n", + "ax.set_ylabel(\"Number of features\", fontsize=15)" + ] + }, + { + "cell_type": "code", + "execution_count": 307, + "metadata": {}, + "outputs": [], + "source": [ + "x_variance = np.diag(cov_scaled)[0::3]\n", + "y_variance = np.diag(cov_scaled)[1::3]\n", + "z_variance = np.diag(cov_scaled)[2::3]\n", + "variance_3d = x_variance + y_variance + z_variance\n", + "xy_covariance = cov_scaled[range(0,cov_scaled.shape[0],3),range(1,cov_scaled.shape[1],3)]\n", + "xz_covariance = cov_scaled[range(0,cov_scaled.shape[0],3),range(2,cov_scaled.shape[1],3)]\n", + "yz_covariance = cov_scaled[range(1,cov_scaled.shape[0],3),range(2,cov_scaled.shape[1],3)]\n", + "radial_positions = linalg.norm(fitter_all.reco_locations[:,:2], axis=1)\n", + "x_positions = fitter_all.reco_locations[:,0]\n", + "y_positions = fitter_all.reco_locations[:,1]\n", + "z_positions = fitter_all.reco_locations[:,2]\n", + "radial_variance = ((x_positions**2)*x_variance+(y_positions**2)*y_variance+2*x_positions*y_positions*xy_covariance)/radial_positions**2\n", + "tangential_variance = variance_3d-radial_variance" + ] + }, + { + "cell_type": "code", + "execution_count": 308, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -6893,6 +7329,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -7150,11 +7590,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -7164,7 +7607,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -7283,10 +7726,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -7294,18 +7737,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -7330,7 +7772,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -7340,6 +7782,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -7350,8 +7805,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -7604,7 +8065,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -7613,6 +8074,32 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 308, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "ax.hist(np.sqrt(x_variance), bins=range(20), histtype=\"step\", color=\"r\", label=f\"x position error\\nmean = {np.mean(np.sqrt(x_variance)):.3} cm\")\n", + "ax.hist(np.sqrt(y_variance), bins=range(20), histtype=\"step\", color=\"b\", label=f\"y position error\\nmean = {np.mean(np.sqrt(y_variance)):.3} cm\")\n", + "ax.hist(np.sqrt(z_variance), bins=range(20), histtype=\"step\", color=\"g\", label=f\"z position error\\nmean = {np.mean(np.sqrt(z_variance)):.3} cm\")\n", + "ax.set_xlabel(\"Fitter error on feature position [cm]\", fontsize=15)\n", + "ax.set_ylabel(\"Number of features\", fontsize=15)\n", + "plt.legend(loc=\"upper right\", prop={'size': 15})" + ] + }, + { + "cell_type": "code", + "execution_count": 309, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -7863,6 +8350,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -8120,11 +8611,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -8134,7 +8628,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -8253,10 +8747,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -8264,18 +8758,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -8300,7 +8793,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -8310,6 +8803,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -8320,8 +8826,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -8574,7 +9086,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -8583,6 +9095,30 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 309, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "ax.hist(np.sqrt(variance_3d), bins=20, histtype=\"step\", label=f\"3D position error\\nmean = {np.mean(np.sqrt(variance_3d)):.3} cm\")\n", + "ax.set_xlabel(\"Fitter error on 3D feature position [cm]\", fontsize=15)\n", + "ax.set_ylabel(\"Number of features\", fontsize=15)\n", + "plt.legend(loc=\"upper right\", prop={'size': 15})" + ] + }, + { + "cell_type": "code", + "execution_count": 310, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -8833,6 +9369,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -9090,11 +9630,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -9104,7 +9647,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -9223,10 +9766,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -9234,18 +9777,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -9270,7 +9812,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -9280,6 +9822,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -9290,8 +9845,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -9544,7 +10105,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -9553,6 +10114,105 @@ "metadata": {}, "output_type": "display_data" }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 310, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "ax.hist(np.sqrt(radial_variance), bins=20, histtype=\"step\", color=\"b\", label=f\"Radial position error\\nmean = {np.mean(np.sqrt(radial_variance)):.3} cm\")\n", + "ax.hist(np.sqrt(tangential_variance), bins=20, histtype=\"step\", color=\"r\", label=f\"Tangential position error\\nmean = {np.mean(np.sqrt(tangential_variance)):.3} cm\")\n", + "ax.set_xlabel(\"Fitter error on radial feature position [cm]\", fontsize=15)\n", + "ax.set_ylabel(\"Number of features\", fontsize=15)\n", + "plt.legend(loc=\"upper right\", prop={'size': 15})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Kabsch algorithm to match reconstructed coordinate system to seed co-ordinate system" + ] + }, + { + "cell_type": "code", + "execution_count": 289, + "metadata": { + "pycharm": { + "is_executing": false + }, + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mean reconstruction error: 2.576439736972181\n", + "max reconstruction error: 10.759373732374454\n" + ] + } + ], + "source": [ + "errors, reco_transformed, scale, R, translation, location_mean = fit.kabsch_errors(pmt_locations, reco_locations)\n", + "print(\"mean reconstruction error:\", linalg.norm(errors, axis=1).mean())\n", + "print(\"max reconstruction error:\", linalg.norm(errors, axis=1).max())" + ] + }, + { + "cell_type": "code", + "execution_count": 290, + "metadata": {}, + "outputs": [], + "source": [ + "ret = 1, 2" + ] + }, + { + "cell_type": "code", + "execution_count": 291, + "metadata": {}, + "outputs": [], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "camera_orientations = np.matmul(R, camera_orientations)\n", + "camera_positions = camera_positions - translation\n", + "camera_positions = scale*R.dot(camera_positions.transpose()).transpose() + location_mean" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check new yaws and depths for manual shifts if necessary" + ] + }, + { + "cell_type": "code", + "execution_count": 292, + "metadata": {}, + "outputs": [], + "source": [ + "drone_yaw = np.array(list(drone_yaw_raw.values()))*np.pi/180\n", + "fitted_yaw = np.arctan2(camera_orientations[:,1,2],camera_orientations[:,0,2])\n", + "drone_yaw -= drone_yaw[21] - fitted_yaw[21] # correct for drone calibration by forcing image 21 (with light injector) to have the correct yaw\n", + "yaw_errors = ((fitted_yaw - drone_yaw + np.pi) % (2*np.pi)) - np.pi\n", + "yaw_errors_deg = yaw_errors*180/np.pi\n", + "depths = camera_positions[:,2]/100 - 2.9" + ] + }, + { + "cell_type": "code", + "execution_count": 293, + "metadata": {}, + "outputs": [ { "data": { "application/javascript": [ @@ -9803,6 +10463,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -10060,11 +10724,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -10074,7 +10741,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -10193,10 +10860,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -10204,18 +10871,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -10240,7 +10906,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -10250,6 +10916,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -10260,8 +10939,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -10514,7 +11199,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -10523,6 +11208,205 @@ "metadata": {}, "output_type": "display_data" }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " yaw depth\n", + "image 755: -0.8644 +0.0450\n", + "image 756: -2.0376 +0.0546\n", + "image 757: -4.1522 +0.0735\n", + "image 758: +3.7006 +0.1559\n", + "image 759: +1.6185 +0.0820\n", + "image 760: -0.9035 -0.0583\n", + "image 761: -0.1234 +0.1054\n", + "image 762: -3.8193 +0.0357\n", + "image 763: +3.9414 +0.1273\n", + "image 764: +1.6909 +0.0614\n", + "image 765: +0.8607 +0.1301\n", + "image 766: -1.2926 -0.0791\n", + "image 767: -2.1103 +0.0463\n", + "image 768: +4.3450 -0.0698\n", + "image 769: +0.7497 -0.1673\n", + "image 770: +3.3188 +0.0157\n", + "image 771: +2.9743 +0.0467\n", + "image 772: +0.2763 -0.0185\n", + "image 773: +0.1406 -0.0055\n", + "image 774: -1.0599 -0.0655\n", + "image 775: +1.1562 +0.1122\n", + "image 776: +0.0000 +0.0718\n", + "image 777: -1.1475 -0.0593\n", + "image 778: +0.8455 +0.0543\n", + "image 779: +3.0151 +0.0442\n", + "image 780: -4.0019 +0.1472\n", + "image 781: -1.3729 +0.1543\n", + "image 782: +2.1631 +0.0293\n", + "image 783: +1.6154 +0.1314\n", + "image 784: -0.2537 +0.1610\n", + "image 785: +3.9184 -0.0257\n", + "image 786: -3.1136 +0.0152\n", + "image 787: -1.8892 -0.0304\n", + "image 788: +3.0924 -0.0490\n", + "image 789: +2.7097 +0.0217\n", + "image 790: -0.0052 +0.1000\n", + "image 791: -1.7324 +0.1661\n", + "image 792: -0.7759 -0.1085\n", + "image 793: +3.1362 -0.0499\n", + "image 794: +4.6417 +0.0778\n", + "image 795: -0.2364 -0.1795\n", + "image 796: +4.7643 -0.0771\n", + "image 797: +2.0038 +0.0796\n", + "image 798: -4.4088 +0.0155\n", + "image 799: -0.1181 +0.1394\n", + "image 800: -1.1673 +0.1913\n", + "image 801: -2.5063 +0.2335\n", + "image 901: -2.4623 +0.1754\n", + "image 902: +3.1176 +0.0282\n", + "image 903: +1.8706 +0.1087\n", + "image 904: +0.8427 +0.0055\n" + ] + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(8,6))\n", + "ax.hist(yaw_errors_deg, bins=10)\n", + "ax.set_title(f\"Yaw error, mean = {yaw_errors_deg.mean():.2f} deg\")\n", + "fig.tight_layout()\n", + "print(\" yaw depth\")\n", + "for i, (e, d) in enumerate(zip(yaw_errors_deg, depths)):\n", + " print(f\"image {fitter_all.index_image[i]}: {e:+6.4f} {d:+6.4f}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Plot overlay of reprojected and observed feature locations for manual checking" + ] + }, + { + "cell_type": "code", + "execution_count": 294, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "#images_to_plot = images ['792']\n", + "for test_image in []:#images_to_plot:\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.stack(list(common_image_feature_locations[test_image].values()))\n", + " repro_coords = np.stack(list(reprojected_points[test_image].values()))\n", + " ax.scatter(coords[:,0], 3000-coords[:,1], marker='.', label='detected')\n", + " ax.scatter(repro_coords[:,0], 3000-repro_coords[:,1], marker='.', label='reprojected')\n", + " for t, f in common_image_feature_locations[test_image].items():\n", + " ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='k')\n", + "# for t, f in reprojected_points[fitter_pmts.index_image[test_image]].items():\n", + "# ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='gray')\n", + " ax.set_title(\"Image {}\".format(test_image))\n", + " ax.set_ylim(0, 3000)\n", + " ax.set_xlim(0, 4000)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()\n", + " plt.savefig(saveLocation+\"image_plots/\"+test_image+\"-plot\"+imageExtension)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Save results to txt file" + ] + }, + { + "cell_type": "code", + "execution_count": 295, + "metadata": {}, + "outputs": [], + "source": [ + "fitter_all.save_result(saveLocation+\"SK_ring_features_relabelled.txt\", saveLocation+\"SK_ring_cameras_relabelled.txt\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Save results to pickle" + ] + }, + { + "cell_type": "code", + "execution_count": 296, + "metadata": {}, + "outputs": [], + "source": [ + "with open(saveLocation+\"SK_ring_relabelled.pkl\", 'wb') as output:\n", + " pickle.dump(fitter_all, output, pickle.HIGHEST_PROTOCOL)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Plots of reconstructed geometry" + ] + }, + { + "cell_type": "code", + "execution_count": 297, + "metadata": {}, + "outputs": [], + "source": [ + "from matplotlib.legend_handler import HandlerPatch\n", + "import matplotlib.patches as mpatches\n", + "class HandlerArrow(HandlerPatch):\n", + " def create_artists(self, legend, orig_handle,\n", + " xdescent, ydescent, width, height, fontsize, trans):\n", + " p = mpatches.FancyArrow(0, 0.5*height, width, 0, length_includes_head=True, head_width=0.75*height )\n", + " self.update_prop(p, orig_handle, legend)\n", + " p.set_transform(trans)\n", + " return [p]" + ] + }, + { + "cell_type": "code", + "execution_count": 298, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([153.92161995, 147.92161995, 140.92161995, 136.92161995,\n", + " 135.92161995, 122.92161995, 121.92161995, 112.92161995,\n", + " 109.92161995, 102.92161995, 99.92161995, 94.92161995,\n", + " 88.92161995, 80.92161995, 77.92161995, 69.92161995,\n", + " 59.92161995, 58.92161995, 48.92161995, 45.92161995,\n", + " 39.92161995, 34.92161995, 28.92161995, 16.92161995,\n", + " 9.92161995, -4.07838005, -11.07838005, 341.92161995,\n", + " 334.92161995, 314.92161995, 303.92161995, 296.92161995,\n", + " 283.92161995, 276.92161995, 258.92161995, 247.92161995,\n", + " 240.92161995, 231.92161995, 219.92161995, 216.92161995,\n", + " 211.92161995, 201.92161995, 193.92161995, 185.92161995,\n", + " 184.92161995, 182.92161995, 173.92161995, 173.92161995,\n", + " 167.92161995, 161.92161995, 151.92161995])" + ] + }, + "execution_count": 298, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "drone_yaw*180/np.pi" + ] + }, + { + "cell_type": "code", + "execution_count": 299, + "metadata": { + "scrolled": false + }, + "outputs": [ { "data": { "application/javascript": [ @@ -10773,93440 +11657,9 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - ":3: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`).\n", - " fig, ax = plt.subplots(figsize=(12,9))\n" - ] - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "images_to_plot = common_image_feature_locations.keys()# ['766', '767', '768', '769']\n", - "for test_image in images_to_plot:\n", - " fig, ax = plt.subplots(figsize=(12,9))\n", - " coords = np.stack(list(common_image_feature_locations[test_image].values()))\n", - " repro_coords = np.stack(list(reprojected_points[test_image].values()))\n", - " ax.scatter(coords[:,0], 3000-coords[:,1], marker='.', label='detected')\n", - " ax.scatter(repro_coords[:,0], 3000-repro_coords[:,1], marker='.', label='reprojected')\n", - " for t, f in common_image_feature_locations[test_image].items():\n", - " ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='k')\n", - "# for t, f in reprojected_points[fitter_pmts.index_image[test_image]].items():\n", - "# ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='gray')\n", - " ax.set_title(\"Image {}\".format(test_image))\n", - " ax.set_ylim(0, 3000)\n", - " ax.set_xlim(0, 4000)\n", - " plt.legend(loc=0)\n", - " fig.tight_layout()\n", - " plt.savefig(saveLocation+\"initial_estimate/image_plots/\"+test_image+\"-initial_estimate-plot\"+imageExtension)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot camera position estimates in 3D" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", - "fig = plt.figure(figsize=(12,9))\n", - "pmt_array = np.stack(list(pmt_locations.values()))\n", - "feat_array = np.stack(list(pmt_locations.values()))\n", - "ax = fig.add_subplot(111, projection='3d')\n", - "ax.scatter(feat_array[:,0], feat_array[:,1], feat_array[:,2], marker='.', label=\"seed positions\", zorder=2)\n", - "for i, f in enumerate(pmt_locations.keys()):\n", - " ax.text(pmt_array[i,0], pmt_array[i,1], pmt_array[i,2], f[:5], size=4, zorder=4, color='k') \n", - "ax.scatter(camera_positions[:,0], camera_positions[:,1], camera_positions[:,2], marker='*', label=\"camera estimate\", zorder=1)\n", - "plt.legend(loc=0)\n", - "fig.tight_layout()" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(9,9))\n", - "pmt_array = np.stack(list(pmt_locations.values()))\n", - "ax.scatter(pmt_array[:,0], pmt_array[:,1], marker='^', label=\"pmt (seed position)\")\n", - "ax.scatter(camera_positions[:,0], camera_positions[:,1], marker='*', label=\"camera estimate\", zorder=1)\n", - "for i, p in enumerate(camera_positions):\n", - " ax.text(p[0], p[1], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", - "ax.set_ylim((-1800,1800))\n", - "ax.set_xlim((-1800,1800))\n", - "plt.legend(loc=0)\n", - "fig.tight_layout()\n", - "fig.savefig(saveLocation+\"initial_estimate/initial_estimate-top\"+imageExtension)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(16,6))\n", - "pmt_array = np.stack(list(pmt_locations.values()))\n", - "ax.scatter(np.arctan2(pmt_array[:,1],pmt_array[:,0]), pmt_array[:,2], marker='^', label=\"pmt (seed position)\")\n", - "ax.scatter(np.arctan2(camera_positions[:,1], camera_positions[:,0]), camera_positions[:,2], marker='*', label=\"camera estimate\", zorder=1)\n", - "for i, p in enumerate(camera_positions):\n", - " ax.text(np.arctan2(p[1],p[0]), p[2], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", - "ax.set_xlim((-np.pi,np.pi))\n", - "ax.set_ylim((0,500))\n", - "plt.legend(loc=0)\n", - "fig.tight_layout()\n", - "fig.savefig(saveLocation+\"initial_estimate/initial_estimate-barrel\"+imageExtension)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Perform bundle asjustment starting from seed geometry and estimated camera poses" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "metadata": { - "pycharm": { - "is_executing": false - }, - "scrolled": false - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", - " 0 1 8.7240e+04 7.81e+06 \n", - " 1 2 1.9348e+04 6.79e+04 6.97e+01 8.76e+04 \n", - " 2 3 1.7435e+04 1.91e+03 2.33e+01 2.33e+04 \n", - " 3 4 1.6627e+04 8.08e+02 7.80e+00 4.91e+03 \n", - " 4 5 1.6382e+04 2.45e+02 3.87e+00 2.63e+03 \n", - " 5 6 1.6216e+04 1.66e+02 2.86e+00 3.28e+03 \n", - " 6 7 1.6138e+04 7.83e+01 1.25e+00 2.09e+03 \n", - " 7 8 1.6085e+04 5.32e+01 9.86e-01 2.07e+03 \n", - " 8 9 1.6034e+04 5.02e+01 1.00e+00 1.91e+03 \n", - " 9 10 1.5985e+04 4.90e+01 9.48e-01 2.01e+03 \n", - " 10 11 1.5938e+04 4.78e+01 9.75e-01 1.83e+03 \n", - " 11 12 1.5891e+04 4.68e+01 9.30e-01 1.99e+03 \n", - " 12 13 1.5845e+04 4.57e+01 9.51e-01 1.82e+03 \n", - " 13 14 1.5800e+04 4.49e+01 9.14e-01 2.02e+03 \n", - " 14 15 1.5756e+04 4.39e+01 9.28e-01 1.84e+03 \n", - " 15 16 1.5713e+04 4.31e+01 8.98e-01 2.14e+03 \n", - " 16 17 1.5671e+04 4.22e+01 9.06e-01 1.99e+03 \n", - " 17 18 1.5630e+04 4.15e+01 8.83e-01 2.27e+03 \n", - " 18 19 1.5589e+04 4.06e+01 8.86e-01 2.09e+03 \n", - " 19 20 1.5549e+04 3.99e+01 8.69e-01 2.40e+03 \n", - " 20 21 1.5510e+04 3.91e+01 8.66e-01 2.18e+03 \n", - " 21 22 1.5471e+04 3.85e+01 8.55e-01 2.61e+03 \n", - " 22 23 1.5434e+04 3.77e+01 8.46e-01 2.54e+03 \n", - " 23 24 1.5397e+04 3.71e+01 8.41e-01 3.19e+03 \n", - " 24 25 1.5360e+04 3.63e+01 8.26e-01 3.17e+03 \n", - " 25 26 1.5325e+04 3.57e+01 8.24e-01 4.29e+03 \n", - " 26 27 1.5290e+04 3.50e+01 8.01e-01 4.39e+03 \n", - " 27 28 1.5256e+04 3.39e+01 7.86e-01 7.48e+03 \n", - " 28 29 1.5224e+04 3.23e+01 7.22e-01 9.04e+03 \n", - " 29 30 1.5196e+04 2.80e+01 5.90e-01 1.47e+04 \n", - " 30 31 1.5189e+04 6.77e+00 3.16e-02 2.28e+03 \n", - "`xtol` termination condition is satisfied.\n", - "Function evaluations 31, initial cost 8.7240e+04, final cost 1.5189e+04, first-order optimality 2.28e+03.\n", - "mean reprojection error: 3.173953418173125\n", - "max reprojection error: 23.9958105832365\n" - ] - } - ], - "source": [ - "# camera_rotations, camera_translations, reco_locations, fitted_matrix, fitted_distortion = fitter_all.bundle_adjustment(\n", - "# camera_rotations, camera_translations, use_sparsity=True, max_error=5, fit_cam=True)\n", - "camera_rotations, camera_translations, reco_locations = fitter_all.bundle_adjustment(camera_rotations, camera_translations, use_sparsity=True)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Kabsch algorithm to match reconstructed coordinate system to seed co-ordinate system" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": { - "pycharm": { - "is_executing": false - }, - "scrolled": true - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "mean reconstruction error: 2.9078601755008577\n", - "max reconstruction error: 13.91719862886112\n" - ] - } - ], - "source": [ - "errors, reco_transformed, scale, R, translation, location_mean = fit.kabsch_errors(pmt_locations, reco_locations)\n", - "print(\"mean reconstruction error:\", linalg.norm(errors, axis=1).mean())\n", - "print(\"max reconstruction error:\", linalg.norm(errors, axis=1).max())" - ] - }, - { - "cell_type": "code", - "execution_count": 35, - "metadata": {}, - "outputs": [], - "source": [ - "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", - "camera_orientations = np.matmul(R, camera_orientations)\n", - "camera_positions = camera_positions - translation\n", - "camera_positions = scale*R.dot(camera_positions.transpose()).transpose() + location_mean" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Check new yaws and depths for manual shifts if necessary" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [], - "source": [ - "drone_yaw = np.array(list(drone_yaw_raw.values()))*np.pi/180\n", - "fitted_yaw = np.arctan2(camera_orientations[:,1,2],camera_orientations[:,0,2])\n", - "drone_yaw -= drone_yaw[21] - fitted_yaw[21] # correct for drone calibration by forcing image 21 (with light injector) to have the correct yaw\n", - "yaw_errors = ((fitted_yaw - drone_yaw + np.pi) % (2*np.pi)) - np.pi\n", - "yaw_errors_deg = yaw_errors*180/np.pi\n", - "depths = camera_positions[:,2]/100 - 2.9" - ] - }, - { - "cell_type": "code", - "execution_count": 37, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - " yaw depth\n", - "image 755: -0.9134 +0.0338\n", - "image 756: -2.1533 +0.0556\n", - "image 757: -4.0510 +0.0566\n", - "image 758: +3.4926 +0.2046\n", - "image 759: +1.5126 +0.1028\n", - "image 760: -0.8427 -0.0716\n", - "image 761: -0.1631 +0.1094\n", - "image 762: -3.9015 +0.0459\n", - "image 763: +3.9012 +0.1552\n", - "image 764: +1.5209 +0.0441\n", - "image 765: +0.8571 +0.1441\n", - "image 766: -1.3648 -0.0956\n", - "image 767: -2.1448 +0.0570\n", - "image 768: +4.2798 -0.0738\n", - "image 769: +0.2458 -0.1893\n", - "image 770: +3.5235 +0.0060\n", - "image 771: +2.8210 +0.0573\n", - "image 772: +0.2321 -0.0221\n", - "image 773: +0.0391 -0.0080\n", - "image 774: -0.9613 -0.0698\n", - "image 775: +1.2070 +0.1100\n", - "image 776: +0.0000 +0.0762\n", - "image 777: -1.2597 -0.0591\n", - "image 778: +0.7023 +0.0644\n", - "image 779: +2.9395 +0.0406\n", - "image 780: -4.1009 +0.1496\n", - "image 781: -1.5613 +0.1545\n", - "image 782: +2.1787 +0.0276\n", - "image 783: +1.4933 +0.1322\n", - "image 784: -0.3455 +0.1668\n", - "image 785: +3.8076 -0.0324\n", - "image 786: -3.1597 +0.0176\n", - "image 787: -1.9293 -0.0298\n", - "image 788: +2.8350 -0.0593\n", - "image 789: +2.7906 +0.0265\n", - "image 790: -0.0754 +0.0996\n", - "image 791: -1.9311 +0.1859\n", - "image 792: -0.7958 -0.1179\n", - "image 793: +2.5060 -0.0615\n", - "image 794: +4.4523 +0.0941\n", - "image 795: -1.2752 -0.2152\n", - "image 796: +4.8223 -0.0972\n", - "image 797: +1.7927 +0.0901\n", - "image 798: -4.5399 +0.0143\n", - "image 799: -0.1932 +0.1516\n", - "image 800: -1.2636 +0.2073\n", - "image 801: -2.5911 +0.2381\n", - "image 901: -2.6524 +0.2025\n", - "image 902: +3.1228 -0.0028\n", - "image 903: +1.8058 +0.1136\n", - "image 904: +0.8779 +0.0281\n" - ] - } - ], - "source": [ - "fig, ax = plt.subplots(figsize=(8,6))\n", - "ax.hist(yaw_errors_deg, bins=10)\n", - "ax.set_title(f\"Yaw error, mean = {yaw_errors_deg.mean():.2f} deg\")\n", - "fig.tight_layout()\n", - "print(\" yaw depth\")\n", - "for i, (e, d) in enumerate(zip(yaw_errors_deg, depths)):\n", - " print(f\"image {fitter_all.index_image[i]}: {e:+6.4f} {d:+6.4f}\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Plot overlay of reprojected and observed feature locations for manual checking" - ] - }, - { - "cell_type": "code", - "execution_count": 38, - "metadata": { - "scrolled": false - }, - "outputs": [ - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", - " );\n", - " // Throttle sequential mouse events to 1 every 20ms.\n", - " rubberband_canvas.addEventListener(\n", - " 'mousemove',\n", - " on_mouse_event_closure('motion_notify')\n", - " );\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseenter',\n", - " on_mouse_event_closure('figure_enter')\n", - " );\n", - " rubberband_canvas.addEventListener(\n", - " 'mouseleave',\n", - " on_mouse_event_closure('figure_leave')\n", - " );\n", - "\n", - " canvas_div.addEventListener('wheel', function (event) {\n", - " if (event.deltaY < 0) {\n", - " event.step = 1;\n", - " } else {\n", - " event.step = -1;\n", - " }\n", - " on_mouse_event_closure('scroll')(event);\n", - " });\n", - "\n", - " canvas_div.appendChild(canvas);\n", - " canvas_div.appendChild(rubberband_canvas);\n", - "\n", - " this.rubberband_context = rubberband_canvas.getContext('2d');\n", - " this.rubberband_context.strokeStyle = '#000000';\n", - "\n", - " this._resize_canvas = function (width, height, forward) {\n", - " if (forward) {\n", - " canvas_div.style.width = width + 'px';\n", - " canvas_div.style.height = height + 'px';\n", - " }\n", - " };\n", - "\n", - " // Disable right mouse context menu.\n", - " this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n", - " event.preventDefault();\n", - " return false;\n", - " });\n", - "\n", - " function set_focus() {\n", - " canvas.focus();\n", - " canvas_div.focus();\n", - " }\n", - "\n", - " window.setTimeout(set_focus, 100);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'mpl-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'mpl-button-group';\n", - " continue;\n", - " }\n", - "\n", - " var button = (fig.buttons[name] = document.createElement('button'));\n", - " button.classList = 'mpl-widget';\n", - " button.setAttribute('role', 'button');\n", - " button.setAttribute('aria-disabled', 'false');\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - "\n", - " var icon_img = document.createElement('img');\n", - " icon_img.src = '_images/' + image + '.png';\n", - " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", - " icon_img.alt = tooltip;\n", - " button.appendChild(icon_img);\n", - "\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " var fmt_picker = document.createElement('select');\n", - " fmt_picker.classList = 'mpl-widget';\n", - " toolbar.appendChild(fmt_picker);\n", - " this.format_dropdown = fmt_picker;\n", - "\n", - " for (var ind in mpl.extensions) {\n", - " var fmt = mpl.extensions[ind];\n", - " var option = document.createElement('option');\n", - " option.selected = fmt === mpl.default_extension;\n", - " option.innerHTML = fmt;\n", - " fmt_picker.appendChild(option);\n", - " }\n", - "\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "};\n", - "\n", - "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", - " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", - " // which will in turn request a refresh of the image.\n", - " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", - "};\n", - "\n", - "mpl.figure.prototype.send_message = function (type, properties) {\n", - " properties['type'] = type;\n", - " properties['figure_id'] = this.id;\n", - " this.ws.send(JSON.stringify(properties));\n", - "};\n", - "\n", - "mpl.figure.prototype.send_draw_message = function () {\n", - " if (!this.waiting) {\n", - " this.waiting = true;\n", - " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " var format_dropdown = fig.format_dropdown;\n", - " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", - " fig.ondownload(fig, format);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", - " var size = msg['size'];\n", - " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", - " fig._resize_canvas(size[0], size[1], msg['forward']);\n", - " fig.send_message('refresh', {});\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", - " var x0 = msg['x0'] / fig.ratio;\n", - " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", - " var x1 = msg['x1'] / fig.ratio;\n", - " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", - " x0 = Math.floor(x0) + 0.5;\n", - " y0 = Math.floor(y0) + 0.5;\n", - " x1 = Math.floor(x1) + 0.5;\n", - " y1 = Math.floor(y1) + 0.5;\n", - " var min_x = Math.min(x0, x1);\n", - " var min_y = Math.min(y0, y1);\n", - " var width = Math.abs(x1 - x0);\n", - " var height = Math.abs(y1 - y0);\n", - "\n", - " fig.rubberband_context.clearRect(\n", - " 0,\n", - " 0,\n", - " fig.canvas.width / fig.ratio,\n", - " fig.canvas.height / fig.ratio\n", - " );\n", - "\n", - " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", - " // Updates the figure title.\n", - " fig.header.textContent = msg['label'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", - " var cursor = msg['cursor'];\n", - " switch (cursor) {\n", - " case 0:\n", - " cursor = 'pointer';\n", - " break;\n", - " case 1:\n", - " cursor = 'default';\n", - " break;\n", - " case 2:\n", - " cursor = 'crosshair';\n", - " break;\n", - " case 3:\n", - " cursor = 'move';\n", - " break;\n", - " }\n", - " fig.rubberband_canvas.style.cursor = cursor;\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_message = function (fig, msg) {\n", - " fig.message.textContent = msg['message'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", - " // Request the server to send over a new figure.\n", - " fig.send_draw_message();\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", - " fig.image_mode = msg['mode'];\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", - " for (var key in msg) {\n", - " if (!(key in fig.buttons)) {\n", - " continue;\n", - " }\n", - " fig.buttons[key].disabled = !msg[key];\n", - " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", - " if (msg['mode'] === 'PAN') {\n", - " fig.buttons['Pan'].classList.add('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " } else if (msg['mode'] === 'ZOOM') {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.add('active');\n", - " } else {\n", - " fig.buttons['Pan'].classList.remove('active');\n", - " fig.buttons['Zoom'].classList.remove('active');\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Called whenever the canvas gets updated.\n", - " this.send_message('ack', {});\n", - "};\n", - "\n", - "// A function to construct a web socket function for onmessage handling.\n", - "// Called in the figure constructor.\n", - "mpl.figure.prototype._make_on_message_function = function (fig) {\n", - " return function socket_on_message(evt) {\n", - " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", - "\n", - " /* Free the memory for the previous frames */\n", - " if (fig.imageObj.src) {\n", - " (window.URL || window.webkitURL).revokeObjectURL(\n", - " fig.imageObj.src\n", - " );\n", - " }\n", - "\n", - " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", - " );\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " } else if (\n", - " typeof evt.data === 'string' &&\n", - " evt.data.slice(0, 21) === 'data:image/png;base64'\n", - " ) {\n", - " fig.imageObj.src = evt.data;\n", - " fig.updated_canvas_event();\n", - " fig.waiting = false;\n", - " return;\n", - " }\n", - "\n", - " var msg = JSON.parse(evt.data);\n", - " var msg_type = msg['type'];\n", - "\n", - " // Call the \"handle_{type}\" callback, which takes\n", - " // the figure and JSON message as its only arguments.\n", - " try {\n", - " var callback = fig['handle_' + msg_type];\n", - " } catch (e) {\n", - " console.log(\n", - " \"No handler for the '\" + msg_type + \"' message type: \",\n", - " msg\n", - " );\n", - " return;\n", - " }\n", - "\n", - " if (callback) {\n", - " try {\n", - " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", - " callback(fig, msg);\n", - " } catch (e) {\n", - " console.log(\n", - " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", - " e,\n", - " e.stack,\n", - " msg\n", - " );\n", - " }\n", - " }\n", - " };\n", - "};\n", - "\n", - "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n", - "mpl.findpos = function (e) {\n", - " //this section is from http://www.quirksmode.org/js/events_properties.html\n", - " var targ;\n", - " if (!e) {\n", - " e = window.event;\n", - " }\n", - " if (e.target) {\n", - " targ = e.target;\n", - " } else if (e.srcElement) {\n", - " targ = e.srcElement;\n", - " }\n", - " if (targ.nodeType === 3) {\n", - " // defeat Safari bug\n", - " targ = targ.parentNode;\n", - " }\n", - "\n", - " // pageX,Y are the mouse positions relative to the document\n", - " var boundingRect = targ.getBoundingClientRect();\n", - " var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n", - " var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n", - "\n", - " return { x: x, y: y };\n", - "};\n", - "\n", - "/*\n", - " * return a copy of an object with only non-object keys\n", - " * we need this to avoid circular references\n", - " * http://stackoverflow.com/a/24161582/3208463\n", - " */\n", - "function simpleKeys(original) {\n", - " return Object.keys(original).reduce(function (obj, key) {\n", - " if (typeof original[key] !== 'object') {\n", - " obj[key] = original[key];\n", - " }\n", - " return obj;\n", - " }, {});\n", - "}\n", - "\n", - "mpl.figure.prototype.mouse_event = function (event, name) {\n", - " var canvas_pos = mpl.findpos(event);\n", - "\n", - " if (name === 'button_press') {\n", - " this.canvas.focus();\n", - " this.canvas_div.focus();\n", - " }\n", - "\n", - " var x = canvas_pos.x * this.ratio;\n", - " var y = canvas_pos.y * this.ratio;\n", - "\n", - " this.send_message(name, {\n", - " x: x,\n", - " y: y,\n", - " button: event.button,\n", - " step: event.step,\n", - " guiEvent: simpleKeys(event),\n", - " });\n", - "\n", - " /* This prevents the web browser from automatically changing to\n", - " * the text insertion cursor when the button is pressed. We want\n", - " * to control all of the cursor setting manually through the\n", - " * 'cursor' event from matplotlib */\n", - " event.preventDefault();\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", - " // Handle any extra behaviour associated with a key event\n", - "};\n", - "\n", - "mpl.figure.prototype.key_event = function (event, name) {\n", - " // Prevent repeat events\n", - " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", - " return;\n", - " } else {\n", - " this._key = event.which;\n", - " }\n", - " }\n", - " if (name === 'key_release') {\n", - " this._key = null;\n", - " }\n", - "\n", - " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", - " value += 'ctrl+';\n", - " }\n", - " if (event.altKey && event.which !== 18) {\n", - " value += 'alt+';\n", - " }\n", - " if (event.shiftKey && event.which !== 16) {\n", - " value += 'shift+';\n", - " }\n", - "\n", - " value += 'k';\n", - " value += event.which.toString();\n", - "\n", - " this._key_event_extra(event, name);\n", - "\n", - " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", - " return false;\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", - " if (name === 'download') {\n", - " this.handle_save(this, null);\n", - " } else {\n", - " this.send_message('toolbar_button', { name: name });\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", - " this.message.textContent = tooltip;\n", - "};\n", - "\n", - "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", - "// prettier-ignore\n", - "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", - "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", - "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", - "\n", - "mpl.default_extension = \"png\";/* global mpl */\n", - "\n", - "var comm_websocket_adapter = function (comm) {\n", - " // Create a \"websocket\"-like object which calls the given IPython comm\n", - " // object with the appropriate methods. Currently this is a non binary\n", - " // socket, so there is still some room for performance tuning.\n", - " var ws = {};\n", - "\n", - " ws.close = function () {\n", - " comm.close();\n", - " };\n", - " ws.send = function (m) {\n", - " //console.log('sending', m);\n", - " comm.send(m);\n", - " };\n", - " // Register the callback with on_msg.\n", - " comm.on_msg(function (msg) {\n", - " //console.log('receiving', msg['content']['data'], msg);\n", - " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", - " });\n", - " return ws;\n", - "};\n", - "\n", - "mpl.mpl_figure_comm = function (comm, msg) {\n", - " // This is the function which gets called when the mpl process\n", - " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", - "\n", - " var id = msg.content.data.id;\n", - " // Get hold of the div created by the display call when the Comm\n", - " // socket was opened in Python.\n", - " var element = document.getElementById(id);\n", - " var ws_proxy = comm_websocket_adapter(comm);\n", - "\n", - " function ondownload(figure, _format) {\n", - " window.open(figure.canvas.toDataURL());\n", - " }\n", - "\n", - " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", - "\n", - " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", - " // web socket which is closed, not our websocket->open comm proxy.\n", - " ws_proxy.onopen();\n", - "\n", - " fig.parent_element = element;\n", - " fig.cell_info = mpl.find_output_cell(\"
\");\n", - " if (!fig.cell_info) {\n", - " console.error('Failed to find cell for figure', id, fig);\n", - " return;\n", - " }\n", - " fig.cell_info[0].output_area.element.on(\n", - " 'cleared',\n", - " { fig: fig },\n", - " fig._remove_fig_handler\n", - " );\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_close = function (fig, msg) {\n", - " var width = fig.canvas.width / fig.ratio;\n", - " fig.cell_info[0].output_area.element.off(\n", - " 'cleared',\n", - " fig._remove_fig_handler\n", - " );\n", - " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", - "\n", - " // Update the output cell to use the data from the current canvas.\n", - " fig.push_to_output();\n", - " var dataURL = fig.canvas.toDataURL();\n", - " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", - " // the notebook keyboard shortcuts fail.\n", - " IPython.keyboard_manager.enable();\n", - " fig.parent_element.innerHTML =\n", - " '';\n", - " fig.close_ws(fig, msg);\n", - "};\n", - "\n", - "mpl.figure.prototype.close_ws = function (fig, msg) {\n", - " fig.send_message('closing', msg);\n", - " // fig.ws.close()\n", - "};\n", - "\n", - "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", - " // Turn the data on the canvas into data in the output cell.\n", - " var width = this.canvas.width / this.ratio;\n", - " var dataURL = this.canvas.toDataURL();\n", - " this.cell_info[1]['text/html'] =\n", - " '';\n", - "};\n", - "\n", - "mpl.figure.prototype.updated_canvas_event = function () {\n", - " // Tell IPython that the notebook contents must change.\n", - " IPython.notebook.set_dirty(true);\n", - " this.send_message('ack', {});\n", - " var fig = this;\n", - " // Wait a second, then push the new image to the DOM so\n", - " // that it is saved nicely (might be nice to debounce this).\n", - " setTimeout(function () {\n", - " fig.push_to_output();\n", - " }, 1000);\n", - "};\n", - "\n", - "mpl.figure.prototype._init_toolbar = function () {\n", - " var fig = this;\n", - "\n", - " var toolbar = document.createElement('div');\n", - " toolbar.classList = 'btn-toolbar';\n", - " this.root.appendChild(toolbar);\n", - "\n", - " function on_click_closure(name) {\n", - " return function (_event) {\n", - " return fig.toolbar_button_onclick(name);\n", - " };\n", - " }\n", - "\n", - " function on_mouseover_closure(tooltip) {\n", - " return function (event) {\n", - " if (!event.currentTarget.disabled) {\n", - " return fig.toolbar_button_onmouseover(tooltip);\n", - " }\n", - " };\n", - " }\n", - "\n", - " fig.buttons = {};\n", - " var buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " var button;\n", - " for (var toolbar_ind in mpl.toolbar_items) {\n", - " var name = mpl.toolbar_items[toolbar_ind][0];\n", - " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", - " var image = mpl.toolbar_items[toolbar_ind][2];\n", - " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", - "\n", - " if (!name) {\n", - " /* Instead of a spacer, we start a new button group. */\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - " buttonGroup = document.createElement('div');\n", - " buttonGroup.classList = 'btn-group';\n", - " continue;\n", - " }\n", - "\n", - " button = fig.buttons[name] = document.createElement('button');\n", - " button.classList = 'btn btn-default';\n", - " button.href = '#';\n", - " button.title = name;\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', on_click_closure(method_name));\n", - " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", - " buttonGroup.appendChild(button);\n", - " }\n", - "\n", - " if (buttonGroup.hasChildNodes()) {\n", - " toolbar.appendChild(buttonGroup);\n", - " }\n", - "\n", - " // Add the status bar.\n", - " var status_bar = document.createElement('span');\n", - " status_bar.classList = 'mpl-message pull-right';\n", - " toolbar.appendChild(status_bar);\n", - " this.message = status_bar;\n", - "\n", - " // Add the close button to the window.\n", - " var buttongrp = document.createElement('div');\n", - " buttongrp.classList = 'btn-group inline pull-right';\n", - " button = document.createElement('button');\n", - " button.classList = 'btn btn-mini btn-primary';\n", - " button.href = '#';\n", - " button.title = 'Stop Interaction';\n", - " button.innerHTML = '';\n", - " button.addEventListener('click', function (_evt) {\n", - " fig.handle_close(fig, {});\n", - " });\n", - " button.addEventListener(\n", - " 'mouseover',\n", - " on_mouseover_closure('Stop Interaction')\n", - " );\n", - " buttongrp.appendChild(button);\n", - " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", - " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", - "};\n", - "\n", - "mpl.figure.prototype._remove_fig_handler = function (event) {\n", - " var fig = event.data.fig;\n", - " if (event.target !== this) {\n", - " // Ignore bubbled events from children.\n", - " return;\n", - " }\n", - " fig.close_ws(fig, {});\n", - "};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (el) {\n", - " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (el) {\n", - " // this is important to make the div 'focusable\n", - " el.setAttribute('tabindex', 0);\n", - " // reach out to IPython and tell the keyboard manager to turn it's self\n", - " // off when our div gets focus\n", - "\n", - " // location in version 3\n", - " if (IPython.notebook.keyboard_manager) {\n", - " IPython.notebook.keyboard_manager.register_events(el);\n", - " } else {\n", - " // location in version 2\n", - " IPython.keyboard_manager.register_events(el);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", - " var manager = IPython.notebook.keyboard_manager;\n", - " if (!manager) {\n", - " manager = IPython.keyboard_manager;\n", - " }\n", - "\n", - " // Check for shift+enter\n", - " if (event.shiftKey && event.which === 13) {\n", - " this.canvas_div.blur();\n", - " // select the cell after this one\n", - " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", - " IPython.notebook.select(index + 1);\n", - " }\n", - "};\n", - "\n", - "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", - " fig.ondownload(fig, null);\n", - "};\n", - "\n", - "mpl.find_output_cell = function (html_output) {\n", - " // Return the cell and output element which can be found *uniquely* in the notebook.\n", - " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", - " // IPython event is triggered only after the cells have been serialised, which for\n", - " // our purposes (turning an active figure into a static one), is too late.\n", - " var cells = IPython.notebook.get_cells();\n", - " var ncells = cells.length;\n", - " for (var i = 0; i < ncells; i++) {\n", - " var cell = cells[i];\n", - " if (cell.cell_type === 'code') {\n", - " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", - " var data = cell.output_area.outputs[j];\n", - " if (data.data) {\n", - " // IPython >= 3 moved mimebundle to data attribute of output\n", - " data = data.data;\n", - " }\n", - " if (data['text/html'] === html_output) {\n", - " return [cell, data, j];\n", - " }\n", - " }\n", - " }\n", - " }\n", - "};\n", - "\n", - "// Register the function which deals with the matplotlib target/channel.\n", - "// The kernel may be null if the page has been refreshed.\n", - "if (IPython.notebook.kernel !== null) {\n", - " IPython.notebook.kernel.comm_manager.register_target(\n", - " 'matplotlib',\n", - " mpl.mpl_figure_comm\n", - " );\n", - "}\n" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/javascript": [ - "/* Put everything inside the global mpl namespace */\n", - "/* global mpl */\n", - "window.mpl = {};\n", - "\n", - "mpl.get_websocket_type = function () {\n", - " if (typeof WebSocket !== 'undefined') {\n", - " return WebSocket;\n", - " } else if (typeof MozWebSocket !== 'undefined') {\n", - " return MozWebSocket;\n", - " } else {\n", - " alert(\n", - " 'Your browser does not have WebSocket support. ' +\n", - " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", - " 'Firefox 4 and 5 are also supported but you ' +\n", - " 'have to enable WebSockets in about:config.'\n", - " );\n", - " }\n", - "};\n", - "\n", - "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", - " this.id = figure_id;\n", - "\n", - " this.ws = websocket;\n", - "\n", - " this.supports_binary = this.ws.binaryType !== undefined;\n", - "\n", - " if (!this.supports_binary) {\n", - " var warnings = document.getElementById('mpl-warnings');\n", - " if (warnings) {\n", - " warnings.style.display = 'block';\n", - " warnings.textContent =\n", - " 'This browser does not support binary websocket messages. ' +\n", - " 'Performance may be slow.';\n", - " }\n", - " }\n", - "\n", - " this.imageObj = new Image();\n", - "\n", - " this.context = undefined;\n", - " this.message = undefined;\n", - " this.canvas = undefined;\n", - " this.rubberband_canvas = undefined;\n", - " this.rubberband_context = undefined;\n", - " this.format_dropdown = undefined;\n", - "\n", - " this.image_mode = 'full';\n", - "\n", - " this.root = document.createElement('div');\n", - " this.root.setAttribute('style', 'display: inline-block');\n", - " this._root_extra_style(this.root);\n", - "\n", - " parent_element.appendChild(this.root);\n", - "\n", - " this._init_header(this);\n", - " this._init_canvas(this);\n", - " this._init_toolbar(this);\n", - "\n", - " var fig = this;\n", - "\n", - " this.waiting = false;\n", - "\n", - " this.ws.onopen = function () {\n", - " fig.send_message('supports_binary', { value: fig.supports_binary });\n", - " fig.send_message('send_image_mode', {});\n", - " if (fig.ratio !== 1) {\n", - " fig.send_message('set_dpi_ratio', { dpi_ratio: fig.ratio });\n", - " }\n", - " fig.send_message('refresh', {});\n", - " };\n", - "\n", - " this.imageObj.onload = function () {\n", - " if (fig.image_mode === 'full') {\n", - " // Full images could contain transparency (where diff images\n", - " // almost always do), so we need to clear the canvas so that\n", - " // there is no ghosting.\n", - " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", - " }\n", - " fig.context.drawImage(fig.imageObj, 0, 0);\n", - " };\n", - "\n", - " this.imageObj.onunload = function () {\n", - " fig.ws.close();\n", - " };\n", - "\n", - " this.ws.onmessage = this._make_on_message_function(this);\n", - "\n", - " this.ondownload = ondownload;\n", - "};\n", - "\n", - "mpl.figure.prototype._init_header = function () {\n", - " var titlebar = document.createElement('div');\n", - " titlebar.classList =\n", - " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", - " var titletext = document.createElement('div');\n", - " titletext.classList = 'ui-dialog-title';\n", - " titletext.setAttribute(\n", - " 'style',\n", - " 'width: 100%; text-align: center; padding: 3px;'\n", - " );\n", - " titlebar.appendChild(titletext);\n", - " this.root.appendChild(titlebar);\n", - " this.header = titletext;\n", - "};\n", - "\n", - "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", - "\n", - "mpl.figure.prototype._init_canvas = function () {\n", - " var fig = this;\n", - "\n", - " var canvas_div = (this.canvas_div = document.createElement('div'));\n", - " canvas_div.setAttribute(\n", - " 'style',\n", - " 'border: 1px solid #ddd;' +\n", - " 'box-sizing: content-box;' +\n", - " 'clear: both;' +\n", - " 'min-height: 1px;' +\n", - " 'min-width: 1px;' +\n", - " 'outline: 0;' +\n", - " 'overflow: hidden;' +\n", - " 'position: relative;' +\n", - " 'resize: both;'\n", - " );\n", - "\n", - " function on_keyboard_event_closure(name) {\n", - " return function (event) {\n", - " return fig.key_event(event, name);\n", - " };\n", - " }\n", - "\n", - " canvas_div.addEventListener(\n", - " 'keydown',\n", - " on_keyboard_event_closure('key_press')\n", - " );\n", - " canvas_div.addEventListener(\n", - " 'keyup',\n", - " on_keyboard_event_closure('key_release')\n", - " );\n", - "\n", - " this._canvas_extra_style(canvas_div);\n", - " this.root.appendChild(canvas_div);\n", - "\n", - " var canvas = (this.canvas = document.createElement('canvas'));\n", - " canvas.classList.add('mpl-canvas');\n", - " canvas.setAttribute('style', 'box-sizing: content-box;');\n", - "\n", - " this.context = canvas.getContext('2d');\n", - "\n", - " var backingStore =\n", - " this.context.backingStorePixelRatio ||\n", - " this.context.webkitBackingStorePixelRatio ||\n", - " this.context.mozBackingStorePixelRatio ||\n", - " this.context.msBackingStorePixelRatio ||\n", - " this.context.oBackingStorePixelRatio ||\n", - " this.context.backingStorePixelRatio ||\n", - " 1;\n", - "\n", - " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", - "\n", - " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", - " 'canvas'\n", - " ));\n", - " rubberband_canvas.setAttribute(\n", - " 'style',\n", - " 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n", - " );\n", - "\n", - " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", - " if (this.ResizeObserver === undefined) {\n", - " if (window.ResizeObserver !== undefined) {\n", - " this.ResizeObserver = window.ResizeObserver;\n", - " } else {\n", - " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", - " this.ResizeObserver = obs.ResizeObserver;\n", - " }\n", - " }\n", - "\n", - " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", - " var nentries = entries.length;\n", - " for (var i = 0; i < nentries; i++) {\n", - " var entry = entries[i];\n", - " var width, height;\n", - " if (entry.contentBoxSize) {\n", - " if (entry.contentBoxSize instanceof Array) {\n", - " // Chrome 84 implements new version of spec.\n", - " width = entry.contentBoxSize[0].inlineSize;\n", - " height = entry.contentBoxSize[0].blockSize;\n", - " } else {\n", - " // Firefox implements old version of spec.\n", - " width = entry.contentBoxSize.inlineSize;\n", - " height = entry.contentBoxSize.blockSize;\n", - " }\n", - " } else {\n", - " // Chrome <84 implements even older version of spec.\n", - " width = entry.contentRect.width;\n", - " height = entry.contentRect.height;\n", - " }\n", - "\n", - " // Keep the size of the canvas and rubber band canvas in sync with\n", - " // the canvas container.\n", - " if (entry.devicePixelContentBoxSize) {\n", - " // Chrome 84 implements new version of spec.\n", - " canvas.setAttribute(\n", - " 'width',\n", - " entry.devicePixelContentBoxSize[0].inlineSize\n", - " );\n", - " canvas.setAttribute(\n", - " 'height',\n", - " entry.devicePixelContentBoxSize[0].blockSize\n", - " );\n", - " } else {\n", - " canvas.setAttribute('width', width * fig.ratio);\n", - " canvas.setAttribute('height', height * fig.ratio);\n", - " }\n", - " canvas.setAttribute(\n", - " 'style',\n", - " 'width: ' + width + 'px; height: ' + height + 'px;'\n", - " );\n", - "\n", - " rubberband_canvas.setAttribute('width', width);\n", - " rubberband_canvas.setAttribute('height', height);\n", - "\n", - " // And update the size in Python. We ignore the initial 0/0 size\n", - " // that occurs as the element is placed into the DOM, which should\n", - " // otherwise not happen due to the minimum size styling.\n", - " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", - " fig.request_resize(width, height);\n", - " }\n", - " }\n", - " });\n", - " this.resizeObserverInstance.observe(canvas_div);\n", - "\n", - " function on_mouse_event_closure(name) {\n", - " return function (event) {\n", - " return fig.mouse_event(event, name);\n", - " };\n", - " }\n", - "\n", - " rubberband_canvas.addEventListener(\n", - " 'mousedown',\n", - " on_mouse_event_closure('button_press')\n", - " );\n", " rubberband_canvas.addEventListener(\n", - " 'mouseup',\n", - " on_mouse_event_closure('button_release')\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", @@ -104465,11 +11918,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -104479,7 +11935,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -104598,10 +12054,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -104609,18 +12065,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -104645,7 +12100,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -104655,6 +12110,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -104665,8 +12133,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -104919,7 +12393,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -104927,7 +12401,37 @@ }, "metadata": {}, "output_type": "display_data" - }, + } + ], + "source": [ + "fig, ax = plt.subplots(figsize=(9,9))\n", + "pmt_array = np.stack(list(pmt_locations.values()))\n", + "ax.scatter(pmt_array[:,0], pmt_array[:,1], marker='o', label=\"seed pmt position\")\n", + "ax.scatter(reco_transformed[:,0], reco_transformed[:,1], marker='+', label=\"reconstructed pmt position\", color=\"green\")\n", + "ax.scatter(camera_positions[:,0], camera_positions[:,1], marker='*', label=\"fitted camera position\", zorder=1, color=\"orange\")\n", + "for i, p in enumerate(camera_positions):\n", + " ax.text(p[0], p[1], fitter_all.index_image[i], size=7, zorder=4, color='k')\n", + "for i, (p, o) in enumerate(zip(camera_positions, camera_orientations)):\n", + " fitarrow = plt.arrow(p[0], p[1], o[0,2]*200, o[1,2]*200, color=\"orange\", width=0.1, head_width=20, head_length=30)\n", + "for i, (p, y) in enumerate(zip(camera_positions, drone_yaw)):\n", + " dronearrow = plt.arrow(p[0], p[1], np.cos(y)*160, np.sin(y)*160, color=\"black\", width=0.01, head_width=20, head_length=30)\n", + "ax.set_ylim((-1800,1800))\n", + "ax.set_xlim((-1800,1800))\n", + "handles, labels = ax.get_legend_handles_labels()\n", + "handles.extend((fitarrow, dronearrow))\n", + "labels.extend((\"fitted camera yaw\", \"drone sensor yaw\"))\n", + "plt.legend(handles=handles, labels=labels, loc=0, handler_map={mpatches.FancyArrow : HandlerArrow()})\n", + "fig.tight_layout()\n", + "fig.savefig(saveLocation+\"top\"+imageExtension)" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": { + "scrolled": false + }, + "outputs": [ { "data": { "application/javascript": [ @@ -105178,6 +12682,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -105435,11 +12943,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -105449,7 +12960,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -105568,10 +13079,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -105579,18 +13090,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -105615,7 +13125,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -105625,6 +13135,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -105635,8 +13158,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -105889,7 +13418,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -105900,118 +13429,33 @@ } ], "source": [ - "#images_to_plot = images ['792']\n", - "for test_image in images_to_plot:\n", - " fig, ax = plt.subplots(figsize=(12,9))\n", - " coords = np.stack(list(common_image_feature_locations[test_image].values()))\n", - " repro_coords = np.stack(list(reprojected_points[test_image].values()))\n", - " ax.scatter(coords[:,0], 3000-coords[:,1], marker='.', label='detected')\n", - " ax.scatter(repro_coords[:,0], 3000-repro_coords[:,1], marker='.', label='reprojected')\n", - " for t, f in common_image_feature_locations[test_image].items():\n", - " ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='k')\n", - "# for t, f in reprojected_points[fitter_pmts.index_image[test_image]].items():\n", - "# ax.text(f[0], 3000-f[1], t, size=6, zorder=4, color='gray')\n", - " ax.set_title(\"Image {}\".format(test_image))\n", - " ax.set_ylim(0, 3000)\n", - " ax.set_xlim(0, 4000)\n", - " plt.legend(loc=0)\n", - " fig.tight_layout()\n", - " plt.savefig(saveLocation+\"image_plots/\"+test_image+\"-plot\"+imageExtension)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Save results to txt file" - ] - }, - { - "cell_type": "code", - "execution_count": 39, - "metadata": {}, - "outputs": [], - "source": [ - "fitter_all.save_result(saveLocation+\"SK_ring_features_relabelled.txt\", saveLocation+\"SK_ring_cameras_relabelled.txt\")" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Save results to pickle" - ] - }, - { - "cell_type": "code", - "execution_count": 40, - "metadata": {}, - "outputs": [], - "source": [ - "with open(saveLocation+\"SK_ring_relabelled.pkl\", 'wb') as output:\n", - " pickle.dump(fitter_all, output, pickle.HIGHEST_PROTOCOL)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Plots of reconstructed geometry" - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [], - "source": [ - "from matplotlib.legend_handler import HandlerPatch\n", - "import matplotlib.patches as mpatches\n", - "class HandlerArrow(HandlerPatch):\n", - " def create_artists(self, legend, orig_handle,\n", - " xdescent, ydescent, width, height, fontsize, trans):\n", - " p = mpatches.FancyArrow(0, 0.5*height, width, 0, length_includes_head=True, head_width=0.75*height )\n", - " self.update_prop(p, orig_handle, legend)\n", - " p.set_transform(trans)\n", - " return [p]" + "fig, ax = plt.subplots(figsize=(9,9))\n", + "pmt_array = np.stack(list(pmt_locations.values()))\n", + "ax.scatter(pmt_array[:,0], pmt_array[:,1], marker='o', label=\"PMT position\")\n", + "#ax.scatter(reco_transformed[:,0], reco_transformed[:,1], marker='+', label=\"reconstructed pmt position\", color=\"green\")\n", + "ax.scatter(camera_positions[:,0], camera_positions[:,1], marker='*', label=\"Fitted camera position\", zorder=1, color=\"orange\", s=100)\n", + "#for i, p in enumerate(camera_positions):\n", + "# ax.text(p[0], p[1], fitter_all.index_image[i], size=7, zorder=4, color='k')\n", + "for i, (p, o) in enumerate(zip(camera_positions, camera_orientations)):\n", + " fitarrow = plt.arrow(p[0], p[1], o[0,2]*200, o[1,2]*200, color=\"orange\", width=0.1, head_width=20, head_length=30)\n", + "for i, (p, y) in enumerate(zip(camera_positions, drone_yaw)):\n", + " dronearrow = plt.arrow(p[0], p[1], np.cos(y)*160, np.sin(y)*160, color=\"black\", width=0.01, head_width=20, head_length=30)\n", + "ax.set_ylim((-1800,1800))\n", + "ax.set_xlim((-1800,1800))\n", + "handles, labels = ax.get_legend_handles_labels()\n", + "handles.extend((fitarrow, dronearrow))\n", + "labels.extend((\"Fitted camera direction\", \"Drone sensor direction\"))\n", + "plt.legend(handles=handles, labels=labels, loc=0, handler_map={mpatches.FancyArrow : HandlerArrow()})\n", + "ax.axes.xaxis.set_visible(False)\n", + "ax.axes.yaxis.set_visible(False)\n", + "fig.tight_layout()\n", + "#fig.savefig(saveLocation+\"top\"+imageExtension)" ] }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 200, "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([154.0157751, 148.0157751, 141.0157751, 137.0157751, 136.0157751,\n", - " 123.0157751, 122.0157751, 113.0157751, 110.0157751, 103.0157751,\n", - " 100.0157751, 95.0157751, 89.0157751, 81.0157751, 78.0157751,\n", - " 70.0157751, 60.0157751, 59.0157751, 49.0157751, 46.0157751,\n", - " 40.0157751, 35.0157751, 29.0157751, 17.0157751, 10.0157751,\n", - " -3.9842249, -10.9842249, 342.0157751, 335.0157751, 315.0157751,\n", - " 304.0157751, 297.0157751, 284.0157751, 277.0157751, 259.0157751,\n", - " 248.0157751, 241.0157751, 232.0157751, 220.0157751, 217.0157751,\n", - " 212.0157751, 202.0157751, 194.0157751, 186.0157751, 185.0157751,\n", - " 183.0157751, 174.0157751, 174.0157751, 168.0157751, 162.0157751,\n", - " 152.0157751])" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "drone_yaw*180/np.pi" - ] - }, - { - "cell_type": "code", - "execution_count": 43, - "metadata": { - "scrolled": false - }, "outputs": [ { "data": { @@ -106263,6 +13707,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -106520,11 +13968,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -106534,7 +13985,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -106653,10 +14104,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -106664,18 +14115,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -106700,7 +14150,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -106710,6 +14160,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -106720,8 +14183,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -106974,7 +14443,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -106985,31 +14454,29 @@ } ], "source": [ - "fig, ax = plt.subplots(figsize=(9,9))\n", + "fig, ax = plt.subplots(figsize=(16,6))\n", "pmt_array = np.stack(list(pmt_locations.values()))\n", - "ax.scatter(pmt_array[:,0], pmt_array[:,1], marker='o', label=\"seed pmt position\")\n", - "ax.scatter(reco_transformed[:,0], reco_transformed[:,1], marker='+', label=\"reconstructed pmt position\", color=\"green\")\n", - "ax.scatter(camera_positions[:,0], camera_positions[:,1], marker='*', label=\"fitted camera position\", zorder=1, color=\"orange\")\n", + "ax.scatter(np.arctan2(pmt_array[:,1],pmt_array[:,0]), pmt_array[:,2], marker='o', label=\"seed pmt position\")\n", + "ax.scatter(np.arctan2(camera_positions[:,1], camera_positions[:,0]), camera_positions[:,2], marker='*', label=\"fitted camera position\", zorder=1)\n", + "ax.scatter(np.arctan2(reco_transformed[:,1], reco_transformed[:,0]), reco_transformed[:,2], marker='+', label=\"reconstructed pmt position\")\n", "for i, p in enumerate(camera_positions):\n", - " ax.text(p[0], p[1], fitter_all.index_image[i], size=7, zorder=4, color='k')\n", - "for i, (p, o) in enumerate(zip(camera_positions, camera_orientations)):\n", - " fitarrow = plt.arrow(p[0], p[1], o[0,2]*200, o[1,2]*200, color=\"orange\", width=0.1, head_width=20, head_length=30)\n", - "for i, (p, y) in enumerate(zip(camera_positions, drone_yaw)):\n", - " dronearrow = plt.arrow(p[0], p[1], np.cos(y)*160, np.sin(y)*160, color=\"black\", width=0.01, head_width=20, head_length=30)\n", - "ax.set_ylim((-1800,1800))\n", - "ax.set_xlim((-1800,1800))\n", - "handles, labels = ax.get_legend_handles_labels()\n", - "handles.extend((fitarrow, dronearrow))\n", - "labels.extend((\"fitted camera yaw\", \"drone sensor yaw\"))\n", - "plt.legend(handles=handles, labels=labels, loc=0, handler_map={mpatches.FancyArrow : HandlerArrow()})\n", + " ax.text(np.arctan2(p[1],p[0]), p[2], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", + "ax.set_xlim((-np.pi,np.pi))\n", + "ax.set_ylim((100,500))\n", + "plt.legend(loc=0)\n", "fig.tight_layout()\n", - "fig.savefig(saveLocation+\"top\"+imageExtension)" + "fig.savefig(saveLocation+\"barrel\"+imageExtension)" ] }, { "cell_type": "code", "execution_count": 44, - "metadata": {}, + "metadata": { + "pycharm": { + "is_executing": false + }, + "scrolled": false + }, "outputs": [ { "data": { @@ -107261,6 +14728,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -107518,11 +14989,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -107532,7 +15006,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -107651,10 +15125,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -107662,18 +15136,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -107698,7 +15171,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -107708,6 +15181,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -107718,8 +15204,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -107972,7 +15464,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -107983,29 +15475,22 @@ } ], "source": [ - "fig, ax = plt.subplots(figsize=(16,6))\n", - "pmt_array = np.stack(list(pmt_locations.values()))\n", - "ax.scatter(np.arctan2(pmt_array[:,1],pmt_array[:,0]), pmt_array[:,2], marker='o', label=\"seed pmt position\")\n", - "ax.scatter(np.arctan2(camera_positions[:,1], camera_positions[:,0]), camera_positions[:,2], marker='*', label=\"fitted camera position\", zorder=1)\n", - "ax.scatter(np.arctan2(reco_transformed[:,1], reco_transformed[:,0]), reco_transformed[:,2], marker='+', label=\"reconstructed pmt position\")\n", - "for i, p in enumerate(camera_positions):\n", - " ax.text(np.arctan2(p[1],p[0]), p[2], fitter_all.index_image[i], size=7, zorder=4, color='k') \n", - "ax.set_xlim((-np.pi,np.pi))\n", - "ax.set_ylim((100,500))\n", + "fig = plt.figure(figsize=(12,9))\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.scatter(reco_transformed[:,0], reco_transformed[:,1], reco_transformed[:,2], marker='.', label=\"reconstructed\", zorder=3)\n", + "ax.scatter(pmt_array[:,0], pmt_array[:,1], pmt_array[:,2], marker='.', label=\"expected\", zorder=2)\n", + "for f in pmt_locations.keys():\n", + " i = fitter_all.feature_index[f]\n", + " ax.text(reco_transformed[i,0], reco_transformed[i,1], reco_transformed[i,2], f[:5], size=6, zorder=4, color='k') \n", + "#ax.scatter(camera_positions[:,0], camera_positions[:,1], camera_positions[:,2], marker='*', label=\"camera\", zorder=1)\n", "plt.legend(loc=0)\n", - "fig.tight_layout()\n", - "fig.savefig(saveLocation+\"barrel\"+imageExtension)" + "fig.tight_layout()" ] }, { "cell_type": "code", - "execution_count": 45, - "metadata": { - "pycharm": { - "is_executing": false - }, - "scrolled": false - }, + "execution_count": 201, + "metadata": {}, "outputs": [ { "data": { @@ -108257,6 +15742,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -108514,11 +16003,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -108528,7 +16020,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -108647,10 +16139,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -108658,18 +16150,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -108694,7 +16185,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -108704,6 +16195,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -108714,8 +16218,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -108968,7 +16478,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -108981,12 +16491,13 @@ "source": [ "fig = plt.figure(figsize=(12,9))\n", "ax = fig.add_subplot(111, projection='3d')\n", - "ax.scatter(reco_transformed[:,0], reco_transformed[:,1], reco_transformed[:,2], marker='.', label=\"reconstructed\", zorder=3)\n", - "ax.scatter(pmt_array[:,0], pmt_array[:,1], pmt_array[:,2], marker='.', label=\"expected\", zorder=2)\n", - "for f in pmt_locations.keys():\n", - " i = fitter_all.feature_index[f]\n", - " ax.text(reco_transformed[i,0], reco_transformed[i,1], reco_transformed[i,2], f[:5], size=6, zorder=4, color='k') \n", - "#ax.scatter(camera_positions[:,0], camera_positions[:,1], camera_positions[:,2], marker='*', label=\"camera\", zorder=1)\n", + "ax.scatter(reco_transformed[:,0], reco_transformed[:,1], reco_transformed[:,2], marker='.', label=\"reconstructed PMT\", zorder=3)\n", + "#ax.scatter(pmt_array[:,0], pmt_array[:,1], pmt_array[:,2], marker='.', label=\"expected\", zorder=2)\n", + "#for f in pmt_locations.keys():\n", + "# i = fitter_all.feature_index[f]\n", + "# ax.text(reco_transformed[i,0], reco_transformed[i,1], reco_transformed[i,2], f[:5], size=6, zorder=4, color='k') \n", + "ax.scatter(camera_positions[:,0], camera_positions[:,1], camera_positions[:,2], marker='*', label=\"reconstructed camera\", zorder=1)\n", + "ax.set_zlim3d(-1500,1500)\n", "plt.legend(loc=0)\n", "fig.tight_layout()" ] @@ -109000,7 +16511,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 202, "metadata": {}, "outputs": [ { @@ -109253,6 +16764,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -109510,11 +17025,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -109524,7 +17042,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -109643,10 +17161,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -109654,18 +17172,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -109690,7 +17207,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -109700,6 +17217,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -109710,8 +17240,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -109964,7 +17500,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -109987,17 +17523,17 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 203, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[[ 0 33 33 ... 3 39 38]\n", - " [ 0 384 383 ... 495 360 397]]\n", + "[[ 0 33 33 ... 39 3 38]\n", + " [ 0 379 378 ... 333 41 373]]\n", "0.0\n", - "02733-00\n" + "00593-00\n" ] } ], @@ -110017,7 +17553,7 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 311, "metadata": { "pycharm": { "is_executing": false @@ -110275,6 +17811,10 @@ " 'mouseup',\n", " on_mouse_event_closure('button_release')\n", " );\n", + " rubberband_canvas.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", " // Throttle sequential mouse events to 1 every 20ms.\n", " rubberband_canvas.addEventListener(\n", " 'mousemove',\n", @@ -110532,11 +18072,14 @@ "mpl.figure.prototype._make_on_message_function = function (fig) {\n", " return function socket_on_message(evt) {\n", " if (evt.data instanceof Blob) {\n", - " /* FIXME: We get \"Resource interpreted as Image but\n", - " * transferred with MIME type text/plain:\" errors on\n", - " * Chrome. But how to set the MIME type? It doesn't seem\n", - " * to be part of the websocket stream */\n", - " evt.data.type = 'image/png';\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", "\n", " /* Free the memory for the previous frames */\n", " if (fig.imageObj.src) {\n", @@ -110546,7 +18089,7 @@ " }\n", "\n", " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", - " evt.data\n", + " img\n", " );\n", " fig.updated_canvas_event();\n", " fig.waiting = false;\n", @@ -110665,10 +18208,10 @@ "mpl.figure.prototype.key_event = function (event, name) {\n", " // Prevent repeat events\n", " if (name === 'key_press') {\n", - " if (event.which === this._key) {\n", + " if (event.key === this._key) {\n", " return;\n", " } else {\n", - " this._key = event.which;\n", + " this._key = event.key;\n", " }\n", " }\n", " if (name === 'key_release') {\n", @@ -110676,18 +18219,17 @@ " }\n", "\n", " var value = '';\n", - " if (event.ctrlKey && event.which !== 17) {\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", " value += 'ctrl+';\n", " }\n", - " if (event.altKey && event.which !== 18) {\n", + " else if (event.altKey && event.key !== 'Alt') {\n", " value += 'alt+';\n", " }\n", - " if (event.shiftKey && event.which !== 16) {\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", " value += 'shift+';\n", " }\n", "\n", - " value += 'k';\n", - " value += event.which.toString();\n", + " value += 'k' + event.key;\n", "\n", " this._key_event_extra(event, name);\n", "\n", @@ -110712,7 +18254,7 @@ "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n", "\n", - "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n", "\n", "mpl.default_extension = \"png\";/* global mpl */\n", "\n", @@ -110722,6 +18264,19 @@ " // socket, so there is still some room for performance tuning.\n", " var ws = {};\n", "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", " ws.close = function () {\n", " comm.close();\n", " };\n", @@ -110732,8 +18287,14 @@ " // Register the callback with on_msg.\n", " comm.on_msg(function (msg) {\n", " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", - " ws.onmessage(msg['content']['data']);\n", + " ws.onmessage(data);\n", " });\n", " return ws;\n", "};\n", @@ -110986,7 +18547,7 @@ { "data": { "text/html": [ - "" + "" ], "text/plain": [ "" @@ -110998,9 +18559,9 @@ ], "source": [ "fig, ax = plt.subplots(figsize=(8,6))\n", - "ax.hist(linalg.norm(errors, axis=1), bins='auto')\n", - "ax.set_title(\"Reconstructed position distance from expected ({} images, {} features), mean = {:.2f} cm\".format(\n", - " nimages, nfeatures, linalg.norm(errors, axis=1).mean()))\n", + "ax.hist(np.sqrt(variance_3d), bins=range(20), color=\"b\", histtype=\"step\", label=f\"Estimated 3D position error\\nmean = {np.mean(np.sqrt(variance_3d)):.3} cm\")\n", + "ax.hist(linalg.norm(errors, axis=1), bins=range(20), color=\"r\", histtype=\"step\", label=f\"Reconstructed position distance\\nfrom expected geometry\\nmean = {np.mean(linalg.norm(errors, axis=1)):.2f} cm\")\n", + "plt.legend(loc=\"upper right\", prop={'size': 15})\n", "fig.tight_layout()\n", "fig.savefig(saveLocation+\"distance from expected.png\")" ] @@ -111029,7 +18590,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.2" + "version": "3.9.4" }, "pycharm": { "stem_cell": { diff --git a/WCTE_16cShort_led_simulation.ipynb b/WCTE_16cShort_led_simulation.ipynb new file mode 100644 index 0000000..7bf9bf3 --- /dev/null +++ b/WCTE_16cShort_led_simulation.ipynb @@ -0,0 +1,3552 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from scipy import linalg\n", + "from scipy.spatial.transform import Rotation as R\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.collections\n", + "import matplotlib.patches\n", + "import pg_fitter_tools as fit\n", + "import sk_geo_tools as geo\n", + "import cv2\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "#%matplotlib notebook\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def get_led_positions(led_count, mpmt_locations):\n", + " led_ring_radius = 24.\n", + " led_positions = {}\n", + " for k, v in mpmt_locations.items():\n", + " for i in range(led_count):\n", + " if abs(v[1]) > 100:\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count),0,np.cos(i*2*np.pi/led_count)])\n", + " else:\n", + " phi = np.arctan2(v[2], v[0])\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count)*np.sin(phi), np.cos(i*2*np.pi/led_count), -np.sin(i*2*np.pi/led_count)*np.cos(phi)])\n", + " return led_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def get_image_feature_locations(feature_positions, camera_matrix, distortion, camera_rotations, camera_translations, image_size):\n", + " image_feature_locations = {\n", + " i : {list(feature_positions.keys())[f]:v for f, v in enumerate(cv2.projectPoints(np.array(list(feature_positions.values())), r, t, camera_matrix, distortion)[0].reshape((-1,2)))\n", + " if v[0] > 0 and v[0] < image_size[0] and v[1] > 0 and v[1] < image_size[1]}\n", + " for i, (r, t) in enumerate(zip(camera_rotations, camera_translations))}\n", + " feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + " print(\"Feature in image counts:\", Counter(feature_counts.values()))\n", + " return image_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def get_smeared_feature_locations(image_feature_locations, pixel_error, image_size):\n", + " smeared_feature_locations = {}\n", + " for k, i in image_feature_locations.items():\n", + " smeared_feature_locations[k] = {}\n", + " for j, f in i.items():\n", + " smeared = np.random.normal(f, pixel_error)\n", + " if(smeared[0] > 0 and smeared[0] < image_size[0] and smeared[1] > 0 and smeared[1] < image_size[1]):\n", + " smeared_feature_locations[k][j] = smeared\n", + " smeared_feature_counts = Counter([f for i in smeared_feature_locations.values() for f in i.keys()])\n", + " print(\"Smeared feature in image counts:\", Counter(smeared_feature_counts.values()))\n", + " return smeared_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_led_simulation(feature_positions, image_feature_locations, focal_length, principle_point, radial_distortion, seed_error=1):\n", + " seed_feature_positions = {}\n", + " for i, f in feature_positions.items():\n", + " seed_feature_positions[i] = np.random.normal(f, seed_error)\n", + " fitter = fit.PhotogrammetryFitter(image_feature_locations, seed_feature_positions, focal_length, principle_point, radial_distortion)\n", + " return fitter" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_images(image_feature_locations, image_size):\n", + " for i in image_feature_locations.values():\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.rint(np.stack(list(i.values())))\n", + " ax.scatter(coords[:,0], -coords[:,1], marker='s', s=0.2)\n", + " ax.set_xlim((0, image_size[0]))\n", + " ax.set_ylim((-image_size[1], 0))\n", + " ax.axes.xaxis.set_visible(False)\n", + " ax.axes.yaxis.set_visible(False)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def run_led_fit(fitter, led_positions):\n", + " reco_cam_rotations, reco_cam_translations, reprojected_points = fitter.estimate_camera_poses()\n", + " reco_cam_rotations, reco_cam_translations, reco_locations = fitter.bundle_adjustment(reco_cam_rotations, reco_cam_translations)\n", + " \n", + " reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_locations)\n", + " print(\"mean reconstruction error:\", linalg.norm(reco_errors, axis=1).mean())\n", + " print(\"max reconstruction error:\", linalg.norm(reco_errors, axis=1).max())\n", + "\n", + " reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(reco_cam_rotations, reco_cam_translations)\n", + " cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + " cam_positions_translated = reco_cam_positions - translation\n", + " cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + " reco_led_positions = reco_positions_dict(reco_transformed, fitter.feature_index)\n", + " position_errors = linalg.norm(reco_errors, axis=1)\n", + "\n", + " return reco_led_positions, position_errors" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def reco_positions_dict(reco_positions, feature_index):\n", + " return {f: reco_positions[i] for f, i in feature_index.items()}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_centre_errors(reco_led_positions, mpmt_positions, led_count):\n", + " reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n", + " for k in mpmt_positions.keys()}\n", + " errors = np.array([linalg.norm(reco_mpmt_positions[k] - mpmt_positions[k]) for k in mpmt_positions.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_coun):\n", + " reco_orientations = {}\n", + " for k in mpmt_orientations.keys():\n", + " c, n = geo.fit_plane(np.array([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)]))\n", + " # flip normal if it is directed away from tank centre\n", + " if np.dot(n,c) > 0:\n", + " n = -n\n", + " reco_orientations[k] = n\n", + " errors = np.array([np.degrees(np.arccos(np.dot(reco_orientations[k], mpmt_orientations[k]))) for k in mpmt_orientations.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def make_fig(title=None, xlabel=None, ylabel=None, figsize=(8,6)):\n", + " fig, ax = plt.subplots(figsize=figsize)\n", + " ax.set_title(title)\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " fig.tight_layout()\n", + " return fig, ax" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_geometry(led_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter([l[0] for l in led_positions.values()], [l[2] for l in led_positions.values()], [l[1] for l in led_positions.values()], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_reconstruction(reco_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter(reco_positions[:,0], reco_positions[:,2], reco_positions[:,1], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "pmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_PMT_locations.txt\", delimiter=\" \")\n", + "#mpmt_locations = {k: v for k, v in pmt_locations.items() if int(k)%19==0}\n", + "mpmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_centrePMT_locations.txt\", delimiter=\" \")\n", + "mpmt_orientations = {k: np.array((0,-1,0)) if v[1]>100\n", + " else np.array((0,1,0)) if v[1]<-100\n", + " else np.array((-v[0],0,-v[2]))/np.sqrt(v[0]**2+v[2]**2)\n", + " for k, v in mpmt_locations.items()}\n", + "led_count = 12\n", + "led_positions = get_led_positions(led_count, mpmt_locations)" + ] + }, + { 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array([-0.98078528, 0. , -0.19509032]),\n", + " '1349': array([-0.83146961, 0. , -0.55557023]),\n", + " '1368': array([-0.55557023, 0. , -0.83146961]),\n", + " '1387': array([-0.19509032, 0. , -0.98078528]),\n", + " '1406': array([ 0.19509032, 0. , -0.98078528]),\n", + " '1425': array([ 0.55557023, 0. , -0.83146961]),\n", + " '1444': array([ 0.83146961, 0. , -0.55557023]),\n", + " '1463': array([ 0.98078528, 0. , -0.19509032]),\n", + " '1482': array([0.98078528, 0. , 0.19509032]),\n", + " '1501': array([0.83146961, 0. , 0.55557023]),\n", + " '1520': array([0.55557023, 0. , 0.83146961]),\n", + " '1539': array([0.19509032, 0. , 0.98078528]),\n", + " '1558': array([-0.19509032, 0. , 0.98078528]),\n", + " '1577': array([-0.55557023, 0. , 0.83146961]),\n", + " '1596': array([-0.83146961, 0. , 0.55557023]),\n", + " '1615': array([-0.98078528, 0. , 0.19509032]),\n", + " '1634': array([ 0, -1, 0]),\n", + " '1653': array([ 0, -1, 0]),\n", + " '1672': array([ 0, -1, 0]),\n", + " '1691': array([ 0, -1, 0]),\n", + " '1710': array([ 0, -1, 0]),\n", + " '1729': array([ 0, -1, 0]),\n", + " '1748': array([ 0, -1, 0]),\n", + " '1767': array([ 0, -1, 0]),\n", + " '1786': array([ 0, -1, 0]),\n", + " '1805': array([ 0, -1, 0]),\n", + " '1824': array([ 0, -1, 0]),\n", + " '1843': array([ 0, -1, 0]),\n", + " '1862': array([ 0, -1, 0]),\n", + " '1881': array([ 0, -1, 0]),\n", + " '1900': array([ 0, -1, 0]),\n", + " '1919': array([ 0, -1, 0]),\n", + " '1938': array([ 0, -1, 0]),\n", + " '1957': array([ 0, -1, 0]),\n", + " '1976': array([ 0, -1, 0]),\n", + " '1995': array([ 0, -1, 0]),\n", + " '2014': array([ 0, -1, 0])}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mpmt_orientations" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony A6000" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "focal_length = np.array([2925.84685880484, 2930.0351899542])\n", + "principle_point = np.array([3000, 2000])\n", + "radial_distortion = np.array([-0.251288719187471, 0.0622370807856553])#[-0.28009, 0.11246, -0.02736])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([6000, 4000])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 128.0\n", + "camera_positions = np.array([\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)]])\n", + "camera_directions = [[-1, -1.9, -1],\n", + " [-1, -1.9, 1],\n", + " [ 1, 1.9, -1],\n", + " [ 1, 1.9, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({2: 696, 4: 432, 3: 144})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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LN8AaXDQMMIMLM6mZ8g0wbuyiYStYsCJff+tX8+oFKN/100/B8qxgwYp8/QUgMv0UPM4KFqG08sXM118AImuln2pl3EEMJljs4taN8ddkbRhrDW2bNT8A5qix7cvcT03Jj6njDphDmHZ2MfXSQmGQY5EfQIu0fbFMyQ+XJbMlEyx2cevG+Gs0jLHID6BF2r5YpuTH1HEHzCHIBfzufD6Xvu/L8XhMuVUCACLQn9KKsSAXVrDgd7Z+AMB8+lNaZ4IFv7P1AwDm05/SOlEE2U20aEyZIykBQBQR+9NoYw7qZgWL3dhCAABswZiDLZlgsRtbCACALRhzsCVRBAEAACYaiyLoDBYAAMBCTLB2kvmwZea0AwA8IvP4J3PaM3IGayeZD1tmTjsAwCMyj38ypz0jK1g7OR6Ppeu6lIctM6d9C74SAZCVPmxc5vFP5rRnJMgFLOxwOJTT6VS6rvOViPTO53Pp+74cj8dQd9pE4f1QG30Y3E+QC9iIr0RtqvWr72VbSd/3eyclpFrfT63lma/pw2A+Z7BgYZcb7GlLrfvb3R1zW63vp9byzNf0YTCfCRbAAmodaBts3Vbr+6m1PANswRksAACAiZzBAlbhrAZQM20cMFXICZbGDPKo9ZA/QCnaOMgi0vwh5Bksh2shD2c1gJpp4yCHSPOHkBMsjRnkUeshf4BStHGQRaT5gyAXAAAAEwlyAQAAsDITLKoV6bAjAHCd/pramGAR1twGV+QnAIhvbn9tgkY0IYNcQCnzo8FEOuwIAFw3t7+OFD0OSjHBIrC5Da7ITwAQ39z+2gdVohFFEAAAYCJRBAEAAFZmgsVmHEKFetVWv2t7HuAH9Zu1NTHBUpFiENUP6lVb/a7teYAf1O8Yah6fNzHBUpFiOB6Ppeu69IdQa24QuG2rvF/y92yV5lrq98WWz7NUHm3ZNmkH21RLvtfWXmVV9fh8GIa7f759+zZk9Pb2NnRdN7y9ve2dFCrQdd1QShm6rts7KWxsq7xf8vcor/EtlUdb5rVy1Sb5zpJqGJ+XUt6HK3OmJiZY1CNCZYyQhqyyv7ut0r/k78n+zluwVB5tmdfZy1X29O8lwnuLkAa4GJtgCdNOKofDoZxOp9J1nTuuEpJ/QATaorzkHZGMhWl30TCpuEwwN/kHRKAtykvekYEVLOAP5/O59H1fjsdjeXl52Ts5AOloR6EdLhpuQC3RfXjc3DJQdUQfgA3MbUf15SgD+dkiWJFLo15KsS+5UXPLgK0XAPPMbUf15SgD+ZlgVcTgmLll4OXlRWPObpbcWmWbFnuZ247qy1EG8nMGC4BRW05UlowOtlWkMRM5gHY5gwVQttvbXsse+i3P5R2Px9J13SJfbZf8t26p5dyiegGwoGuXY439uGgY2NMSF0x2XTeUUoau6xZM2X6/Z20u9bytlveTqV7U8s6B/MrIRcPOYAFpLHHwd6u97bXsoXcu77Za3k+meiEAABCdM1jAYtY+j+K8C6CdAaIYO4NlggUsZqvAAgBr0Y4B9xLkguo4LB3PVoEFANaiHYtHf082Jli/U3nzqSV61y3ZyuXlPIptNUBW2dqxbP3EI1ro72vUQtkcY4L1O5X3a9EqSgtfGZVLAG5poZ+I1t9HGw9F1ULZHCOK4O9qifi1pmiRm5aO3hXxYLNyCcAtEfuJpfvTaNE6o42HoopYNrciyAV3izgBWZKDzQAwX+39ae3jIe4nyAWz7bkvfYvl+GhbEAAgo63607226mU7p8f2rGCRQu1fwwCAaYwN2NvYCpYzWKTQ8j5eAOBXxgZEZQULAABgImewAAAAVmaCBcBstd0LU9vzALCdKiZYOkKAfdV2oWRtzwOQTebxfRUTLB0hsIfMjf/SarvmoLbnmUM5B/aQeXxfRRRBUWQgnxouarw0/qWU5kMEX+6FqUVtzzNHDeW8hvYGWpN5fF/FBCtDR6hxh5/VMGjL3PjDvWoo5zW0N7CkDOPSDOP7MVVMsDLQuMPPahi0ZW784V41lPMa2htYknHpukywNqJxh5/VMGgDctDewM+MS9dVRZCLDC6Ne9Rl2EymHrjOdEA7U1oBiCdTP/JIWjM9X2TGpeuygkU6U5e1My2DZ0orAPFk6kceSWum56NdJlikM3VZO9MyeKa0AhBPpn7kkbRmej7a9TQMw91/+fn5eXh/f18xOQAAAPE9PT39NgzD8+c/dwYLAABgISZYpOfAKwDUSR9PRs1MsFTQel0OvPZ9v3dSAIAF6ePrVPu4vJkgF6LO1MuBVwCokz6+TrWPy5uZYKmg9XKBJADUSR9fp9rH5c1sEZxyoVrty5YAALC0e8fQtV903MwK1hS1L1sCAMDSjKG/a2YFa4rj8Vi6rqt22TIiq4YAwFKMK/ZhDP2dCdYVtS9bRiRKEORX04CmpmeBFhlX7MMY+jsTrAZFHDj44kFmEevUHmoa0NT0LI9Srsks4rhCnWrIMAx3/3z79m0gv67rhlLK0HXd3kmBYRiG4e3tbei6bnh7e9s7KQ9Rp77Lno8f1fQsj6qhXMtHIqmhTvGzUsr7cGXOJMhFg2oPjUk+2Q/FqlPf1RROuaZneVQN5Tp720JdaqhT3Ofp++TrPs/Pz8P7+/uKyQE+Op/Ppe/7cjweq97P3MpzAttqoW1p4Rkhqqenp9+GYXj+5c9NsCCuw+FQTqdT6brO11cAfqGfgP2MTbBsEYTAbCcA4Bb9BMRjBQsAAGCisRUsYdppmpCpALAe/SwtskWQpokwBQDr0c/SIitYgfjKs72IFxECQC30s/swptyXM1iBiAQEAMBcxpTbEEUwAZGAAACYy5hyX7YIBvLy8lJeX19dFLiQJZbHLbEDwG1z+0p97fKMKfdlBYtqLXGw1uFcALhtbl+pr6U2VrCo1hIHax3OZUmZv9JmTvsaMr+PzGknprl9pb6W2ghyAbCRzIeOt0j7+Xwufd+X4/E4a1vLUv/OLfISABcNV8TXR7Jau+xGPweQ+SvtFmm/bBPq+z7Ev3OLvBwX/fyrPpSslN1EhmG4++fbt2/DV97e3oau64a3t7cv/y6P6bpuKKUMXdftnRSCyFLv1i67c/99dWtfS5XjLPWhVkvUozXrYpZ6rhzzWZaym9nUeldKeR+uzJkWn2DJ/PVpdPksS71bu+zO/ffVLZhviXq0Zl3MUs+ztOtsJ0vZzWxqvRubYC1+BmuLve/Az9Q7gLpo12F7U+vd2BksQS5m0PgBAFAz491xglysYIuD1Jk5jAkARGe8cpvx7nQmWDNkjiK1BRUSlhU9Ohv3kY8Qi/HKbca7D7h2MGvs554gF3DhMCYsK3p0tovMdX+LtGfJR2hF5jaLfZWtoggC7dAp/Sx6lMSl/o2vZB78Z5mAZihrtfAugDEmWMBVcwYPaw5GMw5qMk8slpQx7y4yp31J2crymvk2510oT1A3EyyYqdaOMurgIdsAbxjqLSO0J1tZjvqxJ2M7do9s5QPWYoJFdbZu4HWU24qaLiCeqO1F1HTNtXV/WOt7JL+xCZZ7sCrVwp0Fh8OhnE6n0nVdeX19Xf33tfBOAeArW/eHW/f3ezDGyGnsHqw/7ZEY1ncJOVpKqbYxuoQL3Sps6MvLS7XvEgDutXV/uHV/v4cWxm0tMcGqVAuNkQkPANSvhf6+hXFbS2wRBAAAmGhsi+B/2SMxAAAANTLBAgAAWIgJFgAAwEJMsBI7n8/lcDiU8/m8d1IAAFiB8V4+oggmJqQnAEDdjPfyMcFKTEhPAIC6Ge/lY4tgYpd7Idz4Dblk3+6RPf1zZH/27OmHFhnv5WOCxd10zKyltbJ12e7R9/3eSXlI9vTPkf3Zs6d/itbaFbalfHGLLYLczR5g1tJa2cq+3SN7+ufI/uzZ0z9Fa+0K21K+uMUEi7u11DGzrdbK1mW7R1bZ0z9H9mfPnv4pWmtX2JbyxS1PwzDc/Zefn5+H9/f3FZMDAAAQ39PT02/DMDx//nNnsAAAABZiggUAALAQE6yKiXCzLO8TAPSHS/M+6yPIRcVEuFmW9wkA+sOleZ/1McGqmAg3y/I+AUB/uDTvsz7VbxFsedn1q5u/W343j3CTOgDoD6f6arzV+vuscTxa/QSrpVvrp8r2bmqsgADAdJnGBNnGW1ur8f1Uv0XQsuu4bO/GHmUAoJRcY4Js462t1fh+XDRMGufzufR9X47HY7PL6ACAMQExjF00bIIFAAAw0dgEq/ozWAAsK9PZhyW1+twATGOCBYTSyiA283PWeCD5HpmfO3N5m6KV5wRiqz7IBZBLpoPLc2R+zhoPJN8j83NnLm9TtPKcQGwmWEAomQexU2R+zsudLa3J/NyZy9sUrTwnEJsgFwAAABMJcsEu7IcHACIzVmFptgiyKvvhAYDIjFVYmgkWq7IfHgCIzFiFpTmDBQAAMJEzWIm1sDe4hWcEALZT+9ii9ufLzAQrgcyXW94r6jNqvADgtqh9ZdSxxVJqf77MnMFKoIW9wVGf0cFXALgtal8ZdWyxlNqfLzNnsOCG8/lc+r4vx+OxvLy87J0cAAhHX0mrnMFiEVG3Aazl5eWlvL6+6jBgomxtRbb0QiQt9ZXaCu5hgsUk9vsSRZZObs10zv2310xbtrZizfRGzif1CKbJ1raxk2EY7v759u3bQNve3t6GruuGt7e3vZPCxubk/Rrlpuu6oZQydF232L+5hjXTOfffXjNt2dqKNdMbOZ9ar0eP5nu28s1y5D0flVLehytzJhMs4C5zBjhrDI6ydHJrpnPuv53lHWYXOZ+ylIG10vlo25RlYgqsywSLKmQZDNQo2goWwFxWsHLy/olibIIliiCpHA6HcjqdStd1oULBAgDbMBYgirEogu7BIhV3PgBA24wFiM4KFgAAwETuwQIosUNmI38ymPOO5Q/QAhMsaFzkAc8aaZt7h8lad6BEzofPIt+fFfk+qy1FzaM18idyvkROG7Cia5Evxn5EEWRrIgWtL3K44Yjh3aOFi95D5PuzIt9ntaWoedTanXiR01YTYwX2UoRpJyOd0/oid0yR07a0TM+aKa1LyvTcmdI6V+RnjZy2mhgrsJexCZYgF4R2Pp9L3/fleDyWl5eXvZMDAARjrMBeBLkgpZeXl/L6+rpqg2mPPAAsb6v+dYuxAkzhHiyadzl0XUpxYSEALET/SqtMsGieCwsBYHn6V1rlDBYAAMBEzmABAACszASL9ASpAID66N/Jyhks0nOIFgDqo38nq5ArWL5YMMXxeCxd140eolWeACCer/rnr/p3+CjSeC/kBOvyxaLv+72T0oxIhXKqr+6/UJ5+ljmvx2R6pkxpnSPjc2ZM8yOyPGeWdE5R4zPN8VX/nPl+K3m9vVDjvWEY7v759u3bsIW3t7eh67rh7e1tk9/HMHRdN5RShq7r9k7K4pSnn9WY15meKVNa58j4nBnT/Igsz5klnVPU+Exz1Nw/y+vt7VGeSinvw5U5U8gJFturuZHjZzXmdaZnypTWOTI+Z8Y0PyLLc2ZJ5xQ1PhPXyes2jE2w3IO1g/P5XPq+L8fjMeWyNwAAuRh/Ls89WIGE2iPKbPZZA1Aj/VtdjD+3I0z7Di7RcETFqYMwsgDUSP9WF+PP7VjB2kHmqDj86t4wsr4EAhDFPX2SMOl1Mf7cjjNYsJHD4VBOp1Ppus6XQAB2pU+C+cbOYNkiCBuxNA9AFPokWI8tgoRXy9Y6S/MARFFDn1TL+ID6WMEiPIdsAYDPjA+IygSL8GxjAAA+Mz4gKlsECW/PbQy2HwDAuD37yRq2OVInEyy4oYVL+WqaRGZ6lkxpfUS258uW3kdkecYs6bxHTc8ypoV+EqayRRBuaGH7QU172DM9S6a0PiLb82VL7yOyPGOWdN6jpmcZ00I/CVOZYMENl+0HNaupc8z0LJnS+ohsz5ctvY/I8oxZ0nmPmp5lTAv9JEzlomEAAICJxi4adgYLgmhhrz4A69OfwL5sEYQgWtirD8D69CewLxMsCKKFvfoArE9/AvtyBgsAAGAiZ7AAAABWZoIFAACwEBMs4C6iUgH8oE0ExphgAXe5RKXq+37vpPzBAAfqF7WeR2wTgRhMsIC7HI/H0nVdqKhUSw9w5gzklh4ERh1UfpQhjUvI8JxrpPHRf3PptESdyERsE4EghmG4++fbt28DdXh7exu6rhve3t72Tgo8bOly3HXdUEoZuq7b9L/d4t9bw1ppnJOva7RtrebFo//m0mnRX1ELZbk+pZT34cqcyQSrURkGDLC1SAP7DB3xWmmMNNEdhnbz4tF/M8P7gj0Ye9XHBGtBNXQeNTzDGrwX2F+kiS4wnXp4Xfb3kj39axibYLlo+AGHw6GcTqfSdV15fX3dOzksSN4CwDz60jrJ11+5aHhBDrbWS94u65HD7hkCCgAxaXNi0JfWSb5OcG1Za+xnjS2Clhv5TJmoxyP7zR2Qn8f2uhicX7pPhEA1zsXUo7X6w33WLBcl6hksDRufKRM/y9xhPJL2CAOurUSLeNdigIhogTpay4MIH1Qiv597ZE//kiK39+xnzXIRdoKlYeAzZeJnOox5IpenaIPpaBO+LUQLNd9aHkSun1lEzt+tKU9c0+QKFnCbDqNeLeRt9GeMnr4ltPCMLZO/sJ+xCZYoggAAABOJIggAALAyEywAAICFmGABAAAsxAQLAABgISZYAAAACzHBAqpyPp/L4XAo5/N576QAD1CHgexMsILRscA8fd+X0+lU+r7fOymLyNAmZEjjI7I8V5Z03qu2Ogxbqq09SOva5VhjP2MXDbvkbjmP3sguD+C72urCo23CljKk8RFZnitLOu9VWx2GRzxaD2prD/Z0Tx6UkYuGF5lgZcnMDI22CgV8VHO7FV2W58qSTuB+tX9wz5DOe/JgbIL19P1/u8/z8/Pw/v7+y5+fz+fS9305Ho/l5eVl7qLaag6HQzmdTqXruvL6+rp3chaVJQ8AALit9nFdhjH5PXnw9PT02zAMz7/8+RITrCxqL6wAABBdLWPysQlWiiAXSx3Ye3l5Ka+vr6kzEgAAMltiTB45oEeKCZaIQmwpcoUFgKj0n2wp8vwgxQTreDyWruvK8XjcOylV0iD+LGKFlUcAfBatb4jYf+4tWh7VJPT84Frki7GfsSiC5LZHBMLI0WMipk2USAA+i9Y3ROw/L/ZKW7Q8YlllJIrgn3ad3RHCZea/5ReAy1euUkq46DGXfcGR7JFHAMQWrW+I2H9e7DXuiJZHbKOpKILEUUv0GAAgPuMO1pA6iiD1EdGRtdn3Dnmor6zNuIMtmWABVarpsHWGwWeGNE4V/Zmip2+KmuorgDNYQJVq2vce+cziRYY0ThX9maKnb4qa6iuACdbC7PGFGCIftp4qw+AzQxqniv5M0dM3RU31FbIzlp1PkIuFHQ6HcjqdStd1ITsLlQYAYD/Rx2LRx7KRjAW5sIK1sOhfFGvaUgIAkE30sVj0sWwGJlgLi77NQaUBANhP9LFY9LFsBrYIAgAATOQeLB42JRTwXmGDp/7emsIbA0B0WfrpDGMeEhiG4e6fb9++DbSn67qhlDJ0Xbfo313S1N+7VzqJ5e3tbei6bnh7e9s7KVAt9YxhyNNPZxjzEEcp5X24MmdyBosvTdkrvNe+4qm/N/r+Z7YR8aBx9OhSxBetDEWsZ2wvSz+dYcxDAtdmXWM/VrBgG774biPie17yi+ijz7f0e4n4nochznMunY5oX9Wj5n9tvGfYXhlZwTLBggm26sCiDZDYzpJl7NFytHT5i1qeozzn0ukw0G7TlvVMGYPvxiZYtgjCBFttdbHtoF1Lhsd9tBwtXf6ilucoz7l0OoRYbtOW9cy2T7hNmHaYINrZBgDYmr4QvhOmHRZw+TKsQ2nXI2F5hfIlokfLpfKMvhBuM8ECfmEANe6yNabv+1X/mzEt5I2B/7gln/HRcrlkea5NC2UQuMO1g1ljP4JcQF5TDiVHDUoQwSOHuyMErlhTlCh4LQSLqDHKZE2m5I/3CPkVUQTJKEIHFCENS9Dx1yFi3kSZ2ESZ6K0pYv7zQ4sfsvYuk3v/ftpmgkVKETqgCGlYgk6ItdRatmp9LmKopXzt3Ufu/ftp29gES5h2QosQ3jlCGpYgdDNrqbVs1fpcxFBL+dq7j9z798M1k4NcOMDJliJEKpqahnvriLoEwBbW7Jf27qf3/v205556MnkFy+VycNu9daSWuuQ+FKBmNbRxrfVLsKaP9WTM5AmWpVi47d46Uktd0iEDNauhjWutX4I1fawnYxOtp+/ns+7z/Pw8vL+/L5I4oA41fN0FGKONA8Y8PT39NgzD8+c/d9EwMIv97+txTo97KCfr0sYBU5lgNUynDLFdtib1fb93UmaJ3NZETtu9aiknUKsa2hmmMcFqmE65Lhrw+hyPx9J1XfrzEJHbmshpu1ct5YQftOd1qaGdYRr3YDXMYda61HAQm5+5J2d9kdN2r1rKCT9oz+tSQzvDNIJcQCUcxAaog/YcchDk4gGW6MnEQWyAOmjPycaY+We2CN5giR4AAG4zZv6ZCdYN9swCAMBtxsw/cwYLAABgImewYAX2HN/HewIi0jbdx3uCaUywYAZ3W9zHe3qcgQ23KB/zaJvu4z3BNM5gwQz2HN/He3pcDQeHo4acjpquKWooH3vSNt3He4JpnMECCKyGScDhcCin06l0XRdqEhA1XVPUUD4AsnIGi/BsdYFf1XAfzvF4LF3Xhfv6HTVdU9RQPmBpxhPszQoWYdTwNRkA2JfxBFsZW8FyBosw7PEGAOYynmBvVrAAAAAmcgYLKma/OUB9tO2QkwkWVMAdJe0yAKub/G2bth1yMsGCCtQQDY3HRBqA1TIZiPQckfKX7WnbISdBLqACl1DNtCfSYe5aLr2N9ByR8pftadshJxMsgMQiDcBqmQxEeo5I+QvAfUQRBAAAmEgUQYDGPXK2KNJ5pIi8UwA+M8ECNmeAuY9HAiYIsnCbd5qHdgfYijNYwOYiBRFoySNniyKdR4rIO81DuwNsxRmsxpzP59L3fTkej+Xl5WXv5NAo5RDYmnaHCJTDuoydwTLBaszhcCin06l0XecLHgDAhozD6jI2wbJFsDG2pgAA7MM4rA2CXDTmcqeKZenlODgNQI30b8szDmuDFSyYycFpAGqkf4PHmGDBTJb7AaiR/g0eI8gFAADARGNBLpzBgkrZOz/Ou4HtqXe3eT9QD1sEoVL2zo/zbmB76t1t3g/UwwoW4fiKt4zj8Vi6rrN3/grvBran3t3m/cxn/EAUzmARjkv4iOh8Ppe+78vxeBRel+apD0Rk/MDWnMH6gq8ecfiKR0SX7Tt93++dFNid+kBExg9xtD6uNsH6nc4iDpfw1W+thnfNBl3HDT+sXR8ythHsz/ghjtbH1YJc/M5dD7CdtQ5zr3lI/NJxA+vXh4xtBPBD6+NqE6zfGTzBdtZqeFtv0KEW2gjIrfVxtSAXAAAAEwlyAQAAsDITLAAAgIWYYAEsTKQyMlJuAZYhyAXAwkQqIyPlFmAZVrCgcb5aL8+dWWSk3K5DGwvtMcGCB0TrMOekp/XLANfgsksyUm7X8WgbW1M/A60xwYIHRJuUzElPtq/WOnloV8b6/2gbW1M/A80ZhuHun2/fvg3E9vb2NnRdN7y9ve2dlKpFe8/R0jMM66Wp67qhlDJ0XbfovwvEt1b9b6kNfVS09NTKe86llPI+XJkzmWBVxuCzDjU0sC0NhIBt+HBzm/Yxv1rKYivGJliiCFbmsgUhy3YvrqshmtdaZfFyTgRoz1r1v5a+s4a+o3W1lMXWOYNVmQyHlDPuod/aFueiHs2He/+7DGURoJT726s5/dcWfV+2M7VbyzD+0HdW4tqy1tiPLYIsYYnlb9sg5ns0H2xfAFo1p/3Tds43t++XByyt2CJIFEssf9sGMd+j+WD7AtCqOe2ftnO+uX2/PGAz12ZdYz9WsPhoz1UkK1iwPfXuB+8CtrdXvVPfGVNGVrCevv9v93l+fh7e39/Xm+2RyuFwKKfTqXRdZxUJkjmfz6Xv+3I8Hu/e66/O/zD1XTzyvoEYtH2MeXp6+m0YhufPf26LIA+z1A7TRRloP7LVRp3/Yeq7iLKtOUr5g0y0fUxlBQtgQ1G+hBpobyvK+45S/gBqMLaCJUw7fJIhjCt5RQmjLBTwtqK87yjljzrpP+E7Eyz45LKVp+/7vZNChaIMtLeQZbCVJZ1LaKn8sT39J3xngvWFljreyObmw5T/3hdeWEaWwVaWdEJ0U/vP6Bc38zX5MOJaaMGxnxbDtLuULoa5+RApH4V7nc87zCFLPmVJZ+vk03zR3qGLm/NrPR/KSJj2tBOsrRqJaI1Rq+bmQ6R8bL0xWoJ3OC5SWWc6+TdOvZ8v2jucU97VlRi2zIeIeV7dBCtaIwH3ithAZOMdjtM25ib/xqn383mHZBaxfaxugtVCI9HCMxKfcpiL/MpN/uUiv4iglXIY8TnHJljuwQrMfSVEoBwCXKd9JALlcD9j92D9aY/EcB83hxOBcghwnfaRCJTDeKxgAQAATDS2guUeLP7gLgMAgPmMqdpmgsUfXLYJ29H5frf2e/Cef/AuYDvGVG0zwVpRts5s6g3swON0vt+t/R685x+8C9hOpjFVtvFqBs0HuTifz6Xv+3I8HsvLy8ui//alMyulpIjq8vLykiKdUAOHkr9b+z14zz94F7CdTGOqNcera46zI5sc5OLf/u3fqnpRa4a2bLVQAQCQw5rj1RpDyH98X//yL/+yTJj2bKsyX1nzi16mrxcAALRnzfFqjSvnH+dCYyafwcq0p/Qel0JlhQnIxr75NshnIKsax9n3zIUmT7BqfFFAPVoajApa0IaW8rml+gvkdM9cqPkgF0BdatvGfEuNWy/4VUv53FL9BeolTDvV8OWTUurbxnyLHQVtaCmfW6q/jNOfk93kKILv7+8rJgceV2OkGgBojf6cLJ6enq5GEbSCRTWif/n0RQ6ACKL3R9H7c/iKCRbViL6NpqWD6vws+mCGdimbbYreH0Xvz+ErJliwkdq+yBmY3S/6YCaKpcqUsnk/ZfN+NZWr2vojiEYUQdhIbRdPi/Z1v5aiwM2xVJlSNu+nbN6vpnJVW38E0ZhgAQ8xMLufwcx9lipTyub9lM37KVfAvUQRBJp3Pp9L3/fleDza8w8LUreAmo1FEbSCBTSvpq0/EIm6BbRIkAugeY8c+K7pwDt85dHyLpgC0CITLKB5j4QEjhR9zWSvTpHy9dHyLtw20CITLKAKWw9GI32ZjzTZYzmR8nXr8h5pcgkwlTNYQBW2PusRKfqa6GZ1ipSvW5d3Z7eAzKxgAVV49At7DV/KbcOqUy35+kgdi7RCDDCVMO1A0w6HQzmdTqXrOl/KYQXqGFCrsTDtVrAaVMMXe1iKL+WwLnUMfjAGa4MJVoMiHZyGvdWyDSujrQYaBjT7UsfgB2OwNphg3VBrp+xrIhnUWv/4YauBhgFNG7QZZFDjGEzd+5UogjfUGsUoUvQzGFNr/eOHraLkRYrGx3q0GWRQ4xhM3fuVCdYNOmXYj/pXv60GGjUOaPiVNgP2oe79yhbBG+wbZwsZl9a3SLP6B0yxdpuhrYbr9Ne/MsGiSpk6lYznQzKmuXWZ6kQL5Ec+Gdu9TGlWJ6iJLYJUKdN+4IxL6xnTvJTz+Vz6vi/H4zHV17pMdaIFWfMja/lfQsZ2L1Oas9YJuMYEiypl6lQyng/JmOalZB0EZKoTLciaH1nL/xIytnuZ0py1TsA1T8Mw3P2Xn5+fh/f39xWTAxBby1/w75X1HWVN95a8I4Afnp6efhuG4fmXPzfBAmBJh8OhnE6n0nVdmq/npeRNNwD7GJtgCXIBwKhHDp5nvUjz0XQ7nA/AR1awABhlVedr3hFAm8ZWsAS5AGCUg+df844A+MgKFgAAwETOYAHhOLsCrE07A2zNFkFgNy3fqQNsQzsDbM0KFrCbrNHmWuHL/328p9i0M8DWTLCAq7YYNL68vJTX11cXlgZ1+fLf9/3eSQnNe4pti3bGJBv4yAQLktmqIzdorMejZcaX//u4P4ut2ktlBnJwBguS2eo8gdDT9Xi0zFy+/HPbo+/J2aB6bNVeKjOQgxUs2NASXx+3WlWwfe8xEb8wW4mKKWK+RCy/GWzVXi5RZuQxrM89WLChw+FQTqdT6brO18dKyePvA7i+78vxeEw1Qc+a7iUpv/WTx7CcsXuwbBGEDe257c7gcRu2VubdxpQ13UtSfrexZ3ssj2F9VrCgEb5aspWsk/ms6SYf7THUYWwFyxmsxtmL3Y6I5z2oU9bze1nTTT7a43YYZ7XJBKtxQnHnMbeRNngEiGFue2zQnodxVptMsBpX01e0LTucPTo3jTQfGWC1RX7z0R79wdZlsJYyX9M4i/sJctG4mu652fKA+h6H4R1M5iMBGdoiv/loj/5g6zJYS5mvaZzF/UywqMaWHc4enZtGmo9MuNsiv/loj/5g6zKozJOZKIIAAAATiSIIhFTLPnsgJm0MsDVbBIFd1bLPHohJGwNszQrW73zhgn2IsASsSRsD+2h5bG2C9TshsGEf7udqV+1XKxCDNgb20fLY2hbB34lWA7Ct2q9WAGhZy2NrK1i/84ULWJIVk69tuXXLNrGvKbPAkloeWwvTDrCCw+FQTqdT6brOigkpKLMA04yFabdFEGAFLW+NICdlFmAZtghCpWz32VfLWyPISZndj/Ya6mIFCyrlUD9ADtprqIsVLKiUQ/318HWba5SLemivoS4mWPBJLYMW233q0fJdIoxTLupRS3tdS/8Jc5lgcbe9Gs6tf69BC9H4us01ygXRbN1/tjIuIR9nsLjbXnvEt/69ImkRzeXrNnykXBDN1v1nK+MS8jHB4m57TTy2/r0GLQAw3db9ZyvjEvJx0TAAAMBEYxcNO4MFhGavOzBG+wBEZIJVIR0ONRF0pA1Lt1vawTZoH6iJdqseJlgVitrhaDh4RPRIacr1MpZut6K2g9lEL9/R2wdiilqutVv1EOSiQlEPX4q6wyOiBx1RrpexdLsVtR3MJnr5jt4+EFPUcq3dqocJVoWidjgaDmqkXC9j6XYrajuYjfJNjaKWa+1WPUQRBAAAmEgUQSaLukcZACAK4yU+s0WQUVH3KAMARGG8xGcmWIyKukcZACAK4yU+s0WQUZfDli8vL3snBSardctGrc/F/WosAzU+E+0wXuIzE6yd6VTYQwvlbs59IpHfj3tSiFwGHq07kZ9pSZHbFuql3G3PFsGd2bfLHlood3O2bER+P7aiELkMPFp3Ij/TkiK3LdRLudueCdbOWulUiKWFcjfnPpHI78c9KUQuA4/WncjPtKTIbQv1Uu625x4sAACAidyDBQAAsDITLPidQ6BxyIv6bZ3HylT95HEc8oLWmWDB71qJYpXB3LzQuce3dX1Tv3OYU3flcRzygtYJcgG/cwg0jrl5IWJSfFvXN/U7hzl1Vx7HIS9onSAXQHXO53Pp+74cj0cXP0Ii6i6QyViQCxMsAACAiUQRBAAAWJkJFkCFBPrIR54B1EGQC4AKCfSRjzwDqEO6FSxf+OKSN1yjXOzjeDyWrutE8UpEnm1P+8QYZSOmLPmSLsjF4XAop9OpdF3nC18w8oZrlAsgKu0TY5SNmKLlSzVBLnzhi0vecE2WcpHlq1hktbzDWp5jT1neYZb2ie0pGzFlyZd0K1gAa4j2VSyjWt5hLc+xJ+8QaEE1K1gAa8jyVWxtc1YeanmHc54jy8rN2mopCwCPsIIFwB+sPMzj/QG0wwoWUErxhZ3brDzM4/1xi/YX2mAFCxrjCzvAPrS/UJexFSwXDUNjLl/WfWEH2Jb2F9pgBQsAAGAiZ7AAAABWZoIFwB8cwp/H+wPABAvuZOBEC/q+L6fTqfR9v3dSUvL+aIU+EcYJcgF3ugycSimiP1Eth/Dn8f5ohT4RxlnBgju534Ys5nxZfnl5Ka+vr+Xl5WWFlNVv7vuzKkAW+kQYZ4J1g46Ojww8x6krsdimlpe8i0XbNk6fyIV68itbBG+w/A33UVdisU0tL3kXi7YNvqae/MoK1g2Wv+E+rdSVLF/p9vqynOX93GOvZ8mwKlBTPn+llbYN5lBPfuWiYYA7HQ6HcjqdStd1vtJdUdP7qelZlubdAHw3dtGwLYIAd7J967aa3k9Nz7I07wbgNitYAAAAE42tYDmDBRVq6YwEQA2021APWwShQiL6AOSi3YZ6mGBBhZyRAMhFuw31sEWQVdjqsK8MoZ65j7rELcpHPbTb+1KXWJIVLFZhqwMsQ13iFuUDlqEusSQrWKzCpXPf+SLGXOoStygfzKWf+k5dYknCtMOKXMgJQGT6KXici4ZhBw4tAxCZfgqWZ4sgrGiJQ8u2b1Cbvcq0ukSN5pZrwTVgeVawIDgHb6nNXmVaXaJGyjXEY4IFwdm+QW32KtPqEjVSriEeQS7gk/P5XPq+L8fj0ZYJALiT/pPWjAW5cAYLPrlst+j7fu+kpOJ8C1ATbdp0+k/4zhZB+MR2i8c4BwDURJs2nf4TvrOCBZ+I/PeYli5pbDF/obVy31KbVsoy+SsiIXznDBaswMWNdZO/tEi5r5v8helcNAwbsk2ibvKXFin3dZO/sBwrWAAAABOJIggQXGtnXFiPsgSwH1sEAYIQtYylKEsA+7GCRVV8tSWz1qKWsR5liaz049TAGSyqIgoSAOSlHycTUQRpgihIAJCXfpwaWMECAACYSBRBAEJa68yFsxwA7MEWQQB2tVbEO5H0ANiDFSwIxBd3WrRWxDuR9GiRfgT25wwWBCJ6EgBz6EdgO6IIQgKiJwEwh34E9meLIATy8vJSXl9fy8vLy95JWUW2rSvZ0gt7yFZPsqV3qtr7EcjABItZau+oWNYl6EDf93sn5S7Z0gt7yFZPsqWXfRnn8AhbBJlFlC6myLZ1JVt6YQ/Z6km29LIv4xweIcgFs5zP59L3fTkej7YjAABVMc7hlrEgFyZYAAAAE41NsJzBAgAAWIgJFkBADlYzlTIDEEMVEyydClAbkc6YSpkBapJ5fF9FFEERXoDaiHTGVMoMUJPM4/sqVrCOx2Ppuk6nApWb+zUr09cwl4UyVZYys0Q9zFSXgcdkHt+LIgikcTgcyul0Kl3XPfQ1a+5/D8y3RD1Ul4EIRBEE0pv7NSvz17Ca7LX6YNUjhiXqoboMRGYFi9Bc8Af12Wv1waoH1MlYgb0sctHw09PT/1dK+Z9LJgy+8D9KKf+1lPK/Syn/z85pAZbxf5VS/u9Syv9bSvk/DfxeYF3GCuzlvw/D8N8+/+GkCRYAAADjnMECAABYiAkWAADAQkywAAAAFmKCBQAAsBATLAAAgIWYYAEAACzEBAsAAGAhJlgAAAALMcECAABYyP8PFd1HlSVAk0kAAAAASUVORK5CYII=\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 13.883385636764606 max: 114.65356241858672\n", + "image 1 reprojection errors: average: 13.713662562824632 max: 132.52230212294577\n", + "image 2 reprojection errors: average: 14.066902502714576 max: 137.72565330474978\n", + "image 3 reprojection errors: average: 13.919607854024123 max: 303.11279610030897\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.7286e+05 1.40e+06 \n", + " 1 2 2.6866e+03 7.70e+05 6.97e+01 1.54e+05 \n", + " 2 3 1.3147e+03 1.37e+03 7.39e-01 3.49e+03 \n", + " 3 4 1.3084e+03 6.22e+00 4.98e-01 8.03e+02 \n", + " 4 5 1.3072e+03 1.20e+00 5.38e-02 9.28e+01 \n", + " 5 6 1.3071e+03 1.06e-01 8.47e-03 1.65e+01 \n", + " 6 7 1.3071e+03 5.05e-02 6.30e-03 2.37e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 7.7286e+05, final cost 1.3071e+03, first-order optimality 2.37e+01.\n", + "mean reprojection error: 0.6392578043382984\n", + "max reprojection error: 2.56533518539307\n", + "mean reconstruction error: 0.1190688526480074\n", + "max reconstruction error: 0.5306016190654083\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 14.36925881990482 max: 103.76676434611505\n", + "image 1 reprojection errors: average: 13.694895095369638 max: 147.19632272808684\n", + "image 2 reprojection errors: average: 14.255586224366864 max: 154.52827868291894\n", + "image 3 reprojection errors: average: 14.402039121180508 max: 283.40543365185306\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.6647e+05 4.14e+06 \n", + " 1 2 1.4074e+04 7.52e+05 7.10e+01 2.44e+05 \n", + " 2 3 1.2307e+04 1.77e+03 7.64e-01 7.08e+03 \n", + " 3 4 1.2291e+04 1.67e+01 5.32e-01 1.84e+03 \n", + " 4 5 1.2285e+04 5.43e+00 8.91e-02 1.38e+02 \n", + " 5 6 1.2284e+04 8.78e-01 3.19e-02 5.64e+01 \n", + " 6 7 1.2284e+04 5.29e-01 1.58e-02 4.16e+01 \n", + " 7 8 1.2283e+04 3.65e-01 1.59e-02 4.27e+01 \n", + " 8 9 1.2283e+04 4.22e-01 1.57e-02 4.96e+01 \n", + " 9 10 1.2283e+04 3.46e-01 1.35e-02 3.56e+01 \n", + " 10 11 1.2282e+04 3.06e-01 1.23e-02 4.62e+01 \n", + " 11 12 1.2282e+04 3.19e-01 1.34e-02 3.76e+01 \n", + " 12 13 1.2282e+04 2.87e-01 1.12e-02 4.57e+01 \n", + " 13 14 1.2281e+04 3.05e-01 1.38e-02 3.96e+01 \n", + " 14 15 1.2281e+04 2.78e-01 1.04e-02 4.37e+01 \n", + " 15 16 1.2281e+04 3.10e-01 1.52e-02 4.72e+01 \n", + " 16 17 1.2281e+04 2.01e-01 6.43e-03 1.92e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 17, initial cost 7.6647e+05, final cost 1.2281e+04, first-order optimality 1.92e+01.\n", + "mean reprojection error: 1.9580852532917954\n", + "max reprojection error: 7.956843795703266\n", + "mean reconstruction error: 0.34158658199936864\n", + "max reconstruction error: 1.6336601724472413\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 15.042639687030883 max: 144.89514178273947\n", + "image 1 reprojection errors: average: 15.175912112787069 max: 110.24093393656742\n", + "image 2 reprojection errors: average: 15.38389189016894 max: 219.02711553402986\n", + "image 3 reprojection errors: average: 15.115226187792024 max: 247.1464281779609\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 8.6401e+05 3.30e+06 \n", + " 1 2 3.5556e+04 8.28e+05 7.40e+01 6.92e+04 \n", + " 2 3 3.4520e+04 1.04e+03 1.14e+00 1.94e+03 \n", + " 3 4 3.4468e+04 5.14e+01 1.12e+00 1.67e+03 \n", + " 4 5 3.4443e+04 2.52e+01 2.81e-01 3.19e+02 \n", + " 5 6 3.4440e+04 3.09e+00 7.73e-02 1.45e+02 \n", + " 6 7 3.4438e+04 2.50e+00 5.96e-02 1.46e+02 \n", + " 7 8 3.4436e+04 1.76e+00 4.37e-02 1.23e+02 \n", + " 8 9 3.4435e+04 7.90e-01 1.49e-02 6.92e+01 \n", + " 9 10 3.4434e+04 5.39e-01 1.58e-02 8.79e+01 \n", + " 10 11 3.4434e+04 5.17e-01 1.17e-02 6.43e+01 \n", + " 11 12 3.4433e+04 5.11e-01 1.54e-02 8.64e+01 \n", + " 12 13 3.4433e+04 4.77e-01 1.08e-02 5.73e+01 \n", + " 13 14 3.4432e+04 4.62e-01 1.45e-02 8.55e+01 \n", + " 14 15 3.4432e+04 4.59e-01 1.05e-02 5.83e+01 \n", + " 15 16 3.4432e+04 4.46e-01 1.40e-02 8.71e+01 \n", + " 16 17 3.4431e+04 4.40e-01 1.01e-02 6.04e+01 \n", + " 17 18 3.4431e+04 4.30e-01 1.35e-02 9.23e+01 \n", + " 18 19 3.4430e+04 4.23e-01 9.65e-03 6.38e+01 \n", + " 19 20 3.4430e+04 4.18e-01 1.30e-02 1.07e+02 \n", + " 20 21 3.4429e+04 4.50e-01 1.04e-02 7.48e+01 \n", + " 21 22 3.4429e+04 3.93e-01 1.15e-02 1.02e+02 \n", + " 22 23 3.4429e+04 3.89e-01 9.47e-03 8.39e+01 \n", + " 23 24 3.4428e+04 3.89e-01 1.14e-02 1.11e+02 \n", + " 24 25 3.4428e+04 3.85e-01 9.30e-03 8.67e+01 \n", + " 25 26 3.4427e+04 3.84e-01 1.13e-02 1.12e+02 \n", + " 26 27 3.4427e+04 3.79e-01 9.16e-03 8.59e+01 \n", + " 27 28 3.4427e+04 3.75e-01 1.12e-02 1.11e+02 \n", + " 28 29 3.4426e+04 3.70e-01 9.03e-03 8.42e+01 \n", + " 29 30 3.4426e+04 3.66e-01 1.10e-02 1.09e+02 \n", + " 30 31 3.4426e+04 3.60e-01 8.89e-03 8.23e+01 \n", + " 31 32 3.4425e+04 3.57e-01 1.09e-02 1.08e+02 \n", + " 32 33 3.4425e+04 3.52e-01 8.77e-03 8.07e+01 \n", + " 33 34 3.4425e+04 3.49e-01 1.08e-02 1.06e+02 \n", + " 34 35 3.4424e+04 3.44e-01 8.66e-03 7.90e+01 \n", + " 35 36 3.4424e+04 3.40e-01 1.07e-02 1.04e+02 \n", + " 36 37 3.4424e+04 3.36e-01 8.56e-03 7.75e+01 \n", + " 37 38 3.4423e+04 3.34e-01 1.06e-02 1.03e+02 \n", + " 38 39 3.4423e+04 3.29e-01 8.46e-03 7.59e+01 \n", + " 39 40 3.4423e+04 3.27e-01 1.05e-02 1.01e+02 \n", + " 40 41 3.4422e+04 3.23e-01 8.38e-03 7.43e+01 \n", + " 41 42 3.4422e+04 3.20e-01 1.05e-02 9.97e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 42 43 3.4422e+04 3.17e-01 8.30e-03 7.28e+01 \n", + " 43 44 3.4421e+04 3.14e-01 1.04e-02 9.82e+01 \n", + " 44 45 3.4421e+04 3.11e-01 8.22e-03 7.14e+01 \n", + " 45 46 3.4421e+04 3.08e-01 1.03e-02 9.67e+01 \n", + " 46 47 3.4420e+04 3.05e-01 8.15e-03 7.00e+01 \n", + " 47 48 3.4420e+04 3.02e-01 1.03e-02 9.55e+01 \n", + " 48 49 3.4420e+04 2.99e-01 8.08e-03 6.86e+01 \n", + " 49 50 3.4420e+04 2.42e-01 7.90e-03 8.73e+01 \n", + " 50 51 3.4419e+04 2.87e-01 8.68e-03 9.00e+01 \n", + " 51 52 3.4419e+04 2.85e-01 8.47e-03 8.58e+01 \n", + " 52 53 3.4419e+04 2.82e-01 8.62e-03 8.83e+01 \n", + " 53 54 3.4418e+04 2.79e-01 8.41e-03 8.43e+01 \n", + " 54 55 3.4418e+04 2.77e-01 8.56e-03 8.65e+01 \n", + " 55 56 3.4418e+04 2.74e-01 8.35e-03 8.29e+01 \n", + " 56 57 3.4418e+04 1.71e-01 4.47e-03 6.49e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 57, initial cost 8.6401e+05, final cost 3.4418e+04, first-order optimality 6.49e+01.\n", + "mean reprojection error: 3.2722951530862043\n", + "max reprojection error: 14.190425769322397\n", + "mean reconstruction error: 0.5786112193562779\n", + "max reconstruction error: 2.76880691795907\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 17.09512975652156 max: 120.87241518847067\n", + "image 1 reprojection errors: average: 16.921944023267525 max: 108.74584660267507\n", + "image 2 reprojection errors: average: 18.028821918415243 max: 123.18558268792229\n", + "image 3 reprojection errors: average: 17.84712610359939 max: 185.33013225169395\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.0159e+06 2.50e+06 \n", + " 1 2 1.4112e+05 8.75e+05 8.61e+01 7.15e+04 \n", + " 2 3 1.4044e+05 6.75e+02 1.42e+00 2.63e+03 \n", + " 3 4 1.4034e+05 1.05e+02 9.14e-01 1.16e+03 \n", + " 4 5 1.4028e+05 5.63e+01 3.25e-01 4.26e+02 \n", + " 5 6 1.4026e+05 2.13e+01 2.19e-01 3.31e+02 \n", + " 6 7 1.4025e+05 1.60e+01 1.34e-01 2.63e+02 \n", + " 7 8 1.4023e+05 1.50e+01 1.78e-01 3.34e+02 \n", + " 8 9 1.4022e+05 1.09e+01 8.65e-02 1.95e+02 \n", + " 9 10 1.4021e+05 8.79e+00 1.18e-01 2.95e+02 \n", + " 10 11 1.4020e+05 7.48e+00 6.08e-02 1.94e+02 \n", + " 11 12 1.4020e+05 7.17e+00 1.03e-01 2.92e+02 \n", + " 12 13 1.4019e+05 6.89e+00 5.73e-02 1.94e+02 \n", + " 13 14 1.4019e+05 4.17e+00 5.95e-02 2.06e+02 \n", + " 14 15 1.4018e+05 5.56e+00 6.24e-02 3.05e+02 \n", + " 15 16 1.4018e+05 3.49e+00 4.01e-02 1.45e+02 \n", + " 16 17 1.4017e+05 2.61e+00 3.26e-02 2.82e+02 \n", + " 17 18 1.4017e+05 2.24e+00 2.58e-02 1.33e+02 \n", + " 18 19 1.4017e+05 2.16e+00 2.81e-02 2.77e+02 \n", + " 19 20 1.4017e+05 2.12e+00 2.51e-02 1.31e+02 \n", + " 20 21 1.4017e+05 2.10e+00 2.76e-02 2.75e+02 \n", + " 21 22 1.4016e+05 2.07e+00 2.47e-02 1.30e+02 \n", + " 22 23 1.4016e+05 2.04e+00 2.72e-02 2.72e+02 \n", + " 23 24 1.4016e+05 2.01e+00 2.44e-02 1.28e+02 \n", + " 24 25 1.4016e+05 1.99e+00 2.67e-02 2.68e+02 \n", + " 25 26 1.4016e+05 1.96e+00 2.41e-02 1.27e+02 \n", + " 26 27 1.4015e+05 1.94e+00 2.63e-02 2.64e+02 \n", + " 27 28 1.4015e+05 1.91e+00 2.39e-02 1.25e+02 \n", + " 28 29 1.4015e+05 1.89e+00 2.59e-02 2.59e+02 \n", + " 29 30 1.4015e+05 1.73e+00 2.15e-02 1.12e+02 \n", + " 30 31 1.4015e+05 1.71e+00 2.45e-02 2.63e+02 \n", + " 31 32 1.4014e+05 1.67e+00 2.08e-02 1.00e+02 \n", + " 32 33 1.4014e+05 1.64e+00 2.37e-02 2.76e+02 \n", + " 33 34 1.4014e+05 1.62e+00 2.01e-02 9.80e+01 \n", + " 34 35 1.4014e+05 1.64e+00 2.37e-02 2.98e+02 \n", + " 35 36 1.4014e+05 1.62e+00 1.97e-02 1.09e+02 \n", + " 36 37 1.4014e+05 1.56e+00 2.25e-02 3.06e+02 \n", + " 37 38 1.4013e+05 1.56e+00 1.91e-02 1.22e+02 \n", + " 38 39 1.4013e+05 1.55e+00 2.22e-02 3.16e+02 \n", + " 39 40 1.4013e+05 1.53e+00 1.88e-02 1.25e+02 \n", + " 40 41 1.4013e+05 1.53e+00 2.20e-02 3.18e+02 \n", + " 41 42 1.4013e+05 1.51e+00 1.87e-02 1.24e+02 \n", + " 42 43 1.4013e+05 1.50e+00 2.19e-02 3.17e+02 \n", + " 43 44 1.4013e+05 1.48e+00 1.85e-02 1.22e+02 \n", + " 44 45 1.4012e+05 1.47e+00 2.17e-02 3.14e+02 \n", + " 45 46 1.4012e+05 1.45e+00 1.84e-02 1.20e+02 \n", + " 46 47 1.4012e+05 1.44e+00 2.16e-02 3.11e+02 \n", + " 47 48 1.4012e+05 1.42e+00 1.82e-02 1.17e+02 \n", + " 48 49 1.4012e+05 1.41e+00 2.14e-02 3.08e+02 \n", + " 49 50 1.4012e+05 1.40e+00 1.81e-02 1.15e+02 \n", + " 50 51 1.4012e+05 1.39e+00 2.12e-02 3.06e+02 \n", + " 51 52 1.4011e+05 1.37e+00 1.80e-02 1.12e+02 \n", + " 52 53 1.4011e+05 1.36e+00 2.11e-02 3.03e+02 \n", + " 53 54 1.4011e+05 1.34e+00 1.78e-02 1.10e+02 \n", + " 54 55 1.4011e+05 1.33e+00 2.09e-02 3.00e+02 \n", + " 55 56 1.4011e+05 1.32e+00 1.77e-02 1.08e+02 \n", + " 56 57 1.4011e+05 1.31e+00 2.08e-02 2.97e+02 \n", + " 57 58 1.4011e+05 1.29e+00 1.75e-02 1.06e+02 \n", + " 58 59 1.4011e+05 1.28e+00 2.06e-02 2.94e+02 \n", + " 59 60 1.4010e+05 1.27e+00 1.74e-02 1.04e+02 \n", + " 60 61 1.4010e+05 1.26e+00 2.05e-02 2.90e+02 \n", + " 61 62 1.4010e+05 1.24e+00 1.72e-02 1.02e+02 \n", + " 62 63 1.4010e+05 1.23e+00 2.03e-02 2.87e+02 \n", + " 63 64 1.4010e+05 1.22e+00 1.71e-02 9.96e+01 \n", + " 64 65 1.4010e+05 1.21e+00 2.01e-02 2.84e+02 \n", + " 65 66 1.4010e+05 1.20e+00 1.70e-02 9.76e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 66 67 1.4010e+05 1.19e+00 2.00e-02 2.81e+02 \n", + " 67 68 1.4009e+05 1.17e+00 1.68e-02 9.57e+01 \n", + " 68 69 1.4009e+05 9.50e-01 1.54e-02 2.55e+02 \n", + " 69 70 1.4009e+05 1.14e+00 1.81e-02 1.30e+02 \n", + " 70 71 1.4009e+05 1.13e+00 1.65e-02 2.52e+02 \n", + " 71 72 1.4009e+05 1.12e+00 1.80e-02 1.28e+02 \n", + " 72 73 1.4009e+05 1.11e+00 1.64e-02 2.49e+02 \n", + " 73 74 1.4009e+05 6.64e-01 9.02e-03 9.66e+01 \n", + " 74 75 1.4009e+05 2.51e-01 3.06e-03 5.72e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 75, initial cost 1.0159e+06, final cost 1.4009e+05, first-order optimality 5.72e+01.\n", + "mean reprojection error: 6.615597051442245\n", + "max reprojection error: 31.49402030061628\n", + "mean reconstruction error: 1.135460440055302\n", + "max reconstruction error: 4.5057558874349075\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_4 = {}\n", + "centre_errors_4 = {}\n", + "orientation_errors_4 = {}\n", + "for pixel_error in pixel_errors:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_4 = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_4, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_4[pixel_error] = run_led_fit(fitter, led_positions_4)\n", + " centre_errors_4[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_4[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_4[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_4[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_4[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_4[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_4[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_4[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)]])\n", + "camera_directions = [[-1, -1.9, -1],\n", + " [-1, -1.9, 1],\n", + " [ 1, -1.9, -1],\n", + " [ 1, -1.9, 1],\n", + " [-1, 1.9, -1],\n", + " [-1, 1.9, 1],\n", + " [ 1, 1.9, -1],\n", + " [ 1, 1.9, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1464\n", + "Number of features in more than one image: 1464\n", + "Feature in image counts: Counter({4: 648, 8: 560, 7: 144, 6: 64, 5: 48})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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8z/20ktdLtme18uzw2pJy3dL2RvV6P/K6HS28yxzzmaz3YLmBHahdCx+KapUr773DcuQ9ULs585l792BlXcFqYdYKezMgieXp6ckHokJyrX60tIpSG/UnFv0LzJdjPpN1gqVhhfkMBvthsPO2XB/pfOx7m3LYD/0LzJdjPiNMOxRmMNgPg5235fpI52Pf25TDfuhfoAwTLCjMYLAfBjtEoBz2Q/8CZWQNcgEAANCDe0EuXDQMAACQSVMTLLdHb0O+UrvWy3Drz9erHt5rD89I25ThbVSfr7duH7738/j4uO/1yDPVeHt0Dbfe15iv8FrrZbj15+tVD++1h2ekbdHLcA3jzFui5+tVSullvDFnairIRY0Hd2uI5lRjvsJrrZfh1p+vVz281x6ekbZFL8M1jDNviZ6v7xHkojD3kQAAsAXjzG3dC3JhggUAADCTKIINqv4AINB9Pd76+eVv388PrVCX62KCVbHrvtrj8Vg6KXREI59X7/V46+eXv30/f27aP0pRl+vSVJCL3tR+AHAt+4rLqPXAbFS91+Otn1/+9v38uWn/ytDfq8u1cQaLaj0/P6fT6ZSGYdDR7UhHB/RK+1eG/p6o7p3BsoJFtXzNKePp6UkHB3RJ+1eG/p7aWMECAACYSRRBCM7haXJSnurjnZGLsgRlmWBlpEFjDRGCyEl5qo93Ri7KEmsYz65ngpWRBq1OURqSw+GQhmGwx3yBKO8wEuWpPt7Zb6nXy0UpS95hnYxnMxjHcfLP4+PjyH3n83kchmE8n8+lk1JMjXkwDMOYUhqHYSidFBbyDuOqoU2oIY09Uq/rV+M71B7IgzlSSi/jjTmTCRZZtd6YanRi8l7iqqFNqCGNPVKvY2q9z9QeMIcJFrtY05jW0BBreGGeGup1DWmEKGrpB5fWa+0Bc9ybYAnTThg1XCTokkkAelZLP1jDmIL6CdNOeFEO5b7leslk5E6FepQ+AF769/eidD6X/v20pZZ+sIYxBe0ywSKMWhrtVhmE7a90pKYlv7/3crLk+Wt8z6zTez2JwJiCkn5XOgFADNdBWErJdoqdXL+slvrCuuT3915Oljx/je+ZdXqvJ9C9Wwez7v0IclG3Xg5u9vKcuck3pui9nPT+/EyjnCzTS7718pw9SIJc0MuBz1afs5aDxQBsq9X+oNX++1u9PGcP7gW5sEWwI71sE2n1OW05ASCldvuDVvvvb/XynD2zggWVaPWLJQDz6A8gBmHaoXJzIyLtHcVK1CygJXu2aXN/lwh5EJsJFmQUaZKxd2hmoaCBluzZpkVqPyP1Y1ArEyzIKFInufcli1N/3xadtwEBtGerej31792zDY10KW6kfgyqdSu04L0fYdrhbUKvvm8YhjGlNA7DEPrv5Lbey3jvz7+nreq19uJtyjhMl+6EaRdFEDK67ovnvi2iJ4nItJ+50cuiH8afm75Wo7dFtFW91l68TT8GGdyadd37sYIF/fAVM4/W8nHu80RfLZibvt7fJ7fJR+hTsoIFzOFLfR6t5ePcr9vRVwvmpq+1r/utlc9S5CPwmgkWcFP0gXEtes/H6BOS6OnbWu/lMxf5CLzmomGAzkU/J1Ur+QrQtnsXDVvBAuic7U3bkK8AfXIPFkDnSt/BU/q+o62UzlcAyjDBWqB0pw1Mo65Ocz2HVGob21YXm5a+MLV0vtZCPYU6qKvTmWAtULrThhZt0XCrq3XYaqXHClIdtqqnBoOQlz51OmewFhAtCPLb4rzKVnVV8IK8tork13uEwNy2Kvdb1VNn4CAv49/pRBGkOga3barpvT4/P6fT6ZSGYTBwoxu1lfua2hSm8U6JRhRBmuGrZJtKrjbM7bR9xaNHc8t96cGwFcz26P+phQkW1TG4Jbe5nbaBGz2aW+4NhslN/08tBLmgOiJzkVvrwRAc9o+p9ffSer1if/p/amGCxa9a7+xLiJinEdNUWuudtshPMbX+XlqvV0tEbX+jpqtW8hNbBPmV7Rz5RczTiGliW7bVxOS99Cdq+xs1XbWSn6RxHCf/PD4+jrTrfD6PwzCM5/O5dFKaETFPI6apB/J9mrX5JJ+nkU9lRM33qOmqlfzsR0rpZbwxZxKmHWAHtYW4LmVtPsnnaeQTwHr3wrQ7gwWw0Jx99g78T7M2n+TzNHPyyXkSgHmsYAEslHsVoPS9QbQhdzmy2gVwm4uGATLLHaTAwWhyyF2OBOMAmMcWQSCEGrch5Q5DbXsbOeQuRzWGW6+xPQHaYYsgEIJtSEAu2hNgD4JcAKFZvcnPV/w6eE/5aU+AkqxgATTKV/w6eE8AdRLkAqAzghPUwXsCaIstggDfaGXLVk3BCbbI81reY03v6T215DnAlqxgAXxDuPT9bZHn3uP+5DmAFSyA70Q6IN/LisAWeR7pPW4pUhnpJc8B3iLIBUBgAiDwHmUEoAxh2qFTkb5uM58VAd6jjNRNGw3tsYIFjfN1GyAubTTUywoWTfClbz5ft7lSf2LwHnhNGz2fOkR0JlhU5Rqh6ng8lk7KmyI1/i2FgGadkvUnUp24KpWmWtox9hGljY5YR+9Rh4hOmHaqUsuFnEIVE1HJ+hOxTpRKUy3tGH2JWEfvUYeIzgSLqly/9EWn8SeikvUnYp0olaZa2jH6ErGO3qMOEZ0gF0ARl8slHY/HdDgcim+NAdqmvQG2IMjFhmratwxR2EMfk/ZsPXkYj/YG5tOWLZd1gtXri9Bww3ylI2dFb69qCMAQPQ9zmfucJfqE6O+idPpKtzdQo17Ht1naq3EcJ/88Pj6ObxmGYUwpjcMwvPnvteZ8Po/DMIzn87l0UrJp8ZngtejtVan0zan70fMwl7nPWaL9jP4uoqcP1mpx3NTiM00xp71KKb2MN+ZMWSdYvb6IFukMaV309ip6+saxjjTmUMNzRk9j9PTBWsZN7ZjTXt2bYAlywU0OBAMATGPc1Kd7QS5MsAAAAGYSRRAAAGBjJljQgdIRvAD4Le0ytOt3pRMAbO8aajWllD59+lQ4NQBol6FdJljQgevdL+6AAYhBuwztskUQOvD09JQ+ffq0W2QjW1+A2uzdbu3dLgP7sYIFZGfrC1Ab7RaQixUsILvD4ZCGYQi99SXKKluUdNCmSOUrUlpuqaHdAupggkX1Snba0QcMpSzZ+rJ3Xl6/Vh+Px11+X/R00KZI5WvPtCxpT2zZu08/CzON4zj55/HxcYRohmEYU0rjMAzV/O7z+TwOwzCez+dV/05LpuRlzjyJkr9R0kGbIpWvXGmZ8veU7BdK2LpPqbGfhT2klF7GG3MmEyyqV3IAsfR3T+kweutUDJqAKfb+GFODrfuUGvtZ2IMJFgQSaQWrps6rprQC26ipHYjUjteUb1CLexOshy//bJoPHz6MLy8vOXcoAoU9Pz+n0+mUhmF4N3LW5XJJx+MxHQ4H5xSAbk1tC+e0r0B9Hh4efh7H8cO3fy5MO3RuzmWXwhgDTG8LXSYMfRJFEDo3J3LWkjDGPUeA6vnZqUuvZXXpc09tC0UmhD7ZIghsqqYtMrm3QNb07PQtd1mtZTuxOgqsYYsgUMTWW2RyDuRyb4G0PYha5C6ruerS1hM1dRTYxK3IF/d+RBGEGESD+ipn6HaRuOBtU8t/rnriaoavtD0QTxKmnfe03HjPfbboeWHQ8dXe70re07O9y3/0tnhPNbQ9c95X6++29efjCxMs3rVn4x19UBz9QkYNdznynp4p/+XU0LfM6TtLTBj3LL81TIhZzwSLd+VoeKb+HdG/gq7JC40qADVa239FX8Ga+nx7joeomwlWIC1Xuj0br6hafjYA2tV6/xX1I/BeWn+/JdybYAnTXkDLYWFrCc0LAHBLq2OZlsefpQjTHkjLYWGvlyoCANSo1bFMy+PPaKxgAQAAzHRvBet/lUgMALFcLpf0/PycLpdL1n+3JXOfu9d8AuidCRawikFkG47HYzqdTul4PGb9d1sy97l7zaeWaN+AJTY/g9XqQUHgi+sgMqXU5J71XszZm9/rPv65z91rPrVE+wZt22qesvkZLBFLoG0RPqJESAOQX+m6Xfr3A9taO08pdgbrcDikYRh8wYNGXaMtlRx82Ip1X6ktTrVtrZJPMZWu2xHaN2A7m81Tbl2Ode/HRcPsyYV4TKWs3FfqwszaLuqUTzGp20yhnFBKunPRsHuwCMved6Zq9c6SHEqdA6rt/JF8ikndZgrjBaIRRbATNW5Dsb10mhrfLfsptcWptq1V8omItO/T1Dhe8G7b1vwESwH+Itc+9j3z08BjmtJnFADYhvZ9mj3HC7nGQd7tF82O02/tG7z3U+MZrDX72yPu6V2aplzP4rxAPBHLKQDrad/jyTUOKj2ey2lNmmofV6Y7Z7Can2C19tJLpylixS5FXgDQA/3dV6XzovQ48JbWFjPmuDfBaj7IxZoDshEPH5dOkwPHXzlUC0AP9HdflR4HlR4H3rImTaXzcyvNn8FaI+IZoIhp6lWNh2ppU0172COkNUIapqglnbRPfxdHxHFgxDSV9vBldWuaDx8+jC8vLxsmB4C51t5Ev6cIaY2QhilqSSdArx4eHn4ex/HDt3/e/BZBgNZF3DJyT4S0RkjDFLWkE4DfskUQmCXCtqUIaYikpu0ZEdIaIQ1T1JLOPZWu+6V/P1AHK1jALBEOO0dIA7C/0nW/9O8H6mCCBcwSYdtShDQA+ytd90v/fqAOglwAAADMdC/IhTNYAAAAmcyaYP3zn/90uBMAAOjSlGA3s85g/eMf/0h///vfU0oOdwIAAH15HezmnlkrWL///e/d5E0IQuXCF7XVhQjpjZCGqWpKK2xJXSCKw+Hw/nxoHMfJP4+PjyNEMAzDmFIah2EonZSizufzOAzDeD6fSyeFQmqrCxHSGyENU9WUVrahnf9CXSCilNLLeGPO1MQEK3LjEzltNZOvX+hwqK0uREhvhDRMVVNa2YZ2/gt1YTtR8zZqul67N8FqIkz78/NzOp1OaRiGcGfDIqeN+l0ul3Q8HtPhcEhPT0+lkwNAZtp5thZ1rBo1Xa/dC9PexEXDkS/+i5w26vf09BS20VnDgAKYq9V2o9V2njiijlWjpmuKJlawgH1tPZCp4asVEMvW7UarEzhguaZXsIB9vQ5RusVApuavVkAZW7cbW7d7QDtmhWkHvug9XOykEKUrXLfE+EoMTLV1u7F1uxdd7/0ezGGLICxgCxsAPdHvwffubRG0gsUkvlz9Vu9fMomtdH3N8fvn/h0lfmdupX8/vEW/9z11lrtuxW6/9xP1Hiy25x4OWG7uXR5r7/4oXV9z/P65f0eJ35lbjt8/p+zUcMcMRFa6zaC81PJFw2xPR8wUU8pJj2Vp78lC6TzO8fv3npTm+jvWyPH755SdHgeH2ihyUlYwwQI2N2XAZlCX/9+HKytYb9NGATndm2AJ0w6d2uJOlylhknsMwT73olAXi7LUnLLTYzkr2Ua5Rwv6IcgFdOp6p8vxeMz2d04JkywEexwlAkm0QL7Vq2QbtUWbC8RkggWNem9QJyLUOqUHzTl+/9wBX44BonxbpoV8691bba78hcbc2jd478cZLChn7nkJ5wi2VTp/9444t+Tfv0W+LdNCvnHf3Pzt8fwcRJQEuYC66YBjKZ2/pX//UqXTXfr3L1U63aV/f+t8QIM63ZtgPXz5Z9N8+PBhfHl5ybyGBkzhgDQAKekPIIqHh4efx3H88O2fO4MFldgjOIRzAADr7NGOChYEsQnTDvzqehg/pdRd+GaAHLSjgBUsmmDlJQ+RBQHW0Y7moV+nZiZYNKH0/SKtdAS2nQCs00o7WrpfK92vwxq2CNKE65fCUl8MbQkBoCWl+7XS/TqsYQWLJpT+YmhLSJtKf8GdK0p6o6RjrijpjpKOqWpLL9OU7tdK9+uwyq3Y7fd+3IMFsbibZlu13TUTJb1R0jFXlHRHScdUtaW3Ntp5iCu5aLg+GtX+uGwyltrqYJT0RknHXFHSHSUdU9WW3tosaee9k7543+Xcm2C5aDiw5+fndDqd0jAMzvV0Yu47d9kkQNuWtPPGD33xvsu5d9GwIBeBOeDZn7nv/LpHHYA2LWnnjR/64n3HYwULdmClCYBI9EuwnhUsKKh0uFsAeE2/BNsRph12UDrc7RJCLwNMU2N7WWO/BLWwRRC4yaFZgGm0l9AnWwSBWRyaBZhGewm81uwWwRqX62sif9t3jVzl8DPA27SX7TPu2VZr+dvsBOt6ePN4PJZOSpNazd/WKjjL1FgOIqU5UlrmiJTuSGmZqsY0k1+r5aDVcU8UzeXvrduH7/08Pj7ueTnyKm613lar+TsMw5hSGodhKJ0UCqqxHERKc6S0zBEp3ZHSMlWNaSa/VstBq+OeKGrN35TSy3hjztTsGSwXsG6r1fy1j56U6iwHkdIcKS1zREp3pLRMVWOaya/VctDquCeK1vJXFEEAAICZ7kURbPYMFtzT6v5wAIhM/0svTLDoTq0HKXVMAKRUb39Qa/8Lc5lgUb25HU2tt9frmABIqd7+YG7/W+tEEpoNckE/rh1NSmnSAck1Bykvl0s6Ho/pcDjsft9JqweHAZinZH+wph+c2//O7d8hChMsqrdnR1OysW8twg4Ay5TsD/bsB31YpFa2CFK9a0ezx4pSrdsLWc9WFfhKfejXnv3gnv075GSCBTP00thHHzzNTV+O54lw5iH6e3lPlPRHScdSEdKfqz7MeZYIz/2W6OnLpZd+EFa5dfvwvZ/Hx8e9L0gGChiGYUwpjcMwlE7KTXPTl+N5Itwyn+u9zH2WXM8epVyVysel/823IuRjiTIR4bnfEj19QH4ppZfxxpzJBAv4ToTJxFtKTRBKKzXRKTkh2ULJCWMrk/1c5jxL9OeOnj4gv3sTrIcv/2yaDx8+jC8vLxnXzwDY29woYCWjZ0a2JF/kJUA7Hh4efh7H8cN3f26CBQAAMM+9CZYgFwAZlQjAAfcsKV/KJMA6JlhACKUHdbl+/9zoajmisZXOuy3SUnKiGiU/S0W/bKFMlv79QOduHcy69yPIBTVy8LgOpSNw1Ryhr3TebZGWUoE4cv9dpdPRa6TD0r+f6fTR1CyJIti+iI1UhDTpaOtQuqyU/v1rREp7rrSUjBQZJT+jpGOJ0mkv/fuZLkIfHbG8REwT37s3wRLkoiHPz8/pdDqlYRjSp0+fSicnpRQjTaJ2AUBMEfroCGOVb0VME9+7F+TidyUSwzYOh8Nv/m8EEdJ0vXUeAIglQh8dYazyrYhpYjpBLhpybaQirdLkTlPUg8t7pCvqswOwv637hMh9Tu609TB+Yl9WsKjKNbpVSqn4F6/X9khX1GcHYH9b9wmR+5zIaYOUTLCoTNQl8z3SFfXZAdjf1n1C5D4nctogpSTIBRDjkDFAS7Sr0L57QS6cwSKMyPu9W5fjYlEAvtKulmVMQUkmWIShMyrncDikYRg23W5RY2cXKc2R0kJ50cpDtPS8Z4/07tGucp8xBUXduhzr3o+LhtmSS/XaFuEyybkipTlSWpaIWL8jpmmqaOUhWnreU1t6ma/m+k090p2LhgW5IIwId2GwnRoPJUdKc6S0LBEx6lfENE0VrTxES897aksv8xlTUJIgFwBsLuKB/4hpAqAe94JcmGABAADMJIogAADAxkywAAAAMjHBggrVFhIZgHW0+1APE6w3aMyIaun9Hso0QFlL22H3OhGVscX3hGl/Q80hfGnb0hDDyjRAWUvbYaHlicrY4nsmWG/QmN0mtHF5S+/3UKYBylraDrvXKQZjoO8ZW3zPFsE3XBszFei3atqm0OOy9VvPXKJM9/gOgHrs3Ua91w731mbW9rw1jYH2Yrx8wziOk38eHx9HOJ/P4zAM4/l8Lp2Udw3DMKaUxmEYSidlN9GeOVp6pqipjEMUtdabaG1UtPRsrbbnrbWcs42U0st4Y85kgkXTSjWEJRvgaI1/tPRMEa3DrzEPX4ua/qjpmipa+qPVm6mi5WNv/Ue0/Ic5TLCYRYO3Tq0DDb6IVv5rL09R0x81XVNFS3+0esN80cpUTZT/Pt2bYAlywU0iwqzjwGfdoh0mr708RU1/1HRNFS390eoN80UrUzUxbuK1hy+Tr2k+fPgwvry8bJgcohAlBwBgGuOmPj08PPw8juOH7/7cBAsAAGCeexMsYdo7UFsIVACA1hmftcsEqwOl7mzQcAAA0ZUar7hTq12CXHSg1KFVBz4BgOhKjVcEFWmXFawOlLph+3A4pGEYNBwzWPUDYC19yTylxiulxmdszwSLzWg45mt9u4BOHyith3ao9b4kN+MVcjPBgkBaX/WL0un3MMCCaKLUuyjt0JZa70sgOhMsCKT1r2hROv1cA6wlA8acg8woA9Zoackh2vPkSk/JMhtlYhOlHdpS630JhDeO4+Sfx8fHEdjX+Xweh2EYz+dz6aQ0I1eeDsMwppTGYRg2/W/2+LsipWXp+8lZVyLl7TjmS0/JMqsty0+eQlkppZfxxpzJBAsKmdoxRhvo8dWSwU3OAVGkwVWEyU2ESd5WcqWndJklrzll3nuE/O5NsB6+/LNpPnz4ML68vGRdQYNePT8/p9PplIZheDMs7OVyScfjMR0OB9s96MLSMq+u0Js5ZX5qnwNM9/Dw8PM4jh+++3MTLCjDYBCAvehzIL97EyxBLqAQh5Dvm3uoPlpAAmA97UBe+hzYjwkWEM7caGNRopNFZeAZk/fyNu0AUKtiEywdCy1TvteZG0Y5V9jlaO+tdHjsaPkR2ZK8yjkhiPSucqWlVDvQq0hlCLawaxm/Ffni3k/OKIIio8XWcrShPZ5N+a5TtPdWOjy2qHzTLcmrCJEXtxApLUy313uL1hbk0upztWSLMp6ihWlXEGNruYPc49mU7zpFe2+l09PqBGAc86enpXfVUlqYbq/3Fq0tyKXV52rJFmU83ASL2FruIFt+NogqWr2Llh7oRat1r9Xn4m33JljCtBcgVOpt8gUAWMt44j55k9e9MO2/K5GY3l0PNqeUXPb3inwBANYynrhP3uxDmPYCRDq6Tb5MJ9oTQF+0+9MZT9wnb/ZhglXAnpf91dQg93AJYumw2wDUqdWw/luoaTyx97uoKW9qZotg4ywFx5LrfVy/PPkCBdCHnO2+sUEc3kWbTLAaZyAeS673cf0CBUAfcrb7xgZxeBdtEkUQAABgpntRBJ3BArrR+rkDqIF6CLTOBAvoRgvBQSIPTiOnbY7IzxE5bVO1UA8B3mKCBZm0MPBpXQvhaSMPTiOnbY7IzxE5bVO1UA97oE+D5QS5qJjbuGMRCSi+FoKDRD4QHTltc0R+jshpm6qFetgDfVosxnx1EeSiYs/Pz+l0OqVhGDR+maxpwDR+ALRiaZ+mL9yGMV9M94JcWMGqWAtfMqNZ88XOV1kAWrG0T7PytQ1jvrqYYFXMgD4/DRgALKcf3YYxX11sEQQAAJjJPViQgahKAPRMPwjvs0UQZrC3HICe6QfhfVawYIao97f4ogjQnohte9R+ECJxBgsaIHwrQHu07RCbMO3QMFGbANqjbYc62SIIDbiGb3Wp420Rt9lA79TL92nboU4mWLAjA4oyroeyj8dj6aSsovyQUjvloJV6WZtWyg9EZoJFlWrtIAwoymjlUHbk8lNrnbwn8vNELgdztFIva1Nr+YlcJ+E74zhO/nl8fBxhHMfxfD6PwzCM5/O5yO8fhmFMKY3DMBT5/UuVzjfqFrn81Fon74n8PJHLAfHVWn4i1Mla847tpJRexhtzJhOsjbReCUs3dK3nL9SmtTrZ2vNA7SLUydJjn61FyOPa3JtgCdO+kdZDq14ul3Q8HtPhcHD4FgBoXutjn9bHrlsQpn1nrYdWvUY2AgDoQetjn9bHrnuyggUAADDTvRUsUQQXEs0GAIBeGPtOZ4vgQtcwpymlppeLAQDA2Hc6K1gLub+jfr7EAMD29LdtMPadzhksuiVaDgBsT39Lq7o+g+XLCbe09iWmtnK+JL05n7G2/IKala67Ndb3GtN8T2v9LXm0VMa/c+tyrHs/tV403PrFcDCO9ZXzJenN+YwR88slj+QQsRyVrrsR6/t7akwzzNFCGU93LhruYoIVsbOB3Gor50vSm/MZI+ZXC53NLRHzehzjpmutiOWodN2t8V3XmGaYo4Uy3vUEC+ZqodJTn9zlbunflzsdEQf845g/XVHyW/tFCcodPTLBqpQGK6+p+Rl1QAhzLC3HUSYeW4sykdTe0IKp5Thqe1Ar+VmWCValdLx56QDoSZQVlV7Ib3rmA2YZ8rMsE6xK6Xjzipaf0dKzRkvPAvStpfYs2rNES0/t5GdZ9yZY7sGCglq6G6SlZwH61lJ71tKzQDRd34MFUbV0N0i0Zyl9707uNMCWItwtFam+RGvP1mjpWaAat5a17v3YIgjUovS9O7nT0BNnmfYX4W4p9QWoTXIGC+hJ6Xt3oqRhDy1H44ua7xFCu0dIA0BJ9yZYzmABVCDyOYrcabtcLul4PKbD4ZCenp42/+/eEjXfo6YLoCf3zmD9rkRiYGtbDLSgpOv5iYjnKHKn7enpadGkYel/95ao+R41XbCGvptWWMGiST193dUhAbSpt/a9p76bNljBois9fd09Ho/pdDqllJIOCaAhvbXvPfXdtE2Ydpp03Sq09Re/CGGFheAFaFOE9n3Pfm6vvhu2ZosgrGA7AwAt08/BfS4aprgIqz25bfV1scW8AmA7W/UbEVbRctPHsjUrWOzGV7DpIuZVb4etAe6J2B5G7DeiklfkYgWrAF9IfqvFr2BbuZdXJcvU9bD18Xjc/XcDRFKyPbzXD+hjp5NX3zNmzezW7cP3fh4fH/e7GrkBwzCMKaVxGIbSSeGG8/k8DsMwns/n0kmZrGSZqjG/ALZQsj2sdWyhD4mt1nJVWkrpZbwxZxKmfUPCjcZWY/jbkmVqi0tc9xZxWw/0qPa6WLI9rHVsUWOf25Nay1VUzmDRrdo7eOaLvO9eeSSn6OUpcl1kG9HLJCzhomH4RgsrMswT+Qtdi193axlQ1ZLOOaKXp8h1kW3oc+mJCRbQjcgdfIsDzuiD/Kta0jlH9PIUuS4CrCWKYOdEjYEYrgPOVlZQUqonUlct6ZyjxfIENTLO6pMzWJ2zDx4AYBvGWW1zD9Y7ev3C0OKXWwCACHodZ/U6rr6ygvV/+cIAAADr9TKuFkXwHdEPBAMAQA16H1fbIvh/ORDcpt6XqAEgMv10m3ofV1vBomkthl8GgFbop2mRFSya1uvh0lx8WQR4m3ZyHf00LTLBomkRlqhr7nyvXxaPx2PppACEVHM7GaF/itBPQ262CMLGat7+0PshVYD31NxO1tw/QWRWsKhChK9sS9W8/aGVL4s1lx9oVSv1suZ2sub+qZXyQ5vcg0UVerlPIaUvncbxeEyHw6HKDjuinsoP1EK93EYvfYjyQwTuwaJqNW/BmMuWjfyil59eBkTsK3q5il4va9VLH6L8ENo4jpN/Hh8fR4jsfD6PwzCM5/O5dFIWu/UMLTwX9w3DMKaUxmEYSiclq1rKbS3pnKvVcsVXLfYXtaefvqSUXsYbc6YmJlgqI1etDihafS6+aLUNq6Xc1pLOuVotV3zVYtlt8ZlYpoY27N4Eq4ktgr0sh/O+VrcMtPpcfHE9JN+aWsptLemcq9VyxVctlt0Wn4llah7fNxHkIvo+cwAAYLoaxvf3glw0Eaa95hCpxFUiBKywswCstXdfou9iCzWP75vYIghbKLE0XfNyOAAx7N2X6Lvgt0yw4I4S+8DtPQdgrb37En0X/FYTZ7AAAAD21PQZLGA/9toDPdMGAu+xRRCYxV57oGfaQOA9VrCgcnt/TT0cDmkYhlB77X1RhjZFrNt7toERnx94nzNYULnn5+d0Op3SMAzdfk2VB9Cm3ut2788P0TmDBY2KuKK0t5x54IsxLJe7/vTevvX+/FArEyw2Z8D6trX5U/NFfLnkzIPr+Yrj8Tj7v81d1tUdptiinCz9O9fUn1t6b9/WPr825G3yh82M4zj55/HxcYS5hmEYU0rjMAylkxKS/InlfD6PwzCM5/N59n+b+11GLxtr8qom0Z9zi3Ky9O+Mnle9id6GlCZ/WCul9DLemDOZYLE5He7b5E87cr/L6GVjq8HJmufeIs+iD8K2eOboZY9pvMe3yR/WujfBEuQC2MTlcknH4zEdDodut/e0bqt3vOZg/xZBAZTl9nnHwBKCXDTOPmKiWXoWQ1mux1bnY9Yc7N8iKEDv54Bqs6QNyX12DNbSF1bu1rLWvR9bBOOKvoWF+WrfurA0/coysMaSNqTX9pa49IV1SHe2CP6u6OyObK5fa4Vybcf1i2pKqcr7T65f/efKWZZt+4H4ctfTJW3I0vYqitr7C75nXFc3Z7AgKJOD9VzSCfGpp+vpL6AMZ7CgMs59rBf9ks5I9xfZ75/XmvyMVC72EL2e1kB/AcHc2jd478cZLCKx55zaRbq/yH7/vNbkZ6RyARHo74kqOYNFa+w5p3Zb7LFf+ndutd+/hq1LW6RxTX5GKhcQgf6e6tyadd37sYJFJJG+aEVKy7cip4321bByUkMaaVPk9jlS2iKlBV5LVrBoTaSoT5G/rkVOG+2rYeWkhjTSpsjtc6S0RervYQoTLJq21/akyAO0yGmjfTUMjGpII22K3D7vlbYathHDXMK00zThfwEgLv00NROmnS7VGP43cjhlAGKrrQ+psZ+G95hgUbX3OpIa7wa57ns/Ho+lkwJAZWrrQ97rp2ubMEJKzmBRuUiHcHOJvCcfgNha60Na7OdpnwkWVWutI0nJgXsAlmutD2mxn6d9tghStRq3AJKPrSPQPvW8b/p5amQFC6iWrSPQPvUcqI0JFlAtW0egfeo5UBtbBIFqtbp1xJYolmi13LRaz4F2mWDBznINglodTFFfmGViUG7apd+Auphgwc7eGgTN6fwMptpV08WbrQ/Yanq+msoN88xp798qs/oN2IczWLCzt84TzDnM7VxCu2oKs9x6AIKanq+mcsM8c9r7t8qsfgN2Mo7j5J/Hx8cRojifz+MwDOP5fG7i9+z9u0r8PtrTehlq/fnYXuvt+h6/Tz0kqpTSy3hjzvTw5Z9N8+HDh/Hl5WW72R7M8Pz8nE6nUxqGYdOvtnv9nhJafjaACFpvZ/d4vtbzkHo9PDz8PI7jh2//vLktgpfLJR2Px3Q4HEQcatxeWx1a3lLR8rMBRNB6O7vH87Weh3zVyji+uRUsXzkAAKA+tY3ju1nB8pUDAADq08o4vrkVLAAAgK3dW8FyDxYAAEAmJlgAAACZmGABAABkYoJFdy6XS3p+fk6Xy6V0UljIO4T+qPf18w7pRXNRBOE9x+MxnU6nlFKqIgQo3/MOoT/qff28Q3phgkV3WgkB2jPvEPqj3tfPO6QXwrQDAADMJEw7u7LPOo6578K7K0v+s4byU542t17eBdmM4zj55/HxcYQphmEYU0rjMAylk9K9ue/Cuyurpvw/n8/jMAzj+XwunZRN1fScNZWfVmlz6+VdMFdK6WW8MWdyBotN2Gcdx9x34d2VVVP+93JgvabnrKn8tEqbWy/vglycwQJgkcvlko7HYzocDunp6al0cjbTy3MCMM+9M1gmWAAAADMJcgEBOEALQEn6IdieCRbs6HqW43g8vvnv6QABmGNqvzG1HwKWE+QCdjT1AG1Nh+oBKG9qvyGQA2zPChbs6OnpKX369Ondg/KHwyENw/CbDtCqFgAp3e4PbvUbt0zth4DlTLDoUvTJyq0OcKttHd/mRfS8AYjqVvu5RZt6qz+oYeKkf6EXtgjSpRq34G21rePbvKgxbwAiuNV+btGm1rrNT/9CL0yw6FKNndP162Ru3+ZFjXlz5b4iaEOtdflW+7lFm7pVf7C1mvsXmMM9WEAznp+f0+l0SsMwVDn4AL5Ql4Ea3LsHywoW0AxfR6EN6jJQM0EuoAIOBk8T/ZC390gENZTD6HU5ghreI/TKBKsTGuK6uRiyDd4jESiHbfAe62ds1i4TrE5oiOs29X6T1zTc8Sx5j1OsfddblZVayuCW6Vzzd2+Vrq3KIcstedfeY/2MzRo2juPkn8fHx5E6nc/ncRiG8Xw+l04KOxmGYUwpjcMwlE4KG1v7rrcqK7WUwS3TuebvriX/WM+77pOxWf1SSi/jjTmTIBedqDWkK8s5JN6Pte96q7JSSxncMp1r/u5a8o/1vOs+GZu1S5h2AACAme6FaXcGi2bUct6DOJQZ2J56xlzKDLUzwaIZEQ6L6hTqsqbMeNf0ZmmZj9A2M12Etk2ZoXbOYNGMpXvYL5dLOh6P6XA4rL5z5doppJTsq67AmnMP3jW9WVrmnS+qS+62bUkfq8xQOxMsmrH0sGjOzkSnUJc1B4y9a3qztMw7yF+X3G3bkj5WmaF2tgjSvZx3iVw7hbUrYVNE2MbRsy3etXca906vmmyVB3u2b3xvr7Kd+z27r4su3Yrdfu/HPVgQh3tT2lPTO93q/paod3rVdF9NTeWI6bxXiCe5BwvaYotae2p6p1udQYt6p1dNZ+5qKkdM571CPdyDBcBsOYPD1KC35wXgfe7BAlZ5vf/fORd6O4/T2/Ny27Xt++tf/6oNBO6yRRAalfuL++stUimlarZLAeRybQdfXl7S58+fU0rlQpkDcZlgQaPWnBm51dnf2v/vLADQk2ub9/Hjx/TTTz/9pg1cM0mq6Ywf8D5nsKBRazr75+fndDqd0jAMOnuACda0m1awoE73zmBZwYJGuUQXYD9r2k0X60JbrGABAADMJIogAADAxkywgMXeCtculDtQk3ttlrYMmMsZLGCxtyJfiYoF1ORem6UtA+YywQIWe+tQt0AZQE3utVnaMmAuQS4AdiIUMxEohwB5CNMOUJitRkSgHAJsS5ALgJ0cDoc0DEPzW41qDQpQa7rn6qUcApRiggWd6WUQGdH1MtHWt2VdV0iOx2PppMxSa7rn6qUcRqT9hT6YYEFl1nbQvQwiKafWFZJa00091ra/JmhQB2ewoDJrz0+IiMXWrisktak13dRjbfvr/BzUwQoWXWjpq9/ar+x7bA9qKb+BPuzRbq1tf1taZdVP0DJh2unC8/NzOp1OaRgGX/12sCS/hY4GclnSnugn9iW/aYEw7XTNtrh9LclvW1+AXJa0J/qJfclvWmaLIF0QNWuduVs57uX3W39PS1tfgLLea09utUVz+wlb3NbRL9MyWwSBd+XaymFLCBBBjrZIewbYIggslmsrhy0hQAQ52iLtGXCPFSzISKAGAGqnL4NprGDBDgRqAKB2+jJYR5ALyKjmQA0ObAPkUXt7WnNfBhGYYEFGU6Mile58b/3+6xfL4/FYJE0ArbjVnkZs9+8R4Q/WsUUQCii9/eLW73dgGyCPW+1pxHYf2IYJFhRQejJz6/dfv1iyDYfGiUaZ3M6t9jRiuw9sQxRBgB24M4dolEmAde5FEXQGC6hW6TMNczg0TjS1lMma6jlASiZYQBBLBlE1Bebo6dB4rQPiWtO9VC1lckk97+1dArGYYEEABgPLBlG1fIHvTU0T39dqTXfrltRz71K/AiUJcgEBiO607AC2wBwx1XqYvtZ0t25JPfcu9StQkhUsCKCXlZi3vqi+t13J19h61LL17Fu1prtH77UHb73LXtqSXvoViEgUQWA3a6KWiXgGXGlLgAhEESSsXr4mlhIpf9d8UfU1FrhqpS2J1D63SP5SihUsivM1cVvyFyAm7fO25C9bu7eCJcgFxTmMvC35CxCT9nlb8pdSrGAB4V0ul3Q8HtPhcBCAAPiVtgEoyQoWUC3hhoFbtA1ARIJcAGFdDyh//Pgxy6F0B54hhlx18Rqw4uPHj+o2EIYVLCCs3F+nfe2GGHLVxet9V9dgBmv/PoAcrGABYeUOpxwpPPNrVtbYQuRy1UvdBvokyAVAYUIJswXlCmBbLhqGTkX+ir2HGp7f13e2UEO5qqF+bqn354dWWcGCxvX+Fbv3599Cz6Gxe372LfReP3t/fqidMO3Qqd4vWuz9+bfQc7CQnp99C73Xz96fH1pliyA07hplK9LX9uu2mL/+9a+bb4+Z8vy26cxTw9azrfT87HNNqVd7tE97tjdzRWyfgfVsEQR2d90W88MPP6TPnz8X3x5jmw7kF6VeRWtvgHYIcgFks2bF53K5pF9++SX9+OOP6U9/+lOI1YCPHz+mH374IX38+LFoOqAlh8Mh/fjjj+mXX34pump0XXX805/+tCo9VrqBqaxgAbOt+TId5av2axHTBC2IVrdaa7uAsgS5ALJZczA74qHuiGmCFkSrW621XUBMVrCAavUcMrvnZ+9R7++79+cHYnIGC2jC63MQ15DZx+OxdLJ2t/bZnSfZ19r87rmsp/T1+f/4xz8qt0B4tggCVXl9D1HPW3bWPrv7nPa1Nr97LuspfX3uX375RbkFwjPBAqryeqB5vUOmR2ufvfcB+97W5nfPZT2lr8//eqsgQFTOYAEkZzwgN3UKaJ0oggBv+OMf/5j+9re/pV9++SX9z//8T+nkQNUul0v6j//4j/T58+eUku18QF8EuQAAsjoej+nz58/phx9+sJ0P6I4JFkBK6c9//nMahiH9+c9//vXPbkV+E32Pnk2tE4fDIQ3DkP77v//b9kCgO85gAdzx/PycTqdTGobh1y1Ot/4MeqFOAHzlHiyAma5f4V9vcXr9Z++tZlntogZzyvF7dQIAK1gAv5ob9ey9L/fXf/7DDz/YKkVIr4NRvFeOp65QiR4I9MIKFsA7rpfBHo/Hm//82y/97325PxwO6YcffkifP3+++3dCSVOCUXxbzt9b8XqvHgE0bxzHyT+Pj48jQKvO5/M4DMN4Pp9v/vNhGMaU0jgMQ5a/873fB7ncK2tLyuB79UC5BnqRUnoZb8yZbBEEmCjn1qcpW7Mgl3//939Pf/vb39KPP/64+p43WwABvrBFEGjWXsEknp6e0qdPn7IMKm9tzRIUgxy2Lkc568Fb1AegViZYQPVqPPNx656gqc9h4Nmnqe/9Vjm6dc9bdDXWa4CUUvpd6QQArHVdAaopTPR1FeC1jx8/ppeXl/Tx48eU0v2tWNeBZ0rJ1sKOvPXeX5eVw+GQfvnll/TLL7+ky+WSnp6ebpa36Gqs1wApWcECGrDllqU9V4t++umn9Pnz5/TTTz+llO5/wXfvUJ/eeu+vy8rT01P613/91/S3v/1t89WfLevHXlsRAXKzggXwhj1Xi779Yn/vC36NqxGs99Z7n1p2crOaCvA9UQQB3lBbxLRrej9+/Jh++umnatLdu9flLKVUTZmrrX4A5HQviqAJFkBDnp+f0+l0+vWC43sh4A2M9/Vefl/f2zAMKaX06/+2KgQQ170Jli2CAIHNnQhdV0Ber2DdYmvXvt7L71tb+qZu7zNZBojFChZAYK9XNt6KHDd3YG1Qvq8t39VbZQSA7bhoGKBCUyPHzfHtgN29Wtu55m1KX1eu5ub1e+9ZVEmAYMZxnPzz+Pg4AhDD+Xweh2EYz+fzrP9uGIYxpTQOw3Dz/7/1O/7yl79897uW/v4affusb+XLa3PyeurvBiCGlNLLeGPO5AwWQKWWhmufE9L7unry8vKSPn/+nFL6uhLT0zmub5/1rXx5LUf4dGH5AepiggXQmW8H7FPuV7oVNGOvu5YiuDdBei+YyJy8BqANglwAsKlod3NFSw8AdRLkAoBVbgXD+PbPXv//1//9xz/+MZ1Op/Rf//VfvwnWsFdwjW9/z3V73+v0XP+dv/71r7OeEQC+c+tg1r0fQS4A2jQlkMKtAA1vBXG4/u8ff/zx14AQP/744/jjjz/++vu+/fu28O3v+ctf/jL+8MMP43/+53/++szXf+eHH36Y9YxvEZwCoG3pTpALEyyARs0Z4E+ZNNz6+96Krvd6MnXr9+w1Afn299x61luTrvee8b10m4gBtM0EC6hWCwPQEs8wZ4Uod/ru/e4I7/JWGrZYTcs9EcspwntYq4VnAOpmggVUq8QANLfeBtG1DX57yyt1CmC9exMsYdqB8FoIB17iGXKGBL9G3psaca+2cORz0zs3P3L+7hzUKYDtCNMOwLuen5/T6XRKwzBUNXHaivwA4F6YditYALzLasFvyQ8A7rGCBQAAMJOLhgEAADZmggUAAJDJrC2CDw8P/29K6f9slxwAAIAq/D/jOP7vb/9w1gQLAACA+2wRBAAAyMQECwAAIBMTLAAAgExMsAAAADIxwQIAAMjEBAsAACATEywAAIBMTLAAAAAyMcECAADI5P8HV+LIv1cqNo4AAAAASUVORK5CYII=\n", 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\n", 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x6EcUQWpRYuSerSJGvc2LEvMGIIJ77ecWbWqpEQT1L9QmPYgiaIsgTSrxcPBWW2be5kWJeQMQwb32c4s2tdQtlPoXWiHIBQR074C3Q98ApKSPgCgeBblwBgt2NHb/+e3pZN/3v/7uFs5VxwnQtnv9wb1+4x7noGB7tgjCjsZu67CNAoApxvYbpW4vhJKYYMGOxnaAXj4IwBRj+w0P8GB7zmABAABM5AwWMIr9+YzVSllp5TpZh/ICmGCxCR1MHFPvxdiD0myjpLrTSlkp6TpLKj+1mlpe3LM43AvW4gwWm3CINo6p98L+/LxKqjutlJWSrrOk8lOrqeXFPYvDvWAtJlhsoqQBSe2m3gsBNvIqqe60UlZKus6Syk+tppYX9ywO94K1CHIBFMcLNaE96j0QjSAX8Hf2WJevpDMxwDrU+/Lpf2mFLYI0xx7r8tnGAe1R78un/6UVJlg0RyddvpLOxADrUO/Lp/+lFc5gAQAATOQMFgAAwMZMsAAAAFZiggUAALCS6iZYQoACAEB5ahnHVxdFUAhQAAAoTy3j+OpWsE6nU+q6TgjQBuz1lKOWpyn31HxtABHU3s7ucX215yG/qWUcL0w7xToej+l8Pqeu6zZ9yrHX9+RQ87UBRFB7O7vH9dWeh5RLmHaqs9dTjj2fpkx5SrfGE71anhSRT+1Plmu/Pra3Rju7d98wxR79iL6K4gzDMPrn+fl5AJa5XC5D13XD5XL56t91XTeklIau6z78nCl/S1neKyPR1F4OS7q+ksoN06zVNygjsK6U0utwZ85UXZALiO69A5y3p3NjntJN+VvKUtIh39rLYUnXV1K5YZq1+gZlBPbhDBbs7Hq9pr7v0+l0SofDIXdyCEgZYQ7lho8oI7CuR2ewTLCAYhksQP3UcyCqRxMsWwSBYtnuAvVTz4HSmGABxSrpfAwwj3oOlMYWQQAAgIm8B4sq1fiOmhqvCYB91NaH1HY9tMEWQYpW4978Gq8JgH3U1ofUdj20wQSLotW4N7/GawJgH7X1IbVdD21wBouqCe8LAHHppymZMO00ydYCAIhLP02NBLmgaqfTKXVdt/nWgsiHcCOnDaBlkdvnvdK2Vz8Ne7JFEFZwPB7T+XxOXdeFewIXOW3Ur4TtPyWkkTpFbp8jpw2iEKad6kR68hf5CVzktLUuUhneKi237T9936/6uWvaIo2R7m1K8dLDZ5Hb50hpU34pzjAMo3+en58HiKLruiGlNHRdlzspMMsWZfhyuQxd1w2XyyV7WpakZ09bpHFJfkZLD+Sm/BJVSul1uDNnMsGiWCUM3MgrehmJNJCOnlelWZKfkSbee4icNmJQRojq0QTLGSwIyrmQ5Vo8Q6DclK+1e9hiPV1ba2UGohCmHQojdO1yLb6g8nA4KC+Fa+0etlhP16a/gFgEuaiEA6D1iXTAeE9rluXbQNUTXYhr7XraYn/Yan9RsxbLcU1sEayELRZEM3fLirIMLDGnDbHFjmj0hWWwRbBytlgQzdwtK8oySwa7BsrMaUNssSMafWHZrGABmzDQrd9W93jJk9stnvoqy/Vzj4E5vGiYbOwjfl+t+VPq+acl92Ptexm9bGz1EuEl50m2OIsS/WXJW5STuZ8Zvcw+Ump79ZFS78de5A+buRe7/dGP92AxhxcEvk/+xLLkfqx9L6OXjVbeTRP9OrcoJ3M/M3qZbY378T75w1LJi4bJJfrgJDf5s9yaebjks9a+l8oGY2xRTuZ+pjoQi/x7n/xhqUcTLGewoHDODoi2BLVqvW5r3yE2UQShUqJfibYEtWq9bmvfoUyCXEDh9n7BZMRDwbUeUIfWRazbe7aBXiAMZbJFEJik9S07QNu0gcCNLYLAKlrfsgO0TRsIfMQWQQgk4va7tyJu2QHYSwltYAl9CdTMBAseyNFBRX+hKQDx7d2XmNDB79kiCA/kiN5k6wkAS+3dl4h2CL9nggUP5Jjs3LaeAMBce/clHg7C71WxRdDSNDdrloUS9tlDZKW0zaWkE6Jas79UH7kpuSxUMcFyboWbWstCyY0M7SqlPpaSTnirxr5BfeSm5LJQxRZBS9Pc1FoW7G+v2/V6TX3fp9PpVNWKaSn1sZR0TlVrueI3NfYNtdZHpiu6LAzDMPrn+fl5ALZ1uVyGruuGy+Xy7u8YL3r+dV03pJSGrutyJ4WKRC9X0etlCfQXkFdK6XW4M2cywaIILXUY0QdFJYqepy2Vb/YTvVxFr5elaiVfo5dv2vBoglXFFkHqV+M2iEeKXhIPKnqeih7JFqKXq+j1slSt5GtL4wLKU0WQC+p3Op1S13VFdhhTDyFHil5YywHqSHkKfFZLvYzWTk7J12hpn6LkcQH1e/q8ujXOy8vL8Pr6umFyoD7H4zGdz+fUdV1xT9lKTjvAHkpuJ0tOO0Tw9PT00zAML29/b4sgbKzk7Rolpx1gDyW3kyWnHSKzgkXVhCkGgLj005TMChZNcggWAOLST1MjEyyqZvsDAMSln6ZGogj+XcmRdHislihVAFAj/XSdWh9XW8H6O0vUAACwXOvjaitYf9fq+xRaf8IAALCVVsdZrY6rb0QRbJx3YAAAbMM4q26PoghawWpc608YIIoan3KWck2lpHOKGq8JSmSc1SYrWAAB1PiUs5RrKiWdU9R4TQDRWMGCNzzhbU/ke17jU85SrqmUdE4R/Zoi10W24Z7TEitYNKvEJ7zeeL9MifccaqQuzldqP+CeU6NHK1jCtG+o1EawFSW+3LD1sKdLlXjPoUbq4nyl9gPueWzGrCsbhmH0z/Pz88B4XdcNKaWh67rcSQnhcrkMXdcNl8sld1KKlTMP3T+Az7TFZZOHXzNmnSel9DrcmTOZYG1IBf49lXe8iGXH/QP4LGJ7GLHfiCri/ctN+Znn0QTLFsENHQ6Hopbvt1bj9oCtltQjbgGp8f4BzBGxPdyq36hx61jE+5ebMeu6BLmABbY6tFtjhwbAdrbqNwSngMcEuYANbPUUzJMkAKbYqt+w2gPTeQ8WLHDr0HKuMnm3CECdIrTvEfo5KI0JFlWK0Cnt5bbvvu/73EkBYEWtte8t9d3UzQSLKrXUKZ1Op9R1ne0bZFPzoKjmayO+1tr3lvpu6maCRZVa6pRs32hD5IH+2oOiude6RR5FHfBFLg+sp7X2vaW+m7oJckGVBImgNhFD99+sfQh+7rVukUdRD/hHLg8wl76bWljBAqq05hP+CCsqkZ/srv2Ufe61bpFHUVcQ1r7WOWV17VU0q3JALbwHC6jSmu9umftZ3h9DKeaU1bXLt/oClObRe7CsYEFGNT2xjXYtaz7hj7SiAluYU1bXLt+R6ku09myJmq4FSmEFi6Zs9ab7uWp6YlvTtQBtq6k9i3Yt0fphWOLRCpYgF8FpiNYV7WB41AP0c9R0LUDbamrPol1LtH64dMaJQQ3DMPrn+fl5YF9d1w0ppaHrutxJqcLlchm6rhsul8sqfweRzS3Hyv888puW6V/zME7MK6X0OtyZM5lgBachykODRQ5r1/e55Xjt8h+1HZPfsB79Zh7qe14mWDBBiQ1WiWmeas1rjJhfUQbaUSYeW5Pf+6m97m6htOssLb2whqYnWCo9LYg4qHrPnHq55jVGzK9a26qo1xU1XUtFvK7cdTdinnwkYhsFayqxXr7V9ARLI8U9NVTsL5V2PbkHSaXlF5Qsd90tcRxQUxtV07WwnhLr5VuPJlhNhGkXYYV7ooWubY16CexFe5OX/pZ7aqiXj8K0NzHB2kINhaJ17iEAbE9/Wwf38WsmWCvzNAYAgFYY+37Ni4ZXFu3FfQAAsBVj3/GsYAEAAEz0aAXrf+RIDAAAQI1MsDZyvV7T8XhM1+s1d1IAAOBdxq7rMcHaSN/36Xw+p77vcydlEyohANCS2sc+tY9d92SCtZHT6ZS6rqv2IGDuSlh7Iwf3RC73kdM2R+TriZw22EqEcp977LO12seuu7r39uFHP8/Pz/u9GpnQcr+VvdS3f+fON8oWudxHTtscka8nctqIr9R+KEK5LzXv2E5K6XW4M2cywaJIpTZyETqIFpVaXt6KfB2R0zZH5OuJnLYparmO0pTaDykvRPRogiVMO+zIW9Dz8HJEiEe9zEM/BOvxomEI4HA4GEhk4OWIEI96mYd+CLYnyAVUIMLh38huAwpPayEO9fJj2nYokxUsqMAtslFKyZNJgEpo26FMVrBggqhPE4VWBahPxLY9aj8IkQhyARM4lA1Ay/SD8BtBLmAFDmUD0DL9IHzMChYAAMBEj1awnMGCL9hbDgDz6UfBBKtoGrH13SI29X0/+b91PwCoxdw+bUk/ymPGGGVxBqtgwreub8necvcDgFrM7dOc0dqGMUZZrGAVLGL41tItefGl+8EeIj/FjJy2KSJfR+S0UZe5fZoXSG/DGKMsglwAzbher6nv+3Q6nYrt/COHSI6ctikiX0fktI1VQz0ESEmYdoAqtlhE3n4TOW1TRL6OyGkbq4Z6CPAeK1hAMzw5h/zUQ6AWwrRDAM5P5OVsAOSnHuanL4JtmWBVTiMai/C1AOSmL4rDOK1OJliV04jGslYUIA0yQFvWbPdFpIvDOK1OglxUrqQD0S3sy79tjVnKIXGAtqzZ7q/VF0VV0niipHEa45lgZbBnxS+pETVpGE+DDNAW7f54JY0n9h6nlTT5LJkJVgYlVfw96TzGK2niDMBy2v3xjCceMwbdhwlWBir+fToPAGAp44nHjEH3kS3IRcuH9EsIUVvz/an52iCqaPUuWnqgFbXWvVKuq4Qx6FZ2vUfDMIz+eX5+HtbSdd2QUhq6rlvtM1lPzfdnj2u7XC5D13XD5XLZ7DtYX7T7tlZ65n7OmvkRrU1ZOz1z8mrN/I1UdiOlhfH2um/R2oK11HpdNdniHqWUXoc7c6ZsEywNcGw13589rk1DW6Zo922t9Mz9nDXzI1qbsnZ65uTVmvkbqexGSgvj7XXforUFa6n1umqyxT0KN8GCmmlol5maf7lXeraS+7qi5UdkVrDWT0uudqBV8g+mezTBevr878Z5eXkZXl9f19mbCPDA8XhM5/M5dV036qDy1L8H4tMOANE9PT39NAzDy9vfiyIIhDM1ypGoSFAf7QBQqmxRBKF1Y6PZlBKZaE1Toxy1HBUJaqUd+NiU/qHFvgRyMcGCTG4v++v7fpW/Y39zBiwGOR+bm0fy9mPKbF2m9A/6EtjRvYNZj34EuYD1jD1Q7OBxXLkjx0UqGxFCuteat8OwXnpyl1nWNaVcRCvTUIMkiiCQW5QOPmd0vggTkS1EmNzUmrfDsF56cpbZ2uo/gAkWkF2UQWuUdCwVaaAYKS1riHY90dIzR5R6FyUdQPkeTbBEEYRArtdr6vs+nU6nKg9qR4nyFSUdS90O9UcQKS1riHY90dIzR5R6FyUdW6q9L4HovAcLAvEeFwCW0pfAPh69B0sUwQbkigAl8tR0p9MpdV1X9ZNVALalL5nGOIm1WcFqQK4nWZ6gAQDRGScx16MVLGewGpBrv3kL+9wBgLIZJ7E2K1gAAAATOYPFJPYFAwCMY9zEl2wR5K6+79P5fE4pJfuCAQDeYdzEl6xgcZcIRMt4klW2aPcvWnqmipr+qOkaK1r6o6WH6dzD+Yyb+J17bx9+9PP8/Lzny5GhWF3XDSmloeu63EnJ7nK5DF3XDZfLJXdSRot2/6KlZ6qo6Y+arrGipT9aesYqsY3aSqn3EHJJKb0Od+ZMJlhMVlJnlCutOfMo2v0pscOOlofR0jNV1PRHTddY0dIfLT1jRWujWus/Sis3paWXbZlgsZpondF7SkrrWqJds84IiCxaGxWtDd9aaddbWnrZ1qMJliAX77her6nv+3Q6ndLhcMidnDBKem9DSWldS7RrPhwODvwCYUVro6K14Vsr7XpLS+8ejJe/5j1Y7/CGbWqjEQTISztMbVoeL3sP1gwiwhDV3EhPtzCyfd9vlDIA3jO3HRbhj6iMl79mi+A7om0bgJu579uwtQEgr7ntsPcsEZXx8tdMsKBAcztojSBAXnPbYQ/IoBzOYAEAAEzkDBYAAMDGTLAAAABWYoIFUIDSI4hFTH/ENI1VctoBameCRRgGDHUr8f5GSnPpIfYjpj9imsaKlvZIdWWM0tLLdO4xOYkiSBhC0NatxPsbKc2lRxCLmP6IaRorWtoj1ZUxSksv07nHZDUMw+if5+fnAbZyuVyGruuGy+WSOynN2SPvS7y/JaYZciitrmjz6if/2UNK6XW4M2cSph1Ix+Mxnc/n1HWdJ30AK9CuQv0ehWm3RRAIt90IoHTaVWiXIBcUJeqh1T3SteV3HA6H9OnTp3Q4HFb/bIAWbd2ubt3vRO1vU4qdNkjJChaFiXpodY90Rb12APa3dZ8Quc+JnDZIyQSrKtfrNfV9n06nU7UrEVG3XOyRrqjXDsD+tu4TIvc5kdO2lhbGdDUT5KIiEQ/UaiAAgMgijlUijun42qMgF85gVeR0OqWu60I90YnwMkx7taldpDIeKS1zRbmGKOmALUUo5xHGKm9FHNMxwb3Y7Y9+vAeLqSK8h6LruiGlNHRdly0NfCx3WVnr+6d+zhrfG6mMr5WWHPl4EyU/10jHnHxZIy9rqc9sL0J9U16YKz14D5YJFtXTcJYhdye71vdP/Zxcg+itrJWWHPl4EyU/c02+18jLWuoz24tS32AOEywgtNydbMkrWDWSj+uwgqU8ANt5NMES5AIAAGAiQS4AAAA2ZoIF0JipUbsiRPmKaE6+yEuA+plgAV+JPgjMMUGIkCdrpWFqSOK1QhhHyMM10zEnX9bIywj5uFYapnxOhOt+T/T0ATu6dzDr0Y8gF9CG6BG4ckSYi5AnpYdAj5CHa6YjVwCJCPmYI+pmhOt+T/T0AetLoggCY0WPwJVjghAhTyKkYYko6Y+SjrkipD9H1M0I1/2e6OkD1vdogiWKIMW7Xq+p7/t0Op3S4XCo5rsAIBp9LvzmURTBP+RIDKzpdqYhpZQ+ffpUzXcBQDT6XPiYIBcU73Q6pa7r0ul0quq73nKAGoCU8vYHrfS5sIQtgjSn1C0Hx+Mxnc/n1HWdJ3kADSu1Pyi1/4VHbBGEvyt1y8HtCZ4neQBtK7U/KLX/halMsGhOqR3T4XDQIQFQbH9Qav8LUzmDRXNuHdO97QnOOQHAfO/1o+/1v1ATEyz4wm37Qt/3uZNCRiVOtCOlOVJapoiU7khpGavENLM+/Sikel807IV/26o1f2u9Lqbpum5IKQ1d1+VOymiR0hwpLVNESnektIxVYppZX639aK3XFUWp+ZsevGi42gmWhn5b8pealdjQR0pzpLRMESndkdIyVolphrGMe7ZVav4+mmBVG6ZdKNBtyV8AoBXGPdsqNX8fhWmvdoIFLFNqYwewN+0ltMl7sIBJvK8EYBztJfAlUQRhByVG1zqdTqnrOu8rAfhAie1lif0SlMIWQdjB8XhM5/M5dV3n6SYA2emXYLlHWwStYMEOxj7d9EQRgKXG9CUlrrpBKUywAjPYrsfYt9d7QSMAS43pS8b2S8RnvBiPCVZgBtvtmfpEUaMKULc57bzVqbYYL8ZjghWYBrI9U58oalS3VdoENkp6o6RjqijpjpKOsUpLb2nmtPNWp9pivBiPMO2B3RpIeOTWmGpUt1Fa6OUo6Y2SjqmipDtKOsYqLb2l0c7zEePFgIZhGP3z/Pw8QESXy2Xoum64XC5Nfj/bKO2+RklvlHRMFSXdUdIxVmnpZZzc9zX398MYKaXX4c6cSZh2qpA73Gzu7weANeXu13J/P4whTDtVy73/OPf3r8VZCoBlamlHc/drub8flrCCBfzKE0OAZbSj0I5HK1iCXAC/cpgaYBntKGAFCwAAYCJnsKBwtezrB2AZ/QHEZoIFhZj6skkd8LZy52/u758rd7pzf/9cudOd+/trNzV/vWQegrsXu/3Rj/dgQT5T3wnSdd2QUhq6rts4ZW3Knb9rfP/UMrXGe2nk2zw15BuPTc1f74iCGNKD92CZYEGlPuqAddDL5M6/HIP2HJOTtcm3Mr+/Bu/lofyFMj2aYAlyAY0SSpjr9Zr6vk+n0ykdDofV/75W8o05tLlQH0EugN/Z4iWOY84ROMsRx+FwSJ8+fRo96J/697WSb+XK2UZ5cS60wwQLGrXFoG/MwesWD2dPHbCZhMqzuabkQ4t5lrONMtGGhtzbN/joxxmsdtkfzhhjykmLZWnvMzu589g5p3zfPyUfWgxcoY1iTcoKSZALlmixI4a17B11Lnd9Fakv3/dPyQeDQ1gmd5tBfiZYLKIj/j35QWS5y2fu758rd7pzfz+8R/n8mjzh0QRLFEGYQTQoAFqi34OviSIIK2o9GlSLh+OBtrXe7rXe78EUJlgwQ+vRoLaOBNj6QAaYbut2o8UIqF9qvd+DKaqYYEUejEVOG8y19ZPM1gcywHRbtxtWcKhV1LFq1HSN8YfcCVjDrVFNKYXbFxw5bTDX7UnmVm4DGAMZYKyt242t2z3IJepYNWq6xqhiBSvyU6XIaStZyU811lRrPtiKAkxVa7tRazs/lXzYTtSxatR0jXIvtOCjH2HaicK7Jz6TD5QWJjhCeiOkYayS0so2tPOfyQciSg/CtFexRZD22EL2mXygtC0UEdIbIQ1jlZRWtqGd/0w+UJJJE6z//u//TsfjMZ1Op+qW4CmLvfCfyQdKG3RESG+ENIxVUlrZhnb+M/lAFNfrNfV9/267POlFw//wD/8w/Nd//ZeXzAEAAM358qXb5/P57ouGJ61g/fM//3M6HA6epAEAAM35cmfBbQv3W5NWsF5eXobX19dVEgcAAFCqp6enuytYVYRpB9oiXC+0Sd0HSmCCBUwSYYBzi6zW9322NAD7y133I7R/QHzCtAOTRAgbLbIatCl33Y/Q/gHxWcECJonwZvVbuF6vi/jMU/U6ua9fy133I7R/QHwmWMAkuQc4fC33tqkpIkwaIqRhjJLuayu0f8AYJlgwUymDNOpX0lP1CJOGCGkYo6T7St30dzCNM1jv+PJNzZ5W8Za9+ERxe6pegtxnaKKkYYyS7it109/xHuPlr1W/grXkqUvEp5yeIsXh6TJMF2GLVYQ0QEn0d3FEHAcuGS9HvJ5VDMMw+uf5+XkoTdd1Q0pp6Lpu8n97uVyGruuGy+WyQcrmmXs9a11LxDwBANhD7vHUknHtVpbkScTrmSKl9DrcmTNVP8GqbUKQu0KWXhFqVFsZB+Az7Xs8ucdTtZWJ0q/n0QSr+jNYte1hn3s9a505KOXsQkvsjQeok/Y9ntzjKePaMjx9nnyN8/LyMry+vm6YHPiNQ5PjyCeAOmnfx5FP5PL09PTTMAwvb39ffZALyhUxyEhEDuzznlwHiEs7uCyfiEj7Po7xAtGYYBGWqEWMZZD6WK6BR2kDHvkUk7rNGMYLRLP5GSzLtsxV675c1uecwmO5zk2Wdl5TPsWkbjOG8QJzbTVP2fwM1vF4TOfzOXVdp/BDhSI8RImQBmB9uet27u8HtrV0npLtDJZlW6hbhC1OziksN2UrVqvbtqZed6v5tKbcdTtC+wZsZ6t5yuZbBC3bQt1scarDlK1YrW7bmnrdreZTTbRvULet5inVvwcL2JaHKHWYMpBsddA59bpbzaeaaN+AObwHCwAAYCLvwQrEvnwAAPZk/LkfE6wMaj40O7byquQAwJ5aH6PUPP6MxgQrg6iRFddoUMZW3r0r+Z6NZa0NMwB1q72v3HOMEnEsEHX8WaVhGEb/PD8/D9Sr67ohpTR0XTf7My6Xy9B13XC5XFb5u7VMvbYl6VsjHz+yd/4BkNce7f7S/mtKGvfoK9/ac4yS4/rYX0rpdbgzZzLB4lc1D9qnXtuShrGETrAme5fbmusJfER9y6eEh3dT0lj7va39+vjMBAsmiN4wRk/fnvaebJrc0jL1LZ8S2v0S0ghrMsECsti6w13z88d81pTvM9igFGtvnVqr7JfUfgDteTTB8h4sYFPH4zGdz+fUdV34F3aundaSrp22tVr2S0knENOj92D9IUdigHbcohWVELVo7bSWdO20rdWyX0o6gbJYwQJGu16vqe/7dDqd0uFwyJ0cgCy0hUBKj1ewvAcLGjflXR1eUggwvi2M+C4kYHsmWJBBpE53yqQp90sKI+UbkEeEdmBsWxjpoVSEfINm3It88ehHFEEiKjEK1JjQw3tdV5T8G5MOIZuBSO3nRyK146W2n1HuJdyThGmnVjk7jbkNf82d4VwlDZqAfLSfX9u6/czZ9rZ2LymLCRbVqrXhb20ysff1RsnfKOmgTpHK155piXTde9j6ekt8kAl7eDTBEkUQFhBJqlxR3n8TJR3UKVL5ipQWptHXwX3egwUbOBwOBgp3lNAZR3n/TZR0UKdI5StSWu4pod3KRV8H01jBAlbnSTVQGu0WMJX3YEHD9g7PmzucO8BUe7dbwqZDvaxgQQM8mQWIRbsM5XMGCxoW/ewDQGu0y1AvK1gAAAATOYMFAACwMRMsAACAlaw6wRIRpx7uJeSlDjKF8gJ5qYP1WONerjrB6vs+nc/n1Pf9mh9LBu4ltYveGZZQB6Pn4VpKuM7o5aWEPIQlotdBxlvlXg7DMPrn+fl5eM/lchm6rhsul8u7f1ebGq+7xmuCL3VdN6SUhq7rciflrlx1cMr3Rs/DtUy9zhz3Lnqb3UpZoV3R6+AcNV7TGFOuO6X0OtyZM606wWqVjgOmy91w5/7+qKa0Z63k4dTr1Cd8LXdZyf39UCJt2cceTbC8B2sF3mUB092W4FNKWV6yeTgcvNzzjintWSt5OPU69Qlfy11Wcrc3UCJt2XzegwVkcb1eU9/36XQ6pcPhkDs5bCzi/Y6YJrbhXgNb8B4s2JED3R+7PdE22GlDxAPgEdPENrQ3H9NvwXpMsChKKR2AgRsR5aw/p9MpdV0XaqtJrjSV0o7RlpL6LXWI6JzBoiil7KO3b5mIctaf3Gdw7smVplLaMdpSUr+lDhGdCRZFKaUDiDSYdPaAm1LqT+3cB74UpY2O1G99RB0iOkEuoHLH4zGdz+fUdV0xnSdAK7TRUC5BLqBREc++MJ6zBnxEGSmbNhrqY4IFlRM9a7pIA9aSDp6TR6QyEqnulEIbDfUxwQJ4I9KAtZWn21sMzFsZ7EcqI5HqDkAuglwAvBHpAHVJB8+X2CIqWCuRxiKVkUh1ByAXEyyANyINWFuxxcDcYH9/6g6ALYIA1Sppi9wW51BKOdtS0n0C4GNWsAAq1coWudK5TwB1sYIFhOAp/voiBT/gMfdpfdoTICcTLCAE0cfWHxSWskWudWvfJ5ML7QmQlwkWEEKJT/HXHsgaFLKGtctRiRO2EtsToB7OYAEhlBh9bO2zM6LesYa1y1GJZ8RKbE+AephgAcy09kDWoJA1rF2OTPwBprFFEGCmKWdnStxmlcPSfJLP40zJJ2f5AKYxwYINGexx43zVOEvzST6PI5/4kr4K1mWCxa80sOuLOIhxn/Nw6H6cpfkkn8eRT3lEbX8j9lUli3qf2dEwDKN/np+fB+rVdd2QUhq6rsudlGpcLpeh67rhcrnkTsqv3Of2RCyHuC8titr+KovrinqfWV9K6XW4M2cS5IJfOci8vohBC9znr12v19T3fTqdTlWeMykxClwLar8vtderOaK2vxH7qpJFvc/s5+nz5Gucl5eX4fX1dcPkwMd02qzteDym8/mcuq6rcpChzsRU+32pvV6xv9rrDOV5enr6aRiGl7e/t4JFcWp/6sv+an/a6Ol0TLXfl9rrFfvT/1MKQS4ojsPZrG1qGGoHmGnR1HIvvDtr0/9TChMsiqPTrtMWk5atJkIibtGircr9VvXUg5D66P8phQnWDBptWN8Wg7etBoSeoq7LALsMW5X7reqpByGwLm3qeM5gzWAPMKxvi/MaW50Bqf3szN62alO11evaqtxvVU+dAYN1aVPHM8GaQaMN69ti8GYiVAYD7LZtVU/Vf1iXNnU8YdoBGif08TbkK0DdhGkH4C7bPrYhXwHaJMgFcJfDrO0QtGMb8rUd2kvgSyZYwF0icK2jhIHXlqGPo1//lukrIaR09PtTCu0l8CUTLOAuT9/XUdvAa+qAPPr1T01fbROS6PenFNpL4EvOYAF3bRWBq7WD/7VFXZp6rij69U9NX23nqqLfny1s0QaJWAj8zjAMo3+en58H4LHL5TJ0XTdcLpfcSQmr67ohpTR0XbfaZ8r3/bSe161f/562yust2qCaKOMwXkrpdbgzZ7KCBSuq7en2FrZ4Yi7f99P6k/rWr39PW9XrFlftptCewnLOYMGKIu3D3/usyNjv2+Lgf6R8B9axVb0e2wbt2YZGOtunPYXlvGgYKnU8HtP5fE5d1+3yFHLv7wPY0p5tmvYTyuRFw9CYvbfB2HYD1GTPNk37CXWxRZDqRNpqsaap17X3O3hKeOcPwFh7tmlTv0s/B7GZYDWklYar1ve61HpdAExTa39Q63W91cp4rGW2CDaklchAtW61qPW6AJim1v6g1ut6q5XxWMusYDWklchAtW5V2/q6PFFjjNbLSevXzzhblxP9XNlaGY+1zASrIa00XMzTytaMSHIP1ud8f+vlZM71l3ifWab1esL7jMfqZ4sgkFJqZ2tGJLm3icz5/tbLyZzrL/E+s0zr9QRaZ4JFGNfrNfV9n06nk6c6GdyeqLGf3IOwOd/fejmZc/0l3meWab2eRGBMQU62CBJGCVsqbLVhTbm3iezx/SXUmdrPy+T+fupSQp1OqYwxBfUywWJVSxreEg59arBjKqXDb1EJdaaENLZIvY6plPoyd0yh3LGKYRhG/zw/Pw/wnq7rhpTS0HVd7qSMdrlchq7rhsvlsurfsp8Sy10rSqgzJaSxRep1TLX3mcodU6SUXoc7cyYTrBWV2JCsrcQ80JiWr8RyB7xPvS5fif2rcicPpjDB2kGJDQlxGpIo6aAOylN53DPWEqUsRUkH0xjPjvdogiWK4IpEaipTlGhPQimzJuWpPO4Za4lSlqL0r0xjPLucCdaKNCQsoUFjTcpTedwz1qIssYTx7HJPn1e3xnl5eRleX183TA4AAEB8T09PPw3D8PL298K0UyyhVPOQ70CrtH95yHdKY4sgxYqyx7w18h1olfYvD/lOaaxgFaz1JzolvJi4RvJ9Xa3X462vX/62ff1r0/7lId/V5dI4g1Ww4/GYzudz6rrOEx0oVOv1eOvrl79tXz/UQl2O6dEZLFsECyZKEJSv9Xq89fXL37avH2qhLpfFChYAAMBETUQRLHF/aolphtLUXs9qv75WtXBfW7hGyKnUOlZqun81DMPon+fn5yGyruuGlNLQdV3upIxWQpovl8vQdd1wuVxyJwVmKaGeLVH79bWqhfvawjVSt+hjpFLrWCnpTim9DnfmTFWdwSpxf2oJaRYeldKVUM+WqP36WtXCfW3hGqlb9DFSqXWs1HTfOIPFh67Xa+r7Pp1Op3Q4HHInBwAgBGOktj06g2WCBQAAMFETQS4AAAByMsEC2EnxUZGognIIsC0TLMjMYKcdt8PQfd/nTgoNUw7boX+BPEywIDODnXacTqfUdV2xUZG2ttZg0KDyfcphO/QvkMeqEyydGkxnsBPLlu3Y4XBInz59EmnqgbUGgwaV79uyHBoHxKJ/gelWacfuvRzr0c9HLxou5aVgwPqiv2xxLO1YPmuVoVrKYolqqj/KEbRpSjuWHrxoeNUJVg2NUQ3XwG/cz/3UMrCaU2aUM2rUel2opU0rQU3lpnU13Msp17DLBKsGGtS6uJ/7qaFRnUs5o0atl+uW27S9tV7WatLavXw0wfrDgi2KVbrtU7ZfuQ7u535u5zpaFKWcXa/X1Pd9Op1OznkVLMp9jFKuc2m5Tdtb62WtJu7lZ0+fJ1/jvLy8DK+vrxsmB4C5jsdjOp/Pqes6A8OCuY8AZXh6evppGIaXt7+3ggVQCU8O6+A+ApTNChYAAMBEj1awvGgYAABgJSZYAAAAKzHBAqqzylvY2cXW90pZKIv7BdRAkAugOn3fp/P5nFJKorAFt/W9UhbK4n4BNbCCBVTndDqlrusmRWHz5DyPOfcq0udz39z65H4BNRBFECB59xCsSX0CWiCKIMA7WnlybqUur1byv5X6BHCPCRa/aqXjpzx7lM3D4ZA+ffqUDofDZt8Rwe2MS9/3uZPSpFbyf4/6pM8iKmUTEyx+1UrHXwoN9G+UzfVYWchL/q9Hu/B7+ow4lE1EEeRXtw5fxx9DSdG0rtdr6vs+nU6nTZ5YK5vrua0skIf8X8/W7cLW7draSuozaqfPQpALCKqkzt2Bdt4qqfymVF562V5p7ZoyDPt7FOTCChYEVdKTbk/r6jZn4Fba0/Q56TWgrVtp7VpJfQbUzgQLWKzFjr2lwfWcyUdpg9M56S1tErlES+X9psV2DViHCRbADC0NrudMPkobnM5Jb2mTyCVaKu8AS5lgAczQ0uC6tMnSXlrKl5bKO8BSwrTTBOFrWVsr782ClJR31qdfpmYmWBNoDMrlnRQAEId+uVzGwx+zRXACe9DLZXsLAMShXy6X8fDHTLAm0BiUq6WzEgAQnX65XMbDH7NFcAJ70GFbth0Aa9CWwHaMhz9mBQsIw7YDYA3aEiAnK1hQgT2e1u7xHafTKXVdZ9sBsMjWbUktbS6wjadhGEb/8cvLy/D6+rphcoA5jsdjOp/Pqeu6zZ7W7vEdACXQ5gIppfT09PTTMAwvb39vBQsqsMfKj9WlNnmK/j750yZtLvAeK1gAjbher6nv+3Q6nUYfTvYU/X1z82fOvQAglkcrWIJcADRizsF/4XjfNzd/BGEAqJctgtAw25u2EzFv52w5Eo73fXPzJ9r2r4jltSbyF9piiyA0zPav7chbSqK8bkv+Qp0EuQC+Eu0pek1azttSn9aXmu41tFxe9yB/oS1WsABYValP60tNNwB5CHIBwC5KDYxRaroBiMUWQe5qeavMnuQzNSo1MEap6YaP6Gu2J4/5kgkWd91CCPd9nzspVZPPLKVTr597zFL6mu3JY75kiyB32SqzD/nMUt6nVD/3mKX0NduTx3xJkAuAgl2v19T3fTqdTra2Vco9BohJmHaaU/O2mlqvrdbr2pJzQ/Vzj6eptR2p9bpSqvvaaJMJFtXacz/03p1DrXu9a70uYD+1tiN7X9ee/Vqt94x2OYNFtfbcD733GYla93rXel3AfmptR/a+rj37tVrvGe1yBgtW4IwEADXRr8HHnMGCDTkjAdPttQXJ+Q6YTr8G89kiCEAWe21BEuYcgD1ZwQLYkNWTx06nU+q6bvNzF3t9T6mUUYB1OYMFsKHj8ZjO53Pqus7qCSEpowDzPDqDZYsgwIZExyI6ZRRgXVawAAAAJhJFEKBwzspwoywAxGWLIEAhRMPjRlkAiMsK1gOeDgLRiIbHjbIARGLc/HsmWA/cng72fZ87KbCYhq8OXvzJjbJQPu0yNTFu/j1bBB8QVYma2E4EEIt2mZoYN/+eFawHPB0cL8dTuD2/s4anjLVsJ6rhXgDL1NIOaJdjf1eO7yuZcfMbwzCM/nl+fh7gra7rhpTS0HVdld+Z4/q4z70AtAOx1NwfK2t8JKX0OtyZM9kiyGI5loX3/E7L3nG4F3W7Xq+p7/t0Op0WPwVd87OIRTsQS839sbLGXF40DLACA/rljsdjOp/Pqeu6xWdS1vysFinPAB979KJhK1gAK3Bgfbk1nxZ78ryM8gwwnwkWwAoM6Je7HZKO9lktUp4B5hNFkKxE6KEWIihRE+WZmhhrsDcrWGRlGwoAsCVjDfZmgkVWtqEAAFsy1mBvtgiSlW0o7MH2EIhJ3WQPxhrszQQLqN5te0jf95P+u6iDv6jpYltR7/uSdM2tmwCR2SIIVG/u9pCo+/ajpottRb3vS9Jl6xZQIxOsynlZJMwP2R118Bc1XWwr6n1fki7h9GmdcVqdnoZhGP3HLy8vw+vr64bJYW3H4zGdz+fUdZ1ODAAgEOO0sj09Pf00DMPL299bwapc1CeeAACtM06rkxUsAACAiR6tYIkiCA2LGpWM+u1d9pR1clH2oD22CELDokYlo357lz1lnVyUPWiPFSw+5OlbvU6nU+q6zt5vdrd32VPWyUXZq5fxEY84g8WHRLgBAPg94yOcwWK2Vp++eTIFAB9rtb9sdXzEx0ywAonaQN1eBNnaC/Bu++b7vs+dFAAIq9X+Mur4KOp4siUmWIG02kBF5clUfjqJZeRfOdyr+eRdfvrLWIwnAxiGYfTP8/PzwHYul8vQdd1wuVxyJwVC6LpuSCkNXddN/m/Vp2X5x75av1dL6mvreQdv6f/2k1J6He7MmYRpD+S21Ax8tuQN90IjL8s/9tX6vVpSX1vPO3jLeDI/UQSBKl2v19T3fTqdTuH2xwO/p74CJRJFEGhK1MPHtSv9PEzp6S+V+grUxBZBAFZT+tbM0tMPQH5WsAD4nSWrOKVHE1uSfqtfAKRkggXsxOCzHEtC/Ja+1WtJ+oVGLof2CNiSLYLALmy9KoeobPPIt3Joj4AtmWABuzD4LIcQv/PIt3Joj4AtVbVF0JI/xFXK1jHtCMxXSv0ppT2CVpXSljxS1QqWJX9gKe0IzKf+AGsovS2paoJlyR9YSjsC86k/wBpKb0uq2iJoyT+G0pd1W+JefU07AvOpP1/TzpbF/Yqh9LakqhUsYih9Wbcl7hXAtrSzZXG/WIMJFqsrfVm3Je4VwLa0s2Vxv1jD0zAMo//45eVleH193TA5AAAA8T09Pf00DMPL299XdQYLAAAgJxMsmMEhWABaot+D8UywYIbbIdi+73MnBVZlELWM/KNW+j0YT5ALmMEhWGolgtYy8o9a6fdgPCtYMEPp72egbktWUU6nU+q6ziBqpiX5Z/WLyPR7MJ4JFrAaA8QYlmzlMYhaZkn+2YIVg3YMWMoWQWA1tkfFYCtPmdy3GLRjwFImWMBqDBBjuK2iUBb3LQbtGLCULYIT2ToAj7WyvUw7cF8t+VLLdWyhhbxppR2DOVpoA9ZgBWsiWwcA7cB9teRLLdexBXkDbdMGjGOCNZGtA4B24L5a8qWW69iCvIG2aQPGeRqGYfQfv7y8DK+vrxsmB1jb9XpNfd+n0+lkywtAMNpoKNfT09NPwzC8vP29FSyonOV8gLi00VAfEyyonOV8gLi00VAfUQShciJilU/UJu5RLuqgjYb6mGDBjgyImOO2hajv+9xJIRDlgrn0RbAtWwRhR/baM4ctRNyjXDCXvgi2ZYIFOzIgYo7bFiL4knLBXPoi2JYtgrCjJXvtbekAIKXl/YFzX7AtK1hQCFs6AEhJfwDRWcFiU1Zd1nM6nVLXdbZ0UIUcbYP2iFroD9ajXWALT8MwjP7jl5eX4fX1dcPkUJvj8ZjO53Pqus5TNuBXOdoG7RHwlnaBJZ6enn4ahuHl7e9tEWRTDtIC9+RoG7RHwFvaBbZgBQtY1fV6TX3fp9Pp5AA1UBTtFzCFFSxgFw5fA6XSfgFrEOQCWFVLh68djqYVrZT1ltovYDu2CALM5HA0rVDWAb5miyDAyhyOphXKOsB4tgjCHa1sh2GZw+GQPn365DA81VPW+Yh+E35jggV33A46932fOyk0xiCFpZQhctBvwm9sEYQ7bIchF1HMWEoZIgf9JvzGChbcscZ2GE+RmUMUM5ZShphqjf7KNlL4jSiCsBFRtwAogf4K5hFFEHZmuwQAJdBfwbqsYAEAAEz0aAXLGSwAAICVmGABkN0WQWEEmgEgBxMsqmRgBWXZ4h063ssD5dBvUxNBLqiS98BAWbY4ZO/gPpRDv01NrGBRJe+Bic2TSt7a4h063svDl7Q7sem3qYkJFlUysIqttK1bBmbwtdLqRWntTmv029TEFkFgd6Vt3bJ1Bb5WWr0ord0BymWCBezu9qSyFAZm8LXS6kVp7Q5QLi8aBgAAmMiLhqEQpZ1rACAG/QfEYIsgBFPauQYAYtB/QAxWsFiFp2brEaqWG/WKsZQVUtJ/rEmdYglnsFjF8XhM5/M5dV3nqRmsRL1iLGUF1qVOMUbTZ7A8hdiep2awPvWKsZQVWJc6tY9ax+hNTLC8XHB7XhDIXpY2xiU15uoVY5VSVlqqv5StlDpVulrH6E0EuSjtXR3AY0sPcTsEDvmov8CXah2jNzHB8nJBqMfSxrjWxhxKoP4CX6p1jC7IBQC7ul6vqe/7dDqddt1+k+t7AajToyAXTaxgARBHrm1etpcBsAcTLAB2lWubl+1lAOzBFkEAAICJmn4PFgAAwB5MsAAAAFZigkURvFwSAPiSsQFRCXJBEUT/AgC+ZGxAVFawKMLpdEpd14n+BXd4ilsn9xXeZ2xAVKIIAhTueDym8/mcuq7zFLci7itAbF40DFAp73eqk/sKUCZbBKEwtg3x1uFwSJ8+fUqHwyHL99daJnNfV+77Sky5yyXwsUlbBJ+env7flNL/3S45wAj/T0rpf6aU/iul9H8ypwVSqrdM1npdlE25hDj+9zAM/+vtLydNsAAAAHjMFkEAAICVmGABAACsxAQLAABgJSZYAAAAKzHBAgAAWIkJFgAAwEpMsAAAAFZiggUAALASEywAAICV/P9JJsys7UgTVgAAAABJRU5ErkJggg==\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 13.828063542394737 max: 218.27011488545185\n", + "image 1 reprojection errors: average: 14.266911731441311 max: 168.02572846508102\n", + "image 2 reprojection errors: average: 13.259631557103953 max: 159.2642398699781\n", + "image 3 reprojection errors: average: 13.422864585752475 max: 137.03572224565602\n", + "image 4 reprojection errors: average: 14.042001696393454 max: 177.2409590707412\n", + "image 5 reprojection errors: average: 14.419637448618259 max: 232.93124855660497\n", + "image 6 reprojection errors: average: 14.28349841175458 max: 95.76014743378593\n", + "image 7 reprojection errors: average: 13.816511440007561 max: 110.1203537367734\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.5083e+06 2.55e+06 \n", + " 1 2 5.9099e+03 1.50e+06 6.91e+01 9.53e+04 \n", + " 2 3 4.1487e+03 1.76e+03 7.89e-01 1.47e+03 \n", + " 3 4 4.1432e+03 5.47e+00 2.66e-01 8.32e+02 \n", + " 4 5 4.1421e+03 1.18e+00 3.87e-02 9.54e+01 \n", + " 5 6 4.1419e+03 1.74e-01 9.74e-03 3.51e+01 \n", + " 6 7 4.1418e+03 7.01e-02 4.36e-03 1.38e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 1.5083e+06, final cost 4.1418e+03, first-order optimality 1.38e+01.\n", + "mean reprojection error: 0.8453353393586547\n", + "max reprojection error: 3.1669253825859003\n", + "mean reconstruction error: 0.07599713093701795\n", + "max reconstruction error: 0.35918856633649\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 14.186361973998029 max: 142.13279660962115\n", + "image 1 reprojection errors: average: 14.3430728296801 max: 114.57890349429739\n", + "image 2 reprojection errors: average: 14.030040315205252 max: 143.10725465392943\n", + "image 3 reprojection errors: average: 14.251753739436086 max: 183.5931418951843\n", + "image 4 reprojection errors: average: 14.207830844722821 max: 149.83951606976632\n", + "image 5 reprojection errors: average: 14.44821544767734 max: 124.8193940574816\n", + "image 6 reprojection errors: average: 13.708985116983074 max: 111.01284859340113\n", + "image 7 reprojection errors: average: 13.930256656976045 max: 135.84947501329322\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.4939e+06 2.77e+06 \n", + " 1 2 3.9147e+04 1.45e+06 6.89e+01 7.63e+04 \n", + " 2 3 3.8133e+04 1.01e+03 8.75e-01 6.73e+02 \n", + " 3 4 3.8086e+04 4.70e+01 8.20e-01 4.48e+02 \n", + " 4 5 3.8072e+04 1.33e+01 1.44e-01 3.80e+01 \n", + " 5 6 3.8071e+04 1.59e+00 4.35e-02 5.31e+01 \n", + " 6 7 3.8070e+04 7.30e-01 1.38e-02 2.72e+01 \n", + " 7 8 3.8070e+04 4.30e-01 1.15e-02 3.81e+01 \n", + " 8 9 3.8069e+04 3.75e-01 9.62e-03 4.53e+01 \n", + " 9 10 3.8069e+04 3.59e-01 9.64e-03 5.63e+01 \n", + " 10 11 3.8069e+04 1.91e-01 3.68e-03 3.71e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 1.4939e+06, final cost 3.8069e+04, first-order optimality 3.71e+01.\n", + "mean reprojection error: 2.5564564934849114\n", + "max reprojection error: 9.98131009620747\n", + "mean reconstruction error: 0.2290003305014601\n", + "max reconstruction error: 1.0506093661635483\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 15.100127042494083 max: 160.51986142773094\n", + "image 1 reprojection errors: average: 14.658957672792338 max: 151.55699428817383\n", + "image 2 reprojection errors: average: 14.687438047915299 max: 77.94474483482014\n", + "image 3 reprojection errors: average: 14.67090740732709 max: 129.3577026301649\n", + "image 4 reprojection errors: average: 14.871906549459718 max: 245.14146882194805\n", + "image 5 reprojection errors: average: 15.002691746208708 max: 181.49916389261205\n", + "image 6 reprojection errors: average: 14.142437625710745 max: 130.7997569389291\n", + "image 7 reprojection errors: average: 15.023724647497383 max: 155.0864057338731\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6006e+06 2.02e+06 \n", + " 1 2 1.0686e+05 1.49e+06 7.10e+01 7.35e+04 \n", + " 2 3 1.0555e+05 1.31e+03 1.24e+00 1.98e+03 \n", + " 3 4 1.0541e+05 1.40e+02 1.38e+00 1.30e+03 \n", + " 4 5 1.0536e+05 5.00e+01 2.58e-01 1.23e+02 \n", + " 5 6 1.0535e+05 6.83e+00 9.27e-02 9.59e+01 \n", + " 6 7 1.0535e+05 3.87e+00 4.56e-02 8.69e+01 \n", + " 7 8 1.0535e+05 1.69e+00 2.22e-02 6.17e+01 \n", + " 8 9 1.0535e+05 1.31e+00 1.96e-02 8.12e+01 \n", + " 9 10 1.0535e+05 1.28e+00 1.87e-02 8.80e+01 \n", + " 10 11 1.0535e+05 1.03e+00 1.38e-02 1.13e+02 \n", + " 11 12 1.0534e+05 7.43e-01 9.27e-03 9.66e+01 \n", + " 12 13 1.0534e+05 3.53e-01 3.94e-03 4.33e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 1.6006e+06, final cost 1.0534e+05, first-order optimality 4.33e+01.\n", + "mean reprojection error: 4.2565467060174385\n", + "max reprojection error: 16.392380585922076\n", + "mean reconstruction error: 0.378511613097883\n", + "max reconstruction error: 1.7280389068962418\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 17.09867179575005 max: 118.48103903261772\n", + "image 1 reprojection errors: average: 17.363731455254754 max: 155.74102883809007\n", + "image 2 reprojection errors: average: 16.937621673918557 max: 107.22656681795047\n", + "image 3 reprojection errors: average: 16.897941538151336 max: 104.96684275768155\n", + "image 4 reprojection errors: average: 17.939475068224173 max: 252.947133817352\n", + "image 5 reprojection errors: average: 17.62125191913709 max: 98.61883188730926\n", + "image 6 reprojection errors: average: 17.390697365602733 max: 135.27484877400363\n", + "image 7 reprojection errors: average: 17.61046441629536 max: 152.50414170677618\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0189e+06 2.49e+06 \n", + " 1 2 4.2301e+05 1.60e+06 7.52e+01 2.75e+05 \n", + " 2 3 4.1944e+05 3.57e+03 2.99e+00 1.15e+04 \n", + " 3 4 4.1905e+05 3.90e+02 1.68e+00 2.64e+03 \n", + " 4 5 4.1885e+05 2.06e+02 5.72e-01 7.90e+02 \n", + " 5 6 4.1880e+05 4.98e+01 2.50e-01 5.96e+02 \n", + " 6 7 4.1876e+05 3.86e+01 1.87e-01 3.64e+02 \n", + " 7 8 4.1873e+05 2.71e+01 1.48e-01 4.46e+02 \n", + " 8 9 4.1871e+05 2.13e+01 1.09e-01 3.56e+02 \n", + " 9 10 4.1870e+05 1.04e+01 5.10e-02 1.98e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 10 11 4.1869e+05 1.00e+01 7.13e-02 3.50e+02 \n", + " 11 12 4.1868e+05 9.55e+00 4.88e-02 1.88e+02 \n", + " 12 13 4.1867e+05 8.06e+00 5.82e-02 2.89e+02 \n", + " 13 14 4.1866e+05 8.05e+00 4.57e-02 1.85e+02 \n", + " 14 15 4.1866e+05 7.56e+00 5.46e-02 2.60e+02 \n", + " 15 16 4.1865e+05 7.38e+00 4.38e-02 1.69e+02 \n", + " 16 17 4.1864e+05 7.17e+00 5.24e-02 2.90e+02 \n", + " 17 18 4.1863e+05 6.95e+00 4.21e-02 1.71e+02 \n", + " 18 19 4.1863e+05 6.47e+00 4.73e-02 3.32e+02 \n", + " 19 20 4.1862e+05 6.56e+00 4.09e-02 2.12e+02 \n", + " 20 21 4.1862e+05 5.75e+00 4.01e-02 3.53e+02 \n", + " 21 22 4.1861e+05 6.16e+00 4.02e-02 2.93e+02 \n", + " 22 23 4.1860e+05 5.53e+00 3.55e-02 3.70e+02 \n", + " 23 24 4.1860e+05 3.24e+00 1.78e-02 2.04e+02 \n", + " 24 25 4.1860e+05 1.70e+00 1.02e-02 1.79e+02 \n", + " 25 26 4.1860e+05 1.76e+00 1.34e-02 2.15e+02 \n", + " 26 27 4.1860e+05 1.69e+00 9.92e-03 1.70e+02 \n", + " 27 28 4.1859e+05 1.79e+00 1.41e-02 2.35e+02 \n", + " 28 29 4.1859e+05 1.71e+00 9.65e-03 1.57e+02 \n", + " 29 30 4.1859e+05 1.86e+00 1.53e-02 2.64e+02 \n", + " 30 31 4.1859e+05 1.61e+00 8.35e-03 1.11e+02 \n", + " 31 32 4.1859e+05 1.62e+00 1.44e-02 2.71e+02 \n", + " 32 33 4.1859e+05 1.50e+00 7.60e-03 9.34e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 33, initial cost 2.0189e+06, final cost 4.1859e+05, first-order optimality 9.34e+01.\n", + "mean reprojection error: 8.486325964905733\n", + "max reprojection error: 30.167549332567813\n", + "mean reconstruction error: 0.7507895219703264\n", + "max reconstruction error: 3.116007122632202\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [camera_radial_position, 0, 0],\n", + " [-camera_radial_position, 0, 0],\n", + " [0, 0, camera_radial_position],\n", + " [0, 0, -camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [-1, 0, 0],\n", + " [1, 0, 0],\n", + " [0, 0, -1],\n", + " [0, 0, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({3: 568, 4: 400, 2: 192, 5: 68, 6: 44})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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0u91YXl6G1+uF0WhEeXk5OI4ryahaKZHN/o0dTRf7HkQQEgilCxGABIJCknn7FXI6B0VR4Hk+5e/9fj8GBgZQV1eH7u5uTUaojEYj6urqUFdXBwAIBoNwu92IRCJ44YUXiAdhHlEjxZ5MEIrfi1hBmNhUQiAQtAMRgASCAsSoX+I4N5qm04oyNUknNldWVjAzM4PDhw/D4XAUZD1qYDabYTabsbKyguPHj0sRQuJBWBoks5wRBAHhcDhpUwkRhARC8SECkECQQaZxboWOACZui+M4jIyMgGVZ9Pb25mTDogWIB2H+KESTjRxBKI6tYxhG6jImEAiFgwhAAiEDcrz9aJqWLGDyTaIA9Pl8GBgYQFNTE5qamkr6Rpps7Zk8CKPRqORBWF5eXvLi90IkmSDkeR6hUEj6WewcY7HLmEAg5A8iAAmEFCjx9itWBHBpaQlzc3M4evQobDZbQbZfbBI9CHmelyxnFhcXwXGc5EHodDqJB2ECWrDZIYKQQCg+5MpIICRBHJvFcZwsv7NCdwHzPI/+/n4AQF9f3wUjcrIR0jRNx3kQchwHj8cDt9uN2dlZUBQVZ0qdyoPwYkELAjAROYLQ5/OhqqqKCEICQSUujLsGgaAiordfYqNHOjJ15qqJz+eD1+tFS0sLGhsbC7LNUoJhmKQehJubm5iamoozrbbb7aQZQYMkE4RjY2NxRuskQkgg5AYRgATCy2Rq9EhHIVLAgiBgYWEBS0tLMJvNF6z4U3s/JnoQRiIRuN1urK6uYnx8HAaDIc6UWqmQKDXhocUIoBwoipIi3WKEMBgMSp9FHFlHBCGBIA8iAAkEJPf2U0K+bWCi0SiGhoag1+vR19eHZ599VtX318rNshDrMBgMqK2tRW1tLQAgFApJ9YNerxdms1kShIUY7UdQjvgdFR/SYut1YwWhGCGkaZocRwIhASIACRc94o1DSco3kXxGALe3tzE4OIiOjg7U19fnZRsXMyaTCfX19aivr4cgCJIp9ezsLPx+P8rKyuI8CBNTk6VGKUYAM605lSAUPTtpmo5LGRNBSCAQAUi4iMkl5ZtIPppABEHA3NwcVldXceLECZSVlan6/lqkkN3UqbZvsVhgsVjQ2NgIQRDg9/vhdrsxOTmJYDAY50FYqpSa+FEqWpPVEIqCUPx9bMqYCELCxQgRgISLEjnefkpQuwkkEolgcHAQZrMZfX19pFGhSFAUBavVCqvViubmZgiCIHkQjo6Owuv1IhwOo7a2FuXl5UWfuSyHUoxait/TbEkmCFmWlSyeiCAkXIwQAUi4qEj09lND/Invo9aNVTQ47uzslOrULha0ftOlKAp2ux12ux2tra0YHR2FzWZDIBDA0tISOI6TTKmdTqdmTam1vp8TEdO4apFMEEaj0T2CUJxUQgQh4UKECEDCRUNiylfNC7oaTSCCIGBmZgYbGxs4derURTvztpQiVGKE0OFwoL29HRzHSabU8/PzEAQhzpRaCx6EpbR/RfJdt0hRVNyxSSYIE+cYE0FIKHWIACRcFGTj7aeEXCOA4XAYAwMDsNls6O3tJSnfEoVhGFRUVKCiogIAwLIsPB4PXC4XpqenwTBMnCl1MY7zhdgEojbJBGEkEkE4HJauH6IgFOcYl9o+JRCIACRc0CTaQ+TrhptLE8jW1hZGR0dx4MAByavuYqXYTSBqo9PpUFVVhaqqKgC7tZ0ejwfr6+uYmJiAXq9HeXk5KioqYLVaifBPQbFFq1xBKKaMiSAklAJEABIuWHL19lNCNk0ggiBgamoKLpcLp0+fhslkytPqCFrBYDCgpqYGNTU1AHYjv263G0tLS/B6vTCZTHn3ICy2mMoGra05VhCKDyyRSASRSATA7gNhYg0hgaA1iAAkXJBEo1HJ1LcQT+NKI1ehUAgDAwNwOp3o7e3VxM1NC2sASrNGLVuMRiPq6upQV1cHQRAkU+q5uTn4fL60HoTZUor7V2sCMJbY0XTAXkG4uLiIpqYmGAwGIggJmoIIQMIFhdjosbOzg4mJCZw8ebIg21XSBLKxsYHx8XF0dXVJ82oJu2j1Jl8IKIqC2WyG2WxGQ0MDBEFAIBCA2+3G1NQUAoGA5EHodDpzahIqtf2sZQGYSKIgXF9fR3Nz854IYWJTCYFQaIgAJFwwxKZ882HMnA45EUCe5zExMQGv14uenh4YjcYCrY6QT/IlTCiKQllZGcrKytDU1ARBEODz+eB2uzE+Po5wOBxnSi33fColMSVSimuOJVbgCYIAQRAQDocRDoel3xNBSCg0RAASLggSTV0ZhsnrbN5EMgnOYDCI/v5+VFdX4/Tp0yV9M8snF1oTiJpQFAWbzQabzYaWlhbwPC+ZUg8PD4Nl2ZLwIMyGUheAsSTzIEwUhOLYOoZhpC5jAkFtiAAklDSpvP2KEQFMJTjX1tYwOTmJQ4cOqTo+TO2b4oV0ky0UxRSrNE3D4XDA4XCgra0NHMdhZ2cnqQehw+GATqeT1lxqx7kU1yyXZIKQ53mEQiHpZ7FzjMUuYwIhV4gAJJQs6ca5qT2aLRPJIlc8z2NsbAzBYBC9vb2qjgkTt6fmjYDcVEobhmHiZhSzLCuZUs/MzICiKJSXl4NlWXAcJwnCUqCUBaDShwQiCAmFonSuAATCyySOc0tWL6PGZA4lJF6AA4EA+vv7UVdXh66uLs0ZTyd7Py1AUsDqodPpUFlZKTUaRaNReDweLC0t4aWXXoJOp5MEo81m03TdWSkLwFwhgpCQL4gAJJQU4ogmjuPS2rsUU0isrKxgZmYGhw8fhsPhyMs21P58gUAAq6urefWfIxQXvV6P6upqzM7Oore3V/IgXF5ehtfrhdFolASh1WrV1DkgRvlLkXw8/CUThMFgMK4DmQhCQiaIACSUDErGuRXjgicIAoaGhhCNRtHb25vXInw1axxXV1cxNTWF2tpazM7Owu/3w2q1xvnPFQoSASwcsR6EwG6jklg/6PP5YLFYpHPAYrEUVUQIgqDpCGUxEa+F4v5JJgjFkXVEEBJiIQKQoHkSGz20eCPw+Xzw+/1obm5Gc3Oz5oynkyHWKIZCIfT29krCOpndiN1ul8SAmrWMBO2QyoNwenoagUCgaA8FwMWdAlZKMkEYOw4TQNyUEiIIL16IACRomkKOc8uWpaUlzM3NwWw2o6WlpSDbzLXJJbFGEUDcXNNEuxGxu3RpaQk8z8PhcKCioiKuu5Rw4ZAvD8JsKVUBqIVodipByLKs9BpREOp0OtA0XZL7mqAccuUmaBYx6icn5VsMWJbF8PAwAKCvrw/PPfdcwbadSwRwfX0dExMTOHz4MJxOJ4D0N1iapuF0OuF0OtHe3i51l7pcLszMzICmaUkI2O32nCK0JAWsTZI9FPh8PrhcLsmDMDZKrHb5QykLQK2tO1kNYawgpCgqLmVMBOGFCxGABM1RCilfr9eLgYEBtLS0oLGxseAXyGyEkjiJxOfz5WRLk9hdGolE4Ha7sbq6ivHxcU03ExDUgaZp2O122O12tLW1ged5yXJmcXFRihKLptS5Rom1KKTkIE4l0jLJBKForD85OYn9+/cTQXiBQgQgQVOk8/bTAoIgYHFxEYuLizh27BisVmtR1qFUAIZCIZw/fx7V1dU4deqUqvvVYDCgtrYWtbW1APY2E5SVlaG8vBwVFRUZa8dKLQJYSmvNJ7FRYADgOA4ejwdutxuzs7OgKCrOlFqckyuXUhWApbju2Ovuzs4OKIpCNBqNm7QUW0NIBGHpQgQgQRPI8fYrNizLYnBwEDqdDn19fYpvYmqiRChtbGxgfHxc9UkkqUhsJvD7/XtqxyoqKi6YhhJy89sLwzBJPQg3NzcxNTUVZ1otp2ygFIUUUBoRwFSI1xdxtGbszxMFYeIc41I8VhcjRAASio5cb79s31uN99ve3sbQ0BDa2trQ0NCgwspyQ44AFAQBk5OT2N7eRk9PT94L9ZNBURSsViusViuam5ul+bUulwtLS0vgOE6KDIn1iIQLD9GDsLq6GsDesgGDwRBnSp34nSUCsPCkWnsyQRiJROKayERBKM4xLsVjdzFABCChqCjx9lOKGuPSBEHA3NwcVlZWcPz4cZSVleV1e3LJJABDoRAGBgZQXl6O06dPa+YCHDu/tr29fU+qMBQKgeM4qYasVG+ehPQklg2EQiGpftDr9cJsNkuCsKysrGR9AEtVuALyxWs6QQjsfuf1er2UMiaCUDsQAUgoCoVo9BDHwWX73pFIBIODgzCZTLjkkksyvo9ozVKI1HA6Abi1tYXR0VF0dXVJKTitkpgqHBkZgclkkjqVDQaDlC4mDSXqoMW6RZPJhPr6etTX10MQBKmOVDQmFyPJTqcTZrO5ZM6DCzECmIlYQSiea5FIBJFIBMDudTmxhpBQHIgAJBScQnn75TIP2O12Y3h4GJ2dnVKUIhOFbGBIti1BEDA1NQW3243Tp0/DZDIVZC1qotPppJQwsBsZcrlccdMpREFYSkKAIB+KomCxWGCxWNDY2CiVMkQiEUxOTiIUCsWZUmv5PL8YIoDpiB1NBxBBqDWIACQUFLHRoxDeftkIQEEQMDMzg42NDZw8eRIWiyWv28uWRAEYiUTQ398Ph8OB06dPXzAXUZPJhIaGhrjpFC6XSxIChTQjvlAoNUFCURQMBgPsdjtqa2shCAK8Xi/cbjdGR0cRiUQ0O6nmYowApoMIQm1BBCChIBTD209pRC4SiWBgYABWqxW9vb2K11isCKAYrTxw4IBUZH8hEjudIrahRPz8LMtKE0rU8J4jaAcxWwDsngeiB2Fra+ueSTUcx8V5EOZzJrecdZeqgCnE2pMJQjFDFCsIE7uMCepArpCEvMPzPFZXV6HT6WC32wsWgVASkXO5XBgZGclJRNE0XTABKH626elpbGxs4NSpUwWfz5oPlIjo2IaStrY2cBwnmRGL3nNiVIg0lJQ26ZpAEifVxJ4H8/PzEAQhrtO8kPZNpZ4CLrTVVTJTakEQEA6HpaYShmGk6KDYZUzIDiIACXkj1ttve3sbRqMRDoejYNuXIwDFujmXy5Vz3Vyu83mVwHEcJiYmUFFRkVW08kKEYRhUVFSgoqICwCvec2JDiV6vl+oHk1mNELSLEiGVeB6wLAuPxwOXy4Xp6WkwDBNnSp3P704pRwA5jiv62pMJQp7nEQqFpJ+JglCMEJLvtXyIACTkhcSUL8MwBe8+zBSRE61SnE4nenp6VCl4LsRn9Hg8WF1dRXNzM/bv35/37RUatfZhovdcotWIxWKJm1BCbhzaJZdImk6nQ1VVFaqqqgDslnokPhiI54HValVV9JR6BLDYAjARIgjVhQhAguok8/YrZIOESLqI3ObmJsbGxlS1Ssn3ZxQ9CVdXV1FfX1/QaGqhyOfFOtFqJBAIwO12Y2pqCoFAQGooqaioIA0lGkNNIWUwGFBTU4OamhoAQDgcluoHvV4vTCZTnAdhLtvVooiSSymsPZ0g3NjYkOaSE0GYHCIACaoRm/JNbPSgaVoaHVQokgkynufzNh0jnxHAaDQqeRL29fVhZmam4IL6QiK2oaSpqUnqLHW5XHENJZkaCbToqXchks9ImtFoRF1dHerq6gC8Mst6bm4ubpZ1NtZDpSCiUlGKa48VhH6/HzqdDjzPIxgMxjWcEEG4CxGABFXI5O1XjAhg4jaDwSD6+/tRVVWFnp4e1b/4+WoCEcfQdXR0SDepQnYcF5Jifa7YztLEhpL5+XkAiKsbiy2Ov5hvIIWikKnUxFnWqSLFoim1VtatNqUoAGMRm1hompY+hxghJIJwFyIACTkjZ5wbwzBFSQGLYkKs9+nu7paKw/OxPTU/oyAIWFhYwNLS0p4xdPkQShfThS8TqRpKNjc3MTU1BZ1Oh/LycsnTkpBfiiWkkkWKfT4f3G43xsfHEQ6H03oQlrKIKuW1A7tNLIldzLElSUByQSjOML4YBCERgISsUeLtR1EUOI4r4Op2I3Isy2JkZASBQAC9vb15NYlVU5SxLIuhoSHodDr09fUlvZAR4VE4EhtKxLqxlZUVDA4OoqysTOowtlgsmr1plOo5o5VIGkVRsNlssNlsaGlpifOiXF5e3lM6oJV1ZwPP8yXtpSmnizmZIOQ4DizLSq8RTal1Oh1omi7Z45mM0j26hKKidJxbMVLALMtiYmICzc3N6OrqyvsXV63P6PV6MTAwgLa2NjQ0NCR9zYUqAEvlc4l1Yy6XC83NzWAYRrIZiU0Tan1UWamgVSGVzItSNKWen5+XxtYZDAY4HI6SElSlHgHMxscwWVNJrCCkKCouQljqgrB0zkaCZmBZVmrokDvOrdA2MKurq1hZWUFzczPa29sLsk01xMvi4iIWFhZw7NgxWK3WvG6LoA6xs2tjG0piR5WJUSGxI7FYaFVIZaJU1s0wjHScAWB6ehqCIMDtdmNmZibOnNxutxfcaFkJpS4Ak6WAlZJMECbe/0pZEBIBSJBNYspXyYlO03RBUsAcx0k33dbW1oLOBc1FlLEsi+HhYVAUlTTlq+a2UqGFm+yFIGyTjSoTG0oWFhakyRQVFRV7GkoIydHCuZktDodD8iAUa0k3NjYwOTkp1ZKK5uRaElylLgDzNcv4QhKERAASZMHzPKLRqOyUbyKFSAH7fD4MDAygsbERzc3NWFxcLGjaOdvPKK67ubkZTU1Nsv6mkFNHCLlB03RcVEicTJHYUFIIEVCqQqpU1x07wxhIXUu6vLwMr9cr+daVl5fDarUW9TMXYxScmqgRAcxEMkEYjUb3CEJxdJ3WBCERgIS0xHr7Acj65pRvAbi8vIzZ2VkcOXIEdrtd2mYhvQeziV6J6z569ChsNltet0XQBomTKRJFgJpGxBcKpSoA080wBlJ7EM7Pz8Pn80nTaorRXKSFUXC5UIxzRpx6FbuGWEE4MjKCqakpvO1tbyvoulJBBCAhJeLJy3FcVlG/WPIlAMUuX57n0dfXF1dkXWiRpOQzchyHkZERcBy3Z91yyNdnK/aN9mIUtrEiQBAESQTMzs7C7/fDarVKE0pybSgp9vHNllJdt9I0ZCoPQrG5SDwXRFPqfFLqKWAtkCgIZ2dnMTo6WsQVxUMEICEpcrz9lJAPASh2y7a0tKCxsbHo5tNyxYvf70d/f7+Uqs5m36ptOi0e44tNfGmN2IaSxsbGON85NRpKSvX4lqoYyUW4JvMg9Pv9cLvdmJiYQCgUius2V3t8Yanucy3j9/vj/FyLDRGAhDiUePspQU0xJggCFhcXsbi4mDZ1WgwBmGl7q6urmJ6exuHDh3Oa5XuhirVS+1yeEIfyMIs0Dds5kcx3bmdnBy6XK66hRPSdk1PzVIqRtIslApgOiqJgtVphtVrR3NwMnufh8/nixhfGmlLn2m1e6gJQi+eLGNHXCkQAEiSUevspQS0xJhokMwyTsVu20AIwXaczz/MYHR1FOBxGb29vzhdn0gSiDX4+FUKFewMfPuMsyPZomobT6YTTubs9saFE9CAUbUgqKiqSNpSUqpAi694LTdNx4wtju83FBrhYU2qlZSalLAC1+hDp9/tTersWAyIACQAgRf3USvkmokZkR5yJm84gWe1tKiHV9gKBAPr7+1FXV4fu7m5V9m2pRcqUUKzPteEN4/vnVnF3TwMcZnkC/YpmI9pbK2VvY20njB+cX8VbexthN+V++U1sKIlEInu6SsUJJVpKPSmlVAVgIUVUYrc5x3HweDxSPSlFUSnnWSejlAWgVtceCAQ09T0kAvAiJ18p30RyuXgLgoD5+XksLy/vmYmbjmJEABPFiziD+PDhw1LURg0uVAFYzJu8L8IhwvIIRjnZArDBxqDeLr/2yhdmEWF5hKKcKgIwEYPBgNraWtTW1gLAnoYSs9mMcDiMYDCY9yYCNSlVAZipCzifMAyDyspKVFbuPqAkzrOONa222+171qlVESUHra7d5/ORFDBBG+Tq7VcIotEoBgcHYTQaZRkkx1LMGkCe5zE+Pg6/35+XGcRqC0Ce57G0tASTySS7luxCo73Sgg9fm9+pMfuqy/K+jVgSu0rdbjfGx8cxPj6OcDgcVzNWSNP0i4VEH8BikuhBKEaLV1dXMT4+DoPBEOdHCWizjk4OhfAAzAZSA0goOmp5++Ubj8eDoaEh7Nu3T/LJUkKxIoDBYBD9/f2oqanBwYMH83IRVVMAhkIhnD9/Hna7HX6/H9PT05I5sVhLVqgbwYUa2dQCsR3Gx44dkxpK3G43lpaWwHFc3IQSrc2tLUUxotVIFLA3WhwKhaT6Qa/Xi3A4jIWFhZL0o9Sqh6Fo5aMVtPUNJ+QdQRDgcrkAQLNfakEQMDs7i7W1NZw8eRIWiyWr9ylGDaDP58PZs2dx6NAhqRYnX9tS47NtbW1hdHQU3d3dsFqtUqpNNCcWbwYWiwUVFRWoqKgoqdShyOpOGC/Oe3DzoRowtPbO+ViiHI+fDW/gsvZyVFnVjcrFplJjG0ra29vjasZmZmbiasqSpQgJmSml1LXJZEJ9fT3q6+shCAKee+450DQtlQ+UlZXFeRBq+XNpdYoJiQASiobo7be+vg6j0aipE1EkEolgYGAAZWVl6Ovry+mmU8gIoJhC3d7exmWXXZb3dFquAlAQBExPT2NrawunT5+GyWRCJBKRfp9oThwIBOByuST/MbvdLjUX5NrRXAhenPdgeNWHaw9UwWLQ3o0hFl+Yw+iaD06zHld2VhRsu4k1Y5FIBB6PR0oRamlMWamg5QhgOsR68MbGRsmPUvQgnJycRCgUijOlztWgXG20mgImNYCEgpPY6MEwjCbTbC6XCyMjI9i/fz9qampyfr9CCcBQKIT+/n6YzWZUV1cXpJYqFwEYjUbR398Pq9WKnp6ejDeoWENa0X8s0YtOvBHI6S7MtK18nJs3HarB1fsrNS/+AKDcosf7r2jNy1qVRKQMBgNqamqk72LimDIxIlSqUeFCUapCOfZ7mOhBKAgCvF5vnEG5lupJtSq8A4GAopGf+YYIwAucZN5+DMOk9KvLJ2KTRDJvssRolBqoPS0jGWIKtaurCzRNY2VlJa/bE8lWKG1vb2NwcBCdnZ1S7Y9SknnRud1uqbtQp9NJ6WKtRIp0NAWrsXQud7Y8dAjnSmJDSbKpFGJUuNgCgJAbma4tFEVJHoStra1J60ljPQgLnSXQagRQa9332rvKEFRDbPRI9PajaVpqACkkYkQuVgCGw2H09/fD4XDIikYpIZ9myYIgYGpqCm63Gz09PTAajdje3i5YZFWpAIybnnLsOHTGvRehbEWlTqeL6y4Ui8ljI0WiIJQj7rUYnb5QUKsmLdlUCq/XC5fLFddQkq0JMaG4KLWvSVZPKppSz8/PZzWxJhe0KgCLaQuUDPKtvADJ5O1XrAhgYkp2c3MTY2NjOHjwoGRkm8/tqUU4HMbAwIAkWsUbaiGncygRaxzHYXh4GADQ19eHLz89g2CUx1/euB90HhoiEovJ/X4/XC4XxsbGEA6H4XA4UFFRkTQyQLqASxOapuFwOOBwOPY0lIgmxLFlAlq6CRL2kmsKlWEY6aEPiJ9YIzYYxZpSq30+aDEFrMXrGhGAFxhyvP0KbY+SuF2e5zE5OYnt7W0pepbP7amJWKd44MABKeIlUkjxIm7LH2bxg5eWcfuJBliTpA39fj/6+/vR1NSEpqYmUBSFG7trMOcKyBZ/UY7HD86t4szBKsVdqbGRInGW7fb2NlwuF+bn5wEgThioBS8I+NJTs2ivNON1x1+xEBIEAb+e2EJ7VRlaK3JPxRTieD92bhVzriA+fG1bztG7QnWlJjMhdrvdkjG66DmnpTIBwiuoLaCSTazxeDxYX1/H5ORknO2U1WrNedscx2ky6qw1v13t7SFCViR6+6U70dLNrM0nNE1LHnmVlZVx0bN8oOZ7C4KAmZkZbGxspKxTLKSwFgXg8nYIc1sBLLiD6K6PLy5eW1vD5OQkjhw5EieuDjXYcajBLntb20EW05sBNDl9qLLm1pWaOK5KnE4gCgNBEGA2m+F0OnOyKaLF/bMTjvs5LwCja37MuoJ4x6XNOX0WkXxf0Je3Q6oJt2LZkuj1+riGksQyAdFmqBQsRi4G8h1BS2wwEm2nlpaW4PV6YTKZpOtENtcBjuM0V4cqCILmooBEAF4AJKZ8M31ZGIYpSgQwEolgcHAQhw8fllIDpYBoTWO1WtHb25vywljICKDY4LKvqgx/fn0nLPpX6l14nsfExAR8Ph/6+vpyLsCushrwZ9e0waRXv6YmcTrB/Pw8dnZ2JO8xq9UqpZJSRYpZXoAuSTTzI2c69vyMoSnce2lT0ten4uzCNs4v7uCeS5T9nVp88Oq2gm1LEAQMrfiwr9oCcx6Ot0himYBoMyRajNhsNkkA5CtDUAi0dsOXS6FTqLG2U8ArHedzc3NxHedyHxC06AMYCoU01QACEAFY8ojefomNHukotAAUx6IFAgEcO3aspMSfOI1EjjVNIbqORUSxSSd0t4bDYZw/fx6VlZU4deqUapGUsgJ10Or1ejgcDslqwufzweVyYXh4GCzLxtUP6nQ6TG8G8IuRDbzhRB1qbPKEglJhs+mLgOUFMBdAUCpTBHDdG8Hj/avoa3Xihu7qlK9Tk2Q2Q6LFiHjcQ6EQNjY2UF5ersnU3oVGsWvoEjvOA4EA3G43pqamEAwGJQ9Cp9OZVFRpcRKIaKatJcg3qUSJTfkma/RIRyFTwIFAAP39/aitrUV1dbXmnspSIQgC5ubmsLq6ilOnTsl6clO7CcTljyAY5dDoTN6xm7gtsT6xq6tLqr0qJFMbfjQ6TTlFCmOjqBRFwWazwWazobW1Na6zUGwsoEx2gBVg1uVPnd1YICGUC7wgYHUnjAZHfGnCv7+whGVPCB870xEn/OZdQZxb2sFth+Mno9TYDHjTyXo0l8uPVDw/58HTE1u47+o2VaKGsQ0lbW1tYFkWzz//PHZ2djA3NweKouJG1mntRi9SSlNAEim2AIwl9gGhqalJejAU51onm2mtxQig1kygASIAS5Jk3n5KKFSt2urqKqampnD48GE4nU6MjIwUJfWslGg0isHBQZhMJkXTSNROAf/z7+YQ4Xg8cMuBPcc4dlvi6Lz19XVVfRSVsB2M4jsvLONgbRnuONWQl20kdhaKjQUWxoWRgXNS3VBFRQUsFsuefcbxgubHwIlwvACakl9f+OL8Np6d9eBNJ+tQZ3/l+G8HXqkJBl4RJc/Pe7DiCYMXBDB4ZRsUReFgrbKbVJjlIQjIW3qcpmno9Xrs27cPQHzdqNhAINYPFnJudSa0JKKUouW1xz4Yio1lYsR4eXkZLMuC4zhp7rVWJhX5/f6sx5rmCyIAS4xsUr6J5NsGhuM4yfIjtgatWN3HStje3sbQ0BA6OjqkehS5qP353n5pM/wRLukxFgVgrFhNV5+YbxxmPV5/vA4tOXbWKhHRiY0FwWAQLpcL09PTkuO+KAwePbeBRU8IH7++A3pGmzc2EY4X8He/moLVqMN9Muv/DtfbYNTRe9LgH7hq799TFIXXH6sDxwuq7Isr9lXgin35K+tIjKQl1o2Gw2G4XK64udViNCjZg0ChKOUIoBZTqKlIjBhzHIfz589L2adYD0KHw1G0EgKtzQEGiAAsGTJ5+ykhn0JMtB1paGhAd3d33AVQywJQEAQsLCxgaWkJJ06cyOpJTe0IYJ0jdSSPoigpNdbe3o76+nrVtptIlONlCYUjDcUdcWQ2m+Nml4rGxMPDwxDcIfh9BnhcW3mpIxMEASGWVyUFytAUDAyNowr2p8XA4Fhj5s5u8fxkaKpkoqGZhJTRaNzTUOJ2uzE9PR1XL5aukSgfaDmKlolSXjvDMGAYBm1tbTAajWBZViodmZmZifOktNvtBUsVEwFIyIpcU76J5KsGcHl5GbOzszhy5Ajs9r03I60KQJZlMTg4CL1ej76+vqwvCIXsAl5eXkYgEMBll12m6KIiCAL+/blFdFSX4bKOzFGbbz27CF+YxXte1VKQyJla+zB2VFVbWxuOxRgTz83NSXY0FRUVsNlsOd/sfjq8gXlXEPde2qSKCPxokg7mRJ6ZdkFHU+htK5f9vtlGpQaXvfCGorLOmWSwvIAf9a/i8o7yuBS1HJSsOVm9WOyDgNhIVIgRZaUcASxlAQjETwLR6XR7PCk9Hg82NjbiPAjFEoJ8fW7SBEJQDMuysrz9lKD2Cc5xHEZGRsBxHPr6+lJGV4plP5PuQuz1ejEwMIC2tjY0NORWu1YIARi7ry0Wi+InSoqisBWIYGdh78082T7qa3Xg7OJOUdKmi54gfjGyiTtO1uc8GzfRmDgSiUg1Q6LvmFhfmI0P3almOygo7zCWQ5Tj8Z0XlnFlZwXaK1+JTP96wgVQUCQAs+UP025wvJC1AAxEOAwue6FnaLzmaP4EYCKJDwIcx2FnZ0cyIhcEIc6IXM1oUCmLKC02USgh3b5PVkIQey0wGo3SOaGmSTlpAiHIRqm3X7EQBVRzc7M0aSIVxTCgFqOOiRczQRCwtLSEhYUFHDt2TJUvZq7HaCcYxR+mXbi+qxq6JIJLrGlpaGhAc3Mznnnmmay282fX7pP92q46G7rqlKd2X5z3wGHWo7M6+yfeCCtAEHY7XNXGYDCgtrYWtbW1EAQBwWAQI/Nr+PJv+3FLC4XaCrtUPyjHULbObsIthzMLm2CUw1d+PYvbj9cp2jfBCIcFVzBOAP7Zte2y/14kWzH1zsuawOdwGOwmHT58bTssBuWiQs1IGsMwcUbkLMvC7XZjc3MTU1NTcRMpcm0oIRHA4qFk/ck8CD0eDxYWFlStKSUpYIIs5IxzKzaigJqfn8fRo0dhs2UWCcUSgIlROZZlMTw8DIqickr5qs25xW38bnILh+ttaK6Ir0EUJ2WIHdVaIrG7VhAE/HRoA3qGxl/eKF9sAvFR1I4qCzqq8t81R1EULBYLGGslLI4oDh5uhoWKwOVyYWlpCTzPpxxkz/ICQlEOclfJ8QKCEQ6L7qBsAahnaLzvytY9P89GTGWLGhFghzm7dGs+hZROp0saDRIbSsxms/QgoPTmX8oiiuf5kvZbzOV8ET0IxZpS0ZR6ZmZGEnGxptRyCQQCRbHnSkfpHuELkMRxblq9eLAsi6GhIdA0nTblmwhN09JnKxSJfnk+nw/9/f1oaWlBU1NTQdeSics6KtBZbUW945VCdUEQMDExgZ2dHfT29qaMRhUr2rDgDuIng+u4/Xgdau2766YoCh+4qhVGXeHO3zDL57y9E012nGgSa1fNcDgcaG9vjxtkPz09HRcl+tcBP2xzi/jUa7plbcNq1OGhWw/ktM5cKMWoVCHXHBsNir35x3aWizf/THZL4gN8KVLK4lVNxIdDi8UiNZf5/X643W5MTEwomlpDbGAIKREtPTiO02zUDwB2dnYwODiYVc1cMZpAYrcpNqnIjVgWGj1Do8H5yk0lEong/PnzcDqdOH36dMpzwh2I4JvPzOOmQzU4VC9/xm8ylN5szXoGRh0Nkz7+ZlFZlv0cTqV1lBPrfnz7+SW8/ZKmvEQMEwfZx0aJuq1hMAYflpaWpPpBLVOKo8mKJVqT3fzFyTSjo6OIRCJSQ0l5efmehpLdST2lKaKIAEwORVGwWq2wWq3S1JrEaUWxptSx54TP59PcfYcIQA2ghrdfNii5sMbapGRbM1csARiNRjE5OZmxSUVLiGOwDhw4IKWnUmHUMdAzNMoMhf9cVVYD3nlZs6rveW4lCGNFCI1Oec0CFWV6WAwMyi3yU4yzWwFs+CLobXUqXl9slIhl+9HY2IhAIBA3lUBMG6rZZRphefzDf0/jNUdrcag++xuJFh4uZ7YCePTFZXzomsx1gVqJWiZOpuF5XrIXWVhYkPzmxAklpSyiSnnthYSm6bgmo9hzYnFxET/5yU+wvLyMa6+9VlETyLve9S488cQTqKmpweDgIADgU5/6FL72ta9J94PPfOYzuPXWWwEAn/3sZ/H1r38dDMPgS1/6Em666SZZ29H+nfACRk1vP6WItVZyLqyi2bDRaMypZq4YApDn+biUrxZuJOnIZgSdxcDgvmsy24aUAhwP/G4+iAn/Iv7yxk5Zf1NZZsD/uEFZreF3XlhGmOVxusUBOodzQowSVVZWShGBnZ0dLK5tSqJArS5TAUAgwmN83Z+1AMynmFrZDqHaZpQ1EWTBFUQgwiHK8QBKQwAmIloJxTaUeDwebG1tYWpqCoIggGEYbG9v59VeJB+UsgAsZuo98Zzo7OzEk08+iaeeegpPPfUUXnrpJdx666247rrrcPnll6e8vr/jHe/Afffdh7e//e1xP//IRz6Cj3/843E/Gx4exne/+10MDQ1heXkZ119/PcbHx2Vda4gALBKCIGB7exsrKytob28v+AkrTgPJ9CX3eDwYGhrCvn37FE/GSKTQAnBlZQUejweHDh3Kq1GyWoh+hAaDAfuPnMCXf7OAP726HdYcLVAKwZInhB+cW8F7r8it9k+vo3HnETuOHlTe4aqED13ThkCEy0n8JYOmaQQoE36/occ1+w9iX6VpT5epaDeTyWIiGOXibGWMOhqffnXx6gfT4Q5E8ejZFRyut+L6rsyzk6/aX4mr9ssriFdDAIaiHLwhFtW2/BlBJ5YKrKysYGNjI85qSBQHZWVlmhS1IqUsALU0xcRut+P222/H7bffjre+9a349Kc/jYWFBfz4xz/G/fffD5vNhmuvvRaf+MQn4gTbVVddhdnZWVnbePzxx3HXXXfBaDSivb0dnZ2deO6553DZZZdl/Fvt31kuQMSonzjcvhgXgkxiTJwvu7a2hpMnT6pSvFooAcjzPEZHRxEOh1FdXa25wttkiM0pYm1l/+I2XIEIVndC6DRpyzogGePrPqx5I/CFWRh12df/jW8EMboeRt+R/F7ArUYdrMb8XP4qywzorLKgwWHa02UaCoXgdrsxPz8Pn8+HsrIySRDGNhUseoJ4YmAdN3ZXq1rXmK9oWrlFj2sOVKKjUv3vmhq1dP/w3zMIRDl88tYDeZtZnIhOp4PNZkN7e3tcQ8ns7GxcN2nisdcCWhJRStGqh6Hf70dDQwNOnjyJ1772tQB23R3++Mc/yl7vV77yFXzrW99CT08P/v7v/x7l5eVYWlrCpZdeKr2mqakJS0tLst6PCMACkpjy1ev1BbdFEUk3DzgSiWBgYABlZWXo6+tT7UJQCAEoeuXV19eju7sbIyMjmpw+Ekuy5pSjjXb8dV039Ix2owSxXL2/Eq/qqIAhQ/TPE4jCmaZW7/yKHzsBVu3lZYUgCNgOsmnXmwyjjsaZFFEwk8kUN7bM7/fD5XJJs7MdDgcqKipgt9hQ7zCi2pq9mC40x2WMosuGRNHqD7P4u19NQ8fszjSWM4LwnksasbIdViT+vv3cEirK9LjlcE1W646NoqVqKHG73dKxz1ftaK5rLzVip4BoCb/fv6cJpKamRhKDmfjABz6ABx98EBRF4cEHH8THPvYx/Mu//EvSxi65D3lEABaIZN5+xZqMAaQWY2Lzwf79+1FTk92FT+k21WJtbQ2Tk5NxXnmFHM8mIjfKIkYqI5HInuYUiqJg0JWG+AMAmqLACzwe71/FmYNVSaNrz8958Ni5Vbz78mbsS+GBd8exKmy5XJpIj/1m0oWfD2/gA1e1orlc/e7e2I7ClpYWqYDc5XLBMz+PJgAbywGwL9cPqnFD1mo9XToSa7o8QRbBKAeGRcYHJF4QsOmLoMlpRpNT2TGc2PCD3qRUEYCJxDaUiMdenFCyuLiY1nuyEGg1iiYHrYrXUCiU0yzq2tpa6b/f85734NWvfjWA3YjfwsKC9LvFxUXZDh1EAOaZdN5+xTBGFkmMAAqCgOnpaWxubspuPlBKvgQgz/MYHx9HIBDY45VX6LpDuc01wWAQ/f39qK2tRXd3d8bXByLcnm5JQRAwuurFgRoraBXSWqnWsLoThlFHZ+yy3fRHsLwdwsp2GPtr9l5a9leX4XiTPW13L0VRqtflZcvhehtWd8Kos+evbiyWxAJycWapaAIujqiqqKhAWVkZfjvlwtPjW/jLGztl110WUwD+9/gmfjfpwv03dmaMFMeSuOYGhxEPv64LQOZIxy9HNnB2YQfveVULqhRGUz95635Fr09Eyb6maRpOp1N6cE30nhQnmKg1uzoTWhVRctBqBBDIzdt3ZWVFqmV/7LHHcOTIEQDAa1/7Wtx999346Ec/iuXlZUxMTKCvr0/WexIBmEcyefslm1JRKGKFUTgcxsDAAOx2O3p7e/P2xc+HGBOFVE1NDQ4ePJh0HxdSAMo5ppubmxgbG8OhQ4ekm306+he38fPhdby1rznOJ3B2h8djv5vDm0434NL27Ga0ZkIQBHzl17PQMxQ+mcHAuNFhwr2XNO/xBBRxWvS483TmJ1OteNVVWQ2y1psvEmeWJtaQDbl08PoZcNEIoNNWDVkyPIEoOAHQySxr2A5G8d0Xl3GmzRT3vVYiYC9pK4fVqENlmfKUaq5CORcRldhQIs6uXllZwdjY2J6HAbVFPRGA6qL0mvaWt7wFTz/9NDY3N9HU1IRPf/rTePrpp3Hu3DlQFIW2tjb84z/+IwDg8OHDePOb34xDhw5Bp9Phq1/9quzPTwRgniiWt59cRGG0tbWF0dFRHDx4ULrY5HubarGxsYHx8fG0QqoYEcBU6RNBEDA1NQW3242enh7Z6YCmcjManaY9N7FmG42Ogw043uiQvb6nxjbw9PgmHrqtK258WyooisI9fY1x3ajpXpvreDKtfU+0hDiiqqGhAYIg4NDLBrRjoyNgWVaqH3Q6nSm9LosZAXzDiXq84UT6bnxBEDCw7MWRBht8YQ7hKA9viIUjywi306LHq/bl5+EI2F3v0IoP3XXWPd8nNfd17OxqYO/DgNhMpHQ8WSpKWQBqde1KdMB3vvOdPT9797vfnfL1DzzwAB544AHFayICUGViU76F9vZTAk3TWFhYQDQaxenTpwvShaZWzSPP85iYmIDX6007Hg0ofJQ1Vc1hJBJBf38/7HY7GjqP4Cu/WcAHr2mHSYawqigz4O6+vWbLOprCpe3lim4yf5h2IczyUHI/PVir/S5kLZA4EzmfJJoSi44CoiigKEqKENntds1ehxLpX/bi359fwh2n6tHT4sSfXduOjY0N+HyRYi8tKePrfvzrc4t47dHaPUIzn0Ik8WFAbCaKNSMXywnSXR9TUYq1oiJajABqtRGRCEAVEQQBkUgkrtFDi4RCIaysrMDhcKCnp6dg61Sj5jEUCqG/vx+VlZVpx6OJJM4CVptQlAMFwPiykEsWcdze3sbg4KDUWPP0+CaWt4NwB6Kod8i7UPG8AF4QoGNeuaEoMfMWeeCWg7JfqwabvggsBkZ2ZLAYTTtyWfeG4TDr4+rtxLU+ObaJeVcQb+1tVFTfphYMw0h2MsBu/aDb7cbyygoe/d0IDteZ0VJbCZZl8zIJZ2YrAHcgilPNDkQ5Hv/2/BKu7qxUbGFzqM6KO07V42jDKx3FWhYjHVUW3HGqHoeTGHMXKhKVrJloZ2cHbrcbS0tL4HleGlmXLjqc7H1LES1a2ASDQU3akREBqBJi1E+rKV8RMW1aVVUFp9NZ0HXmui2xdq6rqwuVlfJMZPOZAvaHWfz1T8Yws+XHX91yEMeaHHECJnZ8XqyX4lWdlbi0vVxW9E/kwR+NQADwmdcfkn6mpljiOA7Dw8MIBAKyjYozIQgC/v7JaRh1ND51m3ID450QiycG1vCao7WwFdkMO8rx+Psnp1FmYPBQQi0kRVFoKTdjdSecF/EX5Xj8dtKFU80O2ZY0er0eNTU14E0OTI5OwymUoY2msbm5iXA4DK/XK6UMk5UiKBVdj/xxEWGWx8mmXeEWCHOYWPcpFoB6hkZPizOntWRD8OUHOSXfSSD5ekWKJVxjG0ra29vBcRw8Ho8UHRZ/ny46rNWHMDlosYNZTNNrDSIAcyTXcW5ihKoQXV3j4+Pw+Xzo7e3F6uqqZsPSiQiCgMnJSXg8HkW1c0B+BaDFwKDWbkCI5VD5coehmHJmWRbDw8OgaXrP+DyapmCilV2gDtRaEWLjo6dqCcBAIIDz58+joaEBLS0t8Hg8klGx1WqVBKFSCwOKovCGE3WoLJOfgoq9YW4Ho/BHOOyE2KILQD1D49VHalMKmv01Zdhfk58LvC/MYXIjgHKLHict8us9AaDWZsD7r2xFg8MoiRtBEGC32+MG2IuWI+Xl5ZhxhfCNZxbw59e2y56c8ZHr2uGP7Da76RkKH7y6TenHTEkhhNRXfz0LUBQ+fka9kYpaqUVjGAaVlZXSQ3MkEoHH48Hq6irGx8elhpLy8vKcH/q0AMdxmpv3TgTgBUgybz+lyB3JlguBQAADAwOorq6W0qYMw0jWNFomHA6jv78fTqczq3R1Ling//ebGXgCUfzlTfuTbpeiKHz0+v17fubz+XB+ZBIVNfU43a3OSLN7L2tJuv1cBaAYET5y5AisViui0WicUbHv5UaDWKEgNhrIecrubXUqXpP4mZrLzXjPq/Z+7mJxZWf+mgkS8YdZfO6XU7jzVD0ON9jx1t4GxdEpYPcciRWtopiKHWAfGyGamZnBkh/w+yhs73hRWaaXdW1ymPVwmPNjXlwIAXjmYJXq9ZtaTV0bDAbU1NRIPq9iQ0nsdJpoNIpgMJgXO7B8o8UIoLhftQYRgFmQ6O2XS8pXFID5cn5fXV3F1NTUnk7ZQnfHZoPL5cLIyEhOHcq5fE6WEwBKWeo6FAphbGwMZ/2VwHwUp7rydxPIRQDGdiSLjTSJ9ZnJGg1ivcl0Oh1MVid+vcThlqMNaM3DGLALBX+YhZ6hZaeIBQARjse6L4rDAMpkjq3LNGkF2Hs+J0aIjkciuNTlgtu9gReWpmEymaQosNlsVv18DrM8zi/uoLfVAQHA986u4GiDDYderqsrhJA62awsspqKCMvjpcVt9LU6NRMBzESyhpJz585hYmICoVAINptNaijKpqGk0GixCUQc/ac1iABUSGLKN9cLUz7NkUdHRxEKhZJ2yqYbBVdsRFPqra2tnDuUs92/giDApKfRUS3vxsDzPMbGxhAMBnH06FEcNFjhC7NZnx+CIGBmK4D2SkvK90jscP7NxCbOLWzjvms60hpDR6NR9Pf3w2q14vTp07JvUolCIRwOY2F1Ax7PJs6e24Cvzp51ulhEy00g2SIIAv76pxPQMzT+12vkNeFYjTo8/LpuRdt5btaD/3hxGe+9oiVl57YcMWUwGFBXV4e6ujpphq3L5cLk5KQkCMT6QTUEwW8mt/CzoQ1UWQ1oqzRjwxfBMzPuggpAtfjDtBs/HliD06zfM8GkFKAoCmVlZTAajTh27Bh4nofX64XL5cLg4CA4joubUKK1VCugzQggEYAXAGqkfBPJhxDz+/0YGBiQ5uEmW6dWI4DiHGKr1Yqenp6cn6CztYGhKAqjaz5Mbvhx65HatK8NhUI4f/48ampqUFVVtSuUbEbUyKyfSsbEuh8/6l/BrUdqcag++YzVRLH008E1RDge6U5Lr9eLgYEBdHR0oK6ubs/7KcFoNKKztQn3tzbJShf7wyx2QizqHepaDkVYPi/NFxwvYM4VxIYvjIl1P+7qaVQ0S1aEoihcf7AKTnN+L7f7a8pwrNGm6ti62Bm2TU1NcYJA7DDNdWTZqzoqUGszoq3SDJqi8MGrWuN+LwhCSUTSAOCSdicqyvTorC7D2FbprDuW2MglTdNwOBxwOBxSQ4k4rjDWbqhcxXGFuaLFLmBSA1jC5NPbT20BuLKygpmZGRw+fBgOR+roVTEFYKon+nzMIc6lBvDztx/O+BrRSLu7uxsVFRUYHh5WJYLVVmnBjYdq0Fmd+qkx8bN95vWHIAiphdzy8jJmZ2dx7Ngx1Z9G5aSLvzXKQ2D0+Ls3HoGeSf4dUhoBXNsJ44nBNVx7oEpxx2kmfjGygV+MbuKKjnIIAiBzgEVSbuiuVm9hKSi36HHvpXv9ImPJNZqWKAhiR5aNTkzBYtTHjSyTsy2LgcGxxlcechL/ppQigGb9K5+lVFLAiaRbdyq7IXFcocFgkI5/sRpKtJgCFhvqtAYRgBnIt7efWgKQ4ziMjOxOBOjr68sYmi9WCjiZd50gCJidncX6+rrqc4hzEbrp0qiCIGBmZgabm5txaWq1hLVBR+NYhgkfiWJp9/zc+zoxPR0KhWSdG2qQLF18T9kaplZcOPvC8zl1F8diM+lgMykb9bXpi8CspzPW1b1qXwXMegZXdlYUzOA5W4JRDjtBFrUFmlssIo4s24EF51cMuLndCZMQxOLiIrxeLywWS1z9YDaUqpAqJeEai5L9LdoNiQ/soVAorqFEPP7ihJJC7A8tni+BQIAIwFKjEOPc1JiO4fP5MDAwgKamJjQ1NclaZ7EigOJ2xS9oNBrFwMAAzGZzXuYQp0sBr3vDWaVpxTVbLJY9aepC1rDJ2ZZonF1dXY2urq6i3ZCMRiNOHWjBqQMtUrpYjPjGpouVPrlbDAzefEr+vF5BEPDEwBoMehp39zSmfB0VcKFy9HHcvPgMhEkjuP23gm2/DtDFny/+CI+H/msK735Va1Enpjx2bhWBCId7L21KGV0Fdq9pn//1KrqbIqp2WFeW6VFl1aOu3AqLwSHVDwYCgT0TKkRBILfx7WIQUloil3WbTKY4F4FAIAC32x1XPyqmjHN58EuHFiOAfr9ftayWmhABmIRcvf2UkMt0DEEQsLS0hPn5eRw9ehQ22143+lQUKwIYKzzFCRn79u3bU4+mFqlSwIPLO/ju84u4s6cJRxuT19glY2dnR1qzOJczlkRhLQgCBpZ2cKjeFjfFQw0yCUBRYCkxzi4EsenilpaWOBuSra0tRCIRzM7OorKyUvU0EkVRONNVBbOeTiks6PUhmH5yH8AGAVoHCDyY5RegP/cIgq/5f4DJKb2WFQCWF+AJFtdS6bYjNdjyR9OKPxFe2J3coSYOs36PEBcbCsrKytDc3CxNqHC5XFhYWIAgCHH1Y+JNe3k7BE8gqpkmkJXtEGiKShldjXI8np314PKOctAJmY2LWbjGHn+xfjSxTlicUFJeXq5aZkKrNYBkEkgJUOhxbtkKMdFomKKorNJ6xYwAchyHubk5rKysxE3IyNf2kn3OjqoyXH2gCvuqXynM/cnAKua2AvjA1e1Jj/vi4iIWFhZw/PjxlAW9iaJsejOAnw6ugReAEypZTaTaloggCPjvl8bx3RdW8IW39MJhy634OMrxsoRFtsSmiz2UHd/6zRQ+3MAgsLAAr9cLq9Uq1RWpMbO6udyM+x8fBQQBD78+odOWi8D0s48AfBQwxjwYCAJo9yyMv/scwtd/Vvqxw0jjs6/Zn7dohlyU+PB94rqGokQjYidUALvXMLfbjc3NTUxNTUGv360f/PLzO+ApBl94QzfoLMYdqs2/PbcEik5tEv3srAePnl2Bw6SLe5i8GCOA6aBpeo//pDi/em5uDhRFxU0oyTaKp8WmIb/fryhAUyiIAIyBZVlVvP2UkI0AFKNQra2taGxMncZKRzGbQIaHh2EymdDb25v3UH2qz2kxMLihO/4m+NTYJlh+781GHJMmCMKeqR6JJIqytkoL3nCqAa0V6ovcZAKQ4zgMDQ3hxbkgDLZy6Ay5CZMFdxA/HVrHq4/WokHl7t1kUBRAUxTqamtRZW2OG3Q/OjqKaDQaN7WCYRgEIhxcgQianJlrzARBwJNjm9gJRpMKJmbhD0DEDxgSRDNFQTBaoZv9NcJBN2Aul96vlBDFlCcQhY6hYJXhL8gLAp4e38Kheivq7OqdAzqdDtXV1aiu3m2QEevHXt8OrHu2MTw0hIqKCqn5rli8pbcBTJrt97Y6YTfp0J0wD7jYwjVbCiVckzWUeDwebGxsYHJyEjqdTioXkNtQJKK1/U5sYDSM2t5+SmAYBuFwWNZrY2fL5trJWYwU8M7ODjweDzo6OtDers6EjEwosYH5uzceRuJL/X4/+vv7ZddXJgpOhqawvya3L74vzOKbf5jDFZ2VONHslH6eKADFkW7Nzc34i6ONEIT0jSxysJt0MBsY2DIIBY4X4I9wsOc4sq2rtgx/1mtD1cuj9RIH3SfaUDAMg28Mc+BoHb74pqMwZpiWQVEUlrfDuLKzEm/p2Vs7SG8vgOIiEJAkakrREGgdaO8KeHP53t+XED84vwqGonDvpU0ZX8tyAsbX/QhGOdx2JH8PAYn1Y7NrbjwzvY5aYQsul0sSC06nM2/G+cnI9GBh1NFxXcwiJAKoDL1eH/dAEA6H4XK54hqKxAc/iyW1P6oWITYwGoXneSwtLcFqtRasSykWuU0g0WgUQ0ND0Ov1GaNQcihkBFAQBCwuLmJxcTHuia8QKLGBSeyiXVtbw+TkJI4cOZLWUifxPdSOChkYGgxN7RkFFrut2JFu4lrVOJUdZj3u6cssEv7qx2MIRDh8/vZuGPPgySeSGDUIh8N4m3kVkytunDv7AsrKyqTfp0oXv62vEal2jWByAkz8ZfHXwQ5Ms5W4p+x56Hl29zUlihiVuqGrSnZa36Cj8fZLmvLitZgKiqLQvx7BUtiIg3XVqK+pBE3TcLlcmJ+fBwDYHU5UVVbk3X+O44WsusBJBDA3jEZj0oaS6elpBAKBuAklxS7ByARJAWuMWG+/zc1N6HS6ohRpymkCEZslOjo6UF9fr8p2C3VhEmsVaZpGX18fxsbGCpp6zkbo8jyPiYkJ+Hy+pFNU1N5eJgw6Gh+4em/9kShuJycn4fF4FK81GRRFYXUnhKfGt3DHqQbZxsf3XtKIF+a3FYm/305uQcfQuKz9lWiaUgG9HQEG3TRedagTB2rK9qSLHQ6HlEYSH5roNOc+23Y1jL/7HMBFAWY3ymSiWNAQoIt6wVV34RfLevzyyRH87WvlTfXQErFzloFdS5zP/3IKH762HY3O1NE9i6HwXZW3Hq5BIMJhbWEGDMNIqX8A8PhC+MTjI9jn2MaVNSyMRqMkBsrKylS7vj0768Z3XljG/TfuUzX9rWW0IgBjSWwoEQQBXq83zklA7DDXYlkGSQFrCEEQEI1GwXEcKIqCTqcr2li0dKlYQRAwNzeH1dXVvDdL5ANx6kRsrWKhaw+Vbi8cDuP8+fOorKzEqVOnFN9ICmkDw/M8xsfHUVlZidOnT8tea4TlseYNp5wY8dTYFn4/7cYNXdVSKjYTXXU2dNUpe8J97PwaKCBOACql3KJHg8OIOrsxY7qYpmkpOpiypshoR/hVfwHjbx+GwIYAQxkuMUzjUgxA0FkQufIBTA4FEOWEtEKy0HhDLPwRDnUyfAApisLTE1uoLjPAbGAQ4Xh4AtG0ArAY6BkaDjON1SSRNHuZEVaLCVccqUNfWzmCwSDcbjdmZ2elm22iz6QgCHhpcQddtVbZgrbCYoCBoWExKL9VlmL0D9CmjUoiFEVJDSWi8bzYYR4MBvHCCy8k7TAvFiQCqBGSefsVcy5uqm1HIhEMDg7CbDajr69Pc09kmVhaWsLc3NweexotC0CXy4WRkREcPHgQL23wePoP83jX5S2Ki48LcS7t7OxgbW0Nzc3N2L9/P/7P09N4cmwDX7nreMZRa0+OrmNyI4B3XtYCa5KavTeerMeZrirZ4i9bPnnr/pxFlJ6hcfOh5B2tieniSCQSV1OUKl3Mdr0Ogq0B+rP/Amb1HARGD/bAqxE5+Q4IjmZ84KqclpwXfjywhhDL4x2XNqXdp+J1b2bTjwV3EPf0NeF/vynzxBs1WfKEUGs3yo4uJ0ul0hSFz9/+Sge32WyG2WxGQ0ND0rGEDocDnMGGf/7jBi5tr8DbL8lc1gDsjteL3Y4aPD/nQb3DKKtpqRhoMQKYCYZhpGaR7e1tHDt2LK7DXKfTKZ5QoyaRSESVudlqc9EIwHTefgzDgGXZoqwrmQAUw9qdnZ1Jvea0jDiRhOO4pPY0hRaAFEWBy7C92Ekk4lSPn/x3P1heAKDMLDfb2cNKEEe61dbWSpYavjCLQITDxLovowC8srMKHdWhpOIP2E055zLHWC7JunDzGUE1GAyoq6uTTIpTpYudTifQ2AuusTcv68gHtx2pgTfMyhbU91zShGIMN9n0RfC3P5vEiSYb3ntFa+Y/gPJaumRjCcVI8BWVQTQJq5iejkh2I4UUOywv4Ef9azDrGXzi5s6CbVcJpSgARXieB8MwezrMw+Ew3G43lpaW4PV6YTKZJEFYqIYSLUaELwoBmMnbr5gp4FhBJAgCpqensbm5qfpItEIgZyJJoQXgU2Ob+N5IFCdOs0kFTzQaxeDgoGRLI174/u6NR9LO1U1FrIAJRbk9jRu5wPM8RkdHEYlE0NfXh5mZGWlbf3Hjfnz4un0ZC/t9YRZlRibl1IpkN9swy+e1sSMdgiAgEOEyjm1Tiirp4hhCUQ7eEIvqAgjnZMj1ARSPr9zoW6b3euTZJbRVmHHNAXlG45Vletx2pAa9rfI9MUNRHl98ehHvuqItZdlCOmIjwZ2dndL82tXVVYyPjysSA94QC5uCTndviMW8O4jDL1vE6GgK77+yNedu+XzC83xBxkXmg1Qm0EajMe7hTywZEBtKxJKB8vJyVbxGY9FyM1BpHmUFiFG/dOPcGIZBJBIpwupeiQCGw2EMDAzAZrPlZSRaKtQ6OVdWVjAzM4MjR47Abk89WaPQArDSagBDASb93v0p1ii2t7fvaa7J1vhYjAAOLO3g58NreFtfM+pU8M8LhUI4f/48ampq0N3dLUWxRQFIUVRGCxRfiMXH/nMAjQ4z2qssuLNnb2dn4rmwthPGjwbWcM3+SuyvKYyNQWwE8FvPLuK5uW38r9ccRLklf9Yf2aaLRX40sI5ghMPdvQ15Nc0uBlGOx89HNnBpW/mesoCzCx70L+3IFoAUReG2I8pMqLfDHJZ3ohhe9WUlABNJnF+brLtUFAOx3aXPz3nwy9FN3HtJk+x6yR+eX8XkRgAfv94sCcdUf7u2E4aOoVBZVtxUYSlHAOXUL1IUBYvFAovFgsbGxriSAfEBO3ZCiRqWQ1oVgResAFQyzq3YNYChUAgvvPACDhw4IIWsC4EoxnIpkOU4TkqhyZlIUmgBeLzJgbu7DXvGsIk1irn4KbIcj50Qi4qYC7bYmVvvMMJh0sOpgmiZX9nA5MQYjh/ujhvppjRdWmZk0FRuRletDRveMCIsHycAk12g7GYdHGYdqvNcD5hsDZ5AFJv+KCwGpuARk3Tp4kgkIk0sCEZ53P+jCdzV24gamzEv4s8diOIng+u4+ZD8ppxUCIKAgZUAHn9qBZ95bZesyG4oymPZE8LMViBu+xRF4e9uP5T3VHKlicJnX70PDlt+uigTxYDX642rHxS7j9sqrDhQU4Yam/xj8PrjdVjeDsmKGn756RkwNI1Pv/pALh8nZ0pZAGaz9sSSAZ7npQkl4shC8RxwOp2K75daHE0nckEKQJ7nEY1GZY9zK5YAFAQBMzMzCAaDuPLKK1UPPWdC/NzZCsBAIID+/n7U19ejpUVes0Qus4/VQBSsLMtmNUIvlo99fxCBKIev3nVcElKiKKuyGvGeK9tyWqtYm/g//2sW5U4nrrsqPsqixONQfP2Dt3ZBEATZJtFmPbNnxms+iT2HjHoajQ4T7ulrzMqHTc01pUoXe3a8WHMx6J8UcGdfa16e9DleAEXt/lsNBlb9CEY42Q8PNpMO917aDD2z93MVojRAEARYjPq4c+C3Uy6MrHjx7stbVD03YrtLxXFl4pxqt3sGHQyDxfmQVBqQ6sYu7lubSYeDJnnC9Z4Cey2mopQFoBodzDRNS9E/YDeL6PF44HK5MD09LTWcZDoHRAKBgCZNoIELTADGevsBkH0SF0MAhkIh9Pf3S3UnhRZ/QG7RuGxMksVtisen0GQjWNPxwWs68NKCJ+6inWmf/nxoDSY9g6sPVKV9b5ZlMTQ0BJ1Oh3de0w2nZW/UIduGiUTD61wJszwMjHoTdMTPZNYzuCvJtI5iE5su9vv9+Ke+ffD5fLLTxUqpshrw1t7sRj4mIggC3na6TtZ31uWPoNyi3y0vKKIwSSaq13bCewyaBUGAOxCNi8jnSuycauCV0oDl5WWpmUA81rGDBLIRUanqcgtNKQvAfKxdp9OhqqoKVVW71+xk54AoGJN5UGp1CghwAQnARG8/JTejQncBi1Mburq6UFlZifX19YJtOxa5U0hi4XkeY2NjCAaD6OvrU1wfUawZxOI+P3ToEAa3eJh9kZw7XQ/UWnEg4aKdSZT98PwKKFBpBaA4fq65uRlNTU1IZdJRSM/BVEQ5Ht9+fgk2ow53nFLHpLyUEAQhZbp4bGwM4XBYShc7nc6iF9fLjVAueoL46/+axA1dlbijgBHgZCRb85tO7j3X/vF383hpYQeffd1BVUVgLInHOhgMwuVyYXJyEqFQSKofLIbViFqUsgAshIdh7DkAQDoHYj0onU4nAoEA9u/fr1gAvutd78ITTzyBmpoaDA4OAti1KLvzzjsxOzuLtrY2PProo1KE8rOf/Sy+/vWvg2EYfOlLX8JNN90ke1sXhABM5u2nhEJ1AYsTJrxeL3p6eoo+vkZpOjYYDKK/vx81NTXo6urK6gJXaAEoCAJCoRDm5ubQ29uLCE/jG3/oR2uFBZ98dZfq28tkA/P5NxxJG31bX1/HxMSErMhqrAB89IVFeIIs/uRVrXGpXZ4XIACy02RKU5h6hkZzuQldKkUvMm07yvGabrJITBfzPA+Px4Pl9U28NDqNSsuuH1llZWVeRILLH4GeoRV1qiajzm7CyWY7XrWvcGMbUyH3nLzlcA1oCnltFooltpmgqakJPM9L9YMLCwvw+/2YnJzMunasWBABqAyz2YzGxsa4hpLZ2Vl87GMfw8bGBg4ePIhIJILNzU0pipiOd7zjHbjvvvvw9re/XfrZww8/jDNnzuD+++/Hww8/jIcffhif+9znMDw8jO9+97sYGhrC8vIyrr/+eoyPj8veB6V5lF9GbPQIh8MAdm++2VxQC5ECDgaDeP7556HX63H69Omiiz9AmRhbX1/H2bNnceDAAbS3t2d941IadUwnpgIRDh/493P4zfhm0t9HIhG8+OKLAIBTp07BYDDAatLh4zd04s/P7JO9hrWdEN7/7XOY2wpkfG2mujybSQdrEksTQRAwMTGB+fl59Pb2ykrRxQpAh8UAht5b13ffd8/jT79zPuN7xb6nUm7oqlalO1Mk1THf8IbxoUeH8MTgmmrbyjeinczXBqL4zwUzug8dhtlsxuLiIp577jkMDg5iaWkJwWBQle391RNj+MSPRlP+Xq6Y0tEUPnBlKxpU6GDPFblrbq0w471XtKouqiOsvOsVTdNwOBxob29HS2c3frlqhN5ig8vlwtmzZ/HSSy9hdnYWOzs7RY/cp6OUBWCx1y42lBw9ehS/+MUv8Mwzz+Dqq6/Gzs4O3vjGN+KSSy7BX/zFX+BnP/sZ/H5/0ve46qqrJDcCkccffxz33nsvAODee+/FD3/4Q+nnd911F4xGI9rb29HZ2YnnnntO9npLNgKYydtPCfkWgGK93KFDh6SwbSLFaBOX87lzmYubDCVRR0EQ8D9/OAyLgcFDt+2N1jEUwHICVnfCe34nmmkfOHAAk5OTcb87VJ/apiYZ3hALjhewHcxcu5iNEXQkEpEsgJSMdIsVmzelmIZxqMEOt784FkdqYzPpYNDRaK/Q9kjEKMdjfN2PrlqrFHn90DVtmHcFYTYZYY5JIQYCAbhcLoyPj0vpYrGe6DdTHqxsh3F3b4Psc+KeviaUFWFubyDCwRWI5GW6RTEtNDZ9EXzjmQVce7ASPS1O2X+35AnCGwVYvRX79++a+YtmxGKtqMViiasf1Aq5OkMUE47jNDVxw2QyYd++fbj66qvx+c9/Hj6fD7/97W/xq1/9Cg899BA++clP4rbbbsv4Pmtra5JVWX19vVQ2trS0hEsvvVR6XVNTE5aWlmSvryQFYK4p30TylZaMrZdLJ57ESE6hL3KZPrfYqJLtXNxsthkLRVGgKSoupRNrXWLUM/jaPSfj/kacn/zixDJ0lc24vKoK09PTOT1xd9ZY92wn3ZqVnEs7OzsYHBxEZ2en5EsmFzk1gPdd06HoPYtNus9k0jP40h2FHVv2uykX6u1G7KuWX8Mz7wri+TkP7CadFBntrC5DZ8J7xA64b25uluwnXC4XJqdn8f/OhmExGnDbgTI4HA5Z379Mc5XzdZ358cAatoMs3nlZk+op+mzXHGF5fPOPC7h6f2XWDRZ2kw5mA4NGhZHQ/VUmvPOYFR1VrzysJJoRJ4p/u90u+Q/G1lY/8sdFGHQU3tKjTiNQJrRsW5IJLc4xFusCAcBqteKWW27BLbfcAiB9hksOyf5eyXelpASgEm8/JeTjguj3+zEwMIC6urqM9XJiJK7QX7p06djNzU2MjY1JjSpqoVRsf+b1h6T/fmHOjUdfXMafXduBpiQpR5ZlMTg4CL1ej3GuEqElP1594hVRlo8Lwx+nXfjDtAvvv6odFgOjqDFjaWkJ8/PzOH78eFZdYlpoAlGbqc0AfjEbwcHDHCxFiGTFwvECvvXsIow6Gl9+8xHZf9daaYHFwChuMoq1n3DpKnHmsBuXN+qxsrKCsbExVSJGmc6XbKe+3Hq4Bq5ANC/1mdmLVgG+MIclTyijAEzsKBYx6Gjcd3VbFtve/dtU604m/nd2dqT6QUEQpHNhbM1b0OBAsdOouaDFtadrApF7XGtra7GysoL6+nqsrKxIwYKmpiYsLCxIr1tcXERDg/ymrZIRgEq9/YrJysoKpqenZVukiAJQDcdxJSRLxwqCgMnJSXg8nrw0qqQTgC5/BAvuII43OTC7FYDDrEN5jP1Jnd0Ei4FJaq7s8/nQ39+PtrY2NDQ0oPMAhzDLg6GpvDaeWAwMGIqCnqEwuupFrSWzKIsd6dbb25t1Z+iFKAD1DA0agiqjymIRBAH3PTqEWpsBD90qz2iXoSl84qZOWSPWRCIsjz///hCu3l+JO09n3z17tMGGOrtRiiAmixiJs4vLy8sVnUOprp1Pjm3iuy8s46Fb9yuu6bSZdDk3nqQjcc2Pnl2BNxTFuy9PPav7Yz8YQYQT8OfXtad979FVH346vI57+ppyNtoWUSpEaJqG0+mUZnuzLAu3243NzU3c3uCDXq/H3NwcKioqYLVa83r/E++xpYhWI4A2my2n93jta1+LRx55BPfffz8eeeQRvO51r5N+fvfdd+OjH/0olpeXMTExgb6+PtnvWxICkOM4aVSblsUfx3EYGRmRTIblCrpiGVEnCsBwOIz+/n44nU709PTkZT+nE2Nf/fU01nfC+Ozth/GpJ0Zh1FH4x7e+knptKjfjU0k6d8UxdEePHpW+aEY9I41Gy6cAPNbkwLEmBza8YXzmp+M4Ul+GM9Xp0+rnz59HbW2tNNItW7IRgPksNeAFAf/x4jKanGZc2Zld92hrhRlnWg1x3opqrFn8+3WfsnrItkpl9YZ6hoIAYCvHukuTnokTYenSxXNzc1L0sKKiAna7PeX+SrcvWyvMMOnpoo8ik8NOMIpMZ/71B6vw/Pw26Aznjt2sg1FHJx0XmS25nrM6nQ7V1dXSZKhQKAS32435+Xn4fD7VvSZjEQRBc1E0uWgxfe33+/eMGk3HW97yFjz99NPY3NxEU1MTPv3pT+P+++/Hm9/8Znz9619HS0sLvve97wEADh8+jDe/+c04dOgQdDodvvrVryoSwCUhAIHCCL9cvrQ+nw8DAwNobGxEc3OzYh/CYnjjxW53a2sLo6OjOHjwoKxW9WxJJ8buu6YDS54QrEYd/vTq9oxP42IkLRwOp53qkU1jhlKqrAa8/bJmHKo2Y3lmLOlrXC4XRkZG0N3dvafLKxMRlgdFxc8oVvq5/u3ZBTw1toGv3HUc5jykV2mKgiAAOyH1PDX/x2Mj2Amx+L93Hcn5+//VO+WncbOFoij837uO5n07idMKIpEI3G43lpeXMTo6mlW6uLO6TFGqu5j8yatSR/5ErjlQiVlXEM/OunFJW+rayAaHCX96VVvOa4pyPB47t4qbDlWrnoo0mUyor69HfX19Uq9JMRrsdDoLnknSElpsYImtAZTDd77znaQ/f/LJJ5P+/IEHHsADDzyQ1dpKQgAWQvzlMhdXnCt75MgR2O3KOkyB4kYAI5EIpqamsLW1hdOnT+d9Ikk6AVhuMUgp3740F2zgFU9COZE0pY0Z2UBRFK7vqkE0GsViwrbExpS1tbWs9/E3n5kHALw3Zryc0gig8eWapFTjpoLBIObn5+FwOLL2Lbs7x4kViZ/JpKfhC+enTlcNtJKCNxgMqK2tRW1tbdp0sWiUXwp854UlVJYZkP5KkBqLgYHFwKDRWRgrm4l1P346vAGHRY+emuwsyeSQzGtSjAbPz+9eJ8SHA4fDobmIWD7RagQw23nz+aYkBGAhyGYuLsuyGB4eBoCc5soWaz6uIAhYWFhAbW0tenp6CvLFUSMdKzaopLPVUXubckkUMGJjisFgQG9vb9b7+ESTfU+RulJhe8fpRtxxOrlAEyPAjY2N2NrawtTUFAwGAyoqKlBZWQmLxVIU4fDXrz6Y8TVRjsfQig/HG4szfSGbbYaiHKY2AjjckFttUKr1pEoXb29vY3BwEFVVVbJnmRaLYITDUjSE8izvUnqGxntkRAqTEYhw+PPvD+G1x2rx6iO1sv6mq86KB27uREu5GTsel6z9uh2M4i8eG8E7Lm3C5R3ZlU0kRoOj0Sg8Ho9kKm80GqXygGSjyhIplQeEZFwIEcBCUhICsBAnpNIonNfrxcDAAFpbW9HYmFvUoxgRQLfbjampKTgcDhw8mPkmqxa5iDFBEDA1NYXB+U30nTiG8vLMN88ox+O/JgN4jSOEQ1lEZ9e9YTjNetlD2mM/nzjSraWlJedzpK99781BjSYQQRAwOzuL9fV1yYNQ/L6JI46mp6cRCARgt9tRWVm5x6ZCbZR+pp8MruOx86u4/8ZOdNcV50LrC7PwhljUy7QL+fofFvD8nAcPv74bdfb8msLHCgS/34/29nYEAgFplqnZbE6ZLi6mB9+7Xm7weP75Vdl/I547ua5Zz+yWMwQj8q9VNEVJVj9iCjjK8dDRqTNYYtmEku1kQq/Xx9UPBoNBuN3uuFFl4vHWwkACNdFqEwiZBaxxdDqdrHnAYtRsaWkJx44dU0XZF1IAxt7w9+/fj52dnYJsVyTVhdAbYmHW09ClsJEQzZLNljI8u23DwDNLeDCJOXQi4SiPJS+HgaUdHGpR5rMXYXl8/fezKDPo8GfXyZscIoqyqfllLM9P4/ixY1mVBSjZVrZwHIfBwUHodDr09vaCoiiEw2H8ftqNS9qccSOOxDFXW1tbku2AONIsXdNBKnhBwO8mXbh8X0Vcx2/i+8gZ/XbdwSrYjDrsryneRfbnwxsIRjm8padR1ti9u3oa0F1nRa2t8A0XBoMBNpstY7r4r365AgHAP77lqKLjO7S8gxcXdnDn6YasLGVy4QPfHZTWnAt6hsbX3nos678XhN0RjF/41TQMOhofO5Pcj9Nm0uW0HTmYzWaYzWY0NDRIo8pcLheGh4fBsmxc/WCxZ1XnilZtYHLtAs4XpX20VUSOCBPTeTqdDn19fao9aRRKAEaj0V0RZTajt7cX29vb8Hg8ed9uJjhewJ9+5xwMDI2vv/3Unt+Laav9+/ejpqYG76zwoaJMXgTKatLhXaecaKh1Jv19ugiHQUfjxkO1aEljibHoDuI/X1rCW/uaUWXdfZre8QfxucfG0VjtwJVX5Ef8AbkJwEAggPPnz6O5uRlNTU0AdvfF+SUv/ul38/CFOdx8qFp6vTjmSrQ1ikajcLlccU0HlZWVsrsSn5314J//sAABwNX7k/tM+sMsHju/isP1NpxsTm2nZDfpcKYrf41LcrjpUDW8IVb2zOXKMgOuOyhvzcvbITw9voXbjtQosqRJRuL5ki5dHA14EeJ2HxiVpIu5lzchd1+oTTZb5QUhY7ewovfjeegYBk4zVJuTrQbiqDKbzYbW1lZwHCcd79nZWekh0OPxwG63a05MyUFrKexAIEBSwLmghRTw9vY2hoaG0N7erqilW+62812jJoqozs5O1Nbu1rQUsjYuEUEQ8McZN4402GEz6fCqfZU41mjf8xox2nry5ElYLLuWHAcUXlAtBh2oJKYR//TbWbgDEXz8hv0pb1anM4x/EvBKGicSiaC/vx8GhsKV3Y24obs67d/mSrYCUKz3O3z4sOQ7JnK43or3X9mKE03phater5eaDla2Q3jwxyP4YE8I6+ujiEajcDqdUlQh2YPS6WYH3n9lK041x28n9jOZ9AxMegb1Du2nqazG5DOe1YChKOgYShWBkimlG5su/pd9++KEfqZ0scixRvue73Kh+H8yIn+CIODc4g6ON9lBUxR+MbKB0VUf3ntFC0x6dR7qxf38ARW6i8X3O7e4g2ONdkxtBvDdF5bxlzfuyznCyjCMdDyBXbuZc+fOYXV1FePj4zCZTFL9YLHqgEsdUgNYAqQSgGIH5+rqatYTGzJB0zSi0cxzZrNBEATMz89jZWUlTkQBxes+BoC1nTC+9cd5XNZRgbdf2oL3XxVv1spxHIaGhkDTdM7R1lR2Kc3lZnhD0bSRiqfGNtDgNKecJNBcbsaHrt2H7e1tPP/8bpRycnISH798P1z+SNzoOrWJFUtPjm7AF4ridSdSmw+L6f+NjY2UJt96hsblHcr6LhfcIUQ4CjpbFY52dYDjOHg8Hql+UKfTSdFBsQjdoMu8HYam8KaT6j5slSK1diPefCp7U+lciBX6appRF5MX5rfxpadn8Y5LmnCmqwr1diOmNgOqpqvVTkWeXdjB/35qBvf0NWInxGI7GAXLZTe1JR0Mw8BoNKKra7e8JhAIwO12S3XANptNOt5arB/USld+LNFoVFPziWMpjW8s8j/1IJkYikQiGBwchNlsRl9fX97C4fkSYtFoFIODgzAajejt7d0joooZAay1G/GBq9rRUbVXUIvNE7HpyVxI1S17y5Fa3JKmw08QBDw/54FxaSftKKnFxUUsLCzgxIkTKCsrw+TkJKIcj2/9cR5lBh3eE2PdIge5hfex34lv/XEevICUAlCs99Pr9VLHt1oF8xMbftx6pAZHX476MAyDyspKaYRgKBSSUkx+v1+aeVpRUZF1M4kvzMKsZ4qWZlQbX5iFSc+oPgElkVyaOlKli38/tgKbMAurgZbqQrPtLh5b8+HZWQ/e0tOwp/bz3OI22iosSScBKeFYox339DXi0nYnAOBoo106d9VC7eaZow023NPXiMs7ylFmYPCGE3WqpqxFEpsoLBYLLBYLGhsbIQgCvF5vXP2g0+mUIsZaa74gZKZkBGC+SRRhbrcbw8PDcSnTQm1bDXZ2djA4OJg2ZV3MCCBFUTjWtLeua3V1VRqjp1bzRLZCl6IofPDq9pRNCDzPS5NfEke66Rka1xyozsqD7N5vngVNA1944xEEIxyaK5JPo4gVgF+96zi4FA9Iyer9AODeR86CAvDIO04rXmMsxxpsaY2lTSYTGhoapCJ0cebp4uIiAMRNsJAjGlhewAf/YxAGHY2v3Z3fAnpgtxnIH+FQnqPwSAUvCLjvPwZzbjyQg5oP0TRNgzZZ8d3RCNor7Xjo5g7JjDo2XVxeXh6XeUiHOxBFlNs7iswXZvGFX82g0WnE517fndO6jToaN+a5PEPtCKAhYc35ekxIt26KomC322G329HW1iZF+t1uN2ZmZsAwjPRdLoa9UDE71lOhxTXFQgTgyzAMA5ZlIQgCZmZmsLGxgVOnTmU9dF3pttUSYoIgYHFxEYuLixlT1sWuAYz9YvA8j/HxcQQCAfT09KgaMs/lc5alqOuKHenW2toKYO9nOpGmcSEdFLVb//aj/lVEWR7vvbIt6UUkVgBaU8xhFT0Tk9X70RRAJdxKsrlYKYmeUBQlNZO0t7cjGo3C7XZjZWUFY2NjsFgsiEQiCAaDKb97OprC6RYHelocEAQB/ctetFdaYM/TLNqfDK7DH+FwV09DXiJ0NEXhkvZydNcWpotZzRuSw6zHh65pRWd1GfR6PWpqalBTUwNBECQbocnJSYRCITgcDpSXl8PmcOIvfjiO1xyrxU0JQuzS9nJc2v5KaYB0fht1+NA1rdiXJGOgRbTYjSoHJetOjPRHIpE99aKiIDSbzXkXQlrd51oWgSUjAPOdAtbpdPD7/XjxxRdhs9lyMu1VilpCjGVZDA0NgWEYWXVzxZxAEvulEMVUdXU1Wjs68c5/O4ejDXbcf/MBVban9rkjNlGIRtSCIOCeb7wIhqZyjqYBr0TkPIEowmzqyQ3pPpecer9v3pv7WnMlUTQEAgGcO3cOY2NjiEQiUjNJYorpz67ZrRkNRHYtfoIRLk44qMl1Byux5Y/mNT37gStb8/besYjfu3VvGD84t4p3Xdacc43qJW3l2PJHsOmLSOMbKYqS0odNTU3geV6K/M7OzWF5M4zv/jGASxsMaaNFsdeJdOPctIaWb/rpyEVEGQwG1NXVoa6uLukDQGz9YD5q4rToAciyrObWFEvJCMB8EwgEsLS0hKNHj0oGmoVCDSGWjTF1vkV1KsTJJzRNS2Kqq6sLlZWVEAQBDEWhtUK9yKtak1YSTZNFuxOKosDQFNpVjk7s1jqlTjumOn7J6v1KAbHGzGAw4MSJE5JFxdbWFmZmZqDT6aTJJGIzicXA4DVHa2FRMNv4sfOrcJr1uPZAcvuZRBxmfUr7Fa0Unf9seB0Okw6XyZwm8ftpN34z6cL1XVWSeXFu298ALwi4py95zS5N03A6nXA6nejo6MB/nIiP/JpMJqkuNDZdrKaQ8oXZvHVqJ1KIaFQ+Po9a6072ACDWDy4tLYHneal+MNuxk/lau5po2QQaIAJQmi6xvr4e555eSHIVgOIs4qNHjyoynCzWE6ooyBYWFrC5ublHTH3rnckjUzwv4BvPzON4kwM9rU5F20vVZS33BpNppJucyN+mL4x1bxiH6tWpbUwmAFPV+2VLMMpheMWH0y3ZpbNzIdGiIhwOY2trS2omESMKFRUVGc2iY+F4Ae5ARLV1FjvSc3ZhG196ahZvOFmXUQCK5/tth2vQ2+pAo8zJJcDurNu/+ekE/uY1B/c8oN18qBo8L18MZ0oXi41C2ZiMJ+Pp8S380+/n8dAt+9FVgGkxqa4rvCAgwvI5281MrPvxyZ+M412XNeN6FT0w8yWiYn1E29vbwbLsHqeA2PrBbI65FiOAWraAAUpIAObjIhsKhTAwMACn04lDhw5JRemFJlsByHEchoeHIQhCTrOIi8HAwABsNpviCNXMph8r20HFAjBZiv2leQ9+ObKOD1zdAVua+jGfz4f+/n60tbWhoUG5Hcd2MIp1bxh/85MxhFgO335XjyLBkopEASjW+x05ckQybFZK4o3rkT8u4tcTW/j87d1oTmOIXQiMRmNcM4k4mWRgYAA8z0vRwUzNJFqxllErusXxAqptBrxG5sxaYLepoMmp7HiyvACKAlhu73epsiz7lF66dPH8/Dz8fj+mp6cVNQol0lljQblFr9hTkhcEBCKc4khbKiH1xSdnEIpy+MTNnTl18dbZjSi36HFA5ek3hYqi6XQ6VFVVoapqV7yGw2G43W4sLi7C6/XCYrFk9JtMhEQAlVM6ikFlNjY2MD4+LqUefT6frFFw+SAbI2ifz4eBgQE0NTWhqamp6FEIuezs7MDj8WD//v1S84RcaJrCp17dBZqiMLbmg4GRl3ZN5QOo19GgaQp6JvW+e3F8HhPT87j1cmUj3WJv7o+dW8FOMIpPv6YLa96wKuIPeOVzyan3y5a7TjegympAmYIUayGI7Uj83boePx/ewP+6wRJnYCsKwsQbSITlQdNU3i1X0jGy6sPf/mw3mtZeKa9DNhW9rU488vYTsl6bregUBAHddVbZ28mF2HRxU1MTBgcHYbVa9xxbJc0FTU4zvnrnEcVr+drv5+EPc/jQNW2KvrepxMiZg5WY2gzkbOFiM+nw5TcfTvk+2U42KZaIMhqNcfWDiX6TYkQ43RxyLUYAfT4fiQBqCZ7nMTExAa/XG3ez1Ol0RbNEUVqjtry8jNnZWVWtUgrB4uIiJmfn49J6ShFnBT/04xHQFPCdd/dm/JtUPoBHGuw40pB8/wmCgImJCXz6p0swmi248yb5qfXEJpc3nWqAOxBFc7k5pzrBcJSDMSZ1JH6u8+fPw2Aw5KXez27WIRjh8OTYJu4okhlxJqwmHWiaQlNDHXR0vZRS3NraijMsrqyshNPpxA/Pr4Mussk0BeTFx00OYZbHTwbXcVVnBaptmR8WJjf8+OOMG68/XlewGjoRQRCg0+lkpYvTiYNsue1IDSbXA4of2lIJ7ZPNjrRjDeXiC7P4m59O4Ip9FXjN0fjIL8cL+PPvD8Fh1uN/veagovfVQhQtmd+kGBFeWFiAIAiS96DD4ZBEnxYFIIkAqoQaEa5gMIj+/n5UVVXh9OnTce9ZbE88OXAch9HR3VFbpZTyFVPVA2th/GbNjNe3U9iXY9fzJ287CKNO3pddFNh//ugALm0vx1296WvjxJFuTqcT//vuPvgjqTtxkyEKM/FCqsaYsMfPrWBlJ4R3XtYiicBgMIjt7W0cOnRIduOPHGJvXjRF4eZD1YqaLArN7cfrcPvxOun/Y1OK4g1ErDeanZ2F3iugqsIJr9cLq9Wa8djuhFh4AlG0qNiY1FVnxbfuPZHxdUueEIw6WuquVYMIJ8Af4eAKRGUJQKOOBkNTskWQP8xidSeMfTk0l0RYHo+eXUZfU1nc8UmXLl5YWACg3FcyHU1Os+JUOZB/IWXSM9AzNOrs8cdPEAS8OL8NCkB3FrWOWhCAicRGhIHdemy3243NzU1MTU1Br9ejvLwcFEVpLhNGBKBGWF9fx8TEhGTdkUgxBaAcxOL+xsZGNDc3q3aiJ4oVtYld91VNVXjxySlUWpJH5JSgpJFCjMgtbwfxo/5wWgEozkw+cOBA1g1BqVLOuXCq1YkX5zyS+Nvc3MTo6CjMZrNq4k+8gCauXY5IKBYsL+CXIxs42ezYczMUoWk6Lup8NByW6svEFI04qi6ZPcVTY5sIRDk0OPPjA5gKQRDwF4+NgKEp/KsMsSj3Pe0mHd5+ifwGoeZyM97SI/8c++B/DCIY5fGNe45n/eAgAAhGeWz4InBkmF0cKw5EX8lc0sVqkG8bGB1NJY3uLW2H8Mizi7iqswJ3nlYesddiFC0RnU4X17AZCoXgdruxtLSEUCiEQCAgHXOxubBYkCaQIsPzPMbGxhAIBNDb25vSfygfN221WF1dxdTUVE7F/akQGyTyIQBF0R277r9/01GMjo4W1IBaFDWPvqcv7evEkW6JM5Oz2Z74+fxhNqWZtBKay81oLjdLRuVi9/S5c+dyfm8lBCKcpqKBgiDAE4xibiuQUgCKjK760OA0wW4yor6+HvX19XHjrQYHB8HzvBRBcjgcoGkaN3RXwx9mZYu/eVcQBt3e6IxSKIrCh69ty0vaNcrxqtWiJvI3rzmIkVVfTueJUUfjPa9qgd/vx+zspuy/k9td/NIGj289v4L/c+eRlBY/uZCPa+qmL4IPf28I913dmrLbu9Fhwp9c3oz9LzeHKD3OPM+rnkbPNyaTCfX19eB5HoIgwOl0wuVyYWxsLG5etdPpLPhnIwJQJbJ5mgoEAujv70ddXR26uro0Fx7OhCheg8Eg+vr68nLy5mMaiFhn6fP5koruQk8gybQ9nucxPDwMnudlGWhnQhSc//vJSfxmYgv/fM9JVOTQJSkiWtEYjUb09PTsidZ5Q2zabmbpfTge//nSMi7rqEBLijFzyVhwB/GxH4zgjpN1mqkH1DM07jzdkHE0ViDC4aEnxmEx0PhmTCND4ngrMb0kPrzERpDkIAgC/vKHI6BpCt9+x8nsP9jLyDE/FgQB3z+3inKzPqMlCEVR2PJH8F+D67i8ozynNG0qxIcVNch1dnGqdPH49AZ8vigW5ucg1Fapki6OJR8CkKZeiYymgqIoqcbwiYE1/GhgDX/7moOyo/g8z2s+ApgKnueh0+lgtVphtVrR0tIizasWI/4A4uoH853u9vv9Wde7F4KSEYBKEaNmyUZgaZXYi10wGMT58+fzLl7VTn2Hw2H09/ejvLwcp06dSrrubLqecyGdABTrQuvq6tDS0qLKfha3d/WBKjw361YlwiCm0ltaWpKmfBfcQfzXwCqu66rG/pr0T5wCdiOTUxt+RQKw2mqASUfjmILRb4VATjOFxcDgfVe2oKs2/b6JTS/xgoDP/nQMnV4/ul0uaZyZ2HCQrAaXoih87PoOWHL0eVMCRe0O9IvK/E5ZjTpYjIwqDyWyCXlAu6ZA+Tcg6C0QKjoh2OoAKv0NWM1Uamy6+EMdHXh/HtPFqdbN8gJoau85O70ZgDsQwekWZ8r3rCgz4N/fKf+horXCDANDw67g+qPFGkC5cBy3xwGBpmlJ8AGvlAiID3hGo1GK+Ivm8mri9/vR3Nys6nuqyQUnAMVGiUgkkreoWT4QRQPDMBnrFfOxXTVwu90YHh7GwYMHJX+nfG9TDqnS+4kj3dRCjMydbHbi32V0KWdCtCxKVwJQYzXgcIMdjTIK1vUMjXe9qk3xOkx6RlbjgprMbgUwvu7Hjd25G7SfOajcMLd/JYCRdQp3vuNkXDRhbm4ONE0jFArB6/XC6XRKN4+eNDfxfCG3o1kQBBh1NN54onAd0JR7BszcbwFaB0FfBiriBeOeBlexD3zz5QCdWizns5YuNl0MQLIeUaO7OJmQEgQBf/+raegYCh870xH3u/94cRlRjsepZkfGz7sdjMJiYDKmdo822vEVhdY3pSwA5aw98ZgHg0G43W7JXN5qtUoPAWrYaZEUcAERvfFyaZQo1gxHhmEQjUYxOTmZMnWar+3mGgGMHZF26tSpjMadFEXJ3qYgCPjDtAtHG+yKnmRjGVzx4clJP44dE0DTVFwdndq+ecArAjDK8YiwfNY1gErWadQzuKJT3mgzQFlt0MiqF2Y9g7Yc/eqy4a9+PI4wy+Hq/ZUw5jizVik0ReGRtx8H83LtX2I0IRKJ4OzZs1haWsJ3fjsCjjHijSfrUVlZmdM5lc/6vGzJek0RP6i534EzV4LWidczC3ijA8zWJARrHYTK/Sn/vJDX42Sjy1bXN3F2bA5VZgo2RzlqqipkpQ7FdYdZXjpvKYpCvcOI2iTp2A9e1YqpzUDGz8ryAh7+xRRMehqfvFWdWemxlLIAzKaBxWw2w2w2S+byPp8PLpcLw8PDYFk2rn4wG9eNQCBABKAaZPpiiOPQcvHGE8VQsexVXnrpJdTW1qZMneaDXKNxLMtiYGAARqMx6Yi0ZChJAW/6Inj8/ApWt0N446nsul1/M+nGmp+LW6/JZMrbnFxxnz7yzDwiLI8PXN2u+Hgm1vupuc4ox+Pbzy6gxmbErUfrMr7+3OIOGJrKWQB+6ifjmHUF8Y23HZO1PwRBwDsuaYTZwCgSf0+Nb+Jrv1/AP7/1WM4NK+lGdhkMBuj1enR1dcFXtoPZ9R1EIhEMDQ2B4zgpteR0OmUfv9FVHx58Ygz/86ZOnHq5lisQ4bDoCWF/tSXn60I2f//7KRemtwK442S94hFmtGcWd/2uDmD0+I8bY8YxUhR4SyWY9UGwGhGAsYijyz742DRCURqff91+fOe5eRzbWEStbkJWuvj80g5+PryBey9tlhqCUnVf/3rShW/+cRF/dXNnnE8gywvYCUaldL2OpnDmYBXaKpM/ZH/56Vlsh6L4q5tT79N0XGwCMBaKomCz2WCz2dDa2irNIhftoyiKUmwxRCKAeYZlWYyMjEgF/LmIt2IJwM3NTWxvb6O7u1tVPzc5KDWhjsXr9WJgYADt7e2or5efUko3mzeRapsR772iTVZqMxUfurYd585tIxDw5zTSTS5iBPD67hp4AlHFN7BM9X65omdomPQMuurlmVu//nidKqbF4+t+RTd0TgA2/RE4eGWR3+nNAFiOR6F0A0VRuLS9Ape27xZ7i80kHo8HGxsbmJychNFojJtMkmof2Ew66Bkazpho99DyDiY2AmhwGAtuxAwAbZUWLG+HsovAhrbRaOVh0idxWNCbQXlXAIFPWQuY6nzheEGKzOaTT992AC/Ob6OhvAxVTht6j9Shzm5EIBCA2+3G1NQUgsEgbDYbKisrUV5eDl8U+I+xCD7YoYfZwMBhznzMJtb9qLDo93j3feFXU/CGWDx4y35JfKdr9Fn0BJGLmUUpC0C11544izwSicDj8cTVjIqC0GJJ/nDm8/mID2C+EAWIeKPM9Umx0F6AgiBgcnISHo8HVVVVsNnkT5tQi2wbMsSI67Fjx9I+4YgXcEEQsOQJoancrDjq2JmhqSETDE0j8nJzytGjR/O+n8XP11ZpAV7Oyo6t+fDAD4fw1bccR609tTeVnHo/Nchkhg3sHru7v3EORxtt+MRNnTlvU0kBO7Ab7bj9RL3iG/27L2/Buy9vUfQ3apM461ScTBJbXyYKhtgHzkanac9+OtHsQGulpSjiT1xT1l3fRiv+4dQMhLKavb9jwxD05rSNIMkE4IY3jB/2r+GGrqqUUemzC9tocppQk6OH5b7qMqlT+n1XvDK6UkwXNzY2Suli0Yz6uZUoBjY5zK26cN9VrbJESYTlsa/KsifC+vZLmjCy6pMdef3c67sVfLq9lLIAzLeHocFg2FMz6na7MT09jUAgAJvNhoqKCqkLGdiNAGZ7v2lra4PNZgPDMNDpdHjhhRfgcrlw5513YnZ2Fm1tbXj00Udzql8vGQEYexEQBAGLi4tYXFzMKECUUEgBGNst29PTg5GRkaIYUSsVYzzPY2RkRNY0kod+PIIFVxBfe9sJPD2+ie+dXcZHzuxDeQGbQHiex+TkJMLhMK6++uqCNAUlM1Ne2wkhygvwhljUJqlQEOv9tra2Clb/mQmKosALAgaWdtK+bmzNh0VPCNcdqFQ9XVfour98YTabpbndyZpJysvLUVlZCZvNtmcf6hk6ZyEjUmivU97RCnrlJYBnATr+WkEFNsE3XZL275MJQLOBgUlHpxTEoSiH//XTSZj0tOKHjmwQ08UOhwPt7e3oDoXRaH4BtYwPL7zwghT9TRcpuj/FA1aDw4QGR+HMjEtZABbawib2ISDWT/Qzn/kMnnnmGfT09CAQyFzXmY6nnnoqrqHy4YcfxpkzZ3D//ffj4YcfxsMPP4zPfe5zWb9/yQhAYPeGFI1GMTg4CJ1Op4pnWyw6nQ4sy6r2fqkQu09ju2WLNYlEyXZFX8X6+npZlikWA4NglIOOoXG61QlvmEVHVRm23aGCCMBIJILz58+jvLwcZrO5YB3hyQTgVfurcNX+5Kmb2LrE06dPZ30BXtkOodpqkOYlq8F/vPtUxtcMLu9gO6RsXJ4W2AmxsBiYgk73AJI3k7hcLiwuLsLr9aKsrExKF6vdoFRwTA7wjX2gF58F9BYIBivARUGF3BBsDeAr0keWwyyHh57axAepclz+svmx1ajDPWkmmZj0DP7yxg60Khzd9/U/LGB1J4QHsqyfE7GYjKiz6dHd1QUgPlIkpotFQZjvaxLLC/jmMwu4obta1v7gOK5kBWAx1x7rJ/qlL30JXq8Xv/rVr/CZz3wGb3jDG1BWVoYzZ87g+uuvR09PT9ZlZo8//jiefvppAMC9996La6655uIRgOKYrnzVcOVbhAmCgOnpaWxtbeH06dNxY2oK7Y0nIjcCKKYmlfgqzm0FYTEw4HgB5RYDbj/RoGibuZA40m19fT2v24tFyefz+3frEltbW3M6p13+CH7cv4qjjfaUUwLkkEy8ZmLBE8LT4y7cergm5+kXhYLjBbzjX8/DwFD47rsyi9x8YjAYUFdXh7q6OgiCAL/fj62tLakT0el0orKyMm7wfbYUQ6Tz1d0QzBWgNkdBBzYBnQlc65UQnK17ooKJCLyA7RCHJwbXJQEoBzkG2on8fGRDtQhp7H5OlS5eXFyEIAh7Js+oiS/E4rdTLoRZHh+8ui3j60s5Aqgl8Wqz2XD77bfji1/8Ip599llsbGzgv//7v/G1r30N73vf+3DmzBl88YtfTPseFEXhxhtvBEVReN/73of3vve9WFtbk+rt6+vrc76vlYwAFAQB8/PzOH78eN6KKvMpACORCPr7+2G325N2dWo1Ahhbp6g0NfnQbQex7g3tqeHKtwBcWFjA4uJiziPdskWuiEpW7+cJRGE36UArjEqVW/S4srMSLTKjHizHIxjlZU0OycQth2qw5Amj2lr8tLVcGJrCqzrKcbIpP6bWoSinuGMW2D13xBqi1tZW/Oj8Cr7x/Co+dHq3lMFgMEhzi1OlE4tNmOXxvn/vxweuapWEmGCthWCthdJvvZ6h8KXb6tHW1qb6OhP57rv2poujHA8dTSnaz4IgYMzF4XCSsYmJ6eLEyTNy0sVKcFr0+MLt3bIttARB0IyIygYtrT32HlBTU4O77roLd911FwRBgNvtzvj3v//979HQ0ID19XXccMMN6Ho5oqwmJSMAKYrCsWPH8ioc8iXCRINkMRqVjFy6cXMhXUeuKFodDoc0ekwJw8s7+Jdn5vGlNx9DZYw4SCcAF9xBrO2E0dPqlH427wrAatRlnFzAcVxcR3ixRhplErhiJNjlcsWJ6mCEw1v/5QWUGZmMc4sToSgK3TK7egHgjq89jyjH40cfuFSx2EzkYK0Vf3d7bsXnxSDRjFctJtb9OLuwjRu7q1FuyS7FJwgCWF7Av72wgijH4+CBA6ApSpptG5tOFJtJ5KQT81EDGOV4/ODcKjqrLTjd4gTHC/AEWfxyZDOrSFwsPM9DxzBZd6Er6TpP3AbHC/h/v52HSb87l1guKzthvLjOoWNxO2PUMnbyDICkx1c0o862LljuGDigeLY7alDo+lY5UNTehweKomSNhxMzQjU1Nbj99tvx3HPPoba2FisrK6ivr8fKyorUkJItJSMAC4HaAlCJQXIxI4DJxIrH48HQ0FBa0ZoJg54BQ1EwJBTypxNIX/vtLIJRDiebHWBoCjwv4J9+OwuDjsZDt6V+AhJH5zU0NEgm4Fu+CCIcj/o8F1HzvAABkCKd6SKA6er9zAYGJ5ocePXRWkXb//3UFqqtRhzIMOYslvdd0Ybzi9s5iz+1iXI8zq2zSaMnpUKt3Yh6uzGn6OoTg+sIRTn8+ztPgAIliROz2YzGxkYpnSjOtl1YWAAAKXpkt9sLdiMXayjFU95iYPCf7zkty4Ynk8F0LoLkkT8ughMEvOuy7EZxMTSFOrsR3XXxGSeOF6TfJ6POZsB1zbqsJsIkHl+XZxsul7sg6WKgOCUCFzLZilK/3w+e52Gz2eD3+/GLX/wCDz30EF772tfikUcewf33349HHnkEr3vd63JaHxGAMYjTONQgEolgcHAQFotFlkEywzCIRCKqbFsJiZFHMdW+srKScwr1ys5KXBkznUIQBPx8eB02HY+yFALwo9d3YicUjZm+QOGeS1vgePlmurodwg/Pr+Cdl7XA+HKKbXNzE2NjY3tGun3zmTmwvID/cWNuRd2Z+P/+ewoUBfz5md2C9lQC0O/34/z582lrWP/29YcUbXt3Xu04dAyFxz9wqey/u/lILW4+Ei80eZ7H9PQ0dDpdRr+6fOEJROEKAevecFEmj6iB3aTDVfvlT2VJxuF6K6Y3A9CluW7EzrYFdueculwuLC8vY3R0VGomqaiokOqN83E8KYrCnafjz2c51j3fO7uMf3t+Gf/3riMpO11TCUA5KXaHWYedUOamvmCUgznFe91xaq+/6Zu/fhYA8J/vOZ30bwRBQINNt+fBVyk0TeP/PrsJAHjwltN5TxeXOlr7/NFoNOsmn7W1Ndx+++0AdoMGd999N26++Wb09vbizW9+M77+9a+jpaUF3/ve93JaIxGAMTAMg2AwmPP7iNGzzs5O1NbKi+YUKwIYG41jWRZDQ0PQ6XTo7e3NSwr1p0NroAUe9+xPLgCdFj2cCWmzgzGRrfE1H5Y8QeyEWFTp6LSj0u7ua0aY5fN+Yfjh+RUArwjAZBFOsd7v6NGjWU+qSQZNUXj49kOoLMut+SIcDuPcuXOorNy1chH96hwOByorK2WPQnL5I/AEWXRUZSfeqqwGXNHIKO7gvNDoqCpDR5X8Wucox0On06G2tha1tbVSM4nL5cLIyIjUTMKybM5+aWqNqttXXQY9Q8WZXieSTACOrfnw6wkXXn+8Nq09zuuPZ55ysxNi8a1nF3Gs0YarZI5SPFBThnRXFDXTqJe0OaX/lpMufnIRmN3h8fDthwre3V5MtJj+9fv9WfcrdHR04Pz583t+XllZiSeffDLXpUmUlADM941cp9PlJMIEQcDc3BxWV1cVR88K0RmbDFF4+nw+qRtVrekT5xe38c+/m8Pn3nAYFgMDiqLw16/phsCxmBwdwqI7iC89NYWPXd8pmSOfnffg8fMreOCWg0mfoK/orERfezl0lIBz587BbDanHJWmNPUb5Xj8n6dncPvJerRUyD92D952MC6CEBsBTFXv9/T4Jlz+CN5wMrdudoqicLjellM6SOyY7urqgt1uB8/zcX51W1tbmJmZkSKDgtGGjzw+hU/fdgBHG+PF7G8mXQhFObRWmLOa1EBRFAyMsqJ7NXhh3oPP/GwKX3/bsazr9ooFLwi445/PgqEpKSoV20zS0tICjuOkKQZnz56FXq+XokdlZWWy9/ffPzmNX09s4V/vPQFHlrO5RU41O/D9P0keRRNJ1pRQazOiymrIuP3t4O4UHnuaVLzVyKDWZsQBBWbzn31d+mJ8NTtpb+xOXX4Tmy4WBAE7OzvwTczAsx3ASy++IB3ffKWLtYQWaxe1PgUEKDEBmG9yicKJ/oRGoxF9fX2Kv3DFjACK4k/tKRkT6z4Eo5xUMwMADrMeLEuB53kEIhx4YXfWqcjwihfBaOr9QNMU2EAQZ/v7FY+gy3SRWPeG8V9Da4jyPD5+g/y08fVd8YW4YlpdrPczm8176v2+8MsJ8AJw+4l6WReuCMvjd5NbuLSjIq42LhvblliWl5cxNzcnPbDElkAk+tWFw2FsbW1haGYeXn8AL4xMo1bfENeAcPOhagSjfEHGdKnJkicElucRZpU9hGkh8kBTFBiawrUHUkewGIaRfAV7e3sRCoUws7yB4f5JlDNh2O12Wd50J5rs+P2UuyBTSfxhNul31mnR4w0nMkf3vv/SKigA77o8dQ0gTVFJ07y5UAwrFYqi4HA4cP9rTwBAVuliLZzL2ZLvKSDZoPU5wAARgHFkK8K2t7cxNDSkWJCose1c4Hkes7OzCAQCuOKKK1Q3JX3TqUa86dTeaKIokA7UWvGFNx6J+93bLmkGkPqCvbq6iunpacViVRRK6cRWo9OMf3zriZy97CiKQjgcxnPPPZey3u9f33kaEQXp6Q1fGJMbfrRUmONG42UrAAVBwNjYGILBIHp7e2Wld41GIxoaGtDQ0IAzfbt+ZltbW5ifnwdN05J5sVPjF71kvO5YHV53LLOoSEa2kQdBEOANc2kjVHJJVY+WCpPJhAd+tYYoJ+AH7+lBwO/D1tYWFhcXASBuMkmsmDlzsApnDqaeRasW5xZ38OL8NnorWdQ4srsu3dhdpcoMa6VoIRqVLl0cCAQkwR/bXayFdWdLoaeAyCGXFHChKCkBmO+TU6kIEwQBCwsLWFpaytmfsNACMBQKSVMy7HZ7waZkANmJFp7nMT4+jkAggN7eXsXrFVPsmZ7M1Wg88Hq9WFlZwenTp1PW+5VblFk6NDhMeEtvE8oSOmOz2ZfRaBTnz5+H0+nEiRMnsvpexfqZdXR0SNMs5ufn4fP54qYdaGGsXb7h+F3bFiWj6/7se8OY2QrgO+88qYofoxxij/VnX9eFRXcIeh0jHUtg9/xwu91YXl7Gzs4OLBaLJO5jzevzSXulGTuhKKyMN+vrfnN5cepItWimnCxd7HK5sLS0BJ7nUV5eDofDUbICUEsm0CIkAlhiKBFhYsMEwzCqeM4VchKI2DXb3d0Nq9WatNhULZ6dceFwgz0uZaT0IiPOTa6oqMDJkydBURQiLA+9zFqxKMfj3AaHg6EonFZlp7wgCBhf92NflSXjiLXYSS+NjY2qNntQFJVUJCgVgGK6f9++fbIblOSQOM1CnHYwMDAAQRAkAVFIe5JC8i/PzCMU5XHf1W2yP9/dPfX4xh8XYTXKv3ZEOR4/H9nALYdqFKfZE8+Tg7XWuAYrEb1eLw29FwQBgUBAGl8ZjUbjGoOSXfdmtwIot+iT1ug93r+KoRUf7r9xX9ronMOsx1WdlZidzV4AFop//N0cdDSFd1++6xWotUja6k4YD/xoFB8904HD9TYpXZxoRr2xsQGfz4fz589L0UEl9aHFRIspYFIDWGLInQXs9XoxMDCgasNEIYygYxsSxK5ZlmXzJjxXtkP4u19M4tL2cnw8SyuWZH6EEZbH534+jhqbEe+7qj3jewwu7eAfzwXBWhbwwesOKNr+vCuInwys4rqD1TjR7Ej6GkEQEAhHMD4yDLPZjH379sHn8ynaTjJGV73480cH8H/uPp6yI1SJAFxfX8fk5GTa9LkazUixczHb2triIkqiPYk4zSLdrFtBEPDjgXXU2Ay4tD03Q+F889i5NbC8gA9dk/l8FLmso0LW2L4FdxD9Szu4+VANfjm6ia/+eg4WPYPrCpCKpSgKZWVlKCsri2smEdOJYmOQ2EzCC8DvplywGHRJ6/S+8cwiOF5I20Ubi9bEVDJ+Mrg7jksUgGIE8Cu/noUgAB+6pq2Iq3vFtzBVfauYLrZarYhGo9i/fz/cbjdmZ2fh9/tLIpqvxagriQCqjBZSwIuLi5ifn8exY8dUPbj5TgFHIhEMDAzAarXGNSTks/u4zm7Eh67rwNEG5ZGw2PR6Yke1QUfDatTJFgVtlRaU6amkk0Qy3WCays247Wgd2tLYkvzTrycxs7CMD17bieamRmxsbKiyT/0vN8cEI6nPCzkCMFH4p7uIZ1NPOLLqg0lPoz1F+jwxopQ461asN0vsVqQoCgIE+ML5+V68MO9BS7k5rZWIXP6/Ow4jwuXnezTvDiIY3X3vaw9Uwqxn8KoO5YJYDTElNpNUVu42nIiNQbFi4VS1A001zqR//+i7T4FTsI5CCMCdEJtTHeb3EjqZxc5lPUPFNcAVi0anCV9/2/GMrxPr6MxmM8xmMxoaGqRo/tbWFgYHB8HzPJxOJyoqKuB0OjUjurQYASQCsMRId6HhOA7Dw8MQBAF9fX2yiuaVkE8hJtp87N+/f8/oGJqm89b9RVEUrt6vPEoh7msAKdPrH7m+U/b7lZcZ8OWbKrB//15LhS8/PQ0aFO67NvlYMIamkqbJRNbX11EeWkHlwRY0N+1Gg3PtzBU53eLEz/7s8rSvyXT8WJaVutMTO5HVQBAEfPwHI6Bp4Mfv7834+sRZtyzLwuPxSN2KJpMJkUgEwWAQZrM568aMTISiHB788TiMOho/fF9Pzu+3vyZ/qZ5XxUQJzTSTttu30MQ2BsWKhcmxYfA8HzeZhKZpxebI+RaAc64gnhhYw02HqtFZnd0xTKz75Pnd5q73XdGqxhLjEAQBwSiflyk5yaJosdF8MV3s8XiwubkpzabOxk5IbbQqAHMd1ZZviACUgc/nw8DAAJqbm9HY2Jg3N321SRdF0wIRlsdf/9co3trbLM2xDQQC6O/vjxvppgapBLZZx8Cc5mIainL4t2cXcPPhWjTFFJULgoCpqSm43W68/rpL46JqFLVrc+MLs3hyZAM3Ha7JOLUgW9KJzUAggPPnz6OlpUW1UoVk2/+Ty5uwshNGhOUV3+B1Oh2qqqpQVVW1e3MLBvHSSy9hbGwMkUhEGn2Vqt4sW0x6Bp+4qTNrw+pSJN9iKlEsiKn/1dVVjI+Pw2QySeniVGMx13bCqCjTS0bT+V5zjc2Aw/XWlJNIsiGf6chHz66gf2kHf3ljpyrd47HIWXfs9xXY7S7WQrpYqylgUgOoIsV4ulheXsbs7KzqHnn5huM4DA0NgaIoVZpU8gHLCwiEOZxf3EZ3vU1qTjl8+LA03kotUkXK3nNlW9q/i7A8/BEW696wJABZlkV/fz/KysqSRtXEba3thLG8HcSGN4xmBcbSsWS6AYpiMxFxAkQ2+1LpTfdIgx2gvNAxuX0/KYqCxWKB0WjEsWPHIAhCXL2ZGG1Qa0zdlZ2Z6+8GlnbwiR+N4ZtvP47KJCUEWuUP02783a+m8J13npQePgrt85asmcTlcmF8fBzhcDgulajT6RCIcPjp8DqanCZc31UtrTmf132znsE1B9StpcznmntbnVjzhtM2Drn8EfDC7lQdJWQjopKli10u1550scPhyOs9SKsRQJICLlE4jpNGKOUj5ZtP/H4/+vv70dzcjKampqKtYzsYxQOPD+P9V7XvioQEzHoaX7zjqBRNi21OUZtUQikTdrMeH77ulXSz2EWbzvNRjMp1VFnwjstaYdJn92QaiHD43tkl9LY4cShFHWViBFCM+oo2NIWw7dhfU5aXFGhivZnoZZY4pi6qs8BhMeYlLfbiwja2Q1H88Pwq3nFpc8kYXP9qdAOBCLenBq1YKbrYZpLm5mbwPA+Px4PZlU2MTEzDatqdTHKyzoyOOqf0d8kmgWgBlz8Ci4FJGtnPZzSqo8qCP8vQaPSZn0+CF4AvvlHhXPEc153Y/FXIdLEWI4CBQIAIwFKDoigp5dvY2KhqGrIQiEbJR44cUdWGJBtYTkCU5bG2E8aRBC9kMSXL8zwGBgZgsVhUq1HjeQE/frlzV7ROUaPGUqxTyzTPN9Z0Ol16ORN6hoKOomAyMBAEAT8bXkdPixPVMU0LsQKQ53kMD+/WXvX09GjqiXjTF8F7vzOAr775sOIRfSKxXmbimLr1jU08MTQBs57Gq4/Vo6KiAj8Y8mDeFcQDN3fm/N2995Im3NRdjUVPqGTEHwA8eMtu133s589nZErpfGBxysxbvzMJigIee/chuFwu6FwbGD4/I6USWZbV3PWXFwTc/Y2XwNAUfvKnfXt/z+d//ng63nVZM7LpPVFbRCWmi0OhEFwuV17SxRzHFdTLVg4kBVyCcByHc+fO4ejRo5IxaiHJ9iKdq1FyPm4OlVYD/vFtJ5P+jqZp7OzsYGRkBB0dHairU6/Yf2jFi394cgoL7iDuu6ZD2t7/z957h0lSl9vjp6pz93SenpzD7sSdvAFYMsIuURAEFPSqiIgoinpV1Ou913SD+jVHzD8TGDAQBQQkbWLyzE7Oqad7pnOq8Ptjtmq7ezpUx+nh7nkeH9mZnq7qrqpPnXrf95yTLAHkKpSbm5sheb7RkC5Bj0RE4m0HtlJRVu0+/PeT42gv1+JrN7fyr+EIoM/nQ29vLwoLC1FZWZlzN82pdTecXgojK864BDA8SznSZwmOqdMWVUBK0PA6NjEzM4OfvWQFSBLv7dKGxNRxGFi0g2ZZtJfFv74JgkCxVp40ac0GGJZF34IdNflK3nsvm8ff6vLjyREzDlbroyrBI4EgCNx5oBQGpQQymQzFxcUoLi4OaSVarVY4HA7k5+fnTK4tSRC4rbskqmn8Tlctm4qTG1XKdBVNLpdvEwylq118rgWcHHYVAczkosYwDEZHR+H3+9HT07Mj836cFUyi7Wav14v+/n7k5+dj7969CX9PQmLS0o1AIIChoSG0t7en/SJpLlbjc9c0oDPIty9ZtXP4vJ+Q7yhdKuBgFGpk+I/rGtEctrgTBAGHw4HBwUHs3buXf9rONfRUavHo+7oTSspw+Sjc9MOTuLzBhI9eHlmlDeBsdJ9aiZKSEjy2l4Ld4YBjcyMkps5gMECtVmPa6gFYCCKA8ZAL+ak+isH4mgs0w6K7Uhf1dZm6xlUyMRQSEXQRjJ/j4bbu7eKk4Fai2+1GaWkp/H5/iFI8ONd2J/COg9HjKnOxHSkE2dzvdLeLc/E75xKRchm7igACmbm5csrToqIi6PX6HTuRkqkcccP+DQ0N/KxUouCIZzY+N8MwvMKzu7s7KfI3tGRHsVYe0dcPAEiS2DbYHWsGkGbYiO09IfN+kbefGUufw3Xbjy83WN/V1ZX2m6HNE8BtP3kdX76+AftKUxsnIAgCigSU0CzLQi4RgSAI6JWJLVMyiRgmgx4mgz4kpm5hYQEOhwM1eXkwGAzw+/1pUSrudLVVIRHh6pYCyDKkNI8HmZjEDW2ZsethWRZisRharRYmk4lXilutVoyPj8Pn80Gr1fLJFbkwqx2rAkgxLMQZHCVgWRa/OrEEo0qCq5q2LEhcPgr3/34Yt3WVxDQP30kSlWq7OBcrgG63+xwBzHVwT5WcWtLhcGQ1kzcYiZhBsyyL6elpmM3mlIf9M+lB+PTIGswOH27rKYPf70dfXx/y8/Oh0+mSunH6KQaPnFqCSibCR68Qni4S7TM+9NIMnD4aH7i4JoQECknNiIZIwoyfvzoHo0qKa/YJJ5KxwLIs3/JvamoSRP6iEd1osHspBCgWQ8sO1JlUgkUWiW4nHNx5ISIJPH7v9hmrRBEeU2ez22GxnG09ccpitVoNkiSxYvfCqJImNNO201DJYi/lNk8Afn9gx8lqouCqls+eXkeBWoaWEjWUSiWUSiXKysr4WVCLxYLZ2Vm+2ms0GpGXl5d47CTF4NcnFnFbdykIAKOrTrSUqGPG1oWDYZiIRPSR15cxa/HgAxdXJVQJTwQEQeDP/asgCfAEUEQSYBgWm55AUvu9E4jVLqZpmreH4trFuUoAc816LRy5cbR3ANzMnMvlCpnrynQiRywI3XYgEMDAwAAUCgV6enpSfmrL5Gf+8cuzYBgWR+rzMDw8zLcpuYzYRCEVk7jzYPl2Sw6WBWGdArF0EvBsAJoSMKXdgHqLcEVrATcXa/D6vI0nLMHzfvFSM6IhnAASBAECBNJVtw4EAujv74dWq0VBQYGg4//lJ8bwxPAq/vS+g9Apo7fqgm+Y5XoFnv7gATwxvIY/96/ipo6iuKSIZlgc+fYxyMQk/nJPfGPobIMgCPxzzgsWSlzbWR0SU2e32yGSKfGx5+yQScR44gMHdnp304ZbHjoFlmXxvxcpYfdSmLG40VqiFkSQXpiwQC4msb8q+3F8LMuCBfClpyYhIrDtmATPggJbiUcWiwVzc3NwOp3IO1PtNRqNgq7lf4xb8ItjiyjSyFGsleHFCSv0SgnK9dGTgCLtc6TvtbEwDys2X8bIH4cfvm0fxCSB4WUHvvDkBP77hkZBSSA0TWfEgSFVxGoXT05OQiKR8ObxuZRdzCWr5DJ2HQFMRwvY6/Wir68PJpNp28ycSCQSlAecCQghYna7HYODg2kVTmSyAvjDt7Vjbn4Bp0+fRmdnJ28Am8o2q8NzcVkG5MifQSwcAyRKQCwHlk5BNP8amMbrwJT2RG0BH6wx4OCZpAWOWCcy7xcJkT7bnYcqEn6f4BsJzbB45NQi9hgk8KxMora2FoWFhTh9+rSg66GhKA9Pj6zxquhEcKBKj8VNr6CKmIgkQJIEDiURVcYhE2Mewag0KkDRW+8fKabuyvkp1Of5cfz4cej1eig0OohkKhRphZOAXMN9F1eBDlAALDi94sCUxSO4qrvu9AvO7k0XnD4KHj8NlmUhIkl88+ZmaBTxz12pVMqLSf45acVHHhvD165SYHn5rNAgUuwgh0vqjdApxOgo04IgAL1CglJdYt2VaK3U5hI1mktSbwmyLIsXJ6xoKVFHHIMREVsWWz6KAYGttrMQ5OIcXSREahf39fVheXkZU1NTfLtYr9fvGKHdDRnWwC4kgKnCbDZjbGwMjY2NMBi2G8GKxeIdrQDGIkULCwuYn5/PSA5xJgggTdOYGhsBSZLo6enZIrgMi+OzG1ATRNq+Z2J1CMT8q4CuEiDOLGAyNUD7sdH3OK7/jQdvbtLhxpbopISb90sHsU4HgfEFaFz5jZfRUqrBt25tAwFgfdOG1TkL/uWKDr4tLXRbN7SX4Ib2kriviwS9UgJ9jKphOJ5IQ9tWKFiWRd+iHaY8meAbdbRsai6m7hPX7gMAvtLw594FbDjcuKxGBdMZNWq0JItcxTUthfB4PJiYsKK9XIuGIrXglv6N7cmNLQwtO9C3YMdt3SUJ3wwfH1qDj2LRIt2yVGkoSny9e21mExQLlJaVQ6uo2RY7KJPJQpJJCIKAVEziQFClsyJGBng0ZPrmb/NQeHLEjBW7D7d0leCVKSu++uw0fvS2fZCJSTz4l9MgAbAAvv3WFl4ZHg+7hQCGQy6XQyqVorGxEWKxmG8XB2eNZ8OMOhJynQT+nyGADMNgYmICNpstptnwTraASZKMuG3OlJphGPT09GQkhzjdn5mLISsrK0N5+VnF3Km5Tfzq2AIuLgEKC9JDOonZFwGl8Sz54yCSQikhQNJ+aBXiqCR3dXUVk5OTaUt7SUdFVSomQRAESrSKM/OeU9ivdaPtwu2xc7mgRN1JzFg8WLb5Eq7UxANXabj1Qj3s3gA0YgYWi4VPstDr9aAoKinl/k5CIiIzKkTg8JHfD4OiWdzUUQyZOLHtvanRBJefxtq0Oemb6AOX1eCBy86qxyPFmFkslhBj8XSISTJNpHRKCe6+oBIm9dY6ML/hBcWwcHgpfPXleZjypKg2KvDajA2JLA27lQACZ0Ug4e1imqaxsbHBt4vFYjFP+jPZLmZZdlesy7tn1TqDZA6Y1+vFwMAA9Ho9uru7Y75Hrs0AckQqk6bU6W4Bc1XW5uZmKPM08AVoXqHYVqaFWERA5lpL2zYJ1xqgjBy6rZDL8fwVS1gsboHX6w35HcuyIQ8F6cquTAcpIwgCz33kAlAUhb6+PshksshG2QSBJZsPiWaOb7j92HAHUBPeTs8iFjY9KNNtr7Ak8v0RBIGjzQUgM0holFIRXy1TKpUoLy8HTdPY3NzEysoKTp06BZlMltaYukTgoxg8PWJGT6UOhZroLS+uMjWwaMe42Y1rWgoEZTezLItrvnscXRVa/Mc1ewXv1+/e3Yk1hz+hmTezw4fbf9qLr97YiNZSDVYzWE1TKBQoKysLEZNYrdYQMQlnHZTIPmTDCDq4MnlLVwlu6SrB/IYHLh+FqztLsL9Kh9t7tlKgvAEaPoqJWwnczQQw2ncuEoliqou5GVGDwZDWdrHf78/Jecpw7DoCmCgsFgtGR0cF26SIRCL4fL4s7FnkbQcTQK5V0dLSklFT6nSRXpZlMTU1BavVygtr3verXoAFvve2dgBbla2Och0mJy3pI50yHUB5AGmENlHAAygN22YAuXm/vLy8lOb9IiFdVTmPx4Pe3t6YkX5f+acZfSs+PHx3Pl6ZsoJhWby1O3783z9Or8MToFFpUO5IwsUzp9fxn4+P41NX1uFNjaaU3ksIiUk3uJg6uVyO7u5u/sYSHlPH5dxmEgzLwk8zcPmFXcNquRhikhCc3UwQBHwUg1emNxPaL61CIrj9yMHupUAzLOY2vGgt1WRtliqSmCTYOkilUvGVo3g39p0ygi7TyfE/b27k98FPs5CJSdz/yDAohsUPb2+N+V3uZgJIEISg8yRcXex0OmGxWPh2cXA+dSrt4t2QAgK8gQlgcL5sIjYpuSAC4drVDodDUPJEqkhHBTBcQMEtJFc0mEBHeOt0Vh2ZyvNBDv9hOwFkaIDxgynuAOk7u71I835+ioEnQCd8w4qEeAuR1eWHViGJSbw4f0fOnigabm0zQKd0okQrh1RMwC/w1L2quRBuP71j8Wad5Vpc0ZCP7ortDza51NbuXbDho38Yxe/v6ox5bigUCpSUlITE1FksFkxPT0MsFvPVwUy0nRQS0bY5PavLj1seeh3fvKUZjWfm5zgyVWVURk2xiIa/f/Bg2vY3FmpNKjz7obPb2qlh+nDrIKfTGXGuTKfTbSNN0YgUw7JgWGxrv9s8AWy4Awkfk3AEf0/feWEGw8sOMCyLaqMSraWaXWmmnEkQBAG1Wg21Ws23izc3N2G1WjE1NcVftwaDIWFLIafTeY4A7hR8Ph8GBgag0WjQ3d2d0Em90yIQj8eDkydPQq/Xo7OzMyuLX6oiEIfDgYGBgYgCips6tzv9A+klgGxxO1jzMAjzKKAwAmIZ4HcCPjuYmksBbRnI9XUwDBN13u/yr78EhmHxwgOHM9pO9PhpXPudVyEmCTz/wOGIr5mbm8PS0pKgB5cqvQwfvEANkiRwfZtwkYdCKhKcU+wJ0Fix+xKK+YoHvVKCB68S7uO4Uzg1bwfFMHD4qKgEkCAIPDG8BobFmXZ0aDXJ5/OFtJ00Gg2MRmPEmLp0wez0g2IYjK44QwhgMthJRWMuqCmDiUJlZWXIXNnExATf/ueSSaLt87efnwXDsvjQJdUhP//JKwvwUjQ+enlt2mYzz6vRY2rdjVdnNtG/5MRHgmYho+H/GgEMB1fV5zqF3HUbbikkpAq8G2LggF1IAONWV85UTvbs2QOTKfHW0k7OAHo8HszPz6O1tTWrkV6piECWl5cxPT2dsDI5UQJodviQnyeNfPxFEjD7bgexOgBi7hUQPjtYdRHY5pvA5u8BAPy+34zpxTXc3OSMmJX84UtrMbRkT4j82TwBvDhhwdUthRH3i6IZ/PbkIror9dhbuPXdKKQiHKjS4/oIyQkMw2BkZAQ0TfOq6XiIlXASC6fmNjFpduGG9uK49i6DSw5Mr7tRkCeNazicDgR/l2OrTohFJGryd8ZQ9V2HyvGuQ9FjvzjoFJKoRrvBObcMw8DhcMBisWB+fh4AQoyoI51HG+4A3H46IZHL3sI8/OP+Q9t+Hun9Yxl3syyLP/WvQi4hcaQpwUHTNCAWAUzVcDwRzFk90CrEW5X7sLkyLplkamoKHo8HFEVBrVbDw5Awac6et3sLVXD5tq+zdxwoxaY7EJf8UQyL/3pqAnsL8/CWjtjK7PYyLdrLtHhh3ILnxi2CLJz+rxPAcITnU4dXgWO1i8+1gLOM4GSMYL+5RLETBJBlWczOzmJ5eRmFhYVZz3MlSTLhtjcX6eb1erF///6oc04Wpx+PDa7gtp4yiIMWIZIkEQhs3TD/1LeMh08u4mfv6Ax5DYcVmxffeX4ah2r0ONISxaJFJAFb0gm2pHPbrwKBAGaW1sCybNSq6ps7SvDmjsRsUv7fM5N4fGgV9QV5PMELBkkQ8AZozFncIb//6s2t217r8/nQ19eHgoICVFZWCq56JNsuFZEECGJ7OyoS2ko1qNArskL+OHCfaWzNBYLAjhFAoThYLcz3kCRJaLVafqY3fNYsLy+PnzXjRj9em96Aj2JQoo38oCEUkcjUd16Ywe9OLeOR93QhP2/7qAlBEBCTRFI5v+lCpM88bXHjX37Rh49fUYujzZklphTD4m+Dq1BIRXhnhAxghUKB0tJSvv3f29uL8VU7nnhhHgeKxeisNsFgMOCKhvyIn8Wokm43tj+DYJLLjWx6osx6ciMdwaKbC+uNuLBeWETobiWA2RDdRKoCh7eLlUolrFYr9u/fn7YK4BNPPIEPfehDoGka73nPe/CJT3wiDZ/mLN4QBNDv9/PzZ6kmY2SbAFIUhcHBQUilUjQ0NMBisWRt2xxEIhH8fr/g13NkJT8/Hw0NDTEvvieGV/HH3mUcqDZgTxAJCq4A/uLVObj9dNS4pQK1DBfWG9FZoRO8jxy4eb+7ziuH2+1O60Jx3yU1OFRjwJ6CyE96JEng3edXxX0fm82GwcFBPiUlESRLANvKtGgrizx/Fw6pmIypLs0krmxKTSCSTSTTrow0a2axWEJi6joK9ZDIlfx7p7MtWm1UgiSImAbh17YWpmVb6cKLk1bQDAOSIJAfhTilE2KSwDWthYLmg0mShEgkQvfeGoi0buwrVsLvsmNxcRGjo6NQqVR8xZdrIz43ZsGqw4e3dhaHHNff9y5jdMWJBy6r4XOxH7yqHgzL4onhNVyyJz+E7H3hiXGQBIH/vFa4UjsYu5kAZnu/I7WLR0dH8ZWvfAXj4+MoKyuDXq/H0tISSkqS81+laRr33nsvnn76aZSVlaGnpwfXXXcdmpqa0vY5dh0BDF/4Njc3MTQ0hLq6OhQWpr5QZZMAcrNzVVVVKCkpwebm5o60nxNpx25sbGB4eFiwqvqmjhJ0VehQH0SSptZduP/3U/jUYSNqAPz+7tiRWyRJ4PLGxJ/yg+f9AGB6ejrh94gFg0qKN6XYFuNa6O3t7YJaBpNmF979i1P4w90HYFBJk24BpxMuH4WXpjZwUb0x6ZirB/88ilKdHO+/sCqE1O6WPN67fz2A0VUn/n7fgaT3OXwonYups5hXYLfboVKpoNfrcfvvZqGQiPHEBxIz3I5EHI80F+BIhito6cb8hgckQYSIRTKNRKLgGIaBQirGRVzlLU+BwsJCPmkmvI34yrgfEqls27GpNioxte7edk2dnLPhm/+YgcNL4+bOs63gKxtNKcXM7ZR6OVXkQg6wTCZDW1sbHnnkEdA0jW984xt45ZVXcOedd2JzcxMXXXQR3vSmN+Hw4cOC84GPHTuGuro61NRszW/eeuutePTRR/9vE0AOXNt0ZWUFHR0daQtdzhYBXFpawszMTMjsXKYSOeJByGdmWRZzc3NYXl5OqMUul4iwt3BLQWXzBPDd56fRValDgGFh9cRuO1td/ohRR/HA+fvZ7XZ+3s/pdOaMshTY2kcuizpWCz0cr89vwhNgML/h4Qkg97lYlkWAZrNui2J1B2D3UnB4KcgitBGF4J+TGyAI4P0XVqV357IEjVwMAokTVovLH7X9Fymmzmq1gqZoSMQ0JiYmYsaavVFxW1dyFZVsIVqFlkuaycvLQ0VFBd9GfEu9BTbbBnp7e/nqoFKpRGe5Fp3l26v07WUafOzyWvRUhv5OaKv3jQaapnPq/BeJRNDpdDh69Cjuu+8+uN1uvPDCC3jqqafw4IMP4te//jXq6+ML4BYXF0NCFMrKyvDaa6+ldV93JQEMBAIYHByETCbD/v3703rwM00AuUH/QCCw7cafiUQOIYhXAaRpGkNDQyGRbkLxzecm8Zf+Ffzurh7MbXiwYveiSCPHL9/WiLW1tah/99TwGv77qXF86YYm9CQQQh8IBNDf3w+1Wh0y75fJvONEwe2jRqNBR0dHQu28G9tLcG1rEU/yggngH3uX4A0wuLW7LCUlc6JEuUwnR3FbUUoKxr9/MLQKnC2ynq52Kue/lgiOz27iw78fxkcvq8ENEURBwQgmD//8WMW2WDO5XB4SaxYJuaCoTQdy/TMIbUmGtxG9Xi8sFgsvJlGr1RHV4hIRiYv3/N8ke5HAMMyOVwDD4XQ6UVy8VZ1VKpW46qqrcNVVVyX0HpHWwHSf+7uOAHq9Xhw7dgy1tbUpZ7ZGQiYXF4/Hg76+PhQVFUUc9N8pBXKs7XJJJLHMiGNhYs2JdacfLh+N1hINvnhDMxQSEjabLeZNvqVEgzqTCrUm4UqqWHm+uUIAU80cJkkCMvLsYhdMADvKdVvtsSSJGJc64nK5+JtPsBghGgiCQIJJX9sQXDnL1g3+/keGcGrOhqc/eDCl1lk4GHYrlivezFi9SYUqgyJilScegmPNWJblY82CY+oiKRRznTy9EZAs0ZbL5SFiknC1uF6v59XiQgimn2Lwy+OLuK61MKLA542CXGgBh8PtdqcsAikrK+OPPQAsLCwkPU8YDbuOAMrl8rS2fLMFLh6tqamJ9wcLx04RwGjkiNvnVJJIDCoZ2su10J9pV3KRWvEIWYlOzqeHCMHKygqmpqai5vmSJJn1FnD4jYD7Pvft25eWzGEglABW56tQnWS0G0f0Kysrodfr4Xa7YbFYMDAwACC+VclOw+LyQ6+URBUSRUJBngwgCEgFJmJwWHf6Y95Q+xbsmLV68KZGE3++R4JOKcEv39kR8XeBM+7pQlrKBEFAqVRui6njFIoSiQRGoxESiQQsy+LYzCb0SknIXG4qWLF7cWzGhiubUptBSwU0w+JPfSu4prUwbfswZ/XA6aPQVCz8Wg3QDB6bCkBX6U7p+w1Xi3PzoEtLS3A4HFAoFPwDWjSv0IVNL16d3kCJVo6rBIipcmlEJhHkoniF8w1MBT09PRgfH8f09DRKS0vxm9/8Br/61a/StIdb2HUEkFvsdgu4ebTNzU10d3fHNJDMFQLIpahsbGyknETy9gPl+Nc/DmHW4kZj0EIaq91N0Qw8ASZEmbjpDkApFW2bb2NZFuPj43xqSjRj3WyLJThixv3/9PQ0LBZL2pNd0pGawcUltrS0QK1Ww+/3bxMjBFuVqNVqnhCm28iYZlgcW/ZDYfShVuB1bvdSuO57J1CileHh93QJ3tanrqrDp66qS2j/+hbtuOfXg7jnwgrcsT9yRXxvYR7UcnFM8hcPT4+sAwSSsjgJby1yPnWLi4twulz4xKtrIEUknv/QgbTE1Dl9NCiG3VEC8cKEFV95Zgo+isHtPaVweCm8vmDDeTWGpEcTnh1bB0WzCRFAAPDSwOk1Z9oINrB9HpR7QBsdHUUgEIjoSVeoluLTR+pRvEMK/mzhjVoBFIvF+Na3voUrr7wSNE3jXe96F5qbm9O0h2e2kdZ3ywKyVX1Ix7yM3+/nZ726u7vjvt9ORWAFE09uPi0vL0/QPsfDwoYHE2tOzFhcPAHk1GbRCNl/PzUOb4DBv13TABFJgGZYfPO5ScglInzsTWeHZ4Nn6aL5+706ZYVGIcbeAlXGCCDNsPj7yBray7Uo1Gw9jXPHkqZpDA4OQiKRhETkpQteKrUb7/z8fEjqSKTvSCKRoLCwkFcycq2p/v5+AMlVB1mWhSfARCRJPorFgs2L2thetzw0cjHayzS480Dk1Jl0oi5fiT2FKpxfY4j6GqVUhLoERhcioak4L6FqZixwPnVKpRJmsxlfPKoA4Xeht7cXIpEo5Zi6OpMq5c+bKi6o1eOzR/fgcO1Wd2Vuw4OJNTeaitRJtz/f2lUCik7s2pKISNxYL0FPS+qOFCzLggW2nQcEQUClUkGlUoWISYIrvnq9Hp96Zh0SsQg/vbNd0LZysbIvBLlYAUyXEfTRo0dx9OjRNOxRZOw6ApgNBFdvkgVnT1NfX4+CAmFP8Tt1AXJkjLOlqa2tTYulDgAsbnogEZGwuLZMn399bB6/O7WE79zSFJWQ3dJVihmr+6wBKkngiqYClGi3yNX8hgd/7Z1Hs8SMvfWx7X9em9mAmCTQWKTOGAGkaAazVg/EIiKEALrdbgwNDaGsrCyp+cl4WHP4cONPh3GoXIFvCVCVBYNhGIyOjoKiKHR3dwt+giYIAhqNBhqNBtXV1QgEArBYLHx1UKbMg4VR4tDeEijl0SsPb/9ZL6bX3XjqvgPICzKYFpEELqyQo6pck9Dn+fZbWxJ6fbJQycT46R1tGd9OqrmwkcA9eF3SclZZuBMxdamAZlg88voyKg2KEPNtiYgMaXM2FOahQq+I6W8IAP8Yt0AlFaGnUrftdwqJCNjBr+Arz0yDZVl87IramK+LJCaxWq1o0TOQw4uRkRE+wizaMc1FEiUUuVgB5Oaocx27kgBmulImFotBUVRSrbpgu5TdMqvIZRAPDAwkHOkWD7d0laKpWMPnkSplYixtevC1Z2dwc2VkQlZXkIe6gtB9OFh9tuLyysgchqaW8OYbOlBo1MXc/l0XVEFEZJZcyyQivONgeUiKCU3T6OvrQ3Nzc9SZz1ShV0pAkgQOlSWWeuP3+9HX1wej0Yjq6upt300i35VEIgkxMj69sI7J0ytgnf3Qy0n+xhQepn5bVwm+/PQkVBEqgDtVCX+jI9J3Gh53ZbfbE4qpyza4h0KKiX1+iEgCebL4pGDW4gFJICIB3GkUqqVwB4SPBK07/XD5aVQaFCgpKcEn31zCH1NuhINlWZ4MajQanvSdI4Dpxbks4F2MZGfxKIrC0NAQRCJRwnYpOwUu0s3v9+O8885Ly0xQMMQiEi0lap4cXd9WjE23H1IRAYZxI0AzeHHCggtqjfx836rdi5FlBy7aExqdxLIsRk6PoUpix9W3nweVIv5sSypzWIlAJjm7nfn5ebjdbvT09CQtnokEq8sPH8Wg+EwlVCIi8eTdbVhdXRX8HpwKua6uTnBlWigIgsCesnyUFeihkor42UEuTD1YWXxNayGuEZAwMbriRH6edNepGGmGxWszmzhUrcsJ4sQh1r4QBJFwTF2mQDMsoo3uvVWAD+DQkh2vL9hxY3txzDUgG2MDyeKOA4l1Db71/Ax8FIMvXreXP87Bx5Sr2G9sbGBlZQVjY2NQKBQwGAzIy8vbtQSQYZi037dSxbkK4C5GMgSQu7FWVlaitDR3F5VgeL1ePn9WoVBk5CI6MbuBn70yj09cVY9S3Val6h2HKsEwDF57bREjyw48MbQKrUKCrjNRb4/2rWB+w40D1QYozizegUAAvX19+OhzTsikEjzVk3uDzZzHI03T0Ov1ab9JPjtqhp9mcVtPacgCL7RaZjabMT4+HlUpnQ6QBMG3dMNjzoKrSyRJ8tWl8OogsEX2KYbFO3/RB5Ik8PID52VkfzOFX59Ywjefn8F/Xd+QM55tiVZVhcTUJWJLIhRcm1cjFyPZVHS1XAIxSUASR+GdCXKeieq1y0fh7T/rxWeO1Ee1Dbr7ggrYvVTMzxRJTGK1WjE5OQmn04mxsTEYDAbo9fpdUcAAcrMC6PF4BIcl7CR2JQHMdIsoUQLIxXml68aajXJ8eKTb8vJyRrajV0ohExNQSUNPNe4YNhWrcdcFVSEzT3ceLMemO8CTv+DZRK1qGhfURh/A3ylw+cgmkwlVVVXo7e1N+zl6ZXMhfBQdssALuRZomsFrQ5MQezfQ3d2d0eoNxbBYsXtRpgtd/IIrETU1NfD7/bBYLHx1kJs9MxgM/OcTkwQ+faQO1YbcH6OweynQDAu9cmvG6uqWAlAMg4PVup3dsTCEkwObJ4Crvn0M/3akHlfFUByHx9RRFAWr1YqlpSU+pi484zZZiEgCMjGJGqMcDk90MvPk8Bo+99g4nrh3/zbPxQqDAhWG7D+IZ+q+5KUY+CkGJ2Y3oxLAYq0cxQk0HILFJAaDAdPT08jPz4fVasX09DTEYjHfLo70kJYryEUCuFti9XYlAcw0hBJArn3q9XpjWpAkuu1MEkAuQm91dZVXfmYStSYV/vctrdt+zt/kRSTqw+b95BIRirRbFzTn78fNJv75/bkVTA8AdrsdAwMD2Lt3L/Lzt2oWmbCdUcvFUCMykY4GhmFw789fxivzPjx8935B5C8VAdTbfvI6pi1uPH7v/qgRZ8BWdSnS7Nnc3By8Xi9EIhEIgsDRJhOQozeeYLw6vQGaYflcXb1SgnceLI/zV9lFtOPKssDoqjMmAQyHWCyOGFPXOzCEZUcAzWUG5OfnJx1Td0NbEWiaRu9i9GM/uupCro2KZkpNa1RJ8bf3J5b9nAi4NA2O8AFnBUKzs7N8S5P7faZHABJBrs0v7iZF9TkCGAFCCGBw+7ShoSFtB5zbdibasdyMolgsRk9PT05dNOEQ4u9n9wSglosFfffzGx78edKPlo4ANHESGsIxvGTHy1NW3L6/fNs8EVf9bW9vD5H9Z8t4OhYB5KqSb+sshEHvR61J2FAy956P9q+ip1KHUp3wh4TPHq3HH3pXYFAK/47Dq4PcOTozM4Pnp+yQyRW4rr0UBoMh52Z9OBys1oOOI0xIFk+PmMECeFNjfDPfRKFVSPDqx85P6T2CY+ocYj28izaQCnFCMXWREO/G/qFLqvGhS6pT2vd0g6v8+CkGbj8NXQLXwU4iUpxauECIs3/iRgC4tJmdzqLO1QrgbiCBubmaxkGmv1iRSASKoqL+njPgbGxs5J+W0rntTJhBu1wu9Pf3Jx3plgrWnT7oFJIQlWwsBAIB9PX1QavVRvX3c/kofPv5aVQblbi1J/7n8VMMWMRXD0aCWESCJIgQQ1mOoDqdTvT09OB3r6+gyuDF+XVb817ZUrJG2054VfKwQOcS7rvecAfwxScnUGVU4nfv7hS8P83FajQnaJwbDpFIhPz8fGg0GlDaTaxY7XA4HJibmwNJnlUWJ+tblwlo4tiNpASCAJGGcykbN6U9hSqY1FIUqGUAtqIOOdNiLqZOp9PBaDRui6nbif1NNzjS+vPXFuClGNxzuJJXLu8EJs0ufPXZaXz6qjpePBYJNE3HJHHh9k8URWFjYwOrq6s8yedGALI9+5aLFcDdgl1JADMNsVgckYSxLIupqSlYLJa4qR7JgmsBpxPck3i8SLdMLLjeAI37fzcApVSEH7w9cuxVMIR6EapkYnRV6NBWJswvrtakwvW1UhgitCUnzS7k50mjZrfuKczDnsKz1bNgA+qOjg4QBAGaZjFjdeN8bBHAbGUPRyKAq6urmJyc3FaVTAQGlRRfubEJDYXC/p5i2KQTF8IRfA62l+uAch3/73DfOq1Wy/vW5Wp1MFVc0ZCsFCK9ELI+SETkGfJ3FuExdTabDRaLJSSmzmAwQKlU8u/PsmzGCSDFsPjNiSU0FKrQnSYbGG6fr2ktxLrTv6PkDwD8Z4ysA3EMrRMlUWKxGCaTCSaTic+itlqtPMnnrkudTpfx6zLXKoBer3dXCECAcwQwIiJV4cITMjL1xBErIi1RcDF0NpstbgQZR1jSfSHJJSIcaSnE/qpQLzwmQnRU+LxfPLypKXEbk/Cbip9i8PjQClRSMf7lvMqIf8MwLFYdPhRr5XC5XOjr60NNTQ2Kior419x5qCLkbzhi5vBScPsp3iA63QgmgNwDChfhl+pM6uE6YdVtmyeA58ct6CjXolyf2sL3u5NL+NMpK771lsjkP7gtxTAMPzs4OzvLG+IaDIacqg4CwC+OLeCVqQ18660taUv4SBSpEKoNdwBXfus1vOtQOd53OPJ1IgThc2YccZiamoLD5YZMpYFaq8PbfjOJ9xwswSFd5r4rEQGwYBPy2osHjkgVaWQoykAEG82wMUnly1MbWNz04C0dxSAIAo1FeYJM0lOpogVnUZeVlYFhGJ7kz8zMxFX8p4pcI4DpSgHJBnYlAcxGC9jv9/P/ttlsGBwcRF1d7NSJdG07HQTQ7/djYGAAarUaXV1dcb8zrvKYiQvpbftDh+FZlsUtPzwOl8uHx85j0TtvA7W5BBGVPjFNJEQiuVIxievbSnj1ZiT0LdrwytQGLqqQYnNpBq2trdBoYlceORHIY4Mr8AYY3HGgHGQGqgHBkXMDAwOQyWTo7OzMaktEIdnKaFbLUl9O/veZKdAMI0j3QZIkdDoddDodgK3qoMViwfT0NDweT0iqRSpVCJePgtNHozCFG/o3/zEDlgV2kpKmQgAVkq3zSSZO7LxiWRYOHx21Rc7F1JWWluLR/hVsbDrRKXaAZRhYzKvwyEg4nc6MEHqCIKLmOSeLTFYtnxxew4k5G+6/pBqqKNfa9/85C4ph8ZYOgTmKZ5DONipJktDr9bwBPle15xT/6faTzLUWMHe+7gbsSgKYaXAkjGVZLCwsYGFhIaV2WjLbTgXc/FcihJWrPGYj/okgCJAkUKgksOn04DtP9qEqX4VP3RCfqKaCaMKMeFWrPQV5WF1ZhtNsjltJDd/WVc2FcPnopMnfwKINp1eduL6tGJIIM5QEQYCiKBw/fjxtkXOJ3sSkYhJXJVGNjYSXHjgPo2PjCRGlkRUHZGIRavKVKCkpQUlJCV+F4NrFYrGYnx0MbjUKwWszm/AEaFzVVJB0S++lB84Dzey+mTYOcokIxz5+QcJ/98GHh/DK9CaeuHd/XDPvi+qMsLo1qMlX4kTjHmxubmJ8fHzXxNQBkcnI8+MW6JUS7CtNLN4wHGV6BfqXHJBLoj+kf+etLfBRTMLnWSZJVLiYJNxPMlUxSa4RwHMVwF0OrgI4MDAAgiCwf//+rJWYUyWAi4uLmJ2dTZiwZnJmzemloJKJQhal3921Hy+99BKG+1/Hey6oRnN1ScZvjslYs9A0jYnRIVSoJGhoEN765ypzWoUk6myhMBBgWUSdr3M4HNjc3ERXV1faBEk7SVIkIhKyOOa94Zi1ekAAqMk/6xcYXIWora3l81Gnpqb46mB+fr4gw9tDNXq4/XRK81wSEYkY9+2sIFPVKYZlEaDZiNXBt3aVYGDJAYMq/jWgU0pCVLMSiQRKpRLNzc27IqYO2CIj4elF//HYOEiSwNP3HUjpveMJrFiWxX89PYkijQzvv7AqoffOFomK5Ce5sbERohjnRgQSiVHNleMPbImedkMMHHCOAEZEIBDAysoK9uzZg7KysqyeXMmKQBiGwejoKPx+P/bv359wyytT6mO7J4BPPTqMlmIN3nfRWcuG5eVluN1udHd3p5SV+8L4OgI0i8sa4ltkJEpyPR4P+vr6UFpaivLyxDzd0kWoW0s1aI1SOVhaWsLMzAw0Gk3a1eg7iUQV1Fc0mOK2jOVyOV8d/PuoGQsOF/aJNzE9PR1ViMBBIRFBsdPsLQZsngBem9nEBbWGrEUfBuOJYTN8FIPr9xVum2+8oNaAf9x/KKn3DSasuRRTF2+fg4kUQRD41ltboJYnf1xW7F78z9NT+Pdr9vApO5FAEAQYFlix+xLexk7FqQWLSQDwySQTExPwer3QarV8MsluEXmdawFnGJkkZJysXavVJnzTTweSEYEEexI2NjYm9f1kqgKolotRoVfg0jMEjWVZjI2NweVyQafTpayW+ve/jYJlkXYCyCWlNDU1JUVQM2kDE2xB097ejqGhoYxsZ7cg0crcVkVWhbq6rXPG6/XCYrFgcnKSv+lwrcZ41cFcsHzwUQwCNIsAzQDIvq1KZ7kWFqc/7eKWWPsrJKbOYDBAo9FktLK1uOnFHT/rxQ9ub0WdSRWxktZYtL0axLIsjnznOIo1MvzkjtgeTafm7RhddWLC7EJ7Weyoj89fuzfxD4HcaaNGEpNwZtScmMRgMORU1TccLpfrXAVwt4FhGJ6YtLW1YWJiYkf2QyQSIRAICH691WrFyMgIH+mWynYzUQEkCAIfv3IPgK2n9v7+fuh0OnR0dKC3tzdl0vmzd3SBEXgTFkoA5+fnsbi4iM7OzqQJaqYINUVRvBq9o6MDNE1nxW5mp8CwbNqJRU+Y5YdcLueFCMEKxuDqIDc7mAgyse+RUKCW4eqW+DOYmSKrmVK8CiWs0WLqVlZWMDY2BqVSmbaYunCsOXygGRaLm17UmVQJ7TOwFSEYD1c2mrC/UgejgDZ6ssgVAhiMcDFJpKqvwWDIufWPE7rsBpwjgNiqAPT398NoNKKzsxOBQCAjZEgIRCIRvF5v3NelO9It0751DocD/f39qK+vR0FBQUrbpGgGj5xawnm1BlQkkBMbrSo3uGiDRCxCvUmJ0dFRBAIB9PT0pDT3Gb4tp4/C44OruKKxIOl0ALfbjb6+PlRWVqKkpITfTqbBsizmN7wo1soiClHSDe67W9j04NrvnsDHLq/B7T3ZyXUNv+lwNiVcSyrcxDja9z+87MDbftqLr9/cjAsF2ulkA7laNYmEZCuW0WLqhoeHQVEU9Ho9jEZjXNGBj2Liqp47yrV4/sNnW9zRiJSPYjBn9aC+4Gxr8Il7hUW7iUgiroAmFoR8j7lIAMMRrerr9Xpx/PhxXkyi0+l29LOcqwBmGOlcxCJV0DJVDRMCIdumKAqDg4OQSqVpi3TLJAHk4tLa2tpCLoxkt0kzLGatbkjFZEIEMNr2XpnaAMPQsM1aYDKZkm6jByOcALr9NLwUDaePSooAcudpuJl3JjKHt23bHcCJORtaStTYU5C92RaVVAyCQEyLnkwj2KaEYRhsbm7yJsZSqRQ+nw9ut3tbdVAqJkHgrH1KLoCbT3th3AIRSeD82vjE1OWj8NyYBT2VupRscJJBOlrWwTF1FRUVoGk6ouggPMHC5gngkdeX0VamQXeFLuV9fnlqA30LdtxxoDRmRnaiYFkW604/TGfMt2csbuiVZ4Vnq3Yf/v3xcdx1Xjk6yqO3j3PNSy8euKqvQqGAxWJBW1sbNjc3sb6+jomJCchkshAxSTYffNxu966Zyd6VBDAdYFkWMzMzWFtb21ZBy1aKQyTE2zYX6VZRUYHS0vRVRTJBehmGwfj4OKbW7FAV1m17Kkr2e5ZJRLj/0lrB0XLxtnddkxbDQ0Oort7LDyOnivBtFahluONARYy/iA7Oiqi0vgXPTbtwpDkPsjOihGxEzhmUEpxXo89oCyocLMvCoJTg1CcOZ22b8RA8gwRsVQdPnToVsTpYZ1Lh1CdzZ9+D4QkIv+a2LJsIZDPQgmVZzG14oWITtzOJBy5mMD9/K12FEx2Ex9SpNVrolVJUJmhsHq2SdqBKhzKdPK3kDwB+eWwRfx5YxX/d0IgKgwKf/stpyMQkHnr71lyhiCQgIqK7CMTb71wH5+sqFotDjitXuefmejmhXDbyxM/ZwOQ4AoEABgcHIZfLI1bQdrJNEouIcU+tQoyIE0W6SW/wvN8j0yL4xudwqDY/pIWYyjZlSagyI5ElLn1kf1dHWi/adFTmGIbB6dOn4ff70dPTgymLB36aRXCccTbOVYIgMjLjFWt7uwEKhQJSqRT79u3bFnEmlUr52cFciYXiqlNXNgl/yFFKRTjanB6PR6FYc/jxypQVtVrAkGFSEiw6CD+GNRIJvJsBuEjhVaRoREopFYW0f5MFy7I4MWfD3sI8aORiXLLXiFWHD+V6OcQkgbsvqESpTo6hJQe++fwMvnJjI755S2aTQHYS0SqX4ZV7zkJobm4OBEFk1ELI6XRCrU4tDz1b2JUEMJUDZrfbMTg4uC3KK1cQiQAmEumWzu0mC86Impv3++8iP8xOXwj5c3qpEAL41/5lEASBq1szd0yCt8d9p3a7fVv6CMuy+MnLc7hoTz5qTckt2iRJJiTmCUcgEEBfXx/0ej0aGhpAEATqC/JQX7A7ZkuyjQDNZGU+MXxb3ANFpIgzi8XCV5aC55N2U6ttJ2BSS3FBnQEinxMeV+KWJski/Bhy6nDOO1KIJUmmlNbf/+csnhpZx7ff2ozHh9awZPPi+n1FKNMp8NHLa7f2N0DjubF1XNtaiBOzW+blPoqBSsCz224lgEL2OzwxyO/3Y2NjgxeTqFSqtIqEzvkA5igWFhYwNzcnOGt2JxBOxLhKmlarFRTplixSJSwcuHm/YCNqY54UxqAh5kmzCz/45wzOK2BwSL9FyH788hwAZIUABitpOzs7t32nG+4Avv/iDJ4ZNeP/e3d3UttKpTXL5Q3X1tYmHD0YLyuUg59i8PzYOvZX61M0qk4/Ev3uXpnewN2/HsD3bm3FeTXJe0oKwazVg2u/dxz3Hq7E3TEycRUKBZ/MQtM0Pzs4OTkJmUy2I9XBTMaUpRMkQaBMp4DZ7NzR/ZXL5Zj2KkAoS3GoWRdiScKRRaPRGBJTlyiRYlkW7/3VABqK8vDAZTVRX7fpocCyLArUMlzekI+Wkq0K04Y7gPE1F7oqtHhlagNOH40fvzIPMUniGzc3C762dysBTGZ2USqVorCwEIWFhRFFQtwYgFarTeph7VwLOAtI5CZB0zRGRkZA03RCJsk7sWAGG0GHV9IyvV0h6uNo4Gx0PB5P3O+4UCNDhV6BMi3Ff9aH7uxIettCQZIkPB4Pjh07hurqahQXR87LNKik+MHb21FljC0woWgGfx1cxbWtRdtIV7IEcH19HadPn8a+ffsSbiNYnH48e9qM82uNKNHFVoV7AzTs3gDWnf5tNwmK2qrObs1/5f5NwaCUgDjz/4nA5aPgpZiE5rL0Z7bFtfOErA8ikYgnfEDo3Jnf7w+ZHdwN33e2kAuE9VOPjgIg8MJHDkXMtw2PqaMoKqGYOoIgsGjzYsnui0kA//WKrSqf3Uvhf/4+hWKNHN+5tQVffmoC0xYPPnJpNZ4aXcdbu0pQaVBgaNmR0IPd/yUCGIxIIiFOTDI5ORnXJD4SXC7XuRZwrsDtdqO/vx8lJSUoLy8XvKBw1aJst2u4CuDi4iLm5uaylkGcyjye3+9HX18fDAYD9u7du+07Pr3qhNXlx6GardZKnkyMey+uwczMDL9NvTI1m4NH+5Zxfq2RV8NFgsfjwfr6Ojo7O6FWq/Gb4ws4VGNAZQSi1xbHcBUAHu1fwRcfPw0CwPVtoWQy0e+Ts/VZW1tDd3d3Uq0IhVQEuYSEShb/nNUoJLihvSRkuJ9lWdA0HbLvNE3zRDBXbxB7C/PQ96kLE/67g//7MgCg/1OHBa8LGrk4ZFvJkPzwubNg9aJcLufJYqrWTuHIBUKVCHJhf39yR1vEfQjPt+VmzFZWVkAQBHw+n+AZs8feL8wOBtg6/27uKOYr3R+7vBbj5q0KoE4hQa1JCYmIxEX1Ww8bY2suiEkiJCYxEnYrAUz3foc/rHFiEm4MQK1Wx82jPtcCzhFwoonm5ma+/y8UHBHbiXkdp9OJ9fV19PT0ZC3+JtkIOiFVyu+/OI0AxeBgtT5kMUyX8GTJ5sX/e3YSx2Y28cUbmrb9nlN8W61WVFdXQ6PRwOry4+vPTeKvAyv45buSa/Ne1VQAEUngTY3bP3ciFUCGYTA8PAyWZdHdLTxvOBxKqQjX7otc1YyE4Koly7KgKAoEQfAzpgzD8EbTNE3zowmZrg5mQ9kMAJ87Wo9lm3fHRV/h1UGLxcL7UabT2ywXCFUiyIX9FTIDHBxTR5IkpFIpRCJRiGExLdOAlqjQURlqDzJhduGlyQ28bX9pXKUuh2BPzPw8Ke8R2HAmcWR0xYnRVSeuaMjHN/8xDZIg8PWbm2O+524lgJm+R4eLSRwOx7Y8ai5xhjtXzxlBZwGxbhJcVBY34J+MaEIsFoOiqKzmSnKRbgRBYN++fVld/JKJoOOyaONVKT9zdC88/u2WDslsMxJKdQp86YZmfgEMBk3TGBoaglgshsJYAqd/65wxqKT45lvb4j4Zx4JKJsYNbZEJF6cCtnkCeGbUjCPNhVBEyGn1+/3o7e1FQUEBKisrs37DY1kWDMPwIfbhBJ27KTAMw1cIOdJOURRvhrwbbx43dQgny9GQ7uPFVQfLy8t5zzqz2Zzx6mAuIhcIIABQDAuGYSGNYwoNbO2zRCKByWTiZ8ycTie+98IUbI4FBNbEyD/TUtRoNOhdsMPi8p+5l8X+rEK/j18eX4TDR+Hvo+vIz5PgPecLs5/Khe86UXAdi2yAJMmQPOpAIACr1YqlpSXcf//9sFqtuPTSS8EwTMrX5+c+9zn88Ic/5G3JvvjFL+Lo0aMAgC996Ut46KGHIBKJ8I1vfANXXnll0tvZtQQwGnw+H/r7+6HX61MSTWTbDJoz+m1sbMTo6GjWL8ZEqnGJzPsBW+1dfQSelYjwhGFYHJvdwL5SbcTAe669HAyv14ve3l6UlpairKwMX/5LHyQki+b6KgBAd1gkWDpBkiRYlsWGOwCXj4LLT20jgFw6yp49e9LmP5gIYpG/cHCLLPe0HVwd5P47+PepLMrZqgCmA5ncz2DPOpZl+dnB4OqgkESL4H3dTTf5XNnf355cAsWweMeBsrivZRgGAQb46avzuKjeiGqjEmq1Gvde0QJPgIZWRvIxdadPn8YehQIHG4xgqAAgij72QTMsvvbsFArVMtwRZz8+fVUdvAEaNz90Cla3DKXa+GRkt1xv4diJMS0OEomEF5M89NBDeP311/HYY49hYWEB+/fvx4UXXogrr7wSF110UVJirw9/+MP46Ec/GvKz4eFh/OY3v8HQ0BCWlpZw+eWXY2xsLOnv4A1FADc2NjA8PJyWG2q2CGAsQ+psQujnjTfvlwgSIZ2LNi+eGTWDZSOTvXBw50JTUxM/uH3FHh0kyA6p50hMlVGJKuP2J/C1tTVMTExsS0fJFhIhf5EQXh0MJoLcjXs3CUlyHQRBQKVSQaVShVQHuTEXhULBVwfTnXe7U4hEANccPrw6vYGrmgoEVeTSgc5yDbwCzbO5ffZTDDbdAeBMPLtSKuIfXINj6txuN9bM6yExdQaDAVqtFk4/wws5RCQRMxKOYliQxJaCWi4RQS4R4a7zK7Bi8+UEic4UaJrOapcuGkiSRFdXFzo7O/H000/jxRdfxIsvvognn3wSn/70p2EwGPDe974Xb3nLW1LazqOPPopbb70VMpkM1dXVqKurw7Fjx3Do0KH4fxwBu5YABp/U3AD9ysoKOjs702KtkA0CmIlIt2QhhIxx836JEmw/xeCJ4VUcaS6MagTtC9BYsnlRnX+2lWzzBPDcaTOu21eMMp0ct/eUoVQX/9hyyRnh50KpVgaPxyN4v1NBtO+TZVlMT0/DYrGgu7t7RxYvrpXL3axSvUFEahWHk8JcF5Iki526uUaqDloslph5t7lSURMKLrouGJueLeU2xbDI1pXTWCRc0ckwDBRSMd57QXSLIA4EQeCXr6/DF2DwgYvbwTIMNjY2sL6+jh89N4o1H4n3HipBeZEJCoUCH740skqYZVl86ckJiEkCn7yyjv/5LZ0lgvd7tyIXZxdZloVSqcSVV17Jt2fn5+dhtVoTep9vfetb+PnPf47u7m585StfgV6vx+LiIg4ePMi/pqysDIuLi0nv664lgByCSdT+/fvTdjJkmgA6nU709/ejsrIyrZFuySKeCETovF8kvDxlxa+PL8CUJwup3gWTpPf9qg9Wtx//37u6kSfbOi1/f2oJD59axJ7CPDQVa0LIYSQwDMO3x3p6eraVxbMZ8RfcxhxasuO+3/bj9+/txtzEaUgkEnR1de3IwsWJPYDU2rTREKtVLFRIsptawLmA4OpgRUUFKIqKWB1Mh89nNhGJsO4pUGU1jzpRJEqyO8o0GFhygCQIIIjUv7O4Eiem16GUsNti6jRaLSRBYzcEQaBALUN5HOunNyJyLcM42vEvLy9HeXl5yM8uv/xyrKysbHvtF77wBdxzzz34zGc+A4Ig8JnPfAYPPPAAfvzjH0dcF1N5qNvVBNDhcGBgYABVVVUoKUnv045IJOJvlOnG6uoqJiYmoka6cQKCbBKEaIIMLo7M6/Um5KEYjPNqDNAqxGgu1oBmWLw4YUF3hRZ/GrSgy7j1HX/umgacmNvkyR8A3NJViqYSNRoKoz+Bmx0+fPnJcTx4ZQ0mR4dgNBrR2NgY8aLgCKDV5YchzZmc4QgmMS9NWrHh9uPZV06hZ08ZKiqSywROBam2fJNFPCHJG7k6uFMQi8UwmUwwmUwh1UGLxYKNjQ3YbLYtIqHR5PR3vtsqlkBiFSmGZbG/So/9VdvNywvUMhzdt1UYCI6pOzm5gq+/Mox37VOip7aA96e7+4Lk15Td/LCVaxVAj8cDpVKYsPDvf/+7oNfddddduOaaawBsnQucAhnY6nalwn12LQFcW1vD6dOn0dramhHTRbFYnPYKIKdOdjgc2L9/f1QfIa4al80TO1IFMHjej4sjSwYBmoGfYiARETi96sTjg6uYWnfhL0MWsLVSdLQClUblNj++PLkYB6tjz/sdn93AyVkr/vAPK64/2BizNU0QBH5yagMvPrpl/RLP6DkVBFcb39KiQx0rRVvzXt7uI5vYKfIXjmjVQY4Ucg9c3P6eQ+oIrg76/X5ewciJEFQqFW90m2uzg9kigAGawdeencbbekpRmmIVjbvG4qF3wYZP/fk0vnZTE/YWxp8B5pJH6lg51AM+7KmrBEl4Eoqpi4ZIrfbdglyrADqdzrT49i4vL/NBBX/84x/R0rKV53zdddfh9ttvx0c+8hEsLS1hfHwc+/cL95EMx64lgGq1OumKlBCIRKK0tkyCI90ixY+Fb5um6ax5AAJnq44cbDYbBgcH0yKo+e7zU/hD7zK+e3s7Wko0eM+ZwPIGowRyz3rUv7M4/fjsX0bw+esbeaNoh5fC7Q8dx8ffVI/D9fnYZ2DxQDuJi/a3QRPnQYAkSVxQIceKT5zyQh8PXAVweXkZMzMzONjdKfjJMBlEu1nmCvmLhEjVQb/fD6vVirKyMvj9fv41u/UGlWvgiARXHXS5XLBYLBgaGgLDMPzsYC5UB7P1EDxhduPR/lXIxSQ+eEk1gK2knGW7D9UJPiSuu2kYfAzi6bqkIhIkQSScX11tVOLX7zqbmsT50wXH1JEkuTX/qTdAq86Le83nWhUtEeQaAUxXDNzHP/5x9Pb2giAIVFVV4fvf/z4AoLm5GbfccguampogFovx7W9/O6XPv2sJoFKpzFiLFkg9Gi0YHJkSGumWLn+8RBC8SCwtLWF2djZtKSQsCzAsIDmjZKsv2Fod95VqMDlpjvp3g8t2TFvcGF1x8rODFMMgQLOYMLtQhA3Y7XZcdeEBQfFLJEmiSivGT97RlvJnigeCIOBwOMAwTMYNvTmyGb7Qp1vskUmQJAmv14uBgQGUl5ejsLBwR0yoE0GAZnB8hYJx3YWaOPOpuYDwcyQ4BquyshIURcFqtWJ5eTmkOmg0GndMrJTMOUszLF6Z3sDeAlXMZCAODYUqPPS2fag0nhWMnZyzYWzNBWOHFBq58Gv3xTkvJnxWvPuC7aM9wWgqVuOv9/QIft9YIElyW0xd79QK/uOZQRypAJpLdbxhcaR1cjcTwFzb93RVAH/xi19E/d2DDz6IBx98MOVtALuYAGb6ZpYuEcjCwgLm5+fR0dEhuAKUbQ9CDizLYmRkBF6vN62k5S1dpaAYFnvD1HSxRBlWlx8VegV+9a5uaORisCyLF8bXUZOvwl/fvx/9/f1g2by41VQAsHsCUMnEvDdfJuD0UTg2vYEL6owgcTbZQ8j+pYpIoolMiz3SDbvdjqGhITQ2NvKpPfFmBzNBBm2eADRysaBjRhIEiDP/LxRuPw2JKPHKTzYgFotDLEq46uDg4CAYhoHBYOCrg9l4mEiWADIsi/kND1iWFUQACYLYZiLfVaFFhUGREPkDgEOlEjTvzU/ob9INmUyGytIimAweHOquRB6xVVVfWFgAAP44cjF1uUaiEkGuVQB3UwwcsIsJYKaRKgnj4r1omsb+/fsTOkl3ggD6/X643W4UFxenNO8XCRq5BMMrDvzjtBmXBcWmxSKAP315Fp4Ag09etQckSYCiGRyb2cSpGQsO5G1FuhlNhXH3008x+MVr81DJxLipRZ+x2bIVmxfzGx6sbDiwODGMkpISwfNAqSKcAHJEKderfhzMZjMmJyfR1tYW8SEpWybUVpcf/5y0oqVEIyghRkQS6C4SC54lZVkWz42tQyYmcXnDzhh/Cz0folUHl5aWMDo6iry8PJ5IxKsOMiwLj5+GSibsdvPxP47gH+MW/PLN8a/vSJCISNzUXhwSdRgJyzYvBpcduHRP/rbXyiUilOsTtxMzyABjXuqzlA4vBYphoVfG72xEgkxM4j+v3XPmQUMBrVaL6upqPr0iOKZuNxGWcOQaAUxXBTBbOEcAoyAVEubxeNDf34+ioiJUVFQkvIhlmwByLWqZTIaamsheU6ng9IodvfM2nCrd5Akgw7BA2NxhMN5xqBKbngDIMwuzWETipiY15qYn0NzcimemXJgZmsL7L6qGXBJ9AZCKSRyo1qPCoARJUhkjgDX5KijhxfTYIJqbm5GXlxdR4p8JcAQwl+f9IoFlWczNzWF9fR1dXV2C2vhAbBNqIPnqoFYhQWORGiXazIghCILAvlJNiNI9m0hFVBFeHXQ6nYKrg/v/+yWwLItXPnq+IPPmf4xbwLJbwWjJ7q+Q7YysOrFq94FhWYjixLAJRbqEKz99dR4Uw0b1/osFimHx0T8MQyYm8Z1bW0N+F5xewR3H5eVl2Gw2nDhxIqdmQIUg16qXLpdrVxHqcwQwCpK1geGC3IMTKJLZdrZUkIuLi5ibm0NHRwd6e3szso1CjRyFGhlKtFtP1INLdrz/1304XGvAdcWRP6cxTwrjGdd7zuh7fW0Nh/b3QCaToa1MDIvLH5P8ceiu3DoOHg+TsRbw0tJiiPk0N3uXDXBtnN1E/jh7IYZh0NHRkfQiHs2EOpgMCrWZ2ZpPzezTezJVpVwDQRBQq9VQq9WoqqpCIBDAxsZGSHWQUxZLpVLcf0kVfn1iSXByx7GPXwAAGBsby+h5fHG9EQwLiONUChNBugjJDW1F8FHC7wE2TwABmkV+nhRiksCVjaaI2ejB4I4jd83U1dVhY2MDKysrGBsb4/0jDQZDTmdP59Ja53Q6zxHAbCDTBz1RGxgu0s1sNqcc6ZYNEQh3A/b5fCHzfpmwXqgtyMPf7j3Ezz1Nr7shIgjolVIwzJZFzJPDq7h0r4lvE/Uv2vDMqBnvO1yJ8dERiEQidHd384trrUmFWlNiN+twpXM6wLIs75MYbD6diOm01eWHXilJ+nsnCAIURfFVr1xaECOBoig+r7uqqipt+xvcKpZIJNtsZnJRSJJNZMpWRSKRRK0OsiyL800GXPf2hoS3n2kbGJIgkEbuByB9+5zog8K3X5gFRTP4zJF6EASBW7qEe8NxFfNo/pEjIyMhMXU6ne7/3LUjFOdmAN8gSKQNy6WRyGSyEJKSjW0nA5/Ph/7+fhiNxpB5v0zZz5gdPnzzH1P40CW1MOZJce2+Ily7rwgA8PLLZsxY3Dg+s4lyvRLt5Vs+ZWOrTjg9fpw6cQLlZaVpMU9OdxJIIBDgrX3a2tq2KSyFwOzw4U3feBn7q/T4/tvaE94HlmWhUqnQ39/PL94qlSpnSSA3HlFVVYXCwsKMbiu46uf1U3jmtBn7ivNgyttqNeeiCTXNsPj7qBlVRqUgf7hcQ6TqYPDMmVqt5tvF8Vr+0ciUN0Djkq+/is9dvQdXNmZ/ljIWdsq8+vbuEngDyc0cR6pahqfLcNnT6+vrmJiYgFwu549jOqJX3yhwuVwp26ZlE+cIYBQIJWFcpFs600gySQBj+ftlKirN4vLD5aOw7vLzbd1g1JlU+MAlNTAGpXNcXqNCsWcGjQ2NMBhCzaBfmrTAqJKiIYGMTmD75+udt2Fq3YUbOxI/bi6XC319faipqUFRUVHCf8/BqJKi0qDAOw8lTnA5IUR9fT0CgQDW19cxOTkJt9sNnU4Hk8kEvV4fc0h6YNEOjUKMSoMwIQPDsvjRS3O4oa0IBQIUlsGw2WwYHh4OUfpmCyRJgmEJ+FgScrk8YnWQZVmIRKIdrQ6SxNYMl9Wd/ti2nSAn4TNnDocDFosF/f39ALYrUoXsL8NuzRD/ZWA15whgOBiWhdtPpzz3ObbmQk2+Mmq7OhVTeyFt6+DsaWCr0mW1WrfF1Ol0upwSZWQb6fIBzBZ2LQHM9EImxDJkZWUFU1NTaU8jEYlE8Pl8aXs/DsHzfpHUlpking1FanzlLa1Rf0+SRAiZ4KxzuHm6YDAMiy88PgYxSeDP7z8Y/lYxserw47UlH7oZFiKSwEceGQBFs7i+Lb5i8K/9y3D4aNzWU8bPeUaL8ksEJEngT/ck9jkiiT2kUilKSkp49fHm5ib/tC6TyZCfnw+TyRQymsCyLN7+01MgAPQ+eLGgbQ8vO/DN56awsOHBf1zbIHifV1dX+SzpnagYSMUkX3UG4kfUcS31bFcHCYLA1S2ZqYymayb1k4+O4skRM45//IK4100wCIKARqOBRqOJqEhVq9X8zJlEIolKAJVSEV47MyeYCv46uIq/Da7hm7e0pHUOENiq5IpIArf86BQcPgqP3t0taF45EibNLnz8jyO4qsmE9x2uTOt+Alvnf6KkTalUQqlUhsTUWSwWTE1NQSKR8MdRqVRm7F6dixF2LpcrI8lkmcKuJYDAzoXGMwyD8fFxOJ1O9PT0CFYvCkW6K3HR5v0yvd1EEbyf0axzSJLA/97UDK1CAo+fxi9fm8eVzQWoEFDB6l+0Y9nJ8Ivzb9/TA4vLL+gm5glsfS9zc3NYXl5Gd3f3jkRnCVH6kiTJG78CW0/r6+vrGB4eRiAQ4JMgtFotvvqWZuQnkIvcXKzGN25pRWeFVvD+zs7Owmq1orOzM+3XSjoQy2bmjTY7mI6b8ZMjZrAsEiJ/kRCtOsj51VEUBbfbnbGRhv95egpMmu8fBEHg2MwGBpYcuK27FO87XIGHX19JmvwBW9W9t3aV4LK9mYmRTFW4wqXLcOuN1+vlyaDH44FGo4HRaEwqpi4Wck0BDJyrAL7hweXj6vX6jJn8prMS5/P50NfXh/z8/Lj+fjtJALnvNXwuMRKaireqbk4vBU+AhsXlF0QA39RUCMXGJK9GNKllvFHsqt0HU56Ut50Jx00dxRgZGcHmJo2enp4dWXiSTfZQKpWoqKhARUVFiJ/byMgIjEoVCjQmBAJKQeSMIAhcItDolmEYjI6OAgDa29tzbrGOhmg2M5FMqHcT0tUCPvWJw2nYm1CEVwe56MyVlRVMT09vqw6mA3//4AHQDJv26l+BWgap2MX7Pabq+SgiCdzWnfiYSoBmML7mQlNx7IpUuomUXC5HaWkpH1Nnt9thsVhCYuoMBgPy8uLH1GVzv9OBczYwb2CkMx83FtJFALn93bt3Lz+7kY3tRsIzI2so0SnQGGExcjgcGBgYQF1dnaCoPA55cjE+eGmt4NeLSAJS0fYFZ9Xuw6N9y9hfpedFKMHgyGl+fn5aVauJIF2xbsF+bq9MWjC0ZoPC6cb8/Ov84pwOIUkgEMDAwAAMBgMqKyuRe80aYQgng8DZ2ctAIACKohAIBCASiXLuZrSbIZVKIZPJUFdXB7lczpOIhYUFEATBzw6mQiIkIhIpFOaiosqoTGkmL114tH8V/xiz4ONX1KLCEH3sgmGYjEVVkiQJnU7Hz/z6fD5YrVbMzc3B6XRCo9HEjKmLhVwzgQbOtYDfcOBuuPPz81hYWEgo0i1ZpIOIxZv3i4RMVQAZhsVvTy5CKibxrVtDc3g5orBv374de3Iy5UlxqMYQ0VaGE/kkSk7TieBkj1gkw+z0gSQIGFVSuPwUbvjecfzntQ04WB3Zj7IyX4UND4W99YUAauH3+7G+vo6pqSm4XC7odDrk5+fDYDBAJBLBTzNY3PCiyqiIedPllL7V1dUoKCjA30fNuP/hQTx8VzcaExTupIINtx8nZjdx8Z78tESvcd89SZLw+XwYGhriHwhomgZFUXjLj/uwp0CF/76hIS2EcH7Dg7kND86r1qf84LFTCtVkwbIsX2nVarXQarcezvx+/zYSwVWVMpm5vZPwUwxW7L6YRC4cVzTko0gjQ7k+tiVZNitpMpkMxcXFKC4uBsuysNvtMWPqYiEXCeA5G5gsItMzgCKRCH6/H+Pj42AYJuFIt1S2mywR49pufr8/4TzfTFUASZLAf1zbCKX07HfHsiwmJiYQCATQs/8AHh+xoKuS3JEnZ5Ik0Fq6XcyxtraGiYmJHSOniSZ7vDRhBUEQuL6tCG4/DbPTjz/3r0QlgCVaOUq0Z28O0YQkk5OTkMlksBFqLHrF0ChKQhTbwdjc3MTIyAiampr4G7ZaJgYBQJrl/Ns1hx+bHgp+iklr9q7L5cLAwADq6+thNG7NZXFCkmmLB9MWD750LZ0Wm5mBJQe8gezngucCohFWqVSKoqIiFBUVgWVZbNps2DhDCLn51/z8/KzbIWXyXvS3wVWMrblwz4VVUfOJHz61BC/F4I79ZQC2km0uqDVEfG0wdqqVGkzso8XUxYobzMUW8Dkj6DcYTp48idLS0qQi3ZJFskbQ3LyfyWRCY2NjwvubyRnAoiCiQVEUBgYG8IWXnQhQJM67gMTgkgN2L4V/OS/9KrdEwZl6r6+vo7u7O27Waab2IdFkj4v35vOBVqY8GV752AVJk65IQpLlVTMCLjPGB1ZgPdMq1mq1/L6trKxgdnZ2m9L3QLUeA5+5JKn9SAV7ClSoM6mSFitwYqFgbGxsYHR0FC0tLSGtHu5GNPzZrc+ZiM1M36Idd/y0F797d+e29IYjTSZspSamvvbEqwBSDAsRkTvJCkKytN1+Glf/aAgHq/X46k3d8Pv9sFgsmJmZgcvlymp1MJMV1ssaTKgvyItK/gDg6dF1sCx4AigUuUKkIsXUBccNhsfU5WIF0O/378j9IlmcI4BRYLFY4HA40NzcjOLi4qxuO5lKXKLzfunarlBwi6Pb7UZfXx8qKyuhVG0NCItJ4IEr6iATGBWVSdA0jaGhIYhEInR1dWV1YaQZFn94fQnX7SuCiGATnvfTKUJnaBRpHHBSKpWora5EbXXlNiFJXl4eWJZFIBBAV1dXzrThCIJAhJFPQXjk1BL+7a+n8ed79vOjAZyVTUdHR9ykn3g2M8HVQZdv65pz+bdfe6l8hkTxl4FViAkC1+7LrEG3UAghVErpFqHeeybCTyqV8i1GhmF4ZTFXHTQajTAajSHVwal1N54eNeOu8ytAJkDgXD4KN/3oFP7lYBne2lWSUQKokYvRUhJ9fIJlWZTrFWiN8ZpoyBUCGIxwQ3GKorbF1Mlksh11rYiGXPsuYyE3VuokkYmLjWVZTE9PY319nV8oso1EiRjnm5fqfGKmKoB+isG//WUEpXkEOpQbaGlpgVarxc/fWYKTJ0+CYRjkyXf+qcnn86G3txfFxcWoqKiAx09DkeJuJXJTeHxoFV96YgwUTeMtHcU5G+sWLCShaRoDAwPw+XwgCAKvv/467zmYy4kk8cC1uPNk4hArm2QIbjSbGY4U9pTn4eTHD/HXX7puIHNWD/LzpPzoRbxzsUgthVxCYnTFGTdHFgAcXgqbnkDG8o2FXDsEQeClB86L+DuSJPkWY01NDS9AmJmZgdvt5quD//P3ZQwtO/GWjuKoow2RIBVvecUubnoBRCZS7/v1AGRiEl+/uVnw+yYDbhxqaNmBG9oSM6bPRQIYjkgxdXNzc9jc3MTx48dzIqZut83YArucAKYbXGtSLpeju7sbo6OjGc/kjQShBDCVeb9o280EARSTgNvtQoD1ofvC/SH+eenYJjd7I/Tii3Sh2u12DAwMoKGhAUajEQ+fXMQ3npvEQ3d0Yk+SkVzcoix0vy7dY0TgSD0u3ZsfsogxLIs/9S3DlCfD4brMeIElAy4Kz2Qyoby8HARB4JVJM56bWUeHbRJej3ubkGS34JK9+Rj67CV81jNN02mzshFiQp1qIomPYvDK9AYK1VJcvGerIxDvXDxUY8D5X3kZbj+Nf9x/EFpFbFXm8+MWuP00ijvkabdSAdJ/Qw0WIATbk9xW5YO1RAqXZQUy1hDy4BKgo8+PSkQknvzAgZj7u7DpRSqfgGFZTK+7BeWef/bonqS2wdka7RZwMXV6vR4qlQqlpaU5E1O320jgOQJ4BpEi3TKdyRsNQk6gVOf9IoEkSQQC6Y2gomkaw8PDuKtNiaam7TnJqVQdzQ4fjCoprvvuqwCAv957KO7fRCJlXKJLe3s7X/HdW5gHMUmiUJO82bPQig437ychgWv3FW07lluh9QTkktxZpN1uN/r7+1FbWxtiiaSSS2HQ69DedmZAP0xIwsVJZXthZlgWoytO1JqUkImFEVGuuqlWq7F3796MLOyRqoMLVhdYNoBCtTRpE2qZmMQle4wxZ8Yi4cdv34cXJqxxyR8AXNaQD5ePzgj5AzJ7Mw22J6mtrYXP54PFYsH09DRvXvzcEvDwwAZ+dmd71Cpn8JxopGv9r/f0ANiaVQwWwc1veCAXk7wPaTQ88voyfn1iCf9+9R7siyBUSweSSQLJBXDfd67E1O2GSmo4djUBTNfiEC3SbacIYDxsbm5iaGgopXm/SEh3C9jr9aKvrw/FxcV8hShd27S6/Pj/js1jX5kWBAhIBA5KBUf8sSyLyclJ2Gy2bYku+8q0eO4jqcVNCVGpCxV73NCW3TnUWOCEEM3Nzdui8PaVarGvdEv9y/m1hSeSjIyM8Ikk+fn50Gq1IEkS3gANmTgzBssWpx+9CzaISAJ7BVR0Oe/H0tLStGV8CwFJkjg+7wAAvLmtKMSEmjuXhFYHw7OahRCqvYV5gr4fYGvGNJ1zppGQrWqKTCYLUcDb7XYUWhZBUxTmJ0bAFubDaDSGRJut2L14x8/78O5D5bilqyQqAZg0u/D0qBnXtBaiTKcAy7K497eDIAkCf7q7O+Z+XbonHz6KQUOSXQgh2I3EBdh6QIvU9QqOqePcDIJj6rjqYLpj6rjUmt2EXU0AUwUX6eZyuSJGuuUiAUzXvF8kpPPzciS1sbGRJwCRkKziWa+U4PxaI/YW5uEv9wrP0iUIgiecXLs/U4kuwduKhGSUvrEwuuLEHT89hSfvOwhDArNMiWB5eZk//+IJIcIRKZFkeXkZo6OjkCtVuPPPFoAgMPDpi9O+3/l5UlzRYIJeFb+yFcnmJZt4U2MBCGJ7q/iRU0v4j8fH8df3daFILd2xvOI3Orjq4I3n63Dj+eCrg1y0mVar3WovKtUgCQJFZ7oE0Qh2gVqGcr2Cny8kCAIfv6IWebL4t9/8PGnCql4OAZrBM6fXcdne2D6Yu5kAxovjDHcz8Hq9sFqtGYmpczqdGfcITjf+zxJAn8+H/v5+GAwGdHR0RLxwRSIRKIragb3bDm7eLxAIZMyPMF0VQM6EurOzM26rL9ltEgSBnqrI/nbxtud2uzE8PIzy8nKUlSW3uArdVrQKYLqSPYLRu2ADfWYoPd0EkGVZTE1NweFwoLOzM+XFMlhIwuXAkoQFV1aJcfz4cb6lk2pcFAeCIGBSy0AzLJ4aWcMVDaaI78v5GIbbvGQT6ghtW5IkQZy5SSvlUvxlyAK1TIRL6vWC84p3Yj5p2uLGyTkbrm4pyHi1MFMIrw7abDZYLBZsTE/jS+dLYZC54HLJo87SqeViXN0SqqwW4s8XDwzLwuzwo1AjA8uyeGp0HU1FeXy7unfBjr8OrMGokqKnUhf9fXYpAUxmv+Vy+bZKb7pi6nZbDBywywlgsosZV52KF+kmFovh8/mS3b2UwS3YmZj3i4RUBRkMw+D06dPw+XzbRCnPj5nx25NL+OpbWkKC0bOdP0zTNPr7+9HS0gK9PnECmQiiVQBZluUfLEiSRIBmwIJN2Sj5rV0leEtnMURpPj8YhsHQ0BCkUina2trSfv5xObB9n97y0OMSSaanpyMmkqSC355cxBeeGMeXrm/EdftC1ZKrq6uYnp5OqrqZCJIlYjd3luDmTm4+mYBMKuatMLhqMkcEI5lQZ9KoOBqIM//L1JxgtkGSJPR6Pb92eL1evjrodDpBEATW19eh1+vT/pDu9tP44UtzuHSPEa2lGnzzHzM4PmvDV29qhFouxm9PLsGglOB/b2xCgGbQXqaB+qIq1JpiV6V2KwFM1QcwPKaO85DkEmYSzZ/ebSbQwC4ngImCZVksLCwIjnTbyRYwNz9ms9kwNDTEq1MziWTbscDZmSmDwYCGhoZtN7jxNRf8FMP7bLEsi/E1F1jEbpOmE4uLi3A6nejo6Egb+Vt3+jBn9aCzQrftd+EVwGgt3wu/+hIA4JWPHeZfO7/hwYnZTVy7rxBigYszQRAQp5mc+f1+9Pf3o7CwEOXl5Qn97ardh5enrLi6tTAhchsvkSQVIck1rYXwUwwuawidnZ2dncXMshkLRAmq/QQyxf/+8PoSKAa4pSu1ucIb28/+fbCQRCKRbLOZ4R42WJbNOgnMRC7u/IYH9/52ED+/sx06ZWL5semGXC5HaWkpSktL+RSLzc1NTE9PQyKR8L6D6WgNcmITitk6hjd1FEEjF8OUJ4XbT6MgT4qb2ovwtWencHrNha+8uVGQnY8Qw+1cRLqJa7CHJNeV4PKngfgxdS6X69wMYK6CU6MCENxC3UkCKBKJMD8/j6WlpazkDwPJE0CHw4GBgYGYebnvuaAK77mgiv/3jMWNX7w2h316BheotwjgidlNuH0ULtyTPmELsHXjGxsbg9vthsFgSKtT+03fP4YAzeLZD58fUtkEQkUgseb9Lt2bD4c3dNRgxuKGO4IxcDbBzcLV1dUlJTZac/jg9tOgaBbSJB/UIyWSxBKSxINGLsE7D1Xw/+bOjUAggH2trVg7bUkoOcTmCUAhFQkmuFqFBJue9CrtwxHJZmZjYwOBQIA37E41om4ncXLOhnWnH2NrLuyv0u307vAgCAIKhQJ1dXUAzlYHJyYm4PV6k1ajvjhhxfPjFnzyyjp86JJq/udlOgX+5VA5HF4Kvzi2AImYxC+PL8Ht3xJTKRO46HYjAcxkEgjXldBoNIJj6s4RwCxD6Enr8XjQ19eHkpKSqGrUSNgpAsgwDNxuNywWS9byh4HkWsCrq6uYnJxMOC+3wqDE9W0lUPmt/Da/+vcJMCybVgJIURT6+vqg0WjQ3t7OxwrFg9Xlx80/PIbv396OuoLon+un7+jE6KpzG/kDzhJAlmVh9/ghJgCZRLTt/PvCdY3b/nan/f6sVitOnz6d0ixca6kmYsZyKggWktA0DYvFguXlZQyPjECpykNRgSlqdmg4aJrG4OAg8vLysGfPHhAEwbdYhYBmWPxlYBUKCYmbOoT93WUN0UdOMgGSJGE2mzE1NYXOzk7IZDLec1Do7GCu4drWQly6Nx9qWW7NFIZXpIKrg+FqVKlUCoPBAL8kD9o8FfLzop+vP3hpDn6KAQvA4vLDoJSAIAjMb3gwaXajQC3FutOPO/eXQSom0btgw/X7EjOD3o3IZhRctJi6J598Ep///Odx3nnnoaSkJKlCzcMPP4zPfe5zGBkZwbFjx9DdfVYZ/qUvfQkPPfQQRCIRvvGNb+DKK68EsBVR+853vhMejwdHjx7F17/+9aRI/K4mgEKwvr6O06dPo7m5me/1C8VOEEAujUIikWDPnj1Z9WdKZB6Ps1DZ3NyMqKAOh9NLYSMoNUBEEuiu1GFuzs5v8+u32skTHgAA6dtJREFUtMJPp68dzMXOVVVV8XF+sYQZwVi2eRGgWAwu2WMSwOp8FarzIz/1cRVViqJw1TdfBUEALz6QmrVMNrC0tISFhQWeMOQqRCIRLyR5+NQiHHYPLspz8y2bWEISbmShpKQEpaWlyW2fJHCgShfz5r3TWFxcxPLyMjo7O/lrNLg6yDAMuv/rn9AqxHjy/d28kCGXyaCIJBL2N0wGTwyb8fjwGr56Y5OgqnCsVmp4Jdvj8WBpdR13PzIECcni60cKo1YHf/z2faAYFjZPAPf+dhCd5Vp8/IpafP6JCXj8NL53Wws+enktFJKt41Zp2Fpj/RQDsYhIKN5uN2GnZhfDY+rOP/98PPbYY3jkkUcwMjKCoaEhXHXVVbjqqqsEiQxbWlrwhz/8AXfffXfIz4eHh/Gb3/wGQ0NDWFpawuWXX46xsTGIRCLcc889+MEPfoCDBw/i6NGjeOKJJ3DkyJGEP8sblgByqkWLxYLu7u6kbmTZJoCcOKWhoQFLS0tZn9cR+nm5xBSlUomuri5BTx5ffnIMbj+N/7qxOcSSILjtHM8UNR4YhgV5ZqG2WCwYHR3lY+c4xLNm4dBUrMZzH7kA8db9WYsbz4+v444D2yvLBEHA6/VCpVLhSHMBSnWZExakAxypd7lc6Orq2lFz2BmLG3qlRJAhMQC0l2qxZJehtjYftbW1MYUkXq8Xp/r6ITWUpezxVx/j4SCdCNAMHh9aw/4qHYo08c8jlmUxMzMDm82Gjo6OiMeSbwETBFgQkEqlfHUwWFDC/W2qN1uWZfGPcQtKtHLBXoM7ia89OwWKYSF0FWZZVvB3pFAoMOtToKvKiCPN+cjPF4VUB7nZQYVCAYmIhEQEyMUkOsq1uLF9q7r3X9c3YNXhg1J69jY+vubCutOH/VU6fOrPo5CKSXzxuoZEP/quQDYrgLFgMBjw9re/HS6XCzfffDMuuugiPPHEE3j3u98Nq9WKiy++GJ/97GejdlIaG7d3gADg0Ucfxa233gqZTIbq6mrU1dXh2LFjqKqqgt1ux6FDW8EHd955J/70pz+dI4AcOIKiUCjQ3b09fUIoxGJx1mxgOH8/zjpldXU169VHIRVArqpWWVmZ0M3z3otrsLjp2eZHlWj6iDdAR2y3rti8eNfPX8ddF1Siy0hheXkZXV1d29ScwZ/R4vTjtoeO4/PXN2F/mKUMQRAQ4i39H38bxeiKE9e0FvHWK9y8n8lkwszMDKampvDWeiNMJm3ORgXRNI2hoSHI5XLs27dvR/eRYhi8MG6BUirCWwS2ZOsL81AfRCqiCUm4dACfqhALawFUlfhTSnvJFhiWxYbbj1mLmyeAz4+tQ6eUoK1MG/JaLr6OYRjs27cv7vrX+6mL+P8Orw6GK4tTqQ4SBIFlmw8WZ2BXEMC/3tMDimEFK5gTrUgdqtGjJv+sSCa4OmixWPhzVa/Xw8ooUVGox79eUcv/vU4p2SaC+c3JJTh9FP48sAaSAC7bG3+cJhfXIyHINfWyy+VCcXExGhsb0djYiA9/+MNwuVx4/vnnk2oNLy4u4uDBsx63ZWVlWFxchEQiCakscj9PBruaAEY6cblIt+rqar7tlyyyUQFkGAYjIyOgKCpk3i8VRW6yiNcejVZVE4JirRzF2u2Vi0TazgsbHjx8ahFHW4q23UBUMjFIEnBbV7ApEqO7uztq1YPbnpeiQTMsFjY82wigUHzlLa2Ysbi3kT+GYfghYW6AeH5+Hg6HAxqNBiaTCQaDQZCfnt0bwIrNl3Am8Y9emkWJVo6jYR5k4eDaocXFxSn7Is5Y3FDJRDDlJU+qxCQJP83gfx+bxEV7jCm9F3C2/RYIBLCxsYHm5mZYNmwQLZoxNbQK+5lWsVAhyU5AJhZtVZnP/JtlWdz3u0EQBND34MX864LnGmtqapK+uUcSkoSTwmSEJLd2l6SUjZsIKIaFiEie4HCVN6FI9OFOIRFFVEgrFAqUlZWhrKwMNE3DurGBn/9jBuzrs7i5URVSHQzHhy+txqY7gH9/bAwX1efHJYA7YQ2ULiRScc0GIvkAqlQqHD16FJdffjlWVla2/c0XvvAFXH/99RHfL9KxiZYulew5vqsJIBD6hUSLdEsWmSaAXFRaYWEhKisrQw5iLqWQsCyLubk5rKysJN1Oj4ZECKBeKUG+SooC9faZKxnJ4N/2i2E06lBdXR1zFoc7X0p1Cjzz4dRm8nRKCdqVW2Q4mtI3fIDYZrPBbDbzVhEmkymmrckL4xasO/2oMiohFQtb8FiWxfdfnAVBICYBdDqdGBwcTEvqBcuyeGHCApmIxFu7k5ur4yAVkSAASFJc4BmWxYcfGUSTnkC33sfPwul0OtRWV4YISUZHR6FSqWAyCReSZBPBs1wEQeAnd7aHtMgDgQBv2ZNOg/NIecXJCkmyOY/225NLkIoSE/akgnRVpEZWHHh+3Io7D5RBKRXBlJ+Pe9+UB5VUDBHj53Nu/X4/dDod/BI1ivP1MOTJkCcTI08mhlwiwrHZTbx9f+zrMNeqaLsZbrc7qhDy73//e8LvV1ZWhvn5ef7fCwsLKCkpQVlZGT/nHPzzZLDrCSCwdRJzNh9CBAlCkcnSePC8X6Qbb64QQM4EmCAI9PT0pH2xSER5rJKJccfBim0/56q+sWxoOAidAUwUQpM9CIIIMR/1eDzbbE1MJhO0Wi3/Hpc3mGD3UoLJH7edv7x/P2Qx/sZisWB8fBwtLS1pMTAlCAJXtxRCnsB+RsOdB8tx58HEfAcjgWVZPDu6jmcB9D140bbzN1hIwqn7zGYz+vr6AMQWkuw0uoK8J7mHyerq6rjXQKqIVB3kCCEQ2YQ6ESxselASoS0/Z/WgUCOLeU4HI18lRaFGOIn3UQxW7T5UGBL3lwTSV5Hy01vOAcHCk7Nzn2I+55arDv7vMzNgApO4Y5+arw7+29E9glrX5whg+uB0OtNqA3Pdddfh9ttvx0c+8hEsLS1hfHyc7xKq1Wq8+uqrOHDgAH7+85/jvvvuS2obu54AcikZsSLdcg3z8/NYXFyMGZW2Ey3gcHA3laKiIlRUVKT03a45fPjsn0dw/2W1aCg6W50NrgB6/DRmre6Q3wdoBn0LdnRVaCNu32w2Y2xsDPv27RNU9c1E8kh4skciUCgUKC8vR3l5OZ+Pu7i4iJGREajVar4aVZCEQCaWWGBhYQHLy8vo6OhIa0XXGCeCzkfRePjUErordCHHORPg2qG/uKkUe+tq4h6bYHVfTU0NZs0O/PX1OXRZJ8H6tzJgudZ9Lgyfc3A6nRgYGEBDQ0PG023CEa06yJFC7r9FIpGg2cHRFSf+5Zd9uLGtEJfoz17vdi+FZ06vo75AJThG7cqmxCx3TsxuYmzNhZs6ipNSGTMMk3JEIgC0lWrQJsA+SSTaqg6+91IF1HIx8kQ0P6YTCASg1+vBGAzQ6XRRv/dzBDB9SDYK7o9//CPuu+8+mM1mXH311Whvb8eTTz6J5uZm3HLLLWhqaoJYLMa3v/1t/jr77ne/y9vAHDlyJCkBCPAGIIDDw8Oorq5Oyqg22+Dm/WiaRk9PT8ybSKqxbKkiXoUyUXA+Vp4ADaePwnefn8ZtPWVQBxGyLz5+GqfXnPje7e38TN3vTizi4VNL+Pz1jWgpObsosiyL2dlZrK2toaenR3C7Lt0EkKt8pCPPNzwf1263w2w2Y3Z2dmuxP9MqTsUUnGVZTExMwOPxoLOzM+tERkQSYFkgQGd29igtc40iETRaDZqai5AnFfGt+8nJSUil0rit+0xi0x2AO0BDyXoxMjKC1tbWtFRxvQEaAZqNmEcsBJGqg3MWF1RSGhr5lqiOe00k4lFrUuKSPUbc2FaIzXkb/3ONXIxL9+ZHHP9IFzortCjTK5K2mMkGmaIZdpslTa3pbNVJqVSivLwcNE1jY2MD6+vrmJiYgFwu56uDwcK43UoAc3F20eVyJTV69uY3vxlvfvObI/7uwQcfxIMPPrjt593d3RgcHEx4W+HY9QSwo6MjJ0+GcMSa94sEkUi0YznEnCI5nQkkxVo5PnJ5HfYUqGB2+uHy05izuvHr12ZxbRXQDOADl9Sgd8HGkz8AuLq1CHqVBA1BAojgtnR3dzcIgsCsxY1KAZFT0YZoE0WsZI9I+O+nJvDPSSv+9L4eQXNQBEFAq9XyYhuv18t7Wvp8vpBWMUmS+N3JRQRoFm/bH53scBUxlUqF1tbWhAirn2Lw25OLaC/ToLU0MQFQMMQkiTsOpN7ajQW3282PBKTyYFhpUOKOA2fPqeAM2Eit+2wKSR4bWoV104FutS2t2cXn/+8/wbLAyU9emPIDDUmSYFgW/5jchExM4taukrizgxLRlm0JRVGwLYRuvzLJ1qxQKCSilLaRaYX/wKId//33KXz2SD3qC2K3GkUiET++wLIsrywOrg4ajUaIxeJdSwBzrdsXawYwV7HrCWC6buix3j/Vp6SNjQ0MDw8nVE3biRlAhmHg9XphNpvR09OTlnYGh7/1L+Nrz07if29qQVelHp+7pgHT6y6YXQFMWrdeU6iR48qm0BuZTinB0ZazrvacUXZwW/rhk4v48cuz+OINTego18XcD5IkMbDsxE/7R/GpI3sTiv3iwJG/YFuMuJ9/cBUsm/wQvFwuD1UGWq28cCEvLw/WDRFUedFvCj6fD/39/SgtLeUHhl0+CiqZsGPMfU9Mjj9r2Ww2DA8Po7m5GRpNelNIghHcug8/HtkQknQYaMx7Hejq6krbzDMA3HNhFdYcvrTdXEmCwJVNBciTiQTNDnLXUy7e4ONB6H3C5gng809M4BNvqo07MhEMlUwMMUlALom/jeDvjyAIKJXKbdXBtbU1WK1WsCyLpaUlGI3GnDZ+D0aueAAGI9kW8E5i1xPATIMjYskSQCHzfrG2my34/X709/dDJBKhpaUlreQPANacfngDDNZdfv5nVUYlvvPWZkyNn476dzZ3AD/45wzed2E1WL8bAwMDqK3bg18N2PAWtQcVBiUu3pOPdacfjQJmykiSxM9OWmD2Ag9cwSSUlwmEij2Ekj8AeP4j50f9HcOyCRFDrh1sMpn40HKl0gyLZRUnTpiRn58Pk8kEpVIJgiDgcDgwNDSEPXv28F5jL09ZMbTkwC1dJYLMlkUkkfHKXao3/bW1NUxPT6O9vT2rbdnw4+F0OrG+vp4RIQnLspienobf6cBl56XfrPs951em9f0AoFgj2/a5g2cHKZrGb04sodogR3eFBgzDwO/fWicy3aKkGBZHv3MMt3QW4z3nbReYhcMboPH73hVcVG9AmS70HBN6/g6vOHF61YnBJQcuqlZBPPl3iCaeBMHSoKouBrXnKCDdTiRq8pX4yR1tcd9/fM2Fn746jw9dUh1xdji4Ori5uYmFhQVQFIXh4WFQFMVXB3PZFikXW9eBQCDnnAPiYdcTwEw/JXJELNGnbIZhMDw8DIZh4s77RdtutmYAHQ4HBgYGUFdXh7m5uYxs97p9RSAAXFx/tiVHEARUMgkQpYL7neenMG12Y2LdhQY9AWNgDe3t7djwk3hubBIKCYl7LqqBSS3DPRdVR3yPcJAkic9eUoCC0oqUyF86Zv6ALd+8Z0+bcX1bcULVAA7BoeW1tbXw+XxYX1/H+Pg4vF4v5HI5nE4n2traQuZTGovy4AvQODazgQf/PIrnPnweVNKdXQ46vvgCCAJ4PciYWCjm5uZgNptDIs92AsFCkurqavj9flgsFj6RJBUhySOnlvCfj53GT64vQMcOmnVvuP3QKiSCHlrWnX5c/e3XcO/FVbgzygOEWCQCzQDzNj/Ol8ng9/sxNjYGk8mU8bxiktiaq/tD74ogAsiwQIBiYPdQgC7sdwJJyYEqHX789jYY2A0ofncLSOfKVheLICBbOgHpyR/Ac/2PwOqqkvpMBCG808CyLGQyGZ+vTVEUNjc3sba2hvHxcSgUCn52MJeqg7lYAdxtFWvgDUAAM41kKnGJzvtFQrZUwGtra5iYmMC+ffuQl5eHxcXFjBBAk1qGGpMKNi+FgiB31ViijDpTHhiGxZvrxRD7N9BxxuJHpQK+d3sb8pMgTCRJQioikJ+guXCw2CPWIr/pCYAkAI1cGAlRyUSQismErFNW7F4YVFJIRdv/RiaT8QH0s7OzWFpagl6v52f/uCd/vVKKS/aa8K9/HAbDApl81lh3+jG+5sTBan3Ma4Egtv6XCFiW5T3ROjo6BN2Al2xelEQwJY8FhmXx2vQG9hTmJUTUpVIpiouLUVxcDIZhYLPZsL6+nrCQhKZpPHpiCgDQuHevoDVlZNmBE3ObeGt3acRzJRnYvQFc8Y1XUaFX4A939+B3Jxchk5C4fl9k032FhASI+H6O7zi0RQ79fj96e3tRWVmJwsLCEBPq4ESSVGxmgkESBJ754MH4LzwDpVSEdx6KTGSF2sCQBIH8PCnkf/4MSMcS2KBqHwsAXhvkj98Pz61/TPyCAFBnUuE/r90r6LXhpFUsFofMDrrdblgsFgwPD4Omab46qNFodrQCl2sVQJZld4UWIRznCGAciESihOLguHm/xsZGvt2W7HYzSQC5rOSNjQ10d3fzpetMEc8Zixuf/NMwusp1+PbtW22MZZsXXj8VlQBetteIAv8SZFIZ9rZ2hVzwpbrkWnyJ+gAmKvb4Q+8ySADvPBS/mgAApjwZ3r5feGvV5aPwaN8KqoxKXNkU2e8tmBQdOHCAN7+O1Jr8zBUV+PINjRl9ej02s4H5DQ86K7SQiaM/tSda+ePi65RKJVpaWgR9hieH1/CxPwzjC9c34NrWoriv5+CjGPQv2uHyUbi8MTmfPZIkeSFJfX19iJDE7/dvE/ZwCAQC6Ovrw5eOViWkaLa6/QjQLEQJin1i+U2qZWLsKVDhngurAABeioGPin49qWRivPbxw4K27fF4ePEONysd3CqWSCQp28xkEtwaIQSEbR6i5dfBSiLM7UqUIB3LIFdeB1PcmdA++CkGn/zzKG7pLMYBAelGsYgUQRBQqVRQqVR8dXBjYwMrKysYGxuDUqmE0WiEwWDIenUwFyuAwO6rAu56ApjpL1wsFgsmRHNzc1haWkp43i8SMkkAg7OSOzs7QxaATPjkAVvJDiQBqORnL9qfvTIHlmVxoWbrcwZohs8K9nq96O3t5YUP6UIiny9R8gcAVzaaMnpOqmRiXFSfj1Jd5AoWRVEYHByEWq3Gnj17QgbBw1uTXCXK7XZDr9fDZDJBr9en/SZ6RaMJngAdk/wlCm5mtaioKKHzo7NCi/1VOvRU6hLankIiwq3dpQmPDcR8zzhCkvz8fKjVagwPD6OmpgYmU2K+dufXGnF+rXALJ7s3gN8cX0RHuRY9UcgDQRD41bu6+H9Ha+sGw08zcSuQLpdra00qrMZ1PxnBL97ZgZr87eQo0ybUqSCRqhRpmwNLiiNX+AgCYFmQm3OCCOBTI2b4KAbXthaCIABPgMFrM5uCCGAiREosFofMurpcrh2rDuYaAcy1/RGKXU8AMw0hRCzVeb9kt5sM3G43+vr6UFFRgdLS7TFBmdpuqV6BL17fhOYzXn6vTlvRt2DDBy+tAbtiweKmB794dR43dZbAJKUwNDSUchU1EuLlHXNIdt4v2cpkImgoiqw083q96O/vR3l5edwcbKlUipKSEpSUlIBhGN4zjHuy59pAkZ7sN9x+kAQhSDwCbGWqjqw40VAoSijNJBo4m5fa2tqESZEpT4Yfvb09qe0K/bzJIFhI4qNoPPTCJDTrayhmR6BUKuFwOCCXyzOaSKKSiqGUiVCmT985PGNx460/OokPXFwVVURks9kwMjKClpYWDJoDYFgWK3ZfRAIYjHSbUKeKRERMrEwLgmX42b9tIEmwcmF2SwNLDrAsi2tbCyERkfjOW1sE73OyrVSCIJCXl4e8vDxUVlZGrQ5mSgmfay1gl8uV1hSQbOEcAYyDeIQonWkZ4dtNdyWO84FqaWnh/eXCkakKoNnhw3Nj6yg3KGFSy1ColiFPLsaeAjVOrwB5MjEUUhF8ditGzItp9SAMhpDPlwmxR6bhcDgwODiYVBoESZL8Ys092a+vr2NgYAAMw/CqYo58XPGNVwEAJz5xoaD3n1534x0/ex0X1hnw9VtaE/5swciWzUu6YfMEBBPIrWoZA8rrwoELD0AqlW4TkuTn58NoNPLkh2ZYeAI08gTa+kSCiCQSGkcQAoNKApIMNSvmML7mAuF3Yn1hGm1tbVAoFDiYB7zyMWEt43DEqw7GM6FOBt4AjfE1F1pK1AmREqagCazSCLgtgCSMcNN+gBSDLj8k6L0+cqkwAVzE/UgTkYpWHRwcHATDMDAYDHx1MB3raa5V3NIdA5ct7HoCmC0VcCSka94vEtI5i8eyLObm5rCysoKurq6YprGZUh+zCFWmVeer8MO3d/D/1sjFOFJGw2m3pd2DMBjxZgCjiT18FI3fnlzCVU0FScWyxQLDspg0u1BfkJyHFJdO0dbWBqVSCU9gK27t2tZC6JWJPX0HP9lXVVUhEAhgfX2dJx86nQ73HCyEViN8X6uMCrz7vApct0/4zF0k7JTNS6roX7TjxQkLbmwvRnEE8QnLslhz+FF4Jv/WbDajS2VD23lnr9VIQpKpqSlIpVLk5+fj6VkKAZbEu8+v4McocgEauSQioaMZFn8+OQ23YxP/esP+tFeJolUHY5lQJ4PhFSdem95AgVqWmI0RQcJ7yX9A8dgHAJ8TrPTMw27AA4Ig4L30PwGxMKFSKvfAdMXXBSNSddBqtWJpaYn3LeUIYbLHPdcI4G70AATeAAQw04hEAFmWxfz8fNrm/SIhXcSWa0+zLIuenp64C12mRCAFahn+7ZqGiL9jWRavv/468vLyBOc5n151Qq+UJEzGwiuA9BlnY5JAzHk/T4CBy0dj2eZNOwH8zvMz+NXxRXz3tla0lSWWssHZnwQbAju8FFw+GmaHP2ECGA6JRBJCPjY3N3FYtA6rdR6vv77Gq1hjPVQQBIEPXHy2SpFINYzD/Pw81tbWsmbzwrAsRlecKNPLBSu6o6EmXwm7J4D8vMjH4otPjOPh15fxu3d3QeHfiPk5owlJKkkrFm0+TE/6kZ+fHzP/NRewvLSIfWoP9l/YnTAJeN+v+jC84sTzHz5P8DoZXh0M/h9H3JIhg60lahSopShQS7GUYDWNKe2G54afQHLi+xDP/RNgWdDFnfD3vA9Mydk5y94FO5qL8zJC7LPRSg2PuHQ6nXx1kGXZkNlBocczF1vA5wjgGxDhkWzhhCqXnkLCESk1Ix4y1QKOBrfbDZfLherqaj6hIh4YhsUn/jgEiYjA7+7an9D2wmcAr/n2K2BZ4G/3Hogp9tApJHjf4eQsfeLhpo5iUAyLpmLhOZIMw2BsbAwURW2zPylQy3D34UpBXmAUw2B42Yl9AsLnSZKEwWCAjZHDqCtBiYrA+vo6hoaGQNM0jEYj8vPzYy7kw8sOPDe2jhvaigTNS7Isi/Hxcfh8PsE2L+nA/3t2Cj99ZR7XthbivkuqUaRJPmotTybGBXXRxRhvbi/G6KoTjG0FVo8L7e3tgteVSEKS1dVVnD59OsT2J5cMamdmZrC5uYlLDyWXRT2y4gTY5B+SOTLIsCxwxr4jmBBSFAWCICASieKebxIRyRtCh5OSx4fW8KOX5/HzO9uiJu4wpkb4jvw/+FgWWx8qdHunV5348lMTuLa1EG/r2T6znSqyTaSCxWhch2FjYyOkOsgpi2Ods8l482YS51rAO4RsqIBdLheAzM37ZQI2m42fCRMaPwdkN4HEarViZGQECoVCMPkDAJIk8PE31SdViQtvATcXa+A6Y0UTb94vU8e7WCvH/ZfWCH49p+LW6XTYG8UTTqgR7DeencavTyzih29rQ3u5sOrjLT86AQA4/okLoVKpUFlZiUAgAIvFgvn5eTgcjohzasBWnuu+Ug1MAo4dZ/OiUCgE27ykC7d2l8Ltp3FejT5q5S4S/j5qRqlOLiiVhkNDoQqf3C8HGAr7UjB4jpdIYjQaQ2Y5k4HdG8CbvvEq/t/NLThYndisKUfm/X4/9u3blzTxiJWqIxRPj5jxxSfH8ZM72lFlVIa0ioPbxIm0isNbwHNWD2iGFRY3SRAAtr+uzqTCOw+W42CVLqHPRzEs1p1+FGliX2c7XUmTSCQxq4Ncq1itVod8t6mkc2UC50Qgb1BwhCiT837pxtLSEmZnZ5MSUmTSgHrd6YOYJKFTSrCwsICFhQV0dXXh1KlTCceAHapJ7hgEVzhZlsWXb2jYVWIPTulbUVGBoqLUZuoA4Pb9pZBLSDSXCCcs37m1dZv3m0QiQVFREYqKisCyLDY3N0Pm1LhWsUqhwOEY1TAOnPddojYv6UKJVo5PH9kT93WbngBOzW3iwnojCBD42B+GQRDAqU8K8zSkaRoDAwPQarWoqqpK2zkYyfZndmkND798Gnvy/DDodREJejy4/TRohsUrU9aECCDDMBgZGYFYLEZzc/OOX2sauRgkgW22Plx1UCwWJ2xCHb6G3X24EncfTi1aT0QSuKopMaU7ADz08hzG11z4zJH6mOMWO00AgxGpOmi1WrGwsACHw8FXB41GIxiGyanu27kW8BsUJElic3MTm5ubcQUUmUBC1gIsi9OnT8Pj8SQtpBCJRHwOZ7rxn4+dBkkA722RwOfz8S10ri2bjZsCty2WZXmD71xZAOOBU8A2NjZCp9Ol5T2LNHK8X2CMHodoHnEcCIIImVNzu9284XEgEOBbxVqtNuIx93g86OvrS8rmJdsYX3ViaNmJtjItjCopvn/7PsGV6UAggN7eXpSUlES0ZEonpFIpnCI1XLIA6luKIGW8vLhHIpHwreJ4D4xFGjmOC1R/c6BpGoODg9BoNDFJbjwT6nTiQLUez3zovJiviWVC7fEFIBWTITYzQO4YAb+5rQi9C3Zo5LHvAblEAMMhkUhQWFiIwsJCPvPcYrGgv78fHo8HFEVBLBZvqw7uBNxu9zkCuBPI5IGnaRrT09Pw+Xy44IILsv7EwVWrhGyXq5jodDq0t7enNB+TqRnAt3WXYG56AlKpCQ0NDfw+ctvMxkJEEARomubnfGJ9TxaXH3IxGXV+J5tIRQG7uOlBoUYG8Q4t9EqlMiRr1GKxYHFxESMjI9BoNHwlSiwWw2az4WT/ENyqUnQZhI8uJAqry4+hZQfOrzUIbpdHQkeFFvWFedCdqbLsF2C+C5xNvUjG4DlZtJaqUZ2vPLOvCt4uiBOSnD59Gj6fDwaDIW1CEoqi+FjMWJXc8TUnnhw24+bOEl4NnWvgqn6zVjf+3LeCa1sLUKKRhljOBFvNZBMuHwURSUB+JmazQC3Dmxrjn1e5TACDEZx5Xl1djaGhIcjlcr46qFar+dnBnZgNdDqdaXsozyZ2/s6Wo+CSKPLz8wFgR8rNXPs53radTidvjFtYWJjSNjPVAna5XKBWxnC4JXQf7Z4AbP4tsp0p6xcOnPhDJBLhxIkTMBqNKCgoiDgTxbIsfnNiETIxifecn1obJxWwLIvZ2VlYrdaEFbB/GVjB156ZwjUtheip0glqvWYCTh+FS772Mu4+XIn3nF8Z8lTPWZrMzMyAZVn4/X4oCmsxsOjDqt2XVlPiYJya28TwihOd5dqUCL6YJKFTbN1AWZbFD/45i6ZidczvmvNsbGpqiurHmQkE72swMiUkCc/1jQWjSgqVTIQ8ee609aJBp5AgTy6GIU8GqXSrMtjf389/xnTazAjFA38YgVRE4Bu3CDeBBnYPAQwHy7IoKCiAUqkMqQ4uLCwAAN8qzqRxejBcLhfKy9ProZkNvCEIIEEQaQ1i5sQJTU1NUKlU/BB1tiHEk29tbQ0TExNobW2FWi18jiuVbSYKrrpQs7cJRn3oDe+BRwZh3XTj/M7MCk+4WR6WZdHR0QGKorb525lMJhgMBn7RvqqpACrZzt2QGIbB6OgoAKC9vT3hhfr/O7YIt5/GxXuM2Fu4c+0JqYgEC2DV4Qv5OUEQ0Ol00Ol0kMlkWF5eRkVFBdYtK2gS++E2U9iACTqdLuYizrAsfvTPOVTnK3GFgKoHAFy0Jx/dlfq0VndplsX3X5wFQQAno8wAbmxs4PTp09i3b19ODo0LEZJwEXWxjgnXxq+vrxckQjOopPgXgfnZwfAGaLj9NAyq7KmctQoJv680TaO/vx9GoxEVFVs/i2ZCnalEEprZGmlJxiYm12bphCJ4v8Org36/H1arFXNzc3A6nVmpDp6bAXwDgDNMXl5e5uf9gp/mso1Y1TiWZTE1NQWr1Yru7sS9tKIhnQSQq16tra2hs6sLX3xqGnLJGh48spd/zYcuq8XJgdG0EvhI+xGe7BHJ385sNmN8fBxKpRImkwnlO2ifEQgEMDAwAIPBgMrK5OxnfvPurvgvSiMohsGf+lbQU6lDpeHsLJlUTEZNDWFZFhMTE/B4POju7gZJkqiqqgJN07BYLHw2rlqt5lvF4Ys4SRBgwcLmCQjeV4mIhE6Z3huxmCTxx/f1QBvFN3B1dZUXZwVH7D0/bsEDvx/Cc/efB3Wcma1sIpKQxGKxYHZ2Fk6nk1d6GwyGkOq90+nEwMBAViqcR771GmiWxT8+fF7SrXyGZZP626eGVuBYncPBvaUhM5yxTKiDBSXc71MlhCKSwLX7ClGbn3hyUq6paYUi1n5LpdIQQVpwdZAgCF5ZnM7q4LkZwF0OmqYxPDwMACH+ftn2xQtGNEsWiqIwODgImUyGrq6utF7A6WoBB/slcjf282r0qDCELlItJRow6/KMfcdCxB6cv53BYOBjjMxmM1/14BWsKlXG2wnPnl7H34dXcG2xEzXV1Sm39LMJhgWWNr3oE9lDCGDU1zMMBgcHoVAo0NraGvLdikSiEHsIu92O9fV1zM3NQSQS8W1Jrop29+GqtH6Wl6esuO+3A/jr+w9sS+8I0AwYloVMvL1yEu1zc0bWHR0d2wjsixMWMAwLP53ddcYToCEREYJnQ6VSacREkmAhiUwmw9TUFFpbWzNyQ5w0u1CglvFE+cGr6jBhdidN/voX7fjII0P4+s0tvBJ+bNWJMr1im0I4GD6/H19+fBRymQQ3XRpZwPPihAVrDh9u6iiJaEIdrCxOtVV8TUty68RubQELTQKJVx3UaDR8dTCVEaRzNjA7iFRbwNy8X0lJCcrLy0NuRDupLopEAN1uN/r6+lBRUZER5WA6CC83+1NQUBBSvTrSEtm2JBMkO9jcNRGLl+AYo2VWi4dPLOL+IjEmJyfh8Xig1+thMpkylrTwub+OwhcI4IGLO2DU69L+/ong+fF1DC45cNf5lYLUmVIRiXsurBLke8aJlvrsCvhEYtTUAqIof0YQBLRaLbRaLWpra+H1bilYx8bG0i5a4LBi94Flt0hSOB56eQ40zeLeoHSTaGBZFpOTk3C73VGNrD99ZI8gy5l0gmVZ/OilWcjEJN57QRX/81mrG/kqadzWeHAiCbDV8p2dncXExATkcjmWlpbSfkx8FI2/DKzAoJTizoNb81aXNxbg8sbk31MiIkCSgPjMybfpCeBvg6toLMrDVc2RSRVnsP+Fq2tQWxadeH3tmSnQLIsb24tDBG/hecXhpJAjgj6axbGZTVxYZ8jYfYhbH3cbknWNCK8O2u12WCwWzM3N8YWAZB72nU7nuQrgbkTwvB+3mOUKwgkgt6/Nzc0ZUxylagTtcDjQ39+PPXv2CFY3pkoAWZbFzT88DpVUhJ+9sytp8heOH740i8UNL4qKm1BZXsb7QXID8nl5eTCZTBHbkslgdXUVnz8kRt3efTDq4ydzZBp5MjFEJAFJNGYWAULmkIJtXuxWYHzNJcws9wzkcjnKyspQVlYWUbTAVWxTOSY3thfjxvbiiL87v0YPlz/+NcJ534lEom0Vzp0GQRBoL9PCFGRy7acYvOUHJyAiCbz68e35vbFgt9tht9t5t4RMJJLIxCLc0FackDH3woYHTwyv4c4D5REfYhqL1HjqvkP8v3UKCa5vK0KeVIyP/2EYH39TXcj2uHN3z549cf1gf3xnOwLUdoJl9wZAgOCrmNHyih/tXcWf+ldhUIrRXKzOyAMny7K7sgIIpF6cCX6wrKmp4UccZmZm4Ha7Q2YH41UHudfvNvyfJYDcvN/KysqO+PsJATePx2UPB88mZgqpkDFOkNLW1pbQ01CqBJBbCNx+Om3kDwC+f3sbAhQDMUni289Po0wnx/VtxcjPz+dnS8xmM9+W5IhHoubbLMtiZmYGGxsbOG9/d8pq6O+/OAOaZfH+CxPz9wtHV4UOXRW6lN4jHHa7HUNDQ/x82KUm4NK9ydugRBItmM1mvP766yBJMqRVnC4C1loaf66NEwfo9fqkZzgzjXClslRM4v0XVaE9wTzqhYUFrK6uorOzkz93w4/JxPwq/jF4CvV6kWAhSSRUGRO7tqYtbji8FAIMAymEEZ2afBVembLi9QUbjs9u4khzAYCtNl9/fz8aGxuhVGtw1y97cXtPGS7Zmx/xfXRRDJjf9YteECDw8F3dIT8Prw5es68IpXo59pgU/Cx6NBPqcLj9NF47Uz1M5OHq/zKCRxwiVQc5ZXGkteRcC3gHkegiws37EQSBnp4eQU9A2TIqDoZIJEIgEMDQ0BA/S5dpxVYyIhCWZTE9PQ2LxZKUICUdLeBH3rs/otgjFUhFJKRnKloEAciCKgjBsyVcW9JsNvNealzsVjSzYw5clYgkyaSUvpFAkgTYnRlbjQmz2YzJycmoXoYsy4Jm2aT9CoNFCzU1NfD5fFhfX+dbsFz7Xq/XZ7Tq4ff70dfXh9LS0oQiDnMBiShxuQcXm80WNb+YOybDThtWRSZc21wKp20jrpAkXThcZ8QFtYm3UPdX6fGLd3bw1T/OuqelpQVqtRp+isGizYtfHV+ISgCj4a7zK+OSMpIkoVXKcPHerRZzsAk1RwaDTajdAQYq6VlD6uOzm/jb4CrKdHLUF0QnJrn4YJILCK8O+nw+WK1Wvjqo0Whgt9tRX18PvV6flAr44Ycfxuc+9zmMjIzg2LFj6O7eeiCYmZlBY2Mj9u7dEksePHgQ3/ve9wAAJ0+exDvf+U54PB4cPXoUX//611M6hm8IApgIuBJ+pHm/aODyY7Mtl2cYBlNTUygvL89aFSFREQjn8i+RSOIKUlbtXjx72oybO0shDmoVpkN5nOlkj3jVNLlcznupURQFq9UaYnbMtYqDz6FAIID+/n7k5+enLVv68Ff+Ca1Cgr++/0DM17n9NEQkIgoZMoGFhQWsrKygs7Mz6gPC/v96ESyA4/96ODT3k2Hh8lPQRFHXRoNMJkNp6ZZCk2EYbGxswGw2Y2xsjFd6p9qWDAe3vtTV1fEeounCvb/px7GZTbz68cM7WtWhGRY/+OcMCggHGgwiQbm+N3YUw+YJQK2UQ62MLSTJz8+HVC7Hj/45h/1VOnSmWIVO5roSkQSKNFudFi6BJ9i6Ryom8ej79id1HK5sKkj4b8Krg8dnN/CzVxfwpWvr4Q3Q+PRfJ9BRrsFd51eAJEkcrNajSCNDrSlxZfA5bIdMJgsRQNntdvzlL3/BBz7wASiVSlAUhbGxsYRiDltaWvCHP/wBd99997bf1dbWore3d9vP77nnHvzgBz/AwYMHcfToUTzxxBM4cuRI0p/r/xQBTHbeTywWC1YdpQs2mw3z8/MoKChAVVVV1rabyGLp9XrR19eH4uJi3gMrFp4dNeP5CQsuaygIictKtQLIzc3kSp6vWCwOUbDabDaYzWZMTU1BJpPBZDJBpVJteSPW1KCgIPEbQiwIsUP54UuzEBEEPiBAyJAKgm1eOjo6Yl5Dh2r0eGVqY9sx/NFLs3D4aHzw4uqko8KCWzjDy3aU5xEh/nYc8UjFGiLTBs+jq04A2PmWHstgcWUNXqUEN14gbLZRIRFBIdmeuxsuJOE8Qz1eL5bWxBgkA2gv0+zYnBrn2xipap2M7146QJIkTszZ4aNYyOUy5CmAcoMCdSYlvvzUOKwuCv95TT3q8hUAy261L95A2ClXDg4kSUKn0+FjH/sYPvaxj2F2dha33HIL/v3f/x1jY2M4dOgQjhw5gssuuyxmVbCxMTH10vLyMux2Ow4d2ppZvfPOO/GnP/3pHAGMh1Tn/VIVRiSKpaUlzM7OoqqqKqP+eKnAZrNhcHAQDQ0NgoxeAeCmzlJc2mDalpXKVVg5CG23p3PeLx1weKltPm7BZsdcLu7c3BzGxsagUCjgcDggk8nwzzkPDtUY4hraOrwU8mSiqJ/1xQcuELSvF9cbY9pcpAMMw2BoaAgymUyQCOIbt7RG/Pn1bUWYWHOlJSf2+bF1fPj3Q/jwpbW440A1bw0RyRRcr9fHfehbc/jw+9eXcO2ePCzMTGbU4Dledm08+CkGD708i8sbTKgvSE6xSNM0BgYG8O6egpi5vskgPJGk3mrF+vo6XnvttRAhiUgsyQoJ5sYH2tvbd3RGPNJ6eG9Yfvdnr27Afz01jlMLTpTrFJCIzj5Up8NmJpeQa+bVFRUVkEqlePjhhxEIBPDqq6/isccewxe/+EXcdtttuP/++xN+z+npaXR0dECj0eDzn/88Dh8+jMXFxZA4xbKyMiwuLqa0728IAhhrEaJpGkNDQyBJUvC8XziyRQBZlsXY2Bjcbjd6enpgtVpht9szvt1Esby8jJmZGXR0dCQkeJCKSRRqti+kwd/v+3/VCy/F4KE7OmIe11wif1d961WwLIvLG0xoLlbjaAxPLpvNBrvdjvPOOw8ikQgWiwUnRqbxn//YQFuRHF+4pj4q8bB7A/j+i7NoLMrDNa2RLXWEoi3BQf9EwbW3CwoKUo5IKtLI+XZcquiu0uG27lJc1XRWeCKVSlFSUoKSkpIQU3DO0oRrFQebN3NYd/qxtmHH0NgqLj7QEfE1uQS3n8aMxZ0UARSa65sOhIt7OG/OYyd78fEX3GguVOArNzYmJSQRgmDT7p0ygweALz81jpFlJ3709raQiiPLsmDY0GrwBy+pwV3nn01FCSaAkUyoc7W4EA+5RgCDIZFIcPjwYRw+vKWiv+yyy/CjH/1o2+u+8IUv4Prrr4/4HsXFxZibm4PRaMTJkydxww038DqAcKR67r8hCGA0cPM4paWlKd2EskEAuRumVqtFe3s7/7S2UykkkcC18+x2O3p6ehIe2p61uHFqbhPXtxWDDFq4SJJEILDVtsyTi+F3BeKSv3SKPaLBTzF4ZcqKC+uNMbdBYOtCbCrKQ3elLuo+T09Pw2az8WrJZZsXTlKNyw4WgdCbUZnHwmKxhKSRBM+oqWViNBXloacqt+yKwuHxeNDf34/q6uq0t7dThUoqxseuqIv6+3BTcLfbDbPZjIGBATAMw4t7OOKRF9jAteU09u1LXb2daUjFJB64PPpn50AxzDYhTiK5vulGsDdnVVUVZK++jKYiFS8kyVNrUFhgSpuQZGlpCUtLSxFNu9OJxU0PAAKluugPNxKSONPBZfHDf87iquYClOsV+Nc/jcDmCeDbt7byxyq4zb7pCUB9xsYp3ISaE5H4/X4QBBGiLt4NyLX0kkAgEPU8eeaZZxJ+P5lMxj9IdnV1oba2FmNjYygrK+OzjoGtuepURWa5vWKlAIvFgtHR0bT4+4lEIl5gkAk4nU709/ejtrY2ZHHNdus5FiiKwsDAAJRKJTo7O5MiXY8NrmJ+w42jLYWQkWef4EiS5J9u/vvG2GHmweQvXYvAhtsPtVy87ab36xOL+NXxBWgUEnSUR6+YPf6BgzHfn2EY9A4M4TsnnfjENa38TeqR15fgpxh85LLaICuUgohpJPn5+TCZTDjaUrjjre5YCLd52c0gCAIqlQoqlQpVVVUIBAJYX1/niQewNe/Z3t6e8+QvFmiG5StJFMPgG89NQ6cQ413nVQJIPNc3kyAIAs99+Hz+3z9+eRYrs07cKNncJiRJ1I4J2EpsMZvNaG5tw9CKG+0xrvtU8ZFHhgAAv31Pd9TXcITd7PThhQkLAOCuCyrRU6HD8xOWiIp5q8uP/3pqAkqpCP929dnYTU5IIhaL4fP5MDo6ivLy8pBKoVCbmZ1Etufx4yHdFjBmsxkGgwEikQhTU1MYHx9HTU0NDAYD1Go1Xn31VRw4cAA///nPcd9996W0rd27agUh+IbI5c+urq6mzTOPE4FkApx3Xmtr6zYjyZ0kgMFzJx6PB729vSmnj7z7/Ep4AjRkEYbBhXzOYLFHtAUq0VxPP8XgB/+cQ55MtG2u5s3tRShQy9BaGtvgk2IY0EzkaDC/34/+/n4E5HpM2hx4asSMujPttzsOlMMboLcRuuCKR/CMGmdnYjAYMppGkizW19d5H8hkbr65Di4/urCwEENDQ2AYBgqFAidPnuTFPfn5+RHXnGTzZhNBMtsYXnbgX37Ri/95cxMurDdCTJKQiUnsK90yIs9mrm8y2FeqgSfAoGHv1rUbLCTx+XwJJffMzMxgc3MT7e3t+MZz03hsaA3fvnVfTBuVVPCJK+shdJTRlCfD/97YDL1yq9J0c1cJbu7aXv1Z3PTg28/PIF8lxU0dkY3MuRSeqqoqvkIfz2Yml9aZXGsBO53OpAjgH//4R9x3330wm824+uqr0d7ejieffBIvvPACPvvZz0IsFkMkEuF73/sebzr+3e9+l7eBOXLkSEoCEOANQgA5pGPeLxIyQcRYlsXU1BSsVmtU77ydIoCcKlckEmFjYwPDw8NpSR+RismIg/zxVMBC5/3mrJ7/n73zjm+jsN//o+G95CF5bzveMzusMAIlZDhAAqGFhlWgrDIKpZT+Ai2jjLL7ZUOBQksWCUkIq2xIQhJb3ntPTcuytu7u94d7hyxLtiSflq3368Uf2I50tqS75z7jeXDLf+qxpSIZV69xzM9MayTQJdXg3vNntsaiQ4MYE1hLRif0GFDomFbspn8cBwngiFUlUKPRoKGhAbm5uRAKhfggKw0xFuawgrAgwI5ZrCWWM2quppH0yrX4qH4U152eOWMbkw0csXlhA7nGiPeOD+LKVel2jXbdiaXBs+V2vlarhUwmQ1NTE8xmM9Mqjo6OhlJrwus/9OPCEhFKU9yT8ELPh56RF4dV2bMnVFgSFsQDF0BM2M+XAvpGiLY/cVeuLxssy4zFssyfOzzWiySWiST2rH/ouD6dTsdY2vxyRRpSBGFutVGZratgi8TouedLhZEhiAjm4fxiIXKEM0UJ3crPzs6eltRkK6KOvuEGfKs66GstYFc8AAFgy5Yt2LJly4yvX3LJJbjkkkts/ptly5ahsbHR6eeyx4IRgGzN+9mCbSFmNpvR2NiIkJCQWb3z2PDHcwVakI2MjGBwcBDV1dU2jXvZfj5b0OLPcpPNHuHBPEzozGgeVTtcDakbVGFwXIdhlR65Nk6Ytth9ahgaI4HK9BgE8bg4tzABcs106xWFQsH4QtGVXWHk/BcEeDwe0+KylUZCt4qtK3BStQE6EwETQbIqAOmLp0ajmdPmxZXHtn69x7Um6EwE1HqzxwUgbfCclpaG5OTp1ZXw8HBkZGQgIyMDJpMJCoUCAwMDUKvVCAqPhNkAhPOdqEwTJLQGAoJw278jQVJ444d+XFSWiJSYUIQG8RDM5yI+wrn3WHZCOH60EftGz6LaM+32B+wtktTX1zPznAkJCRgeHgZFUSgtLWXeb8KoEGyzUWHzdYJ4HEgnjfjXT0MzFr3oDOO8vLxZW/n09cg6os5XqoO+1gLWarV+mQICAJw5NoH8Yk1Io9Hg2LFjbsvzHRwcBEEQyMzMnPdj0e3U9PT0OTfp6AvO8uXL5/28znDixAmEhobCbDajrKzM7R82pVKJkZERFBcXT/u6K8seGqMZOiPpcF4oQVKQThogigpxuH2mMxGY1JshjLJ9sR0eHsbg4CAqKio8uhWq1+shk8kglUphMBig5ETh4W8V+NfVS5HpZISWI1javOTn57M6m9g+NolfvnUKz20txeocxytabGMiSPC5HGaxxdk5OEsfSIVCwcyoCYXCWYXVc192Q2ckcNe6XJtzXt0yDS577SQuKBbir5uc8xObC3oDtrKy0qsbsO6Enufs6uqC2WxmhKK7Ekk8SZdUg6hQ/jS7Lb1ej7q6OocyjGfDVnWQnsf2VHVQIpFAq9V61B93Nr755hscOXIEzz//vLcPZTZsnpz9+53+P8LCwrB8+XK3nax4PB6MRuO8H4c2ona0neqNFrDJZMLExAQiIiKccjV3BI3BjJ0HW3HDGVnMHBxguwLo6qZvRDAfc1jpTcPS8d9RbJnaAtOrYUuXLvX4XWpoaCjS0tKQlpYGgiBw6FQvzASBH07UYjJNwOoFjt5aFwqFDpmAuwIHYGVu7oGPWiEI4zu0AWsJSVF45r/dAGHC6THjKCkpQXS0cy1cSx9I4OcZtZaWFphMJmae0zoy8JKqFIyo9HZj8XISIvDCZWUoSma3NWsr13chwuPxIJVKkZycjOzsbExMTEAqlaKnpwd8Pt/lXG9fwLqTQYu/goKCeRdI7FUHLbeL6Z9zV3XQ1yqAk5OTPjsiMRcL4hPO4XDceqfKhhDr7+/HyMiIU4spbGTkOoNGo4FYLEZERATS0tJY3zbVm0hojAQ6JJN2BeC3HTL882g/nthShKjQIHC5XPTItHjkSDueurTE6TgwT0HPn4aGhqK8vNzrm7o8Hg+bludi0/LcaVUoelOSrni4siTlCZuXJYmROH7vmaw81pEmCYApnzSJ2jir7YYlXA4HHLMRMYQCFRXVDokBkqIwNK5Heqzt6p7ljJp1ZGBUVBQzz5kqCJ3zOFdms9PtIEgKX7ZJkYAJcIwau7m+nmDXqWGodCZcd5rz3RaKovBT3ziEkSHITrD/WtFznHFxcUxXx1Kk05V0VxZJfA16NKqwsHDeM9y2sJ4dtPyPvnlnWwySJOlTr4OrM4C+wIIRgO5kPjYwJEmipaUFBEFg2bJlTp1YPSkiaNucsrIy9Pf3u0V4xkcG4x/bK2Z8vV9pgMk8Ve2TTRpAEBR4FvN+HdJJTBoIPP15F647PcvhC7inoFv1ycnJTFv/sxYJWscmcctZ2ey9jmYDeM17wK99CxydAqSwBOYVN4FMn92GxroKZbmwQBDEDG+72aBtXoqKitxyQXEH3919Gjjg4KP6UbSMTuLmtdkOzQ+OjIzgzPhJVFaucPgG83jvOD5vleJXK9KQNUfb3ToykK5C9fb2gs/n253nZBul1ohP6npRFM/DjvOqvHpx/cfXPaAA1wQggC/bZAjmc3HHubk2f8YRM2vrSrpSqYREIpm2SBIfH+/R8Q6tkcAnzRJsKEt0OIJOq9Wivr4eRUVFHtngtrVIYikIzWYzOBwOeDzevN5jBEH41GiCVqsNCMCFjKs2MAaDAWKxGCKRCJmZmV6vCtmDrk4uW7YMISEhbqs8yiYNePqLLly9OoOpAA4qdfjbFz1YEmFEZQWJDaUibCyb7nW3rlCIyrRovPZ9P+Qa2xUcnYnAqX4V1uTEevTvPDk5icbGxhmzYY3DapgIctqxtI5OIkUQ4loV06RDyPtbwJW1g2PWAQA4E8Pg9X0L0+rfwbz6NocfKiwsDGFxiVj6v4UFuVzOeNvNFoPmLZsXrXHq5iAixLXTFW3Pc06hEOmxYYgJnftx+vr6IJfLnW6FlqVGgQMgLda5mxQOh4OYmBjExMQgLy9vRhXKslXMpkAjSRJjfZ24tDgKlSVL8G2nAssyBS7/refLgZtWgiBdGz3ncji44Ywsu5GBJpMJdXV1Npd47GG9dKXRaCCTyewag7uLH7oV2CceRVZ8uEPbwxqNBvX19SgtLZ1hL+YJbLWKLdvE82kV+2IL2HKj2p9YMAKQw+G4LdrGlRYwnZVbUFCAhIQEtxzXfLGsTlra5rhr9pDOJTdbnOBTBaHYUpGEkPE+aLVahIWF2fTFS4gMwR9/scTuY7//0xAONY5BGFmEJYlz342JB1UYGtfPGts2F/SmZGlp6Yw7QOsKhM5E4Ob/1COYx53TONoWQT8+A660FRzCwHyNAwow6xD04zMg8s4HJSx06LEahtXYLx7BZUtTsSQxEklJSUhKSpoRgxYWFsZUoaRSKYaHh91u82KLF7/uAUlRuPf8/Hk9jiAsaM4UFYqi0NHRAaPRiMrKSqfFVkQwn5XWrHUVSqFQYGRkBK2trYiMjGREyXySKuhcX4FAgJKsLHRKNbj3wxacW5CAhzezu1jiKNZZ2s5ib2uatj+x9L5zFutEkhGlBi9/3YlzUyfBN2sRHR0955ytQmPEbR804i8bC2dtU1tzZl48kqNDUZg097mN9m70JfseSxNqy+ogfZ1xxmbGF1vA2dnZc/+gD7JgBKA7cVYQjYyMoKenB5WVlT67Hk63LRMSEmaEururAiiMCsFfNxXP+PqGsiQMDpoZMUqLjsjISHA4HLSNTeKRIx344y/yUfA/cafUGnH7B4247exsLMuMxSVVychJCEeeg6atDx1uh4mg8IsSkUuLBkNDQ0xclCOtoLAgHm4/OwelKS7cjVMU+LX/nCb+pkEYwa99E6bz/+bQw+UKw3Fabjwy4qbPqdmKQZNIJDh27BgIgkB6ejqMRiOCgoI8WmXdWJbkclXIGUiSRHNzM4KDg1lfgJoP1nYmtPVPbW0tuFzutFaxo8dML/FYtkJzE8Jxz/l5OCPXe1vX7oBegrC1wd00rMaE3oTVOXEgSAoUKLuLN9aYwUVYeDgyclORERsGlUoFmUzGLJLYauHLJg3Qmgj0KbROCcBgPhclDpw71Go1GhsbUV5e7rPXHstCQ1BQkNM2M75WAQy0gBc4jgpAiqLQ3t4OjUaDFStWsLZFZ8sPbT7Q0XN5eXk274bduX18om8c6bGhSIwOnXYHaOmhRp9ENRoN4uLioA+KBp/LQYhFa4cgAYKiMK6bms2MCQvC2iWOV1pf/WUFJvRmp8UfnYes0+lQXV3t1IloU3mSU8/FQBgBo9rutzkUAa6s3eGHiwjm45yCn/9WRoJEsNVcEYfDQVhYGDQaDUQiEbKysiCXy92aRkJRFHQmEuHB0/+mjlQ9OiQaaI3mGd5njmI2m1FfX4/4+HhW7J5mg6QofN0uQ2V6DGLDHa+m0h2O6OhoREdHIzc3FwaDATKZDB0dHdDr9Q4tLNjL9eVwOLi40rHWqKOo9WZIJw3ISfCOGKHn4OwtQdyzrxkkReHwzSvx9H+7QJCwaQpvi/TYsGlVaXrO1lYLPzY2FgkJCfimcxLLMgRY4wZrI3o+15fFny2cNaH2NQEYWALxAdzZAubz+XMugdB31NHR0aiqqmJNsNFm0Gy94enoufLycrtvWndVAI1mEs/9twtxEUF46pISm8kedNxWcnIySJKEQqGAVCrFdXk6qIe7MGYWTRm4RgbjX1cvdflY4iKCEeeMXwymTkSNjY0IDw9HWVmZ5ypEvGCAHwaYNDa/TXG4IAWuiZZxnQkbXjyGNblxeHzLz9VZWzYvdBoJ/brQCQsRERGMbcZ8WpKbX/oJYxMGfHnHmhkicC4+FI/ATFAoT412+nWhZ3UzMjKQlOSiSHeCca0J33YqoDORTo0grHnyO4DCNOPmkJAQpKamIjU1dUZKTEREBNMqptv2jub6WuYDWyJRG/DfNhkuW5ri0N9500vHYSYofPG71TNuMtiCIClwOTOX5uhW6Gz2Pf+3vRxa45TAKEmOglrPTua7rUUSqVSKsAkZ1OM8SMfCkZCQwNoiiUqlgrixGYfGohCXQ6HAf/TfNByxmaGvxb7SCmY7C9iTLBgB6E7mEpd0RS0nJ4f1CwhbdzwURaG3txcymcxu9ByN+2YAKQTzuAjmceeMdQOACQOBuP+59dOtL4lEgt7e3nlbmTiLwWBAfX09UlJSnM5DNhEkDGYSka4O1nM4MJf/Evy6t8AhbPhR8kJAVO1w6aGjQ/ngcTk4M+9nMaDX63Gqtg7jwUKUp87clKTbjvTrMjk5ybQkZ0sjsYaiKNQNTiA7IRyCsCBcuTINf/+iy2nxBwA3npE1Y+nG3nN+16XAquxYBPG4TIXIWYPn+RAXEYzrT89EvJM3IADs2LlOYb2wMDk5CZlMBrFYDGCqciiVSlFaWjrrBvf7Pw2iR67D3eflzlio+PsXXfimQ47TcuPsWt1Y8sK2MjSNqN0q/h7/tBMRITzcdnYO83W6GjbXHJzlGMSFJa7PA8+G5etSUGB7kSQhIQHR0c7fvADA+Pg4WltbUVRSij1DfagfUjGjMv6OdXVQLpdDr9cjKCiIEYPeziv25wrggkgCAaYqFu70zPvhhx+wZs2aGV+XSqVob29HeXm5W7atTp06haKionnFMdEedTweD0VFRXN+UIaGhmAymVh3WqcoCq0jExBGBkEQHoyRCQMe+6QD912Qj+SY6SJuQm/C3z/vRkFSBLYvmylCdDodpFIppFKpzblBNqE3fV110X/8s04YTST+eGG+68bGBjVC31kPjmoQHELPfJkKCoe54kqYztnp2uNaQc8QceMz8XG7Glsqk5xqq1qnkdBbktZGxwAwaTDjqc+7kCeMwC9XzJ6KwxY/ditw2weNuHZNBq6ojENTU5NLBs/+Bm0+HRERMa0lGRcXN+N8cLxXia875Lj7vNyZUXw6E5qH1VjjpjnBPoUWUSF8p6rzT37eicq0GJxXOLWJSQui8vJynzdyprfwZTIZ1Go1oqOjkZCQgPj4eIdGiOjIycrKSoSGhjKFCl+ZX2UTuVyOzs5OVFVVITg4eFp10FLH0MUSTwnCSy+9FG+88YbThQEPY/MNsWAEoNlsdmtqhrUApCgKPT09kMvlqKiocNtmpFgsRm5urst3GHT+Y3JyssOJDaOjo9BqtcjJyZn7hx3EVrJH84gaL3zVg9vPyZlxx0pRFA41jmFZpmDOpA56blAqlTJzg2zNp9HWJ2VlZS6X+TskkxhRGXBm/jwrTEYN+KfeBL/ubXAMKpBxeTCvug1E/gXze9z/QW81l5WVISQsDL1yHTLjwhz2HfuyTYYhlQ6/XD5lIk4QBORyOaRSKSYmJmxe3HrlWgijghER7JlmhJEg8Z8Tw1idGgTZYA8qKir8NuvWUejXlf5dSZKEUqmETCaDQqFAeHg4U6Fi29uuaViNUbUe5xbMbZNBUhTOfeZH8LjA57fPvNl2BMsMY8vOgNZIwGAmnJq59DS0YbtMJkPXsAyCMD6SRFOjFbbOPbQgqqys9KgnoTewFn/WeMqE2hYXXnghDh065BGvxXkQEIDzwVIA0rNgwcHBKCgocOubq7GxEenp6S69uSYmJtDQ0IDCwkKn2lsSiQQqlQr5+fOz3aChKIqZ23D3XZnl3OD4+DgiIyMhEokcvqO2ZGBgAGNjYygvL/cp49HZIEgK33cpsCJLgFAbcXX2oLeaHbmZGRrX4e1jg7jrvNxprb3HPu0AQVC4/8KZdj27Tw2BMhtRFTclCj3dwrdkZGSEyWr2l9fVVebK9bX0tpNKpaAoitVq+jnP/DCVNHLHGoeq34cbx5AUHYLqDIHTz0WPh9j6Xf/2aSeMZhJ/upDdzGp3YDSTeORIB0L5wK9KIyCTyZgFn4SEBMTGxkKhUKC7u3tB5zXTzCX+rLE2obasirojr/iss87CsWPH5jX/7AEWbhawp6AoCnq9HmKxmBnwdTf0EoizjI6OMicIZytXbC2BWH4IncnznQ/W82m0ZYYzc4P0NrfRaERVVZVPbZzNRZdUg89bpQgP5mFZpmDOn6coCt3d3ZicnHR4q3n3qRF8VD+KmookFCX9PPZw7zr725N//6IHHA7w/d2nIy8vj2nhNzU1wWw2M6LDGUNdV7bje3t7oVQqnd7gdjdsb/oDjuX6WnvbWW/hCwQCplVs/fca15kQE8qf9bjf2VEFhcbk8OiD9VLMpMGM0CDunNYstKivqqqyeSG+bGkKxrUmnxd/wJTlywXFQmQnhCMpOnTGIklzczPMZjNycnLctvjoKygUCqfEH+D5vGKSJP02N3vBVAAtt4PcwdGjR5GXl4e2tjYUFxfPO1TbUdra2pghYUegKApdXV1QqVQoLy936a5EqVRiZGQExcUzPfscxd3ijyAp3L23CecWCLGhzLHhbXtzg8Fh4QjmcZm2ZUNDA6KiopCTk+OxC8bFr/wEjcGMT25dzXyNpCi89E0vqtJjsNpB2wiCpNAr1yI9LmzOwXva965OYoYuWIDrTnMsrUZnIjCg0CFfFOHw32dswgAuZ8oL0hp6DkoqlWJychIxMTGMoa49kSbXGPHi1z24uDIZpSlzz+/Rot5kMqG4uNgntgdpHjrUipEJA168vNz1GVEL6IWviYkJlJaWuix0aWNwulUcEhLCbHvLdBRe/q4P5xcJcUaee5ZnCJLCXz5uR1gQl7Fb0ZkIHG6UoKYiidlSpoVuRUWFT12ISYqa1+sp1xhx775m3HZ2DspTp97jdEV3yZIlzGvDxiKJL6JQKNDR0eGU+JsLWzYzgOvVQYqicNZZZ+HUqVO+/ncPVADng9lsRnt7O5YuXerRlpUzG7m0eAkNDUV1dbXLb8j5VgA9UfnjcgCp2og9tcMOC8CwsLAZfoNd3d249wslgoP4eHVrHvr6+pCRkeFwVBRbaA0zX2MOANmkEd90yh0WgDwuB7nCuSu+JpMJDQ0NiI+Px8CQEWa9je1iO4QF8RxKW7EkMdr+jFJQUNCMNBKZTIauri6EhoYyosNyzimIxwGfy2Vi3maDJEk0NTUhNDTUYYNnucaI934awg1nZLptg5XmQIMEZoKE0Uw61ba3BS10zWYzysrK5iV0LY3BATCt4qamJhhMZiQHhSAtgnK4eqnWm9El1aAizTGRwuNycFpOLDIsto331Y3g1e/6kRwTgjU5cUxFt7Ky0qcqup82S/Dq9/14/rLSOWeY7UGQFEhqqgoKTHV1BgcHmYquQCBgqrZyuRwDAwMuLZL4IrT4Y7vFba86SItCuojkzGaxO6r3niJQAZwDOi5NKpVi6dKlHs9V7OnpQUhICFJSUmb9OZ1Oh7q6OqSnp8+7NT05OYnu7m6Ul5c7/W9tLXvMF52JwDvHBnBJVYpr1hlzcMUbJ7E0MQhLIxTg8/mIiYlxeW4QmKp2fdQwiitXpjkkUDwNPcaQlZWFeKEQW189iYsrk3HlSsfeN80jatz0fj323rDcLa+HJRqNhqnaAmCqthERjlUfaYPnhIQEh5egAOCV7/rw2vd9ePGysjnj4+bL0LgO3TLtvCtpdEU3JCQEeXl5dv8+E3oTIoL5Nn3+5nwOioJab0Y4H9O2V2NiYhjRYU+I/efEEBqH1bjrvFy7kW1zoTGY8VPfOE7LjUV/by80Gg1KS0udEroqnQm/eusUdl5UgKUuzBo6wtEeJZ79bzdeuqIcMWHznw0bHh7GyMjInFVOy0USuVzOJJLYWyTxRSzFnyeXW2xVBymKYiqDtt5jFEXhzDPPRF1dnceO00UWdgXQHQqcNogVCoUea/la40gFcHx8HE1NTay1pmnvQWdx17KHVG1Ev0KHHpnWLYLj2Y0Z6OrqQlnZcoSHh7s0N2hJ66gavXItVDozRFG+JQBpm5eioiIIBAKQFAXZpBGv/9DnlAA0kxSkaqPbBWBERAQiIiKQlZUFo9HIVAa1Wi2TehEbG2vz/UZ/fq0TLxzhVyvSUJkWjaUOzFHSGAkSNS8dx41nZDmV+pIqCEOqYH6byJa5vrPZNxnNJJ78rAvhITz8wYVs5cteO4nRCT2O3LKKqdpSFMVUbbu7uxEcHMxUbS03rDeUJaIqPcZl8QcAESF8nJUfj/b2dhAE4ZIhu85EwGSm0CHRuE0ArsqOxaprXTeqt2RoaAhjY2MOVTk5HI7NRBLLpBh6kcSXxiBovCX+ANdmB41Go19vYC+YCiBJkjCZTKw9Hr1BW1BQgISEBDQ1NSE1NXVWA1V3MDg4CIIg7MZTDQ0Nob+/H5WVlazZWej1ejQ1NWHpUsdOYO5u+VIUBa2JQFgQj5UZKUv6+/shlUrtzku64jdIkBT0ZsJj1iaOYmnz4i/VAHvQViZSqRRKpXJGGolGo0FDQ4PL3o2uYCRInPnU90iKDsGHN67wyHPKJo0YVmpgknQjKSnJIS+ygw2jKE2OQpaD8WxmksSJPhWWZwrwbaccb/44gH/+usruz2u1WshkMshkMphMJmY+zZYXpLNQFIWWlhbweDwsWbJk1sf7ul2GYZUBly9zLLXEFxkYGMDImBTfjUejpjLZZqTepMGMYD53zlEFepFEJpNBqVS61f7HFbwp/ubC3uzg+Pg4rrnmGnz11VfeOzjHWNgVQDYZGRlBT0/PtA1ad+bjzgaPx4PROHM+i5710Wq1WL58OauzHs78rmyIP4KkYCLszz9xOBzWxRRFUWhra4PZbEZVVZXdu2Fbc4P0hmRsbCxEItEMv0Eed+7jrR9SYV/dKO44NwfRoe63DxgeHsbQ0BCqq6tdmqk51DCGk/3j+MMv8t0+E+cIXC4X8fHxiI+Pn5FGQpIkDAYDiouLPSb+ACCYx8WPvz/dY88HAC99043BESn+dGE+UlMcqzpuKHMurahpWI2P6kcRFsTF2iUJc2Zuh4eHM58Zs9kMuVyOoaEhtLS0zGs+jZ7lDA8Pd2hB69suBcyk/85n9ff3Q6FQoKikFAc+60bTsHqGAKQoCvcfaEUIj4vHL559ac86KYbtRJL5QBtaV1VV+Zz4A+xXB/ft2weJROLNQ5sXAQFoAUVR6OjowOTkJFasWDHtBOVNAWj9vGazGWKxGNHR0aisrGT9w+roEghblb+79zTBQJB44bIy1it8tjCbzWhoaEBMTAwKCgocPm7rnGLL3NXIyEimAuXIhc1ETBXX3f37Diq10MqGodU4bvNiCyNBggIQ5MLcGDBVpTARpFuMeDkcDibJIMQmpSE6Ohrt7e3IyMjA4OAgurq6Zk0jccexOEK/Qoe4iCDX4wExVZ1eFaVEfEEu0hwUf65QlByFX61Mc2i5yBo+n4/ExEQkJiaCoihMTEww4xV8Pp8Zr5ire+Foi9uSP/4iH/7qktLb28s4OXC5XOzcsAQ8G+8tDoeDc5bEI1Xg3KKJLfsfby2S+Lr4swWXy8W+ffuwf/9+HDt2zNuH4zILpgVMUZTNSpmjmEwm1NfXIzo62uYAtaPLGGxD22MUFhYCmGqv1NXVITs7222bqhRF4ccff7QZfWf5M2wte3zeKkXziHpalqezSNQGvPJdH246M2vWuTS9Xo/6+npkZGQ4ndtsJkk89kkn1uTE4hyLZANLv0GZTOZVk2NL5JMGbHzxKFKieNh102lerYSc8dR3oCjgu7vZr5BRFIX/d7ANRr0Ol2SZpxk802kkMpkMKpUKUVFREAqFbrmwaY0E1j33I2oqkvD7WTwRjQSJBw+1ITyYh/t/MdM02xEmJyfR0NCA4uJiX08gsItOp2NaxXRsIN0qtqyoEwQBsVgMkUg0Y8HNnzcw7UH7cjq73MIWnlwkUSqVaGtr8yvxBwAHDhzA888/j0OHDnl8LMxFAi1ge2g0GojFYuTk5NgVBd6sANLVOLlcjtbWVpSWlrr1pD/XCZXtZY/zCoVMjqerjGtNMJhIqPVmuwKQDoinFyAoigIFx6twPA4HJoJEy+jkNAHI4XAQHR2N6Oho5ObmTjM5dndOsT3MZjN62xqxLi8K20/zfvrBvefnY0LP3oyuNWelcGDWETOqnDweDyKRCCKRaEYFim2hHsLngqKACf3sbgTBPC62Vacg5X/51xRFQW8mEeagBYxl1q0/z3KGhYUhPT0d6enpjFAfGRlBa2sroqKimHZkc3MzUlNTZ9zwHu9V4k8HWvHKLyuQFe/ZzN/94lEYzAS2LWUv/5X2cNXr9S4tt7CFpxZJ/FX8HTlyBM888wwOHz7sL+LPLou+AiiVStHe3o6ysrJZA+GHhoZgMpkcbj+whVqtRm9vL2JiYhgbAE9Ulayzj2noIVhPJXuwhUQiQU9PD8rKypiA+IcOtYEEhZ0XFbrtea1ziu3NDVrSOjqJFEGIy7OBdJXTle1Xf4Oe5SQIAkVFRU5dkCwXfOg0EssZKLnG/VvOwFR1lCCBr+9cMy13+WiPAjwOZ5oNjXWury/xTYcMMWFBqEib380pXVGnfe/CwsKQkpIyowJ1om8cfzrQipd/WY7MOOcFoFpvxi/fPIlfrUzDtmrnhNzWV0+AAoXd1y+3+f1XvuvF1+1yvPXrKoeytCmKQmdnJ0wmE4qKiqZM6UnKJased8LWIom/ir8vvvgCf/nLX3Do0CEIhfMrWniYhV0BdFaM0G75MpkMy5cvn3MwnsfjQa/Xz+cQXYLD4UCpVIKiKCxbtsxrZqfeiHVzFqnagPAQ3rQFDIqi0N/fD5lMhurq6mmbvskxoVDNUZV65bteyDVG3HeBa606W3ODEonE7tyg3kTg5v/UI5jHxce3rHL6+Wibl8LCQq9ZF3kKkiTR2NiI8PBwp2Y5aSwXfOhlBXoG6ntpEHa1aPB/28tRneHev+PVq9Ox69TIDKHwcdPUcDktAEdHR9Hf3+/yIo87oSgKn7XKwONy5i0AORwOgoODoVQqUVFRgYiIiBkVKKFQiOp0AY7c6vhnxEyS4Fmcu+iKrS0T9rl466pKkLOURzokGhAUwHdAwNELfSRJMuLv+y4FXv2+Dw9vLERqrO8IfTYWSWjx54vbvrPxzTff4MEHH/RH8WeXBVMBBKZ8vxyBIAg0NjYiKCgIhYWFDlUNaLuJJUtcEwKuYDQaUVtbC6PRiNNPP92josuyAkiLP4IgGA8kX4OiKPzyzVMI4nEZiwqSJNHW1sacWF1pV1zyyk8gKQr7bpi/rYdcY0RceBA4HM6sc4Ofto+jJDnK6aF7T9m8UBQFhdbkkeqYPeiZXZFIhPT0dIf+zbBKj1GVHtVzeL+RJAlxzxgePNKF2yt4iI0Ms5lGYguCpPBNhxyrcmIdbunaY9JgBgdT3ncDAwOQSCRujTvrkGjwm3/V4f1rl7qUXqHWm8HjchAePL/fW6fTQSwWo6CgYMZNDEEQUCgUkMlkGB8fZ+x/4uPjZxXFZpLEzoNtiAzh4w8XzO5/aCSmfvbyZalMBBtbfNIsgVJrwmVLU5jzQGtrK7hc7jRbm/ohFW7/oBHnFwlxn4tzop6GXiShzcFtLZJYij9vzkc7y/fff4977rkHhw4d8vgeAEss7AogAOYDNRv0ySU1NdXhCwcwtc3mzqxhayYnJ1FfX4+srCwMDg56TXRZLnv4qvgDpl77q1alI/l/kWN01FlcXBwyMx3LuLXFruuXsbJJ2K/Q4YWvu3F+kQjnFQpnnRtMIghgIh7qUJHDc4O0zYsnWirfdCpwqHEUN52RjewEz85eAa4bPL/+fT+0RgLladHgz3IzwOVyUZWbjA9vnpo5o9NIGhoaQFEUUwGx9dp0STX4uFmCED4Xa3LnZ0ETGcIHRVHo7u6GWq12e9xZj1wDE0lhbMLgkgCMCp3/5USj0aC+vh4lJSU2R3J4PB5zo2Rp/1NXVwculzttWcHytaFjA1dkCeY8BqOZRMPQBPhcjk0BSFEULn/9JBKjQ/DctjKnfr9/HR8ESQGXL0tlPA2DgoJmLB6Wp8bg7IIEnDbP95AnsYx0tJy37evrA4/HQ0REBBQKBaqqqvxK/B07dgy///3v8dFHH/mr+LPLgqoAGo3GWQWgUqlEc3OzS4kZExMT6OvrQ1mZcx94V6DnEukh72PHjmH16tVuf15LfvjhB6xatYoxwPTVtq8tdDodI559ZQbORJA42DCGs/LjETdH5czW3KC9xAuKotDT04OJiQmUlZV5ZERAqTXiq3Y5LipL9LgnIG3wbKs6NBcqnQkqnRkZcY611EiKwivf9aE8JZoRc0ajkdnMt/XakBSFLqkGmXHhCObP729jmetbXFzsN58/V6HHF8rKyhAZ6VzWNDB1Y0BvFTuSFDMbE3oTQoN4dt/fl712AhwOB/92Mu1DYzSDJIHIEB6TT52bm+vUayseVOFIswR3npvr0HyhLyCRSNDa2orIyEgYDAbExcX5dCIJzalTp3DzzTdj//79Hp//Zxmbb7BFIwAHBgYwNDTk8vC0RqNhXMrdBUVR6Ovrg0QiYUKwHbFkcQdHjx5FWVkZQkJC/OrCo1KpGJHvr/YYllgnXljODXK5XLS0tIDL5aKwsBAcDgc6E4G3fhzAjtXp825Behq5xohvOuSoqUia9p4bVumh1JiQFjGVdVtaWuqRTG7aZDeYx8XODQUzvj9XGsl8sJXrO6jUISqUz0q2rK9hudlML2nNB+vXJjw8nHltvD0/SRtaR0REICfHeeurxz/rQJ9ch6e3lvqEKftc0K8t3fa1fm3CwhwfsfAkYrEYN9xwA/bs2YP8fOdjE32MhS8ATSbTDANjkiTR2toKk8mE0tJSlyskzsajOQt9UuBwOCguLp52V2RvI9cd0PN+Q0NDGBwcRHBwMEQiEYRCoddPnHMxNjaG3t5elJeX+9yGJBtYzw3qdDoIBAIUFBQwv++RZgkeO9KBey/Iw4UlvlH9dJQ/HWjBf9tkePfq6mmJB//vYCtUk1pclmVEpYe3X0nKMcNuy3akTCZj2pFCodCpeUz682dtekxSFM546nvwOBx8c9dpLv8+nsRRjz7aCNhdc2H0sgL92gCYtY0/aTDPy6B7NujXNiQ8Cvm52S5t+RIkBYKi/FL8WUNRFLRaLfPakCSJuLg4CIVCrySS0DQ1NeHaa6/FBx98wHjw+jmLTwAajUbU1dVBKBQiKytrXm8mk8mE2tparFjBfsanwWBAXV0dkpKSkJGRMeM4PSUAbW360idOqVQKDofDzN+wcZduj38e7cepgQk8c2mJQ68ZvdGtVCpRVlY27+qLK8zXkJakKAyN65HuwMYfbfNCe1bSOcXx8fGIjU9A1ziJivQYn7xADI3r8e8TQ7j5rKwZ0X9KrRF1AxNYuyR+2t+yqbMPPUNjuGBNlUOvLUlReOvHAVSlx6AqfXoVWK034+JXfsIzl5aiJMV9VUSDwcB8buiWl1AohEAgsPs+UevNePjjNhSGTmBdecaMXN89tSNIjw3FiiznWt/eQK4x4qnPu3DlyjQUJdn/O0ulUvT09KCiosJj1R+j0ci0ijUaDQQCAdMqPtE/gd21w7j5rGzWvQVJkkR9fT1iBAK8XKtFCJ+LBzfaFxc/9SpROziB60+beU3wB+YSf7YwmUxQKBSQSqVQq9WMcXtcXJzHzuutra3YsWMH3nvvPZSWlnrkOT3Awl8CsWRiYoIJg2djZdtdRtD0cRYUFCAhYfaMTXdiL9kjIiICERERyMrKYi5qbW1tMBqNiI+Ph0gkQlRUFKsnqFP9EzD/T4TOBUmSTBu0srLSK/MkKp0JV71Vi61Lk/GrFY4vFlnyxGed+KxFhld/WTHrYgWdAGFp82KZUzzY3wezRoNuvevzT+6kbWwSoxN6qHTmGQIwNjwYZxf8/Bmghb1pUoULT1/qVPW+bWwSfQrtDAEonTRAYzDjaK/SrQIwJCQEaWlpSEtLYzZXLU2ObaWRkGYjlAoFEqtSZ4g/ALikyj3JP+6CA8y6QDU6OoqBgQFUVTkm7AHg6S+68FmrFAduWjHrIs9sBAcHIyUlBSkpKSBJEuPj45BKpejs7IQOwRDweRA40ezQGgkMjeuQL7I/t0gQBOrr65GQkID09HRUyoaQO8cC1ZtHB2Awk7hmdTqO9ylRlhLNyqKNJ3BF/AFTiyS2ogPpRRI61jE8PNwtorijowM7duzAO++8s5DEn10WVAXQbDaDIAiMjo6iu7ub8ZBiC7YrcWNjY+jq6przON1dAXQl1o32TZNIJJicnHTI4JhtaCuQhIQEm5VTNuiUanCiT4nLlqbafXyjmcS2107gypXpDl2kCZLC4cYxrMqJhTByquoxoNRhX90Ibj7LfluIbpXNZfMy29ygKxYiFEXhi1Yp8hMjXTLcnXZsFAUTQSKEP7uYow2eSZJ02KrJEiNBgsuBTZFgNJPg8zgeyZ22xvKiJpfLGfufyMhItLW1YcmSJYiL85/NT1cZGhrC6Oio07Y2W189AbXejI9vWTnj86gzEfOae7XVjqQFx2w3uf/4ugddMi12XlRgU6DZirL7/d4myCeNeOOqKrvHYzSTMBIkVDoz/t/BVpyWE4er12S4/Pt5ClfF31zQiST0+Mt8lnxs0dvbi8svvxxvvvmm20a9vMjiaAG3tbVhYmLCLX5ZbAkx2tqBNjqd6+73hx9+wOrVq90icNhI9rAWHHSFIyEhwW1bqVqtFg0NDcjOzoZIJHLLcwDANe/UQq4x4b1rqqcZTLvCoFKH/eJRXFyVhCc+68LpuXG4uMoxW4GRkREMDAw43SqznBukcz2djT8zEiT++GELwoN5eGiWlhVb0D6dkZGRyMnJ8cv2l6PodDoMDQ2hv78foaGhzLytN+ef3E1/fz/kcjnKy8tZOz/0yrV44aseXLE8dU6fx7kwkyT21o7igsI4aCemUi8mJycRExPDtCMtj1upNaJLqsWyzJnPazabIRaLkZycPM1C5Jq3a0EBeHMWAUhDURRqB1TIF0X6fAVQpVKhpaXF7Uk1thZJ6LlOV0TnwMAAtm3bhldeeQUrV650wxF7nYUvAOnWZH6+e7JP2RCABEFMDQGHhKCgoMChO5djx45h6dKlrApadyV7WFc43LFEMj4+jpaWFpteYWaSxKEGCX5RIpyzyuQIar0ZErVhTlPmcZ0J0aH8WatKz33ZjcONErz8y3IE8biIjwhyqBLW09MDlUrFygXTMv6MnhsUieb2GxybMCAqlD9vk9+5oKu6iYmJTLVkIUNXS+iNe9piRq1W2xUcbFI7oMLxXiV+c7rrXpmOQr+XJycnUVpaOuu5b3RCj/BgnsNxiGq9GU9+3onfnpmNxGjHbpBIikKPTDvjs32sR4m/ftyO60/PxKbyqTlbkiShUqkglUqhUCgQEhLCLPnYExxmsxl1dXU2c4wXIp4Sf9ZYVm7lcjkIgnBqkWR4eBhbt27Fc889hzPOOMNDR+1xFr4ApFvA7mK+AlCv16Ouro6ZDXKUEydOMBcINvBkrJtWq4VEImG27+a7RELHYZWXl9s88R7tUeLpL7pw/emZOK/QsdnPbzvleOGrHvzf9vI5PfpsoTMR2PbqCUSF8vHeNfZbBzoTgRGVftqG62zQG+wcDsfhmwVnoJ37JRLJnH6Dc0FRFP7+RRey4sNxiYNVTWv0ej3EYrHbq7o0R5olON6rxJ8uXOKVdrBMJkNnZ6fNVpm14AgNDWUEB5vLEmc/8wPMBIUvbl89b9/C2aCzbo1G45yehhRF4Z59zQjmc/HwpiK3HdNnLVIcbhzDLWuzp4lAM0mitl+FstToGXOqNFqtlvHqNJvNTKuYFhwmkwl1dXXIyMjwGS9Sd+It8WcLZxZJRkdHsXXrVjz55JM4++yzvXTEHmHhL4F4omXi6rbn+Pg4mpqaUFRU5PSMD5sLKK7M+82H8PBwZGVlMUskMpnMpSUSy0pYdXW13Wro0owY3Ht+HkpTHI9w0hgJUNTcVh/2CAvioTI9BhtKZxctYUE8h8Wf2WxGQ0MDYmNj55VkMhuWzv2WLZX29nZmbjA+Pt6hAX0OhwOJ2gi5xuSSAJycnERjY6NLBs+u8m2nHEYzZfvMCAAUCehVAJcPhLC7MEIvQNjL9eVyuYgRCMALi8SSJUumpZGQJImEhAQI4uIRGzO/VvH+G5dDqTWxJv7GdSYIrHwK6bgz2uJqruPlcDi4YnkaYsPdu/W5MlsAPpeDzPjpgoXP5TL5y/YIDw9ncqRpwUHnSEdGRmJiYgI5OTkB8ecFbC2SyGQy9PX14eDBg+ByuaipqUFycjK2bt2KRx99dKGLP7ssqAogQRBujWtztRU7PDyMvr4+VFRUuFT5qq+vR05Ojkvu+JZ4WvzNBr1EQt+lzbZEQpvi8vl8FBQULNjZKBqDwYDaujocH4/AhVXZyBe5vsj0wckhRITwcVGp7QtRv0KHT5ol2LE6nUkVYGNu0Bnolr5lAgRFUdhfP4rqdIHDyR2sQVHgDp8At+sLcAwqgKJACTJBLFkPSpA574d3NNf3TwdaoDUSeKymeJpAMxqN2HWsB8//MII7q4JQnhHvExvf33cpsOvUMG5Zm428/1XU6M+uK4kX/ojBYMDJkycRGRkJnU6HoKAgpnLrC+KIbXxN/M1Fb28vPvzwQxw5cgStra1YtWoVbrnlFpx11lk+ZULtBgIVwPlC5wE7KgApikJHRwcmJyexfPlyl2f4uFzuvCuAFEUx4tgXbEH4fD5zl0ZXnyQSCdra2qbZZNDGqcFRcahXByOPosBfwBcRuhKWmZOH/3wzikONo/jdObkuP94r3/WDw4FdAfhDtxzNI2pojQRiwqbeF7PlFDszN+gIUqkU3d3dM/JBJw0EnvisC6LIYOy7cX7emzoTAYOZnFGZsge357/gtR8BFSkCFZ025WWilYF//P9gXn4DqNhsl46DrmKr1WpUVVXN+Tn81Yo01A6oZlTngoODUZqdhJCfZDhrZTX4Zi1TuaXTSOLj4z1u3F6YFInSlCikCqZeR/qzGx0djexs1/5m/gTt51pQUID4+HgAUzO3MpkMLS0tTNdDKBQiJibG78Wwv4k/AMjKysKOHTtw4MABvPjiixAIBDh06BDuvfdeZGVl4aKLLsJFF120KGY2gQVWASRJEiaTyW2PX1dXh/z8fIesZcxmM+rr6xEZGTnvpZSWlhYkJia6ZA/hyXk/NqCrTxKJBBKJBHq9HikpKWjRRuKjRhn+eGE+U11YaNA2L6WlpYiMjMSkwYwQPtfhvM9BpQ7Pf9WD36/LQ0Lk1MVfrjGCx+FAYKedZiZJ6Iykw9uF9NygVCpl7H9crT4NDg4yViC22sw/9SqRI4xAvAtzmZac+ffvQVIUvr3ztLnf/4YJBH3zKKjIpKnWryX6cSA4CubVtzl9DHSuL0EQKCoqcsvnkE4joWfTXE0jYQPa+kQoFCI9fbo3ZuvoJFIFoTPecxqDGXvrRnD5slSfyrgdmzDAYCZnrUTT892z2fiYzWZmNm1iYsIrJsds4Y/iD5jy3b3kkkvwu9/9Dlu3bp32vfb2dhw8eBARERG44YYbvHSEbmPhVwDdjaOzeFqtFmKxGJmZmdNW/939vNb4m/gDfq4+EQQBmUyGsrIyaDQaJI4PY3M6Bd6kBNqIRLutdJKivDLQT6M1EtgvHsHmimSnNmZpm5eqqiqmFeFsHJVKZ4aJIDFpMDMCcC7xxOdyERXq+MWWjblB60qYvQ3XueawHOV352RjRGVw6P3PVXRPVfysxR8AhArAUQ0CWhkQ7rhpu2Wu75IlS9z2OeRwOIiKikJUVBSys7OZmduOjg7o9XpmMzImJsatXQB6+5U2W7ZEayTwf9/0QBQVgvsvXDLte0eapfjn0UHkJkRgTa7veCE+9UUXCJLCkxfbnl/U6XQQi8UoLCyEQCCw+zh8Ph8ikQgikWiaW0Jvby/4fD4j1t2ZssQGExMTfin+Jicncdlll+Hmm2+eIf4AYMmSJbjzzju9cGTeY0FVACmKgtFodNvjNzc3Izk5edYhdYVCwViUzHYycIauri5EREQw0V+O4I/ij2Z4eBiDg4MzNn3pC5pEIrG5RLKvbgQfikfw7NYyuxUvS+Yb32aLU/3jePPHAVyzJmNGCgVJUfiuU4HT8+IYkUqnXYyPj6OsrIx170p3QwtuuvokkUhmnRukFwIAoLCw0KfelyRFgT98ArymPaBibCe6cCaGYF51G6goxz6LdAJEbGwsk+vLNhK1AcLI4Fn/lnQaiVQqhUqlsptGYjATNq2JCJKCUmtibizsQcdvZmZm2l2AqB1QISMubMbNid5EQDw4gaWZMS6nfLiDfoUOBjNhM+mDFn9FRUWIiYmx8a+n0zSsxpLEiBkVTtrk2Do60N1i3VkmJibQ3Nzsd+JPq9Vi27ZtuOqqq7Bjxw5vH443WPg2MO4WgG1tbYiPj7cb2TYwMIChoSHWHdB7enoQEhLicDXRl5Y9nIE2yFar1SgrK5vV+8xsNmNUIsM7R/tRHW9GZmIcenSh2NWgxP9dUe6QB+Av3zwJDjh49+pqm9+f0JvwyJEO3HRmlsMJGARJYUxtQGJUyIxEj0+aJXjmv92467xcnFcoZGxeakcNaFCF4K+bC33qwjcXn7VIcLhRgv93UcEMwa3X6xm/QdomIz4+Hr29vcxMmC+9L/sUWjz9RTduqgxBac9roGJsJC4QRnD04zCddT/Am7stbTKZGBNgW9FubDA0rsOjn3RibX48Lq12/PxgnUaSkJCA12rV+KZ7HHt/s3yGHdJfP26HRG3AozVFdg3R6Rm43Nxcr8ZaegqtVov6+noUFxfP8CO1RbdMg/sPtOKCIiF2rLaf6GEt1iMjIxmTY2+2iicmJtDU1ITKykq/En86nQ7bt2/HpZdeit/85jfePhxvEWgBzxd7rViSJNHW1gaDwYDly5ezbtrqTAvY15Y9HIUgCKZNVlFRMac44PP50PIi0TLBR1leBoTCIEAqxfX5enS0ttisbljDsW8AAgBQ6wlojQSGx/UOC0Ael4OUGNvi/4y8eJhJCmty4hibF4FAgEFzEPRmg1db164gjAxBEI9rs9UdGhqK9PR0pKenw2QyQSKRoK6uDlwuF6GhoVAoFF7fWrUkhM9FMI+L0LgUUMpMcNQjU3OANBQJjnoYRP6FDok/g8EAsViMrKwst3oaJseE4uwl8TgzP97hf0NQFMQSM07LzUVeXh6zqJAeNAnCZIJ0qA+8RNE0E90dq9JRO6iyK/7oSpg/Rdm1jKrxz6MDeGhDodM2OBqNBvX19SgtLUVUlGMWQVnx4fjVijSszp59tIHH4zHVc8uN/Nra2mlzne7Kw7WFv1b+DAYDrrzySmzevBnXX3+9tw/H5whUAJ3AViWOvsuPjY11W2zV0NAQTCbTrC0kf275Go1GJv3BemB8NiiKwuC4HonRIQi2sjChW5HuSCKZL7Q4SE9PXxTbZrTBc05ODuLj46dFOEVEREAkEjnsN+gRDBPg1709Ne/H4U75AYICmbYSROFmgDv7DZ6jYmhCb3I46YJNjvYo8c6xAVy9OmNGfJm1PZMjaSS0GCouLp7RBh3Xmhwax/AGT33eia865PjnVVVOGcBPTk6ioaFhmm2Rp6DHYKRSKXQ6HeLi4pCQkODWmyla/JWXl/v8fKIlRqMRv/71r7F27Vr87ne/86trohtY+C1gYOoD4i76+/sBABkZU+V7jUYDsViM3Nxctxp+jo6OQqPRIDfXth2IP4s/jUaDhoYG5OfnM9YJbEInkUilUgBTSSQikchrJzLa5sWXKiUvft2D/eJRHLhphd3kA1ehL5ZFRUUzZmKt5waHtcDTJw1456pyZAjnnqdyKxQJjrIXHNUAwOWDjM8HIueu5NG/r62YQktaRyfx/Ffd+PWqdKxwYNmFpCg8/UU3zilImDFb6ixGM4mWUTWKkqOYGydbUBSF8fFxyGQyyOVyhISEgAoTIDs1EbFRU58ftVqNxsZGm5WwXrkW171bh4srk/Hbs3zPBsZIkNAZCcQ4aA8E/Pz7lpeXe3yz2hqCIKBUTmUV0zdTdKuYrZtdfxV/JpMJ11xzDVasWIF77rnHr66JbmJxtIA5/xtIdwd8Pp8RmHSiRVlZmUPzH/OBx+OBJEmb3/Nn8Wdte+IOLJNIjEYjpFKpS0kkbKBUKtHW1ubW39cVhsb1ICmwHgWmVCqZnFtbv6/l1mpubi721w7CTHbjWEMbRiPBeKax/fo4tCnO4YKKywEVl+PQY3ZIJhHJMaCvq8MhcZAqCEWeMMLhZBiDmcR+8QgONozhyzvml0cezOeiIm1uEcnhcBAbG4vY2Fjk5+djQj2Jja/UAmQfnjgrHJGRkVAoFKisrLT5+qbEhCI9Ngyn58XhpW97cUllMoRRvmO2G8zjIjjM8fc8PQM3FJQCntSIFV4WgDwejxF8lhZAYrEYAKZZALny+aF/X1cDDLyF2WzGDTfcgIqKioD4m4MFVwE0Go1uE4BjY2OYmJhAUFAQ4+TvCfdwuiVTWFg47ev+uuwBTLW1h4eHUV5e7nEHdoqicPeeJhTF87BKSDBJJO5MU6BtXuxlGM9F84gab/zQjwc3FCDCSXsYbyCRSNDT04OKigqXfl82/QYtGZ3QY9urJ3HTmZnYvtzxPO7ZUOvNuOODOkRDh0e2LXdLWgoA/PNoP77vVuLedXnTsms9ya5Tw8iOD0dGmBFtbW2IjIyEXq+f9fXplWvx+GeduLgyedZ8bjNJok+u89rvNhvj4+NobW1FeXk57jvYBT6Pi6cuKfH2YdnFaDQyrWKtVovY2FgkJCQgLi7Ooc8PXen0N/FHEARuvvlmpKen469//atfXRPdzOKoALoTDocDiUSC6OhoLFu2zGMD7LaWQPx12YMOhddqtaiurmZ9YcZRzBTQoiBx3dmlM/zs7FlkuIKlzctsGcZzMTiug95MwkT47j2ZQmNEXEQwBgcHMTY2hurqapfn+mbzG5zP3GBEMB9cDpAQGQKjmYSRIJ32W7RGMy7D6UITLlhV5TbxBwAXV6YgOz4CWfHeuyBvrU6BTCZDV1cPVqxYgZCQkBmvT3h4OPP5+aFXjdU5AvxlYyFiwmb/Oz90qB1He5R486pKpAp8Z9GArtzT7g5/2VToU0bVtggODmZ8GOnXh/aEDA8PZyqHtm6+/VX8kSSJO+64A4mJifjLX/4SEH8OsOAqgCaTyW67dD4YjUacOHECXC4XK1eu9OibS61Wo6enB+Xl5QCm7nL8seVLEASampoQFhaGvLw8nzx2W0sk9Eaes5VKejucoigUFhb6lVCfixN948gXRTDzUx0SDf7+eSfOSOWiRECitLR0mrjXmQj0yLQoTnZsY9Ie1nODlhuTzm4n3rm7ESaCwnPbSl1+Lw4MDEAqlaK8vNzvPBxdYWxsDH19faisrLQ5Z0ZRFDQaDaRSKX7sGMP/1elRUxKLG9fmzdkWH1Tq8EmLFNesTveZcwM9psK2tZe3oF8fmUwGmUwGkiSZVnFkZCQzo+yP4u/3v/89goKC8Mwzzyyocy1LLI4lEHcIQLVajfr6eqSnp2N8fJwRYp5Cq9Uyd6D+Ou9nMBhQX1+PlJQUt3miuQOtVsv42VEU5fASCW0ALBAIkJWV5dBr5e0UE0cZ15mw5aWfkCIIwb+uXgoA0BpMePJgLdblRGBV5czEhGvfqUOnVIM9v1k+p5mwM1j6DZpMJuZi5sjc4I/dCsg1Rmwoc9xgncYyzaSsrGxRXHCGh4cxPDyMyspKh8QuQVI4KB7GkhgChgmFR9NI2EAul6OzsxOVlZUeH1PxFCaTiWkVq9VqGI1G5OfnIzk52WvdGWchSRL3338/DAYD/vGPf/j8+8pLBASgK0gkEnR2dqK8vBxcLhdtbW2oqqpi7fEdwWAwoKGhAVVVVX4p/nxx89USiqLwwalhrMmJQ3qs/SoSvUQikUhgMBgYsWHplwa4ZvOi1Bpx5Vu12LY0BVetdNwKx1scahxDZVoMUgWhIAgCDQ0NiImJsSt2+xU6fN+lwPbl7hP/7pgbNJgJdEq0KEn5uXJJURTa2tpAkiQrub56EwGSglPRgbPRp9AiMoQ/7wxlS+hKZ0VFhcvCwFYaSUJCgsOtfIqisKd2BJXpMW7PA5dKpejp6bFb6ZyNca0Jr33fh5vOyrLrm+hrqNVqNDQ0ICsrC5OTk1AoFAgJCYFQKERCQoLPVj9JksSDDz4IuVyOV199dV6i9ZprrsHBgwchEonQ2NgIANi5cydeffVVCIVTs6uPPPII1q9fDwB49NFH8frrr4PH4+G5557DBRdcMP9fyH0EZgCdgb7Dl8vlWLZsGYKDg2EwGFzK5J0vXC4XWq2WOWn6k/iTy+Xo6OhAWVmZ120T7DGhN2P3qRE0Dqvxl42Fdn8uODgYqampSE1NZfzSBgYGpi2RBAcHo6mpyWmxGx7MA5fDgZDF6pg7uah0yvbIZDKhrq4OqampsybVZMSFISPOvZXfueYG6YuZo2JjWKXHF60yfN+twJ/XFyBVEDot17egoICVz+L6F4+Boih8ecdp834siqLw+KedCOZx8fTW0nk/HjDlfzoxMYHKysp5VVfsGRz39/c71MrXmUi88UM/woN52P2b5S4fh5kkwZvlJloikaC3txdVVVUuzbCKhyZwsl+F1tFJLM0QuHycnsJy5s/yHE23ipuamkAQBJOCZX3D6y0oisKjjz6K0dFRvPXWW/OuWO7YsQO33HILrrrqqmlfv+OOO3D33XdP+1pzczP+/e9/o6mpCcPDwzjvvPPQ3t7uN1VTmgUnANl4YxIEgcbGRgQFBWHp0qXMSc+ZRA62oCu0eXl56Ovrg0ajQVxcHEQiEQQCgU98EO0xODiIkZERVFdXe92Emf472vp7xYQF4W9bipDohEUFn89HYmIiEhMTQZIkxsfHMTAwAJlMhri4OJhMJpjNZofnwkL4PBy4aYXDz89mjnHj8ARe/b4fj28pcihCjyApPPdlN07LigIl60FOTg5zhzwXar0ZoUFctw/Rq/RmxMXFIT4+ftrcYG1trUNi493jQ3jlu148vKkI2QnhSIkJcVuu77bqFGiN7JxXOBwOfnN6JmLD5/95oxe2DAYD0+Y2EuSs3oGOIB5U4a0fB/DXzYXIzc1Fbm4u08pvaWmByWRiLIAsxUZ4MA9Pby1FYrTr7ViSorDt1ZPgcTnYdf2yGd8fGxtDf3//NPFHuwZUpcfgVw5U50/LjUVBYgREPmR5Y4/ZfA0jIiIQERGBzMxMprpO3/DGxMQw1VtviB6KovDUU0+hq6sL7777LivHcOaZZ6K3t9ehn92/fz8uv/xyhISEIDs7G3l5eTh+/DhWr1497+PwJAtOAM4XOrUgOTmZMXym8bQAtFz2oMUG3UYZHh5Ga2srYmJiIBKJHF7v9wQURaGjowN6vd6rm76W3L6rERwAz24rs/l9R/3YbMHlcmE0GmEwGLBmzRom+qy3t3deSyT26JRq8PcvunDPujxWNkI/FI+iaXgCkwbCIQFoJEgcEI/gk/oB/OeaqhnpD/YgKQr37GtGMJ+LZ1mqTtmiT6HFwx934KLSRGyuSJrhN2gtNmzNDZ5TEI92ySSWZQoQHsxjEn/ozUpbUBSFD8WjWJUdi2Q7cYC2uPHMLDZ+bQZHPP7mgm5zUxSFkpIScDgcaAxm1Lz0E4qSI/Gcnc+RI/TKtdCbSVhOH1lGB1pX16Ojo5mt4oLE+flncjkc8LkcrMmdab49MjKCoaEhVFVVTbtx43A4MBAUTvSrHBKAfC4XSdG+2TK1xBlTa8vquqVBeHd3N3OOS0hI8EhMHEVReP755yEWi/Hvf//b7ctXL7zwAt5++20sW7YMTz31FGJjYzE0NIRVq1YxP5OWloahoSG3Hoc7CAhAC1QqFRobG1FYWGgzlcJT1bbZzJ2t2yjj4+OQSCTo6OhAZGQkY4/hrY1EunoaERGBsrIyn6lQcjkccN1wKBRFoa+vDwqFgrF5CQsLQ3R0NPLy8pglkoaGBqeWSGaDx+GAx+WArT/tPefn4Zazsh2O7NJPTuDuKi5WVFYjJsZxE3Quh4NzCuKR7aRobRlVIyMuzOF5qpSYUFSkRWN5lsDm961ziuVyOfr6+qbNDSbHxjLjAI7m+somjXj6i26UpkbhH5d7dlGMTUiSREtLC4KDg6dt64cH88DjcXD2koR5Pf7mimRsrrA/G2tZXacoCiqVClKpFN3d3azMpX1go/I3PDyMkZERuwsuL1zmuuD1Rei5bFcSTawNwrVaLWQy2bTqbUJCAmJiYlg//1MUhZdffhk//PADdu/e7fb4yJtuugkPPPAAOBwOHnjgAdx111144403bHoN+8q1zhkW3BIIQRCMP54zjIyMMEO/s12cf/jhB6xZMz8n/tmgxR9BEOByuQ6/qSztS2QyGUJCQjyegavX61FfX4+0tLRZ58EWChRFobW1lVkGmKsC6+gSiS9iME9VB2kbEE+ZoKt0Jty9twn5okjcsy7Prc9Ft/IlEgkTrSUQCDA0NISCggKHZjp/7FagMCmSlRasNyBJEg0NDYiKikJ2drbPvS/pGyqZTAaCIKZZmLh6rIODg4yxvy90K9wNHVfojjg7unork8kwMTGB6OhoplXMhqfqG2+8gcOHD2Pfvn1uWUzp7e3Fhg0bmCUQe9979NFHAQD33XcfAOCCCy7Azp07fbkFvDi2gJ0VgPScy8TEBCoqKuZ8k7pTALKZ7KHRaBgxyOVymcqTu7a51Go1mpqaUFBQgNjYubNN/R168zU6OtqlCyV9oqTtF9yVRGImSYxNGJEqcP1175Bo8MRnnahZEoZErhrl5eUu3XnrTATCXMga/qFLgSWJkazax8wFRVEYGxtDW1sbgoODp7XyPdHm8gb0jGN8fPyM8RdfxNLCRKPROJ12AYCZ2y0vLw+IP5ahKAoTExOQSqWQy+Xg8/lM9daVDsjbb7+NPXv24MCBA277DFoLwJGREcbJ4emnn8axY8eY5Y8rrrgCx48fx/DwMM4991x0dHT48nsosAVsjdlsRkNDA8LDw1FdXe3Vu122Y90iIiKQnZ2N7OxsZuaJ3uaixSBbJwCpVIquri6f3vRlE9rTcK7N19mwtUQikUjQ3t7Oaiv/+nfFGBrX44Prl0HwP9Pm0Qk9EqNCHH6PxYXzQRh0CDaTqFpZ5dDFlaIoSNRGZmD/pW968cGpYbyzo8rplIc1uZ61DvqxW4EQygCjtA/Lli1DRESEQ3ODehOBq9+pw53n5GB5lm/cBBnNJA41juGi0sRZs57NZjPEYjGSkpJ8xqfzsU86EBMWhJvszEgaSA6SkpKQnJzMfIakUimTdkGLDXsdkL6+PkhkCrzTycfWqHGckTdz7McWZpLEpJ5weGTCV/Ck+AOmWqIxMTGIiYlBXl4edDodZDIZ2traYDAYprWK5zqnvP/++/jPf/6DgwcPuk38bd++HV999RVkMhnS0tLw4IMP4quvvkJdXR04HA6ysrLw8ssvAwBKSkqwbds2FBcXg8/n48UXX/Rl8WeXBVcBJEkSJpNpzp/T6XSoq6tDRkaGUye8H3/8EStXrmS1SuPJZA86I1IikUCv18+7DTkwMICxsTGUl5d7fdPXE2g0GjQ0NCA/P9/mnOh8YTOJBJiq3n3RKmUWDdrGJvG3TzuxtToZF5Ykzvnv6XkwHo/nlO3JgfpRfCgexR9/kY88YQRO9I3jj/tbcOCmFQh1oQroKUiKwrX/PAGjXovXd6y0WTE3m81M5clybpAbGomal0/grPx4PDSLnZA1s22oz5ejPUq8+l0frj89E6uybYtS2sonPT0dSUnOm2K7i9/+ux4cAC/amKfUGMy47PWTyIgLmzZvSf8t6TQSmUwGAMxnKDw8HBwOBz09PRiSqVBYWIg/HmhDYVIk7jw316Hj2vF2LQwmEv/cUTXvjWhP4WnxNxcEQTCtYpVKhcjISGbRx7q7sGfPHrz66qs4dOgQoqLmlyS0iFkcLWBHBKBSqURzczNKSkogEAicevzjx4+77A9lzWzLHp6AIAhGDNIXMtpeZi6BS28Jms1mFBcX+8wGsiOYSRIcTC1SOIJSa0RkCB+TEyq0traitLTUrScitd6MPbXDuGJFGsyGqcrT8KgEfO7PFzJXT+JGM4kPTg7hwtLEOY2CLW1PMjMznXp/SicN+KRJgsuWpfp8bqolIyMjONnWj2WVpRBGh8/5HrGeG+SHhCM5UYhEkdDhc8R5z/4AAPj8dvZHS0wEiU6pBnnCCJuvg8FgQF1dnVNWPr4ARVH4zXv1+PXKNJxuUbmbEo0cvHj5z0sb9OytVCqFXq8Hl8sFj8fDIyem5qxt2cHMxqn+cZzoG8dvzshi69dxK74m/qyx9ISUyWR46KGHsGLFClx88cXo6enB888/j0OHDjl9rQ4wjYAABKYGfgcHB1FRUeFSKfnkyZMoKSmZ9yydt8WfNbRx7tjYGFQqFaKjoxl7GevSNt06j4mJ8clB8bm46f16cDhwaFPTTJK44o1T4JBm3FXJRXl5udtd8T8Uj+Dlb/uw86ICrMyOxYTehLt2N2NpeiQ25oUyFzJ3LpEYjUaIxeJ5tbn9Dctc32+6xvGXw+14/coKhy2CaL9B+kLmaE7xec/+CAD4/HbPDpDrdDqIxWJWE3pIisLL3/ZhdXYsKtPnb0fjLDf/ux4cDsfm1i5tTzUxMYHw8HB82aGAIDIM55akTqs86UwE+FyOX9242IMWf2VlZYiMnJ+Fjqfo6enBhx9+iAMHDqC9vR1XXHEFtm7ditNOO83tW78LmMUxA2jvQkhXrPR6PZYvX+5yv57H47m0ZWx9LGzO+7EBl8tFfHw8Y5yrUqmYGDzLFAW6KuRMzJmvkScMd9hShMfhYFUyH0nBBGPz4m4uLBEhMy4c5alTFiuRIXyEBHGxPDseqakCpKamMi0U2itNIBBAJBKxskRCC4O8vDwkJMzP8sMfoCgK3d3d0Gg0TNpFTBgfPC6cWlqx9BvMyclxaG4Q8LzwA6a2acViMYqKipjKykvf9qJTqsETW2ZmOTsKQVI42T+OllE1nkv3vHWKrXYx8LP4M5vNWLp0KTgcDoqKZqaRJCQk4O5PxxDM4+Ff1yz18NGziz+KPwDIzs5GWVkZ9u/fj/r6ejQ2NmLXrl24/fbbUVxcjA0bNuCiiy4KVARZYMFVACmKgtFonPY1k8mE+vp6xMTEIDc3d16Cq7GxEenp6Q6b39o6Pl8Tf7NhmaIwNjYGvV6P9PR0ZGRkLNiAdBr6poEgCIdsXrwF3YbsGxqFWjWO2Jgol5dIaHPY4uJil9/jzjCuNSEmjO+1zwHbub72oLe+6XELNgW7s9DCwHqU4YLnfwRFAZ/eNiVIKYrCvR82IzMuHDefle344xvMCOZzHZ6PMxEkbt/ViItKRLiojP0ZRIqi0N7eDoqiZp1jpQX7i9/2IzaYwiWVSW7zs3M3/ir+AODrr7/Gn/70Jxw+fBiJiT/PKVMUhYaGBnz00Uc499xzpxkxB5iTxdECthaAGo0GYrEYOTk5rAw4t7S0IDEx0aWWCe3vB8BnxYQ9JBIJuru7sWTJEma1HwBEIhFEItGCs8agbV7oao6vXwCmZqLE4HE4eHxDNtOGdGaJRKFQoL293WPb3JMGM279TyOyE8Lw5/UFbn8+a0iSRFNTE8LCwuZ9Y+js81r7DTqTUzwfVCoVmpubbc6DkRQFisK0uccb3hODy+Hg/7a7z9iapCjc8C8x0mLD8P8uYvd9QHt1crlcLFmyxOHX2Gw2Q6FQQCqVMn529JKCr297ajQa1NfX+6X4+/7773Hvvffi4MGDi2b0xEMsDgEITA02A4BcLkdrayvKysoQHe14YsFstLe3M1t/juJr837OQFEU+vv7Ga8sywuUwWBgjI3pFldiYiIiIiL86ne0xmg0oq6uDskpqUhPc68lBkVRoDCVkjFf9tYOIz4iGNJJIyb0ZlyzJoMxzpVKpUwSia0lktHRUfT393vM4BmY+t1f+LoHvygWIV8UCYqi8F2XAqtzYsF38w0SPcoQFxeHzMxMuz83NK7Dh+JRXH96pls2Pp2ZG5SoDRBGBs/52WoaVuNk/ziuXJk27WeVSiXa2tpcnn/2NyiKQnNz84xEE1ceh04jkcvlrKSRuAt/Fn/Hjh3DnXfeiQMHDiA9fe7IvQBOsbgEYH9/PxPtw+YFraurCxEREQ5XE/1Z/JEkOa09NlvVkjZllUgk0Ol0iIuLg0gk8rv2CW3z8mobH1weHy//soIVcWaPG94Tg6KAV35ZwdpjbvjHMVAUcOjmldO+br0NSc+kjY+PQy6Xo7y83GsRggDwQ7cC9+9vxfWnZ+CK5Wluex5Hcn1p/nV8EJ+2SPG3LUUeyXel25BSqXTa3KDSxMeOt+uwrigBf/zFklkf47fv10NnIvDyLysY0SqTydDV1YWKigqfEy3ugKIoprrLdgXfOo0kPj4eIpFoXmkkbODP4u/kyZO45ZZbsH//fmRlZXn7cBYii0MAkiSJuro6EASB0tJS1lutvb29CAoKcsg70J/FH73pKxAIkJWV5dSx0wsKdPvEm/NOzjA+Po6WlhaUlpbiP/UKnOxXOdz6MhEkPm2W4NwiIUL5jreIdh5sg8ZoxhMXl+DzFgn4PC7WzjNrVWM0gySBqFD7Yo62AOrq6oLBYGBMqb35GhnNJD5qGMN5hQmICXNPK3RSq8N9H/yEX67KwqrCudMujAQJlc4EYaTn510t5wYn1Gr8s42D605Lx7K8lFlfI72JgNZIIO5/Nj90fF9lZaXfe3U6kiZDkiQaGxsRGRmJnJwctx4PnSVNe0IKBAIIhUKn0kjYwJ/Fn1gsxg033IC9e/ciL8+9cY+LmMUhACmKwtDQEBISEtwiuAYGBkCS5KxtI/o4/GnZwxKdTof6+npkZWVNG8J1Bet5p6ionxcUfGmWZmxsDL29vS5XSD5ukuCBj1qREx9uM2zeEba8dBzgAPtuWOHSv3cGkiTR3NyMoKAg5OXlMVvfSqWS1SQSX0Kr1eKbn8R45IQZZy0R4i9OmDV7G8ukC4VC4fDc4PDwMIaHh1FRUTHt5yYNZty9pwn3np+P7ATnY7m8wX/bpLhnbzMeqSnC+UUimz9DZxnHxMR4vJJk+RoplUqEhYXNmUbCBv4s/pqamnDttdfigw8+QGGh/3we/ZDFYwMjEokwh7B1GT6fD51ON+vPUBTFWMX4csXLFvSQOFtboFwuF3FxcYiLi2OyIemFktDQUIhEIgiFjpvmuoO+vj7I5XJUV1e7fBxrl8RjQ5kIJcmzz5rOlvrw8i8rbH9KWcbS4Jm+SFq+RrQ1Rm9v77yTSHwFert5TVUJ3isPQrwHc4XZwPpzRM8N1tbW2p0bpH0Nq6qqZtxsKbUm6EwE2iWTfiMAAQ4oTFnN2IIkSWau0xtZxtavEZ1GIhaLAYBp57M5I02Lv9LSUr8Tf62trbj22mvx/vvvB8Sfl1hwFUBgqixPkqRbHlsikUClUiE/P3/G9/y55Qv8XAUrLy/3yJA4fRGTSqXg8XiMGPTUjBJtD2EymTyWZrLttROgKDidPmALV9qTtMFzWlqaQz6Oji6RsIHOREBn0bpki/HxcWYZzF3bzf9tkyEjLgx5QvdtT1MUhU9bpChIjERW/M+izXpuMD4+HmazGTqdDuXl5XYr7SRFgQP3RNC5A4qiQFIAlzPzmOmbmoSEBJ9cIKAjOKVSKXQ6HbNI6Ejqkj0sxZ+/RaR1dHTgyiuvxDvvvIOKCvbmnwPYZXG0gAH3CkB63sP6jsWfxR9FUejr64NCoUBZWZlXqnE6nY7ZKHa30ACmLhiWc0Keer1+8y8xVDoT/nPd/AXgb/4lht5E4LUrKx3aUNVqtaivr3c5x9jeEglbSSTXvVsHM0HhzasqWXs9pFIpuru73br8YCZJXPuOGCF8LqvLPNYYzASu/5cYYUE8vHyF7ecxmUxobm7GxMQE+Hz+rDNpBEnh8c86cVZePNbkspME4g0IgoBYLEZiYqJTue7egiAIKJVKSKVSjI+Pz5qDaw9/Fn+9vb24/PLL8eabb2LpUv822/YjAgKQDcbHxzE0NISSkhLma/4s/kiSRGtrKwCgsLDQJ1rWtNCQSCQwGAxISEiASCSakaAwn8ent0D94YJhj/axSbSMTmJzxdwb6RMTE2hqakJJSQkrlkj0oo9EImEtiaRuQAXppBHritjJpB0ZGWFiH929/NAr10IQHgSBg8srJEXh+S97sDxT4JT46pZpkBAZjOjQmc9DV7Rp43KKomadGzQSJC568RiCeBwcvtk/TXXNZjPEYjGSk5P90jfOcuRCLpcz7fyEhASEh9tuzdMpLv4o/gYGBrBt2za88sorWLly5dz/IABbLB4BaDabGcNltlGr1ejp6UF5+dR2qD8ve5hMJjQ0NDBeaL547GazmbGX0Wg0jL2MQCBw6XhpmxdXq2D+iFwuR0dHB8rLy+1eVOaD9aIPXdFISEjw2hKJpXelvWMgSAriQRWq0j1vVUSQFK5+uxbBfC5e+1Wl0/+eoigYCRIh/9s4pz3vgoKCkJ+fP+P3sec3yI8QIC46AqFORN75CmazGXV1dUhLS2PF5N8X0Ov1TKvYaDQiLi4OQqGQsdPyZ/E3PDyMrVu34vnnn8fpp5/u7cNZbAQEIBtotVq0tbWhqqrKr5c96E3f7OxsiES2N+p8DZIkoVAomDnMmJgYpnXiyN/f0ubF306ernK8tQ/3H+7BK7+qRraIHTP02bCsaMhkMgQFBTGznc4ukXzfpUAQj4MVWbFOPT+d6zuXDdTHTRK8c2wAd52Xi6UZAqeOjQ20RgJ8Hsclg+nNLx2H1kjg0M0rwedMRVRGREQ4PM5ga26QzSq7uzGZTKirq0NGRsa8nQp8FWs7rfDwcExMTKCsrMzvcnBHR0dx6aWX4qmnnsLZZ5/t7cNZjNj8UPuXavEB+Hw+IzDNZjM4HI7fib/x8XHU1dWhqKjIb8QfMCWyExISUFxcjFWrViE5ORkKhQLHjh1DfX09RkdHGUFuzdjYGCPcF4v46+vrQ3v/GIKCQzFh9My9HIfDQXR0NHJzc7Fy5UoUFhYysXo//fQTent7odFoHHqsnYfa8KcDrQ79rMZoxn7xCJpbWmEwGFBWVsZ8Lk0ECYXGOOPfnJEXh1+vSkdZquPCWGsk8KF4BGYWRkzCg3kup4tsq04Bn8sBDxTEYrFDOee1Aypc924dtEYCoaGhSE9PR3V1NZYuXYqoqCj09/fj6NGjaGlpgUwmc9sYzXwxGo2ora2FLlyE+z8bgcZo+zPv79CLcSUlJSgvL4darUZcXBza2tpQW1uLwcFB6PV6bx/mnEilUmzduhWPPfbYvMXfNddcA5FIhNLSUuZrCoUC69atQ35+PtatWwelUsl879FHH0VeXh4KCgrwySefzOu5FyKBCqALj338+HEsW7YMXC7XL+6WLaEjv8rLyxdMIgBddZJIJJDL5QgODmaqTsHBwejv74dUKp0RZbdQoSgKHR0dMBqNHttudgR6E1IikUCv1zNVJ3tLJF1SDXhczrSNV3scrB/Fq1934PrlcbhoZfG0x7vg+R9hJih8fOuqece5fdIswVtHB3C3l6qGltDzb4mJiUhLmzs55a0f+/FZqwwvbS+3axLuqt/gfCFICltfPYHT8+Jw57m5dn+OFn+5ubn4oteAAw2jeH5bGeub476ErbavVqtlWsV0GolQKPS5Cq5cLsfFF1+MnTt34qKLLpr3433zzTeIjIzEVVddhcbGRgDAPffcg7i4OPzhD3/AY489BqVSib/97W9obm7G9u3bcfz4cQwPD+O8885De3u7T/nPepDF0wKmq3NsQ8/7tba2QqlUIjY21i8SLoCpY+/p6YFKpUJZWdmCMvi1hvbfoi0XQkJCUFZW5pb5N1+BoigMjuuRGhOC5uZmhISEzCv/1N3QSSQNPaOIoLTzWiIhCAInasVQIgLrqpeAx53+O3/XKcePPUr8ft38UwYMZgKto5MoSYlye17xbNAtUEftfFzBmZxiNp5ry8s/ITqMj7d/XW3zZwwGA+rq6pCXl7do5ndp8Tfb8pa9NJLY2Fivip3x8XFcfPHF+MMf/oCamhrWHre3txcbNmxgBGBBQQG++uorJCcnY2RkBGvXrkVbWxseffRRAMB9990HALjggguwc+dOrF69mrVj8SMWhxG0u7Bc9igsLGQ27CQSCdrb2xEdHQ2RSIS4uDifu8OgUx/4fD4qKip8XqzOl4iICISGhkKlUiEqKgrh4eFoaWkBQRDMBczfTFPn4u1jAzjcKMGVSyiUZYrmTKrxNjweDy0qHl5rMuH2tUuQGMuBVCpFe3u7U0skdK5vekoKVtrZAj09Lx6n57EjGEL4PFSkzd8gfT4YjUbU1dUhKyuL1REOucaI8GAeE7XG4XAQFRWFqKgo5OTkMHODLS0tzNwgWzZAHA4HH95oPwFHr9ejrq4OS5YsQVyc/1rWOANt2zTX5n5QUBCSkpKQlJQ0rYLb2dnpsTQSayYmJrB161bcddddrIo/W4yNjTE3QcnJyZBIJACAoaEhrFr183Z7WloahoaG3Hos/kZAADqArWUPDoczzfWdjtLq7OxEREQEEhMTfSJKy2Qyob6+HkKh0Cvu+N7Als1LRkYGTCYTc2J0pAXpT5yTF4vBgQFU5eUgNcU9FSG2qUqPwYayJJSnxyAimD8t5UIikaCvr2/WJRK6IuRPi0zzhRZCbG+xkxSFX75xCnweBwd/a9ueg54bTE9PZ3KKBwYGGBsgd2Xg6nQ6iMViFBYW+t3yg6s4Uvmzha00EplM5tY0EmsmJyexbds23Hzzzdi6datbnsMRbHU3/f08zzYLUgCy+SITBDGnvx+Hw4FAIIBAIGAuYGNjY+jp6fFq3Bl9B5mbmwuhkB1vNV+H/p3z8vKQkJAw7XtBQUFISUlBSkoKs2FHX8Dodv58nPm9hVarxVBnE248p9CvWmMxYUH41Yrps2uWVafc3FzodDr81DaIzv56RASBqeByOBzU19f7bEVoWKUHRQGpAvbmbOn3tjuEEJfDwVWr0pAZ59iYBJ/PR2JiIhITE6dVnTo6OlidG6R/56KiIlaiKf0B2qFhvp6dHA4HkZGRiIyMRFZWFjOD29XVxVoaiTUajQaXX345rr32WlxxxRWsPOZcJCYmYmRkhGkB0zeDaWlpGBgYYH5ucHDQL70i3cmCnAEkSRImk2lej8GWubNGo4FEIoFUKgWfz4dIJIJIJHJ7OV6pVKK1tXVRWZ7QOcbOnjhJkoRSqYREIsH4+Diio6MZexlfa+dbw5bBs1pvtrsY4E1MBImr3qpFSBAXr1xeAplMhuHhYahUKiQlJSEtLc0nK7hXvnkKFIB3r7Y9z+Ysk5OTaGhoYM3I213QVSeJRIKT3WOQ6zlYX57i0twgnXbh678zm9DVzuLiYrf+zrbSSBISEuYl2nU6HS6//HJs27YN119/PctH/DPWM4C///3vER8fzyyBKBQKPP7442hqasIVV1zBLIGce+656Ojo8PlzuptYPEsg8xWAtPgjCILVTV+dTgeJRAKJRAIOh8OIQba3cUdGRjAwMLCgNn3nQiKRMAbd8xlQt2znKxQKhIWFQSQSuX0L0hVog+eKigqHf2eNwYzwYN609/SAUocb/iXGxVXJuO40dmYHNUYzwoN4Tn12FBojrnjzFH53djZ+UfKzt9u3nXJkxIUhMy4cSqUSbW1tKC4uhl6vZzWJhE0ahiZAUhQr84ITExM4WtuIp+s5eHF7OXIS2IlHfPyzDkSF8HHTmdkO/fy41oR3jw/g+tMzGQPq2djy8nEYTST+sSkVcpnUqblBWvBa38B+2iLBh+JRPLet1KtLOO7AU+LPGsuxCzqNhG4VO7o4ZzAYcMUVV2DDhg347W9/67Ybsu3bt+Orr76CTCZDYmIiHnzwQdTU1GDbtm3o7+9HRkYGdu3axXQFHn74Ybzxxhvg8/l45plncOGFF7rluPyAxSMAKYqC0TjT98vRf+uJZA96oFoikYAgCEYMzmdTlTbBVavVKC0t9fr8oadwl80LXc0YGxubt6kx27gSc6bUGnHje/VYlR2LOyysNoxmElf9sxYPXLgEJSnzrxbTjxfC5+Kfv65y+N+pdCZse+0Erj8tE5dWz2zV2Mv1tbYumWuJRGcimEUHX2d8fBytra0IEuXi3o86cee5OVhfyo7x8a/ePAUOB3hnh2NVygP1o/jH1714aGOBQ+bc0kkD5JMmFCZNLVzRc4NSqXTWuUFa/JWVlc1Y1rrxPTFUOjPevbp6xra3P0OLP19odVumkRgMBka002kk1hiNRlx11VU4++yz8bvf/c7nqvEBAAQEoGP/zhuxbpbZt0ajEQkJCUhMTHRqUJckSTQ1NSE4OBhLlixZFB9COvvUZDJ5xO+OruBKpVJQFAWhUDhv0e4Kvb29UCqVKC8vd6qdQVIUbnq/Hr89M8upytTYhAHCqGBwnXhP3buvGReWiLB2ScLcP+wAtOCtrKycVeRbVjNsifZxrQlbXzuB1dmxeGhjISvH5i7oCm9lZSVCQkJAUgCX471BdqOZRJdMg4LESKfeC7aw5zcYGhqKtrY2lJWVISKCnUqnr+NL4s8a6zSS6OhoDA8PY/ny5RAIBDCZTLjmmmuwYsUK3HPPPYviuuOnBATgbDiy7OEJzGYzIwZ1Op1Dm6pGoxH19fVITExEenq6h4/YOxAEgaamJoSHh8+ZgOAODAYD8zqZTCYkJCRAJBIhMjLSbcfiacELTFmD3PhePUpTovD/Lipw+/PZwpFcX3tYi/bYuHjccngUf/xFAc7M992FGYlEgt7eXlRWVnrUvsMb0JX2gYEBDA8PIyoqCklJSW7xG/Q1fFn8WUOPxzz++OM4cuQIBAIBQkNDsWzZMjzxxBMB8efbLB4BCExdoB2BrWUPd0DffdFzTnFxccymKn2cGo0GDQ0NNrdeFyq04KWXALyNyWRiWiZarZZ5ney1TFyBrvCGhoZ61OCZoii8+l0fzi8WTUvk+LhpDOLBCdxzfp5D1SCDmcBL3/ThqlVpiA13TNA4k+vrCM4mkXgLR6udCwm61V1RUQEOh8O8Tmz7DfoS/iT+rCEIAr/5zW+gUqlgMpmgVqvxi1/8Ahs3bkR1dfWCep0WCAEBaI0viz9rSJKEQqGARCKBSqVCTEwMwsPDMTIysqg2fWezefEFCIJgXqeJiQlWlhPMZjPq6+uRkJDgM16Om/7vGAgS+Oi3KxwSgD/1KnH/gVbcdGYWtlTO7lOoNxEYVemhlw0wxutsfzatb67c6WMHAB2SSeQKI+b8Ww0ODmJsbAwVFRU+McNrJkm8c3QQ64qESIt1TzWOdizo56WgKDUW5RbZzI7ODfob/iz+SJLE7bffjri4OPztb38Dl8uFSqXCJ598ggMHDqC+vh533303rrrqKm8faoCfWVwC0Gg02jSCpPHWvB8bkCSJrq4uDA8PIygoCNHR0UhMTPTJFBI2cdXmxVvQc04SiQRKpRKRkZHMRrGjr5PBYIBYLEZmZiYSE9kZ/mcDo5mEiSQREeyYSCEpCh0SDbLjwxHMn/3C/et/noJ0fBKPX5CEkoJ8t382bc2j0a8TGyLsVP84/vpxB3asTsem8qQZ328ZVSMhIhhaxSiUSiXKysp85nMsURtw0/v1OD03btriEFsoFAp0dHSgtLwCO95tRAifa9c6x/J1UiqVPr2hPxv+Lv7uvvtuhISE4Omnn7Ypws1mM1QqlV95ki4CAgKQxp/FH0VR6OrqmtYWo21L5HI56xcvX4EtmxdvQVEUJiYmmFxVRwzC6fa+r5oduwOCIPDpD7UYMobiunNLPf789BLJwPAoPm+RYE16KJISE+e1+W0wE9hTO4L1JYkQhE9/rQmSwvoXj4IizHjynBhWWt1s0yvXIjE6xOHNaZKi8MiRDpyeGzfrEpBcLkdnZyez5DI0rkdUKA/RoXOLOXpukP48cblcZg7Xl88P/i7+/vjHP8JkMuHFF1/0ufdpgFkJCEDAd5Y9XIFefAgLC7M5B2aZQuKoyPAHBgYGIJFIWLd58SaWBuE8Ho95nWh7E7rauZja+yaTCXV1dUhNTfW6Y/+/jg/izR8H8P9+kY3MMCMkEgkoimJEBlsbqhRF4b2v6hEfClywqtzvzkm2IEgKl71+AsE8Lt67ZqnNn5FKpejp6WFtycXSusRoNPrk3CAd4+ev4u/BBx+EQqHAK6+84jMV6gAOs7gEoMlkAkmSzP/707yfLeh82+TkZIcXH2ylkPiCh52jUBSFjo4OGAwGlJSULNg7TtrQWCqVgiRJhIeHQ6VSoaqqyqerGWxC5/rm5OT4RGzhpMGMoz1KrF0SzxgOz7VEojGYsePtOjy4oQDFyXOLdoqi0NLSAh6Pt+Csm3QmAnwuB0G8mZ9ZesO5qqrKLTd0vjg3SIs/f8wzpigKjzzyCPr7+/HWW28FxJ9/sngFoL+Lv8nJSTQ2Ns4rAN5TKSRsMVe1c6HS39+P/v5+hIeHM56QIpEIUVFRC/ZvQC/2FBQUIDZ2boNhX8DaH00gEMAUEoO7DvbhiuWpuHr17Ms69FZ3WFiYV2yMvMXY2Bj6+/s9tuHsC3OD/i7+nnzySbS2tuKdd95ZUGNFi4zFKQD9ed4P+NkMtrS0dIYrvqsYDAZGDBIEAaFQiMTERI8bGtvDZDJBLBb7jM2LJ6AoCr29vRgfH2cMnulKhkQiweTkpE0bIH9HrVajsbHRr1vdliJDIpMjKjICSYmJdudwSZJEfX09BAIBsrKyPH/AXmJkZARDQ0OorKz0ipCwnBukRy/cPTfo7+Lvueeew4kTJ/Dvf/97wYzfLFIWlwA0m80wm81+Lf4GBwcxMjLiVNyXs9hKIXG3ofFs0EPSubm5PtEK9AS0wbPZbEZRUZHNNpW1DVB0dDREIhHi4+P9tjVO5/rOlfogmzQiPiLILz6/9Bzu0MgYRiQyxIQHTxu9IAgCYrEYQqFw0Zi2A8Dw8DBGRkZQWVnpMy1Ed88N+rv4e+mll/D1119j9+7dC96MfBGwuASgQqFAUNDURcPfLpD07Jter0dJSYnHTpiupJCwCb34UFxc7HdD0q5CkiQaGxudSjShKIqxl3GHbYknsJfra02nVIO79jTh0qoUXLnSf6rB2147ATNB4Z0rSyD/39wgQRAwmUxIS0tbVJW/wcFBSCQSVFRU+Iz4s8Z6bjAmJgYikcjluUF/F3+vv/46jhw5gr179/rsmFAAp1g8ApCiKKxfvx5arRYbN25ETU0NkpOT/aKCQBAEGhsbERER4dXZIEdSSNiEFgT+avPiCiaTCfX19RCJRC5Xg6yzb4ODf644+epduzNJF0aCxF8Pt+Pa0zKQGecbIwqO8N82KbplWlx3WiaAqUr7qVOnIBAIoNfrmSUSoVDIamKMr9Hf3w+5XO50brU3sTU3KBQKHXZT8GfxBwBvv/029uzZgwMHDiyac/EiYPEIQGDqwjg4OIg9e/Zg7969IAgCGzZswJYtW5Cenu6TJ1yDwYD6+nqfsMGwxFYKSWJi4rzSLSwZGBhg0g8Wy5yJuwyetVots1FML/v4UqYqnevry9UgttHr9cxYA51eY71EMt+Kky/S19eH8fFxlJWV+e3vZG9uUCgU2pyZ9nfx9/777+Nf//oXPvroI9asjgL4BItLAFpCURRGR0exd+9e7N27F5OTk9iwYQM2b97sMxt4arUaTU1NPm/6a51uERUVxcyiOXtBpygKnZ2d0Ol0PmmA6y5og2d3b73Syz5SqRRms3mah52n3/O0gblWq11UrzU90zrba20viSQ+Pt5vb4h6enqgVqsX3GttMBgYMWg9N0hbGfnTNrslu3fvxmuvvYZDhw757UJWALssXgFojUQiwYcffog9e/ZAoVBg/fr12LRpk1syRx1BJpOhs7NzzmF4X4OiKJdTSOjZt8Vm8+Itg2eTycR42Hl6vpOiKLS2tgKAWz9jJEU5lEvsqefRaDSor693aqbVuqUfFBTEtB/9YRaLoih0d3dDq9UuaO9OYPrcoEqlgslkQlZWFjIyMvzu9z5w4ACef/55HDp0yC8rlwHmJCAAbaFQKLB//37s2bMHw8PDuOCCC1BTU+Oxkxfd/iwvL/fZmS1HcCaFhLZ5SUxMXFSbkL4y52g93xkbGwuhUMhaS98SV5ZcXOG+D1vQOqrGf65bNmfW8HxoHlHjvv0teHRz0axmz7S9TVlZ2bzsm3Q6HbOYRZIkhEIhq0kkbEJXeQ0GA4qLixfNTZ1er0dtbS1SU1Oh0+lcmhv0Jh9//DGeeOIJHD58mPXuU1ZWFqKiosDj8cDn83HixAkoFApcdtll6O3tRVZWFj744AO/rJj6GQEBOBcqlQofffQR9u7di+7ubpx33nmoqalBZWUl6xdG2vrDZDKhuLjY7+4Y58JeCglJkovO5gUAhoaGGEsfX7ogkCQJpVIJiUSC8fHxebX0rSEIAvX19YiPj0dGxuzGyPPl/77pxWetUuy5fplTwsNIkAi2kVZhjw6JBvfua8bfthQhX2Rb2I2Pj6O1tRXl5eWsemvaSiLxlSUS2rmAtjLy9vF4CoPBgNra2mltX+ucYg6Hw4hBX/Fapfnss8/w8MMP4/Dhw8x8KptkZWXhxIkT0x77nnvuQVxcHP7whz/gscceg1KpxN/+9jfWnzvANAIC0BnUajUOHz6MPXv2oLW1FWeffTZqamqwfPnyeYs1s9mMxsZGREVFIScnZ8GfLOkUkpGREWg0GqSlpSEzM9MvWlrzhTZ4VqlUKCsr8+nFB4qiMDExwbT055OaQOf6pqWlITk52U1HPD/ePTaAD04N49VfViIxmp14RIVCgfb2dlRWVrr1/e1LSyQURaGtrQ0AUFBQsODPZzS2xJ+9n7M3N+jNv9VXX32FP//5zzh06BCri2iW2BKABQUF+Oqrr5CcnIyRkRGsXbuWef8EcBsBAegqOp0On3zyCXbv3o26ujqceeaZqKmpwerVq52+oOv1etTX1yM9Pd1nL4zuQCqVoqurC0VFRYzIoFNIfLWlNV/oCyNJkigsLPSrKi9dxaBn0fh8PvNazZUlTW+9+kqurz2O9yrx2Ked+NfV1QgLmr8wp1v8lZWVHs3b9uYSCZ1nzOfzkZ+fHxB/c2DPbzA2NtajN4ffffcd/vCHP+DgwYNudZzIzs5GbGwsOBwObrjhBvzmN7+BQCDA+Pg48zOxsbFQKpVuO4YAAAICkB0MBgM+//xz7Nq1Cz/99BPWrFmDLVu24LTTTpvzZDsxMYGmpiYUFhYuqpmHwcFBjI6Ozmh/0i2tsbExn0ghYRPazzEyMnJBVHnpKq5UKgVFUYwYtG5p+WOuLxuMjo5iYGDAYxm39rBcIpHL5Yxwd8cSCUVRaG5uRnBw8KJa5KK3ffPz8+c1M0eSJLNEZzk3mJCQ4NZ58GPHjuGOO+7ARx995PYZ7OHhYaSkpEAikWDdunV4/vnnsWnTpoAA9DwBAcg2JpMJX375JXbv3o3vv/8eK1aswObNm7F27doZH+DDhw8jOjoa1dXVPjcH4i4sbV7mSjQxm82MGPRGCgmb0AbPiYmJCzLL2Gg0MmLQUrhTFIWmpia/zvV1haGhIeYGx9eSWOglEqlUCpIkp1kBzQeSJNHc3IywsLAFcYPjKHTlj227Lk/NDZ48eRK33norPvzwQ4+n0ezcuRORkZF49dVXAy1gzxMQgO7EbDbj22+/xa5du/DNN9+gsrISmzdvxtlnn42///3v+PTTT7Fv3z7Ex8d7+1A9AkmSaGpqQkhIiNOtIU+nkLAJ3f7Mzs6GSCTy9uG4HVq4Dw4OQqVSISkpCampqT6xmOAJ/Cnpgq64S6VS5ibLlSUSerM7KioK2dnZbjxi34Ktyp+jz8X23KBYLMYNN9yAvXv3Ii8vj+UjnolGowFJkoiKioJGo8G6devw5z//GV988QXi4+OZJRCFQoHHH3/c7cezyAkIQE9BEAR++OEH7Nq1C7t27UJaWhpuvfVWrF+/flFU/9iIOKNxdwoJm0xOTqKxsXHRtT/p2beysjJmbtDbiwnuhqIoxuzYH5MuXF0iIUkSDQ0NiImJWVR5xp4Uf9aYzWbmHEjPDQqFQsTFxTl809HU1IRrr70Wu3btQkFBgZuPeIru7m5s2bIFwNTvcMUVV+D++++HXC7Htm3b0N/fj4yMDOzatcunww8WCAEB6EkmJiawfft2nHbaaTjnnHOwZ88efPrpp8jNzcXmzZvxi1/8YkG2yXQ6Herr691SAaMoirEsmW8KCduMj4+jpaVl3r5v/sbw8DCGhoZmzL5ZLyZERkYyr5WvtUmdhR5tMBqNKCoq8jvxZ43lLBq9RELPolm+pp609fElvCn+rKFfK/pz5cjcYGtrK3bs2IH3338fJSUlHj7iAD5CQAB6iv7+fmzduhV33XUXtm3bxnyd9sDbtWsXPv74Y6SlpWHz5s1Yv379gnBfp5dcnEk+cBVry5Lw8HCHU0jYhq6AVVRULAprGxpHc30pioJarWY2immTcHcPu7sDOtWEw+EsSMsTe0sk8fHxaG1thUgkWpBzrfYwGo2ora31CfFnja25Qfr8U1paCgDo6OjAlVdeiXfeeQcVFRXePNwA3iUgAD2BWq3GWWedhX/84x9YtWqV3Z+jKAqNjY3YvXs3Dh06hISEBNTU1OCiiy7yyzlBOs6ObfNbR7COzwoJCbGbQsI29jacFzLzzfW1NAnn8XjMRrGvi2d68SEkJGTRbL3qdDqMjY2hp6cHQUFBSE1NhVAo9EqetKehxV9eXp5fnJMNBgOOHz+Ohx56CDKZDMuXL8dPP/2Ed999F8uXL/f24QXwLgEB6CkmJyedagPSfnG7d+/GwYMHERkZiU2bNmHjxo0QiUQ+f6KlRZCvxNnZSyFh05vNcgastLTU6y1oT8F2rq9er2deK1/2haRn36KjoxfV4oPZbEZdXR1SU1MRHx/PyhKJP+Bv4s+a5uZm3HbbbYiNjcXAwABWr16NTZs24dxzz/X5G60AbiEgAP0BOkx99+7d2L9/P4KDg7Fx40Zs3rwZycnJPnWitawEzWXz4i1o/zqJRMJYK4hEonll8bItgvwFevszIiLCLdYf1lFntGVJVFSUV//GBEFALBYjISFhUc2+0Wku6enpSEpKmvY9X0oiYRt/F3/Dw8O49NJL8cILL+D000+H2WzGDz/8gP379+O///0vcnJy8MILLyyqIIIAAQHod1AUhf7+fuzduxf79u0DSZLYsGEDampqkJ6e7tWL4nxsXryFwWBgxKCr1Sba4Jm2wPCH35sNPC2CCIJgxODk5CRiY2MZKyBPCgy6ApaSkuLWxARfgxZ/mZmZcy5zObpE4g/4u/gbHR3FpZdeir///e9Yu3btjO/TyS25ubkeTasJ4HUCAtCfoSgKIyMj2Lt3L/bu3QutVosNGzZg8+bNHjdipW1ehEKh31ZETCYTpFKpUykkJpMJYrEYSUlJi2oQ3tu5vtZWQNHR0Uy1yZ1VZ6PRCLFYjIyMDLdlpfoiRqMRdXV1yM7OdjrKz5NJJGzj7+JPIpHgkksuwWOPPYZ169Z5+3AC+BYBAbiQkEgk2LdvH/bs2QOlUon169dj8+bNbt9MdKfNi7egzYwlEgm0Wq3NFBJ/ybdlG1/7vSmKYqpNcrmcyb1le/ubtv7wld/bU9AiKDc3FwkJCfN+PMskErrq7otLJP4u/uRyOS6++GI8+OCDWL9+vbcPJ4DvERCACxW5XI79+/djz549GB0dxfnnn48tW7aguLiY1XaZJ21evIV1CklsbCyio6PR29uL4uLiBWHX4ygajQYNDQ0+a2xtvf0dFBQEkUgEkUg0r2UknU4HsVjMetyXr+Nuvzu2kkjccVz+LP6USiUuueQS3Hfffdi8ebO3DyeAbxIQgIuB8fFxfPTRR9i7dy96enqwbt061NTUoKKiYl5i0Js2L96CJEn09/ejp6cHwcHBiI2N9dkUErahxb4/5fpqtVpmo9jVhR+NRoP6+voFfZNjC71ej7q6Oo+JfV9ZIqHb3bm5uX4p/iYmJnDJJZfgjjvuwKWXXurtwwnguwQE4GJDrVbj0KFD2LNnD9ra2nDOOeegpqYGy5Ytc+okOzQ0hOHhYVRUVPiEzYunkEgk6OnpQUVFBUJCQnw2hYRtlEol2tra/Frs01mqEokEZrOZmfGcrfWoVqvR2NjoV6KXDeiKZ2FhoVcq3BRFYXx83ONLJLT4y8nJYaXd7WkmJydx6aWX4qabbsL27du9fTgBfJuAAFzM6HQ6fPzxx9izZw/EYjHOOuss1NTUYNWqVXYFDG3zotFoFpXXHTDlbTg2Noby8vIZFyFfSiFhm4WYamIymZgZT3utR5VKhebmZpSXl/ucB6E70Wq1qK+vR1FRkU9UPOm2Pp1uwePxGB9PNt+P/i7+NBoNLrvsMvz617/Gr3/9a28fTgDfJyAAA0xhMBjw2WefYdeuXTh58iTWrFmDmpoanHbaaYzY0ev1uOWWW3DjjTdi6dKlPjWw7U5oH8bJyUmHRK/1HFpwcDASExM9kkLCNvZyfRcS1jOeAoEAYWFhGBkZQWVl5bz8If0Nut1dUlKC6Ohobx+OTdyxROLv4k+n0+Hyyy/Htm3bcP3113v7cAL4BwEBGGAmRqMRX375JXbv3o0ffvgBK1aswLp16/D000/j/PPPx/333+/tQ/QYJEmitbUVXC7X5W1q65gzeinB1z23+vr6oFAoUF5evmgqvSRJoq+vD319fQgODmbsZRZiW9+ayclJNDQ0+FW7m7ZuopdI4uLiIBKJnFoi8XfxZzAYcMUVV2Djxo246aabFs2NeYB5ExCAAWbHbDZj9+7duP3225GdnY28vDzU1NTgnHPOWTDtQHsQBIGGhgbExMQgKyuLlRMrnUIilUpBURQjBn2pykS3+XU6HUpKShb8coslY2Nj6OvrYyqelm39sLAwptq00Kqh9KxjWVmZU5GVvgRBEIw3JL1EIhQKZ/WGNJlMqK2t9VvxZzQaceWVV+Lcc8/F7bffHhB/AZwhIAADzE5dXR127NiBl156CcuXL8f333+PPXv24L///S+Ki4tRU1ODdevW+e1igD1oo+PU1FS3pT2wkULCNnSkHYfDcbt/pK8xPDyM4eFhVFZWzpjbpCiKqeTKZDLGzNgfKrlzQW93L6RZR0eWSGjx54q5tS9gMplw9dVXY9WqVfj973+/qD6rAVghIADZYNeuXdi5cydaWlpw/PhxLFu2DADQ29uLoqIiFBQUAABWrVqFl156CQBw8uRJ7NixAzqdDuvXr8ezzz7rcx/gTz75BPfddx8++OAD5OXlTfseSZI4fvw4du/ejU8//RT5+fmoqanB+eef7zftI3vQxtaeNPx1JYWEbdyd6+vLDAwMQCqVoqKiwqFWLz2HJpFIQFEUIwb97UZIpVKhpaXFr7e758LWEkl8fDxGR0eRm5vrl+LPbDbj+uuvR2lpKf70pz8tqs9qANYICEA2aGlpAZfLxQ033IAnn3xymgDcsGEDGhsbZ/ybFStW4Nlnn8WqVauwfv163Hbbbbjwwgs9feh20Wq1uPLKK/HSSy/NeYIkSRJ1dXXYtWsXPv74Y2RkZGDz5s1Yv369T2wROgPdCvOm55sjKSTueM76+nqP5fr6Ej09PZiYmEBZWZlL7W6j0ciIQW+Jd1cYHx9Ha2srKioqfGoEwd2o1WrU1dWBz+eDx+P5bBKJPQiCwG9/+1tkZWXhoYcecusxHzlyBLfffjsIgsB1112HP/zhD257rgAeJyAA2WTt2rUOCcCRkRGcffbZaG1tBQC8//77+Oqrr/Dyyy97/JjZhqIoNDY2YteuXTh8+DCEQiE2b96Miy66yOdNVWmvu7KyMp9phdlKIRGJRIiNjWXtxE/n23or19db0LOOer2etYQcS/Gu0WiYpQSBQOBT4oJ+r1dWVi74WV5LrNu+bCyReBKSJHH77bcjPj4ejz32mFvncwmCwJIlS/DZZ58hLS0Ny5cvx/vvv4/i4mK3PWcAj2LzDe7fpmU+Rk9PD6qqqhAdHY2//vWvOOOMMzA0NIS0tDTmZ9LS0jA0NOTFo2QPDoeDsrIylJWV4cEHH0Rrayt2796NSy+9FNHR0di0aRM2btwIoVDoUydYevi/qqrKp2a6LLeGSZKEQqHA6Ogo2traWElK8LVcX09BURTa2tpAURRKSkpYey/y+XwkJSUhKSkJJElCLpdjZGQEra2tXku2sEYul6Ozs9Pn3uvuxtbMX1BQEFJSUpCSksIskQwNDaGlpcWhJRJPQpIk7r77bkRFRbld/AHA8ePHkZeXh5ycHADA5Zdfjv379wcE4AInIABtcN5552F0dHTG1x9++GG7WYvJycno7+9HfHw8Tp48iZqaGjQ1NcFWhdWXxBBbcDgcFBUV4YEHHsCf/vQndHV1Yffu3bjiiisQHByMTZs2YfPmzUhKSvLq7z8wMACJRIKqqiqf3u7kcrlISEhAQkICM+Q+NjaGjo4Ol1JIfD3X111QFIXm5mYEBQUhPz/fbe89LpfLtBctlxI6OjoQGRnJvF6eNAqXyWTo6upCVVXVokrwcWThw7IdbPl6dXZ2eiyJxB4kSeKPf/wjuFwu/v73v3vkBmJoaAjp6enM/6elpeHYsWNuf94A3iUgAG3w+eefO/1vQkJCmDvspUuXIjc3F+3t7UhLS8Pg4CDzc4ODg27bNPUVOBwO8vLy8Ic//AH33nsv+vr6sHfvXuzYsQMURWHjxo2oqalBWlqax8Qg3QLUarWoqqryK7sTDoeD2NhYxMbGTksh6e7udiiFxB9zfdmAXnSJjIxEdna2x95r1q+XWq2GRCJBb28vgoODmWQLd4oyqVTKdCQWm/irq6tDVlaWw1Vu69eLXiKpra11WxKJPUiSxM6dO6HRaPDqq6967Dy1WAoVAaYTEIAsIZVKmfZBd3c3Ojo6kJOTg7i4OERFReHo0aNYuXIl3n77bdx6663ePlyPweFwkJWVhTvvvBN33HEHRkZGsGfPHtx4443Q6/XYsGEDNm/e7NYLNEmSaGlpAZ/PR1lZmV+f2DgcDmJiYhATE4O8vDwmhYQ2M7ZOIaHnvyoqKhbs5qctCIJAfX094uLikJmZ6bXj4HA4iI6ORnR0NPLy8hh7GbFYzFQNRSIRq+KCfj/4epWbbWjxl5mZCZFI5NJjcDgcREVFISoqCjk5OcwGeFNTEwiCcChT2lUoisIjjzyCsbExvPXWWx69SU1LS8PAwADz/4uhUBEgsATiNPv27cOtt94KqVQKgUCAyspKfPLJJ9izZw/+/Oc/M9tmDz74IDZu3AgAOHHiBGMDc+GFF+L555/3axHCBhRFQSKRYN++fdi7dy+USiXWr1+PmpoaLFmyhLW/Dy0EYmNjkZmZuaD/7tYpJGFhYVCpVKiurl5U819msxlisRhJSUlITU319uHYRa/XMxvFbHlDjo6OYmBgYEHH+dmCDfHnyHO4a4mEoig88cQTaGtrwzvvvOPxTHGz2YwlS5bgiy++QGpqKpYvX4733nsPJSUlHj2OAG4jsAUcwHeRy+X48MMPsXfvXoyOjuKCCy7Ali1bUFRU5PKdML3x6k6DZ1+lt7cXg4ODCA4OBofD8ckUEndAC4H09HQkJSV5+3AchhYXEokEer3eJTugkZERJsvZ0wLCm3hC/FnjShKJPSiKwnPPPYcTJ07g3//+t9eE++HDh/G73/0OBEHgmmuuWVQxoIuAgAAM4B+Mj4/jwIED2Lt3L/r6+nDeeedhy5YtKC8vd1gM6nQ6iMVi5OXl+WXs03ywzvU1GAyMuDCbzT6RQuIODAYDk/Pqz1vOBEFAJpNBKpVOswMSCAR23/9DQ0MYHR1FZWWlT2yxegpviD9r6CUSqVQKuVw+bS53LjFHURReeuklfP3119i9e/eimtcM4FECAjCA/zExMYFDhw5h7969aGtrw7nnnouamhosXbrU7sXQFwyevYEjub6WKSQGg4ERg75uZDwXer0edXV1yM/P93kPSmcgSRJKpRISiQTj4+OIjo5m7GVooTc4OAiJROJwsslCwRfEnzXWMYKzLZFQFIXXX38dR44cwd69exeVR2MAjxMQgAH8G61Wi48//hh79uxBfX091q5di5qaGqxcuZK58B08eBAffvghnn322QVX4ZoNiqKYlBpHc329kULiDrRaLerr61FYWAiBQODtw3EbFEVBpVIxmbdhYWHg8XgwGo2orKz0q832+WI2m1FbW4uMjAwkJiZ6+3DsQi+RSKVStLe3QywW49JLL0V1dTXeffdd7N27F/v371/woxkBvE5AAAZYOOj1enz22WfYtWsXTp06hdNOOw1xcXE4cOAA9uzZs6giztjI9fVECok7mJycRENDw6KzuKEoCu3t7ZDL5eDxeAgKCmIqTQt94cdfxJ81crkcu3btwsGDB9HT0wOKovDaa6/h7LPPXlSV2wBeISAAAyxMjEYjbr/9dnz88ceIjo7GsmXLUFNTgzPPPHPBz9S4I9eXbjuOjY1BpVL5TKqFNSqVCs3NzSgvL19U1V5gKnVIrVajtLQUXC4XWq2WmfMEsGCXfvxV/Fmye/duvPbaa7jtttvwySef4NixY1i5ciVqampw7rnnBlrBAdxBQAAGWHhQFIX7778fvb29jHcWPVD97bffoqqqCjU1NTj77LMX3InVE7m+likJCoXCpRQSd2Dpb7jQRM5sUBSF7u5u6HQ6u5nGlks/JpOJ8a7z9znPhSD+9u/fjxdeeAGHDh1ixhUIgsDRo0fx4Ycf4vPPP8f777+PwsJC7x5ogIVGQAAuVnbt2oWdO3eipaUFx48fx7Jly5jvPfroo3j99dfB4/Hw3HPP4YILLgAAnDx5kvEuXL9+PZ599lmfu3iYTCZcf/31iI+PxxNPPDHjYkgQBL777jvs2bMH//3vf1FaWoqamhqcd955fm+K7I1cX8sUErlcjrCwMCQmJs6aQuIO6HzbioqKBSfqZ4OiKHR2dsJoNKK4uNihz6PJZGLmPNn2rvMkC0H8HT58GE8++SQOHz6MuLg4mz9DX4/96bUJ4BcEBOBihV4OuOGGG/Dkk08yArC5uRnbt2/H8ePHMTw8jPPOOw/t7e3g8XhYsWIFnn32WaxatQrr16/HbbfdhgsvvNDLv8l0Pv/8c9TV1eHuu++e82dJksSxY8ewe/dufPbZZ8jPz8eWLVtw/vnnIzIy0gNHyx50rq83lx7oyCx629FTEWd0pFplZeWCb+9bQs/8kSSJwsJCl+c8Lb3rBAIBM+fpS619a8xmM+Pt6K/i77PPPsPDDz+Mw4cPLzpbqgA+QUAALnbWrl07TQA++uijAID77rsPAHDBBRdg586dyMrKwtlnn43W1lYAwPvvv4+vvvoKL7/8sncOnGVIkkRtbS127dqFI0eOIDMzE5s2bcL69et93jbGV3N9rVNI6Bk0NhcSRkZGMDg4uOhSLiiKQltbGwA4vOE9FyRJMq19pVKJqKgoCIVCJCQk+NRCAi3+0tLS/MrY25KvvvoKf/7zn3Ho0CG/FbAB/B6bJ43FYxcfYAZDQ0NYtWoV8/9paWkYGhpCUFAQ0tLSZnx9ocDlcrF06VIsXboUjzzyCBobG7Fr1y5s2LABiYmJ2LRpEzZs2GC3TeMtFAoF2tvbfTLXNyIiAtnZ2cjOzmasLxoaGkBRFCsLCQMDA5BKpaiurvYpgeJuaHsfPp+P/Px81lqDXC4XcXFxiIuLm9ba7+npQWhoKFPN9abQXgji79tvv8Wf/vSngPgL4JMEBOAC4bzzzsPo6OiMrz/88MPYvHmzzX9jq/rL4XDsfn0hwuVyUV5ejvLycjz00ENoaWnB7t27cfHFFyMmJgabN2/Gxo0bkZCQ4NW/AX1xrqqq8nmbj7CwMGRkZCAjI4NZSGhpaXE5haS3txfj4+OLzuiYoig0NzcjJCQEubm5bnv/cTgcxMTEICYmBvn5+ZicnIRUKkVtbe2sRsbuZCGIv6NHj+Lee+/FwYMH3bakFSDAfAgIwAXC559/7vS/SUtLw8DAAPP/g4ODSElJQVpaGgYHB2d8faHD4XBQXFyMP//5z3jggQfQ2dmJPXv2YPv27QgJCcGmTZuwefNmJCYmelQMDg8PY3h4GNXV1X7X+gwJCUFaWhrS0tKYFJKOjg7o9XokJCQgMTHR7naqZbKJMzGACwGSJNHU1MR4O3qSyMhIREZGIjs7G3q9HhKJBE1NTSBJEkKhEEKh0K22OwtB/J04cQJ33HEHDhw4MK2bEiCALxGYAVxEWM8ANjU14YorrmCWQM4991x0dHSAx+Nh+fLleP7557Fy5UqsX78et956K9avX+/l38A7UBSFvr4+7NmzB/v27QOHw8HGjRtRU1OD1NRUt4pB61zfhYJlColGo0F8fDwSExOZFBJ66YEgCBQVFS3YCrQtaGPvqKgoZGdne/twGIxGI2MvYzAYGHuZqKgo1l6fhSD+6urqcOONN2Lfvn3Izc319uEECAAElkAWL/v27cOtt94KqVQKgUCAyspKfPLJJwCmWsRvvPEG+Hw+nnnmGWbT98SJE4wNzIUXXojnn39+UV2E7UFRFIaHhxkxaDAYsGHDBmzevBlZWVms/Y1oyw+9Xm8313ehYCuFRKfTISwsjLWlB3+BJEnU19cjNjYWmZmZ3j4cu5jNZuY1m5ycZOxlBAKBy68XLf5SU1P9tmXa2NiI6667Drt27UJBQYG3DydAAJqAAAwQgE0oioJEIsHevXuxd+9eqFQqrF+/HjU1NfMa2Hcl13ehQPu9EQQBkiQZqxJfSyFxBwRBMKku6enp3j4chyFJkrGXoZNjhEIh4uPjHX7NCIJAXV0dUlJS/Fb8tbS04Oqrr8b777+PkpISbx9OgACWBARggADuRCaT4cMPP8TevXshkUhwwQUXYMuWLU61MEmSRENDAyIjI13O9fVXCIJAQ0MDU/3y1RQSd0AQBMRiMUQikV/PjFm/ZhERERCJRLOahS8E8dfR0YErr7wS7777LsrLy719OAECWBMQgAECeAqlUomPPvoIe/bsQX9/P9atW4ctW7agrKzMblWEzvUVCoV+VQFiA7PZDLFYjMTERJsCyFYKCb2d6skUEndAC6Dk5OQFtWzliFn4QhB/PT092L59O9566y1UV1d7+3ACBLBFQAAGCOANJiYmcOjQIezZswcdHR0499xzsXnzZixdupQRg6Ojo/jd736Hp556CqmpqV4+Ys9iMpmYwX9HRIC3UkjcwUKYe3MUrVbLmIVzOBwkJCRAIpEgPT3db3/3/v5+XHbZZXj11VexYsUKbx9OgAD2CAjAAAG8jVarxeHDh7F79240NTVh7dq1WL16NR566CHcd9992Lp1q7cP0aMYjUbU1dUhKysLIpHIpcfwRAqJO6CFrz/n27qKVqtFbW0tuFwueDwes1HsT7GMQ0ND2Lp1K1544QWcfvrpbnuenTt34tVXX2Uyvx955BHGkcFelnuAAFYEBGCAAL6EXq/Hm2++iQceeAB5eXmorKxETU0N1qxZ4/dtTUfQ6/Woq6tDfn4+4uPjWXlMOoVEIpGwlkLiDkwmE2pra+clfP0V67Yv7Q8plUqh0+kQHx8PkUjEWAL5IqOjo7j00kvx97//HWvXrnXrc+3cuRORkZEzMs9ny3IPEMCKQBRcgAC+RHNzM15++WV8+eWXKCgowBdffIFdu3bhrrvuwqpVq1BTU4MzzzzT78yfHUGr1aK+vh6FhYUQCASsPS7bKSTugK56ZmdnM1WdxYLlvCPd9g0KCkJKSgpSUlIYS6CBgQHGEoi2l/GVLXCJRIKtW7fib3/7m9vF32zs378fl19+OUJCQpCdnY28vDwcP34cq1ev9toxBfAvfOMTFSDAHOzcuROpqamorKxEZWUlDh8+zHzv0UcfRV5eHgoKChh/Q1/nq6++wnXXXYe9e/eirKwMwcHBuPDCC/H666+jrq4O27dvx6FDh3DaaafhxhtvxJEjR2AwGLx92KwwOTkJsViM4uJiVsWfNXQKSXV1NROh19HRgaNHj6KzsxNqtdpm7KE7MRgMqK2tRW5u7qIWf/aWXegWfmlpKVauXAmhUIixsTEcO3YMjY2NkEgkIAjCw0f+M3K5HFu3bsVf/vIXrFu3zmPP+8ILL6C8vBzXXHMNlEolgKkWtOWy2ELLbA/gfgIt4AB+wUJqg0xMTKCmpgbvvffenGkHBEHgu+++w+7du/Hll1+irKwMNTU1OO+883yurekIExMTaGpqQllZmdfmvSxTSLRaLWNiHBMT49aWo16vh1gsRn5+PuLi4tz2PL7IfDedKYqCSqWCVCqdtgWekJDgsQq5UqnEJZdcgj/+8Y/YtGkTq489W5b7qlWrmCzyBx54ACMjI3jjjTdw8803Y/Xq1fjVr34FALj22muxfv16XHLJJaweW4AFQaAFHGDh4Y9tkOjoaHzxxRcOiQ0ej4ezzjoLZ511FkiSxNGjR7F792789a9/RUFBAWpqanD++ef7xfD8+Pg4WltbUVFRgfDwcK8dB5/PR1JSEpKSkkAQBBQKBQYHB9HS0uK2liM971hQUIDY2FjWHtcfoD0O52Nzw+FwIBAIIBAIkJeXxyz+1NbWgs/nM1vg7lr8UalU2LZtG37/+9+zLv4Ax7Pcr7/+emzYsAGA/Sz3AAEcJSAAA/gNL7zwAt5++20sW7YMTz31FGJjYzE0NIRVq1YxP+MvbRBXKk1cLhdr1qzBmjVrQJIkTp06hV27duGJJ55AdnY2Nm3ahPXr1yM6OtoNRzw/5HI5Ojo6UFlZidDQUG8fDgOPx4NQKIRQKARJklAqlRgdHUVbWxtiYmJYSSHR6XQQi8Wszzv6A7T4S0pKYk2ccDgcREZGMmbpOp0OEokEDQ0NoCiKmfVk6yZDrVbjsssuwy233OKV6trIyAgzL7lv3z6UlpYCADZt2oQrrrgCd955J4aHh9HR0RGwogngFAEBGMBnmK0NctNNN+GBBx5g2iB33XUX3njjDZszXL66OcgmXC4Xy5Ytw7Jly/Doo4+ioaEBu3btwkUXXYSkpCRs2rQJGzZs8Ilqk0QiQW9vL6qrq33ap4/L5SI+Ph7x8fHTEi06OjpcTiGhl12KiooQExPjxqP3PWjxl5iY6NbKVFhYGDIzM5GZmQmj0QiJRILW1laYTKZp9jKunBc0Gg22b9+O6667Dtu3b3fD0c/NPffcg7q6OnA4HGRlZeHll18GAJSUlGDbtm0oLi4Gn8/Hiy++6NOjLwF8j8AMYAC/o7e3Fxs2bEBjYyMeffRRAMB9990HALjggguwc+dOn24BuxM6R3j37t04ePAgBAIBNm/ejA0bNnhl6WBkZASDg/+/vTuPiuo+/wf+HkBxYZNVdFQIVFRcqFUjGiONuLDNjBoXsOJSjVqqptWj9pAaNOEYzVKtMW3M0Sa2DZwyA4OCCS4tJqYqwbihVlAw7JvDEgkgzNzfH/6Yr1FU9jvL+/WX3rkMD3M43refez/PUwg/Pz+j3c3c0SkkdXV1uHbtGnx9fWFra9uDFYvv0fAnVmPzR5/1rKur07eXaeuznvX19Vi0aBEWL16MVatW9UDFRN2GfQDJeD16G+RPf/oTLly4gPj4eFy/fh0RERH6TSAzZsxATk4O/yeMh8Hl9u3bUCqVOHr0KPr27QuZTAaZTAY3N7duXyktLCxEWVkZxo0bZzJ9DQVBQF1dHcrKyp45heT+/fu4du2aqJtdxGII4e9xLc96lpeXo7a2Fvb29nBzc8OAAQNavb3f0NCAiIgIyGQyrFu3zizuKpBJYwAk47V06dInboO0BMLY2FgcPnwYVlZW2Lt3L4KCgkSu1vAIgoC7d+9CpVJBrVbDwsICYWFhUCgUGDRoUJdf4L7//ntoNBqMHTvWpMN4XV2dvvF0SwuTfv36ITs7G2PHjhW952BPM8Tw9zidTqe/vV9VVQUbGxtkZ2cjMDAQ9vb2ePDgAZYuXYoZM2Zg48aNDH9kChgAiehhGCwqKoJKpUJSUhIePHiA0NBQyOVyeHh4dOqCJwgCcnNzUVdXh9GjRxtM896e0NDQgPz8fBQWFqJ///4YOHCgQU4h6S4t4c/V1RVSqVTsctqk5fZ+TEwM0tPT4erqCgsLCwQEBCAmJobhj0wFAyAR/ZQgCCgrK0NiYiISExNRW1uLkJAQKBQKeHt7t+sCKAgCcnJy0NTUhFGjRpndxbOmpgY3b97EuHHjYGFhoV8ZNKQpJN1Fq9Xi6tWrcHFxMZrw97jm5masXLkSdXV1qK2tRd++faFQKKBQKIz2ZyL6/xgAiejZKioqoFarkZiYiIqKCgQFBUEul2PkyJHPDHQtm08sLS0xfPhwswt/j/Y4fHzFr2XWbXl5ORoaGuDs7Aw3N7cO70w1NKYQ/rRaLdatWwdPT0/s3LkTEokEhYWFUKvVUKvVqK+vR1RUFCIiIsQulagjGACJqO2qqqpw9OhRqFQqFBQUYNasWZg7d+4Tt3YfPHiATz75BLNnz4aXl5dJhJr20Gg0yM7OblOPw+bmZty7dw9lZWUd2plqaEwh/Ol0OmzYsAEuLi7YtWtXq48t3Lt3D6WlpfD19RWhQqJOYwAkoo6pra1FSkoKVCoVbt++jcDAQP3K4IIFCzBhwgTs3LlT7DJ73L1793D79m34+fm1ewrF4ztTu2sKSXfR6XS4cuWK0Ye/TZs2oW/fvvjggw+M4nMn6gAGQCLqvPv37+OLL75AfHw8vvnmG/j7++O3v/0tJk2aZNI7fh9XWVmJ3Nxc+Pn5dbrBdcsUkvLyclRXV8POzg5ubm6dnkLSXVrCn7OzM4YMGSJ2OR2i0+nwhz/8AVqtFh9++KFBfs5EXYQBkIi6Rk1NDRQKBZYuXQonJycolUpcunQJ06ZNg1wux5QpU0ym919rKioqkJeX1yXh73GPTiHRaDSwsbGBm5tbu6eQdBdTCX8xMTGorq7GwYMHGf7I1DEAEonhyy+/xMaNG6HVarFq1Sps27ZN7JI6pbKyEjKZDJs3b8a8efP0xxsbG3H69GkolUpcuHAB/v7+UCgUmDZtmtFOAWlNWVkZ8vPze2S6SUenkHQXUwh/giAgNjYWhYWF+Nvf/mYQoZqomzEAEvU0rVaL4cOH4+TJk5BKpZg4cSLi4uIwatQosUvrEI1Ggzlz5uCtt97C7Nmzn3peU1MT0tPToVKp8PXXX2PChAlQKBQICAho97NyhqS0tFQ/2q6nA1hbp5B0F1MJf++++y5u3bqFv//97ya9Sk30CAZAop527tw5xMTEIC0tDQCemF1sbHQ6Hf73v/+1K8A2Nzfj7NmzUCqVSE9Px9ixY6FQKDBjxgyjapJcXFyMkpISgxlt9+OPP6K8vPwnU0hcXFyeuxO5I3Q6Ha5evQonJyejDn/79u3Dd999h7i4OJNalSZ6jlYDoPj/ihGZsKKiop9cMKVSKS5cuCBiRZ1jYWHR7tVLKysrBAQEICAgAFqtFufPn4dSqcTbb78NHx8fKBQKzJo1y6CbJBcVFaGsrAx+fn4Gc8uwX79+8PDwgIeHBxoaGlBeXo6srCwIggAXFxe4ubl1ScA2lfD3l7/8BRcuXEBCQgLDHxEYAIm6VWsr7MbY762rWFpaYurUqZg6dSp0Oh0uXryIhIQEvPvuu/D09IRMJkNQUBDs7OzELlWvoKAAlZWVGDdunMGEv8f16dMHQ4cOxdChQ/HgwQOUl5fj5s2baG5u1jee7kjANpXwd+jQIfz73/9GUlJSj9wuJzIGDIBE3UgqlaKgoED/98LCQgwaNEjEigyHhYUFJk6ciIkTJ+Kdd97B1atXoVQqERwcDHd3d8jlcoSEhGDAgAGi1Zifnw+NRqMf72YMevfuDalUCqlUqp9CkpOT0+4pJC3hz9HR0WjDHwAcOXIEKSkpSE5ONurnT4m6Gp8BJOpGzc3NGD58OE6fPo3Bgwdj4sSJ+PzzzzlR4BkEQcCNGzegVCqRkpICR0dHyOVyhIaGwtnZucfquHv3LmpqajBmzBijCX/P0p4pJI+Gv6FDh4pUcef985//RFxcHFJSUtCvXz+xyyESCzeBEInh+PHjeP3116HVarFy5UpER0eLXZLREAQBOTk5UCqVOHbsGPr27Qu5XI6wsDC4ubl12+303Nxc3L9//4mxd6biWVNIAJhE+EtISMDhw4eRmpoKGxsbscshEhMDIBEZL0EQkJeXB5VKBbVaDUtLS8hkMsjlcgwaNKhLwqAgCLhz5w4aGhrg6+trFs9rPjqFpKqqClqtFk5OThgxYoTRht/k5GQcOHAAqampsLe377L3TUhIQExMDG7evImMjAxMmDBB/9quXbtw6NAhWFpa4s9//rO+TdLFixexfPly1NfXIzg4GPv27TOL3ysyKAyARGQaBEFAYWEhVCoVkpKS0NzcjNDQUMjlcgwbNqxDF1hBEHD79m00NTVh5MiRZneRbrnt26dPH0gkEv0UEldXVzg7OxvsBpjHHT9+HO+//z5SU1Ph6OjYpe998+ZNWFhYYM2aNXjvvff0AfDGjRsIDw9HRkYGiouLERgYiOzsbFhaWmLSpEnYt28fJk+ejODgYGzYsAFBQUFdWhfRc7ANDBGZBolEgiFDhuD111/Hxo0bUVpaisTERKxfvx73799HSEgI5HI5vL292xTkBEFAdnY2dDqd2Ya/a9euYcCAARg2bBiAh5/JDz/8gLKyMuTl5emnkDg7OxtsG5WTJ09iz549OH78eJeHPwAYOXJkq8eTk5OxePFiWFtbw9PTE97e3sjIyICHhwdqa2vh7+8PAIiMjIRarWYAJIPAAEhERk0ikcDd3R1RUVGIiopCRUUF1Go1tm7disrKSgQHB0Mul2PEiBGtBruW5taWlpZPPceUtYQ/BwcHffgDHn6udnZ2sLOzg7e3t34KyXfffdfjU0ja4j//+Q/eeustHD9+vEc3CwEP+0ROnjxZ/3epVIqioiL06tULUqn0ieNEhoABkIhMiouLC1avXo3Vq1dDo9Hg6NGjiImJQVFREWbNmoW5c+fC19cXFhYW0Gq1WLp0KYKCgvCrX/2K4e8pJBIJbGxsYGNjAy8vL/0UkitXrsDCwqJbp5C0xddff40//vGPSE1Nhaura6feKzAwEKWlpU8cj42NhVwub/Vrntbvk31AyZAxABKRyXJ0dMTy5cuxfPly1NTUICUlBbt378adO3cwY8YMXLt2DZ6enliyZInZXZhbwp+9vf0zw19remoKSVucO3cOW7duRUpKCtzd3Tv9fqdOnWr31zyt36dUKkVhYeETx4kMgXFu8SIiaid7e3ssWbIEiYmJOHPmDDIyMlBdXY3z588jOjoa58+fh1arFbvMHqHT6ZCVlQV7e3t4eHh06r1appBMmDBBPye5ZZdsSzud7pKZmYnf//73SE5O/smt1p4mk8kQHx+PxsZG5OXlIScnB5MmTYK7uztsbW1x/vx5CIKAI0eOPHUVkaincRcwEZmVpqYmREREYMKECdi6dSvq6+uRlpYGlUqFS5cuYdq0aVAoFPD394eVlendJGkJf3Z2dp0Of8/SMoWkvLxcP4XE1dUVtra2XbLaevnyZaxduxZqtRovvPBCF1T8fElJSVi/fj0qKirg4OAAPz8/pKWlAXh4i/jw4cOwsrLC3r179Rs9MjMz9W1ggoKCsH//frNbbSbRsQ0MET2fh4cHbG1tYWlpCSsrK2RmZkKj0WDRokW4e/cuPDw88K9//UvUEW0d1djYiEWLFmH69On43e9+1+rrp06dglKpREZGBqZMmQKFQoGXXnrJYHe+tkdPhb/HtWcKSVtkZWVh1apVSEhIgI+PTzdUTGRSGACJ6Pk8PDyQmZn5k52UW7ZsgaOjI7Zt24Z33nkHVVVV2L17t4hVdszBgwfR1NSEqKio557b1NSE9PR0KJVKnD17FhMnToRCoUBAQIDB7HxtD7HC3+OeNYWkLY2nb968iRUrViA+Ph6jRo3qgYqJjB4DIBE9X2sB0MfHB+np6XB3d0dJSQkCAgJw69YtEavsWc3NzTh79iwSEhJw5swZjBs3DgqFAjNmzBBt52t7tIQ/W1tbeHp6il2O3qNTSKqrq2FnZwdXV1c4OTm1Ggazs7MRGRmJf/zjHxg7dqwIFRMZJQZAIno+T09PDBgwABKJBGvWrMFrr70GBwcHVFdX688ZMGAAqqqqxCtSRFqtFufOnYNSqcTp06cxcuRIyOVyzJo1C/379xe7vCcYavh7nCAIqKmpQVlZGTQaDZqbm3Hnzh3MmzcPdnZ2yMvLQ3h4OD799FOMHz9e7HKJjAkDIBE9X3FxMQYNGoTy8nLMnDkT+/fvh0wmYwBshU6nQ2ZmJhISEnDixAl4eXlBJpMhKCgItra2YpcHnU6H69evw8bGxqDD3+Na5j7v3bsXZ86cwcCBA1FWVoa//vWveOWVV8Quj8jYMAASUfvExMTAxsYGn3zyiVnfAm4LnU6HK1euQKlU4osvvsCgQYMgl8sREhICBwcHUeoxxvD3uMLCQixbtgy+vr64du0anJycMH/+fMhkMri4uIhdHpExYAAkomerq6uDTqeDra0t6urqMHPmTGzfvh2nT5+Gk5OTfhOIRqPBnj17xC7XYAmCgOvXr0OpVCI1NRWOjo5QKBQICQnpkTFlphL+SktL8eqrr+KDDz5AQEAAAODOnTtISkpCcnIyevfujTfffBMvv/yyuIUSGTYGQCJ6ttzcXMydOxfAw40PERERiI6Oxr1797Bw4ULk5+dj6NChSEhIgKOjo8jVGgdBEJCdnQ2lUoljx46hX79+UCgUCAsLg6ura5f3hBMEAVlZWejfv3+P9cfrDuXl5Zg/fz52796NwMDAVs8pKiqCTqfDkCFDerg6IqPCAEhEJCZBEJCbmwuVSgW1Wo1evXpBJpNBLpfD3d2902HQVMJfZWUl5s+fj507d+obKhNRhzEAEhEZCkEQUFhYCKVSCbVajebmZoSGhmLu3LkYMmRIu8Ngy23nfv36GXX4q6qqwrx58xAdHQ2ZTCZ2OUSmgAGQiMgQCYKAkpISJCYmIikpCffv30doaCjkcjm8vLyeGwZNJfzV1NRg/vz52LRpE+bPny92OUSmggGQiMgYlJeXQ61WQ6VSQaPRIDg4GDKZDCNGjHgiDDY3N+Obb76BVCqFl5eXSBV33g8//IBXX30VUVFRWLx4sdjlEJkSBkAiImOj0WiQnJwMlUqF4uJizJ49GwqFAr6+vtDpdAgPD8eYMWOwfft2sUvtsLq6OixcuBArVqxAZGSk2OUQmRoGQCIiY1ZTU4Njx45BpVIhNzcXffr0gY+PDz766KM2zdE1RPX19Vi0aBHCw8Px61//WuxyiEwRAyARkSnQarVYtmwZGhoaIJFIcOvWLbzyyiuQy+WYOHGi0YTBhoYGREREQC6XY+3atV3eEoeIADwlABrHvxJERK1YuXIlXF1dMXr0aP0xjUaDmTNn4mc/+xlmzpz5k5F1u3btgre3N3x8fJCWliZGyZ2m1WqxatUqeHl5QalUIiEhARcuXMD06dNx6NAhTJ48GZs3b8bZs2eh1WrFLvepHjx4gGXLliEoKIjhj0gEXAEkIqP11VdfwcbGBpGRkcjKygIAbNmyBY6OjvqpJVVVVdi9ezdu3LiB8PBwZGRkoLi4GIGBgcjOzoalpaXIP0Xb6XQ6rFq1ClKpFDt27Gg1NDU2NuLkyZNQKpX49ttvMWXKFMydOxdTp05Fr169RKj6SU1NTVixYgX8/f2xefNmhj+i7sUVQCIyLS+//PITE0mSk5OxbNkyAMCyZcugVqv1xxcvXgxra2t4enrC29sbGRkZPV1ypxQUFGD48OFPDX8AYG1tjdDQUHz66ae4fPkyFixYALVajSlTpiAqKgonTpzAgwcPerjy/9Pc3IzVq1dj/PjxDH9EImIAJCKTUlZWBnd3dwCAu7s7ysvLATwcG/boyDCpVIqioiJRauyoYcOGYdu2bW0OTb169cKsWbNw8OBBXLlyBZGRkThx4gReeuklvPbaa0hNTUVDQ0M3V/1/tFotfvOb32DEiBGIjo5m+CMSEQMgEZmF1h53MacAYmVlhV/+8pf46KOPcOXKFaxZswZnz57F9OnTsWLFCqjVavz444/d9v21Wi02bNiAwYMHIyYmpks/+4SEBPj6+sLCwgKZmZn643fv3kXfvn3h5+cHPz8/rF27Vv/axYsXMWbMGHh7e2PDhg2t/n4QmTIrsQsgIupKbm5uKCkpgbu7O0pKSuDq6grg4YpfQUGB/rzCwkIMGjRIrDJFZWlpiWnTpmHatGnQ6XT49ttvkZCQgN27d8PLywtyuRxz5syBra1tl3w/nU6HTZs2wcHBAbt27eryXcqjR49GYmIi1qxZ88RrXl5euHz58hPH161bh4MHD2Ly5MkIDg7Gl19+ybnDZFa4AkhEJkUmk+Gzzz4DAHz22WeQy+X64/Hx8WhsbEReXh5ycnIwadIkMUs1CBYWFnjxxRfx3nvv4dKlS3jjjTdw69YtzJkzB4sWLcLnn3+O6urqDr+/TqfDtm3b0KtXL7z//vvd0qJm5MiR8PHxafP5JSUlqK2thb+/PyQSCSIjI/XPihKZC64AEpHRCg8PR3p6OiorK/U7Y7dt24aFCxfi0KFDGDp0KBISEgAAvr6+WLhwIUaNGgUrKyscOHDAqHYA9wQLCwuMHz8e48ePR2xsLLKysqBUKiGTyeDs7AyFQoGQkBA4OTm16f10Oh3efPNNNDY24uOPPxalP2FeXh5+/vOfw87ODm+//TamTZuGoqIiSKVS/TnG+DwoUWcxABKR0YqLi2v1+OnTp1s9Hh0djejo6O4syWRIJBKMGTMGY8aMQUxMDG7dugWlUokFCxbAxsYGMpkMYWFhcHV1bfV5PkEQEBsbi8rKShw+fLjT4S8wMBClpaVPHI+NjdWv8j7O3d0d+fn5cHJywsWLF6FQKHD9+nWzfx6UCGAAJCKi55BIJBgxYgTeeOMNREdHIzc3F0qlEkuWLEHv3r0RFhYGhUKBgQMHQiKRQBAE7NmzB99//z2OHDnSJSutp06davfXWFtbw9raGgDwi1/8Al5eXsjOzoZUKkVhYaH+PHN+HpTMFwMgERG1mUQigZeXF7Zu3YotW7YgPz8fKpUKK1asgE6nQ2hoKDQaDXJzcxEXFwcrK/EuMxUVFXB0dISlpSVyc3ORk5ODF154AY6OjrC1tcX58+fx4osv4siRI1i/fr1odRKJgZNAiIio0wRBQElJCeLi4hAXF4f//ve/6N27d49876SkJKxfvx4VFRVwcHCAn58f0tLSoFKpsH37dlhZWcHS0hI7duxAWFgYACAzMxPLly9HfX09goKCsH//ft4GJlPV6i82AyARERGR6eIoOCIiIiJiACQiIiIyOwyARERERGaGAZCISEQrV66Eq6srRo8erT8WExODwYMH62fYHj9+XP/arl274O3tDR8fH6SlpYlRMhGZAG4CISIS0VdffQUbGxtERkYiKysLwMMAaGNjg82bN//k3Bs3biA8PBwZGRkoLi5GYGAgsrOzOdGEiJ6Fm0CIiAzNyy+/DEdHxzadm5ycjMWLF8Pa2hqenp7w9vZGRkZGN1dIRKaIAZCIyAB9+OGHGDt2LFauXImqqioAQFFREYYMGaI/hzNsiaijGACJiAzMunXrcOfOHVy+fBnu7u7YtGkTAHCGLRF1GQZAIiID4+bmBktLS1hYWGD16tX627xSqRQFBQX68zjDlog6igGQiMjAlJSU6P+clJSk3yEsk8kQHx+PxsZG5OXlIScnB5MmTRKrTCIyYuJN6SYiIoSHhyM9PR2VlZWQSqXYsWMH0tPTcfnyZUgkEnh4eODjjz8GAPj6+mLhwoUYNWoUrKyscODAAe4AJqIOYRsYIiIiItPFNjBERERExABIREREZHYYAImIiIjMDAMgERERkZlhACQiIiIyMwyARERERGaGAZCIiIjIzDAAEhEREZkZBkAiIiIiM8MASERERGRmGACJiIiIzAwDIBEREZGZYQAkIiIiMjMMgERERERmhgGQiIiIyMwwABIRERGZGQZAIiIiIjPDAEhERERkZhgAiYiIiMwMAyARERGRmWEAJCIiIjIzDIBEREREZoYBkIiIiMjMMAASERERmRkGQCIiIiIzwwBIREREZGasnvO6pEeqICIiIqIewxVAIiIiIjPDAEhERERkZhgAiYiIiMwMAyARERGRmWEAJCIiIjIzDIBEREREZub/AT1ZjrjElh7wAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 13.828063542394737 max: 218.27011488545185\n", + "image 1 reprojection errors: average: 14.266911731441311 max: 168.02572846508102\n", + "image 2 reprojection errors: average: 13.259631557103953 max: 159.2642398699781\n", + "image 3 reprojection errors: average: 13.422864585752475 max: 137.03572224565602\n", + "image 4 reprojection errors: average: 14.042001696393454 max: 177.2409590707412\n", + "image 5 reprojection errors: average: 14.419637448618259 max: 232.93124855660497\n", + "image 6 reprojection errors: average: 14.28349841175458 max: 95.76014743378593\n", + "image 7 reprojection errors: average: 13.816511440007561 max: 110.1203537367734\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.5083e+06 2.55e+06 \n", + " 1 2 5.9099e+03 1.50e+06 6.91e+01 9.53e+04 \n", + " 2 3 4.1487e+03 1.76e+03 7.89e-01 1.47e+03 \n", + " 3 4 4.1432e+03 5.47e+00 2.66e-01 8.32e+02 \n", + " 4 5 4.1421e+03 1.18e+00 3.87e-02 9.54e+01 \n", + " 5 6 4.1419e+03 1.74e-01 9.74e-03 3.51e+01 \n", + " 6 7 4.1418e+03 7.01e-02 4.36e-03 1.38e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 1.5083e+06, final cost 4.1418e+03, first-order optimality 1.38e+01.\n", + "mean reprojection error: 0.8453353393586547\n", + "max reprojection error: 3.1669253825859003\n", + "mean reconstruction error: 0.07599713093701795\n", + "max reconstruction error: 0.35918856633649\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 14.186361973998029 max: 142.13279660962115\n", + "image 1 reprojection errors: average: 14.3430728296801 max: 114.57890349429739\n", + "image 2 reprojection errors: average: 14.030040315205252 max: 143.10725465392943\n", + "image 3 reprojection errors: average: 14.251753739436086 max: 183.5931418951843\n", + "image 4 reprojection errors: average: 14.207830844722821 max: 149.83951606976632\n", + "image 5 reprojection errors: average: 14.44821544767734 max: 124.8193940574816\n", + "image 6 reprojection errors: average: 13.708985116983074 max: 111.01284859340113\n", + "image 7 reprojection errors: average: 13.930256656976045 max: 135.84947501329322\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.4939e+06 2.77e+06 \n", + " 1 2 3.9147e+04 1.45e+06 6.89e+01 7.63e+04 \n", + " 2 3 3.8133e+04 1.01e+03 8.75e-01 6.73e+02 \n", + " 3 4 3.8086e+04 4.70e+01 8.20e-01 4.48e+02 \n", + " 4 5 3.8072e+04 1.33e+01 1.44e-01 3.80e+01 \n", + " 5 6 3.8071e+04 1.59e+00 4.35e-02 5.31e+01 \n", + " 6 7 3.8070e+04 7.30e-01 1.38e-02 2.72e+01 \n", + " 7 8 3.8070e+04 4.30e-01 1.15e-02 3.81e+01 \n", + " 8 9 3.8069e+04 3.75e-01 9.62e-03 4.53e+01 \n", + " 9 10 3.8069e+04 3.59e-01 9.64e-03 5.63e+01 \n", + " 10 11 3.8069e+04 1.91e-01 3.68e-03 3.71e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 1.4939e+06, final cost 3.8069e+04, first-order optimality 3.71e+01.\n", + "mean reprojection error: 2.5564564934849114\n", + "max reprojection error: 9.98131009620747\n", + "mean reconstruction error: 0.2290003305014601\n", + "max reconstruction error: 1.0506093661635483\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 15.100127042494083 max: 160.51986142773094\n", + "image 1 reprojection errors: average: 14.658957672792338 max: 151.55699428817383\n", + "image 2 reprojection errors: average: 14.687438047915299 max: 77.94474483482014\n", + "image 3 reprojection errors: average: 14.67090740732709 max: 129.3577026301649\n", + "image 4 reprojection errors: average: 14.871906549459718 max: 245.14146882194805\n", + "image 5 reprojection errors: average: 15.002691746208708 max: 181.49916389261205\n", + "image 6 reprojection errors: average: 14.142437625710745 max: 130.7997569389291\n", + "image 7 reprojection errors: average: 15.023724647497383 max: 155.0864057338731\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6006e+06 2.02e+06 \n", + " 1 2 1.0686e+05 1.49e+06 7.10e+01 7.35e+04 \n", + " 2 3 1.0555e+05 1.31e+03 1.24e+00 1.98e+03 \n", + " 3 4 1.0541e+05 1.40e+02 1.38e+00 1.30e+03 \n", + " 4 5 1.0536e+05 5.00e+01 2.58e-01 1.23e+02 \n", + " 5 6 1.0535e+05 6.83e+00 9.27e-02 9.59e+01 \n", + " 6 7 1.0535e+05 3.87e+00 4.56e-02 8.69e+01 \n", + " 7 8 1.0535e+05 1.69e+00 2.22e-02 6.17e+01 \n", + " 8 9 1.0535e+05 1.31e+00 1.96e-02 8.12e+01 \n", + " 9 10 1.0535e+05 1.28e+00 1.87e-02 8.80e+01 \n", + " 10 11 1.0535e+05 1.03e+00 1.38e-02 1.13e+02 \n", + " 11 12 1.0534e+05 7.43e-01 9.27e-03 9.66e+01 \n", + " 12 13 1.0534e+05 3.53e-01 3.94e-03 4.33e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 1.6006e+06, final cost 1.0534e+05, first-order optimality 4.33e+01.\n", + "mean reprojection error: 4.2565467060174385\n", + "max reprojection error: 16.392380585922076\n", + "mean reconstruction error: 0.378511613097883\n", + "max reconstruction error: 1.7280389068962418\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 17.09867179575005 max: 118.48103903261772\n", + "image 1 reprojection errors: average: 17.363731455254754 max: 155.74102883809007\n", + "image 2 reprojection errors: average: 16.937621673918557 max: 107.22656681795047\n", + "image 3 reprojection errors: average: 16.897941538151336 max: 104.96684275768155\n", + "image 4 reprojection errors: average: 17.939475068224173 max: 252.947133817352\n", + "image 5 reprojection errors: average: 17.62125191913709 max: 98.61883188730926\n", + "image 6 reprojection errors: average: 17.390697365602733 max: 135.27484877400363\n", + "image 7 reprojection errors: average: 17.61046441629536 max: 152.50414170677618\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0189e+06 2.49e+06 \n", + " 1 2 4.2301e+05 1.60e+06 7.52e+01 2.75e+05 \n", + " 2 3 4.1944e+05 3.57e+03 2.99e+00 1.15e+04 \n", + " 3 4 4.1905e+05 3.90e+02 1.68e+00 2.64e+03 \n", + " 4 5 4.1885e+05 2.06e+02 5.72e-01 7.90e+02 \n", + " 5 6 4.1880e+05 4.98e+01 2.50e-01 5.96e+02 \n", + " 6 7 4.1876e+05 3.86e+01 1.87e-01 3.64e+02 \n", + " 7 8 4.1873e+05 2.71e+01 1.48e-01 4.46e+02 \n", + " 8 9 4.1871e+05 2.13e+01 1.09e-01 3.56e+02 \n", + " 9 10 4.1870e+05 1.04e+01 5.10e-02 1.98e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 10 11 4.1869e+05 1.00e+01 7.13e-02 3.50e+02 \n", + " 11 12 4.1868e+05 9.55e+00 4.88e-02 1.88e+02 \n", + " 12 13 4.1867e+05 8.06e+00 5.82e-02 2.89e+02 \n", + " 13 14 4.1866e+05 8.05e+00 4.57e-02 1.85e+02 \n", + " 14 15 4.1866e+05 7.56e+00 5.46e-02 2.60e+02 \n", + " 15 16 4.1865e+05 7.38e+00 4.38e-02 1.69e+02 \n", + " 16 17 4.1864e+05 7.17e+00 5.24e-02 2.90e+02 \n", + " 17 18 4.1863e+05 6.95e+00 4.21e-02 1.71e+02 \n", + " 18 19 4.1863e+05 6.47e+00 4.73e-02 3.32e+02 \n", + " 19 20 4.1862e+05 6.56e+00 4.09e-02 2.12e+02 \n", + " 20 21 4.1862e+05 5.75e+00 4.01e-02 3.53e+02 \n", + " 21 22 4.1861e+05 6.16e+00 4.02e-02 2.93e+02 \n", + " 22 23 4.1860e+05 5.53e+00 3.55e-02 3.70e+02 \n", + " 23 24 4.1860e+05 3.24e+00 1.78e-02 2.04e+02 \n", + " 24 25 4.1860e+05 1.70e+00 1.02e-02 1.79e+02 \n", + " 25 26 4.1860e+05 1.76e+00 1.34e-02 2.15e+02 \n", + " 26 27 4.1860e+05 1.69e+00 9.92e-03 1.70e+02 \n", + " 27 28 4.1859e+05 1.79e+00 1.41e-02 2.35e+02 \n", + " 28 29 4.1859e+05 1.71e+00 9.65e-03 1.57e+02 \n", + " 29 30 4.1859e+05 1.86e+00 1.53e-02 2.64e+02 \n", + " 30 31 4.1859e+05 1.61e+00 8.35e-03 1.11e+02 \n", + " 31 32 4.1859e+05 1.62e+00 1.44e-02 2.71e+02 \n", + " 32 33 4.1859e+05 1.50e+00 7.60e-03 9.34e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 33, initial cost 2.0189e+06, final cost 4.1859e+05, first-order optimality 9.34e+01.\n", + "mean reprojection error: 8.486325964905733\n", + "max reprojection error: 30.167549332567813\n", + "mean reconstruction error: 0.7507895219703264\n", + "max reconstruction error: 3.116007122632202\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony a7R-IV" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "ratio = np.array([9504/6000,6336/4000])\n", + "focal_length = np.array([2925.84685880484, 2930.0351899542])*ratio\n", + "principle_point = np.array([3000, 2000])*ratio\n", + "radial_distortion = np.array([-0.251288719187471, 0.0622370807856553])#[-0.28009, 0.11246, -0.02736])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([9504, 6336])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, camera_halfz_position, camera_radial_position],\n", + " [0, camera_halfz_position, -camera_radial_position],\n", + " [camera_radial_position, -camera_halfz_position, 0],\n", + " [-camera_radial_position, -camera_halfz_position, 0]])\n", + "camera_directions = [[0, -1.1, -1],\n", + " [0, -1.1, 1],\n", + " [-1, 1.1, 0],\n", + " [1, 1.1, 0]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.520390402995194 max: 185.70287979566353\n", + "image 1 reprojection errors: average: 22.26358912963671 max: 267.1689273880863\n", + "image 2 reprojection errors: average: 21.984447896212796 max: 222.64995498925018\n", + "image 3 reprojection errors: average: 22.211958002703994 max: 283.77446306759606\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8934e+06 6.15e+06 \n", + " 1 2 3.6471e+03 1.89e+06 6.72e+01 1.95e+05 \n", + " 2 3 1.3059e+03 2.34e+03 4.38e+00 2.03e+03 \n", + " 3 4 1.3035e+03 2.45e+00 1.21e-01 6.84e+02 \n", + " 4 5 1.3029e+03 5.78e-01 3.15e-02 1.28e+02 \n", + " 5 6 1.3027e+03 2.18e-01 1.61e-02 8.96e+01 \n", + " 6 7 1.3026e+03 1.04e-01 8.21e-03 2.85e+01 \n", + " 7 8 1.3025e+03 5.72e-02 4.60e-03 2.74e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 1.8934e+06, final cost 1.3025e+03, first-order optimality 2.74e+01.\n", + "mean reprojection error: 0.6388473110821935\n", + "max reprojection error: 2.6315289284078736\n", + "mean reconstruction error: 0.07395240275817924\n", + "max reconstruction error: 0.32834927168588207\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.711888913566533 max: 184.46919675350037\n", + "image 1 reprojection errors: average: 22.549763121108743 max: 195.46446511289201\n", + "image 2 reprojection errors: average: 22.861226692956464 max: 244.14570798266172\n", + "image 3 reprojection errors: average: 23.888202881192218 max: 483.1818774192915\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0557e+06 8.29e+06 \n", + " 1 2 1.9304e+04 2.04e+06 7.12e+01 7.65e+05 \n", + " 2 3 1.2004e+04 7.30e+03 8.34e-01 3.02e+04 \n", + " 3 4 1.1981e+04 2.25e+01 2.27e-01 2.31e+03 \n", + " 4 5 1.1977e+04 3.99e+00 4.71e-02 2.83e+02 \n", + " 5 6 1.1976e+04 1.69e+00 3.37e-02 1.65e+02 \n", + " 6 7 1.1975e+04 1.18e+00 1.86e-02 1.21e+02 \n", + " 7 8 1.1973e+04 1.23e+00 3.04e-02 1.87e+02 \n", + " 8 9 1.1972e+04 8.49e-01 1.13e-02 6.25e+01 \n", + " 9 10 1.1972e+04 9.18e-01 2.82e-02 1.87e+02 \n", + " 10 11 1.1971e+04 8.16e-01 1.03e-02 4.96e+01 \n", + " 11 12 1.1970e+04 8.74e-01 2.92e-02 1.84e+02 \n", + " 12 13 1.1969e+04 7.97e-01 9.66e-03 4.00e+01 \n", + " 13 14 1.1969e+04 3.66e-01 1.22e-02 9.61e+01 \n", + " 14 15 1.1968e+04 4.12e-01 7.55e-03 5.03e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 15, initial cost 2.0557e+06, final cost 1.1968e+04, first-order optimality 5.03e+01.\n", + "mean reprojection error: 1.9470376716553401\n", + "max reprojection error: 8.76596845887681\n", + "mean reconstruction error: 0.22444447866170772\n", + "max reconstruction error: 1.0470452237867538\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.958458395369146 max: 191.04954543740516\n", + "image 1 reprojection errors: average: 22.471435732132797 max: 262.8019902299815\n", + "image 2 reprojection errors: average: 23.02204045802236 max: 359.79576912051186\n", + "image 3 reprojection errors: average: 23.02568017986665 max: 385.04619593986587\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0767e+06 6.26e+06 \n", + " 1 2 3.8056e+04 2.04e+06 7.05e+01 1.97e+05 \n", + " 2 3 3.5071e+04 2.99e+03 7.76e-01 3.34e+03 \n", + " 3 4 3.5017e+04 5.33e+01 7.22e-01 2.76e+03 \n", + " 4 5 3.5002e+04 1.52e+01 1.41e-01 3.33e+02 \n", + " 5 6 3.4998e+04 3.74e+00 6.49e-02 1.80e+02 \n", + " 6 7 3.4996e+04 2.39e+00 3.76e-02 9.19e+01 \n", + " 7 8 3.4995e+04 1.15e+00 1.93e-02 7.15e+01 \n", + " 8 9 3.4994e+04 6.47e-01 1.02e-02 4.74e+01 \n", + " 9 10 3.4994e+04 4.14e-01 7.63e-03 4.95e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 2.0767e+06, final cost 3.4994e+04, first-order optimality 4.95e+01.\n", + "mean reprojection error: 3.3216849504158836\n", + "max reprojection error: 13.65539615610933\n", + "mean reconstruction error: 0.362063983717853\n", + "max reconstruction error: 1.4649157297696673\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 23.741571765472546 max: 237.00736672231469\n", + "image 1 reprojection errors: average: 24.750985504093233 max: 330.2517559366125\n", + "image 2 reprojection errors: average: 24.546894133014984 max: 317.998241764834\n", + "image 3 reprojection errors: average: 25.441199696266413 max: 451.3968358437266\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3795e+06 9.89e+06 \n", + " 1 2 1.4743e+05 2.23e+06 7.59e+01 5.37e+05 \n", + " 2 3 1.3847e+05 8.96e+03 1.14e+00 2.01e+04 \n", + " 3 4 1.3829e+05 1.78e+02 1.20e+00 1.79e+04 \n", + " 4 5 1.3824e+05 5.21e+01 1.62e-01 1.39e+03 \n", + " 5 6 1.3823e+05 8.50e+00 6.18e-02 5.73e+02 \n", + " 6 7 1.3823e+05 4.49e+00 2.84e-02 1.76e+02 \n", + " 7 8 1.3823e+05 3.11e+00 2.70e-02 3.95e+02 \n", + " 8 9 1.3822e+05 3.99e+00 3.19e-02 2.01e+02 \n", + " 9 10 1.3822e+05 2.09e+00 1.40e-02 1.29e+02 \n", + " 10 11 1.3822e+05 1.96e+00 2.14e-02 1.94e+02 \n", + " 11 12 1.3822e+05 1.92e+00 1.33e-02 1.21e+02 \n", + " 12 13 1.3821e+05 2.01e+00 2.25e-02 1.98e+02 \n", + " 13 14 1.3821e+05 1.92e+00 1.30e-02 1.06e+02 \n", + " 14 15 1.3821e+05 1.90e+00 2.19e-02 1.91e+02 \n", + " 15 16 1.3821e+05 1.86e+00 1.28e-02 9.95e+01 \n", + " 16 17 1.3821e+05 1.85e+00 2.17e-02 1.82e+02 \n", + " 17 18 1.3820e+05 1.82e+00 1.26e-02 9.34e+01 \n", + " 18 19 1.3820e+05 1.80e+00 2.15e-02 1.79e+02 \n", + " 19 20 1.3820e+05 1.77e+00 1.23e-02 8.74e+01 \n", + " 20 21 1.3820e+05 1.74e+00 2.11e-02 1.76e+02 \n", + " 21 22 1.3820e+05 1.71e+00 1.21e-02 8.14e+01 \n", + " 22 23 1.3820e+05 1.69e+00 2.08e-02 1.73e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 23 24 1.3819e+05 1.67e+00 1.19e-02 7.55e+01 \n", + " 24 25 1.3819e+05 1.65e+00 2.05e-02 1.71e+02 \n", + " 25 26 1.3819e+05 1.63e+00 1.17e-02 7.04e+01 \n", + " 26 27 1.3819e+05 1.62e+00 2.04e-02 1.79e+02 \n", + " 27 28 1.3819e+05 1.60e+00 1.15e-02 7.26e+01 \n", + " 28 29 1.3819e+05 1.59e+00 2.04e-02 1.88e+02 \n", + " 29 30 1.3818e+05 1.57e+00 1.15e-02 7.13e+01 \n", + " 30 31 1.3818e+05 1.56e+00 2.02e-02 2.08e+02 \n", + " 31 32 1.3818e+05 1.54e+00 1.13e-02 7.37e+01 \n", + " 32 33 1.3818e+05 1.31e+00 1.70e-02 2.00e+02 \n", + " 33 34 1.3818e+05 1.31e+00 1.04e-02 8.36e+01 \n", + " 34 35 1.3818e+05 1.30e+00 1.69e-02 2.14e+02 \n", + " 35 36 1.3818e+05 1.28e+00 1.03e-02 8.49e+01 \n", + " 36 37 1.3818e+05 1.26e+00 1.66e-02 2.26e+02 \n", + " 37 38 1.3817e+05 1.24e+00 1.00e-02 9.13e+01 \n", + " 38 39 1.3817e+05 1.10e+00 1.43e-02 2.97e+02 \n", + " 39 40 1.3817e+05 1.21e+00 1.01e-02 1.38e+02 \n", + " 40 41 1.3817e+05 9.00e-01 1.06e-02 2.78e+02 \n", + " 41 42 1.3817e+05 8.58e-01 7.20e-03 1.89e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 42, initial cost 2.3795e+06, final cost 1.3817e+05, first-order optimality 1.89e+02.\n", + "mean reprojection error: 6.60901696250545\n", + "max reprojection error: 30.188506880869582\n", + "mean reconstruction error: 0.7296500078394403\n", + "max reconstruction error: 3.2310657203260353\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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59u3bR1JSEjk5OQAMHz6cOXPmAPDHP/6RLl26kJaWxpQpU0qM+4knnqBr16507NiRMWPGcOzYsVAMkydPplu3bqxcubLI9MyZM2nfvj3t27fnz3/+MwBbt24lJSWFG2+8kfT0dLZt2xZ1u71792bChAn06tWLlJQU3nvvPQYPHkxiYiJ33nlnifGNGzeOjIwMUlNTC+xn69atmTJlCunp6XTo0IHs7OwS26A4zjneeustrr76agBGjhzJSy+9VKTc66+/Tt++fWnSpAmNGzemb9++vPbaawXKfPPNN7z11lsRe1oOHTrEsGHDSEtLY+jQoRw6dCi0bPHixfTo0YP09HSGDBnCgQMHAHj11VdJTk6mZ8+ejB8/nssvv7xc+1oSJS0iIqeQHTt2cM4554SmExIS2LFjR5FyBw8eJD09nXXr1nHRRRcxderUAssbNmzIrFmzyMzM5JlnnuHrr7/m+uuvZ/HixWzZsoXVq1ezfv161q5dy7Jly6LGs3nzZhYsWMCKFStYv3491atX58knnwzF0L59e7KysujZs2eB6Tp16jB37lyysrJYtWoVc+bM4f333wcgJyeHESNG8P7779OqVSv69+/Pzp07I27/tNNOY9myZYwdO5aBAwdy//33s3HjRubNm8eePXuKje93v/sda9asYcOGDSxdupQNGzaE6m3atCnr1q1j3LhxzJgxo8h2c3JyQpdrCr/27t1boOyePXto1KgRNWrUKPaYxXJsX3zxRfr06UODBg2KrP/ggw9St25dNmzYwB133MHatWsB+Oqrr5g2bRpLlixh3bp1ZGRkMHPmTA4fPsyYMWNYtGgRy5cvDyW2FUmXh0RETiHOuSLzIn2Lo1q1agwdOhSAX/ziFwwePLhImb59+7Jw4UJuuukmPvjgA8D7RL548WI6deoEwIEDB9iyZQu9evWKGM+bb77J2rVr6dKlC+B92m/WrBkA1atX56qrrgqVDZ9evnw5gwYNol69egAMHjyYd955hwEDBtCqVSu6d+8eWu/VV1+N2h4DBgwAoEOHDqSmptKiRQsA2rRpw7Zt21i+fHnU+J599llmz57N0aNHyc3NZdOmTaSlpYXiAejcuTMvvPBCke0mJSWxfv36qHGFi/WYxVLu6aef5rrrrou4nWXLljF+/HgA0tLSQvuyatUqNm3axAUXXADAkSNH6NGjB9nZ2bRp0yb0nJXhw4cze/bsmPaprJS0iIicQhISEgpcMtm+fTstW7Yscb1I/ySPHz/O5s2bqVOnDnl5eSQkJOCc47bbbmPMmDExxeOcY+TIkfz+978vsqx27doF7lsJn470DzpffiITi1q1agFekpb/Pn/66NGjUeP77LPPmDFjBu+99x6NGzcmMzOzwDNH8uuqXr06R48eLbLdnJycUFJY2Ntvv02jRo1C002bNmXv3r0cPXqUGjVqRD1mCQkJvP3226Hp7du307t379D0nj17WL16NS+++GLU9oiWDPXt25enn366wPz8nq3KpKRFRKQCbMrdH/MNtLHU1a5F0e78shgwYACzZs1i2LBhZGVl0bBhw1DvQrjjx4/z3HPPMWzYMJ566il69uxZpMx9991HSkoK99xzD6NHj2blypVceuml/Pa3v+XnP/859evXZ8eOHdSsWTPUO1FYnz59GDhwIBMmTKBZs2bk5eXxzTff0KpVq2L3o1evXmRmZjJp0iScc7z44os8/vjjZWuUYkSLb//+/dSrV4+GDRuya9cuFi1aVCBBKElpelrMjIsvvjh0PObPnx/xRtpLL72U22+/na+//hrwer3Ck62FCxdy+eWXU7t27Yjb6dWrF08++SQXX3wxGzduDF3u6t69OzfddBOffPIJbdu25dtvv2X79u0kJyfz6aefsnXrVlq3bs2CBQti3v+yOimTlkjPSNAzDkSksrRrGZ8EI1RfiwYx1Tl8+HDefvttvvrqKxISEpg6dSrXXnstDz30EABjx46lf//+vPrqq7Rt25a6desyd+7ciHXVq1ePjz76iM6dO9OwYcMi/5A+/vhjHnnkEVavXs3pp59Or169mDZtGlOnTmXz5s306OF9c6p+/fo88cQTUZOWdu3aMW3aNC655BKOHz9OzZo1uf/++0tMWtLT08nMzKRr164AXHfddXTq1ImtW7cWKdu/f38eeeSRmHqUYo2ve/fudOrUidTUVNq0aRO6dFJRpk+fzrBhw7jzzjvp1KkT1157LQBr1qzhoYce4pFHHqFJkyb89re/DV3Kmjx5coEbs5955hkmTZoUdRvjxo1j1KhRpKWl0bFjx1DbnnnmmcybN4/hw4fz3XffATBt2jTOO+88HnjgAfr160fTpk1D5SuSFdfFFm8ZGRmuMr7zPfThlQU+meS/j9fXD0VECtu8eTMpKSlVHUbc1K9fP/QNEZFoDhw4QP369XHOcdNNN5GYmMiECRNiXj/S742ZrXXOZUQqf9J+eyg/SVkwpkfculVFRETkP+bMmUPHjh1JTU1l3759Md/LVFYn5eUhEREpH/WySCwmTJhQqp6V8jppe1pERETk5KKkRURERAJBSYuIiIgEgu5pERGJt0WT4IsP41tn8w5w2b3xrVMkYNTTIiISb198GN+kJYb6Dh8+TNeuXTn//POLDOAXzjnH+PHjadu2LWlpaaxbt65UoUyePJklS5aUap189evXL9N64j2Bt1u3biQmJjJ06FCOHDlSpMz69evp0aMHqamppKWlFXi2TizrF9a7d28q4zElpVFiT4uZ1QaWAbX88s8556aYWRNgAdAa2Ar81Dn3dcWFKiISIM07wKh/xKeuuT8psUitWrV46623qF+/Pt9//z09e/bksssuKzAGD8CiRYvYsmULW7ZsISsri3HjxpGVlRVzKHfffXepw4+HY8eOFXikf+HpSJxzOOeoVi34n88nTpzIhAkTGDZsGGPHjuXRRx9l3LhxBcrUrVuXxx57jMTERHbu3Ennzp259NJLadSoUUzrB0EsR/I74EfOufOBjkA/M+sOTALedM4lAm/60yIiUgXMLNST8f333/P9999HHEfm5ZdfZsSIEZgZ3bt3Z+/eveTm5hYpV79+fW699VbS09Pp06dPaATfzMxMnnvuOfbt20dSUhI5OTmA9zTeOXPmAPDHP/6RLl26kJaWFrXHJ9wTTzxB165d6dixI2PGjOHYsWOhGCZPnky3bt1YuXJlkemZM2fSvn172rdvz5///GcAtm7dSkpKCjfeeCPp6ekFxlkqrHfv3kyYMIFevXqRkpLCe++9x+DBg0lMTOTOO+8sMb5x48aRkZFRpGerdevWTJkyhfT0dDp06EB2dnaJbVAc5xxvvfUWV199NQAjR47kpZdeKlLuvPPOIzExEYCWLVvSrFkzdu/eHfP6hw4dYtiwYaSlpTF06FAOHToUWrZ48WJ69OhBeno6Q4YMCX0l/tVXXyU5OZmePXsyfvx4Lr/88nLta0lKTFqcJ/8L+zX9lwMGAvP9+fOBKysiwFhNfeUjhj68MvQ0XBGRU82xY8fo2LEjzZo1o2/fvnTr1q1ImR07dnDOOeeEphMSEtixY0eRcgcPHiQ9PZ1169Zx0UUXMXXq1ALLGzZsyKxZs8jMzOSZZ57h66+/5vrrr2fx4sVs2bKF1atXs379etauXcuyZcuixrx582YWLFjAihUrWL9+PdWrV+fJJ58MxdC+fXuysrLo2bNngek6deowd+5csrKyWLVqFXPmzAkN4JeTk8OIESN4//33adWqFf3792fnzp0Rt3/aaaexbNkyxo4dy8CBA7n//vvZuHEj8+bNY8+ePcXG97vf/Y41a9awYcMGli5dGhqrB7xBDtetW8e4ceOYMWNGke3m5OTQsWPHiK+9e/cWKLtnzx4aNWpEjRo1ij1m4VavXs2RI0f44Q9/GPP6Dz74IHXr1mXDhg3ccccdrF27FoCvvvqKadOmsWTJEtatW0dGRgYzZ87k8OHDjBkzhkWLFrF8+fJQYluRYroR18yqA2uBtsD9zrksMzvLOZcL4JzLNbOIA0uY2Q3ADQA/+MEP4hN1BJt27g89rj/WcTpERE4m1atXZ/369ezdu5dBgwaxceNG2rdvX6BMpKFbIvXIVKtWLTQK8S9+8QsGDx5cpEzfvn1ZuHAhN910Ex988AHgfSJfvHgxnTp1AryH1G3ZsoVevXpFjPnNN99k7dq1ofFyDh06FBqnqHr16lx11VUF9i9/evny5QwaNCg0ovPgwYN55513GDBgAK1atSpwWezVV1+NuG3wBpAE6NChA6mpqaHBI9u0acO2bdtYvnx51PieffZZZs+ezdGjR8nNzWXTpk2kpaWF4gHo3LkzL7zwQpHtlmbAxFiPWb7c3FyuueYa5s+fT7Vq1WJef9myZYwfPx6AtLS00L6sWrWKTZs2hcZXOnLkCD169CA7O5s2bdpw7rnnAl5v2+zZs2Pap7KKKWlxzh0DOppZI+BFM2tfwirh684GZoM39lBZgoyVxhcSEYFGjRrRu3dvXnvttSJJS0JCQoFLJtu3b49pIMFI/+SOHz/O5s2bqVOnDnl5eSQkJOCc47bbbov5ce7OOUaOHFlgNOJ8tWvXLnDfSvh0cePm5ScysahVqxbgJWn57/Onjx49GjW+zz77jBkzZvDee+/RuHFjMjMzOXz4cJF6q1evztGjR4tsNycnJ5QUFvb222/TqFGj0HTTpk3Zu3cvR48epUaNGsUes/379/OTn/yEadOmhRK30qwf6Tg75+jbty9PP/10gfn5PVuVqVR3Jznn9gJvA/2AXWbWAsD/+WW8gxMRCawvPvRuoI3HK4ZvIu3evTt0WeHQoUMsWbKE5OTkIuUGDBjAY489hnOOVatW0bBhw1DvQrjjx4/z3HPPAfDUU0/Rs2fPImXuu+8+UlJSePrppxk9ejTff/89l156KX/9619D9zzs2LGDL7+M/u+hT58+PPfcc6EyeXl5fP755yXub69evXjppZf49ttvOXjwIC+++CIXXnhhieuVVrT49u/fT7169WjYsCG7du1i0aJFpao3v6cl0is8YQEvkbj44otDx2P+/PkMHDiwSJ1Hjhxh0KBBjBgxgiFDhpR6/V69eoUufW3cuDF0uat79+6sWLGCTz75BIBvv/2Wjz/+mOTkZD799NPQyNqFRwKvCCUmLWZ2pt/DgpnVAX4MZAN/A0b6xUYCL1dQjCIiwdK8g/eqxPpyc3O5+OKLSUtLo0uXLvTt2zd0U+RDDz3EQw89BED//v1p06YNbdu25frrr+eBBx6IWF+9evX46KOP6Ny5M2+99RaTJ08usPzjjz/mkUce4U9/+hMXXnghvXr1Ytq0aVxyySX87Gc/o0ePHnTo0IGrr76ab775Jmrc7dq1C62XlpZG3759I94YXFh6ejqZmZl07dqVbt26cd1114UuSRVW3D0tJYkW3/nnn0+nTp1ITU1l9OjRoUsnFWX69OnMnDmTtm3bsmfPHq699loA1qxZw3XXXQd4l6uWLVvGvHnzQvfH5F+CirZ+uHHjxnHgwAHS0tL4wx/+QNeuXQE488wzmTdvHsOHDyctLY3u3buTnZ1NnTp1eOCBB+jXrx89e/bkrLPOomHDhhXaDlZcFxuAmaXh3WhbHS/JedY5d7eZnQE8C/wA+DcwxDmXV1xdGRkZrqK+8z304ZUAES8PFbdMRCQeNm/eTEpKSlWHETf169fXoIlSogMHDlC/fn2cc9x0000kJiaWagDFSL83ZrbWOZcRqXyJ97Q45zYARdJX59weoE/MkYmIiMhJZc6cOcyfP58jR47QqVOnmO9lKis9xl9ERIpQL4vEYsKECaXqWSmv4D8mUERERE4JSlpEREQkEJS0iIiISCDonpYK8sU99/Dd5vKNN1EetVKSaX777VW2fZFT2fTV08nOi+/vf3KTZCZ2nRjXOkWCRj0tFeS7zdkcLucgWWV1ODu7ShMmkVNddl42OXk5casvJy8npiSodevWdOjQgY4dO5KREfEbozjnGD9+PG3btiUtLY1169aVKpbJkyezZMmSUq2TL39ARym9zz77jG7dupGYmMjQoUM5cuRIkTKff/45nTt3pmPHjqSmpoaezQNw7bXXcv7555OWlsbVV18d043WvXv3pqIeU1JW6mmpQLWTk2n1+GOVvt3PrxlR6dsUkYKSmiQxt9/cuNQ16rVRMZf95z//SdOmTaMuX7RoEVu2bGHLli1kZWUxbtw4srKyYq7/7rvvjrlsPB07dqzAI/0LT0finMM5R7Vqwf98PnHiRCZMmMCwYcMYO3Ysjz76KOPGjStQpkWLFrz77rvUqlWLAwcO0L59ewYMGEDLli257777aNDAG5PvlltuYdasWUyaNKkqdqVcgn8kRUQkZi+//DIjRozAzOjevTt79+6N+ATa+vXrc+utt5Kenk6fPn1CI/hmZmby3HPPsW/fPpKSksjJ8XqUhg8fzpw5cwD44x//SJcuXUhLS2PKlCklxvTEE0/QtWtXOnbsyJgxYzh27FgohsmTJ9OtWzdWrlxZZHrmzJm0b9+e9u3b8+c//xmArVu3kpKSwo033kh6enqBcZYK6927NxMmTKBXr16kpKTw3nvvMXjwYBITE7nzzjtLjG/cuHFkZGSQmppaYD9bt27NlClTSE9Pp0OHDmSXs9fdOcdbb73F1VdfDcDIkSN56aWXipQ77bTTQmMefffddxw/fjy0LD9hcc5x6NChiGMMHTp0iGHDhpGWlsbQoUM5dOhQaNnixYvp0aMH6enpDBkyJNRT8+qrr5KcnEzPnj0ZP3586CnMFUVJi4jIScLMuOSSS+jcuXPU0XZ37NjBOeecE5pOSEhgx44dRcodPHiQ9PR01q1bx0UXXcTUqVMLLG/YsCGzZs0iMzOTZ555hq+//prrr7+exYsXs2XLFlavXs369etZu3Yty5Ytixrz5s2bWbBgAStWrGD9+vVUr149NP7NwYMHad++PVlZWfTs2bPAdJ06dZg7dy5ZWVmsWrWKOXPmhAbwy8nJYcSIEbz//vu0atWq2Mf4n3baaSxbtoyxY8cycOBA7r//fjZu3Mi8efPYs2dPsfH97ne/Y82aNWzYsIGlS5eGxuoBb5DCdevWMW7cOGbMmFFkuzk5OaFH7Rd+5Y8hlW/Pnj00atSIGjVqFHvMALZt20ZaWhrnnHMOEydOLDAw4qhRo2jevDnZ2dn88pe/LLLugw8+SN26ddmwYQN33HEHa9euBeCrr75i2rRpLFmyhHXr1pGRkcHMmTM5fPgwY8aMYdGiRSxfvjyU2FYkXR4SETlJrFixgpYtW/Lll1/St29fkpOT6dWrV4EykYZuifSpu1q1aqFRiH/xi18wePDgImX69u3LwoULuemmm/jggw8A7xP54sWLQ+MAHThwgC1bthSJI9+bb77J2rVr6dKlC+B92m/WrBngjZB81VVXhcqGTy9fvpxBgwaFRnQePHgw77zzDgMGDKBVq1ahEY7B6w2IZsCAAQB06NCB1NTU0OCRbdq0Ydu2bSxfvjxqfM8++yyzZ8/m6NGj5ObmsmnTJtLS0kLxAHTu3JkXXnihyHbzB0yMRazHDOCcc85hw4YN7Ny5kyuvvJKrr76as846C4C5c+dy7NgxfvnLX7JgwQJGjSp42XHZsmWMHz8egLS0tNC+rFq1ik2bNoXGVzpy5Ag9evQgOzubNm3acO655wJeb1u0ZDlelLSIiJwk8j9VN2vWjEGDBrF69eoiyUJCQkKBSybbt28v8Gk8mkj/JI8fP87mzZupU6cOeXl5JCQk4Jzjtttui/lx7s45Ro4cye9///siy2rXrl3gvpXw6eLGzctPZGKRfzmlWrVqoff500ePHo0a32effcaMGTN47733aNy4MZmZmRw+fLhIvdWrV+fo0aNFtpuTkxNKCgt7++23C4z03LRpU/bu3cvRo0epUaNGTMesZcuWpKam8s4774QuK+XHM3ToUP74xz8WSVog8nF2ztG3b1+efvrpAvPze7Yqk5IWEZEKkJOXU6obaEuqK6lJUrFlDh48yPHjxzn99NM5ePAgixcvLjIyM3g9C7NmzWLYsGFkZWXRsGHDUO9CuOPHj/Pcc88xbNgwnnrqKXr27FmkzH333UdKSgr33HMPo0ePZuXKlVx66aX89re/5ec//zn169dnx44d1KxZM9Q7UVifPn0YOHAgEyZMoFmzZuTl5fHNN9/QqlWrYve3V69eZGZmMmnSJJxzvPjiizz++OPFrlMW0eLbv38/9erVo2HDhuzatYtFixbRu3fvmOstTU+LmXHxxReHjsf8+fMZOHBgkXLbt2/njDPOoE6dOnz99desWLGCW265Becc//rXv2jbti3OOV555RWSk5OLrN+rVy+efPJJLr74YjZu3Bi63NW9e3duuukmPvnkE9q2bcu3337L9u3bSU5O5tNPP2Xr1q20bt2aBQsWxLz/ZaWkRUQkzpKbFP2HUB5JTZJKrHPXrl0MGjQIgKNHj/Kzn/2Mfv36AYS++jp27Fj69+/Pq6++Stu2balbty5z50b+hlO9evX46KOP6Ny5Mw0bNizyD+njjz/mkUceYfXq1Zx++un06tWLadOmMXXqVDZv3kyPHj0A72baJ554ImrS0q5dO6ZNm8Yll1zC8ePHqVmzJvfff3+JSUt6ejqZmZl07doVgOuuu45OnTqxdevWImX79+/PI488ElOPUqzxde/enU6dOpGamkqbNm1Cl04qyvTp0xk2bBh33nknnTp14tprrwVgzZo1PPTQQzzyyCNs3ryZW2+9FTPDOcevf/1rOnTowPHjxxk5ciT79+/HOcf555/Pgw8+WGQb48aNY9SoUaSlpdGxY8dQ25555pnMmzeP4cOH89133wEwbdo0zjvvPB544AH69etH06ZNQ+UrkhXXxRZvGRkZrqK+8z304ZUALBjTo1TLKkr+146r8ivPVbFtkVPV5s2bSUlJqeow4qZ+/foaNFFKdODAAerXr49zjptuuonExMRSDaAY6ffGzNY65yI+aEjfHhIREZEymTNnTuhhdvv27Yv5Xqay0uUhEREpQr0sEosJEyaUqmelvNTTIiIiIoGgpEVEREQCQUmLiIiIBILuaRERibMv7rkn7iOt10pJpvntt8e1TpGgUU+LiEicfbc5m8PlHCQv3OHs7JiSoNGjR9OsWTPat29fYH5eXh59+/YlMTGRvn378vXXX0dc/7XXXiMpKYm2bdty7733lirGNWvWhB4BX1r5gzBK6TnnGD9+PG3btiUtLY1169ZFLXfHHXdw3nnnkZKSwl/+8hfAG9wyf8yj9u3bU716dfLy8ord5rx587j55pvjvi+xUE+LiEgFqJ2cHLdnJeU/e6kkmZmZ3HzzzYwYUbD8vffeS58+fZg0aRL33nsv9957L9OnTy9Q5tixY9x000288cYbJCQk0KVLFwYMGEC7du1i2nZGRgYZGREfrVGh8h9tH2061vWCatGiRWzZsoUtW7aQlZXFuHHjyMrKKlJu3rx5bNu2jezsbKpVq8aXX34JwG9+8xt+85vfAPDKK69w33330aRJk0rdh9JQT4uIyEmiV69eEf/hvPzyy4wcORKAkSNH8tJLLxUps3r1atq2bUubNm047bTTGDZsGC+//HKRcpmZmYwdO5YLL7yQ8847j7///e+AN17O5ZdfDsD48eO5++67AXj99dfp1asXx48fZ+3atVx00UV07tyZSy+9lNzc3GL351//+hf9+vWjc+fOXHjhhWT7vVeZmZnccsstXHzxxUycOLHI9Pr16+nevTtpaWkMGjQo1LPUu3dvbr/9di666CL+93//N+p2582bx5VXXskVV1zBueeey6xZs5g5cyadOnWie/fuoZ6IaPG98sordOvWjU6dOvHjH/+YXbt2AXDXXXcxevRoevfuTZs2bUK9HeXx8ssvM2LECMyM7t27s3fv3ojt+uCDDzJ58mSqVfP+7Ud6QvHTTz/N8OHDI25n7ty5nHfeeVx00UWsWLEiNH/37t1cddVVdOnShS5duoSW7d69m759+5Kens6YMWNo1aoVX331Vbn3V0mLiMhJbteuXaHxhVq0aBH6lB1ux44dnHPOOaHphIQEduzYEbG+rVu3snTpUv7xj38wduzYAgMFgtezs2DBAv75z38yfvz4AqMLP/fcc6xdu5bRo0dzxx13FBv3DTfcwP/93/+xdu1aZsyYwY033hha9vHHH7NkyRL+9Kc/FZkeMWIE06dPZ8OGDXTo0IGpU6eG1tu7dy9Lly7l1ltv5aGHHgoNcVDYxo0beeqpp1i9ejV33HEHdevW5f3336dHjx489thjxcbXs2dPVq1axfvvv8+wYcP4wx/+EKo3Ozub119/ndWrVzN16lS+//77ItseOnRo6JJN+Ct/u+FiPW7/+te/WLBgARkZGVx22WVs2bKlwPJvv/2W1157rcCo2vlyc3OZMmUKK1as4I033mDTpk2hZb/61a+YMGEC7733Hs8//zzXXXcdAFOnTuVHP/oR69atY9CgQfz73/+O2M6lFfy+MRERKbdIQ7pEGvEX4Kc//SnVqlUjMTGRNm3ahHoY8tWtW5c5c+bQq1cv7rvvPn74wx+yceNGNm7cSN++fQHvclSkgRrzHThwgHfffZchQ4aE5uWPewMwZMiQAiNA50/v27ePvXv3ctFFFwFez1J4HeEjK48dOzbq9i+++GJOP/10Tj/9dBo2bMgVV1wBQIcOHdiwYUOx8W3fvp2hQ4eSm5vLkSNHOPfcc0NlfvKTn1CrVi1q1apFs2bN2LVrFwkJCQW2XZqBB2M9bt999x21a9dmzZo1vPDCC4wePZp33nkntPyVV17hggsuiNhTl5WVRe/evTnzzDMBrw0//vhjAJYsWVIgidm/fz/ffPMNy5cv58UXXwSgX79+NG7cOOZ9Ko6SFhGRk9xZZ51Fbm4uLVq0IDc3N+KlgYSEBLZt2xaa3r59e9QBBgv/U4z0T/LDDz/kjDPOYOfOnYD3zzU1NZWVK1fGFPPx48dp1KhR1JGQ69WrV+x0NLGWq1WrVuh9tWrVQtPVqlXj6NGjxcb3y1/+kltuuYUBAwbw9ttvc9ddd0Wst3r16hw9erTI+kOHDiUnJ6fI/FtuuaXI/UqxHreEhIRQL8qgQYMYNargCOTPPPNM1EtDED2BPX78OCtXrqROnToF5lfUuIZKWsph+urpZOdFvqN/mD//rmKGpk9ukszErhMrJDYRqVqHs7NjvoE2lrpqJ5d95OgBAwYwf/58Jk2axPz58xk4cGCRMl26dGHLli189tlnnH322TzzzDM89dRTEetbuHAhI0eO5LPPPuPTTz8lKSmJVatWhZZ//vnn/OlPf+L999+nf//+XHnllXTq1Indu3ezcuVKevTowffff8/HH39MampqxG00aNCAc889l4ULFzJkyBCcc2zYsIHzzz+/2H1t2LAhjRs35p133uHCCy/k8ccfD/W6xFNx8e3bt4+zzz4bgPnz55e67tL0tAwYMIBZs2YxbNgwsrKyaNiwYcQerCuvvJK33nqL0aNHs3TpUs4777zQsn379rF06VKeeOKJiNvo1q0bv/rVr9izZw8NGjRg4cKFoeNwySWXMGvWrNDNvOvXr6djx4707NmTZ599lokTJ7J48eKo31grLd3TUg7Zednk5BXNhmORk5cTNeERkWCrlZJcriSjsNrJydRKKbm+4cOH06NHD3JyckhISODRRx8FYNKkSbzxxhskJibyxhtvMGnSJAB27txJ//79AahRowazZs3i0ksvJSUlhZ/+9KdRE4qkpCQuuugiLrvsMh566CFq164dWuac49prr2XGjBm0bNmSRx99lOuuu47jx4/z3HPPMXHiRM4//3w6duzIu+++W+z+PPnkkzz66KOcf/75pKamRrwxOJL58+fzm9/8hrS0NNavX8/kyZMjlivunpZYRIvvrrvuYsiQIVx44YU0bdq0zPXHon///rRp04a2bdty/fXX88ADDxRYlt/TNWnSJJ5//nk6dOjAbbfdxiOPPBIq9+KLL3LJJZdE7YVq0aIFd911Fz169ODHP/4x6enpoWV/+ctfWLNmDWlpabRr1y7UnlOmTGHx4sWkp6ezaNEiWrRowemnn17u/bWK6sKJJCMjw61Zs6ZC6h76sNfluGBMj1ItK49Rfi/K3H5ziyzL/4QV7SuPxa1bXiVtW0Tib/PmzaSkpFR1GBUuMzOTyy+/nKuvvrqqQ5ET2HfffUf16tWpUaMGK1euZNy4cREvpUX6vTGztc65iN+f1+UhERERiat///vf/PSnP+X48eOcdtppzJkzJy71KmkREZGYzZs3r6pDkABITEzk/fffj3u9uqdFRCROKvNyu0jQleX3RUmLiEgc1K5dmz179ihxEYmBc449e/YUuIk7Fro8JCISBwkJCWzfvp3du3dXdSgigVC7du0iD9YriZIWEZE4qFmzZoEnn4pI/OnykIiIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEgglJi1mdo6Z/dPMNpvZR2b2K3/+XWa2w8zW+6/+FR+uiIiInKpiGTDxKHCrc26dmZ0OrDWzN/xl9znnZlRceCIiIiKeEpMW51wukOu//8bMNgNnV3RgIiIiIuFi6WkJMbPWQCcgC7gAuNnMRgBr8Hpjvo57hPG0aBJ88WF86mreAax8VeTk5TDqtVGlXi+5STITu04s38ZFREQCJuYbcc2sPvA88N/Ouf3Ag8APgY54PTF/irLeDWa2xszW7N69u/wRl8cXH8YnaYlDPclNkklqklTq9XLycsjOyy7XtkVERIIopp4WM6uJl7A86Zx7AcA5tyts+Rzg75HWdc7NBmYDZGRkuPIGXG7NO8Cof5Svjrk/KXcYZe0pKUvPjIiIyMkglm8PGfAosNk5NzNsfouwYoOAjfEPT0RERMQTS0/LBcA1wIdmtt6fdzsw3Mw6Ag7YCoypgPhEREREgNi+PbScyLecvhr/cEREREQi0xNxRUREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCDWqOgCpGIezs/n8mhFVtv1aKck0v/32Ktu+iIicfJS0nIRqpSRX6fYPZ2dX6fZFROTkpKTlJFTVPRxV2cMjIiInL93TIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBMIpk7Rsyt3PR7n7+Ch3H1Nf+aiqwxEREZFSqlHVAVSGdi0beG/2wLdHjrFp5/6qDUhERERK7ZRIWqZckeq9mduQj3L3VW0wIiIiUianzOUhERERCTYlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigVBi0mJm55jZP81ss5l9ZGa/8uc3MbM3zGyL/7NxxYcrIiIip6pYelqOArc651KA7sBNZtYOmAS86ZxLBN70p0VEREQqRIlJi3Mu1zm3zn//DbAZOBsYCMz3i80HrqygGEVERERKd0+LmbUGOgFZwFnOuVzwEhugWdyjExEREfHFnLSYWX3geeC/nXMxD95jZjeY2RozW7N79+6yxCgiIiISW9JiZjXxEpYnnXMv+LN3mVkLf3kL4MtI6zrnZjvnMpxzGWeeeWY8YhYREZFTUCzfHjLgUWCzc25m2KK/ASP99yOBl+MfnoiIiIgnllGeLwCuAT40s/X+vNuBe4Fnzexa4N/AkAqJUERERIQYkhbn3HLAoizuE99wRERERCLTE3FFREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAIhlq88n/Smr55Odl527CvYLgBy8r4mqUlSBUUVbIezs/n8mhFVsu1aKck0v/32Ktm2iIhUHCUtQHZeNjl5OaVOQJKaJJHcJLmCogquWilV1yaHs0uRfIqISKAoafElNUlibr+5sRWe+xPvZ6zlTzFV2ctRVb07IiJS8XRPi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUCoUdUBxNPIfQ/B3GnRC3zxIfCDSotHRERE4uek6mlpdfRffmISRfMOfF7jh5UXkIiIiMTNSdXTAkDzDjDqH1EXz394ZSUGIyIiIvFyUvW0iIiIyMlLSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCCUmLSY2V/N7Esz2xg27y4z22Fm6/1X/4oNU0RERE51sfS0zAP6RZh/n3Ouo/96Nb5hiYiIiBRU4sPlnHPLzKx1JcQSLF98CHN/UszynXBavcqLR0IOZ2fz+TUjqmz7tVKSaX777VW2fRGRk1V5noh7s5mNANYAtzrnvo5UyMxuAG4A+MEPTpJxf5p3KLnMkYMVH4cUUSsluUq3fzg7u0q3LyJyMitr0vIg8P8A5//8EzA6UkHn3GxgNkBGRoYr4/ZOLJfdW3KZpzpVfBxSRFX3cFRlD4+IyMmuTN8ecs7tcs4dc84dB+YAXeMbloiIiEhBZUpazKxF2OQgYGO0siIiIiLxUOLlITN7GugNNDWz7cAUoLeZdcS7PLQVGFNxIYqIiIjE9u2h4RFmP1oBsYiIiIhEpSfiioiISCAoaREREZFAUNIiIiIigaCkRURERAKhPE/EDaxNufsZ+vDK0PSX9Q/S+owKeOT+kYPFP+ofvKfrxvKwunKavno62Xllf1prcpNkJnadGMeIRERESueUS1ratWxQYHpT7n7qtjoW/w3FMu7QFx/Gf7tRZOdlk5OXQ1KTpFKvm5OXUwERiYiIlM4pl7RMuSK1wPTQh1eytSI21KSN93PUY9HLlNQLE2dJTZKY229uqdcb9dqoCohGRESkdHRPi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQalR1APE0v+EhdttheG0UAD96YSvNdhwsdp1hR45xjMNUpzaLZlxJ3dOq0/qMeuWO5XB2NrWTk8tdj4iIiHhOqp6WrTWPkcOR0HSzHQdptuPbYtepVs2oTm2qUYuD3x3l2yPH4hJL7eRkaqUoaREREYmXk6qnBSCJ05jbby4Anz85AppAp8cfi2ndoQ+vBGDBmB4VFp+IiIiUzUnV0yIiIiInLyUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJhBKTFjP7q5l9aWYbw+Y1MbM3zGyL/7NxxYYpIiIip7pYelrmAf0KzZsEvOmcSwTe9KdFREREKkyJSYtzbhmQV2j2QGC+/34+cGV8wxIREREpqKz3tJzlnMsF8H82i1bQzG4wszVmtmb37t1l3JyIiIic6ir8Rlzn3GznXIZzLuPMM8+s6M2JiIjISaqsScsuM2sB4P/8Mn4hiYiIiBRV1qTlb8BI//1I4OX4hCMiIiISWSxfeX4aWAkkmdl2M7sWuBfoa2ZbgL7+tIiIiEiFqVFSAefc8CiL+sQ5FhEREZGo9ERcERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAKhRlUHIKWXk5fDqNdGlXqdpCZJFRSRnOq+uOcevtucXaUx1EpJpvntt1dpDCJSsZS0BExyk+QyrZfUJKnM64qU5LvN2RzOzqZ2ctWcY4ezqzZhEpHKoaQlYCZ2nVjVIYhEVDs5mVaPP1Yl2/78mhFVsl0RqVy6p0VEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQU/ErWpffAhzf1K+Opp3gMvujU88IiIiJyglLVWpeYfy1/HFh+WvQ0REJACUtFSlePSOlLeXRkREJCB0T4uIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBD5eTCjN99XSy87LLtG5yk2Qmdp0Y54gqx+HsbD6/ZkRVh1GpDmdnUzs5ucpjqKp2r5WSTPPbb6+SbYucSpS0SIXJzssmJy+HpCZJpVovJy+ngiKqeLVSqvYfd1WpnZxcpftelds+nF22xFxESk9Ji1SopCZJzO03t1TrjHptVAVFU/H0abtqVGW7n2q9aiJVSfe0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCYRyfeXZzLYC3wDHgKPOuYx4BCUiIiJSWDye03Kxc+6rONQjIiIiEpUeLlfIptz9DH14ZWi6XcsGTLkitUi5qa98xKad+0ssVym++BDm/qT89TTvAJfdG3FRTl5OqR/6Vpan4YqIiERT3qTFAYvNzAEPO+dmFy5gZjcANwD84Ac/KOfmKla7lg0KTG/K3R+lJGzauZ9Nuftp16JBseUqXPMO8anniw+jLkpuUrZHpCc1SSrzuiIiIoWVN2m5wDm308yaAW+YWbZzbll4AT+RmQ2QkZHhyrm9ClW4pyS8xyWSdi0asGBMjxLLVagoPSOlVkxPTVAHLhQRkZNLub495Jzb6f/8EngR6BqPoEREREQKK3PSYmb1zOz0/PfAJcDGeAUmIiIiEq48l4fOAl40s/x6nnLOvRaXqEREREQKKXPS4pz7FDg/jrGIiIiIRKUn4oqIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQY/xlxNP3qdw5GDJQxMUM+xAZZm+ejrZedllWje5SXKlPrgvSLGKiESipEVOPEcOeq+axZQpZtiBypSdl12mMZZy8nIqKKLoghSriEgkSlrkxHRaPcj8R/Tl8RggMk6SmiQxt9/cUq1T2sEn4yVIsYqIFKZ7WkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEgh6uFwJNuXuZ+jDKwFo17IBU65ILXGdqa98xKad+0PTsa53Ulg0Kban1ZbwCP4cjhT/UDPb5f0sVEaPmxcROXkpaSlGu5YNQu835e4vpmRBm3buZ1Puftq1aFCq9U4KX3zovZp3KL5MMZI5rUyb1uPmRURObkpaihHeO5Lf2xKrdi0asGBMj1Kvd1Jo3gFGlf0R/BNdY+9NcY+bz68jrIweNy8icnLTPS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEPVwuTsIf95//NNxIy+AEfqz/Fx+W+OC3kh6/X6kKx5v/aP/weTHGO331dLLzsksdQk5eDklNkkq9Xv66ZXkgnoYqOPEczs7m82tGVHUYVaJWSjLNb7+9qsOQU4SSljgIf9w/eE/DzZ9XeNkJ+1j/4h67ny+WMYUqS5zjzc7LLlMCktQkieQmyaVaByjTOqChCk5EtVLKdixPBoezS5/oi5SHkpY4KK7XpPCyE/ax/rH0npTUC1OZIsWb32uR/2j/Usab1CSJucUNHRBHZe0p0VAFJ55TuZfhVO1dkqqje1pEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEPRE3FIobnyhstZTnBNyjKKSxif64sPYH7EfrZ5Y6zhFlXXMovKMkyQSzak87tKprKrGnFLSEqPixhcqTz3RnJBjFMWSSDTvUHK5WJYraYmorGMWQdnHSRKJ5lQed+lUVpVjTilpiVG8ejxireeEHKMoXqM7nyijRAeQRneWE8mpPO7Sqawqe9Z0T4uIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAKFfSYmb9zCzHzD4xs0nxCkpERESksDInLWZWHbgfuAxoBww3s3bxCkxEREQkXHkeLtcV+MQ59ymAmT0DDAQ2xSMwkbIo8Ih72+X9jOGR93rEvYjIic+cc2Vb0exqoJ9z7jp/+hqgm3Pu5kLlbgBu8CeTgJyyhxtVU+CrCqhXYqP2r1pq/6ql9q9aav+qU1Ft38o5d2akBeXpabEI84pkQM652cDscmyn5EDM1jjnMipyGxKd2r9qqf2rltq/aqn9q05VtH15bsTdDpwTNp0A7CxfOCIiIiKRlSdpeQ9INLNzzew0YBjwt/iEJSIiIlJQmS8POeeOmtnNwOtAdeCvzrmP4hZZ6VTo5Scpkdq/aqn9q5bav2qp/atOpbd9mW/EFREREalMeiKuiIiIBIKSFhEREQmEQCUtJQ0bYJ6/+Ms3mFl6VcR5soqh/Xub2T4zW++/JldFnCcjM/urmX1pZhujLNe5X4FiaH+d+xXEzM4xs3+a2WYz+8jMfhWhjM7/ChJj+1fa+V+e57RUqrBhA/rifd36PTP7m3Mu/Am8lwGJ/qsb8KD/U8opxvYHeMc5d3mlB3jymwfMAh6LslznfsWaR/HtDzr3K8pR4Fbn3DozOx1Ya2Zv6G9/pYml/aGSzv8g9bSEhg1wzh0B8ocNCDcQeMx5VgGNzKxFZQd6koql/aWCOOeWAXnFFNG5X4FiaH+pIM65XOfcOv/9N8Bm4OxCxXT+V5AY27/SBClpORvYFja9naINF0sZKZtY27aHmX1gZovMLLVyQhN07p8IdO5XMDNrDXQCsgot0vlfCYppf6ik8z8wl4eIbdiAmIYWkDKJpW3X4Y0ZccDM+gMv4XXXSsXTuV+1dO5XMDOrDzwP/Ldzbn/hxRFW0fkfRyW0f6Wd/0HqaYll2AANLVBxSmxb59x+59wB//2rQE0za1p5IZ7SdO5XIZ37FcvMauL9w3zSOfdChCI6/ytQSe1fmed/kJKWWIYN+Bswwr+TvDuwzzmXW9mBnqRKbH8za25m5r/vind+7an0SE9NOverkM79iuO366PAZufczCjFdP5XkFjavzLP/8BcHoo2bICZjfWXPwS8CvQHPgG+BUZVVbwnmxjb/2pgnJkdBQ4Bw5weuRwXZvY00BtoambbgSlATdC5XxliaH+d+xXnAuAa4EMzW+/Pux34Aej8rwSxtH+lnf96jL+IiIgEQpAuD4mIiMgpTEmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtEjgmNkgM3NmllzOejLNbFZFlffXub30kcWXmbU2s59VdRzRmNldZvbrqo4jVmZ2t5n9uIzrdvSfGFqqcmY2wCKMrF6G7bc2s0NhX10tvLzMx8LMfuiP8HugXEGKFENJiwTRcGA53gPuTnRVnrQArYGISYuZBeJZTSdKnGZW3Tk32Tm3pIxVdMR7nkipyjnn/uacu7eM2yzsX865jnGqK8Q5VyH1ioRT0iKB4o9/cQFwLWFJi5n1NrO3zew5M8s2syfDntDY35+33Mz+YmZ/j1DvmWb2vJm9578uiBLCOWb2mpnlmNmUsPV/YWar/U+aD5tZdTO7F6jjz3vSzP7HzMb75e8zs7f8933M7An//SVmttLM1pnZQn9/MbPOZrbUzNaa2evmj2Dr7/N0f9sfm9mFEWK+F7jQj2OC32O00MxeARb7bRdqEzObZWaZxW23UNtdYWZZZva+mS0xs7P8+XeZ2V/9GD/N33d/2R1+Gy4BkiI1tJnNM7OZZvZPYLr/Sf41P5Z38nvazOwsM3vRvMHaPjCz//Ln32JmG/3Xf0c5nuHb6+Pvw4d+3LX8+VvNbLKZLQeG+HFdXdrjYt6TpO8GhvrHYqiZdTWzd/3tvmtmSVHKhXr5zKyVmb1pZhv8nz8Ia6+/+PV8mh9jDPsd8VgU094/NLNV5v2e3G3qWZHK5JzTS6/AvIBfAI/6798F0v33vYF9eGOOVANWAj2B2nijv57rl3sa+Lv/PhOY5b9/Cujpv/8B3iOrC287E8gFzgDqABuBDCAFeAWo6Zd7ABjhvz8Qtn53YKH//h1gNd5TVacAY4CmwDKgnl9mIjDZL/MucKY/fyjeE4kB3gb+5L/vDyyJEHfv/H0O24/tQJMoy2f5ZaJut1D9jfnPgyqvC4vnLn/9Wv6+7fHr7Ax8CNQFGuA9xfTXEeqdB/wdqO5Pvwkk+u+7AW/57xfgDeIG3tOaG4Ztox5QH/gI6FTMeZV/npznTz8WVudW4H8KxXV1WY4LYeecP90AqOG//zHwfJRyoWm8c22k/3408FJYXAvxzv92wCcR9rM1sDFsOuqxKKa9/w4M99+PJewcL3zO66VXvF8nRJerSCkMB/7sv3/Gn17nT692zm0HMO+afWvgAPCpc+4zv8zTwA0R6v0x0M4sNFhsAzM73Tn3TaFybzjn9vjbeAEvMTqK98f/PX/9OsCXEbaxFuhsZqcD3/lxZwAXAuPxkpp2wAq/ntPwkq8koD3whj+/Ol7ylO+FsPpbR9huJG845/JKKFPSdvMlAAv8XobTgM/Clv3DOfcd8J2ZfQmchbe/LzrnvgUws8JjiIVb6Jw7Zl6P038BC8OOUS3/54+AEQDOuWPAPjPr6W/joL+NF/ztvl/Mvn7mnPvYn54P3MR/zrUFUdYp73FpCMw3s0S8UYlrRikXrgcw2H//OPCHsGUvOeeOA5vye7xKEPFYlNDePYAr/fdPATNi2I5IXChpkcAwszPw/kG1NzOH90/Cmdn/+EW+Cyt+DO/8jjRkfSTVgB7OuUMllCs87oXztzHfOXdbsSs6972ZbcUbF+VdYANwMfBDYLP/8w3n3PDw9cysA/CRc65HlKrz9zt/n2NxMOz9UQpeKq6dv+kStpvv/4CZzrm/mVlvvB6WwrEVji/W8UPy46wG7HWx3zMR63GPtfzBCPNKap9Yjsv/A/7pnBtkZq3xemhKK7wtw9s71jaIdCxK294ilUL3tEiQXA085pxr5Zxr7Zw7B+9Tfc9i1skG2vj/EMDrwo9kMXBz/oSZdYxSrq+ZNTGzOnifNlfgdaNfbWbN/HWbmFkrv/z35g3rnm8Z8Gv/5zt43evrnXMOWAVcYGZt/Xrqmtl5QA5wppn18OfXNLPUYva5sG+A04tZ/jleL1MtM2sI9PHnx7rdhsAO//3IGOJZBgwyszp+r9MVJa3gnNsPfGZmQ/xYzMzO9xe/CYzz51c3swb+Nq7027AeMAivvaPJBlrntz3eAHFLSwirLMel8LEIb7vMYsqFe5f/3M/1c7yb0ssq4rEoob1XAVf574NwM7ycRJS0SJAMB14sNO95onwzBsDvObkReM2/kXIX3r0vhY0HMvybGzfhJRORLMfrkl+Pd//BGufcJuBOvJtaNwBvAPk3rM4GNpjZk/70O/6ylc65XcBhfx7Oud14/7ie9utZBSQ7547gJWzTzewDf9v/FW2fI9gAHDXvJtUJhRc657YBz/rlnsS/hFKK7d6FdxnhHeCrkoJxzq3Du9yyHu/4FZdMhPs5cK0fy0fAQH/+r4CLzexDvEsxqf425uHdN5QFPOKcex9Clw4Lx3QYrwdsoV/PceChEvajLMfln3gJ4nozG4p3aef3ZrYCr+cwWrlw44FR/jlyjb//ZVLCsYjW3v8N3GJmq/HO5Ui/TyIVQqM8y0nPzOo75w6Yd3H+fmCLc+6+qo5LpLL5PY5/d861L0cddYFDzjlnZsPwbsodGLb8gHOufvmjFSlKPS1yKrje/3T9EV53/MNVG45IlTkGNIzU21QKnYH1fk/PjcCt8J+Hy+H1ZopUCPW0iIiISCCop0VEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBD+P+QBTXX/8qLEAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_4_a7r = {}\n", + "centre_errors_4_a7r = {}\n", + "orientation_errors_4_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_4_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_4_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_4_a7r[pixel_error] = run_led_fit(fitter, led_positions_4_a7r)\n", + " centre_errors_4_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_4_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_4_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_4_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_4_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_4_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_4_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_4_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [-camera_radial_position, -camera_halfz_position, 0],\n", + " [0.5*camera_radial_position, -camera_halfz_position, -camera_radial_position*np.sqrt(3)/2],\n", + " [0.5*camera_radial_position, -camera_halfz_position, camera_radial_position*np.sqrt(3)/2],\n", + " [camera_radial_position, camera_halfz_position, 0],\n", + " [-0.5*camera_radial_position, camera_halfz_position, -camera_radial_position*np.sqrt(3)/2],\n", + " [-0.5*camera_radial_position, camera_halfz_position, camera_radial_position*np.sqrt(3)/2]])\n", + "camera_directions = [[1, 1.1, 0],\n", + " [-0.5, 1.1, np.sqrt(3)/2],\n", + " [-0.5, 1.1, -np.sqrt(3)/2],\n", + " [-1, -1.1, 0],\n", + " [0.5, -1.1, np.sqrt(3)/2],\n", + " [0.5, -1.1, -np.sqrt(3)/2]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.821718286013542 max: 448.8736259901742\n", + "image 1 reprojection errors: average: 22.507822032865693 max: 281.5605900558616\n", + "image 2 reprojection errors: average: 22.50313075982111 max: 225.6310710251895\n", + "image 3 reprojection errors: average: 22.64851799167888 max: 273.8561613485784\n", + "image 4 reprojection errors: average: 22.418917817688715 max: 282.37009397011036\n", + "image 5 reprojection errors: average: 22.21851888722326 max: 244.10096633609555\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.1149e+06 1.27e+07 \n", + " 1 2 7.4368e+03 3.11e+06 6.91e+01 2.02e+05 \n", + " 2 3 2.8400e+03 4.60e+03 3.02e+00 4.37e+03 \n", + " 3 4 2.8005e+03 3.95e+01 1.12e+00 2.73e+03 \n", + " 4 5 2.7908e+03 9.68e+00 2.00e-01 4.19e+02 \n", + " 5 6 2.7893e+03 1.54e+00 6.48e-02 1.95e+02 \n", + " 6 7 2.7888e+03 5.11e-01 1.89e-02 6.17e+01 \n", + " 7 8 2.7885e+03 2.32e-01 1.23e-02 3.82e+01 \n", + " 8 9 2.7884e+03 1.73e-01 8.05e-03 2.79e+01 \n", + " 9 10 2.7882e+03 1.51e-01 8.87e-03 4.04e+01 \n", + " 10 11 2.7881e+03 1.40e-01 6.92e-03 2.52e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 3.1149e+06, final cost 2.7881e+03, first-order optimality 2.52e+01.\n", + "mean reprojection error: 0.7868649617435626\n", + "max reprojection error: 3.129771899326001\n", + "mean reconstruction error: 0.05711351307439404\n", + "max reconstruction error: 0.3396403915949969\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.862734373565793 max: 186.16706774726129\n", + "image 1 reprojection errors: average: 22.054740438011294 max: 189.43979052623146\n", + "image 2 reprojection errors: average: 22.276412178476143 max: 197.06857257346005\n", + "image 3 reprojection errors: average: 22.52924304280216 max: 246.73167389704759\n", + "image 4 reprojection errors: average: 22.076165806960965 max: 260.7772267231314\n", + "image 5 reprojection errors: average: 21.89693685872337 max: 191.36005640244286\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.8280e+06 1.06e+07 \n", + " 1 2 2.6974e+04 2.80e+06 6.85e+01 1.50e+05 \n", + " 2 3 2.5350e+04 1.62e+03 1.11e+00 1.40e+03 \n", + " 3 4 2.5231e+04 1.19e+02 1.47e+00 7.51e+02 \n", + " 4 5 2.5184e+04 4.66e+01 2.78e-01 2.06e+02 \n", + " 5 6 2.5177e+04 7.04e+00 1.14e-01 1.93e+02 \n", + " 6 7 2.5172e+04 5.12e+00 6.15e-02 2.42e+02 \n", + " 7 8 2.5170e+04 2.14e+00 3.36e-02 1.23e+02 \n", + " 8 9 2.5168e+04 1.77e+00 2.79e-02 2.30e+02 \n", + " 9 10 2.5167e+04 1.68e+00 2.87e-02 1.29e+02 \n", + " 10 11 2.5165e+04 1.61e+00 2.60e-02 2.38e+02 \n", + " 11 12 2.5163e+04 1.54e+00 2.68e-02 1.31e+02 \n", + " 12 13 2.5162e+04 1.46e+00 2.39e-02 2.41e+02 \n", + " 13 14 2.5161e+04 1.35e+00 2.37e-02 1.29e+02 \n", + " 14 15 2.5159e+04 1.25e+00 2.06e-02 2.38e+02 \n", + " 15 16 2.5158e+04 1.16e+00 2.06e-02 1.24e+02 \n", + " 16 17 2.5157e+04 1.09e+00 1.82e-02 2.31e+02 \n", + " 17 18 2.5156e+04 1.01e+00 1.83e-02 1.19e+02 \n", + " 18 19 2.5155e+04 1.02e+00 1.78e-02 2.39e+02 \n", + " 19 20 2.5154e+04 8.98e-01 1.57e-02 1.18e+02 \n", + " 20 21 2.5153e+04 1.01e+00 1.88e-02 3.02e+02 \n", + " 21 22 2.5152e+04 7.91e-01 1.19e-02 1.07e+02 \n", + " 22 23 2.5152e+04 3.90e-01 6.49e-03 1.81e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 23, initial cost 2.8280e+06, final cost 2.5152e+04, first-order optimality 1.81e+02.\n", + "mean reprojection error: 2.378321481670786\n", + "max reprojection error: 8.340049722185547\n", + "mean reconstruction error: 0.17568703377497497\n", + "max reconstruction error: 1.1540460514721482\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.79238975954296 max: 289.7260298321374\n", + "image 1 reprojection errors: average: 21.96597762744127 max: 248.8319462627144\n", + "image 2 reprojection errors: average: 22.131168968436516 max: 190.10154718052814\n", + "image 3 reprojection errors: average: 22.04396962605084 max: 454.3865274451203\n", + "image 4 reprojection errors: average: 21.819963266705855 max: 191.14970620162597\n", + "image 5 reprojection errors: average: 22.532078742252363 max: 206.8246314333731\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.8597e+06 7.23e+06 \n", + " 1 2 7.2424e+04 2.79e+06 6.83e+01 3.50e+05 \n", + " 2 3 6.9468e+04 2.96e+03 1.58e+00 8.35e+03 \n", + " 3 4 6.9240e+04 2.28e+02 1.70e+00 6.36e+03 \n", + " 4 5 6.9137e+04 1.03e+02 3.82e-01 6.00e+02 \n", + " 5 6 6.9120e+04 1.67e+01 1.55e-01 5.85e+02 \n", + " 6 7 6.9108e+04 1.18e+01 8.36e-02 2.38e+02 \n", + " 7 8 6.9103e+04 4.89e+00 4.10e-02 2.55e+02 \n", + " 8 9 6.9099e+04 4.02e+00 3.42e-02 2.09e+02 \n", + " 9 10 6.9095e+04 3.94e+00 3.68e-02 2.27e+02 \n", + " 10 11 6.9092e+04 3.86e+00 3.35e-02 1.97e+02 \n", + " 11 12 6.9088e+04 3.78e+00 3.60e-02 2.06e+02 \n", + " 12 13 6.9084e+04 3.73e+00 3.30e-02 1.84e+02 \n", + " 13 14 6.9080e+04 3.67e+00 3.56e-02 2.00e+02 \n", + " 14 15 6.9077e+04 3.48e+00 3.10e-02 1.61e+02 \n", + " 15 16 6.9074e+04 3.43e+00 3.45e-02 1.87e+02 \n", + " 16 17 6.9070e+04 3.38e+00 3.03e-02 1.85e+02 \n", + " 17 18 6.9067e+04 3.34e+00 3.40e-02 1.97e+02 \n", + " 18 19 6.9064e+04 3.28e+00 2.97e-02 2.03e+02 \n", + " 19 20 6.9060e+04 3.25e+00 3.36e-02 2.08e+02 \n", + " 20 21 6.9057e+04 3.19e+00 2.92e-02 2.12e+02 \n", + " 21 22 6.9054e+04 3.16e+00 3.33e-02 2.14e+02 \n", + " 22 23 6.9051e+04 3.10e+00 2.86e-02 2.14e+02 \n", + " 23 24 6.9048e+04 3.06e+00 3.30e-02 2.15e+02 \n", + " 24 25 6.9045e+04 3.00e+00 2.81e-02 2.14e+02 \n", + " 25 26 6.9042e+04 2.96e+00 3.26e-02 2.18e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 26 27 6.9039e+04 2.91e+00 2.77e-02 2.13e+02 \n", + " 27 28 6.9036e+04 2.88e+00 3.22e-02 2.18e+02 \n", + " 28 29 6.9033e+04 2.81e+00 2.71e-02 2.06e+02 \n", + " 29 30 6.9030e+04 2.78e+00 3.19e-02 2.14e+02 \n", + " 30 31 6.9028e+04 2.67e+00 2.58e-02 2.08e+02 \n", + " 31 32 6.9025e+04 2.72e+00 3.22e-02 2.30e+02 \n", + " 32 33 6.9022e+04 2.66e+00 2.56e-02 2.01e+02 \n", + " 33 34 6.9021e+04 1.22e+00 1.26e-02 1.17e+02 \n", + " 34 35 6.9020e+04 9.46e-01 1.12e-02 1.60e+02 \n", + " 35 36 6.9019e+04 9.40e-01 1.09e-02 1.15e+02 \n", + " 36 37 6.9018e+04 9.34e-01 1.11e-02 1.59e+02 \n", + " 37 38 6.9017e+04 8.87e-01 1.03e-02 1.10e+02 \n", + " 38 39 6.9017e+04 8.40e-01 1.02e-02 1.53e+02 \n", + " 39 40 6.9016e+04 8.39e-01 1.00e-02 1.16e+02 \n", + " 40 41 6.9015e+04 8.38e-01 1.02e-02 1.54e+02 \n", + " 41 42 6.9014e+04 8.31e-01 9.95e-03 1.15e+02 \n", + " 42 43 6.9013e+04 8.26e-01 1.01e-02 1.52e+02 \n", + " 43 44 6.9012e+04 8.22e-01 9.90e-03 1.14e+02 \n", + " 44 45 6.9012e+04 8.17e-01 1.01e-02 1.50e+02 \n", + " 45 46 6.9011e+04 8.12e-01 9.86e-03 1.12e+02 \n", + " 46 47 6.9010e+04 8.08e-01 1.00e-02 1.48e+02 \n", + " 47 48 6.9009e+04 8.03e-01 9.81e-03 1.11e+02 \n", + " 48 49 6.9008e+04 7.98e-01 9.94e-03 1.47e+02 \n", + " 49 50 6.9008e+04 7.91e-01 9.71e-03 1.12e+02 \n", + " 50 51 6.9007e+04 7.75e-01 9.62e-03 1.55e+02 \n", + " 51 52 6.9006e+04 7.85e-01 9.68e-03 1.21e+02 \n", + " 52 53 6.9005e+04 7.62e-01 9.28e-03 1.58e+02 \n", + " 53 54 6.9005e+04 7.77e-01 9.66e-03 1.35e+02 \n", + " 54 55 6.9004e+04 7.72e-01 9.26e-03 1.55e+02 \n", + " 55 56 6.9003e+04 7.67e-01 9.59e-03 1.34e+02 \n", + " 56 57 6.9002e+04 7.59e-01 9.13e-03 1.55e+02 \n", + " 57 58 6.9001e+04 7.43e-01 9.27e-03 1.40e+02 \n", + " 58 59 6.9001e+04 7.53e-01 9.09e-03 1.65e+02 \n", + " 59 60 6.9000e+04 7.38e-01 9.08e-03 1.40e+02 \n", + " 60 61 6.8999e+04 6.86e-01 8.08e-03 1.77e+02 \n", + " 61 62 6.8999e+04 7.43e-01 9.24e-03 1.75e+02 \n", + " 62 63 6.8998e+04 6.60e-01 6.96e-03 1.72e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 63, initial cost 2.8597e+06, final cost 6.8998e+04, first-order optimality 1.72e+02.\n", + "mean reprojection error: 3.93161102514504\n", + "max reprojection error: 13.95317275359787\n", + "mean reconstruction error: 0.2898542552146252\n", + "max reconstruction error: 1.8021597218804615\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 24.42884832001907 max: 204.19052467142072\n", + "image 1 reprojection errors: average: 24.861555626407068 max: 329.51098954993284\n", + "image 2 reprojection errors: average: 25.420273339451597 max: 374.91162553451653\n", + "image 3 reprojection errors: average: 24.325791255441985 max: 231.62720190071104\n", + "image 4 reprojection errors: average: 25.675480611429162 max: 454.6677484980528\n", + "image 5 reprojection errors: average: 25.71749791605633 max: 246.76199955676117\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.5852e+06 1.07e+07 \n", + " 1 2 2.8563e+05 3.30e+06 7.27e+01 5.38e+05 \n", + " 2 3 2.7767e+05 7.96e+03 2.08e+00 1.90e+04 \n", + " 3 4 2.7657e+05 1.10e+03 4.34e+00 1.13e+04 \n", + " 4 5 2.7634e+05 2.29e+02 4.96e-01 1.44e+03 \n", + " 5 6 2.7632e+05 2.34e+01 1.02e-01 3.33e+02 \n", + " 6 7 2.7630e+05 1.77e+01 1.05e-01 3.81e+02 \n", + " 7 8 2.7628e+05 1.48e+01 7.99e-02 2.71e+02 \n", + " 8 9 2.7627e+05 8.67e+00 5.20e-02 3.99e+02 \n", + " 9 10 2.7627e+05 4.25e+00 1.98e-02 2.03e+02 \n", + " 10 11 2.7627e+05 3.09e+00 2.19e-02 3.35e+02 \n", + " 11 12 2.7626e+05 2.90e+00 1.60e-02 2.88e+02 \n", + " 12 13 2.7626e+05 3.03e+00 2.16e-02 4.43e+02 \n", + " 13 14 2.7626e+05 2.76e+00 1.38e-02 2.68e+02 \n", + " 14 15 2.7626e+05 6.27e-01 2.92e-03 1.34e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 15, initial cost 3.5852e+06, final cost 2.7626e+05, first-order optimality 1.34e+02.\n", + "mean reprojection error: 7.855400463165263\n", + "max reprojection error: 31.882406803939908\n", + "mean reconstruction error: 0.5661356555731609\n", + "max reconstruction error: 2.5364666494769206\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_6a_a7r = {}\n", + "centre_errors_6a_a7r = {}\n", + "orientation_errors_6a_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_6a_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_6a_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_6a_a7r[pixel_error] = run_led_fit(fitter, led_positions_6a_a7r)\n", + " centre_errors_6a_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_6a_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_6a_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_6a_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_6a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_6a_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_6a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_6a_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration B" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [camera_radial_position, 0, 0],\n", + " [-camera_radial_position, 0, 0],\n", + " [0, 0, camera_radial_position],\n", + " [0, 0, -camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [-1, 0, 0],\n", + " [1, 0, 0],\n", + " [0, 0, -1],\n", + " [0, 0, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, 0.0, np.pi/2, 0.0, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.565729053514865 max: 152.1488367594276\n", + "image 1 reprojection errors: average: 23.11204394099042 max: 114.59310733158614\n", + "image 2 reprojection errors: average: 21.80960044715278 max: 86.10990621973482\n", + "image 3 reprojection errors: average: 21.587067334506248 max: 89.88571900946815\n", + "image 4 reprojection errors: average: 21.468444368757538 max: 144.31598575884195\n", + "image 5 reprojection errors: average: 21.321646408707455 max: 109.0396202223829\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6601e+06 5.14e+06 \n", + " 1 2 2.0076e+03 1.66e+06 6.76e+01 7.20e+04 \n", + " 2 3 1.6639e+03 3.44e+02 1.08e+00 3.02e+02 \n", + " 3 4 1.6610e+03 2.89e+00 1.54e-01 1.51e+02 \n", + " 4 5 1.6602e+03 7.36e-01 3.06e-02 4.02e+01 \n", + " 5 6 1.6600e+03 2.37e-01 1.83e-02 2.19e+01 \n", + " 6 7 1.6598e+03 1.77e-01 1.39e-02 3.34e+01 \n", + " 7 8 1.6597e+03 1.23e-01 1.07e-02 2.72e+01 \n", + " 8 9 1.6596e+03 8.28e-02 6.46e-03 6.49e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.6601e+06, final cost 1.6596e+03, first-order optimality 6.49e+01.\n", + "mean reprojection error: 0.7144993273496786\n", + "max reprojection error: 2.597876815391286\n", + "mean reconstruction error: 0.0670771326397725\n", + "max reconstruction error: 0.24996472551891238\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.980721934744473 max: 90.25168446666399\n", + "image 1 reprojection errors: average: 22.58173294546419 max: 191.01272984020522\n", + "image 2 reprojection errors: average: 23.86013903834583 max: 141.53116229341418\n", + "image 3 reprojection errors: average: 22.241348192322835 max: 82.63293282640078\n", + "image 4 reprojection errors: average: 23.33013144897648 max: 108.24464988149926\n", + "image 5 reprojection errors: average: 22.125563855499134 max: 114.12431468480719\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8382e+06 3.19e+06 \n", + " 1 2 1.5711e+04 1.82e+06 6.97e+01 1.76e+05 \n", + " 2 3 1.5258e+04 4.53e+02 8.11e-01 2.11e+03 \n", + " 3 4 1.5237e+04 2.12e+01 4.18e-01 1.44e+03 \n", + " 4 5 1.5229e+04 7.27e+00 9.65e-02 3.12e+02 \n", + " 5 6 1.5228e+04 1.58e+00 4.18e-02 9.44e+01 \n", + " 6 7 1.5227e+04 1.04e+00 3.22e-02 9.90e+01 \n", + " 7 8 1.5226e+04 5.39e-01 1.31e-02 1.02e+02 \n", + " 8 9 1.5226e+04 1.59e-01 2.67e-03 2.82e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.8382e+06, final cost 1.5226e+04, first-order optimality 2.82e+01.\n", + "mean reprojection error: 2.163784970412014\n", + "max reprojection error: 8.958974288238476\n", + "mean reconstruction error: 0.19746123616511485\n", + "max reconstruction error: 0.7696435131254048\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.827677526002947 max: 140.92204446340207\n", + "image 1 reprojection errors: average: 23.536173009552297 max: 122.11260418406036\n", + "image 2 reprojection errors: average: 22.05154849818754 max: 105.0879488237886\n", + "image 3 reprojection errors: average: 21.89029096306905 max: 85.97086745987528\n", + "image 4 reprojection errors: average: 25.032289238649703 max: 101.85081057017354\n", + "image 5 reprojection errors: average: 21.887227705940255 max: 95.17368480404258\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7863e+06 4.01e+06 \n", + " 1 2 4.2077e+04 1.74e+06 6.97e+01 2.10e+05 \n", + " 2 3 4.1736e+04 3.41e+02 8.82e-01 4.95e+03 \n", + " 3 4 4.1696e+04 4.00e+01 4.18e-01 1.55e+03 \n", + " 4 5 4.1674e+04 2.14e+01 2.03e-01 5.14e+02 \n", + " 5 6 4.1668e+04 6.77e+00 9.97e-02 2.07e+02 \n", + " 6 7 4.1663e+04 4.74e+00 7.01e-02 1.46e+02 \n", + " 7 8 4.1659e+04 3.47e+00 5.88e-02 1.76e+02 \n", + " 8 9 4.1658e+04 1.97e+00 2.63e-02 2.37e+02 \n", + " 9 10 4.1657e+04 6.74e-01 6.05e-03 4.84e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 1.7863e+06, final cost 4.1657e+04, first-order optimality 4.84e+01.\n", + "mean reprojection error: 3.558183858331999\n", + "max reprojection error: 13.775201561511091\n", + "mean reconstruction error: 0.34032198962378424\n", + "max reconstruction error: 1.621345181174321\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 28.84832363773859 max: 148.57887396141717\n", + "image 1 reprojection errors: average: 24.747460502345294 max: 99.2363672847776\n", + "image 2 reprojection errors: average: 24.843015301494958 max: 133.8216993263272\n", + "image 3 reprojection errors: average: 23.9458815313349 max: 108.5640200123744\n", + "image 4 reprojection errors: average: 24.0287504136491 max: 111.20992265257573\n", + "image 5 reprojection errors: average: 23.872870537917695 max: 96.65070949034367\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.1247e+06 4.42e+06 \n", + " 1 2 1.6664e+05 1.96e+06 7.49e+01 1.68e+05 \n", + " 2 3 1.6600e+05 6.45e+02 1.45e+00 5.19e+03 \n", + " 3 4 1.6590e+05 1.02e+02 5.13e-01 1.90e+03 \n", + " 4 5 1.6586e+05 4.05e+01 2.35e-01 4.53e+02 \n", + " 5 6 1.6583e+05 2.41e+01 1.82e-01 3.56e+02 \n", + " 6 7 1.6581e+05 1.83e+01 1.32e-01 2.02e+02 \n", + " 7 8 1.6580e+05 1.37e+01 1.15e-01 3.13e+02 \n", + " 8 9 1.6579e+05 1.06e+01 8.32e-02 3.21e+02 \n", + " 9 10 1.6578e+05 6.28e+00 4.49e-02 3.60e+02 \n", + " 10 11 1.6578e+05 2.41e+00 1.19e-02 1.05e+02 \n", + " 11 12 1.6578e+05 1.32e+00 1.39e-02 2.57e+02 \n", + " 12 13 1.6578e+05 1.78e+00 1.25e-02 1.83e+02 \n", + " 13 14 1.6578e+05 9.60e-01 7.48e-03 1.74e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 14, initial cost 2.1247e+06, final cost 1.6578e+05, first-order optimality 1.74e+02.\n", + "mean reprojection error: 7.126804036202681\n", + "max reprojection error: 28.18925758067823\n", + "mean reconstruction error: 0.6531858960413859\n", + "max reconstruction error: 2.9247299713583197\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_6b_a7r = {}\n", + "centre_errors_6b_a7r = {}\n", + "orientation_errors_6b_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_6b_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_6b_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_6b_a7r[pixel_error] = run_led_fit(fitter, led_positions_6b_a7r)\n", + " centre_errors_6b_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_6b_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_6b_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_6b_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_6b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_6b_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_6b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_6b_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [-camera_radial_position, -camera_halfz_position, 0],\n", + " [camera_radial_position, -camera_halfz_position, 0],\n", + " [0, -camera_halfz_position, -camera_radial_position],\n", + " [0, -camera_halfz_position, camera_radial_position],\n", + " [-camera_radial_position, camera_halfz_position, 0],\n", + " [camera_radial_position, camera_halfz_position, 0],\n", + " [0, camera_halfz_position, -camera_radial_position],\n", + " [0, camera_halfz_position, camera_radial_position]])\n", + "camera_directions = [[1, 1.1, 0],\n", + " [-1, 1.1, 0],\n", + " [0, 1.1, 1],\n", + " [0, 1.1, -1],\n", + " [1, -1.1, 0],\n", + " [-1, -1.1, 0],\n", + " [0, -1.1, 1],\n", + " [0, -1.1, -1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 23.16023849813648 max: 237.1378339335638\n", + "image 1 reprojection errors: average: 22.258383622107594 max: 205.02063303998966\n", + "image 2 reprojection errors: average: 21.683871414266537 max: 200.40748838371658\n", + "image 3 reprojection errors: average: 22.25487641545825 max: 258.55315396221374\n", + "image 4 reprojection errors: average: 22.803637616002245 max: 295.38866241477945\n", + "image 5 reprojection errors: average: 22.44502611617866 max: 332.596701244076\n", + "image 6 reprojection errors: average: 21.576365755998225 max: 200.80861434675163\n", + "image 7 reprojection errors: average: 21.701061206764738 max: 227.40493639576755\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8679e+06 1.05e+07 \n", + " 1 2 8.2753e+03 3.86e+06 6.87e+01 4.20e+05 \n", + " 2 3 4.1365e+03 4.14e+03 7.63e-01 8.30e+03 \n", + " 3 4 4.1302e+03 6.32e+00 1.54e-01 1.49e+03 \n", + " 4 5 4.1288e+03 1.44e+00 2.35e-02 1.71e+02 \n", + " 5 6 4.1285e+03 2.81e-01 9.32e-03 6.01e+01 \n", + " 6 7 4.1283e+03 2.18e-01 7.81e-03 5.28e+01 \n", + " 7 8 4.1281e+03 1.43e-01 5.14e-03 3.32e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 3.8679e+06, final cost 4.1281e+03, first-order optimality 3.32e+01.\n", + "mean reprojection error: 0.8451041107593343\n", + "max reprojection error: 3.3229975321646963\n", + "mean reconstruction error: 0.04784805961485911\n", + "max reconstruction error: 0.21173449573698008\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.503281887528427 max: 176.96438484533192\n", + "image 1 reprojection errors: average: 22.257378896644195 max: 318.106280674425\n", + "image 2 reprojection errors: average: 21.582307849784605 max: 163.03098440600422\n", + "image 3 reprojection errors: average: 21.58623183293511 max: 203.05945195832578\n", + "image 4 reprojection errors: average: 21.51197259652079 max: 204.13617946232478\n", + "image 5 reprojection errors: average: 21.88043923509194 max: 255.47504294338654\n", + "image 6 reprojection errors: average: 21.390647924212054 max: 181.4775823125873\n", + "image 7 reprojection errors: average: 22.307667661297863 max: 265.0648246743963\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.6969e+06 5.19e+06 \n", + " 1 2 4.0678e+04 3.66e+06 6.81e+01 2.93e+05 \n", + " 2 3 3.7180e+04 3.50e+03 8.63e-01 4.96e+03 \n", + " 3 4 3.7124e+04 5.56e+01 5.92e-01 1.58e+03 \n", + " 4 5 3.7113e+04 1.10e+01 9.03e-02 1.72e+02 \n", + " 5 6 3.7112e+04 1.13e+00 1.92e-02 9.17e+01 \n", + " 6 7 3.7111e+04 6.70e-01 9.93e-03 6.12e+01 \n", + " 7 8 3.7111e+04 4.48e-01 9.09e-03 9.61e+01 \n", + " 8 9 3.7111e+04 3.56e-01 5.41e-03 9.48e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 3.6969e+06, final cost 3.7111e+04, first-order optimality 9.48e+01.\n", + "mean reprojection error: 2.5334890390097002\n", + "max reprojection error: 8.976515547015872\n", + "mean reconstruction error: 0.14565701518637408\n", + "max reconstruction error: 0.7202115888135266\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.777532335892012 max: 229.39633390272587\n", + "image 1 reprojection errors: average: 22.641300822259478 max: 315.4032025626577\n", + "image 2 reprojection errors: average: 21.863181973759712 max: 202.24830929226184\n", + "image 3 reprojection errors: average: 22.57934433777671 max: 154.6404110153907\n", + "image 4 reprojection errors: average: 23.008818114732623 max: 237.21220705806553\n", + "image 5 reprojection errors: average: 22.854114056476956 max: 281.30293119405826\n", + "image 6 reprojection errors: average: 22.278023974179774 max: 237.7568903823768\n", + "image 7 reprojection errors: average: 22.482293295072 max: 317.39192810426204\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8191e+06 1.03e+07 \n", + " 1 2 1.0728e+05 3.71e+06 6.88e+01 2.89e+05 \n", + " 2 3 1.0312e+05 4.16e+03 8.97e-01 5.85e+03 \n", + " 3 4 1.0296e+05 1.59e+02 1.04e+00 4.35e+03 \n", + " 4 5 1.0293e+05 3.51e+01 1.61e-01 4.86e+02 \n", + " 5 6 1.0292e+05 5.42e+00 6.38e-02 5.29e+02 \n", + " 6 7 1.0292e+05 2.25e+00 1.58e-02 1.51e+02 \n", + " 7 8 1.0292e+05 1.04e+00 1.14e-02 1.27e+02 \n", + " 8 9 1.0292e+05 8.64e-01 8.95e-03 1.44e+02 \n", + " 9 10 1.0292e+05 2.69e-01 2.26e-03 9.52e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 3.8191e+06, final cost 1.0292e+05, first-order optimality 9.52e+01.\n", + "mean reprojection error: 4.2060594127098865\n", + "max reprojection error: 15.259265442825486\n", + "mean reconstruction error: 0.2374936086291789\n", + "max reconstruction error: 1.0753439525273152\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 25.204027727484483 max: 236.1548285345105\n", + "image 1 reprojection errors: average: 25.056256207399546 max: 234.61202356342926\n", + "image 2 reprojection errors: average: 25.061580665851945 max: 248.891441782651\n", + "image 3 reprojection errors: average: 24.693883865970797 max: 246.49983416754839\n", + "image 4 reprojection errors: average: 25.20779669763003 max: 190.59478655525834\n", + "image 5 reprojection errors: average: 24.343545487107626 max: 221.01305038283488\n", + "image 6 reprojection errors: average: 24.999538438564233 max: 182.2041140163001\n", + "image 7 reprojection errors: average: 24.047252776062056 max: 197.23707287197377\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 4.4157e+06 4.47e+06 \n", + " 1 2 4.2376e+05 3.99e+06 7.34e+01 2.78e+05 \n", + " 2 3 4.2064e+05 3.12e+03 1.41e+00 1.15e+04 \n", + " 3 4 4.2028e+05 3.63e+02 1.06e+00 6.63e+03 \n", + " 4 5 4.2010e+05 1.77e+02 2.86e-01 1.21e+03 \n", + " 5 6 4.2006e+05 4.07e+01 1.51e-01 5.54e+02 \n", + " 6 7 4.2003e+05 3.30e+01 9.99e-02 6.87e+02 \n", + " 7 8 4.2000e+05 2.65e+01 1.07e-01 5.04e+02 \n", + " 8 9 4.1998e+05 2.38e+01 7.77e-02 7.65e+02 \n", + " 9 10 4.1996e+05 2.17e+01 9.18e-02 5.00e+02 \n", + " 10 11 4.1994e+05 1.34e+01 3.96e-02 5.16e+02 \n", + " 11 12 4.1994e+05 7.53e+00 3.34e-02 3.37e+02 \n", + " 12 13 4.1993e+05 7.17e+00 2.73e-02 5.21e+02 \n", + " 13 14 4.1992e+05 6.97e+00 3.18e-02 3.64e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 14 15 4.1991e+05 6.77e+00 2.60e-02 5.37e+02 \n", + " 15 16 4.1991e+05 6.59e+00 3.05e-02 4.03e+02 \n", + " 16 17 4.1990e+05 6.25e+00 2.38e-02 5.88e+02 \n", + " 17 18 4.1990e+05 5.37e+00 2.42e-02 4.53e+02 \n", + " 18 19 4.1989e+05 5.06e+00 1.86e-02 7.08e+02 \n", + " 19 20 4.1989e+05 2.38e+00 7.97e-03 2.46e+02 \n", + " 20 21 4.1989e+05 1.90e+00 8.78e-03 5.57e+02 \n", + " 21 22 4.1989e+05 1.71e+00 6.32e-03 2.17e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 22, initial cost 4.4157e+06, final cost 4.1989e+05, first-order optimality 2.17e+02.\n", + "mean reprojection error: 8.509951010491672\n", + "max reprojection error: 28.415799931362407\n", + "mean reconstruction error: 0.4694068935599997\n", + "max reconstruction error: 2.1361386958101996\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a_a7r = {}\n", + "centre_errors_8a_a7r = {}\n", + "orientation_errors_8a_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a_a7r[pixel_error] = run_led_fit(fitter, led_positions_8a_a7r)\n", + " centre_errors_8a_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration B" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [0, -0.3*camera_halfz_position, -camera_radial_position],\n", + " [camera_radial_position*np.sqrt(3)/2, -0.3*camera_halfz_position, 0.5*camera_radial_position],\n", + " [-camera_radial_position*np.sqrt(3)/2, -0.3*camera_halfz_position, 0.5*camera_radial_position],\n", + " [0, 0.3*camera_halfz_position, camera_radial_position],\n", + " [camera_radial_position*np.sqrt(3)/2, 0.3*camera_halfz_position, -0.5*camera_radial_position],\n", + " [-camera_radial_position*np.sqrt(3)/2, 0.3*camera_halfz_position, -0.5*camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [0, 0.3, 1],\n", + " [-np.sqrt(3)/2, 0.3, -0.5],\n", + " [np.sqrt(3)/2, 0.3, -0.5],\n", + " [0, -0.3, -1],\n", + " [-np.sqrt(3)/2, -0.3, 0.5],\n", + " [np.sqrt(3)/2, -0.3, 0.5]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.422028355745763 max: 131.08734346825418\n", + "image 1 reprojection errors: average: 23.059369067133957 max: 147.66618029913195\n", + "image 2 reprojection errors: average: 21.558002496038306 max: 128.06426023309228\n", + "image 3 reprojection errors: average: 23.883543045759055 max: 124.71660288440314\n", + "image 4 reprojection errors: average: 21.479280831184923 max: 149.9566093137041\n", + "image 5 reprojection errors: average: 21.361177657263422 max: 120.99911973590952\n", + "image 6 reprojection errors: average: 22.14661158118147 max: 147.5254203234643\n", + "image 7 reprojection errors: average: 21.176473811631524 max: 111.66855343886763\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3516e+06 2.44e+06 \n", + " 1 2 3.4700e+03 2.35e+06 6.81e+01 1.94e+05 \n", + " 2 3 2.8300e+03 6.40e+02 1.05e+00 1.14e+03 \n", + " 3 4 2.7994e+03 3.06e+01 1.06e+00 1.64e+03 \n", + " 4 5 2.7919e+03 7.55e+00 1.49e-01 1.16e+02 \n", + " 5 6 2.7914e+03 5.19e-01 2.39e-02 7.99e+01 \n", + " 6 7 2.7912e+03 1.85e-01 1.00e-02 3.40e+01 \n", + " 7 8 2.7911e+03 5.18e-02 2.18e-03 2.69e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 2.3516e+06, final cost 2.7911e+03, first-order optimality 2.69e+01.\n", + "mean reprojection error: 0.8000912011398097\n", + "max reprojection error: 3.119895201927475\n", + "mean reconstruction error: 0.05689303529191649\n", + "max reconstruction error: 0.3056160519467431\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 25.32758273333326 max: 144.64320875087458\n", + "image 1 reprojection errors: average: 22.219997981121306 max: 108.03847553151358\n", + "image 2 reprojection errors: average: 22.234508469801238 max: 105.11071047915048\n", + "image 3 reprojection errors: average: 21.438734028768312 max: 153.66659836950546\n", + "image 4 reprojection errors: average: 21.860292327743366 max: 151.49040466065887\n", + "image 5 reprojection errors: average: 21.38242071390782 max: 126.77067444731263\n", + "image 6 reprojection errors: average: 21.770786610251065 max: 114.41257542233666\n", + "image 7 reprojection errors: average: 21.71873383515036 max: 84.9996050791673\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3649e+06 4.02e+06 \n", + " 1 2 2.5301e+04 2.34e+06 6.79e+01 1.29e+05 \n", + " 2 3 2.4753e+04 5.48e+02 1.29e+00 5.83e+03 \n", + " 3 4 2.4664e+04 8.85e+01 1.04e+00 5.22e+03 \n", + " 4 5 2.4626e+04 3.85e+01 2.67e-01 7.82e+02 \n", + " 5 6 2.4616e+04 9.13e+00 1.29e-01 5.71e+02 \n", + " 6 7 2.4610e+04 6.66e+00 9.11e-02 2.94e+02 \n", + " 7 8 2.4605e+04 4.50e+00 6.71e-02 2.84e+02 \n", + " 8 9 2.4602e+04 3.02e+00 4.33e-02 1.77e+02 \n", + " 9 10 2.4600e+04 2.70e+00 4.67e-02 2.44e+02 \n", + " 10 11 2.4597e+04 2.59e+00 3.94e-02 1.68e+02 \n", + " 11 12 2.4595e+04 2.50e+00 4.46e-02 2.33e+02 \n", + " 12 13 2.4592e+04 2.42e+00 3.78e-02 1.71e+02 \n", + " 13 14 2.4590e+04 2.38e+00 4.37e-02 2.34e+02 \n", + " 14 15 2.4587e+04 2.32e+00 3.69e-02 1.69e+02 \n", + " 15 16 2.4585e+04 2.25e+00 4.25e-02 2.19e+02 \n", + " 16 17 2.4583e+04 2.18e+00 3.57e-02 1.62e+02 \n", + " 17 18 2.4581e+04 2.06e+00 4.00e-02 2.10e+02 \n", + " 18 19 2.4579e+04 1.87e+00 3.09e-02 1.87e+02 \n", + " 19 20 2.4577e+04 1.90e+00 3.76e-02 2.55e+02 \n", + " 20 21 2.4575e+04 1.77e+00 2.77e-02 1.95e+02 \n", + " 21 22 2.4574e+04 1.22e+00 2.19e-02 2.40e+02 \n", + " 22 23 2.4573e+04 1.02e+00 1.48e-02 1.95e+02 \n", + " 23 24 2.4573e+04 4.05e-01 5.20e-03 7.20e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 24, initial cost 2.3649e+06, final cost 2.4573e+04, first-order optimality 7.20e+01.\n", + "mean reprojection error: 2.3685530283975633\n", + "max reprojection error: 9.411649519711146\n", + "mean reconstruction error: 0.17255798063474972\n", + "max reconstruction error: 1.117199368392498\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 24.462329162159996 max: 105.08312346985481\n", + "image 1 reprojection errors: average: 23.237335036456873 max: 173.10657532516018\n", + "image 2 reprojection errors: average: 21.94132209799502 max: 95.53772695975297\n", + "image 3 reprojection errors: average: 22.702155566902302 max: 140.22789352736598\n", + "image 4 reprojection errors: average: 21.774981057729036 max: 106.86162680331809\n", + "image 5 reprojection errors: average: 21.880901627446285 max: 131.2418169304274\n", + "image 6 reprojection errors: average: 22.50804294111662 max: 166.80537500737773\n", + "image 7 reprojection errors: average: 21.248653890435623 max: 131.65170041896732\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3875e+06 2.11e+06 \n", + " 1 2 6.9147e+04 2.32e+06 6.96e+01 1.04e+05 \n", + " 2 3 6.8513e+04 6.34e+02 1.14e+00 5.16e+03 \n", + " 3 4 6.8432e+04 8.06e+01 6.11e-01 3.37e+03 \n", + " 4 5 6.8387e+04 4.49e+01 2.45e-01 6.05e+02 \n", + " 5 6 6.8372e+04 1.56e+01 1.42e-01 3.37e+02 \n", + " 6 7 6.8360e+04 1.16e+01 9.66e-02 1.88e+02 \n", + " 7 8 6.8350e+04 9.75e+00 1.01e-01 2.22e+02 \n", + " 8 9 6.8342e+04 8.70e+00 7.87e-02 1.57e+02 \n", + " 9 10 6.8334e+04 7.91e+00 8.68e-02 2.25e+02 \n", + " 10 11 6.8326e+04 7.38e+00 6.96e-02 1.42e+02 \n", + " 11 12 6.8320e+04 6.85e+00 7.81e-02 2.06e+02 \n", + " 12 13 6.8313e+04 6.47e+00 6.39e-02 1.62e+02 \n", + " 13 14 6.8307e+04 6.13e+00 7.30e-02 2.34e+02 \n", + " 14 15 6.8301e+04 5.76e+00 5.91e-02 1.77e+02 \n", + " 15 16 6.8296e+04 4.93e+00 6.00e-02 2.92e+02 \n", + " 16 17 6.8291e+04 4.76e+00 5.01e-02 2.72e+02 \n", + " 17 18 6.8288e+04 3.46e+00 3.70e-02 3.66e+02 \n", + " 18 19 6.8286e+04 2.38e+00 2.02e-02 2.47e+02 \n", + " 19 20 6.8285e+04 1.02e+00 8.93e-03 1.36e+02 \n", + " 20 21 6.8284e+04 1.02e+00 1.33e-02 2.56e+02 \n", + " 21 22 6.8283e+04 1.00e+00 8.84e-03 1.36e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 22 23 6.8282e+04 1.01e+00 1.33e-02 2.62e+02 \n", + " 23 24 6.8281e+04 9.93e-01 8.77e-03 1.33e+02 \n", + " 24 25 6.8280e+04 9.96e-01 1.33e-02 2.65e+02 \n", + " 25 26 6.8279e+04 9.83e-01 8.70e-03 1.31e+02 \n", + " 26 27 6.8278e+04 9.86e-01 1.34e-02 2.67e+02 \n", + " 27 28 6.8277e+04 9.74e-01 8.63e-03 1.28e+02 \n", + " 28 29 6.8276e+04 9.78e-01 1.34e-02 2.69e+02 \n", + " 29 30 6.8275e+04 9.66e-01 8.58e-03 1.25e+02 \n", + " 30 31 6.8274e+04 9.48e-01 1.31e-02 2.65e+02 \n", + " 31 32 6.8273e+04 9.48e-01 8.55e-03 1.26e+02 \n", + " 32 33 6.8272e+04 8.99e-01 1.24e-02 2.54e+02 \n", + " 33 34 6.8271e+04 8.94e-01 8.24e-03 1.28e+02 \n", + " 34 35 6.8270e+04 6.47e-01 8.37e-03 1.92e+02 \n", + " 35 36 6.8270e+04 7.75e-01 8.46e-03 1.82e+02 \n", + " 36 37 6.8269e+04 4.95e-01 5.01e-03 1.08e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 37, initial cost 2.3875e+06, final cost 6.8269e+04, first-order optimality 1.08e+02.\n", + "mean reprojection error: 3.949204890330875\n", + "max reprojection error: 15.192389605457588\n", + "mean reconstruction error: 0.2750591763571097\n", + "max reconstruction error: 1.6234636194473386\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 24.11787868754015 max: 135.82672226334222\n", + "image 1 reprojection errors: average: 25.39669178283399 max: 142.57251798757773\n", + "image 2 reprojection errors: average: 23.348801056128675 max: 134.6472632033062\n", + "image 3 reprojection errors: average: 23.938861047542225 max: 97.72349908494542\n", + "image 4 reprojection errors: average: 23.618093640063453 max: 100.75482634257735\n", + "image 5 reprojection errors: average: 26.462076449678616 max: 128.7692466927361\n", + "image 6 reprojection errors: average: 25.507897635877992 max: 113.7731514619232\n", + "image 7 reprojection errors: average: 23.2688795641142 max: 102.62315348025858\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.7471e+06 2.35e+06 \n", + " 1 2 2.7247e+05 2.47e+06 7.24e+01 1.70e+05 \n", + " 2 3 2.7169e+05 7.77e+02 1.33e+00 1.04e+04 \n", + " 3 4 2.7152e+05 1.69e+02 6.16e-01 5.29e+03 \n", + " 4 5 2.7142e+05 1.06e+02 4.22e-01 1.72e+03 \n", + " 5 6 2.7136e+05 5.81e+01 2.65e-01 9.66e+02 \n", + " 6 7 2.7132e+05 3.59e+01 1.71e-01 5.85e+02 \n", + " 7 8 2.7129e+05 2.86e+01 1.49e-01 4.42e+02 \n", + " 8 9 2.7127e+05 2.62e+01 1.38e-01 4.47e+02 \n", + " 9 10 2.7124e+05 2.28e+01 1.24e-01 3.56e+02 \n", + " 10 11 2.7122e+05 2.30e+01 1.30e-01 5.09e+02 \n", + " 11 12 2.7120e+05 2.17e+01 1.19e-01 2.75e+02 \n", + " 12 13 2.7118e+05 1.57e+01 8.69e-02 5.98e+02 \n", + " 13 14 2.7117e+05 1.34e+01 6.97e-02 4.34e+02 \n", + " 14 15 2.7117e+05 5.33e+00 1.74e-02 1.90e+02 \n", + " 15 16 2.7116e+05 5.53e+00 4.25e-02 5.03e+02 \n", + " 16 17 2.7115e+05 5.22e+00 1.70e-02 1.85e+02 \n", + " 17 18 2.7115e+05 5.36e+00 4.28e-02 5.58e+02 \n", + " 18 19 2.7114e+05 5.24e+00 1.70e-02 1.85e+02 \n", + " 19 20 2.7114e+05 5.33e+00 4.34e-02 5.98e+02 \n", + " 20 21 2.7113e+05 5.16e+00 1.65e-02 1.75e+02 \n", + " 21 22 2.7113e+05 3.58e+00 2.89e-02 4.69e+02 \n", + " 22 23 2.7113e+05 4.10e+00 1.63e-02 2.66e+02 \n", + " 23 24 2.7112e+05 2.47e+00 1.74e-02 3.11e+02 \n", + " 24 25 2.7112e+05 3.43e+00 1.85e-02 4.81e+02 \n", + " 25 26 2.7112e+05 2.89e+00 1.63e-02 2.66e+02 \n", + " 26 27 2.7112e+05 1.66e+00 8.09e-03 2.14e+02 \n", + " 27 28 2.7111e+05 1.31e+00 9.02e-03 2.01e+02 \n", + " 28 29 2.7111e+05 1.29e+00 7.10e-03 2.07e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 29, initial cost 2.7471e+06, final cost 2.7111e+05, first-order optimality 2.07e+02.\n", + "mean reprojection error: 7.8864156247103026\n", + "max reprojection error: 30.072301247081743\n", + "mean reconstruction error: 0.5577996926293278\n", + "max reconstruction error: 2.657465229043437\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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27JhjP1u2bMl9991H165diYuLIyUlpdBjUBDnHB9++CHXXnstAGPGjOHNN9/MU+69995j4MCBNGrUiIYNGzJw4ECWL18OwJ///GemT58eSOyaNGmSZ/2srCx+85vfEBcXR3x8PE8++WRgf6ZNm0bv3r1JSEhg48aNDBo0iAsuuIC5c+eWaN8Ko2RGRETy2LdvH82bNw9Mx8TEsG/fvjzlfvjhB7p27crGjRu55JJLmDFjRo7l9evXZ86cOSQmJvLyyy/z3Xffccstt7BixQp27tzJunXr2Lx5Mxs2bOCTTz7JN54dO3awZMkSPvvsMzZv3kzVqlV58cUXAzF06tSJpKQk+vTpk2O6Vq1aLFy4kKSkJNauXcv8+fPZtGkTAKmpqYwePZpNmzbRokULhgwZwv79+0Nu/4wzzuCTTz5h4sSJDBs2jKeeeoovv/ySRYsWcfjw4QLje+ihh0hOTmbLli18/PHHbNmyJVBv48aN2bhxI5MmTWL27Nl5tpuamkrnzp1DvjIyMnKUPXz4MA0aNKBatWoFfmYFfbb/+Mc/WLJkCQkJCVx++eXs3Lkzz/rz5s1j165dbNq0iS1btnDDDTcEljVv3pw1a9bQt2/fQEK7du1apk+fHvK4lhZdZhIRkTycc3nmhbrDpEqVKowcORKAG2+8kREjRuQpM3DgQF599VVuv/12vvjiCwBWrFjBihUr6NKlCwDHjh1j586d9OvXL2Q8K1euZMOGDXTv3h2An376KdBqULVqVa655ppA2eDp1atXM3z4cGrXrg3AiBEj+PTTTxk6dCgtWrSgV69egfXefffdfI/H0KFDAYiLi6Njx440bdoUgNatW7Nnzx5Wr16db3yvvPIK8+bNIzMzk7S0NLZv3058fHwgHoBu3brx+uuv59luu3bt2Lx5c75xBQv3Myuo3IkTJ6hZsybJycm8/vrrjBs3jk8//TRH2Q8++ICJEycGkqbgVr7g43Ts2DHq1q1L3bp1qVmzJhkZGTRo0CCsfSkqJTMiIpJHTExMjksve/fupVmzZoWuF+rL89SpU+zYsYNatWqRnp5OTEwMzjnuueceJkyYEFY8zjnGjBnDH//4xzzLatasmaNfTPB0qC/ubNkJTjhq1KgBeMlb9vvs6czMzHzj27VrF7Nnz2b9+vU0bNiQxMTEHM9Pya6ratWqZGZm5tluampqIFnMbdWqVTmSg8aNG5ORkUFmZibVqlXL9zOLiYlh1apVgem9e/fSv3//wLLsRHD48OGMHTs2z/rOuXxvnS7sOEWKkhkRkXK0Pe1o2B13w6mrQ9N6pVLX0KFDmTNnDqNGjSIpKYn69esHWiOCnTp1itdee41Ro0bx0ksv0adPnzxlHn/8cWJjY3n44YcZN24ca9asYdCgQfzhD3/ghhtuoE6dOuzbt4/q1auH7KMBMGDAAIYNG8bkyZNp0qQJ6enpfP/997Ro0aLA/ejXrx+JiYlMnToV5xxvvPEGzz//fPEOSgHyi+/o0aPUrl2b+vXrc/DgQZYtWxZIHMJRlJYZM+PSSy8NfB6LFy9m2LBhecoNGjSIadOm8d133wFeK1l2Enb11Vfz4YcfMm7cOD7++GMuvPDCPOtfdtllzJ07l/79+1OtWjXS09ML7YMVaUpmcls2FQ5sDa/suXFw+czIxiMiFVaHZqWTeATqa1ovrDqvv/56Vq1axb/+9S9iYmKYMWMGN998c6CT5sSJExkyZAjvvvsubdq04cwzz2ThwoUh66pduzbbtm2jW7du1K9fnyVLluRY/tVXX7FgwQLWrVtH3bp16devHw8++CAzZsxgx44d9O7t3clVp04dXnjhhXyTmQ4dOvDggw9y2WWXcerUKapXr85TTz1VaDLTtWtXEhMT6dGjBwDjx4+nS5cu7N69O0/ZIUOGsGDBgrBaoMKNr1evXnTp0oWOHTvSunVrLr744iLXXRSzZs1i1KhR3HvvvXTp0oWbb74ZgOTkZObOncuCBQto1KgRf/jDHwKXxKZPnx5IRqZOncoNN9zA448/Tp06dViwYEGebYwfP56vvvqK+Ph4qlevzi233MIdd9wR0f0qjBXUBFdWEhISXHJycnmH4Vl4hZfMnBtXcLnsMmPfKZu4RKRC2LFjB7GxseUdRqmpU6cOx44dK+8wpAIK9btiZhuccwm5y6plJpRwkpSFV5RNLCIiIlIgJTMlcWBreEmNLkeJSAWlVhk5HSiZKa7CLkNlC7f/jYiIiBSLkpniCrelRZejREREIkpPABYREZGoppYZEZHyUpRHQYRLffSkElLLjIhIeTmwtXSTmTDqO378OD169OCiiy7KM/BhMOccd955J23atCE+Pp6NGzcWKZTp06fzwQcfFGmdbHXq1CnWeuI9cbhnz560bduWkSNHcvLkyZDlBg8eTIMGDbjyyitzzO/bt29g7KdmzZpx9dVXl0HUJaeWGRGR8lSaz6sKo49ejRo1+PDDD6lTpw4///wzffr04fLLL88xRhHAsmXL2LlzJzt37iQpKYlJkyaRlJQUdigPPPBAkcMvDVlZWTmGNsg9HYpzDudcYKToaDZlyhQmT57MqFGjmDhxIs8++yyTJk3KU+63v/0tP/74I88880yO+cHjMF1zzTUhnyB8Oor+T05ERMJmZoGWj59//pmff/455Dg7S5cuZfTo0ZgZvXr1IiMjg7S0tDzl6tSpw913303Xrl0ZMGAAhw4dAgiMmHzkyBHatWtHamoq4D19eP78+QA88sgjdO/enfj4+HxbiIK98MIL9OjRg86dOzNhwgSysrICMUyfPp2ePXuyZs2aPNOPPfYYnTp1olOnTjzxxBMA7N69m9jYWG677Ta6du2aYxyq3Pr378/kyZPp168fsbGxrF+/nhEjRtC2bVvuvffeQuObNGkSCQkJeVrCWrZsyX333UfXrl2Ji4sjJSWl0GNQEOccH374Iddeey0AY8aM4c033wxZdsCAAdStWzffur7//ns+/PDDkC0zWVlZ/OY3vyEuLo74+HiefPLJwP5MmzaN3r17k5CQwMaNGxk0aBAXXHBB4OnSkRJ2MmNmVc1sk5n93Z9uZGbvm9lO/2fDoLL3mNnXZpZqZoMiEbiIiBRPVlYWnTt3pkmTJgwcOJCePXvmKbNv3z6aN28emI6JiWHfvn15yv3www907dqVjRs3cskllzBjxowcy+vXr8+cOXNITEzk5Zdf5rvvvuOWW25hxYoV7Ny5k3Xr1rF582Y2bNjAJ598km/MO3bsYMmSJXz22Wds3ryZqlWr8uKLLwZi6NSpE0lJSfTp0yfHdK1atVi4cCFJSUmsXbuW+fPns2nTJsAbxHH06NFs2rSJFi1aMGTIEPbv3x9y+2eccQaffPIJEydOZNiwYTz11FN8+eWXLFq0iMOHDxcY30MPPURycjJbtmzh448/ZsuWLYF6GzduzMaNG5k0aRKzZ8/Os93U1NTAZZ/cr4yMjBxlDx8+TIMGDQKjWef3mYXjjTfeYMCAAdSrl3d4jHnz5rFr1y42bdrEli1buOGGGwLLmjdvzpo1a+jbt28goV27di3Tp08vVhzhKsplpv8EdgDZezYVWOmcm2lmU/3pKWbWARgFdASaAR+Y2YXOuaxSjFtERIqpatWqbN68mYyMDIYPH86XX35Jp06dcpQJNdRNqBacKlWqBEZ1vvHGGxkxYkSeMgMHDuTVV1/l9ttv54svvgC8wQ1XrFhBly5dAO/hezt37qRfv34hY165ciUbNmwIjCf0008/BcZxqlq1amCk59zTq1evZvjw4YERskeMGMGnn37K0KFDadGiRY7La++++27IbYM38CZAXFwcHTt2DAy62bp1a/bs2cPq1avzje+VV15h3rx5ZGZmkpaWxvbt24mPjw/EA9CtWzdef/31PNstykCT4X5m4fjrX//K+PHjQy774IMPmDhxYiBpCh5kMvg4HTt2jLp161K3bl1q1qxJRkZGjlG+S1NYyYyZxQBXAA8Bd/mzhwH9/feLgVXAFH/+y865E8AuM/sa6AGUzrCwIiJSKho0aED//v1Zvnx5nmQmJiYmx6WXvXv3hjUAY6gvz1OnTrFjxw5q1apFeno6MTExOOe45557mDBhQlixOucYM2ZMYHTnYDVr1szRLyZ4uqDxB7MTnHDUqFED8JK37PfZ05mZmfnGt2vXLmbPns369etp2LAhiYmJHD9+PE+9VatWJTMzM892U1NTA8libqtWrcqRHDRu3JiMjAwyMzOpVq1a2J9ZbocPH2bdunW88cYbIZc75/JNkgo7TpESbsvME8DvgOALbOc459IAnHNpZpY91Ol5wNqgcnv9eTmY2a3ArQDnn39+0aIWEakowh0WJdy6Cnk6+aFDh6hevToNGjTgp59+4oMPPmDKlCl5yg0dOpQ5c+YwatQokpKSqF+/fqA1ItipU6d47bXXGDVqFC+99BJ9+vTJU+bxxx8nNjaWhx9+mHHjxrFmzRoGDRrEH/7wB2644Qbq1KnDvn37qF69er6jZg8YMIBhw4YxefJkmjRpQnp6Ot9//32ho2b369ePxMREpk6dinOON954g+eff77AdYojv/iOHj1K7dq1qV+/PgcPHmTZsmX0798/7HqL0jJjZlx66aWBz2Px4sXF6sD76quvcuWVV1KzZs2Qyy+77DLmzp1L//79qVatGunp6TlaZ8pDoX1mzOxK4Fvn3IYw6wyVruVJjZ1z85xzCc65hLPPPjvMqkVEKpBz48IfGqWU6ktLS+PSSy8lPj6e7t27M3DgwMDtuXPnzg101BwyZAitW7emTZs23HLLLTz99NMh66tduzbbtm2jW7dufPjhh3n6Rnz11VcsWLCARx99lL59+9KvXz8efPBBLrvsMn71q1/Ru3dv4uLiuPbaa/n+++/zjbtDhw6B9eLj4xk4cGDIDsm5de3alcTERHr06EHPnj0ZP3584NJWbgX1mSlMfvFddNFFdOnShY4dOzJu3DguvvjiYtUfrlmzZvHYY4/Rpk0bDh8+zM033wxAcnJyjstGffv25brrrmPlypXExMTw3nvvBZa9/PLLXH/99fluY/z48Zx//vnEx8dz0UUX8dJLL0Vuh8JkBTXBAZjZH4GbgEygJl6fmdeB7kB/v1WmKbDKOdfOzO4BcM790V//PeB+51y+l5kSEhJccnJyaexPyWX/h1Tat0qWVn0iEtV27NhBbGxseYdRaurUqaPBJiUiQv2umNkG51xC7rKFtsw45+5xzsU451ridez90Dl3I/AWMMYvNgZY6r9/CxhlZjXMrBXQFlhX3J0RERERKUhJHpo3E3jFzG4G/g+4DsA5t83MXgG247Xm3F5Z72SatW4WKXbQm1g+tkjrtm/Unik98l7HFhE5nahVRk4HRUpmnHOr8O5awjl3GBiQT7mH8O58qtRS0lNI5STtOKNI66Wmp0YoIhERkYpHwxlEWDvOYKE7BwYvDHudsUVsxREREanMNJyBiIiIRDW1zIiIlJNZ62aRkl6y8XhyU387qYzUMiMiUk5S0lNKtY9canpqWMlRy5YtiYuLo3PnziQk5LnLFfCe8nrnnXfSpk0b4uPj2bhxY5FimT59Oh988EGR1smWPRCmFN2uXbvo2bMnbdu2ZeTIkZw8eTJPmc2bN9O7d286duxIfHw8S5YsCSxbuXIlXbt2pXPnzvTp04evv/66LMMvNrXMiIiUo3aN2rGwCH3qClKU/nYfffQRjRs3znf5smXL2LlzJzt37iQpKYlJkyaRlJQUdv0PPPBA2GVLU1ZWVo6hDXJPh+KcwzlHlSrR///9lClTmDx5MqNGjWLixIk8++yzTJo0KUeZM888k+eee462bduyf/9+unXrxqBBg2jQoAGTJk1i6dKlxMbG8vTTT/Pggw+yaNGi8tmZIoj+T05ERErd0qVLGT16NGZGr169yMjICPnE3Tp16nD33XfTtWtXBgwYwKFDhwACIyYfOXKEdu3akZrqtUBdf/31zJ8/H4BHHnmE7t27Ex8fz3333VdoTC+88AI9evSgc+fOTJgwgaysrEAM06dPp2fPnqxZsybP9GOPPUanTp3o1KkTTzzxBAC7d+8mNjaW2267ja5du+YYhyq3/v37M3nyZPr160dsbCzr169nxIgRtG3blnvvvbfQ+CZNmkRCQgIdO3bMsZ8tW7bkvvvuo2vXrsTFxZGSUrJLjs45PvzwQ6699loAxowZw5tvvpmn3IUXXkjbtm0BaNasGU2aNAl8bmbG0aNHAThy5EjIsZ2ysrL4zW9+Q1xcHPHx8Tz55JOB/Zk2bRq9e/cmISGBjRs3MmjQIC644ILAk6UjRcmMiEglY2ZcdtlldOvWjXnz5oUss2/fPpo3bx6YjomJYd++fXnK/fDDD3Tt2pWNGzdyySWXMGPGjBzL69evz5w5c0hMTOTll1/mu+++45ZbbmHFihXs3LmTdevWsXnzZjZs2MAnn3ySb8w7duxgyZIlfPbZZ2zevJmqVavy4osvBmLo1KkTSUlJ9OnTJ8d0rVq1WLhwIUlJSaxdu5b58+ezadMmwBvEcfTo0WzatIkWLVoUOJzBGWecwSeffMLEiRMZNmwYTz31FF9++SWLFi3i8OHDBcb30EMPkZyczJYtW/j444/ZsmVLoN7GjRuzceNGJk2axOzZs/NsNzU1lc6dO4d8ZWRk5Ch7+PBhGjRoEBjNOr/PLNi6des4efIkF1xwAQALFixgyJAhxMTE8PzzzzN16tQ868ybN49du3axadMmtmzZwg033BBY1rx5c9asWUPfvn0DCe3atWvzDHNR2nSZSUSkkvnss89o1qwZ3377LQMHDqR9+/b069cvR5lQQ92EGim5SpUqgVGdb7zxRkaMGJGnzMCBA3n11Ve5/fbb+eKLLwBYsWIFK1asCIyTdOzYMXbu3JknjmwrV65kw4YNdO/eHYCffvopMChl1apVueaaawJlg6dXr17N8OHDAyNkjxgxgk8//ZShQ4fSokULevXqFVjv3XffDblt8AbeBIiLi6Njx46BQTdbt27Nnj17WL16db7xvfLKK8ybN4/MzEzS0tLYvn078fHxgXgAunXrxuuvv55nu0UZaDLczyxbWloaN910E4sXLw5cYnv88cd599136dmzJ4888gh33XUXCxYsyLHeBx98wMSJEwNJU/Agk8HH6dixY9StW5e6detSs2ZNMjIycozyXZqUzIiIVDLZlw6aNGnC8OHDWbduXZ4kIiYmJsell71794a85JBbqC/PU6dOsWPHDmrVqkV6ejoxMTE457jnnnuYMGFCWDE75xgzZgx//OMf8yyrWbNmjn4xwdMFjT+YneCEo0aNGoCXvGW/z57OzMzMN75du3Yxe/Zs1q9fT8OGDUlMTOT48eN56q1atSqZmZl5tpuamhpIFnNbtWpVjuSgcePGZGRkkJmZSbVq1Qr8zI4ePcoVV1zBgw8+GEjoDh06xBdffEHPnj0BGDlyJIMHD86zrnMu3ySpsOMUKUpmRETKUWp6aqk9KDM1PZV2jdoVWOaHH37g1KlT1K1blx9++IEVK1aEvAQwdOhQ5syZw6hRo0hKSqJ+/fqB1ohgp06d4rXXXmPUqFG89NJL9OnTJ0+Zxx9/nNjYWB5++GHGjRvHmjVrGDRoEH/4wx+44YYbqFOnDvv27aN69eqB1ozcBgwYwLBhw5g8eTJNmjQhPT2d77//nhYtWhS4v/369SMxMZGpU6finOONN97g+eefL3Cd4sgvvqNHj1K7dm3q16/PwYMHWbZsGf379w+73qK0zJgZl156aeDzWLx4McOGDctT7uTJkwwfPpzRo0dz3XXXBeY3bNiQI0eO8NVXX3HhhRfy/vvvhxwU9bLLLmPu3Ln079+fatWqkZ6enqN1pjwomRERKSftG7Uv1fraNWpXaJ0HDx5k+PDhAGRmZvKrX/0q8N93difNiRMnMmTIEN59913atGnDmWeeycKFoe+4ql27Ntu2baNbt27Ur18/x22+AF999RULFixg3bp11K1bl379+vHggw8yY8YMduzYQe/evQGvE+8LL7yQbzLToUMHHnzwQS677DJOnTpF9erVeeqppwpNZrp27UpiYiI9evQAYPz48XTp0oXdu3fnKTtkyBAWLFgQVgtUuPH16tWLLl260LFjR1q3bs3FF19c5LqLYtasWYwaNYp7772XLl26cPPNNwOQnJzM3LlzWbBgAa+88gqffPIJhw8fDtyptGjRIjp37sz8+fO55pprqFKlCg0bNuQvf/lLnm2MHz+er776ivj4eKpXr84tt9zCHXfcEdH9KowV1ARXVhISElxycnJ5h+FZeIX3c+w7Ja5q7PKxcGCrN5xBEerL/i+ttG7XFJHTx44dO0L+txut6tSpo8EmJSJC/a6Y2QbnXJ6HI+luJhEREYlqSmZERKTY1CojpwMlMyIiIhLVlMyIiIhIVFMyIyIiIlFNt2aLiJSTAw8/zIkdJRuPJ7case05d9q0Uq1T5HSnlhkRkXJyYkcKx0s4uGCw4ykpYSVH48aNo0mTJnTq1CnH/PT0dAYOHEjbtm0ZOHAg3333Xcj1ly9fTrt27WjTpg0zZ84sUozJycnceeedRVonW/ZYP1J0zjnuvPNO2rRpQ3x8PBs3bgxZLjExkVatWgXGfwp+YN+qVavo3LkzHTt25JJLLimjyMOjlhkRkXJUs317Wjz/XKnU9c1No8Mql5iYyB133MHo0TnLz5w5kwEDBjB16lRmzpzJzJkzmTVrVo4yWVlZ3H777bz//vvExMTQvXt3hg4dSocOHcLadkJCAgkJeR4TEnHZj/jPbzrc9aLVsmXL2LlzJzt37iQpKYlJkyaRlJQUsuwjjzwSGHk7W0ZGBrfddhvLly/n/PPP59tvvy2LsMOmlhkRkUqmX79+IR8/v3TpUsaMGQPAmDFjePPNN/OUWbduHW3atKF169acccYZjBo1iqVLl+Ypl5iYyMSJE+nbty8XXnghf//73wHvv/srr7wSgDvvvJMHHngAgPfee49+/fpx6tQpNmzYwCWXXEK3bt0YNGgQaWlpBe7PP/7xDwYPHky3bt3o27cvKX5rV2JiInfddReXXnopU6ZMyTO9efNmevXqRXx8PMOHDw+0RPXv359p06ZxySWX8L//+7/5bnfRokVcffXVXHXVVbRq1Yo5c+bw2GOP0aVLF3r16kV6enqB8b399tv07NmTLl268Itf/IKDBw8CcP/99zNu3Dj69+9P69at+dOf/lTg/odj6dKljB49GjOjV69eZGRkFHpcg7300kuMGDGC888/HyDfJzUvX76crl27ctFFFzFgwIDA/owZM4bLLruMli1b8vrrr/O73/2OuLg4Bg8ezM8//1zi/VMyIyIigDfUQfb4S02bNg353/e+ffto3rx5YDomJoZ9+/aFrG/37t18/PHHvPPOO0ycODHHAIvgtQQtWbKEjz76iDvvvJOFCxeSlZXFr3/9a1577TU2bNjAuHHj+P3vf19g3LfeeitPPvkkGzZsYPbs2dx2222BZV999RUffPABjz76aJ7p0aNHM2vWLLZs2UJcXBwzZswIrJeRkcHHH3/M3Xffzdy5cwNDPeT25Zdf8tJLL7Fu3Tp+//vfc+aZZ7Jp0yZ69+7Nc889V2B8ffr0Ye3atWzatIlRo0bxP//zP4F6U1JSeO+991i3bh0zZswI+YU/cuTIwOWg4Ff2doMV5XP7/e9/T3x8PJMnT+bEiROB4/bdd9/Rv39/unXrFnIbhw4d4pZbbuFvf/sbX3zxBa+++mpg2T/+8Q/eeecdli5dyo033sill17K1q1bqVWrFu+8U/In7kd/25mIiJSZUEPg5DeC8i9/+UuqVKlC27Ztad26daBFItuZZ57J/Pnz6devH48//jgXXHABX375JV9++SUDBw4EvMtaoQa4zHbs2DE+//zzHAMmZn8BA1x33XU5RtTOnj5y5AgZGRmBvh9jxozJUUfwSNUTJ07Md/uXXnopdevWpW7dutSvX5+rrroKgLi4OLZs2VJgfHv37mXkyJGkpaVx8uRJWrVqFShzxRVXUKNGDWrUqEGTJk04ePAgMTExObadexysgoT7uf3xj3/k3HPP5eTJk9x6663MmjWL6dOnk5mZyYYNG1i5ciU//fQTvXv3plevXlx44YWBddeuXUu/fv0C+xHc+nf55ZdTvXp14uLiyMrKCowHFhcXF3KcrKKqtMnMjLe3sX3/UQA6NKvHfVd1LOeIRETK1znnnENaWhpNmzYlLS0t5KWEmJgY9uzZE5jeu3dvvgMz5v6yDPXluXXrVs466yz2798PeF+6HTt2ZM2aNWHFfOrUKRo0aJDvyNK1a9cucDo/4ZarUaNG4H2VKlUC01WqVCEzM7PA+H79619z1113MXToUFatWsX9998fst6qVauSmZmZZ/2RI0eSmpqaZ/5dd92Vpz9UuJ9bduJYo0YNxo4dy+zZswPrN27cmNq1a1O7dm369evHF198kSOZcc7lm9gGH5fq1asHymUfp5KqtMnM9v1H2Z52tLzDEJFK7nhKStgdd8Opq2b74o/EPXToUBYvXszUqVNZvHgxw4YNy1Ome/fu7Ny5k127dnHeeefx8ssv89JLL4Ws79VXX2XMmDHs2rWLf/7zn7Rr1461a9cGln/zzTc8+uijbNq0iSFDhnD11VfTpUsXDh06xJo1a+jduzc///wzX331FR07hv6Hs169erRq1YpXX32V6667DuccW7Zs4aKLLipwX+vXr0/Dhg359NNP6du3L88//3xE7tApKL4jR45w3nnnAbB48eIi112UlpmhQ4cyZ84cRo0aRVJSEvXr1w/Z4pWdzDrnePPNNwN3vA0bNow77riDzMxMTp48SVJSEpMnT86xbu/evbn99tvZtWsXrVq1Ij09PWTfrEio1H1mOjStR4em9co7DBGppGrEti9R8pFbzfbtqRFbeH3XX389vXv3JjU1lZiYGJ599lkApk6dyvvvv0/btm15//33mTp1KgD79+9nyJAhAFSrVo05c+YwaNAgYmNj+eUvf5lvotGuXTsuueQSLr/8cubOnUvNmjUDy5xz3HzzzcyePZtmzZrx7LPPMn78eE6dOsVrr73GlClTuOiii+jcuTOff/55gfvz4osv8uyzz3LRRRfRsWPHkB2SQ1m8eDG//e1viY+PZ/PmzUyfPj1kuYL6zIQjv/juv/9+rrvuOvr27Uvjxo2LXX84hgwZQuvWrWnTpg233HILTz/9dI5l2S1jN9xwA3FxccTFxfGvf/2Le++9F4DY2FgGDx5MfHw8PXr0YPz48Xlu7T/77LOZN28eI0aM4KKLLspxqS7SLNR1tLKWkJDgkpOTy3SbI5/J2YS5ZEJv783CK7yfY//dIWnWulmkpBf9WRCp6am0O3mShe6cHPUVZuzysV4ogxcWeZsicnrbsWMHsbGx5R1GxCUmJnLllVfmucVXJFyhflfMbINzLs+9/ZW6ZSZcKekppKbnvS5ZmHaN2tGeMyIQkYiIiGSrtH1miqpdo3bFaynJbukREalEFi1aVN4hSCWilhkRkTJ2OlzeFzmdFfV3RMmMiEgZqlmzJocPH1ZCI5IP5xyHDx/O0WG8MLrMJCJShmJiYti7dy+HDh0q71BETls1a9bM85DAghSazJhZTeAToIZf/jXn3H1mdj9wC5D9GznNOfeuv849wM1AFnCnc+69ouyEiEhFVb169RxPehWRkgunZeYE8B/OuWNmVh1YbWbL/GWPO+dmBxc2sw7AKKAj0Az4wMwudM5llWbgIiIiIhBGnxnnOeZPVvdfBV3sHQa87Jw74ZzbBXwN9ChxpCIiIiIhhNUB2Myqmtlm4Fvgfedckr/oDjPbYmZ/MbOG/rzzgD1Bq+/154mIiIiUurCSGedclnOuMxAD9DCzTsCfgQuAzkAa8KhfPNQoU3lacszsVjNLNrNkdYQTERGR4irSrdnOuQxgFTDYOXfQT3JOAfP596WkvUDzoNVigP0h6prnnEtwziWcffbZxYldREREpPBkxszONrMG/vtawC+AFDMLHm5zOPCl//4tYJSZ1TCzVkBbYF2pRi0iIiLiC+dupqbAYjOripf8vOKc+7uZPW9mnfEuIe0GJgA457aZ2SvAdiATuF13MomIiEikFJrMOOe2AF1CzL+pgHUeAh4qWWgiIiIihdNwBiIiIhLVlMyIiIhIVKtUYzPNeHsb2/cfBWB72lE6NK1XzhGJiIhISVWqlpnt+4+yPc1LZjo0rUeHZkpmREREol2lapkBL4lZMqF3YHrkM2vKMRoREREpqUrVMiMiIiIVj5IZERERiWpKZkRERCSqKZkRERGRqKZkRkRERKKakhkRERGJakpmREREJKopmREREZGopmRGREREolqlewJwRXDg4Yc5sSMlotuoEduec6dNi+g2RERESoNaZqLQiR0pHE+JXDJzPCUl4smSiIhIaVHLTJSq2b49LZ5/LiJ1f3PT6IjUKyIiEglqmREREZGopmRGREREopqSGREREYlqSmZEREQkqimZERERkaimZEZERESimpIZERERiWpKZkRERCSqKZkRERGRqKZkRkRERKKakhkRERGJakpmREREJKopmREREZGopmRGREREopqSGREREYlqSmZEREQkqhWazJhZTTNbZ2ZfmNk2M5vhz29kZu+b2U7/Z8Ogde4xs6/NLNXMBkVyB0RERKRyC6dl5gTwH865i4DOwGAz6wVMBVY659oCK/1pzKwDMAroCAwGnjazqhGIXURERKTwZMZ5jvmT1f2XA4YBi/35i4Gr/ffDgJedcyecc7uAr4EepRm0iIiISLaw+syYWVUz2wx8C7zvnEsCznHOpQH4P5v4xc8D9gStvtefl7vOW80s2cySDx06VIJdEBERkcosrGTGOZflnOsMxAA9zKxTAcUtVBUh6pznnEtwziWcffbZYQUrIiIikluR7mZyzmUAq/D6whw0s6YA/s9v/WJ7geZBq8UA+0saqIiIiEgo4dzNdLaZNfDf1wJ+AaQAbwFj/GJjgKX++7eAUWZWw8xaAW2BdaUct4iIiAgA1cIo0xRY7N+RVAV4xTn3dzNbA7xiZjcD/wdcB+Cc22ZmrwDbgUzgdudcVmTCFxERkcqu0GTGObcF6BJi/mFgQD7rPAQ8VOLoRERERAqhJwCLiIhIVAvnMlOFtz3tKCOfWQPArO9/oOVZtcs5ovJ3PCWFb24aHZG6a8S259xp0yJSt4iIVD6VPpnp0Kxe4P32tKP8cEZmOUZzeqgR2z5idR9PSYlY3SIiUjlV+mTmvqs6Bt6PfGYNHC7HYE4TkWw1iVRrj4iIVF7qMyMiIiJRTcmMiIiIRDUlMyIiIhLVKn2fmdNVanoqY5ePDblsVLrXifb+fJa3b9SeKT2mRCw2ERGR04mSmdNQ+0bFv5soNT21FCMRERE5/SmZOQ0V1qryzYveHUELBy/Msyy/1hwREZGKSn1mREREJKopmREREZGopmRGREREopqSGREREYlqSmZEREQkqimZERERkaimZEZERESimpIZERERiWpKZkRERCSqKZkRERGRqKZkRkRERKKakhkRERGJakpmREREJKopmREREZGoVq28A6ioDjz8MCd2pMCB/d6MD0eXWt3HU1Ko2b59qdUnIiISzdQyEyEndqRwPCUlInXXbN+eGrFKZkREREAtMxFVs317WvzHYW9i7HPlG4yIiEgFpZYZERERiWpKZkRERCSqKZkRERGRqKZkRkRERKKakhkRERGJakpmREREJKoVmsyYWXMz+8jMdpjZNjP7T3/+/Wa2z8w2+68hQevcY2Zfm1mqmQ2K5A6IiIhI5RbOc2YygbudcxvNrC6wwcze95c97pybHVzYzDoAo4COQDPgAzO70DmXVZqBi4iIiEAYLTPOuTTn3Eb//ffADuC8AlYZBrzsnDvhnNsFfA30KI1gRURERHIrUp8ZM2sJdAGS/Fl3mNkWM/uLmTX0550H7AlabS8hkh8zu9XMks0s+dChQ0WPXERERIQiJDNmVgf4G/BfzrmjwJ+BC4DOQBrwaHbREKu7PDOcm+ecS3DOJZx99tlFjVtEREQECDOZMbPqeInMi8651wGccwedc1nOuVPAfP59KWkv0Dxo9Rhgf+mFLCIiIvJv4dzNZMCzwA7n3GNB85sGFRsOfOm/fwsYZWY1zKwV0BZYV3ohi4iIiPxbOHczXQzcBGw1s83+vGnA9WbWGe8S0m5gAoBzbpuZvQJsx7sT6nbdySQiIiKRUmgy45xbTeh+MO8WsM5DwEMliEtEREQkLHoCsIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRLZy7mURK1fGUFL65aXTE6q8R255zp02LWP0iInJ6UTJTFg5shYVXFF7u3Di4fGbk4ylHNWLbR7T+4ykpEa1fREROP0pmIu3cuPDKHdga2ThOE5FuMYlki4+IiJyelMxEWrgtLeG03IiIiEge6gAsIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVlMyIiIhIVFMyIyIiIlFNyYyIiIhENSUzIiIiEtWUzIiIiEhUUzIjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVlMyIiIhIVFMyIyIiIlFNyYyIiIhENSUzIiIiEtWUzIiIiEhUKzSZMbPmZvaRme0ws21m9p/+/EZm9r6Z7fR/Ngxa5x4z+9rMUs1sUCR3QERERCq3cFpmMoG7nXOxQC/gdjPrAEwFVjrn2gIr/Wn8ZaOAjsBg4GkzqxqJ4EVEREQKTWacc2nOuY3++++BHcB5wDBgsV9sMXC1/34Y8LJz7oRzbhfwNdCjlOMWERERAYrYZ8bMWgJdgCTgHOdcGngJD9DEL3YesCdotb3+vNx13WpmyWaWfOjQoWKELiIiIlKEZMbM6gB/A/7LOXe0oKIh5rk8M5yb55xLcM4lnH322eGGISIiIpJDWMmMmVXHS2RedM697s8+aGZN/eVNgW/9+XuB5kGrxwD7SydcERERkZzCuZvJgGeBHc65x4IWvQWM8d+PAZYGzR9lZjXMrBXQFlhXeiGLiIiI/Fu1MMpcDNwEbDWzzf68acBM4BUzuxn4P+A6AOfcNjN7BdiOdyfU7c65rNIOXERERATCSGacc6sJ3Q8GYEA+6zwEPFSCuERERETCoicAi4iISFQL5zJTxbBsKtMPr/beL6wfssj0w0do+fM/8e4+FxERkWhQeVpmDmz1E5WCbXctePdQY0Y+s4YZb28rg8BERESkJCpPywywu3prHjjrEZaM7R1y+Wtvb2P7fu8ROtvTCnqUjoiIiJwuKlUyU5j7ruoYeD/ymTXlGImIiIiEq/JcZhIREZEKScmMiIiIRDUlMyIiIhLVlMyIiIhIVFMyIyIiIlFNyYyIiIhENSUzIiIiEtWUzIiIiEhUUzIjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVlMyIiIhIVFMyIyIiIlFNyYyIiIhEtWrlHYCUvtT0VMYuH1vk9do3as+UHlMiEJGIiEjkKJmpYNo3al+s9VLTU0s5EhERkbKhZKaCKW7LSnFackRERE4H6jMjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVCk1mzOwvZvatmX0ZNO9+M9tnZpv915CgZfeY2ddmlmpmgyIVuIiIiAiE1zKzCBgcYv7jzrnO/utdADPrAIwCOvrrPG1mVUsrWBEREZHcCn0CsHPuEzNrGWZ9w4CXnXMngF1m9jXQA1hT/BArkQNbYeEVhZc7Nw4unxn5eERERKJASfrM3GFmW/zLUA39eecBe4LK7PXn5WFmt5pZspklHzp0qARhVBDnxnmvwhzY6r1EREQEKP7YTH8G/htw/s9HgXGAhSjrQlXgnJsHzANISEgIWaZSCbelJZyWGxERkUqkWC0zzrmDzrks59wpYD7epSTwWmKaBxWNAfaXLEQRERGR/BUrmTGzpkGTw4HsO53eAkaZWQ0zawW0BdaVLEQRERGR/BV6mcnM/gr0Bxqb2V7gPqC/mXXGu4S0G5gA4JzbZmavANuBTOB251xWRCIXERERIby7ma4PMfvZAso/BDxUkqBEREREwqUnAIuIiEhUUzIjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVlMyIiIhIVFMyIyIiIlFNyYyIiIhEtULHZqooZtl3bGj8I99Un83Y5fUKLb/7jKMAjF1ej9T0VNo1ahfpEEVERKQYKk3LTAon+aZ68QbwbteoHe0btS/liERERKQ0VJqWGYAWP1fF3G9YOLh3oWVHPrMGIKyyIiIiUn4qTcuMiIiIVExKZkRERCSqKZkRERGRqFap+sxI5XA8JYVvbhodkbprxLbn3GnTIlK3iIgUj5IZqVBqxEburrPjKSkRq1tERIpPyYxUKJFsNYlUa4+IiJSM+syIiIhIVFMyIyIiIlFNyYyIiIhENSUzIiIiEtWUzIiIiEhUUzIjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMFGB72lFGPrOGGW9vK+9QREREJB96AnA+OjSrB3gJjYiIiJy+lMzk476rOgIw8pk15RyJiIiIFESXmURERCSqFdoyY2Z/Aa4EvnXOdfLnNQKWAC2B3cAvnXPf+cvuAW4GsoA7nXPvRSRyKXWp6amMXT62WOu2b9SeKT2mlHJEIiIihQvnMtMiYA7wXNC8qcBK59xMM5vqT08xsw7AKKAj0Az4wMwudM5llW7YUtraN2pf7HVT01NLMZLT2/GUlIiOnl0jtn1ER/4WEamICk1mnHOfmFnLXLOHAf3994uBVcAUf/7LzrkTwC4z+xroAajjyWmuJK0qxW3NiTY1Youf8IXjeEpKROsXEamoitsB+BznXBqAcy7NzJr4888D1gaV2+vPE4l6kW4xiWSLj4hIRVbaHYAtxDwXsqDZrWaWbGbJhw4dKuUwREREpLIobsvMQTNr6rfKNAW+9efvBZoHlYsB9oeqwDk3D5gHkJCQEDLhKQ0z3t7G9v1HcZbJqVOOqqHSLREREYlaxW2ZeQsY478fAywNmj/KzGqYWSugLbCuZCGWzPb9RwMPvqtSxQIPwxMREZGKIZxbs/+K19m3sZntBe4DZgKvmNnNwP8B1wE457aZ2SvAdiATuP10uJOpQ9N6nHmGt6vZD8MTERGRiiGcu5muz2fRgHzKPwQ8VJKgRERERMKlJwCLiIhIVFMyIyIiIlFNyYyIiIhENSUzIiIiEtWUzIiIiEhUUzIjIiIiUU3JjIiIiEQ1JTMiIiIS1ZTMiIiISFRTMiMiIiJRTcmMiIiIRDUlMyIiIhLVCh1oUk5DB7bCwisKLnNuHFw+s2ziERERKUeVNpk58PDDnNiRUmi5xLSj/HAik2WveofqzDOq0vKs2oWudzwlhZrt25c4zjzOjSu8zIGtpb9dERGR01SlTWZO7EgJK+E484yqgfc/nMgMu/6a7dtTIzYCyUw4rS2FtdqIiIhUIJU2mQEv4Wjx/HMFlmkR9H7kM2sAWDKhdwSjEhERkaJQB2ARERGJakpmREREJKopmREREZGopmRGREREopqSGREREYlqSmZEREQkqimZERERkaimZEZERESiWqV+aJ6UntT0VMYuH1vk9do3as+UHlMiEJGIiFQWSmakxNo3Kt6wDanpqaUciYiIVEZKZqTEituyUpyWHBERkdzUZ0ZERESimpIZERERiWpKZkRERCSqKZkRERGRqKZkRkRERKKakhkRERGJaiW6NdvMdgPfA1lApnMuwcwaAUuAlsBu4JfOue9KFqaIiIhIaKXRMnOpc66zcy7Bn54KrHTOtQVW+tMiIiIiERGJy0zDgMX++8XA1RHYhoiIiAhQ8mTGASvMbIOZ3erPO8c5lwbg/2wSakUzu9XMks0s+dChQyUMQ0RERCqrkg5ncLFzbr+ZNQHeN7OUcFd0zs0D5gEkJCS4EsYhIiIilVSJWmacc/v9n98CbwA9gINm1hTA//ltSYMUERERyU+xW2bMrDZQxTn3vf/+MuAB4C1gDDDT/7m0NAIVqQyOp6TwzU2jI1J3jdj2nDttWkTqFhEpTyW5zHQO8IaZZdfzknNuuZmtB14xs5uB/wOuK3mYIhVfjdj2Eav7x/Xr+XH9ek7sCPtKcJEpWRKR8lLsZMY590/gohDzDwMDShKUSGUUyUTgwMMPRzSROZ4SubpFRApT0g7AIhIFIt1iEqlLYyIi4VAyU1Ed2AoLryi83LlxcPnMyMcjIiISIUpmKqJz48Ird2BrZOMQEREpA0pmKqJwW1rCabkRERE5zWnUbBEREYlqSmZEREQkqimZERERkaimPjNSrlLTUxm7fGyx1m3fqD1Tekwp5YhERCTaKJmRctO+UfGfeJuanlqKkYiISDRTMlNMM97exvb9RwPTHZrV476rOpZjRNGnJK0qxW3NERGRikfJTDFt33+U7WlH6dC0HtvTjha+goiIiESEOgCXQIem9VgyoTcdmtYr71BEREQqLSUzIiIiEtWUzBTR9rSjjHxmjS4tiYiInCbUZ6YIOjT79+WkDk3r5ZgWERGR8qFkpgh0t5KIiMjpR8lMZXdga3gDTp4bF/4AllIpHU9J4ZubRkek7hqx7Tl32rSI1C0i0U/JTGV2blx45Q5sjWwcEvVqxBb/AYiFOZ6SErG6RaRiUDJTmYXb0hJOy005KO5QCBoGofRFstXkm5tGR7TVB9TyIxLtlMxIVCruUAgaBiH6RLLVB9TyI1IRKJkpJdm3bGtYg7JR3JYVDYMQfSLdYhLJFh8RKRtKZkpB9i3aevaMiIhI2VMyUwqyW2JGPrOmnCMRERGpfJTMlLLsy01QwUbS1i3cIiJymlIyU4qCnwhcoS456RZuERE5jSmZKUXBrTAV6pJTlN/CLSIiFZuSmQiqsJecRCoYPb1YJLopmYmQCnvJqTBR0LemrB+2N2vdLFLSi/csEz3gL/Ii+RybH9ev58f16zmxI3LPslGyJKJkJmIq7CWngkRB35ryeNheSnoKqemptGvUrsy2KeGLZCJw4OGHI5rI6IF/Ih4lM1J6oqBvTXk9bK9do3YsHLywTLcp5a8sHvinS2QiSmZERKKWBvgU8SiZOY3MeHsb2/f/u39Nhe40HAV9a3Irbl+b4lxiKuk2Qf1tKoNID/ApEi2UzJShwpKV7fuPsj3tKB2a1iNpVzpJu9ID5StUYhNu35pvVnuvcPrYRDjpKW5fG/AuMRVn/ZJsM/lgMskHk4vV8VhJkIhEm4glM2Y2GPhfoCqwwDl3evx7XU62px0laVc6AD1bNQqZrAB0aFqPJRN650h8gu+GCp4ftQlOuEnHsqnhJTLhdigOtz7IkxyVx5d7SbY565WrSPkxLbz9PaM2NGoNqNOx5BTJ/jiRFq39fSLdaTxaj0thIpLMmFlV4ClgILAXWG9mbznntkdie6e74Nu0sxOQ4KQkO7GpW7MaHZp6ZXPfDZX9zJrshKhuzUrQqFaUDsXhXLb6ZrX3s0WfwsuF2yJUmkqxdWnKD6fgwLeFt4Id2OqV8TsnF/eSVkluPy+Jsm5FKul+RlOrVyT740RaWdwSHyk/rl8PwJndu0ek7or6qIBIfSP2AL52zv0TwMxeBoYBlTKZCdV6Ejwvd2tLbsHzerZqRIdm9XJcrqr0wr1s1aJPeAlDUVpwSktpJ1DZScrYdwouFyIBLE4/neSDyQAknJNQpPVKoiSX0kqyTSjefmavGy2i+b/3SLduRNKZ3btHLCGI9HHJTsTKgznnSr9Ss2uBwc658f70TUBP59wdQWVuBW71J9sBkWzfbgz8K4L1i45xWdFxjjwd47Kh41w2KtpxbuGcOzv3zEi1zFiIeTmyJufcPGBehLafMxizZOdc2f3LWAnpGJcNHefI0zEuGzrOZaOyHOcqEap3L9A8aDoG2B+hbYmIiEglFqlkZj3Q1sxamdkZwCjgrQhtS0RERCqxiFxmcs5lmtkdwHt4t2b/xTm3LRLbClOZXM6q5HSMy4aOc+TpGJcNHeeyUSmOc0Q6AIuIiIiUlUhdZhIREREpE0pmREREJKpVmGTGzAabWaqZfW1mU0MsNzP7k798i5l1LY84o10Yx7m/mR0xs83+a3p5xBnNzOwvZvatmX2Zz3Kdy6UgjOOsc7mEzKy5mX1kZjvMbJuZ/WeIMjqfSyDMY1zhz+UK8Uz8MIdPuBxo6796An/2f0qYijBMxafOuSvLPMCKYxEwB3gun+U6l0vHIgo+zqBzuaQygbudcxvNrC6wwcze19/mUhXOMYYKfi5XlJaZwPAJzrmTQPbwCcGGAc85z1qggZk1LetAo1w4x1lKyDn3CZBeQBGdy6UgjOMsJeScS3PObfTffw/sAM7LVUzncwmEeYwrvIqSzJwH7Ama3kveDzOcMlKwcI9hbzP7wsyWmVkUDut92tO5XHZ0LpcSM2sJdAGSci3S+VxKCjjGUMHP5QpxmYkwhk8Is4wULJxjuBFv7IxjZjYEeBOv+VhKj87lsqFzuZSYWR3gb8B/Oedyj5Kr87kUFHKMK/y5XFFaZsIZPkFDLJRcocfQOXfUOXfMf/8uUN3MGpddiJWCzuUyoHO5dJhZdbwv2Redc6+HKKLzuYQKO8aV4VyuKMlMOMMnvAWM9nvO9wKOOOfSyjrQKFfocTazc83M/Pc98M6xw2UeacWmc7kM6FwuOf/4PQvscM49lk8xnc8lEM4xrgzncoW4zJTf8AlmNtFfPhd4FxgCfA38CIwtr3ijVZjH+VpgkpllAj8Bo5weM10kZvZXoD/Q2Mz2AvcB1UHncmkK4zjrXC65i4GbgK1mttmfNw04H3Q+l5JwjnGFP5c1nIGIiIhEtYpymUlEREQqKSUzIiIiEtWUzIiIiEhUUzIjIiIiUU3JjIiIiEQ1JTMigJll+aPJbvMf+X2XmVXxlyWY2Z8KWLelmf2q7KLNs/07/RFzX4zwdv7LzM6MUN3legzLkpm9a2YN/NdtQfObmdlrpbSN3Wa21cwSSqGuR8zsgJn9pjRiE4kE3ZotApjZMedcHf99E+Al4DPn3H1hrNsf+E15jUhrZinA5c65XbnmV3POZZbidnYDCc65f4VYVtU5l1WCuvtTgmNY0u2XB38cnb875zpFoO7d5PNZFbO++4FjzrnZpVGfSGlTy4xILs65b4FbgTv8p5L2N7O/A5jZJX4LzmYz22RmdYGZQF9/3mS/leFTM9vov/6fv25/M1tlZq+ZWYqZvRj0VM7uZva53yq0zszqmllV/7/i9Wa2xcwm5I7VzOYCrYG3/G3fb2bzzGwF8JyZtTCzlf76K83sfH+9RWb2ZzP7yMz+6e/XX/wWnkUhtnMn0Az4yMw+8ucdM7MHzCwJbxC73eY/It1vzVrlv6/t173eP2ahRlrPfQxrmtlCv3Vhk5ldGiKm/n78L+E9MCzf42Vmv/Pr+sLMZvrzOpvZWr/sG2bWsKDzwj+2z5vZh2a208xu8eebv90v/W2M9Oc3NbNP/H360sz6+vOzj9NM4AJ/+SP+efOlXybk/ptZopm9bmbL/Rj+p6CYg2IPdX4lmtmbZva2me0yszvMa5Hc5B+XRuHULXJacM7ppVelf+H915l73nfAOXhPif27P+9t4GL/fR28p2gHlvvzzwRq+u/bAsn++/7AEbyxZ6oAa4A+wBnAP4Hufrl6fr23Avf682oAyUCrEHHuBhr77+8HNgC1guId478fB7zpv18EvIw3yN8w4CgQ58e1Aehc0Hb8aQf8Mp84EoBV/vuHgRv99w2Ar4DauerOfQzvBhb679sD/5d9THOt80P2McnveAGXA58DZ/rLGvk/twCX+O8fAJ4o5By5H/gCqAU0xhvpuRlwDfA+3lOxz/Fjbervw+/9dasCdYOPE9AS+DKo/sB0fvsPJOKdK/X96W+A5oWcE/mdX4l4T92tC5yNd25O9Ms8jjdgYfC+/6a8f0/10iu/l1pmRPIXajTfz4DH/JaKBi70ZZzqwHwz2wq8CnQIWrbOObfXOXcK2Iz3BdYOSHPOrYfAoHCZwGV4Y9ZsBpKAswhvpNu3nHM/+e97410yA3geL3nK9rZzzgFbgYPOua1+XNv8uAqThTe4XWEuA6b6+7EK70v4/ELW6ePHi3MuBe9L+8IQ5da5f19ey+94/QIvMfjRry/dzOrjfX4f++suBvqFsS9LnXM/Oe/yzUdADz/WvzrnspxzB4GPge54Y5mNNe8STZxz7vsw6g9n/1c65444544D24EWhdSV3/kF8JFz7nvn3CG8ZOZtf/5WwjsHRE4LFWJsJpHSZmat8b6svwVis+c752aa2Tt4Y8msNbNfhFh9MnAQuAivpeN40LITQe+z8H4HDa+VI08YwK+dc+8VMfwfClgWvJ3sWE7liusU4f1tOO5y9lPJ5N+XrmsGzTfgGudcahh1Bq8TjuB9DXm8zGwwoY9vceSux5FPrM65T8ysH3AF8LyZPeKcey7M7RS0/6HOocLqym//c3/uweeEvh8kaqhlRiQXMzsbmAvM8Vsugpdd4LdgzMK7jNEe+B6vqT5bfbz/hE/hDQBXtZBNpgDNzKy7v426ZlYNb0DPSWZW3Z9/oZnVLuLufI43ujnADcDqIq4fLPd+5rYb6Oa/vyZo/nvAr80C/YO6hFH3J3jxYmYX4rXkFJYM5Xe8VgDjzL8Ty8waOeeOAN9l92PB+5w+DlVpLsP8/ixn4V3mWu/HOtLvs3M2XgvPOjNrAXzrnJuPN6px10L2OVhx9j8/+Z1fIhWGTmgRTy3/8kR1vBaG54HHQpT7L78zZhZeE/8yvP9iM83sC7y+KE8DfzOz6/AuRRTUUoJz7qTfafRJM6uFN6rtL4AFeE39G/1E4BBwdRH3607gL2b2W3/9koxIPA9YZmZpzrk8HXKBGcCzZjYN7zJPtv8GngC2+PuxG8h919IW8h7Duf6lukwg0Tl3goKFPF7OueVm1hlINrOTeKM0TwPG+Ns4E69PyVgAM3sAr5/TWyG2sQ54By+5+G/n3H4zewPvct4XeC0gv3POHTCzMcBvzexn4BgwOrgi59xhM/vM7/S7DHgqaHHI/ffzwSIp4PwSqTB0a7aISBgsim5PNt2aLZWMLjOJiFQ8h4CVVkoPzQNupJAWRpHypJYZERERiWpqmREREZGopmRGREREopqSGREREYlqSmZEREQkqimZERERkaj2/wFWK/r6hhOv4AAAAABJRU5ErkJggg==\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8b_a7r = {}\n", + "centre_errors_8b_a7r = {}\n", + "orientation_errors_8b_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8b_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8b_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8b_a7r[pixel_error] = run_led_fit(fitter, led_positions_8b_a7r)\n", + " centre_errors_8b_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8b_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8b_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8b_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8b_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8b_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Summary Plots" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "led_pos_res_4 = np.array([np.percentile(e, 68) for e in position_errors_4.values()])\n", + "led_pos_res_6a = np.array([np.percentile(e, 68) for e in position_errors_6a.values()])\n", + "led_pos_res_6b = np.array([np.percentile(e, 68) for e in position_errors_6b.values()])\n", + "led_pos_res_8a = np.array([np.percentile(e, 68) for e in position_errors_8a.values()])\n", + "led_pos_res_8b = np.array([np.percentile(e, 68) for e in position_errors_8b.values()])\n", + "led_pos_res_4_a7r = np.array([np.percentile(e, 68) for e in position_errors_4_a7r.values()])\n", + "led_pos_res_6a_a7r = np.array([np.percentile(e, 68) for e in position_errors_6a_a7r.values()])\n", + "led_pos_res_6b_a7r = np.array([np.percentile(e, 68) for e in position_errors_6b_a7r.values()])\n", + "led_pos_res_8a_a7r = np.array([np.percentile(e, 68) for e in position_errors_8a_a7r.values()])\n", + "led_pos_res_8b_a7r = np.array([np.percentile(e, 68) for e in position_errors_8b_a7r.values()])\n", + "fig_led_pos_a6000, ax_led_pos_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_led_pos_a7r, ax_led_pos_a7r = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_led_pos, ax_led_pos = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.09768923 0.29892812 0.49070657 0.98510866]\n", + "[0.0965059 0.29540936 0.49112376 0.98235441]\n" + ] + } + ], + "source": [ + "print(led_pos_res_6a)\n", + "print(led_pos_res_8b)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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7/vfffz8Ty4gRI2jcuDFbt25Fp9MZ9j1asWIFxYsXJykpibp169KxY0ecnZ1JTEykSZMmTJ06lfbt2zNhwgT++9//cvnyZXr37k27du1Yvnw5jo6OnDhxgpSUFN58801atmwJwPHjx7l48SJeXl7Pvc7du3cJDQ3l4sWLgFo+lCRJyrOioqBHD9i7V+17mTcP0re8yc0K5AhMbKyavID6NTb29c6n1Wo5ffo0Q4YM4cyZMzg4OBh6OjQaDS4uLobHHjx4kICAAHx9fTlw4ACXLl0y3Ofq6kpYWNgz5584cSInT56kZcuWrF+/3jCic+TIEXr27AlA06ZNiYqKIjb9xbz99tsUKlSIEiVK4OrqSkREBOXKlcPZ2ZkzZ84QGBhIrVq1cHZ2fuZ6GzZsoFu3bgB069aNDRs2GF7nn3/+adjZ+fbt26xatSrT3bSf7Dz9vPuyek5GBw4cYMiQIYA6+uSYnmnOmTOHGjVqUL9+fYKDg7lx4wagjn49eX98fX1p3Lgx1tbW+Pr6Gvp1AgMDWbNmDTVr1iQgIICoqCjD8+vVq2dIXp53nfLly3P79m2GDx/Onj17KFq06DNxS5Ik5QmnT4O/vzpVeskSdZXdPJC8QD4cgclqpOSJJxtopqaCjQ2sW/d6KyB7eHjg4eFBQEAAAJ06dTIkMHZ2diQnJwOQnJzM0KFDOXnyJJ6ennz11VeG+57cb2dnl+k1KlSowJAhQxgwYAAuLi5ERUVlmQRk3AzS0tISrVYLQP/+/Vm1ahXh4eH069fvmedHRUVx4MABLl68iKIo6HQ6FEXhxx9/xMPDg1q1alG+fHlALa8cO3aMfv36ERMTg1arxcrKipCQEEqVKmV4b4KDgw3nf3JfampqpseNcejQIfbt20dQUBD29vY0adLE8D5aW1sb3gMLCwvD+2BhYWF4D4QQzJ07l1atWj1zXgcHhxdep1ixYpw7d469e/cyf/58fv31V1asWGFU7JIkSbnG6tUweLA6RfrwYUj/DMsrCuQITIMG6rYNkydnz/YNbm5ueHp6cu3aNQD2799v6FPx8fHh5s2bAIYP2RIlSpCQkMDmzZufOs/169epXr36M+f/448/DMnKjRs3sLS0xMnJiUaNGrFu3TpA/bAtUaLEC0cD2rdvz549ezhx4sQzH+Cg9uz06tWLe/fucffuXYKDg/Hy8uLIkSPUrVuX6OhoHj58CKijI1WrVkVRFN566y3D61m9ejXvvfceAO3atWPNmjUIITh27BiOjo64u7tTt25dbty4wZ07d0hNTWXjxo20a9fumXiaNWvGwoULAbX3JC4ujtjYWIoVK4a9vT1Xr17l2LFjWb7mf2vVqhULFy4kLS0NUN/3xMTEZx73vOtERkai1+vp2LEjkydPfmpmlSRJUq6Xmgoffwx9+qizjU6fznPJC+TDERhjNWiQvftOzZ07lx49epCamkr58uVZuXIloJZyFi9eTP/+/XFycmLAgAH4+vpSrlw56tata3h+WloaN2/exN//mQ03+fnnnxk9ejT29vZYWVmxbt06LC0t+eqrr+jbty9+fn7Y29uzevXqF8ZpY2PDW2+9hZOTE5aWls/cv2HDBj7//POnjnXs2JH169fzn//8h+nTp9OsWbMnM8IYMGAAAFOnTqVbt25MmDCBWrVqGRqa27Zty65du6hYsSL29vaG98XKyop58+bRqlUrdDod/fr1o1q1as/EM3v2bAYOHMjy5cuxtLRk4cKFtG7dmkWLFuHn54e3tzf169d/4evOqH///ty9e5fatWsjhMDFxcXQdJzR864TGhpK37590afXIadMmfJS15ckSTKbsDDo1EktRYwZAz/8AFZ5MxVQMitD5Gb+/v7i5MmTTx27cuUKPj4+ZoroxRo2bMjOnTsNM5Mys3XrVk6fPs3kyZNNGoter6d27dps2rSJSpUqmfRaBV1u/72UJKmA+fNP6NwZEhLUXaS7dDF3REZRFOWUEOKZv+4LZAkpp82YMYP79+9n+RitVsuYMWNMGsfly5epWLEizZo1k8mLJElSQSEEzJ4NTZtC0aLw9995JnnJSt4cN8pjAoyoLXbu3NnkcVStWpXbt2+b/DqSJElSLpGYCAMHwvr10K4drFmT9boheYgcgZEkSZKk/OjWLbXZc8MG+PZb2Lo13yQvIEdgJEmSJCn/2bVLXZxOUdTvM6wIn1/IERhJkiRJyi/0evj6a3jnHShXTt0SIB8mLyBHYCRJkiQpf4iOhp494Y8/1K+LFoG9vbmjMhk5ApNNYmJi6NSpE1WqVMHHx4egDLtEjho1isOHDwNQrlw5IiMjn3n+vHnzDGuk/Nu1a9do0qQJNWvWxMfHh4EDB5rmRWRw5swZFEVh7969Tx1/3ut89OgRLVq0oFKlSrRo0YLo6GjDc6ZMmULFihXx9vZ+6nynTp3C19eXihUrMmLEiExXFpYkSZKMcP481K2r7mc0b566ym4+Tl4AntmeOrf/q1OnzjNbbV++fPlVdujOVr169RJLly4VQgiRkpIioqOjhRBCREVFiYCAAMPjypYtKx4+fPjM8xMTE0XNmjUzPXfLli3Ftm3bDLfPnz+fjZFnbty4caJhw4aid+/eTx1/3uscN26cmDJlihBCiClTpohPP/1UCCHEpUuXhJ+fn0hOTha3b98W5cuXF1qtVgghRN26dcVff/0l9Hq9aN26tdi1a5fJX5ex9Hq90Ol0r3WO3PB7KUlSAbBunRB2dkK4uwtx5Ii5o8l2wEmRST5QYEdggoKDmPLnFIKCg1784BeIi4vj8OHDhtVnbWxsDIvWbd682bC54BPTpk2jXr161KtXz7DNgL29PeXKlct0d2iNRoOHh4fhtq+vL6BuTdC3b198fX2pVasWBw8eBGDVqlV06NCB1q1bU6lSJT799FMAli9fzujRow3nWbp0KZ988skz1xNCsHnzZlatWkVgYKBhC4SsXuf27dvp3bs3AL179zasbLt9+3a6detGoUKF8PLyomLFihw/fhyNRkNcXBwNGjRAURR69eqV6Wq4CQkJhtfo5+fHb7/9BsCQIUPw9/enWrVqTJo0yfD4cuXK8cUXX9CgQQP8/f05ffo0rVq1okKFCixatOipn0HdunXx8/MzPP/u3bv4+PgwdOhQateuTXBw8HOv8/nnn1O1alX8/PwYO3bsM3FLkiSZXFoajB6tNuvWqaP2u7z5prmjyjH5rgdm1J5RnA0/m+VjYlNiOR9xHr3QY6FY4FfSD8dCz59aVtOtJrNaz3ru/bdv38bFxYW+ffty7tw56tSpw+zZs3FwcODo0aN06tTpqccXLVqU48ePs2bNGkaNGsXOnTsB8Pf3588//6RevXpPPX706NE0bdqUN954g5YtW9K3b1+cnJyYP38+ABcuXODq1au0bNmS69evA3D27FnOnDlDoUKF8Pb2Zvjw4XTr1g0/Pz9+/PFHrK2tWblyJYsXL37m9Rw9ehQvLy8qVKhAkyZN2LVrFx06dMjydUZERODu7g6Au7s7Dx48ANRl9zMu9e/h4UFoaCjW1tZPJWVPjv/b5MmTcXR05MKFCwCG0tR3331H8eLF0el0NGvWjPPnz+Pn5weAp6cnQUFBjB49mj59+nD06FGSk5OpVq0agwcPJjAwkBs3bnD8+HGEELRr147Dhw9TpkwZrl27xsqVK1mwYMFzr+Ph4cHWrVu5evUqiqIQExPz3N8NSZIkkwgPh65d1U0YR4yA6dPB2trcUeWoAjkCE5sci16o+9johZ7Y5NjXOp9Wq+X06dMMGTKEM2fO4ODgYNiNWqPR4OLi8tTju3fvbviasVfG1dWVsLCwZ87ft29frly5QufOnTl06BD169cnJSWFI0eO0LNnTwCqVKlC2bJlDQlMs2bNcHR0xNbWlqpVq3Lv3j0cHBxo2rQpO3fu5OrVq6SlpRlGczLasGED3bp1A6Bbt25s2LDhha/zecRzdsx+3vF/27dvHx9//LHhdrFixQD49ddfqV27NrVq1eLSpUtcvnzZ8Jgnm0L6+voSEBBAkSJFcHFxwdbWlpiYGAIDAwkMDKRWrVrUrl2bq1evcuPGDQDKli37VMKV2XWKFi2Kra0t/fv3Z8uWLdjn9zqzJEm5S1CQOuJy4gSsXauuslvAkhfIhyMwWY2UPBEUHESzNc1I1aViY2nDug7raOD56js7enh44OHhYVhxt1OnToYPdjs7O0MJ5omMH9QZv09OTsbOzi7Ta5QqVYp+/frRr18/qlevzsWLF7Nsei1UqJDhe0tLS7RaLaBuZPj9999TpUoV+vbt+8zzdDodv/32Gzt27OC7775DCEFUVBTx8fFZvs6SJUui0Whwd3dHo9Hg6upqeG+Cg4MN5w8JCaFUqVJ4eHgQEhLyzPF/E0I8k9jcuXOH6dOnc+LECYoVK0afPn2eeo+fvHYLC4un3gcLCwu0Wi1CCMaPH8+gQYOeOu/du3dxcHB44XWsrKw4fvw4+/fvZ+PGjcybN48DBw5k+nOQJEnKNkKoM4tGjgRPTzWRqVHD3FGZTYEcgWng2YD9vfYz+a3J7O+1/7WSFwA3Nzc8PT25du0aAPv376dq1aoA+Pj4GPpcnvjll18MXxtk2BL7+vXrVK9e/Znz79mzh7S0NADCw8OJioqidOnSNGrUiHXr1hmee//+fby9vbOMNSAggODgYNavX28YCcpo37591KhRg+DgYO7evcu9e/fo2LEj27Zty/J1tmvXzrAb9urVq3nvvfcMxzdu3EhKSgp37tzhxo0b1KtXD3d3d4oUKcKxY8cQQrBmzRrDczJq2bIl8+bNM9yOjo4mLi4OBwcHHB0diYiIYPfu3Vm+5n9r1aoVK1asICEhAVDLXE9KXhk97zoJCQnExsbStm1bZs2axdmzZ1/q+pIkSS8tKQn69oWhQ6F5czh5skAnL5APR2CM1cCzwWsnLhnNnTuXHj16kJqaSvny5Q1Tot9++20WL15M//79DY9NSUkhICAAvV5vKM+A2nuSsVH0icDAQEaOHImtrS2gNqC6ubkxdOhQBg8ejK+vL1ZWVqxateqpEYfn6dKlC2fPnjWUYzLasGED7du3f+pYx44dWbhwIT179nzu6/z888/p0qULy5cvp0yZMmzatAmAatWq0aVLF6pWrYqVlRXz58/H0tISgIULF9KnTx+SkpJo06YNbdq0eSaeCRMm8PHHH1O9enUsLS2ZNGkSHTp0oFatWlSrVo3y5cvz5ks2rbVs2ZIrV64YksfChQuzdu1aQ1xP1KhRI9PrxMfH895775GcnIwQgpkzZ77U9SVJkl7K3bvQoQOcOQMTJ8KkSWBRIMcfnqJkVYbIjfz9/cXJkyefOnblyhV8fHzMFNGLNWzYkJ07dxpm7GTmzJkz/PTTT/z8888mj+edd95h9OjRNGvWzOTXKshy+++lJEl5QGAgdO8OOh38/DO8+665I8pxiqKcEkL4//u4TOFywIwZM7h//36Wj4mMjGTy5MkmjSMmJobKlStjZ2cnkxdJkqTcTAiYMkXdBqBUKbVkVACTl6wU2BJSTnrS9JqVFi1amDwOJycnwywlSZIkKZeKi4PevWHbNujWDZYtgwwTDCSVTGAkSZIkKbe4fBnat4dbt2DmTHXGUSZLTEgygZEkSZKk3GHzZujTRx1t2b8fGjc2d0S5muyBkSRJkiRz0mrh00+hc2fw9VW3BJDJywuZNIFRFKW1oijXFEW5qSjK51k8rq6iKDpFUTo97zGSJEmSlO88fAitWsG0aTBkCBw6BBm2WZGez2QJjKIolsB8oA1QFeiuKErV5zxuKrDXVLHkhJkzZ1KtWjWqV69O9+7dn1oZdtSoURw+fDjL548dO/a5q7keO3aMgIAAatasiY+PD1999VV2hp6prVu3oigKV69efer4/fv3admyJT4+PlStWpW7d+8C6qq1AQEBVKpUia5du5KamgqoK+mOGDGCihUr4ufnx+nTpw3n2rNnD97e3lSsWPGFWxJIkiTlOydOqFsCHD0KK1fCggVgxFpeUrrMtqjOjn9AA2BvhtvjgfGZPG4U8DGwCuj0ovPWqVPnma22L1++/Fpbdb+ukJAQUa5cOfH48WMhhBCdO3cWK1euFEIIERUVJQICAl54jrt374oWLVpkel/lypXF2bNnhRBCaLVacenSpewJPAudO3cWDRs2FJMmTXrqeOPGjUVgYKAQQoj4+HiRmJhoePyGDRuEEEIMGjRILFiwQAghxB9//CFat24t9Hq9CAoKEvXq1TO8jvLly4tbt26JlJQU4efnlyOvy1harfa1z2Hu30tJknKxpUuFsLERomxZIU6eNHc0uRpwUmSSD5iyhFQaCM5wOyT9mIGiKKWB9sCirE6kKMpARVFOKopy8uHDh9kSXFBsLFPu3SMo9vU2cnxCq9WSlJSEVqvl8ePHhn19Nm/eTOvWrQ2P++abb6hbty7Vq1dn4MCBhv2MypYtS1RUFOHh4c+c+8GDB4adni0tLQ3L9z969Ij3338fPz8/6tevz/nz5wH46quv6NevH02aNKF8+fLMmTMHgP/7v/9j9uzZhvN++eWXhvsySkhI4OjRoyxfvpyNGzcajl++fBmtVmuY8l24cGHs7e0RQnDgwAHDrtu9e/dm27ZtAGzfvp1evXqhKAr169cnJiYGjUbD8ePHqVixIuXLl8fGxoZu3bqxffv2Z2KJiIigffv21KhRgxo1avDXX38B8P7771OnTh2qVavGkiVLDI8vXLgwn332GXXq1KF58+YcP37c8D7s2LEDUPd7GjduHHXr1sXPz8+wI/ehQ4d46623+OCDDwybXGZ2HZ1OR58+fahevTq+vr5yJV5JkoyXkgIDB8KAAdCokbq+S5065o4qTzLlLKTM5n39e9nfWcBnQghdZjsRG54kxBJgCagr8WZ10VE3bnA2fY+b54nVajmfmIgetYbm5+CAo9Xz34qahQszq1Kl595funRpxo4dS5kyZbCzs6Nly5a0bNkSULcHePLBDjBs2DAmTpwIQM+ePdm5cyfvpi9OVLt2bY4ePUrHjh2fOv/o0aPx9vamSZMmtG7dmt69e2Nra8ukSZOoVasW27Zt48CBA/Tq1cuwL8/Vq1c5ePAg8fHxeHt7M2TIED766CM6dOjAyJEj0ev1bNy4kePHjz/zerZt20br1q2pXLkyxYsX5/Tp09SuXZvr16/j5OREhw4duHPnDs2bN+eHH34gOjoaJycnrNLfQw8PD0JDQwF1nyFPT0/DuZ/cl9nxv//++5lYRowYQePGjdm6dSs6nc6wf9GKFSsoXrw4SUlJ1K1bl44dO+Ls7ExiYiJNmjRh6tSptG/fngkTJvDf//6Xy5cv07t3b9q1a8fy5ctxdHTkxIkTpKSk8Oabbxp+XsePH+fixYt4eXk99zp3794lNDSUixcvAuoCgZIkSS8UHAwdO6qlo/HjYfJk+NcWJpLxnjsCoyhKbSP++WZx7hDAM8NtDyDsX4/xBzYqinIX6AQsUBTl/Vd7KcaL1WrRp3+vT7/9OqKjo9m+fTt37twhLCyMxMRE1q5dC4BGo8HFxcXw2IMHDxIQEICvry8HDhzg0qVLhvtcXV0JC/v3WwQTJ07k5MmTtGzZkvXr1xtGdI4cOULPnj0BaNq0KVFRUcSmjyi9/fbbFCpUiBIlSuDq6kpERATlypXD2dmZM2fOEBgYSK1atXB2dn7mehs2bKBbt24AdOvWzbBfk1ar5c8//zTs0Hz79m1WrVqV6a7YTxLS592X1XMyOnDgAEOGDAHU0SdHR0cA5syZQ40aNahfvz7BwcHcuHEDABsbG8P74+vrS+PGjbG2tsbX19fQrxMYGMiaNWuoWbMmAQEBREVFGZ5fr149Q/LyvOuUL1+e27dvM3z4cPbs2UPRokWfiVuSJOkpBw+qIy1Xr8KWLfD99zJ5eU1ZjcD8DzhB5iMpT3gB5Z5z3wmgkqIoXkAo0A34IOMDhBCGTwpFUVYBO4UQ214UdFayGil5Iig2lmbnzpGq12NjYcG6qlVpkP7B+Cr27duHl5eXIVHp0KEDf/31Fx9++CF2dnaGht7k5GSGDh3KyZMn8fT05Kuvvnqq2Tc5ORk7O7tMr1GhQgWGDBnCgAEDcHFxISoqKsskIOOmjpaWlmjTk7T+/fuzatUqwsPD6dev3zPPj4qK4sCBA1y8eBFFUdDpdCiKwo8//oiHhwe1atWifPnygFpeOXbsGP369SMmJgatVouVlRUhISGGEpqHhwfBwf9UEp/cl5qamulxYxw6dIh9+/YRFBSEvb09TZo0MbyP1tbWhvfAwsLC8D5YWFgY3gMhBHPnzqVVq1bPnNchw2qXz7tOsWLFOHfuHHv37mX+/Pn8+uuvrFixwqjYJUkqYISAGTPgs8+gcmXYuhWqVDF3VPlCVj0wJ4QQTYUQbz3vH3D7eU8WQmiBYaizi64AvwohLimKMlhRlMHZ+zJeTgNHR/bXqMFkLy/216jxWskLQJkyZTh27BiPHz9GCMH+/fsNm/j5+Phw8+ZNAMOHbIkSJUhISGDz5s1Pnef69etUr179mfP/8ccfhmTlxo0bWFpa4uTkRKNGjVi3bh2gftiWKFHihaMB7du3Z8+ePZw4ceKZD3BQe3Z69erFvXv3uHv3LsHBwXh5eXHkyBHq1q1LdHQ0T/qQDhw4QNWqVVEUhbfeesvwelavXs17770HQLt27VizZg1CCI4dO4ajoyPu7u7UrVuXGzducOfOHVJTU9m4cSPt2rV7Jp5mzZqxcOFCQO09iYuLIzY2lmLFimFvb8/Vq1c5duxYlq/531q1asXChQtJS0sD1Pc9MTHxmcc97zqRkZHo9Xo6duzI5MmTn5pZJUmSZBAfD127wrhx6uq6x4/L5CUbPXcERgjR9EVPftFjhBC7gF3/OpZpw64Qos+LrpedGjg6vnbi8kRAQACdOnWidu3aWFlZUatWLQYOHAiopZzFixfTv39/nJycGDBgAL6+vpQrV466desazpGWlsbNmzfx939mw01+/vlnRo8ejb29PVZWVqxbtw5LS0u++uor+vbti5+fH/b29qxevfqFsdrY2PDWW2/h5OSEZSbDlxs2bODzz59esqdjx46sX7+e//znP0yfPp1mzZo9mRHGgAEDAJg6dSrdunVjwoQJ1KpVi48++giAtm3bsmvXLipWrIi9vT0rV64EwMrKinnz5tGqVSt0Oh39+vWjWrVqz8Qze/ZsBg4cyPLly7G0tGThwoW0bt2aRYsW4efnh7e3N/Xr13/h686of//+3L17l9q1ayOEwMXFxdB0nNHzrhMaGkrfvn3R69VC5JQpU17q+pIkFQDXrkGHDmrJaOpUNYmRWwJkKyWzMsQzD1IUP9RSkSHhEUJsMV1Yz+fv7y9Onjz51LErV64YRjxyo4YNG7Jz506cnJye+5itW7dy+vRpk+9IrdfrqV27Nps2baKSEeU26dXl9t9LSZJMZNs26NULbGzgl1+gWTNzR5SnKYpySgjxzF/3L5xGrSjKCmAF0BF4N/3fO9keYT42Y8YM7t+/n+VjtFotY8aMMWkcly9fpmLFijRr1kwmL5IkSdlNp4MJE9Rykbc3nD4tkxcTMmYadX0hxDMr6ErGCwgIeOFjOnfubPI4qlatyu3bz21bkiRJkl5VVBT06AF798JHH8G8eWBra+6o8jVjFrILymwLAEmSJEmSgDNnwN9fnSq9ZAksWyaTlxxgzAjMatQkJhxIQZ1WLYQQfiaNTJIkSZJyu9WrYfBgcHaGw4fBiBF3KXsYk8CsAHoCF8Cw/pskSZIkFVypqTB6tLoBY5MmarOuq6u5oypQjElg7gshdpg8EkmSJEnKC8LCoFMnCAqCMWPghx8gi+1oJNMwpgfmqqIo6xVF6a4oSocn/0weWR4zc+ZMqlWrRvXq1enevftTK+yOGjWKw4cPA1CuXDkiIyOfef68efMMa6T827Vr12jSpAk1a9bEx8fHsMaMKZ05cwZFUdi7d+9Tx2NiYujUqRNVqlTBx8eHoKAgQN1YskWLFlSqVIkWLVoQHR1teM6UKVOoWLEi3t7eT53v1KlT+Pr6UrFiRUaMGJHpysKSJEm5yp9/Qu3acP68OuoyfbpMXszEmATGDrX3pSVyGnWmQkNDmTNnDidPnuTixYvodDrDLs6PHj3i2LFjNGrUKMtz9OvXL9OdoUHd0HD06NGcPXuWK1euMHz48Gx/Df+2YcMGGjZsaNgH6YmRI0fSunVrrl69yrlz5wzrnPzwww80a9aMGzdu0KxZM3744QdAnbq9ceNGLl26xJ49exg6dCg6nQ6AIUOGsGTJEm7cuMGNGzfYs2ePyV+XsYQQhoXqJEmSEAJmz4amTaFoUfj7b+jSxdxRmV1QcBBT/pxCUHBQjl/7hQmMEKJvJv+e3UQnj4kNiuXelHvEBsVmy/m0Wi1JSUlotVoeP35s2Ndn8+bNhs0Fn5g2bRr16tWjXr16hm0G7O3tKVeuXKa7Q2s0Gjw8PAy3fX3VPTSTk5Pp27cvvr6+1KpVi4MHDwKwatUqOnToQOvWralUqRKffvopAMuXL2f06NGG8yxdupRPPvnkmesJIdi8eTOrVq0iMDDQMJoUFxfH4cOHDavs2tjYGBbn2759O7179wagd+/ehpVtt2/fTrdu3ShUqBBeXl5UrFiR48ePo9FoiIuLo0GDBiiKQq9evTJdDTchIcHwGv38/Pjtt98ANfnx9/enWrVqTJo0yfD4cuXK8cUXX9CgQQP8/f05ffo0rVq1okKFCixa9M8i0NOmTaNu3br4+fkZnn/37l18fHwYOnQotWvXJjg4+LnX+fzzz6latSp+fn6MHTv2mbglScpHEhPhww9h1Cho21bdTTqTlcMLmqDgIJqtacaEAxNotqZZjicxLxz3UhRlNTBSCBGTfrsYMCO3JjE3Rt0g4WxClo/RxmpJPJ+otiRbgIOfA1aOz38rCtcsTKVZz1/4rXTp0owdO5YyZcpgZ2dHy5YtadmyJQBHjx6lU6dOTz2+aNGiHD9+nDVr1jBq1Ch27twJgL+/P3/++Sf16tV76vGjR4+madOmvPHGG7Rs2ZK+ffvi5OTE/PnzAbhw4QJXr16lZcuWXL9+HYCzZ89y5swZChUqhLe3N8OHD6dbt274+fnx448/Ym1tzcqVK1m8ePEzr+fo0aN4eXlRoUIFmjRpwq5du+jQoQO3b9/GxcWFvn37cu7cOerUqcPs2bNxcHAgIiICd3d3ANzd3Xnw4AGgjk5lXOrfw8OD0NBQrK2tn0rKnhz/t8mTJ+Po6MiFCxcADKWp7777juLFi6PT6WjWrBnnz5/Hz0+dGOfp6UlQUBCjR4+mT58+HD16lOTkZKpVq8bgwYMJDAzkxo0bHD9+HCEE7dq14/Dhw5QpU4Zr166xcuVKFixY8NzreHh4sHXrVq5evYqiKMTExDz3d0OSpDzu1i11YbqLF+Hbb2H8eLAwpniR//18/meStEkApOhSOHT3EA08G+TY9Y35Kfg9SV4AhBDRQC2TRZQDtLHaf+ZT6dNvv4bo6Gi2b9/OnTt3CAsLIzExkbVr1wLq6MmTXaqf6N69u+Hrkx4SAFdXV8LCwp45f9++fbly5QqdO3fm0KFD1K9fn5SUFI4cOULPnj0BqFKlCmXLljUkMM2aNcPR0RFbW1uqVq3KvXv3cHBwoGnTpuzcuZOrV6+SlpZmGM3JaMOGDXTr1g2Abt26GcpIWq2W06dPM2TIEM6cOYODg4OhVPQ8z9sxO6udtDPat28fH3/8seF2sWLFAPj111+pXbs2tWrV4tKlS1y+fNnwmCebQvr6+hIQEECRIkVwcXHB1taWmJgYAgMDCQwMpFatWtSuXZurV69y48YNAMqWLftUwpXZdYoWLYqtrS39+/dny5Yt2NvbZ/keSJKUR+3apa7vEhKifv/llzJ5AeJT4hmxewQLTy5EQcFCsaCQZSGalGuSo3EY03lkoShKsfTEBUVRihv5PLPIaqTkidigWM41O4c+VY+FjQVV11XFscGrb+y4b98+vLy8DIlKhw4d+Ouvv/jwww+xs7N7qqEXnv6gzvh9cnIydnZ2mV6jVKlS9OvXj379+lG9enUuXryYZdNroUKFDN9bWlqi1apJWv/+/fn++++pUqUKffv2feZ5Op2O3377jR07dvDdd98hhCAqKor4+Hg8PDzw8PAwrCzcqVMnQwJTsmRJNBoN7u7uaDQaXNOnE3p4eBAcHGw4f0hICKVKlcLDw4OQkJBnjv+bEOKZxObOnTtMnz6dEydOUKxYMfr06fPUe/zktVtYWDz1PlhYWKDVahFCMH78eAYNGvTUee/evYuDg8MLr2NlZcXx48fZv38/GzduZN68eRw4cCDTn4MkSXmQXg+TJ8PXX0ONGrBlC3h5mTuqXGHn9Z0M/WMoIXEhDKs7jPeqvMeJ0BM0KdckR0dfwLgRmBnAX4qiTFYU5RvgL+BH04ZlWo4NHKmxvwZek72osb/GayUvAGXKlOHYsWM8fvwYIQT79+83NLf6+PgY+lye+OWXXwxfGzT45wd+/fp1qlev/sz59+zZQ1paGgDh4eFERUVRunRpGjVqxLp16wzPvX//Pt7e3lnGGhAQQHBwMOvXrzeMBGW0b98+atSoQXBwMHfv3uXevXt07NiRbdu24ebmhqenJ9euXQNg//79VK2qLtLcrl07w27Yq1ev5r333jMc37hxIykpKdy5c4cbN25Qr1493N3dKVKkCMeOHUMIwZo1awzPyahly5bMmzfPcDs6Opq4uDgcHBxwdHQkIiKC3bt3Z/ma/61Vq1asWLGChAS11BgaGmooeWX0vOskJCQQGxtL27ZtmTVrFmfPnn2p60uSlItFR0O7dvDVV2rfy9GjMnkBwhPC6bKpC+9ueJeihYpytN9R5radS/PyzRn/n/E5nryAESMpQog1iqKcBJqirsLbQQhx+QVPy/UcGzi+duLyREBAAJ06daJ27dpYWVlRq1Ytw1Tnt99+m8WLF9O/f3/D41NSUggICECv1z81y+fo0aNPNYo+ERgYyMiRI7FNX5p62rRpuLm5MXToUAYPHoyvry9WVlasWrXqqRGH5+nSpQtnz541lGMy2rBhA+3bt3/qWMeOHVm4cCE9e/Zk7ty59OjRg9TUVMqXL2+Y+v3555/TpUsXli9fTpkyZdi0aRMA1apVo0uXLlStWhUrKyvmz5+PpaUlAAsXLqRPnz4kJSXRpk0b2rRp80w8EyZM4OOPP6Z69epYWloyadIkOnToQK1atahWrRrly5fnzTfffOFrzqhly5ZcuXLFkDwWLlyYtWvXGuJ6okaNGpleJz4+nvfee4/k5GSEEMycOfOlri9JUi51/jx06AD37ql7GQ0dCpmUtgsSvdCz/PRyPt33KUlpSXz71reMe3McNpY25g4NJa+tveHv7y9Onjz51LErV64YRjxyo4YNG7Jz507DjJ3MnDlzhp9++omff/7Z5PG88847jB49mmZyl1STyu2/l5IkZbB+PfTvD05OsGkTvOQfRvnRtchrDNw5kMP3DtO4bGOWvLuEys6VczwORVFOCSH8/338uSUkRVFOG3HSFz5GghkzZnD//v0sHxMZGcnkyZNNGkdMTAyVK1fGzs5OJi+SJEkAaWnqlgA9ekCdOnDqVIFPXlJ1qUz+32T8FvlxPuI8y95dxsHeB82SvGQlqxKSj6Io57O4XwGypwaTzwUYsblXixYtTB6Hk5OTYZaSJElSgRceDl27qpswjhihrqprbW3uqMwqKDiIAb8P4NLDS3St1pVZrWfhVtjN3GFlKqsEpooRz9dlVyCvK7PZKpJkLnmtNCtJBU5QkLqfUXQ0rF2rjsAUYHEpcYzfN56FJxfiUdSDnd138nblt80dVpaem8AIIe7lZCCvw9bWlqioKJydnWUSI5ndk6nnT5quJUnKRYSARYtg5Ejw9FQTmRo1zB2VWW27uo1hu4YRFh/GiIARfNv0WwrbFDZ3WC+Ua9dzeRlP1hR5+PChuUORJEBNqjOuNCxJUi6QlARDhsDq1dCmDaxbB5nMxiwowuLDGL57OFuubMGvpB9bum6hXul6L35iLpEvEhhra2u85Dx9SZIk6Xnu3lWnSJ85AxMnwqRJBXZVXb3Qs+TUEj7b9xmpulSmNJvCmAZjsLbMW/0/+SKBkSRJkqTnCgyE7t1Bp4MdO+Ddd80dkdlceXiFgTsHcuT+EZp6NWXxO4upWLyiucN6JS9MPxVF6aAoyg1FUWIVRYlTFCVeUZS4nAhOkiRJkl6ZEDBlCrRuDaVKwcmTBTZ5SdGm8NWhr6ixqAaXHlxi5Xsr2ddzX55NXsC4EZgfgXeFEFdMHYwkSZIkZYu4OOjdG7Ztg27dYNkyyLDXWUFy5P4RBv4+kCuRV+hevTuzWs/C1cHV3GG9NmMSmAiZvEiSJEl5xuXL0L493LoFM2eqM44K4AzV2ORYPt/3OYtOLaKsY1l2fbCLNpWe3bIlrzImgTmpKMovwDYg5clBIcQWUwUlSZIkSa9k82bo00cdbdm/Hxo3NndEZrHlyhaG7RpGRGIEn9T/hK/f+jpPTI1+GcYkMEWBx0DLDMcEIBMYSZIkKXfQauGLL2DaNKhfX93PqAAuZRAaF8qw3cPYdnUbNd1qsqP7DvxLPbONUL5gzG7UfXMiEEmSJEl6JQ8fqn0uBw6o67zMnAmFCpk7qhylF3oWnVzE5/s+R6vX8mPzHxlVf1Semxr9Ml6YwCiK4gHMBd5EHXk5AowUQoSYODZJkiRJytqJE9CxIzx4ACtXquWjAubSg0sM+H0AQSFBNC/fnEVvL6JC8QrmDsvkjFnFZyWwAygFlAZ+Tz8mSZIkSeazbBk0bKguSHf0aIFLXpK1yUw8OJFai2txPeo6a95fQ+CHgQUieQHjemBchBAZE5ZViqKMMlE8kiRJkpS1lBQYPhyWLoXmzWHDBihRwtxR5ajD9w4z8PeBXIu6Rk+/nsxoOQMXBxdzh5WjjBmBiVQU5UNFUSzT/30IRJk6MEmSJEl6RnAw/Oc/avIyfjzs2VOgkpfopGgG7BhA41WNSdWlsvfDvaxpv6bAJS9g3AhMP2AeMBO1B+av9GOSJEmSlHMOHoSuXSE5GbZsUdd6KSCEEGy+vJnhu4cT+TiScW+MY1LjSTjYFMzF+cC4WUj3gXY5EIskSZIkPUsImDEDPvsMKleGrVuhShVzR5VjgmODGbprKDuv76S2e21299hNLfda5g7L7J6bwCiK8qkQ4kdFUeaijrw8RQgxwqSRSZIkSVJ8PHz0kbquS8eO6kyjIkXMHVWO0Ol1LDixgC8OfIFe6JnRcgYjAkZgZSH3YYasR2CebB9wMicCkSRJkqSnXLsGHTrA1aswdSqMG1dgtgS4EHGBAb8P4O/Qv2lVoRUL316IVzEvc4eVqzw3gRFC/J7+7WMhxKaM9ymK0tmkUUmSJEkF27Zt0KsX2NhAYCA0a2buiHJEUloSkw9PZtpf0yhmW4x1HdbRvXp3lAKSuL0MY2YhjTfymCRJkiS9Hp0OJkxQG3S9veH06QKTvBy8cxC/RX5MOTKFD/0+5MrHV/jA9wOZvDxHVj0wbYC2QGlFUeZkuKsooDV1YJIkSVIBExUFPXrA3r1q38u8eWBra+6oTO5R0iPGBo5l5dmVVChWgX0999GsfMFI2l5HVj0wYaj9L+2AUxmOxwOjTRmUJEmSVMCcOaP2u4SFwZIlMGCAuSMyOSEEv1z6hZF7RhL1OIrP3/yciY0nYmdtZ+7Q8oSsemDOAecURVknhJAjLpIkSZJprF4NgweDszMcPgwBAeaOyOTuxdxjyB9D2H1zN3VL1SXww0BquNUwd1h5ijFzsW4oipLZNOryJohHkiRJKihSU2H0aFiwAJo0gV9+AVdXc0dlUjq9jjl/z2HCwQkoKMxqNYth9YZhaWFp7tDyHGMSGP8M39sCnYHipglHkiRJKhDCwqBTJwgKgjFj4IcfwCp/r29yNvwsA34fwMmwk7St1JYFbRdQ1qmsucPKs4xZifff+x7NUhTlCDDRNCFJkiRJ+dqff0LnzpCQoI66dOli7ohM6nHaY74+9DUzgmbgbO/Mxo4b6VKti5xd9JpemMAoilI7w00L1BGZgrEMoiRJkpR9hIC5c9URFy8v2L8fqlUzd1Qmte/2PgbtHMTt6Nt8VOsjfmzxI8XtZBEjOxgzXjcjw/da4C6Qv9NlSZIkKXslJsLAgbB+PbRrB2vWgKOjuaMymcjHkYwJHMOac2uoVLwSB3sfpEm5JuYOK18xpoT0Vk4EIkmSJOVTt26pC9NdvAjffgvjx4OFMeuo5j1CCNZdWMfovaOJSY7hy/98yYRGE7C1yv/r2eS0rBay+ySrJwohfsr+cCRJkqR8ZdcudXE6RVG/b93a3BGZzJ3oOwz5Ywh7b+0loHQAS99dim9JX3OHlW9lNQIj+1wkSZKkV6PXw+TJ8PXXUKMG/PYblM+fq29o9VpmHZvFxIMTsbSwZG6buQzxHyKnRptYVgvZfZ2TgUiSJEn5REwM9OwJO3eqXxctAnt7c0dlEqc1pxnw+wBOa07zbuV3md92Pp6OnuYOq0B4YRFSURQPRVG2KoryQFGUCEVRflMUxSMngpMkSZLymPPnwd8f9uxR9zJavTpfJi+JqYmMCxxHvaX1CIsPY1PnTWzvtl0mLznImFlIK4H1qAvYAXyYfqyFqYKSJEmS8qD166F/f3BygkOH4M03zR2RSQTeCmTwzsHcibnDgNoDmNp8KsXsipk7rALHmDZwFyHESiGENv3fKsDFxHFJkiRJeUVamrolQI8eUKcOnDqVL5OXh4kP6bm1J63WtsLG0ob/9fkfS95dIpMXMzFmBCZSUZQPgQ3pt7sD/16dV5IkSSqIwsOha1d1E8YRI2D6dLC2NndU2UoIwc/nf+aTvZ8QlxLHxEYTGf+f8XJqtJkZk8D0A+YBM9NvH00/JkmSJBVkQUHqfkbR0bB2rToCk8/cenSLwX8MZt/tfbzh+QZL3llCNdf8vXpwXmHMQnb3gXY5EIskSZKUFwihziwaORI8PdVEpkYNc0eVrdJ0acw8NpOvDn2FlYUVC9ouYJD/ICyU/LkAX15kzCykHxVFKaooirWiKPsVRXlSUpIkSZIKmqQk6NsXhg6F5s3h5Ml8l7ycDDtJ3aV1+WzfZ7Sq2IorH19hSN0hMnnJZYz5abQUQsQB7wAhQGVgnEmjkiRJknKfu3fV5tzVq2HiRHWdl2L5p4E1ITWBT/Z+QsCyAB4kPmBLly1s7bqV0kVLmzs0KRPG9MA86cZqC2wQQjySW4BLkiQVMIGB0L076HSwYwe8+665I8pWu2/sZsgfQ7gXe48h/kOY0mwKjrb5d7PJ/MCYEZjfFUW5CvgD+xVFcQGSTRuWJEmSlCsIAVOmqHsYlSqllozyUfISkRBB99+603Z9W+yt7TnS9wgL3l4gk5c8wJgm3s8VRZkKxAkhdIqiPAbeM31okiRJklnFxUHv3rBtG3TrBsuWgYODuaPKFkIIVp1dxZjAMSSmJfJ1k6/57M3PKGRVyNyhSUZ6YQKjKIo98DFQBhgIlAK8gZ2mDU2SJEkym8uXoUMHuHkTZs5UZxzlk/aBG1E3GLRzEAfvHqRhmYYseWcJPi4+5g5LeknGbiVwCngj/XYIsAmZwEiSJOVPmzdDnz7qaMv+/dC4sbkjyhZpujSm/TWNb/73DbZWtix+ZzH9a/eXs4teQ2xQLDGHYnBq4oRjg5wtuxmTwFQQQnRVFKU7gBAiSZFdvJIkSfmPVgtffAHTpkH9+rBpE3jkj717/w75mwG/D+DCgwt0qtqJOa3n4F7E3dxh5Wkxh2M41+IcIlVgYWdBjf01cjSJMSbtTFUUxQ4QAIqiVABSTBqVJEmSlLMePoRWrdTkZfBgdTPGfJC8xKfEM2L3CBosb8CjpEds77adTZ03yeTlNWhjtdyfdp8L715ApAoA9Kl6Yg7F5GgcxozATAL2AJ6KoqwD3gT6mDIoSZIkKQedOAEdO8KDB7BypVo+ygd2Xt/J0D+GEhIXwsd1P+a7Zt9RtFBRc4eVZyUHJxMyOwTNEg26eB2Faxcm8WIiQiewsLHAqYlTjsaTZQKjKIoFUAzoANQHFGCkECIyB2KTJEmSTG3ZMvj4Y3B3h6NH1d2k87jwhHBG7B7BpsubqOZSjaP9jtLAs4G5w8qzEs4lEDw9mAcbHyCEwLWzK55jPSlSp0ju7YERQugVRRkmhPgV+COHYpIkSZJMLSUFhg+HpUvVLQE2bIASJcwd1WvRCz3LTy/n032fkpSWxLdvfcu4N8dhY2lj7tDyHCEE0fuiCZ4WTPR/o7FwsKDUx6XwGOWBXTk7w+McGzjmeOLyhDElpP8qijIW+AVIfHJQCPHIZFFJkiRJphMcrJaMTpyA8eNh8mSwtDR3VK/lWuQ1Bu4cyOF7h2lctjFL3l1CZefK5g4rz9Gn6XnwywOCpweTeC4RGzcbvL73otTgUlgXs37xCXKQMQlMv/SvH2c4JoDy2R+OJEmSZFIHD0LXrpCcDFu2QPv25o7otaTqUpl6ZCrf/vkt9tb2LHt3Gf1q9UNOln052jgtmqUaQmaFkBKSgr2PPd7LvSnZoyQWhXLnNHNjVuL1etWTK4rSGpgNWALLhBA//Ov+94DJgB7QAqOEEEde9XqSJEnScwgBM2bAZ59B5cqwdStUqWLuqF5LUHAQA34fwKWHl+harSuzWs/CrbCbucPKU1JCUwiZHULY4jB0cTqcmjhReVFlircpjmKRu5NAY0ZgXomiKJbAfKAF6uJ3JxRF2SGEuJzhYfuBHUIIoSiKH/ArkLf/i5IkScpt4uPho4/UdV06dlRnGhUpYu6oXllcShzj941n4cmFeBT1YGf3nbxd+W1zh5WnJFxIb8xd/wChF7h0dsFzrCdF/fPOLC2TJTBAPeCmEOI2gKIoG1H3UDIkMEKIhAyPdyB9rRlJkiQpm1y7pm4JcPUqTJ0K48bl6S0Btl3dxrBdwwiLD2N4veF82/RbihTKu8lYThJCEHMghvvT7hO9NxoLewtKDU1vzPWye/EJchlTJjClgeAMt0OAgH8/SFGU9sAUwBXINIVWFGUg6j5MlClTJtsDlSRJype2bYNevcDGBgIDoVkzc0f0ysLiwxi+ezhbrmzB19WXLV23UK90PXOHlSfo0/Q83PSQ4OnBJJxJwLqkNV7fpTfmFs9djbkvw6gERlGU0kDZjI8XQhx+0dMyOfbMCIsQYiuwVVGURqj9MM0zecwSYAmAv7+/HKWRJEnKik4HkybBd9+Bvz/89hvk0T/+9ELPklNL+GzfZ6RoU/i+6feMfWMs1pZ594M3p2jjtWiWpTfm3k/Bvoo93su8ce3hiqVt9sw6CwqCXbugbVtokMNL7RizG/VUoCtq6UeXflgAL0pgQgDPDLc9gLDnPVgIcVhRlAqKopSQC+VJkiS9oqgo6NED9u5V+17mzQNbW3NH9UquPLzCwJ0DOXL/CE29mrLo7UVUcq5k7rByvZSwFELmhBC2KAxdrA7HRo5Uml8J57bO2daYK4S6hNDQoWq+PH06HDiQs0mMMSMw7wPeQoiX3f/oBFBJURQvIBToBnyQ8QGKolQEbqU38dYGbICol7yOJEmSBHDmjNrvEhYGS5bAgAHmjuiVpGhTmHJkCt//+T2FbQqz8r2V9K7RW06NfoGEiwmEzAghYl0EQidw6ZjemFsv+xpzU1Lg119hzhw4efKf42lp6vZZuS2BuQ1Y85IbOAohtIqiDAP2ok6jXiGEuKQoyuD0+xcBHYFeiqKkAUlAVyGELBFJkiS9rDVrYNAgcHaGw4ch4JmWwzzhyP0jDPx9IFcir9C9endmtZ6Fq4OrucPKtYQQxByMIXh6MI92P1IbcweVwmO0B3bls68xV6OBRYvUfw8eqDPwx46F+fMhNVVts2rSJNsuZxTlRfmCoii/ATVQpzwbkhghxAjThpY5f39/cTJj2idJklSQpabC6NGwYIH6CfLLL+Ca9z7wY5Nj+Xzf5yw6tYiyjmVZ+PZC2lRqY+6wci29NkNj7ukErF2tKT28NKWHlMbaOfv6g/7+Wx1t+fVXtVT09tswYoS6+4SiqD0whw6pv3qmGn1RFOWUEML/38eNGYHZkf5PkiRJyk3CwqBTJ/VTZMwY+OEHsDLl5FLT2HJlC8N2DSMiMYJP6n/C1299TWGbwuYOK1fSxmvRLE9vzL2Xgp23HZWXVKZkz5LZ1pibkqIuGTRnjrrbRNGiMGyYuudnxYpPP7ZBg5xv3n3CmJV4VyuKYgM82VTimhAizbRhSZIkSVn680/o3BkSEmDjRnV7gDwmNC6UYbuHse3qNmq61WRH9x34l3rmD20JSNGkEDonlLBFYWhjtDj+x5FKcyrh/E72NeZqNLB4sVomiogAb2+1RNSzZ+5c99CYWUhNgNXAXdSp0Z6KovQ2Yhq1JEmSlN2EgLlz1REXLy/Yvx+qVTN3VC9FL/QsOrmIz/d9jlav5cfmPzKq/ig5NToTiZcTCZ4erDbmpglKdChBmXFlKBqQfY25f/+t/kr9+qvajJuxTGSRO7dBAowrIc0AWgohrgEoilIZ2ADUMWVgkiRJ0r8kJsLAgbB+PbRrpzbuOjqaO6qXcunBJQb8PoCgkCCal2/OorcXUaF4BXOHlasIIYj5XwzB04J5tOsRFnYWuA9wx3O0J3YVsqcxNzX1nzLR8eNqmWjoULVMVCmPzFQ3JoGxfpK8AAghriuKItNkSZKknHTrlrpz9MWL8O23MH587v7z+F+Stcl8/+f3/HDkB4oWKsqa99fwod+Hcmp0BnqtnsjfIgmeHkz8yXisXawp93U5Sg0thU0Jm2y5Rnj4P2Wi8HB1X89589QFm3NjmSgrxiQwJxVFWQ78nH67B3DKdCFJkiRJT9m1S12cTlHU71u3NndEL+XwvcMM/H0g16Ku0dOvJzNazsDFwcXcYeUa2gQt4SvCCZkZQvLdZOwq21F5cXpjrl32NOaeOKGOtvzyi1omattWLRO1aJGn8uCnGJPADAE+Bkag9sAcBhaYMihJkiQJ0Oth8mT4+muoUUPdEqB8eXNHZbTopGg+/e+nLDuzDC8nL/Z+uJeWFVqaO6xcIyU8hdC5oYQtDEMbraXom0WpMLMCJdqVyJbG3NRU2LxZTVz+/lsdYRkyRJ1RlFfKRFkxZhZSCvBT+j9JkiQpJ8TEqNM/du5Uvy5aBPb25o7KKEIINl/ezPDdw4l8HMm4N8YxqfEkHGwczB1arpB4JZHgGcFE/JzemNu+BJ5jPXFskD39TBERaplo4cJ/ykRz5kDv3mqvS37x3ARGUZRfhRBdFEW5QOabMPqZNDJJkqSC6vx5dUuAe/fUBoWhQ9XyUR4QHBvM0F1D2Xl9J7Xda7O7x25qudcyd1hmJ4Qg9nAswdODidoZhYWtBe4fueMx2gP7StmTmJ44oc4m+uUXdfSlTRu1TNSyZd4tE2UlqxGYkelf38mJQCRJkiTUGUb9+4OTk7rE6Ztvmjsio+j0OhacWMAXB75AL/TMaDmDEQEjsLLIewvrZSe9Vk/klvTG3BPxWJewptxX6Y25Lq/fmJuaqlYW58yBY8egcGF1R4lhw9SRl/zsub9ZQghN+rdDhRCfZbwvfYfqz559liRJkvRK0tLg009h1ixo2FBdlMPd3dxRGeVCxAUG/D6Av0P/plWFVix8eyFexbzMHZZZ6RJ1aFZqCPkphOQ7ydhVtKPSwkq49XLD0v71G3MjItT9OhcuVBegq1Qpf5aJsmJMatyCZ5OVNpkckyRJkl5FeLi6ku7hw+qY//TpYJ37V6tISkti8uHJTPtrGsVsi7Guwzq6V+9eoKdGp0akEjI3hLAF6Y25DYpSYUZ6Y67l678vp06picrGjeroS+vWsHw5tGqVP8tEWcmqB2YIMBSooCjK+Qx3FQH+MnVgkiRJBUJQkLqfUXQ0rF2rTpfOAw7eOcjAnQO5+egmfWr2YXqL6TjbO5s7LLNJvJpIyE8hhK8JR6QKSrxXAs9xnji+8fqNuWlpaplo7lz46y+1TDRwoFom8vbOhuDzqKxGYNYDu4EpwOcZjscLIR6ZNCpJkqT8Tgh1ZtHIkeDpqSYyNWqYO6oXepT0iLGBY1l5diUVilVgX899NCvfzNxhmYUQgtgjsQRPCybqd7Ux162PG56feGJf+fUbcx88+KdMFBambqQ4axb06ZPnFmA2iax6YGKBWEVRZgOPhBDxAIqiFFEUJUAI8XdOBSlJkpSvJCWpC3KsXq1OFVm3DooVM3dUWRJC8MulXxi5ZyRRj6P4/M3Pmdh4InbW2bO0fV4idIKHWx+qjbl/x2PlbEXZiWUp/XFpbFxfvzH31Cl1tGXDBrVM1KoVLF2qlosKWpkoK8b0wCwEame4nZjJMUmSJMkYd++qU6TPnIGJE2HSpFz/qXQv5h5D/hjC7pu7qVuqLoEfBlLDLfePFmU33WMd4SvDCf4pmOTbydhWsKXS/Eq49Xn9xty0NNi6Ve1vOXoUHBxgwAC1TFSlSja9gHzGmARGEUIY1oERQugVRSnY8+IkSZJeRWAgdO8OOh3s2AHvvmvuiLKk0+uY8/ccJhycgILCrFazGFZvGJYW2bO8fV6R+iCV0HmhhC4IRRulpUhAESr8WIES779+Y+7Dh/+UiUJD1YWWZ86Evn1lmehFjElEbiuKMgJ11AXUxt7bpgtJkiQpnxECfvgBvvwSqlWDLVty/VruZ8PPMuD3AZwMO0nbSm1Z0HYBZZ3KmjusHPX4+mOCZwQTvlptzHVu56yumPum42vPtDpzRh1t2bABUlLUxeYWLVIripYFKz98ZcYkMIOBOcAE1BV59wMDTRmUJElSvhEXpy7OsW0bdOsGy5ap9YFc6nHaY74+9DUzgmbgbO/Mxo4b6VKtS4GZGi2EIO6vOO5Pu0/UjigUGwW33umNud6v15j7pEw0dy4cOaL+Gnz0kVom8vHJphdQgBizF9IDoFsOxCJJkpS/XL6s9rvcvKnWBUaOzNVbAuy7vY9BOwdxO/o2/Wr2Y1rLaRS3K27usHKE0Akit0cSPC2YuGNxWBW3ouyE9Mbckq/XmPvwodqEu2DBP2Win35Sy0ROTtkTf0H0wgRGUZSVZL4XUj+TRCRJkpQfbN6sznd1cID9+6FxY3NH9FyRjyMZEziGNefWUKl4JQ70OsBbXm+ZO6wcoXusI3x1OCE/hZB0Mwnb8rZUmpfemOvwerWcM2fU0Zb169UyUYsWskyUnYwpIe3M8L0t0B4IM004kiRJeZxWC198AdOmQf36sGkTeHiYO6pMCSFYd2Edo/eOJiY5hi8afsGERhMKxNTo1IephM4PJWx+GGmRaRSpV4Sqm6ri0t7ltRpztVq1WjhnDvz5p7qBeL9+apmoatXsi18yroT0W8bbiqJsAPaZLCJJkqS86uFDtc/lwAEYPFhddaxQIXNHlak70XcY8scQ9t7aS0DpAJa+uxTfkr7mDsvkHt94rK6YuyocfbL+n8bchq/XmBsZ+U+ZKCQEvLxgxgw1eZFlItN4lenQlYAy2R2IJElSnnbiBHTsqC6funKlWj7KhbR6LbOOzWLiwYlYWlgyt81chvgPyfdTo2P/iiV4ejCR2yJRrBXcernhMcYDhyqv11B99qxaJlq3Ti0TNW8O8+fD22/LMpGpGdMDE8/TPTDhyI0cJUmS/rF8OQwdqu4effQo1Klj7ogydVpzmgG/D+C05jTvVn6X+W3n4+noae6wTEboBJE7IgmeHkzcX3FYFbOizBdlKD2sNIXcXn1kTKuF7dvVMtHhw2qZqG9ftUxUrVo2vgApS1kmMIo6nlZNCHE/h+KRJEnKO1JSYPhwtXbQvLm6qEeJEuaO6hmJqYl8degrZh6biYuDC5s6b6KjT8d8OzVal5ShMfdGErblbKk4pyLu/dxfqzE3KkqdBT9/PgQHQ7ly6sbh/frl+p0g8qUsExghhFAUZSuQO/+ckCRJMpfgYLVkdOIEjB8PkyfnyppB4K1ABu8czJ2YOwyoPYCpzadSzC5/ftqmRqYSNj+M0HmhamOufxGq/lKVEh1KYGH16ts1nDv3T5koORmaNlVvv/NOrvyRFxjG9MAcUxSlrhDihMmjkSRJygsOHoSuXdVPsy1boH17c0f0jIeJD/kk8BPWnl+Lt7M3/+vzPxqVbWTusEzi8c0MjblJepzfSW/MbfTqjblarbrbw5w58L//gZ2duh7hsGFQvXo2vwDplRiTwLwFDFIU5R7qRo4K6uCMn0kjkyRJym2EUKeWfPYZVK6sLquay3baE0Lw8/mf+WTvJ8SlxDGx0UTG/2c8tla25g4t28UeiyV4WjCRW9XG3JI9S+L5iScOVV+9MfdJmWjBArh/H8qWVWfE9+sHxQvGmn55hjEJTBuTRyFJkpTbJSSon2KbNqmlo5UroUgRc0f1lFuPbjH4j8Hsu72PNzzfYMk7S6jmmr+6SoVeEPV7FPen3SfuaBxWTlaUGZ/emOv+6o2558+rZaG1a9WBtbfegtmz1f02ZZkodzImgflWCNEz4wFFUX4Gej7n8ZIkSfnLtWvqlgBXr8LUqTBuXK7aEiBNl8bMYzP56tBXWFlYsaDtAgb5D8JCefW+j9xGl6Qj4ucIgmcEk3Q9vTF3dkXc+rlhVfhVVgRRy0S//66WiQ4dUstEvXqpZSLf/L8kTp5nzE/9qfRdURRLZFOvJEkFxbZt6qeajQ0EBkKzZuaO6Cknw07Sf0d/zkWc4/0q7zOvzTxKFy1t7rCyTVpUGqELQgmdG0rawzQK1ylM1Y1VKdHx1RtzHz1SZ77Pnw/37kGZMvDjj+rGirJMlHc8N4FRFGU88AVgpyhK3JPDQCqwJAdikyRJMh+dDiZNgu++U9d1+e03tSEil0hITWDiwYnM/ns2JR1KsqXLFtr75L5m4leVdCuJ4JnBhK9QG3OLty2O5zhPnBo7vXJj7oUL/5SJkpKgSRN1j8133wWrVxvEkczouT8yIcQUYIqiKFOEEONzMCZJkiTzioqCHj1g7171z/J588A29zTB7r6xmyF/DOFe7D2G+A9hSrMpONo6mjusbBH3dxzB04N5uOUhiqVCyQ9L4jnGE4dqr9aYq9P9UyY6eFD9MfbsqZaJ/ORUlDzNqM0cFUVxEEIkKoryIVAbmC2EuGfi2CRJknLemTNqv0tYGCxZAgMGmDsig4iECEbtHcXGixvxKeHDkb5HeLPMm+YO67UJvSBqZxTB04OJ/TMWS0dLynxahtLDS1Oo1Ks15kZH/1MmuntXLRNNnarmo87O2Ru/ZB7GJDALgRqKotQAPgWWA2uA3Ls3vCRJ0qtYswYGDVI/4Q4fhoAAc0cEqFOjV51dxZjAMSSmJfJ1k6/57M3PKGSVOzeKNJYuOUNj7rUkCpUpRIWZFXD/yB2rIq9W07l4US0T/fyzWiZq3Fid+d6unSwTmUJQbCybHjygs6srDRxzdhTQmB+nNn1F3vdQR16WK4rS29SBSZIk5ZjUVBg9Wl38o0kT+OUXcHU1d1QA3Ii6waCdgzh49yANyzRkyTtL8HHxMXdYryUtKo2wRWGEzA0hLSKNwrUK47PeB5fOLq/UmKvTwc6dapnowAG1TPThh+ouD7JMZBrxWi3f3rvHtOBgBLAgLIyDNWvmaBJjTAITn97Q+yHQKH0WkrVpw5IkScohYWHQqRMEBcGYMfDDD7niT/U0XRrT/prGN//7BlsrWxa/s5j+tfvn6anRSXeSCPkpBM0KDfrHeoq3KY7nWE+c3nq1xtzoaFixQm1RunsXPD3VH1///rJMZApCCI7FxbFMo+GXBw9I1OsN92mF4FBMTK5LYLoCHwAfCSHCFUUpA0wzbViSJEk54M8/oXNndZG6jRvV7QFygb9D/mbA7wO48OACnap2Yk7rObgXcTd3WK8s7kR6Y+7m9MbcHiXxGONB4eqFX+l8ly79UyZ6/BgaNVI3VXzvvVyRe+Y7UWlp/BwezjKNhkuPH+NgYUE3V1fqFy3KiJs3SdXrsbGwoImTU47G9cIftRAiHPgpw+37qD0wkiRJeZMQ6ifgmDHg5QX790M1869YG58Sz5cHvmTe8XmUKlKK7d220867nbnDeiVCL4jaFUXwtGBiD6uNuZ7jPPEY7kGh0i/fu6PTwR9/qGWi/fvVMlGPHmqZqEYNE7yAAk4vBAdjYlim0bDl4UNShaBekSIsrVyZrq6uFEnPFKs5OHAoJoYmTk65rwdGUZQOwFTAFXUdmCd7IRU1cWySJEnZ7/FjdWbR+vVqZ+eaNZDD/+PNzM7rOxn6x1BC4kL4uO7HfNfsO4oWynv/m9Ul63iw7gHBM4J5fOUxhTwLUeGn9Mbcoi8/PBIT80+Z6M4d8PCAKVPUMlGJEtkff0EXlpLCqvBwlms03E5OxsnKikGlStHf3R2/ws+OmDVwdMzxxOUJY36bfgTeFUJcMXUwkiRJJnXrljpF+sIF+PZbGD8eLMzbUxKeEM6I3SPYdHkT1VyqcbTfURp4NjBrTK8iLTqNsIVhhMxJb8ytWRifdemNudYv/x5fvqwmLatXqznnf/6jrpb7/vuyTJTdtHo9ux89YplGwx9RUeiAJk5OTPbyon2JEtjl0s2gjPk1iJDJiyRJed6uXWrNQVHU71u3Nms4eqFn+enlfLrvUx6nPWbyW5P59M1PsbG0MWtcLyvpbhIhM0PQLNegT9RTrFUxyowrg1PTl2/M1enUH82cObBvHxQq9E+ZqGZN08RfkN1OSmKFRsPK8HDCUlMpaW3NuDJl6OfmRiV7e3OH90LGJDAnFUX5BdgGpDw5KITYYqqgJEmSso1eD5Mnw9dfq80Sv/0G5cubNaRrkdcYuHMgh+8dpnHZxix+ZzHeJbzNGtPLij8Vz/1p93m46SGKhYLrB654jvGksN/LN+bGxKibe8+bB7dvQ+nS8P33aqVPlomyV4pez7bISJaGhbE/JgYLoE3x4sx3d+dtZ2eszTwi+TKMSWCKAo+BlhmOCUAmMJIk5W4xMeq68Tt3ql8XLQIz/mWZqktl6pGpfPvnt9hb27P03aX0q9Uvz0yNFnrBoz2PCJ4WTMyhGCyLWuI5xpPSI0pj6/HyWy1cufJPmSgxERo2VKdBv/8+WMvFOrLVpcRElmk0/BweTpRWS9lChfimXDn6uLnhmYu2yXgZxsxC6psTgUiSJGWrCxegfXt1u+F582DoULV8ZCZBwUEM+H0Alx5eoku1LsxuPRu3wm5mi+dl6FP0RKyPIHh6MI8vP6aQRyEqTK+A+4CXb8zV6/8pE/33v2qZ6IMP1DJRrVomegEFVKJOxy8PHrBMoyEoLg5rReH9EiXo7+5O82LFsDDjfw/ZwZhZSB7AXOBN1JGXI8BIIUSIiWOTJEl6NRs2qNNUHB3h0CF403z7BcWlxDF+33gWnlyIR1EPfu/+O+9Ufsds8byMtOg0whaHETonlFRNKg41HKjycxVcu7q+dGNubOw/ZaJbt9Qy0XffqWUiFxcTvYACSAjBqfh4lmo0bHjwgHidjir29kyvUIGeJUviapO3eqyyYkzqvBJYD3ROv/1h+rEWpgpKkiTplaSlwaefwqxZaj3i11/B3XwLwG27uo1hu4YRFh/G8HrD+bbptxQpVMRs8Rgr+V4yIbNCCFsapjbmtihGldVVKNa82Es35l69qiYtq1apZaI331T7W9q3l2Wi7BSdlsa6iAiWaTScS0zEzsKCLi4u9Hd3501Hx1da6Ti3MyaBcRFCrMxwe5WiKKNMFI8kSdKrCQ9XV9I9fBhGjFCXZjXTJ2RYfBjDdw9ny5Ut+Lr6sqXrFuqVrmeWWF5G/Ol4gqcH8+DXByiKgmv39MbcGi/XmKvXw+7dapkoMBBsbKB7d7VMVKeOiYIvgIQQHI6NZZlGw+aHD0nW66lduDALKlXig5Ilcczn882NeXWRiqJ8CGxIv90diDJdSJIkSS8pKEjdzyg6Wl1f/sMPzRKGXuhZcmoJn+37jBRtCt83/Z6xb4zF2jL3DjUIkd6YOz2YmAMxWBaxxGOUBx4jPbD1fLnmzthYdaRl3jy4eRNKlVKX2xkwINfsjZkvRKSmsjp9af8bSUkUtbSkr5sb/d3dqV0k94/wZRdjEph+wDxgJmoPzF/pxyRJksxLCHVm0ciR6k5+QUFmW1f+ysMrDNw5kCP3j9DUqymL3l5EJedKZonFGPpUtTE3ZEYIiRcTsSltQ/kfy1NqYCmsHF/uL/dr1/4pEyUkwBtvqIlLhw6yTJRddEIQmL7Y3I6oKLRC0NDRkS/LlqWziwv2uXSxOVMyZhbSfSBvbsYhSVL+lZQEQ4aoc3DbtIF166BYsRwPI0Wbwg9HfuD7I9/jYO3AyvdW0rtG71zbc5AWk4ZmsYaQOSGkhqXi4OtAldVVcO3mioWN8Y25ej3s2aNuKbVnj1om6tZNLRP5+5vwBRQw95KTWanRsCI8nOCUFFysrRnl4cFHbm5UcXAwd3hmZcwspNWos45i0m8XA2YIIeQojCRJ5nH3rvrn/ZkzMHEiTJpkli0Bjtw/wsDfB3Il8grdq3dnVutZuDrkzlpJ8n21MVezVIMuQUex5sWosqIKxVq+XGNuXNw/ZaIbN9Qe6cmTYeBAWSbKLql6Pb9HRbE0LIzA6GgAWhYrxk8VKtCuRAls8tBic6ZkzDih35PkBUAIEa0oipytL0mSeQQGqh2hOh3s2AHvvpvjIcQmx/L5vs9ZdGoRZR3LsuuDXbSp1CbH4zBG/Jn0xtxfHgDg2s0Vz7GeFKn5cr0S16+rScvKlWqZqEED+OYbNY/MRzNzzera48cs02hYHR7Ow7Q0PAoV4v/KlqWvmxvl7OzMHV6uY0wCY6EoSjEhRDSAoijFjXyeJElS9hFCXab1yy+hWjXYsgUq5XyPyZYrWxi2axgRiRF8Uv8Tvn7rawrbvPzy+aYkhCA6MJr70+4Tsz8Gy8KWeIxMb8wtY3xjrl4Pe/eqZaLdu9VEpWtXtUxUt64JX0AB8linY/PDhyzTaPgzNhYrReFdZ2f6u7vTqnhxLHNpKTI3MCYRmQH8pSjKZtQm3i7AdyaNSpIkKaO4OOjdG7ZtUxstli2DHK7/h8aFMmz3MLZd3UZNt5rs6L4D/1K5q9lDn6rnwcYHBE8PJvFCIjalbCg/tTzuA92xdjK+mzYuTm0tmjtXLRO5uamjLQMHQsmSJnwBBciZ+HiWaTSsi4ggVqejop0dP5QvT++SJXErVMjc4eUJxjTxrlEU5STQFFCADkKIyyaPTJIkCeDyZbVOcfMmzJypzjjKwb9K9ULPopOL+Hzf52j1Wn5s/iOj6o/KVVOjtbFawpaEETI7hNTQVByqO1BlVRVcu79cY+6NG/+UieLjoX59dQ/Mjh1lmSg7xGm1rE9fbO5UQgKFFIVO6YvNNXZ6+d27CzpjS0HFgUQhxEpFUVwURfESQtwxZWCSJEls3gx9+6obMO7fD40b5+jlLz24xIDfBxAUEkTz8s1Z9PYiKhSvkKMxZCU5OJmQ2SFolmjQxetwauaE9zJvircqbvSHoV6v7kk0Z466R5G19T9lonq5f+29XE8IwV9xcSzTaPj1wQMe6/X4Ojgwp2JFPixZkmJynvkrM2YW0iTAH/BG3ULAGliLujeSJElS9tNq4YsvYNo0dRhg0ybw8Mixyydrk/n+z+/54cgPFC1UlDXvr+FDvw9zzV/ICecS1MbcjQ8QQuDaJb0xt7bxjbnx8f+Uia5fV8tEX30Fgwap30uv52FqKj+nj7ZcefyYwpaW9ChZkgHu7vgXKZJrfpfyMmNGYNoDtYDTAEKIMEVRCs5Sf5Ik5ayHD9U+lwMHYPBgdV+jHOwJOHzvMAN/H8i1qGv09OvJjJYzcHEw/26DQgii/xtN8PRgov8bjWVhS0oPL6025pY1vjH35k21TLRihZrEBASoS+h06iTLRK9LLwT7o6NZptGwNTKSNCGoX7Qoy7296eLiQuF8vrR/TjPm3UwVQghFUQSAoigFe+UcSZJM58QJteHiwQO1EaNPnxy7dHRSNJ/+91OWnVmGl5MXez/cS8sKLXPs+s+jT8vQmHs+ERt3G7ymeFFqUCmsixlXfnhSJpo7Vy0TWVlBly5qmSggwMQvoAAISU5mVXg4y8PDuZucTHErK4aWKkV/d3eqF85dM9TyE2MSmF8VRVkMOCmKMgB1G4Glpg1LkqQCZ/lyGDpUXRnt6NEc2/VPCMHmy5sZvns4kY8jGffGOCY1noSDjXn/VtPGqY25obNDSQlJwb6qPd4rvCn5QUksChnXmBsfD2vWqInLtWvqDKKJE9UykRk36c4X0vR6dqUv7b8rKgo90NTJiSleXrxfogS2BXBp/5yWZQKjqEW6X4AqQBxqH8xEIcR/cyA2SZIKgpQUdShg6VJo3hw2bIASJXLk0sGxwQzdNZSd13dS2702u3vsppa7edfpTA5JJnROKGGLw9DF6XB6y4nKiytTvI3xjbk3b8L8+WqZKC5OXbNl7Vq1TCRn6L6eW0lJLNdoWBkeTnhqKu42Nnxepgz93N2pIBeby1FZJjDppaNtQog6gExaJEnKXsHBasnoxAkYP15dkz4H/nLV6XUsOLGALw58gV7omdFyBiMCRmBlYb4ehYTz6Y25G9Ibczu74jHGg6L+RY16vhCwb586m+iPP9S3sUsXGDFCloleV7JOx9bISJZqNByMicECeDt9sbm2xYtjJZf2Nwtj/ms9pihKXSHECZNHI0lSwXHwoDpfNykJfvtNXeslB1yIuMCA3wfwd+jftKrQioVvL8SrmFeOXPvfhBBE709vzN0bjYWDBaU+LoXHKA/syhn313xCglommjcPrlxR9yP6v/9Ty0SlSpn4BeRzFxMSWKrR8HNEBNFaLV62tnzr5UUfNzdKy6EsszMmgXkLGKQoyj0gEXUxOyGE8DNpZJIk5U9CwIwZ8NlnULkybN0KVaqY/LJJaUlMPjyZaX9No5htMdZ1WEf36t3NMp1Vn6bn4a8PCZ4eTMLZBGzcbPD6Pr0xt7hxjbm3bv1TJoqNVXeA/vln6NxZloleR4JWyy8PH7I0LIy/4+OxURTalyhBf3d3mhYrhoWc/pxrGJPA5M4dyiRJynsSEqBfP3Vdl44d1ZlGRUy/KsPBOwcZuHMgNx/dpE/NPkxvMR1ne2eTX/fftHFaNMs0hMwKISU4BXsfe7yXe1Oyh3GNuUKo6/nNmQM7d6plos6d/ykTyc/WVyOE4ER8PEs1GjY+eECCToePvT0/VahAz5IlKSHnl+dKxmwlcC8nApEkKZ+7dk0tE129ClOnwrhxJv/EfZT0iLGBY1l5diUVilVgX899NCvfzKTXzExKaAohc0LUxtxYHY6NHam8ML0x1+LF70Fiojq6MmeOWiZycYEJE9RlcmSZ6NU9SktjbfpicxcSE7G3sKCrqyv93d1pULSoXGwul5Or6kiSZHrbtkGvXupKaYGB0My0SYQQgl8u/cLIPSOJehzFZ29+xsTGE7G3tjfpdf8t4WJ6Y+76BwidwKWTC55jPSla17jG3Nu31TLR8uVqmahOHXX13K5dZZnoVQkhOBQTwzKNht8ePiRFCPyLFGFR5cp0d3WlqFxsLs+QPylJkkxHp4NJk+C779RP399+g7JlTXrJezH3GPLHEHbf3E3dUnUJ/DCQGm41THrNjIQQxByMIXhaMI/2PMLC3oJSg0vhMdoDO68XN+YKoS5CPGcO/P67Wibq1EktE9WvL8tEryo8JcWw2NzNpCQcLS3p7+5Of3d3auZAGVPKfjKBkSTJNKKioEcP2LsXPvpInSZja/yS9y9Lp9cx5+85TDg4AQWFma1mMrzecCwtcmZBMX2anoeb0xtzTydgXdIar2+9KDXEuMbcJ2WiuXPVDbhdXODLL9UyUenSOfAC8iGdEOxJX2zu98hIdEAjR0cmli1LJxcX7ORic3maMZs5dgCmAq6oM5CezEJ64RiooiitgdmAJbBMCPHDv+7vAXyWfjMBGCKEOPdSr0CSpNznzBm13yUsDJYsgQEDTHq5s+FnGfD7AE6GnaRtpbYsaLuAsk6mHel5QhuvRbNcQ8jMEFLup2BfxZ7KSytT8sOSWNq++APyzp1/ykQxMVC7tlom6tLFpPlevnY3KYkV4eGs0GgITU3FxdqaTzw9+cjdHW/7nC0jSqZjzAjMj8C7QogrL3NiRVEsgflACyAEOKEoyg4hxOUMD7sDNBZCRCuK0gZYAsgllyQpL1uzRl2ExNkZDh826Spqj9Me8/Whr5kRNANne2c2dtxIl2pdcqT5MiUshdC5oYQtCkMbo8WxkSOV5lXC+W3nFzbmCqEugzNnDuzYARYW/5SJGjSQZaJXkarXsz0ykmUaDf+NjgagVfHizHF35x1nZ2zkYnP5jjEJTMTLJi/p6gE3hRC3ARRF2Qi8BxgSGCHEXxkefwzweIXrSJKUG6SmwujRsGABNGkCv/yirqpmIvtu72PQzkHcjr5Nv5r9mNZyGsXtipvsek8kXkokeEYwEWsj1Mbcji54jvGkaMCLG3MTE9Wdn+fMgUuX1B0TvvhCLRN5yP/7vZIriYks12hYHRFBZFoanoUKMalcOfq6uVFGDmHla8YkMCcVRfkF2AakPDkohNjygueVBoIz3A4h69GVj4Ddmd2hKMpAYCBAmTJlXhyxJEk5KyxMHUIICoIxY+CHH9Qtj00g8nEkYwLHsObcGioVr8SBXgd4y+stk1zrCSEEMYdiCJ4ezKNdj7Cws6DUoPQVcyu8uDH37t1/ykTR0VCrlroETrduskz0Kh7rdGxKX2zuaFwcVopCO2dnBri706J4cSzlEFaBYMz/YYoCj4GM+8oL4EUJTGa/QSLTByrKW6gJTMPM7hdCLEEtL+Hv75/pOSRJMoOgIFi1Sl2YLjUVNm5U5/iagBCCdRfWMXrvaGKSY/ii4RdMaDQBO2vTbaCn12ZozD2VgLWrNeUml6P0kNJYO2fdmCsEHDr0T5lIUdS1+0aMgDfekGWiV3E6Pp5lGg3rIiKI0+mobGfHj+XL08vNjZJysbkCx5iF7Pq+4rlDAM8Mtz2AsH8/SFEUP2AZ0EYIEfWK15IkKacdPqzuHp2Wpn4a//yzyZKXO9F3GPLHEPbe2ktA6QCWvrsU35K+JrkWgDZBS/jycIJnBpNyLwW7ynZUXlKZkj1f3Jj7+PE/ZaKLF9VWoM8/hyFDZJnoVcRqtayPiGCpRsOZhARsLSzo7OJCf3d3/uPoKBebK8CMmYXkAcwF3kQdQTkCjBRChLzgqSeASoqieAGhQDfgg3+duwzqSE5PIcT1lw9fkiSzOHRInSaTlqbetrCA+/ez/TJavZZZx2Yx8eBELC0smdtmLkP8h5hsanSKJr0xd2F6Y25DRyrNqYTzOy9uzL13Ty0TLVumlolq1lT3KerWDexMN0iULwkhOBoby1KNhk0PH5Kk11PDwYF5lSrxgasrxayN2y9Kyt+MKSGtBNYDndNvf5h+rEVWTxJCaBVFGQbsRZ1GvUIIcUlRlMHp9y8CJgLOwIL0LForhPB/lRciSVIOePAAxo5VR1vc3NSVdXU69WuTJtl6qdOa0wz4fQCnNad5t/K7zG87H09Hzxc/8RUkXs7QmJsmKNGhBJ5jPXGs75jl84SA//1PHW3Zvl0diOrQAYYPh4YNZZnoZT1MTWV1eDjLNBquJSVRxNKSXiVL0t/dnTpFisjRFukpihBZt5QoinJWCFHzRcdyir+/vzh58qQ5Li1JBZder67nMn68OpVm3Dh1lbVz59TRmCZN1Pm/2SAxNZGvDn3FzGMzcXFwYW6buXT06ZjtH15CCGIPx3J/2n0e/aE25rr1dcNjtAf2FbNeK+TxY1i/Xk1cLlxQy0QDB6plIk/T5Fj5ll4I9kVHs1SjYXtkJGlC8EbRovR3d6eziwuF5dL+BZ6iKKcyG9ww5jcjUlGUD4EN6be7A7JXRZIKijNn1Hm+x4+ricqCBeDjo97XoEG2JS4AgbcCGbxzMHdi7jCg9gCmNp9KMbti2XZ+UBtzI7dEEjw9mPgT8Vi7WFPu63KUGloKmxJZN4Leu6e+/GXL4NEjqFFDnVnUvbssE72skORkw2Jz91JScLayYljp0nzk7k41BwdzhyflAcYkMP2AecBM1B6Yv9KPSZKUn8XFwf/9n7oFQIkSatmoRw+T1EUeJj7kk8BPWHt+Ld7O3vyvz/9oVLZRtl5Dl6hDs0JdMTf5TjJ2leyovKgyJXuVxNLu+T01Qqj9ynPmqHtSglomGjFCloleVppez86oKJZpNOx59Ag90LxYMaZWqMD7JUpQSC42J70EY2Yh3Qfa5UAskiTlBkLAr7+qi9KFh6ujL999B8WydyREvZTg5/M/88neT4hLiWNio4mM/894bK2yb3GUlPAUQueFErYgDG20lqJvFKXCTxUo0a5Elo25SUn/lInOn4fixeHTT9UykVyO6uXcePyY5RoNq8LDiUhLo5SNDePLlKGfuzvl5dCV9Iqem8AoivKpEOJHRVHmksn6LUKIESaNTJKknHfjBgwbBoGB6mpr27ZBvXomudStR7cY/Mdg9t3exxueb7DknSVUc62WbedPvJpIyIwQwteEq4257UvgOcYTxzeybsy9fx8WLlRbfh49Aj8/tWT0wQeyTPQyknU6fktf2v9QTAyWwDvOzvR3d6d18eJYydEW6TVlNQLzZPsA2TErSfldcjJMnQpTpqgzimbPhqFDTbKabpoujZnHZvLVoa+wsrBiQdsFDPIfhIXy+h9oQghij8QSPC2YqN+jsLC1wL2fOx6feGBf6fmNuULAn3+qO0Fv3arebt9enU3UqJEsE72M8wkJLNNoWBsRQbRWS3lbW7738qK3mxulChUyd3hSPvLc/zsJIX5P//axEGJTxvsURemcyVMkScqL/vtfNVm5eVNdiO6nn6BUKZNc6mTYSfrv6M+5iHO8X+V95rWZR+mipV/7vEIneLj1IcHTgok/Ho91CWvKfZXemOvy/MbcpCTYsEEtE507p5aJxo5Vy0Rlc2Yz63whXqtl44MHLNNoOB4fj42i0DF9sbkmTk5YyAxQMgFj/rwaD2wy4pgkSXlJWJja5/Lrr1Cxolo2apHl8k6vLCE1gYkHJzL779mUdCjJli5baO/T/rXPq0vUEb4qnOCfgkm+nYxdRTsqLayEWy83LO2f35gbHPxPmSgqCnx9YelStUxkn/UMaimdEIK/4+JYptGw8cEDEvV6qtnbM6tiRT4sWRJnudicZGJZ9cC0AdoCpRVFmZPhrqKA1tSBSZJkIlqtOhd4wgR1/6KvvoLPPjPZroK7b+xmyB9DuBd7jyH+Q5jSbAqOtln3obxIakQqofNDCZ0fivaRlqINilJhenpjrmXmf+0LAUeOqGWiLVvU2++/r5aJGjeWZSJjRaWlsTYigmUaDRcTE3GwsKCbqyv93d0JKFpULjYn5ZisRmDCUPtf2gGnMhyPB0abMihJkkzk+HF1VtGZM9Cypbr2fcWKJrlUREIEo/aOYuPFjfiU8OFI3yO8WebN1zrn42uPCf4pmPDV4YhUQYn3SuA5LuvG3OTkf8pEZ8+qk6nGjFGrZrJMZBy9EByKiWGpRsOWhw9JFYJ6RYqwpHJlurm6UkQuNieZQVY9MOeAc4qirBNCyBEXScrLoqPhiy9g8WJ1C4BffoHOnU0y7CCEYNXZVYwJHENiWiJfN/maz978jEJWr9bAKYQg9mgswdODidoRhWKj4NbHDc9PPLGv/Px6T0jIP2WiyEioXl39vkcPWSYyliYlhVXh4SzXaLiVnIyTlRWDSpWiv7s7foULmzs8qYDLqoT0qxCiC3BGUZSM06gVQAgh/EwenSRJr0cIWLtW7UyNjFRXX/vmGyha1CSXuxF1g0E7B3Hw7kEalmnIkneW4OPi80rnEjpB5DZ1xdy4Y3FYOVtR9v/KUvrj0ti4Zt6YKwT89Zc62vLbb+rtdu3Ul92kiSwTGUOr17Pn0SOWajT8ERWFDmji5MTXXl50KFECO0vTbKQpSS8rq3G/kelf38mJQCRJymZXrqh1kkOHICAA9uxR13YxgTRdGtP+msY3//sGWytbFr+zmP61+7/S1Gjd4wyNubeSsa1gS6X5lXDr8/zG3ORk2LhRTVzOnAEnJ/jkE/Xllyv3eq+toLiTlMRyjYaV4eGEpaZS0tqasZ6efOTuTiU5ZCXlQlmVkDTp30YCSUIIvaIolYEqwO6cCE6SpFfw+DF8+y1Mnw4ODrBoEQwYACZYOCwoOIifz//M3lt7uR19m44+HZnbZi7uRdxf+lypD1MJnZfemBulpUhAESpMrUCJ95/fmBsaqpaJFi9WB5iqVVO/79FDfelS1lL0eralLza3LzoaC6B18eLMd3fnbWdnrOVic1IuZkzn1WHgP4qiFAP2ozb2dgV6mDIwSZJewc6d6rSau3ehVy+YNg1cXU1yqU2XNtH9t+7ohA4FhR+a/cBnDT976fM8vq425kasjkCfrMe5nbPamPumY6YzWp6UiebOVctEOt0/ZaK33pJlImNcTkxkmUbDmvBworRayhQqxNflytHXzQ1PE81Gk6TsZkwCowghHiuK8hEwN317gTOmDkySpJdw/z6MHKku/e/jo5aNGjc2yaWuRV7juz+/Y+35tYj0XUYsFAv0Qv9S54n9S10xN3J7pNqY2zu9Mdc783JFcrLaezxnDpw+rZaJRo1Sy0ReXq/5ogqARJ2OX9MXm/srLg5rReG9EiUY4O5Os2LFsJSZn5THGJXAKIrSAHXE5aOXeJ4kSaaWlqYu+//VV6DXq1sBfPKJuh1ANrv04BLf/vktv1z8BVsrW7pW68q2a9tI06VhY2lDk3JNXngOoRNE7ogkeFowcUFxWBW3ouyXZSk9rDQ2JTOPOTRUrYItXgwPH0LVqurtDz+UZaIXEUJwKj6eZRoN6x88IF6nw9vOjukVKtCzZElcTfB7Ikk5xZhEZBTqyrtbhRCXFEUpDxw0aVSSJL3Y0aPqmi4XL8I776g1FRN0rJ4NP8u3h7/ltyu/4WDtwKdvfsonDT7B1cGVoOAgDt09RJNyTWjg2eC559Al6QhfHU7ITyEk3UjCtrwtlealN+Y6PNuYKwQcO6aOtmzerJaJ3n1XLRM1bSrLRC8Sk5bGuvTRlrMJCdhZWNAlfWn/Nx0zL81JUl6jCPHMRtOZP1BRiqBOn04wbUhZ8/f3FydPyv0lpQIsMlJdOXfFCvD0VD/l33sv2z/VT4adZPLhyey4toOihYoyot4IRtUfhbO9s9HnSH2YStiCMELnhZIWmUaRukXwHOeJSweXTBtzU1LUMtHcuXDyJDg6Qv/+apmofPnsfHX5jxCCP2NjWabRsOnhQ5L1emoVLswAd3e6u7riJJf2l/IoRVFOCSH8/338hSMwiqL4AmuA4upN5SHQSwhxKfvDlCTpufR6WLkSPv0U4uLUrxMnZnsdJSg4iMmHJ7P75m6K2Rbj6yZfMyJgBE62Tkaf4/HNx4T8FEL4ynC1MfddZzzHeuL4n8z/+g8L+6dM9OCB2sazcKFaJpLrpWUtIjWVNeHhLNNouJ6URFFLS/q6udHf3Z3aRYqYOzxJMhljSkiLgU+EEAcBFEVpAiwF3jBdWJIkPeXCBbVc9Ndf0LCh+ulevXq2XuLwvcNMPjyZfbf34WznzPdNv+fjeh9TtJDxi97FBqkr5kZujUSxVnDr5YbHJx44+DybZAkBf/+tDiBt2qSWid55Ry0TNWsmy0RZ0QnBfx89YplGw/aoKLRC0NDRkS/KlqWTiwsOcrE5qQAwJoFxeJK8AAghDimKIlvnJCknJCSoDbqzZqnTblasgN69s21NFyEEB+8e5Jv/fcP/7v0PVwdXprWYxmD/wRS2efHQR2xQLDEHY8AConZGEXc0DqtiVpT5ogylh5WmkNuz2wekpKgJy5w5cOKEWiYaPhw+/hgqVMiWl5Vv3U9OZmV4OCs0Gu6npFDC2pqRpUvzkbs7PrKjWSpgjElgbiuK8n/Az+m3PwTumC4kSZIQArZuVadGh4SojSA//ADOxvefZH16QeCtQL45/A1/Bf+Fe2F3ZrWaxYA6A7C3Nm7V1Zi/Yjj31jlEqtpHZ+NmQ8U5FXHr64ZV4Wf/16LRqGWiRYvUMlGVKuqm2D17yjJRVtL0en6PimKpRsPeR48AaFGsGNMrVOC9EiWwkYvNSQWUMQlMP+BrYAvqPkiHgb6mDEqSCrQ7d2DYMNi1C/z81K7WN7KnYiuE4I8bf/DN/77hRNgJPIt6Mr/tfPrV6oetlfELmKVoUrg+4LohecECSg0rhcdwj2ce+6RM9Ouvapno7bfVMlHz5rJMlJXrjx+zTKNhdXg4D9LSKG1jw4SyZenn5kY5OztzhydJZvfCBEYIEQ2MUBTFEdALIeJNH5YkFUCpqery/5Mng5UVzJihftJbvf6yS3qhZ9vVbXx7+FvOhJ/By8mLJe8soXfN3thYGr8WiBCCiDUR3Bx1E91jHYq1gtALLGwsKNa0mOFxT8pEc+fC8ePq3pHDhqlloooVX/vl5FtJOh2/PXzIUo2Gw7GxWALvlihBf3d3WhcvLhebk6QMjJmFVBdYARRJvx0L9BNCnDJxbJJUcBw8qM4VvnoVOnZUe148nh3NeFk6vY7Nlzfz7Z/fcvHBRSoWr8jK91bSw7cH1pYvN602+X4y1wdd59GeRzg2dMR7uTdpUWnEHIrBqYkTjg0cCQ//p0wUEQHe3jB/vlomkhNinu9cQgJLw8JYGxFBrE5HBVtbpnh50cfNDbdCz/YRSZJkXAlpOTBUCPEngKIoDYGVgJ8pA5OkAiEiAsaMgXXr1PXwd+2CNm1e+7RavZZfLv7Ct39+y9XIq1QpUYW17dfStXpXrCxebkRH6AWapRpujbuF0Asqzq1I6aGlUSwUgoLgEI64XoaD89UyUVra02Ui2aKRuTitlg3pi82djI+nkKLQ0cWFAe7uNHJywkKOtkhSloz5P1n8k+QFQAhxRFEUWUaSpNeh08GSJTB+vLp79IQJ8MUX8Jq9DWm6NNZdWMd3f37HzUc3qe5anV86/UJHn45YWrz81NqkW0lcG3CNmIMxODVzwnupN3Zeaox//qkmKKmp6mPt7dVBpI8/hkqVXutl5FtCCILi4lim0fDLgwc81uvxdXBgTsWK9ChZkuJysTlJMpoxCcxxRVEWAxsAgboT9SFFUWoDCCFOmzA+Scp/Tp9W13Q5cUJdF3/BArXW8hpSdamsPrua7498z92Yu9R0q8mWLlt4r8p7WCgvPwQidILQeaHc/uI2ipVC5aWVcf/IHUVRSEqCVavgyy//SV4sLGDcOHXGt/SsyNRUfo6IYJlGw+XHj3GwsOCDkiUZ4O5O3SJF5NL+kvQKjElgaqZ/nfSv42+gJjRNszMgScq3YmPh//5PbQpxcVHLRt27v9ZUnGRtMstPL2fq0akExwVTt1Rd5raZy9uV3n7lD8XEq4lc++gacX/FUfzt4lReVBlbD1tiYtRca/ZsdRp01aqQmKgOJtnYQKtWr/wy8iW9EByIjmaZRsPWyEhShSCgSBGWeXvTxcWFItnQnC1JBZkxs5DeyolAJCnfEkKdCj16tNrzMnQofPutujDdK3qc9pglp5bw49Ef0SRoeMPzDZa+u5SWFVq+cuKi1+oJmRHCnUl3sHSwxGetD64fuBIWpjBrnNqYm5AArVvD559Do0bqhouHDkGTJtDg+Xs5FiihKSmsCg9nuUbDneRkillZMaRUKT5yd8dXLngjSdlG/gkgSaZ044aasOzbB3XqwI4dULfuK58uITWBRScXMe2vaTxIfECTck1Y22Etb5V767XKEAnnE7ja7yoJpxIo0bEEledX5na0DV/0h59/VkdZunVTt1+qUeOf5zVoIBMXAK1ez65Hj1iq0bArKgo90NTJie+8vGhfogS2cml/Scp2MoGRJFNIToYpU9TVc21tYd48te/lFT/I4lLimH98PjOCZhCVFEXz8s35v0b/R6OyjV4rTH2qnnvf3+P+d/exKm5F1U1VuePpSrchsG0bFCoEAweqE6W8vF7rUvnSraQklms0rAoPR5OaipuNDZ+VKUM/Nzcq2hu3orEkSa9GJjCSlN327lWn4ty6pfa4zJgB7u6vdKropGjm/D2H2X/PJjo5mjYV2/B/jf6PBp6vP+wRdzKOa/2ukXghEdcPS3L/3Yp0nW/NoUNQrJjapDt8OLi6vval8pVknY5tkZEs1Wg4EBODBdDW2Zn+7u60LV4cazlvXJJyhDEL2dkDY4AyQogBiqJU4v/bu+/wKIvtgePfSQ8J6W1DSahBaUq5iiJi16siiooVLGD5icBVsYAgUrw04YKK0osiqICKBQVRFARUFERBAtIxu5ve6+7O749ZlJKEBBKSwPk8Dw/Z8r7vYTdkT2bOnIEErfWn1R6dEHXJX3+ZOpcPPoCWLWH1arPO+BSk5acxZdMUXvvxNbKLsumR0IPh3YbTKbbTaYfpLHSyf+R+Dk08hE+MD+nPtGHw6gh+fcf0zps8Gfr3l/2Jjvd7bi6zrVbetttJdziI9/NjdHw8D1osNJBmc0KccRUZgZkH/Awc+ZXvMPABIAmMEAAOh5kiGjHCrCseNcoUi5zCh1pyXjKvbniV6Zunk1ucy+3n386Ll71I+5j2Jz+4ArI2ZLHzoZ0UJBaQcYmFFw83Zcckb847D+bNg3vuMSuKhJHrcPBeSgqzrVY2ZWfjrRS3RkTQ32LhytBQaTYnRA2qSALTTGvdWyl1N4DWukBJ0wIhjE2b4PHHYetWszzn9dehWbNKn8aaY2XShkm8uflNCh2F3NXmLoZdNozWUa2rJExnnpO9w/by17S/KAz2ZWJwO77eEEaXLvDRNLj5ZumYe4TWmp9ycphttbI4OZlcp5Pz6tVjcrNm3B8dTYRkeELUChVJYIqVUv6Yni8opZoBRdUalRC1XXq66aI7axbExpppo169Kt3T5XD2YcavH8+sX2bhcDm4p+09DL1sKK0iWlVZqBlfZ7D9wUQcBwv5xKsB0zObcOW/vfjueejaVXaEPiK9pIRF7mZz2/LyqOfhQe+oKPpZLHQJCpJmc0LUMhVJYF4CvgAaKaUWAZcCD1RnUELUWlqbdcXPPGOSmMGD4eWXK71T4f7M/YxbP455W+fh0i76tOvDC5e9QPOwqtuq2ZHt4Of+eyh438pf+DPJ4wLa3BXCj89C27ZVdpk6TWvNt5mZzLZaWZqSQpHWdAwM5K2WLbkrKopgaTYnRK1V7v9OpZQHEArcBlwMKGCQ1jr1DMQmRO2yY4fp6fLtt3DxxaZIt33lalP2pO/hlXWvsHDbQhSKhy58iOe7Pk98SHyVhrp+choZw3ZRr7CID70a4d0vng+f8yS+ai9TZ9mKiljgHm35s6CAYE9P+lksPGyxcKFsmy1EnVBuAqO1dimlBmit3wc+O0MxCVG75OfD6NEwaZIZaZk5Ex5+uFJFI4mpiYxdN5Z3f3sXLw8vHuv4GM9e+iyNghtVWZhaw8r3S0gc9CcX2u1ketZj10MdeGlcEJGRVXaZOsupNV+mpzPbauWTtDQcWtMtOJgRcXH0ioyknjSbE6JOqcj46Gql1DPAe0DekTu11unVFpUQtcUnn5hmKAcOwAMPwIQJVCYb2J68nbHrxrLk9yX4efkx6KJBPHPJM1jqn1pfmNI4HGangpVDU7jt4C7aUYL92jhueTeOoHCpzD1QWMhcq5W5NhuHi4qI9PbmPw0b8rDFQoI0mxOizqpIAvOQ++8njrpPA02rPhwhaomDB2HgQPj4Y2jdGr77Di67rMKHb7VtZcx3Y1j2xzICvAMYcskQnr7kaaICqq4rXH4+zJkDMycUc9vh3fQjheLGgXT4oB2h/zq3p0GKXS5WuJvNrc7IAOC6sDD+17w5N4eH4yNLroSo8yqSwJyntS48+g6llF81xSNEzSopgSlTTGEuwPjxpjmdt3eFDt+ctJnR341mReIKgnyDGHbZMAZfPJiIehFVFmJamtnQ+rVpmrZpyYzz+pN6Xg7iX2pC4+ca4eF97n4478zLY47NxgKbjZSSEhr5+jIiLo4HLRbi/OTHlhBnk4okMBuADhW4T4i6bd0609Nl+3a45RaYOhXi4ip06MZDGxn93WhW/rmSEL8QRl4+koEXDSTUP7TKwjt0yHTJnTUL/PKKGBe9i+akUb9jfVrNbUXA+QFVdq26JN/pZGlKCrOsVtZnZeGlFD3crf2vDQvDU5Y/C3FWKjOBUUrFAA0Af6XUhZgVSABBgEwci7NHSorpnDt/vklYVqwwnd0qYN2BdYz6bhRf7f2KcP9wxl45lgH/GkCQb1CVhbd9uym9efddQGtG/MtGt9//RGVpmrzajIaDGqI8z70P6S05OcyyWllkt5PtdNLC35/xTZvSNyaGaGk2J8RZr7wRmOsw/V4aApOPuj8HGFqNMQlxZrhcpojk+echOxueew6GD4eA8kcytNZ8s/8bRn07im8PfEtUQBQTr5nIY50eI9Cn6jYQ+v57M4P1ySdQrx48c38hPfckUvBdBkHdgkmYnUC9FufW7xJZDgfvupc//5Kbi5+HB7dHRtLfYuGy4GBpNifEOaTMBEZrvQBYoJTqpbVedgZjEqL6/fqrmS7auBG6dYPp002xbjm01qzas4pR341iw6ENWAItTLluCo90fIR63lWTSLhc8PnnJnFZvx7Cw2HkCM3dgUnYR+2lSGtavNGC2MdiUR7nxoe11poN2dnMSkri/ZQUClwu2gcE8HqLFtwTFUVoBeuThBBnl4rUwHyqlLoHiD/6+VrrUdUVlBDVJicHXnoJpk2D0FBYsADuv7/cfvpaaz7b/Rmjvh3FT0k/0TCoIa/f8DoPd3gYP6+qKQwtKYElS0zisn07NG5sQrzn8nwODkwk6dssQq8JpeXMlvjH+1fJNWu7lOJiFrpHW3bm5xPo6cn90dH0t1joWL++jLYIcY6rSALzMZCF2ZFa9kASdZPWsHw5DBoEf/0FjzwC//0vhIWVeYhLu/h458eM/m40W2xbiA+JZ8ZNM+jbvi++XpXfabo0eXlmFuvVV83K7TZtzE4Fd96usb95mO0X70P5KBLmJBDzYMxZ/6Ht0pqvMjKYbbXyUWoqJVrTJSiIuQkJ3BEZSaC09hdCuFXkp0FDrfX11R6JENVl714YMABWrjSt/5cuNVsBlMHpcrJ0x1LGrBvD78m/0zysOXN7zOW+dvfh7Vk10xWpqWbj6tdfN8uiL7vMzGL9+9+QvzOP369IJHtTNuE3hdPyrZb4NqiahKm2OlxYyDybjTlWKweKigj38mJAgwY8bLHQ+iQ1SUKIc1OFllErpdpqrX+r9miEqEpFRTBxIowdC15epr/LgAHm61I4XA7e+/09xqwbw87UnbSKaMU7t75D7za98fKomt/8DxwwS6FnzzaN6Hr0MLXDl1wCrhIXB8cdYv/I/XgGenLeovOIujvqrB11KXG5+CwtjdlWKyvT03EBV4eGMr5ZM3pGROArzeaEEOWoyE/lrsADSql9mCkkBWitdbtqjUyI0/H112bjxcREuOMOk7w0aFDqU0ucJSz6bRFj143lz/Q/aRPVhiW9lnD7+bfj6VE1++P89ptZCr14sSm3ufdes3L7/PPN47m/5rLzoZ3k/pJL5B2RtHitBT7RZ+dS4D/z85ljszHfZsNWXEysjw8vNG7MQxYLTf3PjfoeIcTpq0gCc0O1RyFEVbHZ4OmnTdOUZs3MtNH1pc+AFjuLWbB1Aa+sf4X9mfu5IOYClt25jJ6teuKhqua3//XrYdw4+Owzszp74EDT2LeRew9HV7GLA2MPcPCVg3iFe9F6aWsie519Oy8WOp0sT01lttXKN5mZeAI3upvN3RAWhpeMtgghKumkCYzW+oBSqivQQms9TykVCVRdswshqoLTCW+9BcOGQUEBjBhh+ruU8ht9oaOQuVvmMm79OA5lH6JzbGemXT+Nm1reVCXTNS4XfPqpWVG0YQNERMCoUfDEE8fWDGf/lE3iQ4nk/Z5H9P3RNJ/SHO/ws2tJ8G+5ucy2WnnbbifD4aCJnx9jmzThgZgYYn3P7roeIUT1OmkCo5R6CegEJADzAG/gHeDS6g1NiAravNn0dNm8Ga6+2mwU1LLlCU/LL8ln1s+zmLBhAkk5SVzS6BJm3jyT65pdVyWJS3GxmSKaMAF27ID4eHjtNXjoIdOI7ghngZP9L+3n0KuH8LH40PbTtoTfGH7a168tchwO3ktOZpbVyo85OfgoxW2RkfSzWLgiJASPs7SmRwhxZlVkCulW4ELgFwCtdZJS6tze6lbUDllZZsRl+nSIjjbZQ+/eJ/R0yS3O5a3NbzFxw0SS85K5PO5y3r71ba6Iv6JKEpfcXLM/0eTJcPgwtG0LixbBnXeeWC+cuT6TxIcSKdhdgKW/hWYTm+EVXPeXBmut+TEnh1lJSSxJTibP5eL8evWY0qwZ98fEEC7N5oQQVawiPzmLtdZaKaUBlFKyplHULK1NsvLUU2YfowEDYPRoCA4+5mnZRdm88eMbvLrxVdIK0ri66dUM7zacbnHdqiSMlBQzwvL665CRAZdfDjNnmpKb4/MiR66DfUP38dfrf+EX50f7r9oTelXVbfRYU75IS+ONv/5iR34+ewsLqefhwV1RUfSzWLg4KOisXUElhKh5FUlg3ldKzQBClFL9gYeAWdUblhBlSEw0xSRr1kDnzqY6tmPHY56SWZjJtB+m8b9N/yOjMIMbmt/A8G7D6dKoS5WEsH+/aTw3Z44pt+nZ0yyFLqu1TMaaDBL7JVJ4oJAGTzagydgmeAXW3VGXYpeLz9PSmHL4MN9lZQFmaeKzjRoxLC6OIGk2J4Q4AypSxDtJKXUNkI2pgxmhtV5d7ZEJccTGjbB6tckcFi0yhblvvAGPPgqe/yxzTstPY8qmKbz242tkF2XTI6EHL172Ip0bdK6SMLZtM/UtS5aAhwfcdx8MGQLnnVf68x1ZDvYM2YN1lhX/lv5c8N0FhHQNqZJYzjStNT/l5LDQZmNxcjLpDgeBHh6mpwLgAYR4eUnyIoQ4YypSxNsEWHckaVFK+Sul4rXW+6s7OCHYuBG6dzcVsgDXXQfz50NMzN9PSc5L5tUNrzJ983Ryi3PpdV4vXuz2IhfEXHDal9ca1q0zS6FXroTAQBg82Pxp2LDs49I+SyPx0USKrcU0erYR8SPj8fSvmp4yZ9LBwkLesdtZaLORWFCAn4cHPSMi6BMdTaCnJ9dt20axy4WPhwfdQ0JqOlwhxDmkIr8ufQBcctRtp/u+qvm1VoiyHDgA/fr9k7x4eJhCE3fyYs2xMmnDJN7c/CaFjkJ6t+nNsMuG0SaqzWlf2uWCFSvMUuhNmyAyEsaMMb3xQsspXSlJL+HPwX9if9tOvdb1aPNhG4I6B512PGdSjsPBspQUFtrtrM3MRAPdgoMZ0rgxt0dGEnzUKMua9u1Zm5lJ95AQuhxXgySEENWpIgmMl9a6+MgNrXWxUursbBEqaoeiIlNkMmaMySS8vc3fPj7QvTuHsw8z4fsJzPx5JiWuEu5tey9DLxtKq4hWp33p4mIzSzVhAuzcCU2amNmqBx8staXMMVKWp7Dr/3bhSHMQNyKOuKFxePjWjQZtTq35OiODBTYby1NTKXC5aO7vz8vx8dwXHU2TMv7xXYKDJXERQtSIiiQwKUqpHlrrFQBKqVuA1OoNS5yzVq0yq4p274ZevWDyZDZu/4K1Py8joU13VqUtYN60ebi0iz7t+vDCZS/QPKz5aV82J8esIJoyxWxW3b69Weh0++1lbp30t2J7Mbuf3E3KBykEXhhI+y/bE9i+bvR63J6Xx0KbjXfsdpKKiwnx8qJPdDR9YmLoIquIhBC1WEUSmMeARUqp1923DwP3V19I4px06JBZFr10KbRoAV98Adddx8ZDG7nyl0EUOYvQv67CU3nSr0M/nu/6PPEh8ad92eRkmDbNjLJkZppymzlz4NprT1wKfTytNcmLk9k9cDfOHCdNXmlCo2ca4eFdu0ddkouLWZyczEKbjV9yc/FSihvCwpgaHc1N4eH4eda9Wh0hxLmnIquQ9gAXK6UCAaW1zqn+sMQ5o7jYDHuMGmUqZseONXsZ+fpSUFLA8G+GU+goBECheLrL04y/ZvxpX3bvXjNLNXeumbG69VazFPpf/6rY8UV/FbHr8V2kfZJG0MVBJMxNIOC82tsiqdDp5JO0NBba7axMS8MJdAwMZGrz5twVFUWUj8wKCyHqlgqvedRa51ZnIOIctGaNmS7audM0U5kyBeLj0Vrz4R/LeerLpziQdQBPZUYEfDx96Nmq52ld8tdfTWHue++ZFdh9+pil0AkJFTtea41tno0/n/oTXaxpNrkZDQc2RHnWvqkWrTUbs7NZaLPxXkoKmQ4HsT4+PNOoEffHxNA6oPYmXEIIcTLStEGceX/9ZUZZ3nsPmjY1Ox/eeCMAO1J2MOiLQXy19yvaRLXh6z5f4+flx9r9a+ke3/2UmtFpDWvXmsTlyy+hfn1z+cGDITa24ucpPFBIYv9EMlZnEHx5MAmzE6jXvN7JDzzD9hYU/L30eY+7O+5tkZH0iY7mytBQPKWuRQhxFigzgVFKXay13nQmgxFnuZISU3AyciQ4HPDyy/Dss+DnR1ZhFi9/+zKv/fgagT6BTLt+Go93fhwvD/MteiqJi8sFH31kEpcff4SoKHjlFbPvY2ValmiXJunNJPY+vxeAFtNbEPtoLMqj9iQCWQ4HHyQns9BuZ11WFgq4IiSE4fHx3BYRQX1pMCeEOMuU91NtOtDhTAUiznJr15otAHbsMKMt06ZB06a4tIv5W+bywpoXSMlLoV+Hfoy9ciyRAZGnfKmiInjnHbMUetcuM8jz5pvQt+/Jl0IfL393PokPJ5K1LovQa0NJmJmAX5zfKcdWlRwuF6syMlhos/FxWhqFLhcJ/v680qQJ90ZH09ivdsQphBDVQX4tE9XLajVFJosWQXy86Q53880A/PjXjwz4fAA/Jf1El4Zd+Pyez+kY27H885UjO/ufpdBJSXDhhabtf69eJ18KfTzt1Bz+32H2vbgPDz8PEuYmEPNATK1YVvxrbi4LbTYW2e3YS0oI9/Kin8VCn+hoOtWvXytiFEKI6lbej/WmSqkVZT2ote5RDfGIs4XDYdYmjxgBhYUwfDg8/zzUq4c9184La15g3tZ5xATGsLDnQu5tdy8e6tSWH9vtMHUqTJ8OWVlw5ZVmt4Grrz75UujS5O3IY+dDO8n5IYfwHuG0fLMlvrG+pxRbVbEWFfGue+nztrw8vJXipvBw+kRH8+/wcHw8avfSbSGEqGrlJTApwKunc3Kl1PXAVMATmK21Hnfc462AeZipqmFa60mncz1RS6xfb3ru//YbXH89vPYaNG9OibOE1zdOYeS3IykoKWDIJUN4sduLBPmeWqv9PXtg0iSYN8+sxu7Vy5TUdD7FTS5cJS4OTTjE/lH78azvyXmLzyOqd1SNjWjkO518nJrKQrudVenpuICL6tfnjRYt6B0VRbi3d43EJYQQtUF5CUyu1vrbUz2xUsoTeAO4BtP87iel1Aqt9Y6jnpYODAR6nup1RC1it5sMYuFCaNwYli83y6OVYvWe1Qz6YhB/pP7Bdc2uY+r1U0mIqODa5eNs2WIKcz/4wEwN9e0LzzwDLVueeug5W3NIfDCR3K25RPaOpMW0FvhEnfneKC6tWZeVxUKbjQ9SUshxOmns68sLjRtzf0wMCfVq36onIYSoCeUlMPtO89z/Av7UWu8FUEotAW4B/k5gtNbJQLJS6sbTvJaoSQ4HvPUWvPgi5OfD0KHmT0AA+zL28fSqp/lw54c0DW3Kx3d9zM0tb67UqMbGjfDNN2b58yefwOrVEBRkSmsGDQKL5dRDdxW5ODDmAAfHHcQr3IvWy1sTeeupFxCfqt35+bxtt/O23c7+wkICPT25w730uVtICB5S1yKEEMcoL4F5Ryl1W1kPaq2Xn+TcDYBDR90+DFxUidj+ppR6BHgEoHHjxqdyClFdNm4000Vbt8I115jpooQE8kvyGf/NS0zYMAEP5cHYK8fyVJen8POq3MqYDRvgiiv+2ZA6NBTGjYPHHoPT3UMw+4dsdj60k/wd+UT3jab55OZ4h525aZn0khLedy993pidjQdwdWgoY5o0oWdEBAHS0l8IIcpUXgKzFNjq/gNw9K+AGjhZAlPar4y6ooEdc5DWM4GZAJ06dTqlc4gqlpJiinLnzoUGDcx8Tq9eaGDZjqU8veppDmYd5K42dzHh6gk0Cm5U6Uts2AD33PNP8uLhAf/5j2n5fzqcBU72j9jPocmH8I31pe3nbQm/Ifz0TlpBJS4XK9PTWWiz8UlaGsVa07pePSY0bco90dE08K3ZYmEhhKgryktgegG9gXbAx8BirfWflTj3YeDoT62GQFKlIxS1i9Np1ioPHQq5uabmZfhwCAzk9+TfGfTFIL7e9zXtotvx9q1v0y2uW6UvsX27Of2KFRAWBt7epimdj49ZWXQ6MtdlkvhwIgW7C7A8aqHZhGZ4BVVvNwGtNT/n5LDQbmdxcjKpJSVEenvzfw0a0Cc6mgsCA2XpsxBCVFKZP7m11h8CHyqlAjC1K68qpcIxq4UqUtz7E9BCKdUE+Au4C7inCmIWNeXHH8100c8/m3mdN96A884joyCDkSsH8cZPbxDkG8Qb/36DRzo+8ncX3Yo6dAheegkWLIDAQBgzxrT737bN9MHr3h26VL4hLwCOXAd7n99L0htJ+DXxo/2a9oReGXpqJ6ugw4WFLHIvfd6Rn4+vUvSIiKBvTAzXhobiLUufhRDilFXkE6YQyAKygcZAhYoYtNYOpdQA4EvMMuq5WuvtSqnH3I+/pZSKATYDQYBLKTUYOF9rnV3pf4moPmlp8MILMHs2xMTA4sXQuzdO7WLeL7N5Yc0LpOWn8WjHRxl95Wgi6kVU+vT//S+8/rrZt2jwYDMCE+6e1enS5dQTF4D0r9JJ7JdI0cEiGgxqQNOxTfEMqJ76klyHgw/dS5/XZGSggUuDgpjRsiV3REYSKkufhRCiSpS3F9IVwN2Y1URfAVO11psrc3Kt9efA58fd99ZRX9swU0uiNnK5YM4cU+uSlQVPPWWGSOrXZ+OhjTy58kl+tv5M18ZdmXb9NC60XFip0+flmQZ048eb2ag+fcz2SFVVp+3IcrDnmT1YZ1vxT/DnwvUXEnzJaVb+lsKpNWszM1los7EsJYU8l4smfn6MiIvjvuhomsvSZyGEqHLljcCsAbYB6wFfoI9Sqs+RB7XWA6s5NlGTfv7ZTBf9+CN062ami9q0wZpj5fmPBrDw14XE1o9l0W2LuLvN3ZWq4SgpMbW/I0eCzQY9ephNFlu3rrrwUz9NZddjuyi2FtP4+cbEvRSHp1/Vjrr8kZfHQrudd+x2DhcVEeTpyT3R0fSJjubS4GCpaxFCiGpUXgLzEKe4akjUYenppp/LW2+Z7ZvfeQfuuYdiVwnTNkxi1LejKHQU8vylzzP0sqHU961f4VNrDUuXwrBhsHs3XHqpWbzUtWvVhV+SVsLuQbtJXpRMQNsA2nzUhqBOp9bptzSpxcUsSU5mgd3O5pwcPIHrwsKY1KwZPcLD8Zelz0IIcUaUV8Q7XykVCcRhGtJlnrGoxJnncpkNhJ57ziQxAwea+ZzgYL7880sGfTGIxLREbmxxI1Oum0KL8BaVOv2aNWYmavNmM9KyYgXcdNOp7VVUluSlyex+YjeOdAdxL8URNzQOD5/TL5Qtcrn4LC2NhTYbn6Wn49CaCwIDmdysGXdHRREjS5+FEOKMK68Gph/wCrAHaKKUekRrXebmjqIO27IFnnjCNKW79FIzXdS+PXsz9vKfJX1YkbiC5mHN+fTuT7mxZeWaJv/yi0lcVq82tS3z58N990FVDlQU24vZ9cQuUpelEtgxkPar2xPYLvC0zqm15ofsbBba7SxJTibD4SDGx4fBDRtyf3Q07QJP7/xCCCFOT3lTSIOB1lrrFKVUU2ARIAnM2SQz0/RwmT7dLPmZPx/uv588RwH//fpFJm2YhJeHF+OuGsfgiwfj61XxkYY9e8xM1JIlppfL5Mnw+OPgV7lGvOXSWmNfZOfPQX/izHPSdFxTGj7dEA+vUx912V9QwDt2OwvtdnYXFODv4cGtERH0iYnhqpAQvGTpsxBC1ArlJTDFWusUAK31XqWUjJOfLbSGt982mwmlpppi3dGj0cHBvL/9fZ5Z/QyHsw9zb9t7GX/1eBoENajwqW02GD3a9Lrz8TH1LkOGnH7b/+MVHi5k12O7SP8snaAuQSTMTSCgVcApnSvb4WBZSgoL7XbWZmYCcHlwMM83bsztkZEEeVVvozshhBCVV95P5oZKqWll3ZZVSHXUtm1mumj9erj4Yli5Ejp0YJt9GwMXDOTbA99yQcwFLO61mK6NK15dm50NEyfClClQWAiPPGIGd05no8XSaK2xzrGy5+k96BJN8/81p8GABijPyhXTOLXmq4wMFtpsfJiaSoHLRQt/f0bHx3NfdDTx/v5VG7gQQogqVV4CM+S42z9XZyCimmVlmXXLr71mdkScMwceeID0okxGfD6ANze/SYhfCG/d+Bb9OvTD06NiRSpFRfDmmzB2rBnMufNO00G3ReVqfCukYF8Bif0TyVyTSUj3EBJmJ+DfrHKJxm+5uSy021lkt2MtLibUy4sHYmLoEx3NRUFBsvRZCCHqiPJWIS04k4GIaqI1vPsuPPMM2O3w6KMwdizOkGBm/zKLYV8PI6Mwg8c7Pc6oK0YR5h9WodM6nbBoEYwYAQcOmD2Kxo2Djh2r/p+Q+X0mB8cfJGN1Bh7eHrR8qyWW/haUR8WSDXtxMe+661q25ubipRT/Dgujb0wMN4aH4yt1LUIIUeecdHJfKdUJGIZZTv3387XW7aoxLlEVtm8300XffgudO8Mnn0CnTnx/8Hue/OBJtti20C2uG9Oun0b7mPYVOqXW8PnnZmXR77+bhGX27NPfZLE0xfZi9o3ch3WG1XQk8oBW77Yi8tbIkx5b6HSywr30+Yv0dJxAp/r1mda8OXdFRRHp41P1AQshhDhjKlKduAgznfQb4KrecESVyMkxPVymToWgIJgxA/r1IynPxrPL72PRb4toGNSQJb2WcGfrOys8bbJxo2kTs24dNG8O770Ht98OVTmAoV2ajK8zsM6wkvpRKtpxVC9FBfk788s+Vmu+z8piod3O+8nJZDmdNPDxYUjjxtwfHc35AadW5CuEEKL2qUgCkyL9X+oIreH9982eRUlJ0L8/vPIKRSH1+d+GiYz+bjQlrhKGXTaMF7q+QIBPxT7Qd+wwmyt+/DFER5tV1/36QVXuS1icXIxtvo2kmUkU7inEK8yLBgMbUL9zfRIfSsRV7MLDx4OQ7iEnHLunoIC3bTbettvZW1hIgIcHvSIj6RMTQ/eQEDylrkUIIc46FUlgXlJKzcbsjVR05E6t9fJqi0pU3s6dMGCAaXnboQMsXw4XXcTnuz9n8OLB7E7fTY+EHky+djLNwppV6JSHDpm9GxcsgMBAU5w7eDBU1UCG1prMbzJJmpFE6oep6BJNcLdgmoxqQsRtEX/vXeQX50fmWlO4G9zFrMfOLCnh/ZQUFtpsfJ+djQKuDAlhZHw8t0ZEEChLn4UQ4qxWkZ/yDwKtAG/+mULSgCQwtUFursksJk82mcX06fDII/yZtY/B797EZ7s/o2V4S1beu5Lrm19foVOmpcF//wuvv24GdQYPhhdegIiIqgm5ONWMtlhnWinYXYBXqBcNnmiA5RELAeedmB3tOB/WxkLXYE22u67l49RUirTmvHr1+G+TJtwbHU2jquySJ4QQolarSALTXmvdttojEZWjNSxbBv/5Dxw+DA8+COPGkRtSj7HfvMjkTZPx8fRh4jUTGXjRQHw8T160mp9vymbGjzd9Xfr0MaU0cXFVEa4m67sskmYkkbIsBV2sCbo0iLjhcUTeHomnf+nLtjdmZXHF1q0Ua/33zqLhXl48EhtLn+hoOtavL0ufhRDiHFSRBGaTUup8rfWOao9GVMyuXfDkk7BqFbRvD++9h+7ShcW/L2bIO0NIykmiT/s+jLtqHJb6J+8kV1ICc+eaZMVqhZtvhldegTZtTj/UkrQSbAtMbUtBYgFeIV7EPhZL7COxBLQuey4qx+FgSXIyo/bvp0j/U8h7f3Q0sxMS8JGlz0IIcU6rSALTFeirlNqHqYFRgJZl1DUgP990jJs0yWwqNG0aPP44W1N/58n53Vh/cD0dLR1ZesdSujTqctLTHRnEGTbM5ESXXmpqgLtWvAFvGefVZK13j7YsTUEXaYK6BBE3P47IOyLxrFf6aIvWmh9zcpiVlMSS5GTyXC6a+PrirRQurfHx8ODx2FhJXoQQQlQogalY4YSoPlqbJUCDBsHBg3D//TBxImn1vRj+5UBm/DyDMP8wZt08iwcveLBCXXS//tr0cvnpJ2jd2pz+5pvhdGZjStJLsL9tJ2lGEvl/5OMZ5Imln4XYR2MJbFv27s3pJSW8Y7czy2rl97w86nl4cFdUFP0tFi4KCmJTdjZrMzPpHhJCl6reVEkIIUSddNIERmt94EwEIsrw558wcKDZs6hNG/j2W5xdL2XGzzN48esXyS7KZkDnAYzsPpJQ/9CTnm7LFpO4rFoFjRrBvHkmH/Ks2M4BJ9Bak70h24y2fJCCq9BF/YvqkzAngajeUXgGlD3asjYzk9lWK8tSUijSms716zOjZUvuioo6ZgPFLsHBkrgIIYQ4hqw1ra0KCkxv/vHjzbbOU6bAE0/wXdJGBs7syK/2X7ki/gqmXj+VttEnr7Hes8dsrrh4MYSFwauvmk2oT3XhTkmmGW2xzrSS93senvU9iXkwBssjFupfUL/M42xFRcy32Zhjs/FnQQEhXl70j42ln8VC+8CyR2mEEEKIo0kCUxt9+qkZddm3D+65ByZO5HCgi2dX9GXx74tpHNyYD+74gF7n9TrpChy7HUaPNs14fXxMvcuQIXAqAxpaa7J/yMY6w0rye8m4ClzU71SflrNaEnVXFF6BpX87ObXmy/R0ZlmtfJKaihPoFhzMS3Fx9IqMxP9Uh3+EEEKcsySBqU327TN1Lp98AuefD998Q2HXi5m8cTJj143F6XIyotsInuv6HPW865V7quxsU+s7eTIUFpqmvCNGgOXki5JO4MhyYH/HTtLMJPK25eEZ6En0/dHEPhpL/Q5lj7YcKCxkrtXKXJuNw0VFRHp781SjRjxssZBQr/z4hRBCiPJIAlMbFBbChAmme5ynJ0yciB44kE/3fcl/prdhT8Yebm11K69e+ypNQpuUe6qiInjzTbNYKTUV7rzT9Llr0aJyIWmtyfkph6QZSSQvScaV7yKwQyAtZ7Qk6u4ovOqX/q1T7HKxIjWV2VYrqzIyALg2NJT/NW/OzeHhsoJICCFElZAEpqatXGl6uuzZA717w6RJ7PLPZ/AHPVn550rOiziPVfet4ppm15R7GqcT3n3X1LkcOGB2h/7vf6FTp8qF48h2YF9kaltyt+biEeBB9D3RWB61ENQpqMzjEvPzmW21ssBmI6WkhIa+vgyPi+Mhi4U46ZArhBCiikkCU1MOHDA9+j/6CBISYPVqci67iDHfjWHKpin4e/sz+drJDPjXALw9y941UWv4/HPT6v+338w2SLNmwTXl5zsnyN5salvsi+248lwEtA+gxfQWRN8bjVdQ6d8mBU4nS1NSmGW1si4rCy+luDk8nH4WC9eFhckmikIIIaqNJDBnWlGRWQI0ZoxpujJuHHrwYN7Z+T7Pvt4SW66NBy94kFeueoWYwJhyT7VxIzz3HKxbB82bw5IlcMcdUNFZGkeOg+TFySTNSCL3l1w86nkQdVeUqW3pXHaL/l9zc5mVlMQ7djtZTifN/f0Z17QpfaOjifH1rewrIoQQQlSaJDBn0qpVZsfo3buhVy+YPJlfvFN5ctGVbDi0gc6xnfmo90dc1PCick+zYwcMHWqaz0VHm/0b+/UD77IHao6R80sOSTOTSF6UjDPXSUDbAFq83oLo+6LxCi79WyLb3dp/ltXK5pwcfJWiV2Qk/S0WLg8Jkf2IhBBCnFGSwJwJhw7BU0/B0qWmmvaLL0jp2oEXv36RWb/MIjIgkrk95tL3gr54qLKHTw4dgpEjYf58s/H06NFmFqoi7VMcuQ6SlyRjnWElZ3MOHv4eRPWOwvKIhaCLg0pNQLTWbMrOZrbVypLkZPJdLtoGBDCteXPujY4mrKIZkxBCCFHFJIGpTsXFpgHdqFGmWGXMGBxPDebNbXMZ8fpd5BTlMPjiwbx0+UsE+5XdmCU93RTkvvaaOc2gQWYEJiLi5CHk/ppL0owk7O/YceY4qde6Hs2nNSf6vmi8Q0tPQNJKSnjbZmO21cr2/HwCPDy4Jzqa/hYLnWX3ZyGEELWAJDDVZc0aM120cyf07AlTprCW/Qyc34Xfkn/jqiZXMe2GaZwfeX6Zp8jPN/s1jhtn+rr06WN2jI6LK//Szjwnye+b2pacH3JQvoqoO01tS9AlpY+2uNyt/WdZrSxPSaFYay6qX59ZLVvSOyqK+l7yrSKEEKL2kE+lqvbXX/D00/Dee9C0KXz6KQe7tmXI6iG8v/194kPiWX7ncnq26lnmSIbDAXPnmmQlKclssvjKK2YrpPLk/nbUaEuWk3qt6tFsSjNi+sTgHVb6aIv1SGt/q5U9hYWEennxWGwsD1sstJPW/kIIIWopSWCqSkmJGS4ZOdJ8PXIkhU8PYtIvr/PK63eg0bzc/WWGXDIEf2//Uk+hNSxbZtr979oFl1xi8qCuXcu+rLPAScr7KSTNSCJ7YzbKVxF5eySxj8YS3DW41CTJ4XLxRXo6s61WPk1Lwwl0DwlhVJMm3BoRIa39hRBC1HqSwFSFtWvhiSfM8qAbb0RPncqKkt/5z5wO7Mvcx+3n386kayYRF1L23M8335gl0T/9ZHYR+PhjM/JSVrlJ3vY8M9ryth1HpgP/lv40e7UZMX1j8A4vfbRlf0EBc2w25lmt/FVcTLS3N8+4W/u3kNb+Qggh6hBJYE6H1Wp2Rly0COLjYcUKdnZpwaAv/o9Ve1bROrI1a/qs4comV5Z5ii1bTBO6L7+ERo1g3jy4/36zo8DxnAVOUpa6R1u+z0Z5KyJ7RWJ51ELI5aUvZS52ufg4NZVZVitfuVv7Xx8WxmsWCzeFh+Mtrf2FEELUQZLAnAqHA954w+yOWFgIw4eT/Z//Y9RPk5j65m0EeAcw9fqpPN7p8TK76O7ZY9r+L14MYWFm48UnnoDSuu7n/ZGHdaYV2wIbjgwH/i38aTqxKTF9Y/CJ9Cn1/Dvz8kxrf7ud1JISGvv68lJ8PA/FxNBIWvsLIYSo4ySBqaz16+H//s/07b/uOlzTpvJ2/iaem3MByXnJPHzhw4y9aixRAVGlHm63m/4tM2aYxnNDh8Kzz0LwcauonYVOUpelkjQziazvslDeiohbI4h9NJaQ7iEojxNHW/KdTj5ISWG21cp6d2v/W9yt/a+R1v5CCCHOIpLAVJTdbjKNhQuhcWNYvpyfOjfgyS/68sNfP3Bxw4v55O5P6Nygc6mHZ2ebHQRefdUM2vTvbwZwLJZjn5efmE/SzCQz2pLmwK+pH03HNSXmwRh8okofbdmSk8Msq5VFdjvZTict/f2Z0LQpfWJiiPYp/RghhBCiLpME5mQcDnjrLXjxRdOYZehQkgf1Y+imscydM5eogCgW9FzAfe3uK7WLblGROXzMGEhNNXsVjRkDLVv+8xxXkYuUD1OwzrCSuTYT5aUIvyWc2EdjCb0qtNTRliyHg8V2O7OsVn7JzcXPw4Pb3a39LwsuffWREEIIcbaQBKY8Gzea6aKtW+HqqymZNoXpWWt4ae6F5JXk8XSXpxl++XCCfINOONTphHffNaMs+/fDVVeZhnSdOv3znPzd+VhnWbHNs1GSWoJfvB9NXmlCzIMx+MacuCmi1pqN2dnMslp5393av11AAK+5W/uHSmt/IYQQ5whJYEqTkgLPP2+6yTVoAO+/z5oOoQz68i62p2zn2mbXMvX6qbSKaHXCoVrDypVmZdG2bdChA8ycCddcYx53FbtI/SiVpBlJZH6dCZ4Q0cPUtoReU/poS2pxMW/b7cy2WtmRn0+gpyf3RUfTz2Khk7T2F0IIcQ6SBOaIjRvh668hMxNmz4bcXHj2WQ4M6svT60ew7J1lNA1tysd3fczNLW8uNWnYtMn0cvnuO2jWDJYsMVNGHh5QsKeApFlJZrQluQTfOF+ajGlCzEMx+FpOHG1xac3XGRnMtlr5MDWVYq25OCiIOQkJ3BkZSaC09hdCCHEOk09BMMnLFVeYghWADh0omD+bCWkrGDevIwrFmCvG8PQlT+PndeIS5D/+MKuJPvoIoqNh+nTo1w88cZG6PBXrDCsZX2WAJ4TfZGpbwq4NQ3memAQlFRUxz93af19hIWFeXjweG0s/i4U20tpfCCGEACSBMdauNe3/Ae2h+PDWVjy15lYOZB2gd+veTLxmIo2CG51w2OHDZueAefMgIMAsjx48GDxTCjj0khXrXCsl9hJ8G/kS/3I8loct+DY4cbTF4XKxMj2dWVYrn6Wl4QKuDAlhrLu1v5+09hdCCCGOIQkMQPfubGzixfstSlgfB5ud79LWty1r+67l8vjLT3h6eropyH3tNXC5YNAgeGGICzalsef2JDJWZYCC8Bvdoy3Xlz7asreggLlWK/NsNpKKi4nx8eG5xo15KCaG5tLaXwghhCiTJDDAxoZweR8XJVoD8NTFTzH+mvF4eRz78uTnm/0ax4+HrCzT8n/4I4V4rExid0cbxdZifBr4EDciDsvDFvwanTjdVORy8VFqKrPdrf09gBvCwpgeG8u/w8Kktb8QQghRAZLAAGv3r8WJCwBP5UlEvYhjkheHwyxIevllSEqCm//t4qXr0vH+IonDl6UDEHZDGLFvxRL27zA8vE5MQna4W/svtNlIcziI8/VlVHw8D8bE0FBa+wshhBCVIgkM0D2+O76evhQ7i/Hx9KF7fHfALIlevhyGDYPERLihYyHvXmvFe7WVnM+L8bH4EDcsDks/C35xJyYheU4nHyQnM8tqZUN2Nt5KcUtEBP0tFq4ODcVDlj8LIYQQp0QSGKBLoy6s6bOGtfvX0j2+O10adeGbb0wrmM0/am5vlMZrna14/5yG/gUCrwvD8rqF8JvCSx1t+Tknh9lWK++6W/sn+Psz0d3aP0pa+wshhBCnTRKYIw53gfVd2LUXXl4MP39ZyN1BNsaGWvE6VIRPiQ8xzzfG0s+CfxP/Ew7PcjhY5G42t8Xd2v/OyEj6WSx0ldb+QgghRJWSBAb3jgHds2hdnMkWFFd4ZfGcSkNlQ+g1ocQ+2pzwHuF4eB872qK15vusLGZZrXyQkkKBy8UFgYG80aIF90RFESKt/YUQQohqIQkMsHlhFuOLt+KNRgElXp7EPdMYS38L/k1PHG1JKS5moXu0ZWd+PvU9PekTHU3/2Fg6BAbKaIsQQghRzSSBAS4gk2J38uIE/O5vRNP/xh/zHJfWrMnIYJbVykepqZRozSVBQcxNSODOqCgCpNmcEEIIccZIAgO06xPClnke6GIXnj4etHsw9O/HDhcWMt9mY47Nxv7CQsK9vBjQoAEPWyy0DgiowaiFEEKIc5ckMEBwl2Au/KY9mWszCekeQsBF9fnY3Wzuc3dr/6tCQhjXtCk9IyLwlWZzQgghRI2SBMZtx/mwLLKE5JIkvtqUgbW4GIuPD883bszDFgtN/U+shRFCCCFEzZAEBtiYlcXlW7f+vZXApUFBvNWyJf8OC8NLRluEEEKIWkcSGGBtZiZOd/LiCdwYHk6PiIiaDUoIIYQQZZLhBaB7SAi+Hh54Aj4eHnQPCanpkIQQQghRDhmBAboEB7OmfXvWZmbSPSSELsHBNR2SEEIIIcohCYxbl+BgSVyEEEKIOkKmkIQQQghR50gCI4QQQog6RxIYIYQQQtQ5ksAIIYQQos6RBEYIIYQQdY4kMEIIIYSocySBEUIIIUSdIwmMEEIIIeocSWCEEEIIUedIAiOEEEKIOkcSGCGEEELUOZLACCGEEKLOkQRGCCGEEHWO0lrXdAyVopRKAQ7UdBx1RASQWtNBiFLJe1N7yXtTe8l7UztV9/sSp7WOPP7OOpfAiIpTSm3WWneq6TjEieS9qb3kvam95L2pnWrqfZEpJCGEEELUOZLACCGEEKLOkQTm7DazpgMQZZL3pvaS96b2kvemdqqR90VqYIQQQghR58gIjBBCCCHqHElghBBCCFHnSAJzllFKNVJKfaOU+kMptV0pNaimYxLHUkp5KqW2KKU+relYxD+UUiFKqaVKqZ3u/z9dajomYSil/uP+efa7UmqxUsqvpmM6Vyml5iqlkpVSvx91X5hSarVSarf779AzEYskMGcfB/C01vo84GLgCaXU+TUckzjWIOCPmg5CnGAq8IXWuhXQHnmPagWlVANgINBJa90G8ATuqtmozmnzgeuPu+95YI3WugWwxn272kkCc5bRWlu11r+4v87B/BBuULNRiSOUUg2BG4HZNR2L+IdSKgjoBswB0FoXa60zazQocTQvwF8p5QXUA5JqOJ5zltb6OyD9uLtvARa4v14A9DwTsUgCcxZTSsUDFwI/1HAo4h//A54FXDUchzhWUyAFmOee3putlAqo6aAEaK3/AiYBBwErkKW1XlWzUYnjRGutrWB+iQaizsRFJYE5SymlAoFlwGCtdXZNxyNAKXUTkKy1/rmmYxEn8AI6AG9qrS8E8jhDw+CifO56iluAJkAsEKCUuq9moxK1gSQwZyGllDcmeVmktV5e0/GIv10K9FBK7QeWAFcqpd6p2ZCE22HgsNb6yGjlUkxCI2re1cA+rXWK1roEWA5cUsMxiWPZlVIWAPffyWfiopLAnGWUUgozj/+H1npyTccj/qG1fkFr3VBrHY8pQvxaay2/SdYCWmsbcEgpleC+6ypgRw2GJP5xELhYKVXP/fPtKqTAurZZAfR1f90X+PhMXNTrTFxEnFGXAvcDvymltrrvG6q1/rzmQhKiTngSWKSU8gH2Ag/WcDwC0Fr/oJRaCvyCWWW5BdlSoMYopRYD3YEIpdRh4CVgHPC+UuphTMJ5xxmJRbYSEEIIIURdI1NIQgghhKhzJIERQgghRJ0jCYwQQggh6hxJYIQQQghR50gCI4QQQog6RxIYIaqYUsqplNp61J/4UzhHz+rahFMpFetellraY2uVUp1O8bzdlVKXHHX7MaVUH/fXrdyvxRalVDOl1IZTvMYxr4tSapRS6upTOVdNUUrFK6UKjmpzUN5zZ5/K94H7Gr+X87i/+/0oVkpFVPb8QtQG0gdGiKpXoLW+4DTP0RP4lEo0U1NKeWmtHSd7ntY6Cbj91EMrU3cgF9jgvs5bRz3WE/hYa/2S+/apdlLtyVGvi9Z6xCmep9KUUp5aa2dZt8s5rrT3ZU9Fvke01v0qH+nJaa0LgAvcXaGFqJNkBEaIM0Ap1VEp9a1S6mel1JdHtd3ur5T6SSn1q1Jqmbvb6CVAD2Ci+7fkZkePjCilIo588CilHlBKfaCU+gRYpZQKUErNdZ9zi1LqllJi+fu3c/dv4kuUUtuUUu8B/kc971ql1Eal1C/uawS679+vlHrZff9v7tGVeOAx4D/umC9TSo1USj2jlPo3MBjop5T6xn2O3KOu86z7PL8qpcZV8nWZr5S63X3MVe5/82/u18C3rHhLeU08lVIT3dfcppR61H1/d6XUN0qpdzHNIY+/7aeUmuc+7xal1BWlvS8n+d6IV0rtVEotcF97qVKqnvuxtUqpTkqpOKXUbvd776GUWud+f0qN+7jzt1ZK/eh+zbYppVqUF48QdYUkMEJUvSPD81uVUh8qszfVa8DtWuuOwFxgrPu5y7XWnbXW7THt0R/WWm/AtOYeorW+QGu95yTX6wL01VpfCQzDbFHQGbgC82Ff3q7KjwP5Wut27pg6gkmSgBeBq7XWHYDNwFNHHZfqvv9N4Bmt9X7gLWCKO+Z1R57o7gJ95LErjr64UuoGzKjKRe7XYMKpvC5KKT9gPtBba90WM7r8eFnxlvI6PIzZ5bgz0Bnor5Rq4n7sX8AwrfX5pdx+wv1vbAvcDSxwxwLHvi8nkwDMdL8P2cD/Hf2g1voAMB7zOj4N7HDvyFxe3Ec8Bkx1j/h0wuz7JESdJ1NIQlS9Y6aQlFJtgDbAaqUUgCdgdT/cRik1BggBAoEvT+F6q7XW6e6vr8VsGHnkQ9oPaEzZe8d0A6YBaK23KaW2ue+/GDgf+N4dsw+w8ajjjmwS+jNw2ynEfMTVwDytdb47hiP/jsq+LgmYDf92uW8vwCQX/6tgvNcC7Y6M5gDBQAugGPhRa73vqOcefbsrJjlFa71TKXUAaOl+7Oj35WQOaa2/d3/9DjAQmHT0E7TWs5VSd2ASkgtOEveuow7dCAxTSjXEJIa7KxiTELWaJDBCVD8FbNdadynlsflAT631r0qpBzB1JKVx8M+Iqd9xj+Udd61eWuvESsRX2n4iCvMBfHcZxxS5/3Zyej9HVBnXn0/FXpejz1Oek8WrgCe11sckSkqp7hz7+sKJr3dZjj+uPMe/Bie8Ju5ppYbum4FADmXHHf/3ibR+Vyn1A3Aj8KVSqp/W+utKxCZErSRTSEJUv0QgUinVBUAp5a2Uau1+rD5gdU8z3XvUMTnux47Yj3t6h/ILcL8EnlTuYROl1IUnie27I9d1jxS1c9+/CbhUKdXc/Vg9pVTL0k9RZswVsQp46KiajzD3/RV9XY7YCcQfiRezoem3lYjjS+Bx9/VQSrU8ydTbEUe/fi0xo12VSR6PaHzk+wMzFbW+lOeMBxYBI4BZFY1bKdUU2Ku1noaZgmuHEGcBSWCEqGZa62JM0jFeKfUrsJV/VuEMB34AVmM+hI9YAgxxF4Y2w0wnPK7M8uPylr2OBryBbcoU6o4+SXhvAoHuqaNngR/dMacADwCL3Y9tAk4ofj3OJ8Ct7tqfy07yXNzX+QLzobpZmWXFR6a+Kvq6HDlPIWb36A+UUr8BLky9SEXNxqxs+sX9us2gYiNL0wFP9zXfAx7QWhed5JjS/AH0db/WYZj35W9KqcsxNS7jtdaLgGKl1IMVjLs38Lv79W0FLDyF+ISodWQ3aiGEOIPc0zufaq3blHb7DMeyH+iktU4909cW4nTJCIwQQpxZTiBYVaCRXXVR7kZ2mNE6V03FIcTpkBEYIYQQQtQ5MgIjhBBCiDpHEhghhBBC1DmSwAghhBCizpEERgghhBB1jiQwQgghhKhz/h9p2Rzpa3WpRAAAAABJRU5ErkJggg==\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "mpmt_pos_res_4 = np.array([np.percentile(e, 68) for e in centre_errors_4.values()])\n", + "mpmt_pos_res_6a = np.array([np.percentile(e, 68) for e in centre_errors_6a.values()])\n", + "mpmt_pos_res_6b = np.array([np.percentile(e, 68) for e in centre_errors_6b.values()])\n", + "mpmt_pos_res_8a = np.array([np.percentile(e, 68) for e in centre_errors_8a.values()])\n", + "mpmt_pos_res_8b = np.array([np.percentile(e, 68) for e in centre_errors_8b.values()])\n", + "mpmt_pos_res_4_a7r = np.array([np.percentile(e, 68) for e in centre_errors_4_a7r.values()])\n", + "mpmt_pos_res_6a_a7r = np.array([np.percentile(e, 68) for e in centre_errors_6a_a7r.values()])\n", + "mpmt_pos_res_6b_a7r = np.array([np.percentile(e, 68) for e in centre_errors_6b_a7r.values()])\n", + "mpmt_pos_res_8a_a7r = np.array([np.percentile(e, 68) for e in centre_errors_8a_a7r.values()])\n", + "mpmt_pos_res_8b_a7r = np.array([np.percentile(e, 68) for e in centre_errors_8b_a7r.values()])\n", + "fig_mpmt_pos_a6000, ax_mpmt_pos_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_pos_a7r, ax_mpmt_pos_a7r = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "mpmt_dir_res_4 = np.array([np.percentile(e, 68) for e in orientation_errors_4.values()])\n", + "mpmt_dir_res_6a = np.array([np.percentile(e, 68) for e in orientation_errors_6a.values()])\n", + "mpmt_dir_res_6b = np.array([np.percentile(e, 68) for e in orientation_errors_6b.values()])\n", + "mpmt_dir_res_8a = np.array([np.percentile(e, 68) for e in orientation_errors_8a.values()])\n", + "mpmt_dir_res_8b = np.array([np.percentile(e, 68) for e in orientation_errors_8b.values()])\n", + "mpmt_dir_res_4_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_4_a7r.values()])\n", + "mpmt_dir_res_6a_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_6a_a7r.values()])\n", + "mpmt_dir_res_6b_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_6b_a7r.values()])\n", + "mpmt_dir_res_8a_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_8a_a7r.values()])\n", + "mpmt_dir_res_8b_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_8b_a7r.values()])\n", + "fig_mpmt_dir_a6000, ax_mpmt_dir_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_dir_a7r, ax_mpmt_dir_a7r = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_dir, ax_mpmt_dir = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.2" + }, + "pycharm": { + "stem_cell": { + "cell_type": "raw", + "metadata": { + "collapsed": false + }, + "source": [] + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/WCTE_16c_led_simulation.ipynb b/WCTE_16c_led_simulation.ipynb new file mode 100644 index 0000000..61695e7 --- /dev/null +++ b/WCTE_16c_led_simulation.ipynb @@ -0,0 +1,3415 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from scipy import linalg\n", + "from scipy.spatial.transform import Rotation as R\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.collections\n", + "import matplotlib.patches\n", + "import pg_fitter_tools as fit\n", + "import sk_geo_tools as geo\n", + "import cv2\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "#%matplotlib notebook\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def get_led_positions(led_count, mpmt_locations):\n", + " led_ring_radius = 24.\n", + " led_positions = {}\n", + " for k, v in mpmt_locations.items():\n", + " for i in range(led_count):\n", + " if abs(v[1]) > 160:\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count),0,np.cos(i*2*np.pi/led_count)])\n", + " else:\n", + " phi = np.arctan2(v[2], v[0])\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count)*np.sin(phi), np.cos(i*2*np.pi/led_count), -np.sin(i*2*np.pi/led_count)*np.cos(phi)])\n", + " return led_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def get_image_feature_locations(feature_positions, camera_matrix, distortion, camera_rotations, camera_translations, image_size):\n", + " image_feature_locations = {\n", + " i : {list(feature_positions.keys())[f]:v for f, v in enumerate(cv2.projectPoints(np.array(list(feature_positions.values())), r, t, camera_matrix, distortion)[0].reshape((-1,2)))\n", + " if v[0] > 0 and v[0] < image_size[0] and v[1] > 0 and v[1] < image_size[1]}\n", + " for i, (r, t) in enumerate(zip(camera_rotations, camera_translations))}\n", + " feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + " print(\"Feature in image counts:\", Counter(feature_counts.values()))\n", + " return image_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def get_smeared_feature_locations(image_feature_locations, pixel_error, image_size):\n", + " smeared_feature_locations = {}\n", + " for k, i in image_feature_locations.items():\n", + " smeared_feature_locations[k] = {}\n", + " for j, f in i.items():\n", + " smeared = np.random.normal(f, pixel_error)\n", + " if(smeared[0] > 0 and smeared[0] < image_size[0] and smeared[1] > 0 and smeared[1] < image_size[1]):\n", + " smeared_feature_locations[k][j] = smeared\n", + " smeared_feature_counts = Counter([f for i in smeared_feature_locations.values() for f in i.keys()])\n", + " print(\"Smeared feature in image counts:\", Counter(smeared_feature_counts.values()))\n", + " return smeared_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_led_simulation(feature_positions, image_feature_locations, focal_length, principle_point, radial_distortion, seed_error=1):\n", + " seed_feature_positions = {}\n", + " for i, f in feature_positions.items():\n", + " seed_feature_positions[i] = np.random.normal(f, seed_error)\n", + " fitter = fit.PhotogrammetryFitter(image_feature_locations, seed_feature_positions, focal_length, principle_point, radial_distortion)\n", + " return fitter" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_images(image_feature_locations, image_size):\n", + " for i in image_feature_locations.values():\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.rint(np.stack(list(i.values())))\n", + " ax.scatter(coords[:,0], -coords[:,1], marker='s', s=0.2)\n", + " ax.set_xlim((0, image_size[0]))\n", + " ax.set_ylim((-image_size[1], 0))\n", + " ax.axes.xaxis.set_visible(False)\n", + " ax.axes.yaxis.set_visible(False)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def run_led_fit(fitter, led_positions):\n", + " reco_cam_rotations, reco_cam_translations, reprojected_points = fitter.estimate_camera_poses()\n", + " reco_cam_rotations, reco_cam_translations, reco_locations = fitter.bundle_adjustment(reco_cam_rotations, reco_cam_translations)\n", + " \n", + " reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_locations)\n", + " print(\"mean reconstruction error:\", linalg.norm(reco_errors, axis=1).mean())\n", + " print(\"max reconstruction error:\", linalg.norm(reco_errors, axis=1).max())\n", + "\n", + " reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(reco_cam_rotations, reco_cam_translations)\n", + " cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + " cam_positions_translated = reco_cam_positions - translation\n", + " cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + " reco_led_positions = reco_positions_dict(reco_transformed, fitter.feature_index)\n", + " position_errors = linalg.norm(reco_errors, axis=1)\n", + "\n", + " return reco_led_positions, position_errors" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def reco_positions_dict(reco_positions, feature_index):\n", + " return {f: reco_positions[i] for f, i in feature_index.items()}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_centre_errors(reco_led_positions, mpmt_positions, led_count):\n", + " reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n", + " for k in mpmt_positions.keys()}\n", + " errors = np.array([linalg.norm(reco_mpmt_positions[k] - mpmt_positions[k]) for k in mpmt_positions.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_coun):\n", + " reco_orientations = {}\n", + " for k in mpmt_orientations.keys():\n", + " c, n = geo.fit_plane(np.array([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)]))\n", + " # flip normal if it is directed away from tank centre\n", + " if np.dot(n,c) > 0:\n", + " n = -n\n", + " reco_orientations[k] = n\n", + " errors = np.array([np.degrees(np.arccos(np.dot(reco_orientations[k], mpmt_orientations[k]))) for k in mpmt_orientations.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def make_fig(title=None, xlabel=None, ylabel=None, figsize=(8,6)):\n", + " fig, ax = plt.subplots(figsize=figsize)\n", + " ax.set_title(title)\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " fig.tight_layout()\n", + " return fig, ax" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_geometry(led_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter([l[0] for l in led_positions.values()], [l[2] for l in led_positions.values()], [l[1] for l in led_positions.values()], marker='*', label=\"LED\", s=10)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_reconstruction(reco_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter(reco_positions[:,0], reco_positions[:,2], reco_positions[:,1], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "pmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16c_PMT_locations.txt\", delimiter=\" \")\n", + "#mpmt_locations = {k: v for k, v in pmt_locations.items() if int(k)%19==0}\n", + "mpmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16c_centrePMT_locations.txt\", delimiter=\" \")\n", + "mpmt_orientations = {k: np.array((0,-1,0)) if v[1]>150\n", + " else np.array((0,1,0)) if v[1]<-150\n", + " else np.array((-v[0],0,-v[2]))/np.sqrt(v[0]**2+v[2]**2)\n", + " for k, v in mpmt_locations.items()}\n", + "led_count = 12\n", + "led_positions = get_led_positions(led_count, mpmt_locations)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony A6000" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "focal_length = np.array([2925.84685880484, 2930.0351899542])\n", + "principle_point = np.array([3000, 2000])\n", + "radial_distortion = np.array([-0.251288719187471, 0.0622370807856553])#[-0.28009, 0.11246, -0.02736])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([6000, 4000])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)]])\n", + "camera_directions = [[-1, -1.8, -1],\n", + " [ 1, -1.8, 1],\n", + " [ 1, 1.8, -1],\n", + " [-1, 1.8, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1464\n", + "Number of features in more than one image: 1464\n", + "Feature in image counts: Counter({2: 680, 4: 584, 3: 200})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 13.883385636764606 max: 114.65356241858672\n", + "image 1 reprojection errors: average: 13.713662562824632 max: 132.52230212294577\n", + "image 2 reprojection errors: average: 14.066902502714576 max: 137.72565330474978\n", + "image 3 reprojection errors: average: 13.919607854024123 max: 303.11279610030897\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.7286e+05 1.40e+06 \n", + " 1 2 2.6866e+03 7.70e+05 6.97e+01 1.54e+05 \n", + " 2 3 1.3147e+03 1.37e+03 7.39e-01 3.49e+03 \n", + " 3 4 1.3084e+03 6.22e+00 4.98e-01 8.03e+02 \n", + " 4 5 1.3072e+03 1.20e+00 5.38e-02 9.28e+01 \n", + " 5 6 1.3071e+03 1.06e-01 8.47e-03 1.65e+01 \n", + " 6 7 1.3071e+03 5.05e-02 6.30e-03 2.37e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 7.7286e+05, final cost 1.3071e+03, first-order optimality 2.37e+01.\n", + "mean reprojection error: 0.6392578043382984\n", + "max reprojection error: 2.56533518539307\n", + "mean reconstruction error: 0.1190688526480074\n", + "max reconstruction error: 0.5306016190654083\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 14.36925881990482 max: 103.76676434611505\n", + "image 1 reprojection errors: average: 13.694895095369638 max: 147.19632272808684\n", + "image 2 reprojection errors: average: 14.255586224366864 max: 154.52827868291894\n", + "image 3 reprojection errors: average: 14.402039121180508 max: 283.40543365185306\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.6647e+05 4.14e+06 \n", + " 1 2 1.4074e+04 7.52e+05 7.10e+01 2.44e+05 \n", + " 2 3 1.2307e+04 1.77e+03 7.64e-01 7.08e+03 \n", + " 3 4 1.2291e+04 1.67e+01 5.32e-01 1.84e+03 \n", + " 4 5 1.2285e+04 5.43e+00 8.91e-02 1.38e+02 \n", + " 5 6 1.2284e+04 8.78e-01 3.19e-02 5.64e+01 \n", + " 6 7 1.2284e+04 5.29e-01 1.58e-02 4.16e+01 \n", + " 7 8 1.2283e+04 3.65e-01 1.59e-02 4.27e+01 \n", + " 8 9 1.2283e+04 4.22e-01 1.57e-02 4.96e+01 \n", + " 9 10 1.2283e+04 3.46e-01 1.35e-02 3.56e+01 \n", + " 10 11 1.2282e+04 3.06e-01 1.23e-02 4.62e+01 \n", + " 11 12 1.2282e+04 3.19e-01 1.34e-02 3.76e+01 \n", + " 12 13 1.2282e+04 2.87e-01 1.12e-02 4.57e+01 \n", + " 13 14 1.2281e+04 3.05e-01 1.38e-02 3.96e+01 \n", + " 14 15 1.2281e+04 2.78e-01 1.04e-02 4.37e+01 \n", + " 15 16 1.2281e+04 3.10e-01 1.52e-02 4.72e+01 \n", + " 16 17 1.2281e+04 2.01e-01 6.43e-03 1.92e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 17, initial cost 7.6647e+05, final cost 1.2281e+04, first-order optimality 1.92e+01.\n", + "mean reprojection error: 1.9580852532917954\n", + "max reprojection error: 7.956843795703266\n", + "mean reconstruction error: 0.34158658199936864\n", + "max reconstruction error: 1.6336601724472413\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 15.042639687030883 max: 144.89514178273947\n", + "image 1 reprojection errors: average: 15.175912112787069 max: 110.24093393656742\n", + "image 2 reprojection errors: average: 15.38389189016894 max: 219.02711553402986\n", + "image 3 reprojection errors: average: 15.115226187792024 max: 247.1464281779609\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 8.6401e+05 3.30e+06 \n", + " 1 2 3.5556e+04 8.28e+05 7.40e+01 6.92e+04 \n", + " 2 3 3.4520e+04 1.04e+03 1.14e+00 1.94e+03 \n", + " 3 4 3.4468e+04 5.14e+01 1.12e+00 1.67e+03 \n", + " 4 5 3.4443e+04 2.52e+01 2.81e-01 3.19e+02 \n", + " 5 6 3.4440e+04 3.09e+00 7.73e-02 1.45e+02 \n", + " 6 7 3.4438e+04 2.50e+00 5.96e-02 1.46e+02 \n", + " 7 8 3.4436e+04 1.76e+00 4.37e-02 1.23e+02 \n", + " 8 9 3.4435e+04 7.90e-01 1.49e-02 6.92e+01 \n", + " 9 10 3.4434e+04 5.39e-01 1.58e-02 8.79e+01 \n", + " 10 11 3.4434e+04 5.17e-01 1.17e-02 6.43e+01 \n", + " 11 12 3.4433e+04 5.11e-01 1.54e-02 8.64e+01 \n", + " 12 13 3.4433e+04 4.77e-01 1.08e-02 5.73e+01 \n", + " 13 14 3.4432e+04 4.62e-01 1.45e-02 8.55e+01 \n", + " 14 15 3.4432e+04 4.59e-01 1.05e-02 5.83e+01 \n", + " 15 16 3.4432e+04 4.46e-01 1.40e-02 8.71e+01 \n", + " 16 17 3.4431e+04 4.40e-01 1.01e-02 6.04e+01 \n", + " 17 18 3.4431e+04 4.30e-01 1.35e-02 9.23e+01 \n", + " 18 19 3.4430e+04 4.23e-01 9.65e-03 6.38e+01 \n", + " 19 20 3.4430e+04 4.18e-01 1.30e-02 1.07e+02 \n", + " 20 21 3.4429e+04 4.50e-01 1.04e-02 7.48e+01 \n", + " 21 22 3.4429e+04 3.93e-01 1.15e-02 1.02e+02 \n", + " 22 23 3.4429e+04 3.89e-01 9.47e-03 8.39e+01 \n", + " 23 24 3.4428e+04 3.89e-01 1.14e-02 1.11e+02 \n", + " 24 25 3.4428e+04 3.85e-01 9.30e-03 8.67e+01 \n", + " 25 26 3.4427e+04 3.84e-01 1.13e-02 1.12e+02 \n", + " 26 27 3.4427e+04 3.79e-01 9.16e-03 8.59e+01 \n", + " 27 28 3.4427e+04 3.75e-01 1.12e-02 1.11e+02 \n", + " 28 29 3.4426e+04 3.70e-01 9.03e-03 8.42e+01 \n", + " 29 30 3.4426e+04 3.66e-01 1.10e-02 1.09e+02 \n", + " 30 31 3.4426e+04 3.60e-01 8.89e-03 8.23e+01 \n", + " 31 32 3.4425e+04 3.57e-01 1.09e-02 1.08e+02 \n", + " 32 33 3.4425e+04 3.52e-01 8.77e-03 8.07e+01 \n", + " 33 34 3.4425e+04 3.49e-01 1.08e-02 1.06e+02 \n", + " 34 35 3.4424e+04 3.44e-01 8.66e-03 7.90e+01 \n", + " 35 36 3.4424e+04 3.40e-01 1.07e-02 1.04e+02 \n", + " 36 37 3.4424e+04 3.36e-01 8.56e-03 7.75e+01 \n", + " 37 38 3.4423e+04 3.34e-01 1.06e-02 1.03e+02 \n", + " 38 39 3.4423e+04 3.29e-01 8.46e-03 7.59e+01 \n", + " 39 40 3.4423e+04 3.27e-01 1.05e-02 1.01e+02 \n", + " 40 41 3.4422e+04 3.23e-01 8.38e-03 7.43e+01 \n", + " 41 42 3.4422e+04 3.20e-01 1.05e-02 9.97e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 42 43 3.4422e+04 3.17e-01 8.30e-03 7.28e+01 \n", + " 43 44 3.4421e+04 3.14e-01 1.04e-02 9.82e+01 \n", + " 44 45 3.4421e+04 3.11e-01 8.22e-03 7.14e+01 \n", + " 45 46 3.4421e+04 3.08e-01 1.03e-02 9.67e+01 \n", + " 46 47 3.4420e+04 3.05e-01 8.15e-03 7.00e+01 \n", + " 47 48 3.4420e+04 3.02e-01 1.03e-02 9.55e+01 \n", + " 48 49 3.4420e+04 2.99e-01 8.08e-03 6.86e+01 \n", + " 49 50 3.4420e+04 2.42e-01 7.90e-03 8.73e+01 \n", + " 50 51 3.4419e+04 2.87e-01 8.68e-03 9.00e+01 \n", + " 51 52 3.4419e+04 2.85e-01 8.47e-03 8.58e+01 \n", + " 52 53 3.4419e+04 2.82e-01 8.62e-03 8.83e+01 \n", + " 53 54 3.4418e+04 2.79e-01 8.41e-03 8.43e+01 \n", + " 54 55 3.4418e+04 2.77e-01 8.56e-03 8.65e+01 \n", + " 55 56 3.4418e+04 2.74e-01 8.35e-03 8.29e+01 \n", + " 56 57 3.4418e+04 1.71e-01 4.47e-03 6.49e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 57, initial cost 8.6401e+05, final cost 3.4418e+04, first-order optimality 6.49e+01.\n", + "mean reprojection error: 3.2722951530862043\n", + "max reprojection error: 14.190425769322397\n", + "mean reconstruction error: 0.5786112193562779\n", + "max reconstruction error: 2.76880691795907\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 17.09512975652156 max: 120.87241518847067\n", + "image 1 reprojection errors: average: 16.921944023267525 max: 108.74584660267507\n", + "image 2 reprojection errors: average: 18.028821918415243 max: 123.18558268792229\n", + "image 3 reprojection errors: average: 17.84712610359939 max: 185.33013225169395\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.0159e+06 2.50e+06 \n", + " 1 2 1.4112e+05 8.75e+05 8.61e+01 7.15e+04 \n", + " 2 3 1.4044e+05 6.75e+02 1.42e+00 2.63e+03 \n", + " 3 4 1.4034e+05 1.05e+02 9.14e-01 1.16e+03 \n", + " 4 5 1.4028e+05 5.63e+01 3.25e-01 4.26e+02 \n", + " 5 6 1.4026e+05 2.13e+01 2.19e-01 3.31e+02 \n", + " 6 7 1.4025e+05 1.60e+01 1.34e-01 2.63e+02 \n", + " 7 8 1.4023e+05 1.50e+01 1.78e-01 3.34e+02 \n", + " 8 9 1.4022e+05 1.09e+01 8.65e-02 1.95e+02 \n", + " 9 10 1.4021e+05 8.79e+00 1.18e-01 2.95e+02 \n", + " 10 11 1.4020e+05 7.48e+00 6.08e-02 1.94e+02 \n", + " 11 12 1.4020e+05 7.17e+00 1.03e-01 2.92e+02 \n", + " 12 13 1.4019e+05 6.89e+00 5.73e-02 1.94e+02 \n", + " 13 14 1.4019e+05 4.17e+00 5.95e-02 2.06e+02 \n", + " 14 15 1.4018e+05 5.56e+00 6.24e-02 3.05e+02 \n", + " 15 16 1.4018e+05 3.49e+00 4.01e-02 1.45e+02 \n", + " 16 17 1.4017e+05 2.61e+00 3.26e-02 2.82e+02 \n", + " 17 18 1.4017e+05 2.24e+00 2.58e-02 1.33e+02 \n", + " 18 19 1.4017e+05 2.16e+00 2.81e-02 2.77e+02 \n", + " 19 20 1.4017e+05 2.12e+00 2.51e-02 1.31e+02 \n", + " 20 21 1.4017e+05 2.10e+00 2.76e-02 2.75e+02 \n", + " 21 22 1.4016e+05 2.07e+00 2.47e-02 1.30e+02 \n", + " 22 23 1.4016e+05 2.04e+00 2.72e-02 2.72e+02 \n", + " 23 24 1.4016e+05 2.01e+00 2.44e-02 1.28e+02 \n", + " 24 25 1.4016e+05 1.99e+00 2.67e-02 2.68e+02 \n", + " 25 26 1.4016e+05 1.96e+00 2.41e-02 1.27e+02 \n", + " 26 27 1.4015e+05 1.94e+00 2.63e-02 2.64e+02 \n", + " 27 28 1.4015e+05 1.91e+00 2.39e-02 1.25e+02 \n", + " 28 29 1.4015e+05 1.89e+00 2.59e-02 2.59e+02 \n", + " 29 30 1.4015e+05 1.73e+00 2.15e-02 1.12e+02 \n", + " 30 31 1.4015e+05 1.71e+00 2.45e-02 2.63e+02 \n", + " 31 32 1.4014e+05 1.67e+00 2.08e-02 1.00e+02 \n", + " 32 33 1.4014e+05 1.64e+00 2.37e-02 2.76e+02 \n", + " 33 34 1.4014e+05 1.62e+00 2.01e-02 9.80e+01 \n", + " 34 35 1.4014e+05 1.64e+00 2.37e-02 2.98e+02 \n", + " 35 36 1.4014e+05 1.62e+00 1.97e-02 1.09e+02 \n", + " 36 37 1.4014e+05 1.56e+00 2.25e-02 3.06e+02 \n", + " 37 38 1.4013e+05 1.56e+00 1.91e-02 1.22e+02 \n", + " 38 39 1.4013e+05 1.55e+00 2.22e-02 3.16e+02 \n", + " 39 40 1.4013e+05 1.53e+00 1.88e-02 1.25e+02 \n", + " 40 41 1.4013e+05 1.53e+00 2.20e-02 3.18e+02 \n", + " 41 42 1.4013e+05 1.51e+00 1.87e-02 1.24e+02 \n", + " 42 43 1.4013e+05 1.50e+00 2.19e-02 3.17e+02 \n", + " 43 44 1.4013e+05 1.48e+00 1.85e-02 1.22e+02 \n", + " 44 45 1.4012e+05 1.47e+00 2.17e-02 3.14e+02 \n", + " 45 46 1.4012e+05 1.45e+00 1.84e-02 1.20e+02 \n", + " 46 47 1.4012e+05 1.44e+00 2.16e-02 3.11e+02 \n", + " 47 48 1.4012e+05 1.42e+00 1.82e-02 1.17e+02 \n", + " 48 49 1.4012e+05 1.41e+00 2.14e-02 3.08e+02 \n", + " 49 50 1.4012e+05 1.40e+00 1.81e-02 1.15e+02 \n", + " 50 51 1.4012e+05 1.39e+00 2.12e-02 3.06e+02 \n", + " 51 52 1.4011e+05 1.37e+00 1.80e-02 1.12e+02 \n", + " 52 53 1.4011e+05 1.36e+00 2.11e-02 3.03e+02 \n", + " 53 54 1.4011e+05 1.34e+00 1.78e-02 1.10e+02 \n", + " 54 55 1.4011e+05 1.33e+00 2.09e-02 3.00e+02 \n", + " 55 56 1.4011e+05 1.32e+00 1.77e-02 1.08e+02 \n", + " 56 57 1.4011e+05 1.31e+00 2.08e-02 2.97e+02 \n", + " 57 58 1.4011e+05 1.29e+00 1.75e-02 1.06e+02 \n", + " 58 59 1.4011e+05 1.28e+00 2.06e-02 2.94e+02 \n", + " 59 60 1.4010e+05 1.27e+00 1.74e-02 1.04e+02 \n", + " 60 61 1.4010e+05 1.26e+00 2.05e-02 2.90e+02 \n", + " 61 62 1.4010e+05 1.24e+00 1.72e-02 1.02e+02 \n", + " 62 63 1.4010e+05 1.23e+00 2.03e-02 2.87e+02 \n", + " 63 64 1.4010e+05 1.22e+00 1.71e-02 9.96e+01 \n", + " 64 65 1.4010e+05 1.21e+00 2.01e-02 2.84e+02 \n", + " 65 66 1.4010e+05 1.20e+00 1.70e-02 9.76e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 66 67 1.4010e+05 1.19e+00 2.00e-02 2.81e+02 \n", + " 67 68 1.4009e+05 1.17e+00 1.68e-02 9.57e+01 \n", + " 68 69 1.4009e+05 9.50e-01 1.54e-02 2.55e+02 \n", + " 69 70 1.4009e+05 1.14e+00 1.81e-02 1.30e+02 \n", + " 70 71 1.4009e+05 1.13e+00 1.65e-02 2.52e+02 \n", + " 71 72 1.4009e+05 1.12e+00 1.80e-02 1.28e+02 \n", + " 72 73 1.4009e+05 1.11e+00 1.64e-02 2.49e+02 \n", + " 73 74 1.4009e+05 6.64e-01 9.02e-03 9.66e+01 \n", + " 74 75 1.4009e+05 2.51e-01 3.06e-03 5.72e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 75, initial cost 1.0159e+06, final cost 1.4009e+05, first-order optimality 5.72e+01.\n", + "mean reprojection error: 6.615597051442245\n", + "max reprojection error: 31.49402030061628\n", + "mean reconstruction error: 1.135460440055302\n", + "max reconstruction error: 4.5057558874349075\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_4 = {}\n", + "centre_errors_4 = {}\n", + "orientation_errors_4 = {}\n", + "for pixel_error in pixel_errors:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_4 = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_4, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_4[pixel_error] = run_led_fit(fitter, led_positions_4)\n", + " centre_errors_4[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_4[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_4[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_4[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_4[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_4[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_4[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_4[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [ camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + " [-camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)]])\n", + "camera_directions = [[-1, -1.9, -1],\n", + " [-1, -1.9, 1],\n", + " [ 1, -1.9, -1],\n", + " [ 1, -1.9, 1],\n", + " [-1, 1.9, -1],\n", + " [-1, 1.9, 1],\n", + " [ 1, 1.9, -1],\n", + " [ 1, 1.9, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1464\n", + "Number of features in more than one image: 1464\n", + "Feature in image counts: Counter({4: 648, 8: 560, 7: 144, 6: 64, 5: 48})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:14.786886373153807 max: 190.10324949905626\n", + "image 1 reprojection errors: average:14.607954358420121 max: 192.53726502903967\n", + "image 2 reprojection errors: average:14.728698043711658 max: 183.91991478592809\n", + "image 3 reprojection errors: average:14.44770821132096 max: 232.5829101540651\n", + "image 4 reprojection errors: average:15.008736661881418 max: 133.28420271451168\n", + "image 5 reprojection errors: average:14.857650597212437 max: 142.22332463053175\n", + "image 6 reprojection errors: average:14.674016276931297 max: 209.7859571449106\n", + "image 7 reprojection errors: average:14.444423437139449 max: 125.5522654996809\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7165e+06 3.44e+06 \n", + " 1 2 5.1499e+03 1.71e+06 6.56e+01 1.12e+05 \n", + " 2 3 4.0778e+03 1.07e+03 8.31e-01 3.76e+02 \n", + " 3 4 4.0689e+03 8.83e+00 4.55e-01 1.29e+02 \n", + " 4 5 4.0667e+03 2.18e+00 8.01e-02 1.31e+01 \n", + " 5 6 4.0664e+03 3.78e-01 2.73e-02 1.00e+01 \n", + " 6 7 4.0662e+03 1.45e-01 1.15e-02 1.20e+01 \n", + " 7 8 4.0661e+03 7.92e-02 6.53e-03 7.25e+00 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 1.7165e+06, final cost 4.0661e+03, first-order optimality 7.25e+00.\n", + "mean reprojection error: 0.8493583260943721\n", + "max reprojection error: 3.1773291096319323\n", + "mean reconstruction error: 0.07784647312357885\n", + "max reconstruction error: 0.37106891173383005\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:15.21555442453697 max: 212.5602805629668\n", + "image 1 reprojection errors: average:15.385701401055705 max: 134.74106546704564\n", + "image 2 reprojection errors: average:15.18630342490676 max: 223.85509090839136\n", + "image 3 reprojection errors: average:15.062735667876268 max: 150.4733324102652\n", + "image 4 reprojection errors: average:15.06790703444719 max: 141.02672234836325\n", + "image 5 reprojection errors: average:15.159452729156817 max: 161.32665153106552\n", + "image 6 reprojection errors: average:15.415041416637276 max: 134.11209568701562\n", + "image 7 reprojection errors: average:15.071208564407637 max: 167.68292921829732\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8218e+06 3.45e+06 \n", + " 1 2 3.8401e+04 1.78e+06 6.70e+01 8.61e+04 \n", + " 2 3 3.7552e+04 8.49e+02 7.58e-01 1.08e+03 \n", + " 3 4 3.7514e+04 3.85e+01 7.20e-01 4.35e+02 \n", + " 4 5 3.7501e+04 1.25e+01 1.46e-01 4.96e+01 \n", + " 5 6 3.7498e+04 2.94e+00 7.93e-02 5.19e+01 \n", + " 6 7 3.7497e+04 1.62e+00 2.61e-02 3.27e+01 \n", + " 7 8 3.7496e+04 7.37e-01 1.93e-02 3.79e+01 \n", + " 8 9 3.7495e+04 6.31e-01 1.58e-02 3.72e+01 \n", + " 9 10 3.7495e+04 6.10e-01 1.70e-02 4.63e+01 \n", + " 10 11 3.7494e+04 5.75e-01 1.43e-02 4.49e+01 \n", + " 11 12 3.7494e+04 4.22e-01 1.10e-02 7.68e+01 \n", + " 12 13 3.7494e+04 3.11e-01 6.17e-03 5.96e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 1.8218e+06, final cost 3.7494e+04, first-order optimality 5.96e+01.\n", + "mean reprojection error: 2.579526455545454\n", + "max reprojection error: 9.485862455868327\n", + "mean reconstruction error: 0.235926820678703\n", + "max reconstruction error: 1.1472195478840423\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:15.770182188947775 max: 163.3502226815795\n", + "image 1 reprojection errors: average:15.7891505816311 max: 161.20079501799412\n", + "image 2 reprojection errors: average:16.104982073994105 max: 223.24028598658467\n", + "image 3 reprojection errors: average:15.650416681820715 max: 161.65908002006174\n", + "image 4 reprojection errors: average:16.222650323038255 max: 164.16128398927933\n", + "image 5 reprojection errors: average:15.92165185959968 max: 212.238726576011\n", + "image 6 reprojection errors: average:15.59909566028454 max: 192.2656584536024\n", + "image 7 reprojection errors: average:15.4762154254655 max: 145.25417091585746\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.9107e+06 6.67e+06 \n", + " 1 2 1.0324e+05 1.81e+06 6.73e+01 1.02e+05 \n", + " 2 3 1.0240e+05 8.39e+02 1.02e+00 2.06e+03 \n", + " 3 4 1.0232e+05 8.28e+01 8.74e-01 1.17e+03 \n", + " 4 5 1.0227e+05 4.30e+01 2.36e-01 1.17e+02 \n", + " 5 6 1.0226e+05 1.18e+01 1.59e-01 9.55e+01 \n", + " 6 7 1.0225e+05 9.36e+00 8.81e-02 7.97e+01 \n", + " 7 8 1.0225e+05 3.92e+00 5.33e-02 6.84e+01 \n", + " 8 9 1.0225e+05 2.96e+00 3.72e-02 7.89e+01 \n", + " 9 10 1.0224e+05 2.45e+00 3.40e-02 7.43e+01 \n", + " 10 11 1.0224e+05 2.36e+00 3.21e-02 7.36e+01 \n", + " 11 12 1.0224e+05 2.28e+00 3.25e-02 7.41e+01 \n", + " 12 13 1.0224e+05 2.21e+00 3.07e-02 6.89e+01 \n", + " 13 14 1.0223e+05 2.16e+00 3.14e-02 7.16e+01 \n", + " 14 15 1.0223e+05 2.09e+00 2.95e-02 6.47e+01 \n", + " 15 16 1.0223e+05 1.95e+00 2.89e-02 6.43e+01 \n", + " 16 17 1.0223e+05 1.92e+00 2.80e-02 7.23e+01 \n", + " 17 18 1.0223e+05 1.82e+00 2.70e-02 6.99e+01 \n", + " 18 19 1.0222e+05 1.91e+00 2.85e-02 9.33e+01 \n", + " 19 20 1.0222e+05 1.80e+00 2.58e-02 8.18e+01 \n", + " 20 21 1.0222e+05 1.74e+00 2.65e-02 1.02e+02 \n", + " 21 22 1.0222e+05 1.70e+00 2.48e-02 8.42e+01 \n", + " 22 23 1.0222e+05 1.60e+00 2.44e-02 1.09e+02 \n", + " 23 24 1.0222e+05 1.31e+00 1.79e-02 1.21e+02 \n", + " 24 25 1.0222e+05 7.27e-01 8.30e-03 8.94e+01 \n", + " 25 26 1.0221e+05 3.59e-01 4.52e-03 6.15e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 26, initial cost 1.9107e+06, final cost 1.0221e+05, first-order optimality 6.15e+01.\n", + "mean reprojection error: 4.255669876037859\n", + "max reprojection error: 16.6184602946805\n", + "mean reconstruction error: 0.38357843001089625\n", + "max reconstruction error: 1.8819894676257656\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:17.87923891188316 max: 163.4670006845407\n", + "image 1 reprojection errors: average:19.01224352505981 max: 200.68993629781923\n", + "image 2 reprojection errors: average:17.774121345865154 max: 139.97253339504144\n", + "image 3 reprojection errors: average:18.140056466892823 max: 200.3031631749373\n", + "image 4 reprojection errors: average:18.399963400294318 max: 207.2190151450603\n", + "image 5 reprojection errors: average:18.097554509746292 max: 177.14510738218078\n", + "image 6 reprojection errors: average:18.160465932142834 max: 286.1350166919545\n", + "image 7 reprojection errors: average:18.062487725828692 max: 211.90072163647443\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3533e+06 5.15e+06 \n", + " 1 2 4.1909e+05 1.93e+06 7.32e+01 3.66e+05 \n", + " 2 3 4.1693e+05 2.17e+03 1.93e+00 1.14e+04 \n", + " 3 4 4.1647e+05 4.61e+02 2.28e+00 5.56e+03 \n", + " 4 5 4.1625e+05 2.16e+02 4.97e-01 7.28e+02 \n", + " 5 6 4.1620e+05 4.82e+01 3.18e-01 2.81e+02 \n", + " 6 7 4.1617e+05 3.59e+01 1.56e-01 2.82e+02 \n", + " 7 8 4.1615e+05 1.66e+01 1.16e-01 1.98e+02 \n", + " 8 9 4.1614e+05 1.22e+01 7.06e-02 1.96e+02 \n", + " 9 10 4.1613e+05 1.03e+01 7.77e-02 1.85e+02 \n", + " 10 11 4.1612e+05 9.97e+00 6.27e-02 1.92e+02 \n", + " 11 12 4.1611e+05 9.58e+00 7.42e-02 1.74e+02 \n", + " 12 13 4.1610e+05 9.38e+00 6.05e-02 1.93e+02 \n", + " 13 14 4.1609e+05 8.99e+00 7.09e-02 1.64e+02 \n", + " 14 15 4.1608e+05 8.85e+00 5.86e-02 1.97e+02 \n", + " 15 16 4.1607e+05 7.74e+00 6.13e-02 2.02e+02 \n", + " 16 17 4.1606e+05 8.20e+00 5.69e-02 3.22e+02 \n", + " 17 18 4.1606e+05 6.79e+00 5.02e-02 2.75e+02 \n", + " 18 19 4.1605e+05 5.15e+00 3.20e-02 4.68e+02 \n", + " 19 20 4.1605e+05 2.42e+00 1.20e-02 1.55e+02 \n", + " 20 21 4.1604e+05 1.18e+01 1.17e-01 1.50e+03 \n", + " 21 22 4.1603e+05 9.96e+00 1.94e-02 1.02e+02 \n", + " 22 23 4.1602e+05 5.32e+00 5.52e-02 7.97e+02 \n", + " 23 24 4.1602e+05 4.64e+00 1.20e-02 7.75e+01 \n", + " 24 25 4.1599e+05 2.70e+01 3.13e-01 1.77e+03 \n", + " 25 26 4.1597e+05 2.47e+01 5.47e-02 9.11e+01 \n", + " 26 27 4.1596e+05 1.15e+00 1.27e-02 2.63e+02 \n", + " 27 28 4.1596e+05 1.11e+00 5.98e-03 7.71e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 28, initial cost 2.3533e+06, final cost 4.1596e+05, first-order optimality 7.71e+01.\n", + "mean reprojection error: 8.584057197663814\n", + "max reprojection error: 30.479432393561016\n", + "mean reconstruction error: 0.7886446430754868\n", + "max reconstruction error: 3.5033006455399907\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [camera_radial_position, 0, 0],\n", + " [-camera_radial_position, 0, 0],\n", + " [0, 0, camera_radial_position],\n", + " [0, 0, -camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [-1, 0, 0],\n", + " [1, 0, 0],\n", + " [0, 0, -1],\n", + " [0, 0, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1464\n", + "Number of features in more than one image: 1464\n", + "Feature in image counts: Counter({3: 848, 4: 352, 2: 216, 5: 48})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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OLoP3wBaaD7B8OPnN2ezsfW2n5UMcAGqjTt7G3H6E95Bfi32/5vdg2RCb35w1897XduxdACiHOnkbc/sR3kN+Lfb9mg+wfDh/2/t+kjmbnb2v7TjEAaAc6uRtzO1H7Pke3A/3vRb7fg656NDpdArn8znEGFXuAAA70P9qz71DLpqfweJvLY4UAACUTP+rH2awAAAAZnJMOwAAwMYEWAAAAIkIsAAAABIRYAF0aOnFji1eCDnHmufvPe8AeiHAoko6KrDO7WLHcRx3+e9aseb5e887WEvbTy0EWCyWs6LTUSGFnhvrYRhCjHH2ccFL/7tWrHn+XvOu5++MtHK2/coxs0zT9PTPy8vLBDcxximEMMUYd//dl8tlijFOl8tl999NmZaUiZxlGHqx5DtTx/OdnOVCe8F3Qgjv0zcxk4uGWSznhXnH49Et6HxyG9kMITxdNlz6CNtb8p0t+Z5pX862X3vBHC4aBppwvV7DOI5hGIZwPB5zJwdYwfcM1ODeRcMCLAAAgJnuBVgOuYDG2ZgLUCb1M7TJHixonL0MAGVSP0ObBFjQOBtzAcqkfoY2bbJE0JQ3lON26pKN4gBlUT9DOVLGL5vMYJnyBgAAapEyftkkwDLlDQAA1CJl/OKYdgAAgJkc0w6J2WsIQA+0dzCPAAvueNSg3NbqjuO4c8oAYD+P2jsBGHwmwII7HjUowzCEGKO9hnSv5c5Vy88Gz3rU3hlwhM/cgwV3PNrseDteF2pwvV7DOI5hGIbkR0K3fHLsVs+25fuA1B61dw43g8/MYHXKqOxj7ifpV4vfx5YjzC3P5m71bC2O+Lf43fAc7eVjvo/OTNP09M/Ly8tEG2KMUwhhijHmTkpSl8tlijFOl8sld1LYyRbvvMXvw7dRlhbfxxbfTYv5xGMtvvcW2xWmKYTwPn0TM1ki2KlWp/NbXqrE97Z45y1+H5a0lqXF97HFd6NO71OL773FdoX7BFidarFxD0EF1qMt3nmr3wdsaYvvRp3epxbfu3alL93twbIGdr6a8sw68Hlqerf3eOfQrla+7xbq2j3V8t691/l6ybPuAqwWNxZvTZ4tU0Ml4t0CbK+GuraGNqs0NbzX0vSSZ90tEWxx2nlr8myZGtaQe7cA26uhrq2hzSpNDe+1NL3k2eHjAIznvL6+Tu/v7xsmB/a15V007rkBoBZbtVnaQlp2OBx+TdP0+tefC7Do2el0CufzOcQYjdgBQGLaWVp2L8Dqbokg/KmXqWoAyEE7S4+6O+QC/lTLSUXQitwb6XP/fuiNdpYeCbAAKlZbwJD7BKncv3+J2t4xQO8EWAAr5ewA1xYwDMMQYozZlgvl/v1L5HrHAjuAZezBAopVy+lTOY83rm1/w225UK+/f4lc77imY7trqSuAPgiwgGLV0sHLGeTUGDAwT653XFPwXktdAfTBEkHgaXsvGaplOZdN3PuxbG0/NZXrvesK5RD4iQALeNree0Fq6uCtobP2vNr2nOXWS9nau65QDoGfWCIIPK2mJUM1sbzpecrgPMrWNpRD4CdmsICnLR0l7mUUfalalkKWoJdZzVSUrfvW1EvKIfATARbspOcgw3Kan+mssRVl676e66We2yPYgyWCsJOel+pYTgOUpud6qef2CPZgBovmlDoy1/NSHaPoQGl6rpdKbY9Kbb9hrsM0TU//5dfX1+n9/X3D5MB6p9MpnM/nEGM0MgcAldB+U5vD4fBrmqbXr39uBqsDvY0IlToyBwDc12P73VsfrRcCrA70tpH30bIPlRkA5PFTG9zjss3e+mi9cMhFB3reyPsdm3sBIA9t8Gf6aG0SYHXgNiLEB5UZAOShDf5MH61NDrkAAACYySEXrGbvEgDQO/0hHhFgzdD7B2UjJgDQO/0hfeJH7MGaofeNmdZNAwC90x/SJ35EgDVD7x+UjZgAQO/0h/SJH3HIBQAAwEwOuQAAANiYAAsAACARARYAAEAiAizYkWNNAchJOwTbc4og7MixpgDkpB2C7ZnBqpDRp3oNwxBijI41hYXUf7COdqhe6r96CLAq5Abxet3uzjgej7mTQmE0nM9R/z1PmeI72qF6qf/qIcCqkNGnz3QiaIGG8znqv+cpU9RO+/6Z+q8i0zQ9/fPy8jKxzuVymWKM0+VyyZ2UZsQYpxDCFGPMnRQeUP7vkzekpkx9T77UQ/uenvKfVgjhffomZnLIxc5sLk3vNpJjRKd8yv99t2U7kIoy9T31UD207+kp//uwRHBnpnfTs568Hsr/NmpbRpMrvfKJENRDNdG+p6f87+S7aa17P5YI0gpT5GwhV7mqbRlNrvTKp+eoH9mCckWLgiWC8Jsp8rpcr9cwjmMYhqHokcxc5aq2ZTS50iufnlNL/VhLvcCHWsoVJPFd1HXvxwwWrTCStt6eeVjLzINyRQtqKcd71wu15Eup5B8tCndmsA4f/99zXl9fp/f3961iPSpnNLEvp9MpnM/nEGPcfDRS2QK+2rte2LPOIy9tDs86HA6/pml6/frnlgiSjOn/vuy5fMlpaMBXe9cLtS0xZTn9GdYSYJGMxqcvgh6gJ+q8fujPsJYlggAAADPdWyLoHiwAAIBEBFiwAxeGAlAabRNsQ4BF8VpoAG4bZsdxzJ0UAAgh1N82tdA/oE0OuaB4LZzmY8MsAKWpvW1qoX9Am8xgUbxhGEKMsdoGIITfp0+5T4PcthrxbXEkeYtnajGfqFftbVML/QPaJMAiizmdjNobAPalU/yzrZYE1b7U6DtbPFNr+ZT622jpW2N7c/oHyhZ7skSQLEzrs5UtylZL5XWrJUG1LzX6zhbP1Fo+pf42WvrWKIuyxa6maXr65+XlZYIULpfLFGOcLpdL7qTwRe3vZov0154nsJXU30bt31rt6W+Zd8MWQgjv0zcxk4uG4Q/X6zWM4xiGYeh2SeLpdArn8znEGI3yAcyg/vygLaUX9y4atkQQ/mAJQXtLmAD2ov78oC2ldwIs+IPG8femYQDmUX9+0JbSO0sEAQAAZrq3RNAx7TtyRGj7vGMAaqYda593vD1LBHdkTXL7vGMAaqYda593vD0B1o6sSW6fdwxAzbRj7fOOt2cPFszg6FkAeqYdhN8c0w4JmFYHoGfaQXjMIRdPsBmQm2EYQozRtDoAXdIOcqN/fJ8lgk9wMzsAAPymf2yJ4Co2AwIAwG/6x/eZwQIAAJjJRcMNsNYVSG1pvdJbfSSfgFKoV8onwKrI7eSecRxzJwWqsaQh6qnxWlqv9FYfyafHfGuwj57qlWpN0/T0z8vLy0Q+l8tlijFOl8sld1JWaeU5WtPqe4kxTiGEKca46X9Tq6XvvdXyco98esy39llP774WrbyTVp6jBSGE9+mbmEmAxe5ablBr1up7WdIQabxgPt/aZ63WqTXzTkjtXoDlFEF259SZMrX6Xo7H4+zjY5f8N9A739pnrdapNfNO2ItTBAEAAGZyiiCbslEZAGiJvg1LWSJIErcTbUIIzS73AAD6oW/DUgIskrCuGQBoib4NS1kiSBK3jcrH4zHpv1va9Hxp6QGAvZXUFm6Zlq36NrTPDBZFK216vrT0AMDeSmoLS0oL3AiwKFpp0/OlpQcA9lZSW1hSWuAm6THt1+s1jOMYhmEwnQoAAFRlTjyzyzHtt2nacRxT/rOwi5LWlANArbSn1CxFPJN0iaBpWmpmHTcArKc9pWYp4pmkM1ilnrZiJIVnDMMQYoyLPyjlDIAWrG3P1ran9KHUflOKeCbpHqxSnU6ncD6fQ4zRSAqbUc4AaIH2jD20UM522YNVKiMp7EE5K8cWo2KljrQtIX8e2+p5Wsqn1M/SUt7UTnvGHpouZ9M0Pf3z8vIyAX24XC5TjHG6XC65kzJbjHEKIUwxxqL/zVzkz2NbPU9L+ZT6WWrOm5rrS2C5EML79E3M5B4s4Fs1b1Le4sCdlg7xkT+PbfU8LeVT6mepOW9qri+B9LrYg9Ujd5KxljIE8Bz1JSkoR/Xpeg9Wj1LdSWZNfL9KPRUUoDTqy36l7Ce5T7Ydlgg2KtVSC8seAAC+l7KfVPMyWT4TYDXqNpq2lo8dAOB7KftJqfpu5GcPFgAAwEz2YNEc+8MAoH3ae2ojwKJaSzaDqqQBIJ8l7bDDH6iNPVhUa8m6Z4d2AEA+S9ph+8GpjRksqrXkWNxhGEKMcddK2qwZAKXau41a0g47Bp/aCLDoSo5KuvWlDXs3zjUErDnSWEO+3ORKqzwq9/fOsWcaa8iPtfZuowRLdGGapqd/Xl5eJmCey+UyxRiny+WSOymbiDFOIYQpxtjk71siRxpryJebXGmVR+X+3jn2TGMN+bFW620UbCmE8D59EzPZgwUba/1ei73XxtewFj9HGmvIl5tcaZVH5f7eOfZMYw35sVbrbRTk4B4sAACAmdyDBVC4HvZ7rCWPHpNHAHkJsIAsdAL/1vqBKCnIo8fk0d/UN8Ce7MECsnAn2d962O+xljx6TB79TX0D7MkeLCCL6/UaxnEMwzA4rhfYlPoG2MK9PVgCLAAAgJkccgEAALAxARYAAEAiAiwAAIBEBFgAAACJCLAAAAASEWABAAAkIsACAABIZPcA63q9htPpFK7Xa1X/ds3m5Eutefgo3bmfK/fvB4A/5W6XSm+3l+qhz7WHrfJmtzyfpunpn5eXl2mtGOMUQphijKv/rT3/7ZrNyZda8/BRunM/V+7fDwB/yt0uld5uL9VDn2sPW+VN6n83hPA+fRMz/dO24dvfhmH49L+1/Ns1m5Mvtebho3Tnfq7cvx8A/pS7XSq93V6qhz7XHrbKm73y/PARfD3n9fV1en9/3zA5AAAA5TscDr+maXr9+ucOuQAAAEhEgAUAAJCIAAsAACARARYAAEAiAiwAAIBEBFgAAACJCLAAAAASEWABWVyv13A6ncL1es2dlGLIk8fk0WPy6G/yBNjTP+VOANCncRzD+XwOIYTw9vaWOTVlkCePyaPH5NHf5AmwJwEWkMUwDJ/+F3nyDHn0mDz6mzwB9nSYpunpv/z6+jq9v79vmBwAAIDyHQ6HX9M0vX79c3uwgFX23ttgLwX0bc86QH0DLCHAAla57W0Yx7HJ37dEjk5ZTR3BXGmVR+X+3jn2rANqqG+AAk3T9PTPy8vLBMxzuVymGON0uVxyJ2UTez9fDfkZY5xCCFOMsenfuVSutMqjcn/vHHvWATXUN2v18IywlRDC+/RNzOSQC9hY66dXHY/HXZ9r79+3RI4N9TVt4s+VVnlU7u+dY886oIb6Zq3W2yjIwSEXdOV6vYZxHMMwDOF4PDb7OwHgGXu3UdpEWuKQC5qzZK9AjvX0txFQDQkApdm7jVrSDtewNxD+ZIkg1VqyrKGG5S8A0Kol7bBljNRGgEW1llTSPaynB4BSLWmHDY5SG0sE+VHJ0/KW3gFA+0pu70vuJ5GPGSx+ZFoeAOB7+kl8xwxWo1KNqAzDEGKMpuUBAL5I2U8yG9YOx7Q36nQ6hfP5HGKMRlQAAAqn71Yfx7R3xswTa9U8klZz2qFXNX+3Naedcui7tUOA1aiSN4RShxx3hqWyRdpb6kBt8Swt5U8I2z1PS/mU+lnUOfRO360h0zQ9/fPy8jLV6HK5TDHG6XK55E4KVKPm72aLtMcYpxDCFGNM9m/mssWztJQ/07Td87SUT6mfRZ0DfWnhuwkhvE/fxExdBFgtNWiUq4WKgvtaer9bPEtL+TNN2z1PS/nU0rPwmXfLHlron98LsLo45OJ6vYZxHMMwDKZd2YzNqQC0QHvGHlron3d9yIU1rTxj7X4Cm1MBaMHa9qylvYZsp+X+edIAywdFzdZuUm65ogCgH2vbM4d+ULMU8cw/JUyP26yp2m2kzgwUACynPaVmKeKZpAGWD4qa3UbsAIDltKfULEU8k3SJoCVSpFbastPS0gMAeyupLSwpLbQhRTyTdAYLUitt2Wlp6QGAvZXUFpaUFrgRYFG00padlpYeANhbSW1hSWmBmy7uwWJ7LdxlAABwo2/DI/fuwTKDRRKm6AGAlujbsJQAiyRM0QMALdG3YSlLBAEAAGa6t0Qw6THt8AxHqpbJewFIR51aHu+EvQiwKtJKxXBb0zyOY+6k8IdW38uS76aVbw325Fv7rNU6tWatvJOWv5tmTNP09M/Ly8tEPjHGKYQwxRhzJ2WVy+UyxRiny+WSOyn8odX3suS7aeVbe8bS995qeblHPj3mW/usp3dfi1beScvfTW1CCO/TNzGTAKsirVQMsKcl301P39rShrq3Bl4+PeZbg334bspxL8ByyAVAx5be89Lb/TDyCYCv7h1yIcACAACYySmCK9hMCAAAv+kf3+ei4Se4yRsAAH7TP77PDNYThmEIMUY3eWO0BoCuaQe50T++zx4smOF0OoXz+RxijEZrAOiOdhB+u7cHyxJBmOE2SmO0BoAeaQfhMUsEd2RavX7H4zG8vb3dPW7ZOwagZo/asUftIOXTV9meGawd2QzYPu8YgJppx9rnHW9PgLUj0+rt844BqJl2rH3e8fYccgF/uF6vYRzHMAyD5Q8AsIC2lF445AKeYNocANbRltI7h1zAH9zpYPMrwFLqzw/aUnonwII/OB3p98jjOI65k7KIDg7Uq/bvt/b6MxVtKb0TYJFF7Y1oy2ofedyig9NSeW3pWWrUWv6nfp7aA5Ta68+WtfbtUbhpmp7+eXl5mSCFGOMUQphijLmTQmMul8sUY5wul0uyf7Ol8rrVs2yR77kpS4+lfp4WyxFlaO3bowwhhPfpm5jJIRdk4YhQtnJbmpJSS+V1q2dpcVP7Fs/UUlkKIf3zbPH9QgjtfXsU7ruo696PGSxyaGFEs4VngJ+0WMZbfCb4U+1lvPb0U79wZwbLPVgU73Q6hfP5HGKM1Y5stvAMALSl9rap9vRTP/dgUa0WpvVbeAYA2lJ721R7+mmXGSwAAICZ7s1gOaYdAAAgEQEWAABAIgIsknGJHwBQO/0Z1hJgkcztzphxHHMnhR1ogICeqPP6oT/DWgIskhmGIcQYnebTiT0bIB0b4Ku96wWd7n7oz7CWAItkjsdjeHt7C8fjMXdSHtJhX2/PBqiWjo1yRQtqKcd71ws63evUUq5CqKs/Q6G+u3343s/Ly8u+1yPDRmKMUwhhijHmTgpPuFwuU4xxulwuuZPyo1zlqpb8ucmVXvn0nFrqx9reZ+9qKVcwRwjhffomZnLRMF1yOWFdbqOJpctVrm4j+SGEKvIpV3rl03NqqR9rqRf4UEu5giS+i7ru/ZjBWs+IGz1T/rdRW76awXpObemthXylZ8p/WuHODNbh4/97zuvr6/T+/r5dtNeB0+kUzudziDEaeUvker2GcRzDMAzWSxdO+QdyUw/VQ/uenvKf1uFw+DVN0+vXP7dEcGemyNOrbdlPz5T/+3QkSE2Z+p56qB7a9/SU/518N61178cSwTKY3v1MftACG8Cf43t/njJF7Xzvn8mP8gSHXLTDiM5nNW10NqLMPUYVn6P+e54yxXdqaodqat/3oP6rhwCrQhrNeqkcuUdH4jnqv+cpU3xHO1Qv9V89HHIBO6pp5BCA9miHIJ17h1wIsAAAAGa6F2D9txyJAQAAaJEACwAAIBEBFgAAQCICrBmu12s4nU7her3mTgoAAGShT/wzAdYMt6NNx3HMnZQsfEwAQO/0h/SJH3EP1gy93z/g7gwAoHf6Q/rEjwiwZuj90kYfEwDQO/0hfeJH3IMFAAAwk3uwAAAANibAojs2pwJAHtpgeiDA6oDK7DMn3wBAHtrgz/TR2iTA6kBvldmjymoYhhBj7HpzKgDk8FMb3GOw0VsfrRdOEexAb6fdPDo+1ck3AJDHT21wj8ef99ZH64UZrA7cKrPj8Zg7KbsodYaqx5E5AMpTantUavu9pd76aL0QYNGcUiurnpcBlNqYA/3quV4qtT0qtf2GuSwRhJ30vAygx2UfQNl6rpd6bo9gDwIs2EnPe7805kBpeq6Xem6PYA+WCAKbs+zjZz0vVWJbytZ96iVgKwIs4Gk6a9sodT9EiZTBeZStbSiHwE8EWMDT9u6s9dKJ6fHkrKUEDPP0Urb2riuUQ+An9mABT9t7z0Ivm9Dth3hez/tmluilbO1dVyiHwE/MYAFP23vPQi2j773MtJXAvpn91FSu964rlEPgJwIsoFi1dGJyLheqqRMcQv705v79S+RKc03L4GqpK4A+WCIIsFLO5UK1LaPMnd7cv3+JXGm2DA5gGQEWwEo597nU1gnOnd7cv3+JXGnuZf8WQGqHaZqe/suvr6/T+/v7hskBAAAo3+Fw+DVN0+vXP7cHi67VuB8DAGqhnaVHlgjStRr3YwBALbSz9Ki7GSwjKfO1nGdbHu3bcr4B0Jat2qxarttYQjs/Xzd5Nk3T0z8vLy9T7WKMUwhhijHmTko15NkyNeTb5XKZYozT5XLJnRSAZtVQ19bQZpVGns3XWp6FEN6nb2Km7pYI1niCVG7ybJka8s3SDYDt1VDX1tBmlUaezddLnjlFEDp2vV7DOI5hGIZqL+hs4RmA77XyfbfyHMBnThHkk1bXwLb6XFu53XNTc4N/GxkexzHZv6kcwXxbfDdbfN85tFDX7qnFOrjFZ+K+7pYI8qGG5QpLtPpc3LfFcgPlCObb4rvpZTkRn7VYB7f4TPzgu41Z935aOOSCDzVsuF2i1ediXy2Woy2fqcX8utnq2VrMsxafiTxaLEstPhP3D7mwBwugA6fTKZzP5xBjTD56uuW/ndtWz9ZyngH0wh4smMl6aVqy5V00Ld9zs9WztZxn9Ed7CZ+ZwYI7Ho0wOxUKgB48au/MyNKrezNYDrmAOx5trrZhFYAePGrvHEYCnwmw4I7bsbr3aFAA6MGj9u5Rewm92WQPlrW49MC9JgD0QHtHD1LGL5vMYFk6BQAA1CJl/LJJgGXpFAAAUIuU8YtTBAEAAGZyDxZ0yp5IgDKpn6FNThGExtkTCVAm9TO0SYAFjbMnEqBM6mdokz1YAAAAM9mDBTTNXgZoh+8ZqJkAi8VyNoAaX7667WUYx/Hp/0Y5gu0t+c6WfM+0T7+DWtiDxWI5N+faGMxXS/YyKEewvSXfmb1JfEe/g2pM0/T0z8vLywQ3l8tlijFOl8ulq99NO3ouR0ufvec8m6Z1z99r3vX63KSn30FpQgjv0zcxk0MuADp0Op3C+XwOMcZZo7FL/7tWrHn+3vMOoDX3DrmwRBCgQ0uXYPW+dGvN8/eedwC9MIMFAAAwk2PaAQAANibAAgAASESA1SF3OQAA7Ev/qx8OueiQuxwAAPal/9UPAVaHnGQFALAv/a9+NL9E0HTs347HY3h7ewvH43GX3zfnHXhfAMBSc/sRe/Y79u5/1aLFvl/zAdZtOnYcx9xJ6dacd+B9bafFCgygVurkbcztR+h35NfiO2h+iaDp2PzmvAPvazvWfgOUQ528jbn9CP2O/Fp8By4ahk5cr9cwjmMYhsHyBIDM1MlQv3sXDQuwAAAAZroXYDW/Bwtoi30L0C/fP1ADARZQla02w+q4QTpbfU8tboYH2tP8IRdAW7baDGvDOaSz1ffU4mZ4oD1msICqbHWPyDAMIcbYZMdty9m51mf+tn6+VvNvq+/JPUJADbIecuEEHYDtnU6ncD6fQ4wx+ezclv92CbZ+vtbzDyC3LeONe4dcZF0iaEkOwPa2XFbV+pKtrZ+v9fwDyC1HvGEGCwAAaFKOGSz3YAEAAMzkHiwAAICNCbCAEEK7p5kB7E19Cn1zDxYQQnDoDEAq6lPomxksqmaUMJ0c90B5f8DWctQzLd+rtzftBDVyyAVFevbEF3fI1M37A7amnqnbs+/PydTkUOQ9WHDPs8sr3CFTN+8P2Jp6pm7Pvj/LMimJJYKNaWUq/dnlFcfjMby9vRmtqlSN76+VbwyWqLH811jP8Nuz76+VZZk1fmP8TYDVmNsIzjiOuZOyigaxHr01Brm/sd7ym89yv//c5X9vufOb57XSb+jtG2uVJYKNsRSCvfW2LCP3N1Z7fpewT6KENCyV+/3nLv97y53f9Ke3b6xVAqzG3EZwYC+9NQa5v7Ha87uEDmsJaVgq9/vPXf73lju/6U9v31irnCIIwG5KmD0qIQ0A1O/eKYICLAAAgJnuBVjdH3JhA2v7vGNKojySmzJISZTHtvX6frvfg1XzWnye4x1TEuVxHcv71lMGKYny2LZe32/3AZYNrO3zjimJ8rhOr411SsogJVEe29br+7UHC4BqmMECoBT2YFGEXtfiAmm0cpkokId+CHvofokg+7K8BwDIRT+EPQiw2FWva3EBgPz0Q9iDPVgAAAAz2YMFAACwMQFWgWzABABgDv3HctiDVSAbMAEAmEP/sRwCrALZgAkAwBz6j+WwRDCRlNOy7nkBAGCOlP1Hyw3XMYOViGlZAABaoF+7jgArEdOyAAC0QL92HfdgAQAAzOQeLPhP1hUDwP60v/RCgEV3buuKx3HMnZQqaSCBnqkDl9P+0gt7sOiOdcXr2PgK9EwduJz2l16YwaI7vR+Dv3b0dRiGEGPUQAJdWlsH9jwD1nv7Sz8ccgGdOZ1O4Xw+hxij0VeAnamDoR27HnLR8+gMlM4MFEA+6mAoU8r4ZZMZLKMzAABALZbEL7vOYBmdAb7qeWa752enXD2Xy56fHfheyvjFHiw2cb1ewziOYRgGm1kJIfQ9s93zs1Ounstlz8/OffouzHVvBssx7WzCMbZ81fPxvD0/e2o6QOn0XC57fnbu03chmWmanv55eXmZqMvlcplijNPlcuni90JqynJZYoxTCGGKMeZOCpPvg7bkKM++obqFEN6nb2ImM1iNyzUac7vrAmpnRLMsZh7K4vugJTn6Lr6hNrlouHEOHIF1SviGbMj/zUWlv5VQLkr4PqBmvqE2CbAapzPSrhI6Vz0o4Ru6jXCO45gtDSmUUmZLScdaJZSLEr6PXrRSbvnMN9QmAVbhVKjcU0Lnin20MsJZSpktJR1rtVIueE4r5Zb09BXLYw9W4azN5R57UfrRyp7GUspsKelYq5VywXNaKbekp69YHvdgFc6RxAAA3KOvmM+9e7AEWAAAADPdC7DswQIAAEhEgMVfWt8s2frz1cy7AdZSj5Srh3fTwzPymEMu+EvrmyVbf76aeTfAWuqRcvXwbnp4Rh4TYPGX1k8qav35arblu7EJGMqx5feoji9XD++mh2fkMYdcAF04nU7hfD6HGKNRRcjM9wi04N4hF2awgC4YVYRy+B6BljnkAujC7VLWHpYH2mRdr17eXU/fI9AfARZAY26brMdx3Ox39BII3Oz1vHu8OwC2ZYkgQGP2WH7V20lZez2vpXMA9RNgATTmtvxqS70FAns97x7vDoBtWSIIBept+RX16W0PTW/PS320G1AOM1hQoN6WXwGwjnYDymEGi+SMoq03DEOIMXaz/AqAdbQb6+m/kIqLhknOBZIAQG30X5jr3kXDZrA20PsIiFE0AKA2vfdfeu+/pmQGawNGQAAAqIn+63z3ZrAccrGB3o4vBgCgbvqv6ZjBAgAAmMkeLKAK1oADa6hDgNwEWDRNQ1uf210u4zjO/m+9b2jDmm95TR3C/tTbtEiAxdNqrAQ1tPVZc4qT9w1tWPMt934SXG1qrLdr7A+xL4dc8LQab4m3YbM+x+NxcfnyvqENa77lNXUI+6ux3q6xP8S+HHLB067XaxjHMQzDEI7HY+7kAADsTn+Im3uHXAiwAAAAZnKKIECH1u4VsNfgZ/IXgK/swQJo2Nq9AvYa/Ez+AvCVGSwojBFtUlp7opoT2X4mfymJ9gPKYA8WFOZ0OoXz+RxijEa0AXia9gP2dW8PliWCUJgaj6wFID/tB5TBDBYAAMBMThEkO2vDAYDc9EfYmiWC7MZpWQBAbvojbM0MFrvZ4rQso1AA0K4t2nmnd7I1e7ComhOTAKBd2nlKZg8WTTIKVR+zjkBO6qC6aOepkRksYFdGI4Gc1EFAKmawqIbRxbYZjQRyUge1S/+BUgiwKM7tdJ9xHHMnhQ0cj8fw9vYWjsfjJv++Bhbqtcf3u3UdRD76D5TCMe0Ux030rOH4XaiX75c19B8ohQCL4txGF2EJDSzUy/fLGvoPlMISQaiMJXA/s/wH6uX7/Zn6H+ogwILKWGPOd3S82uOd8pX6H+ogwILKOAGL7+zV8eq907/n8+tM85X6H+pgDxZUxhpzvrPX3pXeDyHY8/ntR+Ir9T/UwQwWT+t95BpKttfeld5H0Pd8fvuRoFz6RPxEgMXTLFchBI1K73rv9Pf+/L1T/3GjT8RPBFhfqDzv633kmg8aFaBX6j9u9Im+px/9wR6sL3rfX/ATa7/rd71ewziOYRiGxSPw9oUAvUpR/6Woh8lPn+h7+tEfBFhf6DzSshQVn0YF6FWK+k8HlJbpR38QYH2h80jLVHwAeamHaZl+9IfDNE1P/+XX19fp/f19w+QAAACU73A4/Jqm6fXrnzvkAuiWzbiwD98a0BNLBIFu2QsB+/CtAT0RYAHdshcC9uFbA3piiSDQrdIujbWMihRKLEelfWsAWzKDBVAIy6hIQTkCyMsMFkAhhmEIMcbmllGVOKMSQrnpWqvVcgRQCwEWwAopO+mtLqO6zaiM45g7KZ+Umq61UpajVoNQgC1ZIgiwguVYj5V6wEGp6SqJ8g0wnwALYAWd9MduMyqlKTVdJVG+AeY7TNP09F9+fX2d3t/fN0wOAABA+Q6Hw69pml6//rk9WABUw54gAEpniSAA1bAnCIDSCbAAqIY9QQCUToAFQDUcTAFA6ezBAgAASESABQAAkIgACwAAIBEBFiEERx8DAKSiX9U3ARYhhN9HH4/jmDsprKBCB6iberwN+lV9E2ARQvg48jjG6OjjTFI1qCp0gLqlrMcFa/noV/XNMe2EEBx9nFuqy1PdEQRQt5T1uIu589Gv6psACwqQqkFVoQPULWU9btAN8jhM0/T0X359fZ3e3983TA4AAED5DofDr2maXr/+uT1YAAAAiQiwAAAAEhFgAf/FiVMA66hHAYdcAP/FiVMA66hHATNYsEJrI5Xu7QBYp7V6tLV2DvbgFEFY4XQ6hfP5HGKMRioBaI52Du67d4qgJYKwgjtGAGiZdg7ms0QQVrhdCHk8HnMnhZ1YLkPPlP/+aOdgvq4CLA0DsNZtA/s4jrmTArtT/oG1euiPLw6waswcDQP0J3Vd1doGdphji/JfY38CWK7G/vjcemrxHqwajyG1jhj6k7quui2XgR5tUf5r7E8Ay9XYH59bTy0OsGrMHB0j6E+NdRX3Xa/XMI5jGIbBnpBG+EahLzX2x+fWU45pB6AajowGoBT3jmnv6pALgFLYd7KMPXDLKG8A+3EPFkAG9p0sU+PSkhIobwD7MYMFzGIkPI1eZmJKLy+lpy+VXsrbHnopM8By9mABs9gDwxyll5fS00d5lBngxh6shhlNY09Gwpmj9PJSevoojzLDXvTv6mUGqwFG09Jw/DMArKc9TUP/rnxmsBpmNC2NGm8Wb5mRO+BZ6ouyaE/T0L+rl1MEG+BUrTRcdlkWp54Bz1JflEV7mob+Xb0EWPCfVGRl0UADz1JflEV7Su/swQIAAJjJHiwAAICNCbAAAAASEWABVMJJaYSgHACUziEXAJVwUhohKAcApTODBVCJHHeimC35WY78cTcOQNmcIgjAXafTKZzP5xBjNFvyDfkD0K97pwhaIgjAXe4X+pn8AeArSwT/YCkMwGe3C0OPx2PupBRJ/gB8pj8twPrktnF4HMek/66CRguUY4AP6kNasFU53qo/XRNLBP+w1VIPJz7RAuUY4IP6kBZsVY4tnRZgfXJb6pGagkYLlGOAD+pDWrBVOd6qP10TpwgCu7per2EcxzAMg30rwO7UQUAq904RnBVgHQ6H/xtC+D8pEwZ053+FEP57COH/CyH878xpAfqjDgJS+Z/TNP2Pr384K8ACAADgPqcIAgAAJCLAAgAASESABQAAkIgACwAAIBEBFgAAQCICLAAAgEQEWAAAAIkIsAAAABIRYAEAACTy/wMr+aUPGIyQagAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:14.786886373153807 max: 190.10324949905626\n", + "image 1 reprojection errors: average:14.607954358420121 max: 192.53726502903967\n", + "image 2 reprojection errors: average:14.728698043711658 max: 183.91991478592809\n", + "image 3 reprojection errors: average:14.44770821132096 max: 232.5829101540651\n", + "image 4 reprojection errors: average:15.008736661881418 max: 133.28420271451168\n", + "image 5 reprojection errors: average:14.857650597212437 max: 142.22332463053175\n", + "image 6 reprojection errors: average:14.674016276931297 max: 209.7859571449106\n", + "image 7 reprojection errors: average:14.444423437139449 max: 125.5522654996809\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7165e+06 3.44e+06 \n", + " 1 2 5.1499e+03 1.71e+06 6.56e+01 1.12e+05 \n", + " 2 3 4.0778e+03 1.07e+03 8.31e-01 3.76e+02 \n", + " 3 4 4.0689e+03 8.83e+00 4.55e-01 1.29e+02 \n", + " 4 5 4.0667e+03 2.18e+00 8.01e-02 1.31e+01 \n", + " 5 6 4.0664e+03 3.78e-01 2.73e-02 1.00e+01 \n", + " 6 7 4.0662e+03 1.45e-01 1.15e-02 1.20e+01 \n", + " 7 8 4.0661e+03 7.92e-02 6.53e-03 7.25e+00 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 1.7165e+06, final cost 4.0661e+03, first-order optimality 7.25e+00.\n", + "mean reprojection error: 0.8493583260943721\n", + "max reprojection error: 3.1773291096319323\n", + "mean reconstruction error: 0.07784647312357885\n", + "max reconstruction error: 0.37106891173383005\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:15.21555442453697 max: 212.5602805629668\n", + "image 1 reprojection errors: average:15.385701401055705 max: 134.74106546704564\n", + "image 2 reprojection errors: average:15.18630342490676 max: 223.85509090839136\n", + "image 3 reprojection errors: average:15.062735667876268 max: 150.4733324102652\n", + "image 4 reprojection errors: average:15.06790703444719 max: 141.02672234836325\n", + "image 5 reprojection errors: average:15.159452729156817 max: 161.32665153106552\n", + "image 6 reprojection errors: average:15.415041416637276 max: 134.11209568701562\n", + "image 7 reprojection errors: average:15.071208564407637 max: 167.68292921829732\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8218e+06 3.45e+06 \n", + " 1 2 3.8401e+04 1.78e+06 6.70e+01 8.61e+04 \n", + " 2 3 3.7552e+04 8.49e+02 7.58e-01 1.08e+03 \n", + " 3 4 3.7514e+04 3.85e+01 7.20e-01 4.35e+02 \n", + " 4 5 3.7501e+04 1.25e+01 1.46e-01 4.96e+01 \n", + " 5 6 3.7498e+04 2.94e+00 7.93e-02 5.19e+01 \n", + " 6 7 3.7497e+04 1.62e+00 2.61e-02 3.27e+01 \n", + " 7 8 3.7496e+04 7.37e-01 1.93e-02 3.79e+01 \n", + " 8 9 3.7495e+04 6.31e-01 1.58e-02 3.72e+01 \n", + " 9 10 3.7495e+04 6.10e-01 1.70e-02 4.63e+01 \n", + " 10 11 3.7494e+04 5.75e-01 1.43e-02 4.49e+01 \n", + " 11 12 3.7494e+04 4.22e-01 1.10e-02 7.68e+01 \n", + " 12 13 3.7494e+04 3.11e-01 6.17e-03 5.96e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 1.8218e+06, final cost 3.7494e+04, first-order optimality 5.96e+01.\n", + "mean reprojection error: 2.579526455545454\n", + "max reprojection error: 9.485862455868327\n", + "mean reconstruction error: 0.235926820678703\n", + "max reconstruction error: 1.1472195478840423\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:15.770182188947775 max: 163.3502226815795\n", + "image 1 reprojection errors: average:15.7891505816311 max: 161.20079501799412\n", + "image 2 reprojection errors: average:16.104982073994105 max: 223.24028598658467\n", + "image 3 reprojection errors: average:15.650416681820715 max: 161.65908002006174\n", + "image 4 reprojection errors: average:16.222650323038255 max: 164.16128398927933\n", + "image 5 reprojection errors: average:15.92165185959968 max: 212.238726576011\n", + "image 6 reprojection errors: average:15.59909566028454 max: 192.2656584536024\n", + "image 7 reprojection errors: average:15.4762154254655 max: 145.25417091585746\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.9107e+06 6.67e+06 \n", + " 1 2 1.0324e+05 1.81e+06 6.73e+01 1.02e+05 \n", + " 2 3 1.0240e+05 8.39e+02 1.02e+00 2.06e+03 \n", + " 3 4 1.0232e+05 8.28e+01 8.74e-01 1.17e+03 \n", + " 4 5 1.0227e+05 4.30e+01 2.36e-01 1.17e+02 \n", + " 5 6 1.0226e+05 1.18e+01 1.59e-01 9.55e+01 \n", + " 6 7 1.0225e+05 9.36e+00 8.81e-02 7.97e+01 \n", + " 7 8 1.0225e+05 3.92e+00 5.33e-02 6.84e+01 \n", + " 8 9 1.0225e+05 2.96e+00 3.72e-02 7.89e+01 \n", + " 9 10 1.0224e+05 2.45e+00 3.40e-02 7.43e+01 \n", + " 10 11 1.0224e+05 2.36e+00 3.21e-02 7.36e+01 \n", + " 11 12 1.0224e+05 2.28e+00 3.25e-02 7.41e+01 \n", + " 12 13 1.0224e+05 2.21e+00 3.07e-02 6.89e+01 \n", + " 13 14 1.0223e+05 2.16e+00 3.14e-02 7.16e+01 \n", + " 14 15 1.0223e+05 2.09e+00 2.95e-02 6.47e+01 \n", + " 15 16 1.0223e+05 1.95e+00 2.89e-02 6.43e+01 \n", + " 16 17 1.0223e+05 1.92e+00 2.80e-02 7.23e+01 \n", + " 17 18 1.0223e+05 1.82e+00 2.70e-02 6.99e+01 \n", + " 18 19 1.0222e+05 1.91e+00 2.85e-02 9.33e+01 \n", + " 19 20 1.0222e+05 1.80e+00 2.58e-02 8.18e+01 \n", + " 20 21 1.0222e+05 1.74e+00 2.65e-02 1.02e+02 \n", + " 21 22 1.0222e+05 1.70e+00 2.48e-02 8.42e+01 \n", + " 22 23 1.0222e+05 1.60e+00 2.44e-02 1.09e+02 \n", + " 23 24 1.0222e+05 1.31e+00 1.79e-02 1.21e+02 \n", + " 24 25 1.0222e+05 7.27e-01 8.30e-03 8.94e+01 \n", + " 25 26 1.0221e+05 3.59e-01 4.52e-03 6.15e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 26, initial cost 1.9107e+06, final cost 1.0221e+05, first-order optimality 6.15e+01.\n", + "mean reprojection error: 4.255669876037859\n", + "max reprojection error: 16.6184602946805\n", + "mean reconstruction error: 0.38357843001089625\n", + "max reconstruction error: 1.8819894676257656\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1464 features\n", + "image 0 reprojection errors: average:17.87923891188316 max: 163.4670006845407\n", + "image 1 reprojection errors: average:19.01224352505981 max: 200.68993629781923\n", + "image 2 reprojection errors: average:17.774121345865154 max: 139.97253339504144\n", + "image 3 reprojection errors: average:18.140056466892823 max: 200.3031631749373\n", + "image 4 reprojection errors: average:18.399963400294318 max: 207.2190151450603\n", + "image 5 reprojection errors: average:18.097554509746292 max: 177.14510738218078\n", + "image 6 reprojection errors: average:18.160465932142834 max: 286.1350166919545\n", + "image 7 reprojection errors: average:18.062487725828692 max: 211.90072163647443\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3533e+06 5.15e+06 \n", + " 1 2 4.1909e+05 1.93e+06 7.32e+01 3.66e+05 \n", + " 2 3 4.1693e+05 2.17e+03 1.93e+00 1.14e+04 \n", + " 3 4 4.1647e+05 4.61e+02 2.28e+00 5.56e+03 \n", + " 4 5 4.1625e+05 2.16e+02 4.97e-01 7.28e+02 \n", + " 5 6 4.1620e+05 4.82e+01 3.18e-01 2.81e+02 \n", + " 6 7 4.1617e+05 3.59e+01 1.56e-01 2.82e+02 \n", + " 7 8 4.1615e+05 1.66e+01 1.16e-01 1.98e+02 \n", + " 8 9 4.1614e+05 1.22e+01 7.06e-02 1.96e+02 \n", + " 9 10 4.1613e+05 1.03e+01 7.77e-02 1.85e+02 \n", + " 10 11 4.1612e+05 9.97e+00 6.27e-02 1.92e+02 \n", + " 11 12 4.1611e+05 9.58e+00 7.42e-02 1.74e+02 \n", + " 12 13 4.1610e+05 9.38e+00 6.05e-02 1.93e+02 \n", + " 13 14 4.1609e+05 8.99e+00 7.09e-02 1.64e+02 \n", + " 14 15 4.1608e+05 8.85e+00 5.86e-02 1.97e+02 \n", + " 15 16 4.1607e+05 7.74e+00 6.13e-02 2.02e+02 \n", + " 16 17 4.1606e+05 8.20e+00 5.69e-02 3.22e+02 \n", + " 17 18 4.1606e+05 6.79e+00 5.02e-02 2.75e+02 \n", + " 18 19 4.1605e+05 5.15e+00 3.20e-02 4.68e+02 \n", + " 19 20 4.1605e+05 2.42e+00 1.20e-02 1.55e+02 \n", + " 20 21 4.1604e+05 1.18e+01 1.17e-01 1.50e+03 \n", + " 21 22 4.1603e+05 9.96e+00 1.94e-02 1.02e+02 \n", + " 22 23 4.1602e+05 5.32e+00 5.52e-02 7.97e+02 \n", + " 23 24 4.1602e+05 4.64e+00 1.20e-02 7.75e+01 \n", + " 24 25 4.1599e+05 2.70e+01 3.13e-01 1.77e+03 \n", + " 25 26 4.1597e+05 2.47e+01 5.47e-02 9.11e+01 \n", + " 26 27 4.1596e+05 1.15e+00 1.27e-02 2.63e+02 \n", + " 27 28 4.1596e+05 1.11e+00 5.98e-03 7.71e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 28, initial cost 2.3533e+06, final cost 4.1596e+05, first-order optimality 7.71e+01.\n", + "mean reprojection error: 8.584057197663814\n", + "max reprojection error: 30.479432393561016\n", + "mean reconstruction error: 0.7886446430754868\n", + "max reconstruction error: 3.5033006455399907\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony a7R-IV" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "ratio = np.array([9504/6000,6336/4000])\n", + "focal_length = np.array([2925.84685880484, 2930.0351899542])*ratio\n", + "principle_point = np.array([3000, 2000])*ratio\n", + "radial_distortion = np.array([-0.251288719187471, 0.0622370807856553])#[-0.28009, 0.11246, -0.02736])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([9504, 6336])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, camera_halfz_position, camera_radial_position],\n", + " [0, camera_halfz_position, -camera_radial_position],\n", + " [camera_radial_position, -camera_halfz_position, 0],\n", + " [-camera_radial_position, -camera_halfz_position, 0]])\n", + "camera_directions = [[0, -1.1, -1],\n", + " [0, -1.1, 1],\n", + " [-1, 1.1, 0],\n", + " [1, 1.1, 0]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.520390402995194 max: 185.70287979566353\n", + "image 1 reprojection errors: average: 22.26358912963671 max: 267.1689273880863\n", + "image 2 reprojection errors: average: 21.984447896212796 max: 222.64995498925018\n", + "image 3 reprojection errors: average: 22.211958002703994 max: 283.77446306759606\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8934e+06 6.15e+06 \n", + " 1 2 3.6471e+03 1.89e+06 6.72e+01 1.95e+05 \n", + " 2 3 1.3059e+03 2.34e+03 4.38e+00 2.03e+03 \n", + " 3 4 1.3035e+03 2.45e+00 1.21e-01 6.84e+02 \n", + " 4 5 1.3029e+03 5.78e-01 3.15e-02 1.28e+02 \n", + " 5 6 1.3027e+03 2.18e-01 1.61e-02 8.96e+01 \n", + " 6 7 1.3026e+03 1.04e-01 8.21e-03 2.85e+01 \n", + " 7 8 1.3025e+03 5.72e-02 4.60e-03 2.74e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 1.8934e+06, final cost 1.3025e+03, first-order optimality 2.74e+01.\n", + "mean reprojection error: 0.6388473110821935\n", + "max reprojection error: 2.6315289284078736\n", + "mean reconstruction error: 0.07395240275817924\n", + "max reconstruction error: 0.32834927168588207\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.711888913566533 max: 184.46919675350037\n", + "image 1 reprojection errors: average: 22.549763121108743 max: 195.46446511289201\n", + "image 2 reprojection errors: average: 22.861226692956464 max: 244.14570798266172\n", + "image 3 reprojection errors: average: 23.888202881192218 max: 483.1818774192915\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0557e+06 8.29e+06 \n", + " 1 2 1.9304e+04 2.04e+06 7.12e+01 7.65e+05 \n", + " 2 3 1.2004e+04 7.30e+03 8.34e-01 3.02e+04 \n", + " 3 4 1.1981e+04 2.25e+01 2.27e-01 2.31e+03 \n", + " 4 5 1.1977e+04 3.99e+00 4.71e-02 2.83e+02 \n", + " 5 6 1.1976e+04 1.69e+00 3.37e-02 1.65e+02 \n", + " 6 7 1.1975e+04 1.18e+00 1.86e-02 1.21e+02 \n", + " 7 8 1.1973e+04 1.23e+00 3.04e-02 1.87e+02 \n", + " 8 9 1.1972e+04 8.49e-01 1.13e-02 6.25e+01 \n", + " 9 10 1.1972e+04 9.18e-01 2.82e-02 1.87e+02 \n", + " 10 11 1.1971e+04 8.16e-01 1.03e-02 4.96e+01 \n", + " 11 12 1.1970e+04 8.74e-01 2.92e-02 1.84e+02 \n", + " 12 13 1.1969e+04 7.97e-01 9.66e-03 4.00e+01 \n", + " 13 14 1.1969e+04 3.66e-01 1.22e-02 9.61e+01 \n", + " 14 15 1.1968e+04 4.12e-01 7.55e-03 5.03e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 15, initial cost 2.0557e+06, final cost 1.1968e+04, first-order optimality 5.03e+01.\n", + "mean reprojection error: 1.9470376716553401\n", + "max reprojection error: 8.76596845887681\n", + "mean reconstruction error: 0.22444447866170772\n", + "max reconstruction error: 1.0470452237867538\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.958458395369146 max: 191.04954543740516\n", + "image 1 reprojection errors: average: 22.471435732132797 max: 262.8019902299815\n", + "image 2 reprojection errors: average: 23.02204045802236 max: 359.79576912051186\n", + "image 3 reprojection errors: average: 23.02568017986665 max: 385.04619593986587\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0767e+06 6.26e+06 \n", + " 1 2 3.8056e+04 2.04e+06 7.05e+01 1.97e+05 \n", + " 2 3 3.5071e+04 2.99e+03 7.76e-01 3.34e+03 \n", + " 3 4 3.5017e+04 5.33e+01 7.22e-01 2.76e+03 \n", + " 4 5 3.5002e+04 1.52e+01 1.41e-01 3.33e+02 \n", + " 5 6 3.4998e+04 3.74e+00 6.49e-02 1.80e+02 \n", + " 6 7 3.4996e+04 2.39e+00 3.76e-02 9.19e+01 \n", + " 7 8 3.4995e+04 1.15e+00 1.93e-02 7.15e+01 \n", + " 8 9 3.4994e+04 6.47e-01 1.02e-02 4.74e+01 \n", + " 9 10 3.4994e+04 4.14e-01 7.63e-03 4.95e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 2.0767e+06, final cost 3.4994e+04, first-order optimality 4.95e+01.\n", + "mean reprojection error: 3.3216849504158836\n", + "max reprojection error: 13.65539615610933\n", + "mean reconstruction error: 0.362063983717853\n", + "max reconstruction error: 1.4649157297696673\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "4 images with total of 1584 features\n", + "image 0 reprojection errors: average: 23.741571765472546 max: 237.00736672231469\n", + "image 1 reprojection errors: average: 24.750985504093233 max: 330.2517559366125\n", + "image 2 reprojection errors: average: 24.546894133014984 max: 317.998241764834\n", + "image 3 reprojection errors: average: 25.441199696266413 max: 451.3968358437266\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3795e+06 9.89e+06 \n", + " 1 2 1.4743e+05 2.23e+06 7.59e+01 5.37e+05 \n", + " 2 3 1.3847e+05 8.96e+03 1.14e+00 2.01e+04 \n", + " 3 4 1.3829e+05 1.78e+02 1.20e+00 1.79e+04 \n", + " 4 5 1.3824e+05 5.21e+01 1.62e-01 1.39e+03 \n", + " 5 6 1.3823e+05 8.50e+00 6.18e-02 5.73e+02 \n", + " 6 7 1.3823e+05 4.49e+00 2.84e-02 1.76e+02 \n", + " 7 8 1.3823e+05 3.11e+00 2.70e-02 3.95e+02 \n", + " 8 9 1.3822e+05 3.99e+00 3.19e-02 2.01e+02 \n", + " 9 10 1.3822e+05 2.09e+00 1.40e-02 1.29e+02 \n", + " 10 11 1.3822e+05 1.96e+00 2.14e-02 1.94e+02 \n", + " 11 12 1.3822e+05 1.92e+00 1.33e-02 1.21e+02 \n", + " 12 13 1.3821e+05 2.01e+00 2.25e-02 1.98e+02 \n", + " 13 14 1.3821e+05 1.92e+00 1.30e-02 1.06e+02 \n", + " 14 15 1.3821e+05 1.90e+00 2.19e-02 1.91e+02 \n", + " 15 16 1.3821e+05 1.86e+00 1.28e-02 9.95e+01 \n", + " 16 17 1.3821e+05 1.85e+00 2.17e-02 1.82e+02 \n", + " 17 18 1.3820e+05 1.82e+00 1.26e-02 9.34e+01 \n", + " 18 19 1.3820e+05 1.80e+00 2.15e-02 1.79e+02 \n", + " 19 20 1.3820e+05 1.77e+00 1.23e-02 8.74e+01 \n", + " 20 21 1.3820e+05 1.74e+00 2.11e-02 1.76e+02 \n", + " 21 22 1.3820e+05 1.71e+00 1.21e-02 8.14e+01 \n", + " 22 23 1.3820e+05 1.69e+00 2.08e-02 1.73e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 23 24 1.3819e+05 1.67e+00 1.19e-02 7.55e+01 \n", + " 24 25 1.3819e+05 1.65e+00 2.05e-02 1.71e+02 \n", + " 25 26 1.3819e+05 1.63e+00 1.17e-02 7.04e+01 \n", + " 26 27 1.3819e+05 1.62e+00 2.04e-02 1.79e+02 \n", + " 27 28 1.3819e+05 1.60e+00 1.15e-02 7.26e+01 \n", + " 28 29 1.3819e+05 1.59e+00 2.04e-02 1.88e+02 \n", + " 29 30 1.3818e+05 1.57e+00 1.15e-02 7.13e+01 \n", + " 30 31 1.3818e+05 1.56e+00 2.02e-02 2.08e+02 \n", + " 31 32 1.3818e+05 1.54e+00 1.13e-02 7.37e+01 \n", + " 32 33 1.3818e+05 1.31e+00 1.70e-02 2.00e+02 \n", + " 33 34 1.3818e+05 1.31e+00 1.04e-02 8.36e+01 \n", + " 34 35 1.3818e+05 1.30e+00 1.69e-02 2.14e+02 \n", + " 35 36 1.3818e+05 1.28e+00 1.03e-02 8.49e+01 \n", + " 36 37 1.3818e+05 1.26e+00 1.66e-02 2.26e+02 \n", + " 37 38 1.3817e+05 1.24e+00 1.00e-02 9.13e+01 \n", + " 38 39 1.3817e+05 1.10e+00 1.43e-02 2.97e+02 \n", + " 39 40 1.3817e+05 1.21e+00 1.01e-02 1.38e+02 \n", + " 40 41 1.3817e+05 9.00e-01 1.06e-02 2.78e+02 \n", + " 41 42 1.3817e+05 8.58e-01 7.20e-03 1.89e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 42, initial cost 2.3795e+06, final cost 1.3817e+05, first-order optimality 1.89e+02.\n", + "mean reprojection error: 6.60901696250545\n", + "max reprojection error: 30.188506880869582\n", + "mean reconstruction error: 0.7296500078394403\n", + "max reconstruction error: 3.2310657203260353\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_4_a7r = {}\n", + "centre_errors_4_a7r = {}\n", + "orientation_errors_4_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_4_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_4_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_4_a7r[pixel_error] = run_led_fit(fitter, led_positions_4_a7r)\n", + " centre_errors_4_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_4_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_4_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_4_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_4_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_4_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_4_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_4_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 163.0\n", + "camera_halfz_position = 168.0\n", + "camera_positions = np.array([\n", + " [-camera_radial_position, -camera_halfz_position, 0],\n", + " [0.5*camera_radial_position, -camera_halfz_position, -camera_radial_position*np.sqrt(3)/2],\n", + " [0.5*camera_radial_position, -camera_halfz_position, camera_radial_position*np.sqrt(3)/2],\n", + " [camera_radial_position, camera_halfz_position, 0],\n", + " [-0.5*camera_radial_position, camera_halfz_position, -camera_radial_position*np.sqrt(3)/2],\n", + " [-0.5*camera_radial_position, camera_halfz_position, camera_radial_position*np.sqrt(3)/2]])\n", + "camera_directions = [[1, 1.1, 0],\n", + " [-0.5, 1.1, np.sqrt(3)/2],\n", + " [-0.5, 1.1, -np.sqrt(3)/2],\n", + " [-1, -1.1, 0],\n", + " [0.5, -1.1, np.sqrt(3)/2],\n", + " [0.5, -1.1, -np.sqrt(3)/2]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1464 features\n", + "image 0 reprojection errors: average:13.978017772964328 max: 145.31136855544065\n", + "image 1 reprojection errors: average:14.136888229601206 max: 139.5719690221988\n", + "image 2 reprojection errors: average:14.465490204161433 max: 139.87661944995034\n", + "image 3 reprojection errors: average:14.4111116339794 max: 161.18948034555348\n", + "image 4 reprojection errors: average:14.71148915244337 max: 277.7149999790131\n", + "image 5 reprojection errors: average:14.406881660720005 max: 197.1780706253896\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.1821e+06 3.76e+06 \n", + " 1 2 5.1431e+03 1.18e+06 6.68e+01 3.03e+05 \n", + " 2 3 2.6178e+03 2.53e+03 1.85e+00 5.78e+03 \n", + " 3 4 2.5903e+03 2.75e+01 1.40e+00 4.62e+03 \n", + " 4 5 2.5802e+03 1.02e+01 2.84e-01 2.89e+02 \n", + " 5 6 2.5788e+03 1.41e+00 9.16e-02 1.06e+02 \n", + " 6 7 2.5782e+03 6.02e-01 3.35e-02 3.16e+01 \n", + " 7 8 2.5778e+03 3.32e-01 2.25e-02 4.62e+01 \n", + " 8 9 2.5776e+03 2.48e-01 1.70e-02 2.63e+01 \n", + " 9 10 2.5774e+03 1.57e-01 1.01e-02 2.66e+01 \n", + " 10 11 2.5773e+03 1.45e-01 1.18e-02 2.67e+01 \n", + " 11 12 2.5771e+03 1.39e-01 9.18e-03 2.63e+01 \n", + " 12 13 2.5770e+03 1.35e-01 1.12e-02 2.59e+01 \n", + " 13 14 2.5769e+03 1.30e-01 8.66e-03 2.53e+01 \n", + " 14 15 2.5767e+03 1.28e-01 1.08e-02 2.49e+01 \n", + " 15 16 2.5766e+03 1.24e-01 8.29e-03 2.44e+01 \n", + " 16 17 2.5765e+03 1.23e-01 1.07e-02 2.41e+01 \n", + " 17 18 2.5764e+03 1.19e-01 8.01e-03 2.36e+01 \n", + " 18 19 2.5763e+03 1.16e-01 1.02e-02 2.28e+01 \n", + " 19 20 2.5761e+03 1.15e-01 7.90e-03 2.34e+01 \n", + " 20 21 2.5760e+03 1.15e-01 1.03e-02 2.20e+01 \n", + " 21 22 2.5759e+03 1.12e-01 7.69e-03 2.31e+01 \n", + " 22 23 2.5758e+03 1.03e-01 9.33e-03 1.99e+01 \n", + " 23 24 2.5757e+03 1.00e-01 7.19e-03 2.25e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 24, initial cost 1.1821e+06, final cost 2.5757e+03, first-order optimality 2.25e+01.\n", + "mean reprojection error: 0.7986354300414925\n", + "max reprojection error: 3.082997216150026\n", + "mean reconstruction error: 0.09823014836580667\n", + "max reconstruction error: 0.5095816120151656\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1464 features\n", + "image 0 reprojection errors: average:14.888396016758051 max: 300.4744421066439\n", + "image 1 reprojection errors: average:14.91760699266425 max: 151.40454721099925\n", + "image 2 reprojection errors: average:15.04713401280328 max: 220.47266862224117\n", + "image 3 reprojection errors: average:14.715367403381425 max: 205.06845461541445\n", + "image 4 reprojection errors: average:14.859446009405374 max: 251.6013293150552\n", + "image 5 reprojection errors: average:14.674553646746586 max: 329.0846716864259\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.3562e+06 4.40e+06 \n", + " 1 2 2.6960e+04 1.33e+06 6.72e+01 4.60e+05 \n", + " 2 3 2.3423e+04 3.54e+03 1.73e+00 1.19e+04 \n", + " 3 4 2.3317e+04 1.07e+02 2.26e+00 9.08e+03 \n", + " 4 5 2.3278e+04 3.89e+01 4.16e-01 5.67e+02 \n", + " 5 6 2.3272e+04 5.47e+00 1.51e-01 3.01e+02 \n", + " 6 7 2.3269e+04 2.99e+00 6.94e-02 8.66e+01 \n", + " 7 8 2.3268e+04 1.31e+00 3.16e-02 4.29e+01 \n", + " 8 9 2.3267e+04 1.16e+00 3.67e-02 8.20e+01 \n", + " 9 10 2.3266e+04 1.12e+00 2.72e-02 4.57e+01 \n", + " 10 11 2.3265e+04 1.02e+00 3.17e-02 8.09e+01 \n", + " 11 12 2.3264e+04 9.62e-01 2.40e-02 4.32e+01 \n", + " 12 13 2.3263e+04 9.37e-01 3.00e-02 8.10e+01 \n", + " 13 14 2.3262e+04 9.04e-01 2.29e-02 4.14e+01 \n", + " 14 15 2.3262e+04 5.58e-01 1.71e-02 4.41e+01 \n", + " 15 16 2.3261e+04 5.39e-01 1.70e-02 4.32e+01 \n", + " 16 17 2.3260e+04 5.41e-01 1.66e-02 5.18e+01 \n", + " 17 18 2.3260e+04 6.77e-01 2.19e-02 5.96e+01 \n", + " 18 19 2.3259e+04 7.50e-01 2.12e-02 6.55e+01 \n", + " 19 20 2.3258e+04 7.73e-01 2.41e-02 6.03e+01 \n", + " 20 21 2.3258e+04 4.40e-01 1.10e-02 2.27e+01 \n", + " 21 22 2.3257e+04 4.14e-01 1.70e-02 4.97e+01 \n", + " 22 23 2.3257e+04 4.15e-01 1.08e-02 2.72e+01 \n", + " 23 24 2.3257e+04 3.92e-01 1.61e-02 4.30e+01 \n", + " 24 25 2.3256e+04 3.97e-01 1.06e-02 3.30e+01 \n", + " 25 26 2.3256e+04 3.61e-01 1.47e-02 4.11e+01 \n", + " 26 27 2.3255e+04 3.56e-01 9.97e-03 3.71e+01 \n", + " 27 28 2.3255e+04 3.50e-01 1.43e-02 4.16e+01 \n", + " 28 29 2.3255e+04 3.46e-01 9.77e-03 3.92e+01 \n", + " 29 30 2.3254e+04 3.37e-01 1.38e-02 4.16e+01 \n", + " 30 31 2.3254e+04 3.31e-01 9.45e-03 4.00e+01 \n", + " 31 32 2.3254e+04 3.14e-01 1.28e-02 3.94e+01 \n", + " 32 33 2.3253e+04 3.04e-01 8.75e-03 4.11e+01 \n", + " 33 34 2.3253e+04 2.71e-01 1.09e-02 3.38e+01 \n", + " 34 35 2.3253e+04 2.60e-01 7.62e-03 4.18e+01 \n", + " 35 36 2.3253e+04 2.38e-01 9.50e-03 3.21e+01 \n", + " 36 37 2.3252e+04 2.35e-01 7.06e-03 4.17e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 37, initial cost 1.3562e+06, final cost 2.3252e+04, first-order optimality 4.17e+01.\n", + "mean reprojection error: 2.3822390565536065\n", + "max reprojection error: 8.84706051004759\n", + "mean reconstruction error: 0.2925136371661761\n", + "max reconstruction error: 2.112809179262706\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1464 features\n", + "image 0 reprojection errors: average:15.057111186827262 max: 214.43711346584686\n", + "image 1 reprojection errors: average:14.698058009892694 max: 267.49348047303477\n", + "image 2 reprojection errors: average:15.047068335305054 max: 200.24305564224068\n", + "image 3 reprojection errors: average:14.599682769043545 max: 139.75207351261867\n", + "image 4 reprojection errors: average:15.875624433428612 max: 751.2307180782722\n", + "image 5 reprojection errors: average:14.942134425345754 max: 171.17733013979486\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.5085e+06 1.45e+07 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 1 2 8.6532e+04 1.42e+06 6.61e+01 2.09e+06 \n", + " 2 3 6.3456e+04 2.31e+04 2.75e+00 2.10e+05 \n", + " 3 4 6.3013e+04 4.43e+02 1.33e+00 2.12e+04 \n", + " 4 5 6.2922e+04 9.13e+01 1.01e+00 4.45e+03 \n", + " 5 6 6.2875e+04 4.71e+01 2.89e-01 7.37e+02 \n", + " 6 7 6.2853e+04 2.16e+01 3.11e-01 6.18e+02 \n", + " 7 8 6.2837e+04 1.61e+01 1.38e-01 3.31e+02 \n", + " 8 9 6.2828e+04 9.34e+00 1.40e-01 4.34e+02 \n", + " 9 10 6.2820e+04 8.04e+00 7.85e-02 2.51e+02 \n", + " 10 11 6.2812e+04 7.95e+00 1.30e-01 4.17e+02 \n", + " 11 12 6.2806e+04 6.40e+00 5.67e-02 1.84e+02 \n", + " 12 13 6.2801e+04 4.19e+00 7.32e-02 2.79e+02 \n", + " 13 14 6.2798e+04 3.84e+00 4.05e-02 1.57e+02 \n", + " 14 15 6.2794e+04 3.71e+00 6.82e-02 2.67e+02 \n", + " 15 16 6.2790e+04 3.44e+00 3.60e-02 1.40e+02 \n", + " 16 17 6.2787e+04 3.59e+00 6.99e-02 2.68e+02 \n", + " 17 18 6.2783e+04 3.33e+00 3.35e-02 1.24e+02 \n", + " 18 19 6.2780e+04 3.58e+00 7.43e-02 2.75e+02 \n", + " 19 20 6.2777e+04 3.31e+00 3.15e-02 1.09e+02 \n", + " 20 21 6.2773e+04 3.42e+00 7.52e-02 2.72e+02 \n", + " 21 22 6.2770e+04 3.28e+00 3.06e-02 1.01e+02 \n", + " 22 23 6.2767e+04 3.36e+00 7.69e-02 2.73e+02 \n", + " 23 24 6.2763e+04 3.22e+00 2.95e-02 9.27e+01 \n", + " 24 25 6.2760e+04 3.24e+00 7.70e-02 2.73e+02 \n", + " 25 26 6.2757e+04 3.09e+00 2.78e-02 8.28e+01 \n", + " 26 27 6.2754e+04 3.02e+00 7.43e-02 2.67e+02 \n", + " 27 28 6.2751e+04 2.86e+00 2.56e-02 7.16e+01 \n", + " 28 29 6.2748e+04 2.80e+00 7.15e-02 2.60e+02 \n", + " 29 30 6.2746e+04 2.70e+00 2.43e-02 6.45e+01 \n", + " 30 31 6.2745e+04 1.06e+00 2.65e-02 1.18e+02 \n", + " 31 32 6.2743e+04 1.58e+00 2.43e-02 1.32e+02 \n", + " 32 33 6.2742e+04 7.93e-01 1.47e-02 5.82e+01 \n", + " 33 34 6.2741e+04 7.37e-01 1.54e-02 1.17e+02 \n", + " 34 35 6.2741e+04 7.22e-01 1.37e-02 5.67e+01 \n", + " 35 36 6.2740e+04 7.13e-01 1.50e-02 1.12e+02 \n", + " 36 37 6.2739e+04 6.73e-01 1.28e-02 5.28e+01 \n", + " 37 38 6.2739e+04 7.12e-01 1.54e-02 1.25e+02 \n", + " 38 39 6.2738e+04 6.93e-01 1.28e-02 5.44e+01 \n", + " 39 40 6.2737e+04 6.26e-01 1.36e-02 1.12e+02 \n", + " 40 41 6.2737e+04 6.32e-01 1.22e-02 6.45e+01 \n", + " 41 42 6.2736e+04 9.54e-01 2.15e-02 1.86e+02 \n", + " 42 43 6.2735e+04 7.49e-01 1.13e-02 4.52e+01 \n", + " 43 44 6.2734e+04 7.44e-01 1.90e-02 1.75e+02 \n", + " 44 45 6.2733e+04 7.38e-01 1.12e-02 4.47e+01 \n", + " 45 46 6.2733e+04 7.33e-01 1.88e-02 1.65e+02 \n", + " 46 47 6.2732e+04 7.27e-01 1.12e-02 4.43e+01 \n", + " 47 48 6.2731e+04 7.22e-01 1.86e-02 1.58e+02 \n", + " 48 49 6.2731e+04 7.17e-01 1.11e-02 4.39e+01 \n", + " 49 50 6.2730e+04 7.11e-01 1.84e-02 1.51e+02 \n", + " 50 51 6.2729e+04 7.06e-01 1.10e-02 4.34e+01 \n", + " 51 52 6.2728e+04 7.01e-01 1.82e-02 1.45e+02 \n", + " 52 53 6.2728e+04 6.96e-01 1.10e-02 4.28e+01 \n", + " 53 54 6.2727e+04 6.91e-01 1.81e-02 1.40e+02 \n", + " 54 55 6.2726e+04 6.86e-01 1.09e-02 4.22e+01 \n", + " 55 56 6.2726e+04 6.81e-01 1.79e-02 1.36e+02 \n", + " 56 57 6.2725e+04 6.76e-01 1.09e-02 4.18e+01 \n", + " 57 58 6.2724e+04 6.71e-01 1.77e-02 1.33e+02 \n", + " 58 59 6.2724e+04 6.66e-01 1.08e-02 4.20e+01 \n", + " 59 60 6.2723e+04 6.62e-01 1.76e-02 1.30e+02 \n", + " 60 61 6.2722e+04 6.57e-01 1.07e-02 4.21e+01 \n", + " 61 62 6.2722e+04 6.53e-01 1.74e-02 1.28e+02 \n", + " 62 63 6.2721e+04 6.48e-01 1.07e-02 4.21e+01 \n", + " 63 64 6.2720e+04 6.44e-01 1.72e-02 1.26e+02 \n", + " 64 65 6.2720e+04 6.39e-01 1.06e-02 4.20e+01 \n", + " 65 66 6.2719e+04 6.35e-01 1.71e-02 1.24e+02 \n", + " 66 67 6.2718e+04 6.30e-01 1.06e-02 4.18e+01 \n", + " 67 68 6.2718e+04 6.26e-01 1.69e-02 1.23e+02 \n", + " 68 69 6.2717e+04 6.22e-01 1.05e-02 4.16e+01 \n", + " 69 70 6.2717e+04 6.18e-01 1.68e-02 1.22e+02 \n", + " 70 71 6.2716e+04 6.14e-01 1.04e-02 4.13e+01 \n", + " 71 72 6.2715e+04 6.01e-01 1.64e-02 1.23e+02 \n", + " 72 73 6.2715e+04 6.01e-01 1.03e-02 4.33e+01 \n", + " 73 74 6.2714e+04 5.97e-01 1.63e-02 1.22e+02 \n", + " 74 75 6.2714e+04 5.91e-01 1.02e-02 4.39e+01 \n", + " 75 76 6.2713e+04 5.86e-01 1.60e-02 1.23e+02 \n", + " 76 77 6.2712e+04 5.84e-01 1.01e-02 4.72e+01 \n", + " 77 78 6.2712e+04 5.76e-01 1.58e-02 1.28e+02 \n", + " 78 79 6.2711e+04 5.75e-01 1.01e-02 4.65e+01 \n", + " 79 80 6.2711e+04 5.26e-01 1.43e-02 1.35e+02 \n", + " 80 81 6.2710e+04 5.46e-01 9.76e-03 5.82e+01 \n", + " 81 82 6.2710e+04 5.44e-01 1.44e-02 1.37e+02 \n", + " 82 83 6.2709e+04 5.41e-01 9.72e-03 5.74e+01 \n", + " 83 84 6.2709e+04 5.16e-01 1.36e-02 1.39e+02 \n", + " 84 85 6.2708e+04 5.25e-01 9.59e-03 6.28e+01 \n", + " 85 86 6.2708e+04 5.23e-01 1.37e-02 1.40e+02 \n", + " 86 87 6.2707e+04 5.17e-01 9.47e-03 6.24e+01 \n", + " 87 88 6.2707e+04 5.16e-01 1.35e-02 1.44e+02 \n", + " 88 89 6.2706e+04 5.14e-01 9.41e-03 6.23e+01 \n", + " 89 90 6.2706e+04 3.88e-01 9.66e-03 1.36e+02 \n", + " 90 91 6.2705e+04 4.64e-01 9.09e-03 1.04e+02 \n", + " 91 92 6.2705e+04 2.09e-01 3.50e-03 5.95e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 92, initial cost 1.5085e+06, final cost 6.2705e+04, first-order optimality 5.95e+01.\n", + "mean reprojection error: 3.9233650372083066\n", + "max reprojection error: 14.956811009998903\n", + "mean reconstruction error: 0.4704561752504083\n", + "max reconstruction error: 2.645674355474469\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1464 features\n", + "image 0 reprojection errors: average:17.957744600122812 max: 306.06577330872835\n", + "image 1 reprojection errors: average:17.4923885209446 max: 280.7879981464677\n", + "image 2 reprojection errors: average:18.09043150588994 max: 176.31748049958998\n", + "image 3 reprojection errors: average:17.97458430847045 max: 179.29133447741557\n", + "image 4 reprojection errors: average:18.070346882322262 max: 292.42433191884066\n", + "image 5 reprojection errors: average:17.922786941086212 max: 131.80736714666142\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6547e+06 6.10e+06 \n", + " 1 2 2.6694e+05 1.39e+06 7.43e+01 4.18e+05 \n", + " 2 3 2.6259e+05 4.35e+03 5.03e+00 2.80e+04 \n", + " 3 4 2.6206e+05 5.27e+02 2.38e+00 6.45e+03 \n", + " 4 5 2.6179e+05 2.71e+02 9.00e-01 1.70e+03 \n", + " 5 6 2.6169e+05 1.05e+02 5.51e-01 5.46e+02 \n", + " 6 7 2.6162e+05 7.32e+01 3.29e-01 7.80e+02 \n", + " 7 8 2.6155e+05 6.49e+01 4.12e-01 5.56e+02 \n", + " 8 9 2.6149e+05 5.79e+01 2.76e-01 5.96e+02 \n", + " 9 10 2.6145e+05 3.88e+01 2.46e-01 4.46e+02 \n", + " 10 11 2.6142e+05 3.22e+01 1.73e-01 4.41e+02 \n", + " 11 12 2.6140e+05 2.44e+01 1.57e-01 3.67e+02 \n", + " 12 13 2.6138e+05 2.25e+01 1.33e-01 3.81e+02 \n", + " 13 14 2.6135e+05 2.12e+01 1.41e-01 3.77e+02 \n", + " 14 15 2.6133e+05 2.01e+01 1.21e-01 3.43e+02 \n", + " 15 16 2.6132e+05 1.53e+01 9.81e-02 3.06e+02 \n", + " 16 17 2.6131e+05 1.35e+01 9.00e-02 2.83e+02 \n", + " 17 18 2.6129e+05 1.30e+01 8.88e-02 3.25e+02 \n", + " 18 19 2.6128e+05 1.27e+01 8.55e-02 2.69e+02 \n", + " 19 20 2.6127e+05 1.24e+01 8.64e-02 3.50e+02 \n", + " 20 21 2.6125e+05 1.22e+01 8.30e-02 2.59e+02 \n", + " 21 22 2.6124e+05 1.20e+01 8.53e-02 3.73e+02 \n", + " 22 23 2.6123e+05 1.18e+01 8.11e-02 2.51e+02 \n", + " 23 24 2.6122e+05 1.16e+01 8.40e-02 3.90e+02 \n", + " 24 25 2.6121e+05 1.14e+01 7.96e-02 2.47e+02 \n", + " 25 26 2.6120e+05 1.03e+01 7.41e-02 3.64e+02 \n", + " 26 27 2.6119e+05 1.01e+01 7.37e-02 2.34e+02 \n", + " 27 28 2.6118e+05 9.95e+00 7.34e-02 3.75e+02 \n", + " 28 29 2.6117e+05 9.61e+00 7.05e-02 2.24e+02 \n", + " 29 30 2.6116e+05 9.50e+00 7.21e-02 3.80e+02 \n", + " 30 31 2.6115e+05 9.35e+00 6.91e-02 2.19e+02 \n", + " 31 32 2.6114e+05 9.33e+00 7.23e-02 3.87e+02 \n", + " 32 33 2.6113e+05 9.18e+00 6.80e-02 2.12e+02 \n", + " 33 34 2.6112e+05 9.24e+00 7.34e-02 3.93e+02 \n", + " 34 35 2.6111e+05 9.05e+00 6.68e-02 2.05e+02 \n", + " 35 36 2.6110e+05 9.21e+00 7.54e-02 4.01e+02 \n", + " 36 37 2.6110e+05 7.98e+00 5.65e-02 1.70e+02 \n", + " 37 38 2.6109e+05 9.86e+00 9.13e-02 4.88e+02 \n" + ] + }, + { + "ename": "KeyboardInterrupt", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mled_positions_6a_a7r\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mled_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mitems\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m 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print(list(jac_sparsity.sum(axis=1)))\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 163\u001b[0;31m self.opt_result = opt.least_squares(self.fit_errors, x0, verbose=2, method=method, xtol=xtol, jac_sparsity=jac_sparsity,\n\u001b[0m\u001b[1;32m 164\u001b[0m kwargs={\"max_error\":max_error, \"fit_cam\": fit_cam})\n\u001b[1;32m 165\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mopt_result\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfit_cam\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfit_cam\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreshape\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m 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"\u001b[0;32m/usr/lib64/python3.10/site-packages/scipy/optimize/_lsq/trf.py\u001b[0m in \u001b[0;36mtrf_no_bounds\u001b[0;34m(fun, jac, x0, f0, J0, ftol, xtol, gtol, max_nfev, x_scale, loss_function, tr_solver, tr_options, verbose)\u001b[0m\n\u001b[1;32m 534\u001b[0m \u001b[0mcost\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcost_new\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 535\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 536\u001b[0;31m \u001b[0mJ\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mjac\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 537\u001b[0m \u001b[0mnjev\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 538\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/lib64/python3.10/site-packages/scipy/optimize/_lsq/least_squares.py\u001b[0m in \u001b[0;36mjac_wrapped\u001b[0;34m(x, f)\u001b[0m\n\u001b[1;32m 884\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 885\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mjac_wrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 886\u001b[0;31m J = approx_derivative(fun, x, rel_step=diff_step, method=jac,\n\u001b[0m\u001b[1;32m 887\u001b[0m \u001b[0mf0\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbounds\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbounds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 888\u001b[0m kwargs=kwargs, sparsity=jac_sparsity)\n", + "\u001b[0;32m/usr/lib64/python3.10/site-packages/scipy/optimize/_numdiff.py\u001b[0m in \u001b[0;36mapprox_derivative\u001b[0;34m(fun, x0, method, rel_step, abs_step, f0, bounds, sparsity, as_linear_operator, args, kwargs)\u001b[0m\n\u001b[1;32m 499\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 500\u001b[0m \u001b[0mgroups\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0matleast_1d\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgroups\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 501\u001b[0;31m return _sparse_difference(fun_wrapped, x0, f0, h,\n\u001b[0m\u001b[1;32m 502\u001b[0m \u001b[0muse_one_sided\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstructure\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 503\u001b[0m groups, method)\n", + "\u001b[0;32m/usr/lib64/python3.10/site-packages/scipy/optimize/_numdiff.py\u001b[0m in 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variables.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m/usr/lib64/python3.10/site-packages/scipy/optimize/_numdiff.py\u001b[0m in \u001b[0;36mfun_wrapped\u001b[0;34m(x)\u001b[0m\n\u001b[1;32m 435\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 436\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mfun_wrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 437\u001b[0;31m \u001b[0mf\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0matleast_1d\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 438\u001b[0m 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self.distortion)[0].reshape((indices.size, 2))\n\u001b[0;32m---> 84\u001b[0;31m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mextend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreprojected\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mimage_feature_locations\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mindices\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 85\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mravel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merrors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 86\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyboardInterrupt\u001b[0m: " + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_6a_a7r = {}\n", + "centre_errors_6a_a7r = {}\n", + "orientation_errors_6a_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_6a_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_6a_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_6a_a7r[pixel_error] = run_led_fit(fitter, led_positions_6a_a7r)\n", + " centre_errors_6a_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_6a_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_6a_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_6a_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_6a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_6a_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_6a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_6a_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration B" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [camera_radial_position, 0, 0],\n", + " [-camera_radial_position, 0, 0],\n", + " [0, 0, camera_radial_position],\n", + " [0, 0, -camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [-1, 0, 0],\n", + " [1, 0, 0],\n", + " [0, 0, -1],\n", + " [0, 0, 1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, 0.0, np.pi/2, 0.0, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.565729053514865 max: 152.1488367594276\n", + "image 1 reprojection errors: average: 23.11204394099042 max: 114.59310733158614\n", + "image 2 reprojection errors: average: 21.80960044715278 max: 86.10990621973482\n", + "image 3 reprojection errors: average: 21.587067334506248 max: 89.88571900946815\n", + "image 4 reprojection errors: average: 21.468444368757538 max: 144.31598575884195\n", + "image 5 reprojection errors: average: 21.321646408707455 max: 109.0396202223829\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6601e+06 5.14e+06 \n", + " 1 2 2.0076e+03 1.66e+06 6.76e+01 7.20e+04 \n", + " 2 3 1.6639e+03 3.44e+02 1.08e+00 3.02e+02 \n", + " 3 4 1.6610e+03 2.89e+00 1.54e-01 1.51e+02 \n", + " 4 5 1.6602e+03 7.36e-01 3.06e-02 4.02e+01 \n", + " 5 6 1.6600e+03 2.37e-01 1.83e-02 2.19e+01 \n", + " 6 7 1.6598e+03 1.77e-01 1.39e-02 3.34e+01 \n", + " 7 8 1.6597e+03 1.23e-01 1.07e-02 2.72e+01 \n", + " 8 9 1.6596e+03 8.28e-02 6.46e-03 6.49e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.6601e+06, final cost 1.6596e+03, first-order optimality 6.49e+01.\n", + "mean reprojection error: 0.7144993273496786\n", + "max reprojection error: 2.597876815391286\n", + "mean reconstruction error: 0.0670771326397725\n", + "max reconstruction error: 0.24996472551891238\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.980721934744473 max: 90.25168446666399\n", + "image 1 reprojection errors: average: 22.58173294546419 max: 191.01272984020522\n", + "image 2 reprojection errors: average: 23.86013903834583 max: 141.53116229341418\n", + "image 3 reprojection errors: average: 22.241348192322835 max: 82.63293282640078\n", + "image 4 reprojection errors: average: 23.33013144897648 max: 108.24464988149926\n", + "image 5 reprojection errors: average: 22.125563855499134 max: 114.12431468480719\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.8382e+06 3.19e+06 \n", + " 1 2 1.5711e+04 1.82e+06 6.97e+01 1.76e+05 \n", + " 2 3 1.5258e+04 4.53e+02 8.11e-01 2.11e+03 \n", + " 3 4 1.5237e+04 2.12e+01 4.18e-01 1.44e+03 \n", + " 4 5 1.5229e+04 7.27e+00 9.65e-02 3.12e+02 \n", + " 5 6 1.5228e+04 1.58e+00 4.18e-02 9.44e+01 \n", + " 6 7 1.5227e+04 1.04e+00 3.22e-02 9.90e+01 \n", + " 7 8 1.5226e+04 5.39e-01 1.31e-02 1.02e+02 \n", + " 8 9 1.5226e+04 1.59e-01 2.67e-03 2.82e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.8382e+06, final cost 1.5226e+04, first-order optimality 2.82e+01.\n", + "mean reprojection error: 2.163784970412014\n", + "max reprojection error: 8.958974288238476\n", + "mean reconstruction error: 0.19746123616511485\n", + "max reconstruction error: 0.7696435131254048\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.827677526002947 max: 140.92204446340207\n", + "image 1 reprojection errors: average: 23.536173009552297 max: 122.11260418406036\n", + "image 2 reprojection errors: average: 22.05154849818754 max: 105.0879488237886\n", + "image 3 reprojection errors: average: 21.89029096306905 max: 85.97086745987528\n", + "image 4 reprojection errors: average: 25.032289238649703 max: 101.85081057017354\n", + "image 5 reprojection errors: average: 21.887227705940255 max: 95.17368480404258\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7863e+06 4.01e+06 \n", + " 1 2 4.2077e+04 1.74e+06 6.97e+01 2.10e+05 \n", + " 2 3 4.1736e+04 3.41e+02 8.82e-01 4.95e+03 \n", + " 3 4 4.1696e+04 4.00e+01 4.18e-01 1.55e+03 \n", + " 4 5 4.1674e+04 2.14e+01 2.03e-01 5.14e+02 \n", + " 5 6 4.1668e+04 6.77e+00 9.97e-02 2.07e+02 \n", + " 6 7 4.1663e+04 4.74e+00 7.01e-02 1.46e+02 \n", + " 7 8 4.1659e+04 3.47e+00 5.88e-02 1.76e+02 \n", + " 8 9 4.1658e+04 1.97e+00 2.63e-02 2.37e+02 \n", + " 9 10 4.1657e+04 6.74e-01 6.05e-03 4.84e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 1.7863e+06, final cost 4.1657e+04, first-order optimality 4.84e+01.\n", + "mean reprojection error: 3.558183858331999\n", + "max reprojection error: 13.775201561511091\n", + "mean reconstruction error: 0.34032198962378424\n", + "max reconstruction error: 1.621345181174321\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1584 features\n", + "image 0 reprojection errors: average: 28.84832363773859 max: 148.57887396141717\n", + "image 1 reprojection errors: average: 24.747460502345294 max: 99.2363672847776\n", + "image 2 reprojection errors: average: 24.843015301494958 max: 133.8216993263272\n", + "image 3 reprojection errors: average: 23.9458815313349 max: 108.5640200123744\n", + "image 4 reprojection errors: average: 24.0287504136491 max: 111.20992265257573\n", + "image 5 reprojection errors: average: 23.872870537917695 max: 96.65070949034367\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.1247e+06 4.42e+06 \n", + " 1 2 1.6664e+05 1.96e+06 7.49e+01 1.68e+05 \n", + " 2 3 1.6600e+05 6.45e+02 1.45e+00 5.19e+03 \n", + " 3 4 1.6590e+05 1.02e+02 5.13e-01 1.90e+03 \n", + " 4 5 1.6586e+05 4.05e+01 2.35e-01 4.53e+02 \n", + " 5 6 1.6583e+05 2.41e+01 1.82e-01 3.56e+02 \n", + " 6 7 1.6581e+05 1.83e+01 1.32e-01 2.02e+02 \n", + " 7 8 1.6580e+05 1.37e+01 1.15e-01 3.13e+02 \n", + " 8 9 1.6579e+05 1.06e+01 8.32e-02 3.21e+02 \n", + " 9 10 1.6578e+05 6.28e+00 4.49e-02 3.60e+02 \n", + " 10 11 1.6578e+05 2.41e+00 1.19e-02 1.05e+02 \n", + " 11 12 1.6578e+05 1.32e+00 1.39e-02 2.57e+02 \n", + " 12 13 1.6578e+05 1.78e+00 1.25e-02 1.83e+02 \n", + " 13 14 1.6578e+05 9.60e-01 7.48e-03 1.74e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 14, initial cost 2.1247e+06, final cost 1.6578e+05, first-order optimality 1.74e+02.\n", + "mean reprojection error: 7.126804036202681\n", + "max reprojection error: 28.18925758067823\n", + "mean reconstruction error: 0.6531858960413859\n", + "max reconstruction error: 2.9247299713583197\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 51, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_6b_a7r = {}\n", + "centre_errors_6b_a7r = {}\n", + "orientation_errors_6b_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_6b_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_6b_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_6b_a7r[pixel_error] = run_led_fit(fitter, led_positions_6b_a7r)\n", + " centre_errors_6b_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_6b_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_6b_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_6b_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_6b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_6b_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_6b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_6b_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [-camera_radial_position, -camera_halfz_position, 0],\n", + " [camera_radial_position, -camera_halfz_position, 0],\n", + " [0, -camera_halfz_position, -camera_radial_position],\n", + " [0, -camera_halfz_position, camera_radial_position],\n", + " [-camera_radial_position, camera_halfz_position, 0],\n", + " [camera_radial_position, camera_halfz_position, 0],\n", + " [0, camera_halfz_position, -camera_radial_position],\n", + " [0, camera_halfz_position, camera_radial_position]])\n", + "camera_directions = [[1, 1.1, 0],\n", + " [-1, 1.1, 0],\n", + " [0, 1.1, 1],\n", + " [0, 1.1, -1],\n", + " [1, -1.1, 0],\n", + " [-1, -1.1, 0],\n", + " [0, -1.1, 1],\n", + " [0, -1.1, -1]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 23.16023849813648 max: 237.1378339335638\n", + "image 1 reprojection errors: average: 22.258383622107594 max: 205.02063303998966\n", + "image 2 reprojection errors: average: 21.683871414266537 max: 200.40748838371658\n", + "image 3 reprojection errors: average: 22.25487641545825 max: 258.55315396221374\n", + "image 4 reprojection errors: average: 22.803637616002245 max: 295.38866241477945\n", + "image 5 reprojection errors: average: 22.44502611617866 max: 332.596701244076\n", + "image 6 reprojection errors: average: 21.576365755998225 max: 200.80861434675163\n", + "image 7 reprojection errors: average: 21.701061206764738 max: 227.40493639576755\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8679e+06 1.05e+07 \n", + " 1 2 8.2753e+03 3.86e+06 6.87e+01 4.20e+05 \n", + " 2 3 4.1365e+03 4.14e+03 7.63e-01 8.30e+03 \n", + " 3 4 4.1302e+03 6.32e+00 1.54e-01 1.49e+03 \n", + " 4 5 4.1288e+03 1.44e+00 2.35e-02 1.71e+02 \n", + " 5 6 4.1285e+03 2.81e-01 9.32e-03 6.01e+01 \n", + " 6 7 4.1283e+03 2.18e-01 7.81e-03 5.28e+01 \n", + " 7 8 4.1281e+03 1.43e-01 5.14e-03 3.32e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 3.8679e+06, final cost 4.1281e+03, first-order optimality 3.32e+01.\n", + "mean reprojection error: 0.8451041107593343\n", + "max reprojection error: 3.3229975321646963\n", + "mean reconstruction error: 0.04784805961485911\n", + "max reconstruction error: 0.21173449573698008\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 21.503281887528427 max: 176.96438484533192\n", + "image 1 reprojection errors: average: 22.257378896644195 max: 318.106280674425\n", + "image 2 reprojection errors: average: 21.582307849784605 max: 163.03098440600422\n", + "image 3 reprojection errors: average: 21.58623183293511 max: 203.05945195832578\n", + "image 4 reprojection errors: average: 21.51197259652079 max: 204.13617946232478\n", + "image 5 reprojection errors: average: 21.88043923509194 max: 255.47504294338654\n", + "image 6 reprojection errors: average: 21.390647924212054 max: 181.4775823125873\n", + "image 7 reprojection errors: average: 22.307667661297863 max: 265.0648246743963\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.6969e+06 5.19e+06 \n", + " 1 2 4.0678e+04 3.66e+06 6.81e+01 2.93e+05 \n", + " 2 3 3.7180e+04 3.50e+03 8.63e-01 4.96e+03 \n", + " 3 4 3.7124e+04 5.56e+01 5.92e-01 1.58e+03 \n", + " 4 5 3.7113e+04 1.10e+01 9.03e-02 1.72e+02 \n", + " 5 6 3.7112e+04 1.13e+00 1.92e-02 9.17e+01 \n", + " 6 7 3.7111e+04 6.70e-01 9.93e-03 6.12e+01 \n", + " 7 8 3.7111e+04 4.48e-01 9.09e-03 9.61e+01 \n", + " 8 9 3.7111e+04 3.56e-01 5.41e-03 9.48e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 3.6969e+06, final cost 3.7111e+04, first-order optimality 9.48e+01.\n", + "mean reprojection error: 2.5334890390097002\n", + "max reprojection error: 8.976515547015872\n", + "mean reconstruction error: 0.14565701518637408\n", + "max reconstruction error: 0.7202115888135266\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.777532335892012 max: 229.39633390272587\n", + "image 1 reprojection errors: average: 22.641300822259478 max: 315.4032025626577\n", + "image 2 reprojection errors: average: 21.863181973759712 max: 202.24830929226184\n", + "image 3 reprojection errors: average: 22.57934433777671 max: 154.6404110153907\n", + "image 4 reprojection errors: average: 23.008818114732623 max: 237.21220705806553\n", + "image 5 reprojection errors: average: 22.854114056476956 max: 281.30293119405826\n", + "image 6 reprojection errors: average: 22.278023974179774 max: 237.7568903823768\n", + "image 7 reprojection errors: average: 22.482293295072 max: 317.39192810426204\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8191e+06 1.03e+07 \n", + " 1 2 1.0728e+05 3.71e+06 6.88e+01 2.89e+05 \n", + " 2 3 1.0312e+05 4.16e+03 8.97e-01 5.85e+03 \n", + " 3 4 1.0296e+05 1.59e+02 1.04e+00 4.35e+03 \n", + " 4 5 1.0293e+05 3.51e+01 1.61e-01 4.86e+02 \n", + " 5 6 1.0292e+05 5.42e+00 6.38e-02 5.29e+02 \n", + " 6 7 1.0292e+05 2.25e+00 1.58e-02 1.51e+02 \n", + " 7 8 1.0292e+05 1.04e+00 1.14e-02 1.27e+02 \n", + " 8 9 1.0292e+05 8.64e-01 8.95e-03 1.44e+02 \n", + " 9 10 1.0292e+05 2.69e-01 2.26e-03 9.52e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 3.8191e+06, final cost 1.0292e+05, first-order optimality 9.52e+01.\n", + "mean reprojection error: 4.2060594127098865\n", + "max reprojection error: 15.259265442825486\n", + "mean reconstruction error: 0.2374936086291789\n", + "max reconstruction error: 1.0753439525273152\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 25.204027727484483 max: 236.1548285345105\n", + "image 1 reprojection errors: average: 25.056256207399546 max: 234.61202356342926\n", + "image 2 reprojection errors: average: 25.061580665851945 max: 248.891441782651\n", + "image 3 reprojection errors: average: 24.693883865970797 max: 246.49983416754839\n", + "image 4 reprojection errors: average: 25.20779669763003 max: 190.59478655525834\n", + "image 5 reprojection errors: average: 24.343545487107626 max: 221.01305038283488\n", + "image 6 reprojection errors: average: 24.999538438564233 max: 182.2041140163001\n", + "image 7 reprojection errors: average: 24.047252776062056 max: 197.23707287197377\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 4.4157e+06 4.47e+06 \n", + " 1 2 4.2376e+05 3.99e+06 7.34e+01 2.78e+05 \n", + " 2 3 4.2064e+05 3.12e+03 1.41e+00 1.15e+04 \n", + " 3 4 4.2028e+05 3.63e+02 1.06e+00 6.63e+03 \n", + " 4 5 4.2010e+05 1.77e+02 2.86e-01 1.21e+03 \n", + " 5 6 4.2006e+05 4.07e+01 1.51e-01 5.54e+02 \n", + " 6 7 4.2003e+05 3.30e+01 9.99e-02 6.87e+02 \n", + " 7 8 4.2000e+05 2.65e+01 1.07e-01 5.04e+02 \n", + " 8 9 4.1998e+05 2.38e+01 7.77e-02 7.65e+02 \n", + " 9 10 4.1996e+05 2.17e+01 9.18e-02 5.00e+02 \n", + " 10 11 4.1994e+05 1.34e+01 3.96e-02 5.16e+02 \n", + " 11 12 4.1994e+05 7.53e+00 3.34e-02 3.37e+02 \n", + " 12 13 4.1993e+05 7.17e+00 2.73e-02 5.21e+02 \n", + " 13 14 4.1992e+05 6.97e+00 3.18e-02 3.64e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 14 15 4.1991e+05 6.77e+00 2.60e-02 5.37e+02 \n", + " 15 16 4.1991e+05 6.59e+00 3.05e-02 4.03e+02 \n", + " 16 17 4.1990e+05 6.25e+00 2.38e-02 5.88e+02 \n", + " 17 18 4.1990e+05 5.37e+00 2.42e-02 4.53e+02 \n", + " 18 19 4.1989e+05 5.06e+00 1.86e-02 7.08e+02 \n", + " 19 20 4.1989e+05 2.38e+00 7.97e-03 2.46e+02 \n", + " 20 21 4.1989e+05 1.90e+00 8.78e-03 5.57e+02 \n", + " 21 22 4.1989e+05 1.71e+00 6.32e-03 2.17e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 22, initial cost 4.4157e+06, final cost 4.1989e+05, first-order optimality 2.17e+02.\n", + "mean reprojection error: 8.509951010491672\n", + "max reprojection error: 28.415799931362407\n", + "mean reconstruction error: 0.4694068935599997\n", + "max reconstruction error: 2.1361386958101996\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a_a7r = {}\n", + "centre_errors_8a_a7r = {}\n", + "orientation_errors_8a_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a_a7r[pixel_error] = run_led_fit(fitter, led_positions_8a_a7r)\n", + " centre_errors_8a_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera configuration B" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [], + "source": [ + "camera_radial_position = 175.0\n", + "camera_halfz_position = 160.0\n", + "camera_positions = np.array([\n", + " [0, -camera_halfz_position, 0],\n", + " [0, camera_halfz_position, 0],\n", + " [0, -0.3*camera_halfz_position, -camera_radial_position],\n", + " [camera_radial_position*np.sqrt(3)/2, -0.3*camera_halfz_position, 0.5*camera_radial_position],\n", + " [-camera_radial_position*np.sqrt(3)/2, -0.3*camera_halfz_position, 0.5*camera_radial_position],\n", + " [0, 0.3*camera_halfz_position, camera_radial_position],\n", + " [camera_radial_position*np.sqrt(3)/2, 0.3*camera_halfz_position, -0.5*camera_radial_position],\n", + " [-camera_radial_position*np.sqrt(3)/2, 0.3*camera_halfz_position, -0.5*camera_radial_position]])\n", + "camera_directions = [[0, 1, 0],\n", + " [0, -1, 0],\n", + " [0, 0.3, 1],\n", + " [-np.sqrt(3)/2, 0.3, -0.5],\n", + " [np.sqrt(3)/2, 0.3, -0.5],\n", + " [0, -0.3, -1],\n", + " [-np.sqrt(3)/2, -0.3, 0.5],\n", + " [np.sqrt(3)/2, -0.3, 0.5]]\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, np.pi/2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 22.422028355745763 max: 131.08734346825418\n", + "image 1 reprojection errors: average: 23.059369067133957 max: 147.66618029913195\n", + "image 2 reprojection errors: average: 21.558002496038306 max: 128.06426023309228\n", + "image 3 reprojection errors: average: 23.883543045759055 max: 124.71660288440314\n", + "image 4 reprojection errors: average: 21.479280831184923 max: 149.9566093137041\n", + "image 5 reprojection errors: average: 21.361177657263422 max: 120.99911973590952\n", + "image 6 reprojection errors: average: 22.14661158118147 max: 147.5254203234643\n", + "image 7 reprojection errors: average: 21.176473811631524 max: 111.66855343886763\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3516e+06 2.44e+06 \n", + " 1 2 3.4700e+03 2.35e+06 6.81e+01 1.94e+05 \n", + " 2 3 2.8300e+03 6.40e+02 1.05e+00 1.14e+03 \n", + " 3 4 2.7994e+03 3.06e+01 1.06e+00 1.64e+03 \n", + " 4 5 2.7919e+03 7.55e+00 1.49e-01 1.16e+02 \n", + " 5 6 2.7914e+03 5.19e-01 2.39e-02 7.99e+01 \n", + " 6 7 2.7912e+03 1.85e-01 1.00e-02 3.40e+01 \n", + " 7 8 2.7911e+03 5.18e-02 2.18e-03 2.69e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 2.3516e+06, final cost 2.7911e+03, first-order optimality 2.69e+01.\n", + "mean reprojection error: 0.8000912011398097\n", + "max reprojection error: 3.119895201927475\n", + "mean reconstruction error: 0.05689303529191649\n", + "max reconstruction error: 0.3056160519467431\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 25.32758273333326 max: 144.64320875087458\n", + "image 1 reprojection errors: average: 22.219997981121306 max: 108.03847553151358\n", + "image 2 reprojection errors: average: 22.234508469801238 max: 105.11071047915048\n", + "image 3 reprojection errors: average: 21.438734028768312 max: 153.66659836950546\n", + "image 4 reprojection errors: average: 21.860292327743366 max: 151.49040466065887\n", + "image 5 reprojection errors: average: 21.38242071390782 max: 126.77067444731263\n", + "image 6 reprojection errors: average: 21.770786610251065 max: 114.41257542233666\n", + "image 7 reprojection errors: average: 21.71873383515036 max: 84.9996050791673\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3649e+06 4.02e+06 \n", + " 1 2 2.5301e+04 2.34e+06 6.79e+01 1.29e+05 \n", + " 2 3 2.4753e+04 5.48e+02 1.29e+00 5.83e+03 \n", + " 3 4 2.4664e+04 8.85e+01 1.04e+00 5.22e+03 \n", + " 4 5 2.4626e+04 3.85e+01 2.67e-01 7.82e+02 \n", + " 5 6 2.4616e+04 9.13e+00 1.29e-01 5.71e+02 \n", + " 6 7 2.4610e+04 6.66e+00 9.11e-02 2.94e+02 \n", + " 7 8 2.4605e+04 4.50e+00 6.71e-02 2.84e+02 \n", + " 8 9 2.4602e+04 3.02e+00 4.33e-02 1.77e+02 \n", + " 9 10 2.4600e+04 2.70e+00 4.67e-02 2.44e+02 \n", + " 10 11 2.4597e+04 2.59e+00 3.94e-02 1.68e+02 \n", + " 11 12 2.4595e+04 2.50e+00 4.46e-02 2.33e+02 \n", + " 12 13 2.4592e+04 2.42e+00 3.78e-02 1.71e+02 \n", + " 13 14 2.4590e+04 2.38e+00 4.37e-02 2.34e+02 \n", + " 14 15 2.4587e+04 2.32e+00 3.69e-02 1.69e+02 \n", + " 15 16 2.4585e+04 2.25e+00 4.25e-02 2.19e+02 \n", + " 16 17 2.4583e+04 2.18e+00 3.57e-02 1.62e+02 \n", + " 17 18 2.4581e+04 2.06e+00 4.00e-02 2.10e+02 \n", + " 18 19 2.4579e+04 1.87e+00 3.09e-02 1.87e+02 \n", + " 19 20 2.4577e+04 1.90e+00 3.76e-02 2.55e+02 \n", + " 20 21 2.4575e+04 1.77e+00 2.77e-02 1.95e+02 \n", + " 21 22 2.4574e+04 1.22e+00 2.19e-02 2.40e+02 \n", + " 22 23 2.4573e+04 1.02e+00 1.48e-02 1.95e+02 \n", + " 23 24 2.4573e+04 4.05e-01 5.20e-03 7.20e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 24, initial cost 2.3649e+06, final cost 2.4573e+04, first-order optimality 7.20e+01.\n", + "mean reprojection error: 2.3685530283975633\n", + "max reprojection error: 9.411649519711146\n", + "mean reconstruction error: 0.17255798063474972\n", + "max reconstruction error: 1.117199368392498\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 24.462329162159996 max: 105.08312346985481\n", + "image 1 reprojection errors: average: 23.237335036456873 max: 173.10657532516018\n", + "image 2 reprojection errors: average: 21.94132209799502 max: 95.53772695975297\n", + "image 3 reprojection errors: average: 22.702155566902302 max: 140.22789352736598\n", + "image 4 reprojection errors: average: 21.774981057729036 max: 106.86162680331809\n", + "image 5 reprojection errors: average: 21.880901627446285 max: 131.2418169304274\n", + "image 6 reprojection errors: average: 22.50804294111662 max: 166.80537500737773\n", + "image 7 reprojection errors: average: 21.248653890435623 max: 131.65170041896732\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3875e+06 2.11e+06 \n", + " 1 2 6.9147e+04 2.32e+06 6.96e+01 1.04e+05 \n", + " 2 3 6.8513e+04 6.34e+02 1.14e+00 5.16e+03 \n", + " 3 4 6.8432e+04 8.06e+01 6.11e-01 3.37e+03 \n", + " 4 5 6.8387e+04 4.49e+01 2.45e-01 6.05e+02 \n", + " 5 6 6.8372e+04 1.56e+01 1.42e-01 3.37e+02 \n", + " 6 7 6.8360e+04 1.16e+01 9.66e-02 1.88e+02 \n", + " 7 8 6.8350e+04 9.75e+00 1.01e-01 2.22e+02 \n", + " 8 9 6.8342e+04 8.70e+00 7.87e-02 1.57e+02 \n", + " 9 10 6.8334e+04 7.91e+00 8.68e-02 2.25e+02 \n", + " 10 11 6.8326e+04 7.38e+00 6.96e-02 1.42e+02 \n", + " 11 12 6.8320e+04 6.85e+00 7.81e-02 2.06e+02 \n", + " 12 13 6.8313e+04 6.47e+00 6.39e-02 1.62e+02 \n", + " 13 14 6.8307e+04 6.13e+00 7.30e-02 2.34e+02 \n", + " 14 15 6.8301e+04 5.76e+00 5.91e-02 1.77e+02 \n", + " 15 16 6.8296e+04 4.93e+00 6.00e-02 2.92e+02 \n", + " 16 17 6.8291e+04 4.76e+00 5.01e-02 2.72e+02 \n", + " 17 18 6.8288e+04 3.46e+00 3.70e-02 3.66e+02 \n", + " 18 19 6.8286e+04 2.38e+00 2.02e-02 2.47e+02 \n", + " 19 20 6.8285e+04 1.02e+00 8.93e-03 1.36e+02 \n", + " 20 21 6.8284e+04 1.02e+00 1.33e-02 2.56e+02 \n", + " 21 22 6.8283e+04 1.00e+00 8.84e-03 1.36e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 22 23 6.8282e+04 1.01e+00 1.33e-02 2.62e+02 \n", + " 23 24 6.8281e+04 9.93e-01 8.77e-03 1.33e+02 \n", + " 24 25 6.8280e+04 9.96e-01 1.33e-02 2.65e+02 \n", + " 25 26 6.8279e+04 9.83e-01 8.70e-03 1.31e+02 \n", + " 26 27 6.8278e+04 9.86e-01 1.34e-02 2.67e+02 \n", + " 27 28 6.8277e+04 9.74e-01 8.63e-03 1.28e+02 \n", + " 28 29 6.8276e+04 9.78e-01 1.34e-02 2.69e+02 \n", + " 29 30 6.8275e+04 9.66e-01 8.58e-03 1.25e+02 \n", + " 30 31 6.8274e+04 9.48e-01 1.31e-02 2.65e+02 \n", + " 31 32 6.8273e+04 9.48e-01 8.55e-03 1.26e+02 \n", + " 32 33 6.8272e+04 8.99e-01 1.24e-02 2.54e+02 \n", + " 33 34 6.8271e+04 8.94e-01 8.24e-03 1.28e+02 \n", + " 34 35 6.8270e+04 6.47e-01 8.37e-03 1.92e+02 \n", + " 35 36 6.8270e+04 7.75e-01 8.46e-03 1.82e+02 \n", + " 36 37 6.8269e+04 4.95e-01 5.01e-03 1.08e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 37, initial cost 2.3875e+06, final cost 6.8269e+04, first-order optimality 1.08e+02.\n", + "mean reprojection error: 3.949204890330875\n", + "max reprojection error: 15.192389605457588\n", + "mean reconstruction error: 0.2750591763571097\n", + "max reconstruction error: 1.6234636194473386\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1584 features\n", + "image 0 reprojection errors: average: 24.11787868754015 max: 135.82672226334222\n", + "image 1 reprojection errors: average: 25.39669178283399 max: 142.57251798757773\n", + "image 2 reprojection errors: average: 23.348801056128675 max: 134.6472632033062\n", + "image 3 reprojection errors: average: 23.938861047542225 max: 97.72349908494542\n", + "image 4 reprojection errors: average: 23.618093640063453 max: 100.75482634257735\n", + "image 5 reprojection errors: average: 26.462076449678616 max: 128.7692466927361\n", + "image 6 reprojection errors: average: 25.507897635877992 max: 113.7731514619232\n", + "image 7 reprojection errors: average: 23.2688795641142 max: 102.62315348025858\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.7471e+06 2.35e+06 \n", + " 1 2 2.7247e+05 2.47e+06 7.24e+01 1.70e+05 \n", + " 2 3 2.7169e+05 7.77e+02 1.33e+00 1.04e+04 \n", + " 3 4 2.7152e+05 1.69e+02 6.16e-01 5.29e+03 \n", + " 4 5 2.7142e+05 1.06e+02 4.22e-01 1.72e+03 \n", + " 5 6 2.7136e+05 5.81e+01 2.65e-01 9.66e+02 \n", + " 6 7 2.7132e+05 3.59e+01 1.71e-01 5.85e+02 \n", + " 7 8 2.7129e+05 2.86e+01 1.49e-01 4.42e+02 \n", + " 8 9 2.7127e+05 2.62e+01 1.38e-01 4.47e+02 \n", + " 9 10 2.7124e+05 2.28e+01 1.24e-01 3.56e+02 \n", + " 10 11 2.7122e+05 2.30e+01 1.30e-01 5.09e+02 \n", + " 11 12 2.7120e+05 2.17e+01 1.19e-01 2.75e+02 \n", + " 12 13 2.7118e+05 1.57e+01 8.69e-02 5.98e+02 \n", + " 13 14 2.7117e+05 1.34e+01 6.97e-02 4.34e+02 \n", + " 14 15 2.7117e+05 5.33e+00 1.74e-02 1.90e+02 \n", + " 15 16 2.7116e+05 5.53e+00 4.25e-02 5.03e+02 \n", + " 16 17 2.7115e+05 5.22e+00 1.70e-02 1.85e+02 \n", + " 17 18 2.7115e+05 5.36e+00 4.28e-02 5.58e+02 \n", + " 18 19 2.7114e+05 5.24e+00 1.70e-02 1.85e+02 \n", + " 19 20 2.7114e+05 5.33e+00 4.34e-02 5.98e+02 \n", + " 20 21 2.7113e+05 5.16e+00 1.65e-02 1.75e+02 \n", + " 21 22 2.7113e+05 3.58e+00 2.89e-02 4.69e+02 \n", + " 22 23 2.7113e+05 4.10e+00 1.63e-02 2.66e+02 \n", + " 23 24 2.7112e+05 2.47e+00 1.74e-02 3.11e+02 \n", + " 24 25 2.7112e+05 3.43e+00 1.85e-02 4.81e+02 \n", + " 25 26 2.7112e+05 2.89e+00 1.63e-02 2.66e+02 \n", + " 26 27 2.7112e+05 1.66e+00 8.09e-03 2.14e+02 \n", + " 27 28 2.7111e+05 1.31e+00 9.02e-03 2.01e+02 \n", + " 28 29 2.7111e+05 1.29e+00 7.10e-03 2.07e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 29, initial cost 2.7471e+06, final cost 2.7111e+05, first-order optimality 2.07e+02.\n", + "mean reprojection error: 7.8864156247103026\n", + "max reprojection error: 30.072301247081743\n", + "mean reconstruction error: 0.5577996926293278\n", + "max reconstruction error: 2.657465229043437\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8b_a7r = {}\n", + "centre_errors_8b_a7r = {}\n", + "orientation_errors_8b_a7r = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8b_a7r = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8b_a7r, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8b_a7r[pixel_error] = run_led_fit(fitter, led_positions_8b_a7r)\n", + " centre_errors_8b_a7r[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8b_a7r[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8b_a7r[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8b_a7r[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8b_a7r[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8b_a7r[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8b_a7r[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Summary Plots" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "led_pos_res_4 = np.array([np.percentile(e, 68) for e in position_errors_4.values()])\n", + "led_pos_res_6a = np.array([np.percentile(e, 68) for e in position_errors_6a.values()])\n", + "led_pos_res_6b = np.array([np.percentile(e, 68) for e in position_errors_6b.values()])\n", + "led_pos_res_8a = np.array([np.percentile(e, 68) for e in position_errors_8a.values()])\n", + "led_pos_res_8b = np.array([np.percentile(e, 68) for e in position_errors_8b.values()])\n", + "led_pos_res_4_a7r = np.array([np.percentile(e, 68) for e in position_errors_4_a7r.values()])\n", + "led_pos_res_6a_a7r = np.array([np.percentile(e, 68) for e in position_errors_6a_a7r.values()])\n", + "led_pos_res_6b_a7r = np.array([np.percentile(e, 68) for e in position_errors_6b_a7r.values()])\n", + "led_pos_res_8a_a7r = np.array([np.percentile(e, 68) for e in position_errors_8a_a7r.values()])\n", + "led_pos_res_8b_a7r = np.array([np.percentile(e, 68) for e in position_errors_8b_a7r.values()])\n", + "fig_led_pos_a6000, ax_led_pos_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_led_pos_a6000.plot(pixel_errors, led_pos_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_led_pos_a7r, ax_led_pos_a7r = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_led_pos_a7r.plot(pixel_errors, led_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_led_pos, ax_led_pos = make_fig(None, \"Feature identification error [pixels]\", \"LED position reconstruction resolution [cm]\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_led_pos.plot(pixel_errors, led_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.09768923 0.29892812 0.49070657 0.98510866]\n", + "[0.0965059 0.29540936 0.49112376 0.98235441]\n" + ] + } + ], + "source": [ + "print(led_pos_res_6a)\n", + "print(led_pos_res_8b)" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "mpmt_pos_res_4 = np.array([np.percentile(e, 68) for e in centre_errors_4.values()])\n", + "mpmt_pos_res_6a = np.array([np.percentile(e, 68) for e in centre_errors_6a.values()])\n", + "mpmt_pos_res_6b = np.array([np.percentile(e, 68) for e in centre_errors_6b.values()])\n", + "mpmt_pos_res_8a = np.array([np.percentile(e, 68) for e in centre_errors_8a.values()])\n", + "mpmt_pos_res_8b = np.array([np.percentile(e, 68) for e in centre_errors_8b.values()])\n", + "mpmt_pos_res_4_a7r = np.array([np.percentile(e, 68) for e in centre_errors_4_a7r.values()])\n", + "mpmt_pos_res_6a_a7r = np.array([np.percentile(e, 68) for e in centre_errors_6a_a7r.values()])\n", + "mpmt_pos_res_6b_a7r = np.array([np.percentile(e, 68) for e in centre_errors_6b_a7r.values()])\n", + "mpmt_pos_res_8a_a7r = np.array([np.percentile(e, 68) for e in centre_errors_8a_a7r.values()])\n", + "mpmt_pos_res_8b_a7r = np.array([np.percentile(e, 68) for e in centre_errors_8b_a7r.values()])\n", + "fig_mpmt_pos_a6000, ax_mpmt_pos_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos_a6000.plot(pixel_errors, mpmt_pos_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_pos_a7r, ax_mpmt_pos_a7r = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos_a7r.plot(pixel_errors, mpmt_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(None, \"Feature identification error [pixels]\", \"mPMT centre position reconstruction resolution [cm]\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_mpmt_pos.plot(pixel_errors, mpmt_pos_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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7ERFXV1eJiooSEZHXX39dZs6cmav9hg0bxM/PT5KTk0VE1Dlv3ryptvnggw9kxowZIiIycOBAeeWVV8RgMMjq1aulfPnycuTIEcnMzJTGjRvLoUOH5MaNG/L8889LUlKSiIhMnTpVPvnkExERcXR0lM8++0wdO7953N3d5dKlSyIi6ufxuMjxvdTQ0NAojRgMxmegjY3IihX/quuG0xvEYrKFmH5iKpaTLWX3xd1FIiKwX/LQB55NC0xiIhgMxvcGg/H8EVi3bh1Vq1alSZMmBbYLDg7mxIkT9OrVi+3bt9O8eXPS0tLYuXMn/fv3B6BRo0Y4Ojqqger8/f2xsbHBwsICV1dXLly4gLW1Ne3atWPdunWcPHmSjIwM1ZqTxf79+2nVqhXly5dX53n55ZdztPntt99o0aKFunwEkJKSgpeXF5UrV+bWrVu0b9/+odefZYXR6/WsWbOGXr165WqzZcsWgoODsbKyAlDnPHr0KM8//zw6nY6lS5dy7Ngxtc/LL7+MoijodDqqVauGTqfDxMQENzc3YmJi2LNnD8ePH6dFixZ4eXmxaNEiLly4oPbPvoyV3zwtWrQgKCiIefPmaUtNGhoazw4JCZCaCooCCxfCkSNQyKV/EWHJkSX0/LknqfpUMiWT9Mx0tsdsL1KRH+Tp20b99dcPb5OVQTM9HczNYenSRwqBvGvXLtauXcuGDRtITU3lzp079OvXL8+M1DVq1CAkJISQkBDc3d05evQoUkA+quxJHU1NTdHr9QCEhoby6aef0qhRI4KDgx/at3z58nh7e+eoX7FiRa7loywfmMTERDp16sSsWbN46623Crz+vn37EhAQQOvWrfHw8KBq1aq52ogIiqLkKg8KCmL16tV4enoSFhbG9u3bc8lvYmKS41pMTEzQ6/WYmprSvn17li9fnqdc1tbWD51nzpw5/P3336xfvx4vLy+ioqKoXLlygderoaGh8UTz11/Qrx9062Z8Znp5FbprTEIMQ9cNZdO5TbjZuXHu9jkyMjMwNzWnjVObopI4T55NC4yfnzFvw6RJjyV/w5QpU7h06RIxMTGsWLGCdu3a5am8bNy4kYyMDACuXr1KfHw8NWvWpFWrVixduhSA06dPc/HiRRo2bFjgnL6+vsTGxrJs2bI8fVgaN27Mvn37yMzM5O+//+by5cscPXpUrU9MTOTPP/+kS5cueY5vY2PDjBkzmD59uipzftStW5fKlSszbty4fP1pAgICWLBggep7krXr6e7du9jb25ORkaHeg8LSvHlzdu3axdmzZwG4d+9evikW8pvn3Llz+Pr6MnHiRKpUqUJsbOy/kkFDQ0PjiSHLUbdNGyhTBl599V9133J+C27fubErdhffvvgth4ceZuuArUxqO4mIARH41dJyIRUPfn7Fnnhq8+bNjBw5EgsLC8C4nbl69eoMHz6coUOHotPpMDMzIywsLIfFIT969+5NVFQUFStWzFXn6OhIUFAQgYGB3Llzh/DwcEaOHMmyZctwcnJi1apVBAQE5LBSPIi3tzeenp6sWLFCXeLKj759+/L+++/TrVu3POsDAwOJioqiadOmmJub89JLL/Hpp58yadIkfH19cXR0RKfTcffu3YdedxZ2dnaEhYXRt29f0tLSAJg8eTINGjTI1Ta/ecaOHcuZM2cQEfz9/fH09Cz0/BoaGhpPDOfPGxWWv/+G4GD45hsoX75QXfUGPWYmZjSt0ZRerr2Y1HYStWyMTr5+tfyKXXHJQilo+aI00rRpU9m/f3+OshMnThS4fflppVOnTowePVrLSF1KeVa/lxoaGqWQkyeNQem++gry8FPMi5SMFCbtmMTmc5uJHBRJGdMyRSxk3iiKckBEmj5Y/mwuIT3hJCQk0KBBAywtLTXlRUNDQ0Mjb27fhlmzQAQaNTJuly6k8rI9ZjueczyZsnMKumo6UvWpRSzsv+fZXUJ6grG1tc3X10NDQ0NDQ4MdO4yOunFxRp8XNzcohGtCUnoSozeO5odDP+Bc0Zk/+v/BC84vFL28/wOaBUZDQ0NDQ+NpISMDPvwQ2rY1Kiy7dxuVl0JibmrO/rj9jH1uLP8M+6fUKi+gWWA0NDQ0NDSeHrp2hQ0bjI66M2bA/bx1BXH5zmXGbx/PFwFfYGNhw9+hf2Nual70sj4imgVGQ0NDQ0PjScYYV974fuhQ+PlnWLDgocqLQQzM3jcb1+9cWfrPUv6+/DfAE6G8gGaB0dDQ0NDQeHK5fduotPj4wJgx8EDE9fw4ceMEg38bzK7YXfjX8Wdup7nUrVS3iIV9vGgWmMdEQkICPXv2pFGjRri4uBCZLUnkqFGj2LFjR4H9x4wZw9atW/Os27NnD76+vnh5eeHi4sKECRMep+h5smrVKhRF4eTJkznKL168SEBAAC4uLri6uhITEwNAdHQ0vr6+1K9fn1deeYX09HTAGIH3rbfeol69enh4eHDw4EF1rI0bN9KwYUPq1avH1KlTi/yaNDQ0NJ4qduwAT0/49dd/3XVcxDiO3zjOwi4L+aP/H0+c8gI8hckcS4gBAwbIvHnzREQkLS1NTQwYHx8vvr6+D+0fExMj7du3z7OuQYMGarJEvV4vx44dezxCF0CvXr2kZcuWMn78+BzlrVu3ls2bN4uIyN27d9XkjL169ZLly5eLiDGh43fffSciIuvXr5fAwEAxGAwSGRkpzZo1U6/D2dlZzp07J2lpaeLh4VEs11VY9Hr9I49RGr6XGhoaTyHp6SL/938iiiJSr57I3r2F6rb74m6JuR0jIiKXEi/J1btXi1LKxwZaMsecREbClCnG10flzp077Nixg0GDBgFgbm6Ora0tAOHh4QQGBqptJ06ciI+PD+7u7gwZMkTNg+To6Eh8fDxXr17NNf7169ext7cHjPmQXF1dAWM4/q5du+Lh4UHz5s05cuQIABMmTCAkJIQ2bdrg7OzMjBkzAPjoo4/45ptv1HE/+OADtS47SUlJ7Nq1i/nz57NixQq1/Pjx4+j1ejXBY7ly5bCyskJE2Lp1Kz179gRg4MCBrF69GoA1a9YwYMAAFEWhefPmJCQkEBcXx969e6lXrx7Ozs6Ym5vTp08f1qxZk0uWa9eu0a1bNzw9PfH09GT37t0AdO3alSZNmuDm5sb333+vti9XrhzvvfceTZo04YUXXmDv3r3qfVi7di0AmZmZjB07Fh8fHzw8PJg7dy4A27dvp23btrz66qtqcsy85snMzCQoKAh3d3d0Oh1fffVVLrk1NDQ0ioxDh2DqVKOj7qFDxuWjAribdpe3fn+LFgtaMOHPCQDUrFCTauWqFYOwRUheWk1pPgpjgWndOvcxa5axLjnZmDncxMTo9WRiYjxfuNBYf+NG7r4P49ChQ+Lj4yMDBw4ULy8vGTRokCQlJYmI0TKzdu1atW18fLz6vl+/fjnqQkNDJTw8PNf4n3zyidja2krXrl1lzpw5kpKSIiIib7zxhkyYMEFERCIiIsTT01NERMaPHy9+fn6SmpoqN27ckEqVKkl6erpER0eLt7e3iIhkZmaKs7Oz3Lx5M9d8P/74o4SEhIiIiJ+fnxw4cEBERFatWiUdO3aUbt26iZeXl4wZM0b0er3cuHFD6tatq/a/ePGiuLm5iYhIx44d5a+//lLr2rVrJ/v27ZOVK1fKoEGD1PLFixfLiBEjcsnSu3dv+eqrr0TEaBVJSEjIcR/v3bsnbm5u6nUAsmHDBhER6dq1q7Rv317S09MlKipKvT9z586VSZMmiYhIamqqNGnSRM6fPy/btm0TKysrOX/+vDp/XvPs379fXnjhBbVNlrXtQTQLjIaGxmPDYBDZt++/54W0WK87tU5qfVlLlAmKvLnhTbmTeqeIBCw60Cww/yUxEQwG43uDwXj+KOj1eg4ePMiwYcM4dOgQ1tbWqk9HXFwcdnZ2attt27bh6+uLTqdj69atHDt2TK2rWrUqV65cyTX+xx9/zP79+wkICGDZsmWqRWfnzp1qjqJ27doRHx9P4v2L6dixI2XLlqVKlSpUrVqVa9eu4eTkROXKlTl06BCbN2/G29s7z8zLy5cvp0+fPgD06dNHzfas1+v566+/mD59Ovv27eP8+fOEhYXlmU07K/N0fnUF9cnO1q1bGTZsGGC0PtnY2AAwY8YMPD09ad68ObGxsZw5cwYwWr+y7o9Op6N169aUKVMGnU6n+uts3ryZxYsX4+Xlha+vL/Hx8Wr/Zs2aUadOHXX+vOZxdnbm/PnzvPnmm2zcuJEKFSrkkltDQ0PjsXH7NrzyitHS8rdxpxD3LfEF8cPBH+i0vBMVylZg96DdzHhxBuXLFi7/0ZPAU7kLafv2/OusrGDpUvD3h/R0MDc3nmfldaxSpeD+eeHg4ICDgwO+vr4A9OzZU1VgLC0tSU01hmBOTU1l+PDh7N+/n1q1ajFhwgS1Lqve0tIyzznq1q3LsGHDGDx4MHZ2dsTHxxeoBGRPBmlqaoperwcgNDSUsLAwrl69SkhISK7+8fHxbN26laNHj6IoCpmZmSiKwrRp03BwcMDb2xtnZ2fAuLyyZ88eQkJCSEhIQK/XY2ZmxqVLl6hRo4Z6b7JneM6qS09Pz7O8MGzfvp0tW7YQGRmJlZUVbdq0Ue9jmTJl1HtgYmKi3gcTExP1HogI3377LR06dMg1bvbklvnNU7FiRQ4fPsymTZuYNWsWP//8MwsWLCiU7BoaGhr/ij//NEbUvXrVuGzUNFdKoByICDfv3cTO2o6erj25nXKbkc1HPjFbo/8Nz6QFxs8PIiJg0iTj66Mmpa5evTq1atXi1KlTAERERKh+Ki4uLpw9exZAfchWqVKFpKQkwsPDc4xz+vRp3N3dc42/fv16VVk5c+YMpqam2Nra0qpVK5YuXQoYH7ZVqlR5qDWgW7dubNy4kX379uV6gIPRZ2fAgAFcuHCBmJgYYmNjqVOnDjt37sTHx4fbt29z48YNwGgdcXV1RVEU2rZtq17PokWL6NKlCwCdO3dm8eLFiAh79uzBxsYGe3t7fHx8OHPmDNHR0aSnp7NixQo6d+6cSx5/f39mz54NGH1P7ty5Q2JiIhUrVsTKyoqTJ0+yZ8+eAq/5QTp06MDs2bPJyMgAjPc9OTk5V7v85rl58yYGg4EePXowadKkHDurNDQ0NB4bEycaI+paWhodNt97D0xN821+7tY5ApYE4L/Yn4zMDGwtbBnbYuxTqbzAU2qBKQx+fo+uuGTn22+/5bXXXiM9PR1nZ2cWLlwIGJdy5s6dS2hoKLa2tgwePBidToeTkxM+2RyvMjIyOHv2LE3z0K5//PFHRo8ejZWVFWZmZixduhRTU1MmTJhAcHAwHh4eWFlZsWjRoofKaW5uTtu2bbG1tcU0jz+E5cuXM27cuBxlPXr0YNmyZTz//PNMnz4df3//LH8kBg8eDMBnn31Gnz59+PDDD/H29lYdml966SU2bNhAvXr1sLKyUu+LmZkZM2fOpEOHDmRmZhISEoJbHuGuv/nmG4YMGcL8+fMxNTVl9uzZBAYGMmfOHDw8PGjYsCHNmzd/6HVnJzQ0lJiYGBo3boyIYGdnpzodZye/eS5fvkxwcDCG++uQU6ZM+Vfza2hoaBSKihVh0CBjBukCgtLpDXq+ivyK8dvHU8a0DNNemIapSf6KztOCktcyRGmmadOmsn///hxlJ06cwMXFpYQkejgtW7Zk3bp16s6kvFi1ahUHDx5k0qRJRSqLwWCgcePGrFy5kvr16xfpXM86pf17qaGhUcoQgbAwo7LSq5fxPA/fwOxcvnOZl5e/zKGrh+jSsAuzXppFzQo1i0feYkJRlAMikuvX/TO5hFTcfPHFF1y8eLHANnq9nnfeeadI5Th+/Dj16tXD399fU140NDQ0ShO3bkHv3hASAvc3TjxMeQGoal0VO2s7wnuFs+qVVU+d8lIQz+wSUnGS5dxbEL169SpyOVxdXTl//nyRz6OhoaGh8S/Yvh369/+vo+6YMQU2jzgfwSd/fsLavmuxtbBlU79NxSNnKUOzwGhoaGhoaJQUR49Cu3bGLbJ79hToqBt/L57gNcG88OMLxCXFcfnO5WIWtnShWWA0NDQ0NDSKm+RksLYGd3dj5uhevYzneSAi/HTsJ0ZuHMmtlFu83/J9Pmr1EZZl8g678aygWWA0NDQ0NDSKCxGYPx8cHeGff4xlQUH5Ki9ZLDq8iNo2tdk/eD+f+n/6zCsvoFlgNDQ0NDQ0iodbt2DIEPjlF2N8l4oV822aachk9v7ZdGrQCSdbJ5Z1X0aFshWeie3RhUWzwDwmEhIS6NmzJ40aNcLFxYXIbFkiR40axY4dOwrsP2bMGLZu3Zpn3Z49e/D19cXLywsXFxcmTJjwOEUvNKNHj8bLywsvLy8aNGigbguPiYnB0tISLy8vXF1dGTBggBokLjsxMTG4u7uTnJxM5cqV1bQHWXTt2pWff/65OC5FQ0NDo3jZvh08PWHtWpg2DbZsAQeHPJseu36Mlgtb8ubvb7LwkDF2VkXLipry8iB5JUgqzUdhkjmWBAMGDJB58+aJiEhaWpqa4C8+Pl58fX0f2j8mJkbat2+fZ12DBg0kKipKRIwJDY8VMolXUTJjxgwJDg4WEZHo6Gg1eaNer5e2bdvKkiVLcvXJ3q5Pnz4SFham1iUkJEjlypUlOTm5GKQvHHq9/pH6l4bvpYaGRinh3XdFGjQQ2b8/3yapGany8daPpczEMlL5s8ry4+EfxWAwFKOQpRO0ZI45iYyEKVOMr4/KnTt32LFjhxp91tzcXLVOhIeHq8kFASZOnIiPjw/u7u4MGTJETRHg6OhIfHw8V69ezTX+9evXsbe3B4x5jbLSFNy6dYuuXbvi4eFB8+bNOXLkCAATJkwgJCSENm3a4OzszIwZMwD46KOP+Oabb9RxP/jgA7UuO5MnT0an0+Ht7c3OnTt5+eWXc7VZvnw5ffv2zVVuampKs2bNuHy5YO/4vn37smLFCvV81apVBAYGYmVllaNdZmYmY8aMQafT4eHhwbfffgvkfx/btGnD6NGjadWqFS4uLuzbt4/u3btTv359PvzwQ3XcJUuW0KxZM7y8vHj99dfJzMwEoFy5cnz88cf4+voSGRmZ7zwzZszA1dUVDw8PNfGlhoaGRg7OnIG9e43vJ02CgwehSZN8m3/616dM3DGRV9xf4cSIE/Tz6JdnkluN++Sl1ZTm42EWmJEjRVq3Lvjw8hIxMREB46uXV8HtR44sWDs8dOiQ+Pj4yMCBA8XLy0sGDRokSUlJImK0zKxdu1ZtGx8fr77v169fjrrQ0FAJDw/PNf4nn3witra20rVrV5kzZ46kpKSIiMgbb7whEyZMEBGRiIgI8fT0FBGR8ePHi5+fn6SmpsqNGzekUqVKkp6eLtHR0eLt7S0iIpmZmeLs7Cw3b97MMVdkZKR4eXlJRkaGLF++XKpVqyZz5szJ0SYmJkaqV6+uWiiyW1ZSUlKkTZs2cvjw4VzXkb1dWlqa2NnZqfN36NBB1q1bl6vPd999J927d5eMjIwc9y+/+9i6dWt59913RUTk66+/Fnt7e7ly5YqkpqZKzZo15ebNm3L8+HHp1KmTpKeni4jIsGHDZNGiRSIiAshPP/2kjp3fPPb29pKamioiolrbHkSzwGhoPKMYDCI//CBiZWV8wBRgRUlMTZTTN0+LiEhCSoJsOrupuKR8YkCzwPyXxES4n8YGg8F4/ijo9XoOHjzIsGHDOHToENbW1mo26ri4OOzs7NS227Ztw9fXF51Ox9atWzl27JhaV7VqVa5cuZJr/I8//pj9+/cTEBDAsmXLVIvOzp076d+/PwDt2rUjPj5e9Svp2LEjZcuWpUqVKlStWpVr167h5ORE5cqVOXToEJs3b8bb25vKlSvnmCsyMpKOHTtiZmZGYGAg169fp1OnTjnarFixgp49e+bIpXTu3Dm8vLyoXLkytWvXxsPDo8B7Zm5uTufOnQkPD+fmzZtERUUREBCQq92WLVsYOnQoZmZGf/NKlSo99D5mJYXU6XS4ublhb29P2bJlcXZ2JjY2loiICA4cOICPjw9eXl5ERESoAf5MTU3p0aPHQz8vDw8PXnvtNZYsWaLKpqGhocGtW8Yt0aGh0Lw5rFuXb0TdNSfX4DrLlVfCX0FEsLGwIaBu7v+DGnnz1P3n/frrh7eJjAR/f0hPB3NzWLr00RI7Ojg44ODgoEbc7dmzp6rAWFpaqlmoU1NTGT58OPv376dWrVpMmDBBrcuqt7TMe2tc3bp1GTZsGIMHD8bOzo74+Hh1OSM7WebGsmXLqmWmpqbo9XrAmMgwLCyMq1evEhISkudcWX3Lli1LzZo1qVkzZ2jqFStWMGvWrFzyRUVFERcXR5s2bVi7dm2e2aWz07dvXyZPnoyI0KVLF8qUKZOrjYjkMqE+7D5myW9iYpLjPpiYmKDX6xERBg4cmGcSRgsLC1UxK2ie9evXs2PHDtauXcukSZM4duyYpshoaDzrXLgALVrA9etGR9133gGT3HaCuLtxvLXxLcKPh+NRzYO5neZqS0X/A8+kBcbPDyIijEuSERGPnpW6evXq1KpVi1OnTgEQERGh+qm4uLhw9uxZAPXhV6VKFZKSkggPD88xzunTp3F3d881/vr161Vl5cyZM5iammJra0urVq1YunQpANu3b6dKlSpUqFChQFm7devGxo0b2bdvHx06dMhV37RpU3bt2gXA2rVruXLlCjdu3FDrT506xe3bt/HL56bZ29szderUQmVobtu2LWfOnGHWrFl5+tMABAQEMGfOHFUBu3Xr1kPv48Pw9/cnPDyc69evq2NeuHAhV7v85jEYDMTGxtK2bVumTZtGQkICSUlJ/0oGDQ2Np5BataBTJ2NE3bFj81ReDl89jOt3rvx26jc+bfcp+wfvx6emTwkI++TzzP5k9PN7dMUlO99++y2vvfYa6enpODs7s3Chcetbx44dmTt3LqGhodja2jJ48GB0Oh1OTk74+Pz3S5uRkcHZs2dp2jRXwk1+/PFHRo8ejZWVFWZmZixduhRTU1MmTJhAcHAwHh4eWFlZsWjRoofKaW5uTtu2bbG1tc2xBJTF888/j5ubGy+99BLJycksXryY7t27s2nTJqysrFi+fDl9+vQp8NdC165dmTBhAn/99RfPP/98vu1MTEzo0aMHK1eupFWrVnm2CQ0N5fTp03h4eFCmTBkGDx7MG2+8ke99LAyurq5MnjyZgIAADAYDZcqUYdasWTg6OuZol9/nlZmZSb9+/UhMTEREGD16dIGZxjU0NJ5iTp2CN980RtN1cIA5c/Jslp6ZjrmpOa52rvR27c07z71Dg8oNilnYpwslr2WI0kzTpk1l//79OcpOnDiBi4tLCUn0cFq2bMm6desKfMitWrWKgwcPMmnSpCKVxWAw0LhxY1auXKllpC5iSvv3UkND4xEQgR9+gFGjwMICfv0VWrfO1SwjM4Ppu6cz7+A8Dr5+EFsL22IX9UlHUZQDIpLr1/0zuYRU3HzxxRdcvHixwDZ6vZ533nmnSOU4fvw49erVw9/fX1NeNDQ0NP5X4uOhRw9jVF0/PzhyJE/lZd/lfTSd15T/2/p/NKnRhIzM3AE+Nf53ntklpOIky7m3IHr16lXkcri6uqq7bTQ0NDQ0/kcmTDDuLvr8c3j77Vy+LhmZGby35T2++fsbqperzqpXVtG1UdcSEfVpRlNgNDQ0NDQ0HkZ6Oty4ATVrwuTJEBIC3t55NjUzMeN0/GmGNB7C1BemYmNhU8zCPhvkq8AoilKpEP0NIpLw+MTR0NDQ0NAoZZw6Ba++agwctm8f2NjkUl5u3rvJe3+8x4etPqROxTqs7rMaMxPNRlCUFHR3r9w/CtqcbgrUfqwSaWhoaGholAayO+paWhrfPxDvSURY9s8yRm0aRWJqIu3qtKNOxTqa8lIMFHSHT4hI3vax+yiKcqiAugVAJ+C6iOQKbqIY9+F+A7wE3AOCRORgoaTW0NDQ0NAoShITITgYVq2CF16ARYugRo0cTWISYhi6biibzm2iuUNz5r08D/equWN5aRQNBe1CKkyUlILahAGBBdS/CNS/fwwBZhdivlJLQkICPXv2pFGjRri4uBCZLUvkqFGj2LFjBwBOTk7cvHkzV/+ZM2eqsWMe5NSpU7Rp0wYvLy9cXFwYMmRI0VxENg4dOoSiKGzatClHeX7XeevWLdq3b0/9+vVp3749t2/fVvtMmTKFevXq0bBhwxzjHThwAJ1OR7169XjrrbfyjCysoaGhUSKULQuxsTB9OmzalEt5Afgy8kt2xe7i2xe/ZWfwTk15KW7ySpCU/QAq5XGUeVi/+32dgKP51M0F+mY7PwXYP2zMhyVzLCkGDBgg8+bNExFjosKsBH/x8fHi6+urtnN0dJQbN27k6p+cnCxeXl55jh0QECCrV69Wz48cOfIYJc+bsWPHSsuWLWXgwIE5yvO7zrFjx8qUKVNERGTKlClqQsVjx46Jh4eHpKamyvnz58XZ2VlNAunj4yO7d+8Wg8EggYGBsmHDhiK/rsJiMBgkMzPzkcYoDd9LDQ2Nf0FamsjkySKJicbz+/+rsnP46mE5FHdIRIzJFy8kXChGAZ9NeIRkjgeBG8Bp4Mz999GKohxUFCX/vOAPpyYQm+380v2yXCiKMkRRlP2KouzPHtb+UYiMjWTKX1OIjI18eOOHcOfOHXbs2MGgQYMAY7TbrKB14eHhavLFLD7//HOaNWtGs2bN1DQDVlZWODk5sTcr9Xo24uLicHBwUM91Oh1gDHUfHByMTqfD29ubbdu2ARAWFkb37t0JDAykfv36vPvuuwDMnz+f0aNHq+PMmzePt99+O9d8IkJ4eDhhYWFs3rxZDalf0HWuWbOGgQMHAjBw4EBWr16tlvfp04eyZctSp04d6tWrx969e4mLi+POnTv4+fmhKAoDBgxQ+2QnKSlJvUYPDw9++eUXAIYNG0bTpk1xc3Nj/PjxansnJyf+7//+Dz8/P5o2bcrBgwfp0KEDdevWZU62CJmff/45Pj4+eHh4qP1jYmJwcXFh+PDhNG7cmNjY2HznGTduHK6urnh4eDBmzJhccmtoaDxhnDxpTL744YfGZSOAbNHKUzJS+L+I/6PJ900Ys9n4N29jYUNtm2fbDTQyEqZMMb4WN4XxMtoIrBKRTQCKogRgXBr6GfgOeHiQk7zJyzk4zzUEEfke+B6MkXgfNnCbsDa5ynq79Wa4z3DuZdyjxYIWHLl2BIMYMFFM8KjmwUjfkQR5BXHz3k16/twzR9/tQdsLnO/8+fPY2dkRHBzM4cOHadKkCd988w3W1tbs2rWLnj1zjlehQgX27t3L4sWLGTVqFOvWreP+tfHXX3/RrFmzHO1Hjx5Nu3bteO655wgICCA4OBhbW1s1oeI///zDyZMnCQgI4PTp0wBERUVx6NAhypYtS8OGDXnzzTfp06cPHh4eTJs2jTJlyrBw4ULmzp2b63p27dpFnTp1qFu3Lm3atGHDhg107969wOu8du0a9vb2gDEfUlaeocuXL9O8eXN1bAcHBy5fvkyZMmVyKGVZ5Q8yadIkbGxs+OeffwDUpan//Oc/VKpUiczMTPz9/Tly5IiaAbtWrVpERkYyevRogoKC2LVrF6mpqbi5uTF06FA2b97MmTNn2Lt3LyJC586d2bFjB7Vr1+bUqVMsXLiQ7777Lt95HBwcWLVqFSdPnkRRFBISEgr8fmhoaJRiRGDePKOjrpUVrF4NXbrkaLI9ZjtDfhvCmVtnCPYKZnrA9BIRtbQRGQnt2kFGhjEx8uPILfhvKIwFpmmW8gIgIpuBViKyByibf7eHcgmole3cAeOupyInMTURgxgAMIiBxNTERxpPr9dz8OBBhg0bxqFDh7C2tlazUcfFxWFnZ5ejfVbiwr59++bwlalatSpXruS+BcHBwZw4cYJevXqxfft2mjdvTlpaGjt37qR///4ANGrUCEdHR1WB8ff3x8bGBgsLC1xdXblw4QLW1ta0a9eOdevWcfLkSTIyMlRrTnay8h0B9OnTh+XLlz/0OvND8smYnV/5g2zZsoURI0ao5xUrVgTg559/pnHjxnh7e3Ps2DGOHz+utsnKgq3T6fD19aV8+fLY2dlhYWFBQkICmzdvZvPmzXh7e9O4cWNOnjzJmTNnAHB0dMyhcOU1T4UKFbCwsCA0NJRff/0VKyurAu+BhoZGKWbSJHj9dWjZ0hhR9wHlZcOZDbRd1JZMyeSP/n+woMsCKlkWJsrI08+330JqKmRmGsPkbN9evPMXxgJzS1GU94AV989fAW4rimIKGB5h7rXAG4qirMBoxUkUkbhHGE+lIIuJVRkrlnZfiv9ifzW51tLuS/GrZVQbq1hVeajF5UEcHBxwcHBQI+727NlTfbBbWlqqSzBZZH9QZ3+fmpqKpaVlnnPUqFGDkJAQQkJCcHd35+jRowU6vZYt+1/d0tTUVM3mHBoayqeffkqjRo0IDg7O1S8zM5NffvmFtWvX8p///AcRIT4+nrt37xZ4ndWqVSMuLg57e3vi4uKoWrWqem9iY/+7Unjp0iVq1KiBg4MDly5dylX+ICKSS7GJjo5m+vTp7Nu3j4oVKxIUFJTjHmddu4mJSY77YGJigl6vR0R4//33ef3113OMGxMTg7W19UPnMTMzY+/evURERLBixQpmzpzJ1q1b8/wcNDQ0Sil6vXFLdHCwMa7Lm2+qEXVFhKtJV7Evb0975/ZMbz+dYT7DsCqj/VgBuH4dRoyA8HBQFONtMzeHNm2KV47CWGBexWgdWX3/qHW/zBTonV8nRVGWA5FAQ0VRLimKMkhRlKGKogy932QDcB44C8wDhv+P1/Cv8avlR8SACCa1nUTEgAhVeflfqV69OrVq1eLUqVMARERE4OrqCoCLi4vq55LFTz/9pL76ZbO3nT59Gnf33F7sGzduJCPDmEPj6tWrxMfHU7NmTVq1asXSpUvVvhcvXqRhw4YFyurr60tsbCzLli1TLUHZ2bJlC56ensTGxhITE8OFCxfo0aMHq1evLvA6O3furGbDXrRoEV3u/4rp3LkzK1asIC0tjejoaM6cOUOzZs2wt7enfPny7NmzBxFh8eLFap/sBAQEMHPmTPX89u3b3LlzB2tra2xsbLh27Rq///57gdf8IB06dGDBggUkJSUBxmWurCWv7OQ3T1JSEomJibz00kt8/fXXREVF/av5NTQ0SpC0NBg7Fl5+2RiYrlYtGDlSVV4u37lM95+70/j7xtxOuU0Z0zK889w7mvJyn6NHwdUV1q41+r78+afRiFXcy0dQCAuMiNwE3lQUpZyIJD1QfTavPvf75X465qwXYERBbYoSv1p+j6y4ZOfbb7/ltddeIz09HWdnZ3VLdMeOHZk7dy6hoaFq27S0NHx9fTEYDOryDBh9T7I7imaxefNmRo4ciYWFBWB0QK1evTrDhw9n6NCh6HQ6zMzMCAsLy2FxyI/evXsTFRWlLsdkZ/ny5XTr1i1HWY8ePZg9ezb9+/fP9zrHjRtH7969mT9/PrVr12blypUAuLm50bt3b1xdXTEzM2PWrFmY3neMmz17NkFBQaSkpPDiiy/y4osv5pLnww8/ZMSIEbi7u2Nqasr48ePp3r073t7euLm54ezsTIsWLR56zdkJCAjgxIkTqvJYrlw5lixZosqVhaenZ57z3L17ly5dupCamoqI8NVXX/2r+TU0NEqIkyeNEXUPHYKhQ43OG/f/ZxrEwPcHvue9Le+RnpnOxDYTKV+2fAkLXHowGIw6XsOG0LkzvPMOuLkZ655/voSEymtrUvYDeA44Dly8f+4JfPewfkV1lNZt1AXRokULdbtxfhw8eFD69etXLPJ07NhRtmzZUixzPcuU9u+lhsYzg8EgMmeOiKWlSOXKItnCUoiIJKYmSssFLYUJiP8ifzkbf7aEBC19GAwiy5aJeHiI3LpVMjLwCNuovwI6APH3FZ7DQKuiUKaeVr744gsuXrxYYJubN28yadKkIpUjISGBBg0aYGlpib+/f5HOpaGhoVFquHvXuM7RsiX884/qqCv3/QjLm5fHydaJhV0W8kf/P6hbqW5JSltquHoVunc3Gq0sLY3BiUsThUrWICKxDzhSZhaNOE8nWU6vBdG+ffsil8PW1lbdpaShoaHx1LNzJzRrBhUqwK5dRn+X+74ukbGRjNo0ihU9VlCnYh1+7PZjCQtbehCB5cuNfs3JyTBtGrz9do6wOKWCwlhgYhVFeQ4QRVHMFUUZA5woYrk0NDQ0NDT+N9LSjE4azz8PM2YYyxwdwcSEu2l3eev3t2ixoAVX7l4hLumxbH596liyBBo0gKgoo89zaVNeoHAWmKEYky7WxBi7ZTMl6HyroaGhoaGRLydOGNc8oqJg+HDjcZ8NZzYwdN1QLt25xAifEXzq/6nmqHsfEVi61LjK5uQEy5ZB+fKlU3HJorC7kF4rBlk0NDQ0NDT+d1auhIEDwdrauM/35ZdzVK87vY7yZcuzK2TXY92F+qRz5YpxU9ZvvxmXir74Au5niSnV5KvAKIryLfmE9gcQkbeKRCINDQ0NDY3/hQYN4IUXYO5csLdHRAiLCsPVzhVfB18+b/85ZUzLYG5qXtKSlgpE4McfjWFwUlPhyy/hrSfoyV6QD8x+4ABgATTGmMjxDOCF5sSbi4SEBHr27EmjRo1wcXHJkSJg1KhR7NixAzAmG7x582au/jNnzlRjqjzIqVOnaNOmDV5eXri4uDBkyJCiuYiH8Pnnn+Pl5YWXl5cal+XWrVuAMdpvVvnLL7+cb36gcuXKAVCnTh01IF4Wo0aNYtq0aUV6DRoaGk8Zf/wB48YZ33t6Gi0v9vacu3WO9j+2J2RtCD8c/AEAa3NrTXnJxqxZRoOVqyscPgyjR5fuJaNc5LW3OvsBbAPKZDsvA2x7WL+iOkprHJgBAwbIvHnzREQkLS1NjfsSHx8vvr6+ajtHR0e5ceNGrv7Jycni5eWV59gBAQGyOlvcgiNHjjxGyf831q5dK23btlXPra2t1fcDBgyQyZMn59kvq924ceNkwoQJanlmZqbUrFlTYmJiikjif49er3+k/qXhe6mh8dSSmiry9tsiIOLqKpKYKCIiGZkZMm3nNLGcbCnlPy0vs/fNlkxDZgkLW3owGERu3jS+T0wU+e47kUf8V1fk8AhxYGoA2b2cyt0ve6KJjI1kyl9TiIx99Bzgd+7cYceOHQwaNAgAc3NzbO8vIIaHhxMYGJij/eeff06zZs1o1qyZmmbAysoKJycn9u7dm2v8uLi4HJmbsxIwpqamEhwcjE6nw9vbm23btgEQFhZG9+7dCQwMpH79+rz77rsAzJ8/n9GjR6vjzJs3j7fffjvXfAsWLECn0+Hu7s6OHTt47rnncrVZvnx5nqkIAPz8/PLMLJ2dvn37smLFCvV8x44dODk54ejomKvttGnT0Ol0eHp6Mu7+L6158+bh4+ODp6cnPXr04N69ewAEBQUxbNgw2rZti7OzM3/++SchISG4uLgQFBSkjrl582b8/Pxo3LgxvXr1UtMKODk5MXHiRFq2bMnKlSvznWflypW4u7vj6elJq1ZaWCQNjWLl+HHw9TWueYwYAfv3G7dKA2FRYby75V0C6gZwYsQJhjYdiolSmEfd08/ly9CpkzFnUVqa8ZYNG/aEWV2yUZhdSFOBQ4qibLt/3hqYUGQSPSKjNo4i6mpUgW0S0xI5cu0IBjFgopjgUc0Dm7I2+bb3qu7F14Ff51t//vx57OzsCA4O5vDhwzRp0oRvvvkGa2trdu3aRc+ePXO0r1ChAnv37mXx4sWMGjWKdevWAdC0aVP++usvmjVrlqP96NGjadeuHc899xwBAQEEBwdja2vLrFmzAPjnn384efIkAQEBapyXqKgoDh06RNmyZWnYsCFvvvkmffr0wcPDg2nTplGmTBkWLlzI3Llzc8wVGxvLhAkTOHbsGMeOHaNr1665kj7eu3ePjRs35shRlEVmZiYRERGqMpcfHh4emJiYcPjwYTw9PVmxYkWeCtHvv//O6tWr+fvvv7GyslKXrLp3787gwYMBY7qB+fPn8+abbwLGfElbt25l7dq1vPzyy+zatYsffvgBHx8foqKicHBwYPLkyWzZsgVra2s+++wzvvzySz7++GMALCws2LlzJwDx8fF5zjNx4kQ2bdpEzZo1810u09DQKAJSU8Hf35iM8bffoFMn7mXc48zVw3hW92Sg50Bqlq9JYL3APDPcP4uIwKJFMGqUMWv0lClQpkxJS/XoPFQtFZGFGLNFr7p/+InIoqIWrChJTE3EIMZE2gYxkJj6aOEF9Xo9Bw8eZNiwYRw6dAhra2s1S3NcXBx2dnY52mc9qPv27ZvDV6Zq1apcuXIl1/jBwcGcOHGCXr16sX37dpo3b05aWho7d+6kf//+ADRq1AhHR0dVgfH398fGxgYLCwtcXV25cOEC1tbWtGvXjnXr1nHy5EkyMjJUa04W+/fvp1WrVpQvX16d5+UHPPl/++03WrRoQaVK/00pn5KSgpeXF5UrV+bWrVuFCsyXZYXR6/WsWbOGXr165WqzZcsWgoODsbIyJlLLmvPo0aM8//zz6HQ6li5dyrFjx9Q+L7/8MoqioNPpqFatGjqdDhMTE9zc3IiJiWHPnj0cP36cFi1a4OXlxaJFi7hw4YLa/5VXXlHf5zdPixYtCAoKYt68eWRmai5hGhpFzu3bxiexhYUxSMk//0CnTkScj0A3W0fg0kBSMlIoY1qGF+u/qCkv97l1y2h1CQ4GDw84ciRH7sonmoJ2IVUXkasA91/XFNSmtFCQpSSLyNhI/Bf7k56ZjrmpOUu7L32kLXUODg44ODioEXd79uypKjCWlpakpqbmaJ/9Dyv7+9TUVCwtLfOco0aNGoSEhBASEoK7uztHjx5Vw2DnRfakjqampuj1egBCQ0P59NNPadSoUS7LSl59y5cvj7e3d476vKwllpaWREVFkZiYSKdOnZg1axZvPcSdvW/fvgQEBNC6dWs8PDyoWrVqrjYikuc/oqCgIFavXo2npydhYWFs3749l/wmJiY5rsXExAS9Xo+pqSnt27fPkUgzO9bW1g+dZ86cOfz999+sX78eLy8voqKiqFy5coHXq6Gh8T+yebPR2/Sjj4xxXfz9uZVyizFrQlgYtZD6leqzvMdyLMvk/f/zWaZ8ebhzxxjPb8SIp0NxyaKgS9lQiP6FaVPq8KvlR8SACCa1nUTEgIhHjgdQvXp1atWqpe6qiYiIwNXVFQAXFxfVzyWLn376SX31y5Z//PTp07i7u+caf+PGjWRkZABw9epV4uPjqVmzJq1atWLp0qVq34sXL9KwYcMCZfX19SU2NpZly5bluWTTuHFj9u3bR2ZmJn///TeXL1/m6NGjan1iYiJ//vknXe7nEnkQGxsbZsyYwfTp01WZ86Nu3bpUrlyZcePG5etPExAQwIIFC1Tfk6wlpLt372Jvb09GRoZ6DwpL8+bN2bVrl/q53Lt3L98UC/nNc+7cOXx9fZk4cSJVqlQhNjb2X8mgoaFRCNLSjIFJOnSASpWMUdaAS3cu4TLLhcWHF/N+y/c5PPQwbZzalKyspYjYWBgwwGi0KlMGduwwpgV4mpQXKNgHxlNRlDsF1CtAQfWlGr9afo81kNG3337La6+9Rnp6Os7OzuqW6I4dOzJ37lxCQ0PVtmlpafj6+mIwGHJYAXbt2sX48eNzjb1582ZGjhyJhYUFYHQCrl69OsOHD2fo0KHodDrMzMwICwvLYXHIj969exMVFUXFihVz1Tk6OhIUFERgYCB37twhPDyckSNHsmzZMpycnFi1ahUBAQE5rBQP4u3trfq1ZC1x5Uffvn15//336datW571gYGBREVF0bRpU8zNzXnppZf49NNPmTRpEr6+vjg6OqLT6bh79+5DrzsLOzs7wsLC6Nu3L2lpaQBMnjyZBg0a5Gqb3zxjx47lzJkziAj+/v54enoWen4NDY1CcPy4MaLu4cPwxhswbRqpZRQsgJrlaxLkGcSrulfxrK797WUhAvPnG3W+zEyjEvPCC/DUrqbltTWpNB+ldRt1QbRo0ULdVp0fBw8elH79+hWLPB07dpQtW7YUy1zPMqX9e6mhUarZvFmkalWRdetEn6mXGXtmSLXPq8m5W+dKWrJSyYULIgEBxl3lbdqInHuKbhOPsI1a4xH54osvuHjxYoFtbt68yaRJk4pUjoSEBBo0aIClpSX+/v5FOpeGhobGv+bGDcgKr9C+PZw/zzEfJ1oubMlbG9/Cs7onZiaF2Tz77DFmjDHh9qxZEBEBzs4lLVHRo0gBjqClkaZNm8r+/ftzlJ04cQIXF5cSkkhDI2+076WGxr8gy1H3zh2Ijkbs7Jj450T+89d/qFC2Al8Hfs1rute03UXZuHDB6NdSq5Yxxkt6OtSpU9JSPX4URTkgIk0fLNcsMBoaGhoaJUdqqjGGfYcOULky7NkDVauiKArXk6/zivsrnBhxgn4e/TTl5T4ixnRP7u5G9yCAmjWfTuWlIApli1MUxRSolr29iBS8JqKhoaGhoVEQej08/7wxku4bb5A46QPG7fyEgRUH0tyhOTNenIGpyRMaJraIiImB0FDjMpG/P3zzTUlLVHI8VIFRFOVNYDxwDTDcLxbAowjl0tDQ0NB4WhExbo0xMzNGWJswgTV19Qxf0ISrSVdpULkBzR2aa8rLA/z5pzEoHcCcOTBkyFO8w6gQFGYJaSTQUETcRER3/9CUFw0NDQ2Nf8/169C5M6wxxkaN69+NXvfC6PpTV6pYVWHPoD2M9hv9kEGeLbJcVb29oXt3OHoUXn/92VZeoHAKTCzwaLH2nwG++uor3NzccHd3p2/fvjmi744aNYodO3YU2H/MmDFs3bo1z7o9e/bg6+uLl5cXLi4uTJgw4XGKnierVq1CURROnjyZo/zixYsEBATg4uKCq6srMTExAERHR+Pr60v9+vV55ZVXSE9PB4zb9N966y3q1auHh4cHBw8eVMfauHEjDRs2pF69emrkYg0NjaeYjRuN8ez/+ANu3gRg2T/L+O3Ub3za7lP2D96PT02fEhay9GAwwOzZ8Nxz/02+uGgR5JHz9tkkr73V2Q9gPrATeB94O+t4WL+iOkpjHJhLly6Jk5OT3Lt3T0REevXqJQsXLhQRkfj4ePH19X3oGDExMdK+ffs86xo0aCBRUVEiIqLX6+XYsWOPR/AC6NWrl7Rs2VLGjx+fo7x169ayefNmERG5e/euJCcnq+2XL18uIiKvv/66fPfddyIisn79egkMDBSDwSCRkZHSrFkz9TqcnZ3l3LlzkpaWJh4eHsVyXYVF/xjyy5f091JDo9SQkiIycqQxSIm7u5ze/ZtsPb9VREQyMjPkbPzZkpWvFHL+vEjbtsZb1r69yI0bJS1RycEjxIG5CPwBmAPlsx1PNJGJiUy5cIHIxMdjXNLr9aSkpKDX67l37x41atQAIDw8nMDAQLXdxIkT8fHxwd3dnSFDhqj5jBwdHYmPj+fq1dyppa5fv469vT1gzGuUlabg1q1bdO3aFQ8PD5o3b86RI0cAmDBhAiEhIbRp0wZnZ2dmzJgBwEcffcQ32Ty+PvjgA7UuO0lJSezatYv58+ezIismA3D8+HH0er2aqLFcuXJYWVkhImzdulXNuj1w4EBWr14NwJo1axgwYACKotC8eXMSEhKIi4tj79691KtXD2dnZ8zNzenTpw9r1uRKt8W1a9fo1q0bnp6eeHp6snv3bgC6du1KkyZNcHNz4/vvv1fblytXjvfee48mTZrwwgsvsHfvXvU+rF27FjBmzB47diw+Pj54eHioGbm3b99O27ZtefXVV9Ukl3nNk5mZSVBQEO7u7uh0Or766qtccmtoaGRj3Tr45hsy3hzO1Bm90UX0ZNj6YRjEgJmJGXUr1S1pCUsNBoMxlotOZ/RtnjcPNm2CKlVKWrJSSF5aTV4HRqWlXGHbF9VRGAtM64MHcx2zLl0SEZFkvV689u4Vk23bhG3bxGTbNvHau1cWXrkiIiI30tJy9S0MX3/9tVhbW0uVKlXk1VdfVcsHDBgga9euVc/j4+PV9/369ctRFxoaKuHh4bnG/uSTT8TW1la6du0qc+bMkZSUFBEReeONN2TChAkiIhIRESGenp4iIjJ+/Hjx8/OT1NRUuXHjhlSqVEnS09MlOjpavL29RUQkMzNTnJ2d5ebNm7nm+/HHHyUkJERERPz8/OTAgQMiIrJq1Srp2LGjdOvWTby8vGTMmDGi1+vlxo0bUrduXbX/xYsXxc3NTUSMUX//+usvta5du3ayb98+WblypQwaNEgtX7x4sYwYMSKXLL1795avvvpKRIxWkYSEhBz38d69e+Lm5qZeByAbNmwQEZGuXbtK+/btJT09XaKiotT7M3fuXJk0aZKIiKSmpkqTJk3k/Pnzsm3bNrGyspLz58+r8+c1z/79++WFF15Q2+QXZVmzwGg80xgMIllWVYNB9m5ZJJ6zPYUJSI+fesiVO1dKVr5SSnq6iLe3SIcOxui6Go9ggVEUxV1RlEPAUeCYoigHFEVxK1KtqohJ1OvV7VSG++ePwu3bt1mzZg3R0dFcuXKF5ORklixZAkBcXBx2dnZq223btuHr64tOp2Pr1q0cO3ZMratatSpXrlzJNf7HH3/M/v37CQgIYNmyZapFZ+fOnWquoXbt2hEfH0/ifYtSx44dKVu2LFWqVKFq1apcu3YNJycnKleuzKFDh9i8eTPe3t55ZlBevnw5ffr0AaBPnz5qvia9Xs9ff/3F9OnT2bdvH+fPnycsLEy1ImUnK15DfnUF9cnO1q1bGTZsGGC0PtnY2AAwY8YMPD09ad68ObGxsZw5cwYAc3Nz9f7odDpat25NmTJl0Ol0qr/O5s2bWbx4MV5eXvj6+hIfH6/2b9asGXWyBVPIax5nZ2fOnz/Pm2++ycaNG6lQoUIuuTU0nmmuXzdul/HxgQsXOHztCM13BXPj3g1WvbKK8N7h2Je3L2kpSw0GgzGuS1byxT/+gN9/h9q1S1qy0k1h4sB8j9HnZRuAoihtgHnAc0Un1qOx3ds73zorU1OWurrif/gw6QYD5iYmLHV1xe/+g7GKuXmB/fNiy5Yt1KlTR1VUunfvzu7du+nXrx+WlpaqQ29qairDhw9n//791KpViwkTJuRw9k1NTcXSMu908HXr1mXYsGEMHjwYOzs74uPjC1QCsid1NDU1RX9fSQsNDSUsLIyrV68SEhKSq398fDxbt27l6NGjKIpCZmYmiqIwbdo0HBwc8Pb2xvl+jOquXbuyZ88eQkJCSEhIQK/XY2ZmxqVLl9QlNAcHhxyZmrPq0tPT8ywvDNu3b2fLli1ERkZiZWVFmzZt1PtYpkwZ9R6YmJio98HExES9ByLCt99+S4cOHXKNmz1JZX7zVKxYkcOHD7Np0yZmzZrFzz//zIIFCwolu4bGU8/vv0NQECQmEjv1/6hVuzYe1GZG4Az6efTDxsKmpCUsVZw9C4MGGTNGJycbEzHm8buy1JIYmUjC9gRs29hi41e8n21hfGCss5QXABHZDuSfivgJwM/GhghPTybVqUOEp6eqvPyv1K5dmz179nDv3j1EhIiICDWEvIuLC2fPngVQH7JVqlQhKSmJ8PDwHOOcPn0ad3f3XOOvX79eVVbOnDmDqakptra2tGrViqVLlwLGh22VKlUeag3o1q0bGzduZN++fbke4GD02RkwYAAXLlwgJiaG2NhY6tSpw86dO/Hx8eH27dvcuHEDMFpHXF1dURSFtm3bqtezaNEiunTpAkDnzp1ZvHgxIsKePXuwsbHB3t4eHx8fzpw5Q3R0NOnp6axYsYLOnTvnksff35/Zs2cDRt+TO3fukJiYSMWKFbGysuLkyZPs2bOnwGt+kA4dOjB79mwyMjIA431PTk7O1S6/eW7evInBYKBHjx5MmjQpx84qDY1nFhEYNQpeeombDpXoP7s9DZOncj4hGkVRGNFshKa8ZMNggBkzjJuyDh+GBQuMAYmfJOLC4jjU8hDRH0Zz2P8wiZHFu2G5MBaY84qifAT8eP+8HxBddCIVD342No+suGTh6+tLz549ady4MWZmZnh7ezNkyBDAuJQzd+5cQkNDsbW1ZfDgweh0OpycnPDx+e92wYyMDM6ePUvTprnSPfDjjz8yevRorKysMDMzY+nSpZiamjJhwgSCg4Px8PDAysqKRYsWPVRWc3Nz2rZti62tLaamuYNELV++nHHjxuUo69GjB8uWLeP5559n+vTp+Pv7Z/kjMXjwYAA+++wz+vTpw4cffoi3tzeDBg0C4KWXXmLDhg3Uq1cPKysrFi5cCICZmRkzZ86kQ4cOZGZmEhISgptb7pXJb775hiFDhjB//nxMTU2ZPXs2gYGBzJkzBw8PDxo2bEjz5s0fet3ZCQ0NJSYmhsaNGyMi2NnZqU7H2clvnsuXLxMcHIzBYFyInDJlyr+aX0PjqURRkEw9y8YEMMruIAmXzvJ+y/epUb5wltVnjQ8+gKlT4aWXjMtHDg4lLVHhSYlJ4ezIs8SvjVfLDOkGErYnFKsV5qHJHBVFqQh8ArQEFGAHMEFEbhe9eLl5EpM5tmzZknXr1mFra5tvm1WrVnHw4MEiz0htMBho3LgxK1eupH79+kU617NOaf9eamg8MiLGLTPNmqFv2pjOyzvz+9nf8a3py7yX56GrpitpCUsVBgMkJkLFinDpkjEdwIABT05AusyUTEwtTUm/kc6BJgeoGFiR60uuY0g3YGJugmeEZ5EoMPklc3yoBea+ovLWY5foGeKLL77g4sWLBSower2ed955p0jlOH78OJ06daJbt26a8qKhofFoXLsGISHIhg0ow4dj1qwZuqo6Xqz3IsN9hmtpAB7g9GkICYGyZWHLFqPFZeDAkpaqcNyNusuFTy6QFpdG48jGmNuZ43veFxMzE+yD7UvMByZfBUZRlK9FZJSiKL9hzH2UAxHJ7bCgkSe+vr4PbdOrV68il8PV1ZXz588X+TwaGhpPORs2QHAwhy0SeH2yE1/1fw0/4LP2n5W0ZKWOzExjwsUPPgALC6Pfy5NC0uEkYj6J4eaqm5jamFLr7VqIXlDKKJiYGV1obfxsil1xyaIgC0yWz8v04hBEQ0NDQ+MJYNMmUrp0ZFJPOz53MVDRPJnbaQklLVWpJDYW+vSB3buNu8rnzoVCbrYsceLXx/NPp38wtTHFaYITNUfWpIxtmZIWKwf5KjAicuD+Wy8RyZGwW1GUkcCfRSmYhoaGhkYpIi0Nypblz/plGPyxHWcMNwjyDGJ6++lUtnqC9v0WIzY2cO8e/PgjvPZa6fd1STqSRPq1dCq1r4Stvy3OU52xf92+1CkuWRRmG3Veq3RBj1kODQ0NDY3SiIhx3aNBA7h+nb1xB8i0Kc8f/f9gYZeFmvLyAKdOQXDwf5MvHjgA/fqVbuUl6UgSR3seZb/nfs69cw4RwdTClNrv1S61ygsU7APTF3gVqKMoytpsVeWB+Lx7aWhoaGg8NVy7BkFB/HphI2bPN6WzojDabzQjmo3AqoxVSUtXqsjMhK++go8+AisreOst8PYGk8KYCUqI5BPJxHwcw43wG5hWMMXxY0ccRjnkGRW9NFLQrd0NfAGcvP+adbwDBBbQ75nkq6++ws3NDXd3d/r27Zsjwu6oUaPYsWNHgf3HjBnD1q1b86zbs2cPvr6+eHl54eLiwoQJEx6n6IVm9OjReHl54eXlRYMGDdRdVTExMVhaWuLl5YWrqysDBgxQg8RlJyYmBnd3d5KTk6lcubKa9iCLrl278vPPPxfHpWhoaDyM9eu53NyVbpU20+MVmPOiHdjZYWZipikvD3DiBLRsCWPHQmAgHDtmVF5KK1nhU1LOpHBr0y0cP3KkeXRz6nxShzIVS6/FJRd5JUgqzUdhkjkWN5cuXRInJye5d++eiIj06tVLFi5cKCLGZIC+vr4PHSMmJkbat2+fZ12DBg0kKipKRIwJDY9lJUgrQWbMmCHBwcEiIhIdHa0mb9Tr9dK2bVtZsmRJrj7Z2/Xp00fCwsLUuoSEBKlcubIkJycXg/SFQ6/XP1L/kv5eamj8r2QaMmV2qJdU+MBELCaWlWk7p0lGZkZJi1UqMRhE/PxEKlUSWbbMeF5aufvPXTna66ic/9iYsNZgMEj6rfQSlurh8AjJHO8qinLn/pGqKEqmoih3ikG3KlIiExOZcuECkYmPJ/SxXq8nJSUFvV7PvXv31Lw+4eHhanJBgIkTJ+Lj44O7uztDhgxRNWFHR0fi4+O5evVqrrGvX7+Ovb0x8ZmpqSmurq4A3Lp1i65du+Lh4UHz5s05cuQIABMmTCAkJIQ2bdrg7OzMjPv79j766CO++ea//tgffPCBWpedyZMno9Pp8Pb2ZufOnbz88su52ixfvpy+ffvmKjc1NaVZs2Zcvny5wPvVt29fVqxYoZ6vWrWKwMBArKxy/rLLzMxkzJgx6HQ6PDw8+Pbbb4H872ObNm0YPXo0rVq1wsXFhX379tG9e3fq16/Phx9+qI67ZMkSmjVrhpeXF6+//jqZmZkAlCtXjo8//hhfX18iIyPznWfGjBm4urri4eGhJr7U0HjiOXIEzp9ny/ktDHOIwqdea46OOMbYFmMxMylM4PZnhxMn4NYto2/LokVw/Dj07Vs6fV2SjyVzrPcx9uv2c+v3W5hYGB/9iqI8WRaXB8lLqynoALoCn/7bfo/reJgFZuTp09L64MECD6+9e8Vk2zZh2zYx2bZNvPbuLbD9yNOnH6ohfv3112JtbS1VqlSRV199VS0fMGCArF27Vj2Pj49X3/fr1y9HXWhoqISHh+ca+5NPPhFbW1vp2rWrzJkzR1JSUkRE5I033pAJEyaIiEhERIR4enqKiMj48ePFz89PUlNT5caNG1KpUiVJT0+X6Oho8fb2FhGRzMxMcXZ2lps3b+aYKzIyUry8vCQjI0OWL18u1apVkzlz5uRoExMTI9WrV1ctFNktKykpKdKmTRs5fPhwruvI3i4tLU3s7OzU+Tt06CDr1q3L1ee7776T7t27S0ZGRo77l999bN26tbz77rsiYvxM7O3t5cqVK5Kamio1a9aUmzdvyvHjx6VTp06Snm785TFs2DBZtGiRiIgA8tNPP6lj5zePvb29pKamiojI7du3c8ktollgNJ4gDAZJ+2q67HYuI9K5sxgMBtl4ZqMYSrM5oYTIyBCZMkXE3Fxk2LCSlubhXJx+UbYp22RHuR1y7v/OSfrN0m9xeRD+VwtMHgrPaqDd41SiiptEvR7D/feG++ePwu3bt1mzZg3R0dFcuXKF5ORklixZAkBcXJyapRpg27Zt+Pr6otPp2Lp1K8eOHVPrqlatypUrV3KN//HHH7N//34CAgJYtmyZatHZuXMn/fv3B6Bdu3bEx8erfiUdO3akbNmyVKlShapVq3Lt2jWcnJyoXLkyhw4dYvPmzXh7e1P5gbSnkZGRdOzYETMzMwIDA7l+/TqdOnXK0WbFihX07NkzRy6lc+fO4eXlReXKlalduzYeHh4F3jNzc3M6d+5MeHg4N2/eJCoqioCAgFzttmzZwtChQzEzM/76q1Sp0kPvY1ZSSJ1Oh5ubG/b29pQtWxZnZ2diY2OJiIjgwIED+Pj44OXlRUREhBrgz9TUlB49ejz08/Lw8OC1115jyZIlqmwaGk8k166xp/dzND4zBv/XMrk241MURaFDvQ5PjDNncXHsGDz3HLz/Prz8MowfX9IS5U3y8WRSLxr9MG3b2lJ7XG2axzTH+T/OlKn8BFtcHuCh/3kVReme7dQEaEoekXlLC18XIkR+ZGIi/ocPk24wYG5iwlJX10dK7Lhlyxbq1KmjKirdu3dn9+7d9OvXD0tLS9WhNzU1leHDh7N//35q1arFhAkTcjj7pqamYmlpmeccdevWZdiwYQwePBg7Ozvi4+PV5YzsZP3DKVu2rFpmamqK/r6SFhoaSlhYGFevXiUkJCTPubL6li1blpo1a1KzZs0c9StWrGDWrFm55IuKiiIuLo42bdqwdu3aPLNLZ6dv375MnjwZEaFLly6UKZP7D0tEcv0Tfdh9zJLfxMQkx30wMTFBr9cjIgwcODDPJIwWFhaqYlbQPOvXr2fHjh2sXbuWSZMmcezYMU2R0XjiuLtvFx9Mbc9MXQo1TW35ufdiqjnmTqqqAeHhxlguFSrAzz9DMQRP/9ckn0jmwsQLXP/pOvah9jT8viHlG5enfOPyJS1akVAYC8zL2Y4OwF2gS1EKVdT42dgQ4enJpDp1iPD0fOSs1LVr12bPnj3cu3cPESEiIkJN4ufi4sLZs2cB1IdflSpVSEpKIjw8PMc4p0+fxt3dPdf469evV5WVM2fOYGpqiq2tLa1atWLp0qUAbN++nSpVqlChQoUCZe3WrRsbN25k3759dOjQIVd906ZN2bVrFwBr167lypUr3LhxQ60/deoUt2/fxs/PL8/x7e3tmTp1aqEyNLdt25YzZ84wa9asPP1pAAICApgzZ46qgN26deuh9/Fh+Pv7Ex4ezvXr19UxL1y4kKtdfvMYDAZiY2Np27Yt06ZNIyEhgaSkpH8lg4ZGSZOUnoRu56vM1KUwot6rHH/3Ip0a5vZ3e9bJ+p3o5wevvmq0wpQ25SX5RDLHXz3OPrd93PztJrXH1abOp3VKWqwipzDJHIOLQ5Dixs/G5pEVlyx8fX3p2bMnjRs3xszMDG9vb4YMGQIYl3Lmzp1LaGgotra2DB48GJ1Oh5OTEz4+PuoYGRkZnD17lqZNcyXc5Mcff2T06NFYWVlhZmbG0qVLMTU1ZcKECQQHB+Ph4YGVlRWLFi16qKzm5ua0bdsWW1vbHEtAWTz//PO4ubnx0ksvkZyczOLFi+nevTubNm3CysqK5cuX06dPnwJNy127dmXChAn89ddfPP/88/m2MzExoUePHqxcuZJWrVrl2SY0NJTTp0/j4eFBmTJlGDx4MG+88Ua+97EwuLq6MnnyZAICAjAYDJQpU4ZZs2bh6OiYo11+n1dmZib9+vUjMTEREWH06NEFJurU0ChN3Dv4N1aTP6Pcjz8yotkbtKzdEr9aef8geZbR62HaNNi5E9atg5o1YeHCkpYqby5/e5mba29S+73aOLzjgHkV85IWqVhQ8lqGAFAU5VsKWCoSkRLJUN20aVPZv39/jrITJ06oFo/SSMuWLVm3bl2BD7lVq1Zx8OBBJk2aVKSyGAwGGjduzMqVK7WM1EVMaf9eajxbSGYmi77oz5j45azdVInnFm+Dh/iqPav8848xmu6BA/DKKzB/Plhbl7RU/+XeqXvETIqhxtAa2La0Jf1GOgDmdsWvuETGRrI1eivt6rQrMkVYUZQDIpLr131BFpj9BdRp/Au++OILLl68WKACo9freeedd4pUjuPHj9OpUye6deumKS8aGs8Q507t4fU5HYmwvUULQ0Uq/fwbNNCUlwfJyIDPPoOJE8HW1uj3ks2nv8TJUlyuL7+OiYUJFdtWxLalbYkoLgCbz22m07JOZBgysPjLgq0DtharNa+gZI451iMURSlvLBZtsf9f4uvr+9A2vYphUdXV1VXdbaOhofFs8O3f3/Le+lGYWRr4rlwfXv9oCSYmuZePNSA1FebNMyot334LVaqUtET/5czIM1yeeRkTCxNqvVOLWmNqYV61ZBSXK3ev8PWer/nm72/IMBijrmdkZrA9ZnvpUGCyUBTFHfgRqGQ8VW4AA0TkWME9NTQ0NDRKjJQUSEsjLTONAMd2zPR8H4emT3QEjCIhIwPmzIEhQ6B8eeOyUWlRXFLOpWDhZIFiqmBRx4Jab9ei1tiSU1xOx5/m812fs/jIYvQGPf51/NlxYQd6gx5zU3PaOLUpVnkKs+/ze+BtEdkGoChKG2Ae8FzRiaWhoaGh8b9wL+Men6wcQdNFW+hVrhlvh6/kHb93tJgueXD4MAQFQVQU2NlBnz6lQ3m5d/YeFyZd4NqSa7gscaFa32rUGlWrxOTZd3kfn+36jF9P/EpZs7IM8h7EmOfG4FzRmcjYSLbHbKeNU5tidwYvjAJjnaW8AIjIdkVRSpE7k4aGhoYGQMS5P3h9aV/OSTzjLKzp9frrmCilOB1yCZGeDlOmwOTJULkyrFoFXbuWtFT3FZfJRsXFxNwEh9EOVGxXsURkEREioiOYunMqEdER2JS14f2W7/OW71tUK1dNbedXy6/EdrEVRoE5ryjKRxiXkQD6AdGFGVxRlEDgG8AU+EFEpj5QbwMsAWrfl2W6iJTSjWoaGhoapZNbKbcYs2YEC0+toH48bIt/jjY/rDaaFTRyMXgwLF5sjOsyY4ZRiSlpRISjXY6Sej4Vh5EO1Bpbi7LVyz6842Mm05DJryd+ZequqRyMO4h9OXs+b/85Q5oMoULZguOMFTeFUc1DADvgV2AVUAV4aGwYRVFMgVnAi4Ar0FdRFNcHmo0AjouIJ9AG+EJRlCdyA/tXX32Fm5sb7u7u9O3bN0dk2FGjRrFjxw4AnJycuHnzZq7+M2fOZGE+QQZOnTpFmzZt8PLywsXFRY0xU5QcOnQIRVHYtGlTjvKEhAR69uxJo0aNcHFxITIyEjAGg2vfvj3169enffv23L59W+0zZcoU6tWrR8OGDXOMd+DAAXQ6HfXq1eOtt97KM7KwhobGw9kWvY0fz4Tzf4dtOOzyDW2W7NSUlwdIT4e7d43vx4wxWl2WLi1Z5SXlXAqn3ziNPkmPoig0CmuEb7Qv9b6oV+zKS6o+le8PfE+jWY3oHd6bpPQk5r08j+iR0Yx5bkypU16Af5fMEaMlpUIh2/oBm7Kdvw+8/0Cb94HvAAWoA5wFTAoa92HJHEuCS5cuiZOTk9y7d09ERHr16iULFy4UEWMyQF9fX7Wto6Oj3LhxI9cYycnJ4uXllef4AQEBsnr1avX8yJEjj1H6vBk7dqy0bNlSBg4cmKN8wIABMm/ePBExJmTMSmQ4duxYmTJlioiITJkyRU2oeOzYMfHw8JDU1FQ5f/68ODs7q0kgfXx8ZPfu3WIwGCQwMFA2bNhQ5NdVWAwGg2RmZj7SGCX9vdR4urmYcFF+jVou8sUXYkhPl3O3zomkpZW0WKWSgwdFPDxE+vcvaUmM3Dt7T04En5BtptvkT4s/5VbErRKTJSElQab+NVWqT68uTECaft9Uwo+Fiz5TX2IyPQj/azJHRVGWKYpS4b7fyzHglKIoYwuhG9UEYrOdX7pflp2ZgAtwBfgHGCkihgfaoCjKEEVR9iuKsj97WPtHITEykQtTLpAYmfhYxtPr9aSkpKDX67l37x41atQAIDw8XE2+mMXnn39Os2bNaNasmZpmwMrKCicnJ/bu3Ztr7Li4OBwcHNRznU4HGEPdBwcHo9Pp8Pb2Zts2o6tSWFgY3bt3JzAwkPr16/Puu+8CMH/+fEaPHq2OM2/ePN5+++1c84kI4eHhhIWFsXnzZtWadOfOHXbs2MGgQYMAY1TfrNg2a9asYeDAgQAMHDiQ1atXq+V9+vShbNmy1KlTh3r16rF3717i4uK4c+cOfn5+KIrCgAED1D7ZSUpKUq/Rw8ODX375BYBhw4bRtGlT3NzcGJ8to5qTkxP/93//h5+fH02bNuXgwYN06NCBunXrMmfOnByfgY+PDx4eHmr/mJgYXFxcGD58OI0bNyY2NjbfecaNG4erqyseHh6MGTMml9waGkVFpiGTmXtn4jqzEUNW9CN53Dso27fjXNEZzJ9IA3aRkZ4OH38MPj5w/Tr07Fmy8hjSDJwcdJK/G/7N9eXXcXjTAd/zviXi53I16Srvb3mf2l/XZlzEOHRVdUQMiGBv6F56uPbA9EnYap+XViM5rSRR919fA74EygBHCtGvF0a/l6zz/sC3D7TpCXyF0QJTD6NvTYEWnsJYYA62PpjruDTrkoiI6JP1stdrr2wz2Sbb2CbbTLbJXq+9cmXhFRERSbuRlqtvYfj666/F2tpaqlSpIq+++qpaPmDAAFm7dq167ujoKJMnTxYRkUWLFknHjh3VusmTJ8v06dNzjb1gwQKpUKGCBAYGypdffqlaPaZPny5BQUEiInLixAmpVauWpKSkyMKFC6VOnTqSkJAgKSkpUrt2bbl48aIkJSWJs7OzpKcb06n7+fnlac3566+/pF27diIi0rdvX/nll19EROTQoUPi4+MjAwcOFC8vLxk0aJAkJSWJiIiNjU2OMWxtbUVEZMSIEfLjjz+q5SEhIbJy5UrZt2+f+Pv7q+U7duzIcS+yePfdd2XkyJHq+a1bxl8q8fHxIiKi1+uldevWcvjwYfX+fvfddyIiMmrUKNHpdHLnzh25fv262NnZiYjIpk2bZPDgwaqVpWPHjvLnn39KdHS0KIoikZGR6nx5zRMfHy8NGjQQg8EgIqJ+Hg+iWWA0HjdHrx0Vvx/8hAlIwABFzjewE9m8uaTFKpUcPy6i04mAyIABIvf/lEuEjIQM9f3hwMNyeuRpSb2SWiKynIk/I6//9rqUnVRWTD4xkd4re8uBKwdKRJbCwv9qgQHKKIpSBugKrBGRDAqXjfoSkH3flwNGS0t2goFf78t49r4C06gQYz8S+kQ9ZNl5DPfPH4Hbt2+zZs0aoqOjuXLlCsnJySxZsgQwWk/sHliLzkpc2LdvX9WHBKBq1apcufLgLYLg4GBOnDhBr1692L59O82bNyctLY2dO3fSv39/ABo1aoSjoyOnT58GjAkLbWxssLCwwNXVlQsXLmBtbU27du1Yt24dJ0+eJCMjQ7XmZCcr3xFAnz59WL58OWC0Mh08eJBhw4Zx6NAhrK2tmTp1aq7+2ZF8MmbnV/4gW7ZsYcSIEep5xYrGXyo///wzjRs3xtvbm2PHjnH8+HG1TVYWbJ1Oh6+vL+XLl8fOzg4LCwsSEhLYvHkzmzdvxtvbm8aNG3Py5EnOnDkDgKOjI82bN1fHymueChUqYGFhQWhoKL/++itWVlYF3gMNjcdB3N04mnzfhNMXDvLjr7AxoRN1dh2H9u1LWrRSSYUKkJkJv/0GixZBpUrFL0NKdAqnBp8i0iGStMtpAOg26Kj/dX3K2hevj8vBuIO8Ev4KDWc2ZGHUQoK8gjj1xil+6vkTje0bF6ssj4vC7EKaC8QAh4EdiqI4AncK0W8fUF9RlDrAZaAP8OoDbS4C/sBfiqJUAxoCjxwq1nu7d751plamuC515bD/YQzpBkzMTXBd6oqNnzGxo3kV8wL758WWLVuoU6eOqqh0796d3bt3069fPywtLXM49ELOB3X296mpqVhaWuY5R40aNQgJCSEkJAR3d3eOHj1aoNNr2bL//eMwNTVVszmHhoby6aef0qhRI4KDc/tiZ2Zm8ssvv7B27Vr+85//ICLEx8dz9+5dHBwccHBwUCML9+zZU1VgqlWrRlxcHPb29sTFxVG1alUAHBwciI3970ripUuXqFGjBg4ODly6dClX+YOISC7FJjo6munTp7Nv3z4qVqxIUFBQjnucde0mJiY57oOJiQl6vR4R4f333+f111/PMW5MTAzW2RKe5DePmZkZe/fuJSIighUrVjBz5ky2bt2a5+egofGoRN+Opk7FOthbV+OHzj/QIbEKdjVi4PXXQYvtkoP9++GHH+C774zJF//5B0xKYBd5SkwKF/9zkathV8EUagypgVLG+FkVZzweEWFbzDam7pzKH+f/oELZCox9biwjfUdiX96+2OQoKh760YrIDBGpKSIv3beUXADaFqKfHngD2AScAH4WkWOKogxVFGXo/WaTgOcURfkHiADeE5HcW3QeMzZ+NnhGeFJnUh08IzxV5eV/pXbt2uzZs4d79+4Z985HRKhJ/FxcXFQ/lyx++ukn9dXP77/750+fPo27u3uu8Tdu3EhGhjFc89WrV4mPj6dmzZq0atWKpUuXqn0vXrxIw4YNC5TV19eX2NhYli1bplqCsrNlyxY8PT2JjY0lJiaGCxcu0KNHD1avXk316tWpVasWp06dAiAiIgJXV+PGss6dO6vZsBctWkSXLl3U8hUrVpCWlkZ0dDRnzpyhWbNm2NvbU758efbs2YOIsHjxYrVPdgICApg5c6Z6fvv2be7cuYO1tTU2NjZcu3aN33//vcBrfpAOHTqwYMECkpKMWTEuX77M9evXc7XLb56kpCQSExN56aWX+Prrr4mKivpX82toFIY7aXcYvn449b6tR+Rb3WDUKPp59MPu+UAYOlRTXrKRlgb/93/QvLnR4pL1m6kklJf0m+nsc9nH1cVXqTG0Bs3PNaf+jPrFGj03ayu07w+++C/255/r/zDVfyoXR11k6gtTnwrlBQqXSqAa8ClQQ0RevL8V2g+Y/7C+IrIB2PBA2Zxs768AAf9W6MeBjZ/NIysuWfj6+tKzZ08aN26MmZkZ3t7e6lbnjh07MnfuXEJDQ9X2aWlp+Pr6YjAY1OUZgF27duVwFM1i8+bNjBw5EgsLC8DogFq9enWGDx/O0KFD0el0mJmZERYWlsPikB+9e/cmKipKXY7JzvLly+nWrVuOsh49ejB79mz69+/Pt99+y2uvvUZ6ejrOzs7q1u9x48bRu3dv5s+fT+3atVm5ciUAbm5u9O7dG1dXV8zMzJg1axampkbnsNmzZxMUFERKSgovvvgiL774Yi55PvzwQ0aMGIG7uzumpqaMHz+e7t274+3tjZubG87OzrRo0eKh15ydgIAATpw4oSqP5cqVY8mSJapcWXh6euY5z927d+nSpQupqamICF999dW/ml9D42GsObmGERtGEHc3jrdO2aL7ZTWMHAsimuLyAPv2GaPpHj9uzCD95ZfGRIzFSeqFVOI3xFNzWE3Mq5jTYE4DbP1tsXCwKFY50vRpLDmyhGm7p3E6/jR1K9Zlbqe5DPAcgIVZ8cpSLOTlGJP9AH4HegOH75+bAf88rF9RHaVxG/XDaNGiRb6OnlkcPHhQ+vXrVyzydOzYUbZs2VIscz3LlPbvpUbpZOCqgcIERDfRXv52NBOxtxf544+SFqtUkpEhUreuSM2aIiURhSElJkVOvn5StpfZLtvLbi8xx9zE1ET5fNfnUuOLGsIEpPHcxvLz0Z9L1VboR4F8nHgL4wNTRUR+VhTl/fsKj15RlMwi0qeeSr744gsuXryobjnOi5s3bzJp0qQilSMhIYFmzZrh6emJv79/kc6loaFReOS+P5uiKDSxb0ID06qMfXUmZfw7Gp06SkOCnlLEgQPg5gYWFvDrr1C7dvFaXdKvpxP9cTRXF1wFBewH21P7/drF7ph7LekaM/6ewXf7vyMhNQH/Ov4s6roI/zr+z0Tuq8IoMMmKolTm/s4jRVGaA48neMozQpbTa0G0L4adBLa2tuouJQ0NjdLBmfgzDFk3hNebvE6fe8682ewN4zLRvhBo2FBbMspGaipMmACffw4TJ8IHH4CHR/HNL5mCYqqACdxYecOouIyrjUWt4l2eOX/7PNN3T2dh1ELS9Gl0d+nOey3ew6emT7HKUdIURoF5G1gL1FUUZRfGtAIlHA5IQ0ND48kmIzOD6bun88mfn2BhZoHhh3nwzVYID4cePaBRkUeUeKLYs8fo43LyJISGwhtvFN/cqbGpXJx6keQjyXjt8MK8ijl+F/0wtS7eYG+Hrx7ms12f8dOxnzAzMWOAxwDGthhLg8oNilWO0kKBCsz9fEat7x8NMQacOyXGWDAaGhoaGv8DB64cIGRtCEeuHaGHvT/fzr6AfdRWY5KeTp1KWrxSx+zZRoWlZk3YuBE6dCieeVMvpXJxykXifogDgeoh1TGkGjC1NC025UVE2HFhB1N3TWXj2Y2UNy/PO37vMKr5KGqUzx164lmiQAVGRDIVRekiIl9hTCOgoaGhofGInL99npv3brLKdihd35hvTLz4xx/wwgslLVqpImvTVcuWMGQIfPaZMUBdcZCwI4HD7Q+riovj+45YOBbfUpFBDKw9tZapO6fy9+W/qWpdlU/bfcown2HYWtgWmxwPIzIxke0JCbSxtcXP5vHs7C0shVlC2qUoykzgJyA5q1BEDhaZVBoaGhpPGZvPbeZi4kVCG4fS07UnL9V/CeuNEdDpGsybV7JpkUsZKSnGHEY3bkBYGOh0RitMUZN2OY2U6BRsW9pSwbcCNd+sicObDsWquKRnprP0yFKm7Z7GyZsnca7ozHcvfUeQVxCWZfIOdFpSRCYm4n/4MOkGA+YmJkR4eharElOYMD/PAW7AROCL+8f0ohTqSeSrr77Czc0Nd3d3+vbtmyMy7KhRo9ixYwdgTDZ482buWH0zZ85UY6o8yKlTp2jTpg1eXl64uLioMWaKm88//xwvLy+8vLzUuCy3bt0CjNF+s8pffvllEhIS8hyjXLlyANSpU0cNiJfFqFGjmDZtWpFeg4ZGcXPz3k0GrBpAhyUd+G7fd2Su/hVl9mysza2hc2fjNhpNeVHZvRu8vGD6dOMuo8xi2POadjmNM2+eYY/zHk4GnUQMgklZE+pNr1dsyktSehJfRX6F8zfOhKwNoaxpWZb3WM6pN04xzGdYqVNebmVk8ElMDGkGA5lAusHA9nz+7xcZee2tLs1HaYwDc+nSJXFycpJ79+6JiEivXr1k4cKFImJMBujr66u2dXR0lBs3buQaIzk5Wby8vPIcPyAgQFavXq2e55WAsbhZu3attG3bVj23trZW3w8YMEBNWPkgWe3GjRsnEyZMUMszMzOlZs2aEhMTU0QS/3v0+keLoVDS30uNksVgMMiSw0ukyrQqYjbRTD7aNE5SXh9kzC7YvLnII36/njaSk0XefltEUUQcHYsn9E3q5VQ5/eZp2V52u2w32y4nB5+Ue9H3in7ibFxPui4fbf1IKk6tKExA2oS1kY1nNqrJYksbp5KTZfipU2L155/Ctm1itn27mG7bJpZ//im7ExKKZE4eIZnjU0liZCIXplwgMfLx7AjX6/WkpKSg1+u5d++emtcnPDycwMDAHG0///xzmjVrRrNmzdQ0A1ZWVjg5ObF3795cY8fFxeHg4KCeZyVgTE1NJTg4GJ1Oh7e3N9u2bQMgLCyM7t27ExgYSP369Xn33XcBmD9/PqNHj1bHmTdvHm+//Xau+RYsWIBOp8Pd3Z0dO3bw3HPP5WqzfPnyPFMRAPj5+XH58uX8bxbGRJYrVqxQz3fs2IGTkxOOjo652k6bNg2dToenpyfjxo1TZffx8cHT05MePXpw7949AIKCghg2bBht27bF2dmZP//8k5CQEFxcXAgKClLH3Lx5M35+fjRu3JhevXqpaQWcnJyYOHEiLVu2ZOXKlfnOs3LlStzd3fH09KRVq1YFXqvGs8nxG8fpv6o/dSvW5WCrpUx8axUW3y+Ad9+FP/8E0+LdwVLaSUiAhQuNWRL++ad43IHuHrjLldlXqN6/Os1ON6Ph9w2xdCoeS0dMQgxvbngTx68dmbxjMm2c2rBn0B62DdxGh3odSmUclzdOn6bR3r38EBfHK1WrcqRpU3aYmTHpwgUiTE2L3QemxC0q//Z4mAXm9MjTcrD1wQKPvV57ZZvJNtnGNtlmsk32eu0tsP3pkacfqiF+/fXXYm1tLVWqVJFXX31VLR8wYICsXbtWPXd0dFStE4sWLZKOHTuqdZMnT5bp06fnGnvBggVSoUIFCQwMlC+//FKN6jt9+nQJCgoSEZETJ05IrVq1JCUlRRYuXCh16tSRhIQESUlJkdq1a8vFixclKSlJnJ2dJT09XURE/Pz8cllzLl68KLVq1ZI7d+5IZGSkVKtWTcaNG5ejTXJyslSsWFHis+Wnz7Ks6PV66dmzp/z+++953qfslhpXV1eJiooSEZHXX39dZs6cmav9hg0bxM/PT5KTk0VE1Dlv3ryptvnggw9kxowZIiIycOBAeeWVV8RgMMjq1aulfPnycuTIEcnMzJTGjRvLoUOH5MaNG/L8889LUlKSiIhMnTpVPvnkExExfj6fffaZOnZ+87i7u8ulS5dERPKNsqxZYJ499Jl6iTgfoZ5vj94u+iuXRSwtRWrUEImIKKD3s0dyssi334pkZhrPr18v2vlSr6TK6ZGnJXpStIgYrWQpF1KKdtIHOHL1iLz2y2ti+omplJlYRkJWh8iJGyeKVYbCkpaZKUuuXpWU+9bCH65ckY/Pn5eraWnGBtu2iZibG62KlpYiu3cXiRxoFpj/ok/Ug+H+ieH++SNw+/Zt1qxZQ3R0NFeuXCE5OZklS5YARutJVpbqLLIsF3379iUyMlItr1q1KleuXMk1fnBwMCdOnKBXr15s376d5s2bk5aWxs6dO+nfvz8AjRo1wtHRUQ1U5+/vj42NDRYWFri6unLhwgWsra1p164d69at4+TJk2RkZKjWnCz2799Pq1atKF++vDrPyy+/nKPNb7/9RosWLaiULT99SkoKXl5eVK5cmVu3bhUqMF+WFUav17NmzRp69eqVq82WLVsIDg7GysoKQJ3z6NGjPP/88+h0OpYuXcqxY//dJPfyyy+jKAo6nY5q1aqh0+kwMTHBzc2NmJgY9uzZw/Hjx2nRogVeXl4sWrSICxcuqP1feeUV9X1+87Ro0YKgoCDmzZtHZnEs0muUeo5cO4LffD9j8rxr/0BSEq2dWmNqX8PoiXrkCLRrV9Jilhp27gRPT3jzTfjrL2PZA/8qHxtpcWmcGXWGv53/5vLMy2TcMEYCURQFi9pF7+MiIvx14S86LuuIxxwPVp9czUjfkZwfeZ75XebTqErpivkTn5HBpxcu4LRnD/1OnGD1fb/NQfb2fFKnDtVu3oSPPjJu+U9PN3ZKT4ft24tVzsLsQkJRlOcAp+ztRWRxEcn0SNT/uv5D2yRGJnLY/zCGdAMm5ia4LnV9pMSOW7ZsoU6dOqqi0r17d3bv3k2/fv2wtLTM4dALOdOpZ3+fmpqKpWXe5ssaNWoQEhJCSEgI7u7uHD16VA0/nhfZkzqampqi1xuVtNDQUD799FMaNWpEcHDwQ/uWL18eb2/vHPUrVqzItXxkaWlJVFQUiYmJdOrUiVmzZvHWW2/lKx8YFZiAgABat26Nh4cHVatWzdVGRPI0pQYFBbF69Wo8PT0JCwtje7Y/nCz5TUxMclyLiYkJer0eU1NT2rdvnyORZnasra0fOs+cOXP4+++/Wb9+PV5eXkRFRVFZc8R8JknJSGHSjkl8vvtzKlpUZFn3ZbjvPgtD2sGyZdC+PfTuXdJilhru3TNmjp4xA5ycYOtWaN266OaLC4vjzLAzGDIMVB9QHccPHLGsWzzLRAYxsP70eqbumsru2N1UsarCpLaTGO4znEqWlR4+QDGTkpnJO+fOEXb1KikGAwEVK7KwUSMCKlY07mnfs8f4wYWHG72rW7aEvXtBrwdzc2jTpljlfagFRlGUHzHuOmoJ+Nw/mhaxXEWKjZ8NnhGe1JlUB88Iz0fOSl27dm327NnDvXv3EBEiIiJwcXEBwMXFRfVzyeKnn35SX7MyIgOcPn0ad3f3XONv3LiRjAzjL4arV68SHx9PzZo1adWqFUuXLlX7Xrx4kYYNGxYoq6+vL7GxsSxbtixPH5bGjRuzb98+MjMz+fvvv7l8+TJHjx5V6xMTE/nzzz/p0qVLnuPb2NgwY8YMpk+frsqcH3Xr1qVy5cqMGzcuX3+agIAAFixYoPqeZO16unv3Lvb29mRkZKj3oLA0b96cXbt2qZ/LvXv38k2xkN88586dw9fXl4kTJ1KlShViY2P/lQwaTweZhkyeW/AcU3ZO4TXda5wI3k/fmdtRunc3JuipXbukRSx1dOkC33wDI0YYjVJt2z7+OdKuppF2JQ2Acp7lsHvFjmYnm9FoQaNiUV4yMjNYfHgxutk6Oq/ozJW7V5j54kwujLrAh60+LFXKi4hw9v7/VwsTE6KSkuhbtSr/NG3KJk9POlhboyxdCr6+8Nxz8PvvMHIknD0LO3bAtm0waRJEREC251lxUBgLTFPAVQr6uf8EYuNn88iKSxa+vr707NmTxo0bY2Zmhre3t7rVuWPHjsydO5fQ0FC1fVpaGr6+vhgMhhxWgF27djF+/Phc42/evJmRI0diYWE0dX7++edUr16d4cOHM3ToUHQ6HWZmZoSFheWwOORH7969iYqKomLFirnqHB0dCQoKIjAwkDt37hAeHs7IkSNZtmwZTk5OrFq1ioCAgBxWigfx9vbG09OTFStWqEtc+dG3b1/ef/99unXrlmd9YGAgUVFRNG3aFHNzc1566SU+/fRTJk2ahK+vL46Ojuh0Ou7evfvQ687Czs6OsLAw+vbtS1qa8Z/c5MmTadAgdzju/OYZO3YsZ86cQUTw9/fH09Oz0PNrPPncTbtLOfNymJqYMtJ3JDXL16R9YmVoGQCnTxsddSdNMv4q1SA5GczMoGxZY3yXDz8sGqtL+rV0Lk67yJXZV7DrbYdLmAvlvcvjEuby+CfLg+T0ZH44+ANfRH5B7J1YdFV1LO2+lN5uvTEzKdSCR7GRZjCw4vp1voqN5WxKCrF+flQsU4a/vL0xVRS4etW4l33OHLh2zZja4rvvoH9/uB8OAzAqLcWsuKjk5RiT/QBWAvYPa1dcR2ncRv0wWrRoka+jZxYHDx6Ufv36FYs8HTt2lC1bthTLXM8ypf17qfHvMRgMEn4sXKpPry7L/1mes3LWLJGaNTVH3QfYvl3E2Vnkgb0Aj5W0q2ly5p0z8qfln7LNZJscH3hckk8nF92ED3Aj+YaM3zZeKn1WSZiAPL/geVl/en2p3Aodn54uk2NipPquXcK2beL299/yw5UrqqOu7N0r8tprImXKGPe0d+oksnmzSAleC/k48RZGJawCHFcUZS+Qlk3x6VwkGtVTyBdffMHFixexLSDf+82bN5k0aVKRypGQkECzZs3w9PTE39+/SOfS0HjauHznMm/8/garT67Gu7q3MYHe5ctw4oRxz++wYfDaa1DcW0lLKUlJ8P77MHMmODvDA9EkHisX/nOBy7MuU61fNRw/dMSqvlXRTZaNi4kX+TLyS+YdnMe9jHt0btiZ91q8x3O1coeeKGn0BgNmJiZcTkvjw+hoAitVYrSDA+0rVkTJyICffzb6t+zZY8zXMGKE8ahXr6RFzxdFHrIypChKnoY+EfmzSCR6CE2bNpX9+/fnKDtx4oTqc6KhUVrQvpdPD0uPLGX4huGkZ6Yzsc1ERvuNxmzNb8a0yGXLQnS08VUDgL//hr59ISYG3noL/vMfKGDV+V+Tfj2d2M9jqdylMrYtbUm7mkbmnUysGhSP4nLs+jGm7Z7Gsn+WAfCa7jXebfEurnauxTJ/YRERtiYk8FVsLLZmZixxNcoXk5KCk6WlcWno+++NeRri4qBBA+O2sIEDoXz5Epb+vyiKckBEcvnePtQCIyJ/KopSDaPzLsBeEbn+uAV8VCSf3SoaGiXBw34YaDxZlDUri08NH+Z2mkvdstVh6HBj/qImTYw7jTTlJQfW1mBlZYzX9/zzj2/c9OvpxE6P5fKsyxhSDZSpWgbblraUrV4Wqj++efJjd+xupu6cym+nf8OqjBVv+LzBaL/R1LYpXc7aaQYDy69d46tLlziSnEzVMmUYmS0YqtPx40Zry4oVxu3PL74ICxZAQACYPDnRVQpjgekNfA5sBxTgeWCsiIQXuXR5kJcFJjo6mvLly1O5cmVNidEocUSE+Ph47t69S506dUpaHI3/gfTMdKbtmoZVGSve9ntbVUiVu3ehWTOjo+5778Enn2iOuvfZuhU2bTJmjAYwGB7vs/DClAtcmHwBQ6qBqn2r4vSRE1YNi97iIiJsOLOBqbumsvPiTipbVuYt37cY4TOCylalM3TC+OhoJl64gLu1NaMdHHi1alUsDAZj3q0ZM4wJp8qVg+BgeOMNo+WlFPM/W2CADwCfLKuLoih2wBagRBSYvHBwcODSpUvcuHGjpEXR0ADAwsIiR/oHjSeHPZf2MPi3wRy9fpQgr6Cc1t0KFaB7d2Nsl6LY//sEcveuUZebPRvq1zf6vdjaPh7lJf1mOmUqlkExVVBMFap0q4Ljh45YN3qM61H5oDfo+enoT3y26zP+uf4PtSrU4pvAb/6fvfMOb7Ls4vD9ppvupi3dFJApAgrIVpC9kSEIOHCgIgIiKH7uzUb2FFAUB4jKlI3sjbI3lHS3adPdzOf74ymbQjctvPd15YKkb5KTNu17cs7v/A4vP/qyXMRZijiZkcG3kZH08vOjjY8Pg4KCaObpSWtvb5TERJlVzpwpNVuVK8O338rkxcPjXodeKPKSwGhuahnpydsW6xLDwcFB/aSroqJSKNKMaXy4+UOm7ZtGsEcwK/quoEu1LhAZCYMGwTffSOvYr7++16GWGjZtgpdfhsuXYcQIOTlergiKIqZEE5ETI4mcFkm1edUo/2x5QkeFlkiFPdOcyYLDC5iwawIRKRE87PcwP3T/gb61+uJg51Dsz59XhBBsSk5mUmQka5OScNZoqOXqShsfH4KdnAg+eRJGjpQtTqNRtofmzJHtojLUJroTeUlg/lYUZR1wxbCkD7Cm+EJSUVFRKXlOJp5kxv4ZvNngTb5q9RUeTh6y5P7KK/IEcO6cTGBUAFl56d1b2v/v2CE9zgqLKdFE5KRIoqZFYc2w4t/XH/fHpJi0uJOXpKwkZuybwdR9U0nMTKRpaFOmd5xOxyod0Sil74Tf+ehR1iQl4e/gwOfh4bweFISfRiNdcqdOlfsZXF1lhjlkCNyHAwV31cAAKIrSE2iK1MBsE0L8UdyB5cbtNDAqKioqBSE+I541Z9fwYt0XAYgwRFDBq4J0Xhs+HObPh/r14aefSr1OoKTYuxcaNJAf4vftg0cegVw2oOSbgw0OknYwDf8+/lT4uAKuNYq/VROZGsmk3ZOYe3AuGeYMOlftzHtN36NZWLNif+78kGAysTA2luEhIThqNPwYG4tZCJ7198fZYJDv1RkzQKeDihVl0vLSS7KfV8bJTQNzz43p8nu5nZGdioqKSn6w2Wxi0eFFwmesj3D6wklEpkTeeMC4cdLEa/RoIa5s3n3ASUkR4tVX5eLhhQuL5jFNiSZx8dOLwpxmFkIIkbwtWaQfTy+aB78LJ+JPiBf/fFE4fO4g7D6zEwOWDxBHYo+UyHPnh+Pp6eKVU6eE09atgi1bxAa9/toX//tPiFdeEcLZWf5gWrUS4q+/hLhiSnefQH6N7BRF2SGEaKYoShpwfZlGkXmPKNvqHxUVlQeS80nneX3162y8sJEmoU2Y12UewR7BcjmdTic3DA4bJhfV3SuL9FLG+vWykxYVBaNGwXUL2wuEOcmMbpKOqKlRWNOtuNZxxa+7H17NvYok3juxJ3IPY3eO5c9Tf+Ji78Lr9V9nROMRhHuFF/tz54dks5l+J0/yd46+5cWAAIaFhFDD2Rn++EO2ibZuleWvF16QFZfb7NK7n8k1gRFCNMv5t/S42aioqKgUgkxzJo2+a4TRYmRmx5m8Vv81qW+IjJQ7Xs6elc667u5q8pLDJ5/A55/LVTg7d0KjRgV/LJvFxqVPL11NXPx6+xH+cTiuDxdvq0gIwbrz6xizYwz/RPyDt7M3Hz/xMUMeH4Kfq1+xPnd+yLZa+S8jg4YeHnjZ22MVgi8rVuS1wEB8MzLkqNf06RARARUqwPjxsk3kU3qWQ5YkdxXxKoqyWAjx3N1uU1FRUSmtnNGfoYpPFco5lOO7rt/xWOBjhHjkjLn//ju8+qo09Jo69cZFdQ8wQoCiwBNPyDHpTz+FnH2y+cZmsqFx1KCx15C6OxWfDj5U+KgCbrWK93ttsVlYenwpY3eO5b+4/wjxCGFyu8m88tgruDmWnp9zvMnEzKgoZkZHk22zEdW4Me729qyvUweOH5d2xosXQ2YmtGghx6C7dAE7u3sd+j0lL1NID19/RVEUe6Be8YSjoqKiUnRkmjP5dOunTNo9iZ96/ESfWn3oWi1njZvRKHe9fPedFOouWSKNTB5wDAZ45x3w95eT461ayUtBMCebifw2kujZ0dQ/VB+nYCdqr62NxrF4p3qyzFks/HchE3ZN4KLhIjV8a7Cw20L6PdIPR7vSYzx4ISuLryMi+DEuDqMQdNZqGRESghvAihUyod60SWaOAwZIm//ate912KWGO2lg3gf+B7goipJ65WbABMwtgdhUVFRUCsymC5sYtGoQF5Iv8Mqjr9C2ctsbD3BwgOho6bz22Wfy+gPO2rWyGBUTI78tBcVsMBM5OZLIbyOxplrx7emLzWwDKNbkxZBtYOb+mXy751sSMhNoFNKIye0m06Val1IzCi2EIN1qxd3eHoPFwpL4eAYGBjI8JIRqJhMsXCjbRBcuQGgojBkjBUja0un6ey/JyyqBb4QQhXgrFy3qGLWKisrdeG/De4zbNY4qPlWY22UuLcJbyC9YrTB5slShhobK6w94GR5k1WXECHnurFkTFi2So9IFwZJqYU/FPViSLPj29CX843DcahdvuyY6LZrJuycz++Bs0k3pdHioA6ObjaZ5WPNSs14my2rlp5z9RPXd3fk+x5clxWLB8+xZmbR8/70c4W/eXArJu3UD+7w0Su5vCrNKYJ+iKJ5CiJScB/ICWggh/izaEFVUVFQKjhACgUCjaGgY0pD3m73PR098hItDjkmJTieFuv/8I/Uu//ufmrzkEBUFv/4qqy4ff5x/rYvZYCZpbRLlny2PvYc94Z+F49XcC7c6xZu4nE48zfhd41l8ZDEWm4W+tfrybpN3qRNQegwH467TtySazdR1c6O9j49cFrV2LZ5Tp8oxLycn6NdPtokeffReh10myEsF5l8hRN2bbjsshLgn32G1AqOionIzuhQdb655kyahTRjdbPStByxbJtcBmEzyk+4LL0iF6gNMcrL8trz6qryekCBddfOD2WAmakoUusk6rKlWGp5riEulInK1uwP7o/YzZucY/jj5B072Trz86Mu80/gdKnqXvpUyI86d49vIyKv6lic1GpRFi+T78Nw5CA6GwYPlDyK/P4AHhMJUYG7XOFRrWioqKvccm7Axa/8sRm8ajU3YbtW5ACxYIO3UGzSQQt2HHir5QEsZq1bBa69BXJycMqpWLX/nTkuaRWpcJkdiMVjkksWPKxRr8iKEYMOFDYzdOZbNFzfj5ezF/5r/j6ENh+Lv6l9sz5sfbEKwLimJyZGRvBcWRitvb0aFhvJ6UBBVIyPlTPrChZCeLncvfPUVPP10mdZf7d4tN5E/9VTJOw/kJRE5oCjKJGAG0tDuLeBgsUaloqKichdOJZ7ipb9eYnfkbtpWbsvsTrNv/ARusUj9QM+esrwwYkSZPlEUBcnJUlqxeLH0PFuxQiYveUXkbOYWJoFugg7vVt5U+LgC7o8Wn12Y1Wbl95O/M2bHGA7HHibIPYgJbSYwqN4g3J1Kh01ZltXKjzn6lpOZmQQ5OpJsNoPNRuCWLQROnSoV0o6O0LevbBPVv9UZv6yxfLmUk1kssu24eXPJJjF5SWDeAj4CfkVOIa0H3izOoFRUVFTuRqoxlXNJ5/ih+w8MqD3gmljTaoVx46S/y44d4OkpjUwecGw2qQ09dQo++gg++EDKLvKCJdVC5NRIUranUPvv2jhoHWh4riGO/sU3kpxtyeb7f79n/K7xnE8+TzVtNb7r+h39H+mPk30eAy8BhBA0PHSIoxkZPOrmxuLq1XnGxQXHxYth2jQ4cwYCAqQb4KBBUL78vQ65UAgBW7bIl/bXX1BDpNCCeLaZ/Nm61bN0JTBCiAzgNk1lFRUVlZJl5+WdbIvYxvvN3+fx4MeJGB5xTaQLNwp1n3lGal4K6r52n2AwgIeHXL44ZgwEBcFjj+XtvlcSl8hJkViSLWi7arGmWbH3sC+25CUlO4VZB2bx7Z5vicuI4/HgxxnfZjzdqncrNaPQR9LTWRgby/hKlbDXaPi4QgX8HB15IiEBZexY2bZMTYWGDWXbsmdPWX0pw2RkyMrd9OnSW89PKxjzqI76hy6gAbrZonHV1gU8SyymvDjxbuHGXUgACCGeKpaIVFRUVG4i1ZjK6I2jmXVgFuFe4Qx5fAjuTu43Ji9Ll8pPuGaz1BmoQl1WrJBalw8+kKtyOnfO+33TDqXxX+v/ZOLSRUv4J+G41yu+lk1MWgzf7vmW2Qdnk2pMpV3ldrzX9D1ahLcoFaPQNiH4OymJSTodmwwGymk0PFe+PI+5udHrv/+k6dzq1bJt+cwzsk3UsOG9DrvQnD8vl1wvWAApKdCgro2lA+MI3a0j61Dm1eMcNYIQvYFSlcAAI6/7vzPQE7AUTzgqKioqN/LXqb94c82bxKTH8Hajt/m85ee32sBbLPD111C1Kvz00wMv1NXrpdblp5+gTh1o2jRv97OkWcg6m4X7Y+64PuyKbzdfgt4MwqN+8e3uPZd0jvE7x7Pov0VYbBZ61+zNe03f49HA0jNKHJmdTZsjRziVmUmwoyNjKlVikIcH3j/+KHspJ09K6+KPP5YZY2DgvQ65UNhssGGDfGlr1ki3gX5dzbziG43diihMC01o6rhS4ZMK6Mbprq6K8GrhVaJx5qWFdLNgd6eiKP8UUzwqKioqV4nPiKff8n5U9q7M8j7LeTz48RsPOHBA2v97espPv35+D7xQd906WXzS6+X+ovffv3v3wpJmIWp6FLoJOuxc7Wh4oSEaJw3VF1YvtjgPRh9k7M6x/H7ydxw0DrxU9yVGNhlJZZ/Kxfac+SHGaORoRgZtfXwIcnKitqsrH1WoQO+MDBymToX582VJol49+OEHWXXJq6iolJKaKr30pk+X0p3y5eGrt7LokBFJ6i8xWDNseLT1pvri6ni38kZRFHza+WDYasCrhReejUuu+gJ5ayFdv+ZSg9yDFFBsEamoqDzQCCFYc3YNHat0xN/Vny0vbOHRgEdxsLsuMbFaYexYOZY6eDBMmSLFHSo4OMhvxd9/Q926dz7WkmYhaoZMXCx6Cz6dfAj/JByNffFoTYQQbL64mTE7x7DxwkY8nDx4r+l7DG04lAC30nFa+TctjcmRkfwcH4+HnR3RTZrgqCj8Ghcne3ErVsiSRK9ecslio0ZlvlV56tQ1I+D0dPmSfv0ijRpHLqOfnkCKRsH/WX9CR4be4qrs2dizxBOXK+TFyO4iUgOjIFtHF4HPhRA7ij+8W1GN7FRU7l/O6s8yaNUgtl7aypp+a+hQpcOtB+l0crHdtm1yhnP2bPDyKvFYSxPLl8PZs9eGrWw2Kdq9G4mrEjnW5Rg+HX0I/zQcjwbF0yqy2qz8ceoPxu4cy4HoAwS4BTCi0Qheq/8aHk7F157KDwdSU3n3wgW2GAy4ajS8FBjIUK2Wh5Ytk/qW48dlhe+11+D116UBXRnGapXtoenTpRGwoyP07SN4o14Szn/pMGwxYOduR9BrQQQPDcY59N6J4QtkZKcoigYYIITYWWyRqaioPPCYrWYm7p7Ip1s/xdnembmd59LuoXa3HrhlC/ToITUvixbB88+X+U+/hSExUYpzf/1V2opcsbrJLXmxpFuInhENGggbFYa2k5Z6h+vhXrd4xLlGi5HFRxYzbuc4ziadlbupOs/luTrP4Wx/76fDMq1WMqxW/BwdsQJns7IYV6kSr1gseM+eLdtEycnS2n/hQunhUsan2pKTpSB35ky5LzI4GL761EYv7zgMc3VkLs7EFuxIpfGVCHo1CHvP0utbe8fIhBA2RVEmACXsr6eiovIg0e2Xbqw9t5aeNXoyrcM0At1zEUFWqSKdsqZNg8qlQytxr/j9d3jjDTkm/cUXsvqSm/zHkm4hemY0uvE6zIlm/Hr7XTWlK47kJdWYypwDc5i8ZzIx6THUC6zH0t5Lebr609hp7v3+qWijkRlRUcyOjqaHnx/zqlWjobs7F41G7IcPlwYniiKT5aFDpQq6jCfKx47JX5sff4TMTOkJNPYjM/WiY4iZHkl0jAnXR1yp/kN1/Pv4F+vW8KIiLy2kz4AjwHJxt4NLALWFpKJyf5BhysDRzhEHOwfWnF2D0WLk6RpP33rgvn3yk/Ds2XnrizwA6HRy0KpWLVmIeuSR3I9N/CuR06+cxpxoxrudN+GfhuPZqHg0C3HpcUzZO4WZ+2eSYkyhdaXWjG46mqcqPlUqRqH/TUtjUmQkv8THYxGC7r6+vOPvT9OVK2Wb6MgR0GrlOP4bb8iN5WUYi0VKdqZNg61bZfGof394s1c27usjiZkXgzXdindrb0JHheLdxrtU/JxupjC7kEYAroBFUZRspBZGCCFKR+NSRUWlzLH+/HpeW/Uagx4bxPvN36djlY63HmS1Sue1Tz6Rde6oqDJ/Qikse/dKa5HQUNlNa9Dg9lUXa4YVa4YVR39HnMKccHvMTSYuxSS2PJ90ngm7JrDw34WYrCZ61ezFe03fo15QvWJ5vvxgEwIFUBSFeTExLE9I4I2gIIba2VF53jyYOxeSkqB2bZko9+sHLsW/kLI4SUyUL2XmTJnsVqggNe/9GqSROl9HfOd4UgD/vv6EvhNarKsgihUhRJm61KtXT6ioqJRNEjISxHPLnxN8iqg2rZrYdmnb7Q+MiBCieXMhQIi+fYVITi7ROEsbcXFC9O4tvx3r1+d+nCXDIi5PuCx2+O8QJ547UexxHY45LPou6ys0n2mE4xeO4tUVr4oziWeK/XnzQrrFImZGRooqe/aIbTnvn7jsbJG8bZsQvXoJYWcnhEYjRI8eQmzdKoTNdm8DLgIOHRJi4EAhnJzke+Wpp4T4Y7lNJKzWi8OtDostbBHb3LaJsyPOiqyIrHsdbp4BDojb5AN5GaPeJIRodbfbVFRUVO7EmrNreOHPF0jJTuGjJz7if83/d3shpxDQpYtUGH7/vVwNUArL2iWBENJg+M03pUfH119Dy5a3HmfNtBI9O5rLYy9jjjfj3caboNeLZ6xcCME/Ef8wZscY1p1fh7ujOyMbj2R4o+G5a5dKkKjr9C3JFgsN3N3lSolFi/CfOhUOHwZvb3jnHTmCX6HCvQ65UJjNcgpt2jTYuRNcXeGll2DwIBu+R+LRfaLj2NEMHAMdqTSmEoGvBeLgdX94JeWawCiK4gyUA3wVRfFGto4APADVcEFFRSVf+JbzpZq2GrM7z6aWf61bD0hLk0Zgjo4wb57UIjzgQt1Bg2QroH59OQRT6zbfNoBLn11CN06Hd+scjUvTom8V2YSNv079xZidY9gXtY/yruX5ptU3vF7/dbycvYr8+QqCVQgeP3iQWJOJ7r6+jHB2psmiRShz5si+Sq1asmXUvz+UK3evwy0UcXEwZ46UhsXEyF+VyZPhuactZPwWTWTnSBKjTJR7uBzVFlajfL/yZUKYmx9yFfEqijIMGI5MVqK4lsCkAvOEENNLIsCbUUW8KiplA6vNyrR909Cl6JjYbiLA1cmXW9i7V2oPeveWupcHmCt/khVF7gG8fBlGjpQrdq5gzbQSPScaj4YeeDbxxBhtJOtCFl7NvIo8HpPVxI9HfmTcznGc1p+mkncl3m3yLi/UfeGej0LbhGCVXs+v8fH8UKMGdorC2sREqp05Q6WpU+WoltUKXbvK3QotWpT5at7evbLa8ttvsvrSvr1cu9Ti4Wyip0USMzcGa5oVr6e8CB0Zik97n1IpzM0P+RbxCiGmAFMURXlLCDGtWKNTUVG5rzgSd4RXVrzC/uj9dKrSCYvNgr3G/tY/pFYrfPON9LwPDoZOne5JvKWFuDg5/PLUU9LfpV+/G79+JXG5PPYy5jgzoaNC8WziiVOQE05BRWtjn2ZMY+7BuUzeM5motCgeDXiUX3r+Qs+aPbHX3FtvkAyrlUWxsXwbGcm5rCzCnJy4lJpK5RUr6DB1qlwx4ekpk5Y334SKFe9pvIXFaJQJy7RpsH8/uLvL98mbb0JQVjq6CTr2/xKPEAL/3tIxtzgXb5YW8vIujFUUxV0IkaYoyofAY8CXQohDd7ujoijtgSmAHTBfCHHLRytFUVoA3wIOQKIQ4sm8h6+iolKayLZk88U/XzBu1zi8nb35uefP9Hm4z+0/AV6+LB11t2+HZ5+VIxMPqKOuEPDLLzJpyciQhYKbifkuhosfXsQUa8KrpRfhv4Xj9YRXkceSkJHA1L1Tmb5/OoZsAy3DW7Kg2wLaVGpTKj7Jn8zIoOnhwyRbLDR0d+erwEB6/Pwz9t27Q3w81KgBs2bJ95ab210frzQTFSVbRHPnypdWvbp0zn3uOYFlbzK6t3QcWJ+MxlVD0JtBhAwPwSW8bE9Q5YvbKXuvvwBHcv5tBmwHugF783A/O+A8UAlwBP4Dat50jBdwAgjLue5/t8dVp5BUVEovl5IvCdevXMULf7wgEjMS73zwkSNC+PkJ8cMP98UESEGJiRGie3c5NdKwoRAnrhsesmRahM0ivzcRYyLE4ZaHRfLW5GKJ40LSBfHm6jeFy5cuQvlUET1+7SH2Ru4tlufKLwdSU8Xv8fFCCCEsNpsYfPq02LVrlxD9+wvh4CCEogjRubMQGzaU+feSzSbE9u1CPPOMEPb28qV16SKnzyxGq4hZHCP21dkntrBF7AzYKS59fUmYkkz3OuxihVymkPKSwBzO+fcboN/1t93lfo2Bddddfx94/6ZjBiOrOeoYtYpKGWTX5V3io80fiWFrhwlbzokjMiUy9zukpgoxf/616xkZxRxh6WfzZiGcnYUYN04Ii0XeZsm0CN0UndgZuFPE/hQrhBBXE5mi5r/Y/0S/3/sJu8/shMPnDuLlv14WpxJOFctz5QeLzSb+TEgQTxw6JNiyRVTavVtYs7OF+OknmemBEB4eQgwfLsTZs/c63EKTmSnEd98JUbeufGleXkK8844Q588LYU4xi8sTLotdIbvEFraIvTX2iujvooU123qvwy4Rcktg8tJCilIUZQ7QGhirKIoTciv13QgGdNddjwQa3nRMVcBBUZStgDswRQjxw80PpCjKIGAQQFhYWB6eWkVFpbjZdXkXLX9oiclqAqBuQF1erPsiwR65LLnbs0dOf1y6JNcB1KxZ5idBCkpMDGzaJLscLVtCRAT4+4M120rkzBguf3MZU4wJzyc9ca4khbKKXdG1b4QQbL+8nbE7x7Lm7BrcHN14u9HbDG80PPefXwmyVq/nrbNnOZ+dTQUnJyb6+/PyH3+gefppiI2FqlVlL+X556UgpAwTESE7XvPmST+9WrXkdFH//mBvMBI5NZLds6OxplrxfNKTqrOr4tPBB0Vz79t595q8JDDPAO2BCUIIg6IogcCoPNzvdt/dm0ee7IF6QCvABditKMoeIcSZG+4kxFxgLsgppDw8t4qKSjFyyXCJgSsGXk1e7BQ7YtJibn+w1SoNTD77DEJC5BbpmjVLMNrSgxDw009yvY7JBO3ayQXH/v7y60c7HcWw2YDnE57UWFID7xbeRfr8NmFj5emVjN05lt2Ru/Er58eXLb9kcIPBeLsU7XPlF112NnaKQpCTE252dvg7OvIN8PSsWdj/8ov8hnXoIIW5bdqU6bUSQkgn5enT5dolgKefltNETzwBGcfSufymjvgl8QirwK+XH6EjQ4ttW3hZ5a4JjBAiU1GUv4DyiqJcKX+cysNjRwLX+36HANG3OSZRCJEBZCiKsg2oA5xBRUWlVGITNtoubosuRYeDxgGbsOFo50iL8Ba3v8PTT8PKlXKkZuZMOR3yABIdDa+/Lr8VTZrIjcA+7laiZsVS/rny2LvZE/Z+GBU+rIB3y6JNJkxWEz8f/ZmxO8dyMvEk4V7hzOg4g4F1B+LicG9FnwdSU5kUGclv8fEMCgpiZsWKNFu3jl1TpsDu3VKI+9prUuFcteo9jbWwZGTA4sUycTl+XFodvfeefF+EhgoMWwwc7agj6e8kNOU0BL0eRMjbIbhUfICEufkgL068bwGfAHGALedmAdS+y133A1UURamI9JHpC9w0FMhfwHRFUeyRQt+GwOQ8R6+iolJi7IvaR92AujjaObKw20LCPMOITI1k66WttAhvQePQm5bWCyE9N55/Hp55RvZLHlAyM6FePbk5etIkGDLISvyiWPZ+E4EpyoRdOTsCXgjAp7VPkT5vuimd+YfmM2n3JHSpOmqXr82SHkvo/XDvez4KvSoxkXE6HdtTUnC3s2OYVstbK1bA5Mko0dFyW+WUKfDii+BRtisP58/DjBkyaU1Jgccek8aEffuCo52NhGUJHJygI/1QOg7+DlT8siJBrwfhoL0/HHOLi7y8g4cB1YQQ+vw8sBDCoijKEGAdciJpgRDiuKIor+d8fbYQ4qSiKH8jt13bkKPWx/L3ElRUVIqT5KxkRm8czdxDc5ncbjLDGw2naVhTAEI9Q29NXFJT5aflxx+X//bqdQ+iLh0kJ0vX+nLlYOJEqFdP4LYpmv3VZOLi2cyTGj/UwKulV5E+b2JmItP2TmP6/ukkZSXxZIUnmdN5Du0fan9PR6EzrVbK2dkB8Jdej85oZLKzMy8tWIDHDz9Iw5O2baUgpH37Mt0mstlgwwbp3bJmDdjZyV+Ft96SEjBruoWY2TFETo7EeNmISzUXqs6rSvkB5bFztrvX4ZcNbqfsFTdOCm0B7O92XEld1CkkFZWSwWaziZ+O/CT8x/sLu8/sxIi/R4g0Y9qd77R7txCVKskleV9/XTKBlkJsNiEWLZKTJMuXi6sTWkIIcfipw+Jg04MiaWPSDbcXBZeSL4m31rwlXL50EXyK6P5Ld7Fbt7tIn6MgRGRliZHnzgnPbdvEboNBCLNZJC9bJsxPPCFHblxdhRg8+MYZ8jJKSooQU6cKUbWqfGnlywvx8cdCREXJr2dHZYvzo8+L7V7bxRa2iEPND4mEFQnCZi3b49/FCYWYQroAbFUUZTVgvC7xmVQsGZWKikqpYPjfw5m6byqPBz/OugHrqBtQN/eDLRYp1P38cwgNlULdpk1LLNbSRFSU3GG0Zg082cRGxaMx7Hs3kjpb6uAc4kytP2ph525XpJWQY/HHGLdzHEuOLkFRFAbUHsC7Td6lhl+NInuOgrAvNZVJOh3LEhIA6OnhgceiRTBhAl6RkdIhd9IkGDiwzJsYnj4ttS2LFkF6OjRsCD/+KKsuTk6QcSKDUx/qiPsxTgpze+QIcxuW7fbYvSQvCczlnItjzkVFReU+xWgxYrKacHdyp3/t/lTVVuX1+q9jp8mlpL17N2zdCr6+8MkncvZzxowHVqj788/S4t1mtLH4mVgq747A8IkRj8YeWAwWCAF7j6LTnuy8vJMxO8ew6swqXB1cGdpwKG83eptQz9C737mYybJaaX/kCFYheNvZmbeWLCFs3jzIzoZWraSgu2NH2Vspo1itsHatbBOtXy/3kPbpI9tEDRrIDofhHwOnx+tIWpOExkVD4KBAQt8OxaWyKswtLHmZQvoMQFEUd3lVpBd7VCoqKiXO1ktbeX3V61Iv0WUOjwc/zuPBj+d+h5075YnIYpF/uRculILLBxirFR572Mpnuv1Yf8vGqZEH1eZXw7uNd5FVXGzCxpqzaxizYww7dTvRumj5vMXnvPn4m/i4FK0IOD+kWSwsiI1lrV7Pmtq1cRGCVUlJPDJ9Ou4bNoCLC7zwgjy7P/zwPYuzKEhOlm/3GTPgwgUICoIvvpCVN39/sFlsxP+aiG6CjrQDaTj4ORD+WThBg4Nw9FXrAEVFXqaQagGLAZ+c64nA80KI48Ucm4qKSgmQmJnIyPUj+f6/76noVZGnazx99zsdPCj3Fxlzusomk3Rne8AQQp7IrEYbPcKT6d9fS79+dujGBeL+qDvebYsucTFbzfxy7BfG7RrHsfhjVPCswNT2U3np0ZdwdXQtkucoCBHZ2UyLjGReTAypVivNypUj8dtv8Z8yhSYREVChAowfDy+9BD73LsEqCo4dk9WWH3+Uk2XNm8vl6d27g4MDWNItRE6NJXJyJNmXsnGp4kLV2VUp/3x57FzKbqWptJKXWuZcYIQQYgtcXb44D2hSfGGpqKiUBBsvbKTvsr6kGFN4v9n7fPjEh5RzuIM7rl4PH3wgt8t5ecnKi9Uq/73dBsL7GJ0OXnvZhmZDLK+6RHA0y0iDYw1wfdiVCqMrFNnzZJoz+e7Qd0zYPYHLKZep5V+LxU8vps/DfXCwu7djtrtSUnji8GEAejs68vaaNTw+ZQpkZcn3w7ffQpcuZbpNZLHAihUycdm6FZydZad0yBCoW1ceY4w1cmFaFNGzorEkW/Bo4kHlyZXx7eqrOuYWI3lJYFyvJC8AQoitiqLcu3RfRUWl0AghUBSFKj5VqB9Un4ltJ/Kw/13K+kaj/IsdEwPDh0vNy4kT8q96ixZyNvQBQAj4bo6NtcNjed50mQCyca/tTvinVSlXs+hWI+gz9czYP4Np+6aRmJlIs7BmzOw4k45VOt6zUWiLzcafiYlk22wMCAjgcVdXPs7O5sU5cwj78095dh8wQLaJat/NKqx0k5gI8+dLm//Ll2UhaexYePllaUAHkHEyA91EHXGL4xBmge/TvoS+E4pnkwdTA1bSKHJC6Q4HKMofwCFkGwlgAFBfCNG9eEO7PfXr1xcHDhy4F0+tolLmyTJn8fX2r/k37l9W9F2RtxPhsWNSs6AosGSJPDHVqlX8wZZSDh2ClvXM/Ga3B/da5aj2TTg+7X2KLKnQpeiYtHsS8w7NI8OcQZeqXXiv6XtXvXfuBakWC9/FxDAlMpIIo5Gmrq7s2L5djt1cvCgnz958E1555drZvYxy+LCstvz8s9QbP/WUzMeuFJKEEKRsT0E3QYd+pR6Ns4aAFwMIGRFCuSoP5m6v4kZRlINCiPo3356XCsxLwGfA8pzr24CBRRibiopKCbDh/AbeWP0G55PPM6D2ALIt2Xe2kY+Lg9Gj5Vzon39Ct25yHcADiNVkY+/ncXic0vPo0odZ+Y8D9QLqUa6KS5ElLicSTjBu5zh+OvoTAP0e6ceoJqOo5X9vk8WFMTEMO3eONKuV5g4OfLtjB13GjpWzws2bS31Lt25gf2+dfQuD2QzLl8vEZedOaTz44ouyTXRFbyysgvilCVKYuy8Ne609FT6pQPCbwTj6qcLce0FeppCSgaElEIuKikoxoM/U89bat/j52M9U8anCxuc20qpSq9zvYLHI8YqPP5ZahtGj5bTRA4jNbOPEt3Gc/SQC76xskh92x5xo5oknHIGi+bS9W7ebsTvH8tfpvyjnUI7B9QczovEIKngVnY4mv+xJSSHYyYlQZ2cqOjnRJTubtxcvpv7ixdLUpF8/WZZ49NF7FmNREBcn5VyzZ8tdVZUr32pLY82wErsoFt0kHdkXsnGu7EyVmVUIeCEAu3JlV9tzP5CXKaQNQG8hhCHnujfwixCiXTHHpqKiUgTYa+zZE7mHT578hNHNRuNs73znO3TqJE0t2raFqVOhWrWSCbSUkXEyg51PHMUxMZtEjRvpg2vRf5oWTRGIMoUQ/H3ub8bsHMO2iG34uPjwyZOfMOTxIfiW8y2C6POPxWbjj8REJkVGsic1lZH+/oxfv54W06fT4vx5CA6Gr76CV1+VK7TLMPv2yWrLb79d2wo+d65cdn1le4EpzkTUjCiiZkRhSbLg0ciDyuMr49vNF8VOFeaWBvJS8/O9kryArMgoiuJffCGpqKgUliNxR5i4eyLzuszD09mTk2+exMneKfc7REfLk5KDAwweLN3YunWTupcHCJvFRvb5bFyqlqPfCBceT3QlsvZDvPunlooVC/+9sNgs/Hb8N8buHMuRuCOEeoTybbtvefmxl3FzdCuCV1AwZkRFMf7yZSKMRirb2THt33958auvpJK1SRPpsvz00/L9UUYxGmHpUpm47NsH7u5yyfWbb96Yo2eezkQ3SUfs97EIk0DbVUvYqDA8mnjc0z1SKreSlwTGpihKmBDiMoCiKBWQ26hVVFRKGRmmDD7d+imT90zGx8WH04mneaT8I7knLyaTHHX9/HN5GTFCJi4PGDaLjbgf44j4MgJhFDQ815Cn2mtw7v4I/xtU+Dwu05zJwsMLmbB7ApcMl6jpV5NF3Rbx7CPP4mh3b/QT0UYjQU7yfbE/NZUKmZlM+fNPOs+ciZ29vVyV/NZbUP8W7WSZIipKtojmzoX4eJmsTJsmPfXc3eUxQghSduYIc1foURwVAl4IIHREKOWqqcLc0kpeEpgPgB2KovyTc/0JYFDxhaSiolIQVp5eyZC1Q7iccplXHn2FsW3G3tmZdf16eYI6cwa6dpVuXA8YNouN+J/iufTFJbLPZxPj7ob7kHAUR4Vhwwr/+MlZyczYP4Ope6eSkJlA45DGTGk/hc5VO6NRSn7TshCC3Tn7if5ITGRf9erUW7qUuTNn4njqFAQGwqefSkvZ8uVLPL6iQggpxp02TYpzrVbo3Fm+3Vu3vpaQCqsg8a9EdON1pO5Jxd7HngofViB4SDCO/qowt7STFxHv34qiPAY0AhTgbSFEYrFHpqKikmesNisfb/0Yd0d3tg/cTrOwZne+w//+B998Aw89BKtXy500DyCGTQZOvXiKrFA3xjvV4oDQMuthpdAVl6jUKCbvmcycg3NIN6XTqUon3mv6Hs3Cmt2TNoTFZmN5YiKTdDr2pqXhpSi8e+YMwc8/Dzodjo0ayRH5nj2lKWEZJStLjj9Pmwb//iuFuMOGya5opUrXjrNmWon9PpbISZFkncvCuZIzVaZXIeDFAOxcVWFuWSEvIl4FaA9UEkJ8rihKmKIojwsh9hV/eCoqKrlhtVmZe3AufWv1xdvFmxV9V1DerXzuLYmsLDlh5O4uhbru7rJl5HQHbcx9hs1iI/7neCwGCyFvhWCo4s3iOrVZ8J83bdsqHJsHYWEFf/xTiacYv3M8i48sxiZs9K3Vl3ebvkvt8vfG1O2KYWGmzcarp0/jb7EwfdMmXpg0CTeL5drmwcfvsPOqDHD5stwNOX++NIuuVQvmzJGOua7X2a6aEqQwN3pGNOZEM+4N3Kn5W038evipwtwySF5aSDMBG/AU8DmQBvwONCjGuFRUVO7AweiDvLbqNQ7GHMRkNTGs0bDcNxALAStXSvfcjh2l+VjTpvLygHAlcYn4IoKss1l4NvMkeEgwu3crLLvow/z5clVPQYsj+6L2MWbHGP489SdO9k68Vu813mnyDuFe4UX6OvLKhawspkZGsi8tjZ1VquCxeDG7ly6l+j//oPH3h3fflQrWwMB7El9RIIQ0gZ42Df76S97WvbvMx5588safZebZTCInRRK7KBZbtg1tFy2hI0PxbO6pCnPLMHlJYBoKIR5TFOUwXJ1CKrs1RhWVMkyqMZWPNn/E9P3T8Xf159dev9K7Zu/c73D2rKyhr10LNWrISZIHDMM/Bk4POk3WmSxca7uinfkw5/x9eVRR6NcP2rSRG4TzixCC9efXM3bnWLZc2oK3szcfNP+Atxq+hb9ryQ9qCiHYmZLC5MhI/kxMRAP0jYwkvWNH3OPiqFm/PvzwA/TuXaarbhkZcpni9OnSJFqrlfnYG2/cWj1L2Z2CbryOxD8TURwUAp6XjrmuNdRtOPcDeUlgzIqi2JEzeaQoih+yIqOiolLCDP97OIv+XcTgBoP56qmv8HS+w86VJUukI5eTk3TnGjKkTI/B5gdhFVjSLDh4OWDnaYfGRUPNpQ/za5Qvo0cqeHpCh05ydU9+kxeLzcKyE8sYu3Ms/8b+S7B7MBPbTuTVx17F3cm9eF5QHlit19Pl2DG8heC9/ft5c8IEgpOToVcvmcQ2bFimx+IvXJD+igsWgMEgPfQWLJDDUi7XGUoLmyBxRY4wd1cq9t72hP0vjOAhwTgFlN3ETeU2CCHueAH6AyuASOAr4DTS2O6u9y2OS7169YSKyoPExeSL4lLyJSGEEBGGCLE3cm/uB9tsQqSlyf+fPy/EwIFCxMSUQJSlA5vFJmJ/ihV7qu0RJwacuHr7mTM28cQTQoAQ7dsLodPl/7GzzFli1v5ZotKUSoJPEdWmVRMLDi0QRouxCF9B3kk2mcT4iAgxLypKiPR0YZw9W8x75RWR7uwshJ+fEB9+KERk5D2JraiwWoVYt06Izp2FUBQh7O2F6NtXiB075Fv9eiyZFhE1O0rsqbJHbGGL2B2+W+im6IQ5zXxvglcpMoAD4jb5wB2XOSqKokFOHyUBrZBTSJuEECeLN63KHXWZo8qDgtlqZvKeyXz2z2e0qdSGP/v+eec7nDgBQ4fKssKqVSUSY2lBWAXxv8UT8XkEmacyca3lSvhn4fj18CM2Vg5b2dtLy5sXXshfIcKQbWDW/llM2TuFuIw4Hg9+nNFNR9Oterd7Mgp9Pkff8l1MDBk2G/2jovhxyJBrZYlhw6Q41/kujsulmNRU+P57WXE5fVpWyV5/Xcp2goJuPNaUaCJ6ZjRR06MwJ5hxq+dG2KgwfHv6orEv+Z+PStFToGWOQgiboigThRCNgVPFFp2KisoN7Nbt5rVVr3E0/ijdqnVjaoepuR+cmipN6KZMATc3afcuRJluF+SXiK8iuPTJJVxruVJzqZwqMaTI1x8QIDtonTpJN/y8Ep0Wzbd7vmX2gdmkmdJo/1B73mv6Hk9WePKeCT+/iojgo4sXsQf6njzJ299+y6Pnz0OPHjJxadKkTP/cT5+W2pbvv4e0NNn1+vFH2QW7WbaTdT4L3WQdsQtisWXZ8OnoQ+ioULye9FKFuQ8KtyvLXH9BbqLuCbJac68vagtJ5X7nl6O/CD5FhEwKEX+c/OPOB+/bJ0RAgKyvv/qqEPHxJRLjvcZmsYm4X+KEYbdBCCFEdlS2iPstTtisNmGxCDF5shBubkLs3p3/xz6TeEa8uuJV4fiFo9B8phHPLntWHI45XKTx5xWT1SqWxMaKy1lZQmRkiM0//ij+N3q0iNJqhdBqhXj/fSEuX74nsRUVVqsQK1cK0batbPE5Ogrx3HPyrX07UvakiKM9j4otyhax1WGrODnwpEg/ll6yQauUKOTSQspLApOGFO2agNSc66l3u19xXdQERuV+xGazifh0mXykZKeIDzd9KFKzU3O/gzFHd5GcLESnTrn/tb/PsFll4rK35l6xhS3i5MCTN3z9zBkhmjaVf9k6dcqfBGR/1H7R67deQvlUEc5fOos3Vr0hziedL+JXkDeSTCYxNiJChOzaJdiyRXw1Z44QPj7yhdWuLcR33wmRmXlPYisqkpOFmDhRiEqV5MsKChLiiy+EiIu79Vib1SYS/koQh5ofElvYIrZ5bhPnR58X2VHZJR63yo3sMhjE15cuiV0GQ7E9R24JzB01MKURVQOjcr9xLukcg1cPJjotmkOvHbrzbpzkZPj4Y9ixA/bvl8KOB4TElYlcGH2BzBOZlKtRjvBPwvHrdc2AbMYMGDlSSj+mToUBA+7eTRFCsOniJsbsGMOmi5vwdPLkzQZvMrThUMq7lbyVvhCCkefPMyc6mgybjaciIxkxaxYd9u5F062bbBM1b16m20THjsk20eLFkJkJzZpJ75bb7Yq0ZluJWxyHbqKOrNNZOIU5EfJ2CIEvB2Lv/uC890sjFpuNeTExDD13DosQOGs0bK5Th8aed5iMLCAF0sCoqKgUH0aLkfG7xvPlti9xtHPk61ZfY6fkYmNus8HChTB6NCQlSW90o/G+T2CETX7AUjQKmacyQUCNn2vg39v/FufU9HS552bOnFuFnjdjtVlZfnI5Y3eO5WDMQQLdAhnfZjyD6g3Cw8mjuF7ObRFCcCQjgzpubihGI0knT9Lr5EnenjuXOklJ8OqrciS+QoUSjasosVikl+K0abBli0wy+/WTiUvdurceb04yEz0rmshpkZjjzLg96kaNJTXw6+2nCnPvIWkWC+uSklih17NGr0dvsVz9mtlmY6vBUCwJTG6oFRgVlXvA5ZTLtPuxHacST9G7Zm++bf8tQe65nHWjo6XF6P798uPq9OlQp06JxlvSCJsgYXkCEZ9FEPpeKAEDArCZbCh2ytXExWqVU0WVK8tvj80mCxN3Kk5kW7L54b8fGL9rPOeSzlFVW5VRTUbxXO3nct/YXUyYbTZ+S0hgsk7HwfR0juzezSOTJiESE1Fq1ZITZf37Q7myuw1Zr5f2/jNnSrv/sDCZe7/yijSgu5msi1lETo4k5rsYbJk2fNrnCHNbqsLce8Xl7GxW6vWsSExkq8GASQh87O3pqNVS3cWFry5fxmSz4ajRsEmtwKio3L/YhA2NoiHIPYgavjWY1HYSHap0yOVgG2g0cobUy0vW3Pv3L9Ptg7txfeKScSyDctXL4eAt+woax2ufvE+dkh59e/bIk2H37vJblRupxlRmH5jN5D2TiU2PpX5QfZb1Xkb36t2x05Ts8r40i4WZ0dFMi4wkymSienIysxctovL69dCuHcqwYdCiRZn+OR8+LPPsJUsgOxtatpRDcl26gN1tvt2p+1PRTdCRsCwBxU7Bv58/oe+E4vaIW8kH/4BjE4KDaWlXk5b/MjIAqOLiwlvBwXT19aWJhwf2Ob9wT3l7s9VgoIWXV4lWXyCPFZgcJ97yXJfwCCEuF2NcuaJWYFTKIkIIFv27iAm7J7Bj4A68XbxzP9hqlX2Q6dNh924o4T8K95LjvY+TsCwBl2ouhH8cjn+fG1tFVqscif7oI7mkb9o0ePbZ3M/1semxTNkzhVkHZpFiTKFNpTaMbjaaluEtS/wTvdFmw0mjwZCRQejevTQ6d44R331HuzNn0Lz8Mrz5JlSsWKIxFSVmMyxfLn8mO3fKwtHzz0sD6IcfvvV4YRPo1+jRTdCR8k8Kdh52BL0eRMjQEJyCVcfckiTLamVTcjIr9HpW6fXEmExogKaennTVauni60u1e1gJLHAFRlGUt4BPgDiurRAQwL1Zr6qiUsY4lXiK11e9zj8R/9AktAkpxpTcE5idO+Vf/H//haeekh4v93ECI2yCxL8S8W7tjb27PQEDA/Dt7ot/31s1LgB//y333nTvDrNmSY+X23Eu6RwTdk1g0b+LMNvM9KrZi3ebvEu9oHrF+4JuQgjBtpQUJul0RKanc2DtWrzmzOGc2Uz5gADZJhowQPr3lFHi4mDuXJg9W3Y7K1WSSebAgbJweDM2o424n+LQTdCReTITp1AnKk+sTOArgdh7qE2BkiLWaGR1UhIrEhPZkJxMls2Gm50d7X186KrV0lGrRVvKV4/k5d0yDKgmhNAXdzAqKvcTVpuVz/75jDE7xuDq6MrcznN5+bGXb+/eajTCoEFy2V5oKCxdCj17luk2wp0QNkHin4lc+uwSGUcyeGjaQ4QMCUHb8VZhhNUq87l69eQy7S1bbt02fIXDMYcZu3MsS08sxV5jz8C6AxnZZCQP+TxU/C/qOkw2G7/FxzMpMpLD6en4ZmXxxu+/Y/7hBxzbtaP8sGHQqlWZ/vnu2yerLb/9BiYTtGsnE5kOHW7fzjMnm4meHU3U1ChMsSZc67hS48ca+D3jh8ZBFeYWN0IIjmVkXG0N7U1LAyDMyYmXAgLo6uvLk15eON2pF1vKyEsCowNSijsQFZX7DY2i4XDsYfrU6sPEthNvv6H4imOuo6Ostvzvf/Lien9uyxXiusTlvwxcqrpQ48ca+Pe9/UbFkyflJ/kjR+DcOTld1KLFrY+55dIWxu4cy/rz6/Fw8mBUk1EMaziMQPfA4n9Rt+HX6GieP3eOGnFxzF28mAF79+IyYIBc9/BQySZTRYnRKHPradNkAuPuLu3933wTqlW7/X2yI7LRTdYRMz8GW4YN77beVP+hOt6tvVVhbjFjstnYZjDIpEWv51J2NgAN3N35PDycrr6+1HZ1LbM/h7wkMBeArYqirAaMV24UQkwqtqhUVMoocelxvLfxPT564iMq+1Tm92d+z93XZcsWGDVKfoStVEkKCMroH5K8oigKUTOisGXaqL64Ov59/W87FmuxwMSJ8MknsruycCEE3pSL2ISNP0/9yZgdY9gfvZ8AtwDGtBrD6/Vfv/OW7mLgTGYm30ZG8ojVyhu//cYz8+fjFxhI29RUNG+9BT//LM/2ZZToaNkimjMH4uNlsjJtmtS4eOQydZ52KA3deB3xS+NRFAX/Z3OEuXXKbrusLJBkNrM2KYmViYmsTUoi1WrFWaOhtbc3/wsLo5NWS9DNexnKKHlJYC7nXBxzLioqKjdhEzbmHZzH6E2jyTRn0rZyWyr7VL598qLTSce1336Tos24OJnA3IfJixAC/Uo9l7+5TM3fauIc6kzNn2pir7XP1c/DaJQtor17ZRdt5kw5iHX16xYjPx75kfG7xnNaf5rK3pWZ03kOz9d5Hmf7kltgKIRgq8HA5MhIVur1OFqtjPr1V5g3D6cOHWg/bBi0aXPn8ahSjBCwa5dMVH7/XbbyOnWS3i2tW9/+ZQkhSPo7Cd0EHYbNBuzc7QgZHkLIsBCcQ8vucsnSztnMzKutoR0pKVgBfwcHevv50dXXl9be3pS73fhXGeeuCYwQ4jMARVHc5VWRXuxRqaiUIY7GHeW1Va+xO3I3LcNbMqvTLKr55lJPHz8ePv1Ujkh/9pmswLi4lGi8JcGVxOXSp5dIP5yOc2VnjJFGnEOdcSx/+89BV7ppTk7Qti2MGAHPPHPt62nGNOYcnMPkPZOJTovmscDH+LXXr/Ss0bPER6EB3jh1ijlxcfhmZPDxsmUM3riR8k8/LTcSVq1a4vEUFVlZ8MsvMnE5fFgKcYcOlW2iSpVufx+byUbckhxh7vFMHIMdqTSuEkGDgrD3VIW5RY1VCHanpFxtDZ3KzATgEVdX3gsLo6uvLw3c3dHchx+KricvU0i1gMWAT871ROB5IcTxYo5NRaVMMP/QfM4mneX77t/zXO3n7txPvnRJqh0nTYLw8JIKsUSxmW0cbnaYtH1pOFd2pvqi6vj3v32r6ArHjsHLL0tjusaN5XLtK8RnxDN171Rm7J+BIdtAq4qtWNRtEa0rtS7R3r3ebGZOdDQv2tsTtHAhfbdupb6TE/0vXsTl9del0Ulu/ZQywOXLsto1f740oKtVS7aM+vfPXZJlNpiJmRND5NRITNEmXB9xpfr3Oa1Bx7JZeSqtpFksrE9OZmViIquTkkg0m7FXFFp4efFGUBBdtFoq3ocfhu7I7RYkXX8BdgEtr7veAth1t/sV10Vd5qhSGlh1epXYrZOrjlOzU0ViRuLtD7xwQYju3YXYuVNeN5tLKMKSxWaziZQ9KVevX/jwgoheGC2sZusd72c2C/HVV3IDsZ+fEGvWXPvahaQLYvCqwcL5S2ehfKqInr/2FPsiS35p5amMDPH66dPCZcsWwZYt4rvOneX2wXbthFi9Wq5TLqPYbEJs3izE008LodHIS48eQmzZIr+WG1kRWeLs22fFNrdtYgtbxL+t/xX6v/XCdqc7qeSby1lZYkZkpGj/33/CcetWwZYtwnv7dtH/+HHxa1ycMNynf09uhlyWOealtucqhNhyXcKzVVGU+3NEQkXlLkSlRjHs72H8fvJ3etboybJnluHudBtxZlYWjB0rL3Z20KMHNGly3+0uMuwyEDMnhtS9qWSdzqLewXq4P+ZOxS/ubsh29KicMDp4ULaKpk8HPz/4L/Y/xu4cy2/Hf0OjaHihzguMajqKqtqSbctYhaDH0aOsSErCyWxmwPr1DF+zhlotW8rxqOrVSzSeoiQjA378UX7Pjx2Ttv7vvgtvvCHt/nMj7d80dBN0xP8SD4B/H39CR4bi/mjZFSiXJoQQHEpPZ0ViIiv0ev5Nl4qNh1xcGJLjgtv0OhfcB508TSEpivIRso0EMAC4WHwhqaiUPqw2KzP3z+SDzR9gtpn56qmvGNlk5O0PXr1amtFdugR9+0rdS0hIicZb3FjSLVx8/yJRM6KkraUCYe+H4fpI3j/brF0r9czLlkGPHoJtEdsYu34sa8+txc3RjRGNRzC80fDcd0QVA0abjX8MBtrabNjNm0dwRgaf6nS88d9/+L/wgjQavJ07WxnhwgW5tXvBAjAY4NFH5f/79s1diiWEIHlDMrrxOpI3JmPnZkfI0BBChofgHKYKcwtLttXKZoOBFYmJrNTric5xwW3i6cnYSpXoqtVSrVy5MjvqXJzkJYF5CfgMWA4owDZgYHEGpaJS2vjxyI8M/Xso7Sq3Y0bHGVT2qZz7wSdPStHAli23mpaUYYRVYIwyXj1pRc+NlskLgAbs3O3uakh25Igcw23dWop0B75kY2fiCposGMueyD34u/rz1VNf8Ub9N+68bqGISTSZmB0dzYyICGKF4PTLL1P1wgVmtm4tFawLFtx+iU8ZQAjYsEGKclevli+jZ085TdSkSe7DbzaTjfhf49FN0JFxJAPHQEcqjalE4GuBOHiVbofW0k68ycTqHAHu+qQkMm02XDUa2vv40MXXl44+Pvg5qkO/d0PdRq2ikgtpxjROJZ6iQXADLDYLa8+upXPVzrd+EkpPh6++grp1oU8fuRQGoJTbcOeVrAtZxC6MJWZhDA7eDtQ/Uh9FUdCv1nO893FsJhsaRw11NtXBs/Ht/VfMZvjmG/jyS9l52XfQxC/HlzB251hOJZ6iknclRjYeyYt1X8TFoeSEiLFGI59evMj3MTFkKwrt9+5lxIoVtK5dGyW3JT5lhLQ0+P572SY6fVqOor/2Grz+ujQEzA1LioXoudFETonEFGWi3MPlCB0ZSvlny6NxUlsXBUEIwYnMzKtVlj2pqQggxMlJ7hrSamnh5YVzGU2Si5t870JSFOVbIcRwRVFWcu1z1lWEEF2LOEYVlVKBEII/Tv3B0LVDsQorF4ddxNnemS7Vutx8oPRyeecdiIqSI9F9+tw3iUvy5mQivorAsNkACvi09yHw5cCrLSNtJy11NtXBsNWAVwuvXJOX//6DF1+U6wB690+n9sB5VJk+icjUSOqUr8PPPX+mV81e2GtKRh8khEBvNuObno7DokUsrVqV57ZuZfiuXdTs0QNWrQLvkqv+FDWnT8s20aJFMol5/HG5yLx3bzminhvZkdlETYkiek401jQrXi29qDavGj7tfdT2RQEw22xsT0m5mrRcyHHBrefmxqfh4XTVaqnj5qZ+bwvBnf5iXNG8TCiJQFRUSgMRhgiGrB3CqjOrqFO+DnM6z7m9Odrx41LnsnWrFBL89pusx5dx0v5NwznUGQetA8ZoI9kXsgn/PJyAFwNua0Tm2dgz18QF5Lepfn3wDk6g96xpbEyZztIdybQIb8H8LvNpW7ltif0BN9psLImLY/K5czjHx7P3uefQZmUR2aYNLoMHXxNcl0FsNlizRraJ1q+Xmyn69JFv0ccfv/N904+kS2Huz/EIIfDvnSPMracKc/NLstnM30lJrNDrWavXk2K14qQotPb25t2wMDprtQTfJy64pYFcExghxMGc/9YVQky5/muKogwD/inOwFRUSprzSeepPVsuWZ/QZgLDGg3LvSpw6pQsLcyaBa++WmZPfCC9POKXxBPzXQzph9KpNK4SYaPC8O/rT/l+5VE0+U8wDAapdXUNiqDx5xM5YJvP0rgsnq7+NO81fY+GIQ2L/HXkRoLJxOyoKGZcvEicRkOtCxd4488/EQMGoLz1Fi6PPFJisRQ1BoOU58yYIQW6QUHwxRfyLVm+fO73E0KQvClHmLs+GY2rhqA3gwgZHoJL+APmJVJIzmdlXa2ybDMYsAJ+Dg709POji1ZLGx8fXMvw34fSzF01MIqiHBJCPHbTbYeFEI8Wa2S5oGpgVIqauPQ4yruVRwjBmB1j6F+7P2GeN82S2mxy7jQ1VX6sFQJSUsr0RIqwCk4NPEXC0gRs2Tbc6roR8HIA5fuVx8GnYG0wk0nKgSb+eJRWH49jdcTPaBQNA2oPYFSTUdTwq1HEryJ3hBAoBgNzV6zgtQoV6LhnD2//8w+tWrRAeeUVOTtcRjl+XFZbFi+GzExo1kyKcp9++s4dTJvZRsJvCegm6Ej/Nx3HAEeChwYT9FpQgX/mDxpWIdibmno1aTmR44L7cLlydPX1pYtWy+MeHtipraEiIzcNTK4JjKIozwL9gGbA9uu+5A5YhRCtiyPQu6EmMCpFhSHbwPsb3+eHIz9w5PUjuU8WHT4sk5Zdu+Cpp2DjxjK7t8gYZcSw3UD5vvLj+fE+x3HQOhD4SiDujxWuZXD4MPR+ZwfnA8dA1dW4OrjyWr3XeLvx24R4lMwYuRCCjcnJTDp1ii67dzP444/Jsli41LkzNfr1g27dyqwXj8UCK1fKxGXLFnB2hn795Fvz0bt8nLSkWoiZH0Pkt5EYdUbK1cgR5vZXhbl5Id1iYUNyMiv0elbr9STkuOA+4el5NWmp9KC54JYg+RbxIh14YwBfYOJ1t6cBR4o2PBWVkkMIwS/HfuHtdW+TkJnA0MeH4u/qf+uBSUnw4YfST12rlSuRn3++zCUvNrMN/So9Md/FkLQ2CRTwbuWNo58jD/9auCmbuWt3s/TAFgx6Bw6k/QVP7sTD3pdRzb9gcIPB+Lj4FNGruDPZVitLYmOZfOoUx+zsKJ+UxNM7dkDfvri89RY16tYtkTiKA71e2vvPnCnt/sPCYMwYyEsRyRhlJHJqpBTmpljxfNKTqrOq4tPBp0CtwQeJyOxsVuWMOm9OTsYoBF729nTw8aGrVkt7Hx+87hPBflnlThqYCCACaFxy4aioFC9Wm5UuP3dh7bm11A+qz5r+a3gs8LHbH3zhgjxzDBkiFy+WwXZR8uZkTjx7AnO8GccgR8JGhxEwMABHv8J7TMxatYvBe1uCnQm8wdE1gC+enM6QpgMp51CuCKLPIykp9Nm6lRWentS+dImFGzfybO3aOM2dK619yyj//iurLUuWQHY2tGwpd0V16XL3IlL6sRxh7pJ4hFXg18uP0JGheDQou7uaihshBIfT069udT6U44Jb2dmZwcHBdNFqaebpiYPqgltqyMsyx0bANKAG4AjYARlCCPU3QaXMYBM2NIoGO40ddQPq0uGhDgxuMPjWLcZ798rJovfek+Mzly7d2TSjlGFJt5CwNAHnMGe8W3lTrno5PJt6EvhyIN7tvO+4UDGvnDoFY384yPfZ/cDTJG+0aXjC+U3ebfFmoR8/LxzPyGDqsWN8/ttvlJ8zh3crVmToo4/yVOfOKD/8UGZH2c1m+OMPmbjs2AHlysELL8gculatO99XCIFhiwHdeB1JfyehKach6PUcYW4ltb1xO7KtVrYYDKzQ61ml1xNpNKIAjT08GFOpEl20WmqoLrillrw0g6cDfYGlQH3geeCh4gxKRaUo2RaxjTdWv8GcznNoFtaMr1t9fetB8fHw/vtypCM4WC6F8fAoE8mLEILUvanEfhdL/C/xWNOtBAwMwLuVN05BTtRafpczXx4wGmUHbe7P0Rz2+R/U/R47xRur1QGwgc2R3o1aFf7F3AEhBBv0eib99x/r7Oxwyc6m8/79dOnVi6ZvvQX16hXr8xcn8fEwdy7Mni0thSpVgokT5a6ou1nS2Cw2EpbmCHMPpePg70D4F+EEvxGMg7ZsJnLFScJNLrgZOS64bX18+CI8nI5aLf6qC26ZIE9qNiHEOUVR7IQQVmChoii7ijkuFZVCk5iZyLsb3mXhvwsJ9wrHYrPcepDFIkehP/pIbrgbNUr+373seGAc73WcxOWJaMpp8O/jT+DLgXg0KXyB1GKBixehShUwiUxGrZpIxhNjsLO38Ebd9/iq/f/4ZfNxfj+4lZ71WjCoQ/F1m7MNBhru3s0RFxcCDAa+3LiR18LC8F269M7zwqWc/ftlteXXX+UEV7t2Monp0OHuk/mWdAux38Wim6zDGGHEpZoLVedWpfxz5bFzVsd2ryCE4GRm5tXW0O4cF9xgR0eeCwigq1ZLS9UFt0ySlzHqbUBrYD4QixT2viiEqFP84d2KOoWkkheWHF3C0LVDSTGm8E7jd/j4yY9vr8uIioKqVaUJ3bRppX7DsLAKkjYkEfdjHNXmVsOunB3xv8ZjSbXg38cfe4/CT9gcPy4t6BcvBkUjGL/mF97f/B66VB29avRibJuxVPKuVASv5s7EmUxsOnmSfgsWwMKFvNuvH7U0Gvo0b45Tz57Sra0MYjTC0qXS4n/vXnBzk07FQ4ZAtWp5uH+MkahpUUTPisZisODZ3JPQkaFoO2tVYW4OZpuNHSkpV5OW8zkuuI+5udFFq6Wrry+Pqi64ZYaCTCFd4TlAAwwB3gZCgR55fNL2wBSkbma+EGJMLsc1APYAfYQQy/Ly2CoqdyImLYZqvtWY3Wk2j5S/yagsOlqeoUePlu2if/+Fhx4q1dNFWRflPqLYRbEYdUYcfB3IOJGBR30P/PvcZoKqAGzYAP/7Hxw4IEWijXrtIf6xtxnw5x4eC3yMH3v8yBMVniiS57oTx9LSmLxvHz8JgUVRaPnrrwR268a4l166u61sKSY6WlZX5s6FuDiZrEybJgfbPPJQMMs4kYFugo64n+IQZoFvD1/CRoXh0VCVIwIYclxwV+r1rElKwmCx4KgotPL2ZmRoKJ21WkKc1e3Z9xN5SWC65zjxZiO3Ul9x4p1ypzspimIHzADaAJHAfkVRVgghTtzmuLHAuvyHr6IiybZk8832b6jpV5M+tfowvNFw3m78NhrlOtGq2QxTpsiJIpMJunaVy/qqVLl3geeBzDOZ7Ku2T44/t/Wm8qTK+Hb1ReNYOEGu2Qzr1kHNmlJzYbPJttHHE3UcCxjN8rNLCNAEsLDbQp6v8/yN38ti4ExiIkP27GGDmxsuZjMvbdvGME9PAg8fhsDAYn3u4kIIaR80bRr8/jtYrdCpkzSda90a7jbQIoTA8I8B3QQdSauT0LhoCHwlkNARobhUVoW5F7KyrlZZtqWkYBECXwcHuvv60lWrpY23N25l1PdH5e7k5Sf7ArcmKy/e5rabeRw4J4S4AKAoyi9AN+DETce9BfwONMhDLCoqt7DxwkbeWP0G55LOMbzhcPrU6nPrdNHGjTB0KJw8CZ07w+TJsupSCkn/L52Y72JQHBQemvgQLlVcqDK9CtouWpzDCv8J8sgRWYD68UcpHv3wQ2k/37RFBl0njWP8rvGIi4IPmn/A6GajcXN0K4JXdXuyrFbizp0jfM4cvJYt49yYMXy9bRuD6tZF+8knd94+WIrJyoJffpGJy+HD4Okp336DB0PlXPwSr8dmsZG4PBHdeB1pB9Jw8HMg/LNwggYH4ehbNltnRYFNCPalprIiJ2k5nuOCW7NcOd4JCaGrry8NVRfcB4Y7baO+4sRbUVGUFdd9yR3Q5+GxgwHdddcjgRsWoCiKEgw8DTzFHRIYRVEGAYMAwsLCcjtM5QEjLj2Od9a/w09Hf+Ihn4fY8NwGWle6jUG00ShFBs7O0sq0c+cSj/VumA1m4n/O2Ud0MB3FUaH8c1KcqigKwW8GF/o5hIDmzWHnTjll3KWLHNFt197G4v9+YvSm0USnRdO3Vl/GtBpDBa8KhX7O3IgzGpm5cyczs7Opfu4c26dNw79XL85VrIjm2WdLdTvvTly+LDXh8+ZJA7qHH5ZtowEDwNX17ve3ZliJWRBD5ORIsi9m41LFhaqzq1L++fLYuTyYItMMq5UNOa2hVXo98WYzdsATXl68HBhIF62Wh8qVoO+QSqmhOJ14b/cX6GbF8LfAe0II653EVEKIucBckCLePDy3ygPATt1Olp5YysdPfMz7zd+/cWu00SjFBoMGyU/xf/8tKy6lqAd+RUCvKAoRn0cQOTkS10dceWjKQ5TvX77QI7Amk9xQvH27HMlVFGjTRm4pfvZZ8PWFnZd30uz74RyIPsDjwY+ztPdSmoQW31btE4mJTNixg59cXTE5ONDlxAne1mik305wMGXRIkwI+OcfWW358095W7dusk3UokXecjFTnInIaZFEz4zGkmzBo4mHbBV28UWxK5vJXGGIMhpZpdezMjGRjTkuuJ52dnTQaq+64HqXUa8flaLjrlNIBX5gRWkMfCqEaJdz/X0AIcQ31x1zkWuJji+QCQwSQvyZ2+OqU0gPNkfjjnIk7gj9a/dHCIEuVXfr4sU1a2DYMDh3DpYtg549702wuWCMNhL7fSyxC2KpOrcq3i29ybqUhTnBjHt990JNRgghNcmLFkkH18REOWV89OiNprSXDJd4b+N7/Hb8N4LdgxnTegz9HulXLDoXmxDYLl3CfsYMZkRHM+r55xl44ADDKlakas+epSqpzA8ZGfDTTzJxOXYMfHzkFug33oAKeSxeZZzKIHJiJLGLYxEmgW93X0JHhuLZxLN4gy9lCCH4Lz39amvoYI4LbkVnZ7rmTA01V11wH1gKPIWkKEoPpMjWH5lsKIDIgxPvfqCKoigVgSikGV6/6w8QQlS87nkWAavulLyoPJjs1u1m/fn1nE06y6/HfyXQLZBeNXvhZO90Y/Jy/jy8/bZsE1WvDuvXy5JDKUBYhdxHND8G/Vo9WMHzCU8Ue5msuIS74BJeeFHmsmXwzDNywrhbN9k5a9v2mvV8mjGNMTvGMHH3RDSKhk+f/JSRTUbi6piH/kY+ybJYWLx9O5OTk3l70SIGrVnDwD59eNbNDZ8PPiizbaILF+Reou++A4MB6taV/3/2WcjLPj8hBCk7UtCN16FfqUfjrCFwYCAhI0IoV+XBaYUYbTa2GgxXtzrrclxwG3l48HXFinT19aWm6oKrcgfyIuIdB3QRQpzMzwMLISyKogxBThfZAQuEEMcVRXk95+uz8x2tygPHbt1uWn7fEqPVCEDnKp1Z1H0RTva3EXe+8AL89x+MHy8Vk6XAJ8SSasHewx5hE5wedBpFoxA2KoyAlwIKfbIyGmHVKllt6dBBCkTbt4cZM6BvX1kRuILVZuX7/77ng80fEJsey3O1n+PrVl8Xy5boWIOBmZs2McvRkUR3dx5LTia4ZUuYOZNyISGUxVO0EHLMfNo0WL1amsz17CnbRE2a5C0XE1ZBwh8JUpi7Lw17rT0VPqlA8OBgHP3v/Xu1JEg0mViTlMSKxETWJSeTbrVSLscF99PwcDpptZQvBb+3KmWDvCQwcflNXq4ghFgDrLnpttsmLkKIFwvyHCr3N3+c+uNq8qJRNDQJbYK2XM4KXiGk6OCJJ+Ra3rlz5bhHcOEFr4XBmmElYVkCMfNjyL6cTaMLjdA4aKi7tS4uVVwKvY/owAGZtPz8s1yYHRgoExiQBsKDB994/D+X/uHtdW9zOPYwjUMa81ffv3g8uBj8VC5fhhkz6F2hAjurV6fr8eO8rdXyxLPPopRRkWVampzYmj4dTp8Gf385tfXaa3l/m1kzrcQujEU3SUf2hWycKztTZWYVAl4IwK7c/S3MFUJwOjOTFXo9K/V6dqWkYAOCHB3p7+9PF19fnvLywkV1wVUpAHlJYA4oivIr8CdgvHKjEGJ5cQWlopJlzsLFwYWnqz/NlL1TsNqsONo50iK8hTzg9GlZZVm/Hj79FD75RBqa3EMyTmUQOTmS+J/jsaZZcaniQvDgYGxmG3Z2drjWKHibJiVF5mYgtx3s3g1PPy2LTq1b33478fmk87y78V2Wn1xOmGcYP/f8mT4P9ynSkvzO7duZd/YsZ+ztWTlsGNrUVCa99hpeDz9MlSFDymyb6MwZmbQsWiSTmMcfl87EvXvnfbLbFG8ianoUUTOjsOgtuDd0p/K4yvh2v7+FuRabjZ2pqVdbQ2ezsgCo6+bGhxUq0NXXl8dUF1yVIiAvCYwHUlzb9rrbBKAmMCrFwuaLm3nuj+f4ofsPtKrUiq0vbGXrpa20CG9BY69aclP05MlyVe/UqVI1eY8wJcptzI6+jmSfzyZucRx+z/gR+HIgns08C/VHOjsbVqyQFYBNm2SBw98f5syR/3p53f5+KdkpfLX9K6bsnYKDxoEvW37JiMYjcHEoGuMzIQRHU1IY//ff/FS+PKJSJRQh+P2ddxj03HM0yKuCtZRhs8HatbJNtG6dHDXv00e2ifJjAJx5JhPdJB1x38dhM9rQdtVKYW7Twr0fSjMpFgvrclpDa5KSSM5xwX3K25vhISF01moJK6NibZXSy10TGCHEwJIIREXFarPy5bYv+eyfz6jmW43ybtIHpXEkNN6BfLd+PgLmz5dreseMkWfyEkbYBMkbk4mZH0PiX4mEvhNKpa8r4dPehyYxTbD3LJzz5+XL8qX9/LMUiYaEwDvvXCtmVK16+/tZbVa+O/wdH27+kMTMRF6s+yJfPvUlQe5Fs1HbZLPhmJZG1KJF1KlTB8Xf/6ovgsZqRR8amvfxm1KEwSA3bc+YIXXgQUHw+edyAj8/eyJTdqagm6Aj8a9EFEeFgBcCCB0RSrlqZbN9djcuXXHB1evZajBgEQKtvT1dtVq6+PrS1tsbd9UFV6UYycsUUlVgFlBeCFFLUZTaQFchxJfFHp3KA0Ncehz9l/dn08VNPFf7OWZ2mikdYHfvhqeekqYmTk5ybvXll6FRo3sSZ8SYCKJnRWO8bMTex56g14Pw7yeTKMVOKXDyEhUlWxXVq0tpzw8/QPfucoqoZcu7bybedGETI9aP4EjcEZqHNWdyu8nUC6pXoFiuJ8Fk4reEBJZcvoxvRAR/DRpESFoaS994g3J169IrLAyTvT2OFgstSqmzcW4cPy7bRD/8AJmZ0LQpfPUV9Oghqy95QVgFiX8lopugI3V3KvY+9lT4oALBQ4JxLH9/iVFtQrA/Le1qa+hoRgYA1cuVY0SOC24j1QVXpQTJy1/becAoYA6AEOKIoihLADWBUSkyfj/5O7t0u1jQdQEv1n1RltqtVulxn7NJFpMJTp2S4o8Swma0YdhqwKedHOnJOJJBuWrlqDyuMtpuWuycCy4+zMqCv/6SOosNG6QQd9UqWcSIj5cdsrtxVn+WkRtGsuL0Cip6VWRZ72X0qNGj0K2K1Xo9M6KiWJ+UhBWodfEiPdatky7G77xDr3oyOdq0cydbz52jxUMP0bhp00I9Z0lgtcop+2nTYPNmmRP36yfbRI8+mo/HybISuyiWyEmRZJ3LwrmiMw9Ne4jAgYHYud4/gtRMq5WNycmsSExklV5PXI4LbjNPTyZWrkwXrZYqZVSgrVL2yUsCU04Ise+mP4iWYopH5QHCarNyWn+amn41eaP+G3R4qAMVvXOsgS5ckOWH7dvlxjtFkWPRLVqUSGzpR+U+orjFcViSLDQ40QDXGq7UWFyjSASYX3wh3XFTUiAsDD74QG4lvsLdzgnJWcl8se0Lpu+bjrO9M2NajWFYo2E3uhHnA5PNxrqkJNp4e+OsKBw6cIDjWVmMWr2afnv28Ei7djBunAz2Oho3bVomEhe9XnYeZ86ULbqwMNmme/ll6UicV0wJJqJnRhM1PQpzohn3Bu7U/K0mfj387hthbkyOC+4KvZ6Nyclk22x42NnR3seHrr6+dPDxwUd1wVUpBeQlgUlUFKUyOWsAFEXphVwxoKJSYGLTY+m/vD8How9y5q0z+Lv6X0te/vlHruy1s5PliSpV5G0tWkDjxsUaV8bJDE69eIq0fWkoDgq+3X0JfDmQclVlRlHQk5ROJ51xhw2TxrNubteM5p588u5bia9gsVmYe3AuH2/5mKSsJF557BW+aPnFVb1QfrAJwfaUFJbExbE0IYFki4Xfo6Pp8fnnjLpwgQ8CAtAMGwYTJlwbgSpj/PuvrLYsWSILeS1bwrffyj1Q+ZFnZJ7LJHJSJLELY7Fl29B21hI6KhTP5mVfmCuE4EhGBisTE1mh17M/LQ2AcGdnBuXsGnrCywtH1QVXpZSRl1/hN5F7iKorihIFXAQGFGtUKvc1my9upt/v/Ug1pjK943T8yuV43AshKy2PPQa9eskyRWio/FqT4tnPc8UVVZgF3k954xTkBAIqT65M+QHlC7X5NzMT/vhD5mCbNsmXV78+tGolDYPzy7pz6xixfgQnEk7QMrwlk9pNom5A3QLFFmU00ujQISKNRlw1GrrHxNBvwQLabNoEdergvGiRnBkug5+0zWb5fZ82DXbskNWsF16AIUOgVq38PVbKHumYm/hHIoqDXLAZ+k5ooUbiSwNGm41/DAYpwk1M5LJROmQ0dHfnq4oV6aLVUsvVtcwnZyr3N3mZQroAtFYUxRXQCCHSij8slfsRIQSf//P51Smjjc9vpJZ/LXlm//FHubZ340bpxrZoUbHGYow1EvdDHDHfxZB1JgvPJz3xfsobe0976u0rvPj10iWoXVsKcytWlDY1zz8v/59fTiac5J3177D23Foqe1fmzz5/0rVa13ydXM5nZfFzXByKovBBhQoEOTrSXqOh1a5ddBk3DteUFFn12rAh7xsISxnx8dLLcPZsKYquVEm26QYOBG/vvD+OsAn0K/VcHn+Z1J2p2HvbE/Z+GMFvBeMUkEcTmFKI3mxmTU5raF1SEmlWKy4aDW28vfk4PJxOPj4E5NXkRkWlFJBrAqMoygAhxI+Kooy46XYAhBCTijk2lfsMRVG4aLjIgNoDrk0ZxcdLH5fly2WVJTlZWssWIxc+vMDlMZflPqJmnoS9H4Z/78KNY1+6JKdZFAU++kgKcd94Q+YEzZrlvUV0PfpMPZ/98xkz98vv1YQ2Exjy+JDbr1G4DXEmE7/Fx/NTXBx7c9oC3bVa2LYNZeJE5q1YIVWszz0HI0ZAjRr5D7IUsH+/rLb8+qvUebdtK5OYDh3uPr11PdYsK3GL49BN1JF1JgvncGcemvIQAS8FYO9WNseBT2dmXm0N7cxxwQ10dKSvvz9dtVpaeXurLrgqZZY7/VZeqZG6l0QgKvcvmy9uprxreR72f5h5XeZhr7GXifAff0hP9pQUKRAdMSJ/Z5w8knkuk9gFsYSMCMHR1xG3Om6EvhNK4EuBhfLoSE+H33+XxaKtW+VtPXrIfxUFxo4t2OOarWZmHZjFp1s/JcWYwmv1XuOzFp/h5+p31/umWiy429mhKAqfX7rEzOho6rq5MS48nL779xM6apTcRaDVykzrzTfzZ3ZSSjCZYOlSmbjs3Ss1RYMGyTZRtWr5eyyz3kzUzCiipkVhTjDjVs+Nmr/UxLenb6HXPpQ0FpuNXampV1tDZ3JccOu4uvJBhQp00Wqp5+6OpgxW2FRUbkYRQuT+RUWxA4YKISaXXEh3pn79+uLAgQP3OgyVPHC9MV336t1Z3uc682arFRo2lPanP/yQf3HC3Z4700rC7wnEfBdDyj8poIGHf38Yv+53TwLuhM0mkxNFkZsMpk2DypWlGPe55wrn4yaEYM3ZNbyz/h1O60/TplIbJrWbJNtsdyDbamVtUhJL4uNZmZjI5rp1aeLpyYWsLLLT0qj5008wZQpEREhB9IgRsp9VBsdfo6OlE/GcORAXJ039hgyRGhcPj/w9VtaFLHSTdMQuiMWWZcOnow+ho0LxetKrTGk/UnNccFfq9azW60myWHBQFFp6edHV15fOWi0VVBdclTKMoigHhRD1b779jnVRIYRVUZSuQKlJYFTKBlemjDZf3MyA2gOY1WmW/MKGDVCvnlyVvGIF+PkVuVDUnGxmb6W9WAwWXB5yoeLXFQl4IUAKdAvI+fMyz/rhBynXadpUeoc884z8f2HPd8fijzFi3Qg2XNhANW01Vj27io5VOt7xRJpoMjH6wgWWJSSQYrXi5+DAq0FB+Dk4QGQklaZOlaKQlBTZx5oyRY7flLFpEiGkn+HUqbLiZbXK1tyQIdCmTf5fTuq+VHTjdSQsT0CxUyg/IEeY+3DZEeZGZGdfbQ1tNRgwC4GPvT2dtFq6arW09fHBQ3XBVbnPycs7fJeiKNOBX4GMKzcKIQ4VW1QqZZqTCSdp+X1LUo2pfNf1OwbWHYiSkQHD3pDihJEjYfx46dleBJiTzMT9GIcx0kjlcZVx8HaQI65NPfF8ouBjrkajNP79/nvYtk0mKa1bX+tyVakiL4UhISOBT7Z+wpyDc/B08mRK+ym8Uf8NHOxuTeqEEBxKTyfRbKZdzglqQ3IyXX196V++PK28vLA/ckS25X75RZaLevWSewjys8ynlJCdLdcpTJ8Ohw7JSe6hQ+W27cqV8/dYwibQr9ajm6AjZVsKdp52hL2bI8wtRGJbUtiE4GBaGityWkNHclxwq7m4MCwkhK5aLY09PLAvY8mpikphuGMLCUBRlC23uVkIIZ4qnpDujNpCKv0YLUZeXvEyo5uNlu2P7dtlj+XiRTk//OWX4FK4xYLCJkjenEzsd7EkLE9AmAQejTyou71uoXQLNpv0bKlQQSYwQUHS6OzFF2HAgGtT3YXFZDUxbe80vtj2BemmdAY3GMwnT36Ctpz2lmPPZmbyc3w8S+LiOJ2VxcPlynEsJyGxCoEdwN9/S7+WzZvB1RVeeUWazhRk7Okec/kyzJoF8+ZJA7qHH5bVrgED5EvLD9ZsK3E/xhE5MZLMU5k4hTkR8nYIgS8HYu9euisUmVYrm5KTWanXs1KvJ9ZkQoN0we2Ss2+oWhlsA6qo5JcCtZAAhBAtiycklfuJuPQ43tv4HpPbTcbbxZsfe/wov7BoEbz0EoSHS6XrE08UyfPpJum4MOoC9t72BL0WRODLgbjVcSvw4509KystP/wgO1rnzskBnUOHpGtrUUkihBD8dfovRm0Yxbmkc3Ss0pEJbSZQw+/2E0Dvnj/PeJ0OBWjh5cXI0FB6+uXoeLKzsfvpJ5g0CU6ckNnW2LFSzZrbqupSihDSq3DaNPjzT3lbt24ycSnIVLc5yUz0rGgip0VijjPjVteNGj/VwK+3HxqH0luliM1xwV2p17MhOZksmw33Ky64Wi0dtFq0ZdCbR0WlOMjLMkdP4BPgypnnH+BzIURKcQamUnbYfHEz/Zf3JyU7hQG1B9C6UmtZytBo5EzrsGHSlM6tYAmGYbuB6NnRZJ3PImx0GH7d/fDv649TsBO+T/sWah/Rhg3w6aewa9e1cF94QYZvZ1e0y5X/i/2Pt9e9zZZLW6jpV5O/+/9Nu4faXf16isXC8oQElsTHM6dqVSq5uNDOx4fyjo708fMj5IoQU6+XJYrp06WStU4dmXn16SPXLZQhMjJkm276dDh6VEqjRo2SI+gF+d5nXcwicnIkMd/FYMu04dPeh9CRoXg9VTqFuUIIjmVkXG0N7csZd6/g5MTLgYF01Wp5UnXBVVG5LXmpoS4AjgHP5Fx/DlgI9CiuoFTKBtdPGVXzrcaG5zZQy7uazAh27oR162RVYHLBNeDRC6I588oZuchCgfT/0vHr7odziDPOz+Z/ssJqla64NWtCSIg8gSYny8LFgAFFJsu5gbj0OD7a8hHzD83Hx8WHGR1nMKjeIOw19hhtNlbp9SyJi2O1Xo9RCCo7O6MzGqnk4kIrb29aXXFhO3dOfi8XLpSbINu3l/qWVq3KnPHchQtyL9F334HBAHXryv8/+2zBuoupB1LRTdCRsDQBRaPg38+f0JGhuD1S8KpccWGy2dhmMFxNWiJyXHAfd3fni/Bwuvr68ojqgquiclfyksBUFkL0vO76Z4qi/FtM8aiUIT7c/CFjdo7hudrPSWO6sxHQoZHsuwwYIFWYhejRR3wVwcWPLuZs4QI0oHEs2CfRU6dki2jxYunS+sUX8OGH0LWrbFUUx7ki25LNlD1T+Gr7V2RZsni70dt8+MSHuDt5Em82E+RkT7rVSt8TJ9Da2/N6UBD9ypengbv7tZOXELI8NHGi7K04OED//nIUuohHz4sbIaTR8rRpcuu2RgM9e8o2UUEmuYRNkLQ2Cd0EHYatBuw87AgdGUrwW8E4h5SuseEks5m1SUmsSEzk76QkUq1WnHNccD+oUIHOWi2Bqguuikq+yEsCk6UoSjMhxA4ARVGaAlnFG5ZKacZqs2KnsWNYo2HU8KvBcw/3Q5k8WWYEnp5y1rVH4Qt0zuHOaLtoSd6QjM1kQ+OowauFV/5itcoFftu3y5ZQ+/bXlvlB8UwUCyH4/eTvvLvhXS4aLtK1WlfGtR5HimMgn0bG8Wv8CaqWK8e2Rx9F6+DAvsce4xFX1xsnSKxWafQ3YYJ0avP2hvffl7PDxexUXNSkpckO1/TpMpH095fbt19/HYKD8/94NqONuCVx6CboyDyRiVOIE5UnVCbw1UDsPUqPMPdsZiYr9HpWJiayIyUFK1DewYFnrnPBLae64KqoFJi8TCHVAX4ArqyjTQZeEEIcKebYbos6hXTvuNIy2qnbydr+a7HT5PzxTUuTi3/q1pUOY/4Fs+U3G8ycH3ket9puhAwNuXp7yu4UDFsNeLXwwrPxnbciWyxS17J3r+xkgdRUBATIwkVAQIFCyzMHow/y9rq32X55O4/4P8LkdpOJcKnJ1xERnM/OxlFR6KzV0r98eXr43cZULz1dtogmT5ZTW5UqycmtgQPzP4JzjzlzRiYtixbJt0iDBte8cwpSbDAnm4meE03U1ChMMSZc67gSOjIU/z7+pUKYaxWC3SkpMmnR6zmVmQnAI66udNVq6errS33VBVdFJd8UZgrpP6COoigeOddTiyE+lVLO9cZ0z9V+DpPFiMuvv8uNxe7usGePTFwK+Mc54Y8Ezr55FlO8ifCPwm/4mmdjz7smLsePX2sRxcbK0efhw+UwzvjxBQopX0SnRfPB5g/4/t/v8fasQq+2vzK7Xje0jk7MjIoi3NmZ/1WoQA9fX7xuN0USHS17K7NnS1FI48ay+tKtW7GsVygubDZYu1a+lHXrZMerTx+ZuBTUiiY7IpvIbyOJnheNLcOGdxtvqn9fHe/W3vdcJ5JmsbA+OZkViYms1uvR57jgPunlxeCgILpotYQX0jJARUXl9uS53qomLg8umy9upt/v/Ug1prKg6wJe1LZC6dxdljqysuTYbgH36RhjjZwdcpbE3xNxrePKIysfwb1e/tZvLVkiqyv29tCxo/Rs6dSpZAZyssxZTNw9kW92T8Po04jQ5kvRabQsM0LflFR6+vkxODiYwbn1So4elfqWJUtk+ahHDynMbdy4+IMvAnbvltPx9erJJHLGDOlaHBgIn39eqLcGaYfS0E3QEf9bPIqi4N83R5hbiHH5okCXnX1119AWgwGTEHjnuOB20Wpp5+ODp+qCq6JS7Ki/ZSp3xGw18+rKV/F28Wbjcxuo9fchGPqI1GjMmgWvvlqox886k0XS6iQqfl2R0JGhd20FmM3yk/2iRVLH8sIL0K6d7Lj061fg7lW+EULw6/FfeW/je1zOSkfT6Ddsih3OLi58Ur48z/r7UzU3AbMQMvmbOBHWr5dC59dekyWj/FrM3kN27YKnnpKLFa90ops2ha++knlYQexKhBAkrUtCN16HYbMBO3c7QoaHEDIsBOfQeyPMtQnBoRwX3JV6Pf+mpwNQxcWFt4KD6errSxPVBVdFpcTJNYFRFKWREGJPSQajUnqIS4/Dy9kLJ3sn1vRbQ7BHMG6ffAVjxsi9OosWFfhkm3Uhi+TNyQS9EoTXE140imiEo3/u5ZLdu6Uzfnw8bNkirU/8/KQ4F+Ri5eHDCxRKvrHYbMw4u4evzuwhIT2GR120/ND9B/ZrKtLS25vH3Nxyb2uYTNIbf+JEWXkJCJBn+9dflwYoZQAh5DLrpUth/nzpVgyyc/jmm7J1VBBsJhvxP8ejm6Aj41gGjsGOVBpXiaBBQdh7lvznrCyrlc0GAysSE1ml1xOd44LbxNOTcZUq0VV1wVVRuefc6S/DTOCxkgpEpfRwxZiu/yP9mdB2AtU8K8mP0wMGXBOXFECXIayCyKmRXPzwIhpHDX49/HDwcbhr8tKqlexUgTTynTsXOnQo8h2Qd+RQWhrTLp/jl7hYsjUuKC7VeEpbmfWNxmCnsePJO905OVmKm6dOhZgY6Y2/YIEsGZWB0VkhYP9+mbQsWwaXLsl2Xf36cPCg1L04OsqXk18sKRai50QTOSUSU7QJ10dcqf59dfz7+hd4ZL6gxJlMrM5pDW1ITibTZsMtxwW3i1ZLRx8ffMuYUaCKyv2M2kJSucrNxnQvVnpaiktA2qU+/LC8FID0Y+mcfvk0afvS8OnkQ9VZVXHwyT0DSU2VGlaQhQu4NgbdtWuBQsg3JzIyqOLigsmSxbCDy9lhDUCTtJ+ePh7MbjoQX5c7C4u5eFHObH/3nXTMa91aThi1bVvqjeeEgH37riUtEREyYWzTBj75RGqLvb2vaWBatMifbCdbJ4W5MfNisKZZ8WrlRfUF1fFuW3LCXCEExzMypJ5Fr2dvaioCCHVyYmBAAF18fWnh5YWT2hpSUSmV3CmBqaQoyorcviiEKKHTiEpJcPOU0UyH7rg9+Yzs23z00bXVAAXAkmLhcJPDaJw01FhSA/++/rmepGw2OUk0erScJvr0U/np3mSS/7ZoUfDXmBd02dlXFyf+l5HBO26J/LJtOFFZafSo3pWJbb4g3Cv8zg+yd6/MvpYvl9+zZ5+Vwtw6dYo3+EIihAz9StJy+bJMWtq2hc8+k4njFVPgKzRunL/EJe1fKcxN+DUBIQT+ffwJfScU98fyJ9wuKGabjW0pKaxMTGSFXs/F7GwA6ru781l4OF20WurcqQ2ooqJSarhTApMATCypQFTuLfpMPf/F/seCtjN5cdFhlLk9pd/+ihVyxKQAZJzKwLW6K/ae9tT4qQYejT1w9M29BL9/vxy33bsXGjWST92ggTyBFuRTfn6IN5noffw421Lkiq+HnRTC4v9k4q5F1Perwq+9fqVpWNPcH8BqlQFPnCjXKHh6SgOat94qmFtbCWGz3Zi06HQyUWzbVroVd+1a+L2QQgiSNySjG68jeWMydm52BL8VLIW5FYpfmJuc44K7Uq9nrV5PSo4LbisvL0aHhdFZqyWoDLTyVFRUbiRXIztFUQ4LIR4t4XjuimpkV3RYbVZWnllJ9+rdAUg3peOWmCorBQMHyjlY5/yfYCzpFi5+cJGoaVHU+qMWvt1883S/rl1lEnNlL1FxVu4zrFZWJCaSabPxcmAgNiFod+QIdZwEp07OYvWRuQS5B/FNq28YUHsAGiWXYDIzpaB58mS5qyg8XGqEXnpJ+uOUQmw22fpZulSaJkdGyqSlXTtp69O1q8y/Cv08Zhvxv+QIc49k4BjoSPDQYIJeC8LBu3gFTOcyM6+2hrYbDFgBfwcHumi1dPH1pbW3N65lyF9HReVBpiBGdheLMR6Ve0xcehz9l/dn08VNbO27jic3nMFt8GAIcoOzZwv8sTtpXRKnXzuN8bKRoMFBeD2V++OYTNKptVs3OdA0Z45cWF1c532zzcaG5GSWxMXxZ2IiGTYb9dzceDkwkExzBg31S5m4eyIKCh8/8THvNn0XV8dc3G9jY6XpycyZkJQkXdp++w2efloqXEsZNpsce76StERFSf1wu3bwzTdyJL0okhYAS6qF6LnRRE2JwhhppFzNclRbUI3y/cqjcSqerNQqBHtSU6+2hk7muODWcnXlvbAwumi1PO7hobrgqqjcR9zpL+2PiqLkutBGCLG8GOJRKQG2XNxCv+X9SMlOYcEjH/FE96Fw6rQU6LZsWeDk5dyIc0ROjqRc9XI8uv1RPJvmfkZct04WKk6dkkWMDz8snhU/VyqMiqIw/Nw5ZkZH421vT//y5elXvjxNPdxZeHgh/9v8P6kDeqQ/37T6hlDP0Ns/4PHjMGkS/PijNKXp2hVGjizYNsJixmaT3awrSUt0tExaOnSAceOgc2fw8Ci658uOzCZqahTRc6KxplrxaulF1TlV8engUyyakvQcF9yVej2r9HoSzWbsFYUnPT15PccFt6Lqgquict9ypwRmGfBvzgXg+r9AAlATmDLIxF0TeXfju1T1qcIGQ1dqPfO1zBzWr79mrJIPhBAgQNEouD/uTtgHYVT4sAJ2zrcvz58/Lxcpr1gBDz0ktxJ36lTYV3Urx9LTWZIjxv2jVi0edXdnUFAQ7Xx8aOfjg5NGw7aIbTT87W0OxRyiUUgj/uzzJw1DGt7uRcLmzVLfsnatbKu9/LLMwKpWLfrgC4HVemPSEhMjw+3QQbaHOncu2gpXyu4U4n+JJ/NsJoYNBoRN4P+MPyHvhOBRvwizoxwic1xwV+r1bEpOxiQEXvb2dPTxoauvL+1VF1wVlQeGO/2m9wT6ALWBv4CfhRDnSiQqlWKjondF+j/Sn5k/JuO2fK60sv322wJVXbIjszk7+CxeLb0IfTuU8n3v7hk/bZrMBcaOhWHDitYGJdViYWZUFEvi4zmakYEd0NbHB2tOFaaOmxt13Ny4mHyRdze+y7ITywj1CGVJjyX0rdX31iqB2Qy//ioTl3//lTa/n38Ob7wh/XBKCVYr7NhxLWmJjZVJS8eOMmnp1KlokxZhE6QdSiN6djSxC2LlxxnAt7cvlcdVxiW86KoeQggOp6ezIqc1dDjHBbeyszNvBgfTVaulqacnDuqos4rKA0detlG7At2QyYwW+EAI8U8JxHZbVBFv/tl8cTMXki/wSp2B8mzn6AjbtkntRvfu+X48YRPEzIvh/LvnEWZBpXGVCBkScvtjhTSfDQ+HJk3knsLMTAgKKtRLukqCyYTOaOQxd3cyrVbK79pFbVdX+pUvzzN+fvhdZzyWakzl6+1fM3nPZOw19rzf7H1GNB5BOYebHFVTUqRb3tSpUuFao4YsGw0YUCBRc3Fgtcof4dKlclo7Lg5cXG5MWtyKcGWQJcVC0vokktYkoV+rxxxnvvEAO6j4RUUqvF+h0M+VbbWyxWCQ1v2JiUSZTChAEw8Puvr60kWrpXq5cuqos4rKA0KBt1ED2UAKkAqEAaXjL7jKXbnemO4Rr6q8MGQeDs1byPLHE08U6DEzz2Vy+pXTpPyTgldLL6rNq4ZL5dt/4j58WE4R79wpCz1NmshCT2HHctMtFv7S6/kpLo71SUnUdHXlSIMGlLOzI6JRI3xusui12qwsOLyAD7d8SHxGPC/UeYGvW31NkPtNWVREBEyZAvPmQXq6bKnNni37L6XgE77FcmPSEh8vk5ZOnWTS0rFj0SUtQggyT2aiX61Hv1pP6s5UhEVg72WPT3sffDr54ODjwPFex7GZbGgcNXi18Crw88XnuOCu1OtZn5REhs2Gq0ZDu5zWUEcfnxuSURUVFZU77UJqCTwLPA5sBKYIIdTSRxnh+imj5xwbMPPjozhonGHIsEI9rinaRMaRDKrNr0bASwG3/RSckCBFufPmyU7L/PlyKrug7E5JYavBQAsvL3akpPDJpUtk2WyEOTkxMjSUftetO745edl8cTNvr3ubI3FHaBbWjNX9VlM/6KZE/sABaTy3bJm83qePNJ577N5v0rBY4J9/riUtCQly9+P1SYtrLoNS+cWaacWwxYB+jUxajBFy0ZFrbVdCR4bi08kHj0YeaOyvJXN1NtXBsNWAVwsvPBvnfYxJCMHJzMyrraE9OS64IU5OPB8QQFetlhZeXjiro84qKiq5cCcfGBtwBNiB7HLfcKAQYmixR3cb1BbS3UkzplF9RnWSM5OYcSKcF38+hdK+vcwkCmCqlnY4jZTtKYQMlW0iS5oFe/fci3dTp8qOy9Ch8PHHhau4bExKosPRowghcNRo+LhCBS4bjfTz96eJp2euY7Fn9WcZtWEUf53+iwqeFRjfZjy9ava6lnDZbLB6tUxctm2TIpFBg2TQYWEFD7gIsFikcd/SpfDHHzJpcXWVAtxevWTSUlR7BLMuZsm20Go9hi0GbNk2NOU0eLf2RttJi08HnyLbAm222diRksKKnH1DF3JccOu5udHF15euWi11VRdcFRWVmyhIC+klbkpaVEo3QggURcHdyZ0Pm39Ic3Mgtb59Reo5Xnkl32O+1iwrEZ9HcHn8ZRzLOxIwMAB7d/vbJi+bNkltS5cuUuPati1Ur17w12K02ZgdHc3/LlzAkpNkm2w2BDDzDpM/hmwDX/zzBdP2TcPJ3olvWn3D8EbDcbbPOQlnZcEPP0jjudOnITRUinRfeaVoZ4rzicUiN21fSVoSE2XS0qWLrLS0b180SYvNbCNlR8rVpCXzpPRLca7sTOCgQLSdtHg+4ZnrFFl+MZjN/J2UxAq9nrVJSRgsFpwUhVbe3owKDaWzVktIKdEVqaiolC1yTWCEEIsURfEDKgDnhBCGEotKJd/Epsfy/B/P816NV2m1M5o3huW0iiLaFKjHYNhm4PQrp8k6m0XASwFUnlD5tonLpUvSBuX336XGpXNnuT+nMMnLT3FxfHjxIpeys6nn5saxjAwsORWYFrmUcyw2C/MOzuPjrR+jz9Tz0qMv8eVTXxLgFiAPiI+XpnMzZsjs4LHHYMkSWdIoybXW12E235i06PVSw3J90lIUNibGWCNJa2XCkrwhGWuqFcVBwetJL5m0dNRSrmoRlXSAC1lZrEhMZKVez7aUFCxC4OfgwNM5VZbW3t64qaPOKioqheROGphXgK+B80BFRVEGCSFyXe6ocu/YfHEz/X7vR2pmMgNn7oJ/rfIsWKlSgZIXU6KJI+2P4BjgSO0NtfFp7XPLMZmZUgs8bpzUt375pZSNFEX1f3lCAt729sypXZs23t7sSU29qoFpfBu72PXn1zNi3QiOJxynRXgLJrebTN2AuvKLp09L47nvvwejUWZY77wDTz55T4znzGZZrVq2TCYtSUkyaenaVSYt7doVPmkRVkHagTQpwF2jJ/2gHD12DHbEv48/Ph198G7tjb1b4ZOI3SkpbDYY8HNw4GJ2NisTEzme44Jbs1w5RoaG0jXHBddObQ2pqKgUIXfSwBwDWgohEhRFqQT8JIQoplV6eUfVwFzj+imjakZ3ln6XSq0KDeTJukaNfD9e6r5UPB6XbZTkTcl4NPLAzvX2rYSVK+VJ99lnZRITcvsp6jyxLzWVDy5eZNpDD1Hd1ZUUiwV3O7u72r6fw438pAAANctJREFUSjzFyPUjWX12NZW9KzOh7QS6VesmHRe3bZOtoZUrpdnM88/D228X6PtSWEwmmbQsXQp//gnJyVJyc33SUtguijnZTNI6OeactDYJc6IZNODR2ANtRy3aTlpca7sWib7EliPAXRQTw+TISKw5t2uAFl5eV/cNVVZdcFVUVIqAgmhgTEKIBAAhxAVFUdR1raWM30/+zqf/fMpzlzyZ+Ws6bv/7AkaPzvcuHlO8ibNDz5LwawKPrH4EbUct3q28bznu6FE4cgT695eFjMOHoW7dgsd/JjOTDy5eZFlCwtVP8NVdXe/qpJqUlcRnWz9j5oGZlHMox/g243nr8bdwwk4az02YAAcPyhGojz+GN9+UJnQliMkEGzfKpOWvv2TS4uFxLWlp27ZwSYsQgoxjGehX60lak0TKrhSwgr1WjjlrO2nxaeuDg7bw7TGzzcah9HS2GwxsT0lhR0oKSRbLDcdogA8qVODzihUL/XwqKioqeeFOZ4oQRVGm5nb9Xk0hqUByVjLeFnt6V++J14B1tDlpQhkWku9sQghB3I9xnBt+Dmu6lfDPw/FufWvikpQk84BZs6QBXa9esqhRmORl+NmzTI+Kwlmj4ZMKFXgnNBT3uyQuZquZ2Qdm88nWT0gxpvDqY6/yecvP8bc6w7SZ0lH48mWoUkX6tzz/fNGISPKIyQQbNlxLWgwGmbR063YtaSmM87A1w0rypmT0a2TSYtTJMWe3R90IGx2GtpMWj8c9UOwKV2XJtFrZk5rK9pQUthkM7ElNJdNmA6CKiwvdfX1p7umJq50dL5w6hclmw1GjoYPPra1GFRUVleLiTmeMUTddP1icgajcnSsto6k7J3HwZ3fCX3uPtm+9BZUL9ninXjxF3A9xeDT2oNr8arjWvFEvY7XKAaYPP5Qn48GD4bPPCn4SzrBacc3x9XDWaHg9KIiPwsMpfxeDsl2XdzH30Fy2XtpKREoErSu1ZlLbSTxi8oJPx8sgU1OlOd+0abI8VELGc0bjjUlLSorc6ty9u0z02rQpXNKSdT7rqpmcYasBYRLYudnh3cab8E/C8engg1NQ4YqjSWYzO1NS2JaSwnaDgYPp6ViEQEGuX3g5MJDmnp409/Qk4KYXE+LkdEd9koqKikpxcacppO9LMhCVOxObHkv/pX3ZfPkfBvwHvlZfqH9LS/CuCGvOdmY7BW0XLe713QkeHHzbT+0nTsjuy5NPSoPa2rULFrvRZmNWVBRfRkTwS82atPbxYUzlu2ddRouRr7d/zZfbv8QmbCgojG8znnecn0J5Z6xsFwkhM4V33oEGDQoWYD7Jzpa7L5ctk0lLaqr0unn6aVlpad1abmsoCDaTDcM2w9Ux56wzWQC4VHMheEgw2o5aPJt7onEseIIWmZ3N9pSUq5djGRkAOCoKDdzdGRkaSnNPT5p4eOB1lwmtxp6eauKioqJyT7irWEJRlPrAB8hx6qvHCyEKeDpTyS+bL26m3y+9Sc1M5rvVMLDZEJTFY/I9YZRxIoPTr5zGr7cfoW+H4t/rVl2ITgdr1sBrr8Ejj8D+/XLiuCDaT6sQLImL46OLF4kwGmnt7Y1/Hs7s0WnRzD4wmzkH5xCfEX/1dg1gnjsL5ftRcnRnyBC5ETI8PP/B5ZPsbFi3TlZaVqyAtDTw9oaePWXS0qpVwZMWY5QR/Vo9SauTSN6YjDXdiuKk4NXC62rSktu6hrshhOBMVtZV/cr2lBQu5hjIudnZ0cTDg77+/jT39KSBuzsuqvOtiopKGSEvas+fkO2ko4CteMNRuR2LjyzG286NjSudqDVxsTxb5gObycblsZeJ+DICOzc7HANuPdNmZ0vt6zffyKJGt24QEAD16hU87g5HjrAhOZnH3NyYV60abe6gkRBCsFO3k2n7prH85HKsNiudqnbiKUsYH5yeiUkDjjZBi4N6Ofb06quFX6p0F7Kz4e+/ZdKycuW1pKV3b3l56qmCJS3CKkjdm3pVgJv+rxxzdgp1ovyA8nLM+SnvXCfA7oRVCP5LT7+qX9mRkkK8WS5e9HNwoLmnJ0ODg2nu5UUdV1fsS8GOJxUVFZWCkJdt1DuEEM1KKJ678qCMUcelx5H6316q/Ksj49UXEQjccMz3GTPtcBqnXjhFxtEM/Pr4UWVqFRz9rz2GELINMmIEXLwoKwoTJhS8qHEwLe3qifGnuDjsgGf8/XMdic4yZ/HzsZ+Ztm8a/8b+i5ezFy/VfYnBlfpQ+ac1MGECu70z2BoOLS4rNH71cynKKSaysm5MWtLTwcfnWnvoqacK5ntn1ssxZ/1qPUl/J2FJsoAdeDb1RNtRi08nH1wfzv+Yc7bVyv60tKv6lV2pqaRZ5WBzuLPzVe1Kc09PqqkbnFVUVMoghdlG/YmiKPOBTYDxyo1CiOVFGJ/KdWw+t4H+P/UgJDqDfasCcH3+eWkcUgCsGVYsBgu1VtTCt4vvLV9PTIQBA2TCsmmTPEEXhNOZmXxw4QK/JyayoFo1BgYG0v+6JYs3E2GIYOb+mcw/PJ+krCRq+ddiTuc59Ld/FNdpc+DHJ6RCtmlTGh84QOMYi0ze8ll9ygtZWbB2rUxaVq2SSYtWC337yqSlZcv8Jy1CCNL/SydpdRL6NXpS96SCDRz8HNB2lr4s3m28cfDO3wOnWCzsuk6/si81FVPOh5CHy5VjQPnyVxMW1aJfRUXlfiYvCcxAoDrgwLUWkgDUBKaIsdqsfPnHcD47Op1qibAwqx3KkZ/ynbwkb0om7UAaYe+F4dXMi4bnGt4g+jQY5Dqgt94CPz+57bhOnXzbxwAQYzTy2aVLzI+JwcXOjk/Dw+nl53fbY4UQbL64men7p7PitDR17l69O281GMKTZ0woH0yGda9Jg5SBA6W+pXp12L1bbjds0QIaF42XYmbmjUlLRoa0jenXT2qCW7TIf9JiSbOQvDFZCnDX6DFFmwBwr+9OhQ8roO0kRdOKJu9VkDiT6Qb9yn/p6dgAe0WhnpsbQ0NCaO7pSVNPT7T3aCWCioqKyr0gLy2ko0KIRwr04IrSHpgC2AHzhRBjbvp6f+C9nKvpwBtCiP/u9Jj3awspKSuJZ37uwSbdPww45cisrnNxe/aFfD2GOdnM+ZHniV0QS7nq5ah3qB52Ltd0FFYrLFwI//ufrLzs21egQaYbaHjwIIfT03k9KIgPK1S4rUg33ZTO4v8WM33/dE4knMC3nC+vPvYqrz/yImGrdkir/+PHpehmyBCpIPa9tVpUWDIypEB52TKZtGRmygSuRw9ZaXnyyfwlcUIIss5mXdWyGP4xIMwCOw87fNr64NPJB5/2PjgF5G3MWQjBxZwJoW05ScvZrJwpJI2Gxh4esrri5UUjD4+rI+kqKioq9zOFaSHtURSlphDiRD6f0A6YAbQBIoH9iqKsuOlxLgJPCiGSFUXpAMwFGubnee4LEhJw9fbAooHvQt5k4Kv/QwkKyt9D/J7A2SFnMSWYCBsdRoWPK9yQvOzaBUOHSoPaZs3kRM2jj+Y/VKPNxpzoaF4ICMDT3p7pVarg4+BwW9v4s/qz/L+9+46Pqkr/OP55Jr2QTCoEQiBU6UgTFFwUVhFBUDd2BRQVFGy767qr69pd1l1+IthBRFEUbFhwlUWwIEhRmkhHpZOZVNJn5vz+OJeQQIAEhRB83q+XLzIzd+49uYPJl3Oec84zS59h6oqp5Jbk0iWlC1OHTOWK+v0If3EqXNXHbrLYsSO8/LIds/kli6ZUoaAAPvrI9rTMmWNDS3KyXeMuI8MuHVOT0OIv9pP7eS7eOXZtluLNdkZPZNtIUu9IJX5gPLFnxeIKOXpxbMAY1hQU2N4VJ7DsLLW9NnHBwfSOjeXGlBTOdrvpEh1NiBbcKqVUuer86O4NDBORrdgaGAFMNaZR98DuYr0FQETeAIYA5QHGGPN1heMXA79gR526x+/3MeGpqxjx6Bzinp/G/GHzj6nIsmRnCT9c8wORbSLpMKcD9U6vPORUVmb3LPL77QbMV1xR82nRfmN4bc8e7nemREcHBXF9SgrdY2IqHRcwAT7Z9AkTl0zk400fE+wKJqNtBmN7jKVnfizy5JPw6mg7xWfgQFs9fO65v+rGivv2VQ4tRUU2tAwbdiC01KTzonhbcfm6LNnzsgkUBnCFu3D3c9P4rsbED4wnounRpzmXBgIsz88vHw5amJtLtrMkf6PQUH7ndpfXr7SNijrqXlBKKfVbVp0AM+AYz90I2Fbh8XaO3LtyA/BxVS+IyE3ATQBpaWnH2JyTy55NK7n6mX7Mi/USOqAFY7p2rVF4McaQPTebuN/HEdYwjM4LOhPdNRpXsP1XekkJvPiinW0cFmbXLmne3C6fUlNzvF7u2bKF1QUFdI2OZnLr1vQ/aEp0bnEuU1dM5emlT7MpaxMNohvwwO8e4KYuN5KyZC3c/LAtOgkPt90fd9zxq26suG+fHRaaNctepqgI6te3pTQZGdCnT/VDS8AXIG/RgWnOBavtQm/hTcNpMKIBCRcm4O7rrtTDVWWbfL7yJfm/zM1lcV4eRc6S/K0jIrg0Kak8sDQND9cZQkopVQNHDTDGmJ+O8dxV/TSusuBGRM7BBpgqp2sbY17ADi/RrVu3Ixft1AGfvfIgV695kNxIw5TIKxkx7dUadQkUbS5i/U3ryfksh45zOxLfP56YMw70hHz0kc0HmzbZX+IZGbZI91hN3LGDQr+fN9q2JSMpqVLPwNrMtUxaMolXVr5CQVkBvVJ78VDfh7i0+SBCZ74Ntw2wu0AmJ8NDD8GoUbbw5FeQn185tBQX2zKa66+333Pv3tW/raWZpWT91+ll+SQbX44PCRZi+8TS7IlmJFyYQORpR56G7C0r4ytnOOiL3Fy+zc/Hj12Ar3N0NDelpNDH7aZ3bOxRt09QSil1ZMcw76TatgONKzxOBXYefJCIdAQmAxcYY7zHsT0nhemrpnPd1gdpbcKYO3gm7c8YXO33BnwBdkzYwda/b0VChFbPtSLu3AObL65fD3feaX+Zn3aarXM577yat3F9YSH3b93KP5s1Iz0igpdPO4244GBCnRoMf8DPBxs+YOKSiXy29TPCgsK4ssOVjOk+hq6hTexGipNawp490L49vPSSHcP6Fab15uVVDi0lJZCSAiNH2tBy1lnVCy0mYNj33T67z9AcL/lL8sFASP0QEi9OtNOc+8cRHHv4/0V+3r8kv1O/srawEIAwEXrExHBPWhp93G56xcQQcyxTvJRSSh3W8fypuhRoKSLpwA7gCuCqigeISBp2Ova1xpgNx7Ette+DD8DjoX/GBdza/RYeP+dRoiNqtofMmqFryPooi4TBCbR8piXhqZUDwciRsGqVndQzZkzNpwHvdKZET3GmRF+ZnEx6RER5b4G30MvkbyfzzLJn+Dn3ZxrHNOaxcx9jZJeRJG3zwkNPwrRptitkwABb39K//y+ub5k3z+7XuHOn3dqgpMTuin3zzTa0nHlm9fZu9OXaac7ej7xkfZxF6e5SEKjXox5NH2xKwsAEok+PrnKaszGGdYWFB/YQysnhpxK7LFJMUBBnxcaWr8HSPSaGMC24VUqp4+qo06h/0clFBgJPYqdRv2SMeVRERgEYY55zFsi7FNg/TOWraqpURXVuGnVuLvPvuZwXMz/h1R1nELTw6xrtlBwoCSDBggQJme9lYkoMSZclISIEAjB9OlxwgR2VWb/erq5/hPXjDusfW7fyxLZt+IxhdMOG3FthSvSK3SuY+M1EXl/zOsW+Yvo27cvYHmO5qNVggj//0iamjz6yxTbXXmvHr9q1q3kjKjAGvvgCxo2zPS1gc1BGhp1N1avX0W+jMYbCdYXltSy5X+ZifIZgdzBx58eRcGEC8QPiCU06dDjHFwiwwlmSf/9/HmdJ/vohIfRxCm7Pjo2lQ3Q0QVq/opRSx8UvmUZ9zIwxc4A5Bz33XIWvRwIjj2cbapP/f5/y6FMZPHh6Hq3qJ7DnuRk0rEF4yV2Yy/qR60m5MYXGdzUmaeiB2pGlS+1CdN98A48+atd2ad26Zu0rCwTKp+ZmlpVxSWIiD6Wn0ywigjJ/GW+ueZOJSyaycNtCIkMiGdZpGLd2v5UOca3hjTfgyu6wcqVNTw88AKNH21qXX+Dnn20nzssvw5YtdvFdERtoXC7o3NkOEx2Ov8hPzvwcvHPs5ojFP9ppzlEdo2j8JztjKKZXTHmx835Ffj9L8vPL119ZlJfHPmdJ/mbh4VwYH8/ZTmhpERGhBbdKKVXLdGD+ONm9ehFXTz+fz7rCNQ0H8OywWUSHVm8KkC/fx9a/bWXH0zsIaxxGVPsDu07v2QN//atdkK5BA/vL/ppratY2vzFMd6ZEz2jbljNjY5nUsiUuEfbs28PDn/+b55Y/x878nTSLa8Z/zvsPIzqPIK4wAM8/D5POh127oG1bmDwZrr76F9W3FBXBu+/a72nePBtWzjnHZqJGjWDQICgttWGmb98q3v9jUfk055zPcggUB3BFuojrH0faPWnED4wnvHHl9uWUlbEwL6+8fmVpfj5lxiBAh6gohtWvX97L0vBXXptGKaXUL6cB5te2fTumUSMuXnIXK5uFMuX8JxnRY1S1/8WevSCbddeto2R7CY3GNiL90XSCow98THffDTNmwJ//bPc0PGgZliMyxvCR18tft25lTUEB3erVI9hp19IdS5i4ZCIzv59JWaCM85ufzwuDXmBAiwEEbdoMf7zXdosUFdnK4KlT7Z/H2BNhjF0JeOpU25mTmwtNmsD999v1WtLTDxw7b17lnQQCZQFyF+aW7zNUuNYWz4Y3DyflphQSLkwg9uxYgsIPVPPuKimpVL+yqqAAA4SI0K1ePe6ssCR/nC7Jr5RSJ73jWgNzPJy0NTAlJfgfuJ/A/40nZP4XLG8SSlhwGO2T29foNLkLc1l/83pav9ia2F62yPfTTyEtzc4s2r7dribbqlXNmzhk9Wre93ppERHBY+npDI6LYebamUxaMomlO5dSL7QewzsP59but9I6oZXdJGn8eFuAHBpqu3ruvNPOLDpGu3fDq6/a4PLDDxARYXfAHjHCBpSqRthyF+Xi/cALLihaX0TWp1n48/xIiOD+nZv4C+NJGJhAZKtIwAa1zUVF5YHli5wcNhc7Q0kuF72ctVfOjo2lR0wMkbokv1JKnbQOVwOjAebX8N137L7xSq5ut54OSe148v6vq901Yoxh7xt7KVxfSPoDttvBBAziEjZvthN53n/frm0yZUrNm7apsJBmERG4RHhuxw4MMCA6wJTlz/PC8hfILMzktMTTGNN9DNd1uo56EgYzZ9rg8t13dk+iW26x/x1LdTB2+OfDD21o+fhjuyJwr142tFx2GcRWMRnLGEPhD4Vsn7idXS/sKt9GNDgxmKShScRfGE9cvziC6wXjd5bk/6LCpoe7nSX5E4KDy4eC+sTG0lmX5FdKqTqlVop4fxPGjeOzyX/jqksgLzqMqwfdVe3wUry9mI2jN+L90Eu9M+rR5G9NcIW6KCgUHn8c/v1v2/ExbpzdmLkmdlSYEj29TRuuSE6mrW8zE5dMZOwP7xIwAQa3HsyY7mPo36w/kp0N//c0TJxo5yu3aWPnLl9zje0mOQYrVthRp9des5tHpqTAn/4Ew4fb3qSDGb+xvS2zvXje81C0qajyAUHQ+M7GNLinMcvy8/kyawdfbrVL8uc6BbdpYWH0c7vLQ8tpkZG6JL9SSp2CNMD8Av6An0d8/+PBqwO0jm/J/654p1pDRiZg2PnCTrbcvQXjMzQf35zU21KRIPuLdvx4eOwxOyP5n/+0a55UV05ZGeO2bePJ7dvxG8OolPrs3vYRnd+dwKo9q4gLj+POnndyS/dbSI9Lh40b7XSmqVPt2FT//rYw9/zzazTdez+v1waWqVNtgAkNhSFDbG/L739/6MaJ/iI/2XOz8cz24P3AS1lmGRIixPWLI/WPqYQ1DGPNFd8TKDUEQuDehnt5+6ufKHaW5G8TGcnlycnluzQ3+RUWy1NKKXXy0wBTU4EATJgA6elsPbs941jI1Z2u4dkLn632LKOSbSVsvnMzsb1jafV8KyKaRfDdd3b9t169bJnJ739vv66p81etYml+Phe5o0ja+wEz3ptEdnE2Het35MXBL3JVh6uIDI6AL7+E8Xfa8amQEDuT6I477M7QNeTz2VV/p061pysrgy5dbGfOlVdCQkLl40s9pXg/9OKd7SXrkywCRQGCYoNIuDCBxCGJxA+IpyxK+Dgri2d37mDnE4bOK2BFZwi0NdwS35A+sbH0jo0lUZfkV0qp3yQNMDWxdSsMH87aH76g7aARtBg6lFWjV9E8rvlRZxkFygJ43vWQlJFEeJNwuiztQlS7KDwe4Y6b7caLffrYutl69aofXvzGMGPPHi5JSiLC5SIjPJuIrW/w/ucv4RIXF7e5mLE9xtInrQ/i89k1+MePh+XLbbK47z5b39KgQY1vx7p1NrS8+qqdVZ2YCLfeantbDs5BRZuL8Mz24HnPQ+7CXAhAWGoYKTekkDAkAffZboqDDB9nZTFr23o+9HopCASIdLkoagdr29nVEB+uX5+/NmlS47YqpZQ6tWiAqQ5j4MUX8f/xTh4508+DtwpvXHo+lwEt4lsc9e353+az/ob17Fuxj84NO+Pu7SasdTQTJ8I//mE3Jbz9dvt19Ztkp0Tfs2UL3xcW8vGWeXz73SOs86wjKTKJv/X5G6O6jSI1JhWys+GJJ+Cpp2DHDrvi3fPP2/qWyMga3YrcXHjzTRtcFi+2+w4NHGhDy4UX2iEjsMNk+cvzy0NL4fd2qnNUxyia3NeExCGJRJ8eTVEgwMdZWczc+AMfOaElKSSEa+rXJyM5mVARzl+1itJAgFCXi75ud43aq5RS6tSkAaY65s1jz103c/XIOObFZXNNx2sY2OrCo77NX+Tnxwd+ZNt/thGaFEq7d9rh7u0G7ESf22+3JScTJtg14arr69xc/rJlC1/l5uIO5BO+8Wle3/0J3Rp2Y9rQaVzW7jLCg8PtdtT3OvUtBQXQr58tzB0woGbbGQRg/nx7mnfesUvBtG1rM9E11xzovAmUBsj6JMeGltkeSneWQhC4z3bT8MaGJFyUQER6BIV+P3O8Xmat/ZkPvV4KAwGSQ0K4tkEDMpKSODs2luAK7ZvXqRMLcnLo63bTq6opS0oppX5zNMAcjjE2ALRsyYLmQVz5tzhyTTFTBk5hROcRRx0yMsaw6rxV5H6VS8rIFJo90YyduSHMnWvrW664wg651HQtuIAJcPP3y9hQVASbX2Df3rlc3vZSxl64mDNSz7Dt/uorO0w0e7atmr3qKltY06lTjW7B1q12FtG0afDTT3a687Bhtrele3fb7rKcMvbMyMIz20PWnCz8+X5cUS7iB8STOMTu6hwSH0KB38+HXi+zvt/CRxVCy7D9ocXtPux+Qr1iYzW4KKWUqkQDTFUyM+2+PnPmwJo1ZJVkExfbgLkZM486y8iX68MV5cIV7CLtnjRcES7CesbxyDj417/sVkGbN9tccf751WvO9uJi/r5lI2k5C5i+7Em2FBZQPyyCW7qM4KarXqBBdANbOTtjhg0uy5ZBfLzdIOnWW+385WoqKIC33rLBZcECG1L694fHH4ehQ+2M6uJtxex8xotntoec+TkYnyGkfgjJVySTOCQRdz83QeFBFPj9vOv1Muv7TD7yeikKBKgfEsJwJ7T0OUJoUUoppY5EA8x+ixbZ39guF4wfz+6ybL7++xVc0qQJlwQ1Y3CrwYQEHXmJec/7HjaM3kDqnamk/SmN+IEJvPUW/PE02LbNzsj5178OnUp8ONllZfxp3bdM8+TjNwbWvcNZ0Sk8du5YLmlziW1PTs6B+pbt2+0Svc8+C9ddV+36FmNg4UI7RDRzJuzbB82bwyOP2NOkphoKVhew59+2nmXft/sAiGgdQepdqSQOTSTmjBjEJezz+Xgry8usTXuZk5VVHlpGNGjAZcnJ9I6N1dCilFLqF9MAAza89OtnizuAz3o34qoLYyhiNueU5hEXEXfE8FK6p5SNt20kc2YmUR2jcPd1A3an6MsusyM3r71mZxlVhy/gY+S3n/JaruBzheHK/JyM8Dz+evF4Tk853R60ZYstnpkyxXabnHOODS4DB1a7vmX7dnjlFdvbsnEjREXZ9o4YAWf1tPsNecd7+eY9j93VWSCmZwzNxjUjcUgika1tQNrn8/Fm5l5mZWbysRNaGoSGcn2DBmRoaFFKKXUcaIABWLCARUklfNYEtsbBS1120rpea/6XMYu4iLgjvtUz28O6EevwF/hJfySd6JGNmb/YxZBu0LMnfPSRHSqqznY7mQWZTP52Ms8ue5ZtKVcTHtmAW+Jc3D/oDhIiEw50lYwfD++9Z4PKlVfa+pbTT6/Wt1pcbEtjpk6FuXNtge7ZZ9vRposv8FO6MAvPZA9fD/Xiy/IhYWJ3db43jcTBiYTWt9OM8n0+ZuzZUx5aigMBUkJDuSElhYykJM7S0KKUUuo40gADLOqcQL9rAxQFAwLnJ/TgrRv/V62F6UISQ4hqH0WLZ1sx/Yso7mtrO3K2bbPLrAwcePTrL9+5nLu/m8180jHrXuLcpJb8p9MZXNJ6MEGuILtS3Jtv2uCyZAnExcFf/mLrWxo1Our5jbHLvkydastksrOhcWMbWq4dVEr0ag/et72sGJWFKTEExwWTMCiBxKGJxJ0XV74bdr7Px1tOaPmvE1oahoZyY4XQosv2K6WUOhE0wAALor2UhriAAC6EsztddNjwYvyGHZN2ULKrhOb/bE7sWbHkPdyZPlcLK1faHZUnTDh09dmDlfpLeXvt2zy26n3WRJ8JsecSG8hjwiUzGZbu9Kbk5tohogkT4OefoUULePppOxUoKuqo39fevTB9ug0ua9ZAeDhcfDGM6F9Iy70est73sPPRPDAQ3jSchqMakjg0kdjesbiC7TBUns/HB3v2MGvvXv6blUWJMTQMDeUmJ7ScqaFFKaVULdAAA/Rt2pfQ4DBK/aWEBoVyTtNzqjyu4PsC1o9cT97iPBIGJWD8hp27hf79hZQUWwD7hz8ceVr0rvxdvLD8BZ5b/hy7U6+HRjdTjzIeTE9lTONmdqfkrVttUe6UKXaVu9/9zq7LP2jQUetbysrs5KmpU+3wlc8HPXsYXr47j+4lHvL/66FoRhE/AtFdomn6QFMShyYS1SGqfGp4ns/H+7ttTcsnTmhpFBrKqIYNyUhOpldMjIYWpZRStUoDDNCrcS/mXTePBT8uoG/TvvRqXHkd/0BpgJ8f/5mfHv2JoJggWkxtwzfRyXQIEho1gg8+sHUkh5v0Y4xh8fbFTFwykVkb5+Er2csFLS4gpeXvaBbflDsaNyYqKMgWE48fb1eLc7ng8sttfUvXrkf9HlavtsW406fbnpfG9f08dlEOfVwe/F96KPtXGZnBgruvm9SxqSRclEB44wMbH+b6fLzv8ZSHllJjSA0LY3SjRmQkJdFTQ4tSSqmTiBhjarsNNdKtWzezbNmyE3rNoi1FLG2/lMSLE9l4XgvufDCUrVttaGh/hGVhin3FvLHmDSYtmcTyzA2Epg/HnzKEiU2TGJ3ubBbk88G779rgsngxuN1w880wZgykph6xXVlZtqZl6lRb4xIfXMbNnb2cG+ohdGUWgYIAQfWCiL8gnsShicRfEE+I+8BsqpyyMt73epmVmcmnTmhpHBbGH5KSyEhK4gwNLUoppWqZiCw3xnQ7+HntgTkMf4GfPTP2kHJDChHNIoib3Z3b/xXB/4ZDu3Ywb97hw8u23G08u+xZXvz2RTzFeSS3HEVEq3EUE8S19eszMCUd8vIO1Lf89JNdeGXiRBg+HKIPXzzs99vZQ1On2olIcaVFXNbQywMtPERvzYFlENowlMRrG5A4NBF3XzeusAPDTjllZcz2epm1dy+fZmdT5oSWMU5PSw8NLUoppeoADTBVyJqbxYabNlD8YzH1Tq9HSLt6nHtVBD6fzRijRh26GJ0xhs9/+pyJSyby3rr3ABjcajAb0m7nh1JhYHw8jzdrRkevF+69124/nZ9vF4d58kkYPPiIc603bLBDRK9MM0Tu3Ef/cA9vxnhwewpgJ0S2iyTxL2kkDk2kXtd6iOtACMkuK2O2Mzw01wktaWFh3NaoERnJyfSoV++oWyMopZRSJxMNMI7cRblkzckib3ke2R9nE9EqgpyHOhN1ej1cLjuLuWNHu39RRQWlBby2+jUmLZnE6r2riYuI5+Izx/Fol0tpHZ/Ohx4P0UFB9N2wAW64Ad5+277xsstsfUv37odtU36+LQyeNiVAwaIceuPlmXAPMZRAKcS2iSVxSHMShiQQ2aJyAU5VoaVJWBi3p6aSkZREdw0tSiml6jANMNjwsrLfSgJFAQDkgvrcvrsV39wfxHsdYcgQOPfcyu/Zkr2Fp5c8zUsrXiKnOIdO9Tvxlwum83lQa97O38cFJeG09vsZ9Pnntr7l66/tboh33QVjx9qFWKoQCMAXX8D0531seyeL7qUe7nF5icSPhLuIPz+OxCFNSRiUQGhSaKX3ZlUILf9zQkvT8HDucEJLNw0tSimlThEaYICcBTkESmx4CQBTPo5ke6MgXnsNLrrowHEBE2Du5rlMXDKRORvn4BIXl7a9lEGdxzCryM04r5eU0FJeSEtj2MyZtr5l61Zo1sxOix4+HOrVq7INP/0EMyaWsOFlD629Xi4nmxAMuENoMDTJLir3+ziCIisPM2WVlfFehdDiqxBaLktKoquGFqWUUqcgDTDA9gQ3xQEXwQTw4SLlAjfrZh6opc0ryWPaimlMWjqJDd4NJEclc9/Z93Fz15tpFNOInsuX80NhDo/FxXH7668T+dxztki3d2/4z39sCqqivqWgwPDhpELWvuihwWYPPcmnJ+CrH0Hq5Y1o8IdEYs+MRYIqBxDv/tCydy/zcnLwGUN6eDh3OT0tGlqUUkqd6jTAAF94Y3nd1YmOgRxWudxc1SeW6GhY51nHpCWTmLZyGvtK99GjUQ9evfhV+rUcylO79hIWngTAyz4fSVOmkDB9uj1hRoatb+nR45BrBXyGRS/msupZD+41HlJMMfWBvEb1iLsqnRbDE4lsE3lIAPGUlpb3tMzLzsYPNAsP54+pqWQkJ9MlOlpDi1JKqd8MDTDY5f8fSF/L940WELKzD8Ftsznv1YnM3TKX0KBQLm93OWN6jKFDg648tWMHbZZ9R57fT4e1a7lq3DhO++oriImxoWXsWEhLq3R+f6GfzW9ms+JpDxErvNTzl9ECYU/DOLi8MWfclUhEatgh7fKUlvKuE1o+c0JL8/Bw/pyWRkZSEqdraFFKKfUbpQEGIHURMqwfJlBMKXD3CkPDeg15+JyHuanrTSRHJTNl1y4u+eYbdpSWMigvj8f+/W86fPklNG1qp0Fff32l+pbSzFL2vOtl7WQPruXZhAQCRBLE5sQE6l+ayIC/x+NudOjtz6wQWuY7oaVFRAR3O6Gls4YWpZRSSgMMwIIfF1AaKAbsqsRXtr+SaUOnERJ0YNXa/27fTuM9e3j9iSc4e9Ei6NUL3nrLTlFyFoUp3FSId7aXH6d78K3MRQzkEMbKqBTiBycw+D43g9odupdRZmkp7zg1LQtycvADLSMi+IsTWjppaFFKKaUq0QCD3cwxPDi8fDPHsT3Gsji/gHu3buX5sjLaTJjA1PffJ6qwELn0UjslulcvTMCQvywfz2wPe972ULK+EIBNRLE4qAlh/RIZfEc0D58nh9Tw7i0t5Z3MTGZlZrIgJ4cA0CoignvS0shITqZjVJSGFqWUUuowNMBgN3N88rK5vL1zEz0Tm/FYdhQfbl5BSl4e2x96iDYbNhB9441w220EUtLInp+Nd/QGPO97KN1ZSkBgFW6+oiF5HRIYOiqCf10B8fGVr7OnQmj53AktrSMi+FuTJmQkJdFBQ4tSSilVLRpggEW5udyxo4xik8ane31Elezk8Vde4bZly4gcPZqyS4eR9VUZnr94yPp4If58P74QF8td8cwjkY3xCVwyLIR/DIcOHSqfe3dJiR0eyszkCye0nBYZyb1OaGmvoUUppZSqMQ0wwIJVqyj1+zFBQUggwJ3z53NHn0vxnPFPNn6YTc7dqzE+gy8mhOXhybyXn8jKgJvzBgZx6wgYOBBCDpTLsLukhLedmpYvcnMxQJvISO5zQks7DS1KKaXUL6IBBui7YgUdy1rR+0uIKDL0/74vi7dHAFswjSNZ2TKVaZsTWZkXQ7v2woh7YPY1kJx84By7Skp42xke+tIJLW0jI7m/SRMykpNpFxVVW9+eUkopdcrRAAO0DevCf24rRgjCYAhKC+WHc5vy4tpElm6LxO2Gq0bCiyOga1fY33mys0Jo+UpDi1JKKXXCaIABVn2XSoCtBAF+hMk/N2HGtjTOOw/eeNLOlA4Pt8dWFVraRUbyj6ZNyUhKoq2GFqWUUuq40wADrMBNS1wYZy+ksB5ufn4bUlPt6ztKSnh7uw0tC53Q0j4qigec0NJGQ4tSSil1QmmAAbpdF8stL3WiXVkOa0PcPP1kLCQWM2G7LcRdmJcHQIeoKB50QstpGlqUUkqpWqMBBruo7ujP4LUffbRsvJc/hW3m68U2tHSMiuLhpk3JSE6mdWRkLbdUKaWUUqABBrDrwIzxraCskYEAtCgN55H0dDKSkmiloUUppZQ66WiAAbv/kLH7IAUB16ek8NcmTWq3UUoppZQ6rEN3FvwN6ut2E+ZyEQSEulz0dbtru0lKKaWUOgLtgQF6xcYyr1MnFuTk0NftpldsbG03SSmllFJHoAHG0Ss2VoOLUkopVUfoEJJSSiml6hwNMEoppZSqczTAKKWUUqrO0QCjlFJKqTpHA4xSSiml6hwNMEoppZSqc45rgBGRASKyXkQ2icg9VbwuIvKU8/oqEelyPNujlFJKqVPDcQswIhIEPA1cALQFrhSRtgcddgHQ0vnvJuDZ49UepZRSSp06jmcPTA9gkzFmizGmFHgDGHLQMUOAV4y1GHCLSMpxbJNSSimlTgHHM8A0ArZVeLzdea6mxyAiN4nIMhFZlpmZ+as3VCmllFJ1y/EMMFLFc+YYjsEY84IxppsxpltSUtKv0jillFJK1V3HM8BsBxpXeJwK7DyGY5RSSimlKjmeAWYp0FJE0kUkFLgCeP+gY94HrnNmI/UEco0xu45jm5RSSil1Cjhuu1EbY3wiMgb4BAgCXjLGfC8io5zXnwPmAAOBTUAhMOJo512+fLlHRH46Xu0+xSQCntpuhKqSfjYnL/1sTl762Zycjvfn0qSqJ8WYQ0pO1ClCRJYZY7rVdjvUofSzOXnpZ3Py0s/m5FRbn4uuxKuUUkqpOkcDjFJKKaXqHA0wp7YXarsB6rD0szl56Wdz8tLP5uRUK5+L1sAopZRSqs7RHhillFJK1TkaYJRSSilV52iAOcWISGMRmS8iP4jI9yJye223SVUmIkEi8p2IfFjbbVEHiIhbRN4SkXXO/z+9artNyhKRO52fZ2tEZIaIhNd2m36rROQlEdkrImsqPBcvInNFZKPzZ9yJaIsGmFOPD/ijMaYN0BO4VUTa1nKbVGW3Az/UdiPUISYA/zXGnAZ0Qj+jk4KINAJuA7oZY9pjF0a9onZb9Zv2MjDgoOfuAeYZY1oC85zHx50GmFOMMWaXMeZb5+t87A/hQ3b4VrVDRFKBC4HJtd0WdYCIxABnA1MAjDGlxpicWm2UqigYiBCRYCAS3TOv1hhjvgCyDnp6CDDN+XoaMPREtEUDzClMRJoCpwPf1HJT1AFPAncDgVpuh6qsGZAJTHWG9yaLSFRtN0qBMWYH8G/gZ2AXds+8T2u3Veog9ffvY+j8mXwiLqoB5hQlItHA28Adxpi82m6PAhEZBOw1xiyv7baoQwQDXYBnjTGnAwWcoG5wdWROPcUQIB1oCESJyDW12yp1MtAAcwoSkRBseHnNGPNObbdHlTsLuEhEfgTeAM4Vkem12yTl2A5sN8bs7618CxtoVO3rD2w1xmQaY8qAd4Aza7lNqrI9IpIC4Py590RcVAPMKUZEBDuO/4MxZnxtt0cdYIz5qzEm1RjTFFuE+JkxRv8leRIwxuwGtolIa+epfsDaWmySOuBnoKeIRDo/3/qhBdYnm/eBYc7Xw4DZJ+KiwSfiIuqEOgu4FlgtIiuc5/5mjJlTe01Sqk4YC7wmIqHAFmBELbdHAcaYb0TkLeBb7CzL79AtBWqNiMwA+gKJIrId+AfwT2CmiNyADZwZJ6QtupWAUkoppeoaHUJSSimlVJ2jAUYppZRSdY4GGKWUUkrVORpglFJKKVXnaIBRSimlVJ2jAUapX5mI+EVkRYX/mh7DOYYer004RaShMy21qtcWiEi3YzxvXxE5s8LjUSJynfP1ac69+E5EmovI18d4jUr3RUQeEpH+x3Ku2iIiTUWkqMIyB0c6dvKx/D1wrrHmCK9HOJ9HqYgk1vT8Sp0MdB0YpX59RcaYzr/wHEOBD6nBYmoiEmyM8R3tOGPMTuAPx960w+oL7AO+dq7zXIXXhgKzjTH/cB4f60qqQ6lwX4wx9x/jeWpMRIKMMf7DPT7C+6r6XDZX5++IMWZkzVt6dMaYIqCzsyq0UnWS9sAodQKISFcR+VxElovIJxWW3b5RRJaKyEoRedtZbfRM4CLgCedfyc0r9oyISOL+XzwiMlxEZonIB8CnIhIlIi855/xORIZU0Zbyf507/xJ/Q0RWicibQESF484TkUUi8q1zjWjn+R9F5EHn+dVO70pTYBRwp9PmPiLygIj8SUQGAncAI0VkvnOOfRWuc7dznpUi8s8a3peXReQPznv6Od/zaucehB2uvVXckyARecK55ioRudl5vq+IzBeR17GLQx78OFxEpjrn/U5EzqnqcznK342mIrJORKY5135LRCKd1xaISDcRaSIiG53P3iUiXzqfT5XtPuj87URkiXPPVolIyyO1R6m6QgOMUr++/d3zK0TkXbF7U00E/mCM6Qq8BDzqHPuOMaa7MaYTdnn0G4wxX2OX5v6zMaazMWbzUa7XCxhmjDkXuBe7RUF34BzsL/sj7ao8Gig0xnR02tQVbEgC7gP6G2O6AMuAuyq8z+M8/yzwJ2PMj8BzwP85bf5y/4HOKtD7Xzun4sVF5AJsr8oZzj3417HcFxEJB14GLjfGdMD2Lo8+XHuruA83YHc57g50B24UkXTntR7AvcaYtlU8vtX5HjsAVwLTnLZA5c/laFoDLzifQx5wS8UXjTE/AeOw9/GPwFpnR+YjtXu/UcAEp8enG3bfJ6XqPB1CUurXV2kISUTaA+2BuSICEATscl5uLyKPAG4gGvjkGK431xiT5Xx9HnbDyP2/pMOBNA6/d8zZwFMAxphVIrLKeb4n0BZY6LQ5FFhU4X37NwldDlxyDG3erz8w1RhT6LRh//dR0/vSGrvh3wbn8TRsuHiymu09D+i4vzcHiAVaAqXAEmPM1grHVnzcGxtOMcasE5GfgFbOaxU/l6PZZoxZ6Hw9HbgN+HfFA4wxk0UkAxtIOh+l3RsqvHURcK+IpGKD4cZqtkmpk5oGGKWOPwG+N8b0quK1l4GhxpiVIjIcW0dSFR8HekzDD3qt4KBrXWqMWV+D9lW1n4hgfwFfeZj3lDh/+vllP0fkMNd/merdl4rnOZKjtVeAscaYSkFJRPpS+f7Coff7cA5+35EcfA8OuSfOsFKq8zAayOfw7W5afiJjXheRb4ALgU9EZKQx5rMatE2pk5IOISl1/K0HkkSkF4CIhIhIO+e1esAuZ5jp6grvyXde2+9HnOEdjlyA+wkwVpxuExE5/Sht+2L/dZ2eoo7O84uBs0SkhfNapIi0qvoUh21zdXwKXF+h5iPeeb6692W/dUDT/e3Fbmj6eQ3a8Qkw2rkeItLqKENv+1W8f62wvV01CY/7pe3/+4EdivqqimPGAa8B9wMvVrfdItIM2GKMeQo7BNcRpU4BGmCUOs6MMaXY0DFORFYCKzgwC+fvwDfAXOwv4f3eAP7sFIY2xw4njBY7/fhI014fBkKAVWILdR8+SvOeBaKdoaO7gSVOmzOB4cAM57XFwCHFrwf5ALjYqf3pc5Rjca7zX+wv1WVipxXvH/qq7n3Zf55i7O7Rs0RkNRDA1otU12TszKZvnfv2PNXrWXoGCHKu+SYw3BhTcpT3VOUHYJhzr+Oxn0s5EfkdtsZlnDHmNaBUREZUs92XA2uc+3sa8MoxtE+pk47uRq2UUieQM7zzoTGmfVWPT3BbfgS6GWM8J/raSv1S2gOjlFInlh+IlWosZHe8iLOQHba3LlBb7VDql9AeGKWUUkrVOdoDo5RSSqk6RwOMUkoppeocDTBKKaWUqnM0wCillFKqztEAo5RSSqk65/8BkPgmGvYKyD8AAAAASUVORK5CYII=\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "mpmt_dir_res_4 = np.array([np.percentile(e, 68) for e in orientation_errors_4.values()])\n", + "mpmt_dir_res_6a = np.array([np.percentile(e, 68) for e in orientation_errors_6a.values()])\n", + "mpmt_dir_res_6b = np.array([np.percentile(e, 68) for e in orientation_errors_6b.values()])\n", + "mpmt_dir_res_8a = np.array([np.percentile(e, 68) for e in orientation_errors_8a.values()])\n", + "mpmt_dir_res_8b = np.array([np.percentile(e, 68) for e in orientation_errors_8b.values()])\n", + "mpmt_dir_res_4_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_4_a7r.values()])\n", + "mpmt_dir_res_6a_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_6a_a7r.values()])\n", + "mpmt_dir_res_6b_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_6b_a7r.values()])\n", + "mpmt_dir_res_8a_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_8a_a7r.values()])\n", + "mpmt_dir_res_8b_a7r = np.array([np.percentile(e, 68) for e in orientation_errors_8b_a7r.values()])\n", + "fig_mpmt_dir_a6000, ax_mpmt_dir_a6000 = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_4, '.r-', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_6a, '.b-', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_6b, '.g-', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_8a, '.c-', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir_a6000.plot(pixel_errors, mpmt_dir_res_8b, '.m-', label=\"8(b) Sony A6000 cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_dir_a7r, ax_mpmt_dir_a7r = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir_a7r.plot(pixel_errors, mpmt_dir_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)\n", + "fig_mpmt_dir, ax_mpmt_dir = make_fig(None, \"Feature identification error [pixels]\", \"mPMT orientation reconstruction resolution [deg]\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_4, '.r--', label=\"4 Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_4_a7r, '.r-', label=\"4 Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6a, '.b--', label=\"6(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6a_a7r, '.b-', label=\"6(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6b, '.g--', label=\"6(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_6b_a7r, '.g-', label=\"6(b) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8a, '.c--', label=\"8(a) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8a_a7r, '.c-', label=\"8(a) Sony α7R IV cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8b, '.m--', label=\"8(b) Sony A6000 cameras\")\n", + "ax_mpmt_dir.plot(pixel_errors, mpmt_dir_res_8b_a7r, '.m-', label=\"8(b) Sony α7R IV cameras\")\n", + "plt.legend(loc=0)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.1" + }, + "pycharm": { + "stem_cell": { + "cell_type": "raw", + "metadata": { + "collapsed": false + }, + "source": [] + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/WCTE_CalibrationErrors.ipynb b/WCTE_CalibrationErrors.ipynb new file mode 100644 index 0000000..95b9835 --- /dev/null +++ b/WCTE_CalibrationErrors.ipynb @@ -0,0 +1,1940 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from scipy import linalg\n", + "from scipy.spatial.transform import Rotation as R\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.collections\n", + "import matplotlib.patches\n", + "import pg_fitter_tools as fit\n", + "import sk_geo_tools as geo\n", + "import cv2\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "#%matplotlib notebook\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def get_led_positions(led_count, mpmt_locations):\n", + " led_ring_radius = 24.\n", + " led_positions = {}\n", + " for k, v in mpmt_locations.items():\n", + " for i in range(led_count):\n", + " if abs(v[1]) > 100:\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count),0,np.cos(i*2*np.pi/led_count)])\n", + " else:\n", + " phi = np.arctan2(v[2], v[0])\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count)*np.sin(phi), np.cos(i*2*np.pi/led_count), -np.sin(i*2*np.pi/led_count)*np.cos(phi)])\n", + " return led_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def get_image_feature_locations(feature_positions, camera_matrix, distortion, camera_rotations, camera_translations, image_size):\n", + " image_feature_locations = {\n", + " i : {list(feature_positions.keys())[f]:v for f, v in enumerate(cv2.projectPoints(np.array(list(feature_positions.values())), r, t, camera_matrix, distortion)[0].reshape((-1,2)))\n", + " if v[0] > 0 and v[0] < image_size[0] and v[1] > 0 and v[1] < image_size[1]}\n", + " for i, (r, t) in enumerate(zip(camera_rotations, camera_translations))}\n", + " feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + " print(\"Feature in image counts:\", Counter(feature_counts.values()))\n", + " return image_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def get_smeared_feature_locations(image_feature_locations, pixel_error, image_size):\n", + " smeared_feature_locations = {}\n", + " for k, i in image_feature_locations.items():\n", + " smeared_feature_locations[k] = {}\n", + " for j, f in i.items():\n", + " smeared = np.random.normal(f, pixel_error)\n", + " if(smeared[0] > 0 and smeared[0] < image_size[0] and smeared[1] > 0 and smeared[1] < image_size[1]):\n", + " smeared_feature_locations[k][j] = smeared\n", + " smeared_feature_counts = Counter([f for i in smeared_feature_locations.values() for f in i.keys()])\n", + " print(\"Smeared feature in image counts:\", Counter(smeared_feature_counts.values()))\n", + " return smeared_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_led_simulation(feature_positions, image_feature_locations, focal_length, principle_point, radial_distortion, seed_error=1):\n", + " seed_feature_positions = {}\n", + " for i, f in feature_positions.items():\n", + " seed_feature_positions[i] = np.random.normal(f, seed_error)\n", + " fitter = fit.PhotogrammetryFitter(image_feature_locations, seed_feature_positions, focal_length, principle_point, radial_distortion)\n", + " return fitter" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_images(image_feature_locations, image_size):\n", + " for i in image_feature_locations.values():\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.rint(np.stack(list(i.values())))\n", + " ax.scatter(coords[:,0], -coords[:,1], marker='s', s=0.2)\n", + " ax.set_xlim((0, image_size[0]))\n", + " ax.set_ylim((-image_size[1], 0))\n", + " ax.axes.xaxis.set_visible(False)\n", + " ax.axes.yaxis.set_visible(False)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def run_led_fit(fitter, led_positions):\n", + " reco_cam_rotations, reco_cam_translations, reprojected_points = fitter.estimate_camera_poses()\n", + " reco_cam_rotations, reco_cam_translations, reco_locations = fitter.bundle_adjustment(reco_cam_rotations, reco_cam_translations)\n", + " \n", + " reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_locations)\n", + " print(\"mean reconstruction error:\", linalg.norm(reco_errors, axis=1).mean())\n", + " print(\"max reconstruction error:\", linalg.norm(reco_errors, axis=1).max())\n", + "\n", + " reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(reco_cam_rotations, reco_cam_translations)\n", + " cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + " cam_positions_translated = reco_cam_positions - translation\n", + " cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + " reco_led_positions = reco_positions_dict(reco_transformed, fitter.feature_index)\n", + " position_errors = linalg.norm(reco_errors, axis=1)\n", + "\n", + " return reco_led_positions, position_errors" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def reco_positions_dict(reco_positions, feature_index):\n", + " return {f: reco_positions[i] for f, i in feature_index.items()}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_centre_errors(reco_led_positions, mpmt_positions, led_count):\n", + " reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n", + " for k in mpmt_positions.keys()}\n", + " errors = np.array([linalg.norm(reco_mpmt_positions[k] - mpmt_positions[k]) for k in mpmt_positions.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_coun):\n", + " reco_orientations = {}\n", + " for k in mpmt_orientations.keys():\n", + " c, n = geo.fit_plane(np.array([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)]))\n", + " # flip normal if it is directed away from tank centre\n", + " if np.dot(n,c) > 0:\n", + " n = -n\n", + " reco_orientations[k] = n\n", + " errors = np.array([np.degrees(np.arccos(np.dot(reco_orientations[k], mpmt_orientations[k]))) for k in mpmt_orientations.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def make_fig(title=None, xlabel=None, ylabel=None, figsize=(8,6)):\n", + " fig, ax = plt.subplots(figsize=figsize)\n", + " ax.set_title(title)\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " fig.tight_layout()\n", + " return fig, ax" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_geometry(led_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter([l[0] for l in led_positions.values()], [l[2] for l in led_positions.values()], [l[1] for l in led_positions.values()], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_reconstruction(reco_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter(reco_positions[:,0], reco_positions[:,2], reco_positions[:,1], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "pmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_PMT_locations.txt\", delimiter=\" \")\n", + "#mpmt_locations = {k: v for k, v in pmt_locations.items() if int(k)%19==0}\n", + "mpmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_centrePMT_locations.txt\", delimiter=\" \")\n", + "mpmt_orientations = {k: np.array((0,-1,0)) if v[1]>100\n", + " else np.array((0,1,0)) if v[1]<-100\n", + " else np.array((-v[0],0,-v[2]))/np.sqrt(v[0]**2+v[2]**2)\n", + " for k, v in mpmt_locations.items()}\n", + "led_count = 12\n", + "led_positions = get_led_positions(led_count, mpmt_locations)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'19': array([160.01661746, 26.7375 , 31.8292842 ]),\n", + " '38': array([135.65553801, 26.7375 , 90.64213261]),\n", + " '57': array([ 90.64213261, 26.7375 , 135.65553801]),\n", + " '76': array([ 31.8292842 , 26.7375 , 160.01661746]),\n", + " '95': array([-31.8292842 , 26.7375 , 160.01661746]),\n", + " '114': array([-90.64213261, 26.7375 , 135.65553801]),\n", + " '133': array([-135.65553801, 26.7375 , 90.64213261]),\n", + " '152': array([-160.01661746, 26.7375 , 31.8292842 ]),\n", + " '171': array([-160.01661746, 26.7375 , -31.8292842 ]),\n", + " '190': array([-135.65553801, 26.7375 , 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" '1786': array([ 0. , 128.05152833, -116. ]),\n", + " '1805': array([ 0. , 128.05152833, -58. ]),\n", + " '1824': array([ 0. , 128.05152833, 0. ]),\n", + " '1843': array([ 0. , 128.05152833, 58. ]),\n", + " '1862': array([ 0. , 128.05152833, 116. ]),\n", + " '1881': array([ 58. , 128.05152833, -116. ]),\n", + " '1900': array([ 58. , 128.05152833, -58. ]),\n", + " '1919': array([ 58. , 128.05152833, 0. ]),\n", + " '1938': array([ 58. , 128.05152833, 58. ]),\n", + " '1957': array([ 58. , 128.05152833, 116. ]),\n", + " '1976': array([116. , 128.05152833, -58. ]),\n", + " '1995': array([116. , 128.05152833, 0. ]),\n", + " '2014': array([116. , 128.05152833, 58. ])}" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mpmt_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'19': array([-0.98078528, 0. , -0.19509032]),\n", + " '38': 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0]),\n", + " '1197': array([0, 1, 0]),\n", + " '1216': array([0, 1, 0]),\n", + " '1235': array([0, 1, 0]),\n", + " '1254': array([0, 1, 0]),\n", + " '1273': array([0, 1, 0]),\n", + " '1292': array([0, 1, 0]),\n", + " '1311': array([0, 1, 0]),\n", + " '1330': array([-0.98078528, 0. , -0.19509032]),\n", + " '1349': array([-0.83146961, 0. , -0.55557023]),\n", + " '1368': array([-0.55557023, 0. , -0.83146961]),\n", + " '1387': array([-0.19509032, 0. , -0.98078528]),\n", + " '1406': array([ 0.19509032, 0. , -0.98078528]),\n", + " '1425': array([ 0.55557023, 0. , -0.83146961]),\n", + " '1444': array([ 0.83146961, 0. , -0.55557023]),\n", + " '1463': array([ 0.98078528, 0. , -0.19509032]),\n", + " '1482': array([0.98078528, 0. , 0.19509032]),\n", + " '1501': array([0.83146961, 0. , 0.55557023]),\n", + " '1520': array([0.55557023, 0. , 0.83146961]),\n", + " '1539': array([0.19509032, 0. , 0.98078528]),\n", + " '1558': array([-0.19509032, 0. , 0.98078528]),\n", + " '1577': array([-0.55557023, 0. , 0.83146961]),\n", + " '1596': array([-0.83146961, 0. , 0.55557023]),\n", + " '1615': array([-0.98078528, 0. , 0.19509032]),\n", + " '1634': array([ 0, -1, 0]),\n", + " '1653': array([ 0, -1, 0]),\n", + " '1672': array([ 0, -1, 0]),\n", + " '1691': array([ 0, -1, 0]),\n", + " '1710': array([ 0, -1, 0]),\n", + " '1729': array([ 0, -1, 0]),\n", + " '1748': array([ 0, -1, 0]),\n", + " '1767': array([ 0, -1, 0]),\n", + " '1786': array([ 0, -1, 0]),\n", + " '1805': array([ 0, -1, 0]),\n", + " '1824': array([ 0, -1, 0]),\n", + " '1843': array([ 0, -1, 0]),\n", + " '1862': array([ 0, -1, 0]),\n", + " '1881': array([ 0, -1, 0]),\n", + " '1900': array([ 0, -1, 0]),\n", + " '1919': array([ 0, -1, 0]),\n", + " '1938': array([ 0, -1, 0]),\n", + " '1957': array([ 0, -1, 0]),\n", + " '1976': array([ 0, -1, 0]),\n", + " '1995': array([ 0, -1, 0]),\n", + " '2014': array([ 0, -1, 0])}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mpmt_orientations" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony a7R-IV" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "focal_length = np.array([3526.4, 3622.6])\n", + "principle_point = np.array([4719.6, 3240.2])\n", + "radial_distortion = np.array([-0.1981, 0.0361])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([9504, 6336])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "all_cam_positions = np.array([[97.47275687, 14.93703117, 99.94996814],\n", + " [29.15674544, 141.7448364, 147.4176074],\n", + " [44.82084089, 266.7725, -44.9380583],\n", + " [29.29952975, 16.2275, -28.97664714],\n", + " [-97.47275687 , 14.93703117, -99.94996814],\n", + " [99.94996814, 272.2629688, -97.47275687],\n", + " [99.94996814, 14.93703117, -97.47275687],\n", + " [-99.94996814, 14.93703117, 97.47275687],\n", + " [-29.15674544, 141.7448364, -147.4176074],\n", + " [-147.4176074, 141.7448364, 29.15674544],\n", + " [-99.94996814, 272.2629688, 97.47275687],\n", + " [97.47275687, 272.2629688, 99.94996814],\n", + " [147.4176074, 141.7448364, -29.15674544],\n", + " [-97.47275687, 272.2629688, -99.94996814]])\n", + "corner_cam_positions = all_cam_positions[(0,4,5,6,7,10,11,13),:]\n", + "cam_offsets = np.mean(corner_cam_positions, axis=0)\n", + "all_cam_positions = all_cam_positions - cam_offsets\n", + "corner_cam_positions = corner_cam_positions - cam_offsets" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "corner_cam_directions = [[-1, +1.9, -1],\n", + " [+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [-1, +1.9, +1],\n", + " [+1, +1.9, -1],\n", + " [+1, -1.9, -1],\n", + " [-1, -1.9, -1],\n", + " [+1, -1.9, +1]]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner_cam_positions\n", + "camera_directions = corner_cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({4: 504, 8: 344, 7: 212, 6: 152, 5: 60})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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nV2awAKim1OyLWR0ASjODBQxppJmMFpWafTGrA0AtZrCArpnJgHjsvQF68GgG6x81CgOwl9sMhpkMiON2tl9KyYcPoDuWCAJds4naMknisYQT6JkAC6Bzt9mC8/lcuygkAW9KPnwAfbNEEKBzlknGYnkcQN/MYMFOSn+13uOruC/vbTJbEIvlcW3SxwJLmcGCnZT+ar3HV3Ff3mG7W8BLW3rpY2VwhPLMYMFOSn+13uOr+LO/w1fZcUW991HLRXnP3vvIfewa9mTCDuZ5Xvzz8vIyA6w1TdOcUpqnaapdlPAul8s8TdN8uVxqFyWLqPc+arme1Vu7Kam3e7+WtgL5pJSu852YyRJBGNSey0QkWViut2WYUe991HI9q7d2U1Jv934tS1RhB/eirkc/ZrDa1tNXq56upZbRv+JGVatte6bycP/4K/cF+pYezGAJsAbS04C6p2upZcuLv9SgwWCknjXP1Gj3ac316pv6s6W9aw/b9dbf9HY9oxNg0dVD3dO1tKjUoMFgpB5BxGOCzzaUqvst7V172K63/qa36xmdAAvIpqUZLAOc/Ear09Gut1WlBq7uf1291X9v1zO6RwHW4fP/W+Z4PM7X6zXb/i+A0t7e3tL7+3uapsnGbgiiRJId5zsBezscDj/meT7+/ueyCAJdGz1jGERUIuuh7HhAFA4aBrp2G3T5op3XKAf1jnKde9vjQF2AWgRYAKx2m4E4n8/f/t1oQcqa8qy5Tpbz4QPomSWCAKy2ZulltENw15THElMA1hJgAbDamv0u0YKUNeWxrweAtSwRBNhZtCVzN6XKFW05WLTylBa1vQH0SoAFsLOo+3qilqsVUQMZ9xVgXwIsILyoA9dnRc2gFrVcrYgayPR2X3vrD4D+CLCgkoiDhIhlSinuwPVZUZeoRS1XK6IGMr3d16j9QdT+E9ifAAsqiThIiFimlMoMXA2G4sh9L2rd294CmRxK3IuogWzU/lNfB/uTRRAqiZZZLaWYZUqpTCa3aKnDR5b7Xri3cZS4F1EzO0btPz0PsD8BFlQScZAQsUylRB0MjSj3vXBv4xjpXkTtP0e6BxDFYZ7nxX/5eDzO1+u1YHEA2vXx8ZHO53M6nU6WidEc7RdgncPh8GOe5+Pvf24GCyATS3FomfYLkIckFwBfWLNBPOrm+7+y4b2OFup9Tftt4XoAarFEEOALb29v6f39PU3T1MVX/d6upxW91Xtv1wPwjEdLBM1gAXyh5KxUjVmAFmbZelSj3ku2L+0I4DEzWDTFJmyiW9NGzQJQ0pr2pW8FWE+SC7pgEzbRrWmj0idT0pr2pW+lBT4E0AoBFk0xICW6NW006rk5NT07gDLw+rs17UvfSgt8CKAVlggCBDZa4PDsssnRlluO1i4gJe2eeCS54BdS7NKaUdvs7Yvt+XyuXZRdPJs8YbSkC6O1i5tR+wE+3WZlBVdEZ4ngoEyz05pR2+xoS7eeXTY52nLL0drFzaj9AG0z8zYeAdagRn05065R2+xogQPLjNouRu0HaJsPA+OxRHBQptlJqa3lNtos0FI/0FL/SlmjLWFuQennM0SApROCOkbdx/GM1vup1svfi5bvQ8tlr0H/yk1LHwZGUfr5DLFE0NQp1GG5zXKt91Otl78XLd+Hlsteg/4V4ir9fIYIsHRCjCTSZtdR93E8o/V+qvXy96Ll+9By2WuI1r9GevdAbaWfT+dgwc5GO68HgPq8eyA/52BBEDa7skWP+2ByX5M6gr/z7oH9mMECaEiPX6FzX5M6AmAPj2awQuzBAmCZHvfB5L4mdQRATWawAAAAVrIHCwAAoDABFsCAJE3Yh3oGGI8ACwjJwLSs0qfY80k9l6WfACISYAEh1RyYjjBok7J5HyPUc83nRQALRCTAogsjDIhHU3NgOsKg7XaK/evr6y6/L8ozunc59q7nGmo+LyMEsEB7pGmnC7cXfErJGTGduA1Ma5ASO78oz2iUcvSk5vNSs5+gnI+Pj3Q+n9PpdOr64wT9EmDRBQPibbzMfmXQll+UZzRKOXriefmV/nQ7H0JonSWCdGGEZTgljbAkrgd7Lm/L/buiPKO5y9HyPaEM/el2ln7SvHmeF/+8vLzMjOtyuczTNM2Xy6V2UbpUs37d2zZM0zSnlOZpmsL8rh7bzpprinhPqEtfDuNIKV3nOzGTAKtzOTtbL/dlnq3zkQe0LLPnvV/6u3rsF9ZcU8R7wriefR61reXUFX8lwBpUzsHPs53KaJ1R6RdcjwNa2tXj893jNdG2pW2y9Ac+YoyriEOANagID+9oHXfpOo9wTwHYT+n36GjvlS3Xa2UQfyXAoprROm6WWdMutCFgZPrAvKIENu5r+x4FWIfP/2+Z4/E4X6/XHLk1gMG9vb2l9/f3NE3Tt2l41/xdoF9rU6BLmc492gW5HA6HH/M8H3//c2nagSrWpOHdM2WvVNiwzp7PzNoU6FKmc0+UYyPolwALCmt9wF6q/GtecEv+bq5yGpDBOjmfme+e47UfW0p9nGm9XwcKu7du8NGPPVj0YO81z1HWej+rlfLnKqc18bDOiJv+WynnV/R1sF2S5CIvHVO7nnkxRsk4VEPJZBQ566b1ev6rnq6FsnprK61cTyvl/MqeQWIP9cUn9/JXAqzMevh6NapnOgf3e5m19aRe71MvLKWtPFbzg08L9jzbUjvth3v5KwFWZj10xD1cw15aqquaZTWgyUO9sJS28lhLH3xauo97rwJpXW/X3tv1bCXA4m98heiT+wrQ1geflvptA+x1Wrq3rPcowPrHTrk02KDUeQ23rEp7pL5mP+4rwM/so6X+fk4t9ds166lFJe+t87zictBwAxyyCgDAXxkf1ueg4YbtechqBM4XIZecbUm7hHzPgecJthttfNiUe+sGH/3Yg8UerFcml5xtyTlbtCriOVX6eXLSr1JLsgeLVrS0Fp3YcralXP/W+XxO7+/vKaVkSQe7yNnmcj0H+nly0q8SjT1YABks3WxsUzJ70zbpnbZLLY/2YAmwADKw2ZjWacMA60hyAexupI3sNhvTutHa8Ej9E7AvM1hAMb6IA1Hpn4CtHs1gSXIBFGMjOxCV/gkoxQwWbGRzLQDAeOzBgkJu6WHP53PtogDAZvanwTaWCMJGlpkA0BPnSsE2ZrBgo9fX1/THH3+EXR44+pfI0a9/raX1NUK9qgtKid5mRssoCdnN87z45+XlZQbaMk3TnFKap2mqXZQqRr/+tZbW1wj1qi7KuFwu8zRN8+VyqV2UarQZ6ENK6TrfiZksEYTOjb6EcfTrX2tpfY1Qr+qiDMvPtBnonSyCAMBuZF4FeiGLIMDg9t73EX2fifqoI/q+VYCtLBEEGMTeS7OiLwVTHwCUIMACGMTe+z6i7zNRHwCUYA/WAKx3BwCAvOzBGthtWcr5fK5dFDpnjwnQKv0Xe9Le+ibAGkBvBwbqlOISzAOt0n/F1eN7X3vrmz1YA7hlbOqFjeJx2WMCtEr/FVeP733trW9msGhObzNyPZF+OYbIX3trlU2d8B39V1w9vve1t75JcgHQmbe3t/T+/p6maQr3tbdW2dQJALlJcgEMY/QZgchfe2uVTZ3ENfrzCvTHDBbQHTMC0A7PK9CqRzNYklwA3bF5GNrheQV6Y4kgbBB5aUvkspVm8zC0Y+TndeR+GnomwIINIp9jEblsAMTupwV/8DxLBGGDyEtbIpcNgNj9dI9nT8FeJLkAYBcfHx/pfD6n0+m0+3Kwmr8bWuSZge9J0w7sxtKSeiLXfc3lUJGXYqUU+771Tt3fN/LeONiquwBLRwn1RR/M9ixy3dc87yn6WVOR71vv1D3E1eq4vrs9WNYMQ32R9xX0LnLd376Ij/a7l4h833qn7iGuVsf13e3BsmYY+uc5hzF41mFs0fuAR3uwuguwgP69vb2l9/f3NE1TU1+0gHU860BkjwKs7pYIAv2zpAfG4FkHWmQGC/hF9Ol4AIAIpGkHUkrfZ+QpmVGr1WxALatV51t+75r/duv1tVg/xPPd/XS/YTDzPC/+eXl5mYG2TdM0p5TmaZru/v+Xy2Wepmm+XC67/+7Svz+SNde5pU6W1HkJW37vmv926/W1WD97tZ1WLLnG0vXw3f2s1c6AslJK1/lOzCTAgsHUHHAt+d2jDET2CiJq3e8tv3fPAKLF+tkzAG3BkmssXQ/f3c8RAl0YkQALOtbTy7una/mKWQiepe38KsIMFjCmRwGWJBc0TUKGT1IZA/TBe+2TeqAFklzQpZIJGZ5VYzPz6XRK0zRJZTyoPRM9jJpUYq86kgyBGu+1iO0u4vsdFrs3rfXoxxJBoom47KPnPQ8R6zuaGnW0Z6KHEZNKrP3v90rwkZNnO44W+5AStElakOzB4kanVVbP9RvxJRxNjTraM9HDiEkl1v73eyX4yMmz/b2e+/aerw1KEmDxJy/SvpV8UXoJf08d0SLt9nsl353qv3/ucZ8eBVj/2HtJIvXd9unYr9On27r1lFL2hBevr6+SaHxDHdEi7fZ7Jd+dJfttYnCPxyLAGpAXad8E0AD5lXx36rf75x6PRZp2AACAlaRph0ZFTJ8LAMB9AiyoZGng5CwQnlE7MK/9+5eqXc7av582aTcQ3L3MF49+ZBGEfJZmpJJ5KJ4W7kntbKG1f/9StctZ+/cv0UJ7H433B8SQZBGEWJZueJWUJJ4WskHV3lBd+/cvVbuctX//Ei2099EsbTfuHdQhyQX8t4+Pj3Q+n9PpdEqvr6+1i0Ng2goj0d7btfe901YYzaMkFwIshrCk0397e0vv7+9pmiZf+gBgpaXvUYEYvXgUYFkiyBCWLJNoYakOAERl6SJ8kkWQIZxOpzRN05ed/m2vk69py8hiBfROP7fO0vfokncytMwSQeApllQCvdPPAV+xRBDIypJKoHf6OeAZZrAAAABWejSDZQ8WTbIuXh3wWO22Ufv3rxGhrBHKQEzaxif1QHPunT786Ofl5WW/o5HhC0tPsS/hcrnM0zTNl8tl99/9VzXrYFRR7v13areN2r9/jQhljVCGJVpp/z1ppW2Uph6IKqV0ne/ETPZg0aSa6+KjpJe1N2B/Ue79d2q3jdq/f40IZY1QhiVaaf89idI2ap9bFaUeYCl7sGCl2i8a6nHvGZn2Py7ZFOG+R3uwBFgLeKkAAKMyDuIrI7cPado3sCwCABjV7QBhuMc4+e9kEVxg9BPHZe8BAOCe0cfJ9wiwFrh9uRlt2vPm9mXifD7XLspDgkAAaF8L7/MWyrin0cfJ91giyLdayN5jehoA2tfC+7yFMlKXGSy+1cKXCdPT1FDzK2aLX1Brl7n273+GNsZoWnift1BGKrt3ONajHwcNA/Mc+8DRNWXbeh01D7/c+rvXXnuOe177sNAcv3/vehuljfXSpwBjSQ8OGhZgAavVHih/ZU3Z9g5Sctp74F4jOMmtRpCoje3zLJYUuWxAXQIsIJvaA+Wv9PLVvLQaM1g9UG/L9fIsRi4bUNejAMtBwwAAACs9OmhYkgvCsbEaxra2D9BnwNj0AUQjwCKcFs7dYl+1Xp45fu+af2Pv31dCjt+/tg/I0Wf0UG8jtLXa94mYjBsI5966wUc/9mCxB+vdlxmpnmptMs/xe/fe6F97Q36LmfrmuY96G6Gt1b5Pexupn99CPVFLkuSCGkbr9Pa83pEGGrXaUY7fu/dG/9rPXO3f/6za5dbW4v7Omvbu50eq35GulXIeBViSXFDU29tben9/T9M0DXHa+Z7X+/Hxkc7nczqdTqEPgQbgOXv38yO9s0e6Vsp5lOTiHzUKwzhup5yPctr5ntf7+vrqpQDQsb37+ZHe2SNdK/szgwUAALCSNO0AAACFCbA6In0tAEDbjOfaJ8DqiHMgKEVnD/BJf0hpxnPtE2AFsrXTPp1OaZomGzbJTmcP8El/SGlbx3M+AtQnwApka6d9yzYkZTe5lQ7eW3kZRClnlHKsEaXMUcqxRpQyRynHV/Yoo4+ZlLZ1POcjQAD3Dsd69OOg4bIceseoWjk0OUo5o5RjjShljlKONaKUOUo5vtJCGaE048n9pAcHDTsHKxDnGq3nsN0+tHIeSZRyRinHGlHKHKUca0Qpc5RyfKWFMrKcd/xzjCfrcw4WTXMSOwD0yTue6JyDRZeshf+phf0RADymH/+VdzytMoMFnfClD6Bt+nFoy6MZLHuwoBP2HgC0TT8OfbBEEDqxNa2rpSkA22ztRx23An0QYK1kEEqvnJsBsI1+lFEYD39NgLVS752nB6ZPS+6rzcQA2yzpR71n+zXSve19PLzZvcOxHv04aLj/w9sc0phPpLbivgLEEKk/jvSe6kGke1uatvMpPThoWIDFLzww+UTqaCPe14hleiRKWaOUY61o5Y5WnqWilDtKOb4TtZyRyhXpPdWDSPeWfQiwYGc62q+19GKPUtYo5VgrWrmjlWepKOWOUo7vtFLOmrynYJtHAZY07VDILRsU97WUjjhKWaOUY61o5Y5WnqWilDtKOb7TSjlr8p6CMhw0DAAAsNKjg4ZlEQQAAMhEgAUBjZTqFYBtvDMgFgHWDnR8rOV8CQCW8s7gWcaoZUhysYNbx5dSspmURWzOBmAp7wyeZYxahgBrBzo+1pLZCYClvDN4ljFqGZYI7uDW8b2+vtYuCoGYlgegNO8avmKMWoYACyqxZv6n2gOA2r8felLzefIs/513DexPgAWVnE6nNE3T6mn5HgcQtQcAOX7/2vuS6z5GaQ9RyrFVlOuo1T5y/N6az3PtvqSULffl2XcNsME8z4t/Xl5eZqCuaZrmlNI8TVPtomRzuVzmaZrmy+XS7O9fe19y3cco7SFnOdbej5ztp7f6rNEuaz7PtfuSUqK0S+BXKaXrfCdmEmDRlV5frn81wjW2qFZQEKU91AxyagZ3pdRqH1Gun1+NcF9GuEb68yjAOnz+f8scj8f5er1mnUGDnN7e3tL7+3uapklGJWjUx8dHOp/P6XQ6Ldp4vfbvA/F4f9Oiw+HwY57n4+9/Lk07XZFuFNq3NuW0FNXQPu9veiLJBV2RbrRfazZ5R0lUAHytVnIYfopSp97f9ESABQVEeWH1ZE12sBpZAaN75np6q4PcatZplHuztRxrn9VeswTWpE7/LsrzRcPubcx69NNDkgubKMtRtz/J+JTfmvZVIytgKbmeq2eup8fkETnLUrNOo7TPreWQhKM+dfp3UZ6vEbTe/pIsgp88NOWo259a7zCIcw9zPVfPXE+P6c9zlqVmnUZpn1HKATlp1/uJ9G54hgDrv3loylG3kF8vz1Wk64hUFoCRtd4fPwqwpGmHHUgjDUAE3keQz6M07ZJcwA5sIgbgO3skV/A+gvKcgwU72ON8D18lAdp2C35SSsXOdnPeFJQnwIId7HEQ6h4vZgDK2SP4cTA3lCfAgk74KgnQNsEP9EGABZ3wYgYAqE+SCwAAgEwEWMCQ9sjWBaPznAEjEmAxJC99Wk5VHLX9Ri3XGhGvIWKZlmr5OSOfltswPOXe6cOPfl5eXvY+IBmKmKZpTinN0zRt/rdaP4V8VC3ft5ztN6eo5Voj4jVELNNSLT9nI8t931puw/CVlNJ1vhMzSXLBkHJm3JMevU0tJwWJmjEyarnWiHgNEcu0VMvP2chyv9dabsPwjMNn8LXM8Xicr9drweJAexzwC0BPvNdgmcPh8GOe5+Pf/lyABQAAsM6jAEuSCwAAgEwEWPAFmY8A4O+8H+ExAVYFOqV2SDEMAH/n/dgmY9B9yCJYgaxz7ZD5CAD+zvuxTcag+zCDVcHpdErTNOmUGnBLMdxaFiVfqADa0Gp/3er7cXTGoPsQYFWgUxpLjZenpRsAbajRX7ca1LGdMeg+LBGEwmpMx1u6AdCGGv21ZWJQlhksKKzGdLwvVI/5cgv789w9VqO/HnGZmDbIngRYVDFSRyfYiaX15ZNRn52o5Vor6nVELddSrT93vRnxvaQNsidLBKnC8gRqaX35ZNRnJ2q51op6HVHLtVTrzx3t0wbZkwCLKnR01HL7ctuqqM9O1HKtFfU6opZrqdafO9qnDbKnwzzPi//y8Xicr9drweIAAADEdzgcfszzfPz9z+3BAgAAyESABQAAkIkAiy60nmELAPjknU7rJLmgC61n2AIAPnmn0zoBFl1oPcMWAPDJO53WySIIAACwkiyCAEDX7N0BIhBgASGsHRjlGkgZkEF+tZ7P296d8/m86ffuSR+0jvqiCfM8L/55eXmZoZbL5TJP0zRfLpcQ/05kLV7jNE1zSmmepqnI3y/97+TS4r37StTriVquZ0W7nlrPZ7R6WCJaH1RKrnszSn3RhpTSdb4TMwmwaEavA+oSWrzGtS/fXgPunPfu2WvLWSdR22Lucj1TZz3Xc6/PZwkjXOM852ujo9QXbRBg0Twv7OVGuMZeRRh0RwjySstdrmfqbIR6hhttlB4JsCAQLxr2EGEGaxS1Z7DgK9oalPEowJKmHSp4e3tL7+/vaZomhygCUJR3DpQhTTsEcjqd0jRNXR+iKNMTEN0o/dQI7xyIRIAFFby+vqY//vgjvb6+1i5KMS2mS/7KKAMx+ErO5yDCM9VbP/XICO8ciESABRQR5YtprkHcswOxCINIuOeZtpkzIIkQ3ETpp4DO3NuY9ehHkgugNbVTA8sUt06UxBxR67p2lsmcvz9qHQMslWQRBEZUexBXe0BcWoR051v+u73+vVwE7ABxPAqw/lFr5gxgD7e9Bz38/tsypkjLmW7LvFJKWa7z2WvMXTcR6zqlvOWq/WwA9EqadgCe9vHxkc7nczqdTjbQA9Xpk9iTNO2EJxnANuqPGmQng3z049tFSJ4ClggSRu6lRqNRfwBt049vF3V5L2Mxg9Ww3r50RUyX21IdR6w/AJZrrR+P+I7sdVY9Yl3zmD1YDXt7e0vv7+9pmiZfugqpUcfWjwOwRq33hnHIftR1TI/2YFki2DDT4OXVqGNLRADiaOGjV633Rs1xSAv3JSdjvraYwaIJI3WkLVxrC2UEyKGFmYMR++QW7gv9M4NF00aa1fnubJoIL9KR7gcwtigzB1/1/SOeaRblvsA9AiyaoCP9KUJw0/L9iBCgwmhafu6iBC8R+v5IotwXuEeARRN0pD9FCG5avh8GKfQsaiDjudsuQt8PLCNNOzSm1xS0e4mcBrm3NLwtXE8LZVwj6iGrkZ+7Vuj7oR1msIChRJ596+0rfwvX00IZ14g6yxH5uQPITYAFEETUwfGzWrieFsq4hkAGoD5p2gEAAFZ6lKbdHiwAAIBMBFgAAACZCLAAAAAyEWABAABkIsACAADIRIAFAEBXejtEnLYIsAhBRxifewSMTj/Yjtsh4ufzuXZRGJCDhgnh1hGmlBySGZR7BIxulH7w4+Mjnc/ndDqd0uvra+3iPKW3Q8RpixksQjidTmmapmY7whG+arZ+jwC2aq0ffPbd1MPsz+vra/rjjz+aDRBpmwCLEFrvCJ95GbUWlLV8j1qra+hZy89ja/3gs4FSa4EkRCPA4m9afvnV8szLqIcvhK1Q1xCH53E/zwZKrQWSURg/cSPA4m+8/NZ75mXkC+F+ote1lzK5RW5T0Z/H1nx1rwVK+zJ+4k/zPC/+eXl5menf5XKZp2maL5dL7aIMyz0YyzRNc0ppnqapdlGyaaUNt1LOtXpsU9znXsfRa3/CYyml63wnZpJFkL+5ffGinlEyVfGpx2xXrbThVsq5Vo9tivvc6ziMn7gRYEFAXphj6fGl3EobbqWca/XYprjPvd6mh5T0xGMPFkVF3gewtzV1Yd08rWulDbdSTsihtXfyHuW1b4oSzGBRVOnlNy19eep1KRIAbWjtPbRHeXudxaYuARZFle64WnpZ6MQBqKm199Ae5bXEkhIOnwkwljkej/P1ei1YHFinpRksAAD6cTgcfszzfPz9z+3Bomn2T9TR2jp+gGfp74C1LBEEVmtpaSbAFvo7YC0BFrBaa+v4AZ6lvwPWskQQGlVz2Uq0pZmW8EBfIj3TNfu7SPUALGcGCxpl2cpP6gL64pn+pB6gTWawoFGn0ylN02TZSspbF74Yw3q5nxv92yf1AG0SYEGjoi3TqylnXdy+GJ/P51X/XYnATLDHd3K3kWf/vWefm0f0b5/UA7RJgAXwF89+Mc49wCz1b+Y0QgAY/Rpzt5Fn/z0zLQB/Mc/z4p+Xl5cZgL+7XC7zNE3z5XIJ/W/mNE3TnFKap2nK9m9uueYS9VXiGnPKfc3R2xz5uNewXUrpOt+JmQRYUNjIL7GRr30E0QKaaAEf8Y18f6N/PIAWCLCgkpFfYs9c+8gDHuLNYNGOZ+7/yP2z5wW2exRgSdMOhY18SOUz1y4t8dhum/r3/m9p3zN9x0j988fHRzqfz+l0OqXX11fPCxR0+Ay+ljkej/P1ei1YHOjf7y85fqV+YAy5n3V9x9fe3t7S+/t7mqZJYAWZHA6HH/M8H3//czNYsDMzNF/L+VXVgAviyt0XmpH52kizdVCbNO2wM+mM9xM9zXlu0VOK872R7qG+cF/O1IL9CLBgZ15y+4k8gCsxkN4SUI40sC9tS12W+CgQ9d7qC4FeWSIIdCvykqESS0W3LAEqUZ4WlmiWKOOWuiyxjMuyZIB9CbAAKigxkN4SUI46sI8W6Jb4KGDvTVwtfIQA1pNFEDrlxU1tLbTBFspIv2T2g7bJIgiDaWH2gL5FXqJ500IZ6ddIs4s+ZjASARbDGaWTH+nFDdCikQJ8H/0YiQCL4YzSyY/04gYgNh/9Hhvlw+9IBFiD8PD+pJMHgH356PfYKB9+RyLAGoSH9yedPAAQhQ+//RFgDcLDCwAQjw+//fkftQtQW9QT7nO7PbyjLw+sZZR2BkB83klE0mN7HD7Aui2dO5/PtYtCx7Sz/HrskIFfec7L8E5aT1ssp8f2OPwSQUvnnidxxnLaWX72FUL/POdleCetpy2W02N7PMzzvPgvH4/H+Xq9FiwOLXECPTUJ8KF/nnOi0Ba553A4/Jjn+fi3Pxdg8SydDeTnueJZ2g7Avh4FWMMvEeR5st5Afpah8CxtByCG4ZNcQCQ20XI6ndI0TU2sRR+hvbZ0jS21Hcpoqb1CzywRhEDsa6MlI7TXEa6RfmivsK9HSwTNYEEgvkDTkhHa6wjXSD/2aK9myeJwL+ISYDXGw1TPHnW/14HQ2hE5jHCA+QjXSHl79bnPttc15evxzKJWuRdxSXLRGJuY61lT99GzeWlHAPuJ3ueuKV+PZxa1yr2IS4DVGA9TPWvqPvrLVDsC2E/0PndN+WQQjsO9iEuSCygg+gwWAADbOAcLduSrEgDAmCS5AAAAyESABQAAkIkACwCApjl+hEgEWABAeAbQfMWZUEQiwCIkL1Ie0TZgTAbQfOV0OqVpmsKmwmcssggSUvRzpKhH24AxRT9Lirpk7yUSARYheZHyiLYBYzKABlrhoGEA6IiDzgH28eigYXuwAAKwt4xc7FUCqEuABYMzsI+htUHxSO2mtWu12T+GXO2mtfYH2IMFzcq1DEjSiBha21s2Urtp7VrtVYohV7tprf0BAixoVq6XbmsD+161Nigeqd2MdK3kk6vdaH/QHkkuoFE2sgMA1PMoyYUZLGhUazMeAAAjkOQCAAAgEwEWAABAJgIsAACATARYAAAAmQiwYFAOrwQo71Ffqw+GfgmwoHOPXuK3c7TO53OlkuVjoAJ96emZftTX9tQHA7+Spr0C5xexp0cHEvd0eGWuQ5eBGHp6ph/1tT31wfTB+DQfAVYFPb04iO/RS7ync7QMVKAvPT3Tj/ra1vpgg+/+GZ/mY4lgBafTKU3T1MWLY1QtLV+5vcR7fiGOcI2QU/Q+zDO9n6VtwZLGGEo+u8anGc3zvPjn5eVlJp7L5TJP0zRfLpfaRRnGNE1zSmmepunLv+feMM/aAfEs7cPon/dZWzy7saSUrvOdmMkSwQ6Y0t3f0uUr7g0paQfE09MSPLZZ2hZyLWm01HAbz24j7kVdj37MYMXkq9I6e9aXe8M8l2sHkdtX5LL9rmRZt/7bLdUjLGEGhp6kBzNYAiyGo3OnF1vbcsnBe0vPWcmybv23W6pHWMJHA3ryKMCyRJDhmF6nF1vbcsmliy09ZyXLuvXfbqkeYYnWsifCMw6fwdcyx+Nxvl6vBYsDwF7shQCA5x0Ohx/zPB9//3Np2oGhRE9PvSepsNmL5w4YiQALGIqzXOB5zwZKnrs+CJRhGQEWMJQtBykaXDC6ZwMlB5iWtVffJFCGZSS5gJX22rdif0wZWzZYO8+K0T2bdENig7L26pskXYFlBFiw0l4vMoP5eEoNLgTT5FaqTQmUYtor8HH/YRkBFqy014vMl8J4Sg0uBNOfcgQFgtVP2tRYBD4QiwALVtrrReaFOY6WgumSAUyOoKBkYNFS8NZSmwLojQALoLKWgunohxOXDCxamhVqqU0B9EaABcBiJQOYHEFBycDCrBAASxzmeV78l4/H43y9XgsWBwAAIL7D4fBjnufj73/uHCwAAIBMBFgAABk4jBxISYAF/MYAAeA5t0Qo5/P5zz/Tp8J4BFgwqEcv/XsDBAC+dzqd0jRNvyRC0afCeGQRhEE9SjktUxrAc+5lsdSnwnhkEYRBtXRoKgBANI+yCJrBgkE5iBQAID97sAAAKpEEA/ojwIKOlXxxGxQAIyjd10mCAf0RYEHHSr64DQqgbT6SLFO6r7uXeTAS7QTWE2DBRpFfPiVf3NEHBVFEbh+MzUeSZZ7t65Y++7f9sFGTDWkn8IR5nhf/vLy8zMCvpmmaU0rzNE21i/K0y+UyT9M0Xy6X2kXpTg/tgz557stq6dn/qi1oJ/BYSuk634mZZBGEjb4646SVVOiPzsRiO2fgtKOV5zUXmUTLaunZ/+odoJ3AegIs2Oirl08rgUtLA4HWjDY4aTlIaeV5pQ0tPfveAZCXAAsKauWl1dJAgNhaDlJaeV4hN+8AyOvwuXxwmePxOF+v14LFAaBlLc9gAcAah8PhxzzPx9//3AwWANn4Eg7A6KRpBwAAyESAVYmzcQAA2mdMx+8EWJW0enCfToSttCGgBn0PpbQ6prvHc5KHPViVtJqtquUMYcSgDQE16HsopdUx3T2ekzwEWJW0uhG8p06EOrQhoAZ9D6W0Oqa7x3OShzTtAAAAKz1K024PFgAAQCYCLACAJ0kKAPxOgAV8yeAB4NO9/rCnDHJAHgIs4Eu/Dx4EXMCo7gVTp9MpTdMkKQDwJ1kEgS/9nlFICldgVPcyrPWUQQ7IwwwW8KXb4OH19TWl5GvtGmb7iE4bXef3/hDgHjNYwCq+1i5nto/otFGA/ARYAIU4sJHotFGA/CwRBCjEcqL2jLZkThsdz2htHGoQYAFNMChoQ+v3ScrtNrTezmrSxqE8SwShgo+Pj3Q+n9PpdPLleCF7RdrQ+n2yZK4NrbezmrRxKE+ABRUYHKxnUNCG1u+TJC5taL2dbbXlI502DuUd5nle/JePx+N8vV4LFgfGYAYLgGe9vb2l9/f3NE2TYAkqOhwOP+Z5Pv7+5/ZgQQVbNpbbewAwNucRQmyWCEJjLC8EGJtlfhCbAAsaM/reAwCAyARY0BhfLgEA4rIHCwDgv9nnCmxlBgsA4L/Z5wpsZQYLyMrXXyCqJf2TDH3AVgIsIKvb19/z+fzw7wjCgBqW9E9bjtEASEmABWS25OvvkkEOMJY9PryYnWqbj3O0QoAFZLXk62/JQU4rL+BWykkfWmhve3x4MTvVNh/naIUkF3Th4+Mjnc/ndDqdvDgbUDLVfCsb1FspJ31oob0544/vaCO0QoBFF1oYPLCPVl7ArZSTPrTQ3pzxx3e0EVphiSBdsK6em1aWALVSzr9qYZlZaa3WQYvtjTJabcPQEjNYdMFXLSjPTLE6oH3aMJQnwIJK7BujNS0sMytNHdA6bRjKO8zzvPgvH4/H+Xq9FiwOjOPt7S29v7+naZp8RQTojI9o0L/D4fBjnufj739uBgsq8RURoF+W4sG4JLmASiJuOrf5GRhJyT5P8iUYlwAL+FOpQxwFbsBfPdMnlOhHSh5cG/Ej2lb6clhGgAX8qdQX19yDmCiDM+A5z/QJJYIhs0zrlAxIoSvzPC/+eXl5mYGfLpfLPE3TfLlcahcltNz1NE3TnFKap2kq+t9Eo73RSxt45jp6ufaWuQfwq5TSdb4TMwmwYIMeBu0tGnVwlqO99VAPrcpR9/qcfXhOgCUeBViyCMIGMgHWseZg6b+mSm49k1eO9iazWT056r63PidqKnPPCbCFAAs2WDPQH0HEwVJPA6Uc7a23AXpLctR9b31O1OfTcwJs4aBhIJuIhydHDPqAT55PoGWPDhoWYAHZGCwBAKN4FGBZIghk09vyJQCAtZyDBQAAkIkACwAAIBMBFgAAQCYCLAAAgEyaC7A+Pj7S29tb+vj4qF0UAACAXzSXRTDqoYQAAADNBVhOVwcAAKJqLsByzg4AABBVc3uwAAAAohJgAQAAZCLAAniSrKa0bGn71c6BEeTs65rbgwUQxdKsph8fH+l8PqfT6ZReX1/3Kh58aWn7lb0XGEHOvk6ABfCkpVlNDVCJaGn7lb0XGEHOvu4wz/Piv3w8Hufr9br5lwKMxAwWrdOGAf7ucDj8mOf5+Puf24MF8KSl67Vvx0s8OzC1B4Z79mwXt1nY8/lc/HcBtM4SQYAn7bX0zxJD7tmzXVgmCLCcGSyAJ51OpzRNU/FB516/h7bs2S5qzsKawQVaYw8W0Lxn94fYVwL7eHt7S+/v72maptWzbVv+W4CSHu3BskQQaN6zS6UsvYN9bFliaHki0BpLBIHmPbtUarSld5ZaxRDlPuxZji1LDLcuTwTYmwALaN6zA7A9B24RBtUywcUQ5T5EKccaEZ4jgO8IsIAmtTbQijCYHW3GLqoo9+FeOaI/VxGeI4Dv2IMFNCny/ql7yTMi7CO5zdhRV5T7cK8ckZ+rlGI8RwDfEWABTYo80Lo3SI0yqIavRH6uUvIcAW2Qph0gM+nf++S+AvBXj9K024MFkFnvWc+i79Mpxf4f9jTqcwY9EGABsMqogUaU5BTUs2fQM+pzBj0QYEGnfP3sX617PGqgUXNm0vMcw55Bz6jPGfRAkgvo1F7ZwOxLqadWxjeJBvZ3u9f/+te/0r/927953irZMwmI5wzaJcCCTu01EIie1rlHt6D2P/7jP1JKcTO+RdfSx4HbPf7Xv/7leatI0AMsYYkgdGqv5UyWsezvFtT+13/9VxPJNKIub2tpj8vtef7P//zPrp63qG0DYAszWMAmLX3RbWnG4ivRzyr6XdRZztbqMaW2nrclorYNgC0EWMAwehnMtTbIjhrItFaPPYraNgC2sEQQGIbljMvlXLp1b7lqjaVhpX+n5W7r9X5mHDAmARYwDIO55UrvT6qx/6nHaxqJAPZ76ghiEGABzTOoyC/HbN9X96XGbOJXvzNHGzJDWpYA9nvqCIKY53nxz8vLywzUcblc5mma5svlUrso4UzTNKeU5mmaaheleTnbWUv3JXdZPa/5qdPvqSPYV0rpOt+JmSS5gEb0kqChBBvl88nZzlq6L7nL6nnNT1KS76kjiEGABY1oabC6N4OKfHK2s5buS+6yel4BxnX4nN1a5ng8ztfrtWBxAAAA4jscDj/meT7+/ueSXAAAAGQiwAIAAMhEgAUA/MmxBwDbSHIBAPxJBkSAbcxgARQy4kxAL9fcy3U8w4HJANuYwQIoZMSZgF6uuZfreMbvKes/Pj7S+XxOp9Mpvb6+ViwZQBsEWACZ/D4QHfEspF6uuZfryGHkYBPgGc7BAsjk7e0tvb+/p2maDETphhksgPsenYNlBgsgE7Me9Oj3JYMAfE2ABZCJgSgAIIsgAEMbOWMgAPmt2oN1OBz+n5TS/ylXHADY3f+dUvqfKaX/L6X0vyuXBYB2/F/zPP+v3/9wVYAFAADAY5YIAgAAZCLAAgAAyESABQAAkIkACwAAIBMBFgAAQCYCLAAAgEwEWAAAAJkIsAAAADIRYAEAAGTy/wM1xtHmfLy0GQAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.278437936550752 max: 400.25971627794144\n", + "image 1 reprojection errors: average:22.03190600363691 max: 272.0990808673007\n", + "image 2 reprojection errors: average:21.63574971852651 max: 326.8181215993555\n", + "image 3 reprojection errors: average:21.69301256883475 max: 179.0624228021027\n", + "image 4 reprojection errors: average:22.60648374913264 max: 329.51644216617495\n", + "image 5 reprojection errors: average:21.961239923829332 max: 381.0160429231665\n", + "image 6 reprojection errors: average:22.05561616144285 max: 251.00725103960175\n", + "image 7 reprojection errors: average:21.378856500094034 max: 239.22639530129806\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.2495e+06 6.41e+06 \n", + " 1 2 9.5121e+03 3.24e+06 6.19e+01 5.16e+05 \n", + " 2 3 3.5917e+03 5.92e+03 8.04e-01 4.62e+03 \n", + " 3 4 3.5802e+03 1.14e+01 3.48e-01 1.77e+03 \n", + " 4 5 3.5783e+03 1.95e+00 3.76e-02 1.16e+02 \n", + " 5 6 3.5782e+03 7.34e-02 3.57e-03 7.64e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 6, initial cost 3.2495e+06, final cost 3.5782e+03, first-order optimality 7.64e+01.\n", + "mean reprojection error: 0.8627458901483573\n", + "max reprojection error: 3.2596030427959573\n", + "mean reconstruction error: 0.05069181762604801\n", + "max reconstruction error: 0.24335889610412395\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:21.46626131274499 max: 163.336848866503\n", + "image 1 reprojection errors: average:21.82183410169516 max: 295.2519591176652\n", + "image 2 reprojection errors: average:22.160224570920704 max: 307.5248598399786\n", + "image 3 reprojection errors: average:21.97131115780974 max: 173.1604463990418\n", + "image 4 reprojection errors: average:21.924835432340235 max: 296.32578672675885\n", + "image 5 reprojection errors: average:23.006535436727653 max: 502.3450448032975\n", + "image 6 reprojection errors: average:22.437602894641014 max: 373.13411265950776\n", + "image 7 reprojection errors: average:21.702431156842717 max: 314.9124657045384\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.3853e+06 6.94e+06 \n", + " 1 2 4.0181e+04 3.35e+06 6.22e+01 8.71e+05 \n", + " 2 3 3.2191e+04 7.99e+03 8.64e-01 1.21e+04 \n", + " 3 4 3.2161e+04 3.06e+01 3.93e-01 4.07e+03 \n", + " 4 5 3.2153e+04 7.63e+00 6.51e-02 4.04e+02 \n", + " 5 6 3.2150e+04 2.62e+00 4.42e-02 3.24e+02 \n", + " 6 7 3.2149e+04 1.65e+00 2.34e-02 1.38e+02 \n", + " 7 8 3.2148e+04 5.69e-01 8.31e-03 7.97e+01 \n", + " 8 9 3.2148e+04 3.58e-01 6.53e-03 7.55e+01 \n", + " 9 10 3.2147e+04 3.47e-01 6.57e-03 7.65e+01 \n", + " 10 11 3.2147e+04 3.28e-01 6.15e-03 7.05e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 3.3853e+06, final cost 3.2147e+04, first-order optimality 7.05e+01.\n", + "mean reprojection error: 2.5913778949980473\n", + "max reprojection error: 10.678450174574559\n", + "mean reconstruction error: 0.15251383926160145\n", + "max reconstruction error: 0.6598931317609269\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.047464696832833 max: 140.05383280415856\n", + "image 1 reprojection errors: average:22.523210315755698 max: 515.6973840240647\n", + "image 2 reprojection errors: average:22.523683321587946 max: 284.6585150084286\n", + "image 3 reprojection errors: average:22.551442543273236 max: 253.15214075881588\n", + "image 4 reprojection errors: average:22.833583059855318 max: 227.63580981356534\n", + "image 5 reprojection errors: average:21.881078104981718 max: 164.39351529709896\n", + "image 6 reprojection errors: average:21.91898738464048 max: 238.77101270429702\n", + "image 7 reprojection errors: average:22.17538263137715 max: 213.71108232178273\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.2111e+06 6.10e+06 \n", + " 1 2 9.3293e+04 3.12e+06 6.29e+01 5.37e+05 \n", + " 2 3 8.8525e+04 4.77e+03 7.54e-01 9.79e+03 \n", + " 3 4 8.8466e+04 5.85e+01 5.08e-01 9.46e+03 \n", + " 4 5 8.8448e+04 1.82e+01 1.15e-01 2.53e+03 \n", + " 5 6 8.8443e+04 5.19e+00 5.14e-02 1.29e+03 \n", + " 6 7 8.8439e+04 3.70e+00 3.93e-02 7.44e+02 \n", + " 7 8 8.8437e+04 2.45e+00 2.60e-02 4.98e+02 \n", + " 8 9 8.8436e+04 1.25e+00 1.14e-02 1.91e+02 \n", + " 9 10 8.8435e+04 7.49e-01 9.22e-03 1.33e+02 \n", + " 10 11 8.8434e+04 7.14e-01 8.51e-03 1.08e+02 \n", + " 11 12 8.8433e+04 6.75e-01 8.43e-03 1.32e+02 \n", + " 12 13 8.8433e+04 6.36e-01 7.64e-03 9.23e+01 \n", + " 13 14 8.8432e+04 5.96e-01 7.48e-03 1.44e+02 \n", + " 14 15 8.8432e+04 5.66e-01 6.90e-03 9.19e+01 \n", + " 15 16 8.8431e+04 5.29e-01 6.69e-03 1.65e+02 \n", + " 16 17 8.8431e+04 5.10e-01 6.27e-03 1.15e+02 \n", + " 17 18 8.8430e+04 4.46e-01 5.38e-03 1.76e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 18, initial cost 3.2111e+06, final cost 8.8430e+04, first-order optimality 1.76e+02.\n", + "mean reprojection error: 4.284849430897322\n", + "max reprojection error: 16.778716726358464\n", + "mean reconstruction error: 0.247597565621731\n", + "max reconstruction error: 1.133533261382152\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:23.587050315416917 max: 227.2639566229149\n", + "image 1 reprojection errors: average:23.764697599180483 max: 366.6758822811075\n", + "image 2 reprojection errors: average:23.36663224179087 max: 158.2538863541532\n", + "image 3 reprojection errors: average:24.089726510516183 max: 276.448463457859\n", + "image 4 reprojection errors: average:23.57341724862648 max: 172.83922526363867\n", + "image 5 reprojection errors: average:24.23354665642377 max: 485.4172174635731\n", + "image 6 reprojection errors: average:24.088121870396005 max: 225.2020802786197\n", + "image 7 reprojection errors: average:23.45682510119552 max: 316.8115091345833\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.4383e+06 4.53e+06 \n", + " 1 2 3.5665e+05 3.08e+06 6.42e+01 1.29e+06 \n", + " 2 3 3.4658e+05 1.01e+04 8.57e-01 3.25e+04 \n", + " 3 4 3.4638e+05 2.03e+02 9.17e-01 1.54e+04 \n", + " 4 5 3.4632e+05 6.43e+01 1.60e-01 1.51e+03 \n", + " 5 6 3.4629e+05 2.11e+01 1.12e-01 4.75e+02 \n", + " 6 7 3.4628e+05 1.56e+01 6.73e-02 3.26e+02 \n", + " 7 8 3.4627e+05 8.50e+00 4.70e-02 3.43e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 8 9 3.4627e+05 4.37e+00 1.76e-02 1.64e+02 \n", + " 9 10 3.4626e+05 3.59e+00 2.47e-02 3.25e+02 \n", + " 10 11 3.4626e+05 3.03e+00 1.33e-02 1.39e+02 \n", + " 11 12 3.4626e+05 2.96e+00 2.19e-02 3.15e+02 \n", + " 12 13 3.4625e+05 2.92e+00 1.29e-02 1.35e+02 \n", + " 13 14 3.4625e+05 2.87e+00 2.14e-02 3.00e+02 \n", + " 14 15 3.4625e+05 2.80e+00 1.25e-02 1.37e+02 \n", + " 15 16 3.4624e+05 2.50e+00 1.88e-02 2.63e+02 \n", + " 16 17 3.4624e+05 2.52e+00 1.17e-02 1.74e+02 \n", + " 17 18 3.4624e+05 2.12e+00 1.53e-02 2.95e+02 \n", + " 18 19 3.4624e+05 2.26e+00 1.11e-02 2.24e+02 \n", + " 19 20 3.4624e+05 1.05e+00 6.20e-03 2.32e+02 \n", + " 20 21 3.4624e+05 7.34e-01 4.26e-03 1.73e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 21, initial cost 3.4383e+06, final cost 3.4624e+05, first-order optimality 1.73e+02.\n", + "mean reprojection error: 8.477722514320375\n", + "max reprojection error: 32.10472616678254\n", + "mean reconstruction error: 0.5003356031509274\n", + "max reconstruction error: 2.0968856047892146\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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xe/ZsevToQXJyMpmZmaUeg5I453j77bcLEpEJEyawYsWKYuX+9re/MWTIEJo1a8Y555zDkCFDeOONN6LeTl5eHr/+9a9JTk4mJSWFRx99tGB/Zs6cSb9+/ejVqxebN29m6NChXHDBBSxYsOC09q00SmZERKSYffv20aZNm4Lp+Ph49u3bV6zct99+S48ePdi8eTMDBw5kzpw5hZY3adKE+fPnk5qaynPPPcdXX33FpEmTWLVqFbt27WLDhg1s3bqVTZs2sXbt2ojxZGRksHz5cj744AO2bt1K7dq1eeaZZwpi6Nq1K2lpaVxyySWFpuvXr8+SJUtIS0tj/fr1PPHEE2zZsgWArKwsxo8fz5YtW2jbti3Dhw9n//79Ybd/1llnsXbtWqZMmcLIkSN57LHH2LFjB0uXLuXw4cMlxnfvvfeSnp7Otm3bePfdd9m2bVtBvc2bN2fz5s1MnTqVBx98sNh2s7KyCi75FH0dOXKkUNnDhw/TtGlT6tSpU+I5K+3c3nHHHaSkpDBt2jROnDhRbP2FCxeye/dutmzZwrZt2xg3blzBsjZt2rBu3Tr69+9fkNCuX7+eWbNmhT2uFUWXmUREpBjnXLF54e4wqVWrFmPGjAHg5z//OaNHjy5WZsiQIbzwwgvcfPPNfPTRRwCsWrWKVatW0b17dwCOHTvGrl27GDBgQNh43nrrLTZt2kTv3r0B+O6772jRogUAtWvX5qc//WlB2dDp999/n1GjRtGgQQMARo8ezXvvvceIESNo27Ytffv2LVjv9ddfj3g8RowYAUBycjJdunShVatWAHTo0IHPP/+c999/P2J8zz//PAsXLiQ3N5fs7Gx27txJSkpKQTwAPXv25KWXXiq23YSEhKj7rUR7zkoqd//999OyZUtOnjzJjTfeyLx584olIqtXr2bKlCkFSVNoK1/ocTp27BiNGjWiUaNG1KtXjyNHjtC0adOo9qWslMyIiEgx8fHxhS697N27l9atW5e6Xrgfz1OnTpGRkUH9+vXJyckhPj4e5xy33347kydPjioe5xwTJkzg/vvvL7asXr16hfrFhE6H++HOl5/gRCMuLg7wkrf89/nTubm5EePbvXs3Dz74IBs3buScc84hNTW10PNT8uuqXbs2ubm5xbablZVVkCwWtWbNmkLJQfPmzTly5Ai5ubnUqVMn4jmLj49nzZo1BdN79+5l0KBBAAVJWlxcHBMnTgzbWuSci3jrdGnHKVaUzIiIVKKd2Uej7rgbTV2dWzWukLpGjBjB/PnzGTt2LGlpaTRp0qTghy7UqVOnePHFFxk7dizPPvssl1xySbEyDz/8MElJSdx3331cd911rFu3jqFDh/K73/2OcePG0bBhQ/bt20fdunULWjOKGjx4MCNHjmTatGm0aNGCnJwcvvnmG9q2bVvifgwYMIDU1FRmzJiBc46XX36Zp556qnwHpQSR4jt69CgNGjSgSZMmHDx4kJUrVxYkDtEoS8uMmXHppZcWnI9ly5YxcuTIYuWGDh3KzJkz+eqrrwCvlSw/CcvOzqZVq1Y451ixYkXYO94uu+wyFixYwKBBg6hTpw45OTml9sGKNSUzFWjehnlk5pS9A1dis0Sm95keg4hEpCrr3LpiEo+C+lo1jqrOa665hjVr1vDll18SHx/PnDlzuP766ws6aU6ZMoXhw4fz+uuv07FjR84++2yWLFkStq4GDRrw8ccf07NnT5o0acLy5csLLf/kk09YtGgRGzZsoFGjRgwYMIB77rmHOXPmkJGRQb9+3p1cDRs25Omnn46YzHTu3Jl77rmHyy67jFOnTlG3bl0ee+yxUpOZHj16kJqaSp8+fQC44YYb6N69O3v27ClWdvjw4SxatCiqFqho4+vbty/du3enS5cudOjQgYsvvrjMdZfFvHnzGDt2LHfeeSfdu3fn+uuvByA9PZ0FCxawaNEimjVrxu9+97uCS2KzZs0qSEbGjRvHoUOHcM7RrVu3sB13b7jhBj755BNSUlKoW7cukyZN4pZbbonpfpXGSmqCO1N69erl0tPTKzuM0zbxjYlk5WSR0Cwh6nXyyy8ZFv4/ChGpXjIyMkhKSqrsMCpMw4YNOXbsWGWHIdVQuO+KmW1yzvUqWlYtMxWsrInJxDcmxjAaERGR6k+3ZouISLmpVUaqAiUzIiIiEmg16jJT0UHdNCCbiIhI8NWoZCZ/ULfOrRpX6OBuIiIiUnlqVDID/xrUraKe6yAiUm4rZ8CB7RVbZ8tkuHxuxdYpUsWpz4yISGU5sL1ik5ko6jt+/Dh9+vThwgsvLDbwYSjnHLfeeisdO3YkJSWFzZs3lymUWbNmsXr16jKtk69hw4blWk+8Jw5fdNFFdOrUiTFjxnDy5Mmw5YYNG0bTpk35yU9+Umh+amoq7du3Lxj/KdoH9lW2GtcyIyJSpbRMhomvVUxdS64otUhcXBxvv/02DRs25Pvvv+eSSy7h8ssvLzRGEcDKlSvZtWsXu3btIi0tjalTp5KWlhZ1KHfffXeZw68IeXl5hYY2KDodjnMO5xy1agX/7/vp06czbdo0xo4dy5QpU1i8eDFTp04tVu43v/kN//znP3n88ceLLXvggQcKRt4OiuCfORERiZqZFbR8fP/993z//fdhx9l55ZVXGD9+PGZG3759OXLkCNnZ2cXKNWzYkNtuu40ePXowePBgDh06BFAwYvLXX39NQkICWVlZgPf04SeeeALwfjR79+5NSkpKxBaiUE8//TR9+vShW7duTJ48mby8vIIYZs2axUUXXcS6deuKTT/00EN07dqVrl278sgjjwCwZ88ekpKSuOmmm+jRo0ehcaiKGjRoENOmTWPAgAEkJSWxceNGRo8eTadOnbjzzjtLjW/q1Kn06tWrWEtYu3btmD17Nj169CA5OZnMzLI/QT6Uc4633367IBGZMGECK1asCFt28ODBNGrUqFzbycvL49e//jXJycmkpKTw6KOPAt7+zJw5k379+tGrVy82b97M0KFDueCCC8I+SbgiKZkREalh8vLy6NatGy1atGDIkCFcdNFFxcrs27ePNm3aFEzHx8ezb9++YuW+/fZbevTowebNmxk4cCBz5swptLxJkybMnz+f1NRUnnvuOb766ismTZrEqlWr2LVrFxs2bGDr1q1s2rSJtWvXRow5IyOD5cuX88EHH7B161Zq167NM888UxBD165dSUtL45JLLik0Xb9+fZYsWUJaWhrr16/niSeeYMuWLYA3iOP48ePZsmULbdu2Zfjw4ezfvz/s9s866yzWrl3LlClTGDlyJI899hg7duxg6dKlHD58uMT47r33XtLT09m2bRvvvvsu27ZtK6i3efPmbN68malTp4Yd1DErK6vgkk/R15EjRwqVPXz4ME2bNi0YzTrSOSvNHXfcQUpKCtOmTePEiRPFli9cuJDdu3ezZcsWtm3bxrhx4wqWtWnThnXr1tG/f/+ChHb9+vXFRt6uaKVeZjKzNsCTQEvgFLDQOfefZnYXMAk45Bed6Zx73V/nduB6IA+41Tn3txjEftryB3jTLdoiUpPUrl2brVu3cuTIEUaNGsWOHTuKDSgYbqibcC04tWrVKhjV+ec//zmjR48uVmbIkCG88MIL3HzzzXz00UeAN7jhqlWr6N69O+A9fG/Xrl0MGDAgbMxvvfUWmzZtKhhP6LvvvisYx6l27dr89Kc/LbR/+dPvv/8+o0aNKhghe/To0bz33nuMGDGCtm3bFrq89vrrr4fdNngDbwIkJyfTpUuXgkE3O3TowOeff877778fMb7nn3+ehQsXkpubS3Z2Njt37iQlJaUgHoCePXvy0ksvFdtuWQaajPacleT++++nZcuWnDx5khtvvJF58+YVS0RWr17NlClTCpKm0EEmQ4/TsWPHaNSoEY0aNaJevXocOXKk0CjfFSmaPjO5wG3Ouc1m1gjYZGZv+sseds4VSiXNrDMwFugCtAZWm9mPnHN5FRn46cofjE23aItITdW0aVMGDRrEG2+8USyZiY+PL3TpZe/evVENwBjux/PUqVNkZGRQv359cnJyiI+PxznH7bffzuTJk6OK1TnHhAkTCkZ3DlWvXr1C/WJCp0safzA/wYlGXFwc4CVv+e/zp3NzcyPGt3v3bh588EE2btzIOeecQ2pqKsePHy9Wb+3atcnNzS223aysrIJksag1a9YUSg6aN2/OkSNHyM3NpU6dOlGfs1D5SVpcXBwTJ04M21rknIuYJJV2nGKl1GTGOZcNZPvvvzGzDOD8ElYZCTznnDsB7DazT4E+QJW6Fzq/JUa3aItIpTqwPaqOu1HX1TK5xCKHDh2ibt26NG3alO+++47Vq1czffr0YuVGjBjB/PnzGTt2LGlpaTRp0qTghy7UqVOnePHFFxk7dizPPvssl1xySbEyDz/8MElJSdx3331cd911rFu3jqFDh/K73/2OcePG0bBhQ/bt20fdunUjjpo9ePBgRo4cybRp02jRogU5OTl88803pY6aPWDAAFJTU5kxYwbOOV5++WWeeuqpEtcpj0jxHT16lAYNGtCkSRMOHjzIypUrGTRoUNT1lqVlxsy49NJLC87HsmXLGDlyZJn2Izs7m1atWuGcY8WKFcWSXIDLLruMBQsWMGjQIOrUqUNOTk6h1pnKUKa7mcysHdAdSAMuBm4xs/FAOl7rzVd4ic76kNX2Eib5MbMbgRsBfvjDH5YndhGRYCsl8ShXfaXUmZ2dzYQJE8jLy+PUqVP87Gc/K7g9N7+T5pQpUxg+fDivv/46HTt25Oyzz2bJkvAD6DZo0ICPP/6Ynj170qRJE5YvX15o+SeffMKiRYvYsGEDjRo1YsCAAdxzzz3MmTOHjIwM+vXrB3ideJ9++umIyUznzp255557uOyyyzh16hR169blscceKzWZ6dGjB6mpqfTp0weAG264ge7du7Nnz55iZYcPH86iRYvK3JpRUnx9+/ale/fudOnShQ4dOnDxxReXue6ymDdvHmPHjuXOO++ke/fuXH/99QCkp6ezYMECFi1aBED//v3JzMzk2LFjxMfHs3jxYoYOHcq4ceM4dOgQzjm6desWtuPuDTfcwCeffEJKSgp169Zl0qRJ3HLLLTHdr9JYSU1whQqaNQTeBe51zr1kZj8AvgQc8B9AK+fcdWb2GLDOOfe0v95i4HXn3J8j1d2rVy+Xnp5+mrtSuvxWmOWT+5U4r7zyR8Auz6jZZVlHRIIrIyODpKSkyg6jwjRs2FCDTUpMhPuumNkm51yvomWjupvJzOoCfwaecc69BOCcO+icy3POnQKewLuUBF5LTJuQ1eOB8N3DRURERE5TqcmMeb18FgMZzrmHQuaHXjwdBezw3/8FGGtmcWbWHugEbKi4kEVEpKpQq4xUBdH0mbkYuBbYbmZb/XkzgWvMrBveZaY9wGQA59zHZvY8sBPvTqibq9qdTCIiIlJ9RHM30/tAuHuwIt6Q75y7F7j3NOISERERiYqeACwiIiKBpoEmRUQqybwN88jMOb3xeIpKbJbI9D7FnxsjUp2pZUZEpJJk5mSSlZNVYfVl5WRFlRy1a9eO5ORkunXrRq9exe5yBbynvN5666107NiRlJQUNm/eXKZYZs2axerVq8u0Tr78gTCl7Hbv3s1FF11Ep06dGDNmDCdPnixWZuvWrfTr148uXbqQkpJS6NlAqamptG/fvmD8p2gf2FfZ1DITjZUzvCdrRtIyGS6fe+biEZFqI6FZQoU9Zyr/uVXReOedd2jevHnE5StXrmTXrl3s2rWLtLQ0pk6dSlpaWtT133333VGXrUh5eXmFhjYoOh2Ocw7nHLVqBf/v++nTpzNt2jTGjh3LlClTWLx4MVOnTi1U5uyzz+bJJ5+kU6dO7N+/n549ezJ06NCCoREeeOCBgpG3gyL4Z+5MOLA9cjJT0jIRkYB65ZVXGD9+PGZG3759OXLkCNnZ2cXKNWzYkNtuu40ePXowePBgDh3yxh7OHzH566+/JiEhgawsrwXqmmuu4YknngC8H83evXuTkpLC7NmzS43p6aefpk+fPnTr1o3JkyeTl5dXEMOsWbO46KKLWLduXbHphx56iK5du9K1a1ceeeQRAPbs2UNSUhI33XQTPXr0KDQOVVGDBg1i2rRpDBgwgKSkJDZu3Mjo0aPp1KkTd955Z6nxTZ06lV69etGlS5dC+9muXTtmz55Njx49SE5OJjPz9C45Oud4++23CxKRCRMmsGLFimLlfvSjH9GpUycAWrduTYsWLQrOWzTy8vL49a9/TXJyMikpKTz66KMF+zNz5kz69etHr1692Lx5M0OHDuWCCy4I+yThiqRkJlotk2Hia8VfFf04chGRGDMzLrvsMnr27MnChQvDltm3bx9t2vzr+afx8fHs27evWLlvv/2WHj16sHnzZgYOHMicOXMKLW/SpAnz588nNTWV5557jq+++opJkyaxatUqdu3axYYNG9i6dSubNm1i7dq1EWPOyMhg+fLlfPDBB2zdupXatWvzzDPPFMTQtWtX0tLSuOSSSwpN169fnyVLlpCWlsb69et54okn2LJlC+AN4jh+/Hi2bNlC27ZtGT58OPv3h3/G61lnncXatWuZMmUKI0eO5LHHHmPHjh0sXbqUw4cPlxjfvffeS3p6Otu2bePdd99l27ZtBfU2b96czZs3M3Xq1LCDOmZlZRVc8in6OnLkSKGyhw8fpmnTpgWjWUc6Z6E2bNjAyZMnueCCCwrm3XHHHaSkpDBt2jROnDhRbJ2FCxeye/dutmzZwrZt2xg3blzBsjZt2rBu3Tr69+9fkNCuX7++2MjbFU2XmUREapgPPviA1q1b88UXXzBkyBASExMZMGBAoTLhhroJN1JyrVq1CkZ1/vnPf87o0aOLlRkyZAgvvPACN998Mx999BEAq1atYtWqVXTv3h3wHr63a9euYnHke+utt9i0aRO9e/cG4LvvvisYx6l27dr89Kc/LSgbOv3+++8zatSoghGyR48ezXvvvceIESNo27Ytffv2LVjv9dcjPnGEESNGAJCcnEyXLl0KBt3s0KEDn3/+Oe+//37E+J5//nkWLlxIbm4u2dnZ7Ny5k5SUlIJ4AHr27MlLL71UbLtlGWgy2nOWLzs7m2uvvZZly5YVXGK7//77admyJSdPnuTGG29k3rx5xRKR1atXM2XKlIKkKXSQydDjdOzYMRo1akSjRo2oV68eR44cKTTKd0VSMiMiUsPkD6TYokULRo0axYYNG4olEfHx8YUuvezduzeqARjD/XieOnWKjIwM6tevT05ODvHx8TjnuP3225k8eXJUMTvnmDBhAvfff3+xZfXq1SvULyZ0uqTxB/MTnGjExcUBXvKW/z5/Ojc3N2J8u3fv5sEHH2Tjxo2cc845pKamcvz48WL11q5dm9zc3GLbzcrKKkgWi1qzZk2h5KB58+YcOXKE3Nxc6tSpU+I5O3r0KFdccQX33HNPoYQuP0mLi4tj4sSJYVuLnHMRk6TSjlOsKJkREalEWTlZZeq4W1pdCc0SSizz7bffcurUKRo1asS3337LqlWrwl4CGDFiBPPnz2fs2LGkpaXRpEmTgh+6UKdOneLFF19k7NixPPvss1xyySXFyjz88MMkJSVx3333cd1117Fu3TqGDh3K7373O8aNG0fDhg3Zt28fdevWjThq9uDBgxk5ciTTpk2jRYsW5OTk8M0335Q6avaAAQNITU1lxowZOOd4+eWXeeqpp0pcpzwixXf06FEaNGhAkyZNOHjwICtXrmTQoEFR11uWlhkz49JLLy04H8uWLWPkyJHFyp08eZJRo0Yxfvx4rr766kLLsrOzadWqFc45VqxYQdeuXYutf9lll7FgwQIGDRpEnTp1yMnJKdQ6UxmUzIiIVJLEZokVWl9Cs4RS6zx48CCjRo0CIDc3l3//939n2LBhAAWdNKdMmcLw4cN5/fXX6dixI2effTZLloS/46pBgwZ8/PHH9OzZkyZNmhS6zRfgk08+YdGiRWzYsIFGjRoxYMAA7rnnHubMmUNGRgb9+vUDvE68Tz/9dMRkpnPnztxzzz1cdtllnDp1irp16/LYY4+Vmsz06NGD1NRU+vTxxkK+4YYb6N69O3v27ClWdvjw4SxatCiqFqho4+vbty/du3enS5cudOjQgYsvvrjMdZfFvHnzGDt2LHfeeSfdu3fn+uuvByA9PZ0FCxawaNEinn/+edauXcvhw4dZunQpAEuXLqVbt26MGzeOQ4cO4ZyjW7duYTvu3nDDDXzyySekpKRQt25dJk2axC233BLT/SqNldQEd6b06tXLpaenx3w7Yx5fB8Dyyf1KnFfMkiu8fye+VuKy/L+uynKbZXnWEZHgysjIICkpqbLDqDANGzbUYJMSE+G+K2a2yTlX7OFIuptJREREAk2XmQLgwH33cSKjYh95XlRcUiItZ86M6TZEpPpRq4xUBWqZCYATGZkcP82HKZXkeGZmzJMlERGRWFHLTEDUS0yk7VNPxqTuz64dH5N6RUREzgQlMyUoGNHWDnozwt0+GbIsmtsiRUREpGIpmSlB/oi20aYn0dwWKSKSLxb94dT/TWoi9ZkpRUKzBJa4H3ivYUuKv4osm95nemWHLCIBUdH94aLt/3bdddfRokWLYg9Ey8nJYciQIXTq1IkhQ4bw1VdfhV3/jTfeICEhgY4dOzJ37twyxZiens6tt95apnXy5Y/1I2XnnOPWW2+lY8eOpKSksHnz5rDlUlNTad++fcH4T/kP7It2/cqilhlgwtcLYMk9xRfkX0I68IUGlBSRmKjI/nDR9n9LTU3llltuYfz4wuXnzp3L4MGDmTFjBnPnzmXu3LnMmzevUJm8vDxuvvlm3nzzTeLj4+nduzcjRoygc+fOUW27V69e9OpV7DEhMZf/iP9I09GuF1QrV65k165d7Nq1i7S0NKZOnUpaWlrYsg888EDByNvlWb8yqGUGaJv7dziwPXKBlslKZkSk2hgwYEDYx8+/8sorTJgwAYAJEyawYsWKYmU2bNhAx44d6dChA2eddRZjx47llVdeKVYuNTWVKVOm0L9/f370ox/x17/+FfDGE/rJT34CwK233srdd98NwN/+9jcGDBjAqVOn2LRpEwMHDqRnz54MHTqU7OzsEvfn73//O8OGDaNnz57079+fTL+1KzU1lV/96ldceumlTJ8+vdj01q1b6du3LykpKYwaNaqgJWrQoEHMnDmTgQMH8p//+Z8Rt7t06VKuuuoqrrzyStq3b8/8+fN56KGH6N69O3379iUnJ6fE+F599VUuuugiunfvzo9//GMOHvT+gL7rrru47rrrGDRoEB06dOC//uu/Stz/aLzyyiuMHz8eM6Nv374cOXKk1ONanvXfeOMNevTowYUXXsjgwYML9mfChAlcdtlltGvXjpdeeonf/va3JCcnM2zYML7//vvT3r/gp5sVpWVy8Sf85nf41dN5RaQGOHjwYMH4S61ateKLL74oVmbfvn20adOmYDo+Pj7iX+h79uzh3Xff5e9//zuXXnopn376aaHlc+fOpXfv3vTv359bb72V119/nby8PH7xi1/wyiuvcN5557F8+XLuuOMO/vSnP0WM+8Ybb2TBggV06tSJtLQ0brrpJt5++23AG05h9erV1K5dm9TU1ELTKSkpPProowwcOJBZs2YxZ84cHnnkEQCOHDnCu+++CxQe5qGoHTt2sGXLFo4fP07Hjh2ZN28eW7ZsYdq0aTz55JP88pe/jBjfJZdcwvr16zEzFi1axO9//3v+8Ic/AJCZmck777zDN998Q0JCAlOnTqVu3bqFtj1mzBiysrKKxfSrX/2qWKtbuPO2b9++sONt3XHHHdx9990MHjyYuXPnEhcXF9X6hw4dYtKkSaxdu5b27dsXJHPgJXTvvPMOO3fupF+/fvz5z3/m97//PaNGjeK1117jqquuKn5iy0DJjIiIRC3cEDiRRlD+2c9+Rq1atejUqRMdOnQoaJHId/bZZ/PEE08wYMAAHn74YS644AJ27NjBjh07GDJkCOBd1gr3g5vv2LFjfPjhh4UGTDxx4kTB+6uvvrrQiNr5019//TVHjhxh4MCBgNcSFVpH6EjV4ZKYfJdeeimNGjWiUaNGNGnShCuvvBKA5ORktm3bVmJ8e/fuZcyYMWRnZ3Py5Enat29fUOaKK64gLi6OuLg4WrRowcGDB4mPjy+07aLjYJUk2vN2//3307JlS06ePMmNN97IvHnzmDVrVlTrr1+/ngEDBhTsR2jr3+WXX07dunVJTk4mLy+vYDyw5OTksONklZWSGRERAeAHP/hBwajJ2dnZYQd9jI+P5/PPPy+Y3rt3b8SBGYv+2IX78dy+fTvnnnsu+/fvB7wf3S5durBu3bqoYj516hRNmzaNOLJ0gwYNSpyOJNpycXFxBe9r1apVMF2rVi1yc3NLjO8Xv/gFv/rVrxgxYgRr1qzhrrvuCltv7dq1yc3NLbZ+WVpmoj1v+YljXFwcEydO5MEHH4x6fedcxMQ29LjUrVu3oFz+cTpdSmZERCrR8czMCntw5fHMTOollv/xECNGjGDZsmXMmDGDZcuWMXLkyGJlevfuza5du9i9ezfnn38+zz33HM8++2zY+l544QUmTJjA7t27+cc//kFCQgLr168vWP7ZZ5/xhz/8gS1btjB8+HCuuuoqunfvzqFDh1i3bh39+vXj+++/55NPPqFLly5ht9G4cWPat2/PCy+8wNVXX41zjm3btnHhhReWuK9NmjThnHPO4b333qN///489dRTBa00Famk+L7++mvOP/98AJYtW1bmusvSMjNixAjmz5/P2LFjSUtLo0mTJmFbvPKTWeccK1asKLjjLZr1+/Xrx80338zu3bsLLjOF65sVC+oALCJSSeKSEk8r+SiqXmIicUml13fNNdfQr18/srKyiI+PZ/HixQDMmDGDN998k06dOvHmm28yY8YMAPbv38/w4cMBqFOnDvPnz2fo0KEkJSXxs5/9LGKikZCQwMCBA7n88stZsGAB9erVK1jmnOP666/nwQcfpHXr1ixevJgbbriBU6dO8eKLLzJ9+nQuvPBCunXrxocfflji/jzzzDMsXryYCy+8kC5duoTtkBzOsmXL+M1vfkNKSgpbt25l1qxZYcstWLCgoN9MeUSK76677uLqq6+mf//+NG/evNz1R2P48OF06NCBjh07MmnSJP74xz8WWpbfMjZu3DiSk5NJTk7myy+/5M477yx1/XznnXceCxcuZPTo0Vx44YWFLtXFmoW7Dnam9erVy6Wnp8d8O2Me95otl0/uV2jerMO/oUurJsU6AE/0OwAvKakD8JIr/MKvRS5Tgmi2kf9XW6yHM4hV/SLyLxkZGSQlJVV2GDGXmprKT37yk2K3+IpEK9x3xcw2OeeK3duvlhkREREJNPWZERGRCrd06dLKDkFqELXMiIicYVXh8r5IVVbW74iSGRGRM6hevXocPnxYCY1IBM45Dh8+XKjDeGl0mUlE5AyKj49n7969HDp0qLJDEamy6tWrV+whgSVRMiMicgbVrVu30JNeReT06TKTiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCrU5lByCQlZPFxDcmRlw+NicTgLtCyiQ2S2R6n+kxj01ERKSqK7VlxszamNk7ZpZhZh+b2f/z5zczszfNbJf/7zkh69xuZp+aWZaZDY3lDgRdYrNEEpollGmdrJwsMv0ER0REpKaLpmUmF7jNObfZzBoBm8zsTSAVeMs5N9fMZgAzgOlm1hkYC3QBWgOrzexHzrm82OxCsEXTuvLZM+MBWDJsCUCJrTgiIiI1TaktM865bOfcZv/9N0AGcD4wEljmF1sGXOW/Hwk855w74ZzbDXwK9KnguEVERESAMnYANrN2QHcgDfiBcy4bvIQHaOEXOx/4PGS1vf48ERERkQoXdTJjZg2BPwO/dM4dLalomHkuTH03mlm6maUfOnQo2jBERERECokqmTGzuniJzDPOuZf82QfNrJW/vBXwhT9/L9AmZPV4YH/ROp1zC51zvZxzvc4777zyxi8iIiI1XDR3MxmwGMhwzj0UsugvwAT//QTglZD5Y80szszaA52ADRUXsoiIiMi/RHM308XAtcB2M9vqz5sJzAWeN7Prgf8FrgZwzn1sZs8DO/HuhLpZdzKJiIhIrJSazDjn3id8PxiAwRHWuRe49zTiEhEREYmKhjMQERGRQFMyIyIiIoGmZEZEREQCTQNNCgDHMzP57NrxMas/LimRljNnxqx+ERGpuZTMCHFJiTGt/3imBsUUEZHYUTIjMW8xiWWLj4iIiPrMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKDpCcAV5MB993EiIzaP7T+emUm9xNgOOSAiIhJUapmpICcyMmM2BlG9xMSYj58kIiISVGqZAf55Mo+Ps7/m7sfX0bl1Y2Zf2aVc9dRLTKTtU09WcHQiIiJSkhqfzHRu3ZizD9cGYGf20UqORkRERMqqxiczs6/sAl82AaDzycaVHI2IiIiUlfrMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAKtxg80WSEObIcD53rvl1xRfHnLZLh87pmNSUREpIZQMnO6Wib7b/aHX35g+xkLRUREpCZSMnO68ltc3h7v/TvxycLLw7XUiIiISIVRnxkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAq3UZMbM/mRmX5jZjpB5d5nZPjPb6r+Ghyy73cw+NbMsMxsaq8BFREREILqWmaXAsDDzH3bOdfNfrwOYWWdgLNDFX+ePZla7ooIVERERKarUZMY5txbIibK+kcBzzrkTzrndwKdAn9OIT0RERKREp9Nn5hYz2+ZfhjrHn3c+8HlImb3+vGLM7EYzSzez9EOHDp1GGCIiIlKTlTeZ+W/gAqAbkA38wZ9vYcq6cBU45xY653o553qdd9555QxDREREarpyJTPOuYPOuTzn3CngCf51KWkv0CakaDyw//RCFBEREYmsXMmMmbUKmRwF5N/p9BdgrJnFmVl7oBOw4fRCFBEREYmsTmkFzOx/gEFAczPbC8wGBplZN7xLSHuAyQDOuY/N7HlgJ5AL3Oycy4tJ5EFyYDssuSL8spbJcPncMxuPiIhINVJqMuOcuybM7MUllL8XuPd0gqpWWiZHXnZg+5mLQ0REpJoqNZmR01RSq0uk1ppq6HhmJp9dOz4mdcclJdJy5syY1C0iIlWfkhmJubikxJjVfTwzM2Z1i4hIMCiZkZiLZatJrFp7REQkODTQpIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpufMBFRWThYT35hYpnUSmyUyvc/0GEUkIiJSOZTMBFBis7I/UTcrJysGkYiIiFQ+JTMBVJ7WlbK24oiIiASF+syIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoOkJwEXszD7KmMfXAfBFw29pd26DSo5IRERESqJkJkTn1o0L3u/MPsrZbfMqMRoRERGJhpKZELOv7FLwfszj69hTeaGIiIhIlNRnRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0HQ3kwTe8cxMPrt2fMzqj0tKpOXMmTGrX0RETo+SGQm0uKTEmNZ/PDMzpvWLiMjpUzIjgRbrFpNYtviIiEjFUJ8ZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmSnBP0/ksjP7KGMeX8ecVz+u7HBEREQkjDqVHUBV1bl1Y/Z86R2endlHKzkaERERiUTJTASzr+zCnjcaA/DPk40rORoRERGJRJeZREREJNBKTWbM7E9m9oWZ7QiZ18zM3jSzXf6/54Qsu93MPjWzLDMbGqvARURERCC6lpmlwLAi82YAbznnOgFv+dOYWWdgLNDFX+ePZla7wqIVERERKaLUPjPOubVm1q7I7JHAIP/9MmANMN2f/5xz7gSw28w+BfoA6yoo3jKb8+rH7NzvdeDdmX2Uzq3U/0VERKQ6KW+fmR8457IB/H9b+PPPBz4PKbfXn1eMmd1oZulmln7o0KFyhlG6nfuPFtyN1LlVYzq3VjIjIiJSnVT03UwWZp4LV9A5txBYCNCrV6+wZSpK51aNWT65Xyw3ISIiIpWkvC0zB82sFYD/7xf+/L1Am5By8cD+8ocnIiIiUrLyJjN/ASb47ycAr4TMH2tmcWbWHugEbDi9EEVEREQiK/Uyk5n9D15n3+ZmtheYDcwFnjez64H/Ba4GcM59bGbPAzuBXOBm51xejGIXERERiepupmsiLBocofy9wL2nE1SNcmA7LLki/LKWyXD53DMbj4iISMBoOIPK1DI58rID289cHCIiIgGmZKYyldTqEqm1RkRERApRMlODZOVkMfGNiVGXT2yWyPQ+02MYkYiIyOlTMlNDJDZLLFP5rJysGEUiIiJSsZTM1BBlbWEpSwuOiIhIZSrvc2ZEREREqgQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAqzl3M62cEfmpuge2l/w0XhEREamyak7LzIHtkZOZlslKZkRERAKq5rTMgJewTHytsqMQERGRClRzWmZERESkWlIyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaEpmREREJNBqzHNm5tlXZHIS3pgY9TpZOVkkNEuIYVQiIiJyumpMy0wmJ8niZJnWSWiWQGKzxBhFJCIiIhWhxrTMACRwFkuGLSnzemO2rItBNCIiIlIRakzLjIiIiFRPNaplJnAObIclV0Re3jIZLp975uKRCnfgvvs4kZEZs/rjkhJpOXNmzOoXEakKlMxUVaWN4h1pBHAJlBMZmRzPzKReYsX3zTqeGbskSUSkKlEyU1WV1uJSUouNVKjjmZl8du34mNVdLzGRtk89WeF1xypmEZGqRsmMSAnikmJ7N1u9xMSYb0NEpLpTMiNSAvU3ERGp+nQ3k4iIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmQmSjuzjzLm8XXMefXjyg5FREREQuiheVHo3Lox4CU0IiIiUrUomYnC7Cu7ADDm8XWVHImIiIgUpctMIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoNWYsZn+7+oTtDh4is/eGl/uOlL9gSY/e79xsWXHMzOpl5hY7rpFRESkfGpMy0yLg6do8cWpmNVfLzGRuCQlMyIiImdajWmZAfiiRS26P/Vkudf/rT9q9vLJ/SoqJBERETlNNaZlRkRERKqnGtUyI7E1b8M8MnMyy7xeYrNEpveZHoOIRESkJlAyIxUmMyeTrJwsEpolRL1OVk5WDCMSEZGaQMlMGe3MPsoYv+9M59aNmX1ll0qOqGpJaJbAkmFLoi4/8Y2JMYxGRERqgtNKZsxsD/ANkAfkOud6mVkzYDnQDtgD/Mw599XphVk1dG79r1uyd/q3aVdnWTlZZUo2ytoqIyIiUhEqomXmUufclyHTM4C3nHNzzWyGP10tOkSEtsLkt85UV4nNyn6beUKzhHKtJyIicjpicZlpJDDIf78MWEM1SWYCY+UMOLA98vKWyXD53BKrUIdcEREJitO9NdsBq8xsk5nd6M/7gXMuG8D/t0W4Fc3sRjNLN7P0Q4cOnWYYUsiB7ZGTmZKWiYiIBNDptsxc7Jzbb2YtgDfNLOr7cp1zC4GFAL169XKnGYcU1TIZJr5WfP6SK858LCIiIjF0Wi0zzrn9/r9fAC8DfYCDZtYKwP/3i9MNUkRERCSScrfMmFkDoJZz7hv//WXA3cBfgAnAXP/fVyoiUBEpu+OZmXx2bfkHVy1NXFIiLWfOjFn9IiLROJ3LTD8AXjaz/Hqedc69YWYbgefN7Hrgf4GrTz9MESmrWA98ejyz7E97FhGJhXInM865fwAXhpl/GBh8OkGJyOmLdYtJLFt8RETKQgNNioiISKBpOIMgO7A9/N1JB7Z7dzOJiIjUAEpmgqqkZKVlspIZERGpMZTMnIZKHXSylCf4BklZx4ACb7gFPaVYRERAyUy51bRBJ2OlPGM5ZeVkxSASEREJKiUz5VSTBp2MpfK0rpS1FUdERKo33c0kIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0HRrtoiU2/HMzJgOOBmXlBjzATNFJPiUzNREkcZ0ytcyuVo9YVhiIy6p7A88LIvjmZkxrV9Eqg8lMzVNaWM2Hdh+ZuKQwIt1i0ksW3xEpHpRMlPTlNbiUlKLjYiISBWkDsAiIiISaGqZEZEqSx2MRSQaSmZEpEpSB2MRiZaSGRGpktTBWESipT4zIiIiEmhKZirIzuyjjHl8HXNe/biyQxEREalRdJmpAnRu3RjwEhoRERE5s5TMVIDZV3YBYMzj6yo5kpojKyeLiW9MjOk2EpslMr3P9JhuQ0RETp+SGQmcxGaxvcsFvGRJRESCQcmMFFfS2E1VYNymM9FaEutWHxERqThKZqSwksZu0rhNIiJSBSmZkcJKanXRuE0iIlIF6dZsERERCTS1zEjZVPH+NCIiUvMomZHoqT+NiIhUQUpmJHrqTyMiIlWQ+syIiIhIoCmZERERkUBTMiMiIiKBpj4zIlJjHc/M5LNrx8ek7rikRFrOnBmTukWkMCUzIlIjxSXFboyvf27cyD83buRERmbMtqFkSeRflMyISI0Uy0TgwH33xTSROZ4Zu7pFgkjJjIhIBYt1i0msLo2JBJWSGak4JT0dGKr9E4LnbZhHZk7Z/2JObJZ4RkYCFxGprpTMSMUo6enAUCOeEJyZk0lWThYJzRKiXicrJyuGEYmI1AxKZirYzuyjjHl8HQCdWzdm9pVdKjmiM6S0Fpca8oTghGYJLBm2JOryE9+YGMNoRERqBiUzFahz68YF73dmH63ESERERGoOJTMVKLQVJr91RoIrKyerTC0nZb3EJCIiFUPJTCWZ8+rH7Nz/r9abGnVJKgASm5X9GSQJzRLKtV5ZkyZ1GBYRKUzJTCXZuf8oO7OP0rlV45pzSaqku52q2J1OZypZKGvyow7DIiLFKZmpRJ1bNWb55H4145JUSXc71YA7nSIpa9KkDsMiIsUpmTkDwl1SqnFKanWpIXc6iYhIbCiZOQNq5CUlEZEwYj3UA2jcqppIyUwM5T9zJj+RqTGXlCSmytphGNRpWKqOExmZHM/MpF5ibAb61LhVNZOSmRgJvZTUuVXjmnlpSSpcee+WEqlK6iUm0vapJ2NSt8atqpmUzMSIbrOWWChP64o6DUtZxfJSUCxbZaTmUjIjVUMNH6RSpKyOZ2bGrBXinxs3AnB2794VXne9xETikpTMSMVSMlMJ8jsBd26lS0+ABqkUKaNYJwNn9+6tTrQSKEpmzrBCfWnUj8ZTFQepXDmj5CRKLUXFzNswj8ycsl+aUOfkslOSIeVRne8kUzJzhqkvTUAc2O69wrUaqaUorMyczDKPT6XOySJnTnW+k0zJjEgkLZNh4mvF5wfwIX9n6nbuhGYJLBm2JOry6pwsQRP01o3qeieZkpkqIv+ZNEVpAEpfaR2Ey6sGXC6q6rdza6BNqWhB7RwNek5OecUsmTGzYcB/ArWBRc656v2LcRoi9Z3J7yhcdDiEoutW+2SntA7C5VVDLhdV5du5y5popR9MJ/1gepn75igBqjmC3jlaz8kpn5gkM2ZWG3gMGALsBTaa2V+ccztjsb2gi5SM5LfUhA6HEKrGDI0Qq5aTAF4uqm7KmmCUp5Ox+uXULOocXTPFqmWmD/Cpc+4fAGb2HDASUDJTRqG3cS+f3K/QMg2NUAEiXb6K1Pm3Binr5Z+ydv4tj6rcyiRSUWJ1maw6P7DQnHMVX6nZvwHDnHM3+NPXAhc5524JKXMjcKM/mQDE6s+n5sCXMapbzhydx+pB5zH4dA6rh6Cex7bOufOKzoxVy4yFmVcoa3LOLQQWxmj7/wrELN051yvW25HY0nmsHnQeg0/nsHqobuexVozq3Qu0CZmOB/bHaFsiIiJSg8UqmdkIdDKz9mZ2FjAW+EuMtiUiIiI1WEwuMznncs3sFuBveLdm/8k593EsthWFmF/KkjNC57F60HkMPp3D6qFanceYdAAWEREROVNidZlJRERE5IxQMiMiIiKBVm2SGTMbZmZZZvapmc0Is9zM7L/85dvMrEdlxCkli+I8DjKzr81sq/+aVRlxSmRm9icz+8LMdkRYru9iFRfFOdT3MADMrI2ZvWNmGWb2sZn9vzBlqsX3sVokMyHDJ1wOdAauMbPORYpdDnTyXzcC/31Gg5RSRXkeAd5zznXzX3ef0SAlGkuBYSUs13ex6ltKyecQ9D0MglzgNudcEtAXuLm6/jZWi2SGkOETnHMngfzhE0KNBJ50nvVAUzNrdaYDlRJFcx6linPOrQVySiii72IVF8U5lABwzmU75zb7778BMoDzixSrFt/H6pLMnA98HjK9l+InLJoyUrmiPUf9zOwjM1tpZtV8yPBqSd/F6kHfwwAxs3ZAdyCtyKJq8X2M1XAGZ1qpwydEWUYqVzTnaDPe2BzHzGw4sAKveVSCQ9/F4NP3MEDMrCHwZ+CXzrmjRReHWSVw38fq0jITzfAJGmKh6iv1HDnnjjrnjvnvXwfqmlnzMxeiVAB9FwNO38PgMLO6eInMM865l8IUqRbfx+qSzEQzfMJfgPF+z+2+wNfOuewzHaiUqNTzaGYtzcz8933wPsOHz3ikcjr0XQw4fQ+DwT9Hi4EM59xDEYpVi+9jtbjMFGn4BDOb4i9fALwODAc+Bf4JTKyseCW8KM/jvwFTzSwX+A4Y6/QY6yrFzP4HGAQ0N7O9wGygLui7GBRRnEN9D4PhYuBaYLuZbfXnzQR+CNXr+6jhDERERCTQqstlJhEREamhlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjAhgZnn+6L8f+49o/5WZ1fKX9TKz/yph3XZm9u9nLtpi27/VHxX3mRhv55dmdnaM6q7UY3gmmdnrZtbUf90UMr+1mb1YQdvYY2bbzaxXBdT1gJkdMLNfV0RsIrGgW7NFADM75pxr6L9vATwLfOCcmx3FuoOAXzvnfhLTICNvPxO43Dm3u8j8Os653Arczh6gl3PuyzDLajvn8k6j7kGcxjE83e1XBn+snL8657rGoO49RDhX5azvLuCYc+7BiqhPpKKpZUakCOfcF8CNwC3+UzEHmdlfAcxsoN+Cs9XMtphZI2Au0N+fN81vZXjPzDb7r//jrzvIzNaY2Ytmlmlmz4Q8RbW3mX3otwptMLNGZlbb/6t4o5ltM7PJRWM1swVAB+Av/rbvMrOFZrYKeNLM2prZW/76b5nZD/31lprZf5vZO2b2D3+//uS38CwNs51bgdbAO2b2jj/vmJndbWZpeIMO7jH/kfZ+a9Ya/30Dv+6N/jELNxJ60WNYz8yW+K0LW8zs0jAxDfLjfxbvoWARj5eZ/dav6yMzm+vP62Zm6/2yL5vZOSV9Lvxj+5SZvW1mu8xskj/f/O3u8Lcxxp/fyszW+vu0w8z6+/Pzj9Nc4AJ/+QP+52aHXybs/ptZqpm9ZGZv+DH8vqSYQ2IP9/lKNbMVZvaqme02s1vMa5Hc4h+XZtHULVIlOOf00qvGv/D+6iw67yvgB3hPQv2rP+9V4GL/fUO8p2gXLPfnnw3U8993AtL994OAr/HGPqkFrAMuAc4C/gH09ss19uu9EbjTnxcHpAPtw8S5B2juv78L2ATUD4l3gv/+OmCF/34p8BzeIHMjgaNAsh/XJqBbSdvxpx3wswhx9ALW+O/vA37uv28KfAI0KFJ30WN4G7DEf58I/G/+MS2yzrf5xyTS8QIuBz4EzvaXNfP/3QYM9N/fDTxSymfkLuAjoD7QHG+k4dbAT4E38Z5a/QM/1lb+Ptzhr1sbaBR6nIB2wI6Q+gumI+0/kIr3WWniT38GtCnlMxHp85WK99TXRsB5eJ/NKX6Zh/EGJQzd919X9vdUL70ivdQyIxJZuNFkPwAe8lsqmrrwl3HqAk+Y2XbgBaBzyLINzrm9zrlTwFa8H7AEINs5txEKBvHLBS7DGzNlK5AGnEt0IxP/xTn3nf++H94lM4Cn8JKnfK865xywHTjonNvux/WxH1dp8vAGsCvNZcAMfz/W4P0I/7CUdS7x48U5l4n3o/2jMOU2uH9dXot0vH6Mlxj8068vx8ya4J2/d/11lwEDotiXV5xz3znv8s07QB8/1v9xzuU55w4C7wK98cYam2jeJZpk59w3UdQfzf6/5Zz72jl3HNgJtC2lrkifL4B3nHPfOOcO4SUzr/rztxPdZ0CkSqgWYzOJVDQz64D3Y/0FkJQ/3zk318xewxvLZL2Z/TjM6tOAg8CFeC0dx0OWnQh5n4f3HTS8Vo5iYQC/cM79rYzhf1vCstDt5Mdyqkhcp4ju/4bjrnA/lVz+dem6Xsh8A37qnMuKos7QdaIRuq9hj5eZDSP88S2PovU4IsTqnFtrZgOAK4CnzOwB59yTUW6npP0P9xkqra5I+1/0vId+JvT7IIGhlhmRIszsPGABMN9vuQhddoHfgjEP7zJGIvANXlN9viZ4fwmfwhvkrXYpm8wEWptZb38bjcysDt6Am1PNrK4//0dm1qCMu/Mh3ujjAOOA98u4fqii+1nUHqCn//6nIfP/BvzCrKB/UPco6l6LFy9m9iO8lpzSkqFIx2sVcJ35d2KZWTPn3NfAV/n9WPDO07vhKi1ipN+f5Vy8y1wb/VjH+H12zsNr4dlgZm2BL5xzT+CNXNyjlH0OVZ79jyTS50uk2tAHWsRT3788URevheEp4KEw5X7pd8bMw2viX4n3V2yumX2E1xflj8CfzexqvEsRJbWU4Jw76XcafdTM6uONQvxjYBFeU/9mPxE4BFxVxv26FfiTmf3GX/90RsRdCKw0s2znXLEOucAcYLGZzcS7zJPvP4BHgG3+fuwBit61tI3ix3CBf6kuF0h1zp2gZGGPl3PuDTPrBqSb2Um8UYJnAhP8bZyN16dkIoCZ3Y3Xz+kvYbaxAXgNL7n4D+fcfjN7Ge9y3kd4LSC/dc4dMLMJwG/M7HvgGDA+tCLn3GEz+8Dv9LsSeCxkcdj99/PBMinh8yVSbejWbBGRKFiAbk823ZotNYwuM4mIVD+HgLesgh6aB/ycUloYRSqTWmZEREQk0NQyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaP8f0xdrjRSlQV0AAAAASUVORK5CYII=\n", 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8qWVeeeUVRo4ciZnRt29fDh06xJ49e4qVa9q0KXfddRc9e/bkoosuYv/+/QBkZGTwwgsv8MUXX5CYmEhOTg4A1157LU888QQAv/3tb+nduzepqancd999Zcb99NNP06dPH7p378748ePJz88PxTB16lTOPfdcVq5cWWz6oYceolu3bnTr1o1HHnkEgB07dpCcnMzNN99Mz549+fTTT0vc74ABA7jzzjtJT08nOTmZtWvXMmzYMDp37sw999xTZnwTJ04kLS2Nrl27Fqpnhw4duO++++jZsycpKSlkZ2eXeQxK45zjnXfe4eqrrwZg1KhRvPzyy8XKvfHGGwwcOJD4+HhatWrFwIEDWbJkCQCDBw/GzDAz+vTpw86dO4utn5+fz913301KSgqpqak8+uijofpMmTKFfv36kZaWxvr16xk0aBBnn302s2fPrlTdyqKkRUTkBLZr1y7OOOOM0HRCQgK7du0qVu6rr76iZ8+erF+/ngsuuIBp06YVWt6iRQtmzZpFRkYGzz33HAcPHmTcuHEsXbqUbdu2sWbNGjZu3Mi6detYsWJFifFkZWWxaNEi3n//fTZu3Ej9+vV55plnQjF069aN1atX079//0LTjRs3Zt68eaxevZpVq1bxxBNPsGHDBgBycnIYOXIkGzZsoH379gwePJjdu3dH3P9JJ53EihUrmDBhAkOHDuWxxx5jy5YtzJ8/nwMHDpQa369+9SsyMzPZtGkTy5cvZ9OmTaHttm7dmvXr1zNx4kRmzpxZbL85OTl079494uPQoUOFyh44cICWLVvSoEGDUs9ZNOf22LFjLFy4kEsuuaTY+nPmzGH79u1s2LCBTZs2cd1114WWnXHGGaxcuZLzzz8/lLiuWrWKqVOnRjyusaKOuCIiJzCvNb6wSL/qqFevHsOHDwfg+uuvZ9iwYcXKDBw4kOeff55bbrmFDz/8EIClS5eydOlSevToAcCRI0fYtm0b6enpEeN5++23WbduHb179wbg66+/pk2bNgDUr1+fq666KlQ2fPq9997jyiuvpEmTJgAMGzaMd999lyFDhtC+fXv69u0bWu/1118v8XgMGTIEgJSUFLp27Urbtm0B6NixI59++invvfdeifH95S9/Yc6cOeTl5bFnzx62bt1KampqKB6AXr168eKLLxbbb2JiIhs3biwxrnDRnrNoyt18882kp6dz/vnnFyv71ltvMWHChFByFN5qF36cjhw5QrNmzWjWrBlxcXEcOnSIli1bRlWX8lLSIiJyAktISCh0yWTnzp20a9euzPUifUgeP36crKwsGjduTG5uLgkJCTjn+PnPf8748eOjisc5x6hRo/j1r39dbFlcXBz169ePOB3pA7pAQSITjUaNGgFeklbwvGA6Ly+vxPi2b9/OzJkzWbt2La1atSIjI6PQPUgKtlW/fn3y8vKK7TcnJyeUFBa1bNmyQklA69atOXToEHl5eTRo0KDEc5aQkMCyZctC0zt37mTAgAGh6WnTprF//37++Mc/Rtyvc67EnyWXdZyqipIWEZFqsHXPYYb/cWXMttWlbfOYbGvIkCHMmjWLESNGsHr1alq0aBFqXQh3/PhxXnjhBUaMGMGzzz5L//79i5V5+OGHSU5OZvr06YwZM4aVK1cyaNAg7r33Xq677jqaNm3Krl27aNiwYah1oqiLLrqIoUOHcuedd9KmTRtyc3P58ssvad++fan1SE9PJyMjg8mTJ+Oc46WXXmLhwoUVOyilKCm+w4cP06RJE1q0aMG+fftYvHhxoQShLOVpaTEzLrzwwtD5WLBgAUOHDi1WbtCgQUyZMoWDBw8CXqtXQbI1d+5c3njjDd5++23q1YvcU+Tiiy9m9uzZDBgwgAYNGpCbm1tmH6mqpqQllhZPhr2by7/eaSlw6YOxj0dEaoUu7WKTYIS217Z5VNu89tprWbZsGZ9//jkJCQlMmzaNG2+8MdRZcsKECQwePJjXX3+dTp06cfLJJzNv3ryI22rSpAkfffQRvXr1okWLFixatKjQ8o8//pi5c+eyZs0amjVrRnp6Og888ADTpk0jKyuLfv36AV5n2qeffrrEpKVLly488MADXHzxxRw/fpyGDRvy2GOPlZm09OzZk4yMDPr06QPA2LFj6dGjBzt27ChWdvDgwcydOzeqFqVo4+vbty89evSga9eudOzYkfPOO6/c2y6PGTNmMGLECO655x569OjBjTfeCEBmZiazZ89m7ty5xMfHc++994YuZU2dOjWUdEyYMIH27duHzsuwYcOK9UcZO3YsH3/8MampqTRs2JBx48Zx6623Vmm9ymKlNanFWlpamsvMzKy2/VW7eZd5SctpKdGvU1B+9GtVF5eIVLusrCySk5NrOoyYadq0KUeOHKnpMKSOifQ+MbN1zrm0SOXV0hJr5U1A5l1WdbGIiIjUIfrJs4iIlEmtLFIbKGkRERGRQFDSIiIiIoGgpEVEREQCQR1xRUSqWkVvh1Aa3SpBTkBqaRERqWp7N8c2aYlie0ePHqVPnz6cc845xQbwC+ec4/bbb6dTp06kpqayfv36coUydepU3nrrrXKtU6Bp06YVWk+8O/Cee+65dO7cmeHDh/Ptt99GLLdgwQI6d+5M586dWbBgQbHlt912W6DOg1paRESqQyzvxxTFrRIaNWrEO++8Q9OmTTl27Bj9+/fn0ksvLTQGD8DixYvZtm0b27ZtY/Xq1UycOJHVq1dHHcovf/nLcocfC/n5+YVu6V90OhLnHM65Eu8AGySTJk3izjvvZMSIEUyYMIEnn3ySiRMnFiqTm5vLtGnTyMzMxMzo1asXQ4YMoVWrVoB3I7qigzHWdsE/cyIiUoyZhb5BHzt2jGPHjkUcR+aVV15h5MiRmBl9+/bl0KFD7Nmzp1i5pk2bctddd9GzZ08uuugi9u/fDxAa4feLL74gMTGRnJwcwLsb7xNPPAHAb3/7W3r37k1qamqJLT7hnn76afr06UP37t0ZP348+fn5oRimTp3Kueeey8qVK4tNP/TQQ3Tr1o1u3brxyCOPALBjxw6Sk5O5+eab6dmzZ6FxlooaMGAAd955J+np6SQnJ7N27VqGDRtG586dueeee8qMb+LEiaSlpRVr2erQoQP33XcfPXv2JCUlhezs7DKPQWmcc7zzzjtcffXVAIwaNYqXX365WLk33niDgQMHEh8fT6tWrRg4cCBLliwBvCTvZz/7Gb/5zW9K3E9+fj533303KSkppKam8uijj4bqM2XKFPr160daWhrr169n0KBBnH322aG7LVeVMpMWMzvDzP5hZllm9pGZ/T9//v1mtsvMNvqPwVUaqYiIlEt+fj7du3enTZs2DBw4kHPPPbdYmV27dnHGGWeEphMSEti1a1excl999RU9e/Zk/fr1XHDBBUybNq3Q8hYtWjBr1iwyMjJ47rnnOHjwIOPGjWPp0qVs27aNNWvWsHHjRtatW8eKFStKjDkrK4tFixbx/vvvs3HjRurXr88zzzwTiqFbt26sXr2a/v37F5pu3Lgx8+bNY/Xq1axatYonnniCDRs2AN5ghCNHjmTDhg20b9+ewYMHs3v37oj7P+mkk1ixYgUTJkxg6NChPPbYY2zZsoX58+dz4MCBUuP71a9+RWZmJps2bWL58uVs2rQptN3WrVuzfv16Jk6cyMyZM4vtNycnh+7du0d8FG0NOXDgAC1btgyNvlzSOSvt3M6aNYshQ4ZEHGeqwJw5c9i+fTsbNmxg06ZNXHfddaFlZ5xxBitXruT8888PJa6rVq0qNhRArEVzeSgPuMs5t97MmgHrzOxNf9nDzrniR19ERGpc/fr12bhxI4cOHeLKK69ky5YtdOvWrVCZSEO5RGqRqVevXmgU4uuvv55hw4YVKzNw4ECef/55brnlFj788EPAG6Rv6dKl9OjRA/BuUrdt2zbS09Mjxvz222+zbt260Hg5X3/9dWicovr163PVVVcVql/B9HvvvceVV14ZGtF52LBhvPvuuwwZMoT27dsXuiz2+uuvR9w3eANIAqSkpNC1a9fQh3rHjh359NNPee+990qM7y9/+Qtz5swhLy+PPXv2sHXrVlJTU0PxAPTq1YsXX3yx2H7LM2BitOespHK7d+/m+eefLzQCdCRvvfUWEyZMCCVH4YMlhh+nI0eO0KxZM5o1a0ZcXByHDh0qNCp1LJWZtDjn9gB7/OdfmlkWcHqVRCMiIjHXsmVLBgwYwJIlS4olLQkJCYUumezcuTOqgQQjfUgeP36crKwsGjduTG5uLgkJCTjn+PnPf8748eOjitU5x6hRo0KjEYeLi4sr1G8lfLq0cfQKEploNGrUCPCStILnBdN5eXklxrd9+3ZmzpzJ2rVradWqFRkZGRw9erTYduvXr09eXl6x/ebk5ISSwqKWLVtWKAlo3bo1hw4dIi8vjwYNGpR4zhISEgolJjt37mTAgAFs2LCBf/7zn3Tq1AmA//73v3Tq1Il//vOfhdZ3zkU8z+H1Kek4VZVydcQ1sw5AD2A1cB5wq5mNBDLxWmMORljnJuAmgDPPPLOy8YqIBNPezbEbayyKgVn3799Pw4YNadmyJV9//TVvvfUWkyZNKlZuyJAhzJo1ixEjRrB69WpatGgR8ZLB8ePHeeGFFxgxYgTPPvss/fv3L1bm4YcfJjk5menTpzNmzBhWrlzJoEGDuPfee7nuuuto2rQpu3btomHDhiWO8nzRRRcxdOhQ7rzzTtq0aUNubi5ffvllmaM8p6enk5GRweTJk3HO8dJLL7Fw4cJS16mIkuI7fPgwTZo0oUWLFuzbt4/FixczYMCAqLdbnpYWM+PCCy8MnY8FCxYwdOjQYuUGDRrElClTOHjQ+2heunQpv/71r4mPj2fv3r2hck2bNi2WsABcfPHFzJ49mwEDBtCgQQNyc3MLtbbUhKg74ppZU+CvwB3OucPAH4Czge54LTG/i7Sec26Ocy7NOZd26qmnVj5iEZGgOS2lfKO/x2B7e/bs4cILLyQ1NZXevXszcOBALr/8cgBmz54d6jA5ePBgOnbsSKdOnRg3bhyPP/54xO01adKEjz76iF69evHOO+8U67vw8ccfM3fuXH73u99x/vnnk56ezgMPPMDFF1/MT37yE/r160dKSgpXX301X375ZYlxd+nSJbReamoqAwcOjNgxuKiePXuSkZFBnz59OPfccxk7dmzoklRRpfVpKUtJ8Z1zzjn06NGDrl27MmbMGM4777wKbT9aM2bM4KGHHqJTp04cOHCAG2+8EfB+ETR27FjAu5xz77330rt3b3r37s3UqVPLlXSMHTuWM888k9TUVM455xyeffbZKqlLeVhpTWqhQmYNgb8DbzjnHoqwvAPwd+dct6LLwqWlpbnMzMwKhhoABd+iKjLKc6x+CikitUJWVhbJyck1HUbMNG3aVIMmSsxFep+Y2TrnXFqk8tH8esiAJ4Gs8ITFzMLbD68EtlQoYhEREZEoRNOn5TzgBmCzmW30500BrjWz7oADdgDR9bISEZHAUSuL1AbR/HroPSBS9+GSfzMmIiIiEmO6I66IiIgEgpIWERERCQQNmCgiUsVmrJlBdm7lxpspKik+iUl9it93RaQuU0uLiEgVy87NJic3J2bby8nNiSoJ6tChAykpKXTv3p20tIi/IMU5x+23306nTp1ITU1l/fr15Ypl6tSpvPXWW+Vap0DBgI5Sftu3b+fcc8+lc+fODB8+nG+//TZiuQULFtC5c2c6d+7MggULQvOdc/ziF7/g+9//PsnJyfz+97+vrtArRS0tIiLVIDE+kXmXzIvJtkYvGR112X/84x+0bt26xOWLFy9m27ZtbNu2jdWrVzNx4kRWr14d9fZ/+ctfRl02lvLz8wvd0r/odCTOOZxz1KsX/O/rkyZN4s4772TEiBFMmDCBJ598kokTJxYqk5uby7Rp08jMzMTM6NWrF0OGDKFVq1bMnz+fTz/9lOzsbOrVq8dnn31WQzUpn+CfORERqbBXXnmFkSNHYmb07duXQ4cORbwDbdOmTbnrrrvo2bMnF110Efv37wcIjfD7xRdfkJiYSE6O16J07bXX8sQTTwDw29/+lt69e5Oamsp9991XZkxPP/00ffr0oXv37owfP578/PxQDFOnTuXcc89l5cqVxaYfeughunXrRrdu3XjkkUcA2LFjB8nJydx888307Nmz0DhLRQ0YMIA777yT9PR0kpOTWbt2LcOGDaNz587cc889ZcY3ceJE0tLS6Nq1a6F6dujQgfvuu4+ePXuSkpJCdnblLhU653jnnXe4+uqrARg1ahQvv/xysXJvvPEGAwcOJD4+nlatWjFw4ECWLFkCwB/+8AemTp0aSuAiDauQn5/P3XffTUpKCqmpqTz66KOh+kyZMoV+/fqRlpbG+vXrGTRoEGeffXboTstVRUmLiEgdZWZcfPHF9OrVizlz5kQss2vXLs4444zQdEJCArt27SpW7quvvqJnz56sX7+eCy64gGnTphVa3qJFC2bNmkVGRgbPPfccBw8eZNy4cSxdupRt27axZs0aNm7cyLp161ixYkWJMWdlZbFo0SLef/99Nm7cSP369XnmmWdCMXTr1o3Vq1fTv3//QtONGzdm3rx5rF69mlWrVvHEE0+wYcMGwBuMcOTIkWzYsIH27duXehv/k046iRUrVjBhwgSGDh3KY489xpYtW5g/fz4HDhwoNb5f/epXZGZmsmnTJpYvX86mTZtC223dujXr169n4sSJzJw5s9h+c3Jy6N69e8THoUOHCpU9cOAALVu2DI2+XNI5K+3c/utf/2LRokWkpaVx6aWXsm3btmLrz5kzh+3bt7NhwwY2bdrEddddF1p2xhlnsHLlSs4///xQ4rpq1apiwzvEmi4PiYjUUe+//z7t2rXjs88+Y+DAgSQlJZGenl6oTKShXCKN7FuvXr3QKMTXX389w4YNK1Zm4MCBPP/889xyyy18+OGHgDdI39KlS0PjAB05coRt27YVi6PA22+/zbp16+jduzcAX3/9dagVoH79+lx11VWhsuHT7733HldeeWVoROdhw4bx7rvvMmTIENq3b0/fvn1D673+esm3GRsyZAgAKSkpdO3aNTR4ZMeOHfn000957733SozvL3/5C3PmzCEvL489e/awdetWUlNTQ/EA9OrVixdffLHYfsszYGK056y0ct988w1xcXFkZmby4osvMmbMGN59991CZd966y0mTJgQSo7Cxy0KP05HjhyhWbNmNGvWjLi4OA4dOlRoVOpYUtIiIlJHtWvXDvCa/q+88krWrFlTLFlISEgodMlk586dofVKE+lD8vjx42RlZdG4cWNyc3NJSEjAOcfPf/5zxo+P7qbpzjlGjRrFr3/962LL4uLiCvVbCZ8ubRy9gkQmGo0aNQK8JK3gecF0Xl5eifFt376dmTNnsnbtWlq1akVGRgZHjx4ttt369euTl5dXbL85OTmhpLCoZcuWFUoCWrduzaFDh8jLy6NBgwYlnrOEhASWLVsWmt65c2do5OmEhIRQwnfllVcyenTxflLOuYjnObw+JR2nqqKkRUSkGuTk5pSrA21Z20qMTyy1zFdffcXx48dp1qwZX331FUuXLo3YdD9kyBBmzZrFiBEjWL16NS1atAi1LoQ7fvw4L7zwAiNGjODZZ5+lf//+xco8/PDDJCcnM336dMaMGcPKlSsZNGgQ9957L9dddx1NmzZl165dNGzYMGIfCoCLLrqIoUOHcuedd9KmTRtyc3P58ssvad++fan1TU9PJyMjg8mTJ+Oc46WXXmLhwoWlrlMRJcV3+PBhmjRpQosWLdi3bx+LFy8OJQjRKE9Li5lx4YUXhs7HggULGDp0aLFygwYNYsqUKRw8eBDwWr0Kkq0rrriCd955hzFjxrB8+XK+//3vF1v/4osvZvbs2QwYMIAGDRqQm5tbrlGiq4KSFhGRKpYUnxTT7SXGJ5a5zX379nHllVcCkJeXx09+8hMuueQSgFBnyQkTJjB48GBef/11OnXqxMknn8y8eZF/4dSkSRM++ugjevXqRYsWLVi0aFGh5R9//DFz585lzZo1NGvWjPT0dB544AGmTZtGVlYW/fr1A7zOtE8//XSJSUuXLl144IEHuPjiizl+/DgNGzbkscceKzNp6dmzJxkZGfTp0weAsWPH0qNHD3bs2FGs7ODBg5k7d25ULUrRxte3b1969OhB165d6dixI+edd165t10eM2bMYMSIEdxzzz306NGDG2+8EYDMzExmz57N3LlziY+P59577w1dypo6dWoo6Zg8eTLXXXcdDz/8ME2bNmXu3LnF9jF27Fg+/vhjUlNTadiwIePGjePWW2+t0nqVxUprUou1tLQ0l5mZWW37q3bzLvP+jn6tatcRkVovKyuL5OTkmg4jZpo2bapBEyXmIr1PzGydcy7ijYX06yEREREJBCUtIiJSJrWySG2gpEVEREQCQUmLiIiIBIKSFhEREQkE/eRZRKSK7Z0+nW+yKjfeTFGNkpM4bcqUmG5TpLZTS4uISBX7Jiubo5UcJC/c0ezsqJKgMWPG0KZNG7p161Zofm5uLgMHDqRz584MHDgwdPOxopYsWUJiYiKdOnXiwQcfLFeMmZmZ3H777eVap0DBWDZSfs45br/9djp16kRqairr16+PWG7WrFl06tQJM+Pzzz8vtnzt2rXUr1+/1p0HtbSIiFSDuKQk2i98Kibb+uSGkVGVy8jI4NZbb2XkyMLlH3zwQS666CImT57Mgw8+yIMPPsiMGTMKlcnPz+eWW27hzTffJCEhgd69ezNkyBC6dOkS1b7T0tJIS4t4q40qVXBr+5Kmo10vqBYvXsy2bdvYtm0bq1evZuLEiaxevbpYufPOO4/LL7884l178/PzmTRpEoMGDaqGiMsn+GeoHKa9+hFbdx8uNK9Lu+bc96OuNRSRiEjVSU9Pj3hH2FdeeSU0Js2oUaMYMGBAsaRlzZo1dOrUiY4dOwIwYsQIXnnllWJJS0ZGBnFxcXz00Ufs27ePhx56iMsvv5xly5Yxc+ZM/v73v3P77bfTunVrpk6dyhtvvMGvfvUrli1bxoYNG/jpT3/KkSNHaN26NfPnz484hECBf/3rX9xyyy3s37+fk08+mSeeeIKkpCQyMjKIj49nw4YN9OzZkwMHDhSavuGGG5gwYQL//e9/Ofvss/nTn/5Eq1atGDBgAD/4wQ94//33GTJkCHfddVfE/c6fP5+XX36Z/Px8tmzZwl133cW3337LwoULadSoEa+//jrx8fElxvfqq6/ywAMP8O2333LKKafwzDPP8L3vfY/777+f//znP/z73//mP//5D3fccUeFW6cKvPLKK4wcORIzo2/fvhw6dIg9e/YUO64FA1hG8uijj3LVVVexdu3aEsssWbKEKVOmkJ+fT+vWrXn77be5//772b59O3v27OHjjz/moYceYtWqVSxevJjTTz+dV199lYYNG1aqfifU5aGtuw+zdc93ScvWPYeLJTEiInXdvn37Qh9ibdu25bPPPitWZteuXZxxxhmh6YSEBHbt2hVxezt27GD58uW89tprTJgwodBAgeC17CxatIh//OMf3H777cybN4/8/Hxuu+02XnjhBdatW8eYMWP4xS9+UWrcN910E48++ijr1q1j5syZ3HzzzaFlH3/8MW+99Ra/+93vik2PHDmSGTNmsGnTJlJSUpg2bVpovUOHDrF8+XLuuusuZs+eHRrioKgtW7bw7LPPsmbNGn7xi19w8skns2HDBvr168dTTz1Vanz9+/dn1apVbNiwgREjRvCb3/wmtN3s7GzeeOMN1qxZw7Rp0zh27FixfQ8fPpzu3bsXexTsN1x5zlsku3bt4qWXXmLChAklltm/fz/jxo3jr3/9Kx9++CHPP/98aNm//vUvXnvtNV555RWuv/56LrzwQjZv3kzjxo157bXK3/n9hGppAejStjmLxntjYAz/48oajkZEpHaKNMRLSSP+/vjHP6ZevXp07tyZjh07kl2k/05Bq0N6ejoPP/wwZ599Nlu2bGHLli0MHDgQ8C5JlNbKcuTIET744AOuueaa0Lxvvvkm9Pyaa64pNAJ0wfQXX3zBoUOHuOCCCwCvZSl8G+EjK5f2QX3hhRfSrFkzmjVrRosWLfjRj34EQEpKCps2bSo1vp07dzJ8+HD27NnDt99+y1lnnRUqc9lll9GoUSMaNWpEmzZt2LdvHwkJCYX2XXScp9KU57xFcscddzBjxoxCx7KoVatWkZ6eHqpH+CCKl156KQ0bNiQlJYX8/PzQeFcpKSkRW/3K64RLWkRETnTf+973QpcM9uzZE3HwwoSEBD799NPQ9M6dO0scYLDoh2KkD8nNmzdzyimnsHv3bsD7cO3atSsrV0b35fH48eO0bNmyxJGQmzRpUup0SaIt16hRo9DzevXqhabr1atHXl5eqfHddttt/PSnP2XIkCEsW7aM+++/P+J269evT15eXrH1hw8fTk5OTrH5P/3pT4v1VyrPeYskMzOTESNGAPD555/z+uuv06BBA6644opQGedciYlQ+HFp2LBhqFzBcaosJS0iItXgaHZ21B1oo9lWXFLFR44eMmQICxYsYPLkySxYsIChQ4cWK9O7d2+2bdvG9u3bOf3003nuued49tlnI27v+eefZ9SoUWzfvp1///vfJCYmsmrVqtDyTz75hN/97nds2LCBwYMHc8UVV9CjRw/279/PypUr6devH8eOHePjjz+ma9fIfQybN2/OWWedxfPPP88111yDc45NmzZxzjnnlFrXFi1a0KpVK959913OP/98Fi5cGGp1iaXS4vviiy84/fTTAViwYEG5t12elpYhQ4Ywa9YsRowYwerVq2nRokWpLVhFbd++PfQ8IyODyy+/vFDCAtCvXz9uueUWtm/fzllnnUVubm6h1paqdEL1aRERqQmNkpMqlWQUFZeURKPksrd37bXX0q9fP3JyckhISODJJ58EYPLkybz55pt07tyZN998k8mTJwOwe/duBg8eDECDBg2YNWsWgwYNIjk5mR//+MclJhSJiYlccMEFXHrppcyePZu4uLjQMuccN954IzNnzqRdu3Y8+eSTjB07luPHj/PCCy8wadIkzjnnHLp3784HH3xQan2eeeYZnnzySc455xy6du3KK6+8EtXxWrBgAT/72c9ITU1l48aNTJ06NWK50vq0RKOk+O6//36uueYazj//fFq3bl3h7Udj8ODBdOzYkU6dOjFu3Dgef/zxQssKWrp+//vfk5CQwM6dO0lNTWXs2LFR7+PUU09lzpw5DBs2jHPOOafQJbaqZpGuf1WVtLQ0l5mZWW37K6qgD0vRPi0F05U27zLv7+hydDaqyDoiUutlZWWRnJxc02FUuYJv41dffXVNhyIBFOl9YmbrnHMRfy+vlhYREREJBPVpERGRCps/f35NhyAnELW0iIhUkeq8/C4SNBV5fyhpERGpAnFxcRw4cECJi0gEzjkOHDhQqNN2NHR5SESkChT8MmP//v01HYpIrRQXF1fsRnplUdIiIlIFGjZsWOjOpyJSeUpaIlk8GfZuLjZ7hh0km29LXu/YV3BSE1gyusxdJMUnManPpMpEKSIickJRn5ZI9m6OmLRk8y05pSUtJzXxHmXIyc0hOze7zHIiIiLyHbW0lOS0lOI3fFsymkRg3iXzKrXp0VG0xIiIiEhhamkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQmEMpMWMzvDzP5hZllm9pGZ/T9/fryZvWlm2/y/rao+XBERETlRRdPSkgfc5ZxLBvoCt5hZF2Ay8LZzrjPwtj8tIiIiUiXKTFqcc3ucc+v9518CWcDpwFBggV9sAXBFFcUoIiIiQoPyFDazDkAPYDXwPefcHvASGzNrE/vwKm7aqx+xdffhQvO27jlMl7bNi80b/seVoeku7ZpzX7VEGGbvZph3WfnWOS0FLn2wauIRERGphaJOWsysKfBX4A7n3GEzi3a9m4CbAM4888yKxFghW3cfLpakdGnbnC7twqbbFU9gADipWkL0nJZS/nX2bo59HCIiIrVcVEmLmTXES1iecc696M/eZ2Zt/VaWtsBnkdZ1zs0B5gCkpaW5GMQctS5tm7NofL8Sl9/3o66FpsNbXKpNRVpLytsqIyIiUgdE8+shA54EspxzD4Ut+hswyn8+Cngl9uGJiIiIeKJpaTkPuAHYbGYb/XlTgAeBv5jZjcB/gGuqJEIRERERokhanHPvASV1YLkotuGIiIiIRKY74oqIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCOUaMFHqhr3Tp/NNVnaN7b9RchKnTZlSY/sXEZFgUkvLCeibrGyOZtdM0nI0O7tGEyYREQkutbScoOKSkmi/8Klq3+8nN4ys9n2KiEjdoJYWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEQoOaDkAqbsaaGWTnZpd7vRH+OvcvGR2alxSfxKQ+k2IWm4iISKwpaQmw7NxscnJzSIxPrNR2cnJzYhSRiIhI1VHSEnCJ8YnMu2Reudb55JmRAKH1Roe1uIiIiNRW6tMiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBt/EXwBt/qLK389egiyIiUpWUtAhJ8UmV3oYGXRQRkaqmpEVi0jqiQRdFRKSqqU+LiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCocykxcz+ZGafmdmWsHn3m9kuM9voPwZXbZgiIiJyooumpWU+cEmE+Q8757r7j9djG5aIiIhIYWXext85t8LMOlRDLCeUSg1QaPv8bRwkMT4xhlGJiIjUXpXp03KrmW3yLx+1KqmQmd1kZplmlrl///5K7K7uSIpPikmykRifGJPBDkVERIKgogMm/gH4P8D5f38HjIlU0Dk3B5gDkJaW5iq4vzql0gMUzrvM+3vJvMoHIyIiEhAVamlxzu1zzuU7544DTwB9YhuWiIiISGEVSlrMrG3Y5JXAlpLKioiIiMRCmZeHzOzPwACgtZntBO4DBphZd7zLQzuA8VUXooiIiEh0vx66NsLsJ6sgFhEREZES6Y64IiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEggNajqAE9ne6dP5Jiu7Aivu9v6+M7JC+z2anU1cUlKF1o2Fo9nZfHJDxWKvrEbJSZw2ZUqN7FtERCpHSUsN+iYru0YSiLikJBol10zSUlP7BS9ZEhGR4FLSUsPikpJov/Cp8q007zLv7+hyrlcL1GQrR0217oiISGyoT4uIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCCUmbSY2Z/M7DMz2xI2L97M3jSzbf7fVlUbpoiIiJzoomlpmQ9cUmTeZOBt51xn4G1/WkRERKTKlJm0OOdWALlFZg8FFvjPFwBXxDYsERERkcIaVHC97znn9gA45/aYWZsYxlSrTHv1I7buPgzAjpMOh+bd96OuNRmWBMze6dP5Jiu7psOodo2SkzhtypSaDkNE6ogq74hrZjeZWaaZZe7fv7+qdxdzW3cfZuuew6Hp/36TF0piRKL1TVY2R7NPrKTlaHb2CZmoiUjVqWhLyz4za+u3srQFPiupoHNuDjAHIC0tzVVwfzWqS9vmLBrfj9FLmnsJzLc1HZEEUVxSEu0XPlXTYVSbT24YWdMhiEgdU9GWlr8Bo/zno4BXYhOOiIiISGTR/OT5z8BKINHMdprZjcCDwEAz2wYM9KdFREREqkyZl4ecc9eWsOiiGMciIiIiUiLdEVdEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQKjobfyDY/FkZuxbQXYU9953lgfA6GPfwElNYMno0CCJo5c0Jyc3B2hbldFWrcWTYe/m8q93WgpcWjfuH3g0O7tGbi9/NDubuKSkat+viEhdUveTlr2byT52kJyTGpLISdGtc1IT71FEYnwi/97VIsYBVqO9m73HaSnlW6eOaJRcc0lDXFJSje5fRKQuqPtJC8BJTUg8LYV5l8wrtdjwP64EYF5Gv+LzLulXaDqwTkuB0a9FX37eZVUXSzU7bcqUmg5BREQqQX1aREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggnBi38S/F3unT+SYrG4CMPYf56ps8Fj//3WG55ps8mjRqwCfvNQ+VAULTlVHXBtHLyc1h9JLRld5OUnwSk/pMikFEItUv/H9KTWiUnKQhK6TOOuGTlm+yskPJw8kn1S+2vEmjBhHnx0JdGkQvKT429fBG0hYJrvD/KdXtaHbNJUsi1eGET1rASx7aL3yK9lGU/V9/wMRF4/uVUfLEEquWkVi01IjUtIL/KdXtkxtGVvs+RaqT+rSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQGtR0ALEy7dWP2Lr7cGh6657DdGnbvAYjkpo0Y80MsnOzY7KtpPgkJvWZFJNtSfXYO30632TF5vyX19HsbOKSkmpk3yJ1XZ1padm6+zBb93yXtHRp25wu7ZS0nKiyc7PJyc2p9HZycnNilvxI9fkmK5uj2TVz3uKSkmiUrKRFpCrUmZYW8BKVReP7FZ45r2ZikZqXGJ/IvEsq9wIYvWR0jKKR6haXlET7hU/VdBgiEkN1pqVFRERE6jYlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEQqVuLmdmO4AvgXwgzzmXFougRERERIqKxR1xL3TOfR6D7YiIiIiUqE7dxj9Iig7wCNClXXPu+1HXGoqoFHs3w7zLyrfOaSlw6YNVE4+IiJyQKpu0OGCpmTngj865OUULmNlNwE0AZ555ZiV3V3cUDPBYMBJ1+GCPtcppKeVfZ+/m2MchIiInvMomLec553abWRvgTTPLds6tCC/gJzJzANLS0lwl91enhA/wOPyPK2s4mhJUpLWkvK0yIiIiUajUr4ecc7v9v58BLwF9YhGUiIiISFEVTlrMrImZNSt4DlwMbIlVYCIiIiLhKnN56HvAS2ZWsJ1nnXNLYhKViIiISBEVTlqcc/8GzolhLCIiIiIl0h1xRUREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEjfJcBSKN4FxU+GCJFVKRkZf3bq7YAIjVLCc3h9FLRld6G4nxibUmHoCk+CQm9ZkUg4iC42h2Np/cMLJG9huXlFTt+xWRqqWkpQoUHcE5ki5tm9OlXQWTloomHqel1PqkJSk+Nh80ifGJMdlWrOLJyc2JyXaCpFFyzSUNcUlJNbp/EakaSlqqSPgIzjFXkZGXA6K2tUTEKp5YtNQEzWlTptR0CCJSx6hPi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBN3GX6pGRQZ0PC2lTg9RIFIdamqQykbJSRq6QaqckhaJvYoMyrh3c+zjEDnB1NQgkUezs2tkv3LiUdIisVeR1pLytsqISDE11dJREy07cmJSnxYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEgi6jX8FbN1zmOF/XFnq8i5tm1djRHVERQZZrE4a0FFEaom906fzTVbNjflUUwNkKmkppy7tyk5GurRtHlU5CVORQRarkwZ0FJFa5JusbI5mZxOXVP2DZNbkAJlKWsrpvh91rekQ6qba3oJRm1uAROSEFJeURPuFT1X7fmtygEz1aREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaDb+AfItFc/Yuvuw2WW69KuuYYbqIVycnMYvWR02QVz/w3fflX1ARU4qQnEd6y+/UWQFJ/EpD6TKrWNGWtmkJ0bmzFRYhHPieZodnaN3t79RFNT4w7VNCUtAbJ19+EyR5DeuqfspEaqX1J8Of65fPuV9zipSdUFFL6vGpaTmxOT7WTnZpOTm0NifGKtiOdE0ij5xPvwrGlxSUkn5HFX0hIwXdo2Z9H4fiUuH/7HldUYjUSrXN/a510GDYGM16osnkL7csAl86p+XyWIqvUpSonxicyrZF1iGc+J4rQpU2o6BDlBqE+LiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBEKlkhYzu8TMcszsn2Y2OVZBiYiIiBRV4aTFzOoDjwGXAl2Aa82sS6wCExEREQlXmbGH+gD/dM79G8DMngOGAltjEdiJaOuew6WOHVTWYIlSxfZu9sbqqY79nJZS9fupRaIeAbuMbVR2sEQRqd3MOVexFc2uBi5xzo31p28AznXO3Vqk3E3ATf5kIlBVQ6i2Bj6vom3XRqpv3ab61n0nWp1V37otlvVt75w7NdKCyrS0WIR5xTIg59wcYE4l9hNdMGaZzrm0qt5PbaH61m2qb913otVZ9a3bqqu+lemIuxM4I2w6AdhduXBEREREIqtM0rIW6GxmZ5nZScAI4G+xCUtERESksApfHnLO5ZnZrcAbQH3gT865j2IWWflV+SWoWkb1rdtU37rvRKuz6lu3VUt9K9wRV0RERKQ66Y64IiIiEghKWkRERCQQan3SUtZQAeb5vb98k5n1jHbd2qqSdd5hZpvNbKOZZVZv5BUTRX2TzGylmX1jZneXZ93aqJL1rYvn9zr/dbzJzD4ws3OiXbc2qmR96+L5HerXdaOZZZpZ/2jXrY0qWd86d37DyvU2s3zz7uFWrnXLxTlXax94HXz/BXQETgI+BLoUKTMYWIx335i+wOpo162Nj8rU2V+2A2hd0/WIcX3bAL2BXwF3l2fd2vaoTH3r8Pn9AdDKf35pkN/DlalvHT6/Tfmu/2QqkF3Hz2/E+tbV8xtW7h3gdeDqqjy/tb2lJTRUgHPuW6BgqIBwQ4GnnGcV0NLM2ka5bm1UmToHUZn1dc595pxbCxwr77q1UGXqG0TR1PcD59xBf3IV3j2folq3FqpMfYMomvoecf6nGNCE725CWlfPb0n1DaJoz9FtwF+BzyqwbrnU9qTldODTsOmd/rxoykSzbm1UmTqD9wZZambrzBtCobarzHkK4jmubMx1/fzeiNeKWJF1a4PK1Bfq6Pk1syvNLBt4DRhTnnVrmcrUF+rg+TWz04ErgdnlXbciKnMb/+oQzVABJZWJapiBWqgydQY4zzm328zaAG+aWbZzbkVMI4ytypynIJ7jysZcZ8+vmV2I9yFe0AegTp/fCPWFOnp+nXMvAS+ZWTrwf8APo123lqlMfaFunt9HgEnOuXyzQsWr5PzW9paWaIYKKKlMUIcZqEydcc4V/P0MeAmvia42q8x5CuI5rlTMdfX8mlkqMBcY6pw7UJ51a5nK1LfOnt8C/gf02WbWurzr1hKVqW9dPb9pwHNmtgO4GnjczK6Ict3yq6kOPtE88FqC/g2cxXcdeboWKXMZhTulrol23dr4qGSdmwDNwp5/gDcSd43XqzL1DSt7P4U74gbuHFeyvnXy/AJnAv8EflDRY1VbHpWsb109v534rmNqT2CX/7+rrp7fkupbJ89vkfLz+a4jbpWc31p9eciVMFSAmU3wl8/G6608GO+fwH+B0aWtWwPVKJfK1Bn4Hl6TJHgvmGedc0uquQrlEk19zew0IBNoDhw3szvweqEfDto5rkx98YZ+r3PnF5gKnIL3DQ0gzzmXFsT3cGXqSx19/wJXASPN7BjwNTDceZ9qdfX8RqyvmdXV81uudSsbk27jLyIiIoFQ2/u0iIiIiABKWkRERCQglLSIiIhIIChpERERkUBQ0iIiIiKBoKRFTij+KKQbzewjM/vQzH5qZvX8ZWlm9vtS1u1gZj+pvmiL7f92M8sys2eqeD93mNnJVbTtGj2G1cnMXjezlv7j5rD57czshRjto2DU4LQYbOu3ZrbXiowsLlKb6CfPckIxsyPOuab+8zbAs8D7zrn7olh3AN7N3i6v0iBL3n82cKlzbnuR+Q2cc3kx3M8OIM0593mEZfWdc/mV2PYAKnEMK7v/mmBmHYC/O+e6VcG2d1DCuarg9u4HjjjnZsZieyKxppYWOWE571baNwG3mmeAmf0dwMwu8FtkNprZBjNrBjwInO/Pu9NvNXjXzNb7jx/46w4ws2Vm9oKZZZvZM+bfUcrMepvZB34rzxoza2Zm9f1vuWvNbJOZjS8aq5nNxhvi/W/+vu83szlmthR4yszam9nb/vpvm9mZ/nrzzewPZvYPM/u3X68/+S028yPs53agHfAPM/uHP++Imf3SzFYD/fxv9639ZWlmtsx/3sTf9lr/mEUa0bXoMYwzs3l+a8EG88bjKRrTAD/+Z4HNpR0vM/tff1sfmtmD/rzuZrbKL/uSmbUq7XXhH9uFZvaOmW0zs3H+fPP3u8Xfx3B/flszW+HXaYuZne/PLzhOD+Ldyn2jv34HM9vil4lYfzPLMLMXzWyJH8NvSos5LPZIr68MM3vZzF41s+1mdqt5LYwb/OMSH822RWqFmr5NsB56VOcD71tk0XkH8e5GOgDvGzHAq3iDmwE0xbuDZWi5P/9kIM5/3hnI9J8PAL7AG2ujHrASb1C8k/Bua93bL9fc3+5NwD3+vEZ4d8M9K0KcO4DW/vP7gXVA47B4R/nPxwAv+8/n4w0Jb3jDwh8GUvy41gHdS9uPP+2AH5cQRxqwzH8+Hbjef94S+BhoUmTbRY/hXcA8/3kS8J+CY1pkna8KjklJxwu4FO/W6Cf7y+L9v5uAC/znvwQeKeM1cj/eLccb492F+FO8RO4q4E28u3t+z4+1rV+HX/jr1ue7W7Xv8NfvAGwJ235ouqT6Axl4r5UW/vQnwBllvCZKen1l4N09uxlwKt5rc4Jf5mHgjiJ1v7u046OHHjX5UEuLSOTRSN8HHvJbHlq6yJdfGgJPmNlm4Hm8W+0XWOOc2+mcOw5sxPugSgT2OOfWAjjnDvvbvRjvtt8bgdV4t3jvHEXcf3POfe0/74d3qQtgIYVHDn7VOeeAzcA+59xmP66P/LjKkg/8NYpyFwOT/Xosw/uwPbOMdfr78eKcy8b7cP5+hHJr3HeXxUo6Xj/ESwD+628v18xa4J2/5f66C4D0KOryinPua+dddvkH3sB2/YE/O+fynXP7gOVAb2AtMNq8Syspzrkvo9h+NPV/2zn3hXPuKLAVaF/Gtkp6fQH8wzn3pXNuP17S8qo/fzPRvQZEaoVaPfaQSFUzs454H8qfAckF851zD5rZa3hjPK0ysx9GWP1OYB9wDl7LxdGwZd+EPc/He68ZkYdmN+A259wb5Qz/q1KWhe+nIJbjReI6TnT/A466wv1I8vju0nJc2HwDrnLO5USxzfB1ohFe14jHy8wuIfLxrYii23GUEKtzboWZpeMNZLrQzH7rnHsqyv2UVv9Ir6GytlVS/Yue9/DXhD4HJDDU0iInLDM7FZgNzPJbIsKXne23SMzAu/yQBHyJ18ReoAXeN9vjwA14lwZKkw20M7Pe/j6amVkDvAHFJppZQ3/+982sSTmr8wEwwn9+HfBeOdcPV7SeRe0AevnPrwqb/wZwm1mo/06PKLa9Ai9ezOz7eC0zZSU9JR2vpcAY83/5ZGbxzrkvgIMF/UzwztPySBstYqjf3+QUvMtTa/1Yh/t9ak7Fa7FZY2btgc+cc08AT+KN7FtancNVpP4lKen1JVJn6AUtJ5rG/mWFhngtBguBhyKUu8PvFJmP1zS/GO9baZ6ZfYjXV+Rx4K9mdg3eJYTSWj5wzn3rd9581Mwa440A+0NgLl4T/Xr/A38/cEU563U78Ccz+5m//ugyypdmDrDYzPY454p1jAWmAU+a2RS8yzMF/g94BNjk12MHUPRXQpsofgxn+5fY8oAM59w3lC7i8XLOLTGz7kCmmX2LNxr6FGCUv4+T8fp8jAYws1/i9UP6W4R9rAFew0si/s85t9vMXsK7DPchXovG/zrn9prZKOBn5o3qewQYGb4h59wBM3vf73y7GHgsbHHE+vt5X7mU8voSqTP0k2cRkTAWoJ/9mn7yLCcYXR4SEQmu/cDbFqObywHXU0aLoUhNUkuLiIiIBIJaWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAuH/B48AODZkXkLGAAAAAElFTkSuQmCC\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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PHoROp0MkEkFFRQUqKioArEcGPR4PlpaWMDw8DLVaDYfDAYfDAYvFQrs4yxQlRgAzIQhCISotRAgDgYC4L8LIOioIKRRpUAFIoSC5t182FDsFnE+0MRwOo7e3FwaDAV1dXSnrFzUaDaqqqlBVVQUACIVCcLvdmJmZwdraGnQ6HZxOJxwOR1xkJh9oCpgiBeE3KtyExNbrxgpCIULIsiwVhBRKAlQAUs56hAtHNinfRMqlCURI+W7duhU1NTVZvVan06G2tha1tbUAgEAgIKaLfT4fTCaTGCE0GAz0gqtQyjECmIlUglDw7GRZNi5lTAUhhUIFIOUsJp+UbyJKbwIRUr4LCws4ePAgjEZj3uswGAwwGAyor68HIQQ+nw9utxtDQ0MIBAKwWCxihFCn02W1Vkph2eziJ1kNoSAIhb/HpoypIKScjVABSDkrkeLtlw1KjgCGw2H09PTAZDKhs7OzILV7DMPAbDbDbDajqakJPM/D6/XC5XKhr68PkUgENptNjBBqNJqU70MpLOUosPNdczJBGI1GRYsnKggpZyNUAFLOKhK9/eQQf8L7KDEC6Ha70dfXh23btqG6urrAKzsDy7KwWq2wWq1obW0Fz/NYWVmB2+3G5OQkCCFxHcalsJw5WynHFLDca04mCCORyAZBKEwqoYKQshmhZ13KWUNiylfuC4qSBGBsyvfQoUMwGAxFWVsqWJYVo3/A+kxlj8cDl8uF0dFRMAwDh8OBUChU8rVSlEehRSvDMHE2R8kEYeIcYyoIKeUOFYCUs4JcvP2yQUkp4GKkfPNFrVajsrISlZWVANbXLAhCt9uNubm5OMsZerGVDxoBzEwyQRgOhxEKhcTzhyAIhTnG5faZUihUAFI2NYn2EIUSQ8U0gk4nAEuV8s0XrVaL6upq+P1+GI1GWK1WuN1uTE1NYW1tDQaDAQ6HA06nE0ajUTEX23IUU+VIqT9nqYJQSBlTQUgpB6gApGxa8vX2ywaWZcV0UaFJJgAJIRgdHcXi4qIiUr65IuybXq9HXV0d6urqQAgRLWdGRkbg9/thNpvjLGco0im1mMoFpa05VhAKv8VwOIxwOAxg/XyQWENIoSgNKgApm5JoNIpQKCTW6hT64lHKGkAh5Ws2m/NK+SrpAhsLwzAwGo0wGo1oaGgAIQRerxdutxsDAwMIhUKwWCxihFCr1ZZ6yYqmXLuAlXx8AkgpCKemptDY2AitVksFIUVRUAFI2VQIjR5TU1MIBALYsmVLUbZbKgEopHy3b98uTuwoZ6R8jgzDwGKxwGKxoLm5GTzPY21tDS6XC729veA4TrScsdvtKS1nzmaUKqZSIUTxy4FEQbiwsICmpqYNEcLEphIKpdhQAUjZNMSmfFUqVVEjHcVsAhG2NTIyUvYpXzlgWRY2mw02mw1tbW3gOE60nJmYmAAhREwX22y2uFqusxElR9NSIUzzKFdi104IASEEoVAIoVBI/DsVhJRiQwUgZVOQaOpaTEEmbLNYgjMSiWBlZSXvlK9SyfdzVKlUcDqdcDqdANaPDbfbjaWlJQwPD0OlUonpYovFsuk+v81IOYrWVCTzIEwUhMLYOpVKJXYZUyhyQwUgpaxJ5e1XbAFYrO0JkzV0Oh127Ngh63sr4SJbiO2r1WpUVVWJKfJwOAy3243Z2Vn09/dDp9OJEUKz2Vzyz6DQKOF7zpZyXLNUkglCnucRDAbFx2LnGAtdxhRKvlABSClb0o1z22wRQEIIRkZGsLy8jP379+P06dOyb+NsuahotVrU1NSgpqYGAMQO44mJCXi9XhiNRjFCaDAYNuXnUm77tJkFYCJUEFKKBRWAlLIjcZxbshQey7JFrQEspAAMhULo6emB1WrFkSNHwPO87OJWKReQYqbSBQwGAwwGA+rr60EIgd/vh9vtxvDwMPx+v9hh7HA4oNfri7q2QkC7gMsLKggphYIKQEpZIYxo4jgurb1LMY2ZgcJFHF0uF06dOhXX5SvUDFHkh2EYmEwmmEwmNDY2ghCCtbU1uN1unD59GuFwOK7DuFwpN4FwNgvARFIJwkAgENeBTAUhJRNUAFLKhmzGuZV7Cjg25Xv48OG4yFMpomRnKwzDwGq1wmq1oqWlBTzPY3V1FS6XS7QaMplM0Gg0sNvtUKuVf0otx2OHCsDUCOdCIROSTBAKI+uoIKTEovyzFeWsJ7HRQ0rXZrFTwHIKzlAohO7ubtjtdhw5cmTD/m5mAaj0fWNZFna7XYz+jY2NIRKJwOPxYGxsDAzDiOliq9WqSMuZchRT5bjmUpFMEMaOwwQQN6WECsKzFyoAKYom13FuxU4ByyVclpeXcfr0aezYsQOVlZUpt1UI6EU2exiGgdlsRl1dHQCIYnBhYQFDQ0NQq9WiIKSWM7lTrsemEm5mUgnCaDQqPkcQhGq1WpyeRNn8UAFIUSxC1E9KyjeRcksBE0IwPDwMt9u9IeVbLJRw0i+2cM+X773shkqlwseuXxeAGo0mznImFArB7XZjZmYGq6ureGgU0Bv0+OAVW2AymUrymZejmCrHNQPKNLBOVkMYKwgZholLGVNBuHmhApCiOHJJ+SZSTj6AiSlferItH3RqFhp16uNTp9OhtrYWtbW1IITgyZVBhIJBjI2NwefzwWQyiRHCzWo5IwflKgDLYYRdMkEYjUYRDocxPDyMbdu2UUG4SaECkKIo0nn7ZUO52MBISflSisOUJ4C+WS+O7qwEK/G4e/0+O7RaraTnMgyDj1y1Xfw3IQQ+nw9utxtDQ0MIBoNxljM6nS6n/chEOYqpclwzoMwIYCaE8y4hBF6vFwzDIBKJxE1aiq0hpIKwfKECkKIIpHj7ZYPSbWAIIRgaGoLH4ylZyleJlLIJ5E+nlrCwFsKl2yqgVRf+gibUD5rNZjQ1NYHnedFypq+vD9FoFFarFU6nE3a7HRqNRpbtlqOYKsc1A+URAUwFz/OiuIttZhKsuGIFYeIc43Ld57MNKgApJUeqt182FFtIZLO9YDCInp4emvJVGHd2NiAQ4aBNk9ItJCzLwmazwWazobW1FRzHiZYzExMTIITAbreLHoRK7DAuFIIYKTfKdd1A6rUnE4ThcBihUEg8fwuCUJhjTM9xyoQKQEpJycbbLxuKfcKRGgFcWlpCf38/du7ciYqKiiKsTKHwUbBL/VDNvATwEfDVu8DV7AdQus5JrZotmfiLJcLx+OGxGVy6zYnWivV0MLDeFOXxeOByuTAyMgKVShVnOSNVaJRjNK0c1wyUZwpYQKp4TScIgfVzo0ajEVPGVBAqByoAKSVBjkYPJZEpAhib8j1y5EjB6rvKgogf2mP/DdY1BKLWAwwL1exLUOt/C3X77YiorKVeYUnheIJpTwDHp1bRWmEUH1er1aisrBRrRcPhMDweD+bm5jAwMACtVhtnObOZLrLlKgA3Qwo4W2IFoXBODIfDCIfDANYFYWINIaU0UAFIKTq5evspmXT7EAwG0d3dDafTSVO+ANR9D4J1D4O3NgKvfBYEAONfgv3UDxHY/Q7Zt/nsiAtPj7jx/kvbFBHlS4deo8JHjm6Bik1/nGi1WlRXV6O6uhrA+nHmdrsxNTWFtbU1GI1GURAajca4467cjsFyFYBnQwQwHbGj6QAqCJUGFYCUoiI0esid8lUqNOWbQGgNqunnwZvrRPEnQIyV0CwMQbM6AaBV1s2uBqPgCTKKKqWQi0jV6/Woq6tDXV0dCCHw+/1wu90YGRmB3++H2WyGw+EoK59FgXIVUuUeAZS7zpQKQmVBBSClKGy2lG8meJ7H0NAQVldXFZfyHV3yoclhgFpV/O+ACbjAACBs6guLOuSSfbtX76rG1buqZX9fpcIwDEwmE0wmExobG0VLD7fbjWAwiOeffx5Wq1WMEEq1sikV5RoB3IxNIHKSTBAKGaJYQZjYZUyRByoAKQWH53nMzs7CZDJBr9eX5Yk8G4SUb0VFBQ4fPqyo/Z3xBPGdZyZwfrsDr95TK/l1K4EIdGoWek2eEQGNESA8QMiGCCCwngrmWeWI5UyUizBhGAYWiwUWiwXz8/M4fPgwVldX4Xa7MT09DY7jYLPZRMsZtVpZl4Zy+ZwTKdd1A6URr8lMqQkhCIVCYlOJSqUSo4NClzElN5T1K6dsKmK9/ebm5tDQ0ACDwVDqZRWUxcVFDAwMoKOjA06ns6Db4niCL/xxALvqrHjNgTpJr6m16nDd3hrsqpPeaEEIwVefGINWxeL/XbUl1+Wuv5exEry9FYx3HsSYkBKPBgFWi6CtPa9tCHA8KZuUb7FhWRZ2ux12ux1tbW3gOA4rKytwu90YGxsDwzCi5YzNZiu55Uy5CikaAcyPZIKQ53kEg0HxMUEQChHCcjxOSgUVgJSCkJjyValUJbH3KNaFQzgpjY+PFy3ly4CAJ+sTLKTCsgzOactOmDIMg2t2V8NhlMGImGEQ2XMbtH/7dzDeORBjFcAwYAJuMFE/Vre9BkSV/2cX4Xh88ZFhNDsMeOM5jfmvu4T4wxwMmsKa66pUKjidTvGmJRKJwOPxYGlpCcPDw6LljNPphMViKbowKFcBWK7rBtbrtUstABOhglBeqACkyE4yb79iz+YFzlizFPoEIKR8GYYpWspX2MY/XbOj4NsCgMPNNtnei9iaEL7gI1ANPwr19DGA8OAqd4LbejXCvA3E6817G2qWgUbFYkuVMfOTFUwoyuNLj46gwqTBey5pLco2Z1eC0KhYVFVVoaqqan0doRDcbjdmZmawtrYGnU4n1g+azeaCH/PlKqSUEEXLlXJYezpBOD09DafTCbPZTAVhCqgApMhGbMo3sdGjFAJQ2GYhT2KxKd/Tp08X7eRSypFpckDMtYjuvxPRfXcAIADzyne0uCjL+zMMg3+4Mr90tRLQqVlsqzaiMw8Bnq14uv+ZSahYBv949dYz69DpUFtbi9ra9brRQCAAt9uNiYkJeL1eGI1GmKx21FZVwGAwyP47oAKw+JTj2mMF4draGpxOJ3ieRyAQiGs4oYJwHSoAKbKQyduvlAKwEPA8j8HBQaytraGzs1PWLspwlMeXHhnELYcasL3GnPQ5ShOAhBD8sW8RO2vNcebFGWEYAAl2MAraLyXw+iMNOb/24d55vDy1io8c3QKdRGuZO7oaoM3QIW4wGGAwGFBfXw9CCH7wtzGcOLWIW7a4wESDsFgsYspYjnKIchWA5bpuYP0cp7RmoGwQbGxYlhWFrBAhpIJwnfL9dimKQco4t80kAAOBALq7u1FVVVWQlG+UJ/CFOZyaXS2qAMxnP6I8wbOjbvTOruHDR3OPvJ1NJ99iYNCowIKBRiX9c23LRsBj/Ts7f2s1lgIE5xxqA7AefXG73ejr60MkEoHNZhNTxhpN9rWk5SqkyjGKJlDOawfWaxgTm5diS5KA5IJQmGF8NghCKgApOZONt1+pBKDcIklI+e7atUuc0RqLHBcqo1aFz924K+1zlBYB1KhY3HN5Owza0naLpiLC8QhGeHA8wU9fmsGth+rlaWqRGUII/jbqRqPDgCZH/h3zl++oxOU7KmVYWXq2VJlwz+VnuretViusVitaWlrA87zYYTw5OQme58UOY6mWM+UqAMt13UD5C0Ap608mCDmOQzQaFZ8jmFKr1WqwbGGbsYoNFYCUnMh2nJtKpSpJE4hc2xRSvl6vN2XKt1hNJ0BhxG2+2GUQVIUStl96dATBCIc3n9+EYITHWjCqSAHIEeD3fYswalS4N6YGr5xhWXbdTsZuR01DM3QqbLCcEaKDNpst6UW7nCeBlOO6gfJeO5A8ApiJZE0lsYKQYZi4CGG5C0IqAClZE41GEYlEAGz8waSCZVnxNcVCrqhjbMr30KFDKfe3GE0nAoUQSrmcMMuF1x6oxZQ7gBanER+4rC2r1xJC0Duzhi1VJhgTIpxyC341y+A9F7fCos98ap5wBVBp1m5Yk1K570/DCIQ5fOKabaioqBBHI0YiEbjdbiwsLGBwcBAajSbOcqaYN1ZyU67CFSjMKLhik+8xk0wQJl7/ylkQUgFIkUxiyjebA71cawCFi1KqlG8sxUzLyhndJIRgZGQEU1NTUKvVskyEKNYFe2zZjz+dWsKbzmlIO6VkR40ZO1LUU2bCE4jisf5lLHrDRUmn1lgzN02Eozy+9dcJGHUqfDSHSGEpBNVr99ege3oNmoQGE41Gg+rqalRXr4/qC4VCcLlcmJqawtraGgwGA8LhMBwOhygIy4VynwVcruIVKEwz2WYThFQAUiTB8zwikYjklG8i5VYDyPM8BgYG4PP5JHf5FnMf5RKbkUgEPT09MBqN6OrqApA8Ped0OmG1WiVdENaCUfzro8O4YkclLtlWkfH5sWS7X4veMIIRDryM5/pEceQwavDaA7Wotmw8BiZXIqhXcSj2lGGtmsUth2rRaF+vEySE4PS8D9uqTVBnmH7CE4Kv/WUMDqMGb+wqnkn2zloLdtZaMj5Pp9Ohrq4OdXV1IIQgEAigr68PMzMzGB0dhdlsFlPGSp8sVM4iqpzXXiySCcJIJLJBEAqj65QmCKkApKQl1tsPQM4nhFIZQeeyTSHlW11djR07dkj+weYryjiegOMJtBLsOuQQgCsrK+jt7cWWLVtQU1ODcDgMhmE2TIRwu92Yn5/HwMCAaADsdDphMpmSfjY6NQs1y8BmKPzppbPFjs4Wu2zvd/8zE5hyB/FPr94WN0au2blRaEQ4Hj8/uQKzIYDPNUkbxccTgl+8PIuDTTZsrTLltdYDjWe8AUeXA/jdyQUc5SqxvyH9mD+WYaBmGVmaTAoNwzAwGo0wGAxobW2F0WiEz+eDy+XCwMAAQqGQaDnjcDiKMoEnG8o1dQ1QAZgLwtQrgURBeOrUKQwPD+POO+8s1RLjoAKQkhLh4OU4LqeoXyzlkgLOJuUrx/Zi+czDpxHlCf75ho6Mn3U+ApAQgqmpKUxNTeHAgQMwmUzieyVesBLTc4IB8NjYGHw+H8xmM5xOJxwOB/R6PYD16NQnrtme09qENZQKs04NlmUkzRDWqFhct8OCporMUS0Bjic4PrWKSXcQH7xCnpnHANDiNOD6vTVoTSJUk/Hui1tl23YxiLWYMpvNMJvNaG5uBs/zcZYz0WhUtJyx2+05Wc7ISTmLKCWOgpOKUoR3oiAcGxvD6dOnS7iieKgApCRFirdfNig9BZxLyjeRfKNyXa0OLPvCkj7rXLe16g/hl3/txv5aHbq6usSTk/AdJ74nTwgYnCmmTjQA9nq9cLvdOH36NMLhsGjv4XA4cqofzPY4W/KG8bUnRvHm85vRIlH8pOO2w/VZPX9bhQ5Go/T91KhYfPTqrZKivNmgYhlsr84voqhkUl3QWZaFzWaDzWZDa2srOI4TSxgmJiZACImznCl2U0O5N4HQtcuLz+eDyaSc3ykVgJQ4svH2ywYlp4D9fj96enqyTvkm214+AvDavbUF3ZbX68WvnjyO0z4DLjm8VdLF8JtPjoMBks6hZRgGFosFFosFzc3N4DgOq6urcLlcGB8fl2TvkS8RjgcPIBjhsnrd3GoQBo0KNkPxI0QmXe6NNX8b86DVaUCdTS/zqtIztOhDi9OwoYEjH8JRXrIQlhrRUalUcSUM0WgUHo8HLpcLIyMjUKlU4jEptaY1H2gTSGlQ6tqFrIlSoAKQIpKtt182KDUFPD8/j6GhIezevRt2u73g25OLbAXg3NwcRkZGcN15e3A5dGiwSxMQDqMGek36EykhBMu+CCrNWvHiCqzXD3o8HjGtrtVqxYtzqvrBbOs262x6fPa6HZKfL6z3q0+MQati8alrc09Vx7IajELF5C7upBDlCR7qnodRq8InXr2tYNtJZNoTxIPH53DhFifOb8+uLCIVk+4AvvHkOG49VIdDTZnnHOea0lOr1aisrERl5Xr3djgchtvtxtzcHAYGBsRj0uFwwGw2F2SGsRKFiBSUKqKkoFRLK5/Ph/r67LIMhYQKQAoAiFE/uVK+iShNAPI8j/7+fgQCAdlm+RbbBkbKtoT9DAaD6OzshEajgTOL7dzRmXkO7e9OLuCJQRf+/rK2OGGp0WhQVVWFqqoqAGfqB8fHx+H1esVuTqfTKdYP9s758NMXVvDJhjAqzfLNV46FYRi84UgDrBK89qTyg+enoGIYvOOiFtneMxGNisV7Lm4puoF1nU2Ha/dUZz0iLh12gwZGjQo1FmlNG3LVdGm1WtTU1KCmpgbAmWNyYmICXq8XRqNRvIkxGo15b7OcI4BA+Y5mVKp49fv9NAVMUQ6FSvkmoqQaQL/fj+7ubtTW1mLnzp2yneTk3MeFtRBmV4LY35g8OiJFAMZ2M8u5n4mc0+pAOMqjNoN/XWL9oNDNKdQP2mw2RAMMVMx6I4nHH8Ejpxdxw75a6GSumdtTL71xQwpXd1TJmh6NJcLx+M6zkzi/zYG9GTp8CwHLMNhdJ+/nZdGr8YlrpEcxC1XUn3hM+v1+uN1ujIyMwO/3J21yyoZyjgCWM0qNAAo3vkqBCsCzmHy9/bJBKTWAcqZ8k21Prgjg1x8fgT8cxa6bdicVFpm2tbS0hP7+/py6mbOl0qzFTQek2aAIJOvmXFlZATc7i1tawhjoPY4l3oThZYJlrwP19uJblqwEIjBoVJLq1LbkaemSDoZhEOEIXP78J+kobXygVGIFYITj8cLECs5ptYOVeM5y+yP40qPDeP2RhpTin2EYmEwmmEwmNDY2Yi0YweicG+FwQLxJsVqtYoRQStag3COA5YpSBSCtAaSUHLm8/bKhVBFAYR9jU75dXV0FsYeQUwDec3QLXL5IyqhS7LbmVoIYWPDioq3rpsvDw8Nwu904cuRIUXzRghEu7RQOYL3g/1/+OITr9lbjSLN9w9+FebEsy0KlUqG9vR0utxv1JhemBnqwUOBarUR4QvAvfxyCTs3iM2lqDIshqNQsg/cmacI5m4gVgC9NruAXL8/CrFVJjoiyzPpvhsvi+/r6X8bh8kfwmeu2o6WlBTzPY3V1FW63G9PT0+A4Lq7DOFnXu1JTkZsdpX7uQlRZKVABeJZBCIHL5YJarYZOpyva3WkpU8CFSvkm255c++gwauEwpo4wxKa3H+6dx/xqEAcbzOjv64XNZsORI0dk2c9wlMdfh124eFtF0gkToSiP/3pqArVWLW4/krpekGGAQITDqTlvUgF45nnrwlaj0aCmuho1r/gPBoPBuFotk8kkCsJCTINgGQbX7qnJmNYW1lwKfKEo/nhqEdftqZG9m7YQPDvqRvf0Kt52QbPkyJ1A7LoPNtpg1Kiws1b6hdRm0OCfr8+uWehtFzRjyhOA4ZWbG5ZlYbfbYbfb0dbWBo7j4PF44qbmCILQZrNBpVIpxo/ubINGAKVBBeBZhODtNzU1hYqKipxqWnIln7FsucIwDFZWVjAzM4M9e/bAZsvcbZjv9orZBMLxPLqnV3BHZwNml9zofvlFbN++XWy6kIOXp1bw294FVJm1SaMtOjWLOpsOXa32tO+jUbH4wms6cl6HXq+PGw+WOA1CMP91OByyRXcv3ppNu0zxOTnrxdPDbnTUWtCRhRgqFb8/uYBwlEcucihWSGnVbFFqISvN2rSNSCqVChUVFaioWI+8C13vS0tLGB4ehlqtRiAQwNraWlEsZyhnUKoApDWAlKKT2OihVqvLthZIKjzPY3p6Gn6/H+eee25RJgIU2wbmhck1/Gl4Dte062DnPDh06FDaaBghBIML6/NipUYlDjXZYNNrsDWNyXC25snpkCKik9UPCv6Dk5OTIITE+Q8q8UIgB4eabWh06CVFKQVKGZH61LXbwZPMEdO51SC0KhZOU7z4UnokLbHrPRQK4cUXX8Ts7Kw4RlGIWqeyQVIK5V67qOQUsMUib0NVPlABuMlJ5u3Hsiw4Ljvj3HJCSPlaLBaYTKaijYOSGgFcDURAgLxMiBmGQUeVFh63C3V6Nfbu7sp4wjs27sH3n5vE3ec143CaNGwsGhWbVaqtFMSm5oB1SyO32x0XiRH8B4tRP1gs1CyD+iIbQqcjwvFQs6mbyViGQaYJe4QQfPmxUahZBp+/cWfa5700uYIaqw6NJWgQkoJOp4NGo0FHRwcIIWIZgzBG0WQyiTcqBoNBUcelUgWUVDiOy2kSUaEJBAIFKVnJFeV9QhTZEBo9Er39SlGPVywEw+Pdu3eD4zjMz88XbdtSBeBnHu4HAHzplj05byscDmN+fhKX794m2Vh0b70VNx2oS2npIXcKO8oTTLkDaJXRP04KarV6QyRGiA6ura2JF16n05nVybh3Zg1Ok0ZRoksKgws+VFu0sBk0BYsAEkLwzSfHoVWzeFceXogMw+DucxvFurtU8AR45PQS9GoV/v7ytoxrK5S44niCj/+2H7vrLGk9MxmGSWqD5Ha7MTQ0hEAgAIvFIkYIi9G8lY5yF4BKXb/SbIGoANyEZPL2U6lUmy4CyHEc+vv7EQqFRMNjt9td1FS3VGH9xnObkM+ypqenMTc3h6ampqxc5Q1aFS7fIV99YCYeOjGHp4Zd+PDRdslRmkLUUep0urj6Qb/fH1c/aLVaxQtvqmgxTwi++7dJ6NQs/uWG1JEppRGK8vjPp8Zh1KqyboLIhnFXAH8dduHucxvzfi8pnoMqlsGbz2uCOcPklShP8KVHh1Fr1cuytkRYBiAEmF8NZfW62DKGpqYm8DwPr9cLl8uFvr4+RCKRgtS1SkWpAkoqSqwBVGLZFRWAmwwp3n6x9iibAZ/Ph+7ubtTX16Ojo6Ookc7xZT+eH3Pj5oP1ksVLKnPnVBBC8P9+eRJbKo24sCKAaDSKlpaWol8UsuXyHZWwG5QVMYv1ehMuvIK1x9TUFHieh91uh9PpjKsfZBkG77m4VdL0EJ4QPHh8Drtqzdgls4FytujULN50ToMowAsVDeN4gvZKI/YV0ai6WsIUETXLQMUyqLcVJqLGMOlT1VJhWRZWqxVWqxWtra3iXG232y3WtcZ2GBc6vbkZBKAS119ov91soQJwk5Do7ZfuQFOpVAgGg8VcnojcF6DZ2VmMjo5i9+7dG7p8iyEAf3V8FkNLXly7t7ZgtZUMwyASieK50xN49ava0dTUJF4UlIzDqMEVOyuzek0wymM1VLzodKK1RzQa3dDJKaSL2yosko5dBsCiN4znxjw5C8CVQAQ/ODaN2w7V5z0S70DMDYeU358/zOHzfxrC2y9oRpNDWuR2S5Upry7vQvKRo1tKvYSsUalUcXO1hePS5XJhZGRE9M0UBKHcYqfcBSDP84qMACrtnE0F4CYgMeWb6QRfqhpAIUImhwDkOA6nT59GJBIRU77Jtlfo/Xznxa1YC0Vh1KrgLpANzMzsPK6p8aLz6gNio0MxLWeKyQPHFzC/FMQ5B0rTrapWq1FZWYnKynXhGgqFxOjg2toajEZjRv9BhmHwzgub4x7zhaIwaFWS/e9c/gj+2LeI/nkvvvo6abWigs/iwUZrXp/dajCCtWAUI0t+yQKQUlgSj8twOAyPx4OFhQUMDg5Cq9WKgtBikXajko5yF4BKTAEHg0FFNYAAVACWPYK3X2KjRzpUKlVJBKAgPPM9sQgp34aGBjQ1NaXuOszTe9DtD8Oq10CVpnVRp1FB90rButyijOd5DA4O4jvHFmF1VOAK65lITqK4JYTgsdOLqLPpsbu++PNigfUu0NVgFBWm3CNWV++sQN+wTzFpEp1Oh9raWtTW1sbVDw4NDYlR9Gg0CpvNFjcaLHb9EY7HP/2mHwaNCv8iMV3YVmHE+y9tQ5NDevr84d4FPDnoQtWV7SmFm5QbsFqrHl967S6oivgVBCPrUd/YiTKT7gCeG/PgNftri7cQGfjWXyfAssBbz2/O/OQc0Wq1qK6uRnWCUbpwo2IwGMTItdFozPr3VO4CUInrFzq/lQQVgGVKbMo3WaNHOkplAyNH5FFI+e7ZswdWa3qhk8/2ghEO//TQKThNGnz2hl1Jn8PxBHOrQTS8Ul8lZ2Q1FArhxIkTqKiowLtffRAzKyGwMUI0mdj81YlZ6NQsvnzLXlnWkC0PvDSLRW8Y77iwOeNouFTUWnXw25R15y6QrH5QaDzq7e0V6weF0WBCBEKjYrG73oLDTdnVfh7NMn3+ql1VaK80otGef81lsqkvheSfftMPhmHwrzedSSO/OLGCkSU/olx5ORYMLvoAFLfoP9EoPRAIwO12Y2RkRBw/Fms5kwklCqhsUGIEUGkm0AAVgGVJMm+/bChVCjif7camfLu6uiQVQeezPb1GhQu2OHFOW+ppEA/3zOHYuAfvu6wd1RadbBFAl8uFU6dOYefOneKUgZaK+DvHxG0xDINPXbczZ+ElB1fvqsKEK5ByDT3Tq+hf8OHmA7WKifClwheK4pMPD+DaPdW4bHtyIcayLHQ6HaxWKyorKzfUacXWD77lvNSRarkw69Q4lEFkKnU02dUdVRsi7dfvrUGY40t6TOeCIGJL1YjAMAyMRiOMRiMaGhpACIHX64Xb7RY73y0Wi3hsxkauBagAlB+fzwejsbiWWJmgArDMyCXlm0ipbGByFWRerxc9PT0ZU77JtperION4giqzLm2n4UXbKmA3alD1SpF+vjWHhBCMjo5icXERhw8fTjuqL9m+VZpL6x1WYdKmTf9+/9g0QhEeN+2vLWp6MRe0ahY8AcKc9OMnVf3g9PT0hrRcqYx/lSoAr+zYaE+kYhkY2OJcxB88PovhRT8+fLRdts9HKZ81wzCwWCywWCzi5Jy1tTW4XC709vaC4zjRcsZut0Oj0ZS9AFTi+pU2BxigArBsyOTtlw3lFAGcmZnB2NiYpJRvIvkIspmVIP7cvwiViknpnecwanHxtjPRoXwEZyQSQU9PD4xGIzo7OyV9v+XWBPKZa7cjFOXT1lQqpblFo2LxbzcnT/0nMrMahrOCbGjwSFY/KBj/BoPBjFGYQqIUcSKFYhwPQ4t+cLy8n4kSRQiwfp6y2Wyw2Wxoa2sDx3FYWVmB2+3GxMQECCHQaDTQ6/WKjKRJQYmfPRWAlJzIN+WbSKmaQLLZLsdxOHXqFDiOk5zyTSQbwekNRnF6fg2Hm+1gGAaNdj3edUkbaq3S66lyFS8rKys4efIk2tvbUVsrreA9077d++BJ+MIcvnrbXsVc6PUaVdml8zIxsxbB97o9uGaVxU0HUn93sfWDjY2NSaMwgv9gbP2g3BBC8MRECPf39+Fz1++AKYORcq7811Pj4Anw7otznwpSTP7hyvysYpa8YQQiXFzzjdKmPqRCpVKJoxKB9aam4eFh+P1+vPTSS6IljdPphMViKYt9UiK0CYSSNdFoVJK3XzaUsglEynaFlG9jYyMaGxtz3udsXvejY5N4YdyDf75xl1jP1+zMrl4jVpQRQsATpI12EUIwNTWFqakp7N+/P6uTQ6Z9YxjhP+mfgRKE4kd/OwQ+6MN/FLiPheMJftMzj/PaHKix5p46rzGpcfkWKy7ZlrpWNBnJojCx9YOFvOjadCxUIabgYjzXw6lnehWhKI8jLXYA5RGt/Jc/DiHKE/zHLbvEtQo37OWGWq2G0WiE1WpFXV0dwuEw3G43Zmdn0d/fD51OJzaUbKbZ2oWGNoFQJJOtt182lCoCKCUlm0/KNx9uO9KIQ80OSdMFUhEbAfzyo0OIcDzuvXp70u+O4zicPHkSDMOgq6sr64hPps/y8zftzm7xCoEngC+SXRQ1mYVIJtz+CB45vYTVYBRvOif3EWEqlsGV221w5mF9A6z/JisqKsSmH+GiOzMzg7W1Nej1etF/MBdbDwFCCA7X6fCmo9LS27nyzjzmAX/nb1MghJSVAHz/pa3whbi4dZZLBDAZsSlUrVaLmpoa1NTUAIDYYTwxMQGv1wuj0Vjy2tZElLCGRGgKmCIJKePc8qEYBsnJSCc85Uj55oPNoBEvOLkSKwB31JjRP+9N+t0JPoZNTU1obMxNfCilVg4AJlwBPNq/hDd2NUCjyu+C94UbtmFgYCCr1/y/X50GAPzH66SL3kqzFh+9emveUzaA9Wji/c9MYluVERdvq8j7/YD4i65g6yFEB/1+PywWi5i2K3b9YKH52NVbwfFnjm0l1nMl0lqxMVtQrhFAIP1nbjAYYDAYUF9fH1fbKqSNhdpWh8ORtpHtbMPv94s3eEqBCkAFkTjOrVAnvVKdlFLVrcmV8i01sft3/b46XJ/kOXNzcxgZGck7wlloARjheMli7tH+JRwb9+DmA7WwGfI7ZmP369ScF8+NeXBnV0NaX7orOyqRyxHTIINfHrAeBSQgWAlGZXm/RDgC/HFwFUeaK7C3sRGEELF+8OTJk4hGo3H+g+lunsohmlZp1iIaIwBTrfmXx+fQM7OKj796W8H2yeUL4zvPTuJdF7VkXS9ZDsI1FVLXnljbKhybbrcbp0+fRjgcjuswLsbNilKFN7WBoaSEEIJIJAKO4xQ3MFoukgnA6elpjI+PY+/evbBYcpubmgvdUyuw6NVoq5SvKDedKBNMg4PBYMrRdXJtKx8IIZheCeJf/jCEO7sacH575tq2Ozsb8Jp9NbAZpO/TXwaXsbAWxi0HU3sC9s97EQhzGcXddXtqJG9XDv467MIDL83iczfsEB8r5NQHQghmPEGcUDFocqyn2KxWK6xWK1pbW8X6QbfbjbGxMXFObLL6wWRiaskbxsnZNVy81amI886xcQ+eGnLhzec1wW7UpBSAfxlaRjQLm55c6F/wYXDRj3FXIOu5zuUgtlORq3iNPTZbWlrA87zYYTw1NSU2O0m5WSn22guN1+st6jVOClQAKgA5vP3KgVgByHEc+vr6QAgpesqXEIKfvTgNjYrFJ6+TNppLCqkinMFgECdOnEB1dTV27twp6ft9dngZz4958O5L25JG4goZAbTpNdCpWdRIrIfUqlk41dnd2T94fA4cT3DLwfjO2djPRqkjwLwhDjwhRZuWoVGxePuFzSkbiqTUDwqCMNkx85MXZ9Azs4Z9DVY4jPndmMhBjUUHnYaFUbte05lKSP37LYWvc+1qsaOjxgybIfvzk1KFiBTkWrtwM+JwOACsNzUKgnBsbAwMw4h/t1qtsnS/K9W6RpjIoiSoACwhcnr7lQOCQBJSvk1NTWhoaCi64GUYBu++pB0GrbyfdzJRtrS0hP7+fnR0dIg2C1KYXQ0hwvMpRUaybQUjnCydnRa9Gl+ReHGdWw3hVyfmcMvBuqzq6b7wmp3gSfJyBKXUNqbiVbuq8Kpdyb0hC0U2tZXJ6geFsWBerxfAeimCw+GATqfD3ec2YsodLJr4i3A8ojyBIcWx2uw04D0Xt4r/ljOS9tyYG5PuoORpNCqWgT3XzyW4Avvc01AHngex1INrPBfQZB7DpgQKJV7VanXczUokEoHb7cbCwgIGBweh0WhEQZhr97tSBSC1gaGIEELg8XiwsLCAlpaWTRv1i4VlWSwvL2NycrLoKd9E6jPUf52YWkGE43GkxSH5PWNFGSEEw8PDcLvdOHLkCHS67LqLX3uwXvK2AOCpoWV879kJ/NM1O5IWpBcKQghYJnvRttn8AJVK4liwlZUVjI+PIxgMoq+vD9FoFDabDZVOJ6JRfVEi8R968BSiPME3bt0t6bwnpwD88QsziHAEN6fxbEy2fQJsMPpOh2r4UVQ//e/goiFodLp1Txy1AaGL/hF83cEcVl5cihW91Gg0qK6uRnV1NYAz03NmZmawuroqTs9xOBwwmUySjgOlRl59Ph9NAVMgRv0EB/ZSiD9BQBRr29FoFNPT00Xv8s11P//ryVEQgqwEoBDhDIfD6O7uhtVqxZEjRwryGScKwCaHAQYNm3YUWyGos+nx9gvlM/tN3K9kBrtKohzrvHQ6HVpbW8X6wZWVFbhcrrj6QSEll+lCOuEKoMmhz+ozuG5PNZZ9YcmvCUY4PDYWxNYd+Ue477txJyJcdt/ZFx8ZAU8I/vHqrZKezy72QfvcVxHSmBDVWKAVCv/DPuj+8lkEr/smiFmZ5Q0CpRJRidNzhOj12NiYGEETjs9UljNKjgDSFPBZTGLKV61Wl8SQGThjylwMIba2toaenh7YbDbo9cWJMggIljfZnhA+fX0HeD67qBbDMIhEIjh27Bi2bdsm3tVm01GbzbZihVJrhRFfu31/2tc8NbiEHzw/iS++dk9WDRul5NO/G0CUJ/jmbXtKJrTCUR4cSZ2yLDdiP8fEKRDhcBgejwdzc3MYGBiATqcT/QcTIzCn5rz48mMjuOVgXVYp8auSzP1NR++sF3+biaBrahXntUm/IUvG+jSa7F5TbdFm1eGtPvkLgGFBVBowXExNsNYE+PxQD/4BkYN3Z7eIIpPLOVNuEqPXhBD4fL6k4xSFcgZA2QKQRgDPUpJ5+6lUqpIKwEJ7ARJCMD09jYmJCezduxeBQAArKysF3WYiwn5me0LI1hBamOrh8/lwwQUXiO3+ky4/vv/cJG470ogtVdnXf4SjPD73+368oasJO2rO3D3m0gQS5giQYTqJEojdr7+/rA2+MJdS/BFCMLocQFtF4Qxof3hsGhxP8NYLknf6hrnie2rmSqZjRqvVxqXkBP9BIQITO794S6UR1+6uxrmtdnj8Efz0xRncnGUtqBT21plw9z4zjjTbZH1fqfzdeU1ZPV+12AuiswIRHokt7ERjADt3XL7FFQiO4xSXRmUYBmazGWazGU1NTeI4Rbfbjb6+PkQiEdhsNqjVakXWEQeDwaxLgQoNFYAFJp23X6kmcgjbLqT4jEaj6OvrEyddqNVqhEKhou8vy7IFOxlMugNwGjXQqYDe3l5oNBqYTKY4ryezXg29RgWrPrefWiDCYcIVwNNDy3kLwCt2VuGKnamjL0pIZSauIZNoHljw4dH+JbyqoyongS2FS7ZVIBRNftx6ghw+99cJvHpvBK87lL5uUwkQQrAS4hGO8tCqM1/gDQYDGhoaxAiM1+uFy+US6wd322yI+FQIqoyI8AT+sPznFBUDtNg1skfRC4ZKBxAOBACTqAB5DlArs5whFqXW0cUSO05RKGdYXV3F5OQkvF4vVlZW4ixnlBAVVNpnSgVgAcnk7VeqmbzCtgslxoSUb0tLCxoaGsTHSyF4CzX1JBzl8Ylfn4Ka4fF3W8NobW1FXV0dnn322bjnOYxafPDoeu1QMMLhngd6cOc5TbhgizRHeJtBg/98w/4NF79CCttyor3SiKOoRLNT2kU1HOXx/LgHXS12SQJI2EYqzFoWWjWLjtrSpnbCUR6PnF7EJdsqYE5jWMzxBP/xnAfO06fwVQmTUzieiBFjhmFgsVhgsVjQ0tIi1g+63W643eM4z8wg6uHhYZ2S6gelUm51lpEtV0LT+1NAZYuPABICJhrEY/qr8MjDA/jYq7YqVtSW22cOQJyfHQwG4XA4UFdXl3S+ttT6VjlR6rmaCsACIcXbr5Q/sEKIMSHlOzk5iX379m0oeC2F4E0UuuPLfvyudx5vvbAlr5OvVs3i2m0msL5F7Nt3QFJxL8swCEZ49EytShaAQPKOWSWNgpOTTPvFExLXjalRsXGR0UxMeYLonl5FvU2fVthJRc0y+NyrmlFRUVoBuOANYWw5gK1VwbSfB8sAV7SbcP7uzI07Dx6fxR/7lvDFm3YmrRlNrB8ULD3m5+fF+kEhXSy1gzMZ2YgRf5gT/QNLRXT7ddAMPwrV6jx4/Ss1i3wUjH8ZxNGOPrQgzIUVX4pRbgJQQKgBVKvVqKysRGVlJYAz/phCfatWq42znCn0/irR45cKQJmJTfkq2dtPbjGWmPJNFm6XO+pICEEoyqftDEzc5h9OzuPZERduO9IAp8SO2W88MYKXJ1fESBzHcTh9+jS2GiPY03Wu5KYWrZrFd+86JOm5sRBC4PJFUBFTWyU1sukPc9CrWbAKv9hIYdwVwD//fhDvv7QVextyG6PXWmHAbYfrFWF4LCcNNj3uOrcRc6shrAQiaZt8Lmo2YKsE0Vxn00OtYiQLqkRLj8QOTrPZLDaUZDMjVupoL6Ep5R0XNqMzz7neeWFwIHj1vyLw+JdhXu4GQwIAgOiWqxE5eDfepkt+s9A9vYrfnVzEh65Ibv5OkUaq5sZYf0xgvSZPmFCytrYGo9EoCkKj0SirWCtVqVcmqACUEUIIwuFwXKOHUpFTjKVK+RZymwDwrh+dQDDK4dt3Hkx5wuQIg9VABEKA7u/Ob8HNh+oliz8A8IXWOwDVLAO/34/u7m7U1dWhubm5KN/x08MuPD28jDed24w62/qFU0oEkOMJ3v3j49CpVfjvOw7ktO3VYBTjy/6cBZecaFVMVoIkGSzDFN0qBwDmV0P47O8H8enrtkve/oQrsD6RxZq5cJxhGOjULD7/x2HoNSy+cduepM/LJpp2XptD7LrNpZPdYDDAYDCgvr5erB9MnBErCMJkF+zvPjuJQITDbbulGQLXWLSw6tVocsgz4zkfiKkas7vfCYuWoMqiAzE4AE36iPNTwy4s+8JFWuHmRWrTn16vR11dHerq6kAIgd/vFw3ThakdsZYz+RAIBBQ3BxigAlA2hKhfuYxzk6MJROh8nZqaSpryTURuAXjLoXr84eRC2gvT97rXoB0cxxdvsYNhGGjVLCrN2XVi/cPV2wFAdKvfvXs37HZ7PkvPin0NVnCExHUmSxGAKpbBrlorDkvonuQ4DqdOnYLP50NFRYWYtnt62IXBRR/aKo1pa8vkIt1+1dn0+M/b9xZ8DYVg0hOAP8JhbjUkSQASQvDZ3w9CxTL4r9dL22eNisVbzm9CszOzAEpMpadj2RfGT16YwaXbK7A7y3m4ArH1g83NzeKMWJfLhfHx8biRYDabDSzLio03UkWr06TFv928K6f1FQJCCPyMCQ9PAFd26JEp5vzui1qyNpymbCQXGxiGYWAymWAymdDY2Bh3wzIwMIBQKASr1Soeo1ptdjeRSpwCAlABmDdyjHMrRcFtvjWA0WgUJ0+ehEqlSpnyTURuAXi0oxpHO6rTPudVW80gBlteny/P8xgcHITX60VnZ2fWP/58sRo0uGRbZdxjUmsA/+HqbRmfEwgEcOLECdTW1qKxsREej0dM29UZzahrsELLKDOFkQvZ1IkFIlzW/n+n57yw6NVoiJk2c6TZju/caZf8HgzD4P2XtsKQZbTz/Pb0PnmEEPAE+J+nJ2A3anCrhM5lk1YFvYZFhUm+tHnijNhIJCJORhocHIRWq8U1LU44nRXw+/2Kv6FOBs/zGFgK4a9jfmyvMWNrhi51htnQM0zJATk8DJPdsKyursLtdosDDYQItt1uz1gGRAXgJiSZt1+25OpTly/51ACurq6it7cXra2tqK+Xbn0hVQD6QlGYZIo2tTl1qKrKvUA/FAqhu7sbTqcThw4dSvsdL66FEOGK05ghVxOIMKt49+7dsFgsiEQiqK+vF9N2a2trcLlc6O3tBc/zsNvtcDqdsNlsBTlmC9XcMrcawjMjLly81YmfvzyHw822jHVik+4APvnbAdx6uA6v2pX+RkOAEIIvPjIMtYrBt96wL681FyLtTgiBWsVCo2LRktA5HeF43P/MJG7cVyOWGgDrTUhvOT+5B6JcaDQaVFVVoapq3aZIqB8cHx+Hx+OBWq0WTamzqR+UE0IIhpf82FIprT6MEIL99WbsbK5Cva30aWmplHtzWSE8DFmWhd1uh91uR1tb24YJOgzDiJYzyc6NXq+XCsDNQqK3Xz4pXyEVWwoBmG00LtuUby7bfHbEha8/MYJ/evUOdOSYboolHxsYl8uFU6dOYceOHWInWSqiHI97HuhBwBvCJRfltLmsyEUoCc8XXjsyMgKXyyXOKk68IWAYBlarFVarFa2trYhGo/B4PFhaWsLQ0BC0Wq3YBZpPl2cx+NWJOTw76sb57U40Ow3YIqEDuMKkhV7DYmuVKW2UPvZxhmHwoaPtOfs+Fotk5sbzayE8O+qGw6jBbYdL62kYWz84NzeH1dVVRKNR9Pf3IxQKxUVfNJqNkUlCCD74i1PY12DJ2sg5FafmvPjZS7O4cV8NDjZlLqvgeR5ajQpVNuX7/sVSjhYwsRTjepqsA144Nw4PD0OlUkGn02F+fh4XXnhh1mPg3vzmN+O3v/0tqqur0dvbC2D9enTbbbdhbGwMra2t+NnPfiZG0D//+c/j/vvvh0qlwle/+lVcffXVkraj7LOUAklM+eb7QynVNJBsU8DRaBS9vb1Qq9WSU76JSBGAzU4DzFq1pMJ3qdvMRSiNjY1hYWEBhw8flhRxUKtY3HqkAf6ZYK5LzYrE4657agUmnTqlGTIhBHd/7yWwDINvvWEvunt6YDIacfjwYcl3y4m2CsFgcMOUCOGkWKw0eYTj8dSQC0da7GlF15vOacSVOytRa9Xhmt3SonlGrQrfvH0v/jbqxpNDLtzR2QBdgndgsmMr1zq5YpDu4t5oN+CLr+mAU8ZUr1zo9Xo0NzfH1Q+63W5MTEyAECLazQj1gwzDYC0Uxd/GPLIJwG3VJly7pxodtdIu5OVgppyMcl23QCnWnxjBDoVC6O/vx3e/+1186EMfgt1uh81mw4kTJ7B3796M67v77rvx3ve+F29605vEx+677z5cccUVuPfee3Hffffhvvvuwxe+8AX09fXhJz/5CU6ePImZmRkcPXoUAwMDkq7RVABmgRwp30SKMZIt1XaFCGYmck35JiLl82qwG/Dfdx4Q/x1rRJsL2X6+kUgEPT09MBqN6OzszOpEcsO+OjzjHQUALHvDiPJENiGbiccHlqBmGbzn0vakf2cYBiqGQYVRhU/99GlYbA7ce/3ODc/JBr1enzJdzHFc3EVZ6g1D4hr+NurGd56dwldu7khaFuDxRzCw4EOVWZs2ZWrUqnKeFGLVq6FmGWhU5RsVSSTKE4Sj/IZayGIdr9mQKFpT1Q8uLi5iaGgIGo0GTqcTX7mhLessRTo0KjZj2cCEK4DP/n4Qn7lue9lG0pQwBzgflDALWKfTYd++ffj+978PALj//vvx5z//GV/84hfR09ODnTt34vLLL8cVV1yBrVu3bjhOLr74YoyNjcU99tBDD+GJJ54AANx111249NJL8YUvfAEPPfQQbr/9duh0OrS1tWHr1q14/vnncd5552VcJxWAEiikt5+SI4CEEExOTmJ6ehr79+8veg3DsjeMz/6uH9fvrcEVGZo9UpGNABSEbnt7O2pra3PaHrD+uf3vsxPgCcFHrsrchCEHd5/XnNGm43NX1WF0dBQuQxtWI/LeIadLFw8PD4sX5WzTxaPLfkS41D5wVRYd3tDZAFMBzX931VmwqwBRvZVABEatShbPt6FFHzieZDTFFkTJ95+bQijK4x0XFsfKKB8yCanE6Ivg7zYxMSHWXgl2M9nYeeRy87kSiCDKE6wGo7JFogghRe0OVuIc4GxQ4vr1ej0uuugifOQjHwEhBKdOncJjjz2Gj3zkI7jnnntwySWXZHyP+fl51NXVAQDq6uqwsLAAAJiensa5554rPq+xsRHT09OS1kUFYAYK7e1XKgGYqQlESPlqNJqcU775YtKpoFUzqM2jgFpKrVxsbWO+QlfY3u2dDYgWqSEEQFrjX57nMTAwAL/fj87OzqQ1U3IjNV3scDjSDkh//ZEGvP5Iam9JYD1CN+kOIMIRWaZ7FANCCD7wwEmoVSz+5478mkUA4MkhFwiBZAF4ybYKuP0RxYs/ILuatAjHg6g0cf5uPp8vzs7DZrOJEcRUv4UoT/C2H3aj0qzFv97UIXmtexus+O4b9wMAehakrdsf5qBTsynF5kd/3Q+eEHzhNdLXkQ80BSw/gq8gsH6N2LVrF3bt2oX3ve99eb93suub1N8LFYBpkDLOLV9KKQBTRcaESFhbW5t4x1EMOJ4gEOFEvzm9RoUvvja5oa1UMkUAOY7DyZMn004wyQZBADbYlVH4HQqFcOLECVRUVODgwYMlu+CnShf39fUhGo3GpYtz4ZMPD4AQiBdfpcMwDK7eVbWhEzdXbj9cn1WtqxShHIxwuP+ZSdx+pL4k5tkChBDJF/R3/rgXHM/ju2/cL56zzWYzzGYzmpqaRDsPl8uFyclJsX4wsXtTzTJQswz2NeQe+ZUiRDie4N0/6YFGzeLbKbrGa626ohpEK1FAZYvSbmx8Pp84ISdXampqMDs7i7q6OszOzorv19jYiMnJSfF5U1NTkku1qABMghzeflIpxEzeXLdb6pTvPzzYi2CUx1dv3bfhbtgbiuL45Aou2OLM6sedLtLp8/nQ3d2NpqYmNDY25rX22O1NufyYWYvgvHanLO+ZKx6PBydPnkzaxTy3EkS1RRc3Io4Qgp++OIPOVofoWcbxBN5QNG2EMVsYhsEDvSsYWAjgvhsPgOd5uN1uLC8vY3h4GH6/HxMTE1mliz969daiRlzlIFNkMxuk+hpmE00bXvLjmVE3tlSZ8KpdVfksLy+SrZkQgjBHNjTl3Li/BrMrwZT7GGvnAWBDqYJarRZLFb71hr05C4klbxiPjQWxbUf656lYBgebbNhbn1pofuCytpzWkCvlLgCVJv6A9WtNvpNAbrjhBnzve9/Dvffei+9973u48cYbxcff8IY34IMf/CBmZmYwODiIrq4uSe9JBWACxR7nppQUcCQSwcmTJ6HVaoua8l0LRvHuH5/A2y5swe1HGtA9tZo0FfLn04v4c/8iWiqMaHJIj5qkanaZm5vDyMgI9uzZA6tVPr81hmHw8d/2IxQlONxsh1Zd/BOpIORnZmZw6NChDXVPcytB/OjYFM5rd8aJ1FCUx29PLuLZsRV89XW7AQA/fXEGnkAEbz2/OeW+5GKW/PSICxy/fmFXqVRx6eLnnnsOarUa4+Pj8Hq94gxZp9OZMl2cyWSXkj27as340k0d0KoY3P/MBG7YW4MqS/GbRJIJwP/+6wSCER7vv6w1rjbuhr01kt4zwvEIRXmYdfGlCqFQSIwOrq2twWQyidHpbOoHe2fWMOTm4PJHYdSn/8yKLfAyUe4CUIkIZS9Sef3rX48nnngCS0tLaGxsxKc//Wnce++9uPXWW3H//fejubkZDzzwAABg9+7duPXWW7Fr1y6o1Wp84xvfkHz9pgIwhmg0Kou3XzbkY8icD7HCc2VlBSdPnixayjf2hM4y61GmhbUQbjnUgM7W5FGzox3V2FZtRqNdWj1gMLK+b4k2MDzPo7+/H8FgsCD1cAzD4PM3bMdykJRE/MWmtDs7O5OeCKotOly8rRI7E+ws9BoVvnjjDjhMZy5YV3VUYXTZn3JfeqZX8YVHhvGhK9oleaMJfOfO1KlalmXj0sVerxfLy8tiulgwo7bb7SXv9hMIRjgsrIXRLFNKt1BkEwFkGAZ1Nj0W10KI8gSBSGmmwQg347FcuMWBwUV/zo0R7/hxDyIcwf+9aX/ce+t0ug3zYV0uV9w4MKF2Nd2548KtTmBZi3oZS0EW1kIYWw6gq9Uu23smgwpA+cnWB/DHP/5x0scfe+yxpI9/7GMfw8c+9rGs10UFIOT39suGUkcAx8fHMTMzU7SUryDIhM/YpFPjR285kvF1Rq0qK2Po+/4wAALg3V1OMdUdDAZx4sQJVFdXY+fOnQX5nlmWhdOoQUNF8YWA3+/HiRMn0NjYiMbGxjRpMAZHUthZ1Nn0cSf/SrMWlebU9V9VFh10arZg9iERjogjmVpbW8FxHDweD1wuF0ZGRuJSdmazuWTpn6eGXBhdDuCOzvqcptiMuwJoduhTrj/C8bJ0C+dClUWHd1zYkvLvhV5bshrAPfVW7KnPPXJ/Z2cDxlyBtMcLwzAwGo0YXeGxc3cDNCzEcWBTU1NpJ+OoWQYmtbw2MB/7dT/8YQ7/c+e+rCPu2VDOAlCpU0zoKDiFwvM8ZmZmYDAYSjLNQKVSIRwuXoGvgGCmajAYipryFYRnoU8wr9pd88qFgwfP8+LIs46ODtG9vRAUapRZJn7yzCB+/fIkvvr6g6h0pp8HKye1Vh3uTxPNy4c/nVrEuCuAN3Y1QP/KBU+lUqGiogIVFRUAzqTsBMsPKeniQnDBFie2VodyEn/981588uEB3LS/NukEjiVvGL88PotLt1diW3V+FxG5veke61/Cd56dxH037syqNCMbhN/Thx/sQ0etBW85P39j58t3pJ/sIzCzEsIvT8zhwi1OXLa9Im4cWLL6QSFdLKT75PysP3/jTkx5AgUVf0B5C0AleAAmI9sUcLE4awVgrLefy+USIwjFphQRwJWVFfT09ECj0WDXrl1F3XaxjK/PfaW2bWlpCS6XCysrK+LIs0KSz+g5YD0d/uVHhnDZjkp0tmYWcsJItx8fm4JGb4TzleL2TLh8Ybz3Jyfwgcu34Jy2M4JYSQXUHbVmuP0RUfwJEELwd98/ga1VJvzTq7fFpey8Xm9cd3Gx0sVGrQptFbkVebdXGte9LlOIEpNOBYNWBYcx/3KFbDpqpVBn1UGrYnMafSdVjAprnl8LY8m7LIsAlEq9TYdbDtahNUlEP9HqKBQKidHBtbU1hEIhTE9Pi/6D+f62MkXj5aKcBaBS155tCrhYnJUCkBCCSCQCjuPAMAzUanVJ0rBAcSeBEEIwPj6Oubk5HDhwAD09PUXZbiyZ9tflC2NhLYSdtfnfLYXDYQwODoIQgq6uroKeGB7vX8RDJ2Zx1/b8IoAcT/DCuBv9C96MApAQgpdffhkmkwlXH2gGxyOuqzcdPCEgBFgLRXNeq/A+Tw+7sL3aLHsauMlhwG2HN154GYYBATDhDmx4XEgXt7S0FCVdLEdETaNicUdn6o5gg0aFO7vk6VKPJd8pO8C6SXYu1jsPvDSDX/fM4xu37c0oHkXz6rsO5LjK3GEYRvLoN51Oh9raWtTW1oIQgueeew48z2NoaAjBYDDO+7JYoxJzoZwngdAIYHacdQIwmbdfqerwgOJFACORCHp7e6HT6UQxVIpUZSYB+L6fdiMU4fGjtxzJq4lCsECpr6+H3+8vmPib8QTBEYKfHJuGyx8Gw+jzEvRaNYvvvOlQxn1fW1uDz+fDli1bUFtbC5XDC39E+nFUadbhx2/tzHmdAhxPcHLWC5c/ghv35T49JVu+96YDGZ+j1HRxKRHOe3OrIXzwF324s7Me1+yR1jkrJyadGgwYGDSZf5e5iuy51RB+2zOPN57TCJ16/Xz3tzEPDjXZNtjHyI1wXWlqahL9BwXvy+npabF+0OFwKKqZCVi/RhbDLL4QKHEKCLAejFCi6D9rBGA6b7/NLgAFMSSIhVIiCMCvPT4MTyCKj18Tb5R132t2YcwVyFn8EUIwMTGB2dlZHDx4ENFoFF6vV46lJ+VHz0+CJwT/dcd+cDxB/+lTeQtrc4aIyOzsLEZHR2EwGFBTs37x3lpdmvSCRsXijV0NJel4zpbEDs9SpYvlxhuKIhjhs0oPWnQqqFUMaqy5T9nJh2t2V+Oa3dKMcXMVgOMuP9yBiDhp49ScF1/58yhu2l+L1x85U2s5txrE30Y9uG5vDdR5RkRTwbIsbDYbbDZbXP1gbHQ6tn5Qyv4GIxze9qMe3LivBrcclM+9geO4sr0hUnL0UknlNQJnhQDM5O2nVqsRCARSvLqwFFIAxqZ8Dx48mLcRpRwIAnBgwZdUKDU5jWhypl8nxxOwzMYfVOL4OpZl4fV6CxrpfOO5zeBfuUCpVUxBm0BiLWy6urpw7Ngx2Yv6k73f8akVdNRaUkZNcml8KDWlSBcXinf9pBccT/DDuw9kXKfw/Zp0avyfhChqLN5QFO/5aS/edVELzm0rXqNRrsd4V4sdh5vtoqjbUWPGOy5sxpHmeLuiFydWcGrOi6M7K8UpRIUmVf3g9PQ01tbWYDAY4vwHE/ffH+agUTHgeYLZlaCsa1NqHZ0UlJgClvscLSfld+bOEiHql26cW6kjgIWoAYxEIujp6RG7fJXygxYjgLflNv+UEIKP//oU1CyDz9xwZjbm2toaenp60NraGjcGJ9+mjEw/3sS6t3Tb8wajWPKF0ZpDs4Aw0q2yslK0sCmE2Ezc19FlPz73h2Fcvt2Jd13cKuu25IIQgoW1cF41iMVOF3M8wS+Oz+Lojko48xyz9sHL27DsK/xcX0KAcJTH0KJvgwD8c/8SeEJwdKf8E0NyvYAyDAN1zMtULJO00ebqXdW4ZFtF0cRfMhLrB/1+P9xud1z9oCAIAxyDTz08iENNVvzw7w7KvpZyFoBKXbtSReCmFYDZjHMrpQAshBG0kPLdunWrmCJUCvk2vTAMA6dJgyrLmYvmzMwMxsbGsHfv3g2FtizLIhDO7fP9rydH8djpRfzf3YdhkDhqK11t5dt/+DKCUR4/fWtnVr5pbrcbfX192LlzpyhQAPktZ5KdoFqcBrzl/CZ0teQ2o7cY/LZ3Af/33BQ+ec127EkzUisbpKaLcz2WR5b8eOClWUQ4krYBRArZGHDncyGy6NX48ZsPJf3b6LIfhYqzJ655JRDB/z03jat3VWF7nrY4wLpnXynFXyIMw8BkMsFkMqGxsVGsH3S73ejt7UUkGoWOY7HTaStIxEupIkoKSowAKrUuEdikApDneUQiEcnj3EodAZRr24QQjI2NYX5+XnLKt9h3JnJ0Pe9rsOG/nxrDpVsr4J0fRyQSQVdXF9TqjYfz8+Mr+HGPD5WtXtTZ9Fmd6DUqBgyDrArG04myz1zfgeEln2TxF1vPmGykWzEaeViGKekcWCl0tdgxsuTHlqrClDikSxcvLCxgZWUFNTU1Yro4zBHMr4bSTgXZWmXEJ6/ZjvbK4pZlFOr3/pbzm+O2MbockG3fEtesYhmoWWSs11vyhvHDY9O49VAd6mzFrXUUfpfBCIclXxiNeUwEia0fFMzQt25ZP/5eeuklqFSquPrBfMUGFYDy4vf7FWkCDWwyARjr7QdA8kFc6gigHCngcDiM3t7erFK+glgpNwFYbdGBZQiGTvVga3M9mpubU+5DW6URVi3w/x48CZZl8PO3SxuSDQBvuaAVb7mgNau1pdu/rdVmyc0awkg3lmVTjnQDlOt8X0xqrLqizlNNTBfbbOuRGCFd3L+mwXJUhzed34oKa/ITP8MwaaOVS94wglEuL+FQKp4YdOHrfxnDPZe34cIt+ZuuJ56jzDq1pHKE9VnTAFeC34ggov77rxNY9oXxj1dvlc3AOfH4C4fDcLvdmJmZwdraGvR6vWg3YzQasz6/l7MAVOLalToFBNhEAjDR2y+bg76UAlAO8ZVryleoPyzmD0aOmsd6XQh/vzuK3bt3w57B+LjebsTN23WY1zdn3alKCMHAgg9bKo1QS4zayZGWjR3p1tSU2vS2mB6SxeL41Ar+NB7B/oN8WXQWA4BGo0F1dbWYLm5zr2BwagkTwwMYybG7+I99C/D4I3h2bAWfu2EHWmSaMVyMG77DzTbctL8WBxpzH9UWS65rrrHq8P5LU98YjC77UW/TF8QSRljzHZ0NGHcVdnqHVqtFTU0NamrWpx8FAgGxmcnv94v+g06nU5IViRJFlFQ4jlOc3QoVgAUmmbdfNqjVakSj+RnilgIh5buwsJBTl69Qf5gsdVooGIbJWWwLpqqrq6vo7OyU9EMXRNIN+7O3SRh3BfDTF6ZwZUc1zmuXFsnIV5QtLi5iYGAAe/bsgc12prarf94LrYpBW+WZE0khLuSlL1Ze37ZapbyCaSkwDINqpx2MxrDe3EH4pHYfFRUVabuLr9tbg5Mza3h8yIUpd0A2AVgMrHo17uzKr64RODNjuBDHpDcUxYcfPAWnSYNvvyG3hrR0CCJK7ukd//nUOJ4cXMb/3XUgaSmJML/YaDSisbERhBDRf/DkyZNi/argP5js3F/uAlBpaxeayJRIWQvA2JRvpkaPdJQyApgr4XAYPT09MJlM6OzszGnfS7HfuQqkUCiE7u5uOBwOHD58WPIFIVVEjuMJHjo+i0Mt9pRduU0OA27cX4ftWXjsxW7vh89NQqdhccuhzBdDQgiGh4fhdruTittH+ubBsgzefUl73LbkjgBm+lx5QsCmeE6E4/Ho6SV0tthzvugdaLQi0qJJuY184AkBg+yEc7r9TcVqMIp3/qQXDXY9vvq63Rm7i4X6Lb3+TJ2azaDB+VucOF+GFGospRf40uB4gm8/PQGdmkWnWd7xdcB6GvnOrgYczqKBJhvkHrknMLrsB08y1z8KMAwDq9UKq9Uq1g96PB643W6MjY2BZdkN9YNK9tLLhBLX7vV6aQRQbjJ5+2VDuaXShK7Qbdu2obpamplqMkqx3yqVSqzRlIrL5cKpU6ewY8cO0TdLKqmOC44n6J5ewZIvjLdf1Jp8rSyD/Y3ZXSBiBeAvXp4BwyCjAIxEIuju7obZbMbhw4eTXjjuOKcJ6oTHC+k5mIzvPjuJ359cwLfesA/2JHNpgxEek+4gKs1+2aIebn8EdoM6b9FCCMEbvvsyWIbBjyRaZ0y4AvjQg334yNEt6Gq1S96WVa/GZdsrcOXOjcdqYnexz+cTj+/Y6IzD4VDchSwfsv0eVSwDi16NvfUWkGV3QUTrTfsLZ4ovXJfk5ouv6cj8JKx7G+o1LHbXxdeZSqkfDAQCCAQCUKvz/90VG6U2gdAIoIzkm/JNRAkHuZQ789iUb7Ku0GwplAdhOrIRnbH7e/jw4bgISb5o1Sw+fNW2vOt/vvP0ODyBCO65YosYhRb27//+7jAyHVmCf2F7e3vaKS0O40ZBVWwB2Ow0QMUyMOmSn2AtejXeeE6DbDVVk+4A3v/ASVy3pzquyzQXGIYByzBozSKVqlExULHpx5Wl+t2+95JWSWsym80wm81obm4Gx3FYWVmBy+XC6OhoTtMhMlGKCKDHH8Hfff8EOmrN+PyNOyW/7o2vzD9+ebEwYkogGOHgCURRm8RHkhACAmQdBS51GvXbT09AxTL4xm170j4vWf3g8ePHMT4+jkAgIPpfOhyOspgOUurPPRk+n48KQDnIxtuvnBBSselq8eRI+SZSCA9CKduUIgBjjayz2t9oEOCjgMYEZDhpZ7KEIYSge3oV7ZUmWFKMZ7MbNVgLRsULVGxaNtP7C/6F+/bty+kEUWwBeMWOyqRGurHIWexea9VhS6UJl26ryPxkCUiN/AnU2fT4SQrfu0KgUqngdDoxvMZiTGXE9R1OeDweTE1NYW1tDSaTSSzmz/VmqBQC0GZQY1edGW84kltdYKHXfP+zk/CFONxzeduGurrXf/dlcDzBz95yKKs1ZLvmCMfjzv89jtfsr8Hrc/ycYvn4q7dBk2UdrVA/qNFosHfv3rj6QcH/0maziQ1Nxawdl4oSI4C0CUQGsvX2KycyiSK5Ur7ZbrcQcAQZt7m6uore3t6MUbFYmIWTUD37NTBTz4MBQOzN4LreDX7bVTmvdSUQxW9OzGJXvRWvPVif9DmJj7MsmzHFnTjSLdcTabEFYL64/RGYtCrJ3b0aFYsvvVZayiuWudUQ3v/ASXzu+h3YJoNRcLH50qMjiPIENx+si5sOIaSLT58+jUgkIl6MlZ4uZhgG/3KD9MhfIoUWgLcdqsfsSjBpU0W9TY+ZlWDBrVRULIMoT/DcqCdvAegLRVFv04FhGIws+WHWqVBtyT56l6x+UIhQj42NrZvyv3L8Wa1WRQRklBoBTBxQoBTKQgByHIdwOAwABRV/pSqQTtWMQQjB6OgoFhcXZUn5St1uofjV8Rk89PIU3nEw+UWZEILp6WlMTk5i//79Se+akn1HzOxxaH71dhASBXRmEDDA2izUf/pHRNdmAGzPab12owav72rKykQ2kygLBoPo7u5GVVWVONItV8pJAHI8wVt+2A0Ny+CnbylsVG01GAXHEyz7wtiG8hOA33rDXgQifFzaMVO6WIgeZkoXF+Mc9/yYByvBCK6UaSxcodecrlP3327elfX7+ULRrJtAWIbBL952OKvtcDyBKqEZxO2P4KO/Po2uFjvuPrcRn/vDIDQqFv/1+r1ZvXcyYo8xYD0r5fF4MDc3h4GBAeh0OlEQmkymklxLlRoBrKvL3oWiGJSFAAQKK/wAlLT7KZkQE1K+ZrNZtpRvIsWOAG6tNkOnZmFI8hFzHIe+vj4QQtDV1ZX0ewhHeXz64dM42GQ701hBCNSPfwYEBNDF+I5pDCCqKFTPfQPqXZ/Nec1bqrITEIIo43mCXx6fwYEmO7ZUmfDuH52AQw9cU+PdMNItVwotANeCUbzlByfwvktbcdHW/NarYhncuLcaO2oKXwuzvdqU9cVUSdgMGtgy3Osluxi7XC5Z08W5cnJ2DbyMhyUhBH1zXuyoMUueovOXwWVoVCzOb3dkfrKM/GVwGV/58yg+ckkdqgtoZcTxBPc+dBpmnQqfvObMDa7NoEaNRYcLtjjBMAzed2kbHEkatuRAq9WiurpazEoJ/oNjY2Ni1EuoYS1W/aBSBSCtAcyDYqR8BRGmBAEodAVu374dVVWFG8NV7CaQPfVWfOGGbZicnIx73Ofzobu7G01NTWhoaEj5XWtUDFgk1Jl5xgDPBKBNItRYNRg+AKf7BIBXybYf6RBENU8IRpf98IY4tFcaMbq4gsFoFP/06vNki+QWIwIY4dfHel20Nf/3uuvc1KbW5QwhBA91z6O1woD9DfKYH2eLVquVlC4WjPILyd3nNsr6fvM+Hv/9635cuq0CH7qiPfMLAHz1iTEwAM5vl34j4A9z+J+nJ3D3eU2wpqj5zUR7pRFmnRo1ZjWYUOFSkSqWgUbFbDjeWIbBp649IwjlMuOWgsFgQENDAxoaGpLOz7bZbGKHe6HqB5WaAqYCUOGUeh4wz/MghGBkZARLS0sFSfkmooQmkLm5OYyMjGDPnj2wWtOfrBiGwWdvjE/JMGEvwKpTNnwQwkEV9RctvS+IMrWKxfsv2wIQHj09PfjS0Qp0dHTIenIqtAC06NX45duPZHxehONx+3dexnltdnz46BZZ1zDpDqDSrC3oJIV8YRgGq4EITs1yBRGAz4y4MLzkx+2H6yVFwNKlixcXF7G6uorq6mpZu4sTty8nVUYGd5/TiIu2SvdE/Nqtu7Pu3D0+tYJH+5ewu86CK5JY+EihyWHAD+4+gKWlJayGN25/3BXA73oX8Jbzm/KedJNPXWWhSTY/e2VlBW63G+Pj42AYRowOyl0/qLT+ACoA86QYX2ip5wEHg0G8+OKLsFgsBUv5JttuqQSg0AgRCATQ2dkJjSa3NAWxNQOEA3gOYJOIBJUGAVNj0QRgrMCNhoM4ceIEmpqa0Ngob1QEyF0AcjzB4loItVnUNqZDza6vY2EtLMv7CQQjHB45vYQaixbX7pE+4lAqK4EIbAZ50mNvPEf+71fApFNDxTCSzX8TiU0XcxyHiooKRKNRRaSLE3lqaBk2gwb7YoQ0yzC4+WB2NVT1ORzb57Q68O+37EaTI//PIFUkqmd6FbOrQYQ5ZY46LNQNZWLJQiQSgdvtxvz8vFg/KAjCUtUPFgraBVwGlFIAhsNhDAwMYNeuXQVN+SaiUqnE5ppiIXTJHjt2DNXV1Xk3QkBvA7/9GrCnfwPoLPGRwJAXMFVjzbEn6QmZ4wnCUR4GrXzRJUGULSwsYHBwcMNIt1SsBaN4309O4NPXd6DllckkUY5HMMqntJMRthXheKhZ6WUSH/hZNwYXfPjxW46sjyvLE4Zh8KCESGG26DUqHN1RKesoLYGTs2v4x4dO410XteDVu/PrrC/kxerh3gX8/uQC/uN1u2XbjlarRWVlZdJ0cTgcjptdnGuq7r0/68XMSgi/eGt29imn5rxQsUycACwWKpZBe2V24zRTkeqG85o91bh6V5XkWsZiU6wUqjA/O7Z+UJhOIkTMhIaSUt+U5AvtAi4DVCpV0ecBCylft9uN1tbWooo/oDQ2MCsrK/B4PDh8+LB4N5gv3EX/AMYzDmbh5LoHIMMCYAC9HZHrvw52eDnpfn7l0SEEozw++qrtYHOMriTD7XbD5/NJnlcMAJNuP2ZXQ3h5akUUgN99dgKBCIf3XNK+odsPWP/+wlEON37zb7AZNfjxWzolbesDl2/B73rnZSsOn/YE8eyoGzfuq5H9wtZcoBm4TQ4Daq26DZMSlMZ3n51EhCeZLC0lkxjhSZcuFkaFSekuTkSIBmcrWv/uvKZNEf1JJaRYhgGr4DnXpaqhMxgMMBgMqK+vF+sH3W63eFMSa3mkRP/BdNBJIHlSjBOCWq0uagQwFAqhp6cHVqsVLS0tJfnRFTLqSQjB73rn0VZpxK46qzjr1uVywWKxyCb+AABaE6Kv/Q6YyefADv4RiAZBms8Hv/UooDGCGXElTW1ctasaY8t+2cRfJBLBwMAACCFZzSsGgI5aC37x9i4YY6KRV++qxrQnmFT8Aeu/CzXLQMWyuHKn9CjWtmozPnC5fCek0WU/VgIRlIkjDYD1cW3fesO+Ui8jIz976yEQkv0kilRkKoWQq7v4ZxKsfuZWg/jwg6fxtVt3izcjSo2MZUuhZgEXGiXM0o2tH2xubgbP8+JNSWz9oMPhgM1mEz9npVpi0RrAMqCYKeDl5WWcPn1a7PKdnp7Oej6uHBQyAsjxBD8+NgWtmsV/3b4HPT09sFgsOHToEI4dOyb/BhkWpPk8cM3nbfhTqv3c12jDvixn/abC7VnBqb6TqKurg9frzfqmhWEYmBM6D5udRjQ7U6ekhKkjv3nPuTmtOVcSRcQF7Q6c3+6QTaQk28bZCsswyDhPEOu/t9VgVHbLj3Tdxfmmi/tmvfD4wxhZ8uNwszy/QzkhhODY+Aq2V5viZl/PrYbwmd8N4r7X7EzZLaykbtQIx6N3Zg0HGq0Zf1NKWrcAy7Ki4APWb7Q9Ho9YZqPVauF0OmGz2RR5zohEIpIzQcVGWd90GoplA1NICCEYGhrC8PAwDh8+LKZ8S5GKBQprA6NWsfjCa3fj01c149ixY2hqasL27duhUqmKfqcm9fMNRTgML/qyfv+//9Ex3PStF7Bt525UVVVl3NbPX5rGdd94FuFofp99KYygu6dXccN/v4CRJX/cOuQUf6VgNRjFfz01jlCS7yQU5RGMJD83KCXqcMv/vIg7//fljMdUPsKaYRiwWgO+/NwaKlp24PDhw6isrITH48HLL7+M5194EaOjo1hdXZX0uVy6vQI/e+thHGoqjXVOJtZCHB4fWMJfh11xj3dPr2Lc5cdQmnNFoSOAqT7fYITDJx8eiDuP/bZ3AV9+bAR9c96M76tEAZiIRqNBVVUVduzYga6uLuzcuRNqtRoTExPw+Xw4efIkZmZmEAwGS71UxaPsb7qIFFoAhkIhvPDCCyCE4MiRI3Hpk1I1oBSyC5gQgqW5GUyMDOLgwYNisW8p7tBYlpV0QXrrD17GO390HKsBadFYnufR19eHBkMUJqMBlQ5rUlE2txLEtCcg/vtXx2cR4Ta6+GdLKQQgTyQFpIoGTwhOzXkRzdN5+KkhF37dM48XJ1Y2/O3B47N48MRcXu9faP7haDsu3OKU1Fkq/AYDEQ7ffnoC/rD0c8C4K4DBRR+eH/OI6eKtW7ein9ThRKACBoMBU1NTeP7559Hb24vp6WkEAoGk78UyDIxalSKjNsB6mcAbz2nElR3xtdlHd1bih3cfTOuxJ4wsLQQnpldx70OnsbgW2vC3YITHsjeME9Or4mNX7KjE3ec2STJhLwcBmIher0d9fT22bdsGu92OlpYWRKNR9Pf34/nnn0d/fz8WFxdLkmVTeiaDpoBfQa1WIxTa+IOSAyHlu2PHDlRWbvSXKpUALFQEMBqN4qUTPfjgo24QRo2/nrdeyB8Ic7J23EpFSJVm4jPXd+CZEResEqxBgsF1i5fq6mp8+DUd+MgrP/JkouwXL8+AI2TdFxDAD94sT8dsIQRgKBSCTqdLedI60GjFr98prdkkV4T9knLiFBpQVCyD7XnM/b1yZyXaKgxJL5LntjkKUt/oD3Ponl7FuW35T6s4r92J89oz19XGHi/Pjrjx4PE5tFYYJI9t21ljwg/vPghLQuqzo9aM+bUwamurxXSx3++Hy+XCwMAAQqGQLN3FxSaZnQzLMHEp4WRkI6SCEQ7/9tgort9bjb0Sup91KhZqlk1aL2k3avCVW3bFWQZZ9WoclehryHFc2QlAAY7joFar45qahPpBt9uNiYkJEEJEu5nY+sFComQRWB6/QhQ+2lEIESY0Prjdbhw+fDhl0fRmigB6vV50d3ejtbUVJr0fVoMaDMPgFy9N40+nFvDZG7KbrUkIgS/EbaiPywapKeC2ShPaKjOLCGFSS7KRbsm2devhBllHYwnI+ZvgeR6nT5+Gx+MBx3Ewm82oqKiA0+lUbP0KsH6BvqqjEjVZDLv3hzkYNGzcSVmrZrErRUdwW4U81iCJ/Mfjo/jLkAv//fq9aMmj2znKE/yxbwGHm22otaa3zIi9GF201YlKsxYdtdIL1BmGSVpneLjZvuF5JpMJJpMJTU1NcYX8QndxrBGwUi+QuZLtRT8Y5TDlCUoSgDtrzfjcDTtS/j2fRppyjAAKJFt7qvrBxcVFDA0NQaPRiN3FZrNZ9uMwGo2WvKkmHWUjAAuN3CIsFAqhu7sbdrsdR44cydh5VyoBKGcEcGZmBmNjY9i7dy8sFgv++IF68W97G2x4asiVdZH6D56bxInpVXz8mh05m/bKtZ+EEIyPj2N+fj6loE8myqqyECexBCMc1CwDdYoTulwCMBwO4/jx46isrMThw+ujs9bW1uByudDb2wue54t615zNfqlYBo126eIpEOHwwEszaLTrcYXEqFeheNsFzdjfaEVznsbDPL9uwj244MsoAGPRqNii+e0JF2Kz1Yb/7YviNXsrYTREMTMzg9OnT8NoNIrdxYWegCQ3I0t+cDzBtpgIdDIxQgjBielVbKk0xUVQ9RoVPnNdakFXTMpZAEoZ5SrUDwr198FgUIwOer1escvd4XDIchwq2QQaoAJQRE4Rlinlm0i5N4HwPI9Tp04hEomgq6sraXpne40Z/37r3qzf+6JtlfCGuJxncwLrguKB4/M42M6gqzW3dFs0GsXJkyehVqvTTmqRmm7OBCEE13/zb1AxDP7w/vNTbitfAbiysoLe3l5s374dlZWVYp2M1WqF1WpFa2srotFonGu/wWAQo4PldrE2aFTYVm3C9urS2zJUmrW4JksTao8/gru+fwL/ccsutL4SmdSqWbzxnEZIKSktdToqFOVxbHwFvjCHf7t5F2pqapKmiwXfN7vdXrK1SuV9P+sFAfC7d3eJjyX7nN3+CH55Yh77Gyx47QFpk00iHI9//v0Q9jda8doDtXIuOymbXQAmotfrUVdXh7q6OrHL3e12xx2HQgQxl2lVSraAAcpIAJZDF7DQ5SsYHUt1MC/nFLDf70d3dzfq6urQ3Nws+/fUWmHEuy5py+s9CBj85OUF/LLXnVJMpcPn86G7u1vSSDepDSeZYBgGBxpt2PaKUJl0+RHmCLZUmeKek4/YnJmZwfj4OA4cOACTyQRCSNILV4Qw4l1z4sV62hMEdGZ0ba2Bw+FQdLpD4HwJtXLZQAjBr7vncU6rHTXW3KK9Upn2BBGK8uib84oCEEDOY+KkEuWJLNsw69T48ZsPxvldpkoXzy4sYXx8HH6/H6Ojo4pNF3/hNR0bmpCSCSmnSYs7OxvQYJcepVWzDAgIPBIb0/KlnAVgvmuPNUUXjsPV1VW4XC5MTk6K9YOC/6CUcx2NAJYJ+YqwYDCInp4eSSlfubedK/meSAUfpt27d2d9p17MSIRaxeJTVzbhwLbs57UK+7h3715YrZnTZXJFAAHgX2/eI/7/P5xcAEcItlSdEcO5RgB5nsfAwIA4hzldQf4LEx6cmFrFLQfrYDNoNlysP/rN5xGOruJrDg1GR0ehVqvF6GCuMz2L0d38+5ML+PpfxvDDuw9mLOjPxLIvim8+OY7nxtz43A07ZVphcnbVmfGbdx7JWYzl8rv767ALgws+vP5IPfSa/AV+pjIQlmUxG1TjiXktXrNvF6YHT8JoNCo2XbynfmPtaCoxsi1Jo1IoyuOLjwzjoq1OXLotvqaYYZiipofLWQDmEgFMB8uysNvt4rUtGo3C4/FgaWkJw8PDUKvV4nGYqn7Q6/XSCGA5kI8IW1paQn9/f9KmgEJvuxQQQjA4OIjV1dWsxp0JCCnvYkWLXpwN4aXZVWxpqpVcRyhEc1dWVrLaR7kigInc3tmIaIKwzEUohcNhnDhxAk6nEzt27MgoBlqdRsyvhjZ0fQp89XW7seANY+crnazBYFAs9BdmYAqCMJcUSiGIcDzWglEQIG8rHgCosmjx2eu359WFLBWGYaDJc5SYL8zhge4pXLTFGRdFTEWTw4BJdwA6CRYzclFn06PGooVdr8acSoWampqM6WIljQkjhODp0VW4w2u4/XBd2t+ZmmVACBDMwo6nUJS7ACzk2tVqNSorK8WyrlAoJEYHhSk5QoTQaFz/XdEIoEwUOlqkVquzngUcm/I9cuQIdLrc0j+l8HPLFaG5xeFwZD3uTKDYAnBXtR6MSo26JJYOyQiHw+ju7obNZst6Hwt1nCYTYNmKzdXVVfT09GDbtm2iL2MyYqNElWYtrt1Tk/K5W6pMcWlpwZNLmOkppFCmpqYAAA6HAxUVFbBYLGlP1oX6PRBC8LOXZqFVMXE1W+me//u+RZzX5kgbuepsscu4yvw5NefFB3/Rh/vv3BdnZUIIgeoV426px2qL04AWZ0OhlpoUh1GDmw/WIRKJxK0zXXexMCYsdnZxqcQMz/M4PuMFw2b2OVSxDD5xzbYirSw9PM8rRkRnS7HXrtPp4uoHhRuTxx57DJ/4xCewb98+tLW15Xyda21thcVigUqlglqtxgsvvACXy4XbbrsNY2NjaG1txc9+9jOxwzkXyvObLgDZirBgMIju7m44nc6sU77Jtl0OCPYnUptbAGBxLbShC7bYTS82gwYXtOglRXukiiQlkM0xOzs7i9HRUbHeL9X7yXkzwjAMbDbb+n/VDbBoGbjdbszMzGB1dRVGo1GMDsbWyxby98AwDKot2qT+bsmYcAfxlT+P4qWtK/inVyvjIi2FRW8YPCFYC0aBmClrhBAYdWrc0VlcQZcKjk9viJ4pZZ1o8xEOh8VjbG1tDQaDQZZ0MSEEvjAHs279kskTgr8OuXDBFmfS9RNC8P6LmxSRos4GJcwCzhWO43IOwuRL4o3JVVddhSeffBI/+tGP8OKLL+K5557DJZdcgqNHj+LCCy+UfFw8/vjjcdfa++67D1dccQXuvfde3HfffbjvvvvwhS98Ied1l2estwBkc9FZWlrCiy++iC1btmDr1q1lI+ByhRCC0dFRDA4O4tChQ5LF33efGcervvYMHu45M0VheNEHMIUVgISQuFFIUgXn9PQ0Tp48iQMHDihe/AHx9YbhKI8p98aJC4QQ9Pf3Y3Z2Fl1dXaL4y2b6Q778798mcev9L2HEFUJ1dTU6OjrQ1dWFtrY2RKNRnDp1CseOHcPg4CCWl5ezFqC+UBR8Fq+5cmcVdqfw/Euk2aHH0R0VqLfpkm5DqZH7i7c68cf3niNp+kOpmPIE8OpvPI8Hj8+mfE62NYtarRY1NTXo6OhAZ2cn2tvbxZrX2KkQ2WZ7fnhsGv/51Lg4EvDP/cv49O8H8buTC0mfLwipcrs2lHMKWElr1+l0uPLKK3HZZZfh/e9/Px555BFcfPHFePjhh3HRRRfh6NGjGBwczPp9H3roIdx1110AgLvuugu/+tWv8lpn2UQAlfBD4nlerAvLJ+WrNNKdZCORCHp7e6HX69PanySjwqyBTa/Gnvr15olpTwD/+qdBtOpD2LkjuQAZXfKhyqIT77Rz4QfPTeLbT4/jyzfvQWerAyzLph0DJJggh8PhjE0RpSAc5XHt15/F2y9qxesOn4ncxEbrnh5eRt/sGu7oahKbGoRUtt1ux8GDB8Xv2BuM4ofPT6Kj1oKLt0sT8/lwQbsTTw254syOYzvumpubwXEcPB4PlpeXsba2hp6eHlRVVcHpdMJoNKY8PsNRHg8en4PDpMF1e2owtxrCXf93HB+7eisu3pZ9PW4iDMPgsu0VmHAHy37eMbD+W+cI0DO9io46S8G7h9Nh0amhYpm0pRn5zi6WK118+Y5KHJ9cEZtgLtjiwHsvacXl25MfY6USI25/BH8bdeOqjqq4yOTsShBGrSpjDbSSRFS2yN0EIgc+n088vq699lpce+21ANYzMjabLe1rGYbBVVddBYZh8I53vANvf/vbMT8/j7q6dQuhuro6LCwkvwGRirKudApGSPlWVFTknfJVEunq8VZXV9Hb24v29nbU1mbvQXXDvnrcsO+MGXS9TY+bD9XD6JtNGjkJRTh89fERWHRqfOaGjqy3J3D17hq4/RHRVT9dWlMY6SZEDeT8Xn/0/CSseg2u25eff5eKZRDhCR54aTqlAOxsdaDOphfFnyCitm7duiGaadKp0FJhxK4k3YuFYFu1CfffuT/tc1QqFSoqKlBRUQG/34/29nbc88sBTHvG8elzNXGF/rHNJFo1iz31FjS/Ii6Fby/MyReZ62p1oKtVtreTHZ4QjC0H0FphkCRSJ9wBHBtfhUWvltQEUihsBg1+/570dZhyugUkmwrhcrniShJSpYvrbfq4sgGDRoWb9qf+XZfKb/HxgSX8uX8ZexssokE6IQT3PnQaapbF/XfuS/v6ch4Fp8T0tc/nQ1NT04bHBRGXjqeffhr19fVYWFjAlVdeiZ075XcYoAIwgWQ/3MXFRQwMDKCjowNOp7weYrGU4u5LMINO/OFMTU1hcnIS+/fvl62LiWEYXNlRjZMnF5OmZHUaFV7f2bjhovTJ35wCwwCfuk6aKKy26PD+y7eI/06VAhZqGgv1vXoCEawGs0s1JUPFMnjigxdueDxWAJp1auysXRd0c3NzGBkZwb59+5JaEDAMg1ftTt3YEUsgwsEgg/VHNjAMA71ej+k1DkSlQWdnp9hMMjExIUZuhGaSg01n7qRrrDr88b3nFHW9pWbcFcBfBpcBVKC9Mr2gI4SgxWmE1aBDdY4TaopJIYWURqMpWHdxqSJp1+yuxv4GKxps8TW1b7ugGRWmzE4G5R4BVNra8zGCrq9fD55UV1fjpptuwvPPP4+amhrMzs6irq4Os7OzeZcqUQEYg2DHIvzYhZTv6upqwVO+ghAr9gEsmEELURWO49DX1wdCCLq6ugpyRyVs0+UL4+GeOdx2pBHaVywmcp3UkWl7sQJQykg3OXj3Je0FeV+BxMimYM+ztraGzs7OvG1X/jK4jM/+fhBfvnkX9hdpZJgAIQR/iBFygh9Xe3s7wuGw2Fks2C8IzSRy/UZLPTEjG5ocBly2vQKNjtSF5cL+EEKgUbGosynDkicThBBEeODB47O4cV+tLLY9yUhMF0eiHLxrqzl3F8t1/EQ4HmpWese2XqOK68oXuHCLtBvccheASosA+v3+nASgz+cDz/OwWCzw+Xz405/+hE984hO44YYb8L3vfQ/33nsvvve97+HGG2/Ma31lIwCLcTKOFYCxKd9c7U5y3XYxiRVHwsSLxsZGNDY2FmyfhW32TK3guTE3zt9SkfSkJfDp63NPBwPxQikajaK3txdarTbrmkalEbtfkUgE3d3dsFqtOHTo0IbvbmEthAqTVryArgYisOjVab/jRrseapZFjSU7n8dCo9VqUVtbi9raWhBC4PV64XK50NfXh2g0Ks4tttvtOX2///PMBH764ix+/tZDOc+fLiZqlsmYyr36688DAD5/fm7nF7kmgWQLIQTPTIXxi8FxOI1aXJqi5k5O/uupcfz85Vn87C2HsGXLmXRxsu7iWM+3RPI9fxJC8NnfD0GrYorWgV7OAlCJa881Ajg/P4+bbroJwPo16w1veANe9apXobOzE7feeivuv/9+NDc344EHHshrfWUjAIuBIMKKlfJNtu1iI2xXSBvu2bNH0sSLfBAE4EVbK7GrzorqGIHx/JgbHM/jvPZUxdUEoSgPg1banV731Aom573YYuJFgdvc3IyGBmXYYOSDIAC9Xi+6u7tT1mp6Q1Hc/N/Pw6pX4+H3ngdvMIofH5vC1moTrtiZOoWwpcqEP7y3Cz99cQb1dj0ukhBFiPIE137zeVy7pxrvvzS3EX7ZWNEwDAOLxQKLxYKWlhbRrX9xcRFDQ0PQ6XRxc4ulXJQ1r1xEjBKPMWC9GYUnRJZJGYUkl8hUz/QqXpxcwWsP1OU1kzsXeJ7H+U167NraggteEWNufwQ/f3kW1++tRq1V/uh9o0MPlmHiGtE0Gg2qq6tRXV0tpovdbjeGhoYQDAbjZher1GrMePm8o4CCZVGmtL6cKFFESUWJEUCv15tTCVV7eztOnDix4fGKigo89thjciwNABWAcbAsi+HhYYRCoZwmXOSDkAIuNgzDYGRkBBzHyZI2lIIgANUqdsPs1AdfngGAlALwvj8OIBDh8anrdkpKB73vp92Icjz+/TIjjh8/LnmkmxJYDUTAskzKjmiGYcRZzHv37oXFkrypw6xT4+pdVbh277o4NOvVONBkw44aaU0gUZ5g2h2U9FwVA/AEeOTUUs4CMB8S3fqFuq7EC3W6uq67zm3EXedmNzbwoe558ITgtsP1mZ9cAv70vvV0+gsvvJD1a6ssOug1Khg02QkDnhB4/BE4JdSepYIQAqNWhYMxkT+eELCvHGfpCEd53P/sJO7obMhKuF63pwbXpTE/j00XNzY2xs2MHR8fx5CHx18nQ2gamceBtuq8BNV7L2nN+bW5UO4CUGlrF6YhKZWyEYCFTsEGAgG4XC5UV1cXJeWbiFAXV0yCwSCWlpZQXV2Nffv2FW2f0/nyfezVO9JGf67bW4uTM6sZxR/PEzx0Yhb/fEMHlmcn4POt4vzzzy+aqJejBui6b/wNDAP85UMXJX3/yclJeL1eXHjhhRmF+z9dE99Bdk6b9Mh2NqbBDMPgkffl34RBCAEhBI+eXkKDXY9dEn37EjEajTAajeKFOtYGhGVZsZkk1SxPKTAMg3Pb7IhmUiQ5EuXXBY8cNjS5HJe1Vh1uz0HYvvPHPRhc8OGXbz+S87zlZOutMGnxlvObM772uTEPfvriDKrNWtx8MHPXZa7Ezoxtb2/HDn8Q4SdehCbkxgsvTECv14v1g6nSxUqhnAUgAMWt3e/3UwEoF4UambawsIDBwUE4HA7U1taWpPi72Cng5eVlnD59Gg6HAzU1NUXd53QCMNXMWYF9jTbsa0zvnwSsXzS7pzyIel24fZ8DHOcsmvgTjtN8P9O3X9QCvXpjSiMajaK7uxsajQYhrRV/HfHgsh1VeW2rmEy6A7jr/07gvht3oqvVvuHvwufGMAyWfGGsBKM5C8BYkk2NWF5exsTEhDi0XUgXSz1WhPNRU5oGjHz5+UuzUKsY3FJAESOFxbUQHCat5FrAt1/YjO8+OwWbIbvLzG965rG7zoL2SmNev6Pz2h348mt3YXddbl2YwQiH58Y8OK/NITapScFi1KOjSou9uzpACBGDC0IU2mq1JrU0kosIx4MnyGl2c7kLQKVBZwErGJ7nMTg4CK/Xi87OToyPj5ekDg8ongAkhGBkZATLy8s4cuQIJicni556LsYouIBvDRdaXeg4sg1WiwnDw8MF3V4swv7leyK985yNUY7Yej+z2Yy3f+15MKpTeOKDFWAYQKPKb5vFmEstRMoiXOZj4PVHClerqdVq42Z5rq2tweVyobe3FzzPi80kNputpBfFBoceFl1utU3JmjdyEVT+MIfX3f8StCpWTCdn4kizHUea7VltJxDh8OXHRqBmGTz6/nPzEoBqlsHh5sw3i6kYdwXwwoQHDXY9tqZpUksHwzAbotBCunhychIAxOPMarXKcpzd+b/HwROCB956OOc1U+ShFI2d2aDclRWYQCCA7u5uVFVViV2TarU66xFBclEMARgOh9HT0wOz2YwjR46AZdmSpJ4zTebIF8HD8NwjB2EymeD3+4sqcgsZqR4aGhLr/fx+Pz59sQ3W+jaMLvvx5MAiXnuwARXm4nbtekNREJI5eivQVmHEnz9wbsq/F0OEJtum1WqF1WpFa2srotEo3G435ufnMTg4CL1eH9dMUkykNN8k46ZvvQC3P4JH3ndO3jcGRq0Kl2+vwKt3F3ZEokGjwr/fskv0sSulHc/WKhPe2NWIShl/T7HpYuBMd/Hc3BwGBgbi0sVSm5YSuXJnJXxFHPVISY5Sx0TGUlYCUK4Lg5Dy3bVrl5gOAkrXiStsu5AixePx4OTJk9i2bVuceWQho3EzniAeOjGDt13YCnXMBahQ2+R5HqdOnUI0Go0b6caybMbjZnjRh/bK1CPHsiHd/kU5Hpd95a+45VADPhBjVp0OQgiGh4fh8Xhw5MiRuPRklZHFwTYnFtdC0GtUMOUYKcqH3/bMg6Cw0bpio1arUVVVBZ3FgeXpVeyp02N5eVk0Cbbb7XA6nSVp3JLK5dsr8csTc3mLP4FPXLNdlvfJxIGYEo98BOCkOwCzTg1HjvWHKpYpuFl2Yndxruni1WAUBg0LjYrFWy/IXB+52VCq2GIY6R6OpaCsBGC+CEPBfT5f0i5flUpV0MhUOgoViROaBWZmZnDw4MENRciFFL3/+ZcRPNw7j61VZly564zoLITYjR3p1tLSEvejYxgm7fb+NurC3/+sB++6uA13nSft5BnleHz5kSHcdLAej/cvguMJ3n1pu7i9VCckFcuA54GHTsxKEoDRaBQ9PT0wGAw4dOhQXIooVthWWXR447mlOfFfsq0Cyjz95s/Hf9OP41Or+OlbDqKpqQlNTU3gOE5sJnG5XAgEAqiqqkJFRQVMJpNiTvjvu7QV77u0NePzSuXxJ4VcBSBPCH7TswCdmsVbzt84ikvAH+YwvxZCm4wj8XIVI7mmi3lC8MbvHYeaZfCLtx0G90qJBQGw5A2j1qrDyJIfzU6DYr/nfFGqcbtShanAWSMAhZRvdXU1duzYkfRgUalUCAal2V3ITSHEZzQaxcmTJ6FWq9HZ2ZnUI6mQ6dh3XtwGX5hDV1v8dI9YQTa86EONVZfS6kQKQkNLYkRXIFPEcX+DDbccqpc8Hg1YH/P24PFZTHkCuHBrBTz+M59huu0xDIOn/+FiSdsQfAtbWlrEsUCJ76WEE0ydTV4vNqXsFwD849VbcWzcE+c3p1KpxDRdJBJBdXU1QqEQxsbGRNsHIV1cDFulfPjKn0fxyxNz+OXbD0saFZaKQonIdBf2R08v4XN/GMRv3tW54fzBMgxu2FcNS4bzym965jG3GsLbL2yWbeShXI0U2aSLr9pZia1V6yL2H351CoQAYY7HwmoY/3zDDnzmdwO4oN2Bd13cmve6lIgSPQAjkYjif/9nhQBMlfJNRKVSlbQGUE7xKTQLtLS0pDU9LqTobXAY8G+v27vhcSHaGQhz+Oqfh2EzaPCZG7Kb9hHleHA8wczUBBYWFtKOdMskAA1aFT58ZXZO+5VmHX70liOotepgSrjIyCFgBDPydL6FmSKblPyptepw/d70NwZarRYVFRWor68HIUSM2kxNTQFYj9oIc4uV1mG5o8YElkFeBs9zq0H8sW8RV3VUyX4zkE4APj/uEaNdyWi0Z67VvHZPNRbWwrLOuyaEFOR7Tpcu7jQEYWWtWFgAtlYYEOaB6/fW4OkRF7ZVGXHzwTpc2J5+zKZSbrpyIdk8+1Kj9A5goMwEYLYh3kwp30TUavWm6AKemZnB2NhYWnNggWJ05CaiUqlACIFBq8Id5zRlHGOVjM//oR9LS8t4R6cz40g3KTWAuZBqfF0+AlDo0na5XBuO2dElH+74zov4+du7UG/XKypSlg+J0aNy3K/nxzz48IN9+N5dB9BWYYPRbEFbW1vcCLHV1VUYjUYxOpjrDGpfKIrP/H4QH76iHVV51qhds7sa1+TZ2GHUqqHXqLKanCKVZALwmREXBhf9uPeqLfjo1Vvzen+zTp1X9iEZPM8XLB0ZjHD4be8CrtldnTJd3GV2rz95leD67U4QQnDT/o0TghJRahpVCko0gc51CkgxKSsBmA1+vx89PT1pU76JlLIJRI4aQJ7ncfr0aYTDYXR1dUlqPy/FBJLYfe1qTX9Xmgyv1wtHeBEtrZXYtWtXxuczDIOpNQ7BCFeUUV25imphTrFOp8Phw4c3nNCGF32I8jwm3P5NIwD9YQ5Xf/057G+w4uu37Sn1cnImyhOAYcDxBCemV9E3u4Yb9tbApNs4QkwoWYhEImIzid1ulxzBODG9ir8Ou3FOqwuvPVBab0BgPXpYqAkoyUTJlCcIjiNpjbG9oSh++uIsXr27CvUyRyUzUUgvveElP46Ne7Cl0oiDTWeaZeToLi5nD0AlpoBznQNcTDalAJyfn8fQ0BB2794t/iCkUM5dwMJIsLq6OnR0dEi+kyuVDUyu+zo/P4/h4WG86YoDkke6efwRPDEZgap3Hq89WPhRXbkIM7/fjxMnTqSdU3y0oxpHO85EazaDADRoWLAMgyMtufu15covT8zhhfEVfPb67XlP2Ti/3YEn7zkPwHrh/YQrsOFmI3aEWHNzMziOw29fnoDONY8KdgQajUacTLIcWu8eTGYwfU6rAz+8+wAa7MUVNqUgmQC89VDm3zDHE0R5An8J7FAIIYjwwNeeGMXVu6qxvVq+KFBHrRkfvLw9ozVNLt3F5SwAlbh2mgKWmUyihud59Pf3IxAI5DTLt9QCMNdtC/Vi2QpeoDQp4Fy2SQjB4OAg1tbWsp5ZbDOocUGDBld2FNbDTCDb/VtaWkJ/fz/27NkDm026ENoMApBhGPzlFeEErM9vfWwsiAv1Phws8N3zvz02knGebC5UmrUZ6wYBgGFZ/OtfZsGyDJ685zwEg0EsLy9jZGQEfxhYhV5vwG2djRssQFQsk1PZRDmSazrVZtDgHReWpiteECOBCI9Jl19WAcgyzIb56ZlI1l28traG5eVlTE5OghACp9OZ1zjEUkMjgLlRVgIwHUIErLa2Fjt37szpQC43ASiIotXV1ZwEb67bzZdYgUQIwa+757C7zoKt1cl/LOFwGN3d3bDb7aJpdzYwDINWKyvZqDiWZW8YD7w0jTvPaZJcKyRVmBFCMDY2hsXFRRw5cgQ6XfoT+4lJDxiWwb4GW1bbKTb5pNpVLANCgGgRduvR95+LCMdnHf0jZD26JPjr5XrRZBkGX79tDypM6+JOr9ejoaEBDQ0NaNsWwerqKrzeFUxMTIBhGDE6aLFY8rpQ84Tg209P4MqdVWivVK6QDEd5EEIkXdi9oSi+8MgwPnR5e85zh+WCEAKdmsU/XCnN57PYsCwLm80m3mwK6eKFhQWsrKygu7s7bzPqYqPECCCtASwSuaZ8Eym1AMwmahQKhdDd3Q2Hw4HDhw/nfhEqcQQwHOXxzb+MQKti8Zv3nLfhuSsrK+jt7cX27dtRVVX8ebeL3hB8IQ5rwaisApDjOPT09ECr1YpTWTLx0uQKAMQJQLnJ93gYWfLjmREXru6oyqlBQcUyuLLdgMZq6cLk+TEPPvRgH37zzs6sLv46NZvTvNSLvvIseAI8ec95eQvwA43JyxjMeg3M+gqgugLt7e0Ih8Nwu92YmprC2toaTCaT2EyS6cYhEZcvgu/9bQovTqzgW2/Yl9f6C0XvzBr+NurGOVUcqqyZv9Pnxjx49PQSOpvtuGGfdDunQlAMMdI9vYpt1SZZupeFdLHRaATLsmhtbYXL5cLw8DACgYBoa1So2cVyQCOAuVFWAjDxgheb8u3q6sr74CxUt6gUshGfbrcbfX192LFjByorK/PebikFoE6jwr/dsjepfYQw0i2ZgbVcPDW0jNElH954TlNSQbWz1oKdtek7qRPJJKKEer+mpiY0NjZKft87uuINbdeCUdmP13zfr8qsRa1VB5sh9W8xwvF41096cUdnAy7bXrHh79lGNvvm1sDxBL4wV5Toz2v21eBX3fNFNdXVarWoqalBTU0NCCHw+XxYXl5GX18fotGoaBBst9szio9KsxbfesM+NDuLO9IuG2osWhh1KhjU0lLAl2yrwP+96QBaK0q/T4WygRGYWw3h3odO41CTDf98/Y6Mz5/yBOALcdhRk16MCFYqmdLFSpmRHQsVgLlRVgIwFjlSvkpCSjOGkDJcWFjAoUOHZJlJWqomkGjMNnfXx0dBXhx348M/O45PX+LABV1dBf1hvzzhQZTPz/7g9NwaPP4Izm1fn9maTsAIHaC5RKu1MdEqly+MK//jaWy3EVxwQc5Llx2LXo2jO9NHankCnJxdw1efGE0qALPl7nObcPe5qac9yM2Hj27Bh4+WLr3HMAzMZjPMZjNaWloQjUbh8XiwtLSEoaEh6HQ6MV2cKoW3pz67m5piU2XR4Q1HGjA2Nibpt6lmGWyTsdYuHwppAwOsi+O3XdCM89rsKZ/j8oXx2d8P4u8vb8c//PIUJtwB/PodR9JG5ZNZqSRLF3s8HtFbVzjWnE4njEZ5RmnmghJTwD6fL27sqhIpSwE4NzeH4eHhrIvmlUym6GMkEkFvby/0en1G37tsKHQEMFkX33t/2oP+qQD+cA6/YU5pIBDAky/2gjAMWrZsK/hd3fsljGOLcBvXGcuTg0uIcEQUgMkigIQQjI+PY35+XlK9XybsBg0MGhUubiy/Gx+dmsWj7zsnTtDGotTaRqWiVqtRWVkpZgMCgQCWl5fFjk+bzSZ2fJYbhfame3LIhZmVIG6X0cam0GKEYZi0vn4/f3kWbn8YoSiPJW8Yd3TW4/vPT8MTiKYVgFLWrdFoUFVVJZbj+P1+uN1ujIyMiOliQRAWM13McZzi0tO0C1hmeJ5HX18fQqGQLCnfcmF1dRW9vb1ob29HbW1mQ89sKOQ0CUIIbvv2MUR5ggffeY74+JZKIwansUFUCdGxuy/bg3teK//FKpeLiT/M4b+fGsWuWguuTjEq7u7zWtZ94F4hUcBwHIeTJ09CpVLJJt5ZlsFfP3IxnnnmmbzfK5FiGMImTk9Jhi8UxQ+OTePN5zWlFeCUeAwGAxobG8UUnjC3eHx8HH6/H2NjY6ioqChY12emG6ZsKPSxODDvjfvtykGpDZWfHXWDAfDN29enMB1utuGGfZmvG7kIVyFd3NDQIKaLhSk4xUwX0xRwbpSVAIxEIjCbzVn53OVCqX/AsQh1cPv27SvIwVTI/WQYBqPLfujUbNxnes8VW3GeaVF8HiEEo6OjWFpakiU6lgwhKpftScKgYWHQqFJ2KAPrqdnY/utYARgIBHDixAk0NDSgqal4acpyRjhOftU9j+88M4nt1WZZUsXFhuMJQlG+IBMypMKyLBwOhxj9e+6556DX6zExMQGv1wuz2Sw2k+TiIpCIxx/BQ93zOKfVjp21+Z+vCn0ufusF8lvFlDod+YXXnBmreWrOC52aldTtne+6Y9PFbW1tiEajYndxodPFpf7Mk+H3+6kAlBO9Xo/m5sJ6OwnNGFKmaBQSjuPQ19cHQgi6ClwHV0ge+cAFCEU58cc+vuzHv/95GOfb1qOO0WgUPT090Ov1krthw1Ee4SgPcxa2Lrk2+DAMg3de3Jb1a3ieR/fILH7yTD/efsVuNNUVv4NZ4PH+RXzo57347XvOQ30RzIPd/ggceTZjEELw2gO1aHYYcG6aWielMLbshz/MYVfdmdq6i/7tGfAEePpD50NVxIaRdLAsi9raWtTW1oIQgrW1NXz+j0MwMWN4Vas674iNSaeCUafKaFQslVQCkBCCTzw8gN21Ftx+pPDm7tlQKjFCCEH3zBq2VZmgZhlECcF/PD4KFcvgGxKm7Mi9brVaHZcuFsyoR0ZG4Pf748yo8735UGoEkKaAywy1Wo1oNFpSAejz+dDd3S2mcZQSjcyF9a7MM2JAq2ahUTHQsOs+Sd3d3WhtbUV9vfST+FceG0IoyuPj10gb8QcUNtWdbFtLS0uYdAfQ1NAARx7WRHKwGoyCAOCKsP8/e3EGX3psBP/1+r041JRffa5Bo0J7ZekKy7Ph+NQqOJ7ECcA3n9+Evwy68hZ/EY6H2x9BdZ5zfxNhGAZW6/9n77vDG7nr9N+ZUe+yLPdur9dl7XXdbDbJppBk00hIQkISeggl9ASOchw/yh1HuTvgODpHOzgIhJJQQ5IjQCBlS3bd67p3FduyujQzvz+8MyvJKiNp1JZ9n+eeI2tbMyONvt933s/n8746/HHOAwLAh17RF6bYcPFh3DCJEEgpEnd1ixdPF08BfHLMiqfHrXlHADOtWk5bXPjJqRU8dE1DmLpsdfrx3ecX0VOlw8lFByQkgQ9c1wiFVBipyzRxVSqVvM+l2OXifFQAL5aARUY2NoJcegESBIHV1VXMzs6ivb39ghlwCUW5XoHP3XEAf/7znzE4OIiOjg5otclNJL6iqwIbO76k7ods+R3SNI3V1VUAwM1XXpIXi9JtB8tx28HkN+UzS9s4WKlL6n3uqdHDrJGhIY2kCq6EbnP58ZcpGzordWjP86nVmw+U7EkVeeBIDR44kn7F4vnZTSxv+fCKg6Wi+L5F4v/efQkokoBEQvGKDRcfZrPZMDk5CZ/Px+cWG43GjKktviAT5s0Yi0wRBIH/e/clWbXiEYpMk5HFTQ/cfhoBmgFw/nMo1sjw+kuq0GhWw+VnUKqTJ2X0zTBM1oQPscvF+agAOp3OpPe2bKOgCCCQ+QnBXBFAhmHg8/mwvLycdNRZIYFhGExNTSEQCODIkSMpXef+Uk1CT6tIZIMAer1enDlzBiqVClqtNi/IX6p4etyKDz8+jve9rCEphaXJrMZv335IlHMoUklxpLEIZUlGX+UCmRxS6asxoMboi0/+WAbwuwCpEiCTW9ajGZyHxodVV1eDYRhsbW3BbrdjdnYWEomEVwfVarUoD+duP42fnFpBQ7EKV+7b7fmMp6YJNWbPNqL5ALLnyrFSisQ7rqxL6/Wvbi7G1c17/V8JgkD3OdX9waO1Sb9uLlW0dMvF+UgA3W73RQJYaMgFAfR6vRgYGABFUWhvb886+eNIdaYVVr/fj4GBARiNRqhUqpS+sKcWtrC/RJNU/x+Q+QcHzpy7ra0NHo8HPp8v7ddkGBY/OrGE1jINemuza+FxpMGINxyuwvWtiY3GaYbF+o4PFVHMvFMFdz/W5rFZcbagklGxs3+DXsie/yJkZ74PBD0AQSHQchv8R/8RrCo9k/hQcMMkUw4Ch/oa4ff7YbfbMTc3B5fLxadFpGP/oZSSKNHKwh7u8mkgTyiiKWkEQZxbg3J0UgKQT2XUWOXi5eVlMAyzp1ycT+fOwe12ZyzAQCxcJIARyDYB5KxPWltbMT8/nxP/M84MOpPyf2Skm81mS/pLa3P68fCjQ9hfqsE3X9Od1PFjKYALdjcc3iAOVESP5EoElmWxuLiIlZUV9Pb2QqFQwOfziaI2kiSBAM1g2uLKGgFkWRYMw0AlkwhWKqY2XDi1sIVrW8xJB9WHwhdk8OuhdXTkd9/0HgghKC5fEDd99QQ+d3sLLqkT6bOkA1A+eg+o9SEQNPfAEYR07BeQzP8F7tc+CVZVxP96umvLLwfW8KknpvHxm5vx8o5SlJeXo7y8nB8msdlsWFpaAgB+g9bpdIK/4wRB4OYDu1ZLQ8sOlOnkebmxJ0Is0vqeq5MbJss28vW9FlIudrvd8Hq9kEgkefPAkIrrRLZRcAQw00qORCLJCgFkWRYzMzOw2Ww8cVhaWspJ+TnT5dHhqVnsWNdwsKsLx5fcOFrEpHRMk0aGh65twqEUyFCs4/1qYA1+mkF7uTbphYPzpWRZFv39/fyXXcx79I1Hki/lpAqXy4UzZ87sEkCVild0FIr4yl59sQoyCQmzNr1Jvp+cWsGX/jSH916ix03iiVcZhdDP2eWn4fTTeHLMKhoBlEz9DpRlNIT87YJggoDbDumJr8J/5T+JciwAeNn+Ymzs+PdY8nDDJDqdDvX19QgEAtjc3MTq6iomJydByRQoM5tgMpkS3kvA7tDLG384CJIAvnuzMW82dKHIVyKVCIVy3tHKxS+99BLm5uZEny5OFYWiXBccAcw0KIpCMBjM6DH8fj+Ghoag0WjCrE9y1X+YqePSNI1vPHEKvxhz4fOv6sKpFQ8+//TuBG9JiqTzFSkMMwCxCeAbjtTAH0w+uokr25eVlaGmpibs77M5cQyIs9hYLBZMTk6ivb0dcrkcXq8XNpsNY2NjfNasyWSKOqEn1GcsEe7oKoNRJcU++c4FlwRSopXjhfeLawcjHfgBiIA76s8Ixg/p8E/CCGC694leKcXbrkj8QCKVSlFSUoKSkhL8+OQy/v2JGXzhRhUslnEEAgF+mMRgMERVSKQUiY/dtA+NxSowtvmcbaRLWx5ISDLpHtRMZAEzLIuNHR/KdJmzcSoExSoalEolZDIZOjo6wLIsHA5H3HJxNpHvJPAiAYxApkkYVwrdt2/fnpzAXBHATCiAnAHyilsCN0NCJpXgcJkO772mEUcaTZgYWckqSYqlymnkEiDJqiXX79fa2oqioqI9P0/VczAVpNu/yUXUbWxs8CpmIBCAWq2GWq1GTU0NnzUbag9iMglXdIRCI5fg5R2lOHvWKdprioEFuwcSiki7x1HsQRHCsxn/5wGXqMeLhS13AC4/jcooHpNN5t0BkQNNNShSy0DTND9MMjMzA6lUyg+ThE57vrzjXCnYmjsl5TdDGyAJ4C2XJ6fCZyIL+GO/ncTJ+W1877UHBbVZsCyLt/9kGPUmFT5wnbDc6mhZwIUGgiByZkYdCpZlC+IhtuAIYKYXA4qiRGngj0Ror1h3d3fU5tBM5/LGgtjHtVqtmJiYQFtbG753dh4VBiXqTSrIpRSubd0lvdmyZeEg1vEWFxexvLyMnp6emN5o0RTAOZsbFEmg2ijuUEM65WaGYTAyMgKCIHglOtoDSGjWLMuycLvdsNvtGB/fVXS4J2yDwZD1DSTIsPjd8AZay9TYFyetJR2cXNgCSRB4RZz81VyAKe0EaZ8GwUZ/aGQM4T1nmSpLPT1hhT/I4N6+ij2v319rwMkPXs7/N0VR/MMDsKukc2SQy5I1mUwwGo2QSqU5LaXd2VWWkmKbiVLqGy6pgl4hQUmcNouXFrdRbVDArJWDIAi4fDRGV3cEH6NQSsDJINF0cWh2sZjlYr/fn5FEK7FRcAQw08iEChcMBsOyYGPJ7LE24ExDrONGi3R78CiBzz45hdG1HXRXG8KOWUgEkGEYjI2NgabpuJ8hd6xIUvb02AZIgsD9l4nb05cqAfT5fDhz5gzKy8tRXV2dlKE2pw5WV1eDpmlsbm7CYrFgenqaVweLiooEmwdHO4bQayKJ3Z6xbY/wtg1vgIaUIgVv7sdazSDz0G/O3/cWSCZ/DQRpuFk5VMT5B1dWqoT/8Luzch43tJnh8dMpETWFQoGKigpUVFTw0542mw2Li4sAdjdSp9MJuVyedSJoTtF4OxOktdGsxvuvbYTd5YdcQu7J0vYFGfzoxDI0cgk+fnMzAOCTtzTjc0+dxeSGC80liSerCpkACl0vQqeLQ4eXhoeHwTBMWHtCOu9FIaSAABcJ4B6ITQC5tIva2lpUVlZm9dhCIQYZ4yLdlEplWF9jc6kGLAv88vQquqsN/OKYCwKYqlLGkaXS0lLU1tYmXNyjEZg7eypAZWADS+W6uDaElpYWXolJFRRFhamDnHnwxMQE3+9lMpkypg6SBIE7k0ieYFkWvx3egFxC4pZzZcZEiNxs8wWMuRXeaz6Jlae+jL/RrThGvogScgegZAi0vwrB/beG/X6m1DSNXCKKJ1/otCewm/3+0ksvYW1tDWfPnoVareYfLvJZXUmGSLEsi+GVHTQUqxLeZyzL4kt/moOUIvCRG/aF/UwuIfG2K2phDongo0gCFElASgn7zAuVAKZaco8cXuJaXaxWK6anpyGXy/nqRrJel06n8yIBLESIScJWVlYwNzcnOO2iUIdAOJJbX1+P8vLwzfj+/zmNOZsL/3VPJ7Y9Afzz7ybwioNlMCVJAN1+GnKJcNUmEqkOZmxtbWFkZCQpshSNABpVmZlGS1YB5JJmYrUhpHsuoebBXL8Xt6AmEy3Gsiw8ARpXffEFfOLmfbihrSTu7ydzjm3lWhiUmV36WJbFr4bWcU1zMbRJelYmg2DHfdCWHUHV334LbTCIgK4UgYOvAVPaGfWc8r0pPRRSqRQymQz79++HRCKBy+WCzWbD6OgoP5iUq9aDeIj2PgfPxcREJpfY3QE8NriOriod3/cYCwRB4PauMmhjEMUmczjhqDYq8V93J84A5lDIBFCM4ZXQVhdgt1y8ubkZ5nUptFxcCDFwQAESwEwvYFwWcDpgGAbj4+Pw+/04dOiQYH+9TPUfJkI6atza2hpmZmZiktxakxILdg/Ust33gCIIyCUUSFr4MWmGxef+MAmFlMKHbmhO6TxTucalpSUsLi4mTZYypW4GaAYUQYSVI4USW5ZlMTU1BafTmdQ9mQ4i+73cbjcfLeb3+2NOg3LfcZbdLW395NSqaAQQAFrLMr8wD67s4OO/ncLAkgP/76bU7lmhUJrr0P+Kd4DGO5CbEMvMgSNTBEFAo9FAo9GgtraWbz0IVWtCHy5ySXQjidSHHh/Hi7ObuK6lGDe2l/BpHcBu2s2reitQFWWAJhoOVqbmVyoEhUoAM5UColQqoVQqUVFRwZeL7Xb7nnKxXq/fc/yLJeACRbpqGDf9WlZWhtbW1qQWolwOgSR7zQzDYHJyEm63O2503WduD38C/ewd7QCAqSmr4GulSAIdlbq0mvyTIWWRBD7ZxSUTXpUsy+JHx5cgk5C4t78qqWMFg0EMDg5Co9Ggu7s76c1xfG0HY+su3NpRmpaNSTR10Gaz4ezZs5DL5WFkEdhNwDj9ocvjvGL+oqNCi4/dtA9Hm/ZOiecKqSqAdpcfKhkFRQZyiKPB6vTjj5M23HKgJOY5h7YeAOeb+6enp+H1eqHX63kvuGzl23KIPOeOcg1Ozm9BK5fs8cokCCJmf97T4xb4ggxvjp1pFJpCzCEbxDW0XFxXV7enXCyTyaBWq+FwONDd3S2aAvjEE0/gPe95D2iaxgMPPIAPfehDIlzNeVwkgBFIhwByXmptbW0wGlMzKy6EHkCfz4fBwUEUFRWlRCiA5MnunT3x+ycTQeg1+nw+DAwMwGw2J03gkz1WMiAIApUGxR4fsEQE0O12Y2BgALW1taioSJzpG+16V7Z9CNAMxJyDiFQHud7ByclJ7Ozs8FnKsbzi0oHbT0NKERnN783HqWFg9/P1BOj4ucIhYFgWT45ZIZeSuD1L1+PwBuHx0/AFGcGkJDI6bHt7G3a7HfPz8yBJklcHNRqNqCSHZVnM2jxhPpiRhOTVh6rw6kNV0f48Lk7MbwNA1gggkP++ddGQixzgyHKx1+vF2NgY/uVf/gUzMzOora2FwWDAxsbGHrs3oaBpGu94xzvw1FNPoaqqCv39/bj11lvR1tYm3nWI9kpZQjZsYJIlYSzLYnp6Gtvb2+jv7095nDyXPYBCCQvXE8dFuqWKbA+BPDayCZvLj/8XZ+KVG47Yv38//8VOBZlKq+EsdIQei4sZPHDgAN9Ynwqu2Z/5WA6lUomqqipUVVVhZmYGLMvCbrfz6mCoV1wknhq3wO2ncVtnYoLCsiyeGN2AjBI+BBKJv0zbUaKRoeVcKblQNk2WZbHtY/DYwDp6a/SCJkNJgsBljUboMtjHGImGYhVPqFJRpbjcYu4hnMstXlhYgNPphEaj4YdJ0rX+eGxgHZ//4ww+9fL9OLpv92Em2SGQL/xxFmU6Oe7rD3/I/cB1jch/J7ncIx8MrBUKBbq7u/HLX/4SwWAQX/ziF/HCCy/gVa96FVwuF66++mpcf/31uOyyywR7px4/fhxNTU1oaGgAANxzzz14/PHH/74JYKaRLAnj1DCDwYDe3t60NoNcTgEHAoG4v8P5GC4vL4syQCCG2kkzLKY2nGgpEzBgQ5IgEHszWV5exsLCgijXlum4QiHHWlhYwOrqKh8zWEggSRIqlYp/cubUQa68FzpZTFEU3vfzMQAQRAAJgkB3tR5qmfANI8iwfPM+w7J450+GAQCDHzlaEGavodDISFRrFShPIt1CbO/KZJEuwZbJZCgrK0NZWRlYloXT6Qyz/kgnKeLoviLM2t3oqTn/gMWyLL7xt0WQJIm3H62L+/cEQYAFsLHj3/MzMVNjLmTkm4G1RCKByWTCLbfcgne9613Y2dnBn//8Z/zqV7/CBz7wATzyyCPYt29fwtdZXl5GdXU1/99VVVV48cUXxT1XUV/tAkAyiw2XCJGuGsYhX21gaJrG6OgoAKTUExfrmOle62f/MIknRjfw3df1oNEcX824o7MYTufehAmGYTAxMQGfz4f+/n5R+oWyqW5GEsAgTWNifBw0TaOvry/nT8apIPKaQtVBhmH43kEuSeLLt1TAYBCucNabhBP8IMPiV4NrMKikuKa5GCRB4Ov3doTZbRQKWHaXyF7emD99idkGQRDQarXQarV8L1doUkQyk+oAYFLL8PA1DWH/xjAM5BIKRBwC5w3QuO0bJ3Gs1Yz3vawh5u9dRGLkogScCE6nk3fE0Gq1uOWWW3DLLbck9RrRHi7FrjYUHAHMh3ILy7KYm5vDxsZG3ESIZJHtsiiHeMTT7XZjcHAQFRUVSRkGx4PbT+O/T1hwe4sW6dgiv/7SGpjUMtQJ2NCjTcv6/X4MDAzAZDKhpaVFtHsrVwrgj16cx9zCIu7tq0RdXV3c62FZFi/M2lFtVKEqxwpPMuD6ubgIPrfbjR+/OA//8hy867PQ6/V8kkSiTeHRl1aglFG4JU6PlYQkoJZJ0BTS43WkIfn+3nwAV07l7pd8WEtzjdCkCM7H0m63Y3JyEj6fDwaDASqtAU/MeHCsrUSQGsqyLB64rCbu+yuT7CpWO77EjhNzNjcq9Ar+by4iHPk4vex2u9MeAqmqquIN0YFdVwohfdzJoOAIYK4RCAQwPDwMhUKB/v5+UW+8fFMAuUi39vZ2GAyGlF6bZVlMrDuxv/R88/XwigMvLjhRr6dwsDX18640KPHWo/WJfxF7r9HhcGBoaEg09TbWsfxBBhIy3LpFTHAb+s7ODrZW51BmLkV9feL3hGWBsxY3Vra8qDKmN2AjNpIh0CqVCtd01kIrl6BIJeFzZmdnZyGVSvler2i5n5/8/TQAxCWAAHCsTdz7IxOwu/zQKaV7fOai4bHBdZCEsJL53xNCfSxD1ebldSvmFqx43mcB02iGyWRKaAyciFyTBIE/vPOShOe07QngHT8ZRrVRia/f25Hw9yc3XFjc9OBlSfbtFlorQyjyVQFMlwD29/djamoKs7OzqKysxCOPPIIf/ehHIp3hLi4SwCTgcDgwPDwc1fBYDOTLEAjLspiZmYHdbucj3VLFC7Ob+PKfZvDmy2txVfPuRvrSwiaqDXL0VUR/3R1vEBPrTvTW6EVTKUJJGWfQ3dXVlRGvJo7AsCyL/3lhAXIJidcerhH9ONyxbDYb1tbW8LprewUvOiRJ4K6eiguizyi0pBuqDnq9Xt5mhrMGCVUHf/f2fkGEKd/hCdB4etyKSoMCl8Up73IKoFpGZXQC+kJBqNrc0doMn88Hu90eZgzMPWDEssFKF3rlrk/gFQLthD71xBT8NIsr95mSurfzUUUTinwkgGIogBKJBF/+8pdx7Ngx0DSN+++/H+3t7SKd4bljiPpqWUA2yhZcuTD0C8GZAnd2dmbM4TuXCiB33EAggKGhIahUKvT29qa9KDSXaLDlDuBHx5d4Auj00dDIJZDE+Ch/P7yG04vbqDepYDrXa8WyLBg29cZojgCOj4/D4/HENUN+bGAVc1YX3nNNY8oRQ9xm22RWoyyJhvtkwLIsHA4HHA5HXC/GWJBnydctWYhVQlcoFHusQWw2G2ZnZ/lGbZ3JVLD+ZxyUUgq9NXrB99n1rfmvaOYj5HI5ysvLUV5eHpYju7S0BJZlebIotpr2uksSW8gwLIuP/3YSPdV63HKgJGxoybLjR2mCe6OQCSDDMFn3ekwEsYygb7rpJtx0000inFF05Ne7lifgiBhHjMbGxsAwjGhDArGQq02Iu96dnR0MDQ2JqnCaNDJ85MbmsCGN91+3D3a7Hevr6wD2Wj3c3FGGg9UGnvwBwH89M4MdbxAfuqE5JRIYDAaxsbGBmpoa7N+/P+57/bk/TIFhWbznmsaYv8OyLCY3XNhfuvdhIPS1r9qfmc2WpmkMDQ2BYRi0tLSkpEAEaQaSvxMlKNIaxOv1wm63Y2ZmBh6PJ6fGwWIg0RAUULhGv7nEm344iCmLC8+853DYuhOZIxsIBLC5uYm1tTW43W4MDQ3xwySpTuEn83mRXHoOwu+Frz87j5cWHfjMbS0ojjO4VMgEMB8VQE4hzncU3kqHzDfZc4TI7/djcHCQn0C8UBdPkiT5RSsTCueRxr0ZupwiZ3P68YX/m8Y9/VU4ULEbc6SWS/YQq45KHU7Ob6VE/nZ2djA2Nga1Wo3GxtikjsOT7z4CPx0/YPyHLy7ii388i8/f1YEr92XeJy8UHo8HZ86cQXV1dcqby++G17DlDuLu3oo9JDDyurc9ATw/u4lrmosvmEZ0hUKBiooKVFRUhKmDc3NzvDqYSgh8viOVa9lyB2BQZabEme9wnhvSSLTuSKVSlJSUoKSkBA6HAw0NDbDb7RgfH0cgEIgZexgL/iCDz/9xBh0VWsFG0J+8Zf+ef7v9YBmK1TKY1PE/v0ImgPl47hezgAsYFEVhbW0Ny8vLaZvo5jsYhsHMzAy8Xi+OHj2aNfWDI4Akufv0SkVsTJFPv1fvN+PqEDWNZlhBZJDLKm5pacHy8rKgc9MIML091l6KlW0f+moMgl5TLHDWQ1zazMTEREqT4/tLNRhY2hakANpcAWy6g3D56awQwGxOUQN71UGfz8eXij0eD3Q6Hd87GOv7MWdzQ6+UwpjHRCmV93TW5sYLM5u4qtmEcn3u/STnbG48O23HKw6WQZsFc+qfvKknqd+nGRajdgadMgWqq6vDYg85xVkqlYYZm0cj5VKKAEkQghNbYqFcr8DdvYknR/ORRAnFRQUwdVwkgBFgGAZOpxM+nw+HDh3KWHNvPoCLPeOmJLNZ+uIIoFElwydvDR8FZhgW//L7CRiUUrw7Shn2rMWFn55cxusvrUFFjBB1lmUxOTkJl8uF/v5+BIPBPRtgOiXQEq0cHzyW2MxTTCwtLWFpaSnMeijVRbvRrEGjWdgTar1JiWqjImeDA6FGzNmAXC4PUwcdDgdsNhvm5+dBURS/eXM9PgzL4szSDuQSEje2pxb7FA/eAA25hExbiUylBFyuk6OzShe3fJhNSCgCEorI2+Gl5S0vRm00Jjdc6KzcrWhExh5Gth9wwyRGo5HfbwiCwAeuS1ytEAsXCaC48Hg8otnDZRIFSQAzpRB4vV4MDg5CIpGgqakpZ+QvG706XKTb/v37UVRUBIvFktHjRSKe5yFJ7i7wJdrojctqGQWZhIRCGn3BCgQCGBwchE6nQ1NrB1YcAZSqw483uLyNB/93AJ+7sx2XRSlR5xMizapDF7tsqGUEQUBK5WbDXXN48dzMFo42FeWEhHB5xJwNEqcOcpOgNE1ja3MTRxuLoVaIf35BhsXvRixQSjNDLhNBIaXQXp4/SkaVQYl7+/LLtigUlQY5rq6WoLUs9sNVZPvB0sYmNre3eM83bphEp9Nlrf2gkAlgPp47y7J5d07RUJAEMBPgclNbWlpgs9lyYsgM7G44mSSAXKTbyspKmJKUbR+oRKbXH7lxbz8LhzK9Au+7rinqz7hBlsbGRpSWluJrf56By0/jwcurw46nU0hBkoBBmd8KbyAQwMDAAIxGY1Sz6mgG1+ki18MCoaRWI5dAKSWhSiK6LZOIVAfPnDkDl8uFtbU1kCTJKz1i9Q5KSAINJiUqYyjdySDXn2shYdMdwM9Pr+LG9pKk3nsCgFkl3GaHBYG3/vwsKJLAbx7sRyAQgN1ux8rKCsbHx6FWq3nFOR07rkTIRxIlFPmmABbS9+zvngBynnc2m43PTd3a2sqJHQtw3pIlE19GmqYxMjICkiT3KEnZRqT3YLoYXNqGHi4sL8yFDbLc218Nm8sPuVQSdrw6kwrPvv+oaMfPBJxOJwYHB3kyGw2hZGnd4cPw8jau2m9Oq0SW7OLFsCxmrW7UmVSil+Y0cklOlC8hIEkSUqkUNTU1UCqVe3ziuN7BoqKitNoruqrF60EulI0JyK05MYHdwY9kb+dkN3+KJHDLgRJeMZRKpSgtLUVpaSlYloXL5YLNZsOTLw5haTuI61qL+WESkiSxuu3FM5M23NNXwU8Cp4KLBFBcFAoJLEgCKNYb6/f7MTQ0BI1Gg76+Pv4LQFEUgsHEET2ZADeBLHb52e12Y2BgAFVVVWEB07lCpALIMCxYpObzt7Llwdv/9yXsM5L45huPhL13BpUUBpUUDMMUlNu9xWLB5OQkOjs74zYThxLAyfUdrGx7BQ/IxHq9ZLHm8OHU4jYokhAUyyfkHHKlwKeDUJ84hmF4n7iFhQXeVNhkMkGj0eRkcyik+x/I7SZqUEnxxkuTXydTIVLvuLIu6r8TBAGNRgONRoP3PWmFn6bwikN6WK1WTE9PQy6X47FZYHDDj6vPDemk+p4xDJN3JEoo8o28FtL3rCAJoBjY3t7G8PAw9u3bh5KScIVBIpHkTAHMhBk0RybSiXQTG6Hm0wBw97eOg2GBX7wtcTxSKAKBAFamR3DXAR3uPNIakzhnmlTEy1d9fsaOOpNK0BQllzNttVrR398PmSx+X1koAbys0YRL6ouybtVSppOf69HLXImq0ECSJPR6PfR6PRoaGuD3+3ky6HQ6wyaLs9lrXAiqBId0COCZJQesTj+ubcmuRVOmSOvX7+2AxelHeakG5aW7bggejwev0VsxvmTF4sQgNlRafPZFJ65sNuOtV9Ql9fqZqjplA/lGAL1eb0EMgAB/hwSQ64FbXl5Gd3c3VKq9igVFUfD7/Tk4O3FLo6GRbkLIRKawtOmBSS2DUhY+vBCKphINtj2BpF6XK5E2NDTgPX3xc00zvfF9//ndBu43HDkf+cayLPxBBu/48QBIksDJD18V9zW4Er1EIhGcwhJKAEmSgCwH05EkQaBMl3uLkHyGTCYLS5HgJouzqQ4WkjIBpEemRlZ3QDOJr3d12yuqvU2myEixRsYPQQ2v7IBlWXRU6tBYV43Gumo+t5imt7GxtoKXXrLzwyRarTbh+5hvJCpZ5NODjVgpINlAQRLAVD/sYDCIkZERUBSFQ4cOxZS8cxXJJuaxuUg3tVotmExk4unVF6Dxr7+fgFJG4T9eGTvM/DO3J5dxuLGxgenpaXR0dOSF35JJE67icMRMLqXwmdvbsa8k/oLg9XoxMDCA8vJy1NQIzw3OtmdeNnAhXlMoCILYow7a7XZeHcxUxmym1CnLjg9yKQWdyL586ZzvfX2Jve+mNlz446QV17eaw/Kk00E2ytaf+N0kAODRB3r5f+MeIn7ylsMAwN9Ti4uLcDqd0Gg0/ENGNCGg0AlgPsHpdF4kgPkGTi2qra1FZWV8G4FcEsDI0mgq4CZhGxoaUFYWXxnjEJpfKybkUgo0CyzYPXD5glDL995yQZoBSRAgBahXLMvi7Nmz2NraQl9fX85UzUi8vDM8Oi+UxFzfFn+IgWtHaG1tRVGRsND3aMcRC4XSwJzPSOY9lMlkKCsrQ1lZ2Z6MWQD8xi1Eyck2WJbFn6ZskElI3NYpbK1J5rWjkZJ1hy9htq2Q96m2SInLGopQJcKENYdsEKnPvuK8b+qszY2vPzuPj93UDIc3gK89u4CHr6kHQZA465KhqboR21Y3asxS2Gw2DA8P7/qvGo0oKiqCXq/n+7ELMQIRyD9l+6ICmGdYXV3F7OysYLWokBVA7lqTjXTjSs+ZWLxed0k1vvPcfFQrD5Zl8cnfTkBCEfh/N7fEfZ1gMIjBwUFe1XxiZB2T6y686+oGQeQxm+B6DhM1Vq+srGB+fj5mO4LQ44iJfCMZhYbhFQfmbB4cazMnbZ4dmTEbqeSkow5mgtgTBIGr9pkgTzOxIhqine+M1Y2/TNtwdXMxaovS67OSSUgcqNBiwe7Bs2ftuK+vIu33J5MEMEAzu7ZAxefXiRNzW5i1eWBz+WFz+eH209jyBPHb4XW8MLuFIpUUrgCN/3xlO+rqtKirq0MwGMTm5iY2NjYwNTXFx0km+/B5EdHhdrsLIgYOuMAJIMMwGB8fh9/vx6FDhwQ/4RQiAeTMgr1eb1LXyoFTHjPxFHhZkwmXNUU3WyYIApUGRUzTZw4ulwsDAwOor69Hefmu2ra85QXNsnlH/oDzfo6xEJlUkur7fiGWS300C7KAr0klk4AiiZTTSwI0g6fGLGgp06ChWJ336qA5wXcXAHa8waSj2xhmbx53lUGBS+qMqNDHP+b/nlgGRRK4R0AM2id+P4XxNSeOtZrTNhvPlHoeoBl89smzMGtleOvltfy/39FdjhvbS6BVSFBtVKKratcy6NX9leivNWCfWYVVhz/s4VsikcBsNsNsNoNlWXg8HkxOTmJ1dRUrKythucX5rgrmY7XiYgk4wxDygXs8HgwMDKCsrAytra1J3SSFNgXMRboVFxdHNQvO1HHFwluP1sf9Ofek2tHRAZ1Ox//7A5fXCT4Gy7L47YwfP5w7A5WMwr/H6UcUA/GUuWAwiIGBAeh0OnR3d6e1gF1oBNDhDeJPZx2o1VNIohUyr9BQrApTaZIFSRBgWCBAh3+ukeogZxq8tLSEnZ0daDQaXh2M1hqRq83yV4Pr+MTvJvGN+zoEZWf/6MQyTi858LHra/acr0xCxk3Z4EARhOBc5v+4vRVTFpcoSTOcAmh1+qFXSkSLT5RSJNRyCpfUGcL+XUISUYm1XilFf+3u7xpUsa+LIAioVCq+R9BgMPC5xbOzs5BIJPwwSa7si+IhH3sXXS7XRQUwl+BsT9ra2viA92SQax/AZEp6m5ubGB0dRUtLC581mQoSJXNkCvE2JTGnmAmCQIABji9sRu1DTASGSU5pjKUARlMyhcIfZGBx+lBpOF/6SqQ05gLeAA1FiiVBjZxCuU6GEnV+bTTZBEUSuKUjuvF3KCJNgzl1cGhoCMBedTBXBLC1bJc41BiFlWy/+MwsWAAfu6465fO9R8AQCAeD6jxZShcsyyLIAD86uQy1TII3HRHPc/WhaxpEe61IcESKGybhysGcufn8/DxcLhe0Wi3/83zov85HE2hu6KYQcEERQJZlMT09je3t7bQIQ66HQAKBxHYoLMtiYWEBq6urYZFuqULsZA4hiLcpBYNBDA0NQa5QxJ1iHlzexl+nbHjb0fqEBO0VTTJ89rWXJr2p2Jx+/OylZVzfVoL6YmHSfjRljosbjFQyheLk/CamLS7c3lXBP/XnmwJod/nxzKQN3dX6lFQwkiDQVaGG1+vNwNllBvmgighRB3O1Ye8rUePkBy8X/PvPvPdS/OL0Kv40vYkGWe7f22TAMAzkUgpX7jOhUkR7mUwjlpIWam4e+pDBDZOE5hbnQonLRwJ4UQHMMKItuD6fD4ODgzAYDOjt7U1rUc6VGgYII5+ZiHQTY/o4lWNGW3i41JIfnpVgwbGNR5tYKGKsLR99fAxOXxBvPFIb5jMYDamqIHIJCbmEhEom/OsSWgLmyPra2hr6+vpSzvTsrjagwqAMK/nkW2qGViFBhV6OEm16am0+kdpCRKQ66HQ6sbCwgO3tbWxvb/PqoE6nywsCGwq1jIJGTqFMS4Dw59e5JQK3vhysTPyA95vhdQyv7OAD1zWmFeMmBoQMrEV7yNjc3MTa2homJyehVCr5+4obLMnGeedbCdjtdhfMQE1BEsBIcGXQ5uZmmM3mtF8vlwtiIgLIkaPq6mpUVVWJdtxckN5ox+TK9wcOHEA/u4XlgTXI4yRb/O+b+rDpDiQkf9zxohGLZ6esGFndwf1HaqOmaGgUErzhSO2efw/FjjcIT4Dmh1m4YzEMg9HRUbAsi/7+/rQWK6WM2hO1lm2yZHP5ce2XXsRnbtuPY1HsbaQUiUsbCmPxEwOFQFQJgoBWq0VJSQlUKhWqqqqwubmJlZUVjI+PJ/SIywVu7yqHw+HAyspWrk8lKSRDSL7x7AJolsUHr2vM8FklRipESiqVoqSkBCUlJWBZFm63G3a7HePj4wgEAmHDJJlS6fJVAbw4BJIFsCyL+fl5rK+vi1IGzQfEI4Ch5EivFy8gPtFxM4XQsvNPTy7hRy/M4kP9cr58/4Yj+oTESyOXQCOwpy+WNYtaLgFJAFIqdeL/+JkV+GgG9x+pBUEQIAgCPp8PY2NjKCkpQW1tbdQHi1mrC3M2N67en9qDSzoE8A+j6/jWs/P40Zv6BMfHMefSFWZsnpSOeRG5A6dORW7cTqdzT1kvnjoYZFisbHlRk6YNi9DzTfZnycAfZESNTkyGSP3szb0I0nsnnXOBdJU0giCgVquhVqtRXV0Nmqb5YZKZmRlIpVK+XKxWq0W75nyMsOPsmgoBBUkACYJAIBDA8PAwFApF2spKPiGaKsaZH29ubmYs0i2XCmAwGMSPnz8LPw309fVCEueJ7p0/HsCczY1fvf1w0vYvsa6xp8aAngTTiW4/DbmEBBXjmDd1lMHtp/mFLRgMYnR0FG1tbSgujp1Hete3ToBhWLzwwStT2ojSIYCff+oslrc9YJL4e7NWjtMfviKl4wnFxRJw9sCpg1rteY84u93Oq4NqtRomkylMHbz7v09h1ubBU++6ZM/kLM2wIAlxqiixSN683YNXffsl/Psdrbi8MXW1+bfD61h3+PGaQ5WikcBkiCnXWpIMttwBvPOnw/jXW1tiEvDHB9fg8dOwuQKQS0jc3VuRMKVFbCJFURR/3wC7SUfcZLHH4+H9LNPNwhZSus42LvoAZhgMw+DkyZOoq6tLepIyGeRiai5SiQsEAhgcHIRGo0FfX1/GzicXQyAkSfJTsV++o2lPQgvDsLC7/SjWnO+Z8wZpgEBK3n+pTswyDIsfvLAAhZTC6y+N7k1SpJah6Jzqv7a2hs3NTbS2tsYlfwDw87ccwuKmJ+UNKB2y9Jt3HoY/yKQ8sXsR4chHT7JQCDk/iUQSpg66XK49CRIfvLoCT045YVLv3bh/PbQOicAp5lTPd/ffISjrNx46K3U4zThypgCmgvUdH7wBBlMW1x4C+J3nFjBn98AXZMCyLFa3fZize6CQknjNofjtQpk+b4VCgYqKClRUVIBhGH6YZHFxN0M9dJgkme/QxRJweihIAsgNP2TSpJJTi7J9c4USQC7SrbGxEaWl6S+o8ZDJIZDpDSemLS4cayvhv9xzNjeGVt3Y2hrDwYMHo5a0H/7ZEKYtLvzv/X3QK3c3m/9+bU/K55HqwARJEuiuMaA8QfwUp9Rub2+jtLSUV0yCNANJDD+wWpMKtWnkkKZDAKUUGdWnLBgMgiRJEASRM2W90BTAiXUnpi1uvGy/CUGGFdyWkE0kS1AJgoBGo4FGo0FtbS2vDvptNlxvcmBkZIQvF3ODTQalFEVRiKGY51tnUuH591+W9utXG5WoFmhNIxSx4uvEQnOJGj99oAfRPsUt76512advawHL7toxTaw7sb80sRqVzWEKkiT5LGwA/MR6qOoceV/FQj4OgXB2OYWA/FulBEIqlWZ0k+CIWK4I4MrKCubm5pKOdEsVmSSAX//LHBzeAK5qNkEhlYBlWTz8yEtwebz4/ms7YvYzvuWKOvzy9KpoIfPplLkP1cX3k+Rsa1QqFXp6ejA5OQmWZbHu8OL3w+u4rq0kzL9PLIhZLmVZli8Fce8TTdM8EUxnoQ0yrOBkjNBN3xugwbCIGiOYT9ApJJBSBN750xEcn9vCM+89DJNanFYNX5BJulSYCcRSB0dHR0HTNIxGI7pKTNDpxFmv8l1RjYZMZ+oSBBGV/AHAw6E+gQTgp1l0V+sFv4e5eq8jJ9ZdLhfsdjtGR0cRDAbDcosj9+N8VAAvloAvAOTKC5AgCDidTmxsbKQU6ZYqKIqC3+/PyGv/44378LYfDeBdPxnC1+/txNDQEIwKwCBXQBrn+trKdWgrj26n8PTYBhRSCpfHiJiLhkz1OXo8Hpw5cwY1NTV8GZsjZiqZBAoZlTFFSCwCyLIsgsEgCILglUuGYUDTNP//ue9DsurgqYVtvOmHA/jKqw7gsiR7tv44aQPLsrj5QGYV8HRRrleg/Jzv2/G5LcEpFIngCzJ4YnQDFTo5+hM8hCSCmIQqmjrIWYJMTExApVLxPWCp2h5lmgAubu6WS5vM4pXrcqVIPT+7iekNF15zqBIEQWDd4cO/PDGFyxuL8CoBcXj5gtD7qqamBjRNY3NzE1arFdPT05DL5bw6qFQqM064U8FFI+gsINON4rkggF6vFwMDAwCAgwcPZvWJLJNDIEVqOa5tMaO3Uo3jx4+juroabTVqGOFM+ZiDyw6QBJImgGLfM3a7HWNjY2hvb4fBYAg7FsMw0CokuKdPPLueSMT6HrAsi7+eteNIQ1HMwRXu9xiG4XNXQ++5UNWPYRheIeQ+s2AwCIqiEpJBrUICEARfxk/mmvpr9KDzvBwc+p5d32rG4EeSn+g+s+TAwcq9eb5yCYlynRyNIpKUTCAyXzaaimMymaDX66PeK24/jd+PbOBIg5En0pkmgK/53hmwAP7y0KWivWamz9my48MPTizjzUdqwvxAnx63IkDvfkd/8tIqagwKdFbq0hqSyQdQFIXi4mK+l9rj8cBut2N6ehperxcEQcBoNCIYDOYNEfR6vVnzQUwX+fGO5SGynQccGuk2MTGR8+ETsXFnmw7j4+M8UXpfFTA9PZ0yAXz31Q1Jv0eRPYDv/ekg/DSLr957MKVzWFxcxPLyMnp7e/d84cV8QNn2BGKSp1jHeWrMgvf/fBjvu7Yp5uBKPPIXCW7T5sotoeogwzDw+gO7pVq5NOz3gd2+pTMpTg6btampR2JgcdMDp48WlD2bDv44YcV7fz6K915dj/sv3Rsdlqj9QCiyVVKNVHE4dZDL9FYqlXxmcej3hiCA0LmOTJ/vF17ZBrdf3DUvmgLoDdD4zvOLOFRrQF+akXMbTj9cviC2PIEwAviPx5rAYvc9fGlhG8MrO/iXl+9P61j5CKVSicrKSlRWVoJhGIyNjcHr9eLMmTNhMXZc/GGukG99ibFwkQDGQLbygENTInLpZZgpBTDUqzGSKKVzzFhDFfEQebyBJUdKx2YYhjc7jZXEItb7Ob62gxPzW7i+tQSlUYZQYhHAy5tMeOdVDbj1YFnU102G/EVDpDr45OAaggyDm9qK+Y0714Mk6eKWr50AAJz58BUZ3UwO1xvxukNVePmBvcbaYiMXm2KkOuh2u2Gz2TA2NhamDr6iszTsXsl0ObWnWlwvVSA6aZVQJEiCgCQNn1EO7eVatJfvHTAIVfk/eUtzXNX/QgFJkpDJZCguLobRaITf798Tf5htg/NC61stWAKY6Tc5GyVgmqYxPDwMiUSScy/DTNjAREbWRV5ftr0HI4/3zMO7+aR2lx+/PLOKO7rLYVTFXyj8fj8GBgZgMpnQ2toa8z4USwGsKVLBF2SiWm4AscvaKhmFt1xRF/VvuFIut1il+10iSRJ99UUI0ixkMlkYueSUwmQGSfLFB/C/X90JhyeY8bVGJaPw/msbEv9imsiH9zTUMJhTB7e2tnh1UKFQ8L2DhbaZAtFJ6+jqDt58WU3WSNnfk61T6BCITCZDWVkZysrKohqchw6TZHKvLaT7tmAJYKaRaQLocrkwODgoeqRbqhB7Ctjj8WBgYAAVFRWoqYlegswFAYy2Cbr9NAI0A4+fgTGOI4vT6cTg4CCamppQUhJfrRGLxKhkFA5WxVYqkj0ON+wBiFumqIgIvo9WKk5nkCQX6A8p1zEsm/O81nSRaYuSVCCRSPger8g4MbfbDaVSCbVaDYPBkHfnHg2Rm//AsgP/8Msx3NdXgTcc3lvezwdwVYBCRKwp4GgG56FtCAqFgi8Xq1Sp23BFopDIH3CRAMZEJgkgdxPGi3TL9o0kJhnjBiPa2tpgNMbuX0qVdLp8QahkVNo9gByqjEq87Wh93L/d2NjA9PS0YFuebJFbod6G6ZZ8U0WiQZJo6mCypHbe7oFZI8uYVcz0hhOTG25cs9+0R13JB1VNTLy0uI3fDm/gH481CVasxCLHkXFii4uLcLvdsFgsmJ6e5tXBoqKisFaZM0sOfPbJaXzntQehFEn9+vOUDVueIG7rTG76PFIBbCvT4PWXVOFYa/oZ9ZlCPj4YCIXQNoHQNgQA/IPG1NQUfD4f9Ho9TCYTDAZDWsMkHo9HVEKZaRQsAcxGCVjsHkCWZTE9PY3t7e24kW65MKEWg/CG9jOG9vvNWl1gWOyZZCRJEoFAIKlj+AI07vrWCegUEjzyQH9Sf5sKKWNZFrOzs7DZbOjr6xPcS5KK6bQvQMPq8iflFyiELOWK/EUi1iAJRwq57xtHFIXAG6AxsLSNSoMCvQni/FKFViGFTEJENc0uJAh5qPzAL8dhd/nx0DX1gqyLdrxBPDVuQW+NAbUiZwNzKk5FRQVYloXH44HNZsPExAQCgQAMBgNMJhN+NWjFnN0DhycoGgFc3PQgFW4fSUikFIlX91fG+YvcIx/NlIUiVR9AlUoFlUqFqqoqMAyD7e1t2Gw2zM3NgaIoXh3UaDRJrZdOp7NgUkCAAiaAmYZEIoHP5xPt9fx+P4aGhqDVatHb2xv3psqFCXW6ihXDMBgZGQEA9PX1hZ37vz81hZHVHXzujgM4VGfEXyat+NZf5/DxayuAJI8pl1Ko0Ctwd2/yi2qy18j1aEqlUvT29ia1SEaSW5Zl8cjJJRhVMtzQHl1VuOI/ngXNsHj+A8JzgRMRwHwhf9EQTR3k0iY4X0rud2K99wophcsai6DNYPJGqU6OUl3+KjgA4A8yokSaPfbWXthcAcG+lVyerToD6msoYSUIgt+0q6urQdM0tra2YLVacW3RJq67Wo2AwwKP1CTKIF2i6DQh55xLbLkD0CklgpRZsXOAswkxyCtJkjAajXy1yufzwW63Y2FhAU6nE1qtlieEiQSAQoqBAy4SwJgQswTscDgwNDSEpqYmQZFuufAgTGcIhPMvLCsrQ01NzZ4F8P4jtXj7jwfwrb/O4VCdEes7PgRZFhKKhN+X/DH/+7XdKZ1nMqVFzlqgsrIS1dXJ9+5EHosgCFBEfBXpK/ccxIn5zaQ28njXJPawRyZBkiRWtjyYnp6CWS1FQ0MDT14T9Q4mm7gxse7ErM2Nl+0vLihVb2xt97xvag/vP522uDC66sRVzaa4qTlCyIlGLknKtFwmITNm0h3vfCmK4odFmgF+snhychJ+vx8GgwFFRUUwGAxZfZDOhJoWoBm85ntn0F+rx/uvbdzz8wW7Bz8+uYx3XVUPlYyC20/j4V+MolQrx6dva8nJOWcLmRBK5HI5ysvLUV5eDpZl+dxibpgkNLc48n27qABmCYUyBby8vIz5+Xl0dXUJvjEyGcsm9jE5/8LW1lYUFUU3HW0p0+JwgxGvO7w7DHJXbyXu6q2EzWaD1ZndIRAh17i1tYWRkZG415QI0YjZ3QkMofvrjEmnPcQzgs7EsEemEAgEcOy/XgAADP7TVWHf71i9g6kOkkjI3TgtodF0+YL7vnsaLIDrWsKJq1kjg1EtzYgKl0sko6ZFUwdtNhvOnj0LuVzOk8Vo6uCM1Y2nxix48+U1afcyJnPOdpcf/3tyBXd1l6MsTs64hCTg9tN4fnYLW+4ADBEpM4ubHrj8NLwBGioZBZWMQpVBAeuOHwGaSfiQU8gEEMgsFyAIAjqdDjqdDvX19QgEAnzizeTkJJRKJfR6PbxeL5qbm0WJgfv4xz+Ob33rW3y/4r/+67/ipptuAgB8+tOfxre//W1QFIUvfelLOHbsWFrHKlgCmGmkSwA5rzi/3590pFsmLFkSIZUv0cLCAlZWVhL6F266A3D6aDi94e9nsqSTOecSS6a4cQvpOVxeXsbCwkLanoyZGAJhWRb+IAN5SJ9TNALIESWxVD+aYbG85UW1UZGRxdbtdmNwcBAfvqYKRsPe7NJEJtTcPcT9PN5m9sjJZXzmqRk88Y7+vFZEo+HXD/Zhddu3Z0PXK6W4QkDiQ76UJ4Ui1fMNVQcB8L2Dk5OT8Pl8fO8gpw7+x//NYHhlB3f1lKMozfzmZMiUn2YBlkWAjr9OEASBz9/Zhl8Pr0etDlzWWLQnYrFcp4DDK6yHvdAJYDYhlUrD8rDdbjemp6fx/ve/HzabDS0tLVAoFHC73WkNgzz00EN4//vfH/Zvo6OjeOSRRzAyMoKVlRVce+21mJycTEsBvUgAYyAdAsiVREtKSuJ6xWXi2NkAwzAYHR0FwzAxjZBDse7w4sTcFi6pNaKpRI1v/GUOb7+yHsokSdIX/3gWAPDwtU0pnXc8UsayLCYnJ+F2u9Hf3592rFAmvOx+PbgGt5/GXb2V/IRm6HH+MmXFQ48O4cl3HYZeKRVts1/c9ODUwjZkEiPKdOJGHG1ubvIJMYd10XOfIxHZOxhJBOOpg9S5/5ZLCk8tqzIoUZXEgFAkUiVUO94g1HIqazY4VuduJrlYhFWpVKKqqgpVVVW8Omi323l18N19BngkZSmRvyDDgmFYnphFO2e3n8Yjp1Zw+8GysIzoMp0c77oquvtAZE/nvhI1Hr5GuFfkg0drBf/uRQKYGrip9YMHD+Kpp56Cy+XCl770JTzzzDM4evQoioqKcOzYMdxwww1oa2tL+15+/PHHcc8990Aul6O+vh5NTU04fvw4Lr009SjDi596DKQaBWe323Hq1Ck0NTWhvr4+5SfYfCWAXq8XJ06cgEajQUdHh6Cnj2KNHEUqKawuP/zBXQIWoJmkVbJqo3KP31wyiOUDGAgE8NJLL4GiKHR1dUEikSBIMzizuJ3WscRWAHtrDKgzqcLsOTgCyLIsXpixgWZY+ILi+npVGhQ4XG+EWSNuLNvq6iqmpqbQ3d0NnUDyFwmSJCGRSCCTySCTySCVSnkFnaZpBAIBBINB/rO4q6ccZz58RdhGnC4KSVUDdgnWiblNMAIeUDwBGk+NW3ByfivzJ3YOz07b8OxZe0YUS04d3LdvHw4dOoTm5uZdcru9guPHj2NychI2m03w+vvyr53ArV8/wf93NDLl8Abg8gWxsSNsqHBl24v/fGYWo6s7wi8sDVwkgOKAMze/4447cPLkSXznO9+B0WjEJz7xCRw8eBBzc3OCX+vLX/4yOjs7cf/992NzcxPAbnUqtB+9qqoKy8vLaZ1zwSqA+WYDEy/yLJVjZ7sELARcb1xLSwtfXhGCWpMKf3rf+SzYT97aCmB3YiqZ67wrhcnfUExseLC940FTiIDocrkwMDCAhoYGlJWdj037r2dm8PPTK/jGq7vQXpE8OcmEAlhpVKLSGK4Acd8Dmqbx0DUNePhljaJ/N6QUiUqDeMofy7KYmZmBw+FAT0+PaCHuoaViqVS6x2amkEyoMwGOUE1ZXLDs+MCwQKJuCqWUQnu5VtTPPxGu2V8MALCuuDK+zoeqgwzD8L2DMzMzcAQp/OIsi0/c0oxiw974td1zNcHuCp/2jzznMp0Cbz9aF9VXkWbYPf9uUEqhklEoyVIOdqESwHz04AztAayqqsL999+P+++/n/c75XDttddibW1tz99/6lOfwoMPPoiPfvSjIAgCH/3oR/G+970P3/nOd6Jeb7rfj4IlgJlGMipcMBjEyMiIaJFu+agALi0tYXFxUdS84mwngZxadsHp9OCWc/9ttVoxMTGBjo6OPQrUfYeqYVBJ0VIWfeFPhGzFmbEsi0AggPn5eZjN5rw3IeXaB6RSKbq6ujK6wadiQv33gEvqDKAZVvAQzP7S9Jrak4VeuavOWnJghs9NeALAI8cXMLyxiD+enkKdOsibBRuNRr7y8Q9RpnJpFggEaSilFGasbpjUUv6aQjG6uoOnx6149aHKsEl2lYzCO66sy8xFRkGhEsB8PG+Xy8UPb4QislL29NNPC3q9N7/5zbjllt0dq6qqCouLi/zPlpaWUFFRkcbZXiSAMRGrXBgJLtKtpqYGlZXiGH7mYgqYQ+QTLDfMEggEcOjQIVFH7rNNAF/VU4r1tfNq7cbGBvr6+iCX733SLtXJ8cYjwvtoIpGNa+PITF9fH6xWK6ampmB1eFBhNqK0xAyj0ZhXC6Tf78fg4CBKS0tTstZJB4lMqLn/TVHUBasOct9tkiBAUvlfts71Bn9nbxWu3F+CUp0cYFm+d3B2dhZSqZRPJVGpVGFr5g+PL8EXZPDGw1V450+HIaVIPP7Wvj2vb1BJIZeSoplXp4pshw6IhVzfH9Eghg/g6uoqysvLAQC//OUvceDAAQDArbfeivvuuw8PP/wwVlZWMDU1hUOHDqV1rIIlgPnQd8NFukVTkNJBrhTAyAQSn8+HgYEBmM3mlIZZhB4vW1BKKUgIBsPDwyAIAn19fRlbQJJRAH0BGu4ADaNKWBN6pLmzQqFAVVUVTKXlmBhYRcAbAGmx8JmXZrMZxcXFYUTX5Q/i2SkbrmwuzsoG5HK5eC/M4uLijB8vERKpg8FgMKEJNZCfZahY+HuZAhYLUorE5IYLI6s7uLbFHKYOer1eWKxW/PjZMbQZaJiMu5PFLMviaJMJNpcfMgmFd15ZhwZTdFW+Qq/AWy9P/SFTLOQjkRKCbIclCIHL5YJWm1rViMMHPvABnDlzBgRBoK6uDt/4xjcAAO3t7bj77rvR1tYGiUSCr3zlK2lff8ESQCB7ZbZICI10SxVcCkK2wfUeUhSF7e1tDA8PY//+/RnbsMUigG4/LSgHNhgMYmNjA42NjVENq8VE5LXFS2q48vN/BcsCz3/gaEKLm3jJHkophZ4aIyr0cqjlEt6mwGKxYHh4GDRNw2Qyobi4GE5WBpefxo5XvPisWLDb7ZicnER7e3vai2MmEM9m5kLvHdz2BHDtl17Eh4414s6u8lyfThhiEUCaYfFff5rFDW0laCnLbHl6cdMLYO8eo1AoMOdV4SdTNN56eTVaS5Sw2Wxwu93YXpxAqckEl0uKG9vMeU+6aZoWrQ83m8hH4iqGAviDH/wg5s8+8pGP4CMf+Uharx+KwvvUcwyujKXX6xNGuqWKXCqANE1jY2MDCwsL6O7uzmhPmRgEcHnLgzf94DTu7KrAm6+oi/l7DocDY2Nj0Gg0qK3N/FN36MPJk6MbWHd48aq+qqgk8MPH9mFywyWI/CVK9thXcn7x4WwK1Go16urqEAgEYLfbsbi4iJ2dHezTaMC6KQQURZBKxZuKDcXKygqWlpbQ3d0dtdSej4hlMxPNhLqQEI1QUSQBFhzRyS/EIoBOXxA/Pb2GM8s7+N5rD2b0HF5zKHZbz6E6Ax6+ph5XNBVBI5fAaDRic3MTra2tsNvtmJmZgcfjgV6vR1FREYxGI0+0GJYFw+aHGXk+EikhyFcFMF0j6GziIgFMgNBFiIt027dvH0pKShL8ZerI1RQwQRCYmpoCTdOieOGFwub0QyOneBNjj5/GT19axvx8AJdeunehZ1kWK9teVOjjmw+bNXLIKDJugsba2hpmZmbQ1tYW1kSbSYQSwAMVOrAsG1MBvK0rcSOvGLFuUqkUpaWlKC0tBcuycDgcsFqtmJ+f5+0xuEGSdMkNy7I4e/YsXC4Xent7826hFopIMgggTB3kbGYkEknWN9HBZQeWtrx7ouGSgUYuwckPXi7iWYmHWARQr5Tih6/vQolW3MpLspBLSNwY5b1XKBSoqKhARUUFGIbB9vY2bDYb5ubmIJFIYDKZ8O7frQEEicei9AamAm6tSeV7e5EAigcxSsDZxEUCGAecEieRSPiEiGQi3VJFLoZA/H4/tra2UF5ejgMHDoiqbgRpBv/8u3EoJBQ+c0c7AOAnJ5fw33+bh14S3WpnYt2JR08t47aD5eis0sd8bZmExK/efjjqz7hSvcPhwKFDhxAIBEQn1v/+1BR+M7SGp99zGSQhCQ2h6maFQYGKNGw0QpM9xFqoCYKAXq+HXq9HY2MjvF4vbDYbpqam4PV6YTAYYDanNkhC0zRGRkagUCjQ2dmZ0r30t7N2fPoPU3j0zX05b5LnwL0P3Gc7MjICg8EAqVSak1LxG38wABbAsVZzVIuRSOS6py5ZxDvfhuL8nnbnQJIkjEYjjMbdB1SfzwebzYZaDQOLy4/x8XF+sjjaA/czkzZMbjjxlstit6ycXtzGr4fWMW/3QKuQ4IuvbE/qHAuVAObjeYsRBZdNFDQBzHQPIEVRCAQCmJiYQDAYFF0Vi3fcbBJArt9Pp9OhoqJC9E1CQpFY3fZCGdKnd3t3BdoqtHDMj0U9Xr1JhWtazNhXcv7L9OKsHS/MbuLBo/Ux1TQOwWAQQ0NDUKlU6OnpAUEQYU3+YuEvUzYwDPZswJH35uefnsbxuU38+E19gt/feP1+YkOhUKCyshKVlZVgGAabm5v8ZLFCoUBxcTGKi4sT+lv6/X4MDAygvLwcVVXxs4/j4ZGTy1jc9MAXYNImgANL2yjRylGehol4KAKBAAYHB2E2m1FTs5tvzQ2SRCaSZNJm5rG39sHm8gsif4WIaARwZMUBjUKK2iJxrKjEhJC9SC6Xo6KiAv/5ml110OFwwGaz8Sp8UVERTCYT1Go1CILAt/62gCDD4s2X1SDWpyyXkJCQJCiSgEYu4c/lhbkt7C9RJ0w4yUciJQT5qAA6nc6LBPBCwunTp1FRUYHa2tqsPT1nkwCurKxgfn4eXV1dWFhYyFjp+X3X7QtbwPRKKQ7VFeG5ld1/dXqDkFAEFOc2e7mUwmWN4WbTTh8d1Tg1Em63GwMDA6itrQ3zSRJq7ZMMYqmPBEGEvZc/P70ClhVeoskm+YsESZJ8lio3SGK1WjEyMgKaplFUVASz2QydThd2Xk6nE8PDw9i3b19SRuHR8IW72uELMlDL0luiaIbFa793GgQBDHzkqrReC9jNlR0cHER9fX1YG4gQE2qxbWaqjUpUG4UToQtBARxbd0FKEXlLAJN5f0mShMFggMFgAHBeHZyemcXkuhMdVQZ89lg5NDpD3Bi+tnIt2srDy44ObxA/PrGM5lIN3pnAU/AiARQPfr9f9KHQTOIiAYwBu92Ora0ttLS0pKVkpIJsEECGYTA5OQmPx8Mrm5ksPR+K06PHsiy++MezkJAEPnRDc8zfe1mLGS9r2WuyGQqbzYbx8XEcOHAAen146TiSlMWDL0Dj35+axv2X1aakHEWSzb/9w1HBfytGvx+wa/WSLoEKHSSpra3lB0mWlpbgcDig1WphNu9OOs7MzODAgQOiPAFLSBISWfqbEkUS+MwrWpMiSrHgcDgwMjKCtra2PfdWJPLVhLrQCeDLO0oTppfkCkPL23hiLoCOLgbyBBWKaODUwQWfErNrNhxQaeH3OHF2ZSnsoYxTB+NBr5TiHVfWCYrOLFQCmK/nnY/nFAsFTQAzsZixLIu5uTlsbGygpKQkJ3Jupv3xuDJdUVER9u/fz7+P2fbl40AQBG46UBpm5eIN0PjyMzO4rLEIlzbuVZOcviC++9w8rtlv5qPaFhYWsLq6GjOKL5nrm9xw4Q9jG6g0KPCGOIbQLMsiyLCQUuFf+mTIZuTriUH+npux4z0/Hcbnbm/D1fvFs/GJNkgyMzODzc1NaLVaWK1WEAQhyiCJWLjpQGnar2G1WjE9PY2DBw8mPRkvxISa+71M9g4WkmchEJ0ApkKs0sG2JxA1xSMaGJYFASLtknxXlQ5GlRT7StQgid171+fzwW63Y25uDi6XCzqdjjeijtWWJDTBJV+JVCLkm31NoSnsQIETQLERDAYxPDwMmUyG/v5+TE1NJZUHLBYyqQDGm2TOlf0My7LoqTGE/ZvknD1FMMaeJSHPJRqcI1rj4+MIBoPo6+vbUxbwBxksbXlQb1IJ3gQPVGjx3df1oCrB8MY1X/gbGJbFnx6+POzLn0q5ObR/LN0FucqgBEUSqIthQisWNjY2QFEUrrzySgSDQZ4oeTyetAZJ8glLS0tYXV1FT0+PKOUdISbUmUgkKbQNKlfnu+7w4c/TNlQblfjoryfw/msbcUNb/MoDALSXaUDuU6Zt7aKQUnvIm1wuR3l5OcrLy8EwDHZ2dmCz2bCwsMBH2JlMJmg0mqTfs0IlgPl43oX2HbtIAM8hWqRbrhM5xMbq6ipmZ2dx8ODBqMpmLhTAyPQRDhKKxD9cvy/m3ymkFN5xVQP8fj9OnTqF4uJi1NXVRf3yvTi3iYHFbdzbL7yUTxAEGs2Jp72vai7GC7P2PcdNZhHIRL9fTZESL3zgirRfJxZomsbw8DDUajU6OjpAEAQoihJlkCRfEGpl09PTk5F+o3gm1JEPBBeaCXUi5Goz3fYG4QkwqNArUKqTo71cuJKWjfMlSZKf4G9o2F0DOTLodDp5ddBoNAry9yzUKLh86wHMR0KaCAVNAMX6sq2vr2N6enpPpFuuCKDYiwjLspicnITL5cKhQ4diyua5uN5YBFAIdnZ2MDg4iObm5qgB3Bx6awwo08lh0ojfnPuxW1rS+vtcDnukCp/Ph8HBQVRUVMTMv051kCRfwDAMRkdHIZVKU7aySQXxTKj5LN8UyaAQQuUN0AgyLD9Nmm0sb3nxtxk77uouzxkBbC5Ro/mcofr/vqFb8N/ligDIZDJeHeTaMpJRBzlj80JDvp232+3OuEWc2ChoApguWJbF1NQUdnZ2oka65YoAigkuucRgMKC7uzvugkqSJAKBQBbPLnXVcX19HWfPno2pZoZCJaPC7GQ4MAyLXw6s4urm4oRWCYLOyeEDzbCCPf8Kkfxxk77Nzc18LmoiCB0kKSrKXCJJMohm85ILRCsVhxJCoXnFoUh0j135xRfAsixe/IfLcnI/fuJ3kxhZdeLqfaaUCdXEuhPDKzt4eUdpQrsoMZEsYQ0yLO777mncfKAEr79EnEHDUH9PTh202+28OqjVavneQe67VojKFZB/yqXT6cxoclYm8HdLAEMj3TifuEhwPoCFip2dHQwNDaGpqUlQcglFUfB6sxsJlSwBZFmWHzro7+9PizDM2d34yp9mML3hxAePxZ4+FopnJi1gGeDeQ4kXc7GGPbIJrr+vo6MjrSfdeIkkJEmiuLhYtESSZOH1ejEwMLDH5iXXiFYqDs0qFlIqFtKT+pbLqrGx48/Z/fjZV7RicsMJs1aOuTQVwHjDGG4/jd8Or+OyxiJBk7JCkCyRogggyDD4v3FrXALIsCxcPhpaRfh2vbLthdXpR2elLsZf7qqDZWVlKCsrA8uyfO/g0tISAKCoqCgnfe5iIN9KwIUWAwcUOAFMdXHgjI8TRbrlghCJBS7+rLOzU/BNmcseQCGgaRpDQ0OQy+Xo6enZs9j6AjQfNScE9SYVPnVbG9rLxYnuuam9FLSATZZlWX7RLZQn78XFRayvr4s2CMEhVLGora8HHQjwRNPtdsNoNGZtkGRnZwfDw8NobW3lvdnyCVw8YqVByat+EolEsAm1EIXqTUdyp3gCgFElxSVxLKOEYH+pRtAEbJABvAHx1rtkFUCCIPCLNyeOgnv456NY3fbhu689GOaU8PHfTsEfpPHt1+zmIS9s7g66xTueTqeDTqdDfX09rw76/X6cOHEiqjqYz8g35bLQTKCBAieAqWBpaQmLi4uCIt0kEklOn45S6YGJLGsn80XOZAbx1IYTCzY3rmkx75mW5Y657vDhVwOreP2lNXtKNx6PBwMDA6iqqorqy+j0BfGqb51AS5kG//HKDkHnRBAELm0QVsYUAl0Cu4hCLPly/aN+vx/d3d0Ze+Kesbrwym+exD/esA+v7Mn+IEk6Ni/ZwocfG8Mfxiz4+Vv60FB8fu1KZELNrWHc/VdIyNR3RCWjcG9f4gzuZJApQvLq/kr8/MxaGPkDgE/esg82VwAUSeDHJ5fx1JgVH71pX1wSGApOHVxcXERfX19UddBkMkGr1eblWpWPCuDFHsA8BcMwGBsbSyrSLZc9gKE5xELB9S7pdLqYZe14yKQR9A9eXITTG8BV+82gQk6LI4A0w+K3Q2t4cmwDV+8vRlNIz97m5iZGR0fR1tbGZ2pycPqCcHiCKNfLIaUIXNeaP2W7UMxYXPAHaTQWK/OK/AUZBpvuAMwa+Z6fcYqrVqtFc3NzRs9Zp5CCIIAS7fnzCB0kAXYX2MhBkuLiYuj1esHnNm1x4e7/PonH33aIN4deXl7GyspK0uomw7J4aswCs1aGnmqD8ItNEW88UgNfkEFtUfwNPlrvoNPphNPp5Pt8c2FCfaEjU0Mr/bUG9Nca4PAGMW9zo+NcybdMp0CZbvdB6NqWYgRoFjUpGp5HqoOhfbo7OzvQaDS8OpgvSRcXCWD6KGgCKPTLxsU3lZWVoaYmdqh2JHJNAJN5Wnc6nRgcHERDQwPKyspSOmYmS8APHKnFR389hl+cXsFdvecnR7ljfve5eSzYPfjnW1vD7Fc4xbanpwdK5d7F7ZETS3D7abz9yno89mD0WLZQeINs1ksHLMvi9d8/BZYF/vTQkbwhfwBwxX/8DTTD4s8PXxaWuev1ejE4OIjq6mqUl5dn/DyKNTKc+vCVcX8ndJAkGAzCZrNheXkZY2Nj0Gq1KC4uhslkiqt6z1rdYFlgcdODKoMCMzMzcDqdvM2LP8gIHhwgCQIEATAC7R63PQEopCTkktQ2rf2lGnzhrgNJ/Q1JknA4HBgdHUVnZyfUajVvM5OqCfW2JwCVjNpjfh4NAZrBu346gvsvrcahOkNS515oyPS68snfTWFl24tv3Nuxpx/w5Pw2JjdcsDh9KFLJEKAZqNOY5I7s0+XUwaGhIQD5oQ7mWwnY5XJBqxWnnShbKGgCKARcNFg09SgRckkAk1HjuInYjo6OtG7ATF5vuUEBg1KKg1XhEVoc0X15ZzlGVh1oKds9f4ZhMDExAZ/Ph0OHDsV80ruzpwJ2VwASAZuRx0/j6YUgvCPruKkj86QGOD/s8R93tIFOIgs4W/jc7W343fB6GPnjeuFaWlqS/s5kCxKJJOogCWd9wZWKI2Ozrms143TrlWAYBiMjI2E2L5YdH56fteNwfVGYEhkP1wtUnBmWxbPTNsglZFZVapvNhqmpKXR1dfEPUIki6uKRQYZlccNXjoMgCDz3viMJj+8NMBhcduDbzy/+XRBAgiDwk1MrqC1S4nC9ON8dX5DB15+dxxVNRhSpZNAqJGBZFo++tIr+OgPqTSocrjdCSpEo0crx0M9GEaBZ6BUUbukoxWWN6bW55Ks6yLJsXhHAizYweQQu0s1iscSMBkuEXCuAiY7Nsiymp6exvb2d9kQskFkFUEqR+M9XdcY8ZqlOjlLdrpdfIBDAwMAAjEYjWlpa4pImo0oGo0rYoqOUUajSUuiqij01Fw80wyYd88T1X/XW5ieRuqLJhCuazkftWSwWnD17lleLCgGhgySNjY3w+XywWq04e/YsP0hSXFwMo9HIT/YPDQ3BZDKhtvZ8zJ9WIYFJLdujrogBkiDQW2OAWp69ktXq6iqWlpZilraFmlBzPydJEiRB4Kp9JsHfIa1Cgt+/49Ce/rULERwh8QRoTFvcohFAKbWrNJfrFDyJ9gQY/HZkAwPLO/jUrfthVElxbctu5OOd3WWw7vjx7Iwdf5vZjEsAU4kHjFQHnU4nbDYbhoeHwTAMrw7mq8dnpsDZ7BQSLkgCyEW6yeVy9PX1pfyUkMshkEQEMBgMYnBwEGq1Gr29vaJ80TI5BBILkaSTK2U3NjaitDT9DNdI9FfIUaxOniivO7x4YmQDx9pKUJbANoJrtjcYDDh+/Djfq2YwGPLqiTUSCwsL/ANTIUwBxoJcLo+aSDI9PQ2ZTAaXy4X6+vo9w0QKKYXLouROi4VykexGhGBubg6bm5tJJZjEMqEOnSwmSRKfenlzUvex0CzdXOGnp1ZQX6xCf60hrdfhSpJvOFwtzomdA0kQePdV9WH/ppJR+PRtLTBEeW+Pnnugu6M7cZUj3b5FgiCg1Wqh1WpRV1eHQCCAzc1NrKysYHx8HBqNhieE+dI7mCm4XK6stMuIiYImgNFuXI5A1NXVoaIivSmvXCuAscgYd4319fWi3nCZHAIRckyLxYLJyUl0dnZm7EkqVZVTIaWgkJJQJlAyQid9m5ubwTAM7HY71tfXMTExAbVaDbPZjOLi4rwhWSzLYmJiAsFgEN3d3aKT1JcWtvC2Hw/iiXceFsVwOxmEDpJwyTFmsxnr6+tYXl6GyWRKepAkn8FNbQeDQRw8eDDlzzKRCXU0m5lCBM2w+NZzi6BIAk+841Bar5Xt5BIx/AvF7qOTSqUoKSlBSUnJ3506eNEHMAcgCIKXscXqhQt97VwhFhnb2NjA1NRURkhSrhRAmqYxOzsLi8USNZFF7ON97dl5PDluw2Nvu4T3DZy1uvDstA139VRGJXl6pRSv6otv8BzN5oWiKJjNZpjNZn5BtFgsOH36dNxetWwhGAxiaGgIer0e+/fvT3gOLl8Q1/zn83jXVXV4zSFhSsfQyg5ohsWmO5B1AshhbmUDj784iXuu7EBp0W4faqqDJJlGMoMooeD6GpVKpahT2/FKxYkGSf44YcW3/raA/3l9l6ChkRmrG/f/cADfum9vu0gmQJEEvv3qTlHK/vk2lCAEmUzTiFQHg8Eg7HY7rw6q1Wr+4exCUAfdbvdFApgLcE+9TqdTlF64fECk+hiZgJGJLwxBEDnxCVtaWoJOp0urXG93+QWRC67Zn2URtiH5aRYsC6S6ZwpJ9ghdEBsaGvb0qnGl4myYHgPnJ31ramoET45LKRIsy2J8zSn4OK8/XI3XRyuLsSwI5yoI6wQInxOs0gjG1AxoxB2SWFlZwfTMImrq6iCVn58kT3WQRGycmNvE+34+it+98xL4gwz+PGVDb40BNUXCLT2CwSAGBgayEl8XTR2MHCThiOD3XljCwqYXNMNCiEf7licAhgXsbj+yRaWSeZ/jId+GEoQgm3m6EokkTB10uVxh6qDRaOTVwUTnxD1k5xOcTmfB9E1zKHgC6Pf7cebMGRiNxpS87/IVoQSQU2mUSmXUBAyxkIvYrfn5eWi1WrS3t0f9HcuOD+/56RA+etN+tMZI7BhZceADvxjBA5fX4vau+GV/kiTx4evq96inQtMDoiHVZI9ovWpcGVylUvGl4kyQfYfDgZGRkaRTL2QSEsc/eDT9E2BZkEsvgrCMAjINQMlBbC9BYpsCXdELtix9BYh7aHI6nbj60r64SkfkIMnEyha++dws7mzcgt/r2TNIIiaembTC6Q9ixxuESSNDsUYGUxJ9qj6fDwMDA6itrc1I32w8xFIHOVL4jXvaQNMMpKQwhaynWo+/PHQpAOCEJbPnLjYYhhHk2+ryBfHR30zi4ZfVo8ogDvlMFblSLQmCgEajgUaj4W2dNjc3sba2xrfKcOViuXzvRH4+qq0XS8A5wPDwMOrq6mA2m3N9KqKCI4AulwsDAwOi9DTmE7g4vvLy8rgbqjdAg2YYWJw+tCI6AawzqdBSpkVfjSHhcUmSTGnyLRY45SNdc+fQXjXu6dhisWBgYAAAeDVKo9GkTdQ3NjYwOzub09QLwrG0S/60FQBxbiGXKsEyNKiVUwhqKwB1ccqvzxm/UxTF27wkg/85sYonJh14y9X9qDEqwgZJxE4kef91TXjvyxohO6dIh05lJ4LL5cLQ0BCam5tRVCReqk2qiFQHpRHqYDAY5H8n3zbwdCGUlCxuejFjdePUwraoBJBmWIyvO9FWJnyNyBciJZFIwlplOHVwdHQUNE3vUQfzzQQauOgDmBP09PSIuqFHQ7abe4FdAri5uYmFhQV0dHRAp0vNuiQfsbq6irm5OXR3d2NnZwc7OzsAgIl1Jz71+wn82x0HUKrbfeqrLlLhJ2+O35ytlkvwH68UZpArVpk7k7FuoU/HXGan1WrF7OwsXC5XymoUy7JYWFiA1WpFT09PTlslCMsoINedJ38cSAqsRAHSNgUmRQLITcibTKakjN9D8ZEbm/GaS6pQdy5WK1YiSTAYDBskYbHrN5mMCS9JEJBRyZ/j9vY2RkdHceDAgbzceNLpHcz0mp4JCN0n9peq8b3XHoRGRLshm8uP7z6/CIvTj/svrYZOIcHKtg+9Nfq4f5cvBDAUidRBlUqVl/f7xR7AHCB0CCQTkEgkSUeypQuWZWG1WrG9vY3Dhw9fEA2ywPmcYq5XUyKRwOVy8YRs2xMAw7DwBOJPIrt8Qbzh+y/hrt5K3B2SKiIEYngdcuQv1DQ3Haxue3Fifgsv7yiN+loymQwVFRWoqKgAwzDY2tqCxWLB1NQUlEolXyqOVirhwDAMxsfHwbIsP+nLsCz+NGmFWibBJUl4lt35zRNYd/jw1/dfntL1AgDh3QakMfplJArAt5XS63J9jemWQ1UyCq1l0TeZeIkk73jGBwD468OXQqUQZiadCjg1MtTgOd8hpHcw9PtUaO08QskUQRAwqJJ/+JqzufH1vy7gYzftCzNuB4DhlR1suoO4Zn8xnpm04fHBdTSZVWgt08T1YMxHAhiJSHXQ7XZjZWUFOzs7OHHiBK8O6vX6nF7LxRLwBQiKohAMBrNGADkPQ4ZhUFZWdsGQv/VtNz766EncfdCEl/V184t7KCE7VGfED+/vS/haMgkJhgWWNj346p9ncFdPJcwCkxvSJYChwx5ikD8A+MivxjC14cJljUUwJRhkIUkSRUVFKCoq4hdDi8WCoaEh0DTNk8HQiCbO+LioqAi1tbXnN1gA//SrCfiCNP700GWCJiEZlsXyljfta2blOhB+F0BF2QiDXkCTfJwhl2CSbF9jOogcJHnQN43Hh9YxPDggyiAJzbCwu/xh9/fKygqWl5eTzi4WC+99dBgqGYV/va015dcIVQdDCWCk92AkQaEZFrd94yRubi/Bg0dr975wDpHpStGphW0sbXpgdwVQaQgndZc1FqGjQositQxnlhwYW3PiwStqEhpwFwIBDAVBEFCr1SgpKQHDMGhsbMTm5ibvjqFUKvlUEjHaM5JBIBAouP264Algpp8Ss+kF6Ha7MTAwgJqaGigUClgs2e+C5hRVMd9Xt9uNE6dewrSDxULgfH/KT04u4et/nsE7+7RoaYn+t9ueAB780QDedkUdjjbvlgSlFImfv/UQ1h1ePDawmtTkbjo9gEImfVPBv93Rjok1Z0LyFwluMVSr1aiuqcVjZ5axbvWg3jUPp9PJDzUsLi6ivr5+jyJGEAS+fl8H/jBqEUT+5u27fUtPvfvStG0zWHMbiLNP7w6AhL6PLAMi6AVtakrq9bjIs9AEk8l1J4o1sqxZzxAEgTdftQ9vvmofACRMJBGC4RUHJjdcuL7VDJ1Cgrm5OWxtbSVl8Cw2XpzbFPX1OALC/f9AIICxsTGYzeY9pWIAcPlp/PzMat4RwEyTqetbzbi+1bznu8ewLCQkwd/nRSop3veyBkHTzYVGADlwPYDR1EGbzYaxsTEEg8GsqoOFplgDFwABzDSyRQCtVismJiZw4MAB6PV6bG1t5cSEmmuwFUvx5LKYL+s5gF+vzOL04jb/s3WHD0GGxbjFF/t8CAIMy8LuCez5WalOgbdeUR/lr2Ij1R7A0GEPsRcSk1qGI2nmdVIkAblMiqYKPVrKtGAYBsvLy5iamoJUKsXKygoCgcCewYXOSj06K+P3CXHQyCWQSUjIU/CoiwSrrwJb3ALCNg7IdIBEDgQ8gN8JuqIbUAsf6oqmiNEMi+GVHSikJG46kN3JWA7xEkmEDpLsL9VAr5RCK6cwMTEBmqbTMngWA8//wxUZe+1AIIDBwUGUlpaiqqoqzISaWw+ffHsv/z3OJ/ISzQYmQDP4xZk1HGkwotqYeqmeZlh8828LUElJPHi0jv93t5/Gfz4zi/5aPS6pM+KPk1a8OLcFAsCnbo3xVB2CfHsPhSLaeYc+ENfU1ICm6TB1UKFQ8L28YquDLMsWZN/qRQKYAJkmgKGZxX19fXwfV65SSMTKA2ZZFouLi1hdXeWv6xuv6Q77nXdf04j7D5ViZmYm5utoFRI88kB/2ufDIdnry+Swh9i4JYToWCwWrKys4JJLLoFSqeRLxSMjI6Bpmh9cSMaR36SWhR0jLRAkmJrDIIw1ICxjIPxOsJoSsMVHwWqFlX9ZlsXs7CwcDsceRYwiCVzfZk7JUDkdxFLPQ6e8gfiDJKF/r5BSqDEqMDw8DJVKJcisOxWsO3w4Pr+JY60lWX/POHCWXqH9m6GlYqlUusdmhvvfFEVl5OEsGUTzpmPZ3SrGWYsrLQJIkQS6KrX8UBIHuYSElCJQrJFhdG0HL85t4eb2EsHehoVKAIVMAVMUxT9kceqg3W7H+Pg4AoEAjEYjioqKRI3ozOf9IRoKngBmowScqTxgmqYxPDwMqVS6xwRZLCKWLMQgnpwFB8Mw6O/vj/vlyvZ1JlMCLiTyx4F7oOByYLlJX5VKhdraWtTW1iIQCMBut2NxcRE7OzvQ6XQwm80wmUwZKSv6gwwe+tkw3nZFHToqQ6bZCRKsrgqsLn7CSjSE2rwcPHgw6mejSWISVwywLItDn30WAHDiQ/G9EuMNkoQmkgDA4OAgSkpKUF0tPGPW5Qti2xsUHBe27QnAF2TAJKFiWJw+GJRSQQkfieDxeDAwMIB9+/bx1x0NyZhQJ9rUzyxto71cK8r5c+cTeUyZhMQDl9VAjJXjZS17VXGKJPD+axsB7KqNtUUqlGplBWcDkyySPe+wdpnqal4dDFXkud7BVIaq8tGWe9nVAAAA071JREFURggKngBmGtwUsNjg+v2qq6v3hNIDhasAck/xJSUlYQMHmTpesggtAbMsi1ML2+iu1oMiI5/cM9PvlypGVxyYtrpxS0cpyBjnwpEikiTR1dUV85ylUmnY4ML29jYsFgtmZ2chlUr5QZJUp0s3dnwoCRla2PYEcHxuC2r5Ej53e1tKrxkKzuYlcqgl1+DOo96UnLdirESS+fl5uFwumM1mGI3GpHpzn5m0wu2ncUd3OSQCNsrmUg2akzBCd/tp/HHciiqjApc1CvctjAan04mhoSG0tbVBrxfWjgAkNqGOpw6Orznx/l+M4ZaOUrz36uTaSGIhpvqbpftTSpEo0yU3eS7UvDrfkC7hClUHAfC9gxMTEwgEAjAYDDCZTILVQZfLVXApIMBFApgQmSBiXF9ce3t7zGnFXBHAdPKAd3Z2MDg4iObmZsHG3LEyjzOFUMJ5fG4TH/3VGN50WW1Yzm++kT8AWN72IUgzMZUErnequLiYjwK74j/+BqmExDPvPRLzdQmCgMFg4O9Dj8cDi8WCsbExBAKBmKXJWFiwe/DcjB1HGor4MpRZK8dv33EJDMr0fQdTia9LFb4gDbkkuU0mkfIXDacXt/HeR4fxm7dfAq1CAr1eD4lEAovFggMHDiAQCCQ9SHLNfjN2vEFB5C8VqGQUDtUZUaJLb8CG8zLs6OhI20IjkToYakK9r0SNB47U4GX70yOvoShENY2m6bj2UfkKsYmrSqWCSqXi1cGtra0wdZBLJYn1UFyIMXDABUAAC2kKmGVZzM/PY319PazfL9PHTQapErL19XWcPXsWXV1dSX0RclECDgR2B0q6qw144LI6XN92Pns2k8Me6eC61tiE2u12Y2hoCPX19SgpOX8tBAFUCiwBclAqlaipqUFNTQ0f3h5amuRKxbEW3zK9HL01BpTrw+/tEoE2PfHAKUUtLS0wGoX7FnJYc3ihV0r3eKhFw5+nbHjfz0fw1Xs6cKgu+WMlgz9PWeHy09jyBCCXkPjlyTloPGu4sr+TJ0XRBknkcjmv1kY2tatkVEILkHRRX5xeigw3uZ0JL8NEJtQAcOdBM7/+iPFdj1QA7S4/JBQJnYiGz2KjEEkrkNmSK0VRYf26XO/g5OQkfD5fWO8gdw6F6AEIXAAEMNOgKAo+X+wpVaGgaRojIyOgKCphXxyQeYPrWEhlSOLs2bPY3t5Gf39/0ukSuewBlElI3N23ayRdiP1+ALC1tYWxsTG0t7fvSYt59n2pGzUDe8PbHQ4HLBYL5ubmePuF4uLisDg5GbWrrogNbgEOtXlJBgGawZ8nbVDLKdzSkVg5rNArQBLiENdEePfVDXj7lfWQUSSWVtcxt7SCG/pb92wooYMk/iCDgM8jaJAkH7G+vo75+fmseRlGqoOh/8cRt2iJJMkgkky9+UdDIAng0Qd6RbmGTOAiAUwMTh2sqqri1UGbzYaRkRF85jOfwVVXXYWWlpaUCOCjjz6Kj3/84xgbG8Px48fR13feB/fTn/40vv3tb4OiKHzpS1/CsWPHAACnTp3CG97wBng8Htx00034z//8z5S/7xcJYAKIocRxDc6VlZWCG7lztYAnc72cabVCoUBPT0/Cc563ufHSwhZuO1gOkjzv9p9NohvNBqZQyd/a2hoWFhbQ3d2dcdNTgiB4X8GmpiZ4vV5YLBZMTEzA5/OhqKgIZrM5I35bq6urWFpaQnd3d8rlKilF4op9JuiVwpa8fSVqHP9g8uXcVMBFwS0vL2NtdRUP33ZJ3AepUwtbmNxw4tbOMn6wJ94gSS4j/yw7PsgkJPQh5f+lpSWsr6+jp6cnJ/1n0UrFoYQwGAyCIAhQFJXUvRxJph68ohYqWX6Tq0IlgAzD5GToIlQd5Fqdfv3rX+OLX/wiFhYW8N73vhc33ngjrrzySkFr8oEDB/CLX/wCb33rW8P+fXR0FI888ghGRkawsrKCa6+9FpOTk6AoCg8++CC++c1v4vDhw7jpppvwxBNP4MYbb0zpegqeAGZ6s053CMRut2NsbAxtbW0pla2yDaGKnMfjwZkzZ1BTU4PKysRxbCzL4r0/HYTV6cf1bSVQyyVYtLsFJ3hE4gtPT0Mlo/DWo8k1cEdeXz72+yUCZ3+yvb2ds01UoVCgurqa75mx2+1YXV3F+Pg4NBoNXypOh3xEXme6C36iiViWZcEie037ocedm5vD9vY2uru7E15nbZEKNpcfqpBSduQgyc7ODiwWCxYWFgQnkviCNL7z3CLuP1KddO9jLDwzaYWUInB7VwV/nQ6HA11dXWl/njTD4v/9ehzXtZpxVXNqudHRSsWhWcXx8oojEVkCvrYl/jm5/bSgMv20xQVvgMGBir3RhF/58xxolsW7r6rnz8ETYASX/wuVAHKxgblGa2srWltb0dnZiRdeeAHHjh3D73//e3z4wx9GeXk5brjhBrz2ta+N2evf2ho9Tefxxx/HPffcA7lcjvr6ejQ1NeH48eOoq6uDw+HApZdeCgB43eteh8cee+zvlwBmGqkqgCzLYmFhAWtra+jt7c16LE2qEHK9m5ubGB0djTvEEglvgMGmJwCFdLc3yRug8U+/GoNKRuG1dcmf5/OzdhBAWgQwH8kfy7KwuQIgCMDm9O+ZzGQYBqOjo5BIJDk3BOZAUVSYG3808mE2m5Mq3XLZxQRBZO06f356FSyAu3oqMnaMSJLAsiwmJibAMAw6OzsFXWexRobrW0ti/pwgCOh0Ouh0OjQ2NsLn88FmsyUcJHlyzILvPb+ISoMCt3aKM2BzdXMxZJLdtovJyUkEg0F0dHSI8nkyLIu/zdjx4txmygQwEpw6KJFIoppQx7OZSWZKe2RlB3+etuGOrvKEk7tPjm6AZomoBDBAMwitn3zi91Ow7vjxudtbBZHAQiaA+WS74nK5YDAYcP311+P6668HAMzOzuKJJ57ge86TwfLyMg4fPsz/d1VVFZaXlyGVSsNcQ7h/TxUXCWACpOIDSNM0RkdHQRCEoH6/fEIiBXBpaQlLS0tJk1qljMKP39QPvUICgiAgo0hc1mjCsbYSLE+cEfw642s7KNXJ8cibUjOH5krOLMvyn2s+fT4P/WwELy1u44EjNZBQBBrNat6ihpv0NZvN/KRvviGUfJRW1cKy7YLEv4OpqSl4vV4YjUaYzea49grBYBBDQ0MwGo1ZtXkp1ckRpDPXjrDlDuAPoxu4qrkYpTo57wOq0WjQ0NCQseuUy+WoqKhARUUFGIbB1tYWLBbLnkGSY60lMCqlog69mLVyMAyDkZERyGQytLW1iXadUorE4287BIU0M9/fZE2oAeEVqSqjAtVGJYpU8RVyq9OP52a3cHdPedSfv/eahrD/fkVnKf7599P4zJPT+MTNzQnPp1AJYL6dt9vt3tMDWF9fjwcffBDXXnst1tbW9vzNpz71Kdx2221RXy9aW1Ssdql0vk8FTwDzbQrY6/XizJkzqKioQHV1dVrnl4u4o1g2MAzDYGJiAn6/H/39/Uk/fbEsi//641mMrzvx9Vd3YXXbi5VtL3Z8wsm1P8jgD6Mb0CskeMOR1HJAuSlnrs8nH1S/ULzx0mr4aQZ395bDG2R58udyuTA0NITGxkbBFju5xtPjFrj9NO7ureAbqDc3N7G+vo6JiQmo1Wq+VMwNAmTT5iUSVzSJZwkSDQQBSCgCEorYE3kmBJ4ADZZFWtO9JEmiqKgIRUW70YNutztskKTMZILbSUEq0iAJTdMYGhqCwWBAXV1d2q8XCX2a1kIObwAKCSUo/SSezQz3v0OtZhKd98s7oqfqTKw7UaaTQ6+UQiElIaFIwTnhXVV63NtXgfF1p6DPL9+IlFDkmwLodDpjVsOefvrppF+vqqoKi4uL/H8vLS2homJ3HV1aWtrz76mi4AlgppEMAeRKo62trfwCmw7EtChI5piRkrXf78fAwACKiorQ0tKS0sZAEARemNvEpjsAlmXRWqYF2U2guUSDk3PCXkMmIfHKnoqU/eRYloVUKuUNPzmD3XxaSA5W6fHVezoBAIpzl7m5uYnx8XEcOHAAWu3eMlC+4rrWcC+6yGgmp9MJq9WKgYEBAMDXh4IYWPPiN2/uQJk5uZLe8pYHL85t4paOMshESnZIBIc3gD+MWnBdixmGBEoOsLvp39ldAa/Xi5deGthj25MIV3/hObAAXvyAeFm8KpUqru1POoMkgUAAAwMDKC8vF9QnnG2wLItXfvMkKJLA7995OPEfhCBUHWQYBoODg/wDS7K9g6HwBRk8OWZBsUaGe/sqoZFL8L3XHkzq3F7ZHV0tjIZCJYD5dt4ulyuppJ5EuPXWW3Hffffh4YcfxsrKCqampnDo0CFQFAWtVosXXngBl1xyCf7nf/4H73rXu1I+zgVBADM5SSqEAHK5tysrK6L2+3HHzmaTf2QJ2Ol0YnBwEE1NTUltVtHwsZtb8JdpK0p1u+9PWCyYQFQaUvML43p55HI5Dh8+zKdfTE9PQ6lU8mWwbFhSJIPV1VUsLi5mZdJXbKhlEqhl0e9dgiCg1Wqh1WpRX1+P9fV1BE+NAQBmpiaxZbNCZzShzGwStNCvO3zw+BkgwTLAsCyGV3ZQb1LB6QuiPEmfxFD4gywYloUvKNzGyOl0Ynh4GC0tLYL7Zznc118JP505y6RI259UBkk4+Hw+DAwMhOX6+oNMznKGo4EgCNx0oAQNxanbFtE0jcHBQZhMJr4tI5YJtZC8YrmExO1dZShSZWcdyjciJRT5dt6p+gD+8pe/xLve9S5YLBbcfPPN6Orqwh/+8Ae0t7fj7rvvRltbGyQSCb7yla/wQsXXvvY13gbmxhtvTHkABACIBMQp+0Z0KcDv92eMALIsi+effx5HjkRPU+Ca8hmGQXt7u6hq0unTp7F///4wn7VMw2KxYHNzE83NzdjY2MD09DQ6Ojoyqjw999xzuPTSSzNWjo037MGFhFssFlgsFgAIG1oI0GxONi2WZTEzM4OdnR10dHQIuq+CDIMHfjiAl3eU4s7uzA0yiA2O5B48eBBy+W7P2BNn5jG6ZENfkR9GrVo0gv71Z+fw7b8t4K6eClTo5bjvUFXWpn45z8ZkUy8CNINfnFlFY7EKfbW5cRLgBkksFkvCRBLO9qq5uZmvhCxtevDMpA3XtRajTFdYDzKx8PDPhrC4vokvvqIxrsIZakIduk9x71suiczJkyfR09OTV2RKCE6cOIH+/tT6wDOBD37wg7jrrrtw9dVX5/pUYiHqIndBKICZRDxS4vV6MTAwgLKyMtTU1IhOYHKRBsL1yM3MzMBms6Gvry/jqhhXRslEKTbRsEdoSHhdXR38fj+sVivOnj2Lz7+whRU3ie/e24KKEmFKlBjghohkMhkOHjwIgiCw4w1i2xNAlTG2AkqAwFmLC//1zGxBEEDOFmRrayvMzoYkSfQ2VQAyFY62mfk+Na5UbDKZYDabodFokv7O3dlVjgDN4r6+XTUtW+TPYrFgZmYmJSVXQhIgAFA53KSFDpJwAzyRub4GlRR6pQTaPE7FSAaBQAAji3ZIpdKE5e1YJtShk8XpmlCnCpZlC4785SMuZgHnELlIzeD6/VpaWvjIGLGR7ZQMYPe9tFgsKC4uRm9vb1YWB+46xSSAqZo7y2QyfqN7JbGKr/9lFg67BYuz09BoNHwZLFPmun6/nx8OCO0p+cPoBtx+GvcdqoyZ70qRBJ556AiImInBmYc3QOOXZ1bRX2tAU0lslYuzeQEQ1ealVCfHTQd2S4cajQYajYYn6DabDbOzs7z1QjK9nGatHO+6KjnroHSxtLSEtbU19PT0pHTfEASBu3vzp4cu1iDJwMAAnE4nysvL+Ul77nunkUtEs5YRguUtD2ZtbhxpKEqJ5H/4sTEMrTjw2Nv693zffD4fzpw5gx++pi3mQBbDsnh8YA3XtZqhkZ/fZhOZUMezmbmI/IXT6bwYBff3gsXFRSwvL6Onp0f0DMtQZFsB9Hq9GBsb4+0asgVOdRSLVImV7PHyznK8vLOcf02n0wmLxYLTp0/zAw1ms1m0Ej036dvU1ITi4vAhiBvbS+AIGaiIhUQ/zzS4hJd4biqcSsRNhibz+chkMpSXl6O8vHyPEqVQKPjPJB8C7jkj652dHUEGz4UKlUoFtVoNlmVx6NAheDwe0RNJZqwu2F1+wSXwF2Y34fbTuLS+KEbxKz6CDAMCe79P0crb0TC8soPvPb8IX5DBPX3RyXuivOJUB0kuIvtwu90FNaDH4SIBTAIMw2BsbAw0TadkhZIsskkAt7a2MDIygrq6Or4XLlsQU+nMVKxb6NBCQ0MDvF4vrFYrH4XGlSVTzWHlsm4PHDgQ9UlSLZdALc//r6uMInFvf2xbE5/Phz88dxpLtBZvaE+vbSJSiXK5XLBarRgaGgLDMPxnotVqUz7O8zN26BRStEcx4Y0HlmV5hbOzszPv7IbEBBdJyOX6arVaUQZJQnF8bhMBmhVMAF9xsBw0c95GKRFsLj+eGNnAje0lKFLL8G93tO/5He4BrbW1FXq9Hn6aiTlxfqBCi4/cuC+p+yaezQwQ34T67wnZrvYJwcUScA6R6cWVIAh4PB4MDQ2hpKQka+a02SKAKysrmJ+fR3d3NwiCwPr6ekaOc9biwqOnlvHQyxohl1LwBxn8ddoGLbs3nxfYnRp8YmQdVzYXC/L7ymayh0KhQFVVFe9vF5rDqtPpYDabUVRUJGiCe2FxCa95ZBpHm0tw+HD+lhFYlsWOLwidIjUlh5uAraquwY6dgdgfD9fLWVtbi0AgAJvNhvn5eTidTuj1ev4zSebB7azVBYokktrIOYNnbsL5QiZ/i4uL2NjYiBpJGJlIEtpfm2iQJBJ3dleASWLjp0hCMPkDdku2JAEwMQ6xs7OD4eFh3opp2xPAa7/3Ei5tKMKHj+3b8/skQaRlqB1LHYxlQv33RAjzzQMQSH0KONe4IAhgpsGyLE6dOoXW1taM9ftFQyxTZrHAxTO53W709/dDIpHA7/dn7JhTG064/DQCNAu5dLes88zEBozwYX/T3mNanD5MbThRZ1Khs0of5RXPX8eHfzmKepMC9x+pyfpiSFFUmH2Gw+GAxWLB7OwspFIpH5MW2fzPsiymp6fhdrshk8kwtOpM+Rw23X4Mr+zgSENRUhtfMnh22oZpixt39VQk3cy/ubmJiYkJXuHsycgZnodUKkVZWRnKysrAMAy2t7d58iGXy/lScaKBjHv7hJk0c+C878rKygQbPKcCb4CGQirOJri85UnaXim0vB0v13dp04PnZuy4vas8rL823iBJtM9Eek5p2/EG8YpvHMer+6tw/xHx0nDMGnlM5Xp7exujo6Po7OzkVR6tQgIpReJwCiQvQDOgSCKp3sRY6uCJ+S0Mrzrxmr4ySCjq70IdzDcLGACitjBlExcJYAIsLS3B7Xajp6dHFHPnZMD1xmUCwWAQAwMD0Ol06Orq4lWKTB7zhvZS9NYYQJ97kt9XooGfBp5b9eEutx86HeDx01CeSzqoNCjx1ivqEyYfMAyDaYsTMzYXHri8LiPnLhQEQUCv10Ov16OpqQkejwcWiwUjIyOgaZovS6pUKoyOjkKpVKKzsxNPH0yPtE2uOzG14UJ3tT6s6VxMHKzSQy2XQCNPjniEehnmojePJEkYjUYYjUbs27dvT/oF95nodLo9al0yZJpzBWhoaMhoWsvkuhN/O2vHLR2lMGvTez9/P7KBT/52Av98awuubRF2zqG5vonK2wt2N9x+eo+fWKxBktHRUQQCARQVFUVtqZCfi33LpB9iKLgHl66urrB+b5Ig8PO3JG9DwrAsXv3dlyAhCfzo/t6UzilUHTy5uINNdwDDa250VWqT6h3Mx1KqEOSbAphMBnS+4YLwAQwGg6KTFm5KkfMY3LdvX9Yl3uXlZQQCAdEjlFwuF79RRcZtMQyDF198EZdeeqmoxwR2vygPPzoMCUXg3+48AACwu/z406lRXHWgBpaADI+fWcU9/ZWoKUo8WJGpfr9k4fIFcdbqRmcCY2uuLLm+vg6r1QqdTof6+npR0kiCDANfgEmqT/Cv0zZ4AjSua03P4DsWQm1eOjo6smpoLhTBYJD3t9vZ2Um6fM/B6XTy/WHJGjwni21PAH87a4c/yEAupXBje+qfn8Xpw+efPot/uK4JRQLixjjfU7lcjqampox857hEEqvViu3t7axM30cDpxh3dXXxDy5OXzDtB6y3/O8Aemr0eNsVdXF/7/7/OQ2zVo7P3h5/IO9Dj41iyx3AF+46ADlFwOUL4rdDa7ih1cSrxNHIIE3TOHPmDHp7UyOiuYLT6cTCwkJWBxXjgWVZHD16FGfOnMn1qcTDhesDKPYixLnYm81mtLa28upNtkFRFLxer6ivyQ0udHR0QKfbS1hIkszYkyFBEHjt4eowklKklqG9VAmGYVCilaFYIxPkgp8v5A8AHvrZCOZsbvz0gb64kWBSqRQajQZzc3O89YnVasXk1BTUKhVflkzFd1FCkpDIkyuLzNk9GfusuexolmWj2rwk/HuWxfeeX8TLWopRK+BhIFVIJBKUlpaitLQULMvypWKufM99JvGm/TmVKLREmEnolVLcdKAUl/7bsyCAtAigWSPHp18hbCPNVK7v1IYTDm8QvTUGANETSaxWK06fPg2SJHnFNtlBkmSwvr7O90Vz38fjc5sYXHbgld0VgqL/YuGbrxYW7cYCsOz4Ev7eB69vwsqWD8pzZG/a6sGJxR20luvQUankB0lCvQe5/vJ8K6UKQT6WgAsVFwQBFBPb29sYHh7G/v37eSuOXBgyi31clmUxPz+P9fV19PX15cwmo+fcIh8Kbgq4WCXD/ZfVJnyNbA57CMHHbm7GqYVtGFRS+II0hpZ30F2t31M+vPG/noPH68dvHuzj1WRSqcVzNgV6jSoEAk7e7Dg0jSRT1/eaQ5npUePisUJtXpItk1idfnzjr/N4cW4T37gvuSzUSEyuOyGXkgmJJEEQMBgMMBgMfPnearVibGwM224fGIUevU0VYWXJjY0NzM7OoqurK+tRfT97cz9iVahZlsW0xY2GYpUoPaHRcn2n1p04Mb+FV/ZWpJW/fHxuC0GG5QlgKEIHSRoaGvhBkpmZGd4Hsri4OOnhnnhYWVnBysoKuru7wxTH5lINggwLnTI72+Z3X9ct6PeMKhmMIQ/NnZU6vP/aRpRo5SBJIqx3MNRixuv1giCIsOniQkC+lYADgUBB9v8BFwlgGJaXl7GwsIDu7u4wb7dCJ4Bc2QYA+vv78+6LnowNTCj5y8Z1DC070FCsiltarTQo+Sb6OZsHpxe3Ua6XhzXWLy0twevzQ6GQh7USKCQkZBISZoMGZbriPWkkbreb74cyGAwgSRJ/nLBgZduL+/oTx5jFs6rIBDj1vLq6GuXlux6KTl8QP3tpBZc1mrCvRJhCVqKV4yuv6hD8+/Hwuu+fBgC88IErkvo7pVKJ6upqVFdX43dDq5hctsMoXYLPvetvR5IkXC5XygbP6aLSEJtwLm568cykFTRjQktZeq0r3GdaV1cXlgdudfnho5mYJFQo7uqtEKxERxskSWW4JxYWFxdhsVii+jYalFIcachuH3gqoEgiasY1NyAikUjg8XgwOTmJurq6grOZyTcFsFAtYIALhACmq5Bw5Sqv18tPw4YilwQw3YlcbvEuLS3NSFydGBBKALlSRraeVrfcAXzwsVHUmVT46j2dgv6m0axCkUoKk2b3iZxlWUxNTcHr9eLph67Ys6kopBTui5g+jNzkNjc3sbGxgYmJCajVaixtycBIlAnJ358nrfjobybw1Xs6cKAifn+iGOB80iJNciXnLDlkkuTuvb5agyjn9W93tCUcJEqEq1tKcLDaiEqDgvcD3dzchEQiweDgoOim4Omi0qDA9a1mVMQhiZFw+2kMLjvQV6vnDZDjGR9f2lCES0UgRKk+oKQ6SBILc3Nz2N7eRldXFwIMC68/CLXsgtgiw+D1ejE4OIh9+/bx710h2czkmwLodDovEsBChd/vx8DAAIqKitDS0hJ1oZBIJHyebDaR7kSuw+HA0NBQWDk7H5GIAOaq38+gkuLtR+vRUxPbggbY7WFSSClUG5WQkCQ/mcn5wanVanR0dKR03lzPk8lk4tNINBYLrNZ1nDpljUs8SnRySEgCxjT6lYQi0uYlFAophddeUh3jLzOPK5rSt25SSilUGih+OIyiKBw5cgQEQewxBS8qKkJxcTGv2OYCFEmgzpQcGZ2zuTG4vI3aIiXK9Qp+sCUy1zdfoVKpUFNTg5qaGn6QZGVlBWNjY3EHSViWxdmzZ+H1etHR0QGSJHH3N4+DYVj8+u2X5OhqMgOv14szZ85g//79MBrPW9gUkgl1vhHAQvUABP7OCSBHkJqbm+PaNhRiCXhtbQ0zMzPo6upK6ekkm6Pt8ZROjvyFBqZnE7d0lMb9OcuyeM+jwyAJAr8J2Sw45bWqqgoVFRWinEuyaSStZVr88b1HRDl2PHBJELnog8smuCEIvV4fFmEXaQput9uxtraGiYmJlCdYF+weyCQEynTZez/3l2pQrpfDoJRia2sL4+PjGR1s8QVpSEgyI76VQgdJVCoVJicnwbIs2tvb+c/01f2VsLkCop9XLsGpuS0tLXEn1fPdhDrfSsBut/uiAphLpEIKVlZWMDc3J4ggURQFv9+f6umljFQIIGcu7HA40N/fn3L4fDYJIEmSURXWyH6/XJevgwyDyXUXWso0fPmVIAh88paWsBIjlxqwf//+jHpHRksj4RQPnU7HZ7Bmyn6FGyyy2+1RkyAuJAQCAZw5cwaVlZVxCT1FUbzxN8uycOzs4K9jS9DNLUApDc+Pjnc/Pz1ugYQi8DoByinDshhccqClTJOWOTRFEjCqZLBarZiens44of/hi8uQUgRedziz6nCsQZKzZ8/CbrdDoVCgqakJDMPwpOfu3uj5vaH461kbpjZcePWhqqz22aYCt9uNwcFBPsYuGSRSB4PBIP872SBmNE2n5JSQKVwsARcQQtMvDh06JGjTKpQewGAwiKGhIahUKvT09KRMmLjjZuspK1oJOFuTvjveID72m3F86Ng+lCQw1Z3acOHPUzaoZFRYeS20V43bPLNlCcIhMo3kxalVuDa2MDc3FzeNJFVwWbcMw6Crq0vwvWLZ8UEuJVOOk8sFPB4PBgcHkzZ4JggCHsiw6FPh0oZKtJgV/P3h8XjCotAi37/bDpZBSgm759ccPjw/uwmSJBJ6USbC8soqlpcW+VzfTOJAhQaGiIjH67/0PADgyXeL70PKQSaToaysDFarFTU1NTAYDLDZbEkPkqikFEiCgDQFBdMfZHD/D87gmv0m3H8ksfNBKGiGxUOPDqOnRo83XJo4DcXlcmFwcJCPsUsHsdTB0Oli7vcypQ7mWwnY6XReLAEXAvx+P29PEZp+kQi5IoDJ9AC63W4MDAygtrY27ZIjd9xMKDrRlMXI68zmsMfUxm6CxsCSA9e1xt/cm8xqqGQUqmLEZi0uLmJ9fT0rm2c8MCwwuOGHSqrCay7ZHzONRKvVpkSsuVIoZ2Qt9DVYlsVjA2uQUoSgjSvX8AVpfO+vMzD41nHD4Y6U+uBKtXLcdrAMxRoZpBSJyspKVFZWgqZpbG5uwmKxYHJyEmq1mi8Vy2QymASYMnMo1+0ew6xJ755bWFjAq348A5lUij8fyvz9e0l9biZqOZuioqIi1Nbuki8u4jOZQZKeGkNUWyshkFIEGJbF8lZsn9eT81v46l9m8dlXtIUlvpAEQLMsxtd3oyPdfhoufxBmzd4HWK6Ps6OjIyMkJVIdDP0/bq0XmwzmWwn4Yg9gjiFkA9rZ2cHQ0BCamprCrAyEQCKR5IwACrFHsNvtGBsbQ3t7uygpBJnKIKYZFv/6xARKtQq8JcQFn1MAWZaFxx/AQ48O41W9FbiyOfk4rbG1HRSpZCjVCfM57KrW4/uv74ZemViRklLRveQ4VTkQCKCnpyfnixNFEnhldwVfllYqlWHN8TabDQsLC9jZ2YFer+eTL4Q8Vft8PgwODiYshUYDQRC4sb2Ej/rLd2xvbWF5dQ3tPftSHoIgiOiWHBRF8YSPZVm4XC5YLJaUfCAJgkBFlGMIRWiur0YpR3d17gY+Mqn8AecjMEtLS6NmNac6SJIsCCJxFBzNsAD2Vj8IgsBXQlwJ/uEXIwjQLL52b2dYPyXXipKtakS0UnEoIQwGgyAIAtS5zOJUkW8KoNvtvkgA8xncQERnZ2dKHxRFUTmZAhaCxcVFLC8vo7e3V7TyXqbygCmSAEUQe5QKjgAyDAOwLHxBFkMrzqQJIMOy+NhvJiClCPzvG4XFG5EEISgCKxaCwSCGh4eh1WrR3Nyc8z5FDrGuKTT5gmEYbG9vw2Kx4OzZs1AoFDCbzSguLo5qFM7ZvOzbt49XTJJFlTF2ogbLspjccGF/ae4XUy4J4iN3HMq4aTpBENBoNNBoNKivr99jdsyVig1GIyQib3zcwwtN0+js7MRTaWZS5zO4Ps7q6uo9EZjREGuQhIv8yrRZ+yX1RlxSf35Sl2HZqNZPOoUEbj8dRv4cDgdGR0ez3orCIVqpOLRMnE6pON8UQKfTmdHs70zigiGA3OBCKDgPtp2dnZQHIoDclYDjgbOjCAQC6O/vF/WJKBlj5mTg8dOw7PhRaQgn05yVRjAYhExC4duv7Urp9UmCwAeua0JxmqUwoeD8tEJNj+OBZtiMTDymCpIkYTQaeTsIToUaGhoCy7JhGxw3FSpGH1EsPDawhs89NY1/fnkLrm3J3YK6uLiIjY2NPUkQ0bDlDuCpcQtu7SyFXCLOdzCqD6TFgpu/NQSSJPCz1+yLSdLj4TdDa7A5A3j9pbtDF6G5vvn08JIJ+P1+nDlzBvX19Slt1rlIJAnFe346BE+Awdfv6wRJEGFryVuvqANF7u5/O74ggh4X/uXXg7jtUHPeDCeEmlCHqoPcvpqMzUy+KYAulwv19fW5Po2UcMEQwEgEAgEMDg5Cp9OlNRAB5B8B5LwLTSYTWltbRV+4M3W9CikJCUWgynheqWRZFiqVClKpFCdOnIBGo+FVqFR6EMUyD04Eh8OBkZERtLa2Ciq721x+vPo7L+Gu3nK8Kcmm73RBMyycvmDUMrcnQOORk8t49aEqqNVqqNXqPWkkDocDDMOguTmzG8qV+0yYs7lxOET1yAQCNANplKlNzg/O7Xaju7tbkMqwsu2FZccHhycIs1b8TSnUB1Ims6KtVI1AIIChoaHd+MRzJF2j0SRcB6xOP5hzD8lcH5zRaBQ11zdVrG574fbTaDSLf39x3nfpKNccWJbFC7ObqClSojJBIklxcXHcDOlk0F6hxelFB0iCgD/I4L2PDqOmSIkPHdvHD6Q9cnIJfxrfwG1VXlBqI/4y48CVLYmVzmwjVB2USqVJ28zkmwJ4sQScZ+D6/RobG1FaGt/HTQjyiQCm08soFJlSAAmCwL/deYD/71B/v9bWVr7MYrFYsLCwAIlEIvr0ajJY3PTg/8YtuLe/Mkzd4UqmBw8eFJz8oJFToEgi5gBJJvHD40tw+oJ48+W1e+wqnhy14LvPLaLKoAwbgpHJZCgvL4ff70cwGER1dTXsdjvm5uagVqt5ki5mBFqRWoaHXtYIYJeknZzfQm+NATKJeIv9k2Mb+NhvJvCN+w7C4Qmgv84AuYTi0z0kEklSpt2tZRo0mdWinmMsPPu+y/n/XVdXh0AgAKvVirm5OTidzoQqFDd4Ey3XVyg8ARpPjlrw8s7ShEk0DMviui89j+YSDb52b/wknSdGNuCnGdEJIGd/ksj7TigYFjiz5MDEhhNvOLz7fsZKJBkbG+MHSYqLi6HX61MmLm+5vI7/31KKgIQi0FYersS3FlE4xTpx5SX9uFEk4pkNJGtCnY8K4EUCmGNwJeB0+/2iIVOESAgIguCfeDY2NniLkUzecJkmvLGSPULLLI2NjVGnV0tKSgSpHWJgY8cHj59GkGEhP3feXFZob29vUuRHLqHw23fkJlXgpvYSLGx6onqVHWszw6yRoa/OEPbvLMtiYmICNE3zahjXC+V0OmGxWHhTXY6kixmDtrTpxcmFbZjUMjSL2BNYopGDJAh4/DTOLDlQopWjsVjJq2G1tbVJ3VsEkXzEnViQSqUoLy9HeXl5VBWKI+mhD0+xcn2F4tFTK/jW3+Zh1soS5uJyBDHepCuHV/ZUwBcUd43lJmDFbFugSAKvu6QK0jiEP9ogyerqKsbHx0UZJCEIAl+6uyPs32w2G7yWBfzL3ZdkvGc1kxBiM8P14+eLEljIWcBEgilTYQndeQC/34/JyUk4HA50dnaKHs7+3HPP4ciRzKcqROL48ePo6urC4uIi7HY7Dh48mHGLkbNnz0KtVgtqlE4Wqca6cWqHxWLhG+PNZnNUD7VMgGEYvlm+tbU1LxaeTIGzeeESR+J9Rj6fDxaLBRaLJWoaSapgWBaWHT+KNbKEfZOeAA27K4DKJHJvGZaFzeWHRgIMD6U21ZzPcLlcsFqtsFqt/MOTVqvF2bNn0zIod/qCeH5mE1fvN/F5wfkIrkUj3hAEy7L46l/m0GRW41hbZqopkcfjBklsNhsA8GQwnYdajvR3d3fnlUGy2GAYBsvLy9jY2EBbWxsv+uQ6r/j1r389/vVf/xUtLS05Ob5ARL25LhgFcGRkBBKJJO1+v3wDSZIYHh6GUqlEb29vVm7yTNnApJPpG6l2hHqopdo3GGQYQZsYZ7BtMBjCIsAuRHD9pUIJkVwuj5lGotVqYTabU0ojIQlCsJXPYwOrsDkDePPlNYIHMUiCgIZiMHBmAE1NTXmdlZ0KuH7O2tpaBAIBLC8vY2RkBFKpFGtrawgGgzCZTEmX0jRySUK/zFyDG1jq6upK2IP3++ENUCSRFQIYa5BkdnY25UESi8WC2dnZC578AcDq6iosFgu6urr4PYpTB0MHSrj3LluE0OVyZWwwLtO4YAhgJoYhcg2v14vt7W3U1dWhsbExa8fNhA2MmMkeoY3xqfYNPjttwxf+bwaff2V7WKpHJLgUiJqaGvhk6ala+Y5ImxeWZfHt5xZQY1Ti+ogN0h9k9vS9MSDwiwk3aotMuOFwKxwOBywWC+bm5jCxReBbQ1489uZemPThiky6sYM3HyjFusOX1BQu55HW1taWlMcfzbB4cXYTnVU6aOSFsXy6XC6sra3h0KFDUKlU2N7exvTiGv7zqQlcUatEe22pqAMLaZ2rLwh1Gu+rzWYLi7GLd28RBIEfvamHfwh0+2n86MQSrms1R/X7FBuR097JDpKsr69jYWFB0LR6oWN5eRnr6+s4ePBgGMGLZkIdus9kMpGEw8UewDxANsyas5mPu7W1hZGREeh0uowNe8SC2ASQZVm+byOVL6LLF8TDPxvB6w9X4Uhj+BQf91St1WrxN6sMZgmJYpZO2DdoUssgpQio45gSb29vY3R0FK2trVh2U3hqYBUv7yjLyKRirrG1tYWxsbGwfininN3E8nZ4D9cjJ5fx1b/M4fuv60Z98fmNUkqRkJAEjCopCIKAXq+HXq9HU1MT/u934wgyHgyNjkFJ0vzm9rORLQRoFm+9PLneu1DoFNKkouXsdjsmJydT8kizu/w4Mb8FKUWgvy6z08pigCMUobm+BoMBjTIVarcUaG4ygPU7+IEFk8nEDyyIsdb9bngdHZU6VMfxf+Tw89Mr+Npf5vC1ezuxr2Tvhjpnc+OZSStec6gq6hT3xsYG5ubmeDXM5vLjkZPLuKGtJOZ3NvS+YVkWAZrBjjf7nq/JDpKsra1haWkJ3d3du9YqLAt/kEkrCzpfsbKysof8RSKRCXUyNjPJwu12i9r/nE1cMAQw0+AGQbIxfbS8vIyFhQX09PRgZmYm6xPIFEXB7/en/TrplHzDFCYCCDAsVh3xz+mJkd1yzg/e0IOamhoEAgHYbDa+xBLaN9hWrsVPHuiL+VobGxuYnZ3ly0hKDQ2aNaOmKPcqSSL4gwyklPD3e319nd84I1XTt4YktnBoMqshIQmYNHtJ1wOXRbe4+cebWvCPN+32yHBpJIuLi/BaNrFNK2C1qjPmoRYKzuC5u7s7pWZ5s1aO+/orYVCJp7j89NQyvvLnOTzxrsNQiriBr62tYXFxMWp50KiShaTxGMJSYpaXlzE2NgadTofi4uKUSvjAbr/g556ahkYuwXdf1xU1qiwUbeVaSCkSZbroyv1ZiwtuP41obeurq6tYXl4OU8NkFAkpRQpOnlHLJXjwaGb93F7//dNgWRb/84aeuL8Xb5CECybgyB8AfP7/zsIXYPChY/uw5vBCLqGy5oeaSaysrGBtbS0u+YtEtvOKGYbJSGxqNnDBDIGETgdlAidOnMj4AAY3een1enHgwAFIJBKMj4/zfVTZwvr6OnZ2dtDU1JTya6RD/r7113mcmN/Cv9/ZlpSy4/AGdhf8KJtoaN/g5uYm3zdoMpnCyicsy2J+fh52ux0dHR0FV1oJMgy+9pc5qGWUoJD5+fl52Gy2nF1raBqJ3W5PmEaSDhYWFmC1WtHZ2Zlwwf6Pp8+CYVn8w3WpfweE4uGfDeP43Bb++NCRqJPaqYCbVhdyrdHAsixfwrfZbHxrRXFxcVJqx4m5TfxpygatQoK3RXmYEANLS0vY2NhIiiTkCq/7/ksAgP95fXwCGAtLS0tYWVlBUVERNjc3AewOkqz45VjcYXBNczE+99RZaBUSfOzm/aKddy6QCvlLhGg2MwBSVgdZlsWVV16Jl156Kd/bgy7sIZBMI9MlZs64Wq/X4+DBg/zNlKmBjHhI1wYmHvn744QFL8xu4f3XNcbc7Lqr9RhcdiTssZqzuUEzLF/eiUcWhfQNmkwmzM3NAQC6uroKctJXQpIo0cjRWamL+3uh+cW5vNZk0khSXWBZlsX09DS8Xq/ga31sYBUAskIAP//KA4l/SSBCc33T+VwjS/herxcWiwUTExP8tLcQb7v+OiOqjMqoJVsh15LoM5+bm8PW1lZuyV/ADXJ9GOTGMACAKe0AU3IAkO6tFqRC/FiWxeMDayiTuCEPONDb28tfKzdIot2xojbgwv/7xSIChATvvqotvWvKMVZWVrC6usoPfIiFWOogRwo5ESmZyeJstoaJjYsKoEAMDg6ivr4+I9M+LpcLAwMDUY2rM2nJEgt2ux3r6+tobW1N+m8TDXv88swqRlZ28I837ktoJJsIb/j+abBg8f0Un6Y5eDwerK2tYX5+HhRFoaKiIqt+gxyytZDQNI3h4WFoNBo0NDQAQFLHZVkWy1veuLm+YsDv98Nms+GFyVWo4EVtaVHS1j9c3JlUKk0q7sx/zpNOiMFz6DR5kGFAgMhJ5B9XQWAYJqNDcacXNvGn0RVcWwU4dxzQarV8qVgsFfkPoxuY3nDtmpdH+QxYlsXMzAzcbjfa29tz97DmtkHy0rdBeLfBynQAWBD+HbBKI4I99wPK1Ox2wg7hp/Hm75+AVkLjq6+/NOa1MgyDk9MrWLFsooxyZSSRJBvIFPlLhGjqIMuyvDIY7X1nWRZHjx7l86HzGBe2ApjpjTNT5siclUlnZ2dUcpmLFJJUVcdEwx40w+LE/BauajaFkb//m7DA6Q3itoOx83Q/++QUZqxufP3eTv6z/qebmkEz4jyjbGxsoLW1FUVFRTH7BjO5yTx31o5P/m4SX7+vM+5Ucrrw+/04feYMnrUqcXlrEcr8NF7+teO4tbMU771G2KT5N/86j/89voyv3NOBjgRKYzqQyWQwlZRifswNvcKEPrOG/74ISSNJJ+5MaLLHN56dgz/I4J1X1YMgCFzzhecBAvjLw5cldbx0EZrru3///oyuhyOrTkjkSrS314MAwtR0iqJ40pGOOW6JVo45mxtSKvw6Jted+O+/zf9/9s47sI36fOPPSfLeS94rdux429lhBhISMu1AdsssoxQoq6xCaCgj7LLaAinjB6WhxHZ2GGGEFUhIiPfeQ7YleWlY8+5+f7h3eMi2ZJ2WfZ//4tjSVzrp7rn3+77Pg2vmCSEEhczMTIdWX0QVHwMGHWj/WPZntGcgCHUPRJVFMC682ernkEracX2GO5bNz5r0HCQQCNBncMO5Pjf8cXkefEUUZDIZp4kktsZR4g+YXu+gXq93aePtGSMAbQ3XQozpNZNKpVi0aNGEvYWOEICWTgGb2+8nIACdkcTJul6sSvt1svlQaTcoGpMKQMmAFjQ9WugnczCNy0y/jrQDiYiIQERExIR+gxNVOhRaA97/qQPrMsNHTceag7tIAIEA4y54XDLS5uXskAIVEgUWxQeCACyyUFmXGY4epQ6pHCZ0TIS7UIBtC6IR4OUGb3chu4VvKo1kpOhg/AxjYmIQGTnx58pasqP9UdujYj+Xc0K94W3m0AFXmCt0Owc0qJeqcenckGmLpiPl3Xj7VDve+k02exM3Mr1Hq9VCLpejvr4eWq2WvYEKDAy0SHTkxQYgL3a8Pc+R8m6cbpIjPzEMF+Q61vqLUHaBULSD9o8b93+0txhEfzOgkgK+03dxaGpqgkqlwoql5m3n58UGoldtQLDPsIE6M0jCeHSOTSQZzph2jmGRrq4uh4k/U5gTUadQKFyqujqWGbMFTFEUDAaDzR6/vr4eAQEBnFiyUBSFyspKEASB9PT0Sb/YEokEOp0OiYm2nU4biVqtRn19PXJzc6f8XWuGPRg0BhIUTcPH3b73I8z0a3Z29pRfYkZ0SKXScU3xzN8qtAZ8cLoDq9PFZotTkqIhIMyrYJMUjW/q5ciNCUCwj2UnbVM2LzMFJo1ELpdDq9XC398ffX19mDdv3owzeB6LJbm+7/7YhkGNAbdfmjhhTx5J0ZNuX5d2DOK+oip8fNOCKT+DJEmir68PcrkcAwMDbNV2uqKDoiiUlleAFHpiQcZch/ddEfJaiEo+AO0fY/r/lZ0w5l4LOmSuxY/NbHFrNBpkZGRw+lpH3kBxmUhiDV1dXZBIJE4j/qaCqQr+61//wttvv42qqipHL2kqTB5UXgCaSVNTE7y8vKyuJuh0OpSUlCAyMhKxsbFTftl6enqgUqnsagSt1WpRWVmJBQsWTPp7XIg/R0DTNNs8npWVBZFIZHYqCINGo2Gj6ZhUhbCwMPj5+Vn0Prx+sglCAWGW/cSgxoB//dCGvFh/XJ5qfhoDY2mTk5MzqTn2TKC/vx8VFRXw8/ODRqOxKo3E2bE011dPUtAbqQmHqzQGEm9+14q0CF/OkzHGig6CIEZtFU/1nWHiCZk0HmeAGGyH6Oc3JxaAinYYF/8BtP/kwnwszNCSXq9nI89sCTNIIpfLp51IYg2uJv4YioqKsHfvXhw7dswVbqr5HkBr4GIKeHBwEBUVFZg3b57Zti62SOUw5zmn6gHkMtnDnlAUherqaggEAuTk5EAgEOBwWTca5WrcdnGC2UaqXl5eiI2NRWxsLOs32NraCpVKZVHfYJifBwK9zGucD/Byw+8uiIOPh/knyba2NshkMsyfPx9ubm6o61EhMsATfp72/eoP6UmIhARnNiem6O3tRX19PRYsWABvb+9RViYtLS1wc3MbV7XlGgNJjauu6YwkmuUazIvgbstco9GgtLQUKSkpZuf6ugsFk77/niIBPESETXpQCYKAn58fmy+t0+nQ29uLxsZGDA0NTfqdIUkSpaWlEIvFiIn5VWydbR1At0KL9VmWDcip9UYcKOnGtgVR05pOZqD9o0F7BQPaQcBzzHa1ZgC0jxi0n2X50sx0PkVRdhF/gPWJJNbgquLv8OHDeOONN1xF/E3IjBGAtkYoFFpVYezq6mIzGy3x0XLGIRBrkz0cBWO1ExYWNqr6miL2RWvv0LRd9N3c3CbsG/Tx8YFYLJ6wb3DbAsuqA+YaEI+0ecnLy4NAIMCQnsShsm5EB3pi5yLTVQtbsfbvP4EAga/vucAmj9/d3c2apzPbi2OtTJiq7cjUi7CwMPj7+3NyoZUpdbjqrZ9xVW4k7lnxa8X+VGM/zrYOIMQnFmF+1jeMMzF2GRkZ8Pf3h4GksPf7VlyYFIycGPNj7cZCEOZVornAw8NjlOgY+Z3x9vZmhTpBEGw29djdlzMt/TBOYwjsyxo5/nOmA3NCvXHBHCumdAkByMwtEJ37F6BSg/YMBUCD0PQCAiGMGdcAFk7X19bWgiAIzJs3zyE31WMTSTQajc0GSVxV/H366ad4+eWXcfz4cQQGBjp6OVbBC0AzEQqF0Gq1U//iGGiaRn19PVQqFRYvXmzxNpSzDYEwTbDOXPVr6R1Cn1qP+XGB7M+GhoZQVlaGpKQkhIWN3j79+JdOlHYocP2yOLMrY31qPVQ6clwyyFi/QaZvkJmQZHKKbdk4zNi8+Pj4YE5yMowU4C4AvN2F2JwXBbGf/Zu+l6eEcva8UqUOOiPFxosxZtbz58+f9Ps1smo7Mo1EqVQiICAAYWFhVm17BXi5QUAQ4yajlyQGITrQc0LxN9b+h6ZpSAa1iA4c/xkZGBhATU3NqBg7AUFAZ6TQ3q+xSgA6irHfGcYLsqSkBCqVCmFhYfD19R33Pv3+kgSTqSBTsSotDFEBnsiNtX6CnQ6IhWHJnRC0/wSBtAwAATJmKajYJYC3+eb9NE2juroaIpEIc+c6vr+RwcvLyyaDJK4q/r788ks888wzOHbsmNmVd2dmxvQAAsM9MbaCSZBISUkx+2+MRiPKysrg6+s77S+1SqVCY2MjcnJyLP5bazh16hQuuODXag2X/X4qnRFKrRGRAbbpR/v7N83QGSncc/kcEATBDkAwFZOx/NDYh9e/acZ/bphv9usa+xzmwJjpWts3OBnM9GtUVBSio6Ox+rUfQdHAiT8u4+TxnYHXTzbBQNG4+7I5qK+vZ3ulpluRMJVGUj/khYAAf6zKsN0EMTDcl3fFKz8iLcIXb+wc/o6Xdgzi0yoZNudFjsqwZbblZkMvp1arZfsbKWrYzoTpT2O2ip1ZOLT0DkFvpJBixqQ8TdOorKyEp6cnkpKSnEb8TYY1gyRMbF9ubq5L9eV+++23ePTRR3Hs2LFxfr0uwMzuAbQ1llbihoaGUFpaivj4eERFWdYHMhJz+vFsDSP+SJJkPZCmi5Gi8OCBKgR6ueGJjfNAYPguw1pT6JHcsCwOeuOwUO3q6mLzUCe6aF6YFIwLkyy7m9uxMBoqHWnRe+Hp6clJ3+BEMFXO5ORkdvp1RWooepTW5zo7EzsWxUCrN6KyshLu7u4WTUkqtUb4eAhHfd5MpZHc/o9zoKkuBKrb2TQSW0xIugkIEARGTdSmhPsOVzhHVJe7urrQ0dFhMtd3psH0N6amprLHJDIyku1Pk8lkaGhosGlsoLU8ergGFE3jPzdOPkjHOEL4+PiwpuyuwNieTmaQhPFPnWiQpLu72yXF3w8//ICHH37YVcXfhMyoCqBer8cUr2faDA4Oor29HZmZU8c29fb2oqamBpmZmay33HTR6XQoLy/HwoULrXocS2EqgFwPe5xrG8De71txWUooti2Mxn1FlaBoGn+bRhzW+fZBvHayGc9flY6QMZYUjI2CUqlkc5WdlbE5xVP1DZpicHAQVVVVE1Y5ZxJMZT0kJATx8VPnHTPojCRe+aoZQd5uuPmiyf+urU8DjcGIo2VdyAoRIEI0ZFdj8JFYm+vrSqjVapSVlZn1OWa2iuVyOSiKsklFfbo0ytTQGSmkR048IEBRFDuxbq3NV/+QHt839GFNptgiNwNbMLai7u7ujrCwMNA0DalU6nLi7/Tp07jnnntw5MgRxMbGTv0HzglfAbQGoVBoVtRcW1sburq6sGDBAk62aRzRA8hgi0nf9EhfXL8slu3Piw3yQr96ehWqIT0JgB7XBzQy/mtkrrKzYm3fIGPzkpub69KmpOag1+tRUlKCuLg4i+MRPURCzI8LQFrE1FN7ccFe0JMUREIRwsUhyI4JMDngMzaNRK03Yt/Pndg8P8rs6e6JYG5iVCqVTfOaa7pV+KJGhqtyIzCgMU4qWmwJM9ySlZUFX9+pt05bFRTuP9aDv2/PQrS/26iKOhc9ndaQNIUPKEVRrHm3qZuYAY0B75xqw60XxcNnikx0YDhJ6Ks6OebHBZjsHbUnYyvqGo0GTU1NkEql8PLyQnNzs9MnkjD88ssvuPvuu3Ho0CFXFn8TwgtAM5nKBoaxFyFJEgsXLuTspOMoAUjTNAwGw4QZiNPl+RON0OhJLPifALz7cvO3PZrlQ1DqjMj+X5O9qa1bvV6PsrIyhIeHO/QLq9IZsff7VqxKEyMjyvwL6sitFSZZgZnCM9U3ONbmZSbDbHHPnTvXbBulsaycZ75/ortQgLtGfD5NCXW5XI6SkhLW107n5odetR6SAa1VAnBkrm92drZNb2K6FVpoDSSu/b/zMFI0TvxxmVX2KNOBGW7Jyckx2yVBYxg+L+qNFNzc3KAgfHFqQIsblqVDrRy2/2GsTBih7gy9k0xyS2ho6ITnqCqJEuWdCjTI1GYN9lyRJkZ2TACibNRXbQ2Dg4PQaDS4+OKLQRAE+vr62EESa83BbUlpaSn+8Ic/oKioyGm8J7lmRglAgiBstgU8mRBjqhJhYWFISEjg9GRt7+oV0+8nFotx+vRpNv2EqzvpnYtiUC9VTesCc7isGwaSYgXgWJios5E9cI5C+L/erunwZY0ML33ZhA9vnI9Ar4n7BgmCYKuclm6p/O3LRggFBP54mWv0HSkUClRWVjrNFvdIoZ6YmAidTjeceCFrx4W+GggVFPo9xdOqcjB9YV5eXnYZClieEorlKaHIz4lAk3zI7uKvr68PdXV1yM3NtUigLYgLxLHbl7D/LpMooNAaQRDEqArU0NAQ5HI5KisrR91EWWv/oycpi30tJ/I0HMuSxCCkhPsi2Me8mwh3kYCdincmenp60NHRMWrbl9nRGHkTVVpaCsDxiSQMlZWVuPXWW/Hxxx9j7lzLk1xchRnVA2gwGGw2MEFRFE6fPo1ly0ZPUyqVSpSVlSElJWWcvQhXjJ3ItRVjJ32B4bs3qVSKvr4+eHl5QSwWj9rysicqnREGkkKQ9/g7xb6+PtTW1s6IqLN9P3fi/dPt+Oh3CxBgoorE2LwIBAK4ubmxfYNjtyMn49WvmxDg5Ybrljr3tgZN03j2eBU8dP34/ZoFLrHFzUSgyWQyDA4OWpRGwlSHgoODLepvdFVkMhnbvmCPChBj/yOTyaBUKuHl64eo8OEbXEtuonoUOrz3UxvWZoSPs/0xhcZA4nCpBNHGHsyJi7JqMNBV6OnpQVtbG/Ly8sx6b/V6PXts1Gq1w7bxa2pqcP311+M///mPWT3/LgLfA2gNAoFgXHWxp6eHtWUwp2fFmZmo3y8wMBCBgYGsP5dUKsX58+fZ3jSxWGy3bZWJIqwkEgk6Ojowf/58p5sGnA47FkVjxyLTBtHMFndERARbQRjZNzjy2EzWN+iMlT+5Sg+F1oA5ob/2T3V3d6O3vx+xURFTij+l1mj3hBNTjHz/TaWRMFPFY18Pk+vLGCSPhKZpHCztxmWpoVb3FjoL3d3d7IS+vW4oRSIRwsPDER4ejgqJAg8dqMTvcoFIYRMq+oDkqFAsSY2e8rPm5ymCl5sQYWZ6W7bJVThV2Yqr5kfz4m8C3N3dERkZyU58Dw4OQi6Xo6mpyS4pPgBQX1+P66+/Hh988MFMEn8T4vizJYfYq2TMNGf39/dj0aJFLt97Zc6wB0EQ8PX1ha+vL+bMmcP2plVWVoIkSYSGhkIsFpuV68nluhsbG6FWq7FgwQKn9gXjAlM2L8DkfYMGg4EVHM4wHTkZW/91FiRF4+t7LoCAINDS0oL+/n7s2b50yotIVZcSB0q6sG1hNJKnaMC3JxOlkZRXVsFgMCA8bPjYeHh4oKysbMJc3+puFf72ZROa5UO4d6X9csFtRWdnJ7q7uy0SCFwT5O0OT3cRclITkRjija8+qYGkRQl/6tfUi7CwMAQEBIwz6j7V1IffLo4ZZd8zEQaDAQPttbjzsjmYE2tbX0lnYDribyymBklGpvhwmUjC0NLSgmuuuQbvvvuu3X13HcWM2gI2Go02HZg4deoUlixZgvLycnh6eiIlJcUuU0ynTp3CsmXLbHLx5iLZw2AwQC6XQyqVQqPRsCfOwMBAmwkOkiRZ81RbOufrjRQGNQZOIryswRKbFwNJQUAQEAoItm9QJpNx5jfIJTKlDiIhgSBvd5R2DKJLocPqtDA2xs5cg2el1ojPqqVYkyGGj/vEF52S9kHcV1SJ4lsXmdxetxcvfNEA0DSuyfZHV1cXent7ERwcjJiYGJNbXjRN45v6XuTFBjh03VzQ1taG3t5eZGdnO9VNm1pnhEhIwEM07PjAbOMrFIpR2/h9GhK37SvDovhAPLR68v4wg8GA8+fPTyjsZxpciL+pGNtiwcUgSXt7O7Zu3Yq33noLS5YsmfoPXA+TF0heAFrA999/D6FQiNjY2EkbeLnmp59+wuLFizm9YHOZ7DGSsV9Of39/q4ZI9EYK7qLRr5tJu4iMjLT5cdjx9jnojBT+e9MCq5rjFVoDaBrTungzNi/Z2dlmbX9c+dpPIAjgkzuWjvq5Kb/ByfoGSYqGnqTgNc2MZHN49vN6iAQE7luZzK6REfbJycmcC/t3TrXivR878OGN8x3aNP9VrQxuQgFyw91RUVGB9PR0UBQFuVyO3t5ednKVqQ7aCwNJQTKoRXyw+Xnl5kLTNJqbm6FSqZCZmcnJ+UxjIHG0vAdrM8Rm2aWYC0XTrFk4s43PHBuhUIgeyhfzkyIREWz6ZsxAUqCMw1v6iYmJNusPdybsIf7GMnKQRC6XA7B8kEQikWDLli149dVXcfHFF9t6yY5i5gtAkiTN8uqbDv39/fj555+xcOFCu2cA/vzzz8jNzeVsq9lW4s/U81gzRPJzSz9O1Mhwy0UJCPUdvrNTqVSoqKiwygrEEso7FajsUmL7QtM9eeby/IkGgAbuX5Vs0d+1t7dDKpUiOzvb7ON/079LEBXgib9umDfh74zsG2QuamP7Bl/+qhE6A4X7VyVzmtQykmb5ENyEBGKCvFiD59DQUMTFxdnk+ZwJxvokKyuLzfVlUKvVkMvlkMlkoCjKpmkkI/m0sgfn2gZxy0XxnFa9mUx0pqrL1Wuol6rx8blObMqNnNC/0EBS+Ll1AIviA826ifvobCcKz0vwr9/kItB7/HdOq9Wyx0an043aKhYIBKBoGte8ew6aITX27si0y3nK0UilUrS2tnJ6nZoOlg6SdHd3Y8uWLXjhhRdw2WWXOWDFdoMXgNOlo6MDHR0doGkaixYtsnvPyrlz55CRkcHJsIUtzJ3NfV7GuV8mk5k1RNI5oMH+XyS47ZIEeIiE6O3tRX19PTIzM11u6KZRpgZF05grNm/dzAVTp9MhIyPD5tu1I3OKmb5BGekFqZbAxuyp+5ZomsaBkm7EBXthYXygxc+v0+nY6MSZFLU0ETKZDE1NTWbl+jItFsxFzZbb+EqtEXVSFebHBnB2bqBpGjU1NSAIAqmpqZyecyiahkJrhL+naMKblEqJEsUlEmzKjURm1NQTuyeqZfjXD614//o8eIgmr36P3fHw9fVFQEAA7jnchMvTInD7iolvwiaCpmmodKRTDDSZg7OIv7GMHCTp6+uDm5sbysvLsXTpUqSmpkImk+Gqq67Cnj17sGrVKkcv19bwAtBSKIpCbW0tdDodsrKycP78eWRlZdl90rSkpARz584dVyWwFEeJP1MwgkMqlYIkSfgGBiM2MnzCCkdnZyckEgmys7NnxKTvZDD9jV5eXtPaBpUMahHi4zblxWsiptM3SNM0nv28AW5CAe6zcEiB8W9MSUmxe3XdETC5vjk5OXB3d0evWg8/D9G4VgdTmNrGZ7a87GmkS1I0jBQ15WeMSeXx9PS0i6ehKYwUhdZeDeJDvDiJSWvrG74xvfOyxFE+gDRNo7e3F5WVlXBzc4O7uztbubXk3P3xL52o61HjrsvmOL0IdFbxZwqNRoN//vOfOHbsGHp7e0EQBG688Ubcd999LhVNN01mvgCkKAoGg4GTx2IsGYKCgjBnzhwQBIHz588jNTXVbKd6rigvL0d8fLxVBrg0TbPi2Bma/0fS1a/GrsNVyAqisTiMRHBwMMRiMQIDAwEADQ0N0Gg0yMjImLSP8GSdHJ9USvFU/jyH52FOhyE9CTeCQmlp6SibF8mgFgICiPCfugKsNZB4/kQjgn3ccPul5ueLKrVG+HoIx12gLekbHDl8Yi7McMtM8G80h7G5vkaKwjOfNcDLTWixcB5ZVZfL5WwaiaWCYzq88EUD9EYKD6+eeACLoiiUl5fD39/f6qxb9jFH9OY5indPteFYZQ9e2ZI5KnZNo9GgtLQUaWlpCAgIYM3BZTIZtFoteyMVGBg46TlYMqjFj019uCo30qmn9l1J/I1kYGAAV199NS6//HL09vbixx9/RFpaGtatW4c1a9Y4PETARvA+gOaiUqlQVlaGpKSkUdtRjopls+Z57dXvZw1hAV4ICfDB2qXxmBPiyUYFMdF6/v7+U4o/ACj8RQKF1jY9oLamf0iPnW+fw1w/A3atSxvVNP7+T+0gCODBVVM70nu6CbE2U4yEEPNvUvrUerz+TTMWxwfiyozR268T5RSb8hu0dEhGLpejoaFh2hnGMqUOQT5uLiH2GesotVo9KtdXJBBgdVoYoqaR3zrSmmlkGkl9fT20Wu243jQuuSQ5BJJB7YTnEybxIiwsbNqRjEN6Ep9W9WBNRji83ISgaBr5/zwDL3chPr5poTXLt4rfLI7BuqxwiEf0SDIWTenp6eyNuoeHB6KjoxEdHQ2SJCGR9uKlLxpwSbgREUG+E1ZuI/09cOncULPO1aUdg2jv12BdZrhdz+2uKv4UCgW2bNmCe++9F1u2bAEw/N0sLy/H0aNHcdVVV+GBBx7A+vXrHbxS+8BXAMfABL1nZ2ePq0hUVVUhMjKS9SayFzU1NeyYuyW4gvibCKYnLCgoCDRNQybvxSDlgdw5EQgLCzN50qFpGjTg8ArBdOgfGMC2d0rw4KpkrMgcPdncOaABQRA2y/mkaBr7f5Fg+dxQhPubv71uqm/QXL9BiUSCzs5OdhvUUtQ6I178ohHxIV64bqlzD4yMzPVNS0uzy/fQ3DSSne+cQ4CXG/65I5uz557I0LpXrYe3u9DsqfKqLiUKf5Fg64JozIsY7p3Nf+MM5scG4C/rUjlbr7Wo1WqUlZVNWcUu71Tgmc/rceOyOCyO9hw3ucpUbv/vp3Z829CHJzfOm/I7//ChauiNFF64irvBmqlwVfGnUqmwZcsW3Hrrrdi5c6ejl2NvZv4WME3T0Ov10/7blpYWyOXyCS9KtbW1CAkJsXuJuL6+ns3kNRdXFn/MpO/InrCvamX4oqoH65PcIdIOmJV2YU/e+7ENJ2pk+OD6+RAQBKokChwq78HtlybA33PykyQzEGCuzYszYm7fIE3TaG1tRX9/v1U+cDRN44fGPsyL8GMnxJ0Re+f6mmKkjUlnjwznpDTWZUUiNiocG/eWgADw+R+XTfk45sDkoo8d5qFoGk9/Wg8PkQD3X2HeJDxF0xjUGBDg5ea0N3UqlQrl5eXIysqacjCNpmlIlXqE+I6uWuv1enareGhoCAZ3P5zvFeL2FSkQTfH90BpI6ElqynMMVzCJNq4m/oaGhrB161Zce+21uP766x29HEfAbwFPBNN0LxKJsGDBggm3S1xlC9iZhj0shdkWHGuNsSQhCP6ebpgfFwABQbDVp6qqKjaJxB42GRPxSaUURopmv2UGigbo8dXIBpkaYj939oTd3t6Onp4ezJ8/36VOqGNxc3NDREQEIiIiRvUN1tXVjTJqbW5uhtFoRE5OzpTbkpJBLdyEBMJ8x1clCYLARcnOba9hy1zfc20D8HITIiHEG15ugkk/8yPTSPQ+YvTK2tChMEA1WI0nlwxv8TOenRM9TlWXEuH+HgiZJPlCp9OhpKQESUlJ426SBQSBdZnhCLNArAsIwmTu91QYSAqvfN2ENenhyIiyXV+pUqlERUUFsrOzzeq5JAjCZIXd3d2drZYy351wXzl+PnMG3t7e7LnNVFHC000ITxv6dI7EVcWfRqPBzp07sX379tkq/iZk1lcAtVotayo8lfdYc3MzPDw87J7l2NraCqFQaJbpsTMPe0wFI4ays7Mt2hYca5MxcojEmcSv3kjh6rd+hrtIgP/+bgEOnapEoh+F3Owspz9WOiOJ6i4VcmImFgmmYPoGe3p60NHRAaFQiLi4OIjF4imrnZe/fAoEgC/vvsDK1dufyXJ9ueDyl08BAC5NDkFurD/yc8yLGKNoGv1DBgR6uUEoIGA0GtnKrVKpREBAAEJDQxESEsJWZw0khac/rYe3u3DC6h0zAJGammr3FpmxMOtNEftgxyLbGMUrFApUVVUhOzvbZkOBNE1DqVLhPz82I1SoQZwf4bAbXZlMhubmZrvmNnOBTqfDb37zG6xbtw5/+MMfnOp6YGf4LeCxDA4OoqKiAmlpaWbZT7S1tYEgiGk3NU+Xjo4OUBQ1qUB15S1fmqZRV1cHvV6P9PR0q+KhuE4iUeuNuLewEn9amWS2h99kfFLZg+RQb9TU1eOLVgN+e1EKFiU49oJpDifr5Pi6To7fXRCPuGDLtqmNRiNKS0shFosRFhZmdt/gl7UyeIqEuDDJOmuY0o5BlEsU+M2iGLt8L5j+VVvGf5V3KuDpJsCJGhnWZYZzktzBGLfLZLJxaSQSJYkgHzcEmkiyYXrg0tPTERAQYPU6nJ3BwUFUV1cjJyfH5i0bJEXjqU/r4OUmxN3L40fd6AYGBiI0NHTa5zZzcVXxp9frcd1112H58uW4++67XeqaaANmvgAEhk++5iCRSNDa2oqcnByz7+AkEgn0ej0SEhKsWKHlSCQS6HS6Ca0UXFn8kSSJ8vJy+Pn5sXY71jAyOs5UEglzQTP3RNY5oMUfPy7H1vlR2Pa/NBCdkRznf6YzkhAQxJSTsAaDAWVlZQgJDYPeMxgJod6jvMS45kBJFz78uRP7bpxvVZSdxkCiWT6EtAjLKg+TGTwbjUb2gqZSqRAYGAixWDwtg+PJ7EFWvnIKRpLG53cts+l7Dfw6DTqVpyFz3nXm7+rQ0BBrMTNRmwWzDTqTbHyOlHdDptTjhmWx445Pf38/amtr7SL+GLQGEiIhMapvkKIoDAwMsCbHnp6e7FQxF4EBDK4q/gwGA2688UYsXrwYDzzwgFN/z+zE7BCAer0ek70mptqkVqtZLy5z6enpgUqlQlKSZX5d1tLT0wOlUonk5PHbL64s/rRaLcrKyhATE8PJNtmgxoC/fdmEpYnj7UwmSiJx8w2EjhZNapuiM5JwEwogIAj0D+nxylfNuCgpCCvTfq3ubNl7FgSBSe0pNBoNysrKMGfOHLtlg27dexaDWiOO377EIn8+LmAMns3ZFmQuaFKp1Kyc4pGQFI09n9YjwEuEOy+bM+7/B4YM6FXrkRRmW288RgxlZGRM6dn5zGf1Zlv7OAOm0ki8vb1ZQ2tb+w7ak+1vnwNF0+O+y319fairq0Nubi6nIosLmOhARqyHhISYPZE/Ea4q/oxGI2655Rakp6dj165dLnVNtCH8EAizFeXv74+8vDyLPxhCodBmWcNTPa+pIRBXHvZgLpbz5s3jrGfI10MEL3eBya3asZ5pzBDJs0fLoDPSuPeSKESEi0321oys9vl5iuDtLkDymOe4KCkYvh4Tb8MoFApUVlbafZvs45sd45dmqcGzQCBAcHAwgoOD2b5BmUxm0m9wLEIBAZGQwJwJBF6gt5vJTFcuYXJ9zR0IEBCwqiJrb9zc3BAZGYnIyEhQFIW2tjY0NTXB3d0dDQ0NrFi3ZxqJrXjv2lyQY4oIvb29aGhoQF5entVJRH1qPRpl6mm1ftT1qHCsoge3Lx+dQuLj4wMfHx/Ex8ezE/ltbW0T9nVOhauKP5IkcccddyApKYkXf2YwayqAQ0NDbF9OZKR5DdNj6e/vR1dXF9LT061dptXP68rDHjKZDI2NjeMmfR2yFqUOUoUGAp0SyoE+kLohzodImNdrz20jR8K1rY01foP2wJJcX0uo61HBSNFIj3SurVXm9ebm5sLd3R1qtRp1bd1490wX1s7xQFqceNppJCRF271SPRWMGGJer7U8cqga7f0a/H179qRRb6ZaTd4+1YqyDiX2FKTB231qMUfT9Kit4pHxdBN9Vl1V/FEUhbvvvhtBQUF49tlnXe66aGNmxxawwWAARVGjftbb24uamhpkZWVZFaemUCjQ2tqKrKwsa5dp8fO2tbUhMzMTwPBdjitu+QLDgzQymQxZWVmTnkyZqqY9oGkaO9/5BSIhgfeuyeF0iKSjowPd3d0WTza7KozBs62sIrjsG+QCJtfXFq/3ieN1oGkaj9nJ9PiVr5oQ5ueOnZNMzvb09KCtrW3c65UMavGv71uxOUeMAGKIjT8LDg5GaGjolPFnALDrSA3Otw/i45sWmiVuLGG6EXJSqRQtLS2ciqE+tR7NvUNYEBc44e80ytR49vMG3HJRPBbG//p7JEXDQFLTtn4ZGhpit4oNBgO7VcxYAMnlcjQ1Nbmk+Lv//vvh5uaGl19+mRd/45l9W8A0TaOtrQ3d3d1YuHCh1aV7R/kACgQCdqvXVfv9mDQEo9GIvLy8Sb+gA0MG/OVoLbYtiMQFSZZ7vUmVOpxrG8CV6WKz3iOCIHDt0hiE+XqM2m4cORXZ2Nho0RAJTdNshnFeXh6EQiEqJUootAYsm2PdVKszwhipDw4OYv78+TabShSJRKP8Bpm+wZF+gxP1DXKdFNPW1ga5XI68vDy2l7iuRwWNgUROjPXb/LdfmjBuK9KWHKvogYAgJhSAEokEEolk1OtliArwHCFUg9j4s76+PnR3d6O2thZ+fn7sVqSp45MV5YeyTgW83Li9eKt1RrzwRSOWJgZhdbr5U9mM2OVaDAX7uCN4Ej9FAPi2oRfNvUMI9B79PgsFBISC6X+3vL29ERcXh7i4ONYCqKOjAwqFAu7u7tBqtS4p/h555BHQNM2LPwuZsQKQoihUVVWBpmksWrSIkw+Fo42gXVX8GY1GlJeXIyAgAKmpqVOu3U1IQCAARNPskfq/n9pR1qnAkoSgKU+0DGvGDI0Aw8IwMDAQgYGBSE5OZodIpupLY9IfPDw8kJWVxb7eA6VdMFIUliYGudTxM0VpxyBO1vfi9ksTICQINuosOzvbbidgS/sGn/q0HjRNY9da6ypqE+X6AsDH5yQw0jQnAtDczy5XHPj9Iggn+FyOFLvmivuxN1NKpRIymQxtbW0mj8/WBdHYuiCas9fD4OEmgEhIIMKCmMOuri50dnaaFLv2ICfaH5JBLZJCffBZlRR1UhXuuDSR0/OGSCRCeHg4wsPDIZPJUF9fj9DQUJSXl8PNzY3dKnbmthWKovD4449DqVRi7969Vp17brzxRhw9ehRisRgVFRUAgN27d2Pv3r3s0N7TTz+NtWvXAgD27NmDt99+G0KhEK+++ipWr15t/QuyMzNyC1ir1aKkpARisRjx8fGcfWmMRiPOnTuHJUuWcPJ45qLT6XDmzBk2bsiVxAMz6RsXF4eIiAi7PKdKZ0Rbn8amvVOm+tLEYjE8PDxQXl4OsVg8zi9SrTfCSNIIMOGl5mr849tmdA3q8OiVyaipqoSvry8nNj7T3aobi6nj83krCT2EuOty86b4JYNavHuqDbcvT2T976bK9R3QGGAkaaeOp7OU5uZmKBQKZGVxZ1g+9viM3Yp0JBKJBF1dXcjJyXGI+BvLvYUVMFI0XtmSaZP3htn2HdnjqNFo2FYLvV7PHp+AgACHHx8Gmqbx9NNPo62tDe+9957Vuw7ffvstfH19ce21144SgL6+vvjTn/406nerqqqwY8cOnDlzBhKJBCtXrkRdXZ1N/RitZHZsASuVSpSUlCA1NZXzzF5HVABpmoZAIEBiYiKampqg0WgQEhICsVjsFCfLyWAmX9PS0hAYGGi35/X1ENm8cd7T0xOxsbGIjY1lLTIaGhrQ19eH4OBg+Pr6jutjFBIE3jzVimuWxJiMN3Mlbrs4AXqDARVlpQgPDzcrpWYqTjX14bEjtXhzZ/Y4yxZLe0JHHh+mb/CisOG+wepqPcLCwhAcHDypoOlXG6A1UFBpjQj0cjMr19eUUTJX3FdUiR6FDv++Yb7NnmMkTBuDTqfjVPwB44/PyK1If39/NjrQ3hfUjo4OSKVS5ObmOs3F/IWrM0DTtvGMNCX+AMDLy4s9PiRJore3FxKJBNXV1VNu5dsDmqbx4osvorGxEf/+9785OVaXXHIJWlpazPrdQ4cOYfv27fDw8EBiYiKSk5Nx5swZLFvGTaa2vZhxAlChUCA3N9cm06X2Flsjhz0YCwbmy9je3g6lUomgoCB2YtWZeh+kUimam5stMtp2Vdzc3ODj4wOtVov58+eDJEl0dXWhpqZm1MWsXqrG13VyJIR446rc6U2i2wKaptGl0CEqwPwJVsbgOTExkbO0Cy834f+2/kd/z94/3Y5m+RAeXZNi9oTokJ5kM3LH9g12yXrRIx3e8pqsbzAjyg9PbJwHwLa5vuZSLlHYbU+GqXQCQEZGhsXnvroeFU439+GHpn68ui1rUgPukVuRI/tum5qa2DQSrg2OTdHe3g65XI6cnBynEX/A/3pWbXDp6e3tRWNjI/Ly8iYdUBMKhRCLxRCLxaBpGgqFAnK5nN3KZ7aK7XWep2kar732GkpLS/HRRx/ZvEr7+uuv4/3338fChQvx4osvIigoCJ2dnVi6dCn7OzExMejs7LTpOmzBjBOAMTExDunT45LJhj1GfhmZ4PCenh7U1tY69M555NqZfqH58+e7VDPxdGGqfyPFbmho6LiLmaenJ/5yWTjSE5xrCOSD0x3495kOvLQ5A5lRU0/JW2LwPJaqLiUOlHTh/lXJ40RBXmwAPr9z/B20m4AAQQx755mDQmvAM581IC/WH1vmj+4pIwgC1+6rh1BA4LM7l5rlN2gwGFBSUoLo6Gib54B/Uy/HN/W9eGjVXDbRhsHUe2MLKIpCdXU13N3dkZyczJ5/pEodrn//PB68IhmXpky+u7LvbCe+b+yDSECAomjAzNPRyL7buXPnsmkklZWVE6aRcEFraysaJb34vs8H8Skkgn3MWzBN01DrSfh6mH8pfe+nNrT2aiy6oeGakb6GlrgTEASBgIAABAQEICkpCVqtFnK5HLW1tdDpdBZNfU8Hmqbx5ptv4tSpUygsLLT59eW2225j/QR37dqF++67D++8845Jqzln3o2biBknAF3xIIyEEX8kSUIgEEz6egQCAUJCQhASEjJObHh5eUEsFpuVpMAVFEWx/VFTTfraFZoC9EOAyB0Qctubxdi8zJ8/f9yJdKIhkoqy0inNje3Jinmh6BjQIMWMrOOBgQFUV1ez/aiWUtapwJCetKiStWMSWxJT+HqIIPZzx8K48eKUIAgsjA9EeuSwh6Cfnx8bQ8j0pVVXV7N9aYGBgWhoaEBSUpJd0lt6FDoYScd54VEUhfLycvj7+4+LnmRWpCOp8X84hrsun4NbL45HsLf7OCFrCd7e3oiPj2cNjuVyOZqbm9ksXHO28ieC6Tdtbm6GUqlEREIy9LJOKLRGswdwPvy5A5USFf585dxJPf1GQtPD76WriT9TeHp6IiYmhi289PX1sQUJS9J8zIGmabzzzjs4ceIEDhw4YBdbrZHxlTfffDPWr18PYLjQ1N7ezv5fR0eHzW8ObcGMGwIhSdKmaR2nTp3CBRdcYJPH5irZg4k9k0qlkMvlEIlEEIuHzVmttcKZCKPRiLKyMgQFBSEhIcE5hDhFQtD0JUR1xwCtAiAIkHEXgkwrALyH7WUUWgP8PS0/OdE0jcbGRqjVamRmZlpccZ1oiMRZh3wMJIWBvl6bGB47I0ajERKJBI2NjXBzc2Ob4KcrNlwBZps7JCQEcXFxjl7OpDAWQDKZDH19ffD29rYojURvpPDb935BmAeF3+d6ISMjY1rHtaV3CCeqZbjpwjin/N6OhUvxNxkjp/J7e3tBEASbVezj4zOt9+r9999HUVERDh8+bLOb5paWFqxfv54dAunq6mKDI/72t7/h9OnT+Oijj1BZWYmdO3eyQyArVqxAfX29U7UOjGF2GEHbWgD++OOPWLJkCecXAVvGumk0GkilUshkMtA0jbCwMIjFYs56NpiM24SEhFF3TA6FpiE8uxei1u9A+YQCbt4AZQSh7gE8AqFfvgvfdgL//LYFf75yLrKizTcIZyyG3N3dMXfuXKuP1dicVa6TSKyluluJN7+qwxXRJFZd4FoeYdOFiSrMzMyEj4/PKLHBdWXDGWBiMiMiIhAdzb0Viy0ZmfMtl8sBgK2ue3t7m/wOURSFq//5IxZFivDwpsVO8T2zNfYSf6bQ6XSsAbVGo0FQUBBCQ0PNNnDft28f/v3vf+Po0aM2S4/asWMHTp48CblcjvDwcDz++OM4efIkSkpKQBAEEhIS8Oabb7KC8KmnnsI777wDkUiEl19+GWvWrLHJujhidghAiqJgMBhs9vhnzpzh3CjTnskeOp0OMpkMUqmUk8oTk/lqj4zbH5v68N9zEjyVPw8+7qa3W5rkani7CxFpaIfbySdB+0cBxOgTDKHoBJm0Ap2JW/DSF43485oUs6c3DQYDysrKEBYWZlWV5GBJF8okCuxakzLqfacoCn19fZBKpWwSiSP7OmmaxpmKenx4Xo5dBXkI8x++89YYSAgIjIuqUuuM8HYXjvssPXSwCqUdChz9wxKnifpS6Yx46ctG3HpRAsJHeMT19/ejtrbWZFThyMqGXC53qq386cL0OMbFxXF6A0fTNEo6FMiJ8bfI2oemaeiM5qddDOlJvH+6HdsXRiPQyw16vZ49PozYCAsLY/vSaJpG0fcVONmswtNbFsLfTrZMJEVDayQnPHfZEkeKv7EwvesymQz9/f1TVm+Lioqwd+9eHDt2zKxccR6TzA4bGFvDWMFw1dNgb3NnDw8PtmeDscdobm7G0NCvGbjmej319PSgpaUFubm5drn49Sh1MJLUhGa1NE3jqU/qIRIS+Fd6GSAQjRN/AED7iCFs/gYR2b/Fc1dlmP38TKWTi8nX0k4FSGq8tYlAIGC3Skz1dVqyzWUtNE2jpqYGfkIar1yzbNRar3rzZxAEcPz2Xyfh1Doj/nq8DnPFPrjpwtGTslKlDjQc1/dkCrlKD5WORMeAhhWAI3NuTW1zm9M3KBaLnSaneCp0Oh1KSkowZ84cq3scexQ6GCka0YHD79vPrQN47GgtfndBHLbMn7w/ykhR2Lr3HFalh0GlM0Ku0uOv6+eZ1T/YOaBBi3wIzfIh5MUGwN3dHdHR0WwaychBOV9f3+G4UJJAcFCQVf2JlnLHf8uhM1LY+5scu34P+vr6nEb8AeN715nqbWlpKZRKJb744gsUFBRg4cKFOHr0KN544w1e/NkIvgJoISUlJZg7d67VZWhni3VjGnilUikUCsWkGas0TaO1tRV9fX3Iyspy6DYYTdMY0pPw+d8UXnmnAn6eIiQ3vAeip4zt9RvzRyAUHdAXvA0IzVs7syVob09DhpEnSplMxlnlqVk+BIIAEkJGtwOQJImKigr4+fkhMXF8AsHrJ5vhIRLg5ot+FXo0TePN71pxRVrYOB8/Z4SmaVD08HQxQRBW5/oyfnZSqZTNKTanb3DTmz9Doyfx6Z1LJ/wdW6DRaFBaWoqUlBQEB1s/mf7o4RpQNI2n89MADPfZFZd04cp0MQK9p45OLHjjZwR4iXDfyiR8VSvHPSvMM+xmJnG93YWTVhqZARetVgtg2H7GntXbk3VynGsbxH0rzXtdXNDX14f6+nqnEX9T0d/fj3379uGTTz5BU1MTDAYDXn75ZWzYsMFm/euzhNmxBUzTNPR6vc0ev7y8HPHx8fD3N79nbCy27PfjgpEZq/39/fD19WUnigmCQHV1NQQCAVJTUx3eEP/q100olyjw4tUZo4Y5BA0nICr7ELS/iX4mnQJw94PhiqfNeg7G5iU7O9uunoZNcjWCvN0Q5D3+xM3VEMkjh6pBEASe/J/fHTC8Jcj0g3Fh8OwKMNZFjAfckJ7E8YoebMqNnFa1ZuyQwmR9g1e+/hNAY5wAHBgy4JWvm3D7pYmcJ4sMDQ2hrKwMaWlpnLVutPYNgaRozAl1PvFP0zTbt8tY25hKIwkNDXWqtAtrcDXxN5IvvvgCTz75JB566CF89913OHnyJBITE7F+/XqsXbvWbqlSMwheAHJBdXU1IiIiLPY/Y3B28TcWxviTOVEyXk/z5s1zipNKVZcS+37uxF83jMkY1ing/tn9oIUegMeIrQOKBKHogHHJHaBip664dHZ2QiKRICcnx66v10hReORQDTzdBHh8/bxJf3eiIZKAgIApBXrngAYEQbAm0FqtlnODZ2dmZK5vZmYm+37t+7kTe39oxdP5aViaOL3v+sjnmE7fYL1Uhbe+b8X1S+OQEcXd9pdKpUJ5eTkyMzMdsq0mU+oQ6utut3MfTdNsgstEcYVGoxF9fX2QyWQOTyPhAkb85ebmulzl7JtvvsGjjz6K48ePsz2pjDH50aNHcezYMXzwwQez5uaUI3gByAV1dXVsU7GlMP5+ABxeObMUpv+NSSNhtiEZexlntAUh5LVwO/U3wKgZ9v8jDQBNg0xZCzJzKzDJBcgam5eBIQO83AXjBiSmQqrUwUD+2kNV1aVEqK87xH7mn8DPtvbDn9DCqOq3eIhEpVKhoqIC8+bNm3Kbu0ehg1BAuHTmLXNRoWka8+bNGyUM1HojfmkbxLI5QRBx/F11ZA7u4OAg6+Noq2nKyajuVuJf37dhy4Ioi4U1TdPQGCh4u5v/vWLi+3x8fDBnzhyzn4fpva1ok6FDLUBBXrTTnufG4sri74cffsCDDz6Io0ePuqSvnhMzOwQgMNzYbCsaGxvh4+NjUQna2fr9LIUx/83IyBi19a3Vall7GYqi2G1IR1xYJkSvhkByFkR/C+AZACp6kelt4REwNi9ubm5ISUmx6HhRNI2HDlbDQyTAExsmr9yN5eq3fgZN0yi+dbFFf8egNZDYdaQGgd5ueOTKlFEXst7e3gmHSBRaA27993nsmGPE5YuzzTJ4Xvv3n0CAwLHbl0xrrY7GnFxfS1Fqjdi89yx+uzga1yyJNetvpts3OB2Y6eacnJxp97wZKcoqQaw1kPisSorLUkMt9t/c8c45aPQkPr5poVnDG0zPX0BAABISEqa13ic/qUOvUos/LPSHor8XJEmygt0ZB31cWfydPn0a9957Lw4fPozYWPO+PzxmwwtALmhpaYGbm5vZXlmuLv66u7vR1taG7OzsSe9+9Xo95HI5pFIptFotKwad8SQ5GYzNS2hoKJv5WtWlBEnRZnsFflvfi8gAD8w1I1kDGK6mvfxVEy5PDYGvhwjL5ky/Ib9BpobYz93kxXWkOThBEGz19udGKR77tBl3X56MgvnmbaucrJPDXSTABVas1VGQJInS0lKEhoaOsvLRGUmLq7Yj0RspbPjnaWxbEI0bL7DcIsiSvkFLkcvlaGxsnLYw0BhIVHUpsetIDXavS8XiBOu2xafDp5U9KCrpxt7f5Ez5uxRFsdnN1tg1aQ0khvQkmwxiMBjQ29sLmUxmc8FuKa4s/s6dO4c77rgDhw4dmrZY55mU2SMA9Xq9yaw+LmhvbwdN02adVFxZ/NE0jebmZgwODiIrK8uiwO2xVQ1nMzaeCKb/bayh9cMHq0ADeKYg3SbP2yRX483vWnHThfGYK7ZP9ZTZhmxvb4dGo4U4Khpx0ZHwt0Cw0zSNz6tlyIzyZ7etnZ2Jcn0rJUq8+2Mbfn9JApKdYILZ3L5BjYGE1kCaHBRi6OnpQWtrK3Jzc6fdx/rwwWoodQa09Wnw4tUZZt/cOAIm0SQ0NNSmlSRr00i4pK+vD3V1dcjLy3M58VdaWopbb70VxcXFSE5OdvRyZiq8AOQCiUQCnU43LidzLK427DESZgtUJBIhJSXFqjtbU8bGYrEYISEhDr9jHslkNi8ylQ6ggTALevGcHWb4QaVSYd68eejv74dUKmWHSEYa507EkJ7ErsM1iAnyNNuyw5EwAt+U551UqcPrJ5tx9+VzzM6BtQaF1oD3f+rADctiWQujyZiob/C5byQwGGk8uynN5DlGIpGwQ0xubm6gaBrv/diO+bEByI01f/q3tGMQQ3rSquq0PWCqu+Hh4SZ3aWQqHQK93OAm5D7JaWwaSWhoKMLCwqYdfWYuzNa+K4q/yspK/O53v8PHH3+MefMsa5nhsQheAHIB45M32Z0KTdNsHJ0ziRxz4CrpwhQ0TbP2MswWF2MvY0mFkWt6e3tRX1/vsMZ4e0NRFGpqalgrH2uSSLoGtQj0doOXGakNKp0RvmaIHVvA2J6kpqZOe4J/KvQkhUGNAWG+U1+Ez7cP4v9+asfNF8ZbPOHLVNhlMhmquwZBuflgRWbMuG3I9vZ2yGQy1toGGE6jeOBAFbzchKOsf2YCTJxdZGSkyQECrYHEb9/9BZ5uQvz7hvk2XQvTEiOTyUymkXCFK4u/mpoaXH/99di3bx8yMsw35OeZFrNHABoMBlAUZZPHZk68pu5WXHnLF/j1IpmUlGR1KsBUMFtcTE+au7s725Nmz+0TxuYFoYnw9fJAWsTMdpsnSXJUY/xkn9GxQySenp6sYLf0GH1ZK8Nznzfg2YJ0iypPXDAy19eWtidr//4TDCSNY39YMuWQAkXTUGiN8PcUWRSTNu5xJugbHBoagkqlQlZW1jjBoTOSEAoIzqebHYnRaMT58+cRGxs76YDe3u9bcWFSMNIj7fc9Z9JIZDIZBgYG4Ovry95UWdPb6crir76+Htdccw0++OAD5ORM3dPJYzW8AOSCgYEBdHZ2jrtjcXXx19/fj5qaGod5gw0NDbETxSMHFGzl0K/SGfDqp+VYHk1gSV42bvh3KQQEgfeuzbPJ8zmKboUWe79vxZ+uSIYIFFshMXeIaSQTDZGYc4xa+4Zw18cV+Ndvc+1qHcNcJG1p4j0wZMDzJxpw6dxgVHercdfl5tmNWIqRoqDSkRPmVjM3VTU1NVCr1ayBu6NzijsHNHjtZDP+tDLZJsfeVlnGppApdXjhi0bcsTwRsUHj31OSonG0vAeXzg0xmX5C0zSUSiV7U8X0doaGhlr0+XRl8dfS0oLt27fj3XffxYIFCxy9nNkCnwXMBUwW8EhcXfx1dXWhvb0deXl5DvO58vb2RkJCAhISEqDT6SCVSlFdXQ2j0TjKXoaL95aiKHz1cyUa5Fqsyk2DUCjE4+vmwV3kWsfNHL5v6MOPzf2o7uiHQdpoVearj48PEhMTkZiYOC4Dd6okkvhgbxz8/fTsbabLVLm+k0HTNBpkarOGHWQqPdR6EuH+nliVbrkA2f72OSi0hlG5yqb4y5FaDBlIPLcpfcIeNolEAl9fXyxcuBA6nW5cTrG9/AZHMjBkhIGkodIZOReAer0eJSUlSExMtPmuBQCo9SRIevi1mKK1bwhF5yXQGklsWzD+JosgCPj7+8Pf3x9JSUns96i2thY6nY49RpOlkTDizxWnfdvb27Fjxw7s3buXF39OwIysABqNxnEijSuGhobYOy/AtYc9mEEApVKJrKwsp3S8Z1IupFIpNBoNQkJCIBaLp30RMxqNKCsrQ1BwMALFUQjwcrNqC85e6EkKfzlSg+UpoVidbn5Ch56k0NLdD3lrLdLT022SY8xYY1g6RGJLzM31Zb63Y/msSornTzTiodXJWDnPtsJi3d9/Ag1MKQBru5Wok6qxIXv8FicTdebm5oa5c+eOe00j+waVSqVT2ZdMF0b8zZkzB6GhoY5eDoDh41DdrUJiqLdZfbEjMSeNZGBgADU1NdO6qXE0EokEW7ZswWuvvYaLLrrI0cuZbcyeLWBbCkCdTofy8nIsXLjQpYc9SJJkszEtNTt2FCRJskJDqVSyjdVBQUFmvf8T2by4AhQ93LyfHOqD31+SYPbfMdUCWw+4qPVGNMuHkB7ha9EQiS0Ym+s7EQ8frAJFA89uGm/vM6Ax4KOzndi5KNpiw2J7Q1EUKioq4Ovri8TExCm/y7b0G7QXOp0OZ86dR3rqXISEhDh6OZwztv/Ww8MDPj4+kMvlmD9/vsuJv+7ubmzevBkvvvgiLrvsMkcvZzbCC0AuIEkSP//8MxYtWuSyW756vR5lZWUIDw93Wcd1iqLYxur+/n74+fmx9jKmLvqT2bzMVBj/t6lMvLlg7/etKJco8Pj6VNaTjsshEnNg4vuGhoZG5fpOxF+O1kJvJLHHRv6O9oDxvAsODmaNyy1hpN9gZ7cMnu5ChDtB3+BkaLVaFJ48h4+bBNi9Pg3z4wIdvSSb093djbq6Onh5eYGmaadOIxmLTCbDVVddhT179mDVqlVWPdaNN96Io0ePQiwWo6KiAsCwB+K2bdvQ0tKChIQEfPzxx+yk/549e/D2229DKBTi1VdfxerVq61+PS4KLwC5gKIonDp1CosWLYJQKHT6L99Y1Go1ysvLkZyc7DTbJtZC0zQUCgWkUikbecYIDTc3N5e0eaFoGoMaw6QGv5PR3t4OqVSK7Oxsu1R1BjQGNMrUWDDJxZgZIpHJZBAIBJwOKNA0jZqaGgAYl+s7U2FsT8LDwxETM5zgwlRiM6PMS61hICkaG/95BkKCxt83RDskp9gcNBoNSktLERCViMdPdOCFq9IRY2IYYyYxdtt3ojSSoKAgp2vj6e3txVVXXYXdu3dj3bp1Vj/et99+C19fX1x77bWsAHzggQcQHByMhx56CM888wz6+/vx7LPPoqqqCjt27MCZM2cgkUiwcuVK1NXVOd17ZCdmjwAkSZLdmuUSZtijvr4ecrl8yqqTs8G4xWdkZDhk0tceMIaszLQqSZIgSRI5OTku9Zqvfe8XKLRG7PvdAot6iSytgjmKscbGUw2RTAazBerj44M5c+ZwKlR61Xrs+bQeN18Uj9Rw50m/YCZfx9qevPFtCyq7lPjrhlSLbx7u3l+Bi5ODcXXesIees/UNMuIvLS0NAQHWWQlRNI0m+ZBZqS96IwWCAOfm0eYwVc/fyO38/v7+CfO+HcHAwACuuuoqPPTQQygoKODscVtaWrB+/XpWAKampuLkyZOIjIxEV1cXli9fjtraWuzZswcA8PDDDwMAVq9ejd27d2PZsmWcrcWF4KeArWHksEdycjKSk5PZqlNTUxO8vb2dwtR4IiQSCTo7O13SNsASCIKAr68vfHx8WOPpkJAQ1NbWgqZphIWFQSwW28wShCvuunwOPq+WWST+KIpCdXU1hEIhsrKynKJiYwoDScHDwwOxsbGIjY1lKxrNzc0WD5FMlOsrVeoQ5utu9XtAUjRoDJsIOwuTTb5uXxiNBpl6WpXjl7dkjvq3SCRCeHg4wsPDRwmN+vr6Uec7e1SYmZ2L9PR0+PtbVt00xcfnJCg634W/bkid0vvzwYNVEBAEXrzavmbF5gx8CAQCBAcHIzg4mL35lcvlKC0tBWC/NJKxKBQKbNmyBffddx+n4s8UPT09iIyMBABERkZCKpUCGPZ4Xbr018GqmJgYdHZ22nQtrobzKRUnZKJhj4CAAAQEBCA5OZk1NW5tbYW7uzvCw8MRFhbm8KZqpiKkVqsxf/58l6hUWstIITR//nwQBIGYuDi0ypQQGZSora2FXq+3qupkaxbEBU66nfrs5/WQq/R4blM6CIJge8ECAwOnNHh2JEaKwv3FVfBwE+DZ//Xeubm5ISIiAkMiPzy6vwIvrQ9AT08PamtrJ62yM1WwmJgY9gIAAJJBLZ76pA4XJQVjx6IYq9Yr9vOw+4XfFM3yIfzf6Xbce2ksqirKMHeu6eGHQG83LIwP5Pz5xwoNpm/w/PnzEAqF7HfJnO380o5BHKvowf1XJJtVVVOpVCgvL+fUo/SKtGHhbE729uL4IHi5D69zSE/ijv+WY026GFsWjE8b4YrpTPsyN7++vr5ISEhg00gaGxttmkYyFpVKha1bt+L222/Hli1bbPY8U2Fqd9NZz4uOYkYKQC4PMkmSUw57EAQBPz8/+Pn5ISkpid2CZE6OYrEYYrHY7pU3kiRRWVkJLy8vZGdnz4oPP2PzwjTFM6/5g9MdONs6gL+sS0VeTAyMRiPkcjlbdWLsZUz5bw0MGTBkIBEV4DyTd3KVHjQ9/NnT6/UoLS1FdHS0yQgsZ0IkEMBdROCS5PHipbpbBZ2Rgl7kg/S0iFG9nU1NTaOGSCiKmjDXN8LfA8tTQnDpXNM9rhRNu4T1z0iOVXTjh4ZezPfqxSXzbWPnYy4jz3dz5swZ5wk5Vd/g13VydCt0ZvUXMeIvKysLvr7cbcGH+Lhj+0LzzNB3LPr19xivUMqG3VGDg4OcWL24u7sjKioKUVFRbBoJc2Pl6+uL0NBQziu4arUa27dvx+9+9zvs3LmTs8edjPDwcHR1dbFbwGLxsE1WTEwM2tvb2d/r6Ohw+vOjvZmRPYAURcFgMFj1GFyZO2s0GshkMkilUtA0zYpBW0/YMaIgMjKSbRCf6Wi1WpSVlSE+Pn6czYtcpcfZtgGsTgsbdyxJkmStSxQKBQICAiAWi9lepxvePw8jReP96/KcTkQzfVFjh3paeoeQEMLdNrdab0SDVI2cGNvFuNH08HYrgdE3cbU9Kvh7iuAvIiGVStHT04OhoSFERUUhPj7eou9St0KL6/+vBDdfFMf2urkCfQMK/Hi+AhcvyORkC9RWmNM3SNE0KJqeMoqOmdzPzs622/BWs3wINT0qXJk+/jxhDwYHB1FdXW1Tn7+RMZxMGgmzVWxNa4xGo8H27duxdetW3HzzzRyueDRjewDvv/9+hISEsEMgfX19eO6551BZWYmdO3eyQyArVqxAfX39rNgFM8HsGQKxVgAy4o8kSQgEAs5OBIwzv1QqhdFoZPvRuD65qVQqVFRUTLhNNBNhLhbz5s1jLQCmw1iPNF9fX/QTfiA8fHDxXNsnDVgC85rT09NHNcV/VSvHS1824v4rknHpXG6O/79+aMUvbYN4fH0qwvzsV8mmaBp3f1wBd5EAL1ydwb7mlJQUaDQaSKVSi4ZIlFojtr19Fg+umsvZe2NrFAoFKisrOa+C2Zqx3yVL+gYZIWTLCD9T/O6DEmgMJN69NhceIvsKBeY15+Tk2NWCR6vVQi6XQyaTmZ1GMhadToedO3di/fr1+MMf/mAz8bxjxw6cPHkScrkc4eHhePzxx1FQUICtW7eira0NcXFx2L9/P4KDgwEATz31FN555x2IRCK8/PLLWLNmjU3W5QLMHgFI0zT0ev20/9YeyR4Gg4EVgzqdjrN+NMbyJDMz06UuFtbATDdzbfPC5HYyE8W29rGzhMle84DGgP+e7cSOCUyMSYqGUGDZZ2xQY0C9VI0FceZfFOp6VKBoYF6EdZ/D2h4VArxE8CA1JnN9me18LpJI9EYKz51owJb5UU4x9cv0gtlbCHHN2Ol8gUDA3gCPFTvMa/aJmot50UE2m76laRonqmWYK/ZFYujwezuoMUCu0iPJjOlgLnGU+BsLY7Y/No0kODh4wuFGvV6Pa6+9Fpdddhnuvvtup9sl4QHAC0Dz/s4RsW4jL2BDQ0PTjjvr6OhAV1cXcnJyHC5Q7AUz3ZydnW3zHsuRPnZMiLtYLLa7Kz9j8JyTk2Pxax4YMmDXkRqsTg/D+qzxkWJcctf+CoCm8crWLKsfi8n1zcnJmfT9piiKjdMaGBiw2KpJpTPigeIqLEkMwnVLHWuS3tvbi4aGhilf81TcX1wJkqLx4tUZTnNxZqpOTAWXqTqRJIm6ujqIE+fh+S9bcfHcEOy0cpBnIgwkhbv3V8DLTYgXHDjo4yzibywjjdz7+vrg5uaGsLAwCIVCtpfOYDDgxhtvxOLFi/HAAw84zeeLZxy8AJwMc4Y97IGpuDOxWIygoKAJ10XTNOrr66HVapGRkTErehxomkZzczMUCoXFOcY6IwmdkbIq4otpfJdKpSBJ0mbb+WNpa2uDTCZDTk7OtOyG9CSFhw5U4ZolsciLtV0/HwB0DmgB0IgOtO6ixoj8qXJ9xzLWINzcCq6epCASEA4dFJFKpWhpaUFubq7VN3P3F1eCpGm8dHXm1L/sAJi+wY6ODgwMDEAsFiMiIgJlvTQWxAUh0Nu8Y67WG/HYkVrcfGG82VXnzgEtArxE8PVwzDyks4o/U2g0GnR3d+PGG2+ESqXCJZdcgs7OTixcuBC7du3ixZ9zM3sEIDDck2AOXA172AIm7qynpweDg4PjhhOAYcHImOAmJSU51fptBUVRqKmpAUEQ00p9uHt/BQwkhde3ceOVx9gtSKVSaLVadjvf0pimx4/VorpbhQ9vmD9qi3ZQY8Djx2qRP0eIYDcjMjIynNbgmWva2trQ29uL7Oxsq29sRm5BEgQx4Rako+nq6kJHR4fFgtcZGNAYsPtoLf5wSQJSLNhCH1ntHBoaGtU3GBYWhrCwMAwZgceO1OCRNSkQm+hD7VPr8ejhGqzPCsfaTOfP+nYl8TcWqVSKu+66C83NzQCAiy66CBs2bMBll13mcjnFswTeCHosziz+gGHvrZCQEISEhLCmxlKpFPX19fDz80NQUBA6OzsRExMza8bbJ7J5sYTrlsZCrtJzdrwZu4XIyEi2gtva2gqVSsVWcM3pR1Pphr0mx/bnKTQGSPsG0R3mi0sumR12Pox/pUajQU5ODieC18fHB4mJiUhMTGQHshjrEmfxhOzo6IBUKkVeXp7NDeVpmsbdhZVIDvPBncsTOXlMnYGCgaQgV+mRYqYGk8lkaG5uRl5eHtzd3eHp6TnK2Jix1GocpNHYY8T5ll6szhp/vgv2ccc/dmRz8jpsjSuLP4qi8MQTTyAlJQUHDhwASZL44YcfcPjwYfz5z39GYmIiHnnkESxYsMDRS+WZghlbAdTr9SaNIBkc1e/HBTRNs+HgQqEQfn5+CA8Pd9oUEq5gbF7i4uJGxV85C9e/fx4UReP//mcXM7aC6+/vz1Zwza1mMQbPQUFBSEhImPR3KyVK7P2hFU9tnAcfB21pcQGT60sQBFJTU23+3eRyiMQaWltb0d/fb3FLgzVs+OdpCAgCh36/eNz/dSu0ePJ4He5YPsfqQZ6JkEql+OhUPeq1fnj+6gx4TpJ8M6TRoL1LCmW/HKTR6HQ5xeaiUChQVVXlsuLvT3/6Ezw8PPC3v/1t3PeD+e76+fnNGvsxF4GvADK4svgDwFaYFi5cCG9v73EpJGKxGGFhYTNqEISxtklNTbXK5sWWRAV4omtQy36exlZwBwcHIZVK0dDQAB8fnymjAxkvx7FJFxPRJFdDayBhoFznvk2m1CF0RGSbLXN9J0IkEiEiIgIRERHsEAljmOvl4wt3v2CkxkXYTJTRNI2mpiao1WpkZ2ebJToVWoNVPawMR25bMuH/Uf8zGqcmLxJMm56eHrS1tSE4IgZ0q2LKaV9vLy+kzokHEM/2Dba3t0OpVJpsj3FGXF38/fnPfwZBECbFHzD8eUlLS3PA6nimw6yrADrLsMd0aW9vR09PD7Kzs00KvLGTqo5KIeESxvJkJljbdA1q8cCBKuy6Ig5C7SDkcjnc3NzY48QcU8bgeSZ7Odb1qPDCF43YPD8Sq9LE43J99SSFwSGDXX0HR0LTNO78qAT9Kg1uTSfg7+PFuQ0QTdOoq6sDSZJIS0sz65zU3q/BLR+WYlNuBG65KMHk70zH6seedHV1sYM91u5amPIbZPoGnamH0tXF3+OPP46+vj689dZbs2LQcIYxuyqABEGMEoDO3u83FcyFwmAwYP78+RPe5Y7sc2JSSMrLy+2aQsIlXV1daG9vR15ent1EbEn7IPb+0Iq/bpiHEB9uq6hSpQ46IwUVKcL8pCQkJM7B85/VIsOgRERXFwiCgL+/P2QyGTIzM0cZPM80EkK8cWFSEBbEBZrM9d2y9yz0RgqHfr8Y7qLpV3Vomkb/kAHBFh5LgiBw/+pUlHYocEl2BHtzVVpayskQCU3TbGa1ueIPAML9PBDo7YYL55i+MfjwTAe+b+zDc5vS4efpfKd4iUSCrq4u5OXlcSIkxuYUq9VqNqeY8Ru0NuXCWlxZ/NE0jT179qC7uxvvvfceL/5mEDO2AmgwGEBRFADXF39GoxEVFRVs9uZ01m+vFBKuoGkaLS0tGBgYQFZWll17G39u6cd7P7XjiQ3zLBINSq0ROiOFUF/z/8ZAUrjjv+UI9HLDs5vSf9169PICTdPscIKPj4/LfW7NRavVmsz1Pd8+iJ9bB3DLRfFWPf6rXzfheIUUb/0mB3HB3Fx8R36fmCGSsLAwsye/KYpCZWUlvL29Od/qPtXYh4/OdeJvmzOdrgrIDLnk5OTYRUiMTLnQ6/UO6RtkxJ8rmnnTNI0XXngBNTU1+OCDD2Z0j/kMZ3bZwDAC0NX7/ZjBh9jYWLP6wMxhZAoJY1sSHh7u8AlIhpE2L6mpqU7d0zOSO/5bBgNJ440dlk3q6o0UhAICMulwTxRj8GwwGNjhBI1GM62Ipv4hPT6vlmFzXpTTiQFguGWhvLzcpr2dtT0qvHayCS9vyZwyf3Y6MEMkMpnMrMlvkiRRXl6OwMDAKQd7bMmrXzfBQyTArRfbZw3WWPocLe/Gp1UyvHh1+rQj2sbmFDN9g0FBQTYTo64u/l599VWcPXsWH330kVNtp/NYzOwSgEajEUaj0aXFH1f5tpMxNoUkODgYYrHYIpHB9XpGXhxd6ZhVSBRQaIy4ICnY4r9ta2uDXC5Hdna2ybvssRFNgYGB7MVrMoH8wel27P9Fgmc3pSMtws/iddkSJuM2MzMTfn7Otbbpwkx+S6VSk0kkTJ+jWCx2+JTkHz4qAwHg79ttb53S2trKVvOnc0P39g+tONs2iNe3ZXFyI2OPvkGlUonKykqXFX9vvPEGvvnmGxQWFs6ogcJZyuwSgEx0DUEQLlNBGolMJkNjY6NdTx4kSbITkOamkHCJTqdDaWkpp9VOZ4emaTQ0NECn0yE9Pd2szypz8erp6cEXNXIkhvlhcUqUybizIT2Juh4VcmKcyyqjv7/fZK7vTGJsEom7uzs0Gg3i4uIQG2t5zJxMqcO/TrXhrsvmwNvddfqwmpuboVQqkZmZ6ZTn4pF9gzKZjJO+QVcXf2+//TY+/fRTFBcX88bOM4PZIwBpmsbatWsxNDSEDRs2oKCgAJGRkU51AZwImqbR3t4OmUyG7Oxsh5XdzUkh4RLG5iUlJQXBwZZX0FwRiqJQVVUFd3d3zJ071+LPJ0nRuPU/pRCCwp+W+KG3txdeXl5OOQE5EibXNzc3d9RgD03TOFDahZzoACSFOWdv6kQ0ydVokqmxYl6YyeOo1+tx7tw5+Pn5QaPRgCAIDAj8kZkQiYhg86qfJ+vk+OB0Bx5clWxRyoajYOxthoaGpkyvGdKT+KZejtXpYodG8AHW9w0yOzc5OTkuJ/4A4P3330dRUREOHz7scgMrPBMyewQgMHzy6ejoQFFREYqLi0GSJNavX49NmzYhNjbWKcUgRVGjLCGc5W55ZApJX1/fuG0ta5lJNi/mwiSahISEID5++kMOXYNa+HqI2GlPxhNSLpdDJBKxwz7OYgMkkUggkUiQk5MzTqDqjCT+sK8c/l4i/G2zc+bWTsSd/y2H1kjiH9uzx/nZMUMuycnJrKXPgGoIf9hXBncYcFu2u1lDJCRFQ6Uzwt9TxPn5q3NAgzs+KsdT+WlIj7R+O55JcmEq21Ott+i8BP8+04m/rE1Bro0zqi3BVN9gWFjYhGburi7+9u3bhw8//BBHjhxx2gFBnmkxuwTgSJjkjOLiYhQXF0OlUmH9+vXIz893mvxcV+l9G7ut5eXlxRpPT2dCjLF5YQYfZgN6vR4lJSU23+pmbICkUilommbFoKMuTK2trejr65t0CKBboYW/p5tdtjh1RhL/PStBQW6E1abKCq0BA0PGcVPGjJ+jqSGXn1v6kRDijSAvoUVDJNPFSFETDsE0yNS4r6gSj1w5F4sTrOs3pmka9fX1MBqNZtvbqPVGlHUosDghyCmHlYCJ+wYZX0hXF3+FhYX417/+hWPHjs2YnlweltkrAMcilUpx8OBBFBUVoa+vD2vXrsXGjRsxb948hwgvpkIQHx/vlBFnE8H0zvT09EAul1uUQuJImxdHMjQ0hLKyMrsbPOv1elYM6vV6u2bfjsz1nWor0J6Udgzib1814bolsbgsNZTzx1er1SgrK0NGRgb8/f3N+puphkimS023Cs+faMB9K5M4qfBNBE3TqK2tBQC7xPg5irF9gzRNQ6fTITMz0yVbWA4fPozXXnsNx44dQ2BgoKOXw8M9vAA0RV9fHw4dOoSioiJIJBKsXr0aBQUFdrtQDQ4OoqqqCmlpaS7/xWNOiFKpdNIUEoqiUFtbC5qmMW/ePKcRBLaGmXq1RBDYAlPZt0zFiesLNmN2LBAIphQEUqUOf/+mGQ+ummuXCiBF02jv1yAqwHPKGDJLYapBWVlZ025rGFtt18AdKbHh04p57BzQ4IlP6vHolXMRE2Sbvi4mB1YoFE6rp9VVUSqVKC8vR3h4OBQKBXQ6Hbul7wo5xZ988gmef/55HD9+nHPxmpCQAD8/PwiFQohEIpw9exZ9fX3Ytm0bWlpakJCQgI8//thp4z1nELwAnIrBwUEcOXIExcXFaGpqwsqVK1FQUIDc3FybiBSpVIrm5mZkZ2fPuGZbrVYLqVTKbj8yYtDNzc0ltrq5pre3F/X19U43FUhR1HC2tKQHX9f348q0YESGh3My7DNVrq+epNAgVbMVqaPlPfjHt814amMa8izoAxvQGPDggSrcelE85scFWrVmcyjtGER8sDcCvU1vGw8MDKCmpobTY32qsQ9/PV6L63P9keQ5xCaRODrhgoGmaXagKTk52S7f6ya5GvHB3g7dMmaEfnZ2NtszZ2nfoCM5ceIEnnrqKRw/fhyhodxXwRMSEnD27NlRj/3AAw8gODgYDz30EJ555hn09/fj2Wef5fy5eUbBC0BLUCqVOH78OIqKilBTU4PLLrsMBQUFWLRokdUXRpqm2X6orKwsp53W5AomNaG7uxsKhQIhISFITk6eNU3GXV1d6OjoQE5OjtP6af33XCf+c6YT9y+PQphAjb6+Pvj6+rLbj5Zu0TNDLkyuryne/bENX9f14okNqYgP9oaBpCBT6RHh72HRJGifWo8HDlRhx6JorEgNm/L3f27px7wIv2nFpKl1Rtz+33JE+HvgmYL08Wv530BTbm4up/YZA0MGvPx1E+64NBGhvu5WJ5FMh8+rpfi5dQAPr5476vgw0+xeXl6s0DdSFH777nlclhJiE6Pptj4Ndh2pweWpIbhuqenPl60xJf7GMlXfoCM5efIkHnvsMRw7dgzh4eE2eQ5TAjA1NRUnT55EZGQkurq6sHz5crZtgMdm8AJwumg0Gnz22WcoLCxESUkJLrnkEhQUFGDZsmUW39ExKRcAZtX2J2PzMmfOHBiNRqdNIeGa1tZWNv3Amfsch/QkKiUKLIgPhOB/OdpKpXKUh525/Z16vR6lpaWjcn1N0afW4+fWAaxKM22dYgvkKj2uee8XpEX44qVpThr/3NKPxFCfcZF/MpkMzc3NyM3NtevF3dIkkumyde9ZGCgKRbcsYgUgU+X18/NDYmIi+7s0TWPrv87Bz0OId67N42wNDBRN42h5Dy6YE2xR9CJXqFQqlJeXTyr+xmILv8Hp8v333+Ohhx7C0aNHERUVZbPnSUxMZH1kb731Vtxyyy0IDAzEwMAA+ztBQUHo7++32Rp4APACkBt0Oh2++OIL7N+/Hz///DMuuOACbNq0CRdeeOGUlTyDwYDy8nIEBwcjPj5+RgoeU/T396OmpmZcPxSzVdLT0wO1Wo2QkBCHppBwCTMJqdfrzTZ4tgY9SeHujyuwbUEULk2xzUDD2AuXWCweV+WaKNfXGpgkH674vFqK3JgAiP24mzrv7u5Ge3s7cnNzHVrRt9UQCTCcW22kaHi5CdnnKi8vR0BAgEMj7ezNdMSfKZgqrkwms2vf4OnTp3HPPffgyJEj0zIktwSJRIKoqChIpVJcccUVeO2117Bx40ZeANofXgByjcFgwNdff43CwkL88MMPWLx4MfLz87F8+fJxFYC6ujq0tbUhKyvLZuV2Z6S7uxttbW3Izs6edEuMSSGRSqVQKBQ2q2LYA4qiUFlZCU9PT7v1QxkpCrf8uxTJYh/8+coUmz6XVqtltx9JkmSrGARBoLy8HPPmzeNsoGlgyIB7iyrxm0XRWDGPG0HJNZ2dneju7kZOTg5b5W2SqxHu7wEfd8dVfccOkXh6erLHytoKJUmSrI/lRFv8MxGuxN9Y7NU3eO7cOdx55504ePCg3UX77t274evri7179/JbwPaHF4C2xGg04rvvvsP+/fvx7bffIjc3F/n5+VixYgV+/PFH3HXXXXjrrbewdOlSRy/VLjB9jv39/RbbvIytYtg6hYRLzOl9m0kYDAbIZDJIJBIMDg4iIiICMTExJqsY1P/ONZb096n1Rvzx4wpcszgGy21Q2bSWtrY2doufuVBrDCRu/bAU3u5CvLEzx8Er/JWRVVxrhkgcmWfc2jeEUB93+HjYX1jbSvyNhaIoDA4Ossb7XPUNlpaW4tZbb0VxcTGSk5M5XLFp1Go1KIqCn58f1Go1rrjiCjz22GP48ssvERISwg6B9PX14bnnnrP5emY5vAC0FyRJ4tSpUygqKsKBAwdAEATuu+8+7Nixwykm9mwNlzYvY1NIfH19ER4ezlkKCZcwWcZxcXEu5ec4HeqlapR0DGBzXhT6+/tRV1eHjIwMaDQaSKXSUVnSTBX3qrd+Bmig+NZFjl6+1dA0jebmZqhUKpMZt1/UyJAW4YvoQOeb7u9R6PDwwUrcvCAQnvpBNu5MLBZPOURCkiRKSkoQERGB6OhoO656uM3hpg9K4OkmxFu/sa+wtpf4G8vIvkG5XD5t4V5ZWYnf/e532L9/P1JTU2244l9pamrCpk2bAAzfGO/cuROPPPIIent7sXXrVrS1tSEuLg779+93Se9EF4MXgPaEpmk888wz+Pbbb3H//ffjk08+weeff46kpCTk5+fjyiuvnJFu6yRJory8HP7+/khMTOR0+5PrFBIuYQyeZ0uW8fa3z0JjoPD6xjhI2lvH5fp29A3h4YMV+E26JwJoNfz9/fH6eS1IQoi3fpPruIVzAE3TaGhoYPs7rf2MV3crERPoNa2p5OnQKFPjyU/qcOfyRMyPC2S3H6VS6aRDJEajESUlJYiOjrZpgs1kfFkrQ1KoDxJC7Hcj7SjxZ4rp9A3W1NTg+uuvx759+5CRkWHnFfM4CbwAtBd6vR633XYbPDw88Oqrr7LihKIolJaWYv/+/fjkk08QExOD/Px8rF271uVNoIHhk1NZWRmio6NtOlkGWJdCwjWMmXdmZqbTi3q5So/OAQ1yYizLWx0bI6bQGlDZ2AE3Ta/JXN/WviE8fqwW91yehMwov1FbWoxwDw0NdVoLpM4BLfrUemRFjzbsZsyOCYLgJOlCrTdi27/OwdtdiI9vWmjVY3GBqSGSsLAwBAQEoLy8HLGxsTO+uj0SZxJ/YzHVN8h8t5i11tfX45prrsEHH3yAnBznaUfgsTu8ALQHNE1j06ZNWL58Oe66664JLxA0TaOiogKFhYU4duwYQkNDUVBQgHXr1tk1Iowr1Go1ysvL7R5xxjA0NASpVMpOqTJikEsvNlPI5XI0NDQgJyfHJcy8b/mwFBoDiX/9NgceIvO20Ft6h/DY0Rr8cfkcLIwPBGBerq8paJqGSqViq7gikYg9Vs6UBX3Vmz/DQFI4dNviUZYnVVVV8PT05DRD/HhFD7Ki/RFro4SO6cJU3Lu7u9HZ2QkfHx/ExMQ45CbLETDiz5o0F3vB9A0eO3YMzz33HGJjY3HxxRejsLAQH3zwARYsWODoJfI4Fl4A2gupVAqxWGz27zP5mYWFhTh69Ch8fX2xceNGbNiwAWKx2OktUSayeXEUE6WQcC3QJBIJOjs7ndrgeSxSpQ7t/RossCAxQ6bU4eFD1Xhw1Vwkh3lzmuvL9Awyeaq2OlaW0tI7BKlSh8UJwxFVjOUJ09owW9Dr9SgpKUFiYiK8vb05GSJxBVxJ/I2FoiicOHECTz75JIxGI4KDg7Fhwwbk5+cjKSnJ0cvjcQy8AHQFaJpGU1MTCgsLcejQIbi7u7Nf3sjISKcTg+bavDgKvV7PikGj0cgaT1uznTNywtnSCpgrY0mu73QwlW4hFosdbhLOTL2GhYVN6pv2S9sAfmzux22XJIyadG7v12D3sVq8eHUGAr043vKmacCoAQRugJDbx9br9Th//jySkpLGxYSN7EWzZIhkIqq7lXjpi0a8vDXTodY5wPBuRllZmUuKP2D4xnTz5s14/fXXcdFFF6G7uxtHjhzBoUOH0N3djVWrVuHRRx+dkcKdZ0J4Aehq0DSNtrY2FBcX48CBA6AoCuvXr0dBQQFiY2MdelEcGWfn7CkXDIxliTUpJDRNo66uDkajEWlpaU5vS8MVU+X6csmgxgB3AY2BvuH+pqGhIQQHBzvEJJwZfIiKipqyr/Xqt36G3kih6NZFcBf++rn4pk6ON79vxe51qUgJ50hQ0DQEzSchOv8uBANtAEGAjLsAxvm/Ax08x+qH1+l0KCkpwdy5c+EXEAg34cSfc3OHSCZj388dOFreg1e2Zjkk2YPB1cVfd3c3Nm/ejJdeegnLly8f9/8qlQpfffUV1q9fP2vOXTwAeAHo2tA0ja6uLhQXF6O4uBhDQ0NYv3498vPzbX5BNrWW2tpakCTpsiJoOikkjAjy9vbmtAfM2WG8DaeqgHGBgaRw/fvn4SkS4u1rcgGMNwkPDAyEWCxGUFCQTT97zPZnfHy8WebtQ3oSar0RYb6jexlHnmO5+swISz+E29m9oN28ADcfADSg6QeE7tCvewV06PStPrRaLUpKSpCamooB0gOPHa3BbRcn4IKkqafbJxoiCQ0NnbRSTtM0KBoQChz3nXJ18SeVSnH11VfjmWeewRVXXOHo5fA4F7wAnElIpVIcOHAARUVF6O/vx9q1a5Gfn2+TrbmR2NLmxVGYk0JiNBpZ81tbiyBnwtxcXy5549sWLIwPwML4oHH/R1EU6wvZ399vtsCwFKYCZmr70+EMyeH5322gPfwBwZjKu3YAdMhc6Df8Y1oPrdFoUFpayqa59Kr1uL+4Cg+vnou5YvPaJvRGCq9/04yrciMQJDKyHnYeHh4Om9SfClcXf729vbjqqqvw+OOPY+3atY5eDo/zwQvAmUpvby8OHTqEoqIitsdj06ZNnGfQMmLAHjYvjmJsBcPf3x/BwcFoa2tDQkLCrIrxY3J9nVIEwXTUGSMwrLGXYURQamoqgoLGi1BHI6w5DNGplwBvE9F4NA1C0wft1n2Ar2WfVcbLMi0tDQEBltkEjaRHocPdhRVYNS8MN1zwaxoOV0kkXOPq4q+/vx9XX301Hn74YeTn5zt6OTzOCS8AZwMDAwM4cuQIiouL0dzcjCuuuAIFBQXIycmxSgw62ubFEdA0je7ubtTW1kIkErGRdFxXm5wR5nhzmetra9RqNTtRLBQKp2UFxLxua0WQLRGW/QduP78J2se00wChHYBu45sW9QIyIigjIwP+/v5T/8EUyFV6+HuJRvVCjoTrIZLp4uriT6FQ4Oqrr8Y999yDzZs3O3o5PM4LLwBnG0qlEseOHUNRURFqa2tx+eWXo6CgAAsXLrRIDA4MDKC6utoljI65ZKTBs6+vL5RKJXp6ekalkDizmfF0USgUqKysdOnjzVgByWQyUBTFThRPNv2tVCpRUVHh9K9b0HYKbl/uArxM9ORRRsCghm7HQcDdvMoaY3niqNfNxRDJdHB18adSqbB582bcdttt2LFjh6OXw+Pc8AJwNqPRaPDJJ5+gqKgIpaWluPTSS1FQUIClS5dOWs3q6elBa2ur09q82AqZTIbGxkaTBs/OlELCNX19fairq0N2drbDt+YYPj7XiWMVUrx9Tc6oNBJz0ev17PT3RNWmwcFBVFdXIysri5PEB5qmbVfJoozw+HgHoB0EPEdUKWka0MhBpm2CcdldZj0UI3qdRQRNd4jEUhjx5+xifyLUajW2bduG6667Dtddd52jl8Pj/PACkGcYnU6HEydOYP/+/Th37hwuuOACFBQU4MILL2SrWTRN4+mnn0ZGRgbWr1/vEjYvXGGpwbOjUki4RiqVorm5eVyur6O5e38FpEodPrxhvtWiamy1KTg4GJ6enpBIJMjNzeXEgJqmaVz7f+chFBB479o8qx/PFERfE9w/vRfQKgCBEKBIgADoiFzor3gaEE392WMqvc4Ycwb82uMpk8nQ29vL2Y2Wq4s/jUaD7du3Y+vWrbj55psdvRwe14AXgDzj0ev1+Prrr1FYWIhTp05h8eLF2LBhAz7++GOo1Wq8//77TiUGbAlN02hpacHg4CCysrKmVXEYm0ISFhaG8PBwhydbTIVEIoFEIjGZ6ztToSgKzc3NaG9vh5ubG4KCghAWFoaQkBCrtx6v/b9f4OUmxJs7bZi/qh+CsPkkBF3nQLt5gUq8DFRkHkBMvXam4ulMld6pGDlEAgBhYWEQi8UWrX9oaAilpaUuK/50Oh127tyJDRs24LbbbpsRLgw8doEXgDyTYzQa8fnnn+OOO+6An58fMjMzsWnTJlx++eUuV82yFMbbkKIozJs3j5PeI1MpJEyyhTMx3VxfV6enpwdtbW3Izc2FSCRi7WX6+vrg4+PD9njOtOr3wMAAampqXCa/2hQjh0h0Oh373ZpsiMTVxZ9er8c111yDFStWTJozz8NjAl4A8kyOTCbD1VdfjRtuuAHXXnstfvjhBxQVFeGrr75Ceno6CgoKcMUVV7hMxcBcSJJEZWWlTVMuDAYD5HI5enp62BQSR0w9joSmaTQ0NECn03FuGeTsSCQSdHV1IScnZ5zAo2kaKpUKUql0xvV49vf3o7a2Frm5uTPmps7UEElYWNgoo3DG4iYjI8MlxZ/BYMANN9yApUuX4v777+fFH4+l8AKQC/bv34/du3ejuroaZ86cwcKFCwEALS0tSEtLQ2rqsAP/0qVL8cYbbwAAzp07h+uvvx4ajQZr167FK6+84nRf4Pr6emzbtg3PPPMMVq1aNer/KIrCmTNnUFhYiM8//xxz585FQUEBVq1a5ZIn05EYDAaUlZXZ1eCZJEnI5XL2gmVOCgnX2DrX155QNI0jZT24NCXErKzd9vZ2yOVysyueI3s8CYLAgMAf6fERiAqx3i7FnvT29qKhocHpejy5hBkikclkrFG4v78/Ojs7XbbyZzQacfPNNyMzMxOPPvqoS39XeRwGLwC5gLlo3nrrrXjhhRdGCcD169ejoqJi3N8sXrwYr7zyCpYuXYq1a9fij3/8I9asWWPvpU8ITdPYsmULdu3ahZycyXuWKIpCSUkJ9u/fj08++QRxcXHIz8/H2rVrndY3bSIYo+PExESIxaY91WyNOSkkXENRFMrLy+Hn5zcj0lzqelR4+FA18rMjcO3SyUV8c3MzFAoFsrKypvX+DqqGcO3/lUBAGfHwEs9R9jLO/D7K5XI0NjYiLy/P5auY5kLTNKRSKaqrq+Hu7s5aN7lSJZckSfzhD39AQkIC/vrXv9r0M/bpp5/irrvuAkmSuOmmm/DQQw/Z7Ll47A4vALlk+fLlZgnArq4uXHbZZaipqQEA7Nu3DydPnsSbb75p9zVPxnRsK2iaRkVFBfbv34/jx48jLCwM+fn5WLdundObRTOGv86U9mAqhUQsFnMylMBgz1xfe0HTNEo6FEgJ94GPu+l+PS63u79v6EViqA/EPkK2D02j0bCVXH9/f6cSgzKZjJ3udhXhwwXMtm96ejr8/f05GSKxJxRF4a677kJISAieeeYZm7ZokCSJlJQUnDhxAjExMVi0aBH27duH9PR0mz0nj10xeUKaWd3NDqa5uRl5eXnw9/fHk08+iYsvvhidnZ2IiYlhfycmJgadnZ0OXKVppnPBIggCWVlZyMrKwuOPP46amhoUFhZi8+bN8Pf3x8aNG7FhwwaEhYU51QWRMbZ2Fu8zBoFAgJCQEISEhICmaQwODqKnpwcNDQ3w9fW1OoXEEbm+9oAgCOTFTlx9ZgZ8aJpGRkYG+1n88EwHRAIC2xZGW/R8FyX/enMTFRWFqKgokCSJ3t5etLe3Q6lU2s3MeCqkUilaW1uRl5c3a6a7gfHiDwB8fHzg4+ODhIQEdoiktrbWoUkkE0FRFP70pz/Bz8/P5uIPAM6cOYPk5GTMmTOcHrN9+3YcOnSIF4AzHF4AmmDlypXo7u4e9/OnnnpqwqzFyMhItLW1ISQkBOfOnUNBQQEqKythqsLqDCcYriEIAmlpadi1axceffRRNDY2orCwEDt37oS7uzs2btyI/Px8REREOPT1y2QyNDU1IS8vz6mb4AmCQGBgIAIDA0HTNJRKJevTN50UEmfP9bUVNE2jqqoK7u7uSE5OHvXZO1LeAwAWC0BTMNFzYrGYreT29PSgtrYWfn5+bCXXnlPW3d3daG9vR25u7qwXf2Px8PBATEwMYmJi2CGS1tbWCYdI7AlFUfjzn/8MgUCAl156yS5r6OzsHLUjEBMTg9OnT9v8eXkcCy8ATfDFF19Y/DceHh5sY/WCBQuQlJSEuro6xMTEoKOjg/29jo4OREVFcbZWZ4QgCCQnJ+Ohhx7Cgw8+iNbWVhQXF+P6668HTdPYsGEDCgoKEBMTY1cx2NnZia6uLsyfP9+lLogEQcDf3x/+/v5ISkpiM29/+eUXuLm5ITw8fNK+JlfM9eUCiqJQUVHB9jqO5d1rc03vi1iJqUouc+NhrwjBrq4udHZ2Ii8vb8bZ2EyGRqOZUvyNRSQSITw8HOHh4aOGSOrq6tgkkpCQELu8jxRFYffu3VCr1di7d6/dBOhsKVTwjGb2nBlsjEwmQ3BwMIRCIZqamlBfX485c+YgODgYfn5++Omnn7BkyRK8//77uPPOOx29XLtBEAQSEhJw77334p577kFXVxeKiorw+9//HlqtFuvXr0d+fr5NhxFomkZzczOUSiXy8vJc2uuOIAj4+vrC19cXc+bMYSdUS0tLTaaQzIRc3+lAkiTKysoQEhKCuLg4k7/j5Wb7z8HISm5ycjIr3s+fPw+RSMQeLy6ncjs7O9Hd3e3yn3VL0Wg0KC0ttUj8jWWseGeSSJqbm+Hh4WHTIRImfamnpwfvvfeeXauPMTExaG9vZ/89GwoVPPwQiMUcOHAAd955J2QyGQIDA5Gbm4vPPvsMRUVFeOyxxyASiSAUCvH4449jw4YNAICzZ8+yNjBr1qzBa6+9NuvvrpgJvQMHDqC4uBj9/f1Yu3YtCgoKkJKSwtn7Q9M0ampqQNM00tLSZvT7zqSQyGQyUBQFHx8fDAwMIC8vz2UNf6eD0WhEaWkpIiIiEB1t/faurdBoNOzxYlJjrB1K6OjogFQqRU5ODi/+OMaWQyQ0TeP5559HbW0tPvjgA7tXbY1GI1JSUvDll18iOjoaixYtwn/+8x9kZGTYdR08NoOfAuZxXnp7e3Hw4EEUFxeju7sbq1evxqZNm5CWljbtO2GSJFFRUcFWy2ay+BtLZ2cnmpub4enpCYqinDaFhGsMBgNKSkoQGxuLiIgIRy/HbJjUGJlMBr1eP+p4mfu5bWtrYxNdZpOptz3E31hGJpFYO0RC0zReffVVnD17Fh999JHD2lOOHz+Ou+++GyRJ4sYbb8QjjzzikHXw2AReAPK4BgMDAzh8+DCKi4vR2tqKlStXYtOmTRZd2AwGA1sFGjmFPRsYm+vLpJBIpVJoNBqnSCGxBTqdjvV1DAsLc/Rypo3RaGSP19DQEIKDg6c0Ch+ZYT0bxV9aWprDfEjNSSKZCJqm8cYbb+Cbb75BYWHhrLLp4bErvADkcT0UCgWOHTuG4uJi1NbWYsWKFSgoKMCCBQsmPLk6g8Gzo2hpaUF/f/+EKRdjU0iCg4MRHh5u1xQSW6DValFSUoKUlBQEBwc7ejmcMdYoPCAgAGKxGMHBweznn+lvzczM5MWfgxmbRMLYN5kaIqFpGm+//TY+/fRTFBcXO7UrAY/LwwtAHtdmaGgIn3zyCYqKilBWVobly5ejoKAAS5YsYcXOuXPn8OKLL+If//jHrJp4nY7R8VhxERgYiPDwcId711kKY/sx06ecKYrCwMAApFIpKy4oigJBELz4c0JG2jf19vaipaUFEokEW7ZsQUxMDN5//30UFxfj0KFDs6pHl8ch8AKQZ+ag1Wpx4sQJ7N+/H7/88gsuvPBCzJ07F2+88Qbee+89zJ8/39FLtBtMrq9QKJz2AI09UkhsgUqlQnl5+aybcqYoClVVVVAqlSAIAp6enuyEqitZHE0HVxB/pmhqasL777+Pzz//HHq9Hnq9HsXFxcjOznb00nhmPrwA5JmZ6PV6PP3003jjjTcQFRWF3NxcFBQU4JJLLpnxPTW2yPUdmULS19fHSQqJLRgcHERVVRWys7Ph4+Pj6OXYDZqmUVdXB4qiMG/ePBAEwdrLyGQy1pR6pB3QTMFVxd9ICgsL8fbbb2Pr1q349NNP0d3djSuvvBIFBQWYP3++S7di8DgtvADkmZns3bsX+/btQ1FREfz8/NiG6u+++w55eXkoKCjAZZddNuMuhvbI9R25jSWXy+1mZDwV/f39qK2tRU5OzqzaPmNi7QAgNTXVpFgYaQdEkiRrV+LqInkmiL9Dhw7h9ddfx7Fjx9h2BZVKhc8++wwHDx5EaWkpPv30U96Dj4dreAE4W9m/fz92796N6upqnDlzBgsXLmT/b8+ePXj77bchFArx6quvYvXq1QCGe+kY78K1a9filVdecbo7U5qm8cQTT6C0tBQffvjhOIFHkiS+//57FBUV4auvvkJmZiYKCgqwcuVKpw2ANxcm19fedicqlYoVF25ubmz8mT0rrb29vWhoaEBOTs6ME/WTwWz1i0QizJ0716zvo16vZ4d+tFqty06AM0M+riz+jh8/jhdeeAHHjx+fcFDJYDBAJBK51LHhcQl4AThbqa6uhkAgwK233ooXXniBFYBVVVXYsWMHzpw5A4lEgpUrV6Kurg5CoRCLFy/GK6+8gqVLl2Lt2rX44x//iDVr1jj4lYymvLwce/fuxd/+9rcptyYpisLp06dRWFiIEydOYO7cudi0aRNWrVrlct54zpLry6SQyGQyCAQCttJkS1EmlUrR0tKC3NzcGb+9PxIm09jDwwNJSUnTEghj7UqCg4NZuxJnFhyM+HPlIZ8TJ07gqaeewvHjx2dVFjeP08ALwNnO8uXLRwnAPXv2AAAefvhhAMDq1auxe/duJCQk4LLLLkNNTQ0AYN++fTh58iTefPNNxyycYyiKwvnz57F//358+umniI+Px8aNG7F27Vqnry44a67v2BQSLlMSGJh8W8bfcLZAURQqKyvh4+ODOXPmcPaYzAT44OAgO/TDxFk6CzNB/J08eRKPPfYYjh07hvDwcEcvh2d2YlIA8lnAs5jOzk4sXbqU/XdMTAw6Ozvh5uY2yjyZ+flMQSAQYMGCBViwYAGefvppVFRUYP/+/Vi/fj3Cw8OxceNGrF+/3un85Jhc36ysLKerWnp6eiIuLg5xcXHQ6/WQyWSoqamBwWBgxaA1a25vb4dMJpt1+bYURaGiooId8uEKgUCA0NBQhIaGskM/UqkUDQ0N8PHxYfs87R1JNpKZIP6+++47PProo7z443FKeAE4Q1i5ciW6u7vH/fypp55Cfn6+yb8xVf0lCGLCn89EBAIBsrOzkZ2djb/+9a+orq5GYWEhrrrqKgQEBCA/Px8bNmxAaGioQ9+Dvr4+1NXVITc31+mHHtzd3REdHY3o6Gg2haSxsXHaKSQtLS0YGBhAbm6uU1vScA1FUSgrK0NQUBDi4+Nt9jwEQSAwMBCBgYGgaZrt82xtbYW7uzsr4O255T4TxN9PP/2EBx98EEePHkVkZKSjl8PDMw5eAM4QvvjiC4v/JiYmBu3t7ey/Ozo6EBUVhZiYGHR0dIz7+UyHIAikp6fjsccew65du9DQ0ICioiLs2LEDHh4e2LhxI/Lz8xEeHm5XMcj0veXl5cHDw8Nuz8sFbm5uiIyMRGRkJJtC0traalYKCU3TrHCcbfm2JEmirKwMoaGhNpvwNgVBEPDz84Ofnx+SkpLYPs/S0lIQBMGKQVvehMwE8Xf27Fncc889OHz48KyLouRxHfgewFnE2B7AyspK7Ny5kx0CWbFiBerr6yEUCrFo0SK89tprWLJkCdauXYs777wTa9eudfArcAw0TaO1tRVFRUU4cOAACILAhg0bUFBQgOjoaJuKwc7OTnR1dc24vjeKotiBBCaFRCwWs/mpjNcdSZJIS0ubsRVoU5AkidLSUojFYqcSDzqdDjKZDFKpFEajka3m+vj4cHZ8ZoL4Kykpwe9//3scOHAASUlJjl4ODw/AD4HMXg4cOIA777wTMpkMgYGByM3NxWeffQZgeIv4nXfegUgkwssvv8xO+p49e5a1gVmzZg1ee+21WXURngiapiGRSFgxqNPpsH79euTn5yMhIYHT92iqXN+ZAhNx1tPTg4GBAfj5+UGn08HX13faySauCkmSKCkpQWRkpFNX3ZmtfalUCo1Gg5CQEIjFYvj7+0/7eM0E8VdRUYGbbroJ+/fvR2pqqqOXw8PDwAtAHh4uoWkaUqkUxcXFKC4uxuDgINauXYuCggKzfdomelxLc31nCiRJ4vz586AoCiRJOm0KiS0wGo0oKSlBdHS0S/WMkSTJVnOVSuW4aq45zATxV11djRtuuAH79u1DRkaGo5fDwzMSXgDy8NgSuVyOgwcPori4GFKpFKtXr8amTZss2sLkItfXVWH63oKDgxEfHz8uhcTT0xPh4eEOTyGxBQaDASUlJYiLi3PpaVEmU1omk6G/vx9+fn5spvREAp4Rf6mpqQgKCrLzirmhvr4e11xzDf7973/z2b48zggvAHl47EV/fz+OHDmCoqIitLW14YorrsCmTZuQlZU1YVXEFrm+roLRaERpaSnCw8Mn7HtjplPlcjlEIpFDUkhsgcFgwPnz55GQkACxWOzo5XAGTdNQKBSQSqXo7e01GSM4E8Rfc3MzduzYgffeew/z58939HJ4eEzBC0AeHkegUChw7NgxFBUVob6+HitWrEB+fj4WLFjAisH+/n7ccccdeOKJJzgz+3UVmOpXTEyM2VufjkghsQV6vR4lJSVITExEWFiYo5djM2iahlqtHiXgg4KC0NXVhbS0NJcVf21tbdi2bRv27t2LxYsXO3o5PDwTwQtAHh5HMzQ0hOPHj6OwsBCVlZVYvnw5Lr30UuzevRu33HILbrrpJkcv0a5wIYC0Wi07nWqrFBJboNPpUFJSguTkZISEhDh6OXZlcHAQpaWlcHd3h1AodJljNpLOzk5s2bIFr7/+Oi666CKbPc/u3buxd+9e9vvx9NNPs44ME2W58/CMgReAPDzOhFarxYcffoiHHnoISUlJyM3NRUFBAS644AKHJjDYC2b7b+7cuZwJICaFpKenZ1QKCZdWJVzAvPaUlBSnS5yxNYzwTUlJQVBQEHvMpFIp9Ho9ay/j6+vrVMdsJN3d3di8eTNeeuklLF++3KbPtXv3bvj6+uJPf/rTqJ9PluXOwzMGPgqOh8eZaGlpweuvv47Dhw9jwYIF+PLLL7F//37cd999WLp0KQoKCnDJJZfMuIEHYLgSWlZWxvnUJ9cpJLZgJvS9TRedTofz58+Peu0jj5nRaIRcLkdzczPUajWCg4MhFosRGBjoNGJQKpViy5YtePbZZ20u/ibj0KFD2L59Ozw8PJCYmIjk5GScOXMGy5Ytc9iaeFyL2eMvwePS7N69G9HR0cjNzUVubi6OHz/O/t+ePXuQnJyM1NRU1t/Q2Tl79iy2b9+ODz74AMuWLYO7uzvWrFmDt99+GyUlJdixYweOHTuGCy+8EL///e/x6aefQqfTOXrZnKBSqVBaWor09HSbWn4wKSQ5OTlYtGgR/Pz80Nraip9++gm1tbUYGBgwGXtoSzQaDWt3MhvF38jKnylEIhEiIiKQnZ2NJUuWIDg4GBKJBD/99BOqqqogl8tBUZSdV/4rvb292LJlC5544glcccUVdnve119/HdnZ2bjxxhvR398PYHgLemRKzEzLbOexPfwWMI9LMJO2QbRaLa688kq8++67SExMnPR3SZLE999/j8LCQnz99dfIyspCQUEBVq5c6fSZwKZQKBSorKxEVlYWfH19HbKGqVJIbAVT9UxLS0NAQIDNnscZYcTf3Llzp7XlTdM0BgYGIJVK0dfXx/pDhoSE2K1dor+/H1dffTX+/Oc/Y+PGjZw+9mRZ7kuXLmWzyHft2oWuri688847uP3227Fs2TL89re/BQD87ne/w9q1a3H11VdzujaeGQG/Bcwz83DFbRBPT0989dVXZokNoVCISy+9FJdeeikoisJPP/2EwsJCPPnkk0hNTUVBQQFWrVrlMDFlCQMDA6ipqUFOTo5Dm/2ZqeGwsDA2hUQqlaKurg7+/v6ssOBSDKrVapSVlSEzMxN+fn6cPa4rYK34A4YzioOCghAUFDTKH7K5uRkeHh6sP6StLIEGBwexdetW3H///ZyLP8D8LPebb74Z69evBzBxljsPj7nwApDHZXj99dfx/vvvY+HChXjxxRcRFBSEzs5OLF26lP0dV9kGmY64EAgEuOCCC3DBBReAoij88ssv2L9/P55//nkkJiZi48aNWLt2Lfz9/W2wYuvo7e1FQ0MDcnNzncqqRSAQIDg4GMHBwaBpGoODg5BKpWhoaICPjw8rLKypKKtUKpSXlzu06ukouBB/YyEIAv7+/vD390dycjJrL1NaWmoTSyClUolt27bhjjvucEh1rauri7VHOnDgADIzMwEAGzduxM6dO3HvvfdCIpGgvr6et6LhsQheAPI4DZNtg9x2223YtWsXuw1y33334Z133jHZw+UszeK2RCAQYOHChVi4cCH27NmD8vJy7N+/H+vWrUNERAQ2btyI9evXO0WfmVQqRUtLC/Ly8pzatJkgCAQGBiIwMHBclWm6KSRKpRIVFRXIzs6Gj4+PDVfvfNhC/JnCx8cHiYmJSExMZC2BKisrQZLkqCnw6aBWq7Fjxw7cdNNN2LFjB8crN48HHngAJSUlIAgCCQkJePPNNwEAGRkZ2Lp1K9LT0yESifD3v//dqVtfeJwPvgeQx+VoaWnB+vXrUVFRgT179gAAHn74YQDA6tWrsXv3bqfeArYlTJRcYWEhjh49isDAQOTn52P9+vUOMRru6upCR0cHcnNzXXqaeTopJAqFAlVVVcjKypp14k+v1+P8+fM2F3+TYTAYWHsZrVaL0NBQhIWFwd/f36ybRI1Gg23btmH79u2zzp+TZ8bB+wDyuC4jt0H+9re/4fTp0/joo49QWVmJnTt3skMgK1asQH19PX8njGEx2NDQgMLCQhw+fBheXl7YuHEjNm7ciPDwcJtXSjs6OiCVSpGdnT2jfA01Gg16enogk8lAEAQrBkduOQ4ODqK6uho5OTkuOaxjDYz4cyaDa5IkIZfLIZPJoFQqERQUxNrLmGrH0Gq12LlzJzZu3IjbbrttVuwq8MxoeAHI47pcc80147ZBGEH41FNP4Z133oFIJMLLL7+MNWvWOHi1zgdN02hpaUFRUREOHjwIgUCADRs2oKCgAFFRUZxf4FpbW9Hf34+srKwZLcZNpZB4enqipaWFF39OIv7GQlEU+vv7IZVKMTAwAH9/fzQ1NeHyyy+Hj48P9Ho9rrnmGqxYsQJ33XUXL/54ZgK8AOTh4RkWg52dnSgqKsKBAweg1+uxfv165OfnIyEhwaoLHk3TaGpqglqtRmZmpk1tVZwNvV6PlpYWdHR0wMvLC2KxGOHh4U6XQmIrXEH8jYWmafT392PXrl34/vvvERcXB4qisHz5cjz22GOz4rjxzAp4AcjDwzMamqbR09OD4uJiFBcXQ6FQYN26dSgoKEBycrJFF0CaplFfXw+j0Yi0tLRZd/EcOeksEAggl8shlUqh0WgQEhKC8PBwh6eQ2ApXFH9j0ev1uOmmmzA4OAiFQoHg4GBcddVVbMsED48LwwtAHh6eyZHJZDh48CCKi4shk8mwZs0a5OfnTynomOEToVCIlJSUGSlyJkMul6OpqQm5ubnjBkOY/jOpVAqVSuWU8WbWMBPEH0mSuO2225CYmIi//vWvIAgCTU1NOHjwIA4dOgQAuPPOO7F582YHr5SHZ1rwApCHh8d8+vv7cfjwYRQVFaG9vR2rVq3Cpk2bxm3t6vV67N27F1deeSXmzJkzI0SNJTA2N6bE31goikJfXx96enrsmkJiK2aC+KMoCn/84x8RFhaGPXv2mDwOPT09kEqlyMrKcsAKeXishheAPDw800OhUODo0aMoKipCQ0MDVq5cyVYGN2/ejEWLFuGvf/2ro5dpd3p6etDW1jYtm5uRKST9/f1sCklwcLBLDM7o9XqUlJQgKSnJpcXffffdBy8vL7z00ksuKcJ5eMyAF4A8PDzWo1Kp8Mknn+Cjjz7CDz/8gGXLluGOO+7A4sWLXUK4cEV3dzfrcWitzc3IFJLe3l42hcSeWbeWMFPE38MPPwySJPH666/z4o9nJsMLQB4eHm4YHBxEfn4+rrvuOgQHB6OwsBDnz5/HxRdfjPz8fFxwwQVOKVy4QiKRoKurCzk5OZy/TpqmoVKp0NPTA7lcDk9PT4jFYoSFhTmFmTYj/ubMmYPQ0FBHL2daUBSF3bt3Y2BgAG+99RYv/nhmOrwA5OFxBJ9++inuuusukCSJm266CQ899JCjl2QVcrkcGzduxP33349NmzaxP9fpdPjyyy9RWFiI06dPY9myZSgoKMDFF1/sFMKFKzo7O9HT04OcnBy7VDynk0JiK2aC+KNpGk899RQ6Ojrw7rvvzqqqNc+shReAPDz2hiRJpKSk4MSJE4iJicGiRYuwb98+pKenO3pp06Kvrw9XXnklnnzySaxatWrC3zMYDDh58iSKiorw3XffYeHChSgoKMDy5cvh4eFhxxVzS3t7O+RyObKzsx0iHMxJIbEVM0X8Pf/886itrcUHH3wwo6vUPDwj4AUgD4+9+fHHH7F792589tlnADAuu9jVoCgKNTU1FglYo9GI77//HoWFhTh58iSys7NRUFCAFStWuFRSRltbG/r6+pCdne0UW4YjU0hIkmTFoLe3N+fPZTAYcP78eZcXf6+88gp++eUX7Nu3b0ZVpXl4psCkAORvf3h4bEhnZydiY2PZf8fExOD06dMOXJF1CAQCi6uXIpEIy5cvx/Lly0GSJH766ScUFhbiySefRGpqKgoKCrBq1Sr4+PjYaNXW09LSgsHBQacRfwDg6emJ2NhYxMbGQq/XQyaToba2Fnq9HqGhoZylkMwU8ffPf/4Tp0+fxv79+3nxx8MDXgDy8NgUUxX22eaTNxKhUIgLL7wQF154ISiKwrlz57B//348//zzSExMxMaNG7FmzRr4+/s7eqksTLRdVlaW04i/sbi7uyM6OhrR0dEwGAyQy+VobGxkU0jEYjH8/f0t/uwx4i8xMdGlxd/bb7+Nr776CgcOHHBI7yQPjzPCC0AeHhsSExOD9vZ29t8dHR2Iiopy4IqcB4FAgEWLFmHRokV45plnUFZWhsLCQqxduxaRkZHIz8/HunXrEBQU5JD10TSNxsZGaLVaZGZmuoxwd3NzQ2RkJCIjI0GSJHp7e9HW1mZxCslI8RcWFman1XPP+++/j6NHj+LQoUMu3X/Kw8M1fA8gD48NMRqNSElJwZdffono6GgsWrQI//nPf5CRkeHopTktNE2jqqoKhYWFOHr0KIKDg5Gfn4/169fbrQpF0zQaGhpgMBhmTK4xk0IilUoxODg4aQrJTBF/H374Ifbt24ejR4/apDeSh8dF4IdAeHgcwfHjx3H33XeDJEnceOONeOSRRxy9JJeBpmnU19ejsLAQR44cgZeXF/Lz87FhwwaEh4fbRJjRNI26ujpQFIV58+bNCPE3lrEpJH5+fggPD0dwcDAoipoR4m///v145513cOzYMfj6+jp6OTw8joQXgDw8PK4LTdNobm5GUVERDh48CKFQiI0bNyI/Px9RUVGcCDWaplFTUwOBQICUlJQZKf7GMjKFRC6XQ6/XIzo6GomJiS5rk3Lo0CH8/e9/x7FjxxAQEMDZ4+7fvx+7d+9GdXU1zpw5g4ULF7L/t2fPHrz99tsQCoV49dVXsXr1agDAuXPncP3110Oj0WDt2rV45ZVXZsXnisep4AUgDw/PzICmaXR0dKCoqAgHDhyA0WjE+vXrkZ+fj/j4+GldYGmaRnV1Ndzc3JCcnDzrLtIGgwG//PILIiIi2EESZ0shMYfjx4/jxRdfxLFjxxAcHMzpY1dXV0MgEODWW2/FCy+8wArAqqoq7NixA2fOnIFEIsHKlStRV1cHoVCIxYsX45VXXsHSpUuxdu1a/PGPf8SaNWs4XRcPzxTwNjA8PDwzA4IgEBsbi7vvvht33XUXuru7UVxcjDvvvBMqlQrr1q1Dfn6+2UKOpmlUVlbC09MTSUlJs1L8lZSUIDExEWKxGACQnJwMtVoNqVSK8+fPOzyFxBxOnDiB5557DsePH+dc/AFAWlqayZ8fOnQI27dvh4eHBxITE5GcnIwzZ84gISEBCoUCy5YtAwBce+21OHjwIC8AeZwCXgDy8PC4NARBIDIyErfffjtuv/12yGQyHDx4EA8++CDkcjnWrl2L/Pz8Cfv5jEYjqqur4ePjgzlz5jjgFTgWRvzFx8ez4o/Bx8cHiYmJSExMhEajgVQqRWlpqd1TSMzh66+/xhNPPIHjx4/b3bKms7MTS5cuZf8dExODzs5OuLm5ISYmZtzPeXicAV4A8vDwzCjCwsJw88034+abb0ZfXx8OHz6M3bt3o7OzE6tWrcKmTZuQkZEBgUAArVaLzZs345ZbbsHGjRsdvXS7M5n4G4uXlxfi4+MRHx8PnU4HqVSKyspKm6eQmMN3332HXbt24dixY1O+jqlYuXIluru7x/38qaeeQn5+vsm/mcjvk/cB5XFmeAHIw8MzYwkODsb111+P66+/HoODgzh69CieffZZNDY24rLLLsPp06dx6aWX8uLPQtHk4eFhlxQSc/jxxx/x4IMP4ujRo4iMjLT68b744guL/2Yiv8+YmBh0dHSM+zkPjzPgnLb2PDw8PBwTEBCA3/zmNyguLsYXX3yBb7/9FkKhEMePH8fDDz+Mn376CSRJOnqZdsEa8TcWJoUkLy8PCxYsgLe3NxobG3H69GnU19djcHDQZCWMC86ePYt7770Xhw4dGrXVam82btyIjz76CDqdDs3Nzaivr8fixYsRGRkJPz8//PTTT6BpGu+///6EVUQeHnvDTwHz8PDMKoaGhrBp0yZs2bIFN910EzQaDT777DMUFRXh/PnzuPjii1FQUIBly5a5rA3KZHAp/iaDSSGRSqVQKpUWpZCYQ0lJCX7/+9/j4MGDduvdPHDgAO68807IZDIEBgYiNzcXn332GYDhLeJ33nkHIpEIL7/8MjvocfbsWdYGZs2aNXjttdf4bWAee8PbwPDw8ExNQkIC/Pz8IBQKIRKJcPbsWfT19WHbtm1oaWlBQkICPv74Y4dFtFmDSqVCQUEBrrnmGlx33XXj/l+n0+GLL75AYWEhzpw5gwsuuAAFBQW46KKLXMYGZTKMRiPOnz9vc/E3lrEpJAEBAQgPDzeZQmIOFRUVuOmmm7B//36kpqbaYMU8PDMKXgDy8PBMTUJCAs6ePTtqkvKBBx5AcHAwHnroITzzzDPo7+/Hs88+68BVTo+XXnoJkZGR2LFjx5S/azAYcPLkSRQWFuL777/HokWLUFBQgOXLlzutDcpkMOIvLi4O4eHhDluHqRQSsViMkJAQCIXCKf++uroaN9xwAz766COkp6fbYcU8PC4PLwB5eHimxpQATE1NxcmTJxEZGYmuri4sX74ctbW1DlylfTEajfj++++xf/9+fPPNN8jJyUFBQQFWrFjhNDYok+Es4m8sI1NIent74ePjA7FYjNDQUJPb73V1dbj22mvx73//G9nZ2Q5YMQ+PS8ILQB4enqlJTExEUFAQCILArbfeiltuuQWBgYEYGBhgfycoKAj9/f2OW6QDIUkSP/74IwoLC/Hll18iLS0N+fn5WLVqFXx8fBy9vHE4q/gbC03TUKlU6OnpYSPpysrKsG3bNoSFhaG5uRk7duzAe++9h/nz5zt6uTw8rgQvAHl4eKZGIpEgKioKUqkUV1xxBV577TVs3LiRF4AmoCgKZ8+exf79+/H5558jKSkJGzduxJo1a+Dn5+fo5bmM+DNFR0cH/vGPf+DEiRPw8vLC4OAgXn31VT5Fg4fHcngByMPDYxm7d++Gr68v9u7dO6u3gM2BoiiUlpaisLAQn3zyCaKiopCfn49169YhMDDQ7usxGo0oKSlBbGysy4m/kXR2duKaa67BokWLUFZWBoIgsGnTJmzatAlxcXGOXh4PjyvAC0AeHp7JUavVoCgKfn5+UKvVuOKKK/DYY4/hyy+/REhICDsE0tfXh+eee87Ry3VamGzhwsJCHDt2DMHBwSgoKMC6devsElM2U8Rfd3c3Nm/ejJdeegnLly8HAHR1deHgwYM4cOAAVCoV/vKXv2D16tWOXSgPj3PDC0AeHp7JaWpqwqZNmwAMi4idO3fikUceQW9vL7Zu3Yq2tjbExcVh//79CA4OdvBqXQOaplFXV4fCwkIcOXIE3t7eKCgowIYNGyAWizn3hGPEX0xMDCIiIjh9bHsilUpx9dVX49lnn8XKlStN/k5vby+0Wi2io6PtvDoeHpeCF4A8PDw8joSmaTQ1NaGoqAgHDx6Em5sbNv5/e/cXU3X9x3H8df4gtWFz2LCTx1YdGiTgwBZCjewP/j+cg1LoySIhG1rTG5hZhxW0GLPVldlmm216EW7nHMW1tVi1mFkrxEkbsQEFpsAxZaA2MgLO6aL9zm/9pF+k4IHzfT6u3Pd8hLfOP899/31cLrndbtlsthuOwViJv4GBARUVFemNN97gnj/gxhGAADBThMNh9fb2yu/3q6GhQWNjY3I6nVq/fr0WLVr0r2MwVuJvaGhIGzZskNfrNeQezcA0IAABYCYKh8MKBoM6cuRI5N42p9Mpt9sth8PxjzEYK/F3+fJlFRUVqaKiQkVFRdEeB4gVBCAAzAYXLlxQQ0ODAoGABgcHtXbtWrlcLqWmpl4Tg5cuXVJLS4vS09Nndfz98ssvevLJJ/XSSy9p06ZN0R4HiCUEIADMNoODgzp27JgCgYD6+/u1atUqFRYWKi0tTVeuXJHT6VR5ebmeffbZaI963YaHh1VcXKzS0lKVlJREexwg1hCAADCbXb58WR999JECgYB++OEHjY6OasOGDXr11VdlNpujPd51uXr1qjZu3CiPx6Pnn38+2uMAsYgABIBYMDw8rHXr1ikjI0Pnz59XR0eHHn/8cbndbj344IOzJgZ/++03Pf3003K73dq2bduUvxIHgKS/CcDZ8a8EAEygrKxMSUlJSk9PjxwbHBzUihUrdN9992nFihV/2bKurq5OycnJSklJUWNjYzRGvmHDw8Nyu93aunWr9u7dK5/Pp2+//VbLly/XgQMHlJOTo8rKSp04cULj4+PRHvdv/f7773ruuee0Zs0a4g+IAs4AApi1jh8/roSEBJWUlKitrU2StGvXLiUmJkZ2LRkaGtKePXvU3t4uj8ej5uZm9ff3Kz8/X52dnbJYLFH+VUzef+Jvy5YteuaZZyZcMzIyok8//VR+v18nT57UQw89pPXr1+vhhx9WXFzcTZ54YqOjoyotLVVubq4qKyuJP2B6cQkYQOw5c+aMnE5nJABTUlIm3Le4rq5OkvTKK69IklatWqXq6mrl5uZGbfZ/6/Tp02pvb9fmzZsntX50dFRffPGF/H6/vvrqK2VnZ8vtduvRRx/VnDlzpnnaiY2NjWnr1q1asmSJvF4v8QdMvwn/kllv9hQAMJ1+/vln2Ww2SZLNZtOFCxckSX19fcrJyYmss9vt6uvri8qM1ysrK0tZWVmTXh8XF6eVK1dq5cqVGhsb05dffimfz6eqqiplZmbK7XbriSee0C233DKNU//X+Pi4XnzxRaWmphJ/QJRxDyAAQ5joaoeRAsRqteqxxx7Te++9p++++07l5eU6ceKEli9frtLSUjU0NOjXX3+dtu8/Pj6unTt3auHChaqurp7S33ufz6e0tDSZzWa1tLREjp85c0a33nqrMjMzlZmZqW3btkU+O3XqlDIyMpScnKydO3dO+OcDiGWcAQQQUxYsWKBgMBi5BJyUlCTpzzN+586di6zr7e3VnXfeGa0xo8pisSgvL095eXkKhUI6efKkfD6f9uzZI4fDIbfbrdWrV2vu3LlT8v1CoZAqKio0b9481dXVTflTyunp6Tpy5IjKy8uv+czhcKi1tfWa49u3b9f777+vnJwcrV27Vp988gn7DsNQOAMIIKa4XC4dPHhQknTw4EG53e7I8cOHD2tkZEQ9PT3q6upSdnZ2NEedEcxms5YtW6a3335bp0+fVlVVlTo6OrR69Wpt3LhRH374oS5dunTdXz8UCmn37t2Ki4vTO++8My2vqLn//vuVkpIy6fXBYFBXrlxRbm6uTCaTSkpK1NDQMOVzATMZZwABzFoej0dNTU0aGBiQ3W5XTU2Ndu/ereLiYh04cEB33XWXfD6fJCktLU3FxcVavHixrFar9u3bN6ueAL4ZzGazli5dqqVLl6q2tlZtbW3y+/1yuVy6/fbbVVhYqHXr1mn+/PmT+nqhUEivv/66RkZGtH///qi8n7Cnp0dZWVm67bbb9OabbyovL099fX2y2+2RNbPxflDgRhGAAGat+vr6CY9//vnnEx73er3yer3TOVLMMJlMysjIUEZGhqqrq9XR0SG/36+nnnpKCQkJcrlcKigoUFJS0oT384XDYdXW1mpgYEAffPDBDcdffn6+zp8/f83x2trayFne/2Wz2XT27FnNnz9fp06dUmFhob7//nvD3w8KSAQgAOAfmEwmpaamqqqqSl6vV93d3fL7/dq8ebPmzJmjgoICFRYW6o477pDJZFI4HNZbb72ln376SYcOHZqSM62fffbZv/458fHxio+PlyQ98MADcjgc6uzslN1uV29vb2Sdke8HhXERgACASTOZTHI4HHr55Ze1a9cunT17VoFAQKWlpQqFQnI6nRocHFR3d7fq6+tltUbvv5mLFy8qMTFRFotF3d3d6urq0r333qvExETNnTtX33zzjZYtW6ZDhw5px44dUZsTiAZeBA0AuGHhcFjBYFD19fWqr6/X119/fdNeNn306FHt2LFDFy9e1Lx585SZmanGxkYFAgG99tprslqtslgsqqmpUUFBgSSppaVFW7Zs0dWrV7VmzRrt3buXy8CIVewEAgAAYDATBiCvgQEAADAYAhAAAMBgCEAAAACDIQABIIrKysqUlJSk9PT0yLHq6motXLgwsoftxx9/HPmsrq5OycnJSklJUWNjYzRGBhADeAgEAKLo+PHjSkhIUElJidra2iT9GYAJCQmqrKz8y9r29nZ5PB41Nzerv79f+fn56uzsZEcTAP8PD4EAwEzzyCOPKDExcVJrjx07pk2bNik+Pl733HOPkpOT1dzcPM0TAohFBCAAzEDvvvuulixZorKyMg0NDUmS+vr6tGjRosga9rAFcL0IQACYYbZv364ff/xRra2tstlsqqiokCT2sAUwZQhAAJhhFixYIIvFIrPZrBdeeCFymddut+vcuXORdexhC+B6EYAAMMMEg8HIj48ePRp5Qtjlcunw4cMaGRlRT0+Purq6lJ2dHa0xAcxi0dulGwAgj8ejpqYmDQwMyG63q6amRk1NTWptbZXJZNLdd9+t/fv3S5LS0tJUXFysxYsXy2q1at++fTwBDOC68BoYAACA2MVrYAAAAEAAAgAAGA4BCAAAYDAEIAAAgMEQgAAAAAZDAAIAABgMAQgAAGAwBCAAAIDBEIAAAAAGQwACAAAYDAEIAABgMAQgAACAwRCAAAAABkMAAgAAGAwBCAAAYDAEIAAAgMEQgAAAAAZDAAIAABgMAQgAAGAwBCAAAIDBEIAAAAAGQwACAAAYDAEIAABgMAQgAACAwRCAAAAABkMAAgAAGIz1Hz433ZQpAAAAcNNwBhAAAMBgCEAAAACDIQABAAAMhgAEAAAwGAIQAADAYAhAAAAAg/kDMIBcELNok4QAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1% errors on parameters" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1% error on focal length" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [], + "source": [ + "param_error = 0.01\n", + "focal_length2 = focal_length*(1+param_error) # np.random.normal(focal_length, focal_length*param_error)\n", + "principle_point2 = principle_point#*(1+param_error) # np.random.normal(principle_point, principle_point*param_error)\n", + "radial_distortion2 = radial_distortion#*(1+param_error) # np.random.normal(radial_distortion, np.abs(radial_distortion)*param_error)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:24.608593769035938 max: 611.3982243689502\n", + "image 1 reprojection errors: average:25.22544332715471 max: 495.0297124939188\n", + "image 2 reprojection errors: average:25.22786374138796 max: 513.9932784446748\n", + "image 3 reprojection errors: average:24.03060745916949 max: 330.44036295317017\n", + "image 4 reprojection errors: average:26.61895385961153 max: 419.4486744329757\n", + "image 5 reprojection errors: average:29.342917584909316 max: 652.9085253560725\n", + "image 6 reprojection errors: average:30.642017945278138 max: 365.20604851963196\n", + "image 7 reprojection errors: average:25.726036338857043 max: 525.6435080715578\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.9460e+06 1.97e+07 \n", + " 1 2 2.6607e+05 5.68e+06 6.70e+01 2.22e+06 \n", + " 2 3 1.9425e+05 7.18e+04 1.95e+00 9.54e+04 \n", + " 3 4 1.9402e+05 2.30e+02 2.67e-01 4.77e+03 \n", + " 4 5 1.9398e+05 3.81e+01 2.28e-01 2.59e+03 \n", + " 5 6 1.9396e+05 2.44e+01 7.72e-02 5.29e+02 \n", + " 6 7 1.9395e+05 8.95e+00 6.16e-02 3.23e+02 \n", + " 7 8 1.9394e+05 7.28e+00 3.17e-02 3.34e+02 \n", + " 8 9 1.9394e+05 4.56e+00 3.19e-02 2.23e+02 \n", + " 9 10 1.9394e+05 3.52e+00 1.84e-02 2.28e+02 \n", + " 10 11 1.9393e+05 3.62e+00 2.94e-02 2.35e+02 \n", + " 11 12 1.9393e+05 3.43e+00 1.77e-02 2.17e+02 \n", + " 12 13 1.9393e+05 3.55e+00 3.01e-02 2.54e+02 \n", + " 13 14 1.9392e+05 3.35e+00 1.69e-02 2.10e+02 \n", + " 14 15 1.9392e+05 2.56e+00 2.19e-02 2.10e+02 \n", + " 15 16 1.9392e+05 2.43e+00 1.37e-02 1.97e+02 \n", + " 16 17 1.9391e+05 2.26e+00 1.97e-02 2.07e+02 \n", + " 17 18 1.9391e+05 2.16e+00 1.25e-02 1.87e+02 \n", + " 18 19 1.9391e+05 2.10e+00 1.87e-02 2.16e+02 \n", + " 19 20 1.9391e+05 1.99e+00 1.15e-02 1.75e+02 \n", + " 20 21 1.9391e+05 1.65e+00 1.50e-02 1.85e+02 \n", + " 21 22 1.9391e+05 1.63e+00 1.03e-02 1.73e+02 \n", + " 22 23 1.9390e+05 1.66e+00 1.52e-02 1.57e+02 \n", + " 23 24 1.9390e+05 1.62e+00 1.01e-02 1.92e+02 \n", + " 24 25 1.9390e+05 1.61e+00 1.49e-02 1.40e+02 \n", + " 25 26 1.9390e+05 1.57e+00 9.77e-03 2.01e+02 \n", + " 26 27 1.9390e+05 1.58e+00 1.49e-02 1.62e+02 \n", + " 27 28 1.9390e+05 1.55e+00 9.54e-03 2.04e+02 \n", + " 28 29 1.9389e+05 1.56e+00 1.49e-02 1.66e+02 \n", + " 29 30 1.9389e+05 1.53e+00 9.35e-03 1.96e+02 \n", + " 30 31 1.9389e+05 1.52e+00 1.48e-02 1.69e+02 \n", + " 31 32 1.9389e+05 1.48e+00 9.08e-03 1.87e+02 \n", + " 32 33 1.9389e+05 7.84e-01 7.04e-03 1.66e+02 \n", + " 33 34 1.9389e+05 5.10e-01 3.19e-03 9.23e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 34, initial cost 5.9460e+06, final cost 1.9389e+05, first-order optimality 9.23e+01.\n", + "mean reprojection error: 5.340241200036941\n", + "max reprojection error: 28.42645205506381\n", + "mean reconstruction error: 0.6470568340568422\n", + "max reconstruction error: 1.8098730751559247\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:24.921566574338737 max: 305.75351838229716\n", + "image 1 reprojection errors: average:23.390754601939754 max: 214.4986553903816\n", + "image 2 reprojection errors: average:26.597163482749533 max: 651.4108094154385\n", + "image 3 reprojection errors: average:23.67992783588362 max: 469.36928731035107\n", + "image 4 reprojection errors: average:24.889145873481695 max: 341.69315064879\n", + "image 5 reprojection errors: average:29.225872165518457 max: 355.10681524367556\n", + "image 6 reprojection errors: average:30.541867184210144 max: 355.0493556668815\n", + "image 7 reprojection errors: average:26.24650626628893 max: 504.1525828204977\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.5667e+06 1.76e+07 \n", + " 1 2 2.6121e+05 5.31e+06 6.81e+01 1.43e+06 \n", + " 2 3 2.2075e+05 4.05e+04 1.68e+00 6.96e+04 \n", + " 3 4 2.2058e+05 1.65e+02 4.21e-01 1.35e+04 \n", + " 4 5 2.2055e+05 3.21e+01 1.03e-01 1.91e+03 \n", + " 5 6 2.2053e+05 1.69e+01 8.98e-02 1.29e+03 \n", + " 6 7 2.2052e+05 1.34e+01 5.44e-02 3.75e+02 \n", + " 7 8 2.2051e+05 6.82e+00 3.40e-02 6.28e+02 \n", + " 8 9 2.2051e+05 6.38e+00 3.61e-02 3.46e+02 \n", + " 9 10 2.2050e+05 6.01e+00 3.14e-02 4.89e+02 \n", + " 10 11 2.2050e+05 3.82e+00 2.04e-02 2.21e+02 \n", + " 11 12 2.2049e+05 3.84e+00 2.53e-02 5.40e+02 \n", + " 12 13 2.2049e+05 3.48e+00 1.82e-02 2.08e+02 \n", + " 13 14 2.2049e+05 3.40e+00 2.36e-02 5.70e+02 \n", + " 14 15 2.2048e+05 3.19e+00 1.68e-02 1.95e+02 \n", + " 15 16 2.2048e+05 3.23e+00 2.34e-02 6.01e+02 \n", + " 16 17 2.2048e+05 2.65e+00 1.33e-02 1.46e+02 \n", + " 17 18 2.2048e+05 2.66e+00 2.14e-02 5.38e+02 \n", + " 18 19 2.2047e+05 2.57e+00 1.30e-02 1.43e+02 \n", + " 19 20 2.2047e+05 2.63e+00 2.18e-02 3.88e+02 \n", + " 20 21 2.2047e+05 2.53e+00 1.27e-02 1.38e+02 \n", + " 21 22 2.2047e+05 2.58e+00 2.20e-02 3.69e+02 \n", + " 22 23 2.2046e+05 2.49e+00 1.25e-02 1.32e+02 \n", + " 23 24 2.2046e+05 2.53e+00 2.23e-02 3.69e+02 \n", + " 24 25 2.2046e+05 2.43e+00 1.23e-02 1.25e+02 \n", + " 25 26 2.2046e+05 1.93e+00 1.72e-02 2.86e+02 \n", + " 26 27 2.2045e+05 1.91e+00 1.08e-02 1.37e+02 \n", + " 27 28 2.2045e+05 1.95e+00 1.75e-02 2.78e+02 \n", + " 28 29 2.2045e+05 1.90e+00 1.05e-02 1.57e+02 \n", + " 29 30 2.2045e+05 1.86e+00 1.69e-02 2.58e+02 \n", + " 30 31 2.2045e+05 1.81e+00 1.00e-02 1.78e+02 \n", + " 31 32 2.2045e+05 1.79e+00 1.64e-02 2.55e+02 \n", + " 32 33 2.2044e+05 1.75e+00 9.48e-03 1.94e+02 \n", + " 33 34 2.2044e+05 1.76e+00 1.62e-02 2.64e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 34 35 2.2044e+05 1.70e+00 8.97e-03 1.97e+02 \n", + " 35 36 2.2044e+05 5.56e-01 4.32e-03 1.62e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 36, initial cost 5.5667e+06, final cost 2.2044e+05, first-order optimality 1.62e+02.\n", + "mean reprojection error: 6.0453435047595665\n", + "max reprojection error: 30.502529209647467\n", + "mean reconstruction error: 0.6581047590467232\n", + "max reconstruction error: 1.8248533765613457\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:25.978179118175426 max: 285.88640917083137\n", + "image 1 reprojection errors: average:25.857737915382835 max: 416.97789242157654\n", + "image 2 reprojection errors: average:27.349217654377938 max: 466.2649834412381\n", + "image 3 reprojection errors: average:25.182904882084554 max: 305.4152031471961\n", + "image 4 reprojection errors: average:25.691279087423936 max: 432.06739353339316\n", + "image 5 reprojection errors: average:30.416077300339172 max: 330.83214210761747\n", + "image 6 reprojection errors: average:30.487701816306803 max: 506.034481104945\n", + "image 7 reprojection errors: average:25.67369911719487 max: 476.4604539491136\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.6912e+06 1.64e+07 \n", + " 1 2 3.0613e+05 5.39e+06 6.90e+01 1.16e+06 \n", + " 2 3 2.7563e+05 3.05e+04 1.49e+00 3.43e+04 \n", + " 3 4 2.7550e+05 1.27e+02 4.86e-01 1.81e+04 \n", + " 4 5 2.7547e+05 3.25e+01 7.67e-02 2.02e+03 \n", + " 5 6 2.7545e+05 1.32e+01 8.20e-02 2.45e+03 \n", + " 6 7 2.7545e+05 7.56e+00 2.22e-02 1.86e+02 \n", + " 7 8 2.7544e+05 6.92e+00 5.50e-02 5.76e+02 \n", + " 8 9 2.7543e+05 6.29e+00 2.06e-02 1.42e+02 \n", + " 9 10 2.7543e+05 4.67e+00 3.81e-02 5.34e+02 \n", + " 10 11 2.7543e+05 4.34e+00 1.63e-02 1.42e+02 \n", + " 11 12 2.7542e+05 3.78e+00 3.14e-02 4.50e+02 \n", + " 12 13 2.7542e+05 3.57e+00 1.41e-02 1.35e+02 \n", + " 13 14 2.7542e+05 2.63e+00 2.21e-02 3.00e+02 \n", + " 14 15 2.7541e+05 2.57e+00 1.18e-02 1.30e+02 \n", + " 15 16 2.7541e+05 2.56e+00 2.18e-02 3.66e+02 \n", + " 16 17 2.7541e+05 2.52e+00 1.14e-02 1.40e+02 \n", + " 17 18 2.7541e+05 2.39e+00 2.03e-02 3.57e+02 \n", + " 18 19 2.7540e+05 2.34e+00 1.05e-02 1.66e+02 \n", + " 19 20 2.7540e+05 8.57e-01 6.32e-03 1.64e+02 \n", + " 20 21 2.7540e+05 6.80e-01 3.75e-03 1.34e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 21, initial cost 5.6912e+06, final cost 2.7540e+05, first-order optimality 1.34e+02.\n", + "mean reprojection error: 7.04835993683155\n", + "max reprojection error: 35.4131300651203\n", + "mean reconstruction error: 0.692124679353594\n", + "max reconstruction error: 1.8258363198465328\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:25.74846156561295 max: 344.45121484980103\n", + "image 1 reprojection errors: average:26.731247718502388 max: 265.014918362224\n", + "image 2 reprojection errors: average:26.273526583549543 max: 404.83354244787324\n", + "image 3 reprojection errors: average:25.656746258191127 max: 287.76186455449084\n", + "image 4 reprojection errors: average:28.816850474623674 max: 446.0532884251406\n", + "image 5 reprojection errors: average:30.70033804636234 max: 390.6549016580771\n", + "image 6 reprojection errors: average:27.656549219690753 max: 288.3008695469598\n", + "image 7 reprojection errors: average:27.145915813003224 max: 433.4518820653641\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.2927e+06 1.20e+07 \n", + " 1 2 5.6422e+05 4.73e+06 6.73e+01 7.03e+05 \n", + " 2 3 5.4440e+05 1.98e+04 1.50e+00 1.97e+04 \n", + " 3 4 5.4378e+05 6.19e+02 2.14e+00 2.23e+04 \n", + " 4 5 5.4364e+05 1.42e+02 2.91e-01 2.68e+03 \n", + " 5 6 5.4360e+05 4.03e+01 1.61e-01 2.06e+03 \n", + " 6 7 5.4357e+05 2.98e+01 1.16e-01 6.60e+02 \n", + " 7 8 5.4356e+05 7.94e+00 2.99e-02 2.97e+02 \n", + " 8 9 5.4355e+05 5.26e+00 2.62e-02 2.48e+02 \n", + " 9 10 5.4355e+05 4.69e+00 2.32e-02 2.40e+02 \n", + " 10 11 5.4354e+05 4.41e+00 2.37e-02 2.91e+02 \n", + " 11 12 5.4354e+05 4.09e+00 2.08e-02 2.04e+02 \n", + " 12 13 5.4354e+05 3.74e+00 2.06e-02 2.88e+02 \n", + " 13 14 5.4353e+05 3.35e+00 1.72e-02 1.96e+02 \n", + " 14 15 5.4353e+05 1.97e+00 1.02e-02 3.02e+02 \n", + " 15 16 5.4353e+05 1.08e+00 4.90e-03 1.78e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 16, initial cost 5.2927e+06, final cost 5.4353e+05, first-order optimality 1.78e+02.\n", + "mean reprojection error: 10.446602604672325\n", + "max reprojection error: 41.48041327017851\n", + "mean reconstruction error: 0.8091727464543381\n", + "max reconstruction error: 3.0868430412151597\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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K2dfwx5eFlC4jI4NbbrmFkSNHlppm0aJFbN26la1bt5KZmcn48ePJzMwMuSz33ntvyGkrUn5+PnFxcaUuB+OcwzlHrVqxP13hxIkTmTBhAiNGjGDcuHE8+eSTjB8/vkS6kSNHcueddzJw4EAOHz5c5NwffPBBfv7zn5/KYp+02P/kREQkLP369aNp06ZlplmwYAEjR47EzOjTpw8HDhwgJyenRLrExERuu+02evTowYABA9i3bx/gBUwvvfQSBw8eJDk5mezsbACuvvpqnnjiCcD70uzVqxfdunXj7rvvLrfczzzzDL1796Z79+7ceOON5OfnF5ZhypQpnHfeeSxbtqzE8kMPPUSXLl3o0qULjzzyCADbt28nNTWVm266iR49erBjx45Sj9u/f38mTJhAv379SE1NZeXKlQwbNoyOHTty1113lVu+8ePHk56eTufOnYucZ7t27bj77rvp0aMHXbt2JSsrq9w6KItzjiVLlhQGIqNGjeLVV18tkW7Tpk3k5eUxcODAwvqrX79+yMfJz8/n9ttvp2vXrnTr1o2//OUvheczefJk+vbtS3p6OqtXr+aSSy7h7LPPZubMmSd1buVRMCMiIiXs2rWLNm1+eDA1KSmJXbt2lUh35MgRevTowerVq7nooouYOnVqke2NGzfm0UcfJSMjg+eff56vv/6asWPHsnjxYrZu3cqKFStYu3YtH3/8Me+//36p5dm8eTPz58/no48+Yu3atcTFxfHss88WlqFLly5kZmZywQUXFFmuV68ec+bMITMzk+XLl/PEE0+wZs0aALKzsxk5ciRr1qyhbdu2DB48mN27gz98W6dOHd5//33GjRvH0KFDeeyxx9iwYQNz585l//79ZZbvvvvuY9WqVaxbt4733nuPdevWFe63WbNmrF69mvHjxzNjxowSx83Ozi685VP8deDAgSJp9+/fT5MmTahdu3aZn9mWLVto0qQJw4YNIy0tjTvuuKMw8AK488476datGxMmTODYsWMl8s+aNYtt27axZs0a1q1bxzXXXFO4rU2bNixbtowLL7ywMKBdvnw5U6ZMCVqvFUW3mUREpATnSg7/FewJk1q1ajF8+HAAfvnLXzJs2LASaQYOHMiLL77IzTffzCeffALA4sWLWbx4MWlpaQAcPnyYrVu30q9fv6Dleeedd/j444/p1asXAN999x0tWrQAIC4ujp/97GeFaQOXP/zwQ6688koaNGgAwLBhw/jggw8YMmQIbdu2pU+fPoX5Fi5cWGp9DBkyBICuXbvSuXNnWrXyHuht3749O3bs4MMPPyy1fC+88AKzZs0iLy+PnJwcNm3aRLdu3QrLA9CzZ09efvnlEsdNTk4Oud9KqJ9ZXl4eH3zwAWvWrOHMM89k+PDhzJ07lzFjxvCHP/yBli1bcvz4cW644QamT59eIhB5++23GTduXGHQFNjKF1hPhw8fpmHDhjRs2JCEhAQOHDhAkyZNQjqXcCmYERGREpKSkorcetm5cyetW7cuN1+wL88TJ06wefNm6tWrR25uLklJSTjn+N3vfseNN94YUnmcc4waNYo//OEPJbYlJCQU6RcTuBzsC75AQYATirp16wJe8FbwvmA5Ly+v1PJt27aNGTNmsHLlSk477TQyMjKKjJ9SsK+4uDjy8vJKHDc7O7swWCxu6dKlRYKDZs2aceDAAfLy8qhdu3apn1lSUhJpaWm0b98egCuuuILly5czZsyYwiCtbt26jB49OmhrkXOu1Eeny6unaFEwIyJSiTblHAq5424o++rUqlGF7GvIkCE8+uijjBgxgszMTBo3blz4RRfoxIkTvPTSS4wYMYLnnnuOCy64oESahx9+mNTUVO6//36uu+46li1bxiWXXMLvf/97rrnmGhITE9m1axfx8fGFrRnFDRgwgKFDhzJhwgRatGhBbm4u33zzDW3bti3zPPr160dGRgaTJk3COccrr7zC008/HVmllKG08h06dIgGDRrQuHFj9u7dy6JFi+jfv3/I+w2nZcbMuPjiiws/j3nz5jF06NAS6Xr16sXXX3/Nvn37aN68OUuWLCE9PR2AnJwcWrVqhXOOV199NegTb4MGDWLmzJn079+f2rVrk5ubW24frGhTMCOnxMmMp6FxM6S66tS6YgKPwv21ahTSPq+++mqWLl3Kv//9b5KSkpg6dSpjxowp7KQ5btw4Bg8ezMKFC+nQoQP169dnzpw5QffVoEEDNm7cSM+ePWncuDHz588vsn3Lli3Mnj2bFStW0LBhQ/r168e0adOYOnUqmzdvpm9f70muxMREnnnmmVKDmU6dOjFt2jQGDRrEiRMniI+P57HHHis3mOnRowcZGRn07u0NUn/99deTlpZW+ChyoMGDBzN79uyQWqBCLV+fPn1IS0ujc+fOtG/fnvPPPz/sfYdj+vTpjBgxgrvuuou0tDTGjBkDwKpVq5g5cyazZ88mLi6OGTNmMGDAAJxz9OzZk7FjxwJwzTXXsG/fPpxzdO/ePWjH3euvv54tW7bQrVs34uPjGTt2LLfccktUz6s8VlYT3KmSnp7uVq1aVdnFkCga/viyiP5rLMhTUY+uilS2zZs3k5qaWtnFqDCJiYkcPny4sosh1VCw3xUz+9g5l148rVpm5JSJJCipqOZ3ERGpvvRotoiIREytMlIVKJgRERGRmKZgRkRERGKaghkRERGJaeoALCJSWRZNgj3rK3afLbvCZQ9U7D5Fqji1zIiIVJY96ys2mAlhf0ePHqV3796ce+65JSY+DOSc49Zbb6VDhw5069aN1atXh1WUKVOm8Pbbb4eVp0BiYmJE+cQbcfi8886jY8eODB8+nOPHjwdN9+WXXzJo0CBSU1Pp1KlT4bg7zjnuvPNOzjnnHFJTU/nzn/98CksfObXMiIhUppZdYfQbFbOvOT8pN0ndunVZsmQJiYmJfP/991xwwQVcdtllReYoAli0aBFbt25l69atZGZmMn78eDIzM0Muyr333ht28StCfn5+kakNii8H45zDOUetWrH///3EiROZMGECI0aMYNy4cTz55JOMHz++RLqRI0dy5513MnDgQA4fPlx47nPnzmXHjh1kZWVRq1Ytvvrqq1N9ChGJ/U9ORERCZmaFLR/ff/8933//fdB5dhYsWMDIkSMxM/r06cOBAwfIyckpkS4xMZHbbruNHj16MGDAAPbt2wdQOGPywYMHSU5OJjs7G/BGH37iiScAePDBB+nVqxfdunUrtYUo0DPPPEPv3r3p3r07N954Y+FMz4mJiUyZMoXzzjuPZcuWlVh+6KGH6NKlC126dOGRRx4BYPv27aSmpnLTTTfRo0ePIvNQFde/f38mTJhAv379SE1NZeXKlQwbNoyOHTty1113lVu+8ePHk56eXqIlrF27dtx999306NGDrl27kpWVVW4dlMU5x5IlS/j5z38OwKhRo3j11VdLpNu0aRN5eXkMHDiwsP7q168PwP/+7/8yZcqUwuAm2IjM+fn53H777XTt2pVu3brxl7/8pfB8Jk+eTN++fUlPT2f16tVccsklnH322UFHEq5ICmZERGqY/Px8unfvTosWLRg4cCDnnXdeiTS7du2iTZs2hctJSUns2rWrRLojR47Qo0cPVq9ezUUXXcTUqVOLbG/cuDGPPvooGRkZPP/883z99deMHTuWxYsXs3XrVlasWMHatWv5+OOPef/990st8+bNm5k/fz4fffQRa9euJS4ujmeffbawDF26dCEzM5MLLrigyHK9evWYM2cOmZmZLF++nCeeeII1a9YA3iSOI0eOZM2aNbRt25bBgweze/fuoMevU6cO77//PuPGjWPo0KE89thjbNiwgblz57J///4yy3ffffexatUq1q1bx3vvvce6desK99usWTNWr17N+PHjg07qmJ2dTffu3YO+Dhw4UCTt/v37adKkSeFs1qV9Zlu2bKFJkyYMGzaMtLQ07rjjjsLA67PPPmP+/Pmkp6dz2WWXsXXr1hL5Z82axbZt21izZg3r1q3jmmuuKdzWpk0bli1bxoUXXlgY0C5fvrzEzNsVTbeZRERqmLi4ONauXcuBAwe48sor2bBhQ4kJBYNNdROsBadWrVqFszr/8pe/ZNiwYSXSDBw4kBdffJGbb76ZTz75BIDFixezePFi0tLSAG/wva1bt9KvX7+gZX7nnXf4+OOP6dWrFwDfffddYatBXFwcP/vZz4qcX8Hyhx9+yJVXXlk4Q/awYcP44IMPGDJkCG3bti1ye23hwoVBjw3exJsAXbt2pXPnzoWTbrZv354dO3bw4Ycfllq+F154gVmzZpGXl0dOTg6bNm2iW7duheUB6NmzJy+//HKJ44Yz0WSon1leXh4ffPABa9as4cwzz2T48OHMnTuXMWPGcOzYMRISEli1ahUvv/wy1113HR988EGR/G+//Tbjxo0rDJoCJ5kMrKfDhw/TsGFDGjZsSEJCAgcOHCgyy3dFUjAjIlJDNWnShP79+/Pmm2+WCGaSkpKK3HrZuXNnSBMwBvvyPHHiBJs3b6ZevXrk5uaSlJSEc47f/e533HjjjSGV1TnHqFGj+MMf/lBiW0JCQpF+MYHLZc0/WBDghKJu3bqAF7wVvC9YzsvLK7V827ZtY8aMGaxcuZLTTjuNjIwMjh49WmK/cXFx5OXllThudnZ2YbBY3NKlS4sEB82aNePAgQPk5eVRu3btUj+zpKQk0tLSaN++PQBXXHEFy5cvZ8yYMSQlJRUGgldeeSWjR48ukd85F/RzDqWeokXBjIhIZdqzPqSOuyHvq2XXMpPs27eP+Ph4mjRpwnfffcfbb7/NxIkTS6QbMmQIjz76KCNGjCAzM5PGjRsXtkYEOnHiBC+99BIjRozgueee44ILLiiR5uGHHyY1NZX777+f6667jmXLlnHJJZfw+9//nmuuuYbExER27dpFfHx8qbNmDxgwgKFDhzJhwgRatGhBbm4u33zzTbmzZvfr14+MjAwmTZqEc45XXnmFp59+usw8kSitfIcOHaJBgwY0btyYvXv3smjRIvr37x/yfsNpmTEzLr744sLPY968eQwdOrREul69evH111+zb98+mjdvzpIlS0hP9+ZuvOKKK1iyZAnXXXcd7733Huecc06J/IMGDWLmzJn079+f2rVrk5ubW6R1pjIomBERqSzlBB4R7a+cfebk5DBq1Cjy8/M5ceIEv/jFL/jpT38KUNhJc9y4cQwePJiFCxfSoUMH6tevz5w5c4Lur0GDBmzcuJGePXvSuHFj5s+fX2T7li1bmD17NitWrKBhw4b069ePadOmMXXqVDZv3kzfvt7ks4mJiTzzzDOlBjOdOnVi2rRpDBo0iBMnThAfH89jjz1WbjDTo0cPMjIy6N27NwDXX389aWlphY8iBxo8eDCzZ88OqQUq1PL16dOHtLQ0OnfuTPv27Tn//PPD3nc4pk+fzogRI7jrrrtIS0tjzJgxAKxatYqZM2cye/Zs4uLimDFjBgMGDMA5R8+ePRk7diwAkyZN4pprruHhhx8mMTGR2bNnlzjG9ddfz5YtW+jWrRvx8fGMHTuWW265JarnVR4rqwnuVElPT3erVq2q7GJIFBXMfh3prNnh5hOpqjZv3kxqamplF6PCJCYmarJJiYpgvytm9rFzLr14Wj3NJCIiIjFNwYyIiERMrTJSFSiYERERkZimYEZERERimoIZERERiWl6NFtEpJJMXzGdrNyTm4+nuJSmKUzsXXLcGJHqTC0zIiKVJCs3i+zc7ArbX3ZudkjBUbt27ejatSvdu3cvHCytOOcct956Kx06dKBbt26sXr06rLJMmTKFt99+O6w8BQomwpTwbdu2jfPOO4+OHTsyfPhwjh8/HjTdl19+yaBBg0hNTaVTp06F4+4sWbKEHj160KVLF0aNGhXVUXsrklpmREQqUXLTZOZcGnxAunCNfrPk0POleffdd2nWrFmp2xctWsTWrVvZunUrmZmZjB8/nszMzJD3f++994actiLl5+cXmdqg+HIwzjmcc4UzRceyiRMnMmHCBEaMGMG4ceN48sknGT9+fIl0I0eO5M4772TgwIEcPnyYWrVqceLECUaNGsU777zDOeecw5QpU5g3b17hwHtVWex/ciIiUuEWLFjAyJEjMTP69OnDgQMHyMnJKZEuMTGR2267jR49ejBgwAD27dsHUDhj8sGDB0lOTiY722uBuvrqq3niiScAePDBB+nVqxfdunXj7rvvLrdMzzzzDL1796Z79+7ceOONhTM9JyYmMmXKFM477zyWLVtWYvmhhx6iS5cudOnShUceeQSA7du3k5qayk033USPHj2KzENVXP/+/ZkwYQL9+vUjNTWVlStXMmzYMDp27Mhdd91VbvnGjx9Peno6nTt3LnKe7dq14+6776ZHjx507dqVrKyTu+XonGPJkiX8/Oc/B2DUqFG8+uqrJdJt2rSJvLw8Bg4cWFh/9evXZ//+/dStW7dwCoOBAwfy97//vUT+/Px8br/9drp27Uq3bt34y1/+Ung+kydPpm/fvqSnp7N69WouueQSzj777MLRpaNFwYyISA1jZgwaNIiePXsya9asoGl27dpFmzZtCpeTkpLYtWtXiXRHjhyhR48erF69mosuuoipU6cW2d64cWMeffRRMjIyeP755/n6668ZO3YsixcvZuvWraxYsYK1a9fy8ccf8/7775da5s2bNzN//nw++ugj1q5dS1xcHM8++2xhGbp06UJmZiYXXHBBkeV69eoxZ84cMjMzWb58OU888QRr1qwBvEkcR44cyZo1a2jbti2DBw9m9+7dQY9fp04d3n//fcaNG8fQoUN57LHH2LBhA3PnzmX//v1llu++++5j1apVrFu3jvfee49169YV7rdZs2asXr2a8ePHM2PGjBLHzc7Opnv37kFfBw4cKJJ2//79NGnSpHA269I+sy1bttCkSROGDRtGWload9xxB/n5+TRr1ozvv/+eghH5X3rppaBB3qxZs9i2bRtr1qxh3bp1XHPNNYXb2rRpw7Jly7jwwgsLA9rly5czZcqUUj/biqDbTCIiNcxHH31E69at+eqrrxg4cCApKSn069evSJpgU90Emym5Vq1ahbM6//KXv2TYsGEl0gwcOJAXX3yRm2++mU8++QSAxYsXs3jxYtLS0gBv8L2tW7eWKEeBd955h48//phevXoB8N133xXO4xQXF1c403Px5Q8//JArr7yycIbsYcOG8cEHHzBkyBDatm1Lnz59CvMtXLgw6LHBm3gToGvXrnTu3Llw0s327duzY8cOPvzww1LL98ILLzBr1izy8vLIyclh06ZNdOvWrbA8AD179uTll18ucdxwJpoM9TPLy8vjgw8+YM2aNZx55pkMHz6cuXPnMmbMGJ5//nkmTJjAsWPHGDRoUGFgFOjtt99m3LhxhdsCJ5kMrKfDhw/TsGFDGjZsSEJCAgcOHCgyy3dFUjAjIlLDFEyk2KJFC6688kpWrFhRIohISkoq8l/5zp07Q5qAMdiX54kTJ9i8eTP16tUjNzeXpKQknHP87ne/48YbbwypzM45Ro0axR/+8IcS2xISEor0iwlcLmv+wYIAJxR169YFvOCt4H3Bcl5eXqnl27ZtGzNmzGDlypWcdtppZGRkcPTo0RL7jYuLC9rZNjs7uzBYLG7p0qVFgoNmzZpx4MAB8vLyqF27dqmfWVJSEmlpabRv3x7wZspevnw5Y8aMoW/fvnzwwQeAF3Bu2bKlRH7nXNDPOZR6ihYFMyIilSg7Nzusjrvl7Su5aXKZaY4cOcKJEydo2LAhR44cYfHixUFvAQwZMoRHH32UESNGkJmZSePGjQtbIwKdOHGCl156iREjRvDcc89xwQUXlEjz8MMPk5qayv333891113HsmXLuOSSS/j973/PNddcQ2JiIrt27SI+Pr7UWbMHDBjA0KFDmTBhAi1atCA3N5dvvvmm3Fmz+/XrR0ZGBpMmTcI5xyuvvMLTTz9dZp5IlFa+Q4cO0aBBAxo3bszevXtZtGgR/fv3D3m/4bTMmBkXX3xx4ecxb948hg4dWiJdr169+Prrr9m3bx/NmzdnyZIlhU+1ffXVV7Ro0YJjx44xffp07rzzzhL5Bw0axMyZM+nfvz+1a9cmNze3SOtMZVAwIyJSSVKaplTo/pKbJpe7z71793LllVcC3u2G//qv/+LSSy8FKOykOW7cOAYPHszChQvp0KED9evXZ86c4E9cNWjQgI0bN9KzZ08aN27M/Pnzi2zfsmULs2fPZsWKFTRs2JB+/foxbdo0pk6dyubNm+nbty/gdUJ95plnSg1mOnXqxLRp0xg0aBAnTpwgPj6exx57rNxgpkePHmRkZNC7d28Arr/+etLS0gofRQ40ePBgZs+eHVILVKjl69OnD2lpaXTu3Jn27dtz/vnnh73vcEyfPp0RI0Zw1113kZaWVvgk0qpVq5g5cyazZ88mLi6OGTNmMGDAAJxz9OzZk7FjxwJep+zXX3+dEydOMH78eP7zP/+zxDGuv/56tmzZQrdu3YiPj2fs2LHccsstUT2v8lhZTXCnSnp6uivocCTB7bn/fo5trtjBtYqrm5pCy8mTo7Lv4Y8vA2D+jX1PST6Rqmrz5s2kpqZWdjEqTGJioiablKgI9rtiZh8750oMjqSnmWLEsc1ZHD3Jx/bKcjQrK+rBkoiISDToNlMMSUhJoe3TT0Vl319cOzIq+xWR6k2tMlIVqGVGREREYpqCGREREYlpCmZEREQkpqnPjIhIJYnGU4rRfCpRpKpSMCOFjmZlRa0jcEbOIfY0bwN6xFqkUMFTigkpFTPeTKhPPF533XW8/vrrtGjRgg0bNhSuz83NZfjw4Wzfvp127drxwgsvcNppp5XI/+abb/LrX/+a/Px8rr/+eiZNmhRyGVetWsVTTz3Fn//855DzFMjIyOCnP/1p4USKEjrnHL/+9a9ZuHAh9evXZ+7cufTo0aNEunfeeYc77riDEydOkJiYyNy5c+nQoQNZWVmMHj2a1atXc99993H77bdXwlmUTsGMAN5/c9HUct+XUd2/SKyqyKcUQ/1nJCMjg1tuuYWRI4umf+CBBxgwYACTJk3igQce4IEHHmD69OlF0uTn53PzzTfz1ltvkZSURK9evRgyZAidOnUK6djp6emFo82eSgVD/Je2HGq+WLVo0SK2bt3K1q1byczMZPz48WRmZpZIN378eBYsWEBqaip//etfmTZtGnPnzqVp06b8+c9/DjoLd1UQ+5+QVIhoN0tv+vEVUd2/iISuX79+QUfAXbBgAUuXLgVg1KhR9O/fv0Qws2LFCjp06FA4r8+IESNYsGBBiWAmIyODhIQENm7cyN69e3nooYf46U9/ytKlS5kxYwavv/46t956K82aNWPKlCn885//5L777mPp0qWsWbOG3/72txw+fJhmzZoxd+7coFMpFPjss8+4+eab2bdvH/Xr1+eJJ54gJSWFjIwMmjZtypo1a+jRowf79+8vsnzttdcybtw4vv32W84++2z+9re/cdppp9G/f3/+4z/+g48++oghQ4Zw2223BT3u3LlzefXVV8nPz2fDhg3cdtttHD9+nKeffpq6deuycOFCmjZtWmr5XnvtNaZNm8bx48c5/fTTefbZZ/nRj37EPffcw5dffsnnn3/Ol19+yW9+8xtuvfXWMD7hkhYsWMDIkSMxM/r06cOBAwfIyckpUa9mxqFDhwA4ePBgkXm8WrRowRtvvFHmcd58800mT55cOAv3O++8wz333MO2bdvIyclhy5YtPPTQQyxfvpxFixZxxhln8NprrxEfH39S56dgRkREAG+qg4Ivt1atWvHVV1+VSLNr1y7atGlTuJyUlBT0P3yA7du389577/HZZ59x8cUX8+mnnxbZ/sADD9CrVy8uvPBCbr31VhYuXEh+fj6/+tWvWLBgAc2bN2f+/Pnceeed/O1vfyu13DfccAMzZ86kY8eOZGZmctNNN7FkyRLAm07h7bffJi4ujoyMjCLL3bp14y9/+QsXXXQRU6ZMYerUqTzyyCMAHDhwgPfeew8oOs1DcRs2bGDNmjUcPXqUDh06MH36dNasWcOECRN46qmn+M1vflNq+S644AKWL1+OmTF79mz++Mc/8qc//QmArKws3n33Xb755huSk5MZP358iS/84cOHk52dXaJMv/3tb0u0ugX73Hbt2lUimJk9ezaDBw+mXr16NGrUiOXLl5da78Xt27ePsWPH8v7773PWWWeRm5tbuO2zzz7j3XffZdOmTfTt25e///3v/PGPf+TKK6/kjTfe4Iorrgj5OMEomBERkZAFmwKntBmUf/GLX1CrVi06duxI+/btySrWp6eglaJfv348/PDDnH322WzYsIENGzYwcOBAwLutVVarzOHDh/nXv/7FVVddVbju2LFjhe+vuuqqIjNqFywfPHiQAwcOcNFFFwFeS1TgPgJnqg4WxBS4+OKLadiwIQ0bNqRx48ZcfvnlAHTt2pV169aVWb6dO3cyfPhwcnJyOH78OGeddVZhmp/85CfUrVuXunXr0qJFC/bu3UtSUlKRYxefB6ssoX5uDz/8MAsXLuS8887jwQcf5Le//S2zZ88O6RjLly+nX79+hecROPnkZZddRnx8PF27diU/P79wPrCuXbsGbSUMl4IZEREB4Ec/+lHhrYecnJygkz4mJSWxY8eOwuWdO3eWOjFj8S/LYF+e69ev5/TTT2f37t2A96XbuXNnli1bFlKZT5w4QZMmTUqdWbpBgwZlLpcm1HR169YtfF+rVq3C5Vq1apGXl1dm+X71q1/x29/+liFDhrB06VLuueeeoPuNi4sjLy+vRP5wWmZC+dz27dvHJ598wnnnnVe4/4KgIxTOuVID28B6iY+PL0xXUE8nS8GMiEglqsinCE/2yaghQ4Ywb948Jk2axLx58xg6dGiJNL169WLr1q1s27aNM844g+eff57nnnsu6P5efPFFRo0axbZt2/j8889JTk4uctviiy++4E9/+hNr1qxh8ODBXHHFFaSlpbFv3z6WLVtG3759+f7779myZQudO3cOeoxGjRpx1lln8eKLL3LVVVfhnGPdunWce+65ZZ5r48aNOe200/jggw+48MILefrppwtbaSpSWeU7ePAgZ5xxBgDz5s0Le9/htMwMGTKERx99lBEjRpCZmUnjxo1LtHiddtppHDx4kC1btnDOOefw1ltvhTUpat++fbn55pvZtm1b4W2mwNaZaNKgeSIilaRuakqFPZYN3pNRoTyZePXVV9O3b1+ys7NJSkriySefBGDSpEm89dZbdOzYkbfeeqvwkevdu3czePBgAGrXrs2jjz7KJZdcQmpqKr/4xS9KDTSSk5O56KKLuOyyy5g5cyYJCQmF25xzjBkzhhkzZtC6dWuefPJJrr/+ek6cOMFLL73ExIkTOffcc+nevTv/+te/yjyfZ599lieffJJzzz2Xzp07s2DBgpDqa968edxxxx1069aNtWvXMmXKlKDpZs6cWdhvJhKlle+ee+7hqquu4sILL6RZs2YR7z8UgwcPpn379nTo0IGxY8fy17/+tci23bt3U7t2bZ544gl+9rOfce655/L000/z4IMPArBnzx6SkpJ46KGHmDZtGklJSYUdhQs0b96cWbNmMWzYMM4999wit+qizYLdRzvV0tPT3apVqyq7GFVawX9u0ZpoMtoW+U8zXfb2q2HlG/6419Q8X+PTSDWxefPmsP7bjVUaE0ZOVrDfFTP72DlX4tl+tcyIiIhITFOfGRERqXBz586t7CJIDaKWGRGRU6wq3N4XqcrC/R1RMCMicgolJCSwf/9+BTQipXDOsX///iIdxsuj20wiIqdQUlISO3fuZN++fZVdFJEqKyEhocQggWVRMCMicgrFx8cXGelVRE6ebjOJiIhITFMwIyIiIjFNwYyIiIjEtHKDGTNrY2bvmtlmM9toZr/21zc1s7fMbKv/87SAPL8zs0/NLNvMLonmCYiIiEjNFkrLTB5wm3MuFegD3GxmnYBJwDvOuY7AO/4y/rYRQGfgUuCvZhYXdM8iIiIiJ6ncYMY5l+OcW+2//wbYDJwBDAUKpvmcB1zhvx8KPO+cO+ac2wZ8CvSu4HKLiIiIAGH2mTGzdkAakAn8yDmXA17AA7Twk50B7AjIttNfJyIiIlLhQg5mzCwR+DvwG+fcobKSBllXYqhLM7vBzFaZ2SoNHiUiIiKRCimYMbN4vEDmWefcy/7qvWbWyt/eCvjKX78TaBOQPQnYXXyfzrlZzrl051x68+bNIy2/iIiI1HChPM1kwJPAZufcQwGb/gGM8t+PAhYErB9hZnXN7CygI7Ci4oosIiIi8oNQpjM4H7gWWG9ma/11k4EHgBfMbAzwJXAVgHNuo5m9AGzCexLqZudcfkUXXERERARCCGaccx8SvB8MwIBS8twH3HcS5RIREREJiUYAFhERkZimYEZERERimoIZERERiWkKZkRERCSmKZgRERGRmKZgRkRERGKaghkRERGJaQpmREREJKYpmBEREZGYpmBGREREYpqCGREREYlpoUw0KVKpNuUcYvjjy8LO16l1I+6+vHMUSiQiIlWJghmp0jq1bhRRvk05hyq4JCIiUlUpmJEqLdKWlUhackREJDapz4yIiIjENAUzIiIiEtMUzIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS0xTMiIiISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLTFMyIiIhITFMwIyIiIjFNwYyIiIjENAUzIiIiEtMUzIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS0xTMiIiISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLTFMyIiIhITFMwIyIiIjFNwYyIiIjENAUzIiIiEtMUzIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS0xTMiIiISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLTFMyIiIhITFMwIyIiIjFNwYyIiIjENAUzIiIiEtMUzIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS0xTMiIiISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLTFMyIiIhITFMwIyIiIjFNwYyIiIjEtHKDGTP7m5l9ZWYbAtbdY2a7zGyt/xocsO13ZvapmWWb2SXRKriIiIgIhNYyMxe4NMj6h51z3f3XQgAz6wSMADr7ef5qZnEVVVgRERGR4soNZpxz7wO5Ie5vKPC8c+6Yc24b8CnQ+yTKJyIiIlKmk+kzc4uZrfNvQ53mrzsD2BGQZqe/rgQzu8HMVpnZqn379p1EMURERKQmizSY+V/gbKA7kAP8yV9vQdK6YDtwzs1yzqU759KbN28eYTFERESkposomHHO7XXO5TvnTgBP8MOtpJ1Am4CkScDukyuiiIiISOkiCmbMrFXA4pVAwZNO/wBGmFldMzsL6AisOLkiioiIiJSudnkJzOz/gP5AMzPbCdwN9Dez7ni3kLYDNwI45zaa2QvAJiAPuNk5lx+VkouIiIgQQjDjnLs6yOony0h/H3DfyRRKREREJFQaAVhERERiWrktMyIVpeW+L/ni2pFR2Xfd1BRaTp4clX2LiEjVpmBGTok9zb2H3JpGYd9Hs7KisFcREYkVCmbklHiz/38BMP/GvhW+72i19oiISGxQnxkRERGJaQpmREREJKYpmBEREZGYpmBGREREYpqCGREREYlpepqpipi+YjpZuaU/YjzC33bPm6NLbEtpmsLE3hOjVjYREZGqTMFMFZGVm0V2bjbJTZPDypedmx2lEomIiMQGBTNVSHLTZOZcOifoti+e9cZSKb59dJCWGhERkZpEfWZEREQkpqllpgLtuf9+jm2ObGj9gj4xBS0wxR3NyiIhJSXisomIiFRXapmpQMc2Z0VtnqCElBTqpiqYERERKU4tMxUsISWFtk8/FXa+gqeUSuszIyIiIsGpZUZERERimoIZERERiWm6zVQNZOdmR/SItgbbExGR6kDBTIxLaRpZp2ANticiItWFgpkYF2nLigbbExGR6kJ9ZkRERCSmKZgRERGRmKZgRkRERGKaghkRERGJaeoAHCVTX9vIpt2HQk6/vY6Xdvjjy+jUuhF3X945WkUTERGpVhTMRMmm3YfYlHOITq0ahZcvJ/QASERERBTMRFWnVo2Yf2PfkNKOftMLer49Hl7wIyIiUtMpmKnpFk2CPevDz9eyK1z2QMWXR0REJEzqAFzT7VkffjATSR4REZEoUcuMeK0so98IPf2cn0SvLCIiImFSy4yIiIjENLXMSLVwNCuLL64dWbic4T8V9sWHFdOhum5qCi0nT66QfYmISMVSMCMxr25qZDOHh+poVlZU9y8iIidHwYzEvGAtJv/9+DKAkB+NL0tgi4+IiFQ96jMjIiIiMU3BjIiIiMQ0BTMiIiIS09RnJkpGHZxJ27zPYE7j0DLYXgCm7L+DL2qfDZx8X49o2b7/CEeO53Gv3y8lFJHMUyUiIhIKBTNR0jbvM9p9/zmQFlY+L0/VduR4Ht8ezw8rT6dWjejUWsGMiIhUPAUzUbQ9vj2dQx1Z983RXp7dCVEsUcWpXyeuQp4UEhEROVnqMyMiIiIxTS0zcupEOkM3aJZuEREplVpm5NSJdLZtzdItIiJlUMuMnFrhztANmqVbRETKpJYZERERiWkKZkRERCSmKZgRERGRmKZgRkRERGKaghkRERGJaQpmREREJKbp0WwJy/QV0/m42WEAGvhTMIQqxb5mojstGsUSEZEaTMGMhCUrN4sv4vNp+31cWPmyc7OB49EplIiI1GgKZiRsbb+P4+5/J9L5hjkh5xn95miN4isiIlGhYKa6CHfeI9vr/dzzlTcqb5jaff95eCPz2l44fgTiwz6UiIhImdQBuLqIdP6ill3DDmaOWT22x7cP/1h1GkQUOImIiJRFLTPVSTjzHhV03r009FtFBfbUbs29p9/O/NF9Q89UeDzNfC0iIhVLLTMiIiIS09QyUwWF3R8FvFtMYd7Cyc7N9jrmhpkHWoWVR0REJJoUzFQxX9Q+G4DO4WYMs+9LStOUcI8AQHLTZD7f1TiivCIiItGgYKaKmdd4HEB4/VEiMLH3xIjzDn98WQWWRERE5OSoz4yIiIjENLXMlGPqaxvZtPtQSGkzcrx0//34Mm4/nk/9OuGNkitl2LM+rH5EU/Yf9N4sugAu0xNUIiLVWbktM2b2NzP7ysw2BKxramZvmdlW/+dpAdt+Z2afmlm2mV0SrYKfKpt2H2JTTmjBTKD6deJoUEexYoWIYCwc8DtSa9RhEZFqL5Rv27nAo8BTAesmAe845x4ws0n+8kQz6wSMwOu/2hp428zOcc7lV2yxT61OrRox/8by+7B88WEjvvzmS+q3ncWMuke9lSE+LZSdm01y0+STKWb1FUHLyr2PL2PK/jvC70gtIiIxp9yWGefc+0BusdVDgXn++3nAFQHrn3fOHXPObQM+BXpXTFFjw7fff+s/vhye5KbJET9hJCIiUpNFeh/kR865HADnXI6ZtfDXnwEsD0i3019XgpndANwAcOaZZ0ZYjKopuWkyc3K+8hbCHGF3+Bo9KSQiIhKOin6ayYKsc8ESOudmOefSnXPpzZs3r+BiiIiISE0RacvMXjNr5bfKtAL8Zgh2Am0C0iUBu0+mgFKzTV8xnazcrLDzba9ziHmNv+OPaIA/EZHqLtKWmX8Ao/z3o4AFAetHmFldMzsL6AisOLkiSk2WlZsVUR+ko7aD7fEx3e9cRERCVG7LjJn9H9AfaGZmO4G7gQeAF8xsDPAlcBWAc26jmb0AbALygJtj/UkmqXzJTZOZE2bfo/Pm/Az4LDoFEhGRKqXcYMY5d3UpmwaUkv4+4L6TKVRVMurgTNrmfQZzQrhdsWc3cNwb22TPVxGNjQKwKedQ2FMGdGrdiLsv14PIIiJS82hUt3K0zfvMG3yNtPAyRjjQW6fWjcLOE8mgfjVGmCMHF2rZVSMHi4jECAUzIdge357Oo98oP+GSkZCbBS07h/1IdoFIWlc08WNwx6xeZK1jGjVYRCSmKJiRamtP7dYw+u/hZ4ykJUdERCqNghmREBzNyuKLa0dGbf91U1NoOXly1PYvIlKdKZgRKUfd1OhOM3E0K/xxdERE5AcKZkTKEe0Wk2i2+IiI1AQVPZ2BiIiIyCmlYEZERERimoIZERERiWnqMyNSje25/36ObY5uB2M9iSUilU0tMyLV2LHNWVF9WupoVlbUgyURkfKoZUakmktISaHt009FZd96EktEqgK1zIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS09QBWCTA9BXTybK93sKbo0POl9I0hYm9J0apVCIiUhYFMyIBsnKzyOY4ydQJOU92bnYUSyQiIuVRMCNSTDJ1mON+BJfOCSn96DBacEREpOKpz4yIiIjENAUzIiIiEtMUzIiIiEhMU58ZOWWyc7PD7l+SnZtNctPkKJVIRESqAwUzckqkNE2JKF9y0+SI84qISM2gYEZOCY3BIiIi0aJgpprYlHOI4Y8vCztfp9aNuPvyzlEoUeU7ajsiu60VpfKU5WhWVlRmoD6alUVCilq2RKR6UzBTDXRq3SiifJtyDlVwSaqOhBNtIurentw0mZQ9p3YQvLqp0Qs2ElJSorp/EZGqQMFMNRBpy0okLTmxomXecADmXNo3/MxzflLBpSlby8mTT+nxRESqGz2aLSIiIjFNLTOlmL5iOlm5WRxpdhiABiH0vRiRm8W3ed9Fu2giIiISQC0zpcjKzYpoAsH6tevpUWIREZFTSC0zZUhumszt27cC0PmG8icd/OJZ72mUS/QYcuzbsz70vjO21/u5aBJc9kD0yiQiIkEpmBEprmXX8PMcP+IFQCIicsopmBEpLtzWlTdHe4GMi05xRESkbOozIyIiIjFNwYyIiIjENAUzIiIiEtMUzIiIiEhMUzAjIiIiMU3BjIiIiMQ0BTMiIiIS0xTMiIiISEzToHlSbW3KOcTwx5eFna9T60bcfXnnKJRIRESiQcGMVEudWjeKKN+mnEMVXBIREYk2BTNSLUXashJJS46IiFQu9ZkRERGRmKZgRkRERGKaghkRERGJaQpmREREJKYpmBEREZGYpmBGREREYpqCGREREYlpCmZEREQkpimYERERkZimYEZERERimoIZERERiWkKZkRERCSmKZgRERGRmKZgRkRERGKaghkRERGJaQpmREREJKbVruwCiFQH2RxntO2FN0eHlS+laQoTe0+MUqlERGoGBTMiJymlaQrsWR92vuzc7CiURkSk5jmpYMbMtgPfAPlAnnMu3cyaAvOBdsB24BfOua9PrpgiVdfE3hNh4/vewqVzQs43OsxWHBERCa4i+sxc7Jzr7pxL95cnAe845zoC7/jLIiIiIlERjQ7AQ4F5/vt5wBVROIaIiIgIcPLBjAMWm9nHZnaDv+5HzrkcAP9ni2AZzewGM1tlZqv27dt3ksUQERGRmupkOwCf75zbbWYtgLfMLCvUjM65WcAsgPT0dHeS5RAREZEa6qSCGefcbv/nV2b2CtAb2GtmrZxzOWbWCviqAsopUvXtWQ9zfhJ6etvr/Vw0CS57IDplEhGpASK+zWRmDcysYcF7YBCwAfgHMMpPNgpYcLKFFKnyWnb1XuE6fiSix7pFROQHJ9My8yPgFTMr2M9zzrk3zWwl8IKZjQG+BK46+WKKVHGRtKy8OdoLZHSTVUTkpEQczDjnPgfODbJ+PzDgZAolIiIiEiqNACxSzKacQwx/fFlYeTq1bsTdl3eOUokqxvQV08nKDbmPfhGadkFEqjIFMyIBOrVuFHaeTTmHolCSipeVm0V2bjbJTZPDyqdpF0SkqqtRwczU1zayaXdoXzzb63jpvj2eT/06cdEsllQhkbSuhNuKU5mSmyYzJ4wpF0DTLohI1VdzgplFk/j5+g9DDk6mNjsMQCf7in11zol26URERCRCNSeY2bOedt9/zvY67encqnG5yRvYUe/nmWk0iOSRW5EoibTvSyS3mEREYkHNCWaA7fHtuff0B5k/um/5iQua1sNskheJtkj7viQ3TSalaUqUSiUiUnlqVDAjJUXy5M6mnEN0ahV+R1mpOJH0fRERqa4UzNRgkTy5A9CpVaOI80pR2RxntO39oSUwlDy6XSQiUoSCmRqsqo+LUt2lNE2JaCoD3S4SESmqRgUztvIIGd9M54sPy29VGOF3sPzi2ZEh7/9oVhYJKfqSkdBM7D0RNr7vLcTwLaOjWVl8cW3ovyfhqJuaQsvJk6OybxGpPmpUMENuHi0PfAmtukRl9wkpKdRNVTAjNUc0r/dvV67k25UrObY5slGLQ6FgSaR6qFnBDLCn+ZmkPf1Uuenu8fswqJOlSOmiGQjsuf/+qAYyR7Oit28RObVqXDAjIrEh2i0m0bo1JiKnXq3KLoCIiIjIyVAwIyIiIjFNwYyIiIjENAUzIiIiEtPUAViksu1ZD3N+En6+ll3hsgcqvjwiIjFGwYxIZYp0RvYIRg4WEamuFMyIVKZIW1YiackBWDQp/EDI9v6QVy1BIlIFKZgRqUn2rPde4bYIHT9SLVuDojkVA2iEYZFTRcGMSE3TsiuMfiP09G+O9gIZF70iVYZoTz2iEYZFTh0FMyJSI2mEYZHqQ49mi4iISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLT1AFYpAaY+tpGNu0+xJT9BwG49/FlIef9KvEI7aJULhGRiqCWGZEaYNPuQ2zKORR+vpxDfHs8PwolEhGpOGqZEakhOrVqROc6jQGYP7pvSHmGP76M7VEsk4hIRVDLjIiIiMQ0BTMiIiIS06r9babpK6aTlZsFtper4vM5ZjsY/ebocvNl52aT3DT5FJRQRERETka1D2aycrO8wCTMfMlNk0lpGt25W0ROyp71Ic+eXfAUE/Zl+JNMiohUcdU+mAEvMJmT8xWbvv+SL+LbMOfSOZVdJJGTE2lA0rKrghkRqXZqRDAjUu1c9kBYyQvGlQn1KabisjnOaNvrzaAdhpSmKUzsPTGiY4qIhErBjIiUKeFEG9rHfRF2vuzc7CiURkSkJAUzIlKmlnnDmVNrq7cQxi3aUDrai4hUBAUzIjGmYGqCcGzKOUSnVo2iVCIRkcqlYEYkxhRMTRBOcNKpVSM6tY4smNmUc4iNdSKc0+n0BhEdU0QkHApmRCpJJC0s8EMry/wbI+vMG47CAGh/ePk25RyiflvN6SQip4aCGZFKEkkLC5xcK0u47r68s/dmjuZ0EpGqS8GMSCU6VS0sIiLVmYIZEanRCqc8iYDG0RGpGhTMiEiNVjjlSZhzsWkcHZGqQ8GMiNR4yU2Tw57mROPoiFQdCmZEpEqZ/sLlZH2bE1HelPqtmPiL1yq4RCJS1dWq7AKIiATK+jaHbHc07HzZ7mjEQZCIxDa1zIhUgE05hxgexoByBXlialTePethzk9CSjpl/0GmNjsMe2rDoklhT4yZbAnMyVgVVp7Rc9O9CTFDvP2zff8Rvj2ez1HbQYJrE/Ln16l1ox8eWS/H0awsvrh2ZEhpw1U3NYWWkydHZd8isUbBjMhJinTMl1M5XsxJa9k1snzHj3hBUAgKBhF0lgcQVnDYqXUjUqgTVtG+PZ7Pt8fyaB8XR/Lx7Yw6eEdIeervj4N/NwbbC3VKH+G4bmpKWOUJx9GsyJ6+EqmuFMyInKRQ/0uPaWG2rNz7+DK+iJ9BJ/sCXGh5CgYRTG0dXtE25XijKM+vc5q3IsSOvMMfXwYG82tPg3+vh1blB2wbcw7+sHD8SJlpo9lqEq3WHpFYpWBGRKqMTq0aUb+O92dpTkboow2ftJZdYfQb5SYrmJtq/ui+MDf95I8rIhVCwYyIxLxIJsOMuT5LIlIqBTMiEtMCJ8Ns9/3nTNlfft8XAOpAg29qw/efR94nqJrac//9HNsc3X456sAsFUnBjIjEtMI+S4sugD2NCb8HU1cFM8Uc25zF0awsElKi04lZHZiloimYEZHqIcxOylK2hJQU2j79VFT2rQ7MUtEUzIiIxKBojmETzVYZkWhQMCMiEmOiOYYNeK0y0T6GSEVSMCMiUZPNcUbbXghhVN7tdbzxYuI4TnKYA+DVNOo4K1KU5mYSkahIONEmoqAkmTphj+YrIjWbWmZEJCpa5g1nTq2t3kIIo/IWDH43p860aBZLRKohtcyIiIhITFMwIyIiIjEtareZzOxS4P8BccBs55wGgRCpifashzk/KTfZlP3+JI72pQaxqwGi+Wi5RhcOrjqP7ByVYMbM4oDHgIHATmClmf3DObcpGscTkSoqkqCkpUbkre6i+di3RhcuXXUe2TlaLTO9gU+dc58DmNnzwFBAwYxIDbEp5xDDGYr3qx9C+uPexI/zR4c2W7bErmj+5/7FtSOj2uoTywoCmeo4srM55yp+p2Y/By51zl3vL18LnOecuyUgzQ3ADf5iMpBdAYduBvy7AvZT06jeIqN6i4zqLTKqt8io3iJTVeutrXOuefGV0WqZsSDrikRNzrlZwKwKPajZKudcekXusyZQvUVG9RYZ1VtkVG+RUb1FJtbqLVpPM+0E2gQsJwG7o3QsERERqcGiFcysBDqa2VlmVgcYAfwjSscSERGRGiwqt5mcc3lmdgvwT7xHs//mnNsYjWMVU6G3rWoQ1VtkVG+RUb1FRvUWGdVbZGKq3qLSAVhERETkVNEIwCIiIhLTFMyIiIhITIu5YMbMLjWzbDP71MwmBdluZvZnf/s6M+tRGeWsakKot/5mdtDM1vqvKZVRzqrGzP5mZl+Z2YZStut6CyKEetP1FoSZtTGzd81ss5ltNLNfB0mja66YEOtN11wxZpZgZivM7BO/3qYGSRMb15tzLmZeeJ2JPwPaA3WAT4BOxdIMBhbhjXXTB8is7HJX9ivEeusPvF7ZZa1qL6Af0APYUMp2XW+R1Zuut+D10gro4b9vCGzR37gKqzddcyXrzYBE/308kAn0KZYmJq63WGuZKZwmwTl3HCiYJiHQUOAp51kONDGzVqe6oFVMKPUmQTjn3gdyy0ii6y2IEOpNgnDO5TjnVvvvvwE2A2cUS6ZrrpgQ602K8a+hw/5ivP8q/lRQTFxvsRbMnAHsCFjeSckLNpQ0NU2oddLXb25cZGadT03RYp6ut8jpeiuDmbUD0vD+Ww6ka64MZdQb6JorwczizGwt8BXwlnMuJq+3aE1nEC3lTpMQYpqaJpQ6WY0358VhMxsMvAp0jHbBqgFdb5HR9VYGM0sE/g78xjl3qPjmIFl0zVFuvemaC8I5lw90N7MmwCtm1sU5F9jXLSaut1hrmQllmgRNpVBSuXXinDtU0NzonFsIxJtZs1NXxJil6y0Cut5KZ2bxeF/IzzrnXg6SRNdcEOXVm665sjnnDgBLgUuLbYqJ6y3WgplQpkn4BzDS74HdBzjonMs51QWtYsqtNzNraWbmv++Nd23sP+UljT263iKg6y04v06eBDY75x4qJZmuuWJCqTddcyWZWXO/RQYzqwf8GMgqliwmrreYus3kSpkmwczG+dtnAgvxel9/CnwLjK6s8lYVIdbbz4HxZpYHfAeMcH5X9prMzP4P7ymIZma2E7gbr5OcrrcyhFBvut6COx+4Fljv92MAmAycCbrmyhBKvemaK6kVMM/M4vCCuxecc6/H4neqpjMQERGRmBZrt5lEREREilAwIyIiIjFNwYyIiIjENAUzIiIiEtMUzIiIiEhMUzAjAphZvj+T7kZ/uPPfmlktf1u6mf25jLztzOy/Tl1pSxz/Vn+24GejfJzfmFn9KO27UuvwVDKzhWbWxH/dFLC+tZm9VEHH2G5m680svQL29aCZ7TGz2yuibCLRoEezRQAzO+ycS/TftwCeAz5yzt0dQt7+wO3OuZ9GtZClHz8LuMw5t63Y+trOubwKPM52IN059+8g2+L8YdEj3Xd/TqIOT/b4lcGfQ+h151yXKOx7O6V8VhHu7x7gsHNuRkXsT6SiqWVGpBjn3FfADcAt/qiX/c3sdQAzu8hvwVlrZmvMrCHwAHChv26C38rwgZmt9l//4eftb2ZLzewlM8sys2cDRiTtZWb/8luFVphZQ/MmgHvQzFaa2Tozu7F4Wc1sJtAe+Id/7HvMbJaZLQaeMrO2ZvaOn/8dMzvTzzfXzP7XzN41s8/98/qb38IzN8hxbgVaA++a2bv+usNmdq+ZZeJN4Lfd/OHh/daspf77Bv6+V/p1FmzG9uJ1mGBmc/zWhTVmdnGQMvX3y/8c3mBppdaXmf23v69PzOwBf113M1vup33FzE4r67rw6/ZpM1tiZlvNbKy/3vzjbvCPMdxf38rM3vfPaYOZXeivL6inB4Cz/e0P+tfNBj9N0PM3swwze9nM3vTL8MeyyhxQ9mDXV4aZvWpmr5nZNjO7xbwWyTV+vTQNZd8iVYJzTi+9avwL77/O4uu+Bn6EN5Lt6/6614Dz/feJeKNoF27319cHEvz3HYFV/vv+wEG8uU1qAcuAC4A6wOdALz9dI3+/NwB3+evqAquAs4KUczvQzH9/D/AxUC+gvKP899cBr/rv5wLP400iNxQ4BHT1y/Ux0L2s4/jLDvhFKeVIB5b67+8Hfum/bwJsARoU23fxOrwNmOO/TwG+LKjTYnmOFNRJafUFXAb8C6jvb2vq/1wHXOS/vxd4pJxr5B7gE6Ae0AxvJuHWwM+At/BG1/6RX9ZW/jnc6eeNAxoG1hPQDtgQsP/C5dLOH8jAu1Ya+8tfAG3KuSZKu74y8EZ1bQg0x7s2x/lpHsabrDHw3G+v7N9TvfQq7aWWGZHSBZst9iPgIb+lookLfhsnHnjCzNYDLwKdAratcM7tdM6dANbifYElAznOuZVQOCFeHjAIb06UtUAmcDqhzfL7D+fcd/77vni3zACexgueCrzmnHPAemCvc269X66NfrnKk483sV95BgGT/PNYivclfGY5eS7wy4tzLgvvS/ucIOlWuB9ur5VWXz/GCwy+9feXa2aN8T6/9/y884B+IZzLAufcd867ffMu0Nsv6/855/Kdc3uB94BeeHOijTbvFk1X59w3Iew/lPN/xzl30Dl3FNgEtC1nX6VdXwDvOue+cc7twwtmXvPXrye0a0CkSoipuZlEThUza4/3Zf0VkFqw3jn3gJm9gTdXyXIz+3GQ7BOAvcC5eC0dRwO2HQt4n4/3O2h4rRwligH8yjn3zzCLf6SMbYHHKSjLiWLlOkFofxuOuqL9VPL44dZ1QsB6A37mnMsOYZ+BeUIReK5B68vMLiV4/Uai+H4cpZTVOfe+mfUDfgI8bWYPOueeCvE4ZZ1/sGuovH2Vdv7FP/fAa0LfDxIz1DIjUoyZNQdmAo/6LReB2872WzCm493GSAG+wWuqL9AY7z/hE3iT38WVc8gsoLWZ9fKP0dDMauNNDDrezOL99eeYWYMwT+dfeLOkA1wDfBhm/kDFz7O47UBP//3PAtb/E/iVWWH/oLQQ9v0+Xnkxs3PwWnLKC4ZKq6/FwHXmP4llZk2dcweBrwv6seB9Tu8F22kxQ/3+LKfj3eZa6Zd1uN9npzleC88KM2sLfOWcewJvRuce5ZxzoEjOvzSlXV8i1YYuaBFPPf/2RDxeC8PTwENB0v3G74yZj9fEvwjvv9g8M/sEry/KX4G/m9lVeLciymopwTl33O80+hczq4c3o++Pgdl4Tf2r/UBgH3BFmOd1K/A3M7vDz38yM97OAhaZWY5zrkSHXGAq8KSZTca7zVPgf4BHgHX+eWwHij+1tI6SdTjTv1WXB2Q4545RtqD15Zx708y6A6vM7DjeLMCTgVH+Merj9SkZDWBm9+L1c/pHkGOsAN7ACy7+xzm328xewbud9wleC8h/O+f2mNko4A4z+x44DIwM3JFzbr+ZfeR3+l0EPBawOej5+/FgWMq4vkSqDT2aLSISAouhx5NNj2ZLDaPbTCIi1c8+4B2roEHzgF9STgujSGVSy4yIiIjENLXMiIiISExTMCMiIiIxTcGMiIiIxDQFMyIiIhLTFMyIiIhITPv/MvV08KLzUKMAAAAASUVORK5CYII=\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length2, principle_point2, radial_distortion2) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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Go5HebEsYJUYA0yEIQrV67ZYlRAj9fr+4L8LIOioIKRRpUAFIoSCxt18mFDoFnMu2CCGYnp7G5OQkdu/eDYvFsk686vV61NXVoa6uDoQQ+P1+OJ1OjI6Owuv1wmw2ixFCg8GQ6y6JlFoTSCmttZSJP87R/pvC74V63WhBKEQIWZalgpBCiYMKQMoFj3DjyCTlG0+pdAFHIhH09/eDYRh0dXWJEZV02zMajTAajWhoaAAhBB6PB06nEwMDAwgGg7BYLGKEsBDj8JREqQmLUowApltzMkEoeHayLBuTMqaCkEKhApByASPnOLdSmAQipHxbWlrQ0NCQ0/YtFgssFguam5vB8zzcbjccDgdmZmYQiURgs9nECKEUkUmhpCJT0ZqohlAQhMLvo1PGVBBSLkTolZlyQSLF2y8TlBwBjE757tmzB2azWdb1sCwLm80Gm80GYC2iurKyAqfTiYmJCQCA3W5HWVkZbDabOD4sEaWWAi5FNmIEMB2JBGEkEhEtnqggpFyIUAFIuaCI9/aTQ/wJn8NxXM6fI3VbUkVSdMq3u7s7pfiSC5VKhfLycpSXl4trcLlcWFpawvDwMFQqFcrKylBeXg6LxUJHglHSIrdoTSQIw+HwOkEoTCqhgpCyEaECkHLBEJ/ylfOCrsQmELlSvrmiVqtRWVmJyspKAEAoFILT6cTs7CzOnz8PnU4nposB2liRby7ECGA6GIaJeThKJAjj5xiX2jGkUOKhApByQZCNt18mKCkFTAjB1NQUpqam8pLyzRWtVouamhrU1NQAgNhhPDExgdXVVTFlLXQY0xutvFABmJ5EgjAUCiEYDIrXD0EQCnOMS+2YUihUAFI2NPH2EPlKNxayCSRVtDESieDMmTNQqVQFS/nmisFggMFgQH19PVwuF6ampkAIwfDwMPx+f4zljF6vL/ZyKUWg2KJVqiAUUsZUEFJKASoAKRuWXL39MqHQzQuJtiWkfFtbW1FfX1+wtcgJy7JQq9VobGxEY2MjCCFwu91wOp04d+4cQqFQTIexRqMp9pJLjmKLqWxQ2pqjBaHwXQyFQgiFQgBePo+jawgpFKVBBSBlQxIOh+H3+6HRaAryNF7ISSDxEUC5Ur5KusEKMAwDq9UKq9WKlpYW8DyP1dVVOBwOTE1Nged5URDa7XZqObNBUZoAjCZ6NB2wXhCOj4+jra2NCkKK4qBXS8qGQmj0WFxcxPz8PHbs2FGQ7RarCaQUU76pSBdJZVkWdrsddrsdwJrljMvlgtPpxNjYGBiGEaODNpuN3mgToGQxlYxSWnO8IFxaWkJbW9u6CGF8UwmFUmioAKRsGKJTvoUUZEDhm0CESFhfX19Jp3xzRaVSoaKiAhUVFQDWIr8ulwsLCwsYGhqCWq2OsZwpFRGRT0pJTAmU4poFhAxEdISQEIJgMIhgMAiACkJKcaACkLIhiDd1ValUBUvJAoVtAgHWOmfPnDmDvXv3wmQyFWy7Skej0aCqqgpVVVUAgGAwCKfTienpabjdbuj1ejFCaDKZchYV1LKmMJSyAEw2xzj69/GCUBhbp1KpxC5jCkVuqACklDTJvP0KLcgKFQEUUr6RSASHDx+WNeWrhJus3MdRp9OhtrYWtbW1IISIljNjY2Pwer0wmUziDGODwZD1mksJJfydM0WY51tqSDnWiQQhz/MIBALiz6LnGAtdxhRKrlABSClZUo1zK3QKuBCCU0j5trS0IBgMyl7vt9FvKgzDwGg0wmg0oqGhAYQQeL1eOJ1ODA4OIhAIwGKxiBFCnU5X7CVTXqIURSsAsRwlE6ggpBQKKgApJUf8OLdEF9hCduUK28uX4CSEYHJyEtPT09i7dy8MBoM4Y1culHQDKWQtpdlshtlsRlNTE3ieFy1n+vv7EYlEYjqMN4rlTCmKKeEhr9SQ41hTQUjJF1QAUkoKYUQTx3Ep7V02Sgo4HA7jzJkz0Gg0YpevUDO0ESnmjYtlWdhsNthsNrS2toLjONFyZmJiAoQQ2O12URCWesd1KVGKohXILgKYjmSC0O/3x3QgU0FISQcVgJSSIZNxboUWgPnY3srKCs6cOYO2tjbU1dWJP6cX88KgUqliZhRHIhG4XC44HA6MjIxApVKJaeJ83OjzRSmKqVJcM1CY2kXhWihsJ5EgFEbWUUFIiYYKQIriiW/0kHJBLfRkDjm3RwjBxMQEZmZmLrgu30L/3TJBrVajsrISlZWVANaMficnJ7G8vIznn38eWq1WbCgxm82KvcmWopgqxTUDxUldJxKE0eMwAcSYUlNBeOFCBSBF0WQ7zq1UI4DhcBh9fX3Q6XQFN3Yu1ZtssdBqtaIh9ebNmxEIBOB0OjE5OQm32w2j0ShGEI1GIz22OVCq56YSIsPJBGEkEhFfIwhCtVoNlmVL8lhTMocKQIpiEaJ+UlK+8ZRiBFBI+W7atAm1tbUyrUw69KKfG3q9HnV1dairqwMhBD6fD06nEyMjI/D5fDCbzWKEUK/XF22dpSimSnHNgDLXnaiGMFoQMgwTkzKmgnDjQgUgRXFkk/KNpxhpl2wFoJDynZ2dRWdnJ4xGo8yrKx2UnALOBIZhYDKZYDKZ0NjYCEIIPB4PnE4nzp8/j2AwCKvVKkYItVptsZesaJQopKSghAhgOhIJwkgkguXlZbjdbjQ2NlJBuEGhApCiKFJ5+ymZbFPA8Slfpd8sNjqzKwGUm7TQqaX9HQJhHks+DpvTvI5hGFgsFkBjwAODEVyzvRW1RiJOKeE4LqbDWK3O36W5FMVUKa4ZKM11C9ddISrIMAzC4XDMpKXoGkIqCEsXKgApikCKt5+SySZytbKygr6+PmzevLkoKd+iEvaDXegDuzIJorOAr90LYqoGULzxaoEwhx89N4UKkxbvPNIs6T33vrgIp9eP/Tt4aFTpz1n2pfskTxjY7TbY7Xa0tbWB4zisrKzA4XBgbGwMDMOIgtBms13wpt+lKKSA0ogAJkNYe/QcY+BlK65oQRg/x7gU/1YXIlQAUoqOVG8/JZPJmgkhGB8fx9zcHPbt23fBpXwZ1xi0J74NJuQBYbUAHwZz7ncIb7kWTPOxoq1Lr1HhlTur0FwmfSTcjbvKMTznlCT+AMCkU+Ofj21a93OVSoXy8nKUl5cDWIsMu1wuLC0tYXh4GGq1WkwXWyyWnERFKabYqQAsPMnWnkgQhkIhBINB8fotCEJhjnEp/u0uBKgApBSVTLz9NgJCylev11+YKd+QF9rj3wZhVSDWJvHHhOegGfg/qHUVAIpne9PZaMvo9eVGNdSV8o+M02g0qKqqQlVVFQAgGAzC6XRiZmYGbrcbOp1ObCgxmUwZP4CU2vesFNcMlO66AeniNZUgBNayORqNRkwZXwjX+VKBCkBKUZCj0aPUcLlcOHPmzIWZ8n0J1dwpMGEviLUx9hesCryhDLqRh0HKbyjO4hRCmOPx1yEHjmwuh/alWkSdTofa2lrxvPH7/XA6nRgfH4fH44HJZBIjhAaDYcPdYAthqJwPNmIEMB3RglCINodCIYRCIQBrgjC+hpBSHKgApBScbL39SpULPeUbDesYBlEnsUDRWsCuTIApiyT+fQ4suIOYWQlgb4NV8efb0KIPz4w4UWPRYWe9JeFrDAYDDAYD6uvrQQiB1+uF0+nE0NAQAoFAjOWMMK1EoBSjUqW4ZqB01w2sCcBcm5GiR9MBVBAqDSoAKQVFaPQoVMq32BfgcDiM3t5eGAyGCzPlGwfRmgA+icAjHMBqQBj5j9G9J6bhC3HYWWeBRqXsG/K2ahPuONSIOps0r0CGYWA2m2E2m9HU1ASe5+HxeOBwONDf349IJBJjOVOKFPt7nC0XYgQwFVQQKgsqACkFoRgpX6Ezt1g3DiHlu2XLFtTU1BRlDUqDq9sP1ehfAMIDcUKP8S4g3HARCOQ/N955uBkuf0Rys0YxUbEMmjJoRImHZVlYrVZYrVa0traC53msrKyIU0o8Hg9GRkZQUVEBu91e0Gkz2VKqQqpUhStQmGOeSBAKGaJoQRjfZUyRByoAKXmH53nMzc1BrVbDai1cCk7w5iv0BYMQgrGxMSwsLOQ15VuKNxdibwXXeBHUE8+CN1UDGgPAc2B8C4DWjFDbMWB0TvbtmnRqmHQX5uWOZdmY6N+JEydgt9vhcDgwOjoKlmVjLGeUeIMtxXMdKF3hChRn7YlMqQkhCAaDYlOJSqUSo4NClzElOy7MKyKlIER7+62srECv18Nmy6zLMhcKPQ8YWEtl9PX1wWAwoKurK28X0Fyim2PLPvhDHLbXJa4vyysMg8ju20CsjVAPPwrG7QABC67hILit1wEaKwiZlWVTC+4gqsxaeoOIg2EYVFZWorp6zXcxFArB5XJhYWEBg4OD0Gq1MZYzSjh+pSwASyHCmgglrD2RIOR5HoFAQPyZIAiFCGEpnifFggpASl6IT/mqVKqCi7FCC8BIJIITJ04UJOUbbTyd6c3xZycmEeEIPn5du+T3nRh34fGBZbz/yjbJUzKSwqrAtR0F13I5EPYCKh2gfqlR4SVz2VwZW/bhR89N4ertVbhkU2nWvUVzft6DlnID9Jrcb8jx54tWq0V1dbUoCAOBAJxOJ6ampuDxeKDX68WGEqPRWJQbbKkKwFLtXgbW6rWVtnYqCOWFCkCK7CTy9itGNI5l2YKY3gop32AwiCNHjsBgyL5+SyqCAFzxh/G1vwzjlTur0dVaLum977q0DWGOz+jC6PCGEOZ4qFgZL6asCtBZ1/1Yjr9Zg12PSzeXY1eSLtpSYskTws+fn8G+Jitu2JN/+yC9Xo+6ujrU1dWBECJazoyOjsLr9cJsNsdYzhSCUhWANAWcX1IJwrNnz2L79u1UEKaACkCKbESnfOMbPViWFUcHFQqGYfIuOkOhEHp7e2EymWA0GqHXS+vczBVB3GpVLNQsA6NW+le53KTNeHvX7KjGNTuqM35fpsh1cdaoWBzrqJTls1JRiAeMCpMGr9tXh9YK+cRWsuM8uuzD/S/O4n2Xt8KoXbtZGo1GGI1GNDQ0gBACj8cDp9OJgYEBBINBWCwWMUKo1WZ+bkmhVAVgqa4bKA0BGI8gCIUHFyHw4Pf7YxpOqCBcgwpAiiyk8/YrVgQwn9t0Op3o7+/H1q1bUV1djeeee65gdTPCRc6gVeGjr2zP+/akMLuyloaRal+yUcj3DYRhmIJFMqddAfhCHMIcD2D9ecwwDCwWCywWC5qbm8HzPNxuNxwOB6anp8FxHGw2mxghzNVHTqBUhVQpiiiBUl67kL6OzkABL0cIqSBcgwpASs5IGee2kVLA0V2++/fvF9Ng0XV5+SYf28r1wnfPM5MgAD7+yq05rSGfx9Af5vDYuSUcba+EUVuaxfmZML8aRJjn0WiXFj08srkcRzZLKyUA1r5jNpsNNpsNbW1t4DhOtJyZmJgAgJgO42wfjkpVAJbquoHSFoDJHsSlCEJhhvGFIAipAKRkTSbefsUQgPlIAQspX7PZvK7LV+59JITgb0PLqDTr1nXsFlJsSuWOQ43pX1RkZlwBDC560VFrxpaq4s0cTsfp6VU8ObiM91zWCnUOdZf3PDMJjpCcRHk6okWOSqVCeXk5ysvXRGQkEoHT6cTS0hKGh4ehUqlQVlaG8vJyWCwWyQKjVIVUqYuoUl07x3GSHjYSCUKO4xCJvGxWL5hSq9VqMaq4UaACkJIVmY5z2wgp4PiUbzz5EGWPnF2EVs3g3+s61m2r0MczHbmYF0eT6TH0hzkYJHTHhiI8WioMeNslzTDrMotEFVqA/G3IgWVPCLlu8a0XNyLE5e9BYW41gO8/PYl/6G5Aa8V6v0u1Wo2qqipUVVUBWHuAcjqdmJ2dxfnz56HT6cR0sdlsTnqMqQAsPBfi2hM1lUQLQoZhYiKEpS4IqQCkZEwkEhEbOqSOcytlAUgIwejoKBYXF2NSvvHILQAZhsE/X7Ul4egyJUYA5SDTi+mSJ4SfHp/C4c3l6GqxJ30dIQR3PzwMrZrBR67ektE2pl0B/ObULG7ZX48aqy79G2TgPZe1AMg9LZ/vekwGDFQMI7k7XKvVoqamRrRJEjqMJyYm4PF4YDQaxYYSg8Eg7n+pCsBSXbdAqa5dagQwHYkEYfz9r5QFIRWAFMnEp3wzOdFLtQYwVco30fbk3ke7UZPw53ILwIWFBQwMDMBoNIopuugbsFKxGdSoterRliD6FA3DMGiw67G1OvOpLCqWgVrFymuBkwYpx50nBGyR/z41Vh0+em16Qc0TgsEFL7ZVm2L2zWAwwGAwoL6+HoQQ+Hw+OJ1ODA8Pw+/3i5YzwjWn1CjlKFopI5cAjGejCUIqACmS4Hke4XBYcso3nlKsAXQ4HDh79iy2bdsmprDSba/UmkB4nsfg4CA8Hg/27duHcDgMp9OJoaEhBAKBglh8xJPJfmlULG49WC/ptW+7pCntdgMRfl06udaqw7subZG8pkIw7Qrgu3+bwO3dDdhWvVbLGOZ4ybOO51eDsBrUklLncvDCxAp+c2oOt3U3YGeSCTQMw8BkMsFkMqGxsRGEELjdbjidTqyurqK3t1dMF5eVlUGjSfxwpCRKPQJYqhRKeCcShOFweJ0gFEbXKU0QUgFISUm0tx+ArL9UpTQJhBCCkZERLC0tpUz5yrW9bJBDAAYCAfT09KCiokIUf1qtVrwBJ7L4sNvtKC8vh91uT/mE7Q1GoFGx0GY4NaSYF8d7npnEmMOPj127JW/CKMIT/HXIgYvb7DlN9dCpWWjVDIzateP74+emsOIP492XtaQVgRGe4KcnpmHUqvDuAgnbXfUWEAJRrEqBYRhYrVZYrVasrq5i06ZNYg3h1NQUeJ4XLWfsdrtsljNyQiOAxSFfEcB0CFOvBOIF4dmzZzE8PIzbb7+94GtLhPK+MRTFIJy8HMdlFfWLplRSwKFQCD09PbBYLBnP8s1VlIU5Hl99dAjX7KzB3sbUM5Nz2RYhBA6HA+fOnUNHRwcqKioSjpVjWRYWqzXG4sPlcsHhcGBkZETs+BRmxkZ30n3p0RGoWSav3adyc2RzOTyhRehzHXWXgsEFLx4+uwizTpWyZjEdlWYt/v3al49tV4sNx8dXJEUA1SyDa7dXFayeEQAMGhW6W+1Zv5/neajVaphMJpSVrY32i0QiouXM2NgYGIYRo4M2m00RwosKwOKglDF28YJwbGwM586dK+KKYqECkJIQKd5+mVAKKeBMU76JtpdrVM7hC+PpoeW8CUCe5/HJX70ALuTHJ27uFieXRDvoCyy6g7j3xAxes7sam6tMUKlUqKioQEVFBYA1sexwODAzMwO32y3OjC0vL8dV2ypg0Wd+eSlmc0tHrRkdteaM3pPpWrdVm/D2S5rQXC7vCLUddRbsSJJaTcTOEhuRlyiVqlarY85HoXxhYWEBQ0NDUKvVMZYzdIbxhUOhDPkzxev1wmRSjv0UFYCUGDLx9ssElmXBcZwsn5XJNqUIQCHlu7y8jAMHDmQ9zi1XkatRsfjCjTskvTYboRQOh9HT0wMGBBft3JJ2P7VqFho1k9QwWavVora2FrW1teLoJYfDgeHhYej8fugsFszN+VFeXp7X+sFv/3Uci+4QPv7KLZJvtmuTLiC5Zi4RhBB89a9z0DAcPtMm7T0qlsHmHPwHOZ4UtBklX8yuBDC3GsS+ptQPOgJShJRGo0F1dbVo0RQMBuF0OjE9PS0+oAgRQpPJVBBhVqoRQKHWu1ThOE6RNaLCLG2lQAUgRSRTb79MKFYKON384WAwiN7eXlitVhw8eDCni7Uc0SupxzzTba2srKCvrw9btmzBZw7USHqPzaDBey9rlbweYWasUD/o8XjgcDjQ19cXUz9os9nS1mtFeCLZAHnREwJBZpGWz/1pCDwh+Myrsx+jt/YdAYRl5jvaM7DgxY+fm8RdR1pkjyCm48XJFYwv+3Hj3hpZ9vH7z0zCH+Kwq94iSYRnc2x1Ot26BxQhXSxEYqItZ/JBqUYAS1W4Cig5AlhfL61prRBQAUgBADHqJ1fKN55ipPbS1QDmmvJNtL1CiVyp9Y2EEExOTmJ6ehr79u2D0Zi5DUo2sCwrFvC3traK9YNOpxOjo6NgWTbpRIjnZiP47UPn8YEr2/CHMwu4aW8tbIbkT/OfyKLO8JJNZfCGco9If+BILXw+H359ag7z7iDecbg5p8kdqbDoVNCq2aKMsHt21IkwJ5+Yef8VrXD5I5IjsLkKKacvjLlVDjsaGtDQ0ABCCLxeL5xOJwYGBhAMBmGxWMQIoU4nX30kFYCFp1hNIOnw+Xw0BUxRDvlK+cZTjItgshpAuVK+ibYnp8gNhDkMLHiwu96a8Pil21YkEkF/fz9YlkV3d3deL4hhjsfp6VUcaLIlXGui+kGn07mufrCsrAxVBgaOMItAmMeKP4K51WBKAZgNV2/PXfBHU2XRYtkbyov4I4SgZ8aNzZVGfPK6bbJ/vhTefWkL5Hx+sxk0Gf1NcxWA33xyDN4Qh8++uh1a9ZoVh9lshtlsRlNTk9jxLkz7iUQiMR3GSkwn5pNSF4BKXb/H46EpYIoyyNXbT+kkisgFg0H09PTAbrfnnPKNR24B+FDPHJ4ZceBfr966bqJDfATQE4zArHv56+zxeNDb24umpiY0NuZ/Ru9zoy482DsPi06N9pr0F7joiRDR6bmRkRHUaYPY2xiBNrSCt19UC6Mhv9Ms5ODSzeW4dHN5Xj57NRDB4+eXseQO4liHvMJVKizDIOe5dDmQqwD8xyvasOAOJrUlYlkWNpsNNptNjFgLHcYTExMghMBut4uCUInRJTlRqoCSilIjgLQGkFJ05PL2UzrxAnB5eRnnzp1De3s7Kisr8769XLlmZw1aK02oTWDXES02V/xhfOuJEexttOFVu2sxOzuL0dFR7N69GxZLfrs9J51+PHpuCa/bVwurQZ1Vg0N0/WBDQwP+/ve/o7GxEQ6HA7Ozs4hEIjE3XyX6veUTm0GD1+2vRZW5cLYtSiTecDcTQVhm1KAsyVSdRPyhfwlhjsdrOzcDWIumx1sgCeliq9W64a6hVADmB5/PRwUgpXgIHnBCimOjRf2iEVLAhBAMDw/D4XDImvJNtD05I4AWvRoHk3jFRae3rXo1NlWa0NloxdmzZxEIBNDV1SVb2irVyLGhRS9W/GGoWBZ7G6wpP8cX4vClR4Zxx6HGlKPbog2Ao6MxDocDY2NjKesH84ESRq412hM3Kaz4w1hwh7A1A4PlUscTjOALfx7CsfZKHG2X/0EOAI6PuUAAvLazDsCa5UxlZaX44CiUMMzNzWFgYABarVYsYTCbzTEzjEuRUheASl0/jQBSiobg7edyuRAOh2G324u9pLzCsiwikQief/75vKR8E22v0JNAQpG17d2wqwI9PT2oqalBR0eHbMI+GOHxyYfOY1uNGXdevH6U2hVbK3D51gpJAskX4uALcRhf9qWd3RuNYDhdXr6WYhVuvrOzszh//rxo71FeXg6j0SjrQ80f+ubx12EnPnrNlqx8DfPNV/4yCl+Iw+de057x1JVSRadmwTIMDHlshvnUq7YhlXSLLmEA1qbqOJ1OTE5Owu12izO1hQfQUnvQVqqAkopSI4C0BpBScOIbPdRqNYLBYLGXlXfcbjcWFhawd+/evKR84ynGLOB//10/AsEg3tASwI4dO8QpCXKhVTFQq1i0JrEdYRhGcmlYpVmLL920Pfc1xd18Bf/B0dFReL1esZuzvLw8527OerseGhUDvUaZN8N/vLwV86vJa9uUBE8InhlxYn+TLadOZo2KxWdfk719jxQy9VrU6/Woq6tDXV0dCCHw+XxwOp0IhUI4fvw4zGazGCHMVwZCTjaCAFTi+n0+X97LcjKBCsANTiJvv2J48kWvJ99Pw4QQDA0NYWlpCeXl5QURf0Dmk0fk2FaHNQK/L4CDBw9KEjscT/CnM/M4sqVCUhcmwzD4jzzfbHPFYDCgIcreI1E3pzC/ONP6wc5GGzrTTGUpJpVmLSrN+TPZzgRCCDiCpJ3QY8t+/ObUHHwhTvYu7GIgPOzFX88YhoHJZILJZMLs7CwOHjwIj8cDp9OJc+fOIRQKwWq1ijWE+TRJz5ZSF4BK9QH0+/1585zMBioANzBCo0e8t59KpSr4VA7g5RRpPr+Y0V2+u3btwsjISN62FU8hp51wHIepqSlc2lqDLVv2ShbVk04//ty/ABXL4NqdsYbQxRzDJhfR9YMtLS0x3ZzR82LLy8s3ZPF+Mfnu3yYQ4nj84+WtCc/HtgoD3n64Ga0ViW+AhBD8++/Po8KsxT8f3ZRyW/2zbrwwsYI3dTUUbTLKv//+fMoHpGiBaLFYYLFY0NzcDJ7nsbq6Kk4pEUzSldTkpFQBlQlKTLsTQhR1zSn+mUaRnXTefsWKAKpUqrxeWJaWlnD+/Hl0dHSgoqICPp+voPuZiYBy+cKYdwclWaYAgDcYgVGrAsMwojVFTU0Ntm7NzAS5pdyADxzbnLSpQG4CYQ48QVHMi4H19YPCvFiheF+n04mpObnGgxFCcP/JWWytMkkedVYo8iXwgxEedTYdvEEu6TFkGAbbU8xaZhgGBIDDm3p6DwA8OeTAij/961y+MJz+cEY1p1JJd64ki6KxLAu73Q673Y62trYYk3ThIUUQhDabrShCTKkp1FJGiQ/XVABuMKR4+xVLAOZru0LK1+VyxaRCC72fmWzvSw8PwBvk8KXX7oROk/oCv+IP4+MPnsW+RhuubCCYm5tDc3NzVl2+DMNgU2XhOkY/9X8D4Alkqf2Tg/h5sfHjwVLVai15QphfDWJn/cs1PIku6gzDwOEN48XAatEFYIQneHbEiYs3leVtQgkA3P3wEFz+CD5/fW7lAp+/vkPS6+460gyepK/Vu+fZtZFzH7lmi+z7n640Qmq5S7xJejgchsvlwtLSEoaHh6FWq8V0cSG63oHSTwErFaX57VIBuEGI9/ZLdaIVOwUsJ4FAAL29vSgrK8PBgwdj9rlQAtDhDaF3ZhXbzNKf8v75qi2YdgXSij9gzeal1qpFJbcIn8+I7u5uzMzMFOVvmCk37a1FMCL9bxAIc5j3FU60GwwGGAwG1NfXgxAizi8WarWESExZWRn+6/G1jtu7b+iIabpI9D1716UtBduHVJyaWsGvT83CoGVxsNkuSZSEOR5jy/6MrGXuOtKM8/NeGCScz3LAMgyk6Lm3HGqEwxvOq/hNRrYiSqPRoKqqShxPGQwGY6bm5CNqHQ/P84pIRW8kCCGKiwLSv/AGID7lm+6CUMwIoJyiJT7lm2h7uXzhnh5eRq1Vn9bc+MHTs3h+woX3XVQJlcTjWmnWoVKisa/H48Hl1mW0tbWJg8RLpV7vorbMupIfPruIZ6Y5HA1GYNIV9vIUXasl1A+urq7C4XBgfHwcxyoATmuG170Ctc2W1wjJgjuICYcfmyqNKDdl3ySwt8EK/SUqtNdIF3MP9c7jiUEH/uWqTWgqk1YqUGvVo9aqvO7WCpMWFTkcv0yZcPjRVKYXv59ynCM6nQ61tbWora0FsD5qbTKZxIcUg8EgiyAs5QigUq+LgUBAUQ0gABWAJY/g7Rff6JGKYkYA5fhy8jyPoaEhrKyspOx+zaUrl+MJfn5iCjq1Cv/vdbtSvvaWAw04tKkcFaoAnE5vVttLxvT0NM4OjeHvbjt0jQbUv/RzJQpAly+M+16cwU17a1Flyc5+5Wh7JSKLYwUXf4mInvYAvFw/uLCwgMHBQeh0OqjVamg0Gtm727/86AgGF7y4fnc17rykOevP0ahY7IpLWadb59H2SpSbtGiwF0bQcTwBTwg0qtIUHALn5jz41lPjuLmzFldsqxDLcOQmPmrt9XrhdDoxNDSEQCAQU8aQrQ1SKQtApa5dEOtKovhXWUpWRKd8EzV6pKKUI4CBQAA9PT0oLy9fl/JNtL1s91PFMvjINdskmf+adGp01FqwtBSUTZRxHIezZ8+C4zhcclEXev42ETPrVy4xLSfBCA+OBwIZpHzjMevUaLQo7+INJK4fHB8fh8vlEr3ehA7j+PrBf/vtWTAMg7tvkFbj9vZLmrDoCaWdrhLNwIIX7kAEB5pzqzu0GTS4fOv6iHq++OiD58DxBF++aXvM9/mHz07CoFHh1oP1Kd6tHDZVGnHdzirsf+n4F0KIMAwDs9kMs9mMpqYm8DwvljEINkjRljNS64aVKqKkoNS1K80EGqACsCRJ5O2XCaVaA7i4uIiBgYGkKd94cn36bpSQ/np+zIk/9S/gA8c2y+YD6PP50NPTg/r6ejQ1NYFhGPzzVVtiXpMoAvg/fxtDiCN4z+VtOa8hG2qsOrz7suS1b2GOx7k5D3bVWxRVCJ2MSacf33hiDP929eaEaUSDwSCm3Zqbm9d5vUX7D0q3y16jvcaM9pr0r4vmnmcmEOYI9jdZkx5fJU6lONhix5IntG5dq4EI3IGI4h50kqFVs3jlzmrx38U41izLxoxR5HletEGanJwEISTGciZZh7FSRZQUlDoFxOv1wmiUvxs9F6gALDGySfnGU6z0YbYCUEj5rq6uSjY8loNJpx8alkGtLUUqjAEYrJnfhmWIygnpxV27dsFmSx7JSSQ2+2fdKcdXFZu/DCzjod55/OMVbdhWArNrHb4wQhwPb5BDRZrlJvJ6E+YXT0xM4JYmwG63w+l0wpan+sF/e8VmBCL5STvmk1v21SX8+fuvXHuQyVcqNZqxZR8eODmL91zWKptlkRJElDA3WyhjiEQicLlc4uQcwZJGsJwR1quEtWeLUi1slDYHGKACsGRI5+2XCcW6QWQjAIWUb0VFBQ4cOFDQtf/P38agYhl84lXJ03YHW8pwsGXt4hrIQVjzPI/BwUF4PB50dXWlnQ6Q6Dh85ZbdWW27UBzeVAaLToXNlcp6Ck7G3gYr/ut1O7N6b/yNV7D2WFhYwNDQEDQajVinZTabZTmvpTSLEEIQiKzNZS6WN2OmFCKSNrMSgC/EIxThZTsuSjP9BQC1Wo3KykpxOpIwG1548NRqtSgrK0MgECi5BwkBpZpYUwFIyYpcU75KIVMBKKR8t2/fLhr5FpI7L2nJqDA92whntMjdv3+/pL9vIcfOyYVZp8Ylmwr/d8w3A0tB6MoCKbtg4609AoGAGB30eDwwmUyiIMxnpyAhBP/TG0DZ5Hn8v5t35G07clIIAXjJpnLZz81CRC5zRavVxtS1BgIBOJ1OeL1enDlzJua8NBqNit8fQNkpYNoEQsmISCQiyduvFJAqkIRomNvtlhQNyxctGU4PiE+tO30hmLTqGM+4eBwOB86ePSu5rjHZtuSglM+tYhHhePyybwUPT4ziyxmYXev1etTX18d0cjocDgwMDCAYDMJms2VcuC+VK5u16NiW38aK7/5tHABw15Hc/RCVWLcYTZjjEz4olmIaVa/Xo66uDktLS9i8eTMAwOl0YmRkBD6fT2x0yveDSi4o9bjTJhCKZDL19isFpAjAYqZ8QxEehBBJ5syJiI7KcTzBNx8fhUHL4l9esX5cGyEEo6OjWFpawoEDB9Z1jUrZVqkUx2fC2LIPvx8JY9+BxDdVufh97zyWvWG85VBjTp+jYhm8ubMMDfV1+P7TE3jlzqqMx+xFd3JG1w/GF+5XVFTAarXmFN0ghGBPtQZ7W+xZf4a07QDZfnX/PubEI2eXxOkdShaAUy4/vvTwMG7vbkR3qz3md0pedzoEI2itVguj0YiGhgbRKN3pdIoPKhaLRYwQFutBPR4lRwCpAKSkRco4t1IknQAsdsr3Qw/0AgC+ceverN4fbc2iYhm8YkcVGhKIgXA4jN7eXhiNRhw8eDCrp9V0AjAY5vCvvz6Do+1VuLEzcZG9EnlqyIGRFQJfiIPNkD8B+PjAMnhCAOQmAAGgtUwLq0kraTKFFBIV7n/rL4MInR3FFbUcNBqNaDcjV/2g3OQyCeXP/YtY8oTEfytZSFl0aujUKlRZ1osfpUaipJCokSJRo5Pb7YbD4cD09DQ4jouJXBdrkohSBaDP58soy1MIqABUEPHj3PJ58RCiVYW8QLEsK+5bNJk2QOSLV2yvRoTPPqoWL8oOta0XsSsrK+jr68OWLVtQU5Ohz0eKbcWjVrHgCYEvFMl6G8XgjQfr0RSZhs2gQSjC494T0ziyuTzlWDJCCCJ8ZkbCmaRrpWA3avC2HAybU6FWq2GzmFFZX46uXTVinVZ0/aAgCNOl5ZQspgT+9apNcAc5cXybkmvpbAYNvvzaxOdSKRzrZEi5N7AsC5vNBpvNhra2NnAcJ0aux8fHwTBMTIdxoUSZUoU3tYGhJIUQgnA4DI7jChL1E6JxhfyiqFQqBIPBmJ/5/X709PSgqqpKcgNEpiS7EPM8ARsVtrl+b26RslQRTkIIpqamMDU1hc7OzpTFwDxP8I0nRtBebca1uxKLxHQCUMUy+GYWkcxsb1rZiLBEaFQsTJq17TPMmrn0oieUUgB++LfnEIxw+MrNOyXPfFVlGa4jhMAb4mJMuQvBWy5uEv9bqNOqq6uLmQQhpOWsVquYlouvHywFUfKj56bgC3N4/5WbxBSwEm/o6VCqEJFCNueJSqVCeXm5mL0ROt+XlpYwPDwsTtYpLy+HxWLJ27HhOE6Rc4w9Hg8sFkv6FxYQ5R2lCxA5vP0ypRjTQOK3KVgP7NixQ0x35Wub8U+foQiPz/7hHLZVm/EPh+SJ3CQTZZFIBP39/WAYBt3d3WmfhFmWAccTjC77Mt5WMZhfDeIbT4xiJRDBV27eIVvtnkbFSkolXtVeiUfPL0kWf7nwvacncGpqFXff0AGbQd7mjGxINAlCmF8s1A8KKblUvpJK4uZ9dZhfDYp/z2KKVqcvDI2KyUrw8zwPnXsc2qd+AtX0cQAMuKZDCO98PUhZcczaMyHXYx7f+R4KheB0OjEzMwO32w2dTieem3KWMnAcp5h6xGiEJholQQVgEZHT2y9TijENRBgFV8iUbzIBqFExULOspGkfmW4rGo/Hg97eXjQ1NaGxUXq9Wfzkj3jiBeD8agC/75nDmw81p+w6loIvxGHBHUSrhC7omZUAHnhxFg12A/yL3ozEHyEELn8EZcbchNQ1O6pwzY6qnD5DKke3VcLpC8MqYURgMRCMfe12O4CXjX+FKAzLsohEIlhdXYXFYsGfzy7ij2cW8YUbOhTjC1ht0aE6apZ0vADkeIIP/bof26pNeM9lrRl9tssXxrI3hM1V0uw4PvHQeahYJis/SN1SH2pP/RdUWi2IvgwAgWriGagmn0Xw6H+Ar0k9Y3yjodVqUVNTI5a++P3+mFIGo9EYY4WUrSBUsg8gtYGhAHjZ2+/kyZPo7OwsysigYkQAQ6EQTpw4kdeUb/w2E0XKGIbBJ1+d2ODZH+LwhT8N4M7DLZJEUPRnRm9rbm4OIyMj2LVrF6xW6TNds9nWsyMOPDPiwNU7qtFcnludyccfOg9fkMNXX7cD+jQd0TUWHS7ZXIbtNWaYMoySfO9vEzg5tYrPX98uycRYCWytNuEjV6cW50oi3vjX5XJhcHAQU1NTcLvdGFxSwecHuHAQ0GZ+3hBCwBHkNfoaLwCF9L3Lt76eOB2f/sMAAhEeX79lp6SHldu6GrITxnwElb3fA68ygBhfzm4QUyUQdEP7zP9D4MZ7AKY0U8RyYDAYYDAYRCskn88Hp9OJoaEh+P1+WCwWMUKYiUuCkieB0BQwRYz6EULg9/uLkt4oRgRwZWUFCwsL2L9/f95SvvFkY5i84g9j2uXH6UlXVgKQ53mcP38egUAAXV1dsvu4AeuF7XW7anHxpnLUpDAjlsq/HNuEwUVfWvEHrN2MDzbbs9rONTuqwAM5RwAp0tFoNDAajdixYwcIIdjl862NBRseQiAQgNVqFW+6UiLzH33wPFb8YXxNoqA6P+/Bd/82gc++epvkBwae5xGO+wpnO6Hlw6/YjJmVoORI9aG2MvzsxDRenFzNyDKIXewHE/aANyWITOssYLxLYJfOg6+StxmpVGEYBiaTCSaTCY2NjSCEwO12r5utLcUbU8kRQJoCvoApZso3nkJGAHmex8DAAFZWVlBRUVEw8Qdkt5+1Nj2+eevejFOpDMOA4zicOHEC1dXV6OjoyJu4j48AatWsJPHH8QSL7mDK+cZ1Nj3qUs0/lonWCiPenYNdSKFYdAfBEaDWWpgZ1IUi+qYr1A9G23rwPA+73Y7y8vKkXZwXtdrx+MCyZEE1uOCFL8QhEOFhkng4v/30DPpnVvCdrbmPr8vm3J5w+jPeDhN0g4ABgyTff4YBE3Rn/LkXCgzDwGq1wmq1oqWlJcYbc2pqCjzPi4LQbrfHNH0o1QaGRgAvYJTm7SfU4+Ubocu3uroaO3bswMjISN63GU22QteQxY1meXkZPp8PXV1dosj1hzh876+juHl/g6z1htk2gXz54UGcn/fgq7fshr0EIm88IXj//WewucqED1y5vnB+yRPC73rmccOeGlSa85NG/n3fAnie4O2H82PzUkgIIXh2OohFzTKu2BbrSRZv6yHUDy4vL2N4eBhqtTqmi5NhGNy4txY37q3F8xMu9Ey78ZZDjWBTXNtevbsGr96dmf1Rd7MZQwurMGiK88CcTcqfN9eCIfyaI3Y8hACEA29Rpj+nUprLoknkjSkIwrGxMTAMI/5eqSngQCAAnU5ZD5FUAOaZQnr7ZYJKpcp7BDC+y9fn8xW87rAQ3bKEEAwPD8PpdMJoNMZEOP1hDp4Qh0mHL2sBGIrwYJk1bz+BbPfr9oua8PcxJ2yG9V/9Yj+URCPUfQliItoYOBruJd/GXPwb03HDnhrwST6fEIKVAJd0HFihODPrxolxF27vbkxbj/fkRBAnnbPrBGA88fWDwWBQjMB4PB4YDAaxaP/FiRWEOJJS/GXLvgYzmnTlijo/00HKNiFoaoIpNA/oYwUv43eAr9wBYmtK8u7iUgpWQWq1GhUVFaKxcjgchtPpxMLCAhwOB0KhECoqKmIeVpSAUu7/AlQA5hEp3n7CjXwjNYEIKV8hGibUEinBemZtfbH+f7ng9Qfwv4++iCu3VeLgwYN49tlnY35fbtLiY69sz2kb7/3FaagYBt+5rVP8WTa1jQDQWGaQNRKZD+K/C994ffJuyRqrDm+7JLMbaabft4oUDSoRnuDLf1tE2WkfvnZLdnVpcjDh8CMQ5pMlHEUIIfhAtxUd7ZmfkzqdDrW1taitrV1XtN+pDcBisWB+fl72sWClIEjWwTCY2f42bD73Lag9C4D6peMRCeETK69ByHgRPlncFSZFqTV0qdBoNKiurkZ1dTW8Xi/a29vhdrvFZieDwSBGCE0mU8HPJyVGVQEqAPOGVG8/IRVbaOPKfDWB+Hw+9Pb2orq6Gu3t7TH7rQQB6AlE8E/39eCyLRV4yyW51Z+5XC788ske/HVBi707KiRdVFy+MP7tN2fwvis2YXeDtM7gg812lMWJECX5AJYS/jCHn52Yxr5GK/Zn2bwSjZplcLjZhEt3Fjc9/Mqd1ZJeRwiBSauS1IAR4UnSaGJ80X6y+kGhRivX+cVSvlsRnmBs2YctEi1e8k1QVwHn0S+jzNUD1cQzAACu5TKEztaDMMq99ZaygTWwtn6DwQCTySQ+rAiWM2NjY6IdS7TlTCFQQulXPMo9C0uU6JSvlEYPQYgVWgDmQ4zNz89jaGgIO3fuFH3I8r3NdMRv06BVQc0yaM6guzceQggmJiYwOzuLW48ewEFnGLvrpYm5MMcjzPFYcAfTv/glbuysw29PzSIQ5sTO3I0sAPMZFdeqWKhYJmPLmlRc125FU13y4m5CCF6YXMG+RlvWE0gKzdxqEJ946DxuPVCPo+2Va93tJPkElUT1gysrK3A4HBgZGYmZEpFpSk7qufCL56fxl4FlfOq6bWguL36Um+d5MDoLuC3XgttyrfjzT25O/Prv/HUc064APvPqbUUVCkqtoZNKvIBlGAZGoxFGoxENDQ3i9ByHwyFOz4m2nMlHnV6h73tSoQJQRgRvv0waPYphxyL3dgXbE7/fn9LYuRgCMF4oqVgG37t9X8af0zezCjXLYEulAX19fdBqteju7gbLsjiQQWNXlUWHH7x5f0bbnnQGsBqIwBfKTgA6fSGUGbNLybl8Yfzq1Cxu7qxTRNNIKMLnZHStYhm85VBha69OT6/iW0+O401d9XhFR2EMq5MRLaZ4krxmz6JTQaNiUfNS5/MPn51ChCd45xFpkc74Gq1QKCRGB1dXV8VaWWF+caJr5YuTKwhHeGwySxOA1+2sRrlJi8ay/HewSyHTh5gpVwA8X/x0d6lHANMRPT2nublZjF47nU709/cjEonEdBjLYePl9/sVNwcYoAJQNoSoX6bj3ArRjJEIlmXFxpRc8Pl86OnpQW1tbVrbk2SmzLng8Ibw3afG8I9HNyUc10TA4L+fnsZ1nWocbLFnvZ2vPDoEnuPwzvYwWltbUV9fn8OqM+NAsw37m2wxdYtSBeAjZxfwv89N4GOvbEdHbXKlyvM8zp07B6/XKxZPG41GuIMRBCM8PKFIQQVgon1zByL451/140CzTdKIOKWws86Ctx5qzOn8k8qfzy4iHOFTdtoyDIMfPTuJCCF4+yWJBZ1Jp8a33vBy7WVrhQFzGUSt49FqtTH1g36/Hw6HA8PDwzGmv+Xl5eID5DMjThBC0LZDWs1WuUmL6ySmwgsBz/OI8Gv7cajNnrZB5j9ek1utsFxsdAEYT3T0urW1FRzHiR3GExMTIITkXM6gxCkgABWAOZOrt1+xIoByROPSpXwLQf+sG/1zqxha8KKzaf2sU5Zl4fSF8cT5xZxuwO/qKsPs9DT27OksuJnn2gPF+p9JEYC7663YUWdNOR3E7/fj9OnTqK2tRX19PVwuF0ZGRsQb883t5SgzFq4oPNnN3qRTQatmcaA5t5m2Uy4/aiy6gnXtalQsLtuauuM2EUueED75fwP492u3SPau+82pORBCkgpA4ZyptuqwmIGgO9peKfm16YhOyUXXDzqdTvT19YHjONjtdry2Y22k3apzuSQFCSEEp2c8+NN5FypMGrTXKMsEOBmlLgBzjaBGlysAL49TjC5nENLFVqtV0rGiAnADIoe3X6H8+OLJRXhGp3y7u7vzMulCKhdvKsf2WgvKTYnXoFGr8K+X16OuLjvPLY7jcO7cOegiEbzqikMFr9VMhtRzrdamx/937bakv19eXsa5c+ewY8cOWK1WhMNhmEwmsVZmdXU1prBfiNLYbLaC3yRYhomJSmWDwxvCQ70L2FVvwZHN5SlfG+Z4zK0G0VSkrukFdxD+EIeZlaBkAfiVm3ekfDAQMhRKipQlisC4XC44nU7MTI4jEonAYDDAZrPBYrGUjDjheR77m2yosZsV05gihVIXgHITb4cUCoXgdDoxNzeHgYEBaLVasaHEbDYnvDZ7PB4qADcK8d5+uXT3FDMCmM12M0n5FgIVy6AihQFwLg0Fwr7W19ejqakp5WcQQvCrkzPQ+PiSsK0ghGB0dBRLS0s4ePAgdDrduvOBYZh1hf2C19bg4CB0Op34pGw0GmXd53w0uBBCUG7S4sptFZJE3Rf+PIzRZR++evN22LOsocyFHXUW/OAf9mb0nlwnZSgBlUoVUz84MTEBj8eDmZkZuN1u6PV68Yab6rwjhCDCE9kivWGOx6mpVexvktbMw/M89Fo1OmqL35CSCaUsAIVgTD7RarWoqalBTc1alN3v98PlconnqVDfarfbYTQawbKsIsfAAVQAZkx8yleOcHOxIoCZpoDn5uYwPDyMXbt2wWbLLQ2XjqEFD/54Zh7vvqwtxgA5U7JNdQsiR2p6ezUQwa9PzqIMEVwT5vDw2UUc7ahKWJeYDx7qmYPDF8KbD6Uv0o9EIujt7YVer8fBgwclX+zVajWqqqpQVbXWyCDUcY2MjMDn88FqtYo35lx84DL5Tq0GIphy+rEjRRcusDbf+UO/6serd9fgxr21kj777Yeb8Pz4Cn57eh5qFYPbu9PPgiWE4Len57C30YZNlcor+k73cOILcTBoWEU9wKhUKthsNjEqLVh6COedxWIRz7voDs4PPtAPTzCC77xpT1pzbCn0zbjxf30LMOvU2F6b/mZeCg+CiSh1AVjotRsMBhgMBtTV1cX4Yz755JP42Mc+hm3btmHLlsymydx555146KGHUF1djb6+PgCAw+HAG97wBoyNjaG1tRX33XefOHTgC1/4Au655x6oVCp8/etfxzXXXCNpO6X5Vy4SgrefXOIPKG4TiNTt8jyP/v5+zM7Ooru7O+/iDwB+c2oWz4064Y+fAp8hmQpAIb09OTmJrq4uybWNNoMGn7thO25p12HK6UPv9CpGFr1ZrjpzJpw+uAORtK/zeDz49WPP4eEpFi2bt62zS8gEg8GAhoYG7N69G93d3WhoaIDP50NfXx+ef/55cTpKLuf3U4PL+PuYM+nvnx1x4KkhB3yh1A9RBo1qLVqcwtQ5nnqbHtfvqYFaxaBBYgo2xBH8rncB//WXwo48BNa6eqXiDkTwo+cmYyashDke77uvD+/5ZV8+lpc10UJKqB+MPu8aGxsRCATQ39+PEydOYHBwEEtLSziy2Q6NipVF/AHArnoL3niwHlurpaXy5BQjy97Ek3DyQSkLwGLPARb8MRsbG/GqV70KL7zwAj74wQ/C6XTisccew759+/Cud70L999/PxYXF5N+zlve8hb86U9/ivnZ3XffjWPHjmFwcBDHjh3D3XffDQDo7+/HL37xC5w5cwZ/+tOf8J73vEdyUIlGACWQqbdfJhSrBlDqdoU0aF1dHbZv316wJ9r3H90MTyCM7/9tDDvqLLh2Z2bzQwVYlkUkkl4YAWujrnp6elBeXo79+/dnvK9tlSYsalVoLtPj3Ze3wWYoXG3key7flPY1pwcn0DM4ji1btmBh2p92akQmRA9vj04XLy4uZpwujm5w+dHfp8AyDC5qLUv42su3VmBvYzht6lOrZvHdN+3Jat+kRP4EdGoWn3tNO+wJRu3lk1+dmoXLF8ZbDjWlTE8KYsof5hAI83AHI+IMZY2KRVOZAVdsTV0bWWhSRdKiz7v4+sFW3oV3tLMYHR0V/QdzuXZrVGxGjRxyRQD7Z9347t8mcFtXA7pb7Tl/XjqoAJQPlUqFiy++GCMjI9i7dy/e//734/jx43jsscfwrW99Cz6fD9/+9rdx4MCBmPdddtllGBsbi/nZ7373OzzxxBMAgDvuuANXXHEFvvjFL+J3v/sdbr31Vuh0OrS1tWHLli04fvw4Lr744rTrowIwDdl4+2WCSqWSxY4lm+2mi8zMzc1hZGQEO3fulC3qJ4wwS3eB0apZlJm0mHT6MbcayFoASh2Z5nA4cPbsWbS3t4vFvtluD1izpFAKPM9jcHAQ//HILLQGE358TQ0u3pbfC3yidLHT6cTo6Ci8Xq+Ytou2/UjEl27cjlQBHL1GhVpN8S74iWoVG+yF96FrLTegP8hJNpqutugSWul8+lXJG4aKRSZCKr5+UCjYn52dxfnz56HX68VGplQPIpNOP/6vbwFvu6RJUg3hsyMO3PPMFP7ztdtj7JLkuF+0VhjR1WJDe01hmghKWQAqde0+nw9msxlarRZHjhzBkSNH8MlPfhJer1fyeufn58Vmxrq6OiwsLAAApqencejQIfF1jY2NmJ6elvSZVACmQOo4t1xQqVQIBAKyf66U7SaLAHIch/PnzyMYDKKrq0vWLl8hJZvspPcGI+KUBoZh8NVbdsuyvWQQQjA2NoaFhQUcOHAAen1uN+9imF2nIhQK4fTp0ygvL8fXb78Ii95QTjWV2SLUydTX14MQsjanc34J09PTos9WeXm5mHIXhFVligYfAZ4QuAORgkZco8nmusATApJiskamHGi244CE0XalWJeWbM39s25sqTKlNAZPVLAfXbca7T8YXT/48NlFPD3ixGs7a1FtST8Zwh/mQUBi7JoGnRFY5z1Jo4aEEPz57CIubitLee4ataqMotC5wvN8UZ0dckFpEUABr9eL6ur1nfdydAYnegiV+h1XnlRWAIQQhMNhBINrPlksm7+iaKXVAHq9Xhw/fhwmkwmdnZ2yXwhSCaSBeQ/+5Vd9eH48ec3XuTk3AmHpKfNU2wuHwzh58qQodHMVf8DL6UueJ5h0+nP+vFxwuVw4ceIEWltbsXnzZtTZDdjTYIPDG8JPnptAMMlxjK8lzKS2TAoMw4BoDPj80yt4wlWGzs5O2O12LC0t4fnnn4fH48H09DQ8Ho+kbuAP/qof/3jfGfgzOC+KzTvu7cE7f9ZT8O1mIgA5/uVjv+QJZfS9k5NEa55dCeAPZxbw/IQro8+Kr1ttbGxEKBQS6wcHBgawtLSEN+6vxX/etF2S+APWfBLvuX1vjJB7ZobHAydnk75ndNmPe49P46He+Yz2Id+U8ig4pa7d6/XmPAmkpqYGs7Nr59Ps7KwoKBsbGzE5OSm+bmpqSvKgAuUdqSIjpHzlbPRIhZKMoGdnZ3H69Gns2LEDLS0tedn3VIKs2qJFpVmHprLEX5RlTwjfeWoMv3x+SvL2khkmr66u4sSJE6ivr0dHR4dsFw0h5fzDZ8fxoQd6MbpUuEaQaCYnJ3H27Fns27dPTMMKTLsCcPjCWEnQNHJm1o13/6IXz4w4AADDi158728TcMhchG7Vq1Fp1uIVHZWiz9a2bdvQ3d0No9EIlUqFsbExHD9+HP39/Zibm0MolHgNdx5qRGeTFYYipoKBtTF1UtlUaVTEvNpk+EIc7vzpaXz1L6OI8AT3vziDX7wwU5S1JBKAtVYdbthTi/1R5u+EEHzy/wbww2cn4z8iIUL9YEtLC/bt24f9+/ejsrISLpcL/X09mBrsw8jICFwuV1YP6Tdt0eB9l7cm/X1bhQEfumozburMzqM0Xyg1jSoFnucVGwG0WDKYGZqA66+/Hj/+8Y8BAD/+8Y9xww03iD//xS9+gWAwiNHRUQwODqK7u1vSZ9IUcBSRSEQWb79MKKYAFISRYHYcDodlT/km2m6ii+kdP3oBHE/wk7ceSHrcy00avLGrAe010r9I8dsjhGBqagpTU1PYu3ev7OacwnF99e5aaFRsygkc+YDjOJw9exY8z6O7uzvhxXBXvQUdteaEtU0NNj2qLTrRwkSYvqHLYf5uIhiGwX+9bmfC36nVatTU1KC5uVlMFzscDvT19YHneTFdbLPZoFKpsLfRhr2N+e9MT8WDvfNYdAfx5osaJdWMfezarQVY1XqkRgANGhZqlsX2GhPULIOj7ZUZdVDLSaI1MwyzrhuXYRiMO/yYcvrx1oszn/ccPwEiHA6Lhr+PvXAOtVYdmmsrUVZWBpMp/Xg6q45JmdplGAadjVZJayOEwBviCmIrVcoCUMkp4Ex8AN/4xjfiiSeewNLSEhobG/HpT38aH/nIR/D6178e99xzD5qbm3H//fcDAHbu3InXv/712LFjB9RqNb71rW9JPgZUAEJ+b79MKFYXsIDX60VPTw8aGhrSmh3LQTIBWGfTY3YlkLY79KI2aR2KhBA8O+JArYEXt8dxHM6cOQOGYZKKo1wRIo41Vr0kTz658AQjeHF0EVrXeFrjaoZhoFEl/p3dqMFXbt4h/rvWqsedaW6mHE/gCeanBi++y1MYy7S0tITh4WFoNBrxpi3lppwv9jZYcXJyJS/j5ZY8ITx8dhE37q0tmNEzwzC45/aXu6aLOcYsk7T1jyQYZ8+uBPDRB8/j06/aljIKq9FoUF1dDVt5JX41NoypVQat9SzGxsbEG7pw7kXXD+aDr/xlFC9OruC/37Ar77WupSwAlbr2TEfB/fznP0/488ceeyzhzz/2sY/hYx/7WMbruuAFIM/zWFxchNfrRX19fcFvIMWKAAJrT7inT5+Wtcs3HckE4N03JY4GZYs3yOH3PXNosqlxWTURhW5TUxMaG/NXUF2sJpD/+nM//ja4iP+6ZReam7PrmM6Wu37Wi0CEww9u35uyIF8qwncwFFmrobp8a4XYWRs/likQCMDhcIg3ZandxXLTUm5AS55Suiv+MHwhDv4wl7MA3EhNINmy4o8gwhM4fGFJaXidmsWtB+pRZdHBqleLhtQejwcOhwP9/f2IRCKw2WzijFi5R0Ze3VGJaVcAVj2NAKZCyRHAXFPA+eCCFYDR3n6hUAgej6coF8ZiNIFEp3wPHz5c0Pm2hRJIZr0a77y0FSYmjNGh8zh9+jR27doFq1VayiVbktUcZkImNzxhpNvF5T5c/ModaG+SPuM1GObw0+OTeMPBRjG1lM134D2XNePpEacs4k+AEAKOJ/CFOMysBBJaqxBCoNfrUV9fH9NdnCpdrFT+55kJ9Ey78bXX7Vj3N9hcZcJmmWbJyi2mfn1qFr/rmce33rArb+lJQggIgM//eQjdLXZc1ZG9TRMAdNSa8ZM7OjN6T/zxZxgGFosFFosFLS0t4DgOKysrcDqdGB8fB8MwCAaDcDqdsszN3t1gjYnM55NSFoA8zytmXns0dBScghC6fDmOW0uHaTRFi8IVOgIYnfJ1uVwF/7IUMkLWUm7AmTNrdg9HjhzJS20jzxOwUVYecgjA23/4AhgAP73zYMrXEUJw8uRJGI1GWBu24vj4Cg5v5aGX2AxxcmoFfzyzgLZKE462V6V/QxL2NtrQ2SR/BNmoVeHthxOn0f/QN49fvDCLr9+yU/RdS5UuHhoaEoe2FztdnIi/DTvB8aUXnROQu0Y0GkIIVCyL/lkPhha8GQnARXcQvTNuXLGtAmwej218/WAoFMLzzz8fMzdbsJtR2rkXTykLQBoBzIwLTgAm8vYrZhq2kDWAMzMzGBsbEyNhU1NTBU8JSRGA86sBjC77cEhivV8iAoEATp8+jbKyMlit1ryIv9mVAP73uQnccqABbRVGBMK8LAKXAZDuT+LxeODz+dDW1ob6+nqcmlwBwyCjsVcHm+34wo070FqRW6PKj5+bgooF7jiUeeF9IqSIaJ1GBZYBdJrkNyqlposTIaV2TQ6E7/snHjqPQJjHl27antPnvbazDq/Noou1b8YNs04l6dwjhIBlWfzwH/ZkfK36+7gLZ+c8uKjVLvqLJmLS6Yc3yKFDwoxfKahUKuh0OrS3twN42Qg9vn6wrKxMFvspOaECUH5CoVDRrzGJuGAEYHyjR/QJXmwBmGvEKB1CZ2gkEkF3d7cY9RNutMUSgKenVqBVsdheF/tk9KEH+uAPc7j3zoOSo1nRLC0t4fz589i+fTtMJpM4TFtudGoWWhULk1aF9/6iB0ueID5+2Jrz3zNd5E+Y0GI0GkWD286mzKNwahWLrdW53/BqrFqYtIW9lBxrr8Sx9sxSganSxRzHiREapaeL5WBs2Y/8XnWSQwjBF/48BLWKwY/f3Jn29cIUpmwabK7ZXoUjm8qx5A3jvb/sw1du3pFwSs+vT80hFOHRXiNPdE5Ys0C8EbrH44HT6cS5c+cQCoVgs9lEI/RimzCXsgBU8tqVGPW9IARgunFuKpVK8rzYUsPj8aC3txeNjY1obGyM2XdB+BbyCxNd8/i9v46BZYBv3Bob/fjKLbsx6fQnFX+r/jAsevW6vyMhBMPDw3A6nTh48CB0Op34d88H5SYtPnjVFgDAzfvq8PMT09Br8lfTyfM8BgYG4PP50NXVhRdffFH2h4f4BwKOJ/CHU9tPvGqX/E0n+X4okqu7ON/rlMJ//HEQFSYN3n1Za9rXCn/f/82wBk4KHE8kTTZhGAYfu3YLLBIbGnJ5SNWoWNiNLHpm3PCHeSx6QgkF4FsONSIQ5mW7SQtRy0RE1w82NzeD53msrKzA4XBgYmICAMRmkmT1g08OLOH/ziziE9dtlb32UskiKh1KjAAqufFqwwtAIeqXapybWq0uqhVLvohP+cZTjI7V6G1+5Npt0CawI6m26JI68Du8IXz+j+fR3VqG1x98uZs3FAqhp6cHVqsVBw4cEC9ghdrHYx3VONZRjaGhoaSiYMrpx7MjDty8rz6mblAKwWAQPT09KC8vx759+8QottwCJP77cedPTyMU4fGTt+zLKL0s5xoKgdR0cVlZ2TrLj2Jf3M/Ne8AAkgRgLtzzzCSeHFzGPbfvWReNOzW1ir+POfGmgw2ShN2OOun1UIluoKEIj3GHf50XYDIu21KOy7YkLymxGTSwydjEnYmIYllWFHzAmjuDy+US6weF2tWysjKYzWacm/fii4+OoNaiy8t3stQFoBLXrlQRuGEFYKqUbzzFTAHnAyHly3FcTMo3nmLsd3TNY1NZ5ldcu0GDHXVWHGwpgy+0Zovhcrlw5swZbN26dd28xVwF4Ko/DJ4gZsB7KlLVr93z9DhOT63gWEdVwihEMoT9a29vFwVKum1lQ6IL1FsvbsLz466Cib9scHhD+MAD/fj3V27FNomCIB3J0sWC5YeQLk52syzkBf+nb9kn+bW5rOv8ggccIQnPhQqTBjo1C32KmsxsSbTm4+MuHB9z4U1dDai1Jvfg43iCCacfbTnWuWaKsGbh+5nJMddoNKiqqhIn+AgPIxMTE/B4PAirjbBpgf/vqpasSmSkrF2JIkoKSpwEolRRCmxQAcjzPMLhcNKUbzxKVObZkirlG0+xIoC5iE6WZXDn4Ra84fvHwRHg/12zNh9x3759CWctMgyDlSC/rltXKm//6UkQAtz/TmmjdVId0w9dtQXTKwHJ4o8QgsnJSczMzCTcP7kFYCKu2FqBK7ZW5HUb8WS6X6uBCIIRHpNOv2wCMH490elijuPgdDqxvLyMhYUF8UFKSBc7fWH8vncBR9srkj7kuHxhvP+BM/joNVsKarKcy839SzcmbxhpKjPgLTI1AcWTSAAeaLahyqxFjSX1d+mFiRU8ObiMWw/WZ/XAmS3Cg8EXHxkGCPCRa7Zk/VnxDyNerxdfrHLAuTCO45MDMf6Dxa4fLDZKTAH7fD7ZJ07JxYYSgNHefgAUq7rjEebH5rre6elpjI+PY/fu3ZJazoslAIW/Ty68trMW50en4PF40N3dnfTYrQYieGAghEX9JF61uxZmnVqyXx0hBO+5fBM4XroYSSVezHo12vXSbvYcx6G/vx8A0NXVlfCiVggBWAq0Vhjxy7ftL9j2VCqVmC42Go0Ih8NQq9UYHx+Hx+MBqzPC51WB4ZM35biDEQTCa2nMRAJwyRPCI+cWccOewk3/UCqJBKBBo5IknHfVW6DTsKi3FbbTVlizXq0CJ3OU3mw2w2w2x9QPOp1OTE5OghAS08xUKvdAuVBi+jrTKSCFZMMIwHhvv1KK6gmNEdmeuIJYEOa/SvX2K1YKOFfR6Xa70RSewqVHWlFfX5/ytVa9GjsrWBzrqMbbf3ISGhWLX76jS9J2vvrYMEIRHh++WvrcVjn2z+fzoaenJ2akW5jjoWZjz2vhwWEj4fSF8fCIH29u4KHMS+Z6NBpNTITG4/Ggyr6MxYkhzI5ERDNqu90uCvmmMkNK0briD8Mf4rHkCaHCpElpYZIJhUhN84TI6rmXy5qNWhX2Nqyvf/YGI3hxchVHNpfl5XgI1/MPHG2T/bOjia8fjEQicDqdWFxcxNDQEDQajSgIzWZzSd0Xs4EKwMzYEAIwkbdfKSEIsWxMmYWUb1NTExoaGjLa92I3gWSD0NgiNcrJMAwuqtOg3q7HDXtr0V6z9h5CCOZWg6hLERnY22jD6amVjFLHuUblBAubnTt3wm63i2v97l/HoFOxeMelrbJtKxHFLlZe8oTgj6zNNi5s4lkeojs8hXSxy+WCw+HAyMgI1Gq12F2c6oYsTP+49QcvgmEY/Pyt0uv8ismk049//fVZvO+KVhzZnL2PJwCcmlqBVa/Jyzn5479P4bHzy2gs0+elPjBfdXTpxLVarV5XP+h0OsX6QZPJJDaUGAyFS4kXEqXd/z0ejyKngAAlLgCjU77pGj3SIVcaNhuyjcRlmvKVa7u5kK0A5HkeZ8+eRTgczijKGc0dF7eI//3siAN/6l/AWy9uRltl4qezYx1VONaR2YQMhmFijumyJ4QKc/qaP0IIRkZG4HA4RAub6M8sN2qwqXL9OKp8dwFnyq9OzqLKosVlW7KTb1urTbhhmwEVpjxMbSHkJZPt/N0gCCH45YuzqLPqcPnWCqhUKlRUVKCiYu14BIPBmIJ+wRC4vLx8XXcxANxxUSMMMhb651vgGzQqqFSMLDNrnxlZaz7qMsm/5jcdbMCuOgta8zS/Od4HUA6+89dxPD6wjP+5bY+kTmuOJ2DUWtTV1aGurk6sH3Q6nRgYGEAwGKT1gwVAEN5KpGQFYDpvv0wphieeQKaNEZFIBGfPngUhJGsxJGy3FCKAQkq0rq4Ozc3NslxYdzfYEOIIGnMsDB+Y98DlC6H7pakl0dYszwwv4+4/D+LDV2/FkRSCKBwOo7e3F0ajMcbCJpo3da8vsC90DeC0K4AP/bofn37VtqT1V+5gBL5wbg8V+dqv2354EgzD4Gd5jqb9+tQc1CyDyxM0z+h0upgbssfjiekujk8Xv3Kn9NnOSqDSrMW9GXQlp+LNFzVAxTI427sku5iyGzW4LI/NTfkIJjSXG6BiGck1oe9/4AwiHMG3b90l3iOF+sGmpibwPI/V1VU4HA6xftButyMSiSiymaJU8fl8NAIoJ/lI+QoCsBhPQZlE4jweD3p6etDc3JxxyjeeUhCAghdWdEpUDix6Na7YlttQeWBtJm2Y40UBGC1e2mss6Gy0YXtt8uis2+1Gb28vNm3ahNra2oy2XWgB6A9zIATwhpKfq3J0guYrQqXXqFCVpms0nr8OOfD8xAref2WrpLo2hmHw3TfuhiaBv2Wi1wrp4paWlqzTxZlQ7BR/JggGx/leMyEEfzm/hG01Ztk6hfOx5ut2VuO6DB4Ijm6rxKTTn3QdLMvCbreL19VIJILl5WXMzc3hxRdfzMv5l2+U2BQnjP5TIiUlADPx9suUYnoBSt321NQUJiYmsk75ZrtdOZEqAHmex9DQEFZXV9HV1ZVyjiIzcxLsyR+DXewH0dnA73od+I7XAJrcanueOL+IEEdw9Y7kF927Lm1FmHt5f6L3r8KsxWeuT26dMTs7i9HRUezZsyerC0ShBeCWKlNBu239YQ53/qQHd17ciFdszywVn4gfZjFv97+fGkeY4/FPV7SuDWmWQJlEz8h4ck0XS6GUBKBAvtcc4QlenFzFyLIf7zjcLMtnKqEZ4bWdmT1QCoLPZDJh37594vk3OTkJt9sNk8kkNpQosX5Qqec2bQKRgUy9/TKl2AIwlSiKRCKiJUguKd94WJYt+Ag8KQJQmHpRVlaGAwcOpPYyPPVTqJ75KkAIoNGDCaxA/dQXwZ/5NSKvvQfQrgmrbC4Oz4+7QICUAtCgVcGAl1MlUkQZz/M4f/48AoFATn/PUrSBmVsNpjTuBV7eL9VL3c89M+6MBOD5eQ/MOjUa7Llbf/zozXsRjPCSRpzJTabpYiURCHOymRTn+8auUbG469IWGBKYWD85uIxAmMM1Ka4BichUAJ6aWsHn/jSEb7x+V9rvRzoIITgz68HOOjOWvWGcm/fg8CZp3c7R644//3w+HxwOBwYHBxEIBGC1WsWGEiXUDyo1bS1MElIiJSEAOY5DKBQCgLx1+RZzHnCqGkAhRdjc3IzGxsaEr8kWlUolHtdC8diAA/cfd+G7HZGE1hYOhwNnz55dN/UiIa4JqJ/5LxCNAWBf+iwVQNR6sEsDUJ34PrjDHxQFRabnzQeObc7o9UB6a5ZgMIjTp0+jsrISHR0dOZ3LpSYA/3x2Ed9+ahwff+VWHGhO7pEnoFWzeOAdBzLaBiEEH33wPFQsg/tkiFbq1Cx0KXwjCxV1kCtdXIj1PjviwOlpN97U1QCjVoWfnZjGq3dVZzT9Jp58rzlZ08o3nxwDgIwE4KPnlvDfT4zjy9dKj8D5QmvXjEgG5THuQAQ8IbAZYsXX8xMr+J9nJnHHRQ145NwSRpd82NNgldSYk0y4MgwDk8kEk8kUUz/odDoxNTUFnufFBxKbzVYUIaaEqGsivF4v6urqir2MhJSEAATyJ/wEijkPOFH0kRCC6elpWVO+8RSjBhAMsxasi5slSgjB2NgYFhYWcODAAej1iaM3K/4w/vORIbzxYAN2j/8WhPAvi7/obWiNYM88AO7ifxL3M9OLg1qV+cUkugnk3JwbmypNovH0T58ewsriDN5wZEd6cSuBQgjAM7NujCz58JrdNTl/1oEmGw5vLkN7Tep0SC77xTAM/v3aLWL9WCFgGAbeYAQhjmSd/hVY8oTwvvv68NlXt6ecc1uIdHG2bKo0YWY1CLNOhXNzHrEp5k1dDQVdhxx85427kemp+NTQMkIcDxUrXQRdsqkMl2zK7GHnP/40CJ4AX74ptsxkd70Ftx6oR2ejDTvrLJh0BiR3ZUsdpRZdP9jW1oZIJAKXy4WlpSUMDw9DrVaL6WKLxVKQhyQlRwBpDWAOFMLbr9gp4OhtCylfhmFkTfmm224huG5XLeojczHTOMLhMPr6+qDX69HV1ZVSqBGyZufhC/OAaxxIdl6oNGACq0DYFyPK8o0gXuZWAniwZw4XbyrHkc3lmJycxA+fnYDJYMB7ZRB/AAqyX5/5wyBCHI9X7qxOOg+YJwTuQGRdJCKeSrMW/3pV5lHVTNnXlD66KDcP9s4jzBG8+aLcovQufxhhjmB2JZBSAMYjNV0sGOXnkxqrDjd3rkU8ttea8bnr27G5srCzeJ8ddaLKrMWWqtxqryqyiFp+5tXtmJqaSnodkysK+6auhoRTivQaFa7cJnQ4q9J+L6PJNoqmVqvF6TjA2gOJEB10u90wGo0x/oP5NN9WGlQAlgDFFoBCKlZI+ba0tKChIb9PzEroAl5dXUVfX5/kLli7UYPP3bBj7R8zLUj6eM6F11LDGmNBJ2YI+1dj1eHGvXWot2nR29sLlmVx7zsOQS9jrUwhIoDfeeNuuPzhpOIPAP7xvjOYdPrxs7fukzXyFghz+M3pORzeVI7mPPm1ycUrOqrgz9H+BlhrtPlVVNqbEAJ/mMczIw5cuqUiZTpaIFW6eH5+Hg6HA16vtyDdnQzDYGddZtmLCE9Snm/p4AnBlx4ZhpplcP/bM4uqyQXP8wkf3L/55BhW/GF89JotOR/3RBNOckUuKzSdTofa2lrU1tbG1A8ODQ0hEAjAYrGIgjBVg18m0Ahg5pSEACxE+LjYAjASiWBqagqTk5NZd4Vms91idAEL2xT2d+/evVl1SXHbb4Tq5P+C8JHYNDAhYMI+cJ1vBlhVQYVudL1ho4XF6ZMvoLGxEU1NudujJNtWPikzatKmNd92SRPue2FWNvEXvV8RjsAdlL82d341iPf8sg+fftU27KrPvbyiUoLZd6Y4vCG87d4evHpXNQAG2z2hrBpbotPFLMvCZDKBEKKIdHE8vdOreHrEiVsP1MNqUONnJ6ZRFczsu8syDD73mnaUZ2gm/n99C/jLwBK+dOP2nJt+kkX5VCwDVsHTqvIRRUtUP+h2u+FwODA9PS3WD5aVleXU0KRkAUi7gBWOSqVCMBgsyrYJIZibm4PNZkN3d3fBTuJiRACFm3tvb69oZJ31/tqbEbnkgy91AfOARg/wHBguDL5iG7iudwBInio9PubEkjuIV+6qke2CLEQbFxcXMTAwkJN/Yf/sKhrtBliTpHCU0gRSb9Pjo9dukf1z9RoV/iHHlGoy/GEOPCFY9ha2CSoThGhfjVWHo9sqE3apZgohBFqtFuXl5XnrLuYJwQ+encSh1rKMxXWlWQu9moVRq8LsShD3vTiLdksE12S4hh0ZRh0B4EfPTSLMkaRVJZmQTEi9+9KWBK9WDoVIo7IsC5vNBpvNFlM/GN3QlE39oJJTwLQLWOGo1Wp4vd6Cb9ftdmNgYAAGgwG7d+8u6LaLIQC9Xi98Pp+Y4s5VePGdt4HU7AR78n/BLvSD6Czgdr8efPurAc1a2jBZCviJ84uI8ASv3JV7g4MAwzBYXV1FMBhM61+YiGdHHLj7zwP4/m2deOTsItoqjLh+b+IOskKmtpPBE4I/nFmAXs3KWuSfb2HbWmHEb955MK/byBWTTp33NUrpLi4rK0NFRYXkdHGYI3iwZx5/6l/EAxmmYOtserzl4rVoeYNdj7tv6MDy2Nms9i1Tfvm2/eAJJBl+p0OpnnTpKIaISlY/OD09DbfbDYPBEOM/mOy4KjUCSCeB5MhGTAETQjA1NYWpqSls27YNS0tLBdu2QL73+YUJF1gG2NdkBwDMzc1hZGQEer1eVksbUtcJrq4TyfYkmdD94FVbQIh851c4HBZH9CUb6ZaOU5MrCEV46DQqvHZfPSpTFKHnEgGcdPjwvl/04L/ftBcN9uzr61iGwTXbq2DWyXfhLcUbZ6mQTphI6S4WbsbJOvV1ahbfeeNu2GSYB7yjzoITU4U5H1iGgZTML09IWpGo1GhUOpSw7vj6Qb/fv65+UDgHox+wizXKNR20BrAEKKQAjEQiOHPmDFQqFbq7u+H3+7GwsFCQbUeT7wjg1/4yDAbAD9+8DwMDA/D5fOjq6sKJEyfyts1EJNvPeCuabCCE4DX//Ry2VOjx+mY/GhoasLy8nPWF6N2Xt+Hdl7cBQNruPSEC+Ie+ORzeXJFRt9/0SgAhjsfcajAnAQhAFsNlijKJ7y72er2iV6eQLi4rK0NZWVlM9KXelvqc4AnBT/4+hSu3VSq6wWfFH8YPn53Ea3bXYHOVCTwheO33XoCKZWKadeIRBhYUGkIIplcCaHzpOx2M8Pin+87gtu4GXLalPO37lSAAo2EYBkajEUajEY2NjWL9oNPpRF9fHziOE0sWIpGIIiOA4XBYtkYXuSkZAZjveqdCCUCh67W1tRX19fUAUhtB55N87/MXbtyBYDCIEydOoLq6Gu3t7UW5KEq1SwlFeLww4cKhNmmu+cDaeRkKh9Ez6cN/vPoiqNVqSdHcSacfK/4wdtVn38nHMAzGnEH812OzOD/nwQevkl6Hd6itHH/8x0uy3nY+KVZtY7LomC/EweUPpxU1pUAuqUmGYWA2m2E2m9Hc3AyO47CysgKHw4He8yPQadWoryqXVLvl8oVx/4uzGFjw4nPXd2S7O3mHYRiAYRB5yW5FiBK2p7HoIYTkTUi5AxEYtKqEndKPnV/Gr0/N4v1XtqG9xgyWAQIRDi9OrpSkAIwnun6wtbU1pmRhYWFBdNQQzkEl74sSKBkBmG/yLYYIIZicnMT09PS6Lt9idSDnOwL4h5PjeOTMDP77jXtRWVGR/g15Qmqt3I+encB9L0zjq7fsxm4JFgvCSLcvXm7B7t27oVarEQwG121rbiWA352exe0XNYnTT9517ylEeII/vu9isFl2HDIMg2abBp94VQf25MESIh3BCC/JliTf+EIcjNrcnvz/3L+Abz41jntu24NqS2wn7B/7F+AJRPCmrgZZosb54Cd/n8KvT8/hl3fuj/HYTES2AjDM8bj3xDRe21kHq14NlUoldg//dXESCHHYpNeL3m8mk0n8fXy6uNykxVdetxMNtuJ2HafDqlfjA1e2xfzs1xLqMvMlpCI8wWf+OAiDhsVnXt2+7vddLTb4wxw2veS7qFGx+PGbOyV/fjL7GqUSXbKg0Wig1WqhUqkwMzMDt9sNvV4v2s0YjcaCByCUXgtaOn/pPJNPERaJRNDX1we1Wp2w67VYAjBfJyYhBCMjI/j58zNYCTNg9evrH6R+MXieZC2QBKQK3dftr0eNVSepgzDZSLdE0UaHLwR/mIM/zIkC8Guv341lbyinfRO2eWSLPOKaEAKXywWz2Zx2tucvnp/GT0/M4Nu37kJTmfwpPKkRwEV3EP93ZgEXt5WhvSb7OhsVy4IFoE0g8K7ZXgWnL5xQ/CmhCxsAXpxcAccTqFWpz6dc1ntqahX3vTgLm16DmzpjPTuPtldCp2ZRa9WJtVtCuvjcuXMIh8Ow2WzizVilUmGbBKNrpRzfTMn0xv/U4DLAAJel+S6rWQaXtNmxLcm5bjNocprao/QIYCo4joNOp0NFRQVqampi6gdHRkbg8/lE/8H4+sF8omQRWDICsBAp4HzMAk6U8k207WJ5EMpNKBRCb28vLBYLPnnDbvzk71PQa9ZOs3/7dR/8YR63Nkn7Uji8IXzp4UHcsLcWF2/KXuRITQGXm7S4IUnHbTROpxP9/f3o6OgQi+UFEp2nO+qs2FEXG6HbUm1GrsYpcn4nIpEIenp6AEC0QyovL0dFRUXCdF5HrRkalslqUkI6MrlY2o0aNJcbUJdBejbRDNWrOipxVUfiCS1mnTqlx2GxL+4cT3Dj3lrsrLNI6mAV1huM8HhycBlXdVRKet/+Jhs+f30HOhKM8muJq+NLlS4eHR2NiR4WalRYIclUSD0xuAwgvQAEgJs68zdXVuooOCUSf8zj6wcJIaL/4JkzZ2JqWO12e14in0qtSxQoGQGYb1Qqlazp0OiUbzqj441y8XO5XDhz5gy2bt2K6upqbANw+bYq8fehyJpYEY51ugukTs1Co2Iyam5IBMMwWPGHIX2ce2IE89zZ2Vns378fBsP6yJfcafVUQlkuGxiPx4Oenh60tbWJgjYUComjnDweD4xGIyoqKkSz4M5GG35zV/FtVDQqFke3ZTZa7//OLIDwBG8s8mza2ZUAwhzJuQkixPEYWfKBZYBL0wiI6AeGX52cxU+OT6PMqEFXiz3tdlQsg87G7EoNogUfsHZ+ORyOtOliJUdPBHhCQAhizKMTrZsQgscHlrGlyrTub/6vr9gMJexlqUcAU4kthmFgtVphtVpj6gedTifGxsbAsmyM/6Acx0HJJtAAFYAicl5khJSvRqMpqLFzsRDE7szMDPbt2wejMfHcz6++fs3n8MSJE5KEi0mnxmev35Hz+oYcIXz+ySl88CoGN3YmjsKmg+M4nDlzBizLoru7O+nFQc6oHMcTvPIbz2BTpQnfua1z3U2FZdmco9YLCwsYGhrC7t27YTabEQ6HAQBarRY1NTViKsXr9WJ5eVk0CxYulHa7PS83jHxG+6/cWgFeAanFu37eC54AD727K6fPMWhUuPVgfcL0dTzR59D1e2pQY9UVdHbyzEoAP3puCh86tinG6iNZuthqtSpeAN7w3edB4v6OiYRUhCf427ADL0yurJuJbdCsv0fMrQbxrSfH8M4jzXkps0iEUq1UpJCpD2C85ZHw0BtdPyhc57KtH1SyBQxQQgJQ6RcBASHl29bWhrq6/IXqlYJgaaNWq9HV1SXpCyh3tDUdjTYdyg0q7GnM7kbn8/lw+vRpNDU1pfUvlPM8VbFrI6PULIPHzy9icMGDt1zcElPkn61QIoRgeHgYLpcLBw8ehFarBSEkYeQizBHM+RlsaWkRzYKdTieWlpYwNDQEtUYLTm/DzpYaWQa95/u7XmOVt/FgJcDhoacn8JZDjRk1iXzm1dsQCGf2PfAGI7j1ByfxT1e04hXbX46uJxIQ6TDr1DjWnln0NFceO7+EpwYdeO3eWnTUrt0YE6WLnS4X7nt+ChWqYdRpgxgbG1NsunhzpRHuQGwJTyIBqFGxeN/lrZIblsIcDzBr379CUcoRwFzXHv/Q6/f74XQ6MTIyAr/fL45MLCsrkzwykUYALxAySfkqjWzTLELqUJjqIZVCTyDxRYC7LqrCpsrM/ybCSLddu3bBZitcpETgz/+0ZtVyctIFFbuWEheQWtsYTyQSQW9vL4xGI/bv35/2onlm1o0XJldg06tRZdFBpVLFOPff9bPTGFqYxacPr0BLQjHF/kruKDwz68ZHfnsOP7mjE/Y0845T8eSoG7/pX0VXiw2dGTxkZPJaAeYlS5LeWXeMAJSK8F33BiMwalWSvveDC15MOP04uq0iZ/H1hv31uGJrBRpTeEeqVCpUlJdDbfLAywAm/RL0EruLi8F/vW7nup8lu6aWJ6iZ5QnBQ73z2Ndki4n0NZUZ8NkEnb75pJQFoJyTQKLrBxsaGmLqB4UsiHCdS1U/KJinKxXlXp2LRDZiKBwO48yZMzmnfItR7yKIsUzXPDMzg7GxMezevTvjOYeF9j38/VkXAmEOr9hPJA95j46QZTPSTW72NdnFiSoC2aSbvV4venp60NraKjlCvaPOgnKTFpXmxMfg367eikfOLeLwwWYQQsRi//HxcbAsKzaTSB0llu+GL6cvjECYw8C8FyGOh9MfzkkAXrPVikvaG7Azw7m32WDUqvDH93Zn/X5CCHxhHg/1zmJThQFXSKifPDHuQigizwObVs1KSmcyDIN3HmlBMBjEuXOupOniUCgUM7tYKQ8cghH0t58aQ61Nj5v21iZ9bSjC48T4CmZXg7jrSHFnBZe6AMzX2hPVDwrXuej6wbKyMlitVnEdNAIoE4UQRsKNJ5Ntrays4MyZMzmnfIVojtIFIM/z4oW3u7s75QU3wvFQJ0iJFToCePv+Kri8AcniLxwOo6enBxaLBQcOHFBcykkg0yYQIZq5e/duWK3Ji/njz0Odml3X5RnNpkqjeONiGEa8EAIvF/tHjxITmkmKJaofPbeEEMfjTQfr19mZJCLd91KnZtFaV3gfxmwxaVXoqDFhe600wXrrwXrwMo5MzIT4Y5+qu1i4ESuhu1gwgnYHOfiWfClfq9eo8KFjm3L2spSDUhaAhexgTtTU5HK5MDc3h8ceewzf//73cdlll6GqqippTXw6WltbYbFYoFKpoFar8fzzz8PhcOANb3gDxsbG0Nraivvuu0+81mZDyQjAQqBWqxGJRCTdmISO0JmZGVlSvoIVTKG/fMJ20/m+AYDf78fp06dRV1eH7du3p7y4OrxBXPP1Z9HVasd/v7ETwFpTg4plCi4ArQYNVHxI0mvdbjd6e3uxefNm1NRk76dVCKTe3ARfRofDkTKayTCM7NE3rVYbE73xeDxYXl5GX18feJ4Xi6xtNlvMuZ/PCOA1O6oQDHOSjl/v9Cr+9Tdn8ZWbd0jyh1QCHE/w9LADR7aUr7N3EQTVJZvST4UQkDojNx9ImV2cTXdxNkw4/Kg0ayULNYZh8OFXbE7/QiCnCLSclLIABIrXK6DValFdXY3q6mp0dHRgx44d+NOf/oT7778fo6OjmJubw1VXXYVjx45lVC71+OOPi6U2AHD33Xfj2LFj+MhHPoK7774bd999N774xS9mvW4qAKOQ6scXDofR19cHnU4nW5evkBaVIsTkRKoYE6JHO3fuhN1uT/t6q35tP1b9a12qEw4fvvTwIN55aSu0BRaAUvdRSGvHT2pRKlIigEJHuk6nw4EDB8SLuycYSeltlw8YhoHFYoHFYkFraysikQicTicWFhYwODgIvV6PioqKjDubp1x+zLgC6Gqxg2EY8UEjGVa9GtBL23e1ikWII3j0/BK2VpsUOwkkmj+cWcA3nhjDv129ueBNHpngCUbwvb9N4K4jzaJBejyZZkXiHzjkShcHIzx++eIMKkxa3Hlxk+T3lRqlLgCVwvbt27F9+3ZUVFQgEAjgyiuvxKOPPoq3vvWtWF5exuHDh/HhD384bVNhPL/73e/wxBNPAADuuOMOXHHFFReGACyEspciAFdWVtDX14fNmzejtjZ9+kjObeeDdNslhGBwcBCrq6sZ1cKpVSxO/H9XiP82aFTQqlhY9RqEvIkF2YsTLvzy+Wl89JXbcvb+m3T48Oi5RdxxqDltVCuTtHampBMjmRDm+BgBEr1fwTCHnx6fwsFmG/a+VCsodC+3tLTEmJB7AhHce3wS22rMuLI980YCuVCr1aiqqkJVVVWMa//y8jIWFxfhcrliJkck47lRF4IRHgdb7Bhe9OI9v+jDx67dgsu35j4hZXutGd94/U70z7oTzl5VIlduqwAhwOFN61NDhBBEeIKBBS+2VhV+NFY0z4268IczC9jTYE1qwp2v2cXRdVvJzM6j0alZXL+7BrVWHZa9Idz+o1P45HVbcagt+/RbPjg5uQJ/mIuJ8I47/Ph97zzuOtKc9gGGCkB58Xq9KC8vx/79+7F//358+MMfRiAQwDPPPJM2a8gwDK6++mowDIO77roL73znOzE/Py+WmtXV1WFhYSGn9ZWMACwEqcQQIQTj4+OYm5tL6XWXy7YLGRUTSBUdCwaD6OnpQVlZWc61cFUWHb5yy5oP4JAz8TbD3NrPVHHb8Yc4GDKsj/n64yM4PubEdbtqoE6xj4FAAKdPn0Z1dXXatHam3PfCNOZXA3jXZW05R47+dGYed/95EN+/vRNbq1+2zxAEoIplwODlB6WlpSWcP38+YfeySafC1moz9jQUrquZ4wm+9MgwjrZX4KLW9TfN6K67SCQCnU4HnU6H3vEFTL4whJ3VOrGZxGQyxfydbthTA44nYBkGZp0KKpZBmYwptZ11FuxUcPo3GOHxYM8cjmwuR51ND7NOjev3JC9fGFz04fRcADa9WnZLnEy4fGs5Gu27sLkq+bVUzrpoKelioSQhkcm7MGpwbjUAnhDMrQZlWZec/PT4NHhCYgTgw2cX8dyoE2/YX4cqS/q/t1JrnksRr9eLpqbYiLFer8fRo0fTvvfpp59GfX09FhYW8IpXvAIdHR2yr48KwCiSCcD4lG8+npCUFgEUxp21t7fH1CDIgSA6x5d9aCoziPNwL2orx0VtsbVJfx1axkO9c3j/lZtRn8I6Ip5PvKoDY8s+1Fj1cDr9CQVgqpFuctBebYIryQzZTKm36aFmGdijIqPRAlCtYnHn4RYQQjA6OorFxUUcPHgwoV8VwzA42lHYyB/Hr01BeHrEmdb4mGEYsZj/Cz8fAscz+N1l27HiWnPs9/l8Mc0kGo0Ggg1erVWfU5dspihhVi3HEwQjBCv+COrSaHpCCLZVm1BtN6PaUtzOdo2KFb0Ak5HPxrj4dLHP54PD4cDAwACCwWDSdHGtVY8/v++ivKwpVz5x3VZwfOw5ecdFjbhxT40k8VeqKOF7mIhcjKCFrE11dTVuuukmHD9+HDU1NZidnUVdXR1mZ2dRXZ3bfCsqAKNIJIaE8WZyp3zjKbQ1SvR2o8URIQRjY2NYWFhIOu5Mjm2OOfy4t3cB1+6swat3Jz+umyqNsOnVqDBlFtGx6NXY3WAVtxd9gRCiufPz8zhw4EDevMT2NtnFdGyu7Gm04dEPHI75WXxqm+M49Pb2QqvV4uDBg7I8qIwt+6BimZwnEWjVLH5+5z7JBfTCfn33jbux4A7CaNDDaKhDXV2d6Mm1vLyMqakpABAjN9EWDIWi2BETo1aF27ulF5Zr1So0mUpDDBTKGYFhGJhMJphMJjQ1NYHn+YTp4kJPJ+F4Ap4QyQ+RiUpntGp2Q4s/QLmpa+FhNVO8Xi94nofFYoHX68XDDz+MT3ziE7j++uvx4x//GB/5yEfw4x//GDfccENO6ysZAViIL5zQBQzkP+UbT7EigNECUIh06vV6dHV15e0LxbIs6swsXr27FofiIn4r/jCserX4926wG/DRV+ZmhhrdLBE/uSRf+1iIG1e0AJQyrSQQ5qB/KVT2zPAy7EYNdqSxL3nHz3oBAL+8c19CE9tMqJD4/ujj1lJuWGdBE+3J1dbWhnA4DKfTibm5OQwMDMBgMIjp4kzFPSEED/bO4/Cm8qS+h6WMUiMlyUj2PcrX94sQgtVABDaDZp2dkTAm7Ny5czAajWI6OdFDslyjBj/3p0HwBPjUq7bJ8nkbFaUKwGwjgPPz87jpppsArN2z3vSmN+Haa69FV1cXXv/61+Oee+5Bc3Mz7r///pzWVzICsBAIIiwcDqO3txcGgyFvKd9k2y40wnaFEXabNm3Ka6QTeCkix3G4dmdsnZInEMGnHzqHrdVmvPvytoTvfXHChbElH27aVyf5BsAwDIJhTjRBljLSLReyNdfOFEEALi8v49y5cymnlTi8Idz4nb/jsi0V+I8bduDcvAdqhkkrAP/jNdvw5KADD/Ut4B+6GyQd8xV/GM+Pr+Boe+6TI6Sg0WhEC4boVJ4wVzY6lZfubzK9EsDXHh/DifEV/MdrMnvw4AlZZ7uiFM7OebCp0piVcHpycBmVZm1R6iAJIehdCOF9D/8dP7h9D5rKDHhmxIEzsx68+aJG6NSJr81hjsd7ftGHNx6sx9EMOqE//+ch/OX8Mu59aydqrS8/PMSPCYtPF0dPv1nwhHHf+TDqt/pzjpzvabBiNZDbvO8LATmngMiJx+PJyiJu06ZNOH369LqfV1RU4LHHHpNjaQCoAIxBpVLB4/FgfHw87ynfRNsuVhPI0tJSQe1PWJZFOBxe93OTToV9TTZctjX5BfuPffMIRnjctE+66farv3cSwWAYX/J6sHfP7ryPdJPLS0/KzdrtdmN4eDhpvZ+AzaCBmmXErt/bu5skebtd1FqGzZUm+ELSfPMA4EuPjuDZESe21ZiyugHmcvziU3kcx8HlcsHhcGBkZAQajUaMDiYa8N5oN+Czr96Wsdh5fGAJ8+4QXrevTnHdwnOrQbz3l33YXW/BW7dm/v4Jhx8zK4GMj4kvxEHNMjGzqzOFEAJhFK5wSlh0aqhYJmYs4vr3AcNLPnz/6cmMBOCrdtXg3LwXVebk36VU6eLx8XGshAhAOAR8HhC7PqeHoBtTTBCRm1KLDkdTDA9dKXi93ownZRWSkhGA+Y4kEELgcDjgcDjQ3d2d95RvPMWIAHIch7m5ORBCZPMzlEKyzmOGYfAPh5pTvvfD16wVOUs5H87NucHzBMdadHhkKIRDF3UXZPqEHEbXEY7Hsf96GttrLfjObZ3rfs9xHAYHBxGJRHDo0KG0Fz8Vy+AvHzwi/juTm3KmqdAPXtmGK9PMe5UCIQTjDj8aywxZiyqVSoWKigqxyScQCIhi0O/3w2KxoKKiAmVlZaIH5+HN0k2SBeptejh94byIP3+Yw7QrgC1V2ZnN11i0eMuhRly5rQJLY+cyvpbe1t2ACJ+ZOCCE4DXfOQEWwCP/dCij98Z/zoF6A95w2W7xZ7sbrGJ9bzK0ahZ/eE9XwklEqehstOInd3Rm9J7oMWDAmmG+kTmFyOoSjk+NpE0XK4ViTKKSi0JOAckEn89HBaBc5GtGaCgUQl9fH4C1zptCiz8geVQsXwjpUMEnq5BfnlyinRoVK3Z8puPXL05haWkJ7+iqxCtb2IKNHpPjPBVuXImEmjCRpaqqCiqVSnFPvpVmbVJfN6kQQjDvDuKpIQe6WuzYnqZbVCp6vR719fWor68Hz/NiM8nk5CQAiDfqTAv922vMok2I3PTNuHF2zoMqszYrf0yGYfDmi9ZKHpbGMn+YDkZ4vOq/T6C9xoRv37o7/Rte2uY126tQk2PzQS6iRC/1QpEEdyCCHz03hSu2lqcVnNGo1Wro9Xps3749bbpY7tnFPCH45QszONRWhraKzO5jSq2jk4JSU8B0FrDCEbp8t2zZArVanbOxYrYUMgI4Pz+P4eFh7Ny5E36/H16vtyDbFSjEKLjV1VUcNDrQevkmtNVX4+TJk3ndXjRyPag8+aFL1/3M4XDg7Nmz2LlzJ3Q6Hc6dOyf+bnDBgwqTNqdmjXw9ZMXz61OzmFsN4t2Xtqy7wQv/rrbocPnWCtTb8tPByLIsbDabWBIQDofhcDjEQn+TySRazaRKr+ebPQ1WNNr1OZujA9ml+fRqFgwD7G/KrHRC6hi0aMYdfjx6bhFvvbgJ7EvNW8USJRoVA1UWKexo0ZouXcwwTMzs4lz31RficN+Ls3h21IWv37Izo/eWsgBU6to5jpNd5MuJcleWZwS7k/n5ebHLd2VlpSiNGEBhBCDP8xgYGIDP50NXVxc0Gg2CwWBexViiJ/h8W95MT09jYmICh7s6YTKZwHFcQetb8iFwhdnTc3NzonVNIBDAx590gX32Ofz6rm785fwiTFoVbr8odRpdbsIcjwd75nF4czlqJRoLf+vJcRAA77msNelrWIZZ1wGcTzQaTUyhvzBGrL+/H5FIRLQBsdvtBb3Z6NQs6mzyWBVlE1FjGAaP5ZDGzYSvPzGKFyZW8JrdNai26IqaltRrVHjPZS0Zvy+VGIlPF0d3F7vdbrGDPdt0sVmnxv977Y6sPB6VKqKkoMQIYCnUVJaUAJQrOhEKhdDb2wuTyRTT5VusTlxh2/kUYoFAAD09PaisrER7e7t4Uc1nNK5/ZhXv/cVpfOY123FpVGNHvrYZPdKtq6tLfPKSMjMXWPvCBsJ8xlNHgmEO3hAnRt5SnacD8x48dm4Rd13aKhpgp4PjOJw5cwYsy8ZY1zAMgyU/D20kDLWKxY1762HWFf4iyPEE3hCHKadfsgB88F0HU9aVFfviGT1GbDhgQmeDGZzfjaWlJQwNDUGnW5tMEgqFCj6/eyPzqeu2YcLhR/VLqeNUAjCdOBxY8OLvY0688WBDQRtzMhGtmXQXS40kbarMroSJCkD5YRhG0XWVJSUA5UCY/rB169Z1LtrFFID5jIoJNiHbt28XxyAJ5HOfnxtzYDUQwbI3FPPzfAhAYaRbTU3NupFuUh8cbv7uccytBvHYBw5nJAJ//Nwk/GEO77tiE1Qsk3L/Pv3QOYwsefHGrkbYJYwrCwQCOHXqFOrr69HcHBvZYxgG37jKiq6utckaxRrrpdeoJFvECJh0yS89SrpgTjr9+NT/DeBQmx1fvHG7OBUnem7x/Pw8VldX81bXlQ2/OTWHeXcQdx1pjjmeSi/0t+jV2Fn/ctF8svU+dn4Jn/nDIH721n1oSNJs1DfjhifAId3eTjj8aCrLrVs3mmyFVDbpYn+Yw20/PImrOqrEaOWCO4gKkxZTrgA+/vvz+OrrdsCqV+PU1CoONtuS7mcpC0Clrr3YD7LpKP6VqkBImXBR7Aig3NsmhGBkZATLy8tJJ17kMwJ4e3czrt5es+4CLWxzbiWAlUAk5+J5oS4ukcAFpAuKN3Y14uuPj2QcAbxhby0WPSGo2JfrfpJ98b9zWyemXX5J4k94WNmxY4eYMoqmUPV6UlCyqMiFRrse/981W3CwObb+zWAwoKGhAZFIBFqtFnq9XrxRC2PshBt1MY7NN54cAyEEdx1JXg7AE4JJZ6CgafZMSSpYCQAGSNXk+9rO9BYqI0s+PNgzh1d0VMUIz1yQS2THp4uja1RXV1dhNBphLytbs8p56Rru8oXx6T8Mor3GhH2NNgQiPJY8ITw15MCvTs7iI1dvwa4k+6lUESUFJdbahcNhxWcHlHXE8kR0yjfV9IeNJACFfTabzSnHguVzn7VqFo0JfOAEAfi1vwwjGOHxnzfvkpwOFZhy+lFl1mJ2elK2kW63HGjALQekj9TqmVrBR37bj/ve0YWaKNPYVMLMolejozb1jYYQgsnJSczOzqbcLyUJQDmRmrIvBAzD4NodqecmJ6rrcjgcmJqagtvthtlsFr0HC9WJ/uC7DiLCrRci0eLky48M46G+BfzPbXtyegibXw3i0fNLeM3uGlj18t5SkompYx2VOJZjpzkANJXpcWV7JTZXyef8kC8hFV+jKqSLP3VIi2BwEefPh1BWVoZj28px8aZy1Nn0uHTL2gNxvU0Pm16dcvZyqQvAQn23pKL0DmCgxARgNk9VqVK+8RSiOzUZcgqxlZUV9PX1KXafhW1+4NgWuAPhjMWfJxDBd54agSG8gpt22PM60i0VTwwsweENwekLwxyV0szlmPI8j/7+fhBCcPDgwZR1LRtJAHqCEQQjvORxcUokwhOomLW6LltFFWpra0EIgcfjwfLyMvr6+sDzvNhMYrPZsjpvn59wwaBRpTRmNqdIsQu8qasBGhWLzVn6CwpwL52DfIZegVJIJACDER4/PT6NzkYLDjTbc/p8jYrF3gwsXqSQLyFFCMHzEyvYVW+BQaNKmi5u5pyYGZpFICoKbdGr0xpiK7WOTgpK9AHMdgpIISkpAZgJhBCMjo5icXExaco3nmKmseRoAhEiRzMzM5LnFxdTANZYdVnVrTFcEJtUTly0swk7tkjr0gtz8t+c3nvFJrzz0tZ1fmPZCjOhjrG2thbNzc1Jz8fhRS++/PAg/vPmnRtGAF733ydACMFTH7wYgPJrZ+LheIKjX3sOLAN8+abtGFr04vrdNTDp1Gs3YIsFra2tiEQicDqdWFhYwODgIPR6vRgdlNr1+c+/OgsGwJMvHatMEc6rpjID/vnYpqw+I5p6mx63dUmPnGcCIWSdmFKzDFQsoE1j8vy/f59Co12f0SQQORBEq3AOy3VfmXAG8KuTc1jxR9b5bCZKFyfqLi4rK0t6Xyj1CKDSBGC2c4ALyYYUgNHpz2JFhzIl1yaQSCSCM2fOQKVSoaurS/KXoRhp71xEp3DjfN1le2C1Sntyf3HChQcGw+jYG4hJ1eaKimWgYtcf52xSmEKkOlkdYzSPnF3AyUkXppz+khNKyfj3a7dg0RMCwzCY80Tg8YfQ1FTsVUlHxTJgGeCKrRXYXGmEP8zBmKCWVK1Wo6qqClVVa2nlwRknCOcRuz6FucV+1oATE6t45c5qGOIeML7x+p3rfrZRSRQBVLEM3nIo/ckRivAYd/jztbSkCELq60+s1WF+4GjuIhsAmsv0+IeLGiR1+Saaj+10OjE0NIRAICB2F9vtdrFOrZQFoBLXTlPAMiPlSSqTlK+SyOUp0ePxoKenBy0tLWhoyOxJvNgCcNUfxtiyD3saU5vMEkIwNDSElZUVdHV1ZVTv0WDXQ6eCLEa6UmBZNiNhNjk5ienpacmR6jsvacGNe+tQa9PjmdFcVqocrt7+cp3dqRkfwhEOlxVxPdnwxAdejshdtqUi7etPjLvwgQfO4q4jzXjzRXvB87w4t/jM5DBGV4AJSwD11ZUwm83iNULulKWSyaWh4u2HC+uHKSCs2aJTQc7EA8MwGc9jFt4npIsbGxvB8zxWV1djuovLXmomUXrTQjJoBDA7SkoApiKblG+qzyqVrsbZ2VmMjo5i9+7dWc0cLEYdWfSxveveU1j2hvCruy6CJUkBeSgUQk9PD2w2Gw4cOJDx36bGqsdrt2qzGg3F8wTf/esYOptsuHiTtBmxUo8pz/M4e/YsOI5LG7VddAfx8NkF3LyvHnqNCrUyGQPngzDHQ5PhDNZojm22IBjK/1jEB07O4muPj+IP7+lOeu7FQwjBi5Or2N+U2ai4ROyss+DotgoxnRfdPbxlyxYEg0E4HA5MTEyINxPh97kUvIc5HvPuIBrtyu3+5QmByxeWfC1e8Yfxxh+exNdetxNbq4sbdRGiUXdeUhwBmg6WZWG322G327Fp0yYxXTw5OYlAIACXyyWeZ8UYi5oNSowA0hrAAiEIBIvFknPKV4hOKe1pIp5o0+Pu7u6sW+CLLXS/fPMu9M6sJr0Br66uore3V5aIbqKbiScYQSjCJx2fxrIMQhyP3ulVyQJQSoo7GAzi1KlTqKmpQUvL+nFo8Sx6gvAGOQTCfM4zTlORa01oz/QqeqbduGFPjWRRFY9OowJDMotKvzi5gsEFL95woF7ye4YWvSAEUKukfwf+1L+Iz/xxEP/2is24cW96m5FUGLUqfPY17Ul/r9PpUFdXh7q6OhBCxLnFQjNJ9NziTK55137rOPwhDn9+X/KHrmLz9zEX+mZW0V0RQZ0h/d9nyhmAyxfG8XGXYgRgPvGFOGhUTE4PWgJCujgYDEKlUsFut8PhcIjpYqvVKtYPKjVCSCOA2aHMb38SEt0kBQ+4bdu2iXU1uSCkRJV2MkXj9/vFZoF40+NSo7HMkNAq5pnhZQxPzWOLdgWdnZ05P0kJadn4Y/WDp8cR5nh86BVbk773/Uczm2maLgIozJ/u6OhARUX6VCEA7KizYkdd/lN/uUaD6216jC37E9a/5ZP3338GHAFu3lcneerDR67ego9cvSWj7RzZXI63HmrClduk/d3kgmEYWK1WWK1WtLW1iVGbubk5DAwMiEX+FRUVae2Qvv66nXjk/JJixR8A7KqzQKdmYQkvS7q+7agz49F/OgRdhnN780G+M0iEENz6gxfBMgx+e9fBhK+ZWw2AEIL+OS+215pRbtSkfXDkeR5arRZGoxFGo3FdunhychIAxC72TB888okS79lUAOYRweR4aWlJFg84AbVaLZq7FoN0F4/FxUUMDAwkNQdWOoQQ/Kl/AXwgeZSJ53l87Nc94AjBYx+8VJanTqExI/6CddO+eniDkZw+e2DejccHlnDHoWboNaqUTSBTU1OYnJyU3KWdDl9YWU0glWYtrt9TI+m1EZ4kFGvZlCX85p0HsewN5X3kl0WvxjujzJWL1YSTqMjf4XDg3LlzCIfDYjOJ3W5fd2PcWW+RzfQ4X1j0auxvsmF4eEmSyGAYJuuHDo4noom7HOQ7AsgwDC7fWoF6W3IHhc//eRgRnsDhDSEQ5lFm1OArN+9AWQoD+kTrjk4XA1j34CF0sQuzi4sVjFBiCtjr9Sq+D6EkBWAwGERvby+sVqvsXb7FHgeXLP2cSxNEMSGEIMITMVXh9IXxjceHUaEK41VH179esEL5z1c1oaqmXraUQ7LUZlOC6GM8/hAHrZpNepNwB7k1092obcULAyFlHw6H0d3dLcvT6k+em8D/e8qPn29zY3sWxeHFZGYlgJu//wLefkkT3iZDrVSlWYtKc3G+E8WOwMePEOM4DisrK1heXsbIyAg0Go14ky61rvF8R9POz3vw2Pll3HqgLmkZSKYksq6Rmw8lse8hhCDEEbz3pbFwEZ7A6Qvj3uPTaSO+UkRU/IOHMBKx2OlipQpAWgMoIwzDyJ7yjUcJ00DixUEwGERPTw/sdntWTRDFghCCY199GnoNi9+/92KoWAblJi0+85rtcIz2r3t9upFuuZBtbRshBN/76yi0ahbvvjzxRfdAsz3GkDY+ghUMBnH69GlUVVXJmrLvbLKDZZB0Fmq2FKIJyqZXg2UYtJSvj4JGHz9CCHwhLuXsYKUSivDQFiElqVKpRMEHrD1UORwOjI2Nwefz4ezZs6ioqMjbTXp+NYgqixasDOdQvs9Fq14NnZrNePxjKnieL9pYsv98bATTrgC+eOP2mHT4kc3pr6eZiiiGYUoyXVwoaApYZvx+P4aHh2VN+cZTbAEYL1IEW5t8CV6BfFxoGYYByzJY8r48J5cQgk2VJoSmmRjDVGFOc77+tplaswgwDIPOZjvqMvAPjPZ0FKaytLe3o7JSXkPa3Q1WfPOoEdYC2dtIxRdK7IEXjUmnxtMfuiTtZ135tecQCPN48oMXK6K+SyqPnlvCv//+PL77pt1Ft23R6/Wor69HfX09jh8/jvr6eiwvL4s36ehmklyvAUueEP7Yv4DORis601g7SSHfArDOpsfbLpHXcJLn+aI9pF++pRy/OT0PnZqFL8Th7oeH8a5Lm1EvwTUg1yhaMdPFSgyK+Hw+KgDlxGAw4ODBg3n9Yxc7BSxsmxCC8fFxzM/P52xrkw5hn/Px1ProBw7H/Pux84v43alZXFm5dsEhhKCvrw9arVZyOt8TiMCkU2V0HuQyX/byrZkJN0HUTkxO4bfPj+CGw3tQWWnPatulxvl5D/7hx6fw3stbccdFjVl/jiDW33d5K3703JTixd+KPwwVy4gj2OptOrAMUGFSljhnGAY2mw0225o4C4fDODM+B+/UNLyeczCZTGIziU6X+ZSecpMGh1rL0Fwuz/UqmQAcWfLh/Q+cwU/v6CyYv6dUCpECTkQowuNgix3drWuefgvuIGZWAuif9UgSgHI3Uig1XVwoaAo4D+Rb6Rc7AshxHCKRCHp7e6HX6wsyyaSQ4+A6G22YcQVQQwLweDzo7+9HS0sL6uul2Xes+MP4yqND2Ntow2v3Sbf8KPTIu/n5eRCVFrDVYcQZRkuRa4GfHl7G3gYbzHnu/Ky36cEyDPbk0GQQ/R1/3b46vG5fnRxLyyuPnlsCyzK46SVrmB11FjzzL4fTvEs6cjcqCKwECd7563FsrjThZ2/thtfrhcPhQH9/PyKRSMzcYinigGUYdNTKF/VIJgCfG3VifjWIMYcfexuUJR7yXY+26A7ie09P4L2XtcL+UlMHIQT//vvz0KgYfOpV2/Avvz6L9mojvn7LTug10taSz3VfiOlimgKWmUKEeYUu4GKgUqngdrvR19eHtrY21NUV5sZXSNFbadbhzYea8fTTk+jt7cWePdJHugFrNTtbq824qC2zDuhCCcBQKITR0VHodDocPNCJ3SEur759Uph2+fHen5/GviY7fnjHfsnv++3pOeg1LK7dIV29WvRqPPev8gifMMfj973z2FRplCWdmE8Oby7PWwfyI+cW4fJHcNPeWtm3UfH/s/fd8Y3cZfrPjLpVbUnufb2212vvuu5mN32zIY00AmlAaKEEDjgCR7kcR7k7uPK7Qj84OhyEGhI4CCSkkIQkm2x23XvvVrXVpSm/P5yZlWSVkTRqyz73yZHYsmZGmvJ83/d9nkctw2s7y3FbTxUIgoBGo4FGo0F9fT1omobT6YTVasXs7CzkcnmEQXA27sfLDh8qdQpeNBaPAN7RV40bOsuhK0Arm3j7zLAsWBYZE3mLOwhvkIbdG+IJIEEQ2GcuQUOZClKSAEkQKFFIU1JG51JIIWa7OJ8t90Rwu91phTPkEoV39SRBtpMrJBIJQqHspxDEgtfrhdVqRW9vb05XDrmsjrEsi+npaQQCAfT396dE/oDd7/9NR1Of2Ul3BjAVcKbVFRUVIAhiV51ZAOKFar0SH7umFZftT8277nO/nwEBpEQAxQLLhlnEFIFwtVKXertUKBrLVBjbcCckf6R1AtLZxwGGAl13HHTNACDgoUgQBP7++taYv5NIJDAajbxXJdfCm5ubg8/ng06n48UkYoyPbPtC+MO4FQcq1Tj+qul6PDIlIYmCa/1yiEekvvjkAhiWxf1xFLxC0VGlxT/d1L7n5+++pIH/9/98fUfK75tPJW0m7eJCVAADu8/zCwSwyCCRSOD3+3O6TZqmMT4+jkAggP379+e8bJzL6hgX6VZaWpryvAnLsvjq0/Oo1CtxWwrtXyCzGUAhWFtbw+LiIrq7u/ng9UzBMCx+eGoZ5VoFrj0ozFsvFgiCwF0Dqc/j/fJdfYIqTjZPECGaFY0EcQ98giDwuu7Cb/9mG/vLNdhfHueeQAWg/PW7IV16FqBDAMsCsq+CMTTB9/ofgy0RT02vUqlQU1ODmpoavoVns9mwuLgYEWOn1WrTqsjoVTJc2WqEQSXFnd9+BR+7eh/kRRTLySEead1nLoHLn5/ukhAUCpGK1S7mUnCWl5fBsmyEcKkQTaCBXQJY6FF6FwhgFHI9A+j1ejE4OIja2tq8nSy5OGZODctFug0NDaVFyH5xZg0kQaRMAOOR3JktNwZXtnFrdzXINFozDMNgamoKPp8PAwMDkEql8Pl8olQbSZLA7v8lhphKSbfbDb/fD4PBIDgr9ulpGyiGxe29qX0n8fDs/A7KZCFkVif5y4Di8b+FdOlZEFTYojXkBWmbhOqhe+B9429E2Y7DG8LEphvHXh29iG7hBYNB2O12rKyswOVyReQWz9iDaC1XC4otazaVYHMngBmLF78c3MAdjcVHAOMRqRu70l/E5QKFQgCjQZLkHuGSw+HA5uYmpqamIJPJEAqF4PV682pGHY1iiJQtOgKYixZwrgjg5uYmZmZm0NnZCb1ej8XFxbwIULJdAVxeXsbKygp6enrw7VMbmH5yA/d2pF6RIwgCD73naFozNPFawH+atsHhDabVZQwGgxgcHERZWRna2toiKldifZ5vvihxu5u7HsS46a2urmJxcRFqtRrT09OCFaEn282gaHGON0gx+Mc/rgIAXu6On5N7AQB8DsgmfgWCDuz5FcFQIK2TIDeHwFQcynhTd3/nDCzuIB5//1F+7iwccrkclZWVqKysBMuycLvdsNvt+N3zQ/jM8z5cUqfCZ29ogV6vT0oyKnQK/PEDR1Eil2BibLRgHuhCkQsfzWygWPY7vF0MAFarFQsLC5idnYXP54NWq82qz6UQFMtnWXQEMNvIBQHkqkYejwdHjhzhT9J8KZCztV2GYXD//z6PU6t+/NvrD6OkpARPTlrAsIBEok2LJKU79xOPlL3lWH1aCkuXy4Xh4WG0tLTsifvJxbyhmNtiWRaTk5Pw+Xzo6+vjb14ejwc2mw1jY2OgaRqlpaUwGo17VHpiDuLLpST+4dp66IjcjmEkQohm4A3SMc89oZ/9Hyet+PjDE/j1e/pRmYKnZCJINofASuQxCeDuztGQrL4kCgH8xt1deHlpOyb5iwZBENBqtdBqtaitq8ccPYerGlXY2trC9PR0xIB/vK4H91nn80HqDlAYWXNhoMGQ0v0hG5W0776wDK1CittSVMRTDIvnZu24tKVMkDF3MZCWaMhkMmi1WrS1tfHtYk5dzLJshJI91xXOQv88LxDAKEgkkqyqgP1+P4aGhmAymSKqRty28yFAyUYF0OfzYWhoCAvbLIIMCemr7Z9fvPsoAGBiYiKntizxjlFCEimTv/X1dczPz+PQoUMx5zWzXaWORibbCoVC/Fxmd3c3GIZBKBSKUIQ2NDSAoihepTc5OYmSkhJeIJCOX1wiHKnTwOEQfh14gzRYls2a4OYP4xZ4gzRu7a6Km12cDDs+CmABRszTQqoAkah2TUgAqTjfTV2pKm5sYpBi8JuRLVzcXIqKqDlQCUng/qv2RfyMyy3mBvz1ej2MRiMMBsMeMUk+CeD4hhunFp1oMpbsOa5EyIYq9RdnNkAQSJkAPjVlwzf/vASZhMTx5uLLjhcCmqZ5YhfeLm5qakIoFILT6eQXHwqFIutKdmD3vC2G2MWiI4DZvhlIpdKsVeFsNhsmJibQ3t7OK+vCcb5UALnj7OjowCfKWXz9mYU9Vii59uUTY3ssy0ZUbuMpH2Nta9sXwrYvhPoY0WeZIJMKoMfjweDgIJqbm1FZWZnwtVKpFGazGWazeTeezevlq4OcX5zRaBRllZ3qNf77cQvAsrg1S4KRS/aVwe4NZWTBcmt3JW7tTvwZpwq6qhdINCHK0qCaT4q6zVigGBbeIAWrOyiIKEUP+HO5xQsLCxExdhqNJq9zad21OtSXqlIif0B2jKB/9LaepAvVjZ0ATBo5f56GaAa9dTq877JG9NcXto1SJkg0ayeTyfj7FgBeoMcp2bVaLX++idkuDgaDoi+Ms4GiI4DZRjZIGMuymJubg81mSxh1Fp4EkkuIRca4SDeLxcIf5355EAerdGg0RhKfWLF32USmrdJQKITBwUEYDAb09PQkJCmxKoCPDK7DG6Rx7yWNohr6pltttFqtmJycRFdXV1pWPGq1Gmq1GvX19Xx1kFtlq1QqfnYwW5GN4TiWoickw7JgWAgmdHqVrDAtRyRyBC57AIqnPgN/iIaKCPK/YqUqhA7eDlYjLumMhRK5BG86kl7qC0mSKC0tRWnp7ncYCARgt9uxtLQEt9uNYDAIi8UCk8kEuVwu5m4nhUxCpkz+gOy0gLVKKbxBGl95egF39VejTB35WWz7Qvh/j89hf3kJbwfz4V+Og2JYfOX2gwXfiswEqaiAucUHp2Tn2sUrKyuitouLIQUEuEAA90BsAhgMBjE8PAyNRoP+/v6EJ1W+KoBiEECKojAyMrJrgPzqcbIsi28+u4AX5h1467H6PdvM5bFmIszg5v327duHiorkSr5Y27qluxo7/pDoaQ6pEkAuYnBrawv9/f2irFLjVQfHx8fTrg5yx7Rg82Jk3YXXdsb/3FO1n/nN8BYYlsUth7NPjrKN0OE3wcPI8H9PPo197AqOy6cAlkWw/10IHvtQvncvZSgUClRVVaGqqgosy+LUqVPw+/0YGRkBwzAR9h+FqFgFUm9b/8cf5yCXkviryxsTvm7TFcD6TgBLDt8eAqhTSnFthxmHas75zt3YWQ67N3Rekz8gfcId3S6OXshm0i52u90XCGAxQswBfs76pKWlRRBxyGcLOBCIM0guAG63G0NDQ2hsbIyIdGNY4JkZG+asXkxb3Hh5MYQnp6z47I0HUiadDm8QpSXpVwBIkkxrvnJjYwNzc3Nx5/3ibSv6HNIqpdBmIbUgFQLIMAxGR3dVlckWI5nsT3h1kKbpiJuqUqnkZwfjVQfDb7S3fuM0WAAnWk0ppRokwj5zCfyh7F5n33l+GT85vYbfvPdI1hJCOMi6b0e59irUy9bhVdBgTO2AdO9nWwwzSeEgCAISiQSNjY0gSTJiDnVqaoqvNHNpEYWCVAkJi905ymRoLFPhb69piRntRhAETrZHZpZffcAsfB+K7NwIh1g+gOELWSDS+Nzr9UaYUSerRhdDDBxQhASwGFYzLMtieXkZa2tr6OnpEezvV4wVwM3NTczOzqKrq2uP67mEJPC5WzrwhSfmUGtQYWbLA4rZTXhIZZuzFg+++/wSbumuQl+9Ia39TPUYucQSl8uFgYGBlOZDsiUCCVIMZBIi4hoQWtkMBAI4e/YsKisrUV9fn/J1FKQYyKWpE0aJRAKTyQSTycRXB+12OyYmJhAKhWAwGHgBQKyH5m/fO4Bpi1c08gcAB6uy787/pacXwLJAlrkfgN1z4OIWEwATcjdUkRuEV9NiVZrtdjumpqYQCAQizqV8+q9FVwC5e97XnllEiGLwgSubIl7/4TjJIBTDIkgx/LlPEISo10E4CtUDUAgYhhEliSYa0cbnqbSLL7SA/0JBURTGxsZAkiQGBgZSuhHlei4ufLupEk9OEOF2uxMSpK4aPb755h4AwJuO1vExbqlU5GoMSvTU6dFiTv+CSqWyyyljdTodent7UyZL2RC4UDSDH720DI1Citf31vA/F0I2uUp0PPFRMkxuunF6aRvXHywXZAMSD+HVwbq6Or46aLVaMTMzw1cHpVIpf0xVeiWq9NmfIxQbr3z80nzvwh6kq6gNUAxIAoKMnMXC2rYfz806UBtHNh3rXOLEJHNzc5BKpTAajSgrK4Narc554YDb3vdfXMH3XljBj97WA5pmE2p2ovGff5xDgGLwt9e2CLJwyQTFTABzkQQipF2sVqvhdrtx6NAh0SqAjz76KD74wQ+Cpmnce++9+PjHPy7C0ZzDBQIoItxuN4aHh1FfX4+amprkfxCFYhGBcAbIpaWlaRGkVLeplEnwuhSTP6IhtFLGtbOFKGMTbUvsCqBUQsKsUeBAZWT1Ktm2OMsaoZXoWN9luVYBvUoKtULcm2x4dRAAPzu4vLwMn88HgiASVgczQboVzfMBLj+FJ6asuKrNBI0A65yHhzYgJXMby7fq9O/a+0BY1ydcPQzs2m3Z7XYsLCzA4/Hw7Tux1Z40w+KxCSuubjfFnO+tNShBkgS0Sin+6orGmO8Rj5jf0FmOtW1/1skfcIEApopY7eLx8XF8+tOfxtLSEhobG2EwGGC1Wvn7W6qgaRrve9/78Nhjj6G2thYDAwO46aab0NGRes5z3OMQ7Z1yhFyt5FJdLXMP2litUKEohhYwV01qbW3lT/5sb1MMuIMMNlxB7E/wmq2tLczMzGT0HQLZyx2+oWsvIY1HAMNb2Iksa4SgtESGGxKIMMQCp9DT6XRYX19HWVkZXx1UKBT87GCm816nFhxYcvjx2s7yPfZE5zN4g+8gDX9o19xaCAHsqdXHnDvLJgYaDBhoMOCll9bT+nulUonq6mpUV1eDZVns7Ozw7TsAEabmmTxTfju6hX99bBYMy+L6g+cM4UM0gxWnHyfaTDjRFp8A0AyL/3xiDmUlMrz9eKRQrqNKi44cjCsAxU0AC2HfVSoVent78cgjjyAYDOK//uu/8MILL+C2225DIBDAiRMn8JrXvAbHjh0TLLw7deoUWlpa0Ny8OyJw55134uGHH/7LJoC5AEfEhDw0GYbBxMQEAoFAxg/aXJMiDkKJZ3ikW6a5xWL58v3dI+NoMpbg3ksaE772F8M2OLZduKRnL7FnWRYzMzPY2dlJed4vFnKZBBKLAFIUhaGhIajV6rQrtPkGV/3jWtbR817c/I3BYMCUxYdTC07cc7RG0LE2m9RwB2koUqgAcnNcHBiWzUllRkxwBLBSp8AdfcIr6vvLC3+WKREIgthjDuxwOLC2toaJiQnBkYexcFWbCSwLXLE/crTi+TkHTi068eYjtQmtZDgj+nJtfj3jCoFEpYt8VAATQS6Xw2w246abbsL73/9+7Ozs4Mknn8TPf/5zfOhDH8JPf/pT7N+fqBSxi9XVVdTVnYsCra2txYsvvijqvl4ggDEglAByaRcVFRU4cOBAxg/afD2ok7WeaZrG+Pg4GIbBkSNHRLnYSJIElWG1kyAIPD9rxwtz9qQE8NYuM+ZX6T2fcTbIUi6TQKK35fV6MTg4iIaGhghFdiwUS14lEGkeTNM0nE4nbDYbZmdn8a7H/WBY4Pp2PcyG5BUTk0aOE60mDK7uoM6g3GOpEY1nZmywuIO4sasCMgmJD/x0BE/P2PHs/cfFOrwLyCHCs2RZloXH44Hdbsf4+HiEMEmv1/P3OpefiqniL5FLcNOhyOo4y7LobzCgtESGcm3sc+vpaRv++Q+z+Mk7evGhE7FFILnEBQIoLtxuN6qqdkcmdDodbr75Ztx8880AhCuuY71O7Pt10RHAXDywhFTELBYLpqam0NHRwZuYFisSiU98Ph8GBwdRVVWVlno0Hn5y1oJfD2/hxw0tGQkLHv3AcUFKS7NWAb868gbHzfs1NTXxF6sYyAcBDNEMfv7iLHT+TVzS1wW9PrHzv90TxKOjm7iq3YwKkbJpxUKyz08ikfDVQX+Ixnv9i/B4PFhbnMP8lDA1qDdI403fPQsAGH7gsoT702gsgStA8yKI1nI1np6xQ62QwFJE9hnFRPhzhfDIQ862yOl0wmq1YnZ2FnK5HH6pFs+tUbjhUDXaKoQN9pfIJeiqiW+wPv2qI4KQ+wTDsnhh3oFjTaVZ+/6KmQAW4r57vd64IhCh32FtbS2Wl5f5/15ZWUm6qE8VRUcAc4FEBJBrF25vb2NgYCDn7vTZQLx2bHikW7ok1+WnMG/zoKv63KwNw7Co1ClAAhnbGggd5I8+RrHm/WIh/AIP0QykJJG1GzdHluYXlzC9tI6TfW1JyR+w23qSSUhIC+zGmSqUMgmu6ayCWSNHiVyyRw0ql8v59l742EKJXIK/vaYFvXXJU1Cic3D/6oom/NUV56w8CoFUzVm9qNDKBeUhT266MbXlwQ2d5UXXxs42whcXwO4CeH3LCgNjx8asA6xDz4tJ4nWIhJwP915cj3svrk/6OgD4v5EtfO2ZRXz86n24bH9yFf+c1YvP/m4a/+/WAzBphD2fCpFECUWhVgAzVQEPDAxgenoa8/PzqKmpwYMPPogf/ehHIu3hLi4QwBiQSqWgKGrPz4PBIIaGhqDX69HX11cQN34xEE14WZbF/Pw8rFZrxmkR33x2AS8tOkBg1xOwvkyFBx4eA0NT+PyJ0pgEbtnhw9SGCyfazaJ9xhwB5GL5HA4H+vv7s0rgWZbF915YgkJC4s0XCbvZp4P5+XlIpVJ8/LbjkEmF3Qj1Khne0Je6Uj1XSKWC2lB2jpxFq0E5M9eZmRn4/X4YDAbezPWufnFX0/mCL0Tj5SUn6gxKHGsui/s6rgI4b/MhSDGpOJL8xUKlUqG5oQ7NDXVgGIYXkywtLfExdkajEVqtNmuV/ytbd0nfkUZD3NdQr4pJrmozwR+iEaQYbPtCfxEEsBD3PVEFUCikUim+/OUv45prrgFN03j729+OgwcPirSHr25D1HfLAfLVAnY4HBgbG8tY/SoEuW7VhFfHKIrC8PAwlEqlKGkRbzlWjwZjCX4zvAGZhARBEFDJJahQy8Ewnph/86NTy3D5KVy63wS5dPdzoBkWsxYP9pen5+lFEARomsbZs2d5xVa8Y3P5Kbzmi8/h7cca8M5LG1PeVvg2q3VK1JZmJ6UgGAxia2sLZrMZHR0d582CRMzjiDZz5WYH5+fnIZPJIpTFxfr5qWQSnGg1QScgaYYgCFzbkd371/kKkiRhMBhgMBjQ3NyMYDDIK4tdLhc0Gg1KS0tFJ4EahRQ3diVX4dvcITw1ZcP9VzXjeNhC4OvPLsGkluG2nvhjLoVIooSiEPddLCPo66+/Htdff70IexQbRUcAc4FwAshlp25ubqK3tzfrkUPcPF4uS9qcajUbM3Flajle11Md4eP39ze0w+/3Y2xsLObffPDEPrgDVER18NSCA78b3cRbLqrHvjQMof1+PxwOBzo6OpLOUSikJMACXgFxYU9OWqCUSeJWXq6PYd0iBlwuF4aGhmAwGFBRUVG05CWXIEkyYXVQr9fDaDSitLS04FpKySCk0lPMcV/5wtDqDppNJTHtcuRyOSorK1FZWcnfP61WK3w+H15++eUIMUm2CYqUJPD5m9ti/m5wZRskQSQkgIXYRk0FhXb/83g8oo8WZQNFSQCzPWTPEUCuGqZQKDAwMJCTVQanyM31xcilX2RjJi4WuKojzbD4xjMLuLzViI6q3XkspUyyx5/tcK0eMgkZ0e4TCovFgsnJSajVakFDtHIpiec/drmg9/7YL0cBAjj18StS3q90wcXvHT58GOvr62ldCy4/hUdHN3HygHlPxnL0zTREM3hyyoaLmkoFVZkyRa5ENNHVQW52kKsOhs8OFtoDJl2kcxw2TxAKKSnIMzAXWHb4YNLIocqyh+O2L4T3PjgCs1aOh97Vn/C1BEFAq9VCqVTC6XSiq6sLTqczIgObW3wIsdDa8VP472cW8YbeKjQZhVluxftuv3R7J5J97YVYRStmXMgCLmJIJBJ4PB6cOnVKdIWokG3n0gyaYRhMT08jFArh+PHjorrkJwJHdBmWxaLdiz9OMDwBjIUSuQT9DYaUtsHNMtpsNvT29mJkZCTDvd6LH7y9H3JJ7szJuflFzq8wXbIUoGjQDItASEA6SoCG3ROCxRXICQHMB7h5Lk7s5Pf7eSGJz+eDXq/nZwdjDf97gzQ2dgJoNmXmj5lNpHOesCyLJyatkEtJ3HwoO9XsVOAL0Xh8wooagxKvOZDdVrZeJcP7r2jERU3CBXC+II2dIAupVLon5Sa62pzofKLo3cWx2793Fj1VxEooicYFAiguLlQAixgulwsWiwX9/f05Z/G5JIBcpFtZWRlUKlXOyB9wrgIok5D47I0HIm5SQYrBb0c2cKLNDJ1q7z45vEGcXnTiyjZz3JsbRVEYGRmBQqFAX18fWJbNism2UFuITEHTNF+NDp9fTDd1xKRR4M6BWkGvLS2R4baeyggj5GyDIyuPjm6BASJSFnIBpVIZszq4sLDA58wajUZ+P0fXdrDk9KNSp8hY2R6NIMVgbduPhrLM5hTTmS0mCAKXtRhzngQCxCasKpkEJ9tNMCbxbhQLqRhmA8D/vryK1c0QLhlgI+5N4T6W3Plkt9uxuLjIjyYYjUZoNBoQBIEytRyfuKZF7MOJC4ZhMgoxyCcKcbTB5/NlfVxMDBTlN56tFhFneOzxeFBdXZ2XEm6uCKDT6cTo6Cgvatnc3Mz6NsMR/h1GK4FXnD6cWnCgSq/E0aa9s3WvLDnxwpwdh2v1MMdw0OfMkOvr62GuqEKAYqGURdrAsCyLR8e2cGmLsWBaW/Hg8/lw9uxZ1NXVobY2krTlql3KeeDlAuEkhQGQ7/t7dHUwEAjw1UGn0wmXy4XqyirUN+lFJ38AMGv1YmzdBYNKlpFnZrpIlGSRTcQjrHVZElWJgRs6TDhD7iSsusU6nzhlsdvthlar5dvFubIZK9YKYKF6W7IsWxSfZ2E/+XIIr9eLoaEhVFdXo6KiAna7PS/7kciUWSzEi3TL5cWUaDtNxhL89VUtKIvzsLu0xYSumtjkz2q1YnJyEp2dndDr9fjSk7s5nR88EbmaHl134bO/mcCt3VX46DWtmR1MFsGpz+N5MWaDAKZzHmTr3Ml15U8IFAoFnzM7OzsLiUQCv8cNx8oy1l61oTEajVCr01OsR6PFXILSkszJX6E+LOMhn/sbpBj8amgDJ1pNgq1UAMBYIkVLmfDX2z1BvOX7Q/jqnZ04eLAKLMvC5XLBbrdjZGQEDMNE5BZni1QUKwEsRPFKMV1nFwggwA/qcqTB4XDkdA4vHMli2TIBV+FkWXZPpBtHJArhxCWIxNmYcikZ8fuZLTdcfgoG2sG37jnvwpPt5QhQewl1R6UWf3d9W0LftEyR6ee5srKClZWVhOrzcAIYCNE4teDAkcZSKDIYkE91n53eEJ6YsuLi5jLRqkWF2NaJBS5Jgpv14qqDCwsL8Hq90Ol0vLI43RabTEKiUqTPtRCub6HI5/3IE6Rh84Swuu1PiQAyDJPSPi85fAhQDMY33Kgr3W3x63Q66HQ6NDY27goRFzbx1/87hr8+LIFZp4LRaOTHdgDgobPr+MXgJr7zpkNpV+qLlQAW6n4XyrM0GYqSAIr1wXICCLfbHZHqkWshRjiytW0u0q26uhp1dXV7PkNuJq8QL6ZkePePziIQCOLrr63Y4114oCr2IC5JErghSxYtQGaEmmEYTE5OIhAIYGBgIOEKN5wAbrkCmLd50WAsQX1ZemKEdPZXKtlNFRGaypKNfcgXoolqeHWQMw622Wz8rBc3OyhWdTCTfS105PMhWloiw73H61Kee0219Xe4Roff3DcAWRwhmVQqhZ1SgJDIUNnchka9BHa7HVNTUwgEdmMP/zjuQYhi+LZzOp9bsd77C7UCWCwoSgIoBvx+P4aGhmA0GtHb2xtxwZxvBJBrix48eBAGgyHhdvM1CPyNZ+bx+7Et/PgdAykRCa/Xi/d0ENAZ63Dw4P4s7mFibPtCkJIEH8UVTswGV7Zx7w/O4JH3XoQqfeLc3VAohMHBQZSWlqK9vT3pjTx8O7WlKryuuxpqRW5viEKNalNBMd1E431H4cbBwLlZr4WFBXg8Hr46mChWTEwUS1WCQyb7u77tx59m7Hhdd2XaVbF0/i5VIkUQBG92Hw8n2oy4ss0I4tXXq9Vq1NXV8bGHfz1AwuFwYPDsWZxxyPHHBT++dEcXylIQyhQrASzE/fb7/UUhAAH+Qgkgl3Hb3t7OZz6GI98EUKwZQM42xGazJY10i5cHnCusbwfAsEhpxc19j1cfiU9sc4WfvbIKGUniLcd2I9+4z1MikWDR7gXDsnB6QwkJIGfEvW/fPlRUCCNU4QSQIAhozgOblmIiKalAoVCgqqoKVVVVYBgGLpcLNpuNjxWLVoL+pSMTAri27Yc3SINiWCSahqAZFgGKEU28kw2STRDEnti+xyYsqDWocKDynLF5IBDA4tklhILbGB18BabSc7nFyRweCpFICUEhVgDFSgHJBYryaZHuBRaecdvX1welMvbDOF4WcC4g1gwgZ2KtUqkERbpli/SyLIuP/GIEJo0Cn7g2vtjiU69tT+k9uXSWTLOKxcLJ9vLdBJFXEU7MbjpUhZsOJfaStFgsmJqawqFDh1Lyj0rXBuYC8guSJKHX66HX6/lYMa5VHF4dLC0tFc2eKVsVwCW7D0GKRku5uK4JmexvX70BffWGpK/7yek1eIM03nos9XZvLOSCSNEMi/9+ZgkyCYEH397L/1yhUOCWo/txy9H9YFmWzy1eWVkBgIjc4uh9vEAAxYPb7b5AAAsNoVAIw8PDUKvVSQlRviuAwWAwo/dIJ9ItWxVAgiBA0SxenLfD6Q3tUTKyLAuGBUhCGLGnaRqjo6OQSCQ5S2cRgsYot36hnyfLslhYWIDFYomYQxUKkiRFX6wUQquwmFrAYkAul/PVQe7hXSzVwdNL22DA5owAMizLt0MzxYk2I5YdftE8LnNx7UhIAv96Szv0r3qkfvxX41h1+vH9t3TjU/83BUOJDB+4ogk/GnTguoMVUKvMMCgJkEEP1tbW4HK5UFJSwlcHlUpl0RLAQtzvCxXAAsP29jZGRkbQ0tIiqLWWzxtspuRzY2MDc3NzKUe6ZZP0vvmiOvz7YzMYXtvBpS3nWu5ctfOzv52GTELgkzckrgJyQpaamhrU1dXhjxMWDK1u4/1XNEOaQ586IRBizxJOZoVUadPdTjrvmU/ke/tiYNHuQ2mJLK3kFIIg9lQHo33iuNnBVKqDWbPq6SwHkwXCHm9/f/rKOiQE8IbexCbNQo63UqdEuVaBTzw8gSONBtx6ODNhWDYJSTjxDc9DX9sOgH315wwLODwhuPwUnp93gmGB4TUXlDIS//X6gygvLwfLsvB6vfwITSgUQjAYxM7ODmQyWcFV1BKhECuAXq+3KGLggPOcALIsy1tpRHveFSrSJWIMw2Bqagper5ePCUsF2ZwB7K0z4At3HNrj3k+SJFiWhUJG4mCCGDgAsNvtGB8fj/DDc/spsKywqCMA8ISAIEVDLs3+DSMZMfP7/RgcHERVVRXq6+uztp1ihD+0G4NVrKAYFoMr21DJJLg6jbgymtk1Ka/WK9FTp4dcLkdlZSUqKysjqoNca4+rDmq1WkGiIbGhSCDacvkpXPuVU/jCGzrQL6AlCwCjay5olFKYFLEJnFougT4JsV52+PDklA03dVUI8k98ZtaO5+YcBUsAWZbFvz42CwlJ4G9O7ov43fff0s3/+z/e2Mb/+3/c1gGdUorxTTcqtOfuvZyQRK1Wo76+HjRN46WXXoLD4cDi4iJkMhm/wCj0HGyapguuAnihBZxlCDkhKYrC2NgYSJLc43lXyEhHBBIIBDA0NISysjL09PSkdcFmkwCSZGxfP+5YH7iuLcZf7YJlWSwtLWFjY2PP3ObN3cIzmoMUg98vhPDr9RHUG0vw4ZMtWb2xJfo8uYp0PBFSKjjfCCDLsnhi2o6tjSB6uvO9N+lBSu7Gp6nSFBZIyN2h/1jrmvDqIAC+Ori8vJy0OpiP82TbH4I/ROPpabsgAsiyLN76w0EQAJ54b3fMa1SI4lwhJSGTEIIWhyRB4PfvOyJKF4GrOk5veaBVSkX1b5RJSNQYErsIhIPzLzxck3hxLZFIIJFIsH//fpAkuScHW6fT8bnFuYwLFQJOaFdI8Hg8FyqA+YTb7cbw8HDM6KxCR6oVQC7Sra2tjTejzcV2xUAywQtN0xgbGwNBEAnn/fwhGsokxsdyKYnDFTJ8Y2QbZ1d38OGT2c3ZjEfM1tbWsLi4mHZF2uWnUCKX8A+2QhSBbPtC0CqlINMg2ARB4GCVBmWh4r41ZZracX2nMBV4dHWQUxbHqg4CuW+v1xpUeOFvLhZcpScIAv/+ug6o5ZKMWtblWgXu6q8R/Hq1SHGQnBH078ctUEgIvPOSBlHeFwA+fFWzaO8VC9z9NToHmxOTLC0t7eYUp1BxzjZoms5ZXJ5QuN3uCwQwX1hfX8f8/HzKM3DR4B6suS4vC1UBsyyL5eVlrK2tJUyKSGW7uSYSiciL3+/H2bNn4xpXc/jEQ6N4adGJX7z7CD8UHQ8HTHL8+j09ICTSlG5cz0xbMbXlxlsuqhdcJYj+PFmWxdTUFDweDwYGBtLyfQtSDB46uwaDSoabDu9WP/N9A46GO0Dh8Qkr9plL0F2rT+s9GstU8G0W1nEVA8JTJJqamhAKhXgy6HK5eLV8MBjM6UMzVT+9wzVa/GZkC1RAAkOBtfeSgTOCvr23CqoM0ngKBeFeltw8qsPh4M8ptVrNV5zz4cZQqCKQCwQwi4ipDHs1PcHv96c1AxcNriKW65NLSCWOq4wBSJoUIeZ2xYZEIolZJePyb5+w6fDK2XX87J21kMZxyr+6oxxnVrahFbCCJwgCSikBpTLy3HD5KcglRNz4tADFACxSahGFVwApisLg4CB0Ol3aLXpgt4rZW2+IaAMVWgVQLZegq0aH2hRaVdEoNFJbrJDJZBHVwbW1Nayvr2N4eBhAarODuYRGIYVBJUWFRoKgq3D2SwgYhoFUKk0YZQkANk8QX3xqAR892Sxa9TEXkMvlqKioQEVFBViWhcfjgc1mw9jYGCiKQmlpKcrKymAwGHLy7CxUEQjnzVjoKJ4zLwF8Ph+GhoZQUVEhKD1BCDhClOuZh2QzgF6vF0NDQ6ipqUFtba1oN+5sZhAL2SbLsvAEadg317C2toa+vj588yejYFg2YfvoRJsZJ9qEDdrHqnKyLIsfvLAEuZTEvZc0xvy7kwfKhR1QGDgC6PF4MDg4mJIlTyJ0VkfO8+R6BnDZ4cNN//0yHnlPP+pK91adCYJAa3nmA9DFMtdYLPtJEARKSkqg1+uxf/9+hEIh3iPO5XJBo9HwlZx8t9QkJIEbOivgcDhgdRcfARRCfF5adOLFeQeG1lw41lSagz0TH1wOtkajQUNDAyiKgtPphNVqxczMDBQKRURucTYWGYVaAbwgAskRuJizcHWoGMiXF2Ci7QqJdMtku5n6D6aKcEL2+Uen8KeJdXzy0lJc9GpV8ztv6Yv5d+HJF+lujwNBELiizQSdMjOiP7Xpwql5B27vr4VcSoIkSTidTqytraGzs5Mf2o+F345s4M+zdnz2xgMgU/QjyzUBnN7ygAUwtemJSQDFQCFVo84nhM/UyWSyiEqO2+2GzWbDyMgIGIbhq4M6nS7m9zG27sLgqgt39Se2YhFrf6NhdQdhVMsyPlfcAQokQeQ8CeRkuxmd1VpU6dKrlCfbTj68PKVSKUwmEz+L7vP5YLPZMDMzA7/fD71ez4tJxIo+LMQKICfGKgYUJQHkHnqzs7NwOBxZSYPIFwGM1dLjIt3sdnvWki/yMQPIbdPv96OesKG0RI6LerogSdJqvfGrL4AA8Ov3HUt5e7HIUkcSCxpfkMaL83Yc32eMm1Ps9FEIMgxIArxVRzAYxMDAQNLv6+9/PQGGYfGZGw8IP5hXkQkBdPkpHP/XP+Ftx+txv0BRzIk2E85+4tK0tne+olgIazxSQBAEtFottFotGhsbEQqF4HA4sLa2homJCWg0Gp4QctXBN3/vLFgWuOVwRcSsG80krtiLsb8rTh9u+59XcGWrEf98s/AEoVj4xdkNSAgCbzoiXDCSCEIrUlKSQK0hvQXUG79zBjTL4sdviz1OcmZ5Gz9+eQ1XtZZheMONgXoDLt+fmdtAOlCpVKitrUVtbS0YhsH29jbsdjsWFxdFMzcvRAJ4wQcwy2AYBqdPn4Zer0d/f39WbsD5JIDhCE8w6evry1q5O18t4J2dHUxOTuK6gXa86VphNyki7P+ngnTn5VacPoxtuNBkUqPBGFu5e6SxFEcaS8EwDEZHRxEKhdDS0iKIrP/pw5fCH6LTenBmQgCVst1zaccXSuvvs4liaa1yKIT0FLEgk8lQXl7OmwbHqg7+9J4DcFLSCPL34rwDK04/buyqiLtQSgXxPtMqnRIdlRq8UYTq4xX7jaKlgAC5OQ8qdAps7gT2bOc3I5t4eXEbN3ZVgCSAn7yygRmrBysOf0ICmItrjSRJlJaW8l26aHPzdEcQLrSAM0NREkCSJNHe3p5Vli2RSPKWB8zB5XJheHgYzc3NqKzMzKA0GdLxHxQKl58CxTAwqCJbNmeXHCiT+HD86JGYKmaGYfGJX42hr96A28MsHVKt/HFIt8rZbFLjroFa6JO0iQOBAAYHB1FeXg6FQvFqDB4DkiAStnZL5JK0W1CZEECZhMTw35/Y83OKokCSJAiCyMvNtRiJ1B8mrCAAfP/FVdSVKvH5DCtT2UA65CS6OkhRFOx2O2w2C6idHYzsnFOB1paqYHEHIYsj2BJrfyUkge+8+bAo22goE3eMIReE5D9u64j586lNDyiGRW+dDn31elhcAfgpBmZNYkKVDxIVbV8UvcjgxCR6vT7hvhViBdDj8VxoAWcbWq02qysXqVSatzxg4JydzaFDh3JSTs5mC/iBX43i5SUnOqp0+Oabe8AwDH73/CD+54wLl+8vw1VxLGwIApjYcGF6yx1BAIHdVpPQ/GAO6R6jhCRQWpL4Jrqzs4Ph4WHej3F2dhYsy+LBl1Ygk5K4oz87fpTx2trpgGVZXvnOfU40TfNEMN2HxLYvhLu+cwZfvr0TzabUvA9ZlgXFsClbieQaUpKAjCQwtLqDodUd0QhggGLw+IQF7RWaiPivfEEqlUZUBzkV6OjoKBiGwYHSUmxvK6DT6TImFcVYVc3nPt8f5RMol5IwaeRJ9yffVbRYiwyHw4GtrS1MT09DqVRGiEnCUYgE8EIL+DxAvlrA3EzcxsYGjhw5ItqwbDJk83jfeLQOdl8IFzWVIhAI4MzZs3h0jkWZRokbD8QX7hAEgYfeczTm777wxCykJIEPnNgX8/fx3i8bJJfLX+7u7uZL/xyJqjao9kTgiQmxRCAsy4KiKBAEwbdgGIYBTdP8/3LnR6rVwVmrF2tOP56dtQsmgNwxPTFlgzdI4/qD5aLNlmUDV7XtDr4PPXBZWn/PsGxM42wpSYAkiKy2VNNFLBWow+HAxsYGJicnoVar+TkvIaMQIZqJIPrZJlMrTh/KSuSiCUCA7JMphmUxtLqDrmpdxPXw2IQF69sBvPlIDQiCgM0TxKf/bxoDDXrcczTx4rPQ0jSkUinMZjPMZjNYluXFJFNTUwgEAjAYDLyYJN/kNRYuGEHnANlWP+aDAHItRIIgcPjw4Zye2NmsAB5tKsPRpjI4nU68/PLLaG9vx5XyAEooFwzKxMcYr3Vq1shRliKxErNaBuw+oGZmZrCzs7PHe5I7P0+0p54Fm85+ZPK3DMPwCQbhD9zwqh/DMHyFkDtPKIqCRCJJSgZ7anV48q+PQZskv5VD+D50VGqwYPMWNPnLFHNWL279xsv45HX78fqeSKsgCUnguoOp2xDlA9EP7nCPOJqmE7b1zi5vY3LLgxu7KnhClk0CGKIZ3PXtM5CQBJ766/RGSmKBu46yhYkNNx4e2gRAoLv2nHjthXknaGb383pq2obfjW5hf3kJrhAg/ijEPF0OnH1RSUkJ6urqwDAMnE4n7HY75ufn4fV6sbS0BKPRCLVaXRAVY7/fHxFZWsgoWgKYbUgkEgQCgZxtjzM/bmtrw+zsbM5XNtkmvCsrK1heXuYj0F5nBFZXVxEKpSdAePNF9Sn/TTjJnbN68NvhDdx3eXNa5IKiKAwPD6OkpAS9vb17bjxiVRv9IRoKKRn3xhaP1FI0g688PY87+mpQqY99M0pE/mJtBwBfKQivDjIMA4qiQDEslHJZxOuB3c+iNMVoNO6YqvRKVMXZ/2zC4Q3h5q+/jG+/6RBastx61Sp2P9OyDOPjkiGX7cl41cHNzU1MT09DpVLBaDTy1cHaUhXWtgO8MCnb+yuTkLj34np0VYs7q8UlgUTD5afww1OruPagGU1xhGRCsL9cjTf0VGF/lNfm310bpuJnd/ON77u0QdDoRCFW0eKBUw9zRssvvvgi5HI5FhYW+Nm7eFnYud7PYsAFAhgHUqkUHo8n69uJFem2sLAAmqZz1v4FslcBZBgGExMTCAaDOHLkSESrIdfWM+Hb++pT83hxwY7b+2uTuvZHw+v1YnBwEPX19aipiW0fIUa1kWZY/PLMGlRyCW7tjq14jFcJH9tw4VvPLcLtp/DA9W17fp8K+YuF6Orgo6Ob8IVoXNtu5Gcz0xWSFMIqftbqgdMXwosLzqwTQLNWgcG/Ta91nCry9dlGVwe9Xu+eBIljNUaAZXeHf5F9wvqWJK3RdBCPTHFXKEVndk+QSUh0VO0lreGf0xWtRlzRKtz2pZgIYDRIkkRVVRWqqqpiZmGXlpbyaTe5OMZim1stWgKY7Q85Fy1gmqYxOjoKkiQjIt3y0X7OBhnjWtpmsxkHDhzY851lU3kcC+Fk6dM3tmPN6YdKJsE3nlnAVe1mQUP2drsd4+PjSc24CYLI+DuUkAT2mdWoL4tfMYhHALuqdfj6G7vRVbPX45Br5XI3q0yvJZIkcbBajwW7FyqlIoJccpXCTIUkuUZfnR5//vDx8yLPlUOhWOsQBAG1Wg21Wo36+vo9Q/8qlQplZWUIhUJ5reKkg1gE4F/+MAuZlMD9J5rj/FV+UcwEMByxsrA5P0uXy8VXncvKyrLaoi0mEli0BDDbyDYJ46pItbW1qKur27PtXJsyi32829vbGBkZ4VWxsSAGSUoF4SRXo5CitUIDT4CChACEdIGXl5exurqKvr6+pDcQseYNjzYlzpSMRwAJgsCx5r1/y4k9uH0UCw3GkgiPxFit4lSEJPkmKwRBQPNqRmsx3dATQehx+EM0lDkkvvGqgxsbG2AYBj6fD0ajMa4lCMuy+M3IFi5uLk15LlhsxCJTT8/YQAAXCKDISHaPiPaz5M6riYkJhEIhXkxiMBhEE8EU273iAgGMg2wSQIvFgqmpqbgRYfkwZRbzpF1dXcXS0hI/7xcP6VQdWZbFz19Zw9Gm0oSVsXjbi/5c1Qop3hEnA5gD18YOhUIRldpEyFVEm9BZw0xbvukimZAkVnWwkG6gFMPisXELzBo5+hsMe36fb6IqNl5adOLdPx7Gv7+uA1cKaCOyLItpixe1BqUoatrw6iB3XigUij2WIEajkV+ELTn8+NzvZ3DJvjL8262pp+nEw4On1yAhgDf0CjecjkUAfv2eAdH2KRsoVgKYyn5HV51pmubFJHNzc5DJZLxivaSkJO17kM/nS/jMKzQULQEsxhZweHzdwMBAXMfzfFnQZAqGYTA5OYlAIICBgQF+hpGiGTw8uI4r20woU+/O24XoXeuBVB+gO34K3/7zIp6asuIrd6VmBkuSZMqik2AwiMHBQRiNxpht7HiIRcz8IRqvLDnR31Aa19bD6g4I8h0M306yzzBf5C8a8YQkHCkMr0ymcl5YXAG8vLSNy1rKoFaIe0uTkgRkEgJl6vityEIirIkgpDph1shBAKjSCZuL9YUYDK3uwO0PobfekPlOhoFlWUgkEj5flqvi2O32PVWcz96wX/Tt0zQDOsXvNhYpKXQF+18CAYyGRCLhFxLArnKXI4M+n48Xk5SWlqY0huB2u4smBQQoYgKYbYhNwlKJdCtGAhhOlNrb2yMeNM/O2PDPv5/G915Yxq/ecxROXwjv/fEgTrToccyY2nHqVTL8222dqC9N3cE/VWLBJbG0tLSgvDw1K45Y29rYCWBqy4O6shLUxdn/6770PADgpU9cIWg7yQhgoZC/WIhXHXQ6nSBJEsFgkH9NouuFIIiUTcFTwckcWPlkgvVtP0bWXTjRakpKNpJ9Ro3GEpz+uPCs5xK5BCdajYItflJB9AM+vIpTV1cHmqbhcDhgs9mgdzmxOquEP45hcDp445HURSLZagEOre6gTC0TnB88teWB0xvCkUZD0tcWKwEU0wRaqVSiuroa1dXVYBiGF5MsLy8DAF8d1Gq1Cb/fYoqBAy4QwLgQk4SlGumWjxnATMClYLS2tsJs3vuwfGbGBrVcApNaDpLcna2SS0i0VWjABH0pb6+zeq+wQQhSsWbZ2trCzMxM2kkssbZVX6rC67qrEj4s//a6Viikwm9qiQig2GKPbIIkSfzDb6cwsebAB7qArq4uSKVSQbODJo0c13QIJ+hPTtlAM0zBE7tozFg8eMM3X8Fv3zsQYY2z6vTDHxI2BpANZGvuLhmZCq8OAuBnvKamphAMBmEwGGA0GmEwGJISHJphRavUiX2dMSyLj/1qHBKCwG/ee2TP71edfnz7+WW88+J6VL5auf3PJ+ZA0SwGGvQFnwSSLrKVAkKSJPR6PT+eFQqFYLfbsbKyApfLBbX6XPxhtMH5hQpgjlAsLeC1tTUsLCykRCTyMQOYLrjjC0/BiMbHrmnFX13ZzLc15VIS339bH7xeLyYnN3O2r0JmDlmWxfz8PGw2G/r7+1MKJo/eVvQDlyQJ6FSJ2wnx7F7iIR4BzJbYI1tgWRY/Pb0KAOh766URFkjxZgfTtZkJ0XTM1I1Cx+SmByyABbsvggDGmk2MhWIbUE91f8MNg7lKstVqxczMDBQKBd/yi64OUgyLk198AVqFFL++L7N5vVRINs2wOL20je5aXcKkF5Ig0FWjgzLOa0I0A+LV9+Nw7/F6PDNrB8MCyaKZi5UA5mq/ZTIZKioqUFFRscfgnKIoaDQazMzM4OTJk6LEwH3605/G//zP//DFlM997nO4/vrrAQCf//zn8a1vfQsSiQRf/OIXcc0112S0raIlgNlGpjdKbh7O7/enHOmWzxaw0Jsuy7KYmpqC1+tNenxSksDj4xacWXbi0689gGWHDxqFFHp57n0AE92gaZrGyMgIZDJZ0jZ9MmRLBBIdlxVrOxxRKvSqHweGYTA2NoafvL4Sra2tkEat6pOZUHPXCvf7RN/bj19axb88NotHCnwwPxZu6CzHDZ3FkQoiBjIhrNEzXtzsIBcnxqWSGAwGSCUSkAQhqF0qJhbtPvxpxoYSuQSdSQyp//G1e708OTQaS/B31+2P+NkL8w4s2LwIUExScQ7DMDn1nBUL+cgBjjY4p2kaCwsLeOSRR/CpT30Ker0epaWlmJ6eRktLS9rn74c+9CF85CMfifjZ2NgYHnzwQYyOjmJtbQ0nT57E1NRURp9B8X3rRYBw/7voeTghkEgkaSdkZAKuQpbshAoGgxgaGkJpaSm6u7uTHt9T01b886NTqCtTgWYYfPvPi1BISXz86mbBBJCiGXz5qXl01+pwRVt6rbtELWC/34+zZ8+ipqZmjy1PutsSmwAyDIuHzq5DKSVx0+EqfjscWJbFutOH0hIpZJL46SGpwukLYWbLjZ46g+gD7aFQCENDQzCbzaivF5buEj07GE0EE1UHzVoFQBBQK84ffz+hYFkWQXp3ZlBousr0lhuzVi+ubjfnTMwwseHC2IYb7SrxYtW46mBtbe0eBahcLsf3b6vl0yVSwctLTjwxacOHr9pNFIq1vw5vCD85vYbXdpVHzPA1lKlwe281qvTJBTepZkG/65J6+ELJyR+QHyIlBgqhcimRSLBv3z78z//8DwDgm9/8Jh5//HH8zd/8DRYWFnD8+HFcc801OHHiBLTazFJnHn74Ydx5551QKBRoampCS0sLTp06hWPH0o8yLL66b4HD4XDg5Zdfxr59+9DU1JTWDSxfFUAhLVKXy4WXX34Z9fX12Ldvn6Djq9Yrsc9cgvdd3gyVXIp3XNyA91zWlJINjIQkQDMsttxBQa+PhXjbczqdOH36NFpbW3nyd3rJiWW7V/RtZQKSJKBXyXAwRrWAZVns+IK4/isv4Novvyhq5W/R5sWyw48gLe7xeL1enD59GvX19YLJXzRIkoRUKoVcLodcLodMJuNnaGmaRigUAkVR/Hdxst2Es5+4FMY8+8XlC2fWvTi16ERI4Hdp9YRA0awgn0yxIJdKICEIkMhOy5qrDu7fvx8DAwNobW0FAExPT+PUqVOYmpqCzWYTdA/+h9/N4PEJKygm8WIv1ucnIQnUl6n2xLXRDIufnF7DrCX9JCqZhIROoDCnEIhUOihE4qpSqXDFFVfgV7/6FU6dOoU77rgDL774Iq6++mrMzs4Kfp8vf/nLOHToEN7+9rfD4XAA2LVXCy9O1NbWYnV1NaP9LdoKYKG1tliWxdLSEtbX1/lIt3SRLxEIRzzjyd43NjYwNzeXsjCirUKDH759ALJXh1GaTbuzglzlRggIgsCHr25J/sIEIEkSM7YAqr1Bfh6R8ywM/85ohsWHfjoMCUngyfsvSWtb2WoBxxM70DSNEhmJq9vNeH0KvmVC0FmtQ1uFRlRzYIfDgYmJCXR2dma8MuYQ3iqWyWR7bGaEmlCfr2BZFn01amhKywRlxALAsabSLO/VXjSbStBsKsHU1E5O7vMqlQq1tbV8dXB7exs2mw1zc3NgSCl2CA0ubq+J6e/24Nt74Ans5nXHQ2mJDO+6pCHm75YdPtQYlBEzqSyAJYcPAYoRlE6UKS4QQPEQPgMol8tx+eWX4/LLL9/zupMnT2JjY2PPz//pn/4J9913Hz75yU+CIAh88pOfxIc//GF8+9vfjmv4nwmKlgDmAlzLMKmCLCzS7ciRIxlfTPkSgcSrWrEsi+npabjdbgwMDKQcz0QQBOTSvSdqrsySOVAM8NKaH77RLdzRX4PJyUn4fL4Iz0Jgd2X+z7d2oEKXflxQrnKOObHH3NwcysvL8flbhHsVCoWEJCAhxbvRrq+vY3l5GT09PVmNZErHhPp8h0JKwqQpjupnPkQrEokEZWVlfDv4r382jDPLW/hU0AMNGeR9B0tLSyGRSKCSSfbEBW7uBLC+E0B3rQ6Ldh/+b2QT77qkAdKoMuCq04+fvbKOS1vKMBAm5JGSBP76yqactdyLlQAW4n57PJ6YThjRePzxxwW93zvf+U689rWvBbBb8eNsaQBgZWUF1dWZLfYvEMAEkEqloCgqoRKUi3Srq6tDba044eL5agHH2i43o6XT6dDT0yPqDTnXN3eFTIIr6hU4ctCEV155BXq9Pu4M4/F9wsPUYyEX5JYjM/39/bDb7VhYWIDL5YLBYIDJZILRaCyoFTLLspibm4PL5UJvb29OB8+TmVBz/y6RSM7b6uD5rgLOBj76mv14etqOK/uqwLIsnE4nbDYb5ufnIZPJeDuQ8Orgo2Nb8IUYdFZr8cNTK3h21oHbuqtQEWWuXalT4ESbCa3le6t8Qiu0YqAQiZQQ0DRdcOIVMXwA19fXUVW1O+P90EMPobOzEwBw00034e6778b999+PtbU1TE9P48iRvbZAqaCwPr0UkIsbQzIilizSLVvbzRaiq1acf+G+fftQUVGR8/0RGyRJQielMXL2FcGejOkiVQLoCGtLJ0O0ubNCoUBVVRWc0GA95EKzWYFtp51/SJlMJpjNZlHMcdMFTdMYGxuDXC7H4cOH8/5gT1YdpChKkAl1MUXBFQKhSgWJ9nd4dQdSCYkDlZlZbiTDC/NO0Mw5H83w6qDf78fvh5bx2JNDeFMbCYNeD4qi8PqeCgQZAlKSwIdONOPugcAe8gfsVta7a9PzNBUTxUwA07XpyhY8Hk/GIy0f/ehHcfbsWRAEgcbGRnz9618HABw8eBC33347Ojo6IJVK8ZWvfCXjBX7REkAg+1WWeESMi3RzOp0JI90y2W4+ZgDDCWC68375gD9EQy4hQSZpmTgcDmxvb+Po0aPQ6bJ7402lBfzVp+bwneeX8MO396OtIvFnnSjZQ6eSQi4lYTaWodK8W8H0+XywWq2YmJhAIBBAWVkZTCYTDAYDVpx+DK7s4DUd5pTMp1MFpxqvqKgQRWEtNhLZzPwlzA4O/Muz0CqleOKDF+V7VyKQiAC+9ycjAIBn7j+e1X2QkATifd1KpRLfO7sNd5BEd08f3Du7voNjw4OQyWRwvZoe0ZhiZnmuUawEUIhjRa4hRgXwBz/4QdzfPfDAA3jggQcyev9wFDUBzDYStUS1Wi36+vqysqLO1wygRCIBRVGYnp7Gzs5OWvN+uQbNsHjdf5+CVELgkffGfoCxLIvFxUVsbGxAp9NlnfwBkYsTuyeIx8ctuL6zApoYyrwr2kz43ehW0ni7ZMkeNQYVaqKiolQqFerq6nhzXLvdjs3NTUxOTmKbVcJBKUGFDFkjgB6Ph4/T4xIbCh3xbGZimVADhSdIi4dEhMrlp3K8N8mRaH+/dHsnZDmYkbv5UOLOx4/f3gt/iIZSLoVEr4darUZPTw/8fj8vJPH5fNDr9fzsoFQqhTdIY9biQVfNhQpguihEEYjH4yn4gkk4LhDABIgmgLlqiearBcyyLGZmZmA0GtHb2yvqgy1IMRFeViGawfNzdpxZpxBrDc8wLII0k1R5KiEJVOgUuPpA7MFbhmEwOjoKgiDQ29uLM2fOZHIYghFeAfSFaNAME9dGpaNKh1+/L3H1RYxYN4lEArPZDLPZDJZl4Xa7dysWI8MAAKPRCLPZDI1GI8p3zxnvHjx4UDSlb64RTQaBc7OXDMNE2Mzk+iHqCVAI0SwMJcIXabG+15c+lp7SPdtIRAALoXUK7IpqOAVw+P4qlUrU1NSgpqYGDMPwyuKFhQVIpVJ8c4zGvJPG9+7p3vWmzCOKlQAW4n6L0QLOJS4QwAQIJ2LpRLqJsd1cwe12Y319HZWVlbwvlljwBWl84KdDaK/Q8lYu//aHafxuZBN6aQgfiHGj/8ITs/CHGHz0mv1J1XDfeUtvzJ8HAgGcPXsWlZWVqK+v59unYmHbF8JNX30BHznZghtfNWbmEF4BrDGocNeR9Fuf4ckeYt3wCIKAVquFVqtFU1MTgsEg/4Byu93Q6/UZCUnW1tawurqKnp6ePXmZQjC56cbPXlnDx69pgbRAbvLcZ88lyszPzyMUCkGr1ealVXzZfz4PAHj5Y5cITu8pJrAsW3AP+ESIR0hIkkRpaSlKS3ctdQKBAN6p3sCfZyyYHx+ETaeD0Wjkq4PheG7Wji8+vYAvv+FgXKLo8Ibw66ENDK+70WRU4b2XNYqy34WOQqwAihEFl0sUNQHM9gygVCpFKBTC2NgYgsFgypFu6SJZZJnY2NrawszMDKqrq7Ny8kpJYHrTjUBYYP2dA7XortODtczGXOmfaDNjYtMVQf7+PGtDXVkJ6pK0SgFge3sbIyMjaG9v5+OgAHEfghKSAMOyWN327/ldeAXw+Tk7PvrLEfzu/cehUQg/fxLN+4kNuVyOqqoqVFVV8RULq9UaISQxmUwxvdCi93l2dhYejwe9vb1p36D/84lZPD/nwL0X16MyAzueGYsHP3ppBZ+4Zr9oykou5pFlWfT09PDfNfd9hSeSZNNm5m9ONsPqCQk+L4pNBMKd9xxG13agkkvRbCrMmTqhREqhUKC7tQHdrQ1gGAY7Ozuw2WxYXFzkbWiMRiPUajUYFiCAhPPNMxYPZqxebO4EIlr5/hANCUkkPe+LlQAW4n673e4LBPB8AcMwmJmZQV1dHQ4cEN9fLd8IF7P09/djY2MjK5VHmVSCr93dHeE/1mxSo9mkxosvLr5KlIiIm9zhOj0O151TVtMMiz/P2aFa3sb7rmhOuL319XXMz8+jp6cngrCI/f1pFFI885HLYv4ufHHy9JQVIZpFIMRAI7AYlkvyF43oigUnJJmcnNwjJAm/AXN+mCqVCocOHcpon//9dQextu3PiPwBwFeenscfJ6x427F6QQuHZKAoCsPDwzAYDGhsbOSPUYgJtdg2M3f212T8HoWMaMI6seUBSRAFSwDTIdgkScJgMMBgMADYrQ7+7NQ8pl8aw/V1LMx6Pb50Yx30ivjnS2+dHm0VGmgVkojtP/DIJEiSwL/deiDpfhTjs60QK4DBYLDglMmJcIEAxoHD4cDKygrKy8vR1NSU790RHRRFYWhoCGq1mhezZDOD+EBV7LkIkiSxse3Dd15cwx19NWiNo4KVkATuvbgRKlliS47p6Wm4XK6Mq7W/GlyH0xPEW4/HdvBPhvAb6seu2Y+PvmZ/UpUyBzHm/QDggUfG8fiEFc/cf3HKWaLhSCQkUavVMJlM0Ol0GB8fR1VVlSh+mGqFFPvLM19J/+ON7Xj3JX5RyB+X8V1XV8f7dMVDIZpQF1sFMHp/b+ysQCHvvj9I4YnFACobg2lHDSoUCmyzShhNCgwMNERUB0mShNFo5KuD3GcjIYmYsW+XtpQJjoMrRhQiAQRQcFXJRCjqsyMbNzNOMbq5uYmmpqa8iDGyDY/Hg8HBQTQ1NUU8yHKVXhEOkiQhIQCZhIggd4+NbcEbonFz2Gxd+LA7y7J4YsKC/RUa1JeV8IRWo9HEFbAwSfI6w/GlJ2bBskhKABdsXtSVqhLOKe6SOGHbFYv8AcCS3QewLB/BJwZiCUnW1tYwMTEBpVKJYDCInZ0daLXagiAbaoUU7SJ4xbndboyMjKC1tZX3gRMKISbU3OvOR5uZdBFNADNZxKSDbV8Id3z7DD7xmn24fH9yY3hPkMZOgMX6diCjrOn3hc3wRVcHOcN3j8cD3auzg2VlZTEXu7cczp7PaSGg0FrAxbbAAoqcAIoNiqIwOjoKqVSKgYEBWK1WbG9v53u3RMXW1hamp6fR1dW1xw4lH+ITkiShV0rw8WsihSeDq9tINK5HMyyGVncwZ/XijX3lGBwcRENDQ9xonF+8sgabJ4gOUhgJfOg9R5MGvM9ZPbjnO6dx9QEzPvXa5G2WZAifHxPjxvaDt8YWx4gFgiAQDAbhcDhw5MgRyOVyvloRLiSJ94AqFnC5xV1dXaLM9wgxoc5GIkmxPaDytb80w+KhwQ3sL1eDZljM27yCCKBOQeLWAxocqMrODBhn+M7N6bpcLthsNiwtLYEkSX52UCwVf6GjEEVCxXaNFe9dWWR4PB4MDQ1FRLrly44FEJ5DLBRcDJfdbo9rXp2vCmCsbX74ZEvCv5NKSLzr0ka4th04c+ZM0jSW2lIldvwhkBB2cepUya01GspKcGt3Nd7Ql1keYz7n/TLBysoK1tfX0dvby59PYghJCgkbGxtYWlrKWm5xIhPq6AXBX0p1MEgxIIj8Pky9QRpbrgAee/9RwX/DsixkEjIn+0ySJPR6PfR6PZqbm3kV/+LiYkR1sLS0tOC9XM8XFFpFUgiKmgCKdaFxVbFoEsFlAecDXBqIGCcUN7iuUqnQ19cX9z3zVQGMRQCFfLe2zTWsr6+jr68v6cP5aFMZjjaV4c9/Xo34OcOwgmfzoiEhCd7WJl0UI/njZi39fn9cpW+6QpJCATcKYrfbc5pbnMiEmiNE6ZJBIYTKE6Bg9YTQUJa/2MCrvvgCCILAv18izcv1ICEJ3HM09TnWdO/XYhDdcBU/y7L87GCy6mCxWQMVMrxeb8YpILlGURPATMEZH29vb8esiuWzAshtO9MHj9frTdoe5VBIFcBEYBgG4+PjoGka/f39aQ8CT2268d4fD+Jzt3TgSGNpWu8RDZZl4QnSguxeipH80TSNkZERqNVqdHV1Cd5nIUISk8lUEAo6zuaFYRh0d3fnjaDGahWHE0KhecXhSPZ9nfjii2BZFs99+LhotjmpoqdOD6NaBmA7rWtix0/hySkbrm43oUSeO5FAtG2NEHz4F2NYtPvw03t7Qab4tyzLwhdi9hwjQRB7qoN2ux1LS0twu93QarX87CA3anABmcPtdhdVdwP4CyaAwWAQw8PDCSPd8kkAxYiDs1gsmJqaStoeDd9moRPAYDCIs2fPwmw2R9hwpAJuxS2TEJCQBJQJlMWp4tkZG+asXtzWm5hsiyn2yBUCgQCGhoZQU1OTdDGRCNFCEo/HA4vFgsHBQQC7iSQmkykvQhKapjE8PAydToempqaC+V5itYrDs4qFtIqFVHu+ekcnRtZdeSN/APDFNxwEALz00ktp/b3LT8EbpOAN0gkJoNMbSilFJRnSmUmTSHYFYonIX4hm4A3S0EeNpXzpqQW8sryNL7zh4J7fhUMul6OyshKVlZVgWZafHVxZWQHLsgUn3CpWFFsMHFDkBDDdk3VnZwcjIyNoaWlBeXl53NcVQgUwHXApBTabLe68n9jbTBepEECXy4WhoSG0trbCbI6MfvOHaHz16Xm89Vg9yhIo8Dh/PoIg0GRS4/cfEDdMvqtGD5VckrACyLIsP1pQiO3PWHC5XBgdHU1LBZsIBEFAo9FAo9EgWGJGY6kc9jwJScQiuNkCy7L4wYsruLzViIayEpAkCalUKtiEWkirsa9ej7765IvFQkaNQYm7kngkrjr9eGLKiouby0TzFUynBfyvtyQXj73jh0MI0gx+9LaeCKJ4easRk1se6JS72cI/emkVd/VXQ53g3kMQBJ+H3tTUBI/Hg5GRESwvL++pDhby7GA61dZso9hMoIEiJ4DpYHV1FUtLSzh8+HDSfn2+CWA61TiKojAyMgKFQpFw3i8WslkBjDdrF56icP/PR9BTp8c9F9Xved3m5iZmZ2dx+PDhmBfZ6LoLfxjfQrNZjVsOx/do47aXLeJlKJGhvyF2O7kYW74AYLVaMTMzg66urqzNuLy86MS9PxzEPRfV4v6r9vFCkp2dHVgslqwLSTweD4aHh7F///6I5Jhk2HIFoJCSCSswYsHmCeE/n5jDb0c38eA7+vmfJzOh5hYbLMtemPl6FeVaObprdKjWi5fDmy3RyjsvrsO0xbunSni4Roev3NEJYPf+9+c5B7pqtDiawjiLRCKBSqXCwYMH91QHAfCzg4VWHSxEwYXH47kwA1ioYBgGExMTCAaDGBgYEFRNyEdLNHzbqZJPbt6vvr4eNTWppwRki/DSDItPPjIOvUqKj0XZvXCfMUEQ2HIF8Pi4JYIAcuplh8OBgYGBPatSlmXx8qITzeYSfPWuw6g1JB5ez3XMHgCMrO3gvT8axP++vReVWnlBkT+LK5CwYrm8vIzNzc0IpW82cKhGh7v6q3FH37nzNjolQQwhydq2H48MbeBdlzTwD1TO5qWzszOlIHfu3JNJCFx9IH4nQSyYNHJ87a5DaC1P/JCJNTvo9Xqxvb2NmpoahEKhnJtQFxpkEhJdNbrkL0wB2SIll7YYcWnL7qJkyxVAeYxM4BazGg9c24JGY2oLo/B9jq4OhkIh2O12rKyswOVyQaPR8NXBfM/qFqIJ9AUCmGMIfYj6/X4MDg6ioqIipUi3fD6kUyVj3INR6LxfLGSL8EpIAmBZPD/nwCOD67gprEInkUiw7QvhB3+Yxr/cehC1YYkN3DyWUqlEb29vzJurJ0jjuVk7LK4Aru9KbnzK2evkCizLYt3pB82ysLsDqNIpCob8sSyLG776IgiCwIsfvXTP76amphAMBuN+9mJCLiXxsWv2J3yNGEKSLz45h0dHt3Cy3YwWsxqbm5tYXFxMy+aFIAgcby5LyaCYZVn4KQYqWXoPr4uaUhMrkSQJj8eD0dFRHDhwADqdjreZSceEetsXwh8nrbj1cKXg8/jS//gzAOCZ+8Udtyg0ZNOXbjcK04Gv/mkB91/VjIEGAwCAYlhIiN15QAkJPHDt/j1/l8ikPhFplclkqKioQEVFRUR1cHh4GMBudbCsrAw6nS4vs7qFSABTWUAWAoqaAAqB3W7H+Pg4Dhw4IOrsUrYhlACyLIuFhQVYLBb09/dDoUi/pZHNiudnbzqA9/9kCKEoc2WSJOH1UgjRDNyBc5Y7Pp8PZ8+ejfBljAWNQoq7j9TCILAFN26ncPr5Zbz14iYo0nwICwVBEKBpGle2luGK/ccKqvIH7O7fB65sRlVUG4wbI9BqtWhtbS2ofeYQT0gyNDQElmXjCkn+9tr9uOlQJfaZSrCwsBBh8+IN0nh62oruWj2q9MLIYKoigjPL21jd9uPqdjOUWT7/AMDpdGJ8fDzCxDpZRF0iMvjVPy3i4aFNtFVocDBOvONfKhiGycqc6hOTVpxd2cGdfdW4uLkU7a/GZT50dh2/Ht7Cv956ADd2lfOClxfmHXhm1o62CjWemrLjU9fvjzuiwDCMICIVrzq4urqKiYmJnFcHC7EFfMEGpoAQHukmxCeu0CCEAHKWHDKZDP39/RlfENl80EslJL52d/een5MkiTIVi7+9ro3/mcPhwNjYGDo6OngfuUSI1RKJB7VMCj/YtFWO7gAlyOIF2D22UCgEqVRacDcrDm86Ekmu/X4/b4ieLO+2UBAuJOEeTlarNaaQRKeU4VhTKSYnJ0HTdITNi4TcrVanaseRClrK1a8qz7NP/iwWC+bm5uJWN4WaUHO/J0kS913agP4GPTpSiNc73yt/HBiGgc1HY3Bst8KcqPKWCqr1SoxtuFGpV+CvrjiXS99gLIFMQkCrlKKn7lzX56evrMMXonFVqxEyCZFQCc0R/lQRXR10u92w2WwYGRkBwzD87GC2qoOFWAHkRDTFhPOSAHIVDLlcjoGBgYwfvvlwpE9GAIVWyAodHEnisLKygpWVFfT29kKlEt+MtsUox2uaq9Iyf57YcOH5OTuu76xEhS4+6eTEHkajEadPn4ZOp4PZbC74SDSXy4WRkRG0t7cLIt6FCplMFmGKu729zQtJpFIpPz/Y0dERcV0rpBK8JsuzfDqlDIdrs6+yXV1d5VNahKo545lQhyuLtQoSV7UaC7IqnC5+/PIaRtdd+IfXZlbtZlkWM9YAtoI0QjQDCSkOQWmv1MTMs+6t0+Prdx/a8/N/u/UAmFdTSXrrDQnfW4xKGkEQ0Gq10Gq1aGxsRCgUgsPh4DPC1Wo1jEYjjEajaNXBQiSAHo+naBbNHAr3aSQAsS5WLtItXSFENLi2aK5PNolEgmAwGPN3NpsNExMTOHjwID8gX6zgPl/OfDcQCGBgYCBrnzdBEKBoGi4/Ba0ytdO/tlSF1nINytTxH6jhSt/GxkY0NjbGjEQzm81ZIbjpwmKx8CprsRW2Nk8Qo2suXCYgT1VsEATBC0mCwSDOnDkDnU4Hn8+HF198sSATSSzuAIxqeVqVSM4CyuVyoaenJ+3rKJkJdSybGbEwuu7CgRQqjJniey8sI0nstyAwDINjjXroS8ugSGEuVGxISAISgZGX2WilymQylJeXo7y8PGvVwUJsAV/wAcwDOF83YDfSbWZmBp2dndDpxFF4cZW4XBPAWCrgYm9rxwJXAXzllVdQWlqK9vb2rFYXSJLEnd8bBsMS+M37jvED/AzD4kcvraChTIVL95ti/q1GIcXFLfFJTDybF46AtLS08ErW8fFxBINBGI1GmM1m6PX6vFVVlpaWYLFY0NfXl7Ra5A3SeN+DQ/jENfvRWiHsZveW753B+rYfj3/wGEpL8qMe3N5x4ftPDOLSriZ07ttdGBZiIondE8Qz03Z0VmsFf74cWJbFxMQEAODQoUOinU+JWsXJhCTeII2vP7uEd11cl9CfjsNLi0586BdjeOtFtTicIxu6X983AIbNfASGZVlIJWReyV+qyDaRiq4OUhQFu92+pzpYVlaW0vx6IVYAvV7vBQKYD3CRbjs7O+jv7xf15s3lAef6gRDdAqZpGqOjo5BIJKK0tQsFgUAAa2trOHjwICoqKtJ6j8cntvDfTy/gf9/el1TYQZIk7j1ahT8veyPUmyS5u5BwB9I33xaS7BGuZOVuhqurqxgfH4dWq+VbxbkwYWUYBlNTU6AoCj09PYLOqVWnD8NrLjw6tiWYoHz97kM4vbQdm/xRARA7awDlBRQ6sJpKQCLusTudToyOjaGqphbyknMLw0RCEpphICkxoLW+MuseaJ4ghVv/+yX8003t6GswoLdev0eYkwzcPLBWq816gkms6mC0kIQjgn+aseHnZ9axv7wEr+1Mfn0frtHhjQM1uLmrAgsTm1k7hnCIlXpSiFWpZMj1Pkul0ojqoMfjgc1mw+joKBiGQWlpKV8dTLRfhfhZu93uCyKQXCMYDGJwcBB6vR69vb2i3/jyZQYdvl2fz4fBwUFUV1ejvn6vSbLYyNXMIzeXZTQa45I/hzeIbz27iPsub4pbQXhiwoIARQvaZ5IkcWWLAa8/um/P794cw4BaCNJN9oi+Ge7s7PDiBYlEwreKs5EvSVEUhoeHodfr0dbWJvj73l+uwe/edxT6FNSvNQYVamL4MxLORZCLzwJMCCAkAEsDUiXophOARpxZvM3NTSwsLKCvtzdhxTxaSPLar76AVccavnqtDwh6s5pI4vJTsHqC+N3YFgYaS1P2cguFQhgcHERlZWXO54HjVQc5UnhZsx7/cWsrDtfqBT205dJdoQnLsljI9s6LDKE2MCzLYmMnIFhpnk3kk0iFX3MNDQ2gKAoOhwMbGxt8RZ5rF0dXBwuxAnihBZwHjIyMoL6+PmGkWybIJwFkGIa3sRGqiBVjuzRNZ1WswFnXWK1WHDhwAFtbWwB249zWt/1oMp1bRZ1Z3sbz83Zc0WaKm7DxuVsOCt622D6AXOUjU4uX8AD3ffv2we/37zE95lrFmd6wOV/MhoYGVFYm906MhjkF1XVceG0g554ESoyANOz9Ql5IZh8DfeAWQJ7ZanpxcRE2my0lIQSHv7uuDd99fgnH+g7vEZKInUhSqVPizx+5JK1KFPddNjU1Ze0emAqiq4MylkV/g5QnhhRF8a9JdB7nQ3iXKYTGk/345TX89JV1/PPN7THFHZlgx0+hRC6BVKDILVvWNelAKpXuqcjbbDaMjY2BpmmUlpairKwMer2+oPabwwUfwDygt7c3q8kO+SKABEFgZ2cHbrc7p/N+2U4/4VrZUqkUfX19cLvd/Pb++qfDcPpC+Nabe/hq32UtRrRVaFClE+f4xTq+bMe6KZVK1NbWora2lp9VW19f5z23OAKSKrHZ2dnhTYENBgMYls2q7Uk8kNbJXeInjSKTshIg4AJhnwNb2ZXWe3Mm1qFQKMLmJRVc1FTKmy6HC0kA7CHnpaWlMJvNMBgMeG7OgQOVWpg0qY2MpGML43a7edV2IYrBMpkdLFYCKORcO9FmhNUdxD6zeJX9sXUXQgyLn72yhhKZBB85uQ/bvhBMGnnCz7EQW6lA/Org5uYmpqen+XZxaWlpRt63YuLCDGAeEC4CyQbyQQBpmsbs7CwCgQAuu+yynF6g2SSAXLWiqqqKb2WHb++B61oxtLoT0eqVSsg97UOWZfHVp+dRU6pKmPsbC2JEwXHkL9w0NxNQDIMQzcZNh4ieVXO5XLBarThz5gxIkoxoFSfal62tLczPz/NK3yDN4EenVlBaIsPNAj9HT5DCif96Hjd1VeCB61qT/0EcEDurgCLOalmuAeFaS4sAcrNwGo0Gra2toqg7oxFNzrkH0ysjE/jIMwEYS2T43fuOZDw3zLAsxtfdaDCq9nhPOp1OPr4u1w+dHX8IOmXqc5pCZge56ykZAXR4QyhN0YQ72xBKWit1Snzgyqakr4vGMzN2TG258fZjdXu28/DQJlgWuLi5DPtMJbjvwWEs2nz41A2tuLQlfgBCoRLAaERXBycmJsCyLMbGxkBRFD87KEaHJF1caAGfh8g1AeRIktls5tsluUS2jvcHz87gT2PL+Kdbu1BuPqeyDSeAdWUlqCuLXBV7AhTG1l0YiAo4f2LSApIgsN+sxti6C7f1VAvy9su0BRwu9hCD/AHA1V94AQzL4qkPHU/6fuGO/M3NzQgEArBarZienobf74dbogEj1+Kqzlq+8sKpx6PboXIJiS8/tQCSBG46JCzaa3rTDYZh0/JRjIBEBjA0EIvzMnRaQhBuHri6uho1NTVYdvjw0oITJ9pNgpNiUgU3q2kymdDezuKTJUuoUQQxNDTEe0Gazea0hCS+EI3xDReCNI2eOgP/c47Id3d359wJYHh1B/f+7yD++spm3DWQvs1WeHUwnAByVXXOAisWQfneCyv4zgvL+NqdXTm1i0mGbJOp7724ghDN4O3H6vb87r2XNYBlzyXTVOgUqNYr0FmduCVZLAQwHARBQCKRoLy8HAaDARRFwel0YmtrC9PT01CpVPzsYC6vj1AolPeM5FRR9AQw220CqVSaMwLIJWBwmZ0WiyUn2w1HNiqAa2trODu7ArWuFP/0xBo+do0aryxtw6yV41ClCk4fFfdvv/7MAp6bteMLt3fxOcEEQeAHb+uHhAB+8OIyAhQDoadBJscnVOmbKm7vq8Lwqiut91MoFKipqUFNTQ1omsZPX5yDw2qD1rvGWyzY7XaQJBlT6fu1u7rgCggT0ADAgs2HT93Qhtd2pafY5sAYW0GungJkMbwQgy6wNQMpvZ/H48Hw8DBaWlpgMu0uMLQKKRQyEsoc2XIQBIHb+hv4/w6FQrDZbFhaWoLL5UrZEFwtl+I1HeaIJIeVlRVsbGykNdcoBurLVFBKSXTXiWOzBZwjg9z/BoNBTE9Po7y8PGar+HhzKR6ftKKhrHB8NIHst63/9ZZ2OLzBiG2wLIsdPxUR9cawLG49XIneOn3SNJJiJIBApAhEKpXyizCWZeH1enmv3FAolLPqYLGNLADnAQHMNiQSSURSRbawtLSEtbU1PgGDWwnnGmJWALlZLI/Hg3954yWYs/nxb3+YxrLDh6HVbUhJAo+N0Xh5xo3enlDMvMq3HqtHd50eNYbIlRz3UHzHxbsPXKEXX7oEMFzsIfZN5L7LUm8HxYJEIsGdx1rAAiCw2yYcGxsDwzBQKpVYXFyE2WyGWq3mP6/oymoyXN9VATESrtiyZrC2KRAeC6AqA0gJwFCAxwJWWwVWL7y6xOXddnZ2RgxhG0pkuEGA9Ui2IJPJUFlZicrKSl5IEm0InkxIwrVaWZbF3Nwc3G53RgbPmUKvkuHp+y/O2vtzVdza2lpUVVVFmFBz96XGUjm+88bOzKvQIiMemfKFaCilmXcLfvLKOrxBGh+8Us2LPH41uIHRdTfef0UjtEopnp9zQCoh8fMz6yAJAn31iVNn8hFyIAbiqYAJgoBarYZarUZ9fT0/osFVB5VKJZ9KImZ1kGXZrI6iZQsXCGASSCQS+P3+rL0/wzD8Qzo8AUOMWbV0IFYFkKIoDA4OQqfToaenBwRBoLVCg/95cw8AoKfOAJIAZrbc2LZtQRcnlaNMLceJNnPc7aR6U42OnkuGbIs9xAZBECCwax00NTWFlpYWVFRUIBgMwmq1Ym5uDh6PB6WlpbytSSqEVi6SZxqkSjAtrwG5PgTCMQ2wLEBIwFR0gq3oAkhhtyauHRov7zbXCFJMhL8kh3AhSUtLS0IhSfT3wTAMJiYmQJKkqAbPsfbdE6QEmXUHKBqPjVtwvLkMZWpx2l7c+Mu+ffv4Km54q1gmk+2xmeH+XSKRZGVxlgpiVQAphsUPT62iRC7BGzNomQPAG3qqYPMEIxS+F+8rg1xKQqeUYtrixf+NbOG6g2a86UiNoLzmdLOA8w2hlcvwEQ2WZeHz+SKqgwaDAUajUbQkoEJ/PkSj6Algtj/wbM4Acje8iooKNDQ0FMTJEyuBJFV4PB7emiJeNiL3kGyr1OLWFlnOjj0V0VChkT+aYUExDBTSxCv27e1tjI2NoaOjA3r9bgVALpejuroa1dXVYBgGDoeDnx0sKSnhb5JiKeqs7iDK1DKQBAG7J4jrv/IivntPT6TtPSjAwgAA1RVJREFUhawETP1FQE0vQAV3FcEpzP5xCSb5aodG45UlJ971oyH8+20HcXmS2LtYQpKtrS1MTk5CpVKhvLwcRqMRUqmU92tsbGwUfA6yLIsQw6ZE2B+bsMAbpHFrdyWkSR6GAYqBN0jD4Q2JQgC5Fn4yRXMqJtQJjYRZFg8PbuKKVqNoYpJYpERKEmgxl6DFnLlBsEkj36MuL9cq+Cr3PlMJ3nqsDo1lqpiLEKH7XAxIxweQIAiUlJSgpKQEdXV1/HVntVoxMzPDVwfLyspSjuksRF9CISh6AphtZIsAOp1OjI6Oor29HUZj7jNS4yF8KDsdcKurrq4uQXF8uSZV0RXOeIKGbM37ZYL/G95EkGZwW09V3P3hjI8TCQRIkuTbINzMjMViwfDwMBiG4VXFGo0mreN2ekN4fMKCA5UaHK7VY9XpB82wGFrdie17JpHv/iMQ4TYvQhNMAGTd8qZMLQdJAOYULWAIkoRUrUe7yYSx9R2cWbCixOfH6tAQXC4XP9CeCn4zsgl/aPdcEXrMl7aUweENJSV/wG5r+va+zLPWgV1rorGxMRw8eDAlH7VkJtSJqoPTWx585U8LWLB78aETzaIcR7wZwCtbY0dLig0JSaC1PDWiWawEUIz9Dq8OAuBnB6emphAMBlOqDno8nqJLAQEuEMCkyAYBXFlZwfLyMj/vV0hItwXMsiyWlpawsbGB/v7+gvFmikb48QUpBjd/7QU0lJXgv9/Yzb+mEMkfAPQ16LHto2LuD2eu7XA40NvbC4lUikv//TlU6hT4+bviCyrCZ2YaGxsRCoVgtVqxsLAAt9sNg8HAt4qFrnD1Kin66g2oLd0loJ3VWrzw0UtFmR3kbF7UajVaW1sFfzcMy+KXZ9ahVkhw3UFhc4EBik5abQ1Ho7EEpz52meDXc7jpa6ewuRPAkx86jhK5FGqVCjVVBjisFhw4cAAEQaQsJOmq1mLZ4U+J8OqUsrTsXTKB3W7H1NQUDh8+nPG9MFl1MNyEurVcjc/c0IquGvHELEDxtQD/kglgNKKrg06nk68OKhQKftEc6zwtxhg44DwggLloAXMxX5mCm+UJhUI4cuRIQZaM0yG83Bwjy7IFn1Mc3gKWS0lICALddecGpbMp9sgUu5Fqe3/OMAzGx8dBkmSE8TFBYI9/XDLIZDJUVVXxA/jcTXB2dhYKhQJmsxkmkylprNr+sEoEQRCQiHCZcgKBqqqqlCPPSIKATEIIVo7+cdKCjz00jm++8XDE+ZENfOhEM772zCI0Cik0CilMCgZDg2d5s24AMYUknDdaLCFJo1GNRmNhP5C2trawsLCAnp4e0ReMyUyoAeBIvRYkSWSNBIVoBv4QA22c+eZCQLESQCC7z36JRMITPmC3OsgtVgKBAF8dLCkpgUqlStsD8Gc/+xk+/elPY3x8HKdOnUJ/fz//u89//vP41re+BYlEgi9+8Yu45pprAACnT5/GW9/6Vvh8Plx//fX4whe+kPZnUbhnZoFALBuYQCDA+/txq/pk4DzrCtkImjuu8vJyQXOM+Xb4jz6+3/zVMQCFN+8nFKFQCENDQzCZTKivr4/Y72c+fElG702SJMrKylBWtmsk6/F4YLVaMTo6CpqmYTQaYTKZoNPpsv55eb1eDA0NRdi8pAqhZtcAUKVTgiQAY4rt3HRwVbsZV7XvCp0cDgcmJydx6NChPRWFTIQk+UK8631tbQ1ra2vo6enJyfxmdHUw/B9uH2MlkmSCN333LEI0g5+/sy8vaTtCUMwEMJfgqoPczK7T6cT6+jre+ta3wmg07nZd0ijodHZ24pe//CXe/e53R/x8bGwMDz74IEZHR7G2toaTJ09iamoKEokE9913H77xjW/goosuwvXXX49HH30U1113XVrHdYEAJoEYLeDt7W2MjIygra0tpYcXt+1cXqASiQSBQEDQa3d2djA8PCz4uByeIN7y3dN4y7F63NZbgxDNCM6sjMau7B4pW0HEIrjFSv44UtTc3JyTHFiuVdzQ0MB73C0vL8PlckGv18NkMsFoNIpe2eZELQcPHhQ0VyoGOqq0abVzM8Hm5iYWFxcTzm+yLItfDW6gUqfAseayuEKSkpISmM1mGI3GvI1j/GpwHRTD4vU91RE/X1xchN1uz5udTaxWcTghpCiKNxvO5N77tmO1mNr0FCz5A4TnF1/AOYRXB19++WWMj4/jO9/5Dk6dOoWenh5cdtlluO6663D55ZcnHWs4cOBAzJ8//PDDuPPOO6FQKNDU1ISWlhacOnUKjY2N2NnZwbFju4WLe+65B7/61a/+cglgoauAV1dXsbS0hJ6enpSD47lt51LhKLQCuLGxgbm5OXR3dwuefXj47BqWHD5MbrrBsizu+9FZSEkS96Rhg3f3t18Gw7B48N6BlM6B6OMr1Hk/ALC4A3huxo7rOyv2qPo477tckqJwxPK4s1gsvMcd15rMdK4rPPUi2/OyZ5adIAkCh2uz1/J1BygEKWaPcnZ5eRlbW1tJK2IEQYBhWVg9wYifR9tdcNVaTtgjJJFkaHUHH3toDD97Z3/KowOxYCyRw+Y9t58sy2JmZgaBQACHDx8WZWG76vThhXknXtctLMkmGrFaxeFZxYnyipPh2o5yXNuR8i7twa5v6g6uO1i+h0zOWDwIhGgcrD53DwjRDGQpqL8L6Z5XjDhw4ABOnDgBnU6Hz3zmM3jmmWfwu9/9Dg888AAqKirwta99DQ0NDcnfKAyrq6u46KKL+P+ura3F6uoqZDJZxPgL9/N0UfQEMNtI14+PYRi+NTMwMCDI+T8amSpy00EyGxjuJr6zs4OBgYGUyOm83Yer28vxkatbdiPNlDIcrtUBrDfl1nCLWYMZizstH0Du+yxE8sewLGyeIMwaBazuIDwhGiE60ltuY2ODX1QUgvddeGsS2PUgtFgsGBsbw9pOEO21u6pivV6f0meca5uXGYsHQHYJ4B/GtxCkWNzZv6ugZVkWs7Oz8Hq9ghXNt0VV1KJBEAQ0Gg00Gg0v7BGSSPKnaSsc3hBsnqAoBPDSMCsclmUxPj4OiUSCgwcPinatfeo3k5je8uDKVqModjRcdVAqlcY0oRZqM5MMZ5a3MbTqwpuO1CRM67B7gvjtyBZ8FIPXMCzIqGHaR4Y2QbMsTwD/NG3Dg6fX8LfXtPDJSecbCtFwmZsBVCqVuPrqq3H11VcDABYWFvC2t70NW1tbe/7mn/7pn3DzzTfHfL9YxxjPwiyTa+kCAcwCuGF1o9GI9vb2tL8gMTz5UkUi0klRFIaHh1FSUoLe3t6Uj+szNx7gbVeCFIPb+2sw0FCKUy+upUQAKZrB63qqcKgm9Qc1N1fJsiwv7imkGZj7fjyE8Q03Hn7PAA5UanGg8pwtBsuymJ+fx/b2Nnp7e9NaVOQCKpUK9fX1oEqMGJ22wg0SwdVVjI+PQ6fT8a3iePvPsiymp6cRCARSsnnJFK/rTkysYmHR7oVJI4daLuy7uLLVhAC1e31x4h2JRIKurq6sLUASJZJwMVpmsxn3XdaEd1zcAJVM3LYswzAYHh6GVqtFU1OTqMf5b6/rwMyWRzQz6nCkakKdCpYdfoRoJqky/iMPjSNEs/j6XZ0xq3r3XlwPhjlHCip0Csxavfj6s4v4hxvbk+5HISx6U0Uheu55vd6YIpDGxkY88cQTKb9fbW0tlpeX+f9eWVlBdXU1amtrsbKysufn6aIwnyApoNBOYG7er7W1FWZz/AQLIcimCXU8xGsBe71eDA4OoqGhIe0T7icvr+Bbzy3if97UA5sniN+PbsGgkvHbFPqgn7F48NSUFWq5FK0VqSmvCIIATdP8nE+hnT/vvawR339hBYaoWDxOaS2VSkVrn2UbdaUqXNZqRm2pElKybje3dGcHFosFCwsLvIrVbDZDpVKBZlgEQhRmJsdRUlKCzs5Owd+P3RMEC8CYARFIlpsajQBF408zNlRoFXjNAWEzmFzKBk3TGBoagsFgEGzwvO0LQa2QCPLpi4d4QpKpqSn4/X7RhSQURWFoaAhmsxl1dXUZv180SkvkGGjMvlAHSGwzQ1EUv6gUUh286VB8KyJfiOZJ+EeuasaOn0JJnAVGdIJSW4UGH7mqOWUvymJCIQpXOMsssXDTTTfh7rvvxv3334+1tTVMT0/zziFarRYvvPACjh49iu9///t4//vfn/Z2ip4AFhLW1tb4IW4xPIHyQQBjbdNut/PzZpmc5FZXAFZ3ELMWNy5pMUGnlKLRWIIzy6kpj1vMaryuu3pPPnAysCwLqVQKn8/HK7LNZnNBeRYertXj318fWdkMBoMYHh6G2WxGfX19nvYsdcgkJBqN5+ZeCYKAXq+HXq/nyYfFYsHExAQCgQDe/6QfDMvioTftS/k4H5+wgAVwh0jmxEKgkEpwss0MQ4pJElyHoKamRvBiimIYXP3F5yEhCDz/0UvT2d2YSJRIkmlCDHecdXV1qKyshD9EQyFCJq6YmNx04wM/HcYX3tAV26Q8DsKrg8FgEGNjY/ycVyazg3ZPEP/70iqONBpwtLEUHVXCjbE5XH0gs8JDoaMQK4AejyetBc5DDz2E97///bBYLLjhhhvQ3d2N3//+9zh48CBuv/12dHR0QCqV4itf+Qp/zF/72td4G5jrrrsubQEIcJ4QwFTivdJFohYlwzCYmpqCz+dLe94vFgqhAri8vIzV1VX09fVlPG/2luMNWLD7QBAE5FISLeWamNtMBqmERIMxNUENN8tDkiSOHj0qevpFtsBFZO3bty/jinKhQalUoq6uDnV1dXC5XDg2fhorHglWV1dhc2yDUelxqKlK0PzfyXYzhNwBaIbF2ZVtHKzSYmMnEEFQ00GVPrVrglt8pGpn4wnQqNYr8bpu4VY2qUKIkESo7U90rm+QYvCzV9ZRpZPjpMBqaS5A0SwIEKDSnLUOBAI4e/ZsRH5xPBNqIXnFOpUMVXol9pmy7+FYiLN0QlCIFcB0fQBvvfVW3HrrrTF/98ADD+CBBx7Y8/P+/n6MjIykvK1YOC8IYLbBEbFYxI5b5ZaVlaGtrU1U8pBPEUi4afXAwIAoKy6NQop/u60z5jazeZyxxB7h6RfBYBA2mw3z8/PweDx8G6y0tDSvNxqHw4GJiQl0dnZCq9UKmpN86Ow6KrQKHN9XlqO93At3gAIBQC1QSMDZvPzjbb3Q6XRgWRZPja3hzNQWtrfWoVdJeWISr7IudAbsf55bxLeeW8K7L22ATELCpJGLIngQApfLhdHRURw4cIDPaBaKAMXg9r5qnGzPzSIgnpCEs/1JNMsZK9dXLiXRUKZEe2XqFa1UQTMsSELYeNDBai0eff9FSV8XDYZl8ZvBVZR5l3HwQDtKS0v53yUyoQ4XlHC/D7/HSEkCr+/JHsmPOIYCJFJCUIgVwHgzgIWOCwRQAOIRQM4HT4x5v1jIlwiEoiicPn0aRqNRsGl1ptvM1nEKEXvI5fKI9AuHwwGLxYLHXp7At0Yp/NN1DejeVw25PHdzNevr61heXuaVvqtOH56csuG1nRVxW44sy+I//jgLkiDw9P0X52xfo/HI0AYIArirP3laRyybF4IgcKy1EvuqylBfpuLn1Kanp+H3+1FWVgaTyZTWnNptrz5cb++thitA5Yz8cSkCXV1daY2HlGsVuHsgtfQTMRFPSMLNcnIEnaZpjI2NobOzc88D8bL9ucnE/cnpVUhJIuOs4kQLrsdH1/Bfj8/gvssacEkY+YuFeCbU4cpisU2oheACARQPF7KA84hst4BjEZT19XX+wZWtLz4fLWCfz4ft7W0cPnw4J+bCQHYqgOmaO5MkyZt8+tROyKbH4fL6cfbsWZAkybeKs/WdsyyLubk5uFwu9PX18Tc6uZSETEJAmiBTjSAI/OCtvSiR5/fmePl+oyDzW877LpbNi1ImQf2rsW3Rc2p2ux2bm5uYnJyEWq3mPQeFtIrNGgXec2kjgN12Wy7AGTxnI/IsH4gnJBkdHYXL5UJlZSUCgQBKSkpEIRjDqzvY9odwyT5j8hcD0CtlMKoz+25fnHfgs7+dwn/ffQh1UXYqLpcLyu1F/M3VLbiiI361bnTNhdYKdYR6N5kJtVg2M0JQrASwEPfb7XZfqACerwgnYizLYmpqCh6PB0eOHMmqFUcqqRxiYGtrC9PT01CpVDkjf4D4BFCsZI+eOgN++2pUHLA77xNdieL87cS4IXHVE7lcjsOHD0fst1mjECRwyHSmTQzUGBL7jwUoGotzs/D7/SnbvEgkEl68w7Is3G43LBYLzp49C4IgIlrFhTDLGe5lWKi2PZlCqVTy1fHjx4/D4/HAYrFgamoqYyEJAIys74BhgEv2CXv9DV3xFbbxYPMEcWZ5G1e0GnmVdazTx+l0YmJiAv093QmN/RdsXvztw+O4qt2ED1zZHPM1yfKKMzGhFoJCJFJCUIgVQK/XC602++MNYuP8vCOJDKlUCoqiEAwGeeuGnp6enLRGczEDyPnL2Ww29Pf34/Tp01nfZjiSEUCKZiAV6GyfzVg3hUKBmpoa1NTU8JWo9fV1TExMQKvV8tFb6TzouXOroqIiK3YZhYIzSw48+vIUrm0zoDtD7zuCIKDVaqHVatHc3IxAIACbzcYbK2c6y/nw4Dq8QQZ3DaTeSuQMnn0+X069DPOB1dVVrK+v8ykmKpWKF5LMrNsxsmqBcX09ZSEJh1wou+etHqw4fAhQDKRyEkebSvGb9x6NeA3Xxuei+ladPpi1Cshj3Jvqy1S456I6XLZf+CxuIpsZQDwTag4XCKB4uNACziNyQcRcLhfGx8fR0tKS09ZotlvANE1jZGQEcrkcfX19Ob8hMAyLU6t+DCgCMMbo8Ng9QXz/hSVc2WZOmtCQy2SP6EpUuL+dTCbjW8VC4ss8Hg+efmkIHfubUVeTevWCgzdIgwUr2JQ41wiFQrAtTaNMp0bXgf2ifz8KhQLV1dWorq6OmOXkKlFcq1joLCdJEkjncuAMnqVSaUpehqngxy+tgCAIPlEkX1hYWIDD4YiZ60sQBE6v+RGgS/Cao22gKEqwkCQc0eMEi3YvyrUKUQ2re+sN6KrRQSGN/Z4WiwVzc3N8G98TpPDuHw2hRC7BT+/tj7nPt2Ug5ohXHYxnQp3OfbtYCWAh7ne6KuB8ozCfFAUGn8+HjY0N9PX15fRLzvYMoN+/O9tWU1OTk6rTt55bgEomwd1Hzm3LG6Tw2ykXNvwkDjTt9URTyyVQSMmkKs9Vhw+ff3QS/3BjG3Sq3JqgRvvb+Xw+WK1WjI+PIxQK8TmssaoedrsdE5OT+LczDKRDc3jsA+kTwIfOroNlgTcdzY5YIEQzoBg2rQcvZ39yuG0fTubAziZ8lpOzNLFYLBgcHAQAvi2ZyPbnxq7KlLfLGTyXlpaisbExk0NICIIgIAat/OxvJ/GHcQue+tDxlAymheb6vq67CkF6txovVEiSqJLiC9F4y/fOQC4h8YcPHIv7ulRBEkRc8rexsYHl5eWIWVW1XIo7+mpwUVNiAUgsLNq9qNIp9+R7J9y/JNXBcANqoeSoEImUENA0nVNBnhDQNJ2TuEqxcYEAJgAXSeVyudDc3Jxzhp9NAuh0OnlLirKy3FiGrG8H4PQFMbruwievb4NSJoFUQiLEEpix+mL+jUImwX2Xx56h4UDTNAaXHVhx+rHsCOBgjglgNFQqFe9vF1310Ov1fA7rxsYG1tbW0Nfbi/er7KhO0VMuGpftN4JJQQxFMQyCFCtYNPLzV9YQYljcczS1xQJn89LR0ZGy/YkYCLc0aWpq2mP7YzAY+FZxJq0lzhKqtrYWVVXZtfIQq/L3zLQdLAtIUqhSppLrK5eSMYlOPCEJN19bWloKk8m0p32vkknwtmP1ONJoSOk408Xq6io2NjbQ09OD0Q0PRtdduL2vGlKSxJvTWGi5/BQ+9LNRVOgU+Npdh5K+3h+ioYxacIVXB88uO/H4hBXHm/RQSgl0VGoEzw4WKwEstP1ONce+kHCBAMZBKBTC0NAQdDpd3tIXskUAV1dXsbS0hN7eXkEtSrHwd9e34eevrOJP0zaEaBZK2a7a828urYBJu0t+hla3wbJI2u4FIuf9rmo34/g+IzSK3M+GvLTgQKlajhbz3sqFVCpFRUUFKioqwLIsnE4nLBYLxsbGAABNTU3wBmlcsq8M5drMFKLRasVk+NnpdQQoGm+5qE7QDeySFiPcASqlbVgsFszOzkbYvOQb0bY/3HcyMzMDpVLJt4pTES1wFc79+/fDGGuWQWSwLIslhw8NZZmJfh77YGpVtGzk+v7y7Dp0SilOtkcmksQTkrzlotzMyC4tLcFms6G7uxsSiQQWdxAUzaZElqOhVUpx10CNIAL77T8v4o+TVnzx9q64EYchmgUI4Ecvr4MkCfzX6w/CH6LxuUenccX+UlzSXBrXZqbQiJRQFOIMYLGSwPOCAIr9wbvdbgwNDWHfvn2oqKjA2toagsGgqNsQArFFICzLYnJyUvTEklRwW081XtddDTIsd7Var+AVd09MWMGCFTTvFy72kJIEtAKFImKCYVl88teTkEqIPUPj0XAFKDDSXV87blbNarXi6384iwDF4u6+SlRWlOcsjeSy/WWwuoOCt5UqwVxeXsbm5ib6+vpSbo94ghSu/sIL+MS1LWm1YoWCJEmUlZXxVXCuVRyefmE2m6HVauN+Ti6XCyMjIzmtcP7zH2bwq8ENfO+enpgRZizLYt7mRZOxRLRzKVu5vr4gDX/o3EJXzESSdMCJ4lwuV0R7WywT7jf0Cov/66s34NlZB/Sq+PfpgcZSDDSWYn3bD4LYPZ/lMoABAatnt1Uaz4SaI4bFhmIlroWI84IAionNzU3Mzs6iq6uLl3Xnw49P7O1yFU29Xo/u7u6EN06CILJ2ke2KMyJ/Fi52edeljUk9HXMp9kgGkiDwz7ccEJRE8fpvvIxAIID/vasFtbW77SO1Wo33lFfDuuODmvEISiNhWRbPztpRY1CiOYPIqBqDKqllSzrg5sM4BSxLEHhpwYFDtfGH7KNBEgQYlsVzs/aMCWCAoiElSUjI5OdJeEIMl36xuLiI6c0dLHgVuOtoPcpNRr4CwSlDDx8+nNAWRGzc1V+DEM2gpTz2NuesXvxx0oqr2kzYF6MynSqic32B3RGCp6ds6KnTC05iiYU3HonfSs0kkSQdcOduMBhEV1dXXonG4Vo9vv3mbkGvDY8klJIkPnfzAf6/o02oORGJz7c7dhOuLi4GFFoFMBQKFeX8H3CBAPLgLvydnR0MDAxEfKFcOkauIZYK2OPxYHBwEM3NzfzNO9l2c7nKIkkSoVAIAJLOo4WTv1zsn8tPQa2QJDQ27q6LrPo8PLiOHT+FNx2p5cmp2+3GLY0MSk21PPnjYFDJYFDJAOj2pJHEU7DOWDxYdvgyIoDZAMMwGB0dhVKpRNerNi/LDh/OruzAUCLD/nJhc7QqmQQvfPTSjPeHZVlc/h9/BkkAf/6b1N4vXLSwId2CfM0Op8OBxfk5KBQKyOVyuFyuvBg8NxpL8PfXt8X9fX2ZCifbTSlVbUM0E2FazCE615f/eYjBvM0LtUKCi5pyM0cshpAkHliWxcTEBAiCQEdHR1G29BKBE4hIpVJYLBZsbW2hq6srazYz2UKhEcBitYABzhMCmOmFGgqFMDw8DI1Gg97e3j3vV8wVQI5EdHV1QafTpbTdXLWIhRpBc62MXK1W/SEad337NLRKKX789j7BfyeTkBFZpDabDdPT07jnxGFBQqJEClbO7PiWDiO02sQ3nbF1F9734DB++LaerFT6osFVmcvLyyNahDUGJW7trkJpnAi7bIIgCDQaS9BdK+zcj4erD5Tj6gPn7J9mZmawubkJhULBZ4HHU3rnAzIJmdLiYGLDjWdnbXhdd1VENS9Wri8HjUKKuwdqoUhBzSom0hWSxALDMBgbG4NCoUBLSwufLlUI36XYsFgsmJ+fR29vL7+gzIbNTLZQaC1gt9t9gQAWK7h5v0TVsXwRwExuPizLYnFxEVtbWxgYGEhJNp+NaLZMtpdNc+dEUMokaDKWJPXzGlzZxsiaC3cP1IAgCFzfec7KZWVlBevr6xE321QQrWDl0kgW52eTppFYXAEwLAunl0KNIeVNpwSfz4ehoSE0NTXt8ckkCQImTf6U2Q++Qzh5TwauU+D3+3Hs2DGQJBnT345TeqeziFqwefHUlBVv6K2GWmBW8Y4/BIbFq5Xk1GFUy6CUSaAOE1Fx6u2urq64C5d0YgdZlsX6TiBj1Xs0oiMDEwlJwsEJW3Q6HZqamgAAt/z3KbAs8Kv3DJxXJHBrawsLCwvo7u6OuB/l2oQ6ExRiBbAYPQCBv3ACyEWfHTp0KGGMS74IYLrg2nAEQaC/vz/lCzYXBtTR24tHADnyF65kyyW+dEdX0td88teTCNEM3tBXDfmrWb2chZDf70dvb69oN6xkaSTcQ04qleLyVhOevt+U/E0zxM7ODkZHR/Nm85IrcFUiuVweYfAcrfTe3t7mqywymQykuhRrARmu6awRNIdIM7vKzlSM/n5xZh0Mw+IdFzekdWxmrQJvCpvFC0+9EFu9PbXlwROTVlx3sDxr0YXRQhKv1wuLxYKRkRHQNM0LSdRqNYaGhmAymSLcHgwlMji9oYT3m5+/soZyrRyX7c/+NSYGNjc3sbS0xCe2xEMuTKgzQaERQK/Xe6ECmE+kSgq4mCan0ymoOlZMBDAQCODs2bOorKxEfX19WoQpVxF04duL9flGz/sVwkr87LITw2su3D1Qyz/Mf/i2Hji9FB8JxaWrqNVqfg4uG4iVRmK1WrG4uAipVIpTdjlkSjXuvTSxj2Im4Gxeci2CyDU4BazRaERDQ3ySFd6WBHYro4+cXsDY6jq07hVUmo18xTbeebHPrE5ZuHFtR/kucRQBXJUoW7ONjUYVLm0pQ41hbwUwSDGQkIQgoiwUBEHEFPdwOc1arRYKhQIURfEV2+/e05P0fV0BCp4gjcv2p7dfDMsmnC0WE+vr61hdXUVPT0/KVelsmFBnggstYPFwXhDAVEBRFIaHh1FSUoLe3l5BJxKXBVzo2N7exsjICNrb2zPyIiuECmCulL47/hD+8XfT+OjVLYLalCtOP4I0i/Dnk04pg065u6IOBAK8GXB1tTC7BzEQnkayb98++Hw+PPf0DOybm3jxRUvCNJJ0sbKygo2NjZTb209NWeEPMbj2YG4iFdOF0xvCI0MbuKHDiNmJEdTV1aVs8KxSqXDb8TbcSLGQkyzsdjtWV1cxPj6ecX50OKpEaqd+4dFhkEE33nNdf9aUjQqpBJ3Ve2cyWZbF9V95AQRB4DERUz6iIZPJUFZWhuXlZXR0dEClUsFisWBxcTGicpjsof62Y+n7w46tu/DZ307iUze04UBl/O4Ty7JwB2holZHnh9MXgsUVxP7y5MRjbW0N6+vr6O7uzvg8i1cdDFcXc6/LZnWwEIoBHNxu94UWcDGAU8M2NTWldCPPdUUsGkKGkdfX1zE/P4+enp6MKzHZPN6h1W08O23Duy9r4lf50QQwl2KPyQ03xtddGFzdxlVtyX2+XpvAksTlcmF0dBStra05S1eJB5VKhQ9cu9u+jjejZjQa02qlcBV0r9cbMwM2GeZtXqQQWJI3bPtD2PH68cLps7joUFvaiyopSUL6Kj8uLy9HeXl5RH40Rzw4pXe+Kqnz8/N4cNAGmUyG9+fB1oIgCLSWa1Bfll3BEtclaW5uhvnVWEJudCETIUkqUMkkkJJk0ljF7z6/jCemrPj32w5GGMV/6teT8IVofPnOLr7zEAsrKyvY2trizazFRnR1MPwf7rmVbTKYb1yYAcwzhKwG0lHDhr9/Mm+6bIEkyYQEkJs1c7vdOHLkiCjK3WyKQJ6ZtsHijjTV5rbHzft96GcjKNfK8YlrW1N67yDF4OO/GsM9R+v2WLPEQ1+DAd++pxtlJZmJFKxWK2ZmZtDV1VVw7YB4M2pzc7t2JlwbWUi7j5svVSgUabe3M6mc5BKlUgp9KisOHuxM+Z6RDOEVW+Ac8ZicnEQgEEgo7kkHDMtibN2F1grNHsIQnuv78H0XQZ5G1rNY+KqAeLRMwCW2xFukhQtJYtkxxROSpIomUwl++LbepK+7pKUMk1tulKkjCfnHr2nBqtPPf5ef/PUESAL4zGvb+dcsLy/DarXi8OHDOZmZi9UqDieEFEWBIAhIJJLzigx6vd4LBLBQwbIs5ubmYLfbU1bDFgISObZzc0kajQY9PT2ilcWzOfN416u2EeEzPhwB5P7xhWgsOfwpv3eIYbDk8ON3Y1uCCSBJEDBrMruZc4kX6Sp9c4nwGbX9+/fvGY43mUwwm80x00g4mxez2ZyVeMQQzeBXgxu45XBlTD+6XIKz7kk22+gJUvj56XVce7AcFbr0z6NoBWu4uEej0cBsNoOWa1BTlt6DZtXpx9PTNrAs0FVzjswyDIPx8XFIpdKkub7FDs7S5sCBA4LEStF2TPGEJNm0/tlfrsE/39Kx5+dVeiXf9nf5KQyv7kRUThcXF+FwOCKSTHKJWK3i8DZxrlrFuYDb7eYrycWG84YAxqrScfN+SqUSfX19RXmScfN40fM4Xq8Xg4ODaGhoEH3WLFsVQJZl8Zn/m4BcQuLfbuvkf04QBHw+H3w+H5RKJf777sNpvb9aLsX/vq0H0hx9zyzLYmpqCsFgUNA86azFA5NGDn2aVh3ZQElJCRoaGtDQ0IBQKASr1RqRRmIymVBWVoZAIBDX5kUs/GHcgv/44yxkEgK3HE5t1k5MrK+vY2VlRRChD1IM/BSNHX8oIwIYjmhxj8vlwnMTK/j7P47j+mY53na0BmazOaVKc41Bidd2VUTMCnJiJZ1Oh8bGxryRP5ph8avBdfTVG7KmCubi+jo7OxM6PsQDJyR5dGobNCpxa0857HZ71hJJouEOUPjoL8fw9uN16G8ojfjdqtOP/gYD7uyvAbDbyt/Z2cGhQ4cK5pkXbkIdXh3kiKBQm5l8deISwePx8PZBxYbzhgBGI5sEKZeIVY2z2WyYmJhAZ2dnVmw3siUCIQgCt/VUR1TcODuBqqoqjI6OgmEYmEwmlJeXQ61Wp/xQEho1JhQLNi/kUnKPZxlFURgZGYFWq0Vra2vS/QzRDO57cAgyCYn/S5IZnEuwLIuPPjSGrmod7rloV+QQnkYS3pZsaGjYYwYsJq5qM0EuIXFJSxkWbF5U65WQi2wyvOMP4eXFbTSbSqBWSPZUfxcXF2Gz2QSrJUtL5Hj3pY2i7mM4CIKATqfDFT1t6J0J4a5L6yFjvREzamazGQaDIeGDkyQINJSdI1cURWFwcBAVFRV7kmnEBPfATnR9sGCxtRPAmeXtrBDA7e1tjI+P49ChQxmPZzh9FMDuCknCxyqi5zkzSSSJhyDNYG07wP/78OoOeuv0aK1Q48Mn90EpJTE2NYMvPLcJpVqHE9jCzYezl6OdLsKrgzKZLCWbmUJTAAMXWsAFB25mQ0yClM183ESIJoBLS0tYX19HX18flEpxjVTjbVNMhHtmha8Ao6tQs7Oz8Pl8gh9w2cLvx7YgJUm84+JzLU+/34+hoaGUVKEyCYkPXtmMFhFyWVPFD19cRoBm8Y7jsdu2Ly06cXppG/dcdC69g2t/seyucvXQoUNwuVwYHBwEAL5CVVJSIlrlSCmT4OoDZjh9IfxmeBMHKjW4ql3c1spn/28Kz87accvhSlRoFXjbq58JN0sbDAbR3d1dcA8ZlUyCr/OV8VLeB9LhcGBrawuTk5NQq9U88UhUuQwGgzh79izq6+sFRUOG49t/XsLjExb84K29gqxarv7i82AB/PGDx+O+RkqSeNeljXsywsVAeFazGH6Gsa6hePOcYgpJNAopvvmmbv6/Hxu34KGz6/jwyX04UKmFUkruWpu5vFCodXB4g3D6QmltK9dIxYS6EAngBRFIAYAjaAsLC7BYLOjv7xfVwyrRLF42wW2Xm9WhaRr9/f1ZHeoNz+bNBhIle8hksogqlN1ux+bmJiYnJ0W1zRCK23qqIZOc2z+uldTe3o7S0tIEf7kXN4QlhOQSIYaN6ylMEAT+8IFjiPUs51JM+vr6IJfLYTKZItJIUq1CCYVBJcM1HWZUx/CJiwWaYfHd55fQXqnBxfsSK3U/+poWXDbvwJEGA0oU5+aTuPziYpqDizY7drvdsFqtPEnn5jnDK+l+vx9nz57F/v3701I1//DUCmiGjXm+xIJcSiJIJW/bien7x4FbSOY6qzkXQpIr9hthUMnQWq7hFy8UReFYbxeOvaotKZbzOBzJbGZ8Ph8IgogghflGMWcBE0l66oXXcI8DLopKLpejvb1d9BPj9OnTOHjwYNaqbvEwOTkJvV6PpaUlmM3mnMzqbG5uwuVyoaWlRfT3TjfWLbzNYrPtWlWUl5fDZDLl7DvhTI8PHTp0XpseczYvHo8HnZ2dCRcbnGDBYrFge3ubFywYjcas+cjFwjeeXUClTombDqVW0eKEVNFJEMWOYDAIq9UKi8UCr9eL0tJSaLVaLC0t4cCBA1lt5RcCuNSLw4cPJ6yGuvwUaJZNO0IvFYQLSWw2myhCEm4OmWEYtLe3FyXpE4pgMIjBwUHU1NTwCu5CyCt+y1vegs997nNob29P/uL8IeaJcd4QwFdeeQV6vT5r8yzcqjnXTH9kZAQ2mw0dHR05UxpZLBY4HA60tqZmw5IMYmb6er1e/gHHqVdTmRtkWBZbrgAqdcnJI8uyWF5ehsViwaFDh3JKbHINLu5MJpMJmm0MB8uyeHZiDX+e3sSl5SEoZFK+VSx2nJgY4Ey7U2mFWtwB/HpoA3f216aVg5sPMAyDlZUVzM3NQSaTQaPRwMZqMO4E3na8sSiOI0DRkJCEIIHX2toa1tbWBBkf3/S1F8GwwCP3HcFvRzZxsEqHJlNuFnehUIhfPKUjJGFZFhMTEyBJMuVrtdhAURTOnDmD+vp6VFTsdlLCq4PhPIZbsOaKEL7+9a/Ht7/9bdTU1ORke2ki5slx3rSAu7q6smrWnI84uM3NTVgsFjQ2NuZUZp6NYxU72aOkpAT19fWor6/n5wbn5ubg8Xh4D7VELcn/9/gs/jxrx1fvOpQwlJ5hGExNTYGiKPT09BREyyFbiGXzsuLwYWLDhRPt5ojYKqcvBL1SGvE9EgSBAGTQG8pw0dEGBAMBWCwWjI+P4ydjHsy5JfjGHbvVJ+7vdvwh/OjUKq7pKM/ZgxfYXUAMDQ2lbNptcQXhCdLwBKmiIE4A4HQ6sba2hqNHj0KpVMLj8WBrchWbG1YMnrGhwhzf+ifXsHmCMKhke1rC33puCXIpiXuTZB1zC7Wenh6wAo7lA1c2I0QzYFgWCzYfnL5Qzs5DoUKSWHO2LMvyudQtLS15/96yiVjkD4hvQh3+nMmFzcyFGcACQLYvgFwSQM670OFwoKGhIecVJ7FtYFiW5aP00r0QF2xe/MsfZvAvtx7gY9c4yGQymMor4Jfp0VmmFDQ3eHtvNRQSEpUJrDs4GyGDwYC2tjYQBAGKYXJmM5NL+P1+DA4OorGxMeIm++ysHRZ3EJe3mkC+Ogvp8lO46Wun0GRU4XtviTSzPXmgHCcP7P67UqlEXV0d6urq8KGnngNFU1hbW8PExASfRqLQ6LMy/J8I29vbGBsbS8sSpKNKi46q1G1E8oXNzU0sLi5GzMFpNBpc3deGq/va9lj/GAwG3von0zljhmXxuq+/hIv3leFvrk4+TuIJULj9my+jrESOn72zP+J33bU6GEoS3wc5+5Pu7m7QLPCNZxZh1shxe1/8yszJMJHRuy5pyMosYjSCFLNH3Z6KkAQAxsbGoFKp0NzcHJMcni+EkKIoXrAUfl+KRjITaqE2M+nA6/UW7UjQeUMAsw2JRJKTPGCapnnvwt7eXqytreU8hk4ssptuy3d6y4NFmwdXtZv5v5m3euEN0nB4Q3sIIAD81xNzeHnRiS/e3oWKsMF4blW9sLAAmUzGtyQbjSX44InmuPvAEaKGhga+PThj8eB3I5u4o78mIpapUDG+4YJRLU+6r5ywJdZs2Ot7qxCi2QhjZo1CgkajCu9MUo0Jx9P3X8z/e3gaiW1uDkc0Csj8Uvj9ZNbnOTmD5+7u7oJpS7Msi5+cXsOVrSbRvAQBYHV1FRsbG+jp6Ym7iIwWXTmdTl48oVQq+SpUOt8LSRBwByj8bnQLpSUyvPFIbcLoM7VCikv2leHGrgoEKDrC0ul4AnFPeJJJV1fX7kMegEJKoq1CeGVGbMuhWHh0bAvffX4Z/3prR8LIu0RCklAoBJ1Oh9raWv7+OLnpxq+HN/DWi+rwlafnQRIkPnm9uCM8uQZH/urq6hKSv2jkOq+YYZiciRLFRnHudQxke8UjlUqzXgH0+Xz8Cc/NMmZbkRsLYlQA45E/mmGTrrK/+OQc/BSNK9pMkL76d1e2mXBlmynu37zpSC2ajCUo154b+A5fVbe0tMDn88FisWB0dDRh6gVXIYomRHqlFEqZJGl+ZyGAZlg8Pm6BUi5JSNS4CLt4HmlSkkT0c5EgCHw/qvKXCuKlkXDfi9FoRHl5uegtyVQMnt0BCr8e2sTtfdVZrwqtOP340pPzOLO8jX+5dW/qQzpYWFiA0+lMKQOWJEmUlZXxLXGPxwOr1RrxvZjNZqg1GgCEoM/l8Q8ex9DqDp6asiIQYpJeO595bTtG11z42p8WcPdAbdLFC8uymJycBMuyexTcydrF+UBjWQkUUnJPtFsicJZMpaWlGBoagtFohFwuj0gkmdqWYscXwmd/O4XNnUBE2ksxgiN/tbW1KZG/WEjFZiZVMljs1dbzRgRC03RWK3RcBSlbg54OhwNjY2Po6OiIsBfJpiI3Hnw+H8bHx9Hbm95DPh758wZp/L/HZtBTp8eNCdSaO/4QdnwUaksTV2gyacdyrS+LxRIxNxgKhbCwsIBDhw4VTIUoXWy5AlDLJVArYq/zHjszg7nVLbztNf0FE2EX/b0YDAaUlplgKC2FUp7eepVlWT4a69ChQ4II0beeW8S3/ryE/3h9Jy5qSs3uJx38ec6OjiptxmrUcD/Djo4O0dpdoVAINpsNVqsVPx60Q65Q4r7LGmE0GkW3pLK4A3hkaANvHKiFMgFhLMg5uIALoPyAQgdIxavmMgyDoaEhlJWVRajVw4UkOzs7+N0KiRu6qtDXUl20YrVw8peqT2WqCJ8ZDBeTCFUWsyyLyy67DGfPns3qfoqA81sEkm1kcwZwZWWFr0xEk458iE8y2WYisYdSRkImJVGXhNjplLI9bV6aYUEQ4IUICzYv/v7XE3j/FU0YaEz9AR3d+rLZbJiZmYHb7YbJZMLOzg5kMllOS/tCqqOpIF71hJsxfXbaCqOpImXy5w3SGFt3ob/BIMJeRiJWS/IrT83B6x3HnV16mM3mpEbH4eBsMiiKSikX9Y7+GjSZ1OhvSM1IPtZ8lxAcbxYuRImHbOb6ymQyVFZWorKyEpeTW9h07GB7exvz8/O8R6TZbBalhW/WKPCO44mrdwzDYGRkBBqNBk1NTfknfx4LJFO/A2mbBAgSICSg646Bab4SkGS2uKJpGk+9eAb/O0nj0zdHigHDhSTbviCesE9DyQZw5swZSCQSvmorpmF7NpFL8gckrw5SFMW/5nwUAJ43BDAXIpBAICDqezIMw8dsDQwMxFxJ54MAptsCTib2IAkCTUYVfvzyKjqqtZC/OldGMyx+cWYNx5vL4lb97vvxEAgCfBqCWi6BTEImHQwXCovFAo1Gg76+Prjd7phzg0Ifbu4ABU2cqls8PDtjwz/8bhpfvqML+8vjWw0FaQYb24GE80OJwNm8SKVS/N1tA2BB4E/TNhyu1QnOKP70/03ihTkH/vftvUnJfCbgWpKvHSARCDHYVy6HxWKJSCPh4rZiXf8cSSgpKUnZJkOjkOJEgpEDDi4/he8+v4yr2k2oK1Xhui+/gJ46Pb50R5fwAxUBQnN9JzfdaDKV8NdeOjjRboKUPJcHzVkyjY2NIRQK8aQjXW+7RDi14MCqw4tGbMFoNBaGd6PXBtlLXwdYBqy2FiAIgA5BsvA0CPcm6O437ZLCNEDTNM6ePQuVrgwSmQs2TzDutb+5E0SAlUD5/9k76/CozrSN32Nxl5m4Q4AQwaW0S4t00QQKFNilpUrlq/tu26XdrW3dtu5CtxGcCqWlRoEiSYiHELeR6ExGz3m/P7LnNDJJxiU5v+va69qGZOadOTPn3Od5n+e+Q6KQNW0yNBoNe2OrVqsRFBSE8PBwqxJJ7Imjxd9QLOkd1Ol0DjUZtzXjRgDaG6FQiL6+Pps9nl6vR1FREYKDg0c18BQIBA4fAjE3C9icYQ+Nvv+1iAZUulQ6A45UytHeq8Vti40PZsQGew+y3Qj398R727JMXuNI6PV6nDt3DiEhIYiPj7e4b5ChrUeDz04240+TQs2qkAX5iCDk88a0FjlaJce55h5csyAOIb7mVRaY1xoaGor4+P4KS2u3Bo/sr8CM2EC8tHG6SY9z95Ik/BTXgRgTkzqsZUZsEPv/mYqPTqdjjbmNRQYyWbcDLW3sgVDAg4APiAQ8+HkKIODzBk2WOgJTc32buzQ4WNKOhUkhFm9r559txWtHa/Hh1VlstvBASyaDwQCFQoGmpib09PSY7W03Fv84UAm1RoNPNqcg1o4ZxubAr/8VoHUgfgMy5wUikIBY8GXloDtrQUKSzX5cRhBFRUUhKioKC8f4ek4S++LRlZMh/N+51cvLC9HR0YiOjh6U7V1dXW31gI+tcbb4M4YpvYM9PT1u3So0bnoAaZq267AE0/+Smppq9WMplUoUFxcjOTl5zAZXpVKJmpoaZGZmjvp7tubYsWNYuHDk/E4GW5k7t/VoEOQtGrXnx9Yw6TFDrU9GYqS+wYF+g3qKxtelUixKCUGwz+gCTaOncKq+C/OTgk3uZVRqDaiV95nd5D2SzQvQP5k4KzYQ4W4w2WwMJhNXJpOhq6sL3t7eUCqVSEpKQlRU1NgP4MYwub7x8fFjfoYJIaiWqhAX4j3i9+xccw+kvdoRM5hP1Hbi7/vKkX/jnDErxsbSe5gbKEsumnq9Hj+eOINgcSRmTe4X9TQhg/wpHQ4hEP2wE8QnHOAPF7g8pRRUZCboqdlmPaxer2cHAm0tiJhEErlcDrlcDoqi2HOZPaq2Y8GIv+joaJOz1Z0NUxV899138d5776GsrMzZSxoLrgfQGmy1FSuTyVBdXY309HSTPMicsQVsKrZM9jAlkcOWMJO+06ZNY723xsLUnOLRBlwGcl6mwvHaTkQFeSEpzLSEGT9PodnibzSbFwD48zTx8D9yIwaa5iqVShQVFSEoKIjNMma2it3Vq2sk1Go1ioqKTM715fF4mDyGLcpP5xUwUGREATgvMRjf3TH2jSHzfEOr6XK5HBUVFdBqtexWcWBg4JjnDq1Wi8LCQmSmJrGm+G/8VAc9ReP2S0e2c7I/BKAMAM+4oCZ8AXiUea1DjPgby/vOUng8Hnx9feHr64v4+Hh2kISp2jLnspCQELsPklAUxca7uYv4A/qrg7t378bevXtx4sQJZy/HYsaNAHRED6A1U8aEENTV1UEul2P2bNOnLl1VANo62cMejFQdaG9vR11d3SAvuDpFH45WyfGXuTGDPO9Ggs/nIzgkFIHBIRDyeejt7YVUKjWrb3BKhB9CfD1GNaO2Fsb3jrF5sfWgiak4wkCbEfUZGRnszZVGo4FMJkNFRQV0Op1ZosMSmrvUiAjwGvQeK1Q6FDZ2Y/HkMJu990qlkhX1pt7AmMKNi+JBj74rZDHe3t6sMThFUVAoFGhpaUF5eTn8/f3ZreKhokOj0aCwsHBYaktymA9qFea35egpGmcaujE3Icj6zwCPDxKcCKhkgPfwbXWeXgU6xHQHB6aim5iY6LD0J2OJJHK5nE0ksdcgCdPfGBUV5VbiDwD27duHN998EwcPHjTbTN6VGDcC0N5YI8QoikJpaSmEQiFmzZplVgOuKwpAWyR72JtvyqQob+vFTRcnsNtdjAjv7OzErFmz2J4klc6AoqZuKFR6sy5+b/xUC4oAd1yahICAAAQEBJjVNyjk80eNobOWlpYWNDc3s75352Uq1l7DlobDY2GgaSx9+TcEeImw7+a5Vj2W1kDhvV8bsGxqOCaJ/6hmMX6GQw2eB6aRGAwGdHR0oLm5GeXl5Wwaia2sTNp7tNj07mlkRgfgP1sy2J+faehCYVMP5iQEGTUxNxdG6Kanp7MRVK8drYWHkI8bF1nnfWfKzY8tEAgEEIvFEIvFg0RHQ0MDW9FlBFBxcTGmTJkyrHq93MLK9RenmrHr92Y8mT0VWbHWi2cqcTGEp98D8fAdPPGr7gTxDAAdPtWkx9HpdDh79iySk5MRFjb2AJI9GFi1TU5OhlarZb9bthwkcWfx9/XXX+Oll17CoUOHjO6ouBOcADQRS4UY03sVGRlpUTO6rWPZrIVpgnXVqh9DRIAnqqUqeAr/aOItLy8Hn89HVlbWoJPXtR8XggDYde0ssyo0GdEBUOuHHxtvb+9hOcVM1JYpOcXWwti89PT0QOoVC5UB8PAA/D2F8BTy4SVyrGgX8vng83i4ZJL1VieEABoDjfYeLSsAhwrdEdchFA4SHUwayYULF+Dp6cluFVvaFC/298Cq6WJsmDG473Dx5DDMiQ+2ifgbKcmEz+ufjHdHhooOJgatrKwM3d3dkEgkbKuJLb4za9Ij4O8lRFqUbSo3JDQFVNp6CCr2A8QAED4AGsQ7BFTmXwHR2P2OzBZ3SkqKSdv5jsLT09PmgyTuLP6OHDmCp59+GgcPHjQrQ9xVGTdDIABsbtMyEIPBgNOnT2PevHkm/013dze7TWPNh8XUgQxbcuzYMSxYsIAVebbq9yOEQKWjzLZJsQa9Xo/i4mKEhYUhLi5u2Np3F7YCANZl2fdkxPQNMsMKfn5+EIvFNpuQZJ6jvLwcAoEAXuGxuPaTIlwyKRQ7V1k/vORqMBXd7u5upKenW1XFY9JImKZ4ZtvL39/frjc6FE2w9OXfcGlqKB5d2X+M9BSNgsJWLEoORfSASWsm1zcrK8tljLvtBVPlTEtLY6tQXV1d8PX1ZYW6yxkd61TgdZwHT68G8QmBLiDRpDWOtMXt6jBJMeYMkriz+Pvpp5/w8MMP4+DBg3bpzbQz3BCINZhbAWxpaWFD2N2x+ZzH47H9fYz4oyiK9UCylD1FbThV34V7lyUj2McDhBDoKWK3HM6+vj4UFxcjKSkJYrHxLSN7Cz8GPp/P3jETQizqGxwNg8HApgUwNi//WJWKjGj37VEZCSYCjKIoZGRkmFwZ6tNR8BTyh1V6fXx8EB8fzzbFl9e34ao3z2BWOA+bs0IxOTYCISEhNq/aCvg80ITgh0oFHl3Z/zMdRaOhQ41S7x5WADY1NaG9vR0zZ860uTl5n44a037IkXR2dqKysnJQlTM8PByEENajs7CwEDwej90qdgmjYw9fkIhMEACP7K/AeWkx3r8qa9T4O2aQx9gWt6tj7iCJO4u/X3/9FQ899JC7ir8RGVcCkBEr9npsU2CSB/r6+jBnzhy3DYlmBC+Px2OHPawVfwAQG+yFXb+roKf6j9NL31/ABXkf/r1+mskZu8wF64UjNahsU+LNrRlG19XV1YXy8nKkpaUhIMC1sjF5PJ5FfYMjodFoUFxcPMwO5E+TXGc7yVYMNHhOTU01+TNJE4L//FgLL5EA/7c4ccTfE4lEUFDeIDwBeL6B8A4IYbdefXx8Rk0j0VM03vipDrPiAnFRsmnv/Y93XzTov309hLj90kS2H6+2thbd3d1m5fqayrGaDvxc04FrF8Yi3M/5NkCMcXFWVtawGyEejwd/f3/4+/sjKSlpUH9aX18fKlXeSI8Px4zkSKf3Ji9IDEa9og9eo9zYMjenthjkKWvtxScnmvDg5SkmG7rbktEGSZgsY5lM5nbTvgBw4sQJ3Hfffdi/f/+4s5VyT3XiojCGrAEBAcjKynL+HakVMGbQAyuBtng9Ph5CJIT6QK3vr6YuTApGS7dm1BPlQEpbenGgpB1b50SjvE0JeoQw7tbWVjQ2NmLGjBlOMzrtVuvxyYkmXDkrakyPPWv6BhmblylTpgzKkR4vnJep0NKlxiWTwtjtfLFYjNjYWLMeh8/jYUZcIOJMSC9ZPDkUP9y1EB4C/qA2CJVKNSiNhBHqTBqJkM+DgSaQ9urMf6ED8BQK2JtJvV5vVpXTHFLEvjgvVyHYRwSNvr866qzzFlMNnzFjhklb3B4eHggKlyA6Ohp6A4XvvipDXVELdPIG+Pr6stV2Z2yXr5wuwcrpI1eKVCoViouLR705rVP0IchbZFLakUprAE0I7FT/MIuhPZ19fX0oLCwEn89HY2Mjent7XTqRZCBnzpzBnXfeib1795p9vnEHxlUPoE6ns1sFEBi9F0+lUqGoqAhJSUk2N+4c2o/nCM6cOYP4+Hib22XoKRoEsDiKqrNPh33F7dg4M8rothUhhK2YpKenO7UC29ylwee/NyEnM2LQxKo5MI3XUqnUaN8gU5lKT0+Hr69pXoIGmkbumf7oPSbNwZV55YcL0Bpo3LooGiXnzplkeuwIdDodawze19dn0wEfppdTJBJh0qRJdv/uUzTBsld+g4DPw+HbF9j1uYzR2tqK5uZmZGZmmtzbt+OzIjR0qpF342z4egih0hkgEvAh4vNYoS6XywGAFYOmVtTH4oJcBUmAJ3w9zD+/KJVKnDt3DtOnTx/RQoSiCXZ8XgQPIR//2Zxh9HfcAWbbNzIyElFRUYMGSTo7O10ukWQgRUVF2LFjB/Lz8zFp0iRnL8daxn8PoD23gEdDoVCgoqIC6enpdtlqZCaBbb39Ywym3y8qKgo1NTXsdqRYLB4xc9Uc/nmoCgTAP9dMsejvg308cPV843diA3NuXaECGx3khfuWme4BBvRvUz7/XQ0yYwKwfKqY3T4JDQ1l+waZnGKmL5Px+DMVA0VQr1DDS9jtFgJwx8Xx6OpRorioCKmpqS5T5fTw8GBjupg0EsYY3M/Pj7WYMXdYwdRcX1si4PMQ5C3C6nTHC+vGxkbIZDLMmDHDrHPclbOj8PYvDfD5X+vIQDHm5+c3KDZwYEU9ODgYYWFhCA4Otuic2qej8N9TLYgO9sJV88yrCjHV+oEWPsYQ8Hm44aJ4h9o12Zqh4g/AoPMZ8McgCdP6EhISgrCwMLv5dJpKaWkpduzYgS+//HI8iL8RGVcVQL1eb1fLlN9++w3z5s1j7+4JIWhoaEBbWxuysrLsFgr9+++/IzMz0+5bGcYmfZntSKlUCrVajZCQEIjFYou/oAdL2qGnaORk2rYPRKfTsVuDLhEQbyE0IVj1+gkI+Tzsv8X4xDlT5ezs7ERoaCgUCoXZfYNaAwUhf/gwhCtizPfOlRko1BUKxSBfu7EGwkzN9R0v1NXVoaury25b3EOhaRpdXV2QyWRsBSo4NAzi8DB4m1GBqmhTIirI02RrH4omOH2hHQbpBWRmZpp1w+aOMAkfERERJvfNMTnScrmcHSQZyRzcnlRUVGD79u34/PPPMX26afnoboDREz0nAM3g999/R1ZWFkQiEVttIoQgLS3NrievM2fOYOrUqXYNnTYl2YOiKHR0dEAqlaKnpweBgYHspJcjqpMjoVKpcO7cOSQnJzvMPd+e9Gj08BDwjea10jSNiooK8Hg8TJkyhT1OQ3OKg4ODIRaL7eo3aGsuyFU4XC7DDYvi2QQXxqcvMzNz1C0iPUXjtaO1mB0fhItTXGvwhfG1k8lk0Gq1KFd5IzAgAOtmD67ujZbr29WnR0lLDxa52GuzFEIIampqoFar7X7+HInWbjVu+rwIkT48BAr1uGKSB7sdaWv7n2OVLfj8WDVuuCwNmfHOMXl2FJaIv6EMHCRRKBSDHBRssRM1EtXV1di2bRs++eQTZGZm2uU5nMTE2AK2J8xkLE3TKCoqglgsRnx8vMOe116YGusmEAhYqxJCCHsnff78efj4+EAsFjvcn6uzsxMVFRWj9tO4GyNVFYbavAw8TkNzio1tR4aFhZnVE9mrMaBHo0d0kP1uPIA/Ivue+64GJS292DgzCiG+HmhubkZraytmzpw55mdKwOeBogkUKuuGL+yBl5cXYmJiEBMTA4qicPhgKapk7Yg0tLFpJD4+PigpKRkx1/e+3WWobFMif8dsl5jWtQZmuIWiKEyfPt2JW308CPgCRIcHYGFSCGYkB7GTq0qlctQbXJ2BBkWISc4FXV1doBT1uHbxNEyLcR+fP0tgxJ9EIrFqYnakRJKamhr09fVZvY1vjLq6Omzbtg0ffPDBeBN/IzKuKoAGg8GuQon5YNfU1CA1NdVhcT0lJSWIi4uzS3+hLZI9mOlIqVQKuVzOxjxZ42k38LH7dBR8jRhHt7S0oKmpCRkZGS7XQDwUWa8W35RLsWlmtEWeh4zNS1xcnFlDRgO3I+VyuVl+gy8eqYFaT+GB5ZPstlV84FwbSlt6cftlSaBogqZODVIlvqitrUVPT4/VBs9D6erTY91bJ3HXkmSszbDtsJapMHGDPPRvb7e0tKC1tRX+/v6IjIw0emzae7Q409iNFWmWxZ+5CoQQlJeXQygU2mS4pb6jDzFB3jb/fNI0zSbFdHR0DEuK2fr+adCE4IvrZo/6OAM9DV39HGUtA8VfdHS03Z7HHoMkjY2N2LRpE95++22zwh7ciPFfAbQ3Wq0W1dXVmDlzpkN7OBhLFltiq2QPoP9ujWm6TkpKMuppZ+kQyWe/N6G+Q427Lktmp36Z7SOlUolZs2bZdfv5pe9rcLy2C59fO5PdlrSEynYl6hRq9GgMCPMzr5eTmRo0xeZFR9HIeeMkrpgZiesWxg/yG0xOTjbLb/Cv82LQodKbdXFlqsimEhPkjSqpCl7/sx9JlfiisrISNE3bpS9MKOCBoF8IOouBnyMej4fu7m62t3hgQ/zANBJJgKdDxF9Xnx7v/9Zgl7xoxr/R19cXSUlJVou/5i4NPjnRhIuTQ/CnycZvxgkhqGhXIjnc1yznAT6fj+DgYPb7xiTFMMdmQaQHeB7eo37eGU/DGTNm2K0/3FVwlPgDbD9I0tLSgs2bN+O1114br+JvRMZVBZCiKBgMBps/LiEE58+fR0tLC6ZOnTpiooS9qKysRGhoqM0qjrYUf2Nh7RBJQ4cax+s6sHFGFGtKXVZWBg8PD0yePNnu20eb3zsNiibIvWH0O/2xoGgCrYE2O3Gho6MDVVVVmD59ukkDEDQhWPHacYT7eeLOy5IwK27k99nWfYPHahT4uaYD//enRKMV27Fgpl+ZGwlnT3HbG8bCJzMzc1h/r16vh0KhgEwmg1KpRFBQEOudZs8bnpZuDT450YgrZkQhJdx2N7kURQ1LqbEWmhCcru/C1Ej/EaMlm7vUeP9YAy5OCcXiEUTiUHo1BnxyohHXLIwzusXLpF7IZDL09vay2/ihoaHssZHJZPi99DyWLJhptvgz9ybK2ThS/I2FuYMkbW1t2LhxI5577jlceumlTlixwxj/QyD2EIAGgwHnzp1jp/cYry9Hcv78+f4qgA28z0zt97MH1g6RMJO+EolkXJpyDoUxs87MzDT7IvLa0Qvo7DPggeUpJm05M9sqzHSkJX2D55p78E2ZFHdclsSmWJgKY/A8UaZfzcn1HTq56u3tPWoaiavhzMlmmhCUtyqRGOZj8s3XdxUyvHa0Fg9ePgnzE0evuBNCBm0Vi0QieHt7Y2+JAme6PPGvtVMxWWL65LpGT+HlHy4gIzoAK9Kc73U5Fq4k/oZibJDk7NmzmDVrFrKysqBQKLB+/Xo89dRTWL58ubOXa284AWgufX19KCoqQnx8POuL5+vra3Oj57Gora2Fl5eX1RE6zhR/xtbCXNQUCsWYQyTMpG9KSorDei+dBSGEtcew1My6T0ehs0/PZsmO9XynG7oxNcIPvp5Cq/oGLUGj0aCoqAiJiYlmVdd1FG2xobgzYXJ9MzMzIRQK2SEYU2D6bZnKLTA8jcQRmLpmvV6PwsJCxMTEmH3+au3WIMBLaFE12Rr0/8tiTgj1GbX9wUDTEA6plDc1NaGurg5qeODXJi02z4xAhDjc5B0PmhC8cKQGl6SEYm6Ca/hdjgQj/sRisVvctGm1WnzwwQfYv38/GhoawOfzsW3bNtx///3jvj8TE0EA0jQNvd42vT0dHR1sjiwT0l1fXw+BQODwD7stnpcQwopjV7MFIYRA2tkDVZfC6BCJqdugMqUWfTrKLcyNjdGrMcDXg4+KigoAYG1efqnpQFSgF5JtuCU3kPYeLd78uQ7zE4Nx+bThAozpG5TJZBblFI+GUqlkY+yY75kpqPUUXviuBpPEvtg0y7UqDyPBCHsmpUYgEKBO0YfPf2/CVfNiEWNCRN1Q7JlGMhJdaj3e+LEOy6aGYXb8yCKFsbVJSEiARuiPfcVtuHFRvEkVaQNN4+lvzsNbJMA9S5NtuXybUFDYgv+easGrV6ZD/L+Yx7a2NjQ2NrJWYQaDgd0q7unpwe8KIYICArB1YbJNEorUegr/+qoKG2dEIis2yOrHMwdmSz88PNwtxN9Aurq6sH79eqxYsQJdXV04evQo4uLisGrVKqxatcrlKpk2ghsCMZXGxkY0Nzdj1qxZg+4M7G3HMhLWPK8j+/0spbVHiycP12PFNDFWzZ0LjUbDNlyr1WrWa9HX1xcypRZhvh5GX8eDe8phoAg+vMr5KSDmknemBe8dq8fN6SKkx4WyCRA0IfipWgEvER/3LDUvVcRUxP4e+OvcmBGrhaPlFAcHB1uc69nV1cVa+Jhr8Owl7PdJTI+2/WS8PSCEoLq6eliur5eID5GAD08LJsOBsdNImOnIkWx0Wrs1iAjwNOv74iXkQyjgwX8UE2SNRoPCwkLW1ua7cik6VDpoDbRJAlDI5yMnM4IVV0B/dSznzd+REu6DFzY416A3LtgHIgGf7T1kouxmzJjBijuhUAixWAyxWAxCCP7zwSnomxWY4tXNWmqFhYUNMwdv6lRjb3EbblgUP2aFW6vvr1Y6UgC6s/jr6enBxo0bcc8992Djxo3sz6uqqnDw4EFs374dt9xyC9atW+fEVToOrgI45O8rKiqg1+sxffr0YX1pra2tUKvVSEpKsnapZmHp87qD+AP6t/Ke/qYaV8+PZat3zOCNUqmEWCzu9+eSK/F9mxDLp0VgRVbcsNdTLVWiW23A7PggJ7yKwUh7tehQ6TElwjRhU9rUgQfyz+HlnGQkxw8+qXap9azgcSWs6RuUSqWora0d0+B5PODoXF+g//ujVCohlUoHpZG06b1QIddh27wYNHaqsf2jQiydEoa/r5hss+fu6+tDcXHxoKouIQQUIcO2TM1l7RsnIfb3wLt/zbJ+oTaiubmZTYMarZe5T9d/E+/jIRhmDs4M+QUGBuLLMy34tlyOJ7OnICLAtb4b7iz+lEolNm7ciB07dmDr1q3OXo6jGf9bwIQQ6HSWGcHqdDoUFRUhNDQUiYmJRk/SUqkU3d3dDs8GtOR53UX8GYOiKJSWlsLb2xspKSns2rV6Aw6cqUOspwaUun/6TiwWOz2JBOjfvqVogiCf/qrIc9+dh1pH429/HttDj9kGnTx5MkJC3NModmj8mVAoHLFvsKmpCW1tbcjMzHSoabgzoCgK586dQ2BgIBITE522DkZwvHy0AWq9AbddFIGwsHC89psU2+bFICnMNu0FjGVRWlqaXXxLXQ0mxzgzM9PicxAzHCeTydDd3Q0vH194BYQgKVqMU41KTI/yR6C3878nTACCO4q/vr4+bNq0CVdddRW2b9/u7OU4A04AjkRvby87YDBaEzpjyzBlyhRrlmk2zFh7amqqSb/vSsMe5qLValFcXIzIyMhRTzLM9J1UKkVHRwe8vb2dkkTCsPGdU6AJQf6NcwD0V+161AbEhYze12WuzYuzKGvtxY/VCtywKM6kKs7QvkHG046xNTFWYR+KOcMRrog9p1+/PN2Cc83duHZhHBJCfUz+jtOEwGCg0NX5R29aQEAAa5UxtHLb2q1BSUsPlkwJH/NY9PT0oLS01CUym4/XdqJPZ8BlqfZzbGhoaIBCoUBGRobNbkAH3kidb5Zhb40B8xOCcMXcRKfmB7uz+FOr1diyZQs2bNiAG2+80dnLcRZcD6AxpFIpzp8/j4yMjDFPWkKh0Ck9gOYYQbvysMdYMJWwkeKwBsLj8RAUFISgoKBBSSRnz55l+2vEYrHDthdvW5wIjeGPYxTkLULQkLt2pdaAj4434tr/+YsVHK/CL1Xt+NfGOfDxdq2tnqH8VtsBaa/W5N831jdYXFwMg8GAiIgIdHV1jdo3qDPQ+PNrx5ES7ou3/+J+sUyj5fragrd/qYfOQIPHA9ZmRJrc9sDn8eAhGtyb1t3dDblcjrq6umET39+WS1ErV+Oi5NBRbVSYfs7MzMxhPW3O4GiVHDQhdhOAzDBPZmamTc+zA43bk5KSkDipG0JdL6qrq6HRaNieW0dmfDPiLywszO3En1arxbZt25CdnY0bbrjB2ctxOSasACSEoLa2FgqFArNnzzbJT8uVh0DcecsX+MMU15JK2NAkku9KW1Dd0I1JMuuTSIxR1tqLKqkS2RkR7ONdMml0wQr0VyW+KpUiPcofscJeHDsvR1BoOLy9XD8l4NoFcaAJLIrc4vP5kEqliIqKQnx8PGv/U1VVNWLfoEjAA58HTDHDQ80YKq0BG945hSfWTsHMuCCrHstU1Go1ioqKRryRoQnBU99UIyLAE9cttMwU+dD/zYNaT6G0uRfTIi3PwB54I5WSkjIsKWZeSAguiQ+Dt2hkscF8d10p7uzuJcls5J6tuXDhApRKJdLT0+0qwng8HiZHBgEIAuJjhw35+Pr6sgbU9vKDHCj+3M17VafTYfv27Vi2bBluueUWt7smOoJxJQBNPcBM4oCHhwdmzZpl8pdYIBDYJWnElOcdTQC6u/hrampCa2srZs6caZMT2YkGJQABNi+axVafmBBxZisyKCjIpPfpmo/PwlPIx5tb/6hC7T/XBo2extqMCON19RG4ZFIoogM9QXU0Qa0H/r11vt3v4s80dOH3+i7cuCje6rg/gQV/rtfrUVRUhMjISNZegYlxGrjd1dDQMKxv8Ls7Fpr8PCqtAb9d6MDi1LBBW9R9Ogp9Ogo/nVc4RAAyPXDTpk1DYGCg0d/h83jg83iwRp94CPjwEPCxMNm2PaNDK7f9bS8tOF5XZdS4XSqVoq6uzmbfXVthSd72WBBCcOHCBajVakyfPt3hOyzMIE9YWBg75COXy1FUVATA9n6Q7iz+9Ho9rrvuOixcuBB33nmn210THcW46gEE+lX/aK+JsSeIjo42+0PNDIrMmTPH2mWahUajQWlpKWbNmjXs39xZ/DHWGBqNBmlpaTbro9FRNECGXwSGNlszQyQ+/oE4Wd+DiyeFDOtv2/r+aQDA59f+8d7rKRp6igzaEquWqhDu58EOgRiDSZUJCgpibV7szer/nICOonHg5nl2uSiOBmPwnJSUZFJ6jrG+QbFYbJLf4G8XOvBVqRTXLIhDYtjgLUgDTbOiy550d3ejrKzMJXrgbM3QNBIvLy94eHigt7cXM2fOhFRlQLVUhT9NCnWrc5AxutR67PisCFfPj8XK6f3b94wrgU6nw7Rp01zuNQ71g7TGngnoP97FxcUIDQ11O/FnMBhw4403Ytq0aXjkkUdc7lg5ifE/BAKMLgC7urpQWlqKadOmsSHf5kBRFH7//XfMnz/f2mWaxUjC052HPZgqrK+vL5KTkx2+9oFDJMdrZDjeDmydHYV5qTFmD5HoKRqb3j0NDyEP/73OeGawVqtFUVERYmNjrU50MQeV1oBujQFRgY7dmmMqYVOnTjXL4JmBqT5JpVKT/Ab1FI32Hi2ig7yc8j0YLdfXUrrUegR6CV3ue81UwlpbW+Hh0e/Jua+eDwPfAzvXTIOni9kVmUufjsI1H5/FX+bGYG1GBAghqKqqAk3TrDm7Ndz4WRFEAh5e35wx4u8QQqCnyKCbNh1F41RdF+YnBY96MzPUnsnHx8es6EB3Fn8UReHWW29FbGws/vWvf7ncd8eJTOwhkObmZjQ0NGDmzJkWn6D5fD5omrbxysbG2BawOw97MGIoJiYGUVFRTlnDwN6nhKRkzGrpgIeux6IhEpGAjzsuTRxx4teZNi++no6P0urs7ERlZSUyMjIsnlwUiUSIiIhARETEoAvaSH2DIgHfpCSN+o4+hPh4wN/Ldu8Jk+vLbIMqVDoE+4isqjg2d6nx5k/1WDolDH+a7FrRhw0NDejt7cWCBQsgEAig0+kQJpGivlWGM6dOOiSNxBwIIahV9CEh1MekY+LjIcB/r5/N/m1lZSUA2ET8Meip0WsrT35djaYuNV7aOB2ewn5BfaK2E1+eboGflxAZoxig8/n8QW0WTHRgcXExCCFsG4yxyro7iz+apnHXXXdBIpHgn//8Jyf+TGDcVQD1ev0gkcZ8gTUaDaZPn251BM+xY8ewcKHpvUm2gBCC3377jX1eiqLccssX6LfcKSkpQWpqqst43jV2quHvKWS3b5kkEqlUanX0WWdnJyoqKpCeng5K4MnGfjlalNkanYGGxkAhYEgahL0Nns3xGxyKnqLx+MEq+HgK8NDltvHyHJrr29mnw3OHa5ARHYArZ1seKaWnaOwpasVlqeEI9XVMb92vNR0wUPSIgpOp/KlUqhF74GiaRkdHB+RyOTo7O9lBBVPsmTR6Cld/dBZ3LUnG/ETb5eDWyFR4/1gDVqSJsShl7GEtBkIIysvLIRQKHWbgDQDFzT147YcLEAj4eH1zOitaNXoKle1KpEX5W2yordPpWDszlUqFoKAgtrLO4/FQXFyMkJAQxMXF2fIl2R2apnHfffdBJBLhpZdecokbDxdj4lUA9Xo9iouLERgYiMzMTLcTSwzMut253w8A5HI5a7kzVmWI2da2N4QQ3F9QBpGQh4+vngkA8PLyQmxsLGJjY4dFn4WEhEAsFps0RNLW1oaGhgbMmDEDXl5eKG7uQVOnBi3dGkwSu3eP2LOHz0NH0di5KpV9HxobGyGVSjFz5ky7eTEOtMlITk4eNrU6Wt+gSMDH5tnREAdYL6iYXN+enp5BCRBB3iJcnBKCWVam0YgEfGyc6dhM0scP9Ve6jAlApl/XYDAgPT19xM8+n88fNqggk8lw9uxZ8Pl8Vqwbs4qhaIJejQHfVchsKgDjQ72xaroEmTGmG1MTQlBWVgZPT0+Ht6h4i/iIC/XBijQx7viyBPcsTUZCqA+8RAJkxhgfLDIVDw8PREZGIjIyclBf5/nz56HVahEcHGwX2yJ7QtM0/v73v4MQwok/Mxm3FUCVSsU2oEdERNjs8Z1RAWSed968eW4r/hobG9He3o6MjIwx+1BKWnrwzq8N+NvlkyAJMN8i5UxDFzr79FgyxTQPsJ+qFZAEeCJ1DMuRkYZIhiaREEJQX1+Pjo4OZGRksFVnmhCo9RR8RAK3O35DqZYqoVDpMT8xmK0MmWrwbC/M7RscC4om+Oh4IxYlh2DygM8G0xNmMBgwderUcXPBaepUgyYY1srAVMIEAgEmT55s8WfXWPxZeHg4AgMD2cekCQEPpjs62AOaplFaWgofHx8kJyc7bR31HX14+fta3LcsGZF27OFltn39/PwgEokgl8sHmbf7+/u77PmKpmk89thjUCgUeOedd6w691x77bU4cOAAxGIxSkpKAAA7d+7EO++8ww6xPfnkk1i5ciUA4KmnnsJ7770HgUCAV155BZdffrn1L8h+TIwhEL1ej/b2dlRVVSE9Pd3mcUTHjh3DggULHPqFIITg119/RWxsLMLDw+Hp6fq+cQzMxVKv12PatGkmXSzLWnvx7q/1eOjySQj3N/+1Xv9pISia4P1tWXY7TsaSSJitrpqaGtA0Pa7EwUgw+dl8Ph+pqal2eb87+3QoaenFouQQ0xMvaBqtUgV6uxSDcopDQ0NNrk7qKBqPH6xEbLA3dlycwD5uWVkZPDw8HLotSNEExy50mPUe2IKBYigpKclmz01RFLsV2dPTA39/f/b4WNumYw00TaOkpAT+/v5Oje5zFIz4G7rty9xMyeVy9Pb2GrUAcjaEEDz55JNoaGjAhx9+aPW6fvrpJ/j5+eGqq64aJAD9/Pxw7733DvrdsrIybNmyBSdPnkRLSwuWLl2Kqqoql3lvjDAxtoAbGhrQ0tKCOXPm2MWXihkEcdSBZoY9MjIyIJPJUFxcDB6PB7FYjPDwcJtNHNoDg8HAnkzNqRxMi/THCxumW/y8z61Pg8ZA2fVCaSyJpL29Hb/++itEIhFiY2Oh1Wpd+vhYy8CcW3NsbQghKG9TYmrE4G1ajZ5C9psnsWNRPNbP+GM46NsyGYqaezA9yh/BPqZ9p2vkanxwQo6/zo3B/NRUKJVKSKVSo36DI+Eh4OORlZPZfivm9TI2Po5kb3EbXj1ai3+snIzFDhoKYcSBPV6vQCAYlEbS09MDmUxmNI3EUdTJVfjlbCkunixBfLxlBt3uBE3TOHfunNGev6FDWExaTE1NDTw9Pdm+aGcZfxNC8Pzzz6OmpgaffvqpTa7Hl1xyCerq6kz63b1792Lz5s3w9PREYmIiUlJScPLkSSxYsMDqdTiScScAQ0JCEBUVZbfKCzOR6wgBOHDYw9fXF76+vkhISGCHFMrLy2EwGGyedGELNBoNiouLHW57AuB/wxyOywPm8XgQiUTo6Ohgh1tkMhnKysoGDZHcvvs8tAZ6kKegK0AIMTvlQ6/Xs36a5k5yFzf3YNfvzdg4KwqzBpgz8/k8GGiC3+u7BwnAtZkRmJcYbLL4A4Bwv/5JX0mAJ3g8Hvz9/eHv78/2DcrlcpSVlcFgMIzaN8hMYDL9xPbI9WXo1Rjw3HfnsSZdgtnxg3vglk0JByGwaW/caFAUhaKiIojF4kGvt09HjRoJx/49TXBeqkRbj3bMKWYej4fAwEAEBgYOSyNhzm9hYWEICAiw2/mNoii8eKgQPJEntiyx3wBEjUyFE3WduHJWtEWpOraCEX/BwcFjDnzw+XwEBwcjODgYkyZNQl9fH+RyOXt8mK1iex6fgRBC8Oqrr6KoqAhffPGF3SvGr732Gj7++GPMnj0bzz//PIKDg9Hc3DzIDi4mJgbNzc12XYc9GHcC0N/f365xbY7IAx5r2GPokIJMJkNNTQ3UajV7MXPUl9EYTCj8lClTLPJbdDdUKhXOnTs3KPrL2BBJm6IbAqEQnZ2dJieROII1b5wETQgO3jJv1DU1daoh9vcEpdeiuLjYZIPnoUyN8Mf6GZGYHjU4wsxDwMcRI+kf3iIBEkLNy5cN8hEZnfStlipx6xfn8PH2GZj5v+OjUChQV1cHpVJptG/Q3rm+DEIBDzzwQBtpvPH3EuKKGY65kWLSW6KjowfdvL3+Yy32Fbfjo6uzEBEwcuWHEILHD1Xi2zIZgn1FWJQSapbYMZZG0tjYOOJWpFpPob1Ha/ZnhIERu7csikFgmMSstcqVOpxr7sbiyWEmfZ+/KZOiqUuDDTOI0wQgI/6CgoIsmvb18fFhj4/BYIBCoUBTUxN6enoQEBDAHh97CDNCCN566y0cO3YMeXl5dhs2Y7j55ptZM+lHHnkE99xzD95//32jXsOucj43h3EnAO19EOydB8yIP4qiwOfzx3w9IpEIUVFRiIqKYvtqmJOltU3wlsCIUVcJhbc3jM3L9OnT4e8/PJNVJBKxU3cH0vqHSFpbW3GurBy7a/lYnRGBxWmxTu0dmRMfhN/ru0b9rCm1Brx2tBYRfgLM8+sYNepsLDyEfMxNcM6NQWOnBgaaQNarQ0SA15h+g4GBgWhubsbkyZON5vraEm+RADtXp9r1OcaCEbsJCQkQi8WD/m1eQjC+LpUiZIxKLI/Hg7+XENcuiMVFZoq/oRjbimTOMV5eXggPD8cXZSrIlAY8smoyfD3Mu6QZDAY2qtAST9Kvy9pR0tKLmXFBCPQeW4zcsCgeOgPt8FQehoHizxbb3EKhEBKJBBKJhO2LZm54RSIRu/thi1YYQgjef/99HD58GLt373ZI9ODAG74bbrgBq1evBtBf8WtsbGT/rampyWmettYw7oZAKIqya15vaWkpoqOjLUo3GAtbJnswFzOpVIquri74+/tDLBYjNDTULmKDEILGxkbIZDJkZGTY/c7MFhBC8G25DHMTgszaXmRgDIAzMjLM7oXRGSj8bXcJYnwozA/VsUMk4eHhLvvefVPUAHQ1Y9Fsyw2e3QVCCKRSKSoqKiASieDp6cken/Ha18lE96WkpNhd7NoClUoFmUyGC81StChpXDRZYlYWrsFgwG+nziIpLhrRFl681XoKsl7diCbwroStxd9YMK0WMpkMer2eNQgfOPVtDh9//DHy8/Oxb98+u30H6+rqsHr1anYIpLW1la2Cv/jiizhx4gS++OILlJaWYuvWrewQyJIlS1BdXe12QyCcADSTiooKdlrNltgz1o25M2PMc729vSEWi00yZzUFmqZRVVUFiqKcPvnardbjvoIyXDU3Ghf7t0Bw4TvweltBfCWgk5eAjsgEeP3ra+7S4J78UlycHIJbF5s+8TeSzYulMEMkTA4uk0TiSmKDEbuZmZmjTqFrDf0XRFNSOVwBmhCj6RBMri/jWcn03cpkskF9T65skWEOarUaRUVFSE1NdWrbhlpPoVbeh2mRw6vpo2FuFq5Op8P3x8/gzRICHy8Pu/flHq2S48dqBR5eMdkpW7+OFn9DYXan5HI5uru72anvkJAQk65Bu3btwqeffooDBw7Y7eZzy5YtOHr0KORyOSQSCR577DEcPXoUhYWF4PF4SEhIwFtvvcUKwieeeALvv/8+hEIhXnrpJaxYscIu67IRE0MA0jQNvV5vt8evrq5GYGDgsO0Ra3BksgcjNqRSKeRyOTsRKRaLLbKXMRgMgyYj7bl+hUqHfx6qwp2XJY3Y76PSGnBXbgk2h9bgz317QEQ+gMgX0KvB0ylBJf4J1MxrWRFY2NiN5HBfk6PBmGQZe4rdoWLDmiQSW8AYPJtS2X328HnIlDrsXJU6aFhAptTis5NNuOWSRKdtfw3ltwsd2H+uHfcuTUbIgLSNsXJ9mb40mUw2Yt+gO6FSqVBcXIy0tDSb2mbtK27DO7/W45PtMxFkwvZoVbsSp+o7UdjcgweWT7I4AWVoFu7QNBK9Xo8PvvkdJT1eEHp4YkVaOJZNtd353Bg37yqG1kDj3b9mWhURaAmM+GOm9Z0NM/Utl8uhUCggEAjYc5yxtqH8/Hy88847OHjwoNE2Gw6TmBg2MPbGlj2Azkj24PF48PPzg5+fH5KSkqBWqyGVSnHu3DkQQlgxaEr/nlqtRnFxMeLj421qtj0SKi0FPUWjQ6UbUQD6egrxznIRRD/vBfGPBvj/EyEibxDvIAjqfgSJnAE6qv+OPyvW9D42xgbE39/fbp53wOAhnz6NFt2dHRYlkVgLIQQ1NTXo6+vDjBkzBombX2s6MFnii3C/wTcN2+fHolqmGjYp+l25HAfOtePSyWFWpxnYikBvEUQCHrwHrJVJb2FyfY0xWt+gr68v22rhqlv5A2GiGdPT0+HnZ3k6jYGmcbhMhkUpoezNVJ+OAkj/cM9Y/FrTgSe+rsJ1C+PwlzkxCPGx/L0bmoU7MI2Ex+NBo9Fg0ZQ4RKo9cfk0sUnrs5bXN6eDEDhF/JWUlLiM+AMGT30nJyezBuGVlZXo6upCbm4uVq9ejaVLl+Lrr7/Gm2++yYk/O8FVAM2kvr4eAoHAaisIV4x10+l0kEqlkEql0Ov1rL2MscoTs0U2depUu/RDmgNFD56oEx5/Ffz2EhBfI/YT6k4gIAb6P/3NrOfQ6XTsZKSjmn3rO/rwnx/r8Ne5MUiPDmBzVqVS6ahJJOago2j881AV5sYHYU3GHyKepmk2B3Woh2OvxoD1b/8Osb8HPrvGtK0zrYFCnUKNSWJfh18ETWVorq+5MGJDKpWylQ1TtvL3FrXhzZ/rsOemOaztDAA0d6nx7q8NuGdpMvzskB3d1dWFiooKZGRkWD2wdUGuwn9+rMOadMmYti/GUOkMyDvTiuzMCJOqhZag1Wpx5swZhISEoK+vj00jCQsLc6mpfFvBiL+AgACXEX9joVarsW/fPhw8eBCnTp2CVqvF448/jg0bNkwIRwk7MjEqgPb+EguFQqsFpj37/azBw8MDMTExiImJgcFgGJaBK5FIEBgYCJlMhtraWmRlZTm9R+2CXIVnvj2POy5NYvuGeL2t/Vu/xhD5gKdsN+s5jNm8OIJALxG8RHyE+vVXoobmrA6ciBw4RNKtJfDzFMBLNLYoFPF5/Y+l+eMzTVEUiouLERwcjPj4+GGfT38vIR5ZMXnM6LyBeAoFZv2+IzGW60sIgUKlR5if6duQQ/0Gh/p1jtQ3eKRSBj01vBexuUsDlc6AHo3B5gKwo6MDVVVVyMrKsomZb2KoD267NNHiyDJfDyGunh9r9TpGQqPRoLCwkPXpBP6IdmxtbUVFRYXLpJHYAncUf0C/BdCVV16J0NBQ1NfX45lnnsGvv/6K1atXw8PDA6tWrcKaNWusiiTk+INxVwEkhECn09nt8dva2qBSqSzOiHRV8TcazImS6Rvk8XiYPHkyxGKx03ueWro1ePLratz7v8B0ABD+9gr40lKbVAC7urpQXl4+os2LLWnr0aBXQ2GS2Lwm54FDJO1SKd45p0OgrzeeyEkzW6A7o9LpTEbK9X3m22p8WybDR1fPsMlAiyv1DTI3cGMN9NiD1m4N1HoKSWGOmyIfKP5GqiINTCNRKBQQiUQIDAlDboUaG2bFICXcfabe3VX8Mfz44494+OGHcejQoUE2LG1tbTh06BAOHDiAJ598ElOmTHHiKt2OiTEEYm8ByDQWT5482ey/Zfz9ADhdOJkLk/lKCEFERAT7Pvj5+bE9T65y18yTlkL009MgAQN6AAGA0OB1N8Gw8E62B3A02tvbUVdXh8zMTIdEHm1453cYKILdO+ZYdWNwtKINngYVPHXdY27lD4SZBE1JSUFYmGPixpwJk+vr6emJlJSUQe9NeVsv3vipDi9umG7W1KZMqR3WF2nseUcbUrAnbW1taGxsRFZWllN6FB/eVw4DRfBUzlSH3Pwyn+kpU6aY1aqiVqtR19yO5442IjWIh/VZEQ5Nu7AUd88y/vXXX/HAAw/gwIEDE+IG1IFMDAEI9Pd62IuOjg60t7dj6tSpJv+NK/b7mYNer2czIwduCRJC0Nvby1YGvby8WHsZR5h0jgghEBR/BkH1NyAevoDI548p4IRLQM26jp0CHon6+nooFAqkp6ejS0Pj+SM1uG5hvEnVuQ6VDifrOrF8mtisfreqdiW61HqbmiQzSSQymWzUIRJmGMAUg2eVzoCdBypx52VJkCt1aOhQY3W6xK0+10NzfbUGCjsPVGHx5FBcPs2yidBzzT24K68E118Uj82zo036G0v7Bi2hubkZbW1tFvc4AsB3FTKE+XqYNTw1EGsqgGWtvfDzFJrsudfX14fi4mJMmzbN4ulmHUUDNIXOjg7IZLIR00hcAXcXfydOnMDdd9+Nffv2ITbWfu0AE5SJ0QNob8ydAnZ38cdM+iYkJAyLweLxeAgICEBAQABSUlJYe5nCwkL2QiYWix0fGM7jgcr4C2hJRr8PYE8rSHAiqOSloCOzRhV/zJagXq9HVlYW+Hw+KLUGPPRPOprCj9UK/HK+AzNigyAJMG2LrUamwscnGvHA8uHxZdYwMImEGSJhep6Y2KZqhRaPfVWDD67KMindo1beh6KmHhyv7cSZxm7oDDRWp9svIs3WMLm+ERERiI7uF2pCPh8EBGqd5RP+yeG+SI8OwIIk0wX8aH2DTPV2NL/Bw+VS6CiCVdNHf/8bGhqgUCiQlZWFjj4DeDza5P7G5i413vq5HvcuTcaLRy5AwAf23TzP5Nc4EEt7BAkh+NvecggFPOTdMGfM32esbaxt3fAQ8AEBn027GCmNJCwszOHb6QNxd/F3+vRp3Hnnndi7dy8n/hzIuKwA6nQ6o1l9tkCpVLJRZ2Ph7uKPmfS1JPZLo9FAKpVCJpOBoihWDLpyggRFUSgpKWEtciw9XloDhbYeLeJDTJ+sPHahAwVnW/Hg5ZPMGjywFGaIpLa2Fl9VdOBwixDPrIxHVnLUmNVbQghkSh2CfUSgCYHOQEz2UXQ2Wq0WRUVFRqPOXA1T+gb/trcchBA8lTPN6GMQQlBbWwulUonp06eDz+fjgd1l4PMw4t8M5WRdJ/57ugV3L0lCn46Gv5dg1Cxge3G2sRv+XsIx+/GUSiXOnTtntbWNKTC9t3K5HDRNO8Wzk6ZplJaWws/Pzy3FX1FREXbs2IGCggKkpKQ4eznjlYmzBWxPAajRaFBWVoaZM2eO+nvuOOwxEKb/LSMjw+qtKMalXyqVQqPRsCdJV+qnYYYfoqKi2KrQeKehoQFyuRzp6enQarUunURiC5h+sMmTJ7OToM6iq0+PwxVS5GRGQmSCD91IfYMBQSEQioSD7GMYCCE4f/48dDodpk2bxn7XKtqUEPCBSWLXnMq2BqaVgUlwGYiBpnH7lyVYkSbGmnTzfUtpQkAIRuwJ1el0rGBXqVQOGfRxd/FXWlqK6667Dl9++SU31GFfOAFoC/R6Pc6ePYu5c+eO+DuEEDaOzt2GPRhLjM7OTpvEnA3FYDBAoVBAKpWyVQ2mJ81Z75WzbF6cBSMMNBoN0tLShr3vA5NIzBkicWWYqpAl1WxToWiCTe+ewoo0Ma6/aPS4rSOVMuwvbh811WYkTOkbJISgoqICPB7PrqblrkRPTw9KS0uRmZlp1NeQJgSb3zsNDwEfn14z+g28MR7cXQYC4Jl1Y1dOHTHoQwhhdyzcUfxVVFRg+/bt2LVrF9LS0py9nPHOxBGAer0etIn9WuZC0zROnDiBBQsWDPs3d9/yZcx/+Xw+UlNT7S7I7GFsbC6MzcsZdSh+b1Thza0ZJvnnuRO/XegAn8fDvMRgdvJVJBKZ5KU10hBJYGCgWZ+PXo0BNCEItJPJ72gwx9hYVcgmj6/W49/fnsdNF8fjhs+KIODxcOj/5o/6N3qKhlypQ0SAp9XniaHRgSEhIejt7YWfn9+w6WZncK65B4lhPnYxs2bo7u5GeXn5iPF9tuCdX+qh0VO47dKkEX+nT0fBU8gfVCUcmEYil8tZP8/w8HCLP4+M+PP19UVS0sjrcVWqq6uxbds2fPLJJya1U3FYDScAbcWxY8ewcOHCQT9zd/HHNMaHhYUhLi7O4etnetKYqgZzxxweHm43exmpVMr6oX16uh2/1HTgg21ZLnvsdAYaOw9WYk26BAuSTN/CXPvGSfAAFNw4izV4tsQfzJhgZ4xzBQIBZL1a9GgMSDbSo7Xy9eMAwZjCyNbI5XKcP3/eZobHxmjsVOPFIzX469wYzIwLMvvvH91fgTA/D9w+irAATLOY0el0OHv2LHv+c3ZOcZdaj50HKjElwg83XZxgl+fo7OxEZWWlXcWfKVA0wQ2fFcFTyMcbWzJG/D2m3UIul0Oj0SAkJATh4eEm31S5u/irq6vD5s2b8cEHH2DWLNOShDishhOAtmKoAHR38cfYJSQlJblEY/zALS65XA6RSASxWAyxWGwze5mGhga0tEnRwJNgVUYkfO1YnbAVeorGA7vLkBEdgO0L4kz+u/qOPhj0enQ0VCEmJgaRkZFWr2VgEolCoYC3tzfeLzWAJxThxY3pw74DX5dJoadoi3qvLIXJ9c3Kyhrxc0OT4QkcDE2dapuYQI/Fn187Dh6Ar0YRx7/XdeKTk824cVEcpkcZtzShKApFRUUIDw9HbGwsaJpGV1cXpFKpw/0GB1LU1I34UB+7RLzZOtHEWl48UoPMmABclhpu0u8zJvsymQzd3d1jppEQQlBaWgofHx+3FH+NjY3YtGkT3n77bcybZ9kkOYdFTBwBaDAYzLJqMZeBAtDdhz2Y7bG0tDSLvbLsTV9fHztRzOPx2IliS+72B9q8kOBYvPtrI7bMicb8xPGbM8kMP9izx1GlUqGktgVN7QrEBwohFoudOkTS2NgIqVQ6qudd3tkW/HahA4+vnjLsBmD/uTa8/H0tHl+TioVmVFstgf7fOXg0z8hutR5fl0mxOl0CX4/hr8dgMKCwsBBRUVFGDXSHbkOOh0EfhULBVnedacFiK4ylkTCC3dvb2+3FX0tLCzZu3IhXX30VixYtcvZyJhqcALQVjAB052EPAGhtbUVjYyMyMjJc4u7ZFJjtE6lUyg4oSCQS+Pr6jim+GZsXX19fJCcng6A/bzUy0BNCNzx+psA0xjtS4DtziISxPent7UV6evqo38vjtZ3YXdiKJ7OnDpvslCm1+OBYA+YnBCM62NvotraroNPpUFhYiPj4+GFenSNh7BiN5jfoagzMI3eq6bwdUavVbP8ts6sVEBAwaKLbXWhra8OGDRvw/PPP49JLL3X2ciYinAC0FceOHcPcuXPdturHXCS7u7uRnp7uMhFu5sIMKEilUqjV6kEDCkOPCWPzEhkZiZiYGCet2HQ6+3SQ9eowWWK5VYdCoUB1dTUyMjKMTkU6AsbLTiqVskMk4eHhdpn6Hpjra4uLJCEEd+WVwkPIx79NmPx0BlqtFoWFhUhOTkZYWBi0BgpaA40AL9O3Ww0GA+RyOepb2kFr+xAUFASxWOy0vsGxkEqlqKurgz4kEcUtKuy4ON6sxB13gxCCc+fOgRACgUDg0mkkxpDJZFi/fj2eeuopLF++3KrHuvbaa3HgwAGIxWKUlJQA6G8DuPLKK1FXV4eEhAR8+eWXbObzU089hffeew8CgQCvvPIKLr/8cqtfj5vCCUBbQAjBiRMnkJSU5LInyNFgpkCFQuG4soegKIoVGr29vYMuYhqNBsXFxW6VcXvlu6egM9D47w2z+9MIjPBTtRyRgV5G/dxM6X9zNGMNkVj72CPl+lpDY6cafp4CBPu4xns4EGZrPzU1lb3g3V9QBj1F44UNaWa9B8cudOCfh6rw6IpJSA3mOb1vcCTa29vZz/W2j4uhM9D48oZZ47aCz2z7ent7Izk5GQAGpZF0dHTAy8uLreC62la4QqHA+vXrsXPnTqxatcrqx/vpp5/g5+eHq666ihWA999/P0JCQvDggw/i6aefRmdnJ5555hmUlZVhy5YtOHnyJFpaWrB06VJUVVW5vGC2ExNHAFIUxW7N2hJm2KOzsxPNzc3o7e11CR87U9HpdCguLoZYLEZcnOlDBO7GwOZ3uVwOvV6PxMRExMbGus2Xv07RhzpFHxZPNi5YaUJwV24JPIR8PLt+sIcWk2NsDx9HayCE4P7dZUgK88FNFycMGiKxJkeaoiij081MhX48wkSdDfU1LGrqhlylwxIThxAYWro1uDuvBC9umM7Gtdmjb7ClW4NAb6HRPsaxaG1tRXNzM7KysiAUCqHWU9DoKYvE+cGSdvx8XoEns6eOWT000LRTBKYx8WcMV0gjMUZXVxfWr1+PBx98EDk5OTZ73Lq6OqxevZoVgKmpqTh69CgiIyPR2tqKxYsXo7KyEk899RQA4KGHHgIAXH755di5c6dRC7cJAJcFbA0Dhz2CgoIQHBzMisH29nZUVlYiICAAEokEISEhLicGGbPj5ORkhIebd3FwN/h8PkJCQmAwGNDV1YXJkyeju7sbv504ib21BOuzIjF7coxLVDRGIiHUZ1SDYD6PhwcvnwRfzz8ELSEE1dXV0Ol0bI6xK8Hj8UCT/ixhHo+HoKAgBAUFYdKkSWyOdFFREXg8nslDJHq9nt3aH5jg8kOlDHuL27Fzdapdpk+dCZN2YSznNjPGMpPrqEAvfHHd7EE/G5hTnJSUZHZO8VAMNI2nv6mGt0hgkpnyQFpaWtDa2sqKPwDwFgngbaFn539PNUNPEeNXxQF8fKIRZxq68cTa/kGhOkUf3j/WgL/9eZJd/UIJISgrKxtT/AGAr68vfH19kZCQwLbF1NbWOiyNxBg9PT3YuHEj7rnnHpuKP2O0t7ezzgaRkZGQSqUAgObmZsyf/8dkfUxMDJqbm+26FneDE4AmMNKwB5/PR2hoKEJDQ0EIYatO1dXV8PPzYysazq46dXZ2oqKiwupgdHeioaEBMpkMs2bN+sNGJiYen9aW4veGbghU/ZFnjNBwlyGYgTCVGuCPLVAPDw+kpZm3/WcqfToKPh7WfZafv8K447+vry8SExORmJhoVGj4B4ciPHhwb+doub5+nkII+Tx4Cl1LBFtKW48G135SiDsvjoa/qsluptaj4eXlhdjYWMTGxrKJPvX19VAqlSb1DQr5fGyeHY2YIPOqh01NTZBKpcjKyrLZufSjq2eAJhjzezJV4oeS5l54/+9z/3t9J2oVfejo0yMq0D7ndUb8eXl5mT3tKxKJEBkZicjIyEFpJFVVVfD19UVYWJhFVXZzUCqV2LRpE2699VZs3LjRbs8zFsZ2N8frjoCljEsBaMuDTFGUSf5+PB4PwcHBCA4OBiEEvb29aG9vR21tLby9vVkx6OiqU0tLC5qamjBjxgy3FDnmwlTBtFotZsyYMehiFOjtgZc2ZUAk6HfqV6vVkMlkKCkpASGE3d4aemGtalfi34fP48UN0+Hv5XpfGYPBgOLiYoSGhiI+Ph55Z1vwxe/N+PSamTarUnx2sgnHLnTgX2un2LUfTq2nIBB5sEJDr9ejsqENj+WVICOEYE36H4K9uLh4xFzfOQnBmJMwfqx9+DweaIpGTV0Dti+b6XTrFqFQCIlEAolEwrZcDBQaI/UNmmup09jYCLlcjszMTJveSPN4PAhMuEwM/Ryty4rEyjSJ3XxDGfHn6emJpKQkq65lQwsUSqUScrmcrbJbm0ZiDJVKhc2bN+O6667D1q1bbfa4oyGRSNDa2spuATM3gzExMWhsbGR/r6mpyahF0kTG9a5mLoI15s48Hg8BAQEICAhASkoKVCoV2tvbcebMGXh4eLBVJ3vehRFCUFNTA6VSiVmzZjm9CukIKIpifbKmT59u9JgNFETe3t6Ii4tDXFwcdDodewHTarWsdYm/vz+qZSqodRR6tQaXE4CMBUhcXBwiIvpNlstblTDQBEJTrnAmMic+CKWtvWZNl1rCFW/9Dh6Ph4O39pvEikQipCZEIz5ChZz5MQjia9DU1ASZTMZu81MUZfLnW2ugcMXbp3DDRXHIzjRuiN2no1DY2I0FScEuUzHgaXrw2DyBS3reMS0XISEhg/oGz549a3HfYJ2iD6U1DYj20CAzM9Mu25fSXi0aOtSYHR/E/uzZw+dR1tqL90dIBBLy+RB62qeqPFD8JScn2/SzN3A7PzExEVqtFnK5HNXV1RalkRhDrVZj69at2LJlC66++mqbrX0s1q5di48++ggPPvggPvroI2RnZ7M/37p1K+6++260tLSguroac+fOddi63IFxOQRC0zT0er3Ff8+IP4qiwOfzbfpFHGhqzOfz7bIFSVEUeyKZNGmSy1zE7Akz4BIREWG1zQtjizHQuoQZ9HGl95JJcDHX4LlPR+H9Yw3469wYBPnYT9AdONcGIZ+HP6eZ5k0HAM98W40wXw9cd1G80X/v6upi2xkoimKjA00dItFRNNb85ySyYgJG7EPbW9SGr0rbcf/yFCSFOd//b+Dkq7k7CHWKPgT7iJySwQxY7jd400cn0KfT4/1rF0Bop5vX+wpK0aej8MKGNHgK+5/j2k8KQdEEH109wy7PORL2FH9jYW4aiTG0Wi22bt2K1atX45ZbbrHb+rds2YKjR49CLpdDIpHgscceQ05ODjZt2oSGhgbExcUhNzeX3RV44okn8P7770MoFOKll17CihUr7LIuN2DiTAETQqDT6Sz+W0cle2g0GkilUkilUnYLUiKRWLW9425+d7aAEUL2GHChaRoKhYI9OTL+W6GhoU4dsrDG4LmstRevHr2Aq+bFmpUpbC53fFkCHg94aeN0mzzeaLm+zBCJXC43a4jEGCqdAVXtKmTFBDhd8Le0tKClpWXQ8IOpGGgad3xZAi+RYMTeS0fC9A1KpdJR+wYvXLiA1o5eRCUkIzHMch/Msejq06O9V4tUK7w2bYEzxZ+xtQxNI2FE+0jfJZ1Oh6uuugqXXnop7rzzTqd/ZziMwglAU/7OWbFuOp2OFYMGg2FQeoKpMJO+9oz8cjW6u7tRVlZmcdKFOVYhAwd9Ojo64Ovry1adbGW30tWnR4C3cFRrCsbgOTMz0+I4vM4+PQK9RcMSMGyJWk+BB9ikD7GtrQ2NjY3IzMwcs3VCo9GwFVxHJ5HYkoaGBqv7307VdyEiwNMhmcbmMLBvkPkuhYeHo6enB3q93qJBpt/rOnGoVIq//XkSRCN4Z7oahBCUl5fDw8PD6eLPGEPTSEJDQ9HT08N+JvV6Pa699lrMnTsX999/v8utn4OFE4CjYeqwhyNgRvnb29uh0WgG9aONtDYmFH369OlmiUZ3RiqVora2FhkZGRYJobvySkCIZRUqZtCHqTp5enpa3dup1Bpw9UdnERPshZc3pg/6Nz1F419fVWFhlAghVIdJQmi80NjYCJlMZpGvobHtfHslkdiS2tpa9PT0jBlnZ280esosAU/RBHyeeYN4TN9geXk51Go1/Pz8jPYN0oRAo6dHnET/56EqtPZo8PLG6W4hABnxJxKJbGpebi+YCu69996LM2fOIDMzE2q1GnPnzsXjjz/u8uuf4EwcAQj09ySYgjXDHo6Aoij2AqZUKhEaGjos7qy5uRktLS3IyMhwuQZxe9HY2AipVIqMjAyLJ6vvzisBAfDiBuu3KBkzVplMZvEWJCEET3xdjbUZEciIHlzN1FM0bvjoJEJEFP69ZZ5LGTzbC3NyfU2BSSKRyWTo6uqCv78/xGKxTZJIbAUhBOfPn4dWq8W0adOcKv5+qlbg89+b8bc/T0JcyNifY5oQ3PFlCUQCPl7YYPqWMxPhRwhBamoqm/c9sOokFotxU1419BTBrutmGjVmJoSAAG4RC+du4m8oWq0WO3bsQGtrK/r6+hAVFYW1a9di9erVrCcfh0vBCcChuLr4GwrTrCuVStHT04OgoCA2JDw9Pd1lLmL2hLlAajQapKWluVQVp0utx4naTlyS6M+KdoqiLNrOHwhzgdTqdEibNm3U41zS0gOaYJiAdDeY10xRFKZOnWrz7ybT62TuEIk9IYSgsrIShBBMmTLFIeejH6vkmCzxG+QpyVCn6MPLP1zAv9ZMMdn25O68EsyMC8Rf58aa9PuEEFRUVIDP52Py5MnDXjNTdZLJZPiuuhPVvUI8tnKSS5rtm4q7iz+apnHHHXcgJCQEzzzzDPh8Ps6fP4/9+/dj//790Gg0+Mc//jGRc3ddkYklAHU6nVEjSAZn9vvZAr1ej8LCQvY1BAQEsNUMdz0xjgVj8+Lt7e2wE2dluxJnGrqweXb0mM/39i91OFIhx7/XT0N8SH+Kh16vh0wmg1QqhUajYasZAQF/DBgQQvBjtQLTowIQ5jdYfNA0jdLSUnh5eZn0mv/vv+cAELx2ZYblL9qBlLT04L1fG/DPtVPg9z+RYa9c39EYOkQSHh4OsVgMLy8vGGhi9y1FmqbZXjBHveY+HYUN7/wOP08hvrx+9th/YGMIITh7rhR7qzS4Zfl0SAJGd0IYqW/QVXKKTWE8iL97770Xnp6eePHFF41eazo6OqDVarlKoGvBCUAGdxd/Wq0WxcXFiIqKQnR0NAgh6O7uRnt7Ozo6OlwqhcRWMJFfEokEsbGmVRdswb0FpehVG/DqlenwGCNVQqk1oKpdiRmxgUY/UxRFQaFQ4GBhI0IFGkyO7heD8PDFA3vKMT0qAHdc9ofzP2PwHBYWZnJ2c1uPBjTpj/ZyB74pk2JPURueyp6KIB/RiLm+joTZgpRKpXjrrBIaiPDSFdMQFGifqWCapnHu3DkEBAQgMTHR5L8zNsCko2i8+0s9VqdHmLRt+3tdJxLCfBDu59jWEUbky3VCfF6uxZWzo8zKL7ZHTrG9GQ/i729/+xv0ej1ef/31cVtoGKdwAhBwrWEPS1AqlSgpKRlx0nfocIIzU0hshVqtRlFRkVNyjDV6Cn06CiG+ttkW1OgpXPXRWXgJ+XhxTTykUim6urqgoLwxLV6C+CgxBAIBG3M20OB5vDM01/fXmg509umwOt15r39/cQsOFrXglkwPuwyRMII3NDTUZJEPAJvfOw2VzoC9N80d1PMmV+rw0N5y/GlSiMnbsI6GpmmUlJTAz88PiYmJ6FLr4e8lNNrXZypD/QaZSrupOcX2htnqFgqFbiv+HnvsMXR0dODtt98eN4WFCcTEEoBMbxyDu/X7GYOx/zBn0lepVLLG0yKRCBKJxO4pJLaEsXmZNm0aAgMtC7p3NcpaexEZ6MlGqjEVXMZeRiQSoa+vD6mpqcMybi2BEII+HWW3+CpbYCzXd80bJ0DTwIFb5rrE95XJVmVEu7VDJAaDAUVFRYiIiEB0dLRZf3t/QRkqpUrsvWl4skFXnx6+ngKXnIRlqp2BgYF2q/AO7Bvs7e1FUFAQwsPDndY3yIg/gUDglsb8hBA8+eSTaGhowIcffsiJP/dk4grA8SD+mpqa0NraapX9hyNSSGyJTCZDTU2NxX53joYQgqNVCqRHD+/lM5Wuri6UlJSwflsikYg9TpZOeD/1TTVO1Hbig6uy7JrjaylMhXdorq9cqYPWQCM6yLrPZ4dKh8ZONTJjbHcDYe0QCdPDGxsb6/AKb1efHv84UIG//XkyJAGO2/qlaRrFxcUICQkxq9oJ/E9EtSsxRWKel6Oz+wbHg/h77rnnUFFRgU8++WRCuA+MUyamAHT3fj9CCJvXmJaWZrO7LyaFRCaTgaZptundx8fHJo9vLY2NjWhvb0dmZqbbbF139ulwX0EZ0of08pkKk3QxUPCq1WrWIByA0eNUp+iDh5A/Yt/f6YYuvPz9BXx49QyXs8jo7e1FSUmJxUbeppD9xkloDTT23DTHJqbUxhhqA8QcJ2M3LlqtFoWFhUhKSjKrpYEQgjqFGolh1n1Hy9t68fx3Nbjp4oRBObj2hKIoFBUVITw83KIe3tMNXXjjpzpsmxeLP02yzOTe0X2D40H8vfLKKzh16hS++OILtzkPcxhlYglAg8HABsW7q/ijKAolJSXw9fW1q0v8wBQSvV7PXrycYSjN2Lyo1WqbCl5HUd7Wi9hgb3ai1VRaWlrQ3Nw8aoV34HDCwISLe/ddgEDAw382u8fkLwOT65ueng5fX/tl7jZ2qlElVZo1ZGAuhBC88XMdogO98ecpwUaPk5+fHzQajdFqpyl8XynHpyebcMeliVZVMwee8x1xTqQoCoWFhRZtdTNo9BR+Oq/ARUkhNmtlMNY3GB4ePmhC31LGg/h788038eOPPyIvL89tWoY4RmRiCUCml4rH47nltJJGo0FxcTFiYmIQFRXlsOdlUkikUinUarVJKSS2wlzLk/EAIQT19fXo7OxERkaGyYKXOU4ymQxlrb0QhwZhZkr0IINwV0Yul7Pb+wNbEM419yDc3wMRY1iCuCI3fV4EAZ+H1wcIcSaJRCaTsTFnSUlJiImJMfu81KPR44dKBS6fFm63SqatYfoco6KiXNoWxJZ9g4yfI4/HM+pt6OoQQvDee+/h66+/RkFBgcu2CHGYxcQRgIQQrFy5En19fVizZg1ycnIQGRnpNl9EZlssNTXV7CqBLRmaQhISEgKJRGIXkaHX61FcXAyxWOxQmxdnwpgdGwwGTJ061eIblaEG4YGBgRCLxS5rltva2oqmpqZh1U6KJrhpVxG8hAK8emX6KI9gGyia2DQLmaL7T5fGHlOpVKK4uBixsbFQKpXo6upCWY8IocHBWDMrwe0q3aZgTp/j8doOvPR9Ld7Yku70PlVr+gbdXfwBwMcff4z8/Hzs27fPLXqvOUxi4ghAoP+L2NTUhPz8fBQUFICiKKxevRrr1q1DbGysy34xmcEHe2+LmQtN01AoFINSSMRiMYKDg60WGWq1GsXFxUhMTLTJ1Ks7wFhh+Pj42HR7n7l4SaVSdHZ2upwn5Fi5vmWtvQjz84DY377DCQaaxq27ziHYV4Snc6bZ9bm6u7tRXl4+6DtNCMH1H5+BTqfFrel8eHl5sf1o42G7jRF/cXFxkEgkY/7+V6Xt+OBYI97YmoFQG1ku2QJCyCCT8NH6BseD+Nu1axc+++wz7N+/36WuPxxWM7EE4EAIIWhra0NBQQEKCgqgVCqxevVqZGdn27W3zlyYwYeMjAyXvggwIqO9vR1dXV1WpZD09PSgtLR0XNm8jAWzLWbvaiczqco0vTOTquHh4Q5v6CaE4MKFC1AqlTbJ9bUFt35RjEXJIdgyJ8bkv2nv0SLYVwQPEy1WOjs7UVlZaXSSvUejBw88+HsJzRoisQd3fFmCxk418m6cbfWgkE6nQ2FhIRITE+3m27mvuA1HKuV44Yo0m1Zxx0Kj0bC7IgP7Bv39/VFVVeXW4i8vLw/vvvsuDh48CH9/f2cvh8O2TFwBOBSpVIo9e/YgPz8fHR0dWLlyJdauXeuw/M2hMHeOBoPB6QHw5jLQw06hUJhVcWKqnRkZGS4zfWxvGL+7+Ph4kyojtoSpZMhkMggEAofZADGfb5qmx8z1ffbwefxa04G8G2ebZQysM9D4x4EK/GVuDKZH2WeaWK2ncMuuYnh7CEwauGH6HLOyssyy8DE27MOIDEvPT70aA+7fXYprFsRhbkLwsH/f9uEZqLQUCnbMsejxGXQ6Hc6ePYvk5GSEhYVZ9VijccuuYugpGm//JdNpYovpG2TOfUx0oTvGce7btw+vvvoqDh48iKCgIGcvh8P2cALQGB0dHdi7dy/y8/PR0tKCyy+/HDk5OUhLS3PIl9hgMLAxUElJSW5558gwNIXEy8sLEonEaO9MU1MT2traXL7aaUtUKhXOnTuH1NRUBAcPvwjbgmqpEi8euYBnr5gGX4+RpyUH2gBRFMVWnGy97WPuYM9NnxehtVuLPTfNMeu7oNIa8H//PYe5CcG4+ZIEK1c9MnuKWpEVE4iE0NFvWNrb21FfX4+srCyrPt8Dh0iUSiWCg4MhFovNTiLp1Rhwd14J1s+IxIo0+9x4MPY2jAiaCDA3N0C/RZNcLkdnZyd8fHzcJqf4q6++wrPPPotDhw7ZvOc8ISEB/v7+EAgEEAqFOHXqFDo6OnDllVeirq4OCQkJ+PLLL+12PuRg4QTgWHR3d2P//v0oKCjAhQsXsHTpUuTk5CArK8suYpCZ9I2NjXXpCTlLYVJI5HI5hEIhW3FqbGxEX1+fW9q8WAqTaDJ9+nS7bq/sKWzFnuI2/HvdNJP76HQ6Hd78oRKURoUFEths8nusXF+tgcLx2i5ckhJikxsfHUVDyOc53euwpaUFLS0tNvWwlCt1uPGzQjy8JBre+h6bJJHYEo1Gg8LCQrve3LgazBAXIQSpqansZ9icvkFnc/jwYTzxxBM4dOiQXSq2CQkJOHXq1KDHvv/++xESEoIHH3wQTz/9NDo7O/HMM8/Y/Lk5BsEJQHPo7e3FoUOHkJ+fj4qKClx66aXIycnBnDlzbCIGmd63qVOnToiSe19fH1sV4fP57BboRLAYkMlkuHDhAjIyMux+AWC+z+YKqive/h18Hg+7rslit7WYye/w8HAEBweb9ZhMrm9UVNSINkYHS9rx39MtuG9pMtKj7bNta4ydBytxtrEbBTfOsXn/GDPkkpmZaVNRVt7Wi3vzy3DXkiQsnRJutL/TWUMkTJLLlClTEBQUBEIIjlTKMT3K3y3tfExhJPFnDKZvUCaTQafT2dRv0BqOHj2KRx99FAcPHrRbO4oxAZiamoqjR48iMjISra2tWLx4MVtF5bAbnAC0FLVajW+++QZ5eXkoLCzEJZdcgpycHCxYsMCik/xE7H1jbF6YrUamx8kVU0hsiSkGz66ASmcAn8eD9wB/OZqmWXuZ7u5udtgnJCRk1M+9sVxfY/TpKJxr7sHs+CCHNvLfvKsYzV0a7DVzm3ks6urq0N3d7ZQhF2NDJOHh4Tb9TmkNFH4+34HLUsPYKmtfXx+Ki4sxdepUdoirV2PAVR+dQUywN17dZH87H0djjvgbiqvkFP/yyy948MEHceDAAbv6zCYmJrI3jzt27MCNN96IoKAgdHV1sb8THByMzs5Ou62BAwAnAG2DVqvFd999h9zcXPz+++9YuHAh1q1bh4suusgkj6iGhgbI5XJkZGS4fG+IrRjN5kWn07FiUKfTDepFc/d+yIGCwNlbdNZCCGHtZRhvNGbYZ6CdCyMILEm6GOv5XfXzQAhBTU0NNBoNO8Sl1BqgNdBOsTRhhkiYipMthkgAIPdMCz490YR/rJqMmXFBUKlUKC4uNhrjV9jYjfhQb6d7+tkaa8TfUAb6DXZ2dsLb25v9Ttnz2nDixAncdddd2L9/v909V1taWhAVFQWpVIply5bh1Vdfxdq1azkB6Hg4AWhr9Ho9fvjhB+Tl5eHXX3/F3LlzkZ2djcWLFw+r9uh0Ohw7dgzh4eFWmf66G+bYvAxNIQkNDYVEInFICoktGTj1OmXKFJc71g/vq0BrjwbvWjhByWSqMj1OHh4ebLWpsrLS5rm+XWo97s4rxZp0CdZluVavLHOsCSGDXARu+KwQFEXw3rYsp352B06qWjNEAvQP2pyq78JFKSHQ9PXh3Llzdu9pdSVsKf6MPTZTxZXL5eDz+Wwvri3bRk6fPo3bbrsNe/bsMdqXa0927twJPz8/vPPOO9wWsOPhBKA9MRgM+Pnnn5Gbm4uffvoJWVlZyM7OxpIlS9DX14eNGzdi2bJleOCBB9xKzFiDXC7H+fPnLdrqdmQKiS2hKAqlpaXw9fV12anue/JL0K024N2/Zln8GD0aPa79uBB/mRuDyycHor6+Hq2trfD19UVERASCQsKwt7QDOVkRCPDqr2ZseOd3eAr5+OyaWWY9l85A49b/FmPb3FhcMsl1pksJISgrK4NIJBqW91rU1I0utQF/cqH10jSNzs7OfuHe0YkfWgVYNyMa0xIizapQM0lF6enpDs0L3/V7M45UyvCfLRkm+zDaCkIIqqurQdO0zcWfMezRN1hUVIQdO3agoKAAKSkpNl7xcFQqFWiahr+/P1QqFZYtW4ZHH30UR44cQWhoKDsE0tHRgX//+992X88EhxOAjoKiKBw7dgz5+fn46quvoFarsX79ejz88MPjss/NGM3NzewkpLW9b/ZMIbElEynOTmugsPX9M9g4MwpLEzzZXF8ejwepVIrfqlrxWakaGzNCkTM7Ab6+vtjwzinweEDeDdZ5zbkCTJKLn58fEhMTXVLoj0Zzlxr35p3D3EgRFoRqTR4iYSr6GRkZDk+KeO678yht6cX7Dq6qMuKPoiineMXaom+wtLQU1113HXJzc5GammrnFfdz4cIFrFu3DkD/a9i6dSv+/ve/Q6FQYNOmTWhoaEBcXBxyc3OdGnk6QeAEoKM5deoUrrvuOtx2222orKzEt99+i+TkZGRnZ+PPf/7zuNw6YfqhVCoVpk+fbvPet6FRZ6YOJtgbjUaDoqKicRtnp9IZjPoKjpTrSxOC6rYeeFMqdCpk7Ja+WCx2+vSjtTD2NiEhIYiPj3f2ciymrUeDEF8PeAj4Jg2RMJF2E2l4zdnibyiW9A1WVFRg+/bt2LVrF9LS0hy8Yg4XgROAjmT37t148skn8eWXXyIxMRFA/5e3qKgIubm5+OqrrxATE4Ps7GysXLlyXFjB0DTNbok5Ig5paAqJr68vJBIJQkNDjebM2gtHGDw7k6Kmbjx3uAZ3LknCrLgg9udj5foOhKIotorLVDFcsYrLQAiBUkvB32vw62Ji/CQSCWJiTI+QG42RxLWzGDpEEhoaCm9vbzQ0NCArK8vlvOzshauJv6EM7Btk0n08PT0hEAgwdepUAEB1dTW2bduGTz75BJmZmU5eMYcT4QSgo3jnnXeQl5eH//73vyMKO0IISkpKkJeXh4MHDyIsLAw5OTlYtWqVW7roD7R5iYuLc/jzM4MJ7e3tDs297erqQnl5ucP7oRyJTKnFPw5UYueqVIj9PdlcX6bKa66AY3rRmCqGKxkaMzzxdRWOX+jEh1fPYCd59Xo9CgsLERsbi4iICJMfa7QJ5h8q5XjhSA2eyplqtwg7SyGE4MPf6uFPKxGql8HT0xMhISEWD5GM9jxHKuXIiA4w2bzc3hBCcP78eRgMBpcUf8bQarU4ceIEHn/8cXR0dGDOnDk4ceIEPvvsM8yZ4/5tFxxWwQlAR1FfX4+oqCiThQczSZiXl4cDBw7Az88Pa9euxZo1ayAWi13+5MNsfyYkJDg833YkjKWQiMVim3rxMQbPmZmZE8LQGjAv19fUx+vp6WGruN7e3uz2ozNtkgobu/HK0Vq8+9dM8Hk86HQ6FBYWIjExEeHh4SY/DiEE13xcCAGfh/e2ZQ379zpFH+7JL8Xbf8l0imXMaBBCsPXdk9BrNfjshvkQiUTsEAmTRMLEnVkj3Lv69Ljli2JMifDDoysd0582Goz40+v1NvmMO4OysjLcfvvtCAwMRHNzMxYuXIjs7GxcdtllZuVSc4wbOAHoDjDVlby8POzduxceHh5Ys2YNsrOzERkZ6XInI2Yi0JUTTdRqNaRSKaRSKXg8HisGrRFtzc3NaG1ttWncl6vD5Pp6e3sjOTnZ5p9FZkurtqkN/zjcjMsSPJGdFQ2xWOzUixYTczZp0qRRq/Pdaj1u+rwYT+VMHZQVfO0nhUgM9cEjKyc7Yrk2Qy6Xo7jiPGbNyESg7+Bt34FJJAqFAh4eHmzF3ZKbrHPNPYgL8Uagt3O/S+NB/LW0tGDDhg147bXXsGjRIhgMBvz666/Yu3cvvv/+e6SkpODVV18dl/GjHCPCCUB3gzGOLigowO7du0HTNFavXo2cnBzExsY6/eSkUChQXV2N9PR0h08EWopGo7EqhYQQgtraWvT29tplyMVVceTgg9ZAYcdnxVgzPQyzw2jIZDIQQpySGMMYWzMxZ6NR0abEfQWluPmSBKyc7hqVcEuRyWSora1FVlaWSYLOEUkk9mY8iL+2tjZs2LABL7zwAhYvXjzs3xnropSUFK4SOLHgBKA7QwhBa2srCgoKUFBQgL6+PqxevRrZ2dlO8Zuzpc2LsxiaQhIWFgaJRDJiCgkhBBUVFSCEuO0FwhJMyfW1NzqdDlKpFDKZDFqtlhWDfn5+djsOSqUS586dM9nYmhACPUUgFPDYqDS7Q1PgySvA06lAB8UDftYLT6lUivr6emRlZVlU3TY2RCIWi13a0H08iD+pVIorrrgCTz/9NJYtW+bs5XC4FpwAHE9IpVLs3r0b+fn56OzsxMqVK5GdnW13k1Jmi1qpVI6rCpixFJKBliUURaGkpAT+/v5u6ftmKVqtlu19cxV7G4PBwB4rlUo1aDDBVseF8btz5eEefsNvEP36HKDpBng88AgNKnY+9IvuB7xGT90Ziba2NjQ2Nlos/oD+vsadByvxZPZUiH2FNksisRfjQfwpFAqsX78ejz32GFauXOns5XC4HpwAHK8oFArs3bsX+fn5aGtrw/Lly7Fu3To2l9RWMDYvQqHQIW74zoKxLGlvb4dSqURQUBC6u7sRHR097g2eB2KvXF9bQlEUOjo6WJPwwMBA1hfS0s9+V1cXKioqXNrvjt9aCNHX9wBCL0D0vzUSGjx1B+jQSdCteQPgm3dz1traiubmZmRlZVllo1TY2I3nj9Tg4RWTkSr5Qzwbm/62xRCJNTC+pTqdzm3FX2dnJ6644go89NBDyM7OdvZyOFwTTgBOBLq6urB//34UFBSgtrYWy5YtQ05ODjIzM60SgwaDAcXFxQgNDXVr81tz6evrw5kzZ+Dt7Q2dTufy/nW2ghnusXWurz0hhLAm4R0dHfDz82PtZUwVNAqFAufPn3f5yW6PA/8HnrxqeKWPEEDTCf2yJ0HHzDP58Zqbm9HW1oasrCyHiDFbD5FYugZ3F389PT244oorcNddd2HDhg3OXg6H68IJwIlGb28vDh48iPz8fFRWVuKyyy5DTk4OZs+ebZZ40Wg0KC4uRnx8vMvYvDgCpgeMmXAemkLi7+8PiUTi9BQSW8NUwNxpuGcohBD09vayVkCenp5jCgypVIq6ujqTBx9GgybEfn2A+j54fbISxDsMMPYcfQpQqatguOgekx6OMfTOzMx02ufY0UMkjPjTarWYNm2aW4o/pVKJDRs24Oabb8aWLVucvRwO14YTgBMZtVqNr776Cvn5+SgqKsKf/vQn5OTkYP78+aOe9N3B5sUeMCJo+vTpRnvAjKWQMJFMjkwhsTWu6m1oraBSqVTsEAmfzx9mBcRE2lnT+8bQp6Nw/aeFmBkXiHuXplj1WEbRqeD16WoQ71DjAlDdASplOQwXPzDmQzU0NEChUCAjI8NlbmLsPUQyHsSfSqXClVdeiauvvhpXX321s5fD4fpwApCjH61Wi8OHDyM3NxenT5/GwoULkZOTg4suumjQxW/37t2QSqX461//6raVIEuQSqWora01WQQ5K4XE1oyU6+tsPj7RiK9LpXhjS4ZNfOIGWgFRFAUPDw/odDrMnDnTJuKdEIKrPzqLDTMisTbTDl5rhMBj7w3gdTcBnkbyxNUK6C97DHT8xaM+TF1dHbq7u5Genu6y7QwGg2HYEEl4eLjFLRjjQfyp1Wps3rwZmzZtwg033ODs5XC4B5wA5BiOTqfDDz/8gLy8PBw7dgxz585FTk4OysrKsGvXLuTn5yM6OtrZy3QYTU1NaGtrs8rgeWC1iUkhCQ8Pd2nfrYaGBsjlcpNyfR3N95VyfPBbA97flgWRwLZCpaamBjJZf8yZVqsdNv3tqvAbf4PH4b+BePgDwv99rggBT9MB2j8KunUfAIKRP78DJ/ldVfwNZaQhElN7PBkHA41G47biT6vVYuvWrVizZg1uvvlmt3wNHE6BE4Aco2MwGPDjjz/iwQcfhEwmw0UXXYR169bhsssuc6ntQHtgL3sbe6SQ2BJrc33dFeZ19/X1IS0tDXw+HxRFsfYyrmpZMhBB9dcQ/vYyeJQOBACPENDhqdBd9jjgazyujnndarXa5i4BjmRgj6epQyQ1NTVuLf50Oh22bduGJUuW4I477nDL18DhNDgByDE6er0eO3bsgK+vL55//nkcP34c+fn5+P777zFt2jTk5ORg2bJlLmuNYSmEEJSXl4PH49k1+F2r1bJikKIohIeHQyKROO39tHWur7tACEFVVRUoihrxdTPVJib3NiAggLWXcZVeOQCAXg1+61lApwIJjgcJmWS8LxB/+N3pdDq3FUEj0dfXx1bdAQxLjampqYFarUZaWppbvm69Xo9rrrkG8+fPx3333eeWr4HDqXAC0Bbk5uZi586dKC8vx8mTJzF79mwA/f00U6dORWpqf5j5/Pnz8eabbwIATp8+je3bt0OtVmPlypV4+eWXXe4L3NPTg02bNmHZsmW4++67B62PpmmcPHkSeXl5+PbbbzFp0iTk5ORg+fLl8Pc30oPkRlAUhXPnziEgIMChBs/GUkjsnWwxEHvn+joapdaAt36ux42L4uHvNfJ2ICP2BQIBJk+ebNLrHjrwc0ElQh/fB1cvSnGpXsnRYEQvTdN2vclxBbRaLVvJ1el04PP5EAqFVlthOQuDwYAbbrgB06dPx8MPPzyujx2H3eAEoC0oLy8Hn8/Hjh078Nxzzw0SgKtXr0ZJScmwv5k7dy5efvllzJ8/HytXrsTtt9+OFStWOHrpo3LLLbfg0ksvxcaNG0f9PZqmUVhYiNzcXHz11VeIi4tDdnY2Vq5cicBAy9IHnAUTcRYZGenUPkcm2aK9vd1oComtcWSur6M4VtOB54/U4M7LknBxSqjR32FEr4+Pj8XxiYQQbHnvd6i1ejw4SwDPAVuPrtrjyVR6AYxrA3djVFdXo6urC15eXjYZInE0FEXhlltuQUJCAh5//HG7Hruvv/4ad9xxByiKwvXXX48HH3zQbs/F4XA4AWhLFi9ebJIAbG1txaWXXoqKigoAwK5du3D06FG89dZbDl/zaBBCzD65EEJQUlKC3NxcHDp0COHh4cjOzsaqVasQGmr8IuwqaDQaFBUVISkpCeHhxvulnAGTQiKVStHb22vzmDO9Xo/CwkJER0c7LdfXHlA0QVuPBpIATwiNXNiZSm9QUBASEhLYnx+70IEpEj+E+JpeyVNqDVDrKYT7eQ7bemR6PL29va1+TbaAqXgKhUJMmjRpQom/odu+1g6ROBqapnHHHXcgNDQUTz/9tF0FK0VRmDx5Mg4fPoyYmBjMmTMHu3btwrRp0+z2nBwOxegX3/U+9W5MbW0tZsyYgYCAAPzrX//CxRdfjObmZsTExLC/ExMTg+bmZieu0jiWXBh4PB7S09ORnp6Oxx57DBUVFcjLy8OGDRsQEBCAtWvXYs2aNQgPD3epC89Qg2dXQiAQsCKCpml0dHSgtbUVFRUVCAwMhEQisbh6weT6uprotQUCPg/RQcZFl8FgQFFRESQSyaDvYpdaj+e/q0FSmA+eXZ9m8nP5eQrh59l/6vTx8UFCQgISEhJY/7ry8nLo9XqHb+sPhRCCsrIyeHp6jottfnNgBl0G9vzx+XyEhoYiNDR00BBJXV2dU5JIRoOmadx7773w9/e3u/gDgJMnTyIlJQVJSUkAgM2bN2Pv3r2cABzncALQCEuXLkVbW9uwnz/xxBMjZi1GRkaioaEBoaGhOH36NHJyclBaWgpjFdbxeCLm8XiYOnUqHnnkETz88MOoqalBXl4etm7dCg8PD6xduxbZ2dmIiIhw6uvv7OxEZWUlMjIyXN7bkM/nIywsDGFhYSCEsEMJVVVV8Pf3Z2POTBlKYHJ9U1NTERwc7IDVuwZMxTMmJgaRkYM9+YK8RbhvWQomiW3zOfD09ERMTAxiYmKg1+shl8vZSWNmWz8wMNChPZ6+vr7sRX2iMHC6e6T3msfjISAgAAEBAUhJSWEruUVFRQCGD5E4Epqm8be//Q18Ph8vvPCCQ7aqm5ubB+Wcx8TE4MSJE3Z/Xg7nwglAI3z33Xdm/42npyfbAzRr1iwkJyejqqoKMTExaGpqYn+vqalpXG29GYPH4yElJQUPPvggHnjgAdTX16OgoADbt28HIQRr1qxBTk4OYmJiHCoGB0Z9uYoNi6nweDyEhIQgJCSEzVGVSqW4cOECfHx8Rk0hccdcX1ug0+lQWFiIhIQEiMVio78zP9E+YlgkEiEyMhKRkZHstn5zczPKy8vtnidN0zRKSkrg7++PxMREmz++K2OK+DPGwEouM6BVWVlplySS0aBpGjt37oRKpcI777zjsD7FiVKo4BgMJwBthEwmYy0iLly4gOrqaiQlJSEkJAT+/v44fvw45s2bh48//hi33Xabs5frMHg8HhISEnD33XfjrrvuQmtrK/Lz83HTTTdBo9Fg9erVyM7OtvsEbmNjI6RSKWbMmOFW6RzG4PF4CAwMRGBgIFJSUqBUKiGVSlFfXz8o81YkErlVxdOWMD2eKSkpTu9HHbqtz+RJM5Xc8PBwhIWF2cRehqZpFBcXIzg4eNwM+JjKQD9La84lHh4eiI6ORnR0NJtE0tDQgN7eXrsOkRBC8OSTT6K9vR0ffvihQ4dUYmJi0NjYyP73RChUcHBDIGaze/du3HbbbZDJZAgKCkJWVha++eYb5Ofn49FHH4VQKIRAIMBjjz2GNWvWAABOnTrF2sCsWLECr7766oS/uyKEQCqVYvfu3SgoKEBnZydWrlyJnJwck+05TH2empoa9PX1TQij44EpJDRNQ6/XIzMzc0JV/tRqNYqKilx+u3tgJVehUFgdIchMd4eFhQ3azpsI1NbWsibu9jq3Dh0i8fPzY9swrB0iIYTg2WefRWVlJT755BOHD6UYDAZMnjwZR44cQXR0NObMmYPPP/8caWmm98ZyuDTcFDCH66JQKLBnzx4UFBSgra0Nl19+OdatW4epU6daLNpommY93yaa/UVraysaGhoQHh6Ojo4OAH/0NbnKhKo9YAZ83HG7W6lUQiaTQSaTsVXD8PBwk9oVKIpCUVERxGLxoEGXiYAjxN9QjCWRhIeHW2QHRAjBK6+8glOnTuGLL75w2g7FoUOHcOedd4KiKFx77bX4+9//7pR1cNgFTgByuAddXV3Yt28fCgoKUF9fj6VLl2LdunXIyMgwWQwy1RDG9mMiiT8m1zczM5PdVjSWQiIWi8fVtnBPTw9KS0uRnp4OPz8/Zy/HKtRqNSsGaZpmJ4qNHS9myjkyMnLCbdsx4o+J83MWfX197PEihJg8REIIwZtvvokff/wReXl5LjGBzDEu4QQgh/vR09ODgwcPoqCgAJWVlViyZAlycnIwa9asEU/4Op0ORUVF487rbixMzfXV6/WQyWRob293SgqJPejq6kJFRQUyMjLGXVThwNQYrVbLHi9/f39QFMX6Og6dch7v1NbWore31+VaO4wdr/Dw8GHG7oQQvPfee/j6669RUFDgdoNpHG4FJwA53Ju+vj589dVXyM/PR3FxMRYvXoycnBzMmzePrXRVVVXh0UcfxauvvjruvO5Gg0l7IISYFfXFpJBIpdJBdiX2SiGxBwqFAtXV1W453W0uzFACYxRuMBgQHR1tcbKJu+Kq4m8ozPGSyWQoKyvDoUOHkJ2djRUrVuDLL79EQUEB9u7dO67bMjhcAk4AcowfNBoNDh8+jNzcXJw5cwYXXXQRMjIy8OKLL+KVV17B4sWLnb1Eh2GrXN+hKSTBwcGQSCQ2SyGxBzKZDLW1tcjKyppQ22d6vR5nzpxBaGgodDoduru7ERAQwA4luLIoshZ3EX9D0Wq1+Pbbb7F792789ttv0Ov1eOaZZ5CTk+P2meocLg8nADnGJzqdDi+99BKee+45xMXFISMjAzk5ObjkkkvGvShgmv9DQ0NtavvBpJBIpVJ0d3cjMDAQYrEYISEhLnPRbWtrQ2NjI7Kystze2sccGH/DxMREtspNCGHtZTo6OuDr6zuqN6S7UldXh56eHrcTfwPJy8vDu+++iyeffBLffvstvvrqK4jFYuTk5GDt2rWQSCTOXiLH+IMTgBzjk7y8PDz//PPYvXs3wsLC2Ibqn3/+GTNmzEBOTg4uvfTScbc96KhcX0ZctLe3sxmq5qSQ2IOmpia0t7cjMzNzXAmcsWDi/EbzNySEQKlUor29nZ1QdaWYM0sZD+Jv7969eO2113Dw4MFBMZQ1NTXYu3cv9u3bh6effhrz58933iI5xiOcAJyo5ObmYufOnSgvL8fJkycxe/Zs9t+eeuopvPfeexAIBHjllVdw+eWXAwBOnz7NeheuXLkSL7/8sktuA77++uvYu3cv8vLyhtl+UBSFX375Bfn5+fj+++8xffp05OTkYOnSpW4/KMAYHTs613eod91YKST2oL6+Hh0dHcjIyHCaAHUGGo0GhYWFmDx5MkJCQkz+OybmTCaTgcfjsWLQnfrOxoP4O3ToEJ577jkcOnTIrOPHwWEDOAE4USkvLwefz8eOHTvw3HPPsQKwrKwMW7ZswcmTJ9HS0oKlS5eiqqoKAoEAc+fOxcsvv4z58+dj5cqVuP3227FixQonv5LB1NbWYufOnXj77bfH9N6iaRonTpxAXl4eDh8+jEmTJmHdunVYvny521mGuEquL1NpkkqlkMvl8PDwgEQisdjI2JTnG+j55q5CwBIY8WftMddoNOyEKkVRg+xlXPEGDxgf4u/w4cN44okncOjQIYSFhTl7ORwTD04ATnQWL148SAA+9dRTAICHHnoIAHD55Zdj586dSEhIwKWXXoqKigoAwK5du3D06FG89dZbzlm4jaFpGmfPnkVubi6+/vprxMfHY+3atVi5ciUCAwOdvbxRYXJ9p0+f7nKN4wNTSAbGn5lrjGsMQgiqq6uh1+sxbdo0lxUr9oBJNpkyZcqgbUNrYeyAZDIZ1Gq1S06Ajwfxd/ToUTz66KM4ePAg19/H4SyMfqEnTvMMxzCam5sH9ZrExMSgubkZIpFoUJoA8/PxAp/Px6xZszBr1iw8+eSTKCkpQW5uLlavXg2JRIK1a9di9erVLrdNw+T6ZmZmuuQWtq+vLxITE5GYmAi1Wg2pVIpz586BEMKKQUu2HQkhqKioAI/Hm3Dij6n2Tps2zebJJiKRCFFRUYiKimInwBsbG+2eeWsq9fX16O7uRnp6utuKv59//hkPP/wwJ/44XBJOAI4Tli5dira2tmE/f+KJJ5CdnW30b4xVf3k83og/H4/w+XxkZGQgIyMDjz/+OMrLy5GXl4f169cjMDAQ2dnZWLNmDcLCwpz6HshkMly4cMFtvO68vb0RHx+P+Ph4aLVayGQylJeXw2AwmJVCYiuLG3dEpVKhuLjYIdXegRVbJvNWKpWiqqrKKUM/9fX16Orqcmvxd/z4cTzwwAM4cODAhDPp5nAPOAE4Tvjuu+/M/puYmBg0Njay/93U1ISoqCjExMSgqalp2M/HO0yF6dFHH8UjjzyC8+fPIz8/H1u2bIGnpyfWrl2L7OxsSCQShwqR1tZWNDU1YebMmW5pd+Lp6YmYmBjExMSw247V1dWDUi2MpZDQNI1z584hMDAQCQkJzlm8k2AyjZ0Ra8fn8xEaGorQ0FAQQtDd3c3egHh7e7NDP/b6LI4H8Xfq1Cncdddd2Ldv34TLZuZwH7gewAnE0B7A0tJSbN26lR0CWbJkCaqrqyEQCDBnzhy8+uqrmDdvHlauXInbbrsNK1eudPIrcA6EENTX1yM/Px+7d+8Gj8fDmjVrkJOTg+joaLuKQWO5vuOF0VJIaJpGUVERwsPDERsb6+ylOhSmzzMjI8OlspoJIWyfp1wuh1AoZKu5tujzBMaH+CssLMRNN92E3bt3Izk52dnL4eAAuCGQicvu3btx2223QSaTISgoCFlZWfjmm28A9G8Rv//++xAKhXjppZfYSd9Tp06xNjArVqzAq6++OqG230aCEIKWlhZWDGq1WqxevRrZ2dlISEiw2XtECEFNTQ36+vrcugHeVAamkPT09MBgMCAyMhIpKSkT6nPX09ODsrIyt8g0Zvo8ZTIZCCGsGLR03eNB/JWUlOD6669Hbm4uUlNTnb0cDg4GTgBycNgSQgikUikKCgpQUFCA7u5urFy5Ejk5OZg0aZLFwoUZegBgVq7veECn0+Hs2bODIs5cMYXEHnR3d6O8vByZmZlu5dEH9B83qVQKqVQKvV4/6ta+MRoaGtDZ2enW4q+8vBzXXHMNdu3ahbS0NGcvh4NjIJwA5OCwJ3K5HHv27EFBQQGkUikuv/xyrFu3DlOnTjVZxNE0jZKSEvj6+iIpKWlCiT8m5SI5OZn1ShsaceYKKST2YOCEt7uJv6EM3NpXqVQICQmBRCJBYGCg0c/zeBB/1dXV2LZtGz799FNkZGQ4ezkcHEPhBCAHh6Po7OzE/v37kZ+fj4aGBixbtgzr1q0b9SLH5PqGhYUhLi7OwSt2LozX3WhGx0NTSLy9vSGRSNw+77ajowNVVVVuM+FtDhRFsZnSPT09w6q5DQ0NbKqLu4q/2tpabNmyBR9++CFmzpzp7OVwcBiDE4AcHM6gp6cHBw8eRH5+Pqqrq7FkyRJkZ2dj1qxZ7EVPKpXijjvuwLPPPjvhpgYZu5Np06aZbMRtLIXEHfNuFQoFzp8/j6ysLJsNUrgqNE2z1dzOzk7weDzweDzMmDHDrY7ZQBoaGnDllVfinXfewdy5c+3yHDt37sQ777zDRj4++eST7EDeSFGeHBxD4AQgB4ez6evrw6FDh5CXl4fS0lIsXrwYCxcuxOOPP4777rsPmzdvdvYSHQoz8Wqt3Yk9U0jshUwmQ21tLbKystxWAFlKfX09pFIpgoKCoFAo4OXlxdrLuMt70dzcjI0bN+K1117DokWL7PY8O3fuhJ+fH+69995BPx8typODYwhcEggHh7Px8fHBhg0bsGHDBmg0Gnz00Ue47bbbMGnSJJw8eRJRUVFYuHChW29pmkpXVxcqKipsYncyNIVEJpPZJIXEXkilUtTV1WHGjBlu6e1oDUzPH1MBnzRpEivgCwsLIRAI2IliV90Sb2trw5VXXomXXnrJruJvNPbu3YvNmzfD09MTiYmJSElJwcmTJ7FgwQKnrIfD/XDPpgsOjnFAZWUl3njjDXz33Xf48ccfkZ2djdzcXCxYsAC33XYbjhw5Ar1e7+xl2oWOjg5UVFQgMzPT5l533t7eiIuLw+zZs5GRkQGBQIDy8nKcPHkStbW1UKlUNn0+c2lvb0d9ff2EFH+NjY1Ge/4YAT937lx2gra0tNRljtlApFIpNm7ciGeeeQaLFy92yHO+9tpryMjIwLXXXovOzk4A/RXIgR6Z4y2yk8P+cAKQwy3YuXMnoqOjkZWVhaysLBw6dIj9t6eeegopKSlITU1l/Q1dnZ9//hnXXHMN8vLy2C3AFStW4L333kNhYSG2bNmCgwcP4qKLLsJNN92Er7/+Glqt1tnLtglMEsiMGTPsXpVjUkhmzpyJGTNmwNPTE9XV1Th+/DjOnz+P3t5eo9GH9qK1tRWNjY0TVvwpFIoxBz68vLwQFxeHWbNmsb2RA49Zd3e3Q4/ZQBQKBTZu3Ih//vOfWLZsmc0ed+nSpZg+ffqw/+3duxc333wzampqUFhYiMjISNxzzz0ARo7y5OAwFa4HkMMtGE99MEqlEmvWrMFnn302ZsQeRVH45ZdfkJeXhx9++AHp6enIycnB0qVLXWpL01Ta29vR0NCArKwspwqgoSkkISEhEIvFI1qV2IKWlha0trYiMzNzQmzxD6SxsZFNtLF02tdgMLBm4UqlEsHBwRCLxQgKCnLIBHFnZyeuuOIK/O1vf8PatWvt/nzGqKurw+rVq1FSUoKnnnoKAPDQQw8BAC6//HLs3LmT2wLmMAbXA8gx/nDHPhg/Pz98//33JgkNgUCAP/3pT/jTn/4EmqZx/Phx5OXl4V//+hdSU1ORk5OD5cuXOzwv1hKam5vR1taGGTNmOF0ACYVCREREICIigrUqaWpqQnl5uV2ERVNTE6RSKbKyslz65sQe2EL8Af3HTCKRQCKRgKZpdHR0oK2tDZWVlQgICGDtZezx/nZ3d2PTpk247777HC7+WltbERkZCaA/1Wn69OkAgLVr12Lr1q24++670dLSgurqartNInOMTzgByOE2vPbaa/j4448xe/ZsPP/88wgODkZzczPmz5/P/o679MFYUmXi8/lYuHAhFi5cCJqmcebMGeTm5uLZZ59FYmIi1q5di5UrVyIgIMAOK7aOhoYGKBQKlxRAzNBBeHg4aJpGZ2cn2tvbUVlZaZMUkoECyNVeu72xlfgbCp/PR1hYGMLCwkAIQXd3N6RSKc6fPw9fX1/2eNriRqO3txdXXnkl/u///g9XXHGFDVZvHvfffz8KCwvB4/GQkJCAt956CwCQlpaGTZs2Ydq0aRAKhXj99dcn3OeLwzq4LWAOl2Hp0qVoa2sb9vMnnngC8+fPR1hYGHg8Hh555BG0trbi/fffx6233ooFCxbgr3/9KwDguuuuw8qVK51yonYWNE3j3LlzyM3NxVdffYWIiAisXbsWq1evHtFU2ZHU1taip6fH7ZIehqaQ+Pn5QSKRmJVCUl9fj87OTrc2OraUpqYmyGQym4u/0RjqDykSidgpcEvsZVQqFa688kps374dV111lR1WzMHhEDgfQI7xAdcHMzKEEJSXlyMvLw8HDhxAUFAQsrOzsXr1atZI1pFrOX/+PLRaLaZNm+bWAshYCgljPD1Slam2tha9vb2YPn26W792S3CG+DNGX18f6w/J4/FYexlT+mfVajWuvPJKbN68Gddff70DVsvBYTc4Acjhvgzsg3nxxRdx4sQJfPHFFygtLcXWrVvZIZAlS5agurqa2wrBHwIsLy8P+/btg7e3N9auXYu1a9dCIpHYdWKQEILKykoAQGpq6riaTiSEQKVSob29fcQUkgsXLkClUiEtLW3Cij/GgsdV0Gq1kMlkkEql0Ov1CAsLg0Qiga+v77DPp0ajwdatW7F27VrcfPPN4+rzyzEh4QQgh/uybdu2YX0wjCB84okn8P7770MoFOKll17CihUrnLxa14MQgrq6OuTn52PPnj3g8/lYs2YNcnJyEBUVZdMLHE3TKCsrg6enJ1JSUsb9xZOpMkmlUggEAvB4PAiFQqSnp4/71z4UVxV/Q9Hr9ewUuFqtxrFjx5CZmYnFixeDoihs27YNS5YswR133DHhjiHHuIQTgBwcHP1isLm5Gfn5+di9ezd0Oh1Wr16N7OxsJCQkWHXBY/oRAwICkJiYaMNVuz7M9rtSqQSfzwchBOHh4ZBIJG5p2WMu7iL+hkJRFAoKCpCbm4uysjIEBgZi9uzZeP31190mlo6DYww4AcjBwTEYQgja29tRUFCAgoIC9PT0YNWqVcjJyTG7ekdRFIqKihAWFoa4uDg7rtr1IISgqqoKhBB2y1un07GVQYPBMGjLcbzB2Ny486SzwWDA9ddfj4CAAHh5eeGnn35CVlYW1q9fj+XLl8PHx8fZS+TgsBROAHJwcIyOTCbDnj17UFBQAJlMhhUrViA7OxtTp04dVQwaDAY2qSA6OtqBK3Y+hBBUVFSAz+dj8uTJRt8nvV7P9p9pNBqEhYVBLBbD39/f7bcYx4P4oygKN998MxITE/H444+Dx+OBpmmcOnUKu3fvxjfffIOLLroIr776qrOXysFhCZwA5ODgMJ3Ozk7s27cP+fn5aGxsxPLly7Fu3bphU63t7e34/PPPsXXrVkgkEieu2PEQQlBWVgYPDw+TK6ZMokV7eztUKhVCQ0PtnkJiL5qbm9He3u7W4o+madx+++0IDw/HU089ZXRohxAChUKBsLAwJ6yQg8NqOAHIwcFhGT09PThw4ADy8/Nx/vx5LF26FNnZ2QgLC8MVV1yBBx54AJs2bXL2Mh0KM+zi7e2NpKQki8Qbk0IilUrR09Pj8Hgzaxgv4u+ee+6Bt7c3XnjhBZd/zzk4LIQTgBwcHNajVCrx1Vdf4aOPPsLx48excuVKXH311Zg7d67bCgFzoWkaJSUl8PPzQ1JSks0es7OzE1KpFF1dXWy8WWhoqMsJk/Ei/h566CFQFIXXXnvN5d5jDg4bwglADg4O21BdXY1Nmzbh5ZdfRmdnJ/Ly8nD27FlcfPHFyM7OxsKFC52e92svmEnnwMBAJCQk2OU5mHiz9vZ2NoVELBYjLCzM6YJrvIi/nTt3oqurC2+//TYn/jjGO5wA5OBwBl9//TXuuOMOUBSF66+/Hg8++KCzl2QV586dw7Zt2/Dxxx8jIyOD/blWq8WRI0eQl5eHEydOYMGCBcjJycHFF18MkUjkxBXbDpqmUVxcjJCQEIdNOhNC0Nvbi/b29kEpJGFhYQ5/X1taWtDW1ubW4o8QgieeeAJNTU344IMP3PZ1cHCYAScAOTgcDUVRmDx5Mg4fPoyYmBjMmTMHu3btwrRp05y9NIsoLy/Hli1b8N///hepqakj/p5er8fRo0eRn5+Pn3/+GbNnz0ZOTg4WL14MT09PB67YdjA2N+Hh4YiNjXXKGpgUEibezFgKib0YL+Lv2WefRWVlJT755JNxW6Xm4BgCJwA5OBzNb7/9hp07d+Kbb74BgGHZxe4GE6cVExNj8t8YDAb88ssvyMvLw9GjR5GRkYGcnBwsWbLEbQySKYpCYWEhIiIiXMrmZmDWLZ/PZ8Wgl5eXTZ9nvIi/l19+GWfOnMGuXbvGTVWag8MEjApA7vaHg8OONDc3D6oWxcTE4MSJE05ckXV4enqaJf4AQCgUYvHixWzM1vHjx5GXl4d//etfSE1NRU5ODpYvX+6yBskGgwFFRUWIiopi4wddBR8fHyQkJCAhIQEajQZSqRQlJSU2TSFpaWlBa2srsrKy3Fr8vfHGGzhx4gRyc3M58cfBAU4AcnDYFWMVdnfzerMlAoEAF110ES666CLQNI3Tp08jNzcXzz77LBITE7F27VqsWLECAQEBzl4qgP6t7MLCQsTGxiIiIsLZyxkVLy8vxMXFIS4ujk0hKS8vZ1NIxGIx/Pz8zHrM8SL+3nvvPXz//ffYvXs3F+/GwfE/OAHIwWFHYmJi0NjYyP53U1MToqKinLgi14HP52POnDmYM2cOnn76aRQXFyMvLw8rV65EZGQksrOzsWrVKgQHBztlfYz4i4uLczuDaw8PD8TExCAmJgZ6vR5yuRznz583K4VkPIg/APj4449x4MAB7N271237Tzk47AHXA8jBYUcMBgMmT56MI0eOIDo6GnPmzMHnn3+OtLQ0Zy/NZWHSNfLy8nDgwAGEhIQgOzsbq1evdlgSg06nQ2FhIRITExEeHu6Q53QEFEVBLpdDKpVCqVQiJCQEEolkWArJeBF/n332GXbt2oUDBw5wWb4cExluCISDwxkcOnQId955JyiKwrXXXou///3vzl6S20AIQXV1NfLy8rB//354e3sjOzsba9asgUQisct2uk6nw9mzZ5GcnDyuo7+GppAEBQVBIpFAo9GMC/GXm5uL999/HwcPHjR765uDY5zBCUAODg73hRCC2tpa5OfnY8+ePRAIBFi7di2ys7MRFRVlEzGo1WpRWFiIlJQUhIaG2mDV7gGTQlJXV4fu7m6IxWJIJBKXTCExhb179+L111/HwYMHERgYaNPHzs3Nxc6dO1FeXo6TJ09i9uzZ7L899dRTeO+99yAQCPDKK6/g8ssvBwCcPn0a27dvh1qtxsqVK/Hyyy9P6F5gDofDCUAODo7xASEETU1NyM/Px+7du2EwGLB69WpkZ2cjPj7eoourRqNBYWEhUlNTndZ36ExaW1vR0tKCzMxMKJVKl0whMYVDhw7h+eefx8GDBxESEmLzxy8vLwefz8eOHTvw3HPPsQKwrKwMW7ZswcmTJ9HS0oKlS5eiqqoKAoEAc+fOxcsvv4z58+dj5cqVuP3227FixQqbr42DYwQ4GxgODo7xAY/HQ2xsLO68807ccccdaGtrQ0FBAW677TYolUqsWrUK2dnZSElJMUkMqtVqFBUVYcqUKQgKCrL/C3AxGPHHbPsGBQUhKCiITSGRSqWora11agqJKRw+fBj//ve/cejQIbuIPwCYOnWq0Z/v3bsXmzdvhqenJxITE5GSkoKTJ08iISEBPT09WLBgAQDgqquuwp49ezgByOF0OAHIwcHh1vB4PERGRuLWW2/FrbfeCplMhj179uCBBx6AXC7HypUrkZ2djSlTphgVg52dnaisrMTUqVNtvl3oDgwVfwPh8XgICAhAQEAAUlJSoFQqIZVKcebMGYhEIojFYojFYpewVvnhhx/wz3/+E4cOHXJK72ZzczPmz5/P/ndMTAyam5shEokGeWcyP+fgcDacAOTg4BhXhIeH44YbbsANN9yAjo4O7Nu3Dzt37kRzczOWL1+OdevWIS0tDXw+H8XFxdi+fTsOHTrEiT8Ttnf9/Pzg5+eHpKQkNoWkqKgIfD4f4eHhEIvFNk8hMYWff/4ZjzzyCA4ePAixWGz14y1duhRtbW3Dfv7EE08gOzvb6N+M5PnJeYFyuCqcAOTg4Bi3hISEYPv27di+fTu6u7tx4MABPPPMM6ipqcG8efPw3Xff4b333nN5k2d70NraiubmZounfY2lkJSWloKmaVYMOsJ65bfffsMDDzyAAwcO2Cyp5bvvvjP7b0by/IyJiUFTU9Own3NwOBv3G+/i4ODgsIDAwED85S9/QUFBAd566y18++23SE9Pxx133IGHHnoIx48fB0VRzl6mQ2hra2PFn1BofR2ASSGZNWsWMjMzIRKJUFFRgRMnTuDChQtQKpVGK2HWcurUKdx9993Yu3ev2RGFtmbt2rX44osvoNVqUVtbi+rqasydOxeRkZHw9/fH8ePHQQjBxx9/PGIVkYPDkXBTwBwcHBOKM2fO4Nprr8WXX36JyZMnQ61W45tvvkF+fj7Onj2Liy++GDk5OViwYIFNxJGr0dbWhqamJpuJv9FgUkikUinUarXJKSSmUFhYiJtuugl79uxBUlKSjVY8Nrt378Ztt90GmUyGoKAgZGVl4ZtvvgHQv0X8/vvvQygU4qWXXmIHPU6dOsXawKxYsQKvvvoqtw3M4Ug4GxgODo6xSUhIgL+/PwQCAYRCIU6dOoWOjg5ceeWVqKurQ0JCAr788ku3tEo5efIkduzYgfz8fKOiQavV4rvvvkNeXh5OnjyJhQsXIicnB4sWLXLJqVdzcaT4G4qpKSSmUFJSguuvvx65ublITU2104o5OMYNnADk4OAYm4SEBJw6dWrQJOX999+PkJAQPPjgg3j66afR2dmJZ555xomrtIzbbrsN9957L+Lj48f8Xb1ej6NHjyIvLw+//PIL5syZg5ycHCxevNglpl7NxZnibyg0TUOhUAxKIRGLxQgODh7TeLq8vBzXXHMNvvjiC0ybNs1BK+bgcGs4AcjBwTE2xgRgamoqjh49isjISLS2tmLx4sWorKx04iodi8FgwC+//ILc3Fz8+OOPyMzMRE5ODpYsWeKUqVdzaW9vR2Njo0uIv6HQNI2uri5IpVJ0dnYiICAAYrHYaApJVVUVrrrqKnz66afIyMhw0oo5ONwOTgBycHCMTWJiIoKDg8Hj8bBjxw7ceOONCAoKQldXF/s7wcHB6OzsdN4inQhFUfjtt9+Ql5eHI0eOYOrUqcjOzsby5cvh6+vr7OUNw5XF31AIIeju7oZUKoVMJsN//vMfLF26FOvXr0dHRwe2bNmCDz/8EDNnznT2Ujk43AkuCYSDg2Nsfv31V0RFRUEqlWLZsmWYMmWKs5fkUggEAixatAiLFi0CTdM4deoUcnNz8e9//xvJyclYu3YtVqxYAX9/f2cv1a3EH9Dvj8ekkKSkpADoz9596aWXoFarcf311zt04IODYzzDVQA5ODhGZOfOnfDz88M777wzobeATYGmaRQVFSEvLw9fffUVoqKikJ2djVWrVjklXq69vR0NDQ2YMWOGW4i/kWhubsbGjRtx7733or6+Hvv370dwcDDWr1+P7Oxsmxg/c3CMc7gtYA4OjtFRqVSgaRr+/v5QqVRYtmwZHn30URw5cgShoaHsEEhHRwf+/e9/O3u5LgshBKWlpcjLy8PBgwcREhKCnJwcrFq1yiExZeNF/LW1tWHDhg144YUXsHjxYvbntbW1KCgowN69ezF//nzus8jBMTqcAOTg4BidCxcuYN26dQD6Bx+2bt2Kv//971AoFNi0aRMaGhoQFxeH3NxchISEOHm17gEhBFVVVcjLy8P+/fvh4+ODnJwcrFmzBmKx2OZ+cONF/EmlUlxxxRV45plnsHTp0hF/T6/XjwuLHg4OO8IJQA4ODg5nQgjBhQsXkJ+fjz179kAkEmHt2rXIzs5GZGSk1WJwvIg/uVyOK664Ao8//jhrpszBwfH/7d1/TNXVH8fx1+VepTZ0Dht289oyboME2o1K0QauQlODezETubVB0Jia039g5nZZwRYj+rG1pW222dI/xO3eKxcrjX5szFwr1EUbugELUoFbyCD7oWFw7/ePtruV9NX8weXez/PxFzufw/28YXfw2rmfc97XjQAIANNFOBxWf3+/fD6fAoGAxsfHVVBQoLVr12rBggX/OQwODQ3pzJkzcjgcMb0iNjo6qqeffloej0dOpzPa5QDxgAAIANNROBxWMBjUwYMH1dzcrN9++00FBQVyuVxKTU29ahiMl/B34cIFrVu3TlVVVVq3bl20ywHiBQEQAGLB0NCQAoGA/H6/RkZGtGbNGjmdTqWnp18RBltbWzV79mw9/PDDMR3+fv31Vz3zzDPasmWLSkpKol0OEE8IgAAQa0ZGRtTS0iK/36/BwUE9+eSTKioqUkZGhvbv36+dO3fq8OHDMb0p5/fff1dxcbHKy8tVWloa7XKAeEMABIBYduHCBX344Yfy+/06deqUJOntt99WXl7eVXvoTleXLl3Shg0b5Ha79cILL0S7HCAeEQABIB60tLTotddeU2VlpY4cOaKuri49/vjjcrlceuSRR2ImDP7xxx969tln5XK5tGnTppt+JA4ASf8SAGPjrwQATKKiokIpKSnKzMyMjI2MjGjFihW67777tGLFir/1LG5oaJDdbldaWppaW1ujUfINO3TokN544w0dOXJEFRUV8nq9+uabb7R8+XLt2bNHOTk5qq6u1rFjxzQxMRHtcv/V5cuXVVZWptWrVxP+gChgBRBAzDp69KiSkpJUWlqqzs5OSdL27duVnJwc6VoyOjqqxsZGnT59Wm63W+3t7RocHFR+fr66u7tlNpuj/FNcu0OHDqmxsVEff/zxv7aXGxsb02effSafz6fjx49r2bJlWrt2rR599NFps0nkzz//VHl5uZYuXarq6mrCH3BrsQIIIL7k5eVdsfmhpaVFZWVlkqSysjIFAoHIeElJiRITE7Vw4ULZ7Xa1t7dPdck35OLFi/roo4/+b2/hxMREFRQU6IMPPlBHR4fWr1+vQCCgZcuWacuWLfr00091+fLlqSv6H8bHx1VZWans7GzCHxBFsXtUPABM4qeffpLVapUkWa1WDQ0NSZIGBgaUk5MTmWez2TQwMBCVGq/Xfz0eZcaMGVq5cqVWrlyp8fFxffnll/J6vaqpqZHD4ZDL5dITTzyh22677RZV/HcTExN68cUXlZ6eLo/HQ/gDoogVQACGMNnjLkYKIBaLRY899pjeffddfffdd9q4caOOHTum5cuXq7y8XIFAQBcvXrxl95+YmNC2bds0f/581dbW3vTfvdfrVUZGhhISEnTixInI+A8//KDbb79dDodDDodDmzZtilw7efKksrKyZLfbtW3btknfI0C8YgUQQFyZN2+egsGgrFargsGgUlJSJP214nfu3LnIvP7+ft11113RKjOqzGazcnNzlZubq1AopOPHj8vr9aqxsVGpqalyuVxatWqVZs2adVPuFwqFVFVVpTlz5qihoeGW7FLOzMzUwYMHtXHjxiuupaamqqOj44rxzZs367333lNOTo7WrFmjTz75hN7DMAxWAAHEFafTqb1790qS9u7dK5fLFRk/cOCAxsbG1NfXp56eHi1evDiapU4LCQkJWrJkid588019++23qqmpUVdXl1atWqUNGzZo//79+vnnn6/79UOhkHbs2KEZM2borbfeumVH1Nx///1KS0u75vnBYFC//PKLli5dKpPJpNLS0sjzooARsAIIIGa53W61tbVpeHhYNptNdXV12rFjh4qLi7Vnzx7dfffd8nq9kqSMjAwVFxdr0aJFslgs2rVrV0ztAJ4KCQkJys7OVnZ2turr69XZ2Smfzyen06k77rhDRUVFeuqppzR37txrer1QKKRXXnlFY2Nj2r17d9TOJ+zr69ODDz6o2bNn69VXX1Vubq4GBgZks9kic2LxmVDgRhAAAcSspqamSce/+OKLScc9Ho88Hs+tLClumEwmZWVlKSsrS7W1terq6pLP59P69euVlJQkp9OpwsJCpaSkTPo8XzgcVn19vYaHh/X+++/flPCXn5+vH3/88Yrx+vr6yErvP1mtVp09e1Zz587VyZMnVVRUpFOnThn+mVCAAAgA+L9MJpPS09NVU1Mjj8ej3t5e+Xw+Pffcc5o5c6YKCwtVVFSkO++8UyaTSeFwWK+//rrOnDmjffv23bSV1s8///w/f09iYqISExMlSQ899JBSU1PV3d0tm82m/v7+yDwjPxMKYyIAAgCumclkUmpqql566SVt375dZ8+eld/vV3l5uUKhkAoKCjQyMqLe3l41NTXJYonuv5nz588rOTlZZrNZvb296unp0b333qvk5GTNmjVLX3/9tZYsWaJ9+/Zp69atUa0VmEp0AgEA3LBwOKxgMKimpiY1NTXpq6++0syZM6fs/s3Nzdq6davOnz+vOXPmyOFwqLW1VX6/Xy+//LIsFovMZrPq6upUWFgoSTpx4oSef/55Xbp0SatXr9Y777zDx8CIR5O+qQmAAAAA8YtWcAAAACAAAgAAGA4BEAAAwGAIgAAQJRUVFUpJSVFmZmZkrLa2VvPnz4/0rj18+HDkWkNDg+x2u9LS0tTa2hqNkgHECTaBAECUHD16VElJSSotLVVnZ6ekvwJgUlKSqqur/zb39OnTcrvdam9v1+DgoPLz89Xd3U03EwBXwyYQAJhO8vLylJycfE1zW1paVFJSosTERC1cuFB2u13t7e23uEIA8YoACADTzM6dO/XAAw+ooqJCo6OjkqSBgQEtWLAgMofetQBuBAEQAKaRzZs36/vvv1dHR4esVquqqqokid61AG4qAiAATCPz5s2T2WxWQkKCKisrIx/z2mw2nTt3LjKP3rUAbgQBEACmkWAwGPm6ubk5skPY6XTqwIEDGhsbU19fn3p6erR48eJolQkgxkW3SzcAGJjb7VZbW5uGh4dls9lUV1entrY2dXR0yGQy6Z577tHu3bslSRkZGSouLtaiRYtksVi0a9cudgADuG4cAwMAABC/OAYGAAAABEAAAADDIQACAAAYDAEQAADAYAiAAAAABkMABAAAMBgCIAAAgMEQAAEAAAyGAAgAAGAwBEAAAACDIQACAAAYDAEQAADAYAiAAAAABkMABAAAMBgCIAAAgMEQAAEAAAyGAAgAAGAwBEAAAACDIQACAAAYDAEQAADAYAiAAAAABkMABAAAMBgCIAAAgMEQAAEAAAyGAAgAAGAwBEAAAACDsVzlumlKqgAAAMCUYQUQAADAYAiAAAAABkMABAAAMBgCIAAAgMEQAAEAAAyGAAgAAGAw/wNzkqW+5d3YbAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 1% change to priciple point" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "param_error = 0.01\n", + "focal_length2 = focal_length#*(1+param_error) # np.random.normal(focal_length, focal_length*param_error)\n", + "principle_point2 = principle_point*(1+param_error) # np.random.normal(principle_point, principle_point*param_error)\n", + "radial_distortion2 = radial_distortion#*(1+param_error) # np.random.normal(radial_distortion, np.abs(radial_distortion)*param_error)" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:25.715267466530307 max: 389.5702996306772\n", + "image 1 reprojection errors: average:26.07413033212313 max: 345.1051858736134\n", + "image 2 reprojection errors: average:26.77905825498852 max: 261.0804710645033\n", + "image 3 reprojection errors: average:31.2411256416308 max: 637.4945383848378\n", + "image 4 reprojection errors: average:27.790161271191213 max: 308.06463497960056\n", + "image 5 reprojection errors: average:26.06536287967614 max: 397.9434694791789\n", + "image 6 reprojection errors: average:26.024265460862825 max: 407.1200419772698\n", + "image 7 reprojection errors: average:25.761487361273964 max: 465.7899440893637\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.3105e+06 2.21e+07 \n", + " 1 2 5.9727e+05 4.71e+06 6.14e+01 9.03e+05 \n", + " 2 3 5.8113e+05 1.61e+04 2.11e+00 2.41e+04 \n", + " 3 4 5.7987e+05 1.26e+03 3.85e+00 4.33e+04 \n", + " 4 5 5.7960e+05 2.67e+02 5.05e-01 2.61e+03 \n", + " 5 6 5.7959e+05 8.75e+00 5.12e-02 4.57e+03 \n", + " 6 7 5.7959e+05 3.83e+00 1.04e-02 8.75e+02 \n", + " 7 8 5.7959e+05 4.75e-01 2.66e-03 4.40e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 5.3105e+06, final cost 5.7959e+05, first-order optimality 4.40e+02.\n", + "mean reprojection error: 8.804476534026158\n", + "max reprojection error: 134.43002984296277\n", + "mean reconstruction error: 0.2957221497626493\n", + "max reconstruction error: 2.1470788380490564\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:27.672572979921753 max: 421.98365335356556\n", + "image 1 reprojection errors: average:26.482222330367023 max: 243.7938260049054\n", + "image 2 reprojection errors: average:27.98205176852066 max: 487.646548237216\n", + "image 3 reprojection errors: average:27.958075798474027 max: 396.0275208049547\n", + "image 4 reprojection errors: average:25.603930393746566 max: 381.48514565845863\n", + "image 5 reprojection errors: average:25.492941883622553 max: 358.92419654212904\n", + "image 6 reprojection errors: average:25.590260224055356 max: 274.13082469028853\n", + "image 7 reprojection errors: average:26.92086016550025 max: 486.78231690416965\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.1824e+06 1.61e+07 \n", + " 1 2 6.1880e+05 4.56e+06 6.32e+01 8.01e+05 \n", + " 2 3 6.0397e+05 1.48e+04 1.90e+00 4.73e+04 \n", + " 3 4 6.0272e+05 1.25e+03 3.79e+00 4.76e+04 \n", + " 4 5 6.0246e+05 2.59e+02 4.92e-01 3.34e+03 \n", + " 5 6 6.0245e+05 9.39e+00 4.81e-02 6.70e+03 \n", + " 6 7 6.0244e+05 4.22e+00 1.32e-02 8.59e+02 \n", + " 7 8 6.0244e+05 1.05e+00 6.34e-03 1.14e+03 \n", + " 8 9 6.0244e+05 6.84e-01 3.05e-03 3.40e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 5.1824e+06, final cost 6.0244e+05, first-order optimality 3.40e+02.\n", + "mean reprojection error: 9.08150464706205\n", + "max reprojection error: 138.6771680194894\n", + "mean reconstruction error: 0.3437069164261501\n", + "max reconstruction error: 2.1766193766423125\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:23.55414956764999 max: 225.4377553821942\n", + "image 1 reprojection errors: average:28.244429033264634 max: 515.3019181730292\n", + "image 2 reprojection errors: average:26.003801590529477 max: 236.37381382794953\n", + "image 3 reprojection errors: average:28.411380544793786 max: 533.2338911356028\n", + "image 4 reprojection errors: average:27.980874815850527 max: 247.35407583847268\n", + "image 5 reprojection errors: average:28.61135988487796 max: 420.3771084508722\n", + "image 6 reprojection errors: average:26.9321379469487 max: 517.5852199717082\n", + "image 7 reprojection errors: average:26.797784105445167 max: 470.8411920662635\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.5426e+06 2.26e+07 \n", + " 1 2 6.8399e+05 4.86e+06 6.00e+01 7.64e+05 \n", + " 2 3 6.6194e+05 2.20e+04 2.24e+00 4.07e+04 \n", + " 3 4 6.6053e+05 1.40e+03 3.97e+00 6.25e+04 \n", + " 4 5 6.6022e+05 3.16e+02 5.43e-01 4.25e+03 \n", + " 5 6 6.6021e+05 1.04e+01 5.48e-02 5.66e+03 \n", + " 6 7 6.6020e+05 4.84e+00 1.42e-02 9.65e+02 \n", + " 7 8 6.6020e+05 4.86e-01 2.88e-03 7.03e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 5.5426e+06, final cost 6.6020e+05, first-order optimality 7.03e+02.\n", + "mean reprojection error: 9.740427603846872\n", + "max reprojection error: 134.81765098329927\n", + "mean reconstruction error: 0.40522672078015226\n", + "max reconstruction error: 2.1973784072303975\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:29.147579324676055 max: 677.0854945212167\n", + "image 1 reprojection errors: average:29.598680830314045 max: 387.5407828456691\n", + "image 2 reprojection errors: average:28.576506142136264 max: 205.33256736305074\n", + "image 3 reprojection errors: average:31.840795577716253 max: 327.29681474501984\n", + "image 4 reprojection errors: average:29.24422851196969 max: 645.1172682131147\n", + "image 5 reprojection errors: average:30.031989605494264 max: 463.56081807559616\n", + "image 6 reprojection errors: average:28.245106424052146 max: 348.39601041459747\n", + "image 7 reprojection errors: average:28.673339440908105 max: 347.55041655608795\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 6.1199e+06 2.20e+07 \n", + " 1 2 9.5260e+05 5.17e+06 6.47e+01 7.08e+05 \n", + " 2 3 9.2979e+05 2.28e+04 1.95e+00 2.65e+04 \n", + " 3 4 9.2804e+05 1.75e+03 4.59e+00 4.92e+04 \n", + " 4 5 9.2777e+05 2.74e+02 4.62e-01 4.60e+03 \n", + " 5 6 9.2773e+05 3.21e+01 1.03e-01 3.99e+03 \n", + " 6 7 9.2772e+05 1.32e+01 4.62e-02 1.87e+03 \n", + " 7 8 9.2772e+05 5.03e+00 1.67e-02 8.84e+02 \n", + " 8 9 9.2771e+05 2.07e+00 9.70e-03 1.13e+03 \n", + " 9 10 9.2771e+05 1.32e+00 4.25e-03 5.13e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 6.1199e+06, final cost 9.2771e+05, first-order optimality 5.13e+02.\n", + "mean reprojection error: 12.404515858698469\n", + "max reprojection error: 140.14598011621857\n", + "mean reconstruction error: 0.6131294943372346\n", + "max reconstruction error: 2.595954325895775\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length2, principle_point2, radial_distortion2) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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rwXEcampqAKwLQ6/Xi+XlZYyOjkKr1cLlcsHlcsFmsxWtg5M2gZSGShNLoiAUI9NihDAUCkn7Io6so4KQQpEHFYAUClJ7++VCJTWBEEIwMTGB+fl5HDhwAGazeYN41el0qK2tRW1tLQAgEonA4/FgdnYWPp8PBoNBEoSlGH9HUY4zQWDH+28CifW68YJQjBCyLEvPUQolCSoAKWc94o0jl5RvMqVsAikEjuNw/PhxmEwm9Pb2yo7kGQwGNDQ0oKGhAQAQCoXg8XgwOTkJv98Pi8UiCUKTyURvtiqmElLAuZJOEIqenSzLJqSMqSCkUKgApJzFKDnOrRI6c+NTvqKQyxeTyQSTyYSmpiYQQhAIBODxeDAyMoJwOAyr1QqXy4WqqioYDAbZ70tTwJRU5HpOpKohFAWh+Pv4lDEVhJSzESoAKWclcrz9ckHNwoUQgvHxcSwsLEgpXyVhGAZWqxVWqxWtra0QBAF+vx9utxsDAwPgOA4Oh0OKEOp0OkW3T8mNSowAFrrmVIIwFotJFk9UEFLORqgApJxVJHv7KSH+gNI2geRCNBpFf39/zinfQmBZFna7HXa7He3t7RAEAaurq/B4PJiamgIhJKHDONlyRq1COhWVKqYqDTGNqxSpBCHHcRsEoTiphApCypkIFYCUs4bklK+SF3Q1RgDFlO+WLVtQX19ftnWwLCtF/4D1ecqrq6twu90YGxsDwzAJv6cUn0oTM8UW2gzDJFgdpRKEyXOMK+0YUijJUAFIOSvIx9svF9TUBFLslG+haLVaVFdXo7q6GsB6Y4rH48Hi4iKWlpag0+kQCoUkyxl6o1WWSo1alnLNqQRhNBpFJBKRrh+iIBTnGFfaMaVQqACknNEk20MU079ODSngaDSK48ePw2KxlCzlWyg6nQ51dXWoq6uD0WiERqOBRqPB9PQ0fD4fTCaT1FBiNpvpjfYspNyiVa4gFFPGVBBSKgEqAClnLIV6++WCGlLAHo8HAwMD2Lp1K+rq6sq6lkLQ6XSor69HY2MjCCGS5czY2BgCgYDUYSxazlByo9xiKh/UtuZ4QSh+76PRKKLRKID1jEByDSGFojaoAKSckXAch9XVVWl0VLFvHuVsAhFTvouLizh48GDeokgNN9hkIc0wDMxmM8xmM5qbm0EIgd/vh8fjwdDQECKRCGw2mxQh1Ov1ZVw9pViID3FqJH40HbBREE5OTmLTpk0JEUIqCClqgApAyhmF2OgRCAQwNDSEQ4cOlWS75YoAxqd8e3p6zvgbC8MwsNlssNlsaGtrgyAI8Pl8cLvd6O/vB8/zkuWM0+mkljMpUFs0TQ6VtOZkQbi0tIT29vYNEcLkphIKpdRQAUg5Y4hP+ZY6IleOJpAzJeVbCCzLwuFwwOFwoKOjAzzPS5Yzk5OTIIRI6WKHw5FQx0WpHCpJACYjZiDiI4SEEEQiEUQiEQBUEFLKAxWAlDOCZFNXjUZTUgFYyiYQ8eYxNDRUUMpXjRQaSdVoNKiqqkJVVRWA9fPC6/VieXkZo6Oj0Gg0UrrYZrOdlTfaShRTlbjmdKTyIEwWhOLYOo1GI3UZUyhKQwUgpaJJ5+1X6ghgqVLAYsqXEILu7m5FI1pn0k1WRKvVoqamBjU1NQDWj5/H48Hc3BxOnToFg8EgRQitVusZt/+pqMTPuRLXLJLtupBKEAqCgHA4LP0sfo6x2GVMoRQKFYCUiiXTOLdS1+SV4oIcn/KNRqOKb1MtN5Vifm56vR719fWSMbbYYTw5OQm/3w+z2SxFCE0mk2qOydlOJQvAXKGCkFIqqACkVBzJ49xSpfHOpAsiIQRjY2NYWlqSUr6nT59WVCip5XiVeh0mkwkmkwlNTU0ghCAYDMLj8WB0dBTBYFDqMHa5XDAajRv+vtzWP/lQiWKqEtcsosSccSoIKcWACkBKRSGOaOJ5/qwwW41Go+jr64PNZkvo8lWD7+CZBsMwsFgssFgsaGlpASEEPp8PHo8Hg4ODiEajCR3GouXMmX4OqoFKFoBKk04QhkKhhA5kKggp2aACkFIxFHucm9pwu904efIktm3bhtra2oTfqWn0nJKoSdgyDAO73Q673Y5NmzZBEASsra3B7XZjenoaPM9Do9HAZrOhpqYGWm1lXE4rUUxV4ppLhXgtFB8OUwlCcWQdFYSUeCrjikU5q0lu9DjTOzcJITh9+jSWl5dx6NChlKlHNQmlswWWZeF0OuF0OgEAPM9jaGgIwWAQR48eBcMwUrrYbrer1nKmEs8bQkhFfu/LcaxTCcL4cZgAEqaUUEF49kIFIEXVlHKcmxqIRCI4fvw47HZ7RmPnYghAGmXJDY1Gg6E1FsGYCbedt1eynFlcXMTIyAi0Wq3UUGK1WlUlYCrtc67Uc1P0JC0n6QRhLBaTXiMKQq1WC5ZlK/JYU3KHCkCKahGjfjTlu5FiCEA1HN9S+ikqwbG5EMCuR1B0Oh1qa2ulzy4SicDj8WBmZgY+nw9Go3HdbsbugEZvgt1UnikllSimKnHNgDrXnaqGMF4QMgyTkDKmgvDMhQpAiuo4W1O+KysraVO+ydAUsPLwAoEnyKHGKn+e8Jv3u9LOHzYYDGhoaEBDQwMIIZLlzL/8fhCBcBRvP+BA9Sum1Uajkd5kM6BGISUHNUQAs5FKEMZiMYTDYYyPj2PLli1UEJ6hUAFIURWZvP3yQe03jkgkgr6+PjgcDnR3d8u+WZypArCc+/XLY/MYXgzgAxe3w26Ud2nUsAw0bPbzi2EYmM1mmM1mvPNyFxbWIuis1cHj8WB4eBjhcDjBcsZgMBS6O2lR+3ciFeL1oNKoBAGYjHjdZRgGgUAADMOA47iESUvxNYRUEFYuVABSVIEcb79cEcWEWi9OKysrGBwcxPbt26VJFXKptFRpJXDptmo02g2wGYrbvNFebUZ7tRkAYLVa0draCkEQJMuZgYEBxGKxBMsZna486WK1oObvcSYqdd3AungVG0TiG5pEK654QZg8x7hS9/lsgwpAStkplrdfqa1S5ApOQghGR0fhdrtlp3zTbYuiHNUWPc7fXFWWbbMsC4fDAYfDgfb2dvA8L1nOTE5OghACp9MpCcJCOowrUZRU4pqByowAivA8n9ZkP1kQRqNRRCIR6fotCkJxjnElfnZnA1QAUspKMb39xChZqew45GxPTPk6nc6cUr6ptnVGCMDIGjSLJ4DIGoilDqxQBUKUvVkIhOCrj4+hq96K1+6qU/S9iwXLslI6GIDUYex2u3H69GloNJoEy5lKFRlyqVQBWKnrBuSL10yCEFg/l3U6nZQypoJQPVABSCkLpWj0YFm2pGnSbKKskJRvrtuqBDRTz0Lb/xMwQgyEYQEioDbGYHHLrQDaFNsOg/UGjwl3SLH3LCanl4N48OU5vOO8VlRb1htMtFotampqpPMmGo3C6/Vifn4eQ0ND0Ov1CZYz2W6wlXYDrlQhVckRwHzXHi8IxWtUNBpFNBoFsH5dTq4hpJQHKgApJadU3n6lFoDptiemfD0eT94p32QqXQCyKyPQ9f0AgqUeRPtqwwNxz6N68PvA5t2A0anIthiGwd9esVmR90qmWMKEZRhkele9Xo+6ujrU1a1HNMPhMDweD6ampuDz+WA2m6UIodlsrkjxFE8lG0FX4roBZcRr/Gg6gApCtUEFIKWkiI0epfD2K7VISrW95JSvUvtbyL4RQhDmBJj05ZtUoTn9BxCdGdAmdrsKBhuY8Co0M0fAb76iTKsrL501Znzsis6c/sZoNKKxsRGNjY0ghCAYDMLj8eD06dMIBoOwWq1ShLASqeQIYCWuGyhO9JIKQnVBBSClJJTD268cEcB4UaZkyjeZQgTgPz8yjCAn4JOv2QadpjwXV83KMARz6mMiaM1glwfPWgFYKAzDwGKxwGKxoKWlBYQQ+P1+eDwenDp1CoFAAIODg1KEMJ2PoZqoZAFYqQKmFGtPJQjFDFG8IEzuMqYoAxWAlKIjCAIWFxchCAKqqqpKdiEvRw2gIAgghGBkZARer1exlG+qbeUrAF+zux4vTq6WTfwBWE/7CjGATYxCMgAIiQE6U3kWdgbCMAxsNhtsNhva2trw3HPPoaGhQZpSwvN8QoexVqu+20KlCsBKXTdQHvGaypSaEIJIJCI1lWg0Gik6KHYZU/JDfd90yhlDvLef3++HIAiorq4u2fbLYQMTiURw4sQJuFwuRVO+qbbFCwJ+8NwU9rc6sLvJLvtv9zQ7sKfZUZR1ySXWej60I78HcbQk/oIQsLEw+Obe8ixMhfTNrMGgZbG93qrI+zEMA6fTCafTiY6ODvA8j9XVVbjdboyPj0u/d7lccDgcJeuiz0Sl1tLRCGBhpBKEgiAgHA5LPxMFoRghpIJQPlQAUopCcspXo9EkDB8vBaU2S45Go+jv78fOnTuLLnTXo5sEI4t+zHhDOQnAXJlbDeNHR2bx3gvaYDEoc8ngN10I7fRzYPzzIOba9Uggz0EbnEPA3gFt7Y6C3p8QgidH3Gh0GLGtzqLImsvFw8cXwLIM7r5qiyLvl3yD1Gg0qHplJB0AcBwHr9eL5eVljI6OQqvVSulim81WFlFQqZE0WgOoLFQQKgsVgBTFSeXtV+p0LFC6FLAgCBgdHUUgEMCePXtKEuVkGAYsA3ziNdtljSIrhLm1CPyRGPwRXjEBCKMD0cMfgfbUr8HOvbz+M1aDYPNFWKruhYUtbDsEwJ9H3NBrWXz8yuJ0AJeK913UXvTPOB6dTofa2lrU1tYCWG9k8ng8mJ2dhc/ng8FgkBpKLBZLSW6wlSoAKzVyCahTACaTSRBOTk6ivr4eZrOZCsI0UAFIUYz4lG9yo8eZKgDD4TD6+vpQVVWF2trako3sEmsA9driX6APtjpwsFX5lDExV4E78DZg9y1guBCI3oqAZw3E7y/4vVmGwV9d0g5DCY5PsXGZlT2nMpVF+CMx/L8/T+Cuw696EBoMBjQ0NKChoQEAEAqF4PF4MDExAb/fD4vFIkUITSZTUW6wlSoAK0FEpUMQBFXWg2YiXhD6fD40NDRAEASEQqGEhhMqCNeprE+XolqyefuVQwAW2wZmeXkZp06dQldXF6qrqzEwMFCyfax0H8AEdOZ1Sxgou18O09k9PxdYT98/MriMO7qbZDX9rAQ4BCI8ZrxhSQAmYzKZYDKZ0NTUBEIIAoEAPB4PRkZGEA6HEyxnDAZDyvfIlUpNpVZyBJDneVXUf+aLKGBZlpU+AzFCSAXhOlQAUgpGzji3MykCKAgCRkZGsLq6iu7ubukmVwxRFuMFaFPcuItR31jIhY8QgiOTq2hzmVBvV+amXyz8kRgMWlaRLuhiRaZ4geClqVUcbHUUlP49PuvD6FIAvnAMVa8IukzrbXMZ8Q+v2QqNzE0yDIPVmBY/PBnB+y7cAZtBA7/fD7fbjYGBAXAcB4fDIUUI842QV3IEsNKiaCKVHL0EUs8yji9JAlILQnGG8dkgCCvzzKSogly8/c4UASimfKurqzd0+Sq9vYf75vH8uAcfv2orrMbEr6raLkocT/Bw/wIsem3BNXfFiGxOeUL41bF5vOv8NvzPs1PQa1m854JNim9HKU7O+/FQ3wK0LIMDBaTfL99eg/M7XbJrNxmGgTbHU8sT5BCJCQhxPBwmHex2O+x2O9rb2yEIAlZXV6UpJYSQhA5jueKoUgVgpa4bqHwBKGf9qQQhz/MJDYuiKbUYTazUzzMVVABS8iLXcW4ajabiBeDS0hKGhoawY8eOlBMVlI4AtteYcWx6NeXEjlJ3OGdDr2XxrvPb4Cow7Vqsi+vJeT+W/FFEYgIu3FKteF2d0myvt+CO7iZsLbCDWcMyyjXupGF3kw27m2wpf8eyrBT9A4BYLCZZzoyNjYFl2QRBmO6GXalCqpJFVCWvXSTXcyZVU0m8IGQYJiFCWOmCkApASs7EYjFwHAdg4xcmHeUQLEoJMjHlu7a2lpDyLdb2RHY32dPau6ixBrDFqV7z5iu6anDptmroNCz2t+Qu/sIcD6OudPVQOg2LnY2pRZWIQAjcAQ411sqY5OGP8LAZtaiurpY65TmOg8fjweLiIoaHh6HX6xMsZ8RrS6UKwEpdN3BmCMBCSSUIk+9/lSwIqQCkyCY55ZvLiV6uFDDP8wW9R3zK99ChQxn3uZT7qLQAFMeEWa1WVFVVwel0lqyjOZ5iCVuWYcDKLWxL4rlxD/4y5sWbe5ulOjo18OBLczg6s4aPXd6Z87oIIeAJoC2RvcxDfQs4MrGKj17ekbBWnU6Huro61NXVAVj/vnk8HkxPT8Pn88FkMsHlckk33EqjkkVUJa+9WJxpgpAKQIosBEEAx3GyU77JlCsFXMiNI1vKN5lCxcux6VW8OOHF2w63gc1yY1YqokoIwcTEBObn59HV1YVoNAq3242JiQkwDCNFYzKl58pFNCbAF4ml7VZVivYqM0YWg7Ar0FUc4nh85dHTeN2uWhxscxb0Xpdtr4HDrJPS2RwvyG5s+e+nJhHlBfzVxe0luUF1b3LAE+TgzJJ6NxqNaGxsRGNjIwghkuWMz+dDf38/7HZ7guWM2qnU7mWACkA5pBKEHMdtEITi6Dq1CUIqACkZiff2A5D3BaGSmkAEQcDw8DB8Ph96enqg18sTGIWOnnvo2BxCUR5y3kGJSFksFsPx48dhMBjQ09ODWCwmeboBr06EiE/PiRMjshkA982swWrQorPGXNAaM3H/c9MIRHl88OJ2xSJZc6thNNgNCftWbzfgzt5mRd6fZRhwvICVYOERrRqrHlfvWDdrXgvH8J1nptC9yYELNmd/WNnVaMO4O1iym1GL04S3H27N6W8YhoHZbIbZbIbH40FHRwcEQYDH48HQ0BAikQhsNptkOSP3e1pKKtkGppIFYLnKY8SpV/HriBeEJ0+exOjoKN70pjeVZX3JUAFISYt48vI8n1fUL55yCcBcLwShUAh9fX2ora3NmvJNptCo3Cdfsx28QGTZfhQqAH0+H44fP46Ojg4p2gIk1iwlT4QIh8NSdNDv9yf4vRmNRum9CSF48OU56DQsPvWarTmtK5f9unFvPebWIiCEYDUUK9j3b3gxgO88O4Xr9tTjvE6XrL/hBYInRtdwhcUpKw1r0LK459rtBa0zFWa9BmY9i01V8qJiF26pwoXILhTVgiikLBYLbDYb2traIAgCfD4f3G43+vv7wfO8ZDlTrhKGZCpZRNG1F06yIBwfH8fg4GAZV5QIFYCUlMjx9ssFJerxciVXQSZGunbu3ClFwXLdXiGiTMMysj3fCok2zszMYHJyEnv37oXVagXwaioj03sajUY0NTUlGAC73W6cOnUKkUgEDodDqh98/0XtMBZ5CketzYBamwGf/+0wghyPe67dXlAkcFOVCZdtr8aeNB2tqfCGeTw76YfJ6sF1e+rz3nahaFkG71axrU0yMYGAZdYjonJIFUljWRYOhwMOhwMdHR3geV6ynJmcnAQhJKGEoRymxrQJpDyo1cQ6EAjAYlHPbHIqACkJ5OLtlwvluAjKjTqKKV+/359TyjfV9kopcnMVgDzP4+TJk+B5Hj09PRk92GICwfhKEFtqU1+sGIaB1WqF1WqVojGpbr6kqiqn+kFCCKZWOWzJ4cZ5e3cTRpeDOYm/VDdmvZbFlV21st8DAKrNWry9uwZdm3L7u3yJxAToNYU/kJUTQgju+c0QNCyDf3ztNtl/I8dqSixRANZLHLxeL5aXlzE6OgqNRiNFrG02W0nETSWLqEpfu1oFoPjQrQaoAKRI5Ortp3bkRMniU74HDx4saJ9Lac2SawQwGAyir68PTU1NaGlpwZKfQ709/df/yIQXfx5x4/aeJln2Lsl+b2L94NLSEkZGRqDT6VBVVQWXywWr1Zr2OJ9cDOHBAT+c9Wuy5w9vrrVgcxqhmgqOF/C53w6js8aCt53bIvvv0tFg05dkJnMwyuPzvxvGtjoL3nZubvV0hfLy1CqeGvXgXee3FmyHwzAMmhxG1OZgX5NPJE2r1aKmpgY1NTUAgGg0Co/Hg7m5OZw6dQoGg0E6ZzOdk4VQyRFAQH2G83JJNQVEDQQCATQ1NZV7GRJUAFIAQIr6KZXyVQPZUsCFpnyTKbQJJBdyEZvifu7evRsOhwPPjbnx2OAS3nROK9qqUjdp7Guxw2bQoslhTPn7eARC8LUnxnGwxY6Ltq77u6WqHxSjg36/HxaLRRKE8d2cW2pMuHCTCTsaiveUrGUZaBgG1RblasQm3CH8fmAJb+pthjmFcbcSmHQsTDoNegrsHs7nHOV4AgKScixhPrz3wtzS1YUKKUIInpv0Y1ejC13166l6scNYPCfNZrMUITSZTIpcAys5ilbJqDUFHAwGaQqYoh6KlfJVA+lSwIIgYGhoCIFAoKCUbzJKWbMIAsFXHh1B9yYnLtueOrUoRwCmS23varQjypOM4s6k02CXzFo4BsCSL4LHh1ckAZhMsr1HIBBI6OYUi/e1Gg0ONuhhKqLpMsMw+MfXyUs9ZkMUJv5wDDGBQCjCAwAhBE+OuLG1zpJzU02q98pH2PS2O9Hb7ixo24WQbKeS6354QzH87/EFTLqDuLN3PeprMplgMpmkmtZgMAiPx4PR0VEEg0Gpw9jlciU0OeW67jPpmlopqPW4i81zaoEKwLOYQr391E4qASimfOvq6rB9+3ZF91mpCCDDACv+KP44uJS3AIw3sE5ObVuNWly4JbVQy2+9DP7p+q6srxMIAS8Q6DSsVD/Y2toKQRCwtrYGt9uN5eVlRCIRaLVaTIT06GqpRpOzeFYySrGrySZbMOdKTCA4NrOGSU8Ib+4tPGVdicQLPkIIPvXwELQsg8/IFPIusw7vvXATGuzpp/hYLBZYLBa0tLSsd5avreHxgTm0zM6D8FxCh7Hch8ZKTwFXKmqNANIaQErZUcrbT+0kCzKlU77JKBUBZBgGX7p5V97bWllZweDgILq6uqSRW2rgnt8Mg+MFfP66ROEtzoN1Op2oqanBzMwMTBYbnjw6hacHpnDtVpNU3F+sWq1UeIIcvvLoKO7obi6auJODTsPirsOtMChQZ1huQeIJcrAaNLINq0Xi180wDLQsI9vyRiQXT0qGYTAX0uCZOQE37tuEwx1O6SFlenoagiAkCMJ0DVVqjUSd6aj1uAeDQSoAKeWDEAK3241YLAaHw1Hym0Epb0CiSCpWyjfV9kpZA8jx6wJwNcTh/mcn8abeFngXZ7C8vIxDhw7lnbZK5vlxL8IcvyG9GxMIfvD8DM7rdGFbXfa6lp5NDoyvhLJ+/gzDoKmhDh+6xgmLQQvwHNxuN6ampuDz+SSzarFWq1iwzCvHWSj/zGWrYeOletkfhUAI6mypo1pqIyYQfPH3IzDqNLjn2txT8PHnjdzIXyFsrbPgbYdbsaXWkvCQAqxHmLxeLzweD8bHxxOm5tjtdin6VG7BnS9qmzOeKzQCKA8qAM8iRG8/r9cLjuOki1mpEAVSqS6I4ii4F154oSgp31TbkxsBLPQ4zK1F8bXnPHif3Ytqix5roSiefrEP2xrs6O7uTvv0uxbisBri0Jqm+SMVD/XNQyBIWd+3GuJwfGZNlgB83e7cfPIkY2WtIWP9oN1ulxpKlDT/dZh0+Px1yps2K8W//fE0BAJ88Ybs6XeRcgoSLcvgmp21aK9Wf0ofWF/vrsbUkV+NRoPq6mopwh4/NWdkZARarRYulws8z1ekCKzENcejVgFIawApJSe50UOr1SISiZR8HaJAKlVofmVlBWtra+jp6SmJ2JUbAfzV0Vk8ObyCe67fkTKyIwebUQsdy6DWqodDw+FSpxtbtmxBfX1mkXXv74cQ4gT88827ZHd0fuLqLUgVBNOyDP760o58lp+WbMcw3n8wvn7Q4/FIqTmn04mqV/wH1XgTUIq3H24Fn2N0stw39su212R9jZh6f++Fm9DqUv+8XwBgNdqErvdIJAKPx4NoNIojR47AaDRKEcJsYxTVgFpTqHIRBCGjz2m5EJuL1IL6jhBFUVJ5+5VjLBtQunFwgiDg1KlTUri9VJFOuU0g9XYjtBqmoEkZDpMO7ztkA/zLGJiZwYEDB2A2Z4+sfPCSzZhbC+dk52HJU6SWgvjUXEdHxwbzXzESI5r/FmolwhMoNne4UNKZdJeL+bUw6mwG2dM90hGIxsDxBO4gVxEC8H+encLJeT/uuXab5JFoMBjQ0NCAqakpdHd3S5Yz4+Pj0jSIUpQx5EulC0Ce52EwqK80IhQKqerzVu+VnVIwYqNHsrefRqMp+Vg2cbvFFoCi4XFDQwO2bduG559/vqjbA9ZtWwD5TSCHO6twuLOwOayCIMDj8YBlWfT29sqOdDU5jWhypq4NVLqGkRACAvnjvpRYQ7L5rxiJmZ6ehs/ng9lsTvAfzEUQfup/T4ETCO69oUv1EZx0FCsCOLcaxg9fWK8HPa/Ac7vFacKXb9qR9XWeIAeXufzzfrfUmjG6HEzbpMMwDMxmM8xmM5qbmxPKGIaHhxEOhxMsZ9QgXM4EAajG6H+qkYblhArAM5Bs3n5nagRwYWEBIyMj2LVrF5xO57oAKUEx88d/cQIsC3zqyk1F2V6Y4/HfT47jlu5mNDqM8Pv96O/vh16vx+7duxXfnlJ86uEhcLxQVsEkRmIaGhokrze3242RkRHpxisKwmzNQTubbBhZDFac+Dsx58PJeT9ev7+haNuotxuwpdaCnWlq5pTm9HIQPz4yg2v31GNfsz3ja/2RWN6lFnK4cEt1TrZKqcoYfD4fPB4PBgYGpAY9scNYybpWuVS6AFTj+tXYWEMF4BmGHG+/ckUAiyUAxZRvKBRCb2+vdMEs1Y26xqqH3aQt2v65AxxGlgM4PrMGBD0YGxvD1q1bMTc3p/i2lGRnoxUDsz7VCKZ4r7f4G6/b7cbMzIxUPyjeeJMjCHd0N5dp5YXx4yOzCHM8btrXIDsCGBMI/uOJcVyxvRp7sggsAJhdDeNPwysghOCm/Y1KLDsjTQ4DDrU60JmloeTJ4RX8acSNd5/fhvo0HoDlhmVZOBwOOBwOtLe3g+d5yXJGnKud6bwsBmqdpSsXtUYA1ea3SwXgGUKyt1+mE62cEUClhWd8yrerqzyRpruv2SatpRhPeU1OI/7p+i5Mnh7B/HwEPT094DgOs7Ozim9LSfIRTKWepyzeeOPrB91uN06fPg2NRiP5D+ZaPzi/FkaDPX8bHl+Yw0d+PoA3HmjE1Tvr8n4fAPjUa7YiEhOgYRnwkPdgRAjBlCeEPw6tyBKATQ4jbtzXgP0t2V+rBEadBtfsyn5cuhqsmHCHUKXg2L9cyOdc1mg0CXO1U52X8ZYzxYh0qTGClgtqXH+pMlK5QAXgGUByyjfbBf5MSQHPz89jdHRUmnFbboo1CzgUCuFkXx/q6+uxaecOMAwj2UucaSz6ohhY5pDZBrs4yKkfTJ4VmyqiNjjvxyODS7h2d31O5sPxTHrCWPJF8fy4t2ABaNCyUn2a3HNGp2HxpRu7oJHZ8MIyDC5OMwYwG6shDl96ZBTvuXBTzubO2aizGfDmc0o3PYXjBfz0xVlcvbNOsVnTyedlNBqFx+PB/Pw8hoaGoNfrpfNSKaN0nudVJ6ByQY0RwHA4rKoGEIAKwIpH9PZLbvTIRKWngAVBwODgICKRSELKV2kW1iI5pY2UmgQSz9LS0rrfnb0VWkdtwjSE+Jt5NCagb2YNh9pKb+6tJL8/5cbsYhQ38kLO0yKUJlX9oMfjSagf5DhuQ/d1e7UJF2yuQqtrPQIoEIKFtQgaM8xeTmZngxU/eNsBWAzyb2ILaxGcWvDjwi1Vac+BXJpASnX8A1EeIU7A/Fp4gwAMcTz84VhJ1qEE82sRPDexihqbAVdury7Kd1Gv16O+vl6yfAqHw/B4PJJRuvig4nK5YDab81qDGiNouaDGFLbY/a0mqACsUOJTvqkaPTJRyQIwPuW7Y8eOoomdvplV/L8/jeEt57bJ7thVMn1JCMHIyAi8Xi8OHDyEr/1pEseXZvHXl21Oua0nhpbxy6OzsBo2o6uhPD5Tfzy1jOHFAO46rzVv8XDrgXoMjgTKLv5EvvX0JIYXA7j3xq6EWbFi/eDo6CgmJiYwNTUl+Q86nU4cbH01Iv2TI7P4y7gXf3/1lrSzaJNhGAY2Y26X5+89P41pTxiH2hyqtu5JpslhxL+9YWfK333nmSkEOR4X2Ssj2t3iNOIfrtkCl1lXso5Po9GYYJQuPqicPn1aGj0mNjrJnQ5U6QJQjRFMtZlAA1QAViSpvP1yoVJTwKVM+W6pteLSbTVpJwGInJhdAwDsarIrdlyj0Sj6+vrgcDjQ3d0NhmHwzgs2wax/9euaLADP31wFu0lbVm84nYYBw2T2yfMEOZh0rOSXloxBy8KmV8+Fe8kfTWllI9YPOp1O2O12uFyulPWDLpcLl2+vhs2kRb2tOCMIRd534SYs+qIZxV+5jaBz5Q0HGrHkjyI04y73UmTBMIw0mo/juJKLkPhGp5aWFhBC4Pf74fF4cOrUKWlyjhghTNf5fiYIQDVGAOV4tZYSKgArjHxSvsmUstA+nnwFEs/z0sWrmCnfeMx6Dd54qBnRWOb1/vLoHBisC0AljqvX68WJEyewbds2aaoAANRYEyNHyelmi0GLczsK818rlGx2GIQQ3PObIeg1LL6UxuetXOdmOj5x9RZZr0seDRaNRuF2uzE7Owufz4c2oxEzM1xC/aDSWA3aotqdlIN6uwF1Nj2OzBR3O8Eoj9nVsKIPUGoQ2wzDwGazwWazoa2tLWFyzszMDHieT+gwFqdnVLoABErnAiEXtc0BBqgArBiyefvlQrm+GPkIwEAggL6+PjQ1NeWd8s33QvzF3w0hzAn4x2vTF8N/4JIOMEhdl5frGicmJjA/P4+DBw9mLRZW28VNDgzD4KZ9DVKEpJyEOB6ErAv9QojyBPc8Oo3XH0psgtDr9Qn1g6FQCG63G6OjowiFQpLxb1VVVVb/QSUhhCAUA+7/yxTeeLCp4P0vBaUQUj99aRbjKyF87IpOxUS0GkVU8uQcnuexuroKt9uN8fFxMAwDp9MJnudV17BQ6VABSMmLQlO+aiFXATg3N4exsTHs2rUr75Rvuk7NVJxeDqDVZZLqz67oqsWLk96MnZAu86s373wFYCwWk4yde3t7Zd005DScBCIxsAwDk4pu8hdl6RTlBYLfnw7D0hjMu4NWDp/49SkQQvDVNxTWb6xhgBhPMO4O4eI0r4mfBCGm5UT/wRMnTiAWiyXMLy7mDFNCCMZXY3hhYRX7Wx1ZTZQL2Q7HE+jzHHfoC8ekGshSCMCb9jVg2hMuSPwt+iJwmXXS9UMNEcBsxFsdAetpa6/Xi8nJSSwvL2N5eVlKF9tsNtUJ2kqCNoFQciYWi8ny9qsE5PoA8jyPwcFBRKNR9PT0FJTyFUVntgvXrDeMe383hPM3V+Oth9sAAL0dVejNIa2az2fj8/lw/PhxtLe3o6mpKadtZRObf/fLE2AA/Mdt+2S/Z7mJCQTHFjng6Dw+dkWn7L8LcTxMaeoKU3HzvnpwfOGpZg3L4J6rWyWLDjkwDAO73Q673S4Z/3q9Xng86ybfLMsmzC9W+qa7o0aHiw9uRY21eJHH7zw7DX8khg9c3J7z7OThxQD+/fEx3NHTjPM6XSURUg6TDg5T/teZQCSGe34zjAa7Af/wmq0A1BkBzIZOp0NtbS2CwSCMRiOcTic8Ho9UymAwGKRz02KxqOKaUSnQJhCKbHL19qsEWJaVxGw64lO+bW1tBe+33Khjo8OAmw40oXeTq6DtAev1RP/5+Ches7see5rTRy5nZmYwMTGBvXv35nxhkHNcbtjbCL22ss4bo06D9+w3o+dAu+y/6Z/14f/9eQLvv2hT1qYdkVxGdxWbVPWD8Tddo9EoNZTka+shQgiBhmWLPhXjvE4nXp5ay1n8AetTPjZVmbCldj0CXAmRNItBi2t21eJAy6vfdzFjU4mI4jXeCglY9yT1eDyYmJiA3++HxWKRIoTFqm3NFTXVEMdDU8AUWcgZ51aJaDSajGJMiZRvMnLNmRmGwWt21SuzTWY9kuWPpI52ihHOWCyG3t7eoqX8rizQQLgcMAwDm56RjIvlUG/Tw6TToL6EtYUCIQmdwacW/KizGeAyF96gFO/zJtYPzi6u4MWBERiExPnFBkP56ylTsaPBhh152hFZDFr87ZWbpX9XggAEgGt3J14/SmUDUwzS+eiZTCaYTCY0NTWBEIJAIJDgjRlvOVOuc1Otxz0YDEoPeWqBCkAVkTzOrZgnsVhDVsovSrponCiIOI5TXBAVw5w5G0adBp94zfaUvxN9DJuamtDa2loRN7ZszK2G8S+PjeEfX7s1Z++6bKyGuKypuVqbAV+5OXVXcTH48h9GMeUJ4V9fv+5dF+MJ/nhqBRaDBm9ReOqEWD/41NwKQpwD7zp/D4IBP9xuNwYGBqT6weQuznSkElNqE1j9sz50VJskO5t063MHopjxhmWNqisHlZgCFpGzdoZhYLVaYbVapdnafn/iuRlvOVMK9wZAnR6AALWBoWSAEAKO48DzfEmifnJr44qxzXjElG9zc3NRBFG5PA9Tsbi4iOHhYVk+hqNLAbAM0FFT2qJh8WabiygYWwkiGI1hyR9VVADOr4Xx4MvzuGCzC/tbyj/qT6Szxoy51bBU7K/VMLhpfz3sxuLd4K7bW4/VUAxaDbuhfjC+i1OsH5Q7JzbE8fi7Xw3igs0u3HJQfg1qsfAGOfx2YBF7m2zSCLx05+IXfj+CQITHv71hZ1pfyWQEQjDjDaPVJb/D9XcnFvHI4DK+fNOOnFLaahPWuZDPvYFlE89NQRCwuroqTSkhhEgPK8VsdlLjFBBgvQbQZiuPSX86qABUAUp4++WKOA2kmB2HySSLsdnZWYyPj2P37t2w24vzFJ9OALoDUZxa8OPcDlfK4y2mjZX4LARBwPDwMPx+P3p6emTZfjx0bN1f8CNXyPOhU5IfH5nBM6c9+NKNO2TZhBzucKFnkzOnm2OY4/HJ/z2FO7qbcajtVXEX39xSYzVgf4sdm0ssgrPxhgONeMOBRgCv3uQb7PLHvOVDtUWPasvG8ya5izN5TqzRaJSK9s1m8wZRYtCyYF75vxpwmnV4w4HGhIkp6YTU3VdtwcxqWLb4A4BfHZvH7weWcPfVW9BRLS8a88yYB1FegCbHS0ElRwCViKLFP4wA6w2N4sOK2OwULwiVOlZqjQCKU1nUBBWAZURJb79cKUdkTOwC5nkeJ0+eLHoNnLjNVDWAv3x5FsNLAexusm+IWhFC8P4fH4OWZWR30KYjEong2LFjqK6uxsGDB2ULyree24Zcted9T42DZRjcdf6mPFb6KnU2AzQsA6NO3vn47WenUG8z4Lo9udVQhqI8js+uJQjAeLQsgws2l9fcutJInhMr+g+OjY0hEAjAaDRCEAREIhEYDAawDIN/f2NhVji58uTICh58eR733tCV8gEjWZilE4A1Vn3OncwXb62GhmXQlkME8J5rU5dzZONsiwBmQ6vVJjQ7cRwHj8cjZUb0en2C5Uy+x06NU0AAagNDiUMs7j558iR27dpV8guFXEsWpbcZjUbx/PPPFy3lm0y6GsDbelqw4IukTFkyDAMNy6DVVVi9htvtxsmTJ9HV1ZVz8W91HhYdL056AaBgAXj59hpcvl2+rQkIsOyP5rQNo06Dr9+2Z8PP1TYJpNIxmUxobm5Gc3MzCCGYn5/HzMyMVKPlcDik+cWlygZ4ghx4gWT014xHSSFVbdHjhr0NOf0NIQQxgeQ8n1rgeZh849C98AiYsBdC9TbEOi4FTIU7DRSbUkQvdTod6urqUFe3nuoPh8PweDyYnp6G3+/Pu/tdrSngQCBAU8AUSFE/0RC2HE+J2Tpyi8Hy8jLcbjd6e3uLlvJNJl2k02LQojOD6et/FhD5I4RgbGwMS0tLOHTokOwB7IXy9dsLi1bmyzvPbyvq+4c5Pqc0HyU1DMPAZDLBbrdj27ZtUv2gx+ORpkCI6WI59YP5csPehpxEWLkjaf/y2GlEYgLuvmqLbNEKIsDRdx/M03+C1mAEWC00k09D1/dDRC78BITmQ8VddIGUI31tNBrR2NiIxsZGKUAiemOKFirxljPpUGsKmNrAnOUkp3y1Wm3Zoh2lTAGLKd9oNAqn01ky8QeUPtVNCMHLL78Ms9mMnp4esCyLMMev11qVINqZjQdemMbsahgfuXxzRaSnFtYi+PT/DeG1u2pzjtxQUsMLBM+c9uDcDueGKRDx9YMGg0GKwKQz/X161I1fH1/A56/bnnOETC6CIKBvkcOWbULek0UK4bxOF16aWpMv/gBoRh6BZfoJcMZq6MxxaT8uCMOfv4DQDfepOhJY7vrF+Ok5YvTa7/fD4/FgaGgIkUgkwQ4pvq5azSlgGgE8S1Gbt5/YBFJs/H4/jh8/jpaWFtTW1qK/v7/o24ynlCnF1dVVBAIBdHZ2orFxvUkgFOXxb4+NoKPajNt7W0uyjkz8aXgZvKDe2qTkz8tl1sGoZdFVn/7JmRfWX5/LDToXRpYCeHrUg9u7m1IKkCDHY2zSi0OtDtUeVxFCCF5eiOKP01MwaNmE+svklJwYgRkfH5eiF+INV4xq/2FwGauh9ZGDniAHo47NaSKLHAYXg/jf4SCcdSu4Zmetou8th/M6q3BeZw61qIRAd+JniOhsYJikY6EzAxE/tGNPILbzJmUXqiDlFoDJMAwDm80Gm82GtrY2CIIgjVOcnZ2VyhlcLhc4jlOlAAyHw6rz7aQCsMiU0tsvF0oRGRO7fPfs2QObzSYJ4FJSrP2MxgT8+x9HcfOBJnTWmDE9PY3p6WlYrVbpBgoARh2LWqtBGik37Qmh0WHMSawIrwgcVgGB8//u2J/2d2oUL3otm7VJ4f7npsEAePvh4ghsd4BDJManbcp5qN+NowtR3HPtNjQ5SpPuTwXHC1mjcIQQ7K0zYPOmWuxtzhyNiDE6EHMVdr9i+it6vIljGp1OJz7Qu56SYxnghy/MwKBl8S6FSwK2VBvx+h1WXLSlQhqC+AiYwAKI1gGkOmc0OrArQyVfVi6UO+2eDZZl4XA4JDut+HKGxcVFyVZN7DBWiyBUy/1fhArAIlJqb79cKGYEUEz58jyf0OVbrs7jYmwzGOUxMOeDzbCA81x+MAyD3t5evPjiiwlFyAzD4F0XtgMAlv0RfOKhAexttuNjV26Vva33//gYCID/vnO/4vuhRnKN2HbWmHOO/skRSyK97U70tjvT/v7anVXo2aJDY5HHq2UiJhB859kpWA1a3NnTnPG1Rh2L3e3Z049//9AgIryAb9y2Bxr21QjMpk2bwPM81tbW4Ha7MTExAYZh0GWxoKXOpXj0iAHBnnpjVksigRAs+iJFt+TJCqsDNHoQngOrTdHMxXMgKk7/iqjpfpWNeDskMcpmNBqxvLyM0dFRaDSaos7XzoZaG9uoACwS5fD2y4ViCSMx5dva2orm5uaE/S6XAIz/8j12chEPvDiDr75xjzRpIB+cZh2+eO1mDA+eQFVVG1pa1idAZEo5V1v0uGFfIw535BbJaKsyISbkdwHJReiogXy+J5dsza3D+uH+Bcx6I3jbuS2K1JTZDBq0N2W/oRczqqJlGThNOuzLEtXLZQ0fvbwTc6vhlOJavKGKHm9i/aDH48GRIxMwGAzSDTdd/aBc5K75289M4S9jHvzT9dvLKwJZDWKdV0DT/ysQXaI1UoQH/sN9Ia5zXYDCevUp6eB5HkajETU1NaipWXczEP0x5+bmcOrUKen8dLlcsFqtJbk/q1EHUAGoMPEpXznefuUYyQYUR4zNzMxgYmJCSvkmU46TP9kGZtEfBZ+jpcPX/jiK/tk1fOOO/VIadn5+HqdPn8a+PYkm1pmOK8MweP2B3Kct/NWlmzGy5M95jNfgvA9f/N0QPnblVtWOy8qVhbUI9Fq2oJm7Oxts8AZjJW0o+MafJ/DS1Cr+/Y27FK+RE7lqRy0eO7WMLXXWnEy509FZY0ZnjTwrJDn1g6IgzKUrXiBEtgC8bk89HEZtSWdCpyO2+1bww0/AEFwCtHUAqwW4IGKhCGbM23DMX0UFYJFI1QSSyh/T4/FgcnISfr8fZrNZqm81mUyK36vUMo0qGSoAFYQQgmg0mlOjh5iKLbUAVDIFHIvFcPLkSRBCim7sHM9TI8v43l+m8G8ZonnJguz2nhbc3pPbvNaT8z7wZL0GTxAEnDp1CuFwGD09PRvmWxaj6eSpkWX0zfjQUW2BM074ZBvZZjfqYNCycJry/zwW1iJ4eWoVV+yoVURUZCPT8SOE4B8ePgUtw+D/3b7RQ1AuuQgbpWh2GnFsZg3GIorOPw2v4Df9izjY6ki7f/lGIQVCwObwdyaTCSaTCU1x9YMej0eqH4z3H0w3I/aZ0248P76Km7vkecA12A245VD5x9kBADFXY/LA36F58XHY558B+CiItR76/W/DPR1XqKYm7UxETkAl+fwMBoPweDwYHR1FMBiEzWaTIoRK2HiFQiHVzQEGqABUDDHql2vKVxRipRqULcKyrNSYUgh+vx99fX1oa2vbkPItNpPuEKJ85hvTYiCGnx5dxmcammGSMdYsFWLjRDgcxrFjx1BXV4eurq6U+5pu8kghXLq9Frua7AniD8guNpucRnzzTQdkb2dhYQF+vx/V1dVSWqR/dg0jywFcFKuGNs/jpxQMw+Dd57fJGk9XSuRGp3KdlJIrr9lVh91NNnRUZ59ysfxKJLxeZt3ifU9PQcsyuOu83BttUnVwiiPBJicnAQBO57olTfxIsBqrAXotA72GAa+y1JkcYnoHfHvvQrD3r2DXETBaA8AwSHWlD3E8vvj7EdzZ04ztGTreKdnJ1QaGYRhYLBZYLBa0tLRI/rzJDywulwtOp1PWKM9k1DgFBKACsGAKHedWDkNmcbuFRgCnp6cxOTmZNuVbbO7obcUdWaxVprwc/FEBvkgsbwEIrJtYnzp1Cjt37pTqnlKRbvJIIRh1GrRVbXx6VCraGB/VdDqdUlrEarViu9OFQ831qhFdPZucBb9HTCAIRfmUU2CSCUZ5eENc2u7eYhZ3Dy0G8JVHR/GZ18nrLjZoWWypzXyTER9QH+qbh0Agu2PXqGMT5vMWQvKMWI7j4PV6sbi4iJGREeh0OlRVVaHR5cL7LtyEpaWlvB8sy1kDKwgClgIxfO+pMVy0pQpX76xL+1peIAhGBQwtBsouANXasCCXQn0AGYaB3W6H3W7Hpk2bIAiC1PA0PT0NQRASBKGcjBcVgGcgSnj7lWMkm7jdfIVKLBbDwMAAAJQ05ZsP52yyYWc1i7o864IIIRgdHYXH40F3d3dWH6dS+g4qsa1wOIy+vj7U1tZi69atiMViCcarbrcbYyOnEIvFpCiN0+ksWgqr2MeP4wX8+MgMIjGCuw63Zu0e/tgvBhCJCfjvO/bKToE/ObwCm1GLA62pZxzLXmtMAAMGMV7543HD3oYNjUV/GfPgO89O4Z9v2gGHKTFO9ZZzciubyAWdTofa2lrU1q57/IXDYSk66Pf7odFoYDAYEA6Hc0rH/eLoHB7uX8SXbuhCbRnqAgkhqLHqsavRlvVcsBq0+MrNO0q0ssyozQMwV5ReP8uycDqdcDqdANYFptfr3TBBx+VywW63p7w2+v1+KgDPFJK9/Qrp7imVIbNS2/X5fDh+/Dja2l7tfC0G0ZgAQggMBRbMazQaMMjvBhqNRtHX1we73Y7u7m5Zn3EpO50LFUsejwcDAwPSrOL48yE+bSfafni9Xrjdbpw+fRparVayXShVF12hcLyA9/74OIw6Dd5zQZss65iPXbEZE+6QbPFHCMH3npuGhmXw33fsLWi9u5ps+O878q91TIUYAaxJMWt6NRyDoAKTcKPRiKamJqk+a2JiAmtrazh16hQikYgUfXG5XBlLZ7bWWqDXsLCblCmvIYRgbi2CRrtB1jESBAF6rQZ3ZLHlURuVLgCLPQlEo9Ggurpamu+eHMHWarWS/6DFYoFer1flGDiACsCcSU75FnqxLJcAzFWoEEIwMzOjSMpXTiH6e354FATAd996MO/tAPkLMq/XixMnTmDr1q0Jxs7piHA8PEGupBHA+HpDXiBYDXGosmSvTyGEYHJyEvPz8zh48GDGuZoiyRe9SCSSEKURp0TE+3DlQ67fp0hMwKkFP3Y32bI2Keg0LPQaFtfsrMVemV3RYsPIaojbEBVLBcMw+Pz1XTCUYWSZHDKdm1fvqMXVO0o/aSMTDMNIlh2tra1S/aDH48HU1BQIIQnzi+Nv/Hua7fhGAc1CyQwuBPDTl2Zx474G7JNx/oiZoUqj0gVgvA9rKUiOYEciEXg8Hrzwwgv4+Mc/jqamJmzbtg0kh472u+66Cw8//DDq6uqk6Vlutxu33norxsfH0d7ejp/+9KdSGcUXv/hFfPvb34ZGo8HXvvY1XH311bLWTgVgDhRjnFsl1ACKKV/R7LiQlK8oWrIdu2t21SEaK/y45CrIRHE0NzeHAwcOyO7c+uADfQhxPP62xyRtTxCIItM7MiFu66FjcxhbDuA9F3XAmqYj+siEB4trYQjeWbw4z+FvrjsEkzGxq1guBoMhYXC7mC4eGBhQNF0cjPLgeCGt+Dq14Mczpz2oterRKKNOLp/u4ZemVvHChBc372uQlUpUqlauWDAMg98NLELLMriiS12CLxXx14vk+sFYLAaPx4OlpSWpflAUhEpHpjtrzLh0Ww22ZqmzjF93JQqpSheA5XDViMdgMKChoQENDQ244oorMDg4iPvuuw/PPvss9u3bh127duGyyy7D5Zdfjs7OzpTv8ba3vQ0f/OAH8Za3vEX62b333ovLL78cd999N+69917ce++9+NKXvoSBgQE88MADOHHiBGZnZ3HFFVdgaGhI1nWXCkAZ5OrtlwtqjwCKKd9NmzahubnwVIZY85jtGN7avZ5efnpkBb86NofPXNuVl3FzLhHAWCyG/v5+6HQ69Pb25vQ5/93VW3FizgeDbnX9QYEX8NXHRtHkMOLOc4ozoiw+AnjJtho0OoxpxR8AfO2xEayu+fBXF7WgtlYLjULncTHTxR9+8AR4geC+O/em/LsdDVZUWXRFFV1bay2I8URWdLVchDgez415cF5nVUZ/Q1FMzXrDJVxdYWR6YNRqtRvqB+P93SwWS4K/Wy5MeUKY8YZxbse62DRo2azj6MIcD62GhZaV7+/qC8fwN78YwF9f0oFdTRszKy9MeAFC0CNjeosSVLoAVJPwZlkWO3fuxKFDh7Bt2zb8zd/8DU6cOIHHHnsMH/7whzE5OYlvfvOb6O3tTfi7iy66COPj4wk/e+ihh/DEE08AAN761rfikksuwZe+9CU89NBDuO2222AwGNDR0YEtW7bg+eefx+HDh7OujwrALOTj7ZcLam0CEVO+U1NT2Lt3r2L1C7mmZANRHgIheXvQ5Sp029vb0dSUu5fYljorttRZcerUGghZN5rWaRh0FNFvLj66WWXR43CGgfWLi4t4U2cEnVv3YEtzLa4o2qqUTRe/6/w2rIZiab93Og2LFqcJ/bM+1Nv0RSn2txm1GUfB5cOUJ4SRpSAu3ZbbFJN0zHjDGFzwo6PGgk1V2YXOXecpO6+3mORyQzcajQmR6UAgAI/Hg6GhIUQiEdjtdkkQZrPe+txvhxGJCTjU5pDVSUwIwQd+0g/tK/WfctN9kZiASEzA6ZVgSgH44MtzAEAFYAUTDAZhtVrBsiz27NmDPXv24MMf/jBisZjs++HCwgIaGxsBAI2NjVhcXASwPoDh3HPPlV7X0tKCmZkZWe9JBWAGSjHOTY1NILFYDCdOnADLsujt7VW0niJXAXjVzjpclcE+QYntzc7OYnx8XBGhG7+9D1++paD3yoYcyxlCCEZGRrC6uopLzuvN6mEVjPJY9IcVNUpOly4+ceIEeJ7PmC6WY/vC8QK+/IdRGHQsvlVg40Wp+PxvRxDieJzX6VKkXrCzxozbu5uzWtvkYgTNCwTHZ9ewr9le1lq2XAQgIQQvTa3hYOv6mq1WK6xWq1Q/KNp5xNcPigX7yefeF67vwkogKttGhmEY7Gu2SwI8zPEgyH7caqx63P+W/Wl//4mri3sdSabUNXRnA4FAIGUtuRIOGqlKnOR+X6kATEGh3n65oNFoEIlEivb+6UgnjJRO+crdLrBez7XkC+OCLTUpf+8Px+AORlN64qUjUw0gz/MYHBwEx3GK2dmU2gYmExzHoa+vDzabDYcOHUp4vT8SS5ku/sjPTyLI8bjvzr3SyLJglFfMB1BMF3/nyDKOTWvw9Vv3IOBbS0gXRyIR+Hw+2elinYbFRy7rQKND3bV38Xzpxi4s+CKKNYuwDCOrSSWXc/MPg8v4/nPT+OjlnTjUVpilTSGkE62pzsunRj34xp8n8J4L2nBR0ozoZDuPWCwGr9eL5eVljI6OSqUKLpcLNpsNNVZ9ym7pTHzo0g5pzT8cCOOx5XF84pptOb1HMnI+VyWhEUDlCQQCBU8Cqa+vx9zcHBobGzE3NycJypaWFkxNTUmvm56elp3FogIwiWKnfJNRSxMIIQTT09OYnp5WNOWbTDoBGOMFfONPp8EJBOdvrk553L/0yDCC0Ri+eOMu2XNc020vGAyir68PjY2NaGtrU+xzZhgG0RiP+5+dwHV7G4taN5ZJbK6traG/vx+bN2+W5l+KjCz68fDxBdywrwEdNYkF7Z+6ZgsGFwOS+HtpahV/GfPgloNNGW+Gy/4odBp5IgRYFyxgAINOC2NSuvjFF1/MOV1cqOdeqXGadRsmu5QKuef6BZvXU457mmx49rQb9XZjyUfoAam7aR/uX8DQQgDvuaAtoTa4e5MDb4u1oEdGyl6r1aKmpgY1NesPnGKpwvT0NHw+HywWi9RQkmv9IMMw2GRncO5WZVL8paTcTRRnIoFAoOBhCddffz3uv/9+3H333bj//vtxww03SD+/44478NGPfhSzs7MYHh7eUFOYDioA44jFYop4++VCuWoA4/dNTPlqNBrFU77JpBJkvEDwtvtfAsswuPemXWmP+wcu7sC0NyxL/PECwdxqGDWmjdtbXFzE8PAwdu3aJUUDlIJlWZxeCeE3/StwmPW4cV+jou8fT7oU8OzsLCYmJrBv376U5qMNDiO21JpRb9/YNdviMqKt+tWb/KYqE6Y8oaxi5W9+MQCWYfA/b94na+1/dUl7yp8bDAbodDrs2rVLquEqRnex0syvhfHYqRXcvL9BEs9qJJcUsNWgxTU7a0EIwbEZHwwLgbIIwFRrPtjqQJgTNkQATToNrpTR2fzlP4xicN6Pb7/p1eai5FKFYDAIt9uN4eFhhMNhqX5Q7jiwi5q16M5Ql5sr+c5xzpVKjgCq1XonVx/A22+/HU888QSWl5fR0tKCz372s7j77rtxyy234Nvf/jba2trws5/9DACwa9cu3HLLLdi5cye0Wi3+67/+S/a1kQpAKO/tlwvlqgEUESNF+TY/5EoqAahhGWg1DC7ZWoMmZ3orjwaHEQ0yrD4A4HcnFvDnkRW894LWOFsWASMjI1hbW0NPT09eMx2zwTAMNlcZ8IUbd6HVlVvUIJ9txUcABUGQZlf29PSkTWlbDVpcu1eeMK226HHD3oasr3v3+W0wKix84mu42trawPO8NENWTBe7XK6E2cWlRrwpe4MxRDgeHE9QjIydOxCFw6STZV6tNAzD4C3ntECnSb1tQgh4grwbtbKRSvg0OYx4w4H8H65OLfghIH00NH4+rFg/6PP5EsaBxc8vTnfDVeqcJITg7d/vg92kxdfeuEuR90xHpQtANa4911FwP/7xj1P+/LHHHkv5809+8pP45Cc/mfO6znoBKAgC5ubmJH+pUt9EyiUAxVT3iRMnipryTSZdSva7bz2k6HbO31wNs16DRocRi4KASCSCvr4+uFyuDfVwSiJefDbL9ApLxYnZNVgMWrRXZ462iAIwFOXxzu+/hG5XGDceaMGOHTtKfh6fv1m5SEc8339+GizD4M6eZmg0GikdDLxquDo1NSWl7MTf5zIyTAm6Gqzoasj/OzSyFMA9vxnGF2/oQnPSQ1AgEsODL8+jo9qEKws0as7XIiNTDeh7fnwcIU7A/7x5X1FEICEEq2EeH//BMXzi6i1Z5x3L4dtvkhep5gWCrz0xhv0tdly6rQYOhwMdHR1S/eDKyopUPyimi202m+K1wOu16ECNpfhlA2oVUXIo9hSQfFEiBVwMzloBGO/t5/f7pQLgUlMOASj63fE8X/SUbzKlqnl0mnW4dHsteJ5HNBrFkSNHsH37dqnep1jI6czNBCEEn/vNKWhZBj+4qzvrtggh8K16sbq2BqGpHh0dHTlti+NJQkpdbekTJk0X5U9enMX/9S/iG7fvQUNDQ0K6WGzscTgcUlG/Gm8K8QSiPAjW/fySsRjWbWg6qosbUc6XS7dV4w+Dy7LFH8cLePePjuO6PXW4eX/2KB4hBIHoulXKjDesiACUC8sAHE9wejmIS+N6OVLVD3o8Hql+0Gw2g+M4BINBmEwmRb5X35EpWguFCkDloaPgVAQhBBzHged5MAwDnU4n1f6VmlI3gcSnfIPBYMm/LKWclSvOEQ2FQrjwwgtLEhUqVAAyDINPv247LHp5X825uTn4/X58/53n4vh8CBwvyLat+Juf92PWG8b9bz1Y0MxlfyQGABlNqPPlTb2pO9Gj/PoxFsVrpnTx2NhYygiNmtjXbMf337o/7e/3t8gbXZeNYtSR3d7djNu75TsGaFgGHC/ghYlV2QKwzWXED992oJBl5gXDMPj4lZuzvi5++oNYP3j06FGMjIwgHA7DZrNJDyPFKD1REkEQFHFEKAdqFa80AqgSUnn7aTQahMPlccYvVQSQEIKpqSnMzMxIzQHj4+MlKywWkSMAP/jAMWhZBl+9JX9PN47jcPz4cZjNZpjN5qKKv7UQhyeHl7G51goHyxb8MLGzMfvNPhaLYXl5GWazGT09PTg578eRCS/aqsxZU8cil2+vxU+OzBQk/gDgpy/NgQHw9sPFmXiSijf3tuDNvS1pf58uXRzf4VmudLFamF0NQ69hc7Y6KRSWYfCDHMRcIdeoaW8IjXZjSWsnxfpBvV6PvXv3JtQPzszMSPWDLpdLdc1MgHpFlBzUGgGMRqOqFP5njQDM5O1XzkaMUnQBJ484E78gYgqx1AKQ53nEeAH3PTWBK3fWbaiXcweigAwD1XSIUc7Ozk40NDTgmWeeKXDV6Tk2vYpfH5vDCxNe2I1a/PNrmjPW/igxHzgQCKCvrw9msxltbW1gWRbb662otRlQk4PtzOv2NOB1e7I3eGTjiu01UFlAbQPJEZp06WKn01mx0Q853+X413z8lyfBsgy+l8GEONXfCwQlFVT5XqPm18L40QuzONzhwoVZRrj5wrGsJtr5wrIsHA5HQv1gqmamXKPTAiHrdkoKU8kCUM1rV1vWAThLBGA2b79yCsBib1sUQx0dHdIYmeRtl/ILI0YAw5yAl6a8EAjB+y9JHIj9o3f0ZHyPUJRHiONTeuxNT09jamoqrQWK0rRXm7GryY5buptRbzMi4nOnFYCPDi7iG0+O42u37M3Y7ZwJ0cJmz549WFhYkLal1bCoU2AMWvLN9vcDi/jhC7P4xu170jYCtMkYPaYmMqWLx8fHwbKsFB1UY7o4FV/+wyj6ZtbwP2/el7EEIP7c/NAlHTkbfL/nx8cRiPK4/y37N9T88QIpijDMVwDW2Qy4bHs1uurXa6/+60/jeG7ci+8kNauMrwTx4yOzuH5PfcpRbEqj1Wo3jEr0eDyYmZnB2toazGZzgv9g8r7HBIJpTwif/N9T2FZnwT++tjCj6WTULKKyocYIYKmDLLlwxgtAMeqXaZybVqstmwAs1omRKuWbTDlMqNlXUqRWoxZfvnl3XhMmvvC7U4jGCO69aad0/Hiex8DAAAghijW2THtC+JsHj+MLN+5K29XrMOlw84FX7XMW/elrAB1GHbQsk9c+x490Ey1slpaWFJ86knw+TnnCiAn5z2IuBbxA8MCRGVy6vQZNMm2C4klOF0ej0Q2GwGpPFxu1LBiGkfU5iZ9xPvONz+1w4U/DKxu288KEFy9OruJNvc2K14LmewNlGQbdbU7p36cWAxAIQbKbTZ3NgK11FrS4lPtsc/leJkenQ6EQ3G53Qv2gKAj1ej2+99w0jk6tQhAIOmSWe+RCJY+CU+va1SoCz1gBmMs4N41Gg1gsVsLVFReO43DixIkNKd9kymFCHV8DmO8khLec24a/nHZL/xZToq2trWhubt7wRQty+YkkfyQGngDekPyavkz2Dz3tLjzwzszRzVREo1H09fXB4XBssLBR2moimXee34Z3nt+m2DaKwUogioeOL2LRH8VHLuvM/gdZ0Ov1stPFhfD+B44jzAn4jkzz7EyII8iyUeiN6K7DrbgrRa1ng90Ao45V3AsSSL3mKU8IT4+68foDjbKbntL555n1moI8BVOR73FmGEaqW25paZHqBz0ej+TcsMtig3WTGTcf6ipKuUIlTwJR49rVuCaRM1IACoIAjuNkj3MrtxmzkqyuruLEiRMpU77JlLIjV8ltTqwE8fOXZ9FWZcZ2ewynT5/G7t27YbdvbJ54amQFD5yKomtvaL07jxOwvV5eO35Xgw0PvlveSB0RpY/p2toajh8/jq1bt24YJs6ybMnmDquZOpsB997QhQa78rOAs6WLI5EIYrEYNBpNQrpYTk2ZL8IDMj4/JaMHxTpfWl0mvO3c4jQBpfIuHJjzYX4tAl4gyKQ5+2d9aHIYijqSMRXiZxaM8vjm05O4/VAT6vM4P+PrB9vb28HzPLxeL6rcbrz88svQaDQJ9YNKCA2aAlaWYDBYknKkfDijBGC8tx8A2SfxmSAACSGYnJzE7Oys7Pq3cuy3EgLpcGcV/JEY7JEFzM5G0NPTA50udTRxe70Vzdb1+rg7v3MEvEDw8/f0Fi0cr6QB7MzMDCYnJ7F///6Un6fSZrNqwR8lCEb5nFLlpRpRlpwuHhwchE6nS0gXCwYbnp3lsX+TC+e0u9K+VybbF14g+PPICk7M+fHnUTe+dcdexZoUSpGKCnG8YiPxUgngK3fU4rLtNRmjf5GYgN+dXEKVWZcyallMRBHlDXHwBjlMekJ5CcBkfBEBoz4NerduBbCeHfB4PJidnYXP54PRaJTsZsxmc16fdSULQDVa2OQ6BaSUqOtIFUCyt18uJ74aBGAhT/kcx6G/vx8GgyGn+rdKjQBqSAyNkSk46+rQ3r4z43GrtRlwdbsOei2Lf7phJ0Icn9NxFgQCnhDZaSYlonJyR7oV6jmoVv48E8Osbg53ZrB5UQuiIHS5XOu+k4te/PXPB7HJBmzTLmEo6sqruzgSEzC6HEQwun6+mvKoG01FKWqRTsz58Nn/G8ZHL+/AuR3pBbBcUq2ZZRiwaUbTiRi0LG471Igq88bony8cw/seOI6/vXIz9jUr47EYj7jmRrsBn7xmi2I1tP/0+xGcXg7i23fuhdOsg16vR319Perr6xPqB0+fPo1gMCj5D4r1g3KoZAGoxgggFYBFJpW3Xy6UO5Umbj+fC7OY8hUtT3KhXE0ghWxzeXkZp06dwo4dO3Ka3EIIwTaZqd94vvrYCKI8wd9dvVXW5xMvyn59bA7ff24K97/tkOxoVjgcxrFjx1BfX58w0k0QCGZWwwnzhYsRAcx0Ho6tBPHJX5/CV9+wU5GO43QcqNOgt6uwkWepeGHCi7UQh8sVfO/448UwDJqqHbCajHjrxZ3Y32zNu7vYrNfg9u5mGLRsWeb/FkKdVQ+Djt0w0i4fYgKRSnnyocWZukM9zPEIcwKGFvxFEYCiiGIYJu0M5Xz4uys349SCP2X9dHL9ICFE8h88ceIEYrFYgv9gugcSKgCVxe/3q3IKCFDhAjA+5Zut0UPN5GPHIqZ85+bmsH//fpjNuafAyt0EkguEEJw+fRputxvd3d0wGOQLEHGbyReGGC+AF0hGI+T9bU5MrARl34DiHybGV4Kv1CjJ+1u3242TJ0+mFLcvTa3iyeFl3HKoGS2viMBiCMBM+zm/FgHHC3AHuLQCcH4tgj8MLuHmfQ2w5NkN2mBhFUmXJfOvj42BJwSXba+R/XlyvACWYWSLML2WxQ/f/qrJcSHdxfl0i2ejFBHAWpshY3pbLkcmvXh+3Iv9pvwFYDpqbQY8+C5l54/HUywRVWPVo8Yq78GXYRjY7XbY7faE+kGPxyM9kKSqH6xkAajGtfv9fhoBVJps3n6VhCjE0tWxJZOc8s33hK+UFHA0GsXx48dhs9lw6NChnPc3XYT3Xx4dAccTfPI129KeP5dtzy1aFB8B/NBlm/Ghy7KPkRJH1i0sLODQoUMpxcDORht0GgaNcTYnpU4BH+5w4WfvzHzTDEZ5xHiCmKC+2sT/uGUXIrHcxMSbvnsUDAM8cNfBgrefqbs4Go3C6XRWvBm1ktRZDTBoWehYdVpoZEKNth8ajSbBfzBV/aDL5ZICKpWIGiOAwWCQRgCVpNCUr9rIpQZxdXUV/f392Lx5c84p30K2qxS5CkCv14sTJ06k7IKVSzqhdPHWGrgD0YLOH0IIvvrYKJxmHd5+3qaco3LilBa9Xo+enp604tas12BfiyPhZ2psAumsMSvWkCEQgt8NLOHiLVV5RxPjyWfk2bY6C6wG5W8o5TKjVqMwSUdblQnvOK8NL720XPY153rcyhWJWg1x+MSvT+H27iZcsDlzpDBV/aDH40E0GsWRI0dgtVql+tZcMi7lRI0+gIFAgApAJcjF2y/f9y/HhUZOLZ4YJZqfn8eBAwfySvkmU44IoNy6w/gUd6H7m24/z+3MnkqJvNI0otemPtfEBxDxtMlFlIn+hW1tbWhubpb1N8nbVpsAzEYu37GTc3586+lJeIMc7ujJ/fgoweeu216S7cR3F5+Y9WFoYQ1NRs2GdLHL5YLJVFmTV1ZDHL7//AzeeV5rXj6Bxb4ue4IcfvTCDO7oaYYrRW3dbd95CQTAT3KIAuez5tnVMP76Zyfwqddsxd486xLFZhM+xwh8fP3g7Owsuru7pfrBgYEBxGKxihiXqEbPPdoEogC5evvlihgNK8eJnS0Sx3Ecjh8/DpPJVFDKN9V2RcucUvCD56bAEB7btZkFYPzs4p6enuxPdISAmfoL2GM/BOsZA7HUQth7B4TNlwOspiCh+9U/jkLDMPjYVVvTvubDl7+a5s20rTDHSzfA+JFuqfwL5VBpArBvZg2f/c0w/vmmHbKihDsarfj4lZuxN4/xXMv+KKosuqLMSi02n/vdMKIxAde985CULg4Gg3C73RgaGkIkEsk7XVyOh9y/jHvx6OAyejc585o+Uuw1r4Y4hDgBa+FYSgEI5D6ZPJ8IYIxf/y5HYvk/lFsMWvzXrbulf6+GOFgN2pwbiVLVDyZHqF0uF1wuF+x2u2pElxpTwIFAADZb8UcM5kNFCECe5xGNRgGgaClftQpAMQWqRMo3mVJHAJ89vT4nd+uW9Nv0+/3o6+vDpk2b5EXFCIHmma9Cc+wHIACgMYAJLELzh78HM3Qh+Nd8paD9PNxZBZNO/sUtnSi7/9kJ/PTFWXzrTfvhX5yCz+eTRrrlSykE4JIvAqtRq4inm4ZloGEAufcilmFwOA8bkZVAFO/6UR/2Ntvx2dcpOye1FHzjtj3whjgpmsMwDCwWCywWC1pbWyEIQsqbcXV1ddZ0cSkeGI5MeNE/58OdPc3QaVhctq0aW2st2JTnzOhiC8D2ajM+dkX6CTL51H++4ydDsOkIvpvD6ddWZcpaY5sNXiAIRHnYjVpEYgI+8uAAjDoWX79tT0Hvm2pcotfrxfz8PIaGhmAwGKQItcViKVvKXo1NIIFAIOtQhnJREQIQKJ7wEynnPOBU3bjFSPkmU+oawH+/ZQ8IITjywvMpfz87O4vx8XHs2bMn7RPToycX0Tezho9cvnn9nJh9EeyxH4LozAArihQ9QAjY8SdBTv4aDLMl7xvfRVtrcnp9vNgMRGIIcTxqrAbsaXbgl0fnMH6qH7VVThw8eLDg87nYAlAgBO/+8XHoWAY/LfDGBAC7Gm2KvE82qsw6nNvuxE37S3vRXfJFUKuAPY7TrMs4JjE++gK8Wsw/MzODtbU1mM1m6WadKl1c7JtzOCZAECBFnXQatuC60LwMjQkpWwSYAPCEi/twfe/vR1Bj1SeMavz4r04izAn46ht2wqBlcU67E+d1Fu7FmIxer0ddXZ1Uly36D46Pj0sRL7HDuJT1g2oVgLQGsABK0ehRTjPo5G1Ho1H09/crnvJNptQRQK1mvRs3WbTEGx/39vZmjML+eWQFHP/q37PHfwIQIU78vQLDABod2GM/ALv3npLtZ7wo++6zk+tP4ZdvxmYHg7/dy2NLR2fezSyZtlUMWIbBW3pb0FFTWTVnDMPg767aUtLtjS4F8KcRN67YXoO2PCNd+ZJczJ+cLhZrt0Sz6mJfSy/YXJW1AaHY/KZ/Afc9M4Wv37YbDfbC/Qhz5b9v7oDP5yvqNrwhDqvhxBn2b+5tRv+sTzKuf8+Fm4q6BhGTyYTm5mY0NzeDEAK/31+2+sFyNwwlQwVgBaDRaBCLxbK/sEjbFgWgmPLdsmUL6uvri7rdcjSBJH85g8Eg+vr60NjYmGB8nI7PXrcj8f28E4AmTRpVowezNlvS/Yzf1usPNGE1HMPMzAympqbSjnQDgIW1MKY8IXRvkv+0XooU8E37lS07yJXhxQDq7QbYFRqDFk8wyuP3A0u4fm99wWbLLS4TztnkRKND2WjHlCeEZX8Um2st0LJMVm/ATOniiYkJhMNh6Zyx2+2qu1kmIxCCf3wmjO6FU7jnWvkNOS6LHhqWgVkv/7zheAGEIG3DVy6kml8MrJcnfOvpSbzjcGvB0eJ7b9yx4Wf7WxzYn+QWkAuFmG6LMAwDm80Gm82GTZs2SfWDov8gwzBSdFBN9YPFggrAAinFRUoNEcCxsTEsLi4WLeWbbrvlQmyE2LVrF5xOZ17vQewtYFZGAF2Kp3w+ClgbStosEb+tOpseK9OjWInFMo50A4B3/eAoojEBD73vnIzG1PEUMsHGH47BqpComvGG8U+/G8GXbuxSbF4tAERjAp4adaPGqsd1e5R/GPr9ySX8z1+m0Ow05tWcEI9By2JXHs0q2fjwgwOI8QJu3t8AnYbNuRs6OV184sQJGI1GzM7OYnBwMGu6uNT0zazhpalVvLm3BRqWkVK4c6uRnN5HjmdlMrd/52UIIPjFu7pz+rtUpEtF+sIxRGICVsMxRcoFlKYYKdTk+kGO4+DxeLCwsKCq+sFiQbuAK4ByiiFBEDA1NYWampqMXnBKU44IILD+dDw0NIS1tbWCGyGEPbdAM/4nECIATNxxIwTgOfD77izpfooXr/iRbps2bcp6Ufv67fsw6Q4miD+OF/DMaTd6NrlSRn7yFbaD8z585GfH8f6LO3Hd3sIjfMdm1jDlDWHSE8KuRuVEkF7L4rW76mA3Fecydc3OWjQ5DDjYln/EpNh89Q07seiLos6mV2SkmOgvaLfbs6aLC03V5ZNuHloMIMIJCY1Cnz3PiJ6evQWtRQ6Xbq+GJ6CMK0K6fW+vNuMfX6vexqRS1NDpdLoN9YNidFCMlonnYCpT/EqDdgFXAOUSgB6PB2NjY3A6nejq6irptsuxz5FIBMFgECzL4tChQwU/7ZGWc8DvvBnswC9eqfszAAIH8DGQll4IO28Ee3oipQCcdAfxsxdn8P6LO2FScOxWLBbDiy++iJ07d0qRl2y0uEzSiDeR+bUIXp7yotqix+6mjVYx+QrAJocRRp0GOxUSa95gFDfuqcfOBuXTHMUYCSdi0mlwTnthBfLFjiy3ukwJ85+VIH52caZ0cbpRYXL421+exOhSAD995yGpm1kObzhQvm7JD1zUrth7qbEZQQ7lWLfJZILJZEJTU5NUP+jxeBIm5IhR7EwPJWq1xKKTQArkTEwBE0IwPj6OxcVFbNmyBX6/v2TbFil2ZIwQglMLfmyvt4JhGHg8HgwMDMBgMGDLFoWK9BkG/MWfgNB2HjQvfw/M6iSIuQXCvjsgbHvteiNImv2ccocQiPIIx/iCBCDHC9C90uAyPj6OSCSCCy+8sOCn1xanEW/qbYXTlMab7BUBGIryMOpY2d8Tu0mHX773nILWFk+11VDwRBVKacgUlUvXXTw7Oyuruzgeq0EDhmEyir8Qx+OlyVWc1+mqqHPHF47hbd8/hntety1t2j9dDaDaKbdwja8fbGtr2/BQItYPulwuOByOhLWq0QMQoDWAFYFWq0UkkludSb6Is20tFgt6enqwurqK1dXVkmw7nmILwMdOLeG+pybw4cs2o55ZxeLiIg4ePIiXX35Z2Q0xDEjnpYh1Xpry1+lq5c7fUo3zt1QXtOnPPjyIv4y58aO3H8TEyCD0ej3MZrMiqQuGYVBjTR8BYxgGoSiPm//7OTQ6jPjOWwqfV5sPV+/IbV6yHCppZNmZSi7dxcmRGTlpzm8/PYnfDizh396wC9vq1FkjFYkJGJjzYX/Lqw0z/sh6Hd/L06tpBaAgCKqZluGPxGCVOUqx3AIwmeSHEo7j4PV6pfpxg8EgRal1Op2q1i7CcVxBZU7FRB1nqAyKXchfqgigGAWLn20rdzya0hR7n89pr4LXHwFWxhG2mhLqG0t5g083C1gJDm1y4rmxFZw49iI6OzrQ1NSEZ555pijbSoZhGOg16w0Irz/QVJJtnq2shWOwGjSqniwSiQkwZOlgzfd7J6aLf9rnxq+ORfHDtx0AF/InRGYcThdqa6plp4vv7G3BljorttQWv+EtX/pm1vDHU8uosuglI+tGhxH/+97MjSLFFlIxgWyIrvojMdzz22F84KJ2aa0n5nz40iOjeO+Fm2T5AapNACaj0+lQW1uL2tr1h06xfnBiYgI+nw88z2N2dhZVVVVnRP1gsakYAVhsii2GCCEYGxvD0tISDh48mJBCSWUEXQqKHQH0eFfRFJ1Ce2dnwhQTcbulCtfL3c8IxyMcE+BIk3JNRU8dg384xGD37t0ZR7rNr4ZRZzOAfeWi/etjc6ix6nHe5vwjkOJD0a/ed27e75EvL0x40V5lKkono7hfcoXKidk12E26gmrlTs77cfdDg/j6rbvR7Ey8cYQ4Hr84OocmhxFXFSHaqQR//9Ag+md9+NHbDyjaiZ1MiONBAJj0WliNr0Zmnj+9gv8bWcCFgWnEwgGYTKas6WKXWYdrdqrzeIrsa7ajyqxDqyvxnMh2bhbzAXfaG8J/PDGON/e2YHdcBNIXjiEY4TG2HJQEYLPDiBqrHp0yvTzVLgCTia8f9Pv9GBkZQSwWk+oH4/0HdTr513WlUHsmgwrAVyimABRTvlarNWWXb7kaUIp5Yj7ZN4K/+78JtFZZ8JPD6xYe4pdBrQLw5v9+HjGB4Hd/dVjWBX54eFga6Zbp4jK/GsYPnp/CeZ1VOG9zNQgh+PqfxsCyDH7zwcM5749IMaLics6JYJTHZ/5vCAYti1+8u3DLjEI5Or0GrYbFrYfyF4CrIW49zRnd+D006TTY3+JAe4kNnnPhiq4aDC74YTVk/k7F35BOLfjxt788if+8Zbds8+r3X9SO96dolmh0mVHtdGDv7iZoGBS1u7iU6LUsNtfmnp7OVUj5IzEwWJ/lmw2zTgO9hoUjqTu+0WHEf8bNAQbWp8r86+t3yl5HpQnAeARBgNFoRFtbW0L9oMfjweTkJABIM7ST6weLiZpFYMV8Eys1BZwq5VuqbZcDnucxMDAAU0yAXq+HTqsFwzCIcDw++mA/9rXYccgsP+VNCAHHk4LMWeWmgP/q0k5Me0JZv6zRaBR9fX1wOuWNdKuzGXDx1hrsaLBJ6/n2Ww4UPF9X6e/EwsIChoeHYbFYUF1dnXaMk1mvwd1XbVFN6u6m/Y05dZqmMvw9t8OFX7+3J+3f7G9JH93NF0IIHhlcxv5me8Hdzt1tDvzLzTtzutH4IzwIWRcfhdLqMuFNva96FGbqLmYYRooO5tpdXCnketP/l0dPg2GAT8uonayy6PG56+SbYudCJQvA5CaQbPWDer1eeiixWq1FEWmxWEyVjSkiFSMAi43Ss4AzpXyTKVcNoNIEAgH09fWhpaUFLS0t+NPBV79Qei0LDcugwW4EK8hPPX/9T2OYdIfw2eu6YMxTMAU4gqdH1/C2TZkvytfsym42vLq6iv7+fmzbtk2qQ8kGyzLoSbIbaXZmj7hEYwLCHA97li7gQiGEYGRkBKurqzh48CAikUjCGCexyNrpdEo3hwu3FG/UV677lW06RjI/PzoPIhDcnqOpstJ4ghy++scxbK2z4Gtv3CX774JRHjoNI437AoBHTi7DH4mh1WVM+Hky8cLkUJsD//u+9KJXKeJvxIQQxGIxuN1uzM7OwufzZUwXq9XaI54wx+Oe3w7j3ee3ob16/aEonZAihEAg2DB55sb9DdCoIEpUyQIw29qT6wfD4bAUHfT7/bBYLJIgVMoUXc0m0AAVgBJKRuGypXyTKVcNoJIsLCxgZGQEu3fvhsOx0ViXYRh87dZ1M9djxxZlC8BzO1xY9EWyFrdn4oGjy/jDkAfn7w5gW33+7fjT09OYmpoq2aSW67/+F8QEgkc+dJ5UOxiPEgKQ4zj09fXBZrPh4MGDiMVi0Ol0sFqtaGtrA8/z8Hg8WF5exsjIiOTaX11dDZPJpNrURia62xwJ86QLRfwc5tciaHTILzyvsujxmddtxZYcUoyEELzxvhfBsgz+Ny5i+brddVgLxzKKP/Hvy4UvHMPt//MyrttTh/dcsElWdzHLyrc3KhezqxG8NLWGPw6t4K7D69eFdDYw//zoacR4gr+/enPCfu1rTh1h9gY5jLtDRYlAp0KtVipyyHXtRqMRjY2NaGxsBCEEgUBgw3koPrjkWz+oZgsYoIIEYLEvAkrNAna73Th58mROESK1X+AyIQgChoaGEAwG0dvbK+uLkkvzyaFNLhzKYT5uKu48VI/NDgZb87SaEAQBAwMDEAQBvb29si4yStR9fODiDgwvBSTx9/yYGy0uM5peaVIoVAD6/X709fWh85UmHULIhnVrNBpUVVeDGGzYtm0bQqEQ3G43RkZGEA6H4XA4YLU7EdaYsblOGWPpYpd75CK45PLNpybxy2ML+Pc37sT2HB4ycjWiZhgG53W60F6V+ABi1mtkR0LzOS8FQgrugDbpNWAYwGF89RqRyYz65Mg4GAZg+ShWV1dVmy7urDHje2/ZB5f51f1KN1N3S60Fs6vhDb9LFxn88YuzGF8JYmutWVZ9YKFUegQwX/HKMAysVqv04CsIAtbW1uB2uzE1NQVCSIL/oNzt0AhghVBoBJAQgtOnT2N5eRmHDh2qqBb0fMVKOBxGX18fampqsH37dtnvUeoRdHajFnvq9HntYygUQl9fHxoaGtDW1ibrPUTfwUIF4HX7Xp2KwAsERya9ODHnw9vP2wSgMKEk1sHs3bs365iiY9NreHFqFTfsqUetzYTm5mY0NzdLN+u7HhiEJxjD5y8wo6W+GtXV1UWrqVGKh/sX8Iuj8/jmHXtzqh9Mx2t318Ed5NBZU/zI8Cev2Zr334rnpS8cg17LyoqsT3tDeHRwBdftqUO1JX8/M21S1DIV8enix+d1EPgY9uoXN6SLXS5XSaLwcqlL6oZPJ6Ru3p969OK9j4yC4wV86jVbE743d/Y0Y241XBLxB6jLvzBXeJ5XTLyyLAun0ynNqI/FYlImZHR0FFqtVipbyHSt8/v9NAJYCRRysxKbAux2e0ln+SpBvh25KysrGBwcxI4dO6Qh37lss5Qp74dPetA36cXnt8RyupCK+5jLSDfg1aYTJc8DDcvgTb2tCXWQ+QhAQghGR0fh9Xplz2HeXm+FlmVQbU18rXiz/sob9uKp0x70HqiTnph9Ph+sVqvUTKI2I9Rv/HkSMV5Atm+9QAiOTq/hQJwRcCpaXSb8/dUKTbcpMoQQ/PLYPPQaFrd1Z/ePNGo10CfVHJaCy7tqwAg8PNOr2LFjx/rUmxQR6HLafKRDFNrHZtbQaDdsEIjJbK+3Ytq7sQHNbtTCbiydgKjkCCDP80W7zmi12oT6QbFOOr5+UKyVjq8fpBFAhVBrNCGflK+aECOfcgWgGOlcWVnJO9JZ6gjgoVY7ZpY8slNk4ki3paWlvPYx3eSRQkluBsl1O7FYDMePH4fZbMbBgwfTXuiTo5dmvQZ70tQoAcDmWotkldHQ0CClk/1+P1ZWVtDf3w9BEKQLZDYLhmKngOdWw3jD/gb0tjs3pNyS+eXReXzjqUl85rVbcf7mjQ86am5S8AQ5WA2aBOEm1qYd7nDJ9gussepxRxkaZjqqzYhGo1idXV8/wzAwm80wm81oaWlJSNPFjwmrrpZvRl0sBEGAQICHjy/ArNfgI5d1Znx9ushgqalkAVjKtRsMhg31gx6PB0NDQzh9+jR+9atf4bLLLoPZbM5bALa3t8Nms0Gj0UCr1eLIkSNwu9249dZbMT4+jvb2dvz0pz/NKTiRTMUIQLWhhBBK9Z6lFrq5iLH45pbu7u68v2ylFoCbqky4cbtF1rEVRZLRaMx7H4s5eSR5O3IFSCAQwLFjx9DR0YHGxsaUr2EYRjHxFT/Ts729XUqhiKlno9GY0ExSSupsBhzudEkdm5m4oqsGwShfsE1LqeEFgtu+8xK0LIP/e3+v9HPxGpNvPWypyTa7WEzTdXZ2guM4eDwezM3N4dSpU9I5VlVVVZR0cTDKp32oJIRAp9Xgree2pJ3lrUYqWQCWq4Elvn6wtbUVXV1dsFqteOSRR/Dkk0/C5/OBYRhcccUVOP/883O63j3++OOoqamR/n3vvffi8ssvx9133417770X9957L770pS/lvXYqAPMgEong+PHjsNvtBQmheEptjiwi14JGtD/J5GeYDl4g0LAMvEEOTrOu6ALwiq8+DaOOxcMfWDdZlrs9sSmivb0dTU35j1YrdgQrfjvx+yUIJGW38NLSEoaGhrBnz56M00qKSXwKJT6VJ3bciQat4tNsLscvGOUR4nipPu0vYx6sBKJ43e7Utj4alpHdqOEw6bCt3oJnTntQa9XnNCWmnGhYBq/ZVYf9zco05hQTX3i9+S5VRDJdM0UqdDod6urqUFdXlzJdbLfbpXMs13QxIQTf+PMEttdbcdn2GvxuYAn/+thpfPUNO7GzceMxFoVUi7OyHhwqWQCqZe0GgwFXXnklrrzySnzve9/D2toa9uzZg4cffhh33303nE4nrrjiCrzjHe/IOWv40EMP4YknngAAvPWtb8Ull1xydgjAUkTG5NRuiXVhSqd8c03FKkW2ejxCCKampjA7O5uX/clTIyv49tMTeO9F7fifZyfx+gNN2GJMLcgCkRh++Pw0bu9pKWicFQEQ5l59fzkCcH5+HqdPn8aePXuyNkVkoxgCVxAI/ufZCVyyrVZKtyZ/J7777CQ0LIO3Hm4D8GqU2u12b6j3m3IHseiLFNxhLZd7HxnBM6c9eOg93SlTeV6vF263G+Pj4wgGg5ienl6/kWsNMOo0GevPfnNiEWGOxx09zWAZBp/5zTAEgeC1u+oUuW7sa7aj0W6sGPEn8uFLOzb8TI1TCd5434sAA/zuA+ds+F0hs4vTpYunpqYAQCpJsNvtWYUDwzCI8gQnF/y4bHsNNteYodUwaSPDahEjwPoxfOzUCg602rM28ahp3bmiRgubQCCA2tpaXHvttbj22msBALOzs3jsscey3iMYhsFVV10FhmHwnve8B+9+97uxsLAgZXAaGxuxuLhY0PoqRgCWAlGEpTPwHB0dhdvtLkqXb7nMoDOJlVgshhMnTkCj0aCnpyevL5dABByfWcXRKS92NNiwp8mOiDeUcptjK0EMzPkwvOjHwTZnztsSeezD5yf8O1OtnCAIGB4eht/vzzrSTS5iBHA1xOHnL83i1u7mgrv4VsMcvveXKTw35sE333QgYTsiWs260TaQmMo+dOjQhnP6T8MrCHM8DrY5SyIInhxxQxBS38xZlpVSdQDw0ksvQafTYWxsDB/8vQdaDYsf3bEVVVVVKT+fK7bXwB+NSTYl33vLPoQ4+ZGjbBh1Gtmj0srFaogDyzCyHpz8kRj+76UFXLS1qqD5yUrx3gs3Id1HpZRgTe7qFNPF8/PzGBoaSkgXp/O3/Os4Qb21zoLfxKXWi7XuXPnKo6NY8EXx5Ru7pO0v+6P47l+mcHzWkbUWkQpAZQkEAmhtbU34WVNTE9785jdn/dunn34aTU1NWFxcxJVXXomuri7F10cFYByiAEy+yUQiEWn0l1Ip33TbLjXptiumQzdt2oTm5vwLwM9pr8L2ehvO21wjNRJMraUWnTsbbPj067Yn1MzwAsFToys43FGV9zi4dDV50WgUx44dg8vlkjXSLZftEUKwsBbBaoiDO8gVLABdZj3++879GSeIvOXc9chfMBjEsWPHsGnTprSp7FsONYPjM4ukRweX8OU/nMaP3n4ANdbCuusy3SyT0Wg0qKurQ2trK66eGUaTlUUwGMTMzIzkxxUfuXGadXDGebBl67g8E/lN/yIYlsFthzKXLpBX/PzUdI+/cV/6BohiCalipouLue5seEPr6fT4bdfaDPj4lZvRIaPmtZIFoBrXXogRtHjtrqurw0033YTnn38e9fX1mJubQ2NjI+bm5nIux0qGCsA4UokhMeW7ffv2hGLMUmy7FKSKAM7NzWFsbEyRdKhBp8EP39G9YZvRaBTfeHIMDXYDbtzf9MrPGVQlpSgG5314uG8eRi2LczryGz+Wah/zGemW6/a21tnwwUs7FbPP6GrI/lksLy/j1KlTaSeyiOi1bFZBvRaOgQBpozOpcAeieODFWbzr/DZF9vsTcZ53HR0dGyI3oi9cdXW1IlH5aEzA158cx5t6WwoWvaXkkm3Vso2aLQYtbu8u7xg8uZRCSCWni73BKBAN5p0ujn/fQplbDWMtHJNds/r5NDOC92bo4o9HjSJKLmqMAAaDwbwEYCAQgCAIsNlsCAQCeOSRR/DpT38a119/Pe6//37cfffduP/++3HDDTcUtL6KEYCleJqKnwcspnw9Hk9JjJ3LNQ4uXngKgoDBwUFEo1H09vYWzRBUo9GAEILhxQBGlwKSAExFV4MN77ygXdbTazqSBeDU1BSmp6eLNtJNjAAyDAOdpjRRgHjrmu7ubhgMiVGw58bcqLEapPrBaEzA8KIfOxpsKRtHAODm/Y24eX/qjuF0/HZgCQ++PI/edie680zjZ/quJ0duxDFig4OD4DhOaiZxOp153QwG5v349fFFVFv1eHNvS17rLwfZRtBNe0N4YXwVLTk0VaiBeAEoNpMB8ieTnF4O4tHBJbzz/DZZrz8x58Nf/fQE/uqSdty0bz1dmk+6WCnue2YK0ZiAe67dVpLPrRyNiEqhRgGYbwRwYWEBN910E4D1cp477rgD11xzDXp6enDLLbfg29/+Ntra2vCzn/2soPVVjAAsBaIYSk75luKLV+4IYCgUwrFjx9DQ0IAdO3YUdZ/FbX7l9bs3/O6rj41g2R/F565fX0Oqjs1cowJrER6CIIDneZw8eTKnkW75UGqbm1gshv7+fuj1+pQlCoJA8Le/OAENw+Dxj14AABha9OPp0RU4zbqMaWVgvb7sD4PLuHZ3XYIRdSpu3t+A3U027GkqLHIspws4eYwYz/NSM8np06eh0+mk6KDZbJZ1zuxrtuG/bt2Njmp5tXFqbKpIxWf/bxijy0H8Q3fu0Z1FXwSPD63g+r31MGX5/JVGPL6/G1jEVx49jfvu3It6uwHff24Ge5qsONyZOSvw74+PoW9mDTfvb5QV0W1xGmHRa7A7rrM3n3SxoJALwPsu3AR/JFayc0zJaRqlRo3RS9EkOlc6Oztx7NixDT+vrq7GY489psTSAFABmIBGo4Hb7cbAwEDRU76ptl2uJhCv14vTp0/nPPEiX8SavFQXtWV/FISkjwI93DePIxMe/N3V22CSYez80qQXH/pJH25sJ2CYF9DY2Ch7pFu+KGEDQwhBTCBZ06iCIOCFF15Aa2srWlpSR6xYlsG/vmEPqi2v1jJtq7PCYdKh0Z49sr3sj8IXjsEXjmUVgCadJu1g+2Kj0WhQXb0+ig5YH1UoisFQKASbzYbq6uqMdV0Mw2BHQ+5P7KeXgzgy4cW1e+plG46Xki/ftAOjywGQheGcz31PkEOI48HxBLk2Qh+dXsOuRmve5QCiAKy26MEyDKwGLQxaFjoNgxpr9lrPf7p+O2a8YdnpfIdJh/99X/pxdXK6i612J34yGMEIM407ewqLItdY9SUtRVCjiMoFtT2MBQKBgsuoiknFCMBif7CEEHi9XkSjUXR3d5d8lm85IoCEECwvLyMUCuGcc84p2biuTPv6+Rt2ZvzbaqseGpaRNcPUH46BZQCnUYN6XQDbt+8tmcAtVABe+m9PQRCAJz56QdoU7crKCoLBIHp7e6XuxnR0b0r8vV7Lyu4A7awxo73anHVqhlLEH78pTwj1NkNeDUBGoxFNTU1oamqCIAjw+XxYWVmRbtRiGs9uzzzmTQ5algHLMorMFU4mxPEYXwmhq16emXkqXGYdutuceGEh92vp9nqr7Bq0eEaWAvjwgydwVVdNQi1nLogCsGeTE4/81as2MW8/3Jrhr17FatDmtXa5pOoudrvdYAhBbHkKfX3ukqWLlaBSItqVQjAYpAJQKYplsBsOh3H8+HEwDIP29vaSiz+g9DWAYppbo9GgpaWlpLNaCxmVdrizKmvaR+RbT41hZsmDv+/WgvDmkog/QJkU8JVddfjzyEpK8UcIwcTEBBYWFkB0Jry0wOEyZ0GbywjDMFC6lFH8/DPdbNbCMTwxvILtdVb0tjsL2h7LsnA4HFJjjHijnp2dxeDgICwWi5QuTq6flENblaloVjFDiwEcm15DvU2/oUlKzXTWmPGO81pxZZf8JiuBEPzx1Aou3VYNDcuUXZCcXg6iwW6QHdXV6XSor6/HrTsm0NPTo3h3sRwIIVgLx/L2raQCUDnoLGCVI3ZNdnV1IRgMliUNC5Q2AujxeDAwMIBt27aB53kEAoGSbFekFDVysVgMB61r2GY24PA5e/CXv/wl4+sJISAEaaNtuaDEg8onX5u6m4/n+QRvxrd/808YfmEAD7yzB21VhTe0lGqKyRX/8RwA4LEPnZvy94QQ2E1aXLK1GrVFSIGJN+r6+npplqdY/hGLxaSuT6fTWfaU2M4GKxpsBkXEX76f7U9fnMUzYx786+t3yu42Zhkm50aaPwwu44u/H0EwyuP6vfVlFYDBKI9fHptHq8uIWw7mNhlIHKuopBm1XL78h1E8N76Kb925J6vxM6W48DxftGZKJVDvyooMIQQjIyPwer1S12QkEkEkEinLejQaDaLRaFG3ER85OnjwIEwmExYXF0sueosd7RQ9DLfmMNLton/5MwgB/vyxCwu+4WSLcIoj8XJFbNRpbm6WzEVv3a4Hajej1WXCb/vnwRPg2j2lHSwfjPJYDXFZO1HjYYC0dWHxx78URsXxszzb2trA8zw8Hg+Wl5cxMjICg8GQMLe41IJEp2HzmkX8wxdmYDdqcd2e1CPxcuGbT09CIOufWzG5cHMVIpd14oqu9frrcgpAs16D6/fUoyHHY5/uu6+EGbUcXre7HnNrEbjyuMZUKqV4aM0VNa4pmYoSgEpFJ8LhMPr6+lBVVZXQ5avVakseDRMpdgSQ4zj09/fDaDSip6dHetosReQx+SJezAhgviPdWl0mTHlCeV90OV6QBE0642kAmHQHcet9L+DGfY34u6u3yX5/t9uNkydPbmjUcRoYnLd7XfAtrJXn4eXRU8vwBjnc3t0ku9j/0TSRPzWg0WhQU1ODmpoacLyA7zw9jisckNJ4DocjYW6xWrnv6UkwDJMgAPM9v3/3wXNKIsbMeg2u3/vqejNt8/jMGlpdprQPU/5IDIEIn5d4Ftlal3v6Tu5xiu8uBiBZGonnmZympVTsbrLhq2/YlfO6Kxm1Nq+IkWC1UlECUAniU75it6BIuaxYxG0XSxT5fD4cP34cHR0d0hxBkWKnY0cW/bjnN6fwyWu2YfsrRsbFmZW7PtItEAjkNdLtR+9I3/mXjYW1CH78wjSu2VWHrgZbxgeVRocRtVYDrtklLypDCMHk5CTm5+ez+lG+7bxNea2/UC7fVg13kFPM8LpUaWg5PDnixg9fXECdvQM37d8LQRCwuroKt9uNiYkJhMNhsCyLpqYmWK1WVV3sf/bOQ1kbd8ZXgiBAVp/N9eaW0u9bOjEVjPJ4/0/6odWwePyvUz9M/PSlOUQ4Ae+5MLMHYJjjYdCyin12+Qrl5HRxfNMSIUR66HA4HAliJxjl8eb7j+JNvc24KWmqysJaBAYtm1fGoZJQqwBUy3UsHWeNABQEASMjI1hbW0tplAuUVwAWKy06PT2Nqakp7N27N6UhZbEFYEwgGJhdw2ceHsSP39mzYZsxXoC2QOEgjnSrqqrCgQMHSnYT9gY5/OylGdza3QyzXiPVaGU6pjoNi1+/X170i+d5DAwMrHdBxkVt1YbFoC141J1auWhLFe69YTsOtq43j7AsC5fLJUX/+vv7YTAYMDU1BZ/PB6vViurqalRVVZW0sSoVqexDkm9Ib/3eutfYnz5yuCRrypV0N3azXoO/ubwz44SLG/bWYy0cyyj+OF7At56ehMWgxV0yO4vzXXMupGpa8nq9WFxcxPDwcEK6WKs3QCAEs94wBELwt784iSanER+9rAMffvAEBAI8cFf266LaxUom1GgCzXFc0Rp9lOLMvGonIaZ8q6urcejQobRfhHJHAJXctmh6zPM8enp60haiFnufuxpseN/Fnbhgy6vRVlEgPTO6ggdfmsXfXb0V9TL86OIRpwJ4vV6cOHFC1kg3pVNYD740g28/PYG9zXa8+8J26edKRLDC4TCOHj2KpqYmtLa2ppyGIFLuTslCuec3w9CyDD5xzZZyL2UDOg2L8zJ0nYveg+3t7SCEwO/3Y2VlBf39/RAEQSryT47aqIV/vmkHCAo7VwVC8NyYBzsabIpHmjKd25lmCANAtUWftQlCp1m3QyrUuDweQojin7VOp0Ntba10jQsGg/B4PBgdHUUoFMIXLrShutoMPhYDmPXrBMMweOu5rfjmUxP43G+H8enXZi45qeTriBoFoNo7gIEKE4D5nJxLS0sYGhrCjh07UFWV2T7kTBGAwWAwoVkg03ErRUfuO85PTE2K26yzGWDQsrDmGD1a9kfwX0+MobeegTPmljXSLX48m1Lc3tOCXU12dG9KrAUr9JiKXdrJ9X7RmICL/+XPaKsy4yfvWo+mFmO/Ss2jp5YBQBKAakoBy2XCHcJb7j+K77xpLza3t6O9vR2xWAwej2dD1EZsJsmXZX8U1RZdXp958t8Uaq8DAKEoj8GF9dppuRZNckl3boc4XrGpJNmEZK6kM7lXgpenVvFw/yI+fuVmNDc3o7m5WUoXi93Ft7cRuFwGeDweXLm9Csdn1mQ1Aqk1jSoHNa493ykgpaSiBGAuyEn5JhM/C7jUKFUDuLCwgJGREezevVtKH2Tbbqn3WeyS3VJnxRdvyr1YWa8BfF43mCoTes+RN9KNJ4ziFwmLQZvyhpepCSQThBBMTU1hdnY2Zb2f/pU6pZ44U+dKFn4if0xTw1UpMAyDRV8EAiFY8EXR6DDi//oXcajNgc5XojbxI8SGhoYQiUQS5hbLtYpYWIvg9fe9iN5NTvzr6zObppcKi0GLNxxolDWZJ1dSCcDhxQAeO7WMG/bWZ+w8Pzq9Cotem1cjRyEUU4xMuEOIcDzikwDx6eKOjo4N6eKr6gywcHoEAkzGkYh0DrCy5DsHuJSckQJQbso3mUqOAAqCgKGhIakJQm79Uann1hZKKBTCwLFj+NBFLVmjmyKCQPDgUBQvBE7jI1fK77zNl3wiWIIgYGBgAIQQ9PT0pL2YPfPxizZsS41Pv7mQPD0jwq/XZhWb//zTOH760hwe+9A5BY0qA4CeTU78+aPnAViP1GpYQBfnnp3KE87r9eL67wxAEAT85xVWaYydxWKBP8LjtwOLuHBzVYLIqbXpsbfJjredm9+IsWJFVm3G4txKUqVT62x6NDuNWW1OXphYBcswJReAomhdCUQRiPCKGoTfuK8ha8QyOV0sPnjEj0QU6wfja9QqfQ6wGgUgjQAqiJybfS4p32RKPY0jnkIEYLzgPXjwYE5RoXKK3lwRO7h37dqVdfRZPCzLoMHK4nCH/L8phFxFdTgcxrFjx9DQ0JDznOJKTJdmghCCJyfDGAys4PZziztT+KlRNwjZWFNZKHoti5v3N2Z8Dcuy635vBh2iMQG7du2C2+3G+Pg4AoEANEYL/D4dYrHEY8AyDL5+225F16tmUkUAHSadrJTmnT3NJRtfGI/4QPaD52cQjQn4mys6ZZtnFwOTyZQyXTw9PQ1CiFSnqtVqK1YAqlG80ghgCRFtQHw+X04RsHjKmU7LN224srKCwcHBlLY2crerdgFBCMHY2BiWl5dlp/OTuarTjB3N+RV6L6xFwPECWmSaEudyTMV6v2yfX4wX8MCRGRxsc2Bn46uioBI+v1xgGAbbq3XY0lZc8QcAD9x1MOe/4XgBl371Lzh/swtfunFHwWv4Q9x828bGRjQ2NoIQAp/Ph+qVFSxNDGFhTEiYW1zIja7SakYLWavc8W1KI0Yt7+xpRiDKl1X8JZOcLo6vU/V4POB5HlNTU6iqqsqYLlYbakwB0xrAEhEKhdDX14fa2tqcUr5qItc1E0Jw+vRprKysZPWHU3K7xeKfHxnGE0PL+OV7z4Fe++oNLhaL4fjx4zCZTOju7s775lfI/OGfvTQDXiD468s2K7qtqakpzMzMSFNZMr4nwyDM8ZhcCRVVABZaErAa4vDoqWVcvaM25+YekXanDnXW3LpJT8z6UG3V5zy1IVfEdLU7wBVtGwzDwG63w263SzVd8RMjTCaT1EyS6/feGyG48N+exYcv7cAbDmSOUpaTaW8IRyZWsdcuwCDjGkUIwbeensTFW6uxvb68URexCaTGqkdNWVeSHa1WK6WLV1dXMT09DZZlN6SLXS5X2W2NMqHGMhgaAVSYVGJFTPkmd0yeyUSjURw/fhxWq7UgUaQm1sIxECTWTYkj3VIZWOdKugjr0alVnJz34dZDzWnnAN/W3QyOly+yskVzBUFIsOiR8+TKsgzeeUF7ym0pKQALfa8Qx4PjCcKcAGsGLTa/FkHfzBqu2pHZukcOvEDwrh8fh4aBVIdXLBiGwVN/U9xtJBM/MYIQIk2MGBwcBMdxCc0k2c4lHbtu56yOx770DC0GsOyPgrfKiwD6Izy++9wMfnNiCb96T3cJVpieYouRwXk//v7Xg/jWHXtTej3G85MXZyEQgtu7m7O+ryAI0Ov1stLFarM1UuPMXSoAi4iY8vX7/XmnfNOh5hTJ6uoq+vv7sWXLFtTXFz7jUy187vrEdFq+I93SkS6y9dTICiIxHpk+7ppMSgbr6dknhpZxsM2JKos+oyiLRCI4evQo6uvrsWnTJkXOMzWlgBvsRtx2KPv85fc9cBxzqxH0bnJu8I7L9ZhoWAafee1WtDjzi4JXEgzDwGKxwGKxoLW1FTzPw+v1SkX+Op1Oig6mSuGZtcUXyUpw6dZqXLylGpMT47LOB5tRi+/cuReNjuJGgOVQ7PvHpCcEjidYDXFpBeBaOAaTjsXD/YsIczzeeLBpQ7NVMsnCNVO6eHh4WJqRrYZ0Mc/zeZUGFZNAICCN+VMrFSkA41O+uTY9ZENM36lNAIoWITMzM7J879ROjKSu2xC7mYPBILbt3g+iVcZYNl1a9gOXdICQwlLh/giP/lkfjDoNLthSnVZsiqbV+dZrJjO3GsY7f+vFRyNzePN5nQW/Xyn5f7ftwcl5f1rj4FxFrRKRxEpENKIWz6dwOLyh4zOfebLlhmEYaJjcxFRXQ+7RlrVwDC+Me3DR1mrFRhkWOwJ41Y7ajOe7NxjFJ359CgYti3+4Zgs+/9th/OiFGbzlnMyd49nWHZ8uBhK7i4PBIOx2e9nSxWpNAdMaQAVhGEZ6+ihWylej0SAWi5Wt3iHVBS8Wi+HEiRPQaDTo7ZXne6cWRhb9sBq00GtZaVRaKMrjs8+GsXW8D9+484D02kgkgr6+Pmmk2zX/8SwA4PcfKjxikS4tuz6sO/3fRWMC7nt6HBdtqcbu5tS+ik6zDned1yYVnaeKAIoj+ZQU70YdCwaAUavsha8UD0ANdoOser2T835YDRq0ymzAUQuzq2F8+uEh/Ovrd8JeJIuUVBiNRjQ1NaGpqWnDPFlgvXxkdXUVdru9aJ+xeO4rFd0u5rk4thLEwLwfu5rsitWPljOAQAjBZ38zDG+Qw0cv78TWOgveeLAJ52/Ofq/MVUSl6y6emZkp+RQcNTaB0BSwwoRCIUxPTyue8o2n3F6AyX5GYh1cW1sbWlry8/7KRrG85GK8gC/8bgj9s2toc61Pr9Cw6+JIywJXdL1aIi1Gx7Zv346amvWff/CSzoziLBfybW5gGCDGE3hCsYyvs5teja7EC0BBEDA4OIhoNKq4eHeZ9fju9bXo7FR7qXluiMePEIK3f/8YGAZ49mPnl3tZOfH0qAfHZ304MefD4Y7y1Canmif7wgsvYHZ2FoODg7BYLFK6WMn02c9engMhwK0ySgGyUWwxtbvRhvYqExwm5aKj5YxGMQyD6/c2oMaiw45GG37w/Ayu6KrJOhIPKGzd5U4Xq9EHMBgMUgGoJCaTCQcP5m7dkAvlFoDxTzJzc3MYGxtTrA4uHaI4UvqipdWweP/FHVhci8AdjELDMnh5yovvPjuJDxy04qpdtQnTL5KjY9ftTW14yvECtCyT00UkXwGo07D4kMzu3+RtRSIRPPrsy7A6XLho/76i3MjkNIH86PkpfOUPI/jjRy5QfFZrMqshDn/9sxO498YuNOQ43zkZhmFw7w1dRV+zEnC8gLnViGT6e+O+ely4xYU6m3rqknQ6HbRaLXbs2AFCCAKBAJaWV/DV3xzFufUMmuuqpGaSQq4FVoMWsRyapjKRSQAe/srTsBm1eOSD56T8vRw0LKOo+AOKOwpODpduWy8HmPaE8OTIutflW89tzfp3St4DMqWLi9FdrFYfQJoCrjDUIADFqFEkEkFPT0/Ra3eKOQ0keU5uk8MIi14Dl0kDjuMwPDwMALK7YQkh+NLvh6HXsPj41Vtlr6MQG5hcYRgG0WgUR44cwWjUCYNfj4uLdEOQIwAXfdENHdbF4visDwPzfjx72oub9uc3YzV+n/a32BNsgdTK8GIAfTNrMOtrUWPVQ6dhCxbAIjGBYGIliM4a5SInDMPAarXi5EoMPx+egtnZhF1OO5aXlzEyMiJFbMS5xbls97W7lCt8TzUJ5NVfAr5w5sh8Oci4ZoUYXwliYS2Cc+KiyyuBKP750dN453mtWPZH8b3nZ/DeC9qwp1mep6YgCEXrpI1PFxNCsLa2pmi6mKaA86OiBGApnqrKKQBZlkUgEEBfXx/q6+uxY8eOM26f6+1GfOHGXXjxxRfR19eH1tZW2SPdgPVzoMqiw/b63CKi+Rpt58PS0hK8Xi/OO+887GX1RR1rJkcAfvjyzfjw5blFMZf9Ubzu68/j76/eknX0VDzndbrw6/f2ZLWnkAMhBH8YXIJey+KGNNFgNcAwDLbUmmEzalFtUf5hbWw5iCMTXlgMGkWiqvEcbHXgizd0oXeTEzajViq/ECM2IyMjCIfDcDgcUsSmlHYbmSKAz/6tOssCiimkRL7//AwiMQE97U7JaJoX1ssmQlEeLS4jzDoW2+qtMMh8gCpVJy3DMIqni9XYBOL3+4uauVOCihKAQPEnH2i12rIJQI7jMDAwgD179pTU07DU84CXl5fh9XrR1dWF5ubs/lTJvP/i3DteS7GPgiDg1KlTCAQCcDqdJenULpaw1bIMCIBANLfvAsswihXTMwyD8zdXwaRT15N9POK1SK9li9ao0l5tgsWgKUo6WcMyuHz7xhrS5AL/1dVVuN1uTExMSGPsqqurYbVaFXtIFQjB06NubK61oOmV+cflTqfmQzrRemrBj5nVMC7dWl3wPn340o4NU0bqbIaE6TRfuXlnTu9ZLhElp7tYjBCmSxerMQIYDAapAKw0yhEBJIRgZGQEfr+/LIbWpdpncXqJ2+1GbW1tSesjii0Ao9Eojh07hqqqKrS3t2NgYECR910NcZhfi6SdblCsByKnWYfnP36B7NdzvKCYjUb8PolC4GxGp2EzHgcmsAjGNwtiqQOxpW+8yPc8YVkWLpdLui5Fo1G43W5MTU3B5/PBarWiuro64w1aDgIBRpeDWPJzuPmV8gE1WnJlI52Q+t3AEiIxAZdsrS7YiNtm1MKmcHe5WqJoyelisZO9v79fShe7XK6EWlW1rD2eYDCoeru2/8/ee8dHctfn48/MbJW2S6tV79KpnHSqd+fzufeCjcEYxwFsg4EYYsBATAkhJN8fkEAaLUAChNBiQjXYYGMb426f73zqvXdpq7S9zMzvD93M7a62zPZd557XK8G32t2Z2Z2deT7v9/t5ngsEMAycDUy24PP5MDIyArVajYqKipycxNmojvn9foyOjqKoqAj9/f2Ynp7OatUxGlFiWRbPz5rRalCgPEmysbe3h9HRUbS2tkKv18Pn86Xt2J6ZNsLo8KGhpCjiLFy6CWAyN1uPn8avhrdQr5PjokZdStu3OH0pvf7/Egj7BmSPfwzU+imAkgC0D7ShG57r/wWstuHA81M9T0wOHzRFYkgkEpSXl6O8vBwsy8LhcBy4QSczzyUiCdzZXwm7l8bHfjGBz97YUpAEMNo+339JHfw0k1fZwMHIRxIVHosYCARgs9kOzKoGAoG8O0/yUZkcjoIjgJluAWezAmi1WjExMcETh7m5uZy0n0mSzOh27XY7RkdH0djYiPLycn6byZCkH7+6ilKlBNd1JJaCEu0Y/TSLU0tWrFjdeMex+Eq5cHBK7Z6eHr6imc5z9LoOA/Y8/qhCiHRui6ZpjI+Pw+PxoLS0lJ/BiQepiIRKJkJDaWoV3TmjE3d+7yyubZTjY1e+sWIdvQEGP3h1De86Vi14JismPDYU/fhmEC4zCJYGaC8AgNo8g+KfvAnOu58Cqzg4N5nsTdLlo3H9N06BJBBSGSYIAkqlEkqlEvX19QfmuWQyWYiYJB5kYgpPTpnw7JwFLy9aUV2ABDAakZKIyLwWNOUjAQyHSLQ/pxo8q2q1WuHz+XDq1CleXZxqNTpVFMrCpeAIYKZBURR8vsxWIViWxfLyMra2ttDX18dfGHMlQOH8BzOBqcVVfOq3M/jiW46gvLwUI+u7+NGrq7inQ5LwNlmWxfdeWgZBEEkRQL/ff+BxiYjEfSfreRPnRPaFSyw5evRoyNB3OiuqcgkFeYx9SxcB9Hg8GBoaQkVFBWpqamC1WjE7Owuv1wuNRoOSkpKoWbMEQeCmw6nHEtZo5ahQS3FJXX63TZLB78d38O0XVlCqkOC2BEQ10SAZ/hEI794++QsCwTJgfU6IT38bvsv/NuRvqdyUiiQULmvR4dau2N9z+DzXnsOJf3h8FicMOyiTBkJyi6MJJa7v0KOzQolanRyT49s5u5EGGBavLdvQU61KaA41Uzf/Z2fNWLN5cNdAZULvL3R/CoEAhkMul0Mul2N9fR0DAwO8GTVXjQ4+33JxbPlOAi8QwDBkmoQFAgGMjo5CKpXi6NGjISdlrghgJlrAnCDi9MoeFvYIfPK3c/j1/aX4zfAWJrfs8LeXJLxNgiDwP/cNJmVnEusYE/WZ49r2Go0GPT09B37kma5Sp3tbnAl3R0cHVCoV/H4/iouLUV1dDZqmsbu7C7PZzGfNctFj6Z5vkYpI/PYvBjE/P5/Q6zK92rY4fXhuzoKr20qhkCZ3yby+Qw+1XIyLGjRp2SfRxM9BBDwR/0Ywfognf32AAKaKf44iKmBZFpt7XlSopAe+BxcjwhNzduwxWnz19h4+t3hpaQkURfHVweLiYv61YopEY2kR/965uolu7nrw2pINSqkIhyuFD/Nnikj9y9MLoFngrgHhBtunlmz42rNL+Kfb2mGII84qRAIYjOB2MVeNDm4XSyQSvjoYfL5lApyRfb6j4Ahgpi8GIpEoYzOAXCu0vr4elZUHf8QURUWsUmUa6SaeXq8Xw8PDKC0tBa00oEK1jg+fM1P+xHUt8PoZmLbWkiKdySoh0+UDyH2Hzc3NUYO+o5GymW0H6qPM8iWLVAng+vo6VlZW+Ep0+HnA3aR1uv3ZvnB7EG6FrdVq0zbvksgxsSyLR0a2IaII3JyGKmQk+M6ZGtNM8p+zTEzxBr3pABHwxv47fbCLkSkytWxx4/k5Cy5p1qG+JHRRUK6S4qfv6UOlWsarh7lzyev18mTQ6XTyucU6nY73Ps0lAazWyHBHf2XClkaZIlI/uLsHvkB0VXS4QT7LsmBYFiSxr/aOh0IlgNGuFdHaxcHnW6baxT6fLyuWOqmi4AhgppGpKtz6+jqWl5fR3d0d1RySoih4vbEv7JlAOiuA4ZFu+soA2ipUOFa/P9MlpkiIKRKWLFvPpMMuZWtrCwsLCzG/Q25b4dje8+LpKSMG67UYqNOktB/h20qGALIsi+npabjdbgwODgr2LQu3B7HZbDCbzVhcXOSrg5mKe4oEgiAgIgmUpcF3MBrKVdKEvBCzgUDNCYgnfs63gK2sAn5QKCN2wYJAoHIga/tSpZHheIMWVZrIIqpmfeTZUKlUioqKClRUVISoPTlzYJ1Ol/FxnFggkrQ0yhRpVcvFmDM6oZSJIAtrSXsDDP72sWnUaOX44KX1AIAHfzGBAM3i++8UlkJUyARQyPFx7eLKykr+fIvULlar1SkvZgshBQS4QAAPIN0EkKZpTE5OgqbpA7Ni4ci0GCMa0nHMwZFuwXONZ1dt+PZzS9Df0o6moBtBtr0HU9key7KYnZ2F3W5POpmlTCnB9Z1labc1SYYA+v1+XnkeqYUtFOEVHa46OD8/z5sHl5SUpLU6GAk3x5lLC4fN5YfF5efbjIUI/+BfQDz9CBDY/90+RfchABJ/JvoTIJLBd/xDB16TKWIipki0lKV2swtXe/r9flitVmxsbGBoaAhFRUV8u1gmy29roESJ1K7bD5phoYuT12tz+fH9V9bQUa7AXYOh/qkSioBURGGwVs0/1lmhxPimXfB3XqgEMBkPwEy3ix0OxwUCWIhIJwF0uVwYHh5GVVWVoLSLXM4AptJ65tSjJEmGRLqxLIv/eH4Jw+u72LF7IBOT+MrT8/jwVU0Jb5NhWBBE8iMAybaAObKkUqnQ19eX9PYJgkhZJRvtfRM5LqfTieHh4RBFdroQyTw4uDrI3cDjVQczPUP54oIFLh+NOp1cUGssGYys7+HbL6zgX9/akRHlJ1PSAvfN34T80Q8ABIFr2DPwU8VgSRk81/wDmMr+tG8zmxCLxSgrK8Pa2hq6urp478GpqSn4/f6Q4f58s9pIlGh/56VVBBgWn7gmdlqPWi7CW3vKIy5cCILA393UGvLYey+uFbwPQOESwHTsd3i72OPxHBhPSKRdXAgxcEABEsBMt5XSRcI4G4TDhw9DrVbHfwEyq8bN1HY5kltdXY2amlAbFYIgMFivgd0TgMvHwBtgwGK/XVGUQEWOZVl84fEZiCkCn7iuNf4LIiCZFjA379fU1ASDITPzZakiEbJkMpkwPT2Nrq4uqFTC8kGTRbh5sMfj4YUkbrdbULQYy7L4lz8u4kSjFhcFZZ6miqvb9HD56LSRv0jXpO+8tIoXF6zYdfuhz0CCBwDQTdfAcf8QRNO/hXx3BTJlJRyH3gTIIl9vCsWaIhhcrm5xcTGKi4tRU1MDmqZ5MQknTBK6uMgGIhGSAMPiW88vY7BWHZLfCwC391bAGzh4bQowLKigRS9BEOitEXYvSQbZyDDOBDKRAiKTyVBZWZl0u/hCC7hAkWoUHMMwmJ2dhcPhwODgYELDpbmsACazXaPRiJmZGXR2dkKj0UR8zoevbMaHr2zm//3ltx4GAOzsOAUTMoIgIKFINJQmH7WVaAt4e3sb8/Pzcef9sokzyzZMbtlxR38VX1USUtnkbId2dnYSPieBfaPnP0yacGmzLmHFNAeZTBaxOri0tASRSHRAWcyyLPw0ix+dWsePX1vH65+8JKntRoJURKbHiw/RB9C/9OY22DJI/nhIihHoulPQU5MlgHZPAAGGhTbJ7z4ZzBudsLn9EfeZoij+fAHOV2u4xQUnJtFqtUmNa6SKSETK66fhCzCYN7kOEMA63cHrGsuy+NIf5iAWkfirqxPL8f6/hkxXLoW2i7VaLYqLi0GS5IUKYKEiFbGAx+PByMgISkpKkmoXFooNTHCkWzKEIpltPnRdS8LbSGZ7XCzf3t5e0vN+mQJJAgT2ExM4xDtfGYbB+Pg4CILAwMBA3AtlpHPW7Wfg9AVgcfmTJoDBCK8Oer3ekOogQRCgaRo6nQ6PvH8Aann6L1PeAJM2EhgJMjGF8jzNMHb5aJxZseF4g1ZQfN+TU0YEGBZ39Am3H0kVry3bEGBYHCLik9bgag3DMLyYZHV1FQD41p1KpcpIdZBbrHCLsvD84i89OY/HJ4x4+N29gl0MCIKAQibCobL8JxG5RrZzgKO1i1988UV84hOfQHt7OxobG9OyT48//jg+/OEPg6Zp3HffffjkJz+Z8nsGo+AIYKbL+8m+v9lsxtTUFNra2viVaaIoBBEIF+lWXFyM/v7+pFde2RaBuPwM/rjowqEO+oCCjgM376dUKlOa98sUems06K3RhDwWiwB6vV4MDQ2hvLwctbW1SR+PtkiMPxuoiv/EJCGVSkNu4NPT03C5XBgaGgJFUWB1OlBhXnHhSITQWZw+PD1tQn+tJmEhiJ9msGr1FKSAhKumGR0+rNm8sDj9cb3hAODylhL46ex6mr21twIMC4yc3UzovCVJEmq1mh+78fv9sFgs2NjYwNTUFIqLi/l2cbpsOq766qugGRZ//PBxUCTBV6RohgVFErikWYenpkxRK6j/c3oDm3sePHhFQ8ixfujyg3F+F3AQ2SaA4QhegFxzzTV4+eWX8f3vfx+nT5/GSy+9hMsvvxzXXnstTp48mZCAiaZpfPCDH8STTz6J6upqDA4O4pZbbkFHR2Q/zmRQcAQw38CyLBYXF2EymdDf35+SQi3fK4CRIt0yvc14sDh9MDt9aImzUl63ebFmD2Brz3vAqwzYV22NjIxkRByRSUSbAdzd3cXY2FhKC5JcgCRJFBUVQSaTwWAw8NXBxcVFuFyuEGUxNzs4tLaLd/33ML54axtuOhzZmzEYSpkIZUop9ElYx9z+ndexaHbh6QeOZb69m2Zw50mtVgZ9twFysTDCHE+dmgkIqUwKeh+xGAaDAQaDASzLwul0wmKxYGJiAoFAgM8tTiUp4rYj5fjt6DY/U8qyLOweGt9/dQUnm/fnV//wwLGor9/e84Jl8z81Il+RT+IViqJw8uRJzM7O4uTJk7j33nvx7LPP4tFHH8UnPvEJlJaW4jvf+c6BeflIOHXqFJqbm9HY2AgAuPPOO/HII49cIID5Aq4aVlRUJKi9Fg+5jIKLt10u8zZdM3HpIoBv/85rCNAsnvzwCYhi3DTaKpS4tVkWcd5mZ2cHc3Nz6OrqglIp3PE/HxCJAG5ubmJpaQm9vb1pT+vINsKrg3t7ezCbzVheXgZJkvtzg6L987FWK2zxJaZIXNayT4pdPjpuDGCA2c+L7qxQ4h9vbcMjo9sJmwPnCwhi3yg40ejDNwIIgoBCoYBCoUBtbS1omobVauVnuaRSaUhusVBC9sDl9Xjg8nr+3wzDoEhKQSoiUBKFPAcYFjf/+2voq1XhC7e0pePw/s8i1xXASHA4HKioqIBCocBNN92Em266CQCwuroqWFC4vr4eQhSrq6vx6quvpnU/C44AZmuVFG9gmquwNDc3p00hms0IsWDEImNcS87j8cT1MUwEry7vgd7zoSvF9/nqHd2YNzljkj8AEFEU5KLQ84dlWczPz8Nms2FgYCDtbvDZUF0GnzMsy+LZ1ydB+l04EcfcmWFYjG3soUlfjOIk480yhWi/A5IkodFoeMERlyTx6tQy3tVOgbWuYUdcCp1OJ+g8/fPvn8XIuh0vfPQiqOXRZxt9AQYbu16oZWJ0VirRVl6Yc1mFqALOJCiKOpAUEZxywynVFSo1fnJmC12VShytj69GJwgCEhGF+88ZMkfc9rmvweLMfvJTJBRCbFk05CMBdLlcEQslQip/HCJ9J+n+/ebXlT9PwBGiSCcVy7JYW1vD2toaenp60ir1ztXFOZoNTHCkW1tbW1L7x7Isli1u1OnOr6j9NIOvPbcK2u/F9Rentu/tFUq0V8Sv2oXPynGZzEVFRejr60t7C4EjMQRBwBdgMuIFF7ydQCCAoeERnF5nUFdVHpcA2dx+DK3tggVwpDpz1hKZBJckcUmRFmdWdlFTJYHFYsHKygpvUl1SUgKFQhHx3L29twIj63aoZLE/qyIJhTd1GZLKoM5HbO15sGHzoLdGfYEQBiGSj6XFYsHi0hJW12ioWRXaS0RRz6dEQBAEHv/Lo4Keu+v24+4fDOMvL6vD1W36uM9/ZGQLFqcf914knGzkUxs1UeTjvjscjpQ7ZdXV1byQCQDW1tYiRsimggsEMAI4K5hwAhgIBDAxMQGCIHD06NG8W3Uki0jiE6vViomJiZRnyIbX9vDlJ2fgC7D4r7v7oJCKMLVlR7lKgptrIv9oR9Z28dvRLXz86mZI06SkDK5ycmbIDQ0NqKioSMv7h4MjZo+NbmHD5sbdF9VlhAQSBAGfz4fXXnsNdXV1eGdLCRTS+J+ZrliCmw6XQ5UBhW22UaGW4eau/fZvsLLYYrFgeXkZTqcTKpXqgDXIbUfKcZvAiLdMKoZThc3lx7NzZlx1qBSKGNVcbkHy2vIuvH4GPTVqXKB/kRGsVG9qakLPkX0j6tXVVdjtdigUCj72MN2dg3AQBAGGZQVVC/00g18MbYFl8X+GANI0nVduDUD0CmAiGBwcxOzsLBYXF1FVVYWHH34YP/nJT9K0h/souKt/NlasFEUhEAiE/LAdDgdGR0dRU1OD6urqjO9DNhFMjliWxcrKCjY3N0Mi3ZJFW7kCjaXFmNtxwhdgAOn+3JWmSAKVOPLc4YrFBY8/vQphjpBx3oWxzJDtngC+9dwiHriiMapiOB44f77DlSo4vIGMVQAdDgc2NzfR398v2HCcQ0mezrGlYxQiPGeWmx0UWh0sJPhoBiwLwUrdGzrLQDMsyAI/7mxCIpGgvLwc5eXlYFkWDocDZrOZNwbmxCSJ/gaFQCUT4Td/MRj3eU9NGfHUtBlffnN7yMJuc9eDUoUkprCmkAlgPu57OoygRSIRvv71r+O6664DTdN497vfjc7OzjTt4bltpPXd3iAIF0VwAojDhw9nPEEhF+DISrRIt1QgE1P4f7eEqpaONegwUKvG6dOnI77m5u4K3NwdWpmb2rLjuVkz3n2iNu68XzR4vV4sLS3F9S58YmIbP3t9Hb21alzdFl9VGglcy7mupAh1EVTH6QBH1MvLyzNy4wlGIc+PEQTBW4M0NjbC5/PxZNDhcPDGwTqdLu8qCUJQppTizQIqmdx3KCKJEC/JC4iOP82YQRDgRUPA/vmkVCqhVCp5Y2Cr1cqnP3k8HqytrfFikmyhRiuHVERCWyTmF5wuH43PPjoDTZEYX76tPepr85FECUU+zgBy8XGp4sYbb8SNN96Yhj2KjIIkgJkWS3AEMFgAkS1T4ODZsWyCYRicOnUqaxVOruro9dP4+p8W8bb+StTqohOlVxYs2Nz1IJlvnZv3Y1lWkHfhLd0VaCwtRldVbLL/89fX8U9PzuG5j11yoMKXyXOUYRhMTU0hEAigtbUVVqs1qfeJNpsYfu49P2/Bjt2LW7vLs0IcMv37lkgkEauDq6urIAiCT5l4I1QHUwXLslixelClkeUFafQFGDw5ZcTJJl1M4U668NlHZwACeO7Bi6I+RyQSQa/XQ6/fn8/jlJozMzPwer0hucWJiOiG13ZRLBWhWS+sknTIoDiQB1wkofDmI+XoropNRmiaLlgCGG1eP5e4kARSwKAoCi6XC9PT0ygrK0taAJEMuHm8dKlthcBoNMLlcuHYsWMZryRx4G7yTh+NHbsXk5v2EALo8dOQikj+c3/X8VowLJtw9Y/LKq6rq4Pb7RZ0kZOISPTVauI+7xdnN0AzkYlKpoyufT4fL8ypr6+HxWJJiixZnD78bmwLR+t1aDXEvlBp5SJYnL68IADpRqTqICckSaQ6OLS6izKVFJXq5H1AM41kFpbbdh9eXrCgr1aD1rLcZ5vavQEY7T5s7XmzQgB/eE9PQs83OXx4fYfBwGAVqqurwTAMn1u8tLQEiqL48YNYxuYsy+J340aISAJ/dU1qUXBCvDHzkUQJRT6S13RVADONCwQwArxeL2ZnZ9Hd3c0PlWcLXPUxGwSQs0GxWq0oKirKGvkLhq5Ygv93S3sIufD6aXzh9zMoV8vwgcv23fBJkgAZNLI+b3SiWEKhPMYN12QyYXp6GocPH4ZarcbS0lJa9/1/3hN9LicTVSzOiLulpYWvNgjJAo4EhVQEtVwMvTL+HODhShUOV+Zm9IFmWJxZsaGtXBlXrZsOhM96cbFia2trAMDfvJVKZch3vGRxY3PPmzEC6PbTkKcoiErmPClTSnBxkw7lAhJDsoGSYgnuGqzKmiI7km9oLIys72Jpj4HTR0MlE/HzpjqdDsB5cdLS0hJPEiItMAiCwPtO1qbNEDseLrSA0wu3253V9n+yKEgCmKkWEUeIdnd30dDQkHXyB2TPDJqLPVMoFBgYGMDLL7+c8W1GQ3gbUiqmUKqQ4NJmXcTnsyyLn51Zh0RE4qNXN0f8+9LSEoxGI3r6+sEQB09zt4/GPz4xgw9c3ig4nzMRpJIpHQnb29uYn5+PaMSdzG9BIiLxpu7MKKBTRfDv2+2nsWr1QCkTQ5Vl/73gEPiGhga+Ori6uspXBz0eDwKBAG7sLOOTININi9OHZ2bM6K1RpxxBl2gFkCQI1GhzcyOLdl5nSlAVDi7KLRGcbNJBZJFEXayEi5Psdjtend2EY3IFNQoiJLc4mol0JlDIBDAfq5csyxbE51mQBDAT8Pl8GBkZgVqtRl1dXd558qUTXCWpqakpxMQ6nwb9P3Rl9LYHQRB45/GaiBWRQCCAsbExSCQSDAwM4FvPL8Hto/HhsPcbWtvFHyZ30FauxJ2D6Z95TLYyFw6WZbGwsACr1RpxDjVd2wnfZr6cBwqpCDceLssLG5ZI1cGJiQlMT0+HKIu56mC6oJKLUaOVwSCgWhsL+fS95jtohsV/vbwKiYjEu44Jvz6QYAXZMAHnFxj/+uoUAOCR9/bAarVia2sLMzMzkMvl/DmVSsSoEBQyAcy3FnAh/c4uEEAANpsN4+PjaG1thV6vx/r6Ovz+3Di0Z7oCuLGxgaWlpQOVpFyJT5JFleZgVYKb9wsWsrypuwKrFteB2cFj9Vr89z39qIshPEkF6ahS0zSN0dFRSKXSqGbV4dvx+umUvROTOQcCDAuKyIxNU6qtz0yAu3kXFxejubkZIpEIFosFa2trafeJE5GEoASKNxpyWUWhSAISEYnOisSqzslcQ7982/4IjFgsRllZGcrKysCyLFwuFywWC6ampuD1+aBUaWDQl0Cj0YRUvF5f3YXHT+NEY+SOiRAUOgHMxwpgIdxLC5IApuuDZVkWy8vL2NraCslNpSgKHo8nLdtIFJFMmdMBTtHs9XojRrpxxLPQLgKvr9jwiV+O42u3NcG8No/Ozk4+KgzYt0YIbmFxP0ySJNBSlrmWYqoiELfbjeHhYVRXV8dUZQe3mi1OHx4d3cJAnQYdFcnN7CXz22JYFr8Z2YJMROFGAQPnQvYh01XwdEMsFsNgMMBgMITMDo6OjgLYN6guKSmBSqXK2Y2hUG5KHHK9v4lU/jgkQ6Q6IyQZEQSB4uJiFBcXo6amBrf/5xn4/FZ8+WpgYWEBYrGYrw7+81MLYACeAPppJuHZwUImgLk+T8JRSLF6BUkA04HgVuHRo0dDTv5szeFFQia27fF4MDIyAr1eH1XRnCnVajywLAuGBe78zmu4uk2P91/akNDrt3Y98Pr9mFlYxHUnBiCVRp/ny3SVM7j6FlyZM9q9+ND/juAbdx6BTsBcD5fC0tHREXcONXg7KpkIZQopKrKsRCUJAhq5GA0l+T/0nA2Ezw76/X5YLBasr69jamoqqykSwSikGxOwT0qS/a3OG50gSQINGfLgjIZMXV+ubS/FqeVdHGrdt3nxeDywWCxYWFjAO5t8kBUVY2dnB7+fd+OpGSu+cnuHoGsNh0ImgEDuYlQjwePxFIQABPg/SgC5Gbj6+vqI2XpvJAIoNNItk8fs8dOQUCTIsIFqjryQBAGaYfHsrCkhAkjTNKqYbXzzRj3a29vjXsA4kpuJC93WrgePDG/iqjY9mssUIVWs15atmN5y4PUVG65uj10hW1tbw+rqquAUlmACKKJIXH/YEOcVmcGVh0rT9l6Z9gHMNsKrg+EpElwlJxvVwXy6UcZDKmTqpUUrSCAuATQ5fChNYyJOpq4v7ztZh/edPP9vH0SorKxEZWUlOhmGrziLHSZ4XD6YNtdA6YWfU4VOAPMJ6UgByRYKkgCmchFbX1/H8vJyRDUlBy4LOBdIlwiEi3Tb2toSRCYyVQFkGBYP/XIcEpLAP72tK+I2RSIRfvkXxxJ6X65FWlVVhZoaYZmXmaxyquVilCgk0J9TFAeLM67rMKC/VhvzRsMwDGZmZuDxeBLKmX6jkaU3OsJTJPx+P6xWKzY2NjA1NYXi4mLeiDrd1cFMVafMTh9MDh8OxfGTTBSp7O9bjpTHfe2azY3HxnZwaXMJ2tOkMM9GO3J8w46/eXQGH7y0Dle1lYIkyRAvy7ddvl9xDj6nuEVGtA4Jdx2+gNThcDguEMB8A03TmJqagt/vjzgDFwwuCzgXSMcMIE3TGBsbg0gkwuDgoKCVXabUxyRJwO2jsbjngcXpC2lLJEvILBYLJicnBbVIQ/clcwRQLqFwe18V/+9gYkaRBAwxfNT8fj+Gh4eh1Wpx6NChhG4gmSCA+TZTU4hgWGFZu+GD/7msDiaLlxascPloNOmL02oWHu08DDBs3O0US+Pf2gxKKY7WaVCfxtGFbFTSqrUyGFQStBr2ScbTUybYPH685Ug5XlywollfhHKDAS6REocOybC0Y4Pfu69YDwQCfG6xRqPh97UQ57/zFRcqgHkGl8uFkZERVFRUoLa2Nu6FNNct4FQUyJGUsEKQKfEJALz/0gZ889kFKMO8sThC9ujIFs6u2fDX1x860CYORnBVs7+/H0/OWLFwdh4fuqJR0M0xE5YpqW7L4XBgZGTkgCWPUGSCAOaaaBR6VfOP0ya4fDRuPFwmiARyiJQxG17J4WYHY826RkOmiP117Xp4Akzak2Ii7e9rS1ZM7Tjx1p4KFElSU36KKRK9Nfvm9xu7nrSYeGeDAKrlYnzzzvPdlP96ZRUMC9zYWYZHRrZRqpDgli4DvvDEHC5u1OLM6i7e1luBa3vrQNM0rFYrTCYT5ubmIJVKodPp4PV6CyK6LBz5KBZzuVwF81m+4QkgF9Adrg6NhVwTwGQVyNyxcskXiSCT1bGBOg2++66+A49zVcexjT0EaBax7k00TWNiYgIEQfBVzUWTCzST2E0tWxcMIUpWo9GImZkZdHd3Jx0bVOhkKRKixevlK8LPv3K1FCsWd0LkLxh+msEfJk1oLStCS1B10Ol0wmw2Y3x8HAzDhCiLc1m9kYjItJoz0wwLkohMAKu0cixZ3JCJo2/PG2DwyMgWLm0uEZRg8uqSFR/9xSQ+dHk93t5/cCY8EWSyem5z+fHtF1bwZwOVqA1KKPnWn3UhQLOQiyk8cFk9SorFkIhI3NJlwKXNOqhlIgzU7t8PKIpCaWkpSkv3Z3bdbjcsFgusViusVissFgt0Oh20Wm1BtITz0QT6Qgs4wxA61Do7OwuHw4HBwcGE5mlyTQATJSksy2Jubg67u7sJH2vwdrN9zBzp/OT1rTGf5/F4MDQ0hMrKStTU1PDffyyz6HCwLItfzbih2l7GVZ2V6K3RpLLrcRGrAhicVJLs98XhjUYAd91+PD2/h/YSEWpzvTNJoqNciY7y5HNASYIAQQBUEKkjCAIKhQIKhQJ1dXUIBAK8afD09LSgOa9CaO2zLIsT//QiQBD44wd6DuxvpVqGt/XFJml+moHLR8Pi9AkigB3lSpxs0uKSKMlDiYCrAJ5etgHYX/ymC36aAc2ycPtDr9OKoHZ3MDF8W99+0s+fDVYhGuRyOaqqquBwOHiRksViwfLyckiMXbrNzdOFfCSATqfzQgUwl/B6vRgZGYFOp0NfX1/i8UdZbBWGI1EixkW6KZVK9Pf3J/0jzYUNjJBtJmKJEgsEQUBEkvj50A4eGTPjyQ+fgCyDBsPRKoA0TWN8fBwURWFgYCDlyk2+EcBk4rOCIRNTkIlIyEX5d7OJhEx89hRJ4MbO2GpxkUgEvV4PvV4fUh2cmJgATdP8nJdarebPsVycJwzL4u9+N4uTTVpc06aP+3yCIACCQG+1KmnCqpCKcM9xYcIwAFDKRPjHN7cnvJ1I4Pb5tZVdEEgvAdQrpfj0dQejL9MBjkgplUr+OstFHwabm3OLjGzaF8VCPs4uOhyOCwQwV+AEAocOHeLL3IWERAjg3t4exsbGkp4fC99uLghgtGNlWRarq6tYX19Hf39/1CikL/1hFk9PGfGb+4/FTcB4a4cSbx6ox4aLSJj8LZicGF7bxS3dFYIITiRi5vF4MDw8zM+iJopfvL4OkiRwW8/5Ckg+EUCaYfHo2DZUUhGuSNIWRioicVmjCm63O81798ZFtOrg9vY2ZmZmUFRUxFtAZbuKQzMsHhvbwe/GdgQRQAB45eMn8KvhLbyytIsqqjAWAhy4CuB7LhJOQPMBkWYXw6MPwwVKkRYZ2UY+poBcqABmGJEuYizLYnFxEUajMSZhyHcIFWNEi3TL9HbTiWgVQIZhMDExgUmjFz+YAL7aQqMhyte569oXzAiZQSJJEhVqCbobEm/1nF3ZhdHuFfz88GPb3d3F2NhYXD/GeGDC5uNyWa0OBxefVadLTVWZj62mQkJ4ddDlcsFsNmNzcxN+vx80TaOkpCQrN24xReL3HxgUpMrlsF89B3bsPlRrC+tc4CqAsa5HLMvin55eQJtBgTd15ca3MxzxxCuRBEpWq5WfO5fJZHx1MJsmyPnYAna5XNDpUh8nyAYKkgCGw+/3Y3R0FEVFRYJtT/IV8SqADMNgamoKPp8vrp1NIsgXAshVycrLy9GqrgY1NR1zmP7zb+5IaXvAfoLHj0+t4dqOMlRrI1+8buupAAvErP7tuv1Qy8UAQlvAm5ubWFpaCokbTAZv7Ts4y5OLCuDmrgd6pTSi6vOGjtSj4C4gfQiOFJPJZHA4HFAqlfyNWy6X88riTC2aOW/MRHB7XwV2d3extbWVgT3KHISqgJ+ZMeO5OUvBEMBwBC8yAPC5xTMzM/B6vdBoNLzVTCbFJPnYAr5gA5NF7O3tYXR0FE1NTSgvL0/re+diaDpWK5YjR2VlZWhvb0/rvlEUBZ/Pl7b3E4JgQvbyvBlf/sM03t/OYLC7AzqdDnUAfn1/YgbR8bYXiSz5aRZOH41tuzcqAYxlTwPsk6Lfjmzi4qYSdFbuqzL9fj9mZmZ4IVKkCyHLsvjui8s4XKXC8SQqk9x7JIszKzbQDIuj9cLmK3fdftz4769BIxfhmY9clPR2YyGf2tpvJLAsC4qiIlYHJycneY84odXB345uo6GkCIcrkxe8xNvfTN7cGZYFzbAJ5+bGfE8BRIogCPzsPX0QpXG7qSJV+5qioiIUFRWhuroaDMPAZrPBYrFgaWkJFEXxYhKFQpHW+1Y+toC5RVYhoCAJIHeDWFtbw9raGnp6etLOuLlKXLal8NEqgNxsY6otxGjItQhkYnkTTpcHXV0D0OlUUV9jcfrwru+fwWduOITjjYkRpmjCDIVMhAeuaIz5WpePxuyOA91VkQ15SxUS9NRoUHcueophGKytrcFgMKC3tzfqRS/AsPjmc4sgCQKvferyhI6HO6ZUcM/3XwcAjH72SkHPV8vFuLFTj7f0VKS03QvIPsJJdXB1sLa2FoFAADabLaStx6WShFcHAwyLv31sBgRB4MwnToY8vuf2J5RDG2t/o53fz81ZsGhy4l3HqpP+DTx8egN+mknpPcIhtGiQSEs8HCsWN1QyETRF4oh/39rzwuryo75EjlNLNgzUquNuL53+hcHqYWBflMkpi51OJ5RKJV91FosjH4NQ5GOE3QUfwAyDYRiMjo6CIIiEYrMSQa4IYHgrlmVZLC8vY3t7O6OzjbmygQkEAhgfH8dgKYN7PnJZ3O/STzOgGRZbe4l7JaZCcsc29nB62YoqjQylioMtLTFF8lU0l8uFhYUFqFQqtLbGtrgRUyR+9r6j0MhTuxAmi4fvG0jYd+/zt7RlaG8uINOIRU5EIhHvEcdVBy0WC5+gFJwgISJJfOfPu2EIa++eWrJizerBzV2GlI2aGYaJur+f+PUkWBZ457FqJEvdDlcqsWP3prUilelINYZl8bFfTkBMkfjJvb0hfzPavfjm88uwewJgARxv0OLbL6ygUi3F1+84fMCIP3y/M0WkpFIpKioqUFFRAZZl+dzi9fV1Pu1Gp9Ml5WeZjxXACy3gDIMgCFRXV2d00DJXecDBbUqOHCUS6ZbKdjNVARxa3YXD68fJ5vPKUIZh8asxC2pEdgy01aGuri7ihfi2b70KkgB+8f79VrBBJcPvHziR1H6kIpjoqVZHJX/BMJvNmJqaQm1tbUiiC8OwUdvIjaW5u1h0Vh6stgYCAZAkCYIgcrK6LrQWMEEQGNvYQ5FEhMbS5Gc8M41ERlqCq4M1NTV8goTRaMTc3BxkMhkMJSXQSUMrfUeqVDAopSmTv3j7+9j9g3B46aTNtgGguyp6pyFZZHpsiCQI/OVl9QeINwCYnH44fTTu6K+EtkiMinMeiOObdiiksb+PbI07EQQBlUoFlUqFhoYGPgt7a2sLMzMzkMvlvJhESLEjHyuAXJWzEFCwBLCkpCSjN4lcmkED+yfRyMgIamtrUVUV3cgzXcjk8f73KytweAI4Wq+FRLR/IZpfN+L3UxZ0GIpw+/X1UV+bzkuSkHSOaJCISFRpYqvbVlZWsLm5iYGBAezt7cFqtQLYnw/8w8Q2bjxcntRAfLbAsiw/VM19TjRN80QwlQut0GzccKxa3SgplqSFUGQSq1YPfDSDj/x8HP/fmw5lhFzkEsEJEizLwu12w2w2Y3p6Gn6/HxqNBiUlJdBoNGjSp2dBE4uU6Iol0OVhkSUbhOSylsgjQO3lihA/Q7efxu29Fbi9N3/HNcKzsMOrzsFikkiVPpqm88aTkMOFFvAbABRFIRAI5GTbfr8fQ0ND6OrqgkqVnRtJJiuAH7+6GQ/+fBSf/e0U/uG2TiytrOIfH59Dq0GB9x+L7Q32y7+ILAJ5fcWG5+fMuP/SBsExVJk6RoZhMDk5CYZh+EptcBVLKiIhodIbl5VusCyLQCCwb2Fx7oLKMAxomub/l1sgJFodNNq9uPbrp/CeEzX4y8vqBe+PN8Dg9ZVdGFRSHG9I3gQ8G7i2XY9liwtLFjd+N76TNgIYYFj8cdqEZn1RypXidFV5CILgh/656qDNZuPzZdNlCVIIySXhyAYBZFgWBELb+SzLwuz0o1Sx/9tdMLnwb88s4p1HqzAowIw6Hz7nSFVnTkyysLAAsVjMn1dFRUUgCCIvW8AXjKCzgEy3iXJRAeQi3fx+Py666KKsrmwySQCrtHLc0b9/IZqYmIDP58Ohuip0lpJItrBjcfkQoJmEUic4ZW464fP5MDQ0hLKyspA2dvDnqSuW4M+OZtcY1uOnsb3n5UUp0cCyLBiG4eetgm8EwVU/hmH4CiF3XIFAABRFxSWD3AB6mULY+cztg1RE4uImHVQxZpfyBRRJoLG0GM8/eFFaq5UksT/3uufOzWJUCCiK4sUiAHhl8czMDHw+X9wqDgeby4/xTTuONWghIomME8B/+MM8FFJK8KJECDK9zyzL4p+eWoCIJPDRq84L115dsuE3I9t490XVeHrGgvoSOYrEJKo1hemHCxw8rzweD08G3W43lEol/H5/StZamYDH4ykYH+L8v7LmCNkmgD6fD6Ojo1CpVJDL5Vkva2f6eN/UWYrh4WHo9Xq0t7ejhyCws7OD3d3dpN7v6rYyXN2WmOdc+AzgvNGJ8c093NKdXIvEbrdjZGQEra2tvB8Wh1zPsV30pefAsCxefuiyqIQkFvkLB0fwuBt4cHWQ++/gvwcTwiIJhbOfuiSp4ygVSBozgdH1PShkIjTEIdHBUCcp5rE4fbjyq6/iR3f3hNiqkASBmw6nxysuWxW1SNVBs9mM+fl5SKVS/qYeXh1csrixYvWgt4aBSEJlfH9/P74DgkBaCWC0CuDQ6i6KpSK0lKVWxd2PtCRgCMs4bi9XwOT0oUYrx7zRiVWrG/+Qpni7fIFMJkNlZSUqKyvBMAzsdjtmZmawtLSEtbW1EDFJriua+TaXGA0XCGAUZJMAcpFuzc3NKCsrg8lkyvpwayYrgFwKRng8X7bj58JnAN//4yH4aAbXtJVBnmDVZnt7G/Pz8zhy5EjEcn+6Ps9fnt0AWBZviWACHQvfv7sPz82a0kL+IiG4Ovi7sS3QDIvr2kpA0zR/405WSJJr8gzsfz7v+O8hAMDwpy+N+bx0YGvPC7AszqzuZsxXLxcIr+Jws4PBhsHc7GB3lRJthmI+pjHTBPAPDxxL64wxEH2fX1ywQkQSKRNAACGVPw5quRg3n1sofOHWNiQSx53r31oyIEkSarUaCoUC1dXVkMlksFgs2NjYwNTUFIqLi/l2sVSavbnrQhtbKFgCmOkPOVsEcH19HSsrKzhy5AgvHeeIUTYJYKaOlzu+SCkY2fYeDN/ew/cNYMXihlxC4bUlCwBgsD62spxlWSwsLMBqtWJwcDCqj1W6SAxBcP8vMRypVuNItTri37hWLnexSvW3RJEkCIKFRCLhW8UcueSqg+kQkmQTBEHgK7d3Qi3PziWyo0KJ1z91SdoJSTAybawsBHK5HNXV1aiurg6Z8eKqg8EzXpm+mUozMJMb6brNsizuOV4d10w+XYiU0BMLhUZagsF93mKxGAaDAQaDASzLwul0wmKxYGJigjc458YQMv0bKKTPs2AJYKYhEong9QrPfk0UwZFu4SkRufAgTDcZYxgG09PT8Hg8UVMwck0ASxVS3tZlaHUPQGwCGAgEMDY2BplMhv7+/pg/8nQRwNt6KlN+j2BwYg8gfW2K64Li32K1ilMRkuQCl7em33A9FlKxNBGCfKv0RKsOzs3NwePxQCQSobi4OC8H/aMh/Ob/g1fX8NMzG/jJvb1Qp2D+nEnko5WKUEQ6NwiCgEKhgEKhQG1tLW9hxImUghcacrk8rWStkMgfcIEARkUmK4BcpJvBYIgY6ZYLAUo6T1qfz4fh4WHodDq0tbVFfe9k84dXLC4YlFJIxYndFGKRsntO1MZ8rdvtxtDQkGBbnlwkq8RCqi3fZBFPSBKpOpgIefafEwJlkjztuv2Qi6m8VnELhZDvfcfuxWcfncGXbmsXLMBJx40vuDrIMAxmZ2fhcrnw+uuvQywW82QxvJMwsr6H+x8ew0/u7UWdLnnVMQeGZbFu86AmSixkzNeGkSmuyihP8FqVTRQyARSy78EWRsD+tdxisfALDbVaDZ1OB61Wm3LRxe12550oJRYKlgAWaguYi3Rrb2+PamSdLDHKB3DZzMHCCK+fxg9eWcVbeitQcq7ixjBsUr58Lh+N9/94CFIRlXBOcCxSFisP1Gq1YmJiAh0dHdBqhdmRRCIxS2YX/AEaLYbsznjlivyFI1p1kCOFXGWSI4rxwLIsnpoyQUwRuLottp1QsmBYFi/MWyATU7jqUGn8F+QxhJK05+YsOLVsw5mVXVwhoAr6+/EdBBgWb+pKj1gF2D9XioqKoFKpUFFREfGmXVJSAq1WC5vLDxaAw5MepfTUlgMvLlhxQ6ce1XG8P8MRnl7y9v5KvL0/vVX8dKOQCWAy1WG5XI6qqipUVVWBYRjs7u7yUXXBMXZKpTLha6XD4SiYFBCggAlgppFuAphIpFuuTaiTxcbGBpaWlg5kM88anfjPF5fwzIwRP3nPIFiWxTu/fwYEy+JjfYmdgkUSCu84VsPHriWCZKpyXN50ojF8kbb1yqIFLIOoBPDTvx7H5JYDv3z/0YQvPNFu7vlC/iIhUnUwEAjAYrGAoij4fD7+OZFuUARBoFItzWiMHkkQ6K1RQ5mn7TsOAYZNePYrGm7tNmCwTiPYQkQpE2EvTeQrGMHndPhNm5sdXFxchEosxk/vqIFOTaalEtmkL4aIIlGhStzKIx/mLLn9YCFsrKCQCWCq+06SJLRaLb+w9/l8sFgsWFtbg91uh0Kh4NvFQpw5CikGDrhAAKMinVFw3OyYRCIRFOlWaASQZVnMzMzA5XLh6NGjB8ro7QYFRAQB5lzmLEEQoEgCLaVFoGlXwtv78yQ99RIhgNwMo9frxeDgYMKrzEgVwDcfqUCs2N2npoxg2cSr29Gen26xRybBfTdzc3MgSRKNjY08eY01OxhN6BILLMvCT7OCW7qV6vz29JrcsmPe6MJVbaUxW41CyZGYIhNqpZ5sykwkZzQyFVylAfZHajibmfDqYDKzg1IRidYk1bqZIFMeP417fjiMKw+V4n0XHxxVYc9VqdVyMW9A/sGfjoMFi2/e2ZWTfc4m0nldk0gkKC8vR3l5OViWhcPhgNlsxtjYGBiG4cUkarU64md2oQKYJRRKCziZSLds26OkAp/Ph5GREWg0GvT09ET8XiiKxEevaQ5JMvjBPf3w+/04e/Zs1vZV6GyZ3+/H8PAwtFptzBnGRLclizMHdOqTlye8neBthScDpFvskUm4PF4c//JLuKJRgX+7ayDkWKLNDiYrJHlh3oI9TwDXdZSlpWqWTWJ95/deR61Wji/ddt7jTa+QYs3mjatqzTcRSDyEt1OjQSaTHWjpmc1mLC4uRkyPCMfw+h60cjFq0zA/mGgFcmPXg4lNO648VBq1WicRkWBZ4JlpEzRyEe7oO9hSfmbGAhF5Pt+4Qi2F2ekTtD8MwxSMyCabIAgCSqUSSqUS9fX1CAQCsFqt2NnZwezsbMTEm0KKgQOA/L8z5AjpIIA7OzsYHh5GZ2dnQnm+uZwBTOQmYbfbcfr0adTW1qK5uTlmJcrto2Fx+UIeT6Ylm8pNTMj2HA4HXnvtNdTW1qKpqSnpm3smRCAsy2Jm2wGHN7TdFj5Lyc3T5bvKloPL5cLw2dcBgsDS3sEbFkmSoCgKEokEMpkMEokEFEXxpNDv98Pv9/Ot7liwewLY8wRQpZalrWWaTUxvO/HUlCnksVKFBNe0RScQwcjnKnA4kmnnci295uZmDA4Ooq2tDSKRCAsLC3jttdcwPT0No9F4ft6UZfHhn43j3h8Op2WfE62m/WnGjNENOwJ09OsaSRD46Xv6MFingdN78L5AEAQ+elUDPnLleX/At/SUg2GBF+atcfeBW0xdQGyIRCLo9XocOnQIR48eRXNzMwDgpZdeQl9fH+677z786U9/Stl38HOf+xyqqqrQ09ODnp4e/O53v+P/9sUvfhHNzc04dOgQnnjiiZS2AxRwBTDTSCULmIt029vbw8DAQMKpHrlqAXOkRchqcGtrCwsLC+ju7o674lmxuPC1ZxZQopDg6rYyvDhvxisLFnz4yqaESNJvhzcxvePAh65oSkqRGY+UGY1GzM7OoqurC0plakKNTJgZu/0MTi9b0eAswkWN54fzCYKAx0/jsi89j5u7DPjM9S1pbfm6/XTGVIw2mw2Tk5Po7OzEyEXC8nPDZwfD00hiVQcf+N8xnF3bw2MfGEzvgWQJySaqAMkrdae3HVDLRShPYiYuGfgCDGZ2nJDQwiqAsRCeHsFVB5eWliASiVBSUoLPXluPqpLkfu+7bn9I+ku0z9jm8mNiy47jDdoQov62vgp4A4yg61kkA2gOirAZ1RZ9MW7sLENPdfzfVKG3gHMFLvGmuroaL774Ip5++mk8/PDDOH36NMbHx3HdddfhuuuuQ1dXV8Ln8YMPPoiPf/zjIY9NTEzg4Ycfxvj4ODY2NnD11VdjZmYmperthW89CpIlYT6fD2fOnAEA9PX1JRXplisCKKT1zM37ra+vY3BwUFC5e9cTgFxCouLcLNUz00bY3P6EcnwBoEwlhYgkk7bjCI+C48CyLBYXF7G0tISBgQEolUqwLIsde/I+kNG2lQqKJBSuaS9Df22oAIYgCFAEC5YFVi3utJI/m9uPx8d3MLvjSMv7BWNzcxMzMzPo7e2FSiWM/IWDJEmIRCJIJBJIJBKIxWL+POaqg4FAgD+vP39LGz55bTOq8nyuL1OgGRZPTBgxsWUX9HyWZTGz48TQ2l6G9+w81mwejG/aYXHTaa1YhlcHOzo69qs6tAm7yxOYmpoKqQ7Gw8SmHW/7zuv4xdlN/rFoBHBobRdnVnZhDxPLiCnyAHkDAKPdix+/tg5fILkugkRE4voOPZQCbHwKlQDm00iDXC7HzTffjBtuuAEf+chH8MMf/hBlZWX44he/iCNHjuDee+/F9vZ2Stt45JFHcOedd0IqlaKhoQHNzc04depUSu9ZsBXATLcyknl/zgKlpaUFZWWJ5dQGg1NAZhtc6zlauoXf78fIyAhUKhX6+voEf0bdVWr88cFL+B/sZ25sS2r/jjXocKwh+YFzgiDg8NIhF2mapjE+Pg6RSIT+/n7+Qvj3j03jqSkjfvLuftToEvd1ylScmV55sL1AEARYhsGrD51Mu9hDKRWhTidPqxCCS1PZ29tDX19f2gzPg21mxGLxAZsZmqZRVkzhjl5D2gxb8+kmFA8sy4IiCTAsC49P2AKTIAhc01aa8GItFdTp5FDLRTCvOzKbBCKVHqgOWiwWvjqo0+mg0eqgUioi7ketTo4ypeRAlS3Scy9u0qG7SnUgK5ph9xdu4Z/vgtmFNZsbe55AxvOwC5UA5uN+czOAFRUVuPvuu3H33XeDpmmcOXMGarVwwdrXv/51/OAHP8DAwAD++Z//GVqtFuvr6zh+/Dj/nOrqaqyvr6e0vwVLAPMNXORZuAVKMsh1CzgS7HY7RkdH0dTUBIMhcb+v/QtcbueP7F4av1/wgC014YpDet6Qu6KiArW1oeq6tw9UweryoTJBH7Bsg2VZFBcXY3h4GGVlZSgtLUVxcXHabpwUSaCvVpOW9wL2L9oTExMQi8VRRUPpQjIm1G90EASBGzoT80yMJ15KNyiSQEmxBGZkb2Yx2A6kqakJXq8XX316Fo9OruCvB8WoLdPwymJuwaKQivCje3pD3odbEOx5AlDJRHD5aIhIAhIRCV3xQSL37RdWwDAsPnhZfcjjg3UadFepsmIgnY9ESgjyMSHG6XTy/rccKIrC0aNHQx67+uqrsbW1deD1n//853H//ffjb/7mb0AQBP7mb/4GH/vYx/C9730v4mIz1d/HBQKYIhiGweTkJAKBQNTIs0SRKxFINOK5vb2N+fl5QfN++QxNkQS1SgJHqtXY3d3F2NhYVEPutnIl/u2O7hzspXBwZKalpQU+nw8mkwnz8/NwuVzQarUoLS1N2gojE+AU4waDATU1yVn5JIt4JtTcf1MUVTDimURRaDFVudxfqVSKIw0GPDnvxCXH++F17duBcGbBXCpJpMXWvNGJJyaNuLGzDA/87zgIAvjNX0SeOa3TyuGlDy66SYLIWnpIoRLAfNxvoT6ATz31lKD3e+9734ubb74ZwH7Fb3V1lf/b2toaKitTMxkvWAKYDxey4Ei3urq69FVd8qQCGCxmGRwcjNoaLhSQJIneMhE8uyYsLy+jt7c3L2J79tx++GiGzyWOh0jmzlKpFFVVVRApS7FgdKBEzfK5qlKpFHq9HqWlpSFm1t4ADYbNTkyV0+nkK8jhK+RcIF51MBAIxDShLkQUUrsayD1hvbZdjysPleLxiR301ajR1NQEAPB6vXyr2OFw8L6DOp0OBEGgQi1DV6UK5Sopru/QQxFjDu/Gw8mPCqULDMNkNXc+XcjXCmCqAsLNzU1UVFQAAH71q1/h8OHDAIBbbrkFd911Fz760Y9iY2MDs7OzByqLiaLwvvUgZGrOKvj9o60yzGYzpqamYka6JYt8EIFw835KpTKheb98Bsuy8Hg82N7eTlu1VgjWbW4opSKooiRWXPvVl8CywKufvCzue8VL9hjb2IPV5cfRhgroz2VfOp1OmEwmjI+PIxAIQKfTQa/X4/kVDwDgTd3lKR5hbFgsFszMzKCzszPli2MmEK06GM+EuhAR6XdstHvx/VfW8OErGvIq7zgaAbQ4ffjhqXV84NK6mBGO6doHo92H6W0HPwcrlUpRUVGB0jIDbv3WaRzS+/HAgAMrKytwuVzY2VhFj6EEUhF5oLWbj8jHSpoQ5CsBTHUE7KGHHsLQ0BAIgkB9fT2+/e1vAwA6Oztxxx138OKlb3zjGykff0ETwEyDI2LBPw6WZbG0tISdnZ2E48ES2W4ujKC51rPD4cDIyAgaGxtRXp5ZcgCkvtL/zgtLCNAs/uKyhqjPCQQCGB7e9/rK9OxZMGiGxTPTJsjEJG7vi+wF+fdvaseu2x/3vYQke1zeWgr63LA/h+LiYhQXF6Ouro6PWltfXwdl3oWsqAhbW0BJSUlGKrwbGxtYW1tDb29vyv5Y2UI0m5lIJtSFhGiL5V8Ob+HhMxu4rKUER+s12d2pGIh2XXhsfAf/+/omjtZrcFFD4pGQiUBMkXjnsWpE0sCISAIEAcilEjQ2NqKxsRGvvvoqpFIplpeX4XQ6oVKp+NnB4N9XgGFBEfnRySpUApiP++10OlMek/rhD38Y9W9//dd/jb/+679O6f2DcYEAxgBHALkfbqKRbskiVzOAJEnCYrHAZDKlxQsvGK8sWuDzM7i0tZR/7Gdn1mExMTge4UJPMyxeXrBgoE4Tdwj918P7NgzRCKDT6cTw8DAaGhrg9XqzetGlSALXtJehWBr9GK7tiN8GEhrrRpEEqBhiG5FIhLKyMpSVlaGjg4XdbofRaMTKygo/26TX61MWkrAsi/n5eTidTvT39+fdSl0owskggJDqIGczIxKJcnIzYlhWkAE0h0jf6TuPVmOgVoPemuSseDKFaATw9t4KHK5Q8qkXmUY0w3CCIPDYB0JbcCRJoqKiAhUVFWBZFnt7ezCbzfzvS6fTQavT4Z7/mQFFEvj5e/uzcQgxkY9ESgjytQKYj12OaLhAAGMguBXLVcXq6+tTHrxMZLvZAsuysNls8Pl8GBwcTMq/MBZ+M7yFAH2eAAZoBl/54zwCAT/ec+PBC9CS2YVnpo2QiSkM1Glivvcv3hd9DoJr1Xd1dUGlUmFxcTHlYwnGAw8PgyKJmIIRgyq1yhdHONLdfiQIAiqVCiqVilc+cpmqLpcLGo0GpaWl0Ol0CV1oOWsdmUyG7u7upIjkSwsWfPDhUTzzkRPQFOXH7Cn32XOzsmNjY3xlJxet4mNffhE0w+LUQxcLIoHRCFWRhEJ/beKZyplGtP2Viyn01uTn/gaDIAio1Wqo1Wo0NjbC5/PBYrFgbXUVXo8bPeVSbG9vQ6fTRa2+m50+bO950VERnVSwLIuRDTsaS4pAEAdNoeOhUAlgPu53oUXBFTQBzPQMoEgkAk3TvAr28OHDSRvWJoJsE8BAIIDR0VGwLIu6urq0kz8AeMfRavzTk3N4ad6ME00lEFEkvvzWTqwtzIKm6QPzeA0lRXjn8doQ/7kX58x4fdWG+y9tgCho9kcaoULIsixWVlawtbWFgYGBjLUfR9aFG+Qm2uqON++XboT7otlsNhiNRszPz0MqlaK0tBR6vT7m2IPP5+Otdaqrq5Pel7Mru2BYFg5vIG8IIAduPrasrIxXM3NCkvBEkkzazByuUGJ4fS+hCmAhIdcikEQRb38lEgnKy8tRXl6OxzrOVwfX1tYAgFcWKxTnfQc/9LNxeP0MfnJvb9T5TKPDh1+c3cTElgNqmQjfvqs7oZjDQs0CzscKoMPhuEAA3yggSRJLS0vw+/1ZVcFmcwYwuD0anJiQblRr5VDKRKjWnvfVu6ixBK/blvltMgwL8tyFiyQJ1JeEKnTXbG74aTauKS3nNceybEZb9QDw7MeERXNd8k/PgWWB5z9+iaCbWrbJXzi4dhUncHK5XDCZTJiYmIDf7+eFJGq1mt83h8OBsbExtLS0oKSkJNbbx8UHL2/ABy+PPtOZCEwOH77x7CI+cW1zyp52brcbIyMjaGhoCDF7F2JCnW6bme++IzGbokIkVOGf04LJhYlNO248XJZ3xDeRilRwdRAAXx1cWVmBw+HAikeKjho9/r+bmrG2648pztErJLhroArbdi/GN+0QkfuFkU/8egoquQifub4l5r4UahZwPhJAn8+XkQJKpnCBAEaBz+eD0WiERqPJugo205VNDkajETMzM3x7dH19HX5/fDFCMlDJxfjK2w/esLh22jf+tACb249PXtcaleC9fSB+Rcnr9fKmyKla8+y5/VGVu0LB3XTlYgpuv7BoK6HzfvHwt49Owe1n8KXbOpJ6fTCKiopQW1uL2traECHJ5OQkFAoFZDIZPzuabyvgR0e38MuhTVzRWopLW5Inpnt7exgfH0dHR0dcV/98NaEuNAJ4wGPP5IQnwOTYUj4yWJaFhz6YDywEwdVBr5/G00/OYGXShMvLt1AEYHFxFyUlJVAqlQc+E4Ig0FauQFu5ApedO7/5RZknfqxdPrZShSBf7WsK6bPMv08vAWTqYsaZBGu1WpSVlRXURVMIuCgui8USMu9HURQ8Hk9W94UjgC1lCgyt2njyx7IsTi/b0FGhRHGEmRaby4//eW0Nd/RXoeRcVBIXxXfo0CGUlpYeeA0HIZWQrz8zj5+f3cAP7ulHbRJRcMB5Ik8QBP7w4YsFvSZd5A8AHh/fSfq1sRAsJOHEHpubm5BIJJicnORbxelMJEkFdw5UobdGjcOVyY9vcK3wI0eOJOwdKcSEmnteJmcHC80HkKt+B+Oattx7SEYDwzB4bi2A6cAW7r0oeaNzqZjCey9phFImgkxMwe/3861iu90OpVIJnU4XV7n/pdvaBe93IZEWDjRN55WzQKFV2IECJ4CZwNraGlZXV9Hb24udnZ2cqHEzCW7eTyaThWTfArGj4DIFbpvXdpSFqGG397z4w8QOHN4Arjh08KLv9AXgoxk4vAGUKCTY2trCwsJCxCg+hmGxZnOjVlfEby9e6+DS1lI8OWlEuSq2zc/sjgNf/sMs/u2ObhRJQt+T25bQi2vw/Fg6LsgvPySsPZ0sOKNwt9uNEydO8BnWwYkkyQpJ0gmZmMKR6uRFA2tra9ja2kJfX19a2jtCTKgzkUhSaDeoXO6vn2awY/fivT8ZxX/e1Y0qTXy7L4ZhcLxKiobm6ItPoQjO/BaLxXx1kGX3lftmsxkjIyMAwJPBSNVBIShkAphvLeBC+41dIIDnwM2NMQyDo0ePgqKonBkyZwoulwvDw8Ooq6uLqGTOJQEMR7lahruOVoeIQIJRpZHjw1c28SRkd3c36pzm2MYenps149aeCpAkKagS0l2lxiMfOB73ec9MGzG5ZcfmrgdN+lDiKbSVn6l5v0zOSNE0jbGxMRQVFaGrq4vfZ4lEckBIwhFCoUKSfAFX3XS5XOjt7c3IzSaWCXX4gqDQTagTRS5vpj8/u4klsxu+AIM5o1MQAWRZFqVFFOp0mcsPD1buNzQ0wO/37yuLz1UHFQoFn0oidLFSqAQw3/Y73/ZHCAqaAKbr4sANdpeXl6O2tpZ/X4qi4PV607KNZJDOCyA373f48OGo80u5ILyxSGdDaWxHda6aWVRUFHNOs9WggIgiUKmWYetcuku68O4Tdbi9rypi0LsQAphrsUcy8Hq9GBkZQWVlJaqqIptbA8kJSfIFDMNgfHwcUqk0hOBmGrFMqLnrQbJkMN71hGZYfOyXE7j5sAFXt6VexUoGLMvipQUrLmrU5pQAdlep0F2pxEPXNEU0gY6EXBAAsVgMg8EAg8EAlmXhcOxnFo+NjYFlWWi1WpSUlEClUkX9LAuRuAD5VwF0uVwpp4BkGwVNANMBzieuo6MDWm2oq7xIJILT6czJfnGVqlQvgFxyidFojGuHkk8VwHhwu90YGhpCbW1tTBIC7LcAOypUB7bnpxl84fczeFt/Jf/3RCGiyBDyF/ydxTu2QiR/nNK3tbU14QjESEKSjY0NXkhSWlqK0tLSnGdOczYver0etbW1OduPSK3iYEKY7rxi5hz5emXRljMC+NS0CZ97bBYPXtmAuiSvfyzLYnLLgVqdPGFPPA6dMXz3Ym030f19dGwbP3h1HT+6uyflGD6CIKBUKqFUKlFfX89XB9fX1zE1NQWFQsG3i4Org5FmLQsB+UZcHQ5HXmTLJ4L/swQwmBhFi3TLZQs4UgxdoghOLhkYGIj7Xrk43mQsb6xWKyYmJtDZ2QmNRpPQa4NJmcMbwLOzJrj8NP7xts6E3icSRtd3Mbq+hzf3VKJIQsWsAKZT7JEtmM1mzM7OoqurK+WVbriQxG63w2Qy4ezZsyAIgieDwZ5o2UA0m5dcI1KrODirWEirOB5BEVMknnzgGKQ5zAO+uFGH+y+pw7XtekyPriX13bv9DIbX7XB4Azhan9mouGAkQ0hemrfCTzOIdZgMy8IbYCAPszB6acGC7728hn95awdUsoO38ljVQYZheDJYaHNrHPKtApiOGLhso6AJYLInLUeMpFJpTGKUSwLIxcElWw3h5v1qamoEG/LmugLo9tEwOrwxVberq6tYX19POoc5eHvaIgn+5z0D0KRo9cJBIxdDTJGQULErgCzLIhAI8M8pBKRbCBGM4LkmLjHBZDJhcXERTqcza0KSRGxecgUu+o2r+olEIsEm1ELmURO1L0k3iiQU3nE0dkVfyHtc36GHIkb8IgAsml14dcmGNx0ui+g0kCiSIVJfuLUt7nPu+cEw/DSLH93TE2KRZXMHzp0P+/92+egDQjQOkaqDVqsVGxsbcLvdGBsb442oC8XHLt8MrAvNBBoocAKYDBKJdMuHCmAy4NraiVbIMk0ALU7fgVk5Imgm7/7/GYLbx+C/7+k7YNjLMAympqZ4U+7wH77F6cO7f/A6PntTG/pqNVH3IbwqZ4ij8k0ENboi1ASR1/BtFWLLl2VZzMzMwOfzZUwIweHf/riAn55ex/MfvziukKS0tBRyefqG7U0mE+bm5hKyefHTDNZtHtTp5Fn5Lq/72sswOnx49aFLIKZC1ftAdBNqbrHBsmzBWcEkC62A9BgRSYAiiZBUoVSQqZbkW3vK8dKi9YA/6o2dZbixc79KfXrFhm89v4KPXtkQMzaOg1gs5ivwdrsddXV1EauDSqUybxep+WZg7XQ6L8wA5jO4SLeuri5Bgc25JoCJkjGWZbG8vIydnZ2k4s8yebyvLlrwszMbeN8l9Wg1nF8lBW/zcze3Y2xj7wD54+LFSkpK0N7efuBm6wsw8PgZ+GkW6zYP+mKMbWWzyhlMAH0BGntuH9QyUcGQP5qmMTo6CqVSidbW1ozv8w9fXQXLAlTQdqIJSSYnJ3khSWlpKdRqteCbgdHhhV5x/reRbHVz1erG2IYdSpkIJRFEQOlGd5UKf5w2hZC/SIg0O2i32+F0OkGSJPx+f05MqPMNNVo5arTpW0Rkapbu1iPluPVIOYD9c65KIzug8K/RyKGWi2BQJn4ehlcHg+dz9/b2UFxczCuL88l3Lx9bwBcIYBYh9MfGVTEcDkdCkW5cFnAukCgZ42w5RCKRoHm/aNvMFDk6ZFCiq0qJam1oxY27IVldPqyYXbix0xDyd65i29zcHHEm68mJHUxu23HfxfV47C8virsf2SSA3LZYlsU1X3kJAYbFUx86nvKwdzrxvZdW8OysGf/1rp6Qm4rH48HIyAiqq6vjVsrThTOfuizucyIJSTY3N/kh93hCkvENO/78+6/j3uM1+NAVDZifn4fT6UyqullzLt5Ql6Ws4i+/JfE5VZIksbu7i8nJSXR3d6O4uJi3mUnWhNrq8kMlE8WNZORgcvigloviEtdCR6TounRi1erGJ349hctbdHjfybqQvxlUUmiLxPiPF1fxqeuasWP3okyZHFkLn891Op0wm80YHx8HwzAhyuJcLyDyaSHtdDoFFZbyCQVNAIWAqx5ptdqEI93yYQZQCNxuN4aHh1FVVcWH0yeD4HZsuiETk3hhzoLJLQf+IUhwwamdX5634PSKDYerVHybeGdnB3Nzc+ju7o46W9FqUGDZ4oJcLOxCZPUwIPa80GZhNpz7PGmaxqeubcLLSzZIRPmzYgWA/3hheX92Kegxu92OsbExtLW1HVDG5xOiCUmGhoYAIKKQpFFfhBZ9Ma5pL8X4+DjEYjG6u7tBEAT8NINXl6zoqlQJmoUTU2RIJVEInL4A5GIqazm2XIJJT08P3zKPF1EXiwy6/TRu/PdTkIpI/Okj8Rdc3gCDW799GhRJ4LkH4z+/kMG1gE0OH56YNOLWbkPSKuRwuHw0NnY9uOlwGa4+tK/Q3nX7MbJux8kmLQiCgIQioVdIcGrJhu+8tILeajX0Sglu762I+r7xRgIIgoBCoYBCoUBdXR0CgQCsViu2trYwPT2N4uJivl2cT9XBXOCCDUyegYt0a21thV6feIRQIiQs3RBKPi0WCyYnJyPa2CSKTK6mZGIKXVUqXHEo1F6C+4yvbi9DT40GumIJWJbF4uIizGYzBgYGYrbl6kqKcN/JesH78cKqG0VmM9rrypM9FMEgCAJutxsKhQLXdBhwTYch/ouyjBc/fhIszg+vc4SBqxYVChIRkvzkniMRbV58AQZWl/9cxSr9VT1vgMYfp00wKKVZUadubGxgfX09amtbqAk193eSJCEXU+iuUuHtfdFJRTCkIhLXtJXiqkPJZzAXCjgRiNNHw+un4fEzSHB9EBVDa3t4ft6Cdx2tgkG1/6b/c3oDLy9a0awvQoVahoeuaQKwTwwvadLh7NouFkxkTAKY6NyiSCSCXq+HXq/nq4MWiwUTExMIBAL8uEYiIxlvFDgcjgsVwHxBcKRbst48uSwvx2vHsiyLlZUVbG1tJa2IzTY+dGXTgce4NqlERKJSI+Nb2WKx+EBUXTpwVaMSiiR+pAzD4mevr6OlTBFTZAKcF3vo9XosLS1haWkpb02P99t4+/uzsrICo9GYEaVvthEtkWRubg4ejwcGg+HAorBYKsL1HWUQCXX+TRBSEYVDZQpUCkiVSAWcxdXu7i76+voEt7ajmVAHK4tJksQ3396Z0O/ycze1Jn4QWYLHT+NbL6zg3uPVKZN+jkxV6+R494n0+kcO1KpRpZGhIigZ6a7BKgzWaVCuCmWZarkY7zxWjTsH4o9upCJcCa4OciMZVqsV29vbmJ2dhVwu55XF/xeqg06nExUVwhZG+YKCJoCRbqSRIt0KEbEqgDRNY3x8HCRJYnBwsKBXWsEzeR6PB0NDQym3smNBWyRGsYwCw7AgE7jRkyQBmmGxanXFJIDBSl+tVgudTnfA9FipVEKv10On0+Xc9Jjb5+npaQQCAfT29qb9fPIFGMybnGgvz83qmBOSiMVimM1mtLe3w+fzRRSSZHpOLVgAlQlw3yVN0+ju7k76u4xnQh3JZqYQ8frqHn47uo06rRy39aTWFcikn55ERB6ImFPJROivjW5XJORcTqdyObw66HK5YDab+eogNzuYjupgPqrZL/gA5gDBSktuFq6ioiIk0q0QEY0AciSpsrISNTU1BX2MwHkCaLPZMD4+jvb29oQTJhLd3rdf3sLLqwv42fuOQnnOQJVlWSyZXagvKYr6md51NDYpjWbzEj6rtre3B5PJhOXlZVAUxefj5sJFnovTU6vVOHTokKDz6WvPLODHr63juY9eLEjQ8sGfjuD1lV385v5jgjJVM4HF9W387vQs3nFlD9TK/Yt0LCFJLv3QVixuqGQiaBIUl3ALw6KiIsHfpRDEahULEZLYXH6o5SJB+/PsrBl/+9gMfn5ff1r2PR6O1Wvw1bd1okWf+rgDwzAQiQrrlpop6xqCIFBcXIzi4uKQ6uDOzg5fHeRmB5PpXuWjebXL5bpAAHOFWJFuqSIXJxunjg0Gl4CRiWPMFUiShN1ux+TkJPr6+iJ6uwn5/G0uv6AbJkEQqFCJQJIEioNMUxdMLvxxyoir2vVojJNBHAlCkz0IgoBarYZarUZTUxM8Hg9MJhOmp6fh9Xr5apRGo8l4ZYVT+tbU1CTUunhh3gKGZSGihP0mPn1dKx4d20alOkobiGUBlxmEdxcgKLCKMkCcPjK8vr6Osdk1lFfXgxCH7kM0Icnw8DCAyEKSdMNPM6AZFjIxBYZlcXZtF3IxiWvbhSeRcPF1ZWVlGauec4hUHQwXknBE0O6lcdM3X0NjaRF+eHdP3Pfe3PWCYfcNr7MBiiSSin2LhHwkJfGQrTi1aNVBzts10epgvlnAAPszgIU0Nw28AQggy7JYWFiAyWRKyvsuHtKVyZsogiuALMtidXUVGxsbWZn3y9bxcnOMbrcbJ0+ejLh6Njm8+MuHR/D+S+pxxaHIQp7R9T186tfj+ODljbihM7bQgiRJ3NCqxvuuOhzyeK1OjisOlSblC5ZKsodMJkN1dTWqq6tB0zQsFgu2t7cxPT2d0XxcLvWivb094Ti9n943kNDzG0qL8MDlDZH/6HOBXHoWhHMbALFPBgkSTGUf2LJOxMzIigPu2uBwOHDDyX4QJBXTuiRYSKKvrMXjY5uolJAZTyS56MsvgGVZnP7kpSAJApe1lAhWtQP7RH54eBj19fUwGLIrNIpWHeRIoZxi0VAiw/svrhFENu4cqORn15Yzu+tph1AyxbAsfje+gytaStKSQJIKcpGnG14dpGk6pDook8n42cFo97p8SwEBLrSAc4LR0dGUvO/igaIoBAKBrLeDOALIzTSyLBsxASNT2810K4OrWMjlcqjV6qjbE1MkCCK2IKdOt2/oerhSFXe70XwAxRSJ5rLEf7zcd5QOc2eKokJWyQ6HA0ajEWfPngVJkiGt4lS2tbOzg4WFhYRSLzIClgG59AwI9y6gDBpYZwIg10+BkRSD1UYhjnHA/W6CbV4SwTeeXcT/vr6B/3pnD450V2U0keTNR8qxanXz+5hINKHT6cTo6CgOHTqUF12BSNXB/37nEZ4YBgIB/jmxrtf5OOMVD0LJ1MSmA995cRW77gD+fDC12LtUkQsCGA5uDKa0tJSvDlosFr46qNFoUFJSEtIVybcUEOCCD2BO0NramlGFUa68ACmKgs/nw2uvvYby8vKszTRmwyjZ6XRieHgYjY2NUKvVmJycBLBvX/Dgz0bx0LUtaDsnGFDLxfif9wzGfD+VXIxv3tUjaNskSfLVulSQ6Vi3YHf+xsZGeL1eXsXqdruh1WpRWloKrVYr+ELIVVxNJhP6+/v5qqLHTx9IX8kGCMcOCMcOoAq7CZIiQF4CcvMsaE19wlVAv9+P0dFRlJSUoK6uLv4LIuD9l9Shu0qFrqr9RUV4Ionb7YbRaMTk5CR8Ph9KSkoSTiTh8JkbklPJ2mw2TE5OoqurKy8rD6nMDhZiO1XoPndUKPCJa5vQXZlessCwLEbW91AsEaGlTFgrMh8IYDCCq4M1NTV8dZC79nHVQalUmncVwAszgDmAXC7PKGHJFQF0Op3Y2dlBb29vRkUR4chkGgjLsjCbzZienkZXVxdUKhV8Ph+/PZePhsdPY9Hs4glgNFicPmiLxAnfJNJhds2Rv2DT3FQRK8gdAKRSKaqqqlBVtV+NslgsMBqNmJmZQXFxMb+CjlapZhgG09PTYBgmROk7vmHHxNYebugUZlobYBj81S8ncNuRClzakqK3m8u0T/YiQSwH7JuA3w1IhFcp09UO1RZJcOPh6K+Xy+V8IglN0zCbzdjY2MDXnhjDxfUKdNSVZ1RIYjQasbCwgN7e3oKwgAKEzQ5yv6d4ZIpmWMFJJNmCUDJFEgQuaki8WrtgcuFPs2bcfaz6wLF//5U1rFld8AZYMOz+6AxFkfj7m1pRqoh+DuYbAQxHcHUQAD87uLS0BLfbjdnZ2QPVwVzhQgv4DYhcEMDV1VWsrKzwNiLZRKbMr71+Gh9/+DRKxT588rajfNU2uOJYoZbhJ3GqfQBgtHvx3h8NobtKhd4aNW7uLhds35FqhTNY7JEu8je15cB7fzyMB69qxFt64osxuHYw1zJxOp0wGo18AgbXRi4uLgZBEAgEAhgZGYFWq0V9fX3IPs8ZHfjSH+bRW6NGsz7+xWvPE8ALcxaMru/hqQ+fSPqY9w9EtD/zFwksu1/5S+CiziWYcHONa1Y3FkxOnGwuyWjyBkVRKCsrg1+iwiO/MWEtwOKTZe60CEkiEZ319XVsbm6ir68v6zZCJocPT00Z8fb+ypTO/eDqYDAB5KrqXJU+EkG58Run4AkwePKBY3lFAjMdBffwmQ1Mbjnwtt4K3r2AQ51Ohm27F++9uAp7ngA+//g8KIZGIM61Lt8JYDiKiopQVFSE4uJimEwm6HQ6vjoolUr52cFUxzKSgd/vLzj/1IIngJluE2STADIMg8nJSdA0jSNHjmBmZiYr2w1GJlrADMNgZmoCfr8fbW31kEqlYFkWX/7DLE4v2yAKOPGTo9Ff/87/Og2AwA/v3beGKCmWoLNCiUPlCqxa3fD6mYQIYLLzRUKVvomiXCWFiCLQKrBtE4xgM9YxuxyBQADVUhILCwv8TMru7i4aGxsjKn0NKhnEFAm5WNil4IU5Cx68sgFv6U09H5hVloNgabAsAxBh3593F6yyAhAJq26ZzWbMzs6GJJhMbNnh8GZv8ValkeFrd3Sho0IJTZE4YiKJWq3mPSDjtbB23X48PW3CQK0GtTo5n5Czt7eXVHZxOvC1Py3g8Qkj+ms1gtuM8cAREO5//X4/xsfHodfrI7aKjzdo8NycJa/IHwB+HCRT+OiVDbC5/QfI3+j6Hup0Rbiidb9KZlAB33lHtyBD83xU0woBTdMQi8U84QPAzw7OzMzA6/XyBRSNRpOVYyy0kQXgDUAAMw2RSJQVAuj1ejE0NASDwYC6ujr4/f6Mz+JFQroJL3dc5eXlEBcxeHrahNv7z7cwLC4f1KQQQnb+OSRJ4PNv7gDNsPDTTELza8m2gIPFHuleMWuKxHjmIylW04BzMXpiVFaWoLKyElarFWNjY1Cr1VheXsbOzg5fjeIqsMcbtHjpr04K3sZFjVqwLNIzMyjTgNG3gzBOAMVlAHVu9ezZAwIeMBW9gt4mWuTZNW16sEDWcncB4ERTaMU+WiLJ/Pw8JBIJ9Hp9VCGJTExCJiKhlFFgWRZTU1NgWTYlg+dU8eBVTbiytRTN+syIh/x+P4aHh0M+s+CRCwD41DUN+PS1jXlXvYq2P78a3oJKJsJVYTGYiYIkCPz0zCZay4pxQ+e+RRDLsnhsfAciksDHrmrE66t7GNvYw/SOE5++rjnuWEe+fYZCEWm/ueog56hgs9lgNpt50VYmq4MsyxakcOkCAYwDTgWcSXAmyG1tbfxqJlezh+msAO7t7fEKxdLSUnxIXoIVi5snfw9d14qHrmvFSy+9FPN9fnhvZNsRiiRAkYkRkUSPL9Nij3Ti4iDysb29jaWlJQwMDEAul/PqOqPRiNHRUTAMw6uKE2lN6tMVbnoOTPVREBIFyO1RgPYDYMEWl4FpuBwoin3D5Gxe7HZ7xMgzgiCQzW8rwDD4/fgObjpsiEg6ExWSSEUUbjxsAE3TGBkZgUKhQGNjY07PQY1cjMtaUyMy0cAtFhsbG/mYvuBWsVgsPmAzw/03RVEZWZwlgmhzi3tuP+ye1O8hYoqAiCT4LGBg/xy/70QtJCISngCDXw1tgQULCUXGnCnmUKgEMF7lkqKokOqg2+2G2Wzmq4PByuJ0Vgfz+f4QCQVPAAu9BRwtszhTs3jxkK7j3drawsLCAnp6eviWXEuZAi1JWK2kE4m0gAuJ/HFgWRbLy8uwWCwhM2LB6rr6+nr4/X6YTCYsLS3B4XAk1JqMB2+AhlR0/j1YlsWjY9u4pk1/sHJIkGANh0Hr2wCfEyAoQBr/HOHGJSiKwpEjR/Liu/nF2U186Q9zoAgipoCEQ7iQJDiRpLi4GHq9HiqVCpOTkygvL0d1dbXgfXF6A1g0u9BRoRRUAfXRDH4/toP28mK0GoSpU/208NGLeHC5XBgZGYlrZ5OICXUsYrPr9kMupgQl2QhFNDJ19/H0GHMTBIEPXlZ/4PFgkce7T9SgTCkRJOgCCjO9BEicuMrl8hC/1d3dXZjNZiwsLEAikfCpJMnaYhVqK73wvvksI1MEkGEYTE1NwefzRcwsztUNLR0iibm5Oezt7WFwcDAvsm6DEX58bh+N2R0HNzweIQAA1SBJREFUuqtDMzUzNe+XLFw+Gk9NGXFpS0lUnzjunAKAnp6emBdIsViMiooKVFRUgGEY7O7uwmg08u0SrjWZqMJ0x+7FMzMmXNyoQ/U5U+1Xl2z4+8dmsGJx44OXRfH1I0WALHquaTA4UUtJSUleRT7efNgAEUniiiRafZE8IDc3NzE5OQmZTAa/3w+73S64WjtvcmFyy45anRwqWfzfoIgkwIIFwwr7LP00g0dGtqBXSHBZS2oVQU6809nZCZUqvpcnh3gm1NGqgwzL4o7vvg6KJPC7D8QYPk4Q+WBd01iaGIEp5ApgsvcWiqIOVOLNZjPm5ubg8XiSqg46nc6CSwEBLhDAuOD8+NIJr9eL4eFh6PV6tLe35/yiEYxUCC+XK1tUVIS+vr68Oi4O4TOAn3t0CmdXbfjhvf0wqPbJTr6RP2C/quYNMHB6AxEJIGeszXnfEQSBP06b8MqiBZ+8riVmFYgkSWi1Wr7ywrWKx8fHQdM035pUqVRxPwuVTAS9QgJtUCzfQJ0an7mhFZe1pmgbg/PxdXV1dQnZvPhpBgzLhlQm041iqQhv7RUeqcdh3ebBW779Gn54Ty9aDQrYvQGQBAGz2Yy+vj4UFRXBbDYnJCTpqFCgTiD5A/bny958RPi+iykSRWIKzSlm6FqtVkxPT4eId5JFvOpgsAn1DZ1lOJQmEQuHQiRThbjPQHorbsHVQW5Ol6sOBgtN5HJ51OtfIcbAAW8AAlhoLeDd3V2MjY3xc3H5hmQrgC6XC8PDw6irq0NlZeoK0Uwh/Pg+clUTXlm0oEy5P1eTSbFHKtAWSfC2vsifq9vtxsjICBoaGlBWdj4/9m8fnQLNAH91TTNIgbm9wP4wdV1dHS9GslgsWF1dhd1u349J0+tRUlIS8QIsE1O4MiyyT0SSuPVIueDtRwNXKWpra0s49eKxsW0EaBa3R/kMw/HivAXPz5nx0LXNGReRbO56wLAsliwuKGUi/G54FTrfDq45foT3FQuv1sYTkohIEmp5Zs9fIW3uWOC8DHt6etLuZRjPhPqDJ/fb6cEt41SRaRVwJlCoBDBT+x1pTtdisfDVQbVajZKSEmi12pDrXyF6AAJvAAKYaYhEorSJQNbX17GysnJg3i+fkAwBtFgsmJycxOHDh6FWC2vj5QrhM4AVahlu66kMqRbkS9VPCLg0iEjts8cfOA63L7U5LbFYDIPBAIPBAJZl+Vbx4uIixGJxTBVrOhHJ5iUR9Ndq4PELX8h99OfjYFgWH72qCRJRZs+FgToNXvvkpQCAjc1tFHmMuOKiHigUB48zuFrb0tICt9sNk8nEC0l0Oh30en1SiSTZxObmJtbW1rLmZRheHQz+P67SHymRJBGE+wD++3NLMDv9+JsbWtJyDJlAoRLAbM3cyeXyEAN+m80Gi8WCxcVFEASBp556CjfccAMCgUBSBPBnP/sZPve5z2FychKnTp3CwMB5weMXv/hFfPe73wVFUfjqV7+K6667DgBw5swZ3HPPPXC73bjxxhvxla98Jen71QUCGAfpqAByKQxerxeDg4MJDd1me66Eoih4vV7Bz19dXcXGxgb6+/tjruJZlsXzc2a0lClQoT74vESPc192v28Jkwgi2cAUotgD2BfaLC8vR02DKJaIUJxGX1KCIKDRaKDRaACEqlj9fn+IijWdnyFn89Lb25t07GONNjGC+vRHLsKeJ5BWkUA8rK2tYWtrC7dfEXt21hdgsGZzo6GkCHK5HDU1NXxsVriQJF5CTCbh8Abw+7EdnGjSoUpz/vzk4ggjKbezgUit4mBCGAgEQBAEKIpKiByFk6lnZsxRfc7zBRcIoHCEVwdtNhuef/55fPrTn8bq6irUajUeffRRXHHFFYIXqYcPH8Yvf/lLvP/97w95fGJiAg8//DDGx8exsbGBq6++GjMzM6AoCvfffz/+4z/+A8ePH8eNN96Ixx9/HDfccENSx1TwBDDfW8A+nw/Dw8MoKSlBW1tbQvvLVeOyeaILrQBygoNAIICBgYG4++gLMPj6MwuQikj88N0D8AUYfOinI7j1SDm0SRznn3/vDGiGxcP3DST1mXLIx3m/eOAMgXd3d9Hf358zFV+wijUQCMBisWB9fR2Tk5NQKpV8qzjZ/Qs2Ps4WWeDOA4VUJFhJmY5tLiwswOFwCDJ4nt1xYnh9F2q5GCVBDD+SkMRkMvGJJCUlJXFtfwIMA5Ig0tL25oJcuDUad5xOpzOuSEkonp8zQyMX85nNiSJSqzg4qzhWXnEkBH+u//uevpjP3XX7oY4i6ArHms2NCpXsgPn15JYdT0yY8L6TtbztSyKL6UIlgPmw3xqNBg8++CAefPBBPProo3jkkUfw3HPP4e/+7u+g0+lw/fXX4/rrr495329vb4/4+COPPII777wTUqkUDQ0NaG5uxqlTp1BfX4+9vT1cdNFFAIB3vetd+PWvf/1/lwBmGqkQQM4Hr7W1lfe1Smbb2SSAQo6XI7WlpaUHosWiQSqmsL3nBYj9CxRFEvDRDCa3HDipSpwAdlepMLK+lzBhCyaA+Uz+vAEaj4/v4IpDpSGD/AzDYGJiAiKRCEeOHMn5RZCDSCRCWVkZysrKwLIs9vb2sL2zgzOTCzAoz8+pCR19yIXNi5/e91Gr1spwojEzEYw0w+Lsqg2tBgVUMjFYlsXk5CQIgkB3d7eg42wxFENbLIauKDp5IAgCSqUSSqUSDQ0N8Pl8B4QkpaWlB2Y5L/3nFwEQCZmDR0OxRIS3nkuMYVkW09PTYFkWXV1dafk+WZbFZ387DYpE6rGE58BVB0UiUUQTaqE2M0Ds4sTMjhNPTRlx02ED6nSxq9M7di/+9/VNDNZqcElz6Hm55wkgwDDgNjW6vof/fHEFD13TxKvwYyEfiFQyyDfbFa/Xi87OTvzN3/wNgP1q/uOPP47PfOYz+PKXv4zGxsaE3m99fR3Hjx/n/11dXY319XWIxeIQOyju8WRxgQDGQbIEcGNjA0tLSyE+eMlsO9tpIPEqgHa7HaOjo2hpaUmY1H7vXb1w+vbbKyRYfPvPeyCmSJw+fVrwcTq8AdAMi09e35rQtjlwx8eyLD/bmU8XwG8/v4SfntnAD+7phdNLw+L08wSQU/rq9XrU1tbmeE+jgyAIqNVqbHsoWKxydNQoQXj3+DGIcMPjcHA2Lzqdjlc0ZwNiioSIQkhVLd1w+2lMbztBEgSOVCkxOjoKlUqFhoYGwccpoUhURhijiPkaiSSikISb5eRMwcvVspjEMhkwDIPx8XHI5XI0NTWl7fskCALfuLMrY5XaRE2oE0G1RoaeahXKVbFHGr71/DJeXbTiA5fVo7384IzZsXotjtWfF0SRJIHpHSe++qdFfOm2jrj7ke0OU7qQb8TV5XKFzABWV1fjvvvuw3333Yerr74aW1tbB17z+c9/HrfeemvE94vkVUsQRNTHk0XBE8BM3xwSjYJjGAYzMzNwu904evRoSu25XJhBxyKdOzs7mJubQ3d3d1IDr1//0yImNvfwn+/owdPTJmzuevDxa1oSIro/enUVNMPig5cntqIKRvCcTz5V/QBg2+4Fy7IoV0nx9oEqvuXDGeU2NTUlVU3OBepLikCRBGpKikCR6ohzagqFgm8Vi8Vi3ualtrYW5eWJKYcZlk25dfmWHuEKdl+AwZkVG/pq1YLtZRRSEW7pLoeIYHD27FlUVFSgqqpK8DZphk05Azfc9idYSPJQNw2dTg2LxQKNRpPyTZZLMeHIfLrRUSHMtDoWhLZMY9nMcOQw2GomFookVMwqM3cuswBAEBioFTZX21mhxMeuakSAETZ8SNN0XhEpoci3CqDD4eBno8Px1FNPJfx+1dXVWF1d5f+9traGyspKVFdXY21t7cDjyaLgCWCmkUh2rM/nw8jICDQaDXp6elImF7mIg4tEOrnZHYvFgoGBgaQHyksUYux5ArC4AuiuUsHi9ENMEQl9xjcdNsBHJzdZzeU1FhUV4dSpU/xMVLpFC6ngszcewmdvPBTymNVqxdTUFA4fPgylMvUbXrYgEZFoCvOJC59Ts9vt+wbUS8v48B9d6NQB/3BrW8Lkj2VZ/OzMBsQiIiESlwqMDi/mjU5UamSo0wlX9YsRwPDQcEjkmRDc/p+nsWpx4/mPXZxWcUokIcnW1hamp6dTEpL4/X4MDQ2hqqoqb62h7vreGVhdfjz6gWMJEevg6iBHcrljTGZ2MBh/nDFhZtuJey+qwf2X1OH+SxIjzte2Cz+n8q2SJhThiutcw+l0oqYmPYkvAHDLLbfgrrvuwkc/+lFsbGxgdnaWD4xQKpV45ZVXcOzYMfzgBz/AAw88kPR23hAEMFppNF3vLQRca7S5uTnEiy0V5IoABpMxmqYxOjoKqVSK/v7+lH50DSXFON6oQ31JETRFYvTXaSNuMxZqErjRBiNY6dfV1QWGYWCxWLCxsZE20UImsLm5yUcFptsrLdcgCAIqlQoqlWp/9fzHEVASOba3t3F6chEBsQKXdlRBq9UKmrcSUwQaSuKfH0tmFyrUUjw/a8ZgvVbwIH44KtUy3HqkAsVS4ZUIh8OB0dFRtLe3R60YRENHuQLLZldGlcnpEJIA+4bdw8MHSS7LsvAz+1m1+YBanRw2tz/pqmogEMDw8DAMBgM/mxXNhFpoXrFBKcWiyQVJAt6dyaIQvQvzEcn6AP7qV7/CAw88AKPRiJtuugk9PT144okn0NnZiTvuuAMdHR0QiUT4xje+wVc8v/nNb/I2MDfccEPSAhAAIOIQpzwXse/D5/NljAACwEsvvYQTJ6IPGXO5t8m2RqNhenqaH9TOFtxuNyYnJ9HX1wePx4OhoSHeJT1V+AIM9jx+lCpC517Gx8dRXV2dMQ/BeGIPTrRgNBphNpt5fzu9Xp8z0sVVXe12Ow4fPiyYlLIsCx/NZDTxIt3gSO6RI0d4m5efnVmDdc+Bk4b9eTUuG7ekpCQlS5OR9T2854dDuPVIOeq0chxt0OKQITsGrlzqRVdXV1JzwT9/fQO+AIM/G6zKyU2bE5KYTCY+PzqSkCRWru8vzm7A62dw52BVxg22Mwm3n8a/PDmLQeUuulvqYlasg02og+9T3GeWy0rWqVOncPRo+uLwsoXXXnsNg4ODud4NHp/4xCfwtre9DVdccUWudyUaIv7Y8qfUUYBgWRazs7Ow2+0Zyb3NZQXQZrNhfHwcHR0dCacuRINERB4gf8HbzASEiD040YJarUZzczPvbzc+Po6xHR8ubtkng0Ki0NIBmqYxMTEBiUSSsAL2zd96DVaXH09++HhOSOC6zQ0AqNLEVyCG29kEk4g391SCZljIxFTEShQnWiguLk7o82krV+BN3Qa861gNypSSrPn87ezsYHFxMaXUi1uOlCNA5y5vVoiQRC6XY25uLuq4wpEqFVas7oImfwAwuWHD05NbqD5aiWvjjCtEM6EOVhanakJ9AbnFhSzgHCKTLWAO4YPCnCJTpVJlLPc2FwSQoii4XC6+CpjphAcgMwQwFXNnzt9u2inHT+bmINew6PDsR6EJyWFNBdwcqcFg4GdKvAEaj45u4/LW0rgK1bf1V+K7Ly7nrAL4/JwFAHDnQGxhA+cjSRBERDsbMUVCfO4QIlmacFFoLpcLWq0Wer1eUKtYQpEHZiwzjdXVVezs7KSceiGhSEjypLAbSUiysrKCubk5yGQybG5uwu/3HxCSNJcp0FyWnYrrL89uwM+weHu/cJENh1WrGx/4nxH881s70RpWIfZ4PPBuzOArbzmEQ7XR4/BohgXDsiFJPPFMqBOxmUkHLrR/0wOHw3EhCu6NinBDZm7er6mpKaFA+mS2m00CyFU0/X4/Tpw4kbVZuHQfZ7qSPU40afE+Tz2u79SjWCLiqx5GoxHz8/OQyWS8v12yCRXBcDqd/BxpcE60x8/A5aNhcvjiEsB3HK3GO46m3q5PFjcJyIcNBAIYHR2FVqtNyuZFIpGgsrISlZWVYBgGVqsVRqMRMzMzKCoq4r+TXKRfBINlWZ6k9vT05JVqMd1wOByw2Ww4ceIExGIxLBYLtre3UxaScGBZFianD/oIHYRoYNgofa8I8Php/GZkCyebS1CplsHuCYBhAZvbH/I8rr0tZIbzzu+eAQsWP39v5FZlvLziVIQkb2Tk49yiy+UqKIEehwsEUAA4KxiKorC9vY35+fm0z/tFQjYrgH6/H8PDw9BoNJDJZFkVQqSzApjOWLd9I9sK/t/hVQ+n0wmj0YjR0VGwLJt0WxLYz1OemZlBZ2fngQuJWi7GO4+lT2GWSShlsc8br9eL4eFh1NTUoKKiIuZzhYAkSZSUlKCkpAQsy8LpdMJkMmFkZAQsywoWLUSDn04uS5mrcJIkmTbj43xFpFzfeEKS0tJSKJVKwZ/L7I4TLy5YcG27XtB4AQDc3idceUyzLLwBBnvuACrV+/Yyj33wWMhzOAFPpNztSOirVWPPLTxHPpbNDJCYCfUbGfmoXL7QAs4hshEH5/f7sby8jL29vYzM+8XabqbhdDp5xV55eTl2dnYytq1npo0gCeCy1n1l4IrFhT0fC7k8MgF0+Wg+4igesp3sUVxcjOLiYtTX1/MD8lzUVSJtyY2NDZyeXsXJ/m4olcmpnAsBDocDY2NjKK9txLPrflyv8UOTpAI3EgiCgEKhgEKhCPlOuPQLjUbDfydCqnEBhsHDp9ehlInw5iPCySqnnFer1YKTcgoV8XJ9t+1e/GlmD7ceqQ1JJFleXo4pJAlHrU4OH61BmVKakXz0Yoko5iJrb28P4+Pj6OrqgkKhwL8+PY8zK7v44T29UfflU9e1JL0/0aqDkUyoAwwLqfgNcSsXhHzzAASSVwHnGv93zpoUQBAExsbGoNVqMzbvFwnZqAByrbOuri5Bq9pU8cKcGThHAFmWxT8+MYsdmx3/cvNBryuHN4D/fH4JrQYFbuqKPWi9tevBAz8dxqeua8aRak2G9j46wgfkg9uSnIK1tLQ0ZOHAtQitew7861AAXx8dxh8+dFHW910odt1+iCgCxZLELxtchfPw4cNwMmIEmB34AplNuQn/Tmw2G4xGIz+nxlVso7XvRSQJtVyMzgrhF3YuJjHT3nc/e30DDMPi7XFmLYUgkUxaDuHt7WiLnD13AF4/jQDNAmJhQpJIkYEyMYXDlSqwLItrv/oKZGISv/3AsYjbTDdsNhumpqZw5MgRfib6hXkLGCY5Ijq97UBDaVFCVjjRqoNzOw78emQHb+8zoFpblFB1MNspU+lCPhJAmqazUhRKNy4QwDhwOBwwm82or69HU1NTVredyRlAlmWxvLyMnZ0dDA4OZmVeyuOn0VJWjBsP75M5giDg8AZARjGCLpZQqNMVobdGE/N9aZqG2+sDywJ2T3ZFM5EQ3pZ0OBwwGo0YGhoCQRC8iGRxcRFyuRwDvUfwfmYDR6qTJ+AeP42fn91Ef40a7WlIR4iE34xsQUwRuHMgsRnDYC9DqVQKBYB3HM1uS5skSeh0Ouh0++kLXKt4bGwMNE3zreLwtuQt3cINqd1uN4aHh7OS1sIwLNg0uHR949lF/OjUGn50T98B0+5oYFkWU1NTABC3vd1qUBwQUXCIlkjCRQbqdDqUlpaGCEn2K/vxRw3SBbPZjLm5OfT09ACUGD98dQ0dFQr84n3JWZBs7nrw6UcmMVinwSeTrBAGVwf1mmIUSUXY855vEwudHczHVqoQ5Nt+Z6IinS1cIIAxwEWf6fX6hE1b04FMVQC5bE6CIDAwMJC1H9P4ph0vzlvQalCir1YDAPjOO3uxtrYOlqVBMyzGNvbQVakCSe63cN8SY44neN6vRleEn943kJXjCIef3r/4RpoVC1awNjY2wuv1YmtrC6dPn4ZIJIJMJoPNZsPb+ytTuohQJLE/8J7AW9AMC5phBVuhXNZSCplY+LnCsiyWlpZgs9nQ19eXVwbbXPu+rq4Ofr8fZrMZKysrvNJbSFsyGHa7HWNjY+jo6MiYn2Uw3j5QBSYNzgcnm3R4ZHgLVRph1jQMw2BsbAzFxcVobGxM640vUiJJJCFJtqrkOzs7WFpaQm9vLyQSCRiWhYgioJYnv1guV0nxjqPVMWPgODwyvIVfD2/iG3d2Rx2D0Suk6KhU4VsvruEjVzbiUFkxViwuPHx6HfefrIFUREa1mck3IiUU+VgBLFQSmD9X5BSQ7g+ea2/YbDYMDAxgeXk563YsQGYIoNfrxdDQECoqKlBTU5PVk/ZIlQp/dW1LSJC9mCIhk4jgdvsxsWnH42PbkImpuOa86RR7pIo3f+s1EATwqICWlN/vx+bmJrq7u6HRaGCxWLC2voGzY5Mo06qSTiMRUyT+PEH17/+eWYePZnH3cWHVuFqdcEsgTgQBIKLNSzy4fDSsLp/ggf9UIBaLUV5ejvLy8pC25MLCAqRSKd8qjubfx7W3u7u7szYIvmP34s3fOoX3XFyL95xIPmP3SLVaMKGiaRrDw8MoLS1FbW0t/3iAYSBKgUj4Agx+NbSJKw6Voky5344XkkiSqJAkEXDClt7eXr61RxIE7hpMTWFPEARu6xE2T2px+sCwLCSi2Md3tF4Lb4BBk74YJEliatsJsysAP0tCKZEcyCsGzt9b8o1ICUGhEtd8xBuCAKYTgUAAIyMjKC4uRn9/PwiC4FXA2QZFUWmd09jd3cXY2Bja2tpipotw2bzp/pGJKBK1EaLcOBXwIYMCMnFl3DivbIs94qGvVg1xnNgmt5/Grf/+Ck6WM/joTb38wLBer8dTS164SAV6qtSwmE1YWlri00g4c92M7HeNGhZX+kVGnM2LRqNJWgRxzVdfBs2weO5jF6ccG5bI6jy4LdnS0gKXywWTyYSJiQl4fT4Uq3WoqzTwpuDb29tYXl7m29vZQrF0P1asQhW9csewbNoMl7lc3+rq6hD1tsnhw29GtnDloVLUC4jhiwRvgIHTR2N7z8sTwGBE8oGMJCTR6XRpqTKvra1hZ2cHvb29Oa1a33uiFveeqI37PI1cjDcFzUhf21GGK9v0/O8m3ISaaxN7PB4AoeriQkC+EVe/31+Q83/ABQIYAk4N29DQEHKRoyiKT5PIJtJZAdzc3MTi4iJ6e3sPDFiHgyNk2bogcNuTiEi0xDGJDSZ/2dg/py+AIjEVk0D8vze18f9tcvjwh4kd3HqkHMXS8z+vnc0N+Px+QGE4oBa7uk2PbbsXOq0KOq2GTyMxmUyYnJyE3+/nZ9Q44vHCvBkrZndKsWCHytM/KxjN5uUXZzfgo1n8mUDRwlfedhjD63tpIX8n/ukFiEgCz3/sZMKvLyoqQm1tLWpra/HjV1dgXLbjisAqXA47//vMNvkD9lWrL348+vEYHV48NrqNazvKQiruySBari8AyMUkZGIypZk8pUyEdwsgOhySFZIIATeycOTIkbwiGYmAJIiIOcKcQEQkEsHlcmFubg5NTU0FZzOTbxXAQrWAAd4gBDAdFaBYaths2bGEIx0iEM7c2eFw4OjRo4JWtNyNLZtG0EIqnVwrI1urVavLh3d+/yyON2jxmRtaBb3G4Q3AE2DgCTAolp7//D0eD55+8JKINxW9Ugp9WOUjeB4qEAjAbDZjdfV8GsnEFgmJXB7z3J/acuDhM+v46+tbkvKySxSczUtraysvtuDgDTBIZGRtoE6DgTpNyvtEEPuzkclWp4JxbYcByxYVumvVmJubw+7uLrRaLYaHh3niodfrs5KeEw9iioREREKaYNTd+MYeFDIR6s5V6mPl+gJAsVSUcls0FSQjJIkELnvb6XSiu7s7rwhGuuF2uzEyMoK2tjZ+tj2WzUy+VQfzrQLocDguEMBCBffDt1gsUdWwFEXx5fJsItUKINfOVigU6O2N7lcVjkxm80ZCvFZ3rub91HIxpCIS17bHVnTuefx4bdmGK1v322BcNYOmaX5gPhUzYJFIBIPBAIPBAJZlYbPZcLnICItlE0ND1qhpJD94dRXPz1nwwUvrDxDMdMNqtWJ6ehqHDx+O6IeVS5Lw0l9dkpb30SulKCkWY2JiAiKRiB8RARBSsfX5fHzFVq1WJ/W9r1jcEFMEKpKs3mnk4qQ+81NLNogpAnXHinhhS7Rc33yEUCFJ8HWeZVnMzMyApml0dXUBAG779il0Varw90HV/XDM7jigkolhUGW3+psKgpNMgsVKhWRCnW8EsFA9AIH/4wSQm1WSy+Xo7++PemLnIpMXSI2IuVwuDA8Po66uLmE/smwfb6zj5MhfsJIta/tFEILsHv792SU8M2NCU2kxX2niWqHV1dVp9YMjCOJAGonJZOLTSIKTLz57YyvMTn/Gyd/W1hZWVlZy0grNJmiaxsjISMQIu3DiYTabsbGxgcnJSSiVSl5VLHRW6OlpIyiSwLsEJMD4AgyemNjBJS0lKRtr39FfCYokeEJ/5MiRpFqp+YBwIQmX3BOcElNSUoK1tTWIRCK0t7fz3ynDAqMbe1Hfm2FZPDtrhlREFkxKj9PpxMjISNwkk0RMqHNRHWQYJq8cBVwu14UKYC6RDClIhCDlSgSSLNkxm82YmprC4cOHk7KkyHYFMNr2wuf9ci32ACLPBL7/kjocq9ei7pxKlqucHDp06EArNN0ItzPhZqGcTidIuQqN1QYwjCQjF2nOS9JqteadzUu6kYjBM0VRKCsrQ1lZGViWxd7eHta3drCysgKKovhWcSxidWt3OURxhEUcdj1+bOx6sGHzpEwAi6UiGI1GLCwsoKenJ6ryOVX4aAbTWw50VirTJlSJheCUmIaGBvj9fp4MMgyD0tJSGI1GXkjyyF8cjfl+5Dk1byK2SOHIpnUIF2OXTDU3XnUwEAjwz8kGGcy3CuCFFnCBgZv3E0qQclUBTAYrKyvY3NxEf39/0hfvXFQAw7eXLaUvy7J4YtKIvhp1RAViMHwBBj8+tYZShQRv6TlPArRFElxxqBQAYDKZMDc3l1VLEA5isZgfjjc7vPjvF+axaFtHnXQ2ahpJsmAYBtPT02BZNimbl0JBgGHgP1fNbW5uRmlpaUKvJwgCQ9t+zBgluOtoHygmIGhGTVcs3GtOr5Di7uM1gv0cY2FjYwPr6+shub6ZwNyOEy/MW6ApEqNGu79w8tEM7vjP03j3idqEDLiTAUmS2NnZQU1NDerq6rC7uwuj0ZiQkKQkge8oHDPbDnzusWl84db2uPOpkYiize2HUioCRca/LnILUi7GLhVEqw4Gq4u552WqOpiPBPBCC7gAwBnTGo1GDAwMCG5X5UoFnAgYhsHk5CRomsbAwEBKP5BcVwCzKfawuf3492cX0V6uxD/e1hHzuRIRiTaDAocMkVfQq6ur2N7eRl9fX1aSVWJBVyzB5R2VaClTQCGl+PYXl0bCVaGSIalcKzRZmxeaYXF62Yb2CgVUsvy1T6AZFv/xpznYTNv44HXdSRs8HypXwOb2n6sci1BdXY3q6uoDM2oKhYInHomSL5k49Rvi/zw/ga+/vIPHHziRcVuLlrJiqGQiVAYZUJMEsOcJ4Men1jJKADk/w7KyMlRX789JajQaXhCRrJAkEQQYFgSx/7+x8E9PzWFy04Fv3tXNK+J9NIOHfjkBuZjCV+44jF23H4ooZJDLMM7UgjS8Ohj8fxxxTTcZzEcV8AUCmEMIuQEFAgGMjY1BIpEknH6R7xVAn8+HoaEh6PX6tITPp9t/ENgn34+ObqFaKz8Q7cYRQG7ez+0LQBbHeiUaHh/fhkIqwsnm6D6HwdAWSfC3Nx1CU6mwi+OlLQcrQNwQuc/nQ19fX15cnAiC4NNWAIS0v7xeL0wmE69O1ul0vGAh3r5Hs3lJBHZvAK+v7oJhWVwkIBEhV9i1WWE2buO6gdaU0j3KVTLceuTgZxXJ7DgSSS8qKspoq5Azvn9xwQaCFGXl/BVTJKq1oWppEUnijx85kdHt+v1+vpUf7fyNJSQpKiriK+mpLPI6KpT48b39cZ+nkolBEIA4iNxJKBKXtujQV62GL8Dgi4/PYnzLjh/c3Qtt0fl92t3dxeTkZNbmOCO1ioMJYSAQAEEQoCgqpXMs3yqALpfrAgHMZ3DzfjU1NfyKLxHkmgDGmhWx2+0YGRlBa2tr2vJHM5VBfHZ1F2Mb9qgEkGEYfO+lZbw4b8U/396Z1DzT919ZA0lAMAEEgP4gopQouIWFUqlEa2trXswpxoNUKkVVVRWqqqr4G9zm5iampqagVCqjppE4nU6Mjo5GtHlJBBq5GG/vrzzgHcewLAK08Gi6TIITtjz05qNZEbZEigzkxglcLhdfhdJqtSndPG1uf8jvKjjX92vvuqggzt9kwS2U6+vrUVZWJug1sYQk3OxgJhNJ3neyDu87uZ/0EmzsHZyl3awvhsnpg8tHQ1u0XyHcMlqwsTSHI0eO5MSWKFKrOLhNnEqrON8qgA6HI+PZ35nCG4YAEgQBNoLRGCeI6OzsTDrPN5cEkKvGRVrxbG9vY35+HkeOHEnrCiQTLWCCIPDRq5rx9WcX8OqiBccadCF/83g82NvbQ1+NGmdWdqGUJndqfu3thyHO0sXB4/FgZGREcDVsdseBIgmVlXgzoQi/we3t7cFkOp9GwlWhPB5PTJuXRBFpxu2yf3kRDAs8/7GLsyIMiIaVlRWYTCZBwpYnJ41Ys7lx9/GatO5zMElnGAZWqxV/HFuDnJ5Gbakiop1JPMwZnXhiYgc3dhrQUFqU0VzffANnZt3c3BwzBSkWIglJghNJVKr9KMd0JZIEY8nswv/3+xk8cHkDjlSHVqPvO1mH+06ejwP821+PwWix4qvvOJoXnpRAqAl1cHWQu68mYjOTbxVAp9OJhoaGXO9GUnjDEMBwcArFnZ2dhOb9IoEkyYjkMhvgqnHBJzznXWi1WjE4OJj2eZ1MEV65hMKGzYPfjGzxBJBlWbAsi+bmZiwuLsLtcuFDvTrs2qxJzdzoFdmxIeEGq9va2iIa5IaDZVl86H/HQBIEHvtg/MzgbMJP75N9MUVCrVZDrVajqamJn4UaGhqC2+1GZWVliDAn3XhTdzn+NG0CeW4xl4lteAM0/vOFFdx7ogbFktDLH8uymJubg8fjQU9Pj6Bzb8/j31epZ5A8kSQJpVqLfz01AYok8Pv3N8JoNPK5uBwZVCgUMT+zKo0MvTVqVKilUXN9c4WZbQfmTU5c31GW9u/d7XZjeHg4qpl1oli3uaGUiaCSnc+QZlk2rYkk4ZCLKYgpkk8XenHeArvHj+s7DSHP+/vfjMJis+HOi1tRlCfkLxzB1UGxWJywzUy+EcALLeA8A2fAKxKJEp73yzeEkzGapjE6OgqZTJaxebNMtYApksC/vq0L3OU9eAXIXUhpmobVasXW1hamp6djtiSzgZH1PdRoZSGzNUajka+8Cr24EwSBv73pEFQpRGYli2WLC9oicVTBxXVfewUADsxfyWQy0DQNqVSK3t5e7O7uhqSRcNWOdF2MH7qmGQ9d04w1qxu/G9/GbT0VaSf0f5ox40en1mBQSeD2MbiqTY8qjQwMw2BiYgISiQSHDx8WTELe2ps+j8dYkIhIfOHWdjSUFkGhKOKrUD6fL8T6R6vV8q3i8O9FLqZwolEHv9+P118/mOsrBH/1y3FUqmV48KqmuM91+2nc8s1TeODyhriijpcWLfD60y88E+p9JxQ0w+I3I9uQS0jcc/w8cSYIgheSNDc3w+PxhAhJtFot9Hp90kISg0qKb/5ZN//vh0+vg2bYEAJoMpmwtG2FTqvD1R3JzefmAomaUOdbC/iCCCQPwLWAudVeVVUVamoKw6AzFoIJoNvtxtDQUNKzjIlsM1PRdxRJhPzAwy1eOJ+00tJSviVpNBr5liTXrsyUP1kwvAEaz8+ZYVBJcfu5G/3KygqMRiP6+/sTrrweb0i9+pAo/DSD343toEhC4u7jkSs9xxu0B2LaWJbF9PQ0aJrmq2EymYxPI+FsM+bn5yGVSvnvJR3zclIRCRFJZqSVf+WhUqhkIhwyKPDTMxvY2vPAoBBhdHQUWq0W9fX1ad9munB560EBkkQiQWVlJSorK8EwDGw2G4xGI+bm5iCTyQ6kxMTK9RWC08s2EAQhiABSBIEAw+KFOXNcAvjOozVgkd6qbzrtTzhQJIGbDhugkse+dcpkshC1t9Vqxc7OToiQpKSkJOnfyz+8uT1EQcxZ2Hzr7uM5dyBIBUJsZgKBAN9CzgciWMhZwESc1mZu+p5JgDP2nJqaQkdHR1pK/cF46aWXcOJEZhVqkTA2Noba2lrQNI2JiYmMHFs4tre3Ybfb0dzcnPb3TiXWzeVywWg0wmg08gPYXOpFpuaXtve8UMtFkFAEZmZmEAgE0NHRkRcXHqFYtbqhkYsPiC6igasyq1QqNDQ0xP1sue/FZDIhEAhApS1BdYUho99LOJ6eMiLAsLiuQ9hwPwfO4DmZalg+g2XZkO+FYRioVCqYzWa0t7cnLeJhzt0vcjGj6QswAAHeDiUWbDYbpqam0N3dHbNKHy6KYTLczueEJCaTif9euPSeZIUkOzs7WF5eRk9PT8bte3IJhmGwvLyM3d1dtLXtR/TlQ17x3XffjS984Qv8PuUpIp5Yb5gK4PLyMjY2NlIyQI6HbDq3c6AoCltbW7BYLOjr68vKUG+mfABTzfQtKipCXV1dSOrFwsICr5JMpMXiCzBYMLnQVh67MmBQSREIBDA8vO97d+jQoYIblq/RCj9nwhMvnN4AP3cUDcHfy3dfWIJp1o5rXQvwuF1860ur1Ub8zu2eAEbW93C8QSvI1DYaFkyuhF/D5aK2tLQkJAzgFs35fB4QBMGnxNTX18NisWBsbAwKhQLT09P7s566EkxZgYubSwX7COZSnPNfL6+AIAheFRsNFosFMzMzcZNM5oxOfOh/R3HXYDXecbQaZqcPPz2zjuvay9Ckz0xFJ1hIUl9fzwtJVlZWYLfbExaSbG1tYXV19Q1P/oB9n9W9vT10d3fz9yiuOhg8TsRVD7NFCJ1OZ8FkZYfjDUMA1Wo1qqqqMvalc63YbM6hceo/iqIwODiYtcHXTIhA0p3sEZx6wTBMiFeXkLnBf/zDLE6v7OLbd3WjXBX9JsG1zOrq6lBentl0glyDs3nhCNGzs2YMr+3iXcdrBFvyXNmmx9S2HL2dBv78NZlM+IfHxvHiJoPv39GE+ioD36aa3nbg9LINLWXFcZNYYuG9cUhBODiD3GRmw7770goYhsX7LqlP6HW5gtVqxczMDAYGBlBUtK/+3d3dxdD8Bp6YMsOxs4r+pnKUlpamffHspxmQBJESuedwrF6LeJcNrhUqxIy9WiNDjUbOj2ZIKBISikSRJHsCA7E4upBEJBLxLfxIVczNzU2sr6+jt7f3DR3DCOwXeGw2G7q6uvh7fDQT6uD7TCYTSThcmAHMA2i12oxatXB5wNn6oXGGpSKRCLW1tVlVPaW7AsiyLJ+kkuwP0eWjQTNsxDYmSZLQ6HT42GOruKS5Em+r0cSdG3zvyTp0zFthiEE6dnd3MTExgfb29qQthAoFNpsNk5OTIVmhnRVKuLyBA8IVs9OHO/7zNL51VzdaykIvfA2lxWg4Z6pNkiRKSkpQUlKCQyYZXjWugmT2z2vO6LilpBR1JVVZU28D+9ZQs7OzSRvklhRL4PDmdzIQBy7Xt7e3l583I0kSWq0Wl/VrcKTdDzHrh8Vswvj4OGiaRklJCUpLS6FSqVJeqN3w9VdAEASe/NBFcZ87vLaLh341gR/c3QeD6uD50FMT24ybq4b19vYKqobJxBS+/edH+H8rZSLcd3FiC4l0IhEhyebmJra2ttDb25tXithMYGVlBVarla/8RUI8E+pEbGYShcvlyorRdibwhiGAmUY2vQAdDgdGRkbQ1NQEl8uV1Vg2IH3HmmrLNxgf/tkoGAb47jt7Iv6dIgjQDIuRtT3cd3Ed1Go1mpub+Tko7ubGzQ0alAq8tTf6zNfOzg4WFxdDSMLpZSvKVbIDCQb5CCGtWw7b29tYXl5Gb29vCEkuVUhww2HDgedv7Xrhp1lMbjkOEMBouO/iuvM316bzRseL8/u2K9YE0khSwebmJlZXV1OK67utJ72zggGGgdHuQ4U6vdW3eLm+JEGc82OUQKko5kcrLBYLr/bmWpIlJSVJEY0mfTFKBWbmGh0+MOz+Yi9RrK+v84QoeJGeyO8gG/jD5A68fgZvEhB1F01IMjY2BpZl0dTUhEAgwH8viyYXAgyLlrLijM8yZgsrKyuwWCwxyV84sp1XzDBMwVZg3zAiEE4dlCmMjo6ivr4+471+o9GImZkZdHd3Q6lUYmVlBSRJZlT1Gw6n04nZ2Vn09PQk/R6pkL/tPS/KlJKQ17w0b4HTR+Oa9uQd17m5QaPRCKfTGXFukPOPtFgs6Orq4m+cNMPim88tQiamclolEAKb24//fmUVPdVqXNYSfbaNZVmsrKzAbDaju7s7ZxcxLo3EaDRid3cXSqWSV4Knc5+Wl5cFH+uCyYlVqyfm55cuvP27p7Fm9eCxDxyDpig9c1zcOdzd3Z10hShY7W2xWPhqOtcqTuQ37aMZ7LkDKFWkX6EafA4HH+uO3YuHT6/jkuYS9MapHmYL7/z+62BZ4Ef39iX1es6kvLm5GRaLJURI8pMJDzYcAeiKJSBY4JPXt0CRR+Q3USRD/uIhks0MgKSrgyzL4rLLLsPrr7+e1zPBeKOLQDINiqIySjBZlsXS0hKMRiMGBwf56kSmtxsJqWYBxyJ/bj8NeYyB89kdJ/7hiVm8uaccb+o6v0o+0XRQtThvdGLZ4saVhw7aY0RCvLnBkpISmM1mkCR5wAiYIgm881gNZOL8V/+qZCK06IvRWRF9sRKgGYxOTEFCsoJNjzOF8DQSu90Oo9GIlZUVUBQFXUkpitU6lGmTW3yxLIvZ2Vn4fD7Bx3rPD4ZAMyz+9OAJiAWoTlPBZ65vxa+GN9NC/rhcX7fbjSNHjqT0vQa3JAHwxuDff3oYq7t+vHOgHBWG/aptvJvfD19dhdNL4y8urRek4p3ZdoAFcMgQvcLMsiwWFxfhcDgiHqu2SIyGkiLUl+RPxf7f7+zmldSJwOry4Y9n59BUfP4cVqlUIUKSqyqd+NZpG2y7FOpLFRARBVO/OYBMkD8genWQI4XcvTYRZXEuxKHpwgUCKBCZbAHTNI3x8XFQFHXAuDpTpsyxkMo2Y4k9jHYvvv7sIq46VIpLWyKTtvoSOa48VIqLGg4SvnB88YlZeAMMLmnWJXyTJkkyxG/QYrFgcnISDMNAoVBgfX39wNygOols4kSQrgsJSRC4MULrlgNN0/j8L0+BJSX4zJt788rShiAIqFQqqFQqNDU1wePx4OtPT8O0u443NZAw6Pdb+ELn0xiGwfj4OGQyGTo7OwV/vj++tw8bNk/C51Uy32FXlQpdVambFHO5vgRBJGRmLRRyuRw1NTUYoBXAshUl2v3fyeTkZFzh1ZuPVGDd5hFE/gDg6WkTADYqAeRSW3w+H7q6uiIeq5giBbVaUwbtB2GcArk9CoLxgSltA2PoAiQHlcRCrZjC8fUnxjC65cQ33jF44PcaLCQZ7KGxa9uDzWrG8NnXIRKJ+OtcoXjVZYr8RUI8E+pAIMA/J5+uk+nCG6YFzDBMxsyLAWBubg5KpRIGQ/QbazLgVKYVFRURI5l2dnawu7uLlpaWtG43FgKBAM6cOYNjxxKLLIsn9vDRDP7t6XnQDHD/pfV8xeP5OTP+NGPGp69viagWZFkWPz2zgVqtPKQSaHP5YXb6UrZscLvdGBkZQX19PQwGA9xuN+83GDw3GM/XjmH3ZxA7KpSQiBK7WLy6aMXnHpvGt+86glpd7IoFzbBJqyo5mxdCqYdPrMKJJh1MDh80RSKIBF7gli0u3PPfQ/jX2zvjDuanA1t7Hiyb3eivUcJsNsNkMmFvby/ufFogEMDIyAhKSkpQV5eZtn2AYfDdF1cwUKeB1eXH3z02jYffM4AqTeaNyoORy1zfYMN2i8XCV3RTiUFzegNggQMtTJPDh3WbGxL7BgiCyL0tk88J0dnvg9hbAytWAiQJwmcHKy4C3fcesMrUCCgX+2nadUKqr0VPjSbqc10+Gl//0wLePlCFOt3+584JSUwmEzweT0hSTD4SmtXVVb6dn+v9C54dDOZJwbODXq8XN910E1599dUc7qkgXGgBp4JMVAB3d3f5PNloPmTZFJ8ku02h834SisStRyrw788uYXbHgcH6ffuFR4a34PbH3t5TU0aIKDKEAGqKxCm3zTilb0dHB9TqfTIjl8tRW1uL2tpafm6Qi9qK5Te4YnHj6WkjCAIHAtuFgADi21w4vPjJa+u4oaMMrTHaY5EQbvMC7KedvO0/T0NMEfiDAKUmcM6QFyycSQzrJ4NylYy36jEYDAfSSBYWFvg0Em4+zev1Ynh4GLW1tRm17yEJAr4Ag2WzG/8/e+cZHkd5duGzRb23VW+WbPXmbhPAYBti2ZZkbNwCxKGEHkyHEMAkAeMEiCn5AhgIARITVFywTTEGU40bVu9dWpXtKtt3Zr4fygwqK2l3tVWa+7r8w9Jq9a5md+bM8z7POb6eIyLUxjvGE6CF7nS5vj+0SFHVO4TbLou3aEBAqTOg8B/nsXNJNG5eOTYGjc6QBjBhejXYggGfyQY3dv3rEoY1GvzfhiikLkh2+NYbr+kTcIb7QAX8fINBeQYCajl4lf+GYeX9AMeyN8ToKufSPONVztFo9ASUOgI9Cg0jAI0NktB95t7e3kx10BoJPjOlq6sLEolkxq0L1sKUiLrBwUG7ePPaCrYCaCKdnZ0AYLXg9J6eHnR0dExrRaFQKNDT04P09HSr/F5TMTX5xNxhD4qiMKAZsRahL0KmGOsOavRw43Gn7B80l/7+frS3tyM7O9ukDzHdNygWi6FQKODr6wuBQMBse5EUhQ6pGtFBniZvdZmLUmvAB+e6UZAdYdbUqDGbF5rnP2vCqgUhWG7CtruzMjr1Qq/XQ6vVIikpCdHR0Q4XCbbEnCSTd850QqUlcM+qxCkf1ylTIzLAY8L2t4Ekce0rP+La9DA8co1pOxLjB3x8fX2Zqq25xsUkSeLkmXLICQ9svyLDrJ+1CdphuH27D5RvBMCdeF7iDHTCsOhWUMHzzH5qiqLQ2NgIkiSRmppq9ffwZIkk1rL/MRdnE3/TQVcH33rrLbz99tuora119JKmw+gBZQWgifT09ECr1SIxceqT53TQDenDw8MmTSMODQ2hvb0dWVlZM/q95mKKALSmzYs9oQduaG8pPp+PDpkKMYFeJm+tjt72kkqlFuUUq3QE/nmmE1ctCEF65Mx7wCaDFro5OTl2yVB2JIODg6iurkZkZCSGhoagVCqZba/g4GCXuLiYykxzfY0hHtbiX2e6sCguEFeZOFxlKqMHfOhhK7q9Yrr+NIIgUFFRgbCwsDEZ7xRFgYJjEko4g0Lwz78Oyi/a+PcHukBkbgEZmWfW89I53ADstsVND5JIJBLG/ic0NHRKM31r4Wrij6a0tBQHDhzA8ePHXSEJZHZvAdv6Q2KNrdiRSLEK+Pn5IS8vz6Q1O2IIxBSsnexhL0iSRF1d3ZhJX6FCjY8u9uDy5BAmFWA6Rm97JScnM32D4/0Gp+ob5HIAigL0hO3us2jrk8m84GYTtMFzXl4eU9ElSRIKhQJisRhNTU3w9vZmtoot9QGcDIqi8H2LDMvnBU3op7S2Hx29nZ+ammpVk/JQH3esTQtDsg2i0MYP+NBekE1NTUx/mrH2CtoUPyoqClFRUWOe8x/fdoCiKNx9pek35iodAZ2BnHH7COXmDVDkyIfY2GecA1B887YHKYpCXV0d+Hw+5s+fb7fz6mSJJO3t7TYdJHFV8Xf06FG8/vrrriL+JmXWCEBbM1MBqFKpUF5ejsTERLNC5x3RAzgd1kj2cAR6vX5MrxR9cg3zc4e/J39K25TpmKpvMCgoCAKBYMKFzdONN+12nKXQW0h6vZ4Rugq1HgGefLuLdT1B4ppXzmBJQhD+smnmrQxSpQ4kRY1JD+nt7UV3d/cEg2cul4vg4GAEBwcz215isXhMGklYWBi8vb1n/Hf5tlmG3x+pw51XJOBXS3/27WyXqlD8Uw82ZIUjLWLmFws6xm70dr6eIKHWE/D3nJmo4XA4FvWvWoKHhweio6MRHR3N9KfRtkw+Pj7MtHdNTQ3i4+ONDuBF+ntAazDPsmrnOxdBkBSO3rl0ZsfcKwhU0DxgsAfwGVeB1atB8T3N2v6lKAq1tbXw8PBAUlKSw26qJ0skGS3UrTFI0t3d7ZLi79NPP8X+/ftx4sQJl0+IYgWgicxEiEmlUtTX1yMzM5NplDbn99o7CWQq6CZYZ636aQ0E3j3ThfWZ4WMSO1QqFSorKzFv3jwIBIIxP/NNkwyf1oiQGu6LKxeYtu01pDFMaukwld/g+L5BW0AQBKqrq+Hr64uk5PkAh4MBtR5vfdeB9Ei/KS1ibAH/f9vqliQ8GOPf57pBAbjvqpGLK72dv3DhwilNjzkcDnx9feHr64vExETodDqIxWI0NzdDrVZPWoEylWWJgbj3qkRcmz72/SXw80BiqDeirJD0IZfL0dDQMKF3+K3vO6HWEbjv6nlWyd21Nzweb4wt0/DwMPr6+lBXVwcvLy+oVCoMDw/Dx8dnzHnHklSW+6+eB9GwzirnL0NqAfjn3wRnUAjKOwzgcMFRywBSC0POTQDPtCozbVdET3E7E5MNkjQ1NcHLy8uiQZLu7m6IxWKnmPY1h1OnTuH555/H8ePHERzsuj3TNLOmBxAAtFqtzZ7bkl48Ommhr68Pubm5Fk1akSSJc+fOYfny5Wb/7Ez44YcfsGLFCuYk6Sr9fkMaA978rgMr5gVh5byRDyg9AJGRkQF//4m9dho9gXPtCixLDIQHf/ohkzaJCiU/9WBjdgRSI0yfxKV7oEQikcV9g9NBDwVERUUhOjoa17xyBhwO8Ok9y/FVoxTZ0f42SWOwJ0KFBhRFITrQE42NjTAYDEhLS5vRhWT0hY0e8LF0WMFcbn6/HBRF4Z83Td0rRscTGjuXCBVq9A5osTg+0IYrtR9qtRoVFRVISUmBj48Pk+CjUqkYoe40ViZqObjCc+AKLwKkHlRYOi7w8zA/McGkJA7awsfPz2/GPeb2xNJBktHiz5VyjL/55hv84Q9/wPHjx61uB2cHZncPoK0xtwJIkiRqa2tBURSWLJlo3mkqHA7HIRVALpcLkiTB4/EY8UcQBOOB5Kz4efLx4Jok5v909uv4nNvReLrxcIUZkV/h/h5IjfBFTJB5om10D5SlfYNTQVc5k5OTERo6Usn09+QjNtgLHA7H5MQUZyc60JO5aHp5eWHBggUzfk+Or0B9W9+DO99vxB+WuSPM52ehbgvLh1aJcsLXpEodPjjbjc15kYgJ8kJPTw96enom7eWMDvRCdKDr2lGMRqlUorKycow1E93/R5Ik5HI5JBIJY2Viq55Ok/EKApl8LcjkawGMHLu9ByuR2dqCp/JTpvxRkiRRWVmJoKAgm3lV2orRFfXRiSSjc6THD5K4qvj7/vvv8fjjj7uq+JuUWSUAORwOpqloWow5AlCn06G8vBwCgQDx8fEzujg5SmzRApAeQqEoyiri78mP69AsUuLtG/Pg7c7DoEZvcd9SQ/8wpEodU+kbDR0TNTAwgIULF1p1u9XbnWeVhAFL+gYnYzKbl5LfLpnxOp0NepgqLCzMLFumAbUe1T1DWDEvaMqpUQ6HAyXJB4fLxbmhIKyNDAKHo0V9fT10Oh1T5ZgsAk2o0JhlBH36/ssmfI2i/jckhJ9zffPy8lzqomkJQ0NDqK6uNmpXBIycl0JCQhASEjKmAlVZWQmKoqB390dclADRoYEOO3eG+Ljj7isSkBE19WQ/QRBMT/LoyWZXZbJBko6ODvB4PPD5fOh0umlbNZyNs2fP4uGHH8bHH388YQjJ1ZlVAtCWmJrJOzQ0hMrKSixYsMBq1gyOgBa8tKi21rbvgNoAuVqPLrkafQMa/PenHjy4OsnkNA89QTL+ZC+cbIGeILEiMWjM2ujqK5/PR25ursMuBObEgk3XN0hXOYwJWXprcKoq52yBNniebChgKi52DuBcuxwp4b7TboOvywjH2rQwvHa6HeDxERsrQGxsLAwGA2QyGROBNj6NpEk0jNJLvVifGT6jeLdQX3fcsyrRarm+06HSEdATpM3jDqeCNmXPzs42adq0vHsQQxoDrpifgISEBGh1Ouw9UQeivgH5cRQCAwMZ+x97C47peolpWxuBQICYmJgpH2sOcpUOL33RgjuvTLRKz6mljM+RbmtrQ29vL7y8vHD+/HmnTySh+emnn7B7924cOXJkVoj08bAC0ERMqQD29fWhtbUVubm5LpO7OBkcDgdKpdIs935T2H99JhQqPYK83RDo5YZ5od6IMrFaUts7hOPV/bhpWSzC/T3wXFEqlFpijMjS6XSorKyEQCCwmmm3JWgNBP5+uh0pEb5Yb+bQxficYrpvsKOjY0LfYGdnJ8Ri8ZyweaGtTxYsWGBRA/YvkoKRFjG9+KPhc7nYffXYhnw+nw+BQACBQDAmjaStrQ3u7u4ICA7BZQn+SBbM7PNP24FwuVyb5PqO563vO6DRE1iWGIwrkoPtftMkk8nQ2NiI3Nxck7fZn/q4HgRF4fL/rdfD3R2//sV8BHjxEejFh0KhgEQiQUtLCzw9PZnPlKNvkgiCQHl5OSIjI6esKH1wrguSYR12X5006WPGM6A2QK0nIRnWOVQAjkYoFEIul2PZsmXMUKMzJ5LQVFRU4K677kJpaSkSEhIcvRybMKuGQPR6vU375SYzR6YoCi0tLVAoFMjJybH6hdjUVA5rQPf7icVidHZ2Mr1pAoFgwgSeJegMJJ453oDEUG/cepl5PS/9g1oU/9SD36yINeqpRguEpKQkh1dfKYrCq6fbcFlSMBbFBZr1s29934HDFX0ovm3xhOST0TnFw8PDcHd3R3p6utnu/e/+2Ak/Dz425zn/lsbB890I9qDgr+yedGvQGRidRkIQBEJCQiAQCMzu6XRErm+7VIU3vm3HmVY5/rEz2yp2NaZCx/mZOygnVGig1hMmeRaOHlagj01YWBj8/PzsKnYNBgPKy8sRHR09rR3YnQcrQVIU3tiZY6fVWR+hUIj+/n7k5OQYrcJSFMV8bqRSKXNsHJVIQlNTU4NbbrkFH330EVJTUx2yBivDDoHYAoPBgKqqKnh5eWHRokU2e8Oas504k99BT/rSAwl0bxq9FTU6C9eS9bjxOHDnc5FmxvQsTbi/x6S+eXK5nLHacQaBwOFw8LurLLNzkAyP+NwZi5Pz8vJCdHQ05HI5IiIi4O/vj46ODrP7BuVKPRQq2yXnWJOWPjkuKRR4Zstip87d9Pb2Rnx8POLj45mG+Pb2dgwPDyMwMBBhYWHTppHQub7jEy9sTUKINx5am4zvW2RIMTNjeib09/ejs7PTogq2OX2WPj4+8PHxGXNsOjo6oBgcQkhQIDOsYOpWsUypQ+mlXtywLMbkeEq9Xo/y8nLExcWZ1L7wjx3ZJj2vszKd+ANGzpP0saEHSWQy2ZSDJLamvr4et9xyC/7zn//MFvE3KWwF0AzGV+LUajXzgY6ONh4HZA3Onj2LRYsW2fQDYEqyx/hcT39/fwgEAof02Iymp6cH3d3dyM7Odvj2jq2ht7gjIiLG9A7R2yoikWiMjclkfYPOiHhIix/b5diQGc68/3p6eiAUCpGTkzPplKeeIPHGt+24Jk2ABXYUL6YyOo1ELpfDzcMTHRovrM2Jh5/3z+/X6XJ9TcnMdiXoyebc3FyHvEd3/esSFGo93tyShAG5DEKRFP5e7iZZM1UKB3Giuh83Los1SYjq9XpcunQJnIBI5CZHT8hZnm2YIv6mY3TcpkwmGzOpb6sWq6amJtx44414//33kZPjupVXI8z+CqA9T4xyuRy1tbXIyMiwuRu4rc2gTY114/F4zMmR7n8SiURoaWmBl5cXBAIBQkND7daLRm+9Dw8PY9GiRS41WWYJxmxeaMZPR9KZq8b6Bp2VvZ814ULHABbHBSLC3wPt7e1QKBTTTg1SAIa0BGp6h5xSAI5PI6nsEOPs2U7ohsuRFMhjJoobGxuNHluaNa+cAUUBX+62TzuILens7IREInHoZPO6TAFKfuqFIDQEAYGBKG0FggwcrAsdSeTQ6/XMVvHo7UihQoNgbz4eWJNktEo/HtoVwicsBkcalBiCbNZYMhnDGuIPGBu3CcBmiSQ07e3tuPHGG/HPf/5ztom/SZlVFUCDwWDT2LQzZ85g2bJlTMUpNzfXLhfUS5cuITU11SbbX9ZI9qDtGEQiESQSCSMUBQKBzf4+BEEwsUm2zsys6RlCQqgXfNwdd79ET0hOZmY9GpWOAJ87stUOjO0bNKc3jaQocGC/GyuZUoea3iH8IikYDQ0NIAhixgbP4+mQqVDbO4x1GYLpH2wjCJJC36AG4f4eIA0GCIVCtLe3w93dnWm9MLaNv/H/zkKlJ3DqPtcWgG1tbRgcHERWVpZVjq3WQJhk4D4dRyt6kRsbiLjgkfOswWCAVCqFRCLB4OAgsx1537EucMDBwVsWTb82rRbl5eVITk5GcHAwKoWDSBb4OPRcYkt6enrQ29uL3Nxcmwr70YMkCoXC4kQSmq6uLmzduhVvvvkmli1bZoMVOxyjJ3FWAJrB2bNn4ePjA4PBgKysLLvdudIRZr6+1qtu2DLZQ6PRQCwWQyQSzWiIhKQo9Cg0YyLdgJ+3yiIjI61qoWAMhVqP37xXjvhgL+y/PtPi5xEq1Ijw97Qopou2ecnOzjbpJuCXr/4ILgc4cc/E9Bi6p1MsFjN9g8ZSFUiKwktftIDPmzgJa03G97bSAxDe3t42yUNdvf8H6AkKn967HN7ujq8Yj8719fb2dlgayWhsJfwpikJzczO0Wi3S09OtIv665Wq8d7Ybm3IjrDa4oiNIuHHHnhNHb0eebxGBx+dj+fyIKc3BNRoNysvLLZ5adzXsJf7GM9NBkp6eHlx//fV45ZVXcPnll9tp1XaH3QKeCTqdjmnmzsjIsOt2M23GbC1sHevm6emJ2NhYxMbGMoKjtbUVKpXKrCGS8+0KfF4vxo1LY5AQMpJ7Sk/6zp8/HyEhpqd3WEqglxvuuDweOTGWe7oJFWq8e6YLlyeHmJU4AsAim5erU0IR4mP8seP9Bum+wcbGxgl9g3weB/NN9GekaRIpERPkaVJjfJdcjQ8vCPGbFXEI9XWHXq9nLHxsNQBx8JZFaJeqnEL80dYno3N9x9v/0NP4dFU9NDR0TAawtbGV8KcoCg0NDaAoyqrnz0BvN/i48xDmax37EIKksPOdi3DjcsdU+EZvR9IpPhKJBPX19dBqtcxWcUBAAP57sQcnqvvw2wU6ZKSlIigoyKw16Awk3HjOG7dpDEeJP2BmgyR9fX3Ytm0bXnrppdks/iZlVlUACYIwyazZXIaHh1FZWQkul4usrCy7e/zV1dUhPDzcKneRpvb72QJzh0iUWgMqhINYEh8INx6XuWBmZmZatRpqawiSwvkOBTKj/EzKBgVGjlNTUxO0Wi0yMjJsbpY6WnBIJBKL+gYH1Hq88lUbUiN8cP3C6Yei2qUqlF7qwU3LYuHvDosNnl0RkUiE9vZ25OTkmLRlRfc/icVi6HQ65kZqsjSSmbD/y1bMF3hjfebM026AkapuXV0d3N3dkZycbHdh8+Z37RjUGPDgatMqyr/+10+4OiUUv15umo8oQRDMVvHAwAD+WUegb0iPt3dmmm1HpSNIvPhFC4K93XD75Qlm/ayjcKT4m47xgyQnTpwAAGzatAkRERHYsmUL9u7di2uuucbBK7U5s38L2BYCUCQSobm5GVlZWejo6EBcXNy0PVjWprGxkdmqmwmOFH/G1kIPkchksmmHSIRCIXp6epCdne1UZqG2gCAI1NTUWLQNqjUQkCr1ZpvA6ghyTEO7pX2Dtb1DiA3ygp+n6ZsLdFU3JSXFrGqJTKnDuz924dbL4iyOE3QE9PSrpZ6htOAQi8VMb9roNBJ7UN6lAJfLRfY0aSckSaKqqgr+/v5ITDRu4WRr9p9qAUFhTEb4THjpVAt+6hzAe7vyJkQKKpVKXLp0CUFBQVAqlczkalhYmMmV21dPt+KK5BDkxARYZb22xJnFnzHa29tx+PBhfPLJJ2hoaMDy5ctxzz334Morr5zt15XZLwBJkoRebx1vMzpLViqVMhYUdXV1iIiIMLukP1NaWlrg6+s7o8oIRVGMOHa26B16iIQWHKOnjT09PdHc3AyVSoXMzEyXOMlYCkFSIAz6CTYvtb1D8PHgIT54+gvIa6fboFDr8fDaJJMb48+3y/FZnRi3Xx5vdCvN1L5BS6CHW7Kyssyu6jb0D+Oji0LcuCyWaRFwduhc3+zsbOa9bCBJ8Cy8IRudRiKTycYMkthyQG3f583gAHjkmuRJH0Nn3YaEhFiUyqMzkHj5q1asnBeEy5JGWieECg0iAzymzHK2Nbe8Xw61nsB/bh47BKJUKlFZWTnGi5Su3EokEmg0GgQGBSHMBSLQTMHVxB+NQqHAddddhwcffBCBgYE4duwYvv76ayQmJmL9+vVYv379tCbdLggrAE2FIAhUV1fDzc0NqampzAfVWpU4c6EnBC0JorZ1v581qBIO4sOLQjydnwJ3PpcZIunv78fQ0BB8fX2Rmpo6bfXpVIMY8cHeJiUDOBsKlR6/eucCcoMN2L02lXmPURSFvZ81wY3HxcNrJ7/Y0kiGdeiSq5EXa3r1oEuuxkcXe3D3lQnwnKZ3z5p+g3QChKnDLa4MPQCh0WjGbOmTFIW/fN4Mdz4XD6yeeYVKpVIxYt2UxIuG/mEkhHiZPUU7rDWAAxhN5AFGBvIqKioQERFhsUcqQVJ44YsWLIz1x9o0AcTDWtz07iVkR/tj36Z0i57TVgwPD6OqqmrKGxmDwYBd//oJhEGP32Vz4ePjw3x2LB3yOVUvxsl6MZ7KT7FrX2tvby/j4ehK4m9wcBCbN2/G7t27cf311zNfp3tUjx8/Dl9fX9x+++0OXKVNmP1DINaAntyKioqacNdqSh6wLbB0CMQVxB8AnG2XY1BtAPm/mxFPT08IBAL09fUhKSkJbm5uaGtrg1KpRHBwMJN2Mfr1GEgS/zrTBQ83Hg78yvEeTnqChM5ATnqBHI9BMwydToulqYljbjA4HA5uWRkPDzfTqgWhvu4mZ93SxAZ5mbw9Zi2/QaFQiN7e3jmRYTxVri+XM2LXkxVlnbYSb29vxMXFIS4ubkzixeg0kqCgIPB4PIiHtLjjP5VIj/TF37eblzoxVS8rnXgRGxuLiIif+wiPVPShUTSMB1YnmTQNz+Ny8OioCmOojzs2ZIYj38xsbVszNDSE6upqZGdnT9kfzufz4eXhjnkxQVi+PBnDw8MQi8UoLy8Hh8NhBoC47p54qLQW6zIE2Jg9dR8mXaFx49nv3O6q4m94eBjbtm3D3XffPUb8ASPn2dTU1Fmf/DGeWVUBpCgKOp3O4p9XKBSoqalBWlqa0YGL9vZ2uLm52TT1wxhCoRB6vd6sQGpXEX/AxISD4eFhVFdXj7FP6B3Q4L0fO3Fdmh/0w3KjQyStEiWCfdwR6GV/QVHdM4hnjjfi/7ZnIczPA3892QytgcTvfzl/2u0qc21enBVT+gYpikJ7ezsGBgbsaqXkKGhbG19fXyQmJjrsc0inkfT1i3CoSowlMT7IiA/Hp206rE2PYLzvZgrtezdv3rwJOyVvfd8BqVKHR9bafxDEVgwODjItDDMZDtRqtcxW8bBShddrKFy1IBS7Lk92qq1iVxV/KpUKW7duxU033YRdu3Y5ejmOgK0ATkVPTw86OjqQl5c3abOuoyqAPB4PWq3W5Mc707CHKYxen1QqRVNT04QT6rDWAAMF+AQEISou0mgSSVhYGHwC7Ls9z6xbqQdJUVDrRxJbNmaFo39QO6346+rqgkgkmhWVMC8vrzHVJ4lEwlRuadd+sVgMiqKQnZ3tVBc2W2DrXF+CpEz2laTTSDx9A2Bo5UDK84Ber0e2hwT9LRIQAyN9g5N5dQ5pDNMO9qjValRUVEzqe3frZfGmvTAXYWBgAHV1dcjJyZnxjZuHhweio6MRHR0NkiSRmjLiB3n27Fl4e3szfZ2TxSHaA1cVf2q1Gjt37sT27dvnqviblDlfAaQoCo2NjVCpVMjKypqyj6mnpwdardbu02y0Mez8+fOnfawzD3tMR3d3N3p7e6fMfTXGVEMk1qioURQFHUFaJW3g8cN1aBQNo/jWRWhsGukJy87KdIlj1SZRQarUYnG8eUNQJElCKpUy6R5BQUEQCARTGhzrCBJPfVyPXy+PtZrBrz2ZLtd3pjx+uBZn2xU4eudS+HrwJxhqT4VaT8CNxwH/f+85nU7H9A2q1Wqmz5lOIznXLseJahFuuSwOsUHGP090TGFqaqrNozFNgaQoGEjKpKg2S1AoFKivr7eK+JsKiqJwtrkPh34SYl0sCR+3n7eKp+uJtia9vb0QCoUOy222FK1Wi1/96ldYv3497rrrLqcvhtgQtgI4HrpR2d/fH7m5udO+Ofh8PpRKpZ1W9zOm9AC60pbveGjPO41GM23uqzE4HA58fX2ZbTZ6iKS2tpZJIgkLC7P4hPlAaQ2ECg3e+3XetEMS09EoGgZJUaiursZ/6rTwDwhAbo7ziz8A+OinHugMJBbFTW/iPRqCINDZ2YmEhARER0eb1DeoUOnxY5scXm48PL0+xeI1UxSF5z9vQlSAF3693Dbm0uPRaDSoqKhAUlLSpLm+5gg2Y+TE+ON8xwB83HkQDWlx4PsO3LA0xqRJ8fEm3fSAWVRUFEiShEwmQ39/PxoaGkY+Vz6BSAzxRLifcZsMegBi9PSro3nhixboDCSe+KX1YyJpP1J7RIFyOBz4+/oiKDAASxYlwo0zcjM1vrJO93XaAlcVfzqdDrt27cLatWvnuviblFlVAQRg8lapUqlERUUF5s2bN6ZReSpo7y17N4oqFAoIhUJkZGQY/b4riz+CIFBVVQVfX1+bRH+NtzCZbIhkKj6t6ccH54T44DcLp3ycRk9MKxD1ej0qKioQHh6OizI+DASFLQvNn+42lTOtMhT/1IN9m9LhNsNqyLDWAI2eNGvIhBZDiYmJEAgm5u9O1TcoHtYhwIs/48rr1ft/AIcDu2To0p6GU1XCCJLCvs+bEBvkhRuXzVyUioa0eOeHTuxYEm2SADQViqKYQQU643u8px1t4zPdAIS9+a5FihaxymzRP6Qx4Pb/VOCeKxOwMmliao9UKkVzczNyc3Md7htH93WKxWLI5XJ4enoyU8XWWltfXx+Te+9K4k+v1+Pmm2/G0qVL8cgjj7jUNdFGzH4bGGBE9U/zmiCRSNDQ0ICsrCyzTJ2nE2K2YmhoiBkSGI8riz+NRoPKykrExMRYZHEzGpWOwCtfteK63EgsCDduw2BuEokxhjQGvPldB25ZGYdA75+3LztlauwursbOJdGTCjq6RyopKcluVkK3fFCObrkaR+9capUtbHOgK0OpqabFYc3Eb7BLrsZPnQpszI6Y0Hep1hPgcmDz1z8613e6StjznzVhXqg3ti6y70DZTBidRqLVauHj44PBwcEp+6ZdjSGNATe/X47NeZHYvnjssaEjLXNzcx3aizcZdBuMRCIBSZLMVvFkFkDT4ariz2Aw4Le//S3S09Px5JNPutQ10YawW8AURaGjowP9/f1YvHix2XdJjhwCIUlywtddbdhjNLR1QkpKilUi7kiKgsZAondQO6kAHN0bSA+RVLX1gtfcDB9vb+Z7Uw1jiIa0GNToIVRoxgjAUF93ePC5SI80fuGnKyXp6ekICLCfw//rO7Kt1r9oDgqFAnV1dWYZPBvLKRaLxWNyiifrGzxZJ0anTIVr0wUTqrCm5BLPFGO5vlPx2LXT9/Nq9AQ8+Fyn+Vx7enoiJiYGMTEx6O/vR1NTE/z9/VFRUQGupy+UPD9cnhbt0sNMfp58FN+2eMLX6eg+ZxV/ACbk4Y62AAoICEBYWJjJN7uuKv4IgsA999yDpKQkVvyZwJypAJIkidraWiaM3JKme5VKhYaGBuTl5VljqSaj1WpRXV2NRYt+dp535WEPsViMlpYWh+Qqj6ZFrMQ/z3RhXUYY0kLccMeH1VgcRmF1guekQyTU/5rL+VzTBTf9em3dMO4s0AbPOTk5VumRGp9TzOfzJxwfHUFCoyccEglnbq6vKSi1BvzlZDNSI3yxY3GMVZ7TWvT396Ojo4MRQxRF4a1vmlHdJUNRAoUAb3ezc6RtjYEkMawlLLKI6u/vR2dnJ3Jzc60ibqVKHX5olWF9ZvikLgEESeFUgxiXJQXDx32sAOsf1EI8rEWmid6RJEmOSYvx8PBgtoqNHR9XFX8kSWL37t0ICgrCvn37XO66aGPmRgWQw+FMEIC0N1V4eDji4+Mtvivg8/kOqwCO/r0EQbjkli8wYnvS39+PhQsXOvxOOi7YC2vTwpATEwBvdx7c3D2g9/FDRkYcxGIx6urqoNfrERoaOsbPzhzTVfr1Llq0yKUrI+OZzIKku7sbfX19VrW14XA48Pf3h7+/P5KSkpi+QXrIZ3Tahb2hc33z8vKseny93Xnw8+RjcVyg1Z5zOgiSQodMhXmhk9+UGXu9HA4HO5cnoictCvMFPszxqampMSmNBAAG1Hrc+O5PuGFZDLYutP62+AsnW6DSEXgyf4FZvbD0AEReXp7VxNDh8l583STFwthARAdOFGAGksTfTrWivGsABElhXcZY4+u/fdkCjZ7EC5vTmUnuqeByuQgKCmLaMOi0GPr4BAcHIywsDP7+/hCJRC4r/h5++GF4e3uz4s8MZl0FUK/Xj9kuHRwcZILmJ5vIMxWCIHDhwgUsW7Zspss0C5IkcfbsWSxfvtxl+/3oqB2DwYD09HSX+YBaOkRCR3+p1Wqm4vx5nRghPu5YHB9ovxdgA7QGAs9/1oz5Ah/sXDJSnaKzs4eGhuya2UxvdYlEIpP6BvUEOeNhGJr29nbI5fIxub4AoNQZwOVw7LL1bE2ePlaP71tk+OdNeUbtXrq6uiAWi5GTk2Py8aWPj1gsZtJIQkNDJ2xFag0Erj9wETuXRE/ovbMGHTIVmkRKrEk1vfeWzrrNycmxqhhS6gzokKonbRfRGgj8+UQjvNx5eGB10oSWBqlSB5lSh/kC87KzjWEwGJjjI5fLQZIkFixYgLCwMJcRgCRJ4oknnoBWq8X//d//ucy1xc7MjSGQ0QKwr6+P2YqyxlYjRVE4c+YMVq60/TTheH744QcsW7bMJcWfwWBAVVUVAgICbJ6GQFIUNHrSJrmYtEWGSCRihkjovrTRFzOSJFFTUwNPT08kJyczVelnTjSAz+XiD+sWWH1t9mQkn7gZV6eEYHliMCiKQn19PQAgNTXVoWkXdN+gXC6Hj4/PGL9BrYHA3s+aERfkhZtXxk3/hJiYUkN/rbm5GVqt1ujNzJ9ONADg4Ml81zrOXXI1TlT347ZfxE/Ymhyd3mLpBZaeWpVIJJDJZMzUqqMNjo3R3d0NkUhklti1JqO9GvsHtTCQJKIDbdc+Qm/rJyUlQSaTQSaTMRZNoaGhTtu6QpIknnnmGUilUhw4cGBGx+rmm2/GsWPHIBAIUF1dDQDYs2cPDhw4wAztPffcc8jPzwcA7N27F2+//TZ4PB5eeeUVXHvttTN/QbZj7ghAgiDQ3NyMwcFBZGdnW3Vr5ocffrC7AKQoCt9++y2Sk5MREhLiMndmwM+TvrGxsSYb4g5q9Nj7aRMeWJOEMF/zeqpu/08FtHoSb92YY9L2iKXQQyRisRhSqZRJIgkMDERdXR0EAsGE9AeVjgCfO5L9OlsgCALV1dXw8/Ozqbg3kKRZx3N036BUKmUsTN6rVmFdZoRJZtYUReFPJxrB43HwxC8XMF+rq6sDj8fDggULjL7ei50K8Lkc5MTYb9jHVlAUhZaWFmg0GqtX7kebtwNgLGYmSyOxF11dXZBIJBMqu47i/pJqkCTw8tZMmzw/3eM4fptbrVYzux96vZ7ZKg4ICHCKAgRFUXjuuefQ2dmJd999d8bH6ptvvoGvry9uuummMQLQ19cXDz300JjH1tbWYseOHTh37hx6enqwZs0aNDY2OsX7ZRLmRg8gQRAoLy+Ht7c3Fi5c6BRv1JlAD3tkZmYymbFeXl4QCAQIDQ116r4y2hYjLS3NrHSAHoUWA5qRbRJzBeC2RVE4166wqfgDRipCgYGBCAwMRHJyMpRKJXp6elBfXw8vLy9QFAW1Wj3mztnbnQelzoA3T7dj14o4+Hq49seP9jSMiIhATMzMBxVqe4fwQEkN3t+Vh7BRpsPft0jxSY0Yu6+eZ7IH4WR9g/kRKhj6GtFiCJ22L43D4YDH4zDvQZIkUVVVNa3YXWSjvj1TfCatCZ2SRJIkMjIyrH4uHT21SqeRtLS0QKVSMWKDTiOxFx0dHZDL5cjJyXGarcR7rkyEnrBNLWYy8QeMRDvGxsYiNjYWBoMBMpkMQqEQdXV18PPzY3Y/HFGQoCgKL774IlpaWvDBBx9YRXhdccUVaG9vN+mxR44cwfbt2+Hh4YHExEQkJyfj3LlzWLFixYzXYU9c+wpkhLa2NggEAkRHu46/1mSMHvYICAhAQEAAIzZEIhEuXbrETEQKBAKHG5OORiQSMdvv5nqEpYT7YP+WTLOGLWiuTgnD1Sn2zQPmcDhM3NmiRYvg4eEx6RDJT50D+LxOgvRIf1ydMrOeVEdCGzzPmzfPap6GnXI19CQJuUo/RgBG+HvC040LXw/LT/Ljc4qlUina29un7RukK3+2zvWdjg8vCHHg+w689atcJIba3nOPoijU1tbCzc3NLtv649NI5HI5RCIRGhoa4OPjw2xF2vKGt729HXKFAlGJKU4j/gAgKcw2TglTib/x8Pl8CAQCCAQCUBSFwcFBSCQSdHR0MPZaoaGhdvGDpCgKr776KioqKvDhhx/aXIC+9tpreO+997B48WK8+OKLCAoKglAoxPLly5nHxMTEQCgU2nQdtmDWbQEbDAabTur+8MMPWLFihU1PiOaYO9OVDZFIBIqiGDHoKGNWiqLQ2dnJbKE4c4XSWtA2L9nZ2RP+7uOHSAICg6B1D0BGvADudvbmmwySovDej11YtSAUCSHTv29og2dzK7v2hKQotIiVSA4bu53YP6jF375swZP5C+DjzjfaNzhebNC5vrGxsSanBlmKeEgLPo+DIO+xlc6K7gE8eqgOJb9dbPPKMUmSqK6uZqIVR//9mkTDcONxp32fyJQ6fNssxT/PdOG9XXkW2/OYkkZiDVpbW6FUKnF20A+tEjUeuzbZppZC9X3D8HLnWjW5xRxEIhFj5TPTc/R4g/DRW8XWFtIUReGNN97A6dOnUVJSYvXe0fb2dmzYsIHZAu7v70doaCg4HA6efPJJ9Pb24p133sHdd9+NFStW4IYbbgAA3HLLLcjPz8fmzZutuh4rMje2gG19p8rlcmec4zkVtPgjCAJc7vQmsKMrGzqdDmKxGA0NDdDpdBPsS2wNSZJoaGgASZLIy8tznrtonRIcRQfA4YAKTADcrNfQPNr2xNjJaLy5MT1EcvF8+6RDJPZmQK3HwQtCVAoH8dKWqfuM5HI56uvrzTJ4Hs9/znejWaTEE+sWGLWSsQY/tslxtLIPv1kRh5RRxuDftUhxtk2But5hLI4f2V4MCQlBSEgIIzbo6jqPx0NQUBD6+/sxf/78GbsImMKrp9vA43Im5B/nxATg03uXT/JT1oMgCFRWViI4OBjx8fETvv+7j6rB5QDH7556LW/90IFLXYPQ6AnIVXqLxRSHw4Gfnx/8/Pwwb948aLVa5hyn1WoZixlz+9KECg0eOVSDv23JwGB/NzQaDTIzMxExrENlzyD8zBDZ5l4PKIrCwfPd4HE5eGoGOdeWYk3xB4w1CKfTlnp7e1FfXz+tgbs5UBSFd955BydPnsShQ4fsMjgUHv6zBc9tt92GDRs2ABip+HV1dTHf6+7unnGalSOYdRVAgiAYg2RbcP78eeTk5NjkzWfNZA+DwQCJRMLYY1iSgWvu76uqqkJgYCASEhKco/eSJMCrOwJe0ycAZQDAAbh8ECkFIFLWAzNYI90cr1KpkJGRYbaAm2yIJDQ01CETkY39w4gK9Jy0uvRNkwRyhQIRpHTGBs//PNOJLpkaT+YbH6KwBiodgfLuASyJDxxj+6InSPQPahEV6DmpCS+NTCZDdXU101pBV54sjdYyhcb+Ybjzp6+w2QKDwcDkVE/W0/lTpwLufO60JsSDGj1Eg1rMC/OZ9u9sKQRBQCqVQiKRYGBgwKy+tB9aZXjhZAtuzvbCvAAu0tLSLDqmeoLEnz9pxHyBD25YanprQM+ABh58LkJ87PtZt7b4mwp6EEsikUAikYDL5Y4Z9DGX9957D6WlpTh69KjNppLHVwB7e3uZ4cW//e1vOHv2LD788EPU1NRg586dzBDI6tWr0dTU5HJDIKwANJOffvoJaWlpVn8D2jLWje5PozNwAwICmAxca1Tp1Go1KisrkZCQMOaOyRaIh7QI9nE3qXLEq/4IvIaPQflGAbz/newIHThDvTBkb0d76NX4qVOBwpwIs/7etM2Lh4cH5s+fb9GxeueHDnTLNYwIovs66RPlZEkkjuKhDy9CpVbj5RuWzYltfXqAia50jvezMyen2BXQ6/UoLy+3yza3LbjUpcA39X34ZTwPCvnPFiaTpZGMHnCZSY8jRVH444lG5MUGoCDbuf9u9hR/xtBqtcxWsUajYT5Dpgz6HDx4EB988AGOHTtms/SoHTt24PTp05BIJAgPD8czzzyD06dPo7y8HBwOBwkJCXjjjTcYQfjss8/inXfeAZ/Px/79+7Fu3TqbrMtKzA0BSJIk9Hq9zZ6/oqICSUlJFm9/GcOeyR4URUGhUEAkEkEmk8HX15fxSrOkmZbOuLVHP9iQxoCHy2oQH+KNxyfJUiUpaqTioB2E+4ndoHwEAHfc6yJ04GgU2G24F90DOrz5qxyT+6r0ej0zDBAXZ5qXnDH+dKIBBEVhz/rUCd/TaDSMPYbBYEBISIhdt/JHQ1EUWltbIVUMIT0jHb6ellUsFKqR/OSMKPundZjL6FxfYwLclL5BV0Kn06G8vByJiYlWG+iZ0XoIEnwux6zK4d7PmjCkMeBPG1PB43KY3mj6MxQaGorQ0FD4+49ULuvr68HhcJCSkuIcuxU2xtHibzwEQUAul0MikTCfIfoYjd8BKS0txYEDB3D8+HGHpP3MElgBaA2qq6sRGxuLgICZe3yZM+xhC+gSvUgkglQqhbu7OwQCgcnGrP39/Whvb0d2drZdKlUURaGsvA/LEgIRYySpYEhjwP0l1Vi1IAQ3xUrAP/MqKH/jfRmcoR7Ilz6EPvd4k6fs6EpnYmIiBALBjF6LqYxPuqC38m3RYD0ekiRRX18PLpc75kKpI0hc98Z5rMsQ4O4rE5nH9w5oIFRojCadrP/7j9AZKHx811K7WplMxelGCdqkKuxaHsu8NnNzfUf3DdJ+g85WvZ0KjUaD8vJyzJ8/HyEhITN6LoqiMKA2INB7RGAotQbseOcnFOVEmGS8fb5djuc/b0ZymDe83fkT+iCngqQoECRlNOVldNrF0NAQSJIEz8MHHwvdsTZNgFULbN/bqSdI3F9Sg6KcCLPSSKyBs4m/8dCfIbo6+PTTT2PRokUoKiqCUCjEa6+9huPHjzvtwJmLMDeGQGzN+FxeS3G0+APGeqWNtpepqKhgtiEFAsGELRSKotDR0QGZTGbVzFdT1rs5b3IzaW93HvhcDmIDvQCKmuQt/zO+7hyTxR+9JZienm4V8W8qbm5uiIiIQEREBDNEQjdYW2uIRK7SoVmkxOL4n/tDCYJg0lvG93TyuRyQJIWa3qExz3Pg+w6otASyY/zhPu5C/Pft2ajrG3Ya8QeMCEA9+fM9rlAoRG9vr1m5vqOHFJKSkpjq7WgLoOn6BmVKHTzcuPBxt+/pWKVSobKyEqmpqVa5uB6u6MMPrTI8vDYZAj8PeLiNvAemKTIw/NAqh85AIjHEe8o8YmNwORxwJ7GN4vP5CA8PH5PwwOW7QyrpR1e7EkIfLUJDQ21qo8XlcKDSEfi8TmxXAUjf0Fg7q9qajP4MJSYm4u2330ZZWRkee+wx1NXV4frrr8e5c+dw5ZVXOpXV2Wxg1lUAKYqCTqez2fM3NTUxPXSWYst+P2tBX8hEIhEIgmDEoJeX15jYL0f3P+kJEopxvnEAALUc7p8+AMonAuCOEx2EHhy1DLr8lwH36ZvtJRIJmpubjdq8OIrxQySenp6MObi5QyT/+KYdrRIlnspPgZ8nn+kHi4qKMstPc1Cjh1yld5i1hbmQ/zv3cTkco7m+Kh0xo0hBU/oGKYrCta/+CC6Xg0/vGTtZS1IUqoSDyIr2t/ogBW3lk5GRwWyLzpT+QS1ONYixfXG0zQY/LIXu2/Xx8cG8efOYr9NpJBKJBBRFOU0aiTUQi8Voa2tzavE3GV988QX+/Oc/4/Dhw6itrcWxY8dw+vRpJCUlYePGjdi4ceOMK9ZzjLmxBWxrAdja2govLy+TY83G4wribzx6vR5isRj9/f2Qy+Xw9/fH/Pnz4e/v7/D1P1hagwG1Hq9szZpwseZVfABe8+eg/KJ/FoGkAZxBIYiM60CkbZr2+bu7u5lAeHtP55IUBQ5MszYaPUTC4XCYrXxTtiGHtQb0DmgwX+DLbHNb0+DZmZks1/efP3Ti3+e78faNuVYRtFP1DR6qFCPM1x1XjTMGv9ChwH8vCnHD0hirxsqNH3CZ7dAJLnQ1ezLoNBKJRDLGINzDxx8+HnyHn+vMwZXF39dff40//OEPOHHixJihQjpz/NixY/jFL37hcqkbDoYVgNaAdj63JPqK9vcD4PDKmbnQwiAuLg5cLpfppwkKCmLsZRzxmjpkKlzqGkBRjhFBTuhHJoFbT428k0fUFIj5+SDSNwGcyddL27wolUpkZmY6ZLz/yY/rweEAf9wwcVBkMtqlKvAoA6AeYDI8TfWDpKtC9t7mdhRT5fpWdA/gscN1KLt9CbzM2LY2Ja7N1L5BrYFAdc8QsqInbqlbikKhQH19vcOq2QqVHt+3SHFthsDmcY3AyDm3srISQUFBRn0Np/o5uVyOpq4+vH5WgoVRXrh+caxLDPq4svj7/vvv8eijj+LYsWMu6avnxMwNAQiMjJvbiu7ubhAEYdbJxBn6/WaCQqFAXV3dBGEwOrJJoVDA39+fsZdxKj8kjQJceRsADsjgJMBj6kkykiSZGKzxwsAU2qUq/POHTjx8TbJZqQ1n2+R46VQL3rkxFz4efPzlZDN8PXi464rE6X8YI++zxw/XwY3PxZ82johGY0MkxqwXLrX0YrivHQtzs02yWbj5/UvQExTe37XQ5NfnTJia62sOl7oG8HBZLf64IQUrk4JN/rnRU9+m9g1aglQqRXNz84x9HGfCJ9X9+KJBggdWJyE60LZroE2tQ0NDLY7vI0gK+79swS8XBMDLMDTGpik0NNRmliSW4sri7+zZs3jggQdw9OhRh8QtznLYIRBrwOPxzKowurr46+vrYybIxm8njk9RGBgYgEgkQktLC7y9vZ3HGsMzEGRknkkPtYbNS49CA5WegFpHmCUAK4QD0BpIEP+7KXtkbbJZv5fD4eCWy+LG/E5jQyR9fX1oaGhghkgGVDo8cKgZsaF+eO8y0y5ooiEdKAr4tlmKJfGBTjXcMR2T5fqSFAWSoiyuTAn8PODG4yDKTGHj6emJ2NhYxMbGMoK9o6MDw8PDCAwMhEAgmNRvUE+QUOuJaZM2Rg8DWNrKIBrS4uGyGuy/PnNCVJ2prE4NQ2a0P6ICzG/mV6j1uPm9cty8MhYbsqb23CMIgjG1nkkuPI/LwYNr6M9h2Jg0ksbGxjHRZ7Yy2TcVVxZ/Fy9exO7du3HkyBFW/NmRWVkB1Ol0Jk+emYtYLIZCocD8+cZ96EbjyuKPoii0t7dDoVAgKyvLLI/A0VtcEokEbm5uTE+aM09xaTQaVFRUMDYvBpLEM8cbsTol1OZWEYx/oZ2gA92bm5sxMDCACwPeWJUagdykKJMFQmP/MF7/th2F2RG40g5WGtZgqlzfPxytA0FS2FuU7qDVjcUUv8EnP66HRk9g36b0Sd8/vb296O7unpENyFvfd6BZpES5cBDPrE/BssQgi1+Xpah0BG7450+4aXmM8ZaP/0EnmkRGRtp8G5GOPqNN9s1JI7Emriz+KioqcPvtt6OsrAzJyebd9LKYzNzZAralAJTJZOjv70daWtqUj3PFYQ8akiTH9EbNtLdPrVZDJBJBLBYDwJiJYmdhaGgI1dXVYwytyf9tqUb4e+D+1Uk2+91ylQ7Pf9aMDVnhuDzZPpNto6PsMjMzmWNkzhAJSVGo7xtGUpg3PPjOXwGkBX5SUpLRXN//XhRCptThThO33O3JZH2DMtIbfSoSv0w37krQ3d0NkUiE7OzsGQmS3x+pA0VR+P0vF8DHg+d0U740BoMB5eXliI6OtnhQz1Lomyp6Mp9OIwkNDbXpuc6VxV9NTQ1uueUWfPTRR0hNNb3XmcVsWAFoDQYGBtDV1YXMzMxJH0NRFBNH52rDHqO3QGNjY60uXOntE5FI5PCUCxpH27yo9QT+/Ekjti+KRla0dSw5pmK0wDeWhKDRaJgcaXOGSJwZpVKJqqoqq3neTUZNzxCSBaYJYnNtZgiSYiIQTekbHF3BH9+Tq1DpEeDlWpOt00HbF8XFxU0aSaknSHzZIMGa1DCT4iRnAp1GIpFIoNfrERISgrCwMKu6J0gkErS2trqk+Kuvr8euXbtw8OBBZGRkOHo5s525IwD1ej1IkrTJcw8PD6OlpQU5OTkTvufKW77Az8awSUlJdrEA0ev1jNBQq9VjUi7s9bcTCoXo6elBRGIq/Lw9mRSD2QrdGE9PRU73dzZ1iGQ6qoSDePxIHd69KQ+hvva106HjCm1te9I7oMGN717CorgA7Ns09TbyhQ4F/nO+G/esSjTJ9PirBjGOVYvw+1/OR4jP2L/feL/BwMBAGAwGkCSJrKysCcepS67G30614JcZAlyTZp9EG1tDx9klJCRM6dF6qkGM//u6Hb+7ah6unG8/H7nxaSQBAQEICwub0cAcLf5yc3PtblE1U5qamnDjjTfi/fffN3otZbE67BCINZgsCcTVxZ9cLkd9fb1VjWGnw83NDZGRkYiMjGR6aYRCIerq6qZtfp8pdMbt8PAw8vLycPMHleBxOfjnTaYNizgCPUGCZ2ZGKjBSYfRy4zH9b9HR0Sb3RhkbIunv7x8zRGJKEkm3Qg0DQWFYa7CrAKRzfY0NMVkTA0kiwt8Dt6yMwxUmCIvYIC+E+rpDMN7AfBLC/T3hzufCx0jFcPQxIggC1dXVUCqV4HA4qK6untA3GOHvgcwof+Ra0VtwKtR6Ap58rs3OiTqdDpcuXZp0a380v0gKhiefh8Xxlr32xw/XgcsFni2YvAXoVL0YccFemC/4+WaDTiMJDw8HSZKMiXtLSws8PT2ZY2Rqj7Qri7/29nbceOON+Oc//8mKPwfDVgDNhL6ILlmyhPmaq4u/3t5edHV1ITs722H2EKMhSRIKhQIikQhyuRx+fn4QCAQzjjwb/fy1tbWokRKoULjjmQ0pON+ugJ8n3y5bsJZAURQeOVQLPpeLvUVT95+O5kKHAnuON+DR1fFwk7cjOTl52oukqesZHBxketJmkkRiK8zN9R1PY/8w5gumT4RoFivxj2/accfl8WMu+qZAURTeO9uF+WG+ZlnHTPZco3t3gZEdC3ob0hE5xUqdAU8ebUBSmPeY3GhrodVqUV5ejuTkZLskQzx+pA5cAM8WGv8MEiSF2z4ohzufh9d3Zpv0nKPTSEiSZLbzJ2u5cGXx19XVha1bt+LNN9/EsmXLHL2cucTcqQDaUoDx+fwxFUBXHvagq2BDQ0NYuHChXafWpoLL5SI4OBjBwcFjhEZraysjNMLCwizqedHr9aiqqkJISAi6+vTQ6DXgcjgzvvjaGg6Hg6gAT7MtRiIDPMHnUFAIW3DFokyrGTxzOBwEBAQgICAA8+fPH5MjzeFwHD7oY0mu72h+aJXhqY8bcNeVCbgud+phAj8PPjz4XLMsf2hICvjP+R7wuRwcv9vyCyIddebt7Y158+Yx5yE6Y3XevHkTcorp/ltr+w2OxtuNh1BfN1xlgylxjUaD8vJyLFiwAMHB9vn87p1E+NHwuBzs2ZCKAC/T3ws+Pj7w8fFBQkICdDodpFIp2traxqSR0Dshriz+enp6sH37dvz9739nxZ+TMCsrgAaDweg2rTWgKApnzpzBypUrXXrYg75guLu7W2R27ChooSEWi8Hj8RgxaErlkp4CTUhImLRJfLZBb4FmZWXZ1LRWqTPgj8cbcf3CSGRFeDODPo4YIplq+GE0r3/bDl8PHm5YOtF3TKUj8O9z3dicF4lgH9teaPsGNfB2503r5TcZBEGgqqoKgYGBU0adjcZgMEAikYzpG6R70lzhXKZWq1FRUWHzoR5HMt4GiM/nQ6PRYOHChU5nQD0dfX192LJlC1588UVcddVVjl7OXGTuVABtCX0BIwjCZbd8dTodKisrER4e7nKmmz4+PkhMTERiYiI0Gg1EIhFqampAkiSzvWXs5GjM5mW209/fj46ODuTl5dncf5HL4cBAkpAo9fDw8EBMTAxiYmIYoUFXNCwdIjGF0bm+2dnZ0z5/q1gJTPLZ9Xbn4bZfmJ72MxMi/C1vu6ANjwUCgVnxlHw+f0xvJ91y0dTUZNRv0JmgxV9aWtqsjiwcbbQvkUjQ2NiIiIgI1NbWgsPhMFvFzi4GxWIxrr/+ejz//PMzFn8333wzjh07BoFAgOrqagAjN7nbtm1De3s7EhIS8NFHHyEoaMSncu/evXj77bfB4/Hwyiuv4Nprr53x65lNsBVAM6EoCt9//z1zUXU18UfbYVirF8xZ0Ol0TNVJp9ON2d6SyWRoamqyeRXMmjT0D4PL4WC+wLL1dnZ2QiKRzNj/zZrQQyS0mbo1eztpaxs+n2+1ijZFUXjlq1akR/pjbZrtp+LNRa/XM0M9tOedeFiLF79owUNrks0atqEoCh9X9WNpfCB8uHqH9g1OhVKpRGVlJTIyMtA1zMGfP23Emztz4OfpHO9xW0BH+I1OcdFqtUwFV6PRMDdWAQEBTlXBlUqluO6667Bnzx6sX79+xs/3zTffwNfXFzfddBMjAB955BEEBwfjsccew/PPPw+5XI59+/ahtrYWO3bswLlz59DT04M1a9agsbHRuWJK7cfcqQDaSpTRwx5xcXGoqqpiMiEFAoFTDE9Mh0wmQ0NDAzIzM+HnN3Uerqvh7u6O6OhoREdHM5YLHR0dUCgUoCgKqampDvH4s5TfH6kDhwOU3LZk+gePgq6CaTQa5ObmOtXFgMvlIjQ0FKGhoZP2dloyREJPvvr7+yMhIcGqn/8OmQY9A1qnE4CT2Z6Ih3RQ6QiIhrRmCUDxsA7/93U7zsYH4NmCNIf2DU4GLf7o81dtsxAaPYlhrcHmAtBAkhZHBM4EY+IPADw8PJjzHe2g0Nvbi/r6eoelkYxHoVDg+uuvxxNPPGEV8QcAV1xxBdrb28d87ciRIzh9+jQA4Ne//jVWrVqFffv24ciRI9i+fTs8PDyQmJiI5ORknDt3DitWrLDKWmYDs7ICSBAE05tnLYwNe9AnR5FIxGxBCgQCpxQaPT096O7utngi0tWgB1wGBwcRHR0NiUSCgYEBxn8rJCTEqcTReOr6hsDnciadKu2Wq3GqQYxfLY1hLkz0dLObm5tT93Uai72jJyHFYrFZQyR07Fd4ePiYLVCFWo//+7oN96xKtLi3DgBjKO9Mf0u6l9Xak68XOhSYL/BBgJfxv5c1+gYpisKjh+uQGemHm5ab3n4yPDyMqqoqq3o5nm2TQ0+Q+MU06Tu1vUN449t23Hf1PJM8G63FZOJvKoylkdBbxfas4A4ODmLz5s3YvXs3rr/+eqs+d3t7OzZs2MBUAAMDA6FQKJjvBwUFQS6X45577sHy5ctxww03AABuueUWrFu3Dlu2bLHqelyEuVMBtDaTDXuMDnGntyAbGhqg0+mYC5iPz/Q2EraEjvxSKpVYtGjRnCh/j066yM3NBYfDAenpj3fqWnBrdAhkMhmam5vh4+PDVJ2cZZuUJi1i6grt6UYJzrUrUJAdgSBv9zEGz6YOAjiCg+e7ca5dgT8XpsLH/ee/OT0JGR8fz3yW6KrTZEMkU+X6dkhV6BnQokOqRla05QLQmYTf57Ui+PAp8GRtSElJYfqcrMXi+MApv2+NvkEOhwOCpFDdM2Tyuuj+3ezsbKu2cLxyuhUUhWkFYIAXHx58Hnzdefi/r9sQEeA57WT4TLFE/AFjp/OTk5OhVqshkUjGVHCtnUYynuHhYWzduhV333231cWfORgrbjnT59kZcK6rnpWw5kE2ddhj9BYknXDR0tICtVqNkJAQhIeH233bhCAI1NTUwNPTE9nZ2XPizW8wGFBZWYmQkBDExcUxr3lIY4CBpMD18MGCuPAx2aodHR1wd3dnJopdwV5h6+Jo5GeGI8jbnRFCMTExds8/NZfYIC/81DUAL7eJNyJ9gxrc/H45HlyThNUpPw+RiMViNLe2QaP6eYjEy8sLFRUVmD9/vtEqWHa0P/ZtSoO3kd/TKVNDpSOQGmG7VBBrQ1EUXjrVAr1Oi0O3LbSbWftkjLdqov0GL126NG3f4IubTY/9olNccnJyrL6z8rctmSBNiAyNDvTCX64bSXa50KkAl8OxqQC0VPwZw8vLiylS0K0xXV1dVksjGY9SqcT27dtxyy23YOfOnVZ5zukIDw9Hb28vIiMj0dvby7RExMTEoKuri3lcd3e3yQb4c4VZuQVMkiT0ev2MnsNa5s4EQTBxZ8PDwwgODkZ4eLjN485oURAZGWnWdKAro9FoUFlZifj4eLNtXlQqFWMvw+FwGDHo5eUF8ZAW/UNaZEY5n0k0PRE5WghV9wyiS6bGukzXsrqRKnW46d1LeGhNEq5K+XlA6ZFDNdAZKPx1UxoGBxQQCoUQi8UICgpCTEyM2UMk6/9+FiRF4cTdy1zmpmhoaAhfnK1EbmYaEiOc27NyfE6xpVUnhUKB+vp65OTk2HX7Uk+QcOMZ39LWEyQ4HNisH5AeWLOG+JsKiqKgUCggkUgglUrh4eHBiHZLW4TUajW2b9+OrVu34rbbbrPyin9m/Bbwww8/jJCQEGYIRCaT4S9/+Qtqamqwc+dOZghk9erVaGpqmhO7YEaYO1nAMxWAtPgjCAJcrvUijEiSZHJVBwcHbRZ3Njw8jOrq6kmrI7MRepsoNTV1xltjoy9gBoMB+8sJUFw+/rVrIdz5znPyGBwcRE1NzYT4vi0HzkNPUCj77RKrBd5/US/GVw0S/HFjqtWe01Q+rRHhfIcCT+YvYCpCmZmZIEnSoiSSur4hKLWE0S1PgqTw2OFaXDk/BBuyIib+sAOghVB2drZFVbBWiRLxwd52P27Azxm49A2wqX2DcrkcDQ0NyM3NtemAHUVRUKj1CPIeec9o9ARu+3cF5oV645kNqTb7vcawl/gzhlKpZPo7TUkjGY9Wq8XOnTuxYcMG3HXXXTa7sdqxYwdOnz4NiUSC8PBwPPPMMygqKsLWrVvR2dmJuLg4FBcXM8bgzz77LN555x3w+Xzs378f69ats8m6XIC5IwApioJOp7P4Z+2R7DE+7szf35+xxJiJGJRKpWhqakJmZqZNg++dCfo128LmRa/Xo6a9Fw1dIsR7G5gpSFv20JgC/ZqNiQKZUocBtQGJodbbMnukrAYaA4mXr8902OumTa2NVYQsHSIZD0VR2F1cA28PLvYWpltz+RYxOsvYEiHULlXh+c+acE26wOZ9a9NBn/PEYjFkMtmkfYMymQyHz9QhI3UBliXZdvr6aEUvPq0V4/FfzkdskBcoisItH1Rg26IoXJsumP4JrAQt/nJzcx0+pEe3MInFYqNpJOPR6XS46aabcNVVV2H37t0uU1WfY7AC0JSfc0SsG0VRGBgYYKoZPj4+CA8PN3uMv7u7G729vcjOznb4ScRe9PT0QCgUIicnx6y7Zp2BBAUKHmZU9AiCYKoZQ0NDCAoKgkAgsImp8VT09fWhs7PT4jgohUqPv33ZgvuvTkKgt22MfkmKglpPjBn0mAm0qbUpU+xarXZCEklYWJhDrEtmglgsRltb24wm9wmSwud1YqxIDLLZsbaE0X2Do/0G+Xw+urq68EGbJ/h8Hv62JdOm6+gd0OBoZR9uuSzOITYvgHOJv/GMTyPx8fFBZ2cnFi9ejIiICOj1etx8881YunQpHnnkEZf6fM0xWAE4Fc6S7EFRFIaGhiASiSCRSEzKvqW939RqNTIyMuZEjwNFUWhra8Pg4OC0kV/GuO+jKlAU8Mq2LIt+P31iFIlEVjc1NgZBUjhU3ot5XmpAPTAjg+eK7gG8/m0H7rg8HjkxtklSeKh0pGK4//qMGV9YhUIh+vr6kJ2dbXYyxXjrEkeJdnPp6+tDV1cXcnNznTKNw9poNBq0tbWhr68PXl5e4PsGQRAWilhBsFnn4wdLaxAZ4IGH1iTbcLXWw5nF33goioJSqcSrr76KI0eOgMvlws/PDwsXLsT+/ftZ8efczB0BCIxUAUzBWsMetoKeVJVIJODz+RAIBBAIBEzlhzbB9fHxQVJSktOt3xaMtnlJSUmx6DUfq+qDnqCwyQrbYnQFl/be8vLyYvrRzLl4d8nVeKSsFn+5Lh2xQWO3LvsGNHj4o5+QK+Dj/o2LZyReKIqCxkDCk2+9/tbxnG2T4ULnAO6+MnFGz2Nqrq8p2Fu0WwoteHNycpzOnsgU6B0UcxCJRGhvb0deXh44HI7RvsE6OfD3bzrwjx1ZTM/eeHYXV4PDgc0rh9bAlcTfeAiCwB133AGlUgkOh4P29nasXr0aBQUFWLlypUu+b2c5rAAcj7OLv/Go1Wr09/czfU7BwcEQi8WIiYlBdHS0o5dnF2ibl+DgYMTHxzvdMaPvkseLdlOm6yq6B/DnT5rwh3Xzx1TmaINnuY6LJVkL4Ok2+0+uFEWhqakJOp0O6enpNskNpg1z6Uo7PQXpSBugzs5OSKVSZGdnO5UoNZVBjR5PHKnHtelhJg/R9Pf3My0N42+YRvcNflorxskuEi9sTERSTIRLV0bp3k575HRbG5Ikcd999yE4OBj79u0Dl8uFWq3Gl19+iY8//hg//PAD7rjjDtx1112OXirLz8wtAajT6YwaQdI4qt/PWkilUtTU1MDd3Z3pn3HWFBJrQdu8xMXFTTD+dQakSh0ePVSLvUVpCPMdOamr1WrGXoaiKLOP02hfw/j4+Gkf3y5Vwc+TjxAf5/cyBP5nsk5SY2w3bJHrOx3GhkjCwsLs9nmiWxqGh4eRmZlpl+3pQY0et35QgeeL0iZNuDjTKsM3zVI8tCbZpCliHUHikbJabFsUhRXzprer6e3thVAoRG5u7rRVo8n6Bp0lp9hU6AlnVxV/Dz30EDw8PPC3v/3N6PuUvrkKCLBNewmLRbBJIDSuLv4kEgmam5uxaNEi+Pj4TEghCQ0NRXh4uMNTSKwJHQVlDZsXW9EuVUGpJdAuUTEC0MvLC/Hx8UzChUgkGnOcjCVc0NB5r6YKXpKi8JfPm+HO52L/9c6/BQYATx1rgEypw/7rM+HG49o013cq6CSShIQEZohk9HGy5RAJ3cOr0+mQlZVlt9fcP6jFsNaA6p6hSQVgyaUeqHWkyc/pzjP9vdfT04Pe3l7k5ubieI0YkQGeWJow+Webw+HAz89vypxiW6dczBRXF3+///3vweFwJhV/wM9pJCzOz5yrADrLsIeldHV1ob+/H9nZ2Ua3qugRfpFIxKSQOINtyUygt0tsYfMyHVoDgUG1AWF+05+sKYqCnqDgxpv8vTWg1qNJpERutC9znHrlSoSFBGFeTARjEK5SqVBZWWm2l2NF9wCCvN0RF+waFZHPakX4tEaEv12faTTX11husD0Z72Nn7SESiqJQX18PDodjVj+rzkDixVMt+NWSmAnH+ly7HHwuBwvjAqf93XqCAp/HmfRvTFIUSIqy+oRsd3c3RCIRcnJywOVyce9/q8A3QzyOhz5OYrEYQ0NDFuUU2xpXF3/PPPMMZDIZ3nzzTZdsT5jjzK0tYL1eD5L8+c7V1fr9xkNRFBobG5meKFM+gLRtSX9/P5NCQl+8XOX19/b2oqura0ZWGDPhvuJqaPQE/r49y6SLoNZAwJ03+XDFY4dq0SJR4cANOQj0GulhuvM/FSAMety3yAuDg4Pw9vZmppsDAwOt+XKcFrraOTrF5YNzXTh4vgfv78pD8Ay2tO/7qBotEiWO3rnULDEpV+nw9LEG3HlFAtIi/Kw+REL3dnp6epo9wNUuVeHOg5UoyonA7ZcnjPnePf+tBAccvGrhhLut6erqgkQiGdPnOKjRg8/lwtt95sJivN+gt7e3RUNZ1sSVxR9FUXjuuefQ2dmJd999lxV/rsnc3QJ2dfFnMBhQXV0NPz8/s3qieDweMzVMkiRkMhl6e3tRX19vsxQSa0H3RA0MDGDRokUOO+ncuyoRrRKlSeLPQJK476NqePB5eHmr8UrGg2uT0NA3zIg/APjNyjh4u/OQEeUPiUSC+vp6BAUFoa6uDr6+vszFa7aeeI3F2QGAwM8DPC5mLAqUOgM4gNmVRD0x0p8oV42kCnG5XISEhCAkJGTMEElra6vZQyQkSaKqqgr+/v5ITDR/UjohxBsHfpUDgZHK9NPrUxxaNZ2Kjo4OyOVypvJH4+9pPWE2XU4x3Xphr77B0akmrij+XnjhBbS2tuL999+fteegucqsrwC6er8fPfgQGxuLyEjrOPlPlkJizVDwma5v9LaYMwrUyXjyaD2uXBCCNanmJxj09vaiu7ubMbW2xBNyPMNaA/7vm3bccXm8VS+y1oKOLUxLS3PpviFzhkgIgkBFRQXCwsIQGxvrgNWObCH/0CrD5ckhdouIa2trw9DQkMVDLgq1Hk8fq8cTv1xgVPiagrVyik3FXpF2toCiKLzyyiu4cOECPvzwQ5eeumaZY1vABoMBBoPBpcWfNfNtJ8NaKSTWwmAwoKqqCkFBQU5p82Ir2tvbIZfLkZWVNenfnbaXEYvFYya/p7qwfNcsxV9OtuCB1fOwakGorZZvEXSub1ZW1qyKLaSHSMRiMXQ6HdOH6+fnB4IgUF5ejqioKERFRTlsjV81SPDv892458pE5MbaVnhTFIXW1laoVCpkZGRYfENX2zuEl0614PZfxGPJFMMipmLrvkE6w9lVxd/rr7+Or7/+GiUlJQ61RmKxCnNLAMpkMri5uYHD4bhUBYlGLBajpaXF4gB4S6C3S/r7+y2uOM0ErVaLiooKq1Y7nR26t1Ov15vld6fRaCASidAq7MeQhkBmQjgEAsGEIRmCpCBUaBAV6OGwqCtj0FnGdK6vzkDiryebsWNJ9KQTqa7I6CGSoaEh6PV6xMTEIDEx0aHnJY2eQG3vELKi/cdY8FgbiqLQ0tICrVaL9PT0Gd3QURQFgqLAs8HNvLX7Bl1d/L399tv49NNPUVZW5nLrZzHK3BGAFEUhPz8fKpUKGzduRFFRESIjI12mmtTZ2QmxWGxR9JU1GV1xMpZCYk3orcCUlBSntXmxNiRJoqamBp6enkhOTrbo/XnPfyuh0RHYc7UAErEYGo2G6XFy1uxbOtd3dJaxTKnDw4dqcfWCUPxqaYyDV2g+XzdJkRzmg+hA4xdLrVaLS5cuQSAQQKvVMkMkYWFhJvd3UhSF49X9SAjxRmaUv7VfgtWhzbwNBgPS0tKmfC9+3yKDcECN6/OiHP6eHe83yOVymWq7KX2Driz+AOC9995DaWkpjh496lL+iixTMncEIDDyIe7u7kZpaSnKyspAEAQ2bNiATZs2ITY21uEnGWOQJInGxkYYDAabpB/MBNrQWCQSgcPhMGLQGic42uYlMzNzVm0FTgVt8BwaGoq4uDiLn6ddqoJkWIfF8YEARvrLaHuZ0bYlQUFBTvGe7+7uRn9/v9GYM6XOAE8+z249acNaA4a1BkT4z+w9rDUQuPvDKni78/DK1omTt/SQy+ibG4qicL65D2U/dWNjHAFvTw+m2j7ZDRZBUrjzYCXc+Vy8ZqMJX6XOADceF+4zrApSFIWGhgYAMMneZsfbF2EgKXx06yKneJ+ORqPRMJ+p6foGXV38HTx4EP/+97/x8ccf291yi8WmzC0BOBqKotDX14eysjKUlZVheHgYGzZsQGFhodPk59K9bwEBAUhMTHSKNU2GVqtlxCBBEIwYtGSr2tE2L46A3uq2daIJPfktEokwMDDg8GEfa+b6WoO7PqyEzkDizV/lzHhqtrF/GAJ/jzHT3cBIFb2qqsrokMv+L1tRJRzEK9syAb3WpCES8bAW3m48+HhYvz+XoihseuM8uFwOyn67ZEbPU19fDy6Xa7JrwZDGAK2BRKivc/eaje8bDAgIYD5Tg4ODLi3+SkpK8NZbb+H48ePw8/Nz9HJYrMvcFYDjEYlEOHz4MEpLSyGTyZCfn4+CggKkpqY6RHhpNBpUVFQgPj7eKSPOpoJOIRGJRGalkFAUNUYQzJXwcFoQLFiwAMHB00dlWQtjwz50j5Ot//b0VqBer0daWprTVLabRMPoG9Ti8mTTjbbNgR7iyszMNHpBNZAkdAZqgs3NVEMklp6fCJLCvf+twpULQrBt0eS54a+ebkW4vwe2LrQsW5yiKNTW1sLd3d3itgZXYXTfID1VPG/ePERFRbncxOzRo0fx6quv4vjx41b1Hk1ISICfnx94PB74fD4uXLgAmUyGbdu2ob29HQkJCfjoo4/mTNuPA2EFoDFkMhmOHDmC0tJS9PT04Nprr0VRUdGMptXMYXBwEDU1NUhLS3N501+DwcCIwalSSGibFwBITU11GkFga+ip18kEgb2ge5xoexk3Nzeb9XfSub5ubm6YP3/+rBAETSIl9ASJ9MjJj+HAwADq6upmnF4zPomE9PBHWkKk2UkkFEXh9v9UIsCLj79el2HxeqaCNrb28vLCvHnz7HKsdQQ54+3qmaJQKFBXV4cFCxZgYGBgTN+gPfOkLeWTTz7BX//6V5w4ccLqN6UJCQm4cOECQkN/diB45JFHEBwcjMceewzPP/885HI59u3bZ9XfyzIBVgBOx8DAAD7++GOUlZWhtbUVa9asQVFREXJzc20iUkQiEVpbW+066Wsv6BQSevqRTiHx9fVFdXU1AgMD7Zr16mjo/GZ66tWZUKlUzLAPvf1oDaNcc3N9JcM63PJBOe69MgFr0gRm/z61noCXm+23lm//TwUoCnjzVzlGv0/3tFr7WB+r7MNrp1tx+0JfRPCUZg+R2BKSJBmzekuMrS3hXz924ZtmKV68LgOB3o6puNFCf/y2rzl9g47k5MmTePbZZ3HixIkxIs1aGBOAKSkpOH36NCIjI9Hb24tVq1Yx/aIsNoMVgOYwNDSEEydOoLS0FPX19bjqqqtQVFSEJUuWzFgMUhSFjo4OSKVSh0/62oPRKSQikYjpc3TWFBJr09PTA6FQyBg82wqKolDbO4z0SF+zLzIaPQEelwPSoGequAaDgZkonm5LfzzGcn3HI1Xq0DegRUbUSCVNodbj1/+6hDuvSMAv080TgN81S/HOmS78Yd18m9vIdMnVIEgKCSETb9roZBBbpD70D2px4PsO7L56HnzceUwSiVQqhbu7+7RDJLaCTjUJCAhAQkIC8/Xf/rsCgxoDPrxlkU1+70+dCrz1fSde3ZZlt8Gh0dDibzqhP1nfYFBQkEOF++nTp/HUU0/h+PHjTPyitaHP8xwOB7fffjt++9vfIjAwEAqFgnlMUFAQ5HK5TX4/CwMrAC1FrVbjs88+Q0lJCcrLy3HFFVegqKgIK1asMPsDTG9/UhTlVP1Qtoa2eaG3AekUkpnmqToztNCXy+Vjck9txfctMrzxXQfu+EU8ViaZt5Wz+c3z4HI4KL5tMfM1vV7PVDHoLf2wsDAEBARMKQaN5foa466DlVDpCby5Mwfu/Jl9DjpkKvzl82bsLUqbNvGkXarChQ4FNudZ1xqqv78fnZ2dyM3NtftNnTlJJDOlVaKEWkciI2rE2LqyshIhISETptl3vH0RFGAzAehITBV/4zHmN0gfK3u+Z7777js89thjOHbsmE0NyXt6ehAVFQWRSIS1a9fi1VdfRUFBASsA7Q8rAK2BVqvFF198geLiYpw/fx4rV67Epk2bcNlll037Adbr9aiqqkJwcPCcSrmg45DG27yMHkwYb77q6kMhtMEz7YFmD6Gv0hH4ukmCVQtCzd4KfeGLZgR7u+PmlcYtacZv6U+WJT1Zrq8x+ge16FaosSgu0Ky1zpRbPyhHz4AG/71lMfw8rfM+6+npQU9PD3Jzcx3+3rXFEMlorj9wASRF4b8356GyshICgWDSKu9sxFLxNx6KosYId3v1DZ49exb3338/Pv74Y7tGEe7Zswe+vr44cOAAuwVsf1gBaG30ej2++uorlJSU4Pvvv8fSpUtRWFiIVatWTdiGaWxsRGdnJ7KysmxWbndG+vr60NnZOa3Ni6NTSKwJ3Q/l7e3tNDZD1mR8ljRdxfXw8EBdXZ3Vc31JioJkWGdx/ut4BtR6CBWaKYc4zKGzsxMSiQQ5OTljqrwqHTFhwtfejB8ioX0hzR0iGU2LWAmlRg+9qAURERGIjrZsYtgVsZb4MwbdNzhauFu7b/DixYu49957cfjw4THb9bZAqVSCJEn4+flBqVRi7dq1eOqpp3Dq1CmEhIQwQyAymQx/+ctfbLoWFlYA2hSDwYBvv/0WxcXF+Oabb5Cbm4vCwkKsXr0aZ86cwX333Yc33ngDK1ascPRS7cJMbV6MpZCEhYU5vVcg3fsmEAjsenftKCiKwuDgILq6utDf34/AwEBERkZaVbjv/7IFP3UO4MUtGQjzda7j39bWhsHBQWRlZY0RVOfb5Xjt63Y8ek2y1YTmTCFJEnK5HGKxmBHuYWFhZud+GwwGlJeXIzo6es5ENgK2FX/jMdY3SOcUW9pKUlFRgdtvvx1lZWVITk628oon0traik2bNgEYeT07d+7EE088AalUiq1bt6KzsxNxcXEoLi62qyXWHIUVgPaCIAj88MMPKC0txaFDhwAADz74IHbu3Dnrpn2NQZIkGhoaQFGUVWxebJlCYk1og+fpet8czakGMc60yvH4tfMtbp7XGUj80CrDlfNDIJPJ0NTUhOzsbJAkydjL8Pl8ZqLYw8MDTaJhKFR6LEkwz/OrS67GF/Vi7FruPAk+FEWhubmZybgd/x7vHdDgmeMNeLYwDSE+zmduTAt3c4dI9Ho9ysvLERsba3fPUoqi8FmdGCvnBU3b52lt7Cn+xjNZ32BoaKjJAz81NTW45ZZbUFxcjJSUFBuvmMUJYQWgPaEoCvv27cPXX3+Nhx56CJ9++ik+//xzJCUlobCwEL/85S9npds63RRuK5uX8SkktMBwdGyRowyeLeG2f1dAZyDxz5tyLU7A+OhiDz4414XfrRTAXysek+sLjLz/NRoNM1FMURT+eFYHDpeHI3cucxohZwl0zBl9g2ON16JQ6SEe1mK+wH5RiD+2yREX7IWoAM8xVkAAmM/V6BtWWvzFx8dDIDDfpmemtEqUeOrjBuRnCrBzif16Dh0p/sZjSd9gfX09du3ahYMHDyIjwzYekCxODysA7YVOp8Ndd90FNzc3vPrqq8z2CkmSqKioQHFxMT755BPExMSgsLAQ+fn5Lm8CDYyIs8rKSsTExNhla0in00EikaC/v59JIaG9Bu0pMJzF4NlUCJICSVFwm4GB7rDWgE8uNiPebRgL88YOPmj0BO48WInc2ADcd9U8ACPHqrK1B529YkR7kw47VjOFNra2dtLFljfPQ0eQKPntErsYG2sNBG77oAJe7jy8sXOsn6FWq2Wmv+letKCgIDQ3N2PevHkICwuz+fqMQVEUKoWDSBb4wMfdPoM2g4ODqK2tdQrxZ4zRfYNarRZeXl6QyWS44oorwOPx0NTUhBtvvBHvv/8+cnKM+1ayzAlYAWgPKIrCddddhyuuuAK7d++e9AJBURSqq6tRUlKC48ePIzQ0FEVFRVi/fv2005POiKMrYAaDgRGDU6WQWBva9y07O9spLxDWQq7SIch7pMJH93cODAwYzfWlKAq3/bsC+RkCXJc30WKCPlYikQhKpZIxCQ8MDHRqMUj73fn7+1vd7LhFrESbVIU1qfYTVzU9Q4gI8Jhyi9pgMKC/vx9NTU3g8XhMtWkueHg6u/gbj8FgQHV1NZ577jnU1tYiIyMD9fX1+Ne//oWVK1c6enksjoUVgPZCJBKZtUVCbymVlJTg2LFj8PX1RUFBATZu3AiBQODUF0VgxOalvr4eWVlZY2xeHMVkKSTWFhj2Mnh2NF83SfHmd+149Jr5yIrys2quL0mSTLP7wMAAY5IbHBzsMIFBkBSePlaPtWkCXDl/5GZsKr+72YxWq0V5eTmSk5MZv7aZDpG4Aq4m/sbT2tqK22+/HfHx8aitrWVaj1y1wMAyY1gB6ApQFIXW1laUlJTgyJEjcHd3x8aNG1FYWIjISOsa11oD2uYlOzvb6YYygJ9TSEQiESMwwsPDZ1TBmK4CNtsQD2nx1g+duOvyeHS3Ndks15eiKMZeRiaTwdfXlzEJt6fA0BMkrnvzPNx5XJT+dgkz2T0TyxOVjoBSa0CYlaxs7IFGo8GBTy9gUWoiVqaOfd0URWFoaAgikcgqSSTNYiX+fKIRzxamIjrQsYKLFn+uGtHZ09ODLVu24LXXXsMvfvELUBSFuro6HDlyBMePH4ebmxsOHDhgl0lgFqeBFYCuBkVR6OzsRFlZGQ4dOgSSJLFhwwYUFRUhNtaxE5F0yoVMJkN2drZLVAAoioJcLp9RCgldrSVJ0ioTzq4CQRBM3Jc9sl5JksTw8LDVBIa5qP8XjcchCatMvd78fjn0BIl//TrP4sGbMQyLwGs8Dq6oBpRnIMj5vwQZtRDgWOf9qFarcam8HK/W8ODl4Y53bsyd8vHjh0hCQ0MRHh5usoCqEg7ihS9a8GT+AiSHOW6gy9XFX19fH7Zs2YKXXnoJq1atMvqY3t5eBAYGumRlk8ViWAHoylAUhd7eXpSVlaGsrAwqlQobNmxAYWEh5s2bZ1cxSIsggiBcNs6OtsGgBYYpKSQEQaC6uhq+vr52/5s7ElNyfa3Jge868G2LFP/Yng0fj5FjYWzy0dZWQPT2pzmDD/u/bIWfBw+3XBY/5utVwkF0KzRYlzHz6Vlu149w+/IpcAg9KJ47QBoAigQZdxn0Vz0N8GZmkaJSqVBZWYm0tDQo4QEfdx4CvEx/zppuOZ45Xo+dKW6I9CKsnkRiK1xd/IlEImzevBnPP/881q5d6+jlsDgXrACcTYhEIhw6dAilpaWQy+XIz89HYWEhUlJSbHqSpStBdCO8M5/QTYVOIaH96zw8PCakkOj1eib2ai4YPNOYmutrTT6pEeGji0K8faNxm5rR9jK0FVBYWJhV+0/pSDtzh5o2vXEOHHBQdvsSq61l7MJk8PhoB8B1A9xGVXAoChyVBPrFt4LIucHip1cqlaisrERGRgb8/f0teo42iQp7jjfg6fULEBfoMcbQOCgoyCmHSIaGhlBdXY2cnByXFH9SqRTXXXcdnnnmGeTn5zt6OSzOBysAZytSqRRHjhxBaWkp+vr6cM0112DTpk1GDWpnAm3zEh0dbdMAcUczPoUkKCgIfX19SEpKcoj/maMwJ9fXUej1ekYMajQaq0x/0xWw1NRUs+2ZdAQJDjAji52p4FUXg3/+H4CXkeNh0ABcLrQ7Dlm0FTw8PIyqqiqb2RmNTyJxVI/neIaGhlBTU+OylT+5XI7Nmzfj8ccfR2FhoaOXw+KcsAJwLqBQKPDxxx+jrKwMbW1tWLt2LYqKipCTkzMjMUjbvDizGLAFUqkUNTU1cHNzg5ubG7P1ONv7Z4aHh1FdXW31XF9bQhAE44lGV5vMzb21tQiaKfyvnwWv9SvAy3iaCkcthWbnEcDDvLXTFTB7TfIbGyKhK7n2jHt09crf4OAgNm/ejPvvvx9btmxx9HJYnBdWAM41hoaGcPz4cZSWlqKhoQFXX301ioqKsHjxYrPEoEKhQF1dndNeFG0F/brpi6KzppBYGzr5IDMz0ylsfSyBrjaJRCIoFAr4+/szliWTDfzQht7Z2dlOe0z5598Av+pDUN6hE79JGgDdELQ3fmJWH+Dg4CBTAXPU6zYlicTauLr4Gx4expYtW3DnnXdix44djl4Oi3PDCsC5jFqtxieffILS0lJUVFTgyiuvRFFREZYvXz7lBGx/fz86Ojqc1ubFVtAGzzk5OUZfN7316OgUEmsjlUrR1NTksv5nxqAoCgMDA0YHfugeT7lcjoaGBqd/3RxZK9wP3wp4BgLcsZ9bjlIMw4J1MFz+qMnPR4t9Z9r+1Ol0zLa+VqtFaGgowsLCrGrq7uriT6lUYtu2bfj1r3+NX//6145eDovzwwpAlhG0Wi1OnjyJ4uJiXLx4EStXrkRRUREuu+wy5oJIkiSee+45ZGZmYsOGDS5h82IthEIhent7kZOTw/w9pmJ0soVKpbJbCom1ocX++Fzf2cT4gR83Nzd4e3tDLpcjLy/Pajc5WgOBk3US/DIjDHwrDzvwz/0DvOr/AnwvwM0HIA3gaBWgvEOh3fg64GOkOmgEhUKB+vp6pxa9BoPB6kMktPhz5krvVKjVamzfvh1bt27Fbbfd5ujlsLgGrABkmYhOp8NXX32FkpIS/PDDD1i6dCk2btyI//73v1Cr1fjXv/5l154cR0JRFNra2jA0NITMzEyLDJ7Hp5AEBQUhPDzc6WPOuru70d/fj5ycHKcT+7W9Q+iUqfDLDOtPIXd1daG9vR0eHh7gcDgQCARW6fH8rFaEt7/vxENrk7A0wXi/nsVQFLitX4Jf8QG48lZQbt4gUjbAkLUNMLY1bAS64pmbm+sylX2SJBmjcEuHSFxd/Gm1WuzcuRMbN27EnXfe6dTnFBanghWALFNjMBjw+eef45577oG/vz8yMjKwadMmXH311S5zkbAUiqJQX18PiqKQlpZmlROrsRQSR8ecjYdONRkcHLRY9Nqam/71E/QGCh/8ZiF4XOtG+fX09DCVXq1Wy2w96vX6GW3ra/QEqoSDyI0NsNlEMACAogAz1yaVStHc3Izc3FyXvbmzZIjE1cWfTqfDjTfeiNWrV+O+++5jxR+LObACkGVqaCPRW2+9FTfccAO+//57lJaW4ssvv0R6ejqKioqwdu1al+yZmQra4NnPz89m3oZ0zFl/f7/FKSS2WJM1c31thUKlx4BGj/hg673vurq6IBaLkZOTY/Tvr9frmW19tVrN5El3DHPwdZMU96xKtE6ih52RSCRoaWlBXl7erNrmV6lUjFE4RVEThkhcXfzp9Xr85je/wfLly/Hwww+z4o/FXFgBaA2Ki4uxZ88e1NXV4dy5c1i8eDEAoL29HWlpaUhJSQEALF++HK+//joA4OLFi9i1axfUajXy8/Px8ssvO90HuLGxEdu3b8e+ffsmuMiTJIlz586hpKQEn3/+OebPn4+ioiJcc801Lj8VrNfrmZxXe6RcAJalkFgbkiRRV1dns1xfe9MmUSEiwANebtOL6fb2digUCmRnZ5skegmCYCq5z5yWQE1y8cbWVESEhTitaDaGWCxGW1vbrO7xBCYOkfj7+0MmkyE3N9clp9oNBgNuu+02ZGZm4g9/+IPLf1ZZHAIrAK1BXV0duFwubr/9drzwwgtjBOCGDRtQXV094WeWLl2Kl19+GcuXL0d+fj5+97vfYd26dfZe+qRQFIUtW7bg6aefRnZ29pSPJUkS5eXlKC4uxieffIK4uDgUFhYiPz/fZfziaDQaDSoqKpCYmOgwg+fxQwnu7u4IDw8fk0Jibeg0l8DAQCQkJNjkd9gTpdaAXe9dQqCXGw7ckDvp4yiKQktLC9RqNTIyMiwSb2qdAb1iGXRDMqaSGxYWhtDQUKfcPqfp7+9HZ2cncnNzbfa+ckYGBgZQWVkJPz8/qNVqp00imQyCIHDXXXchISEBf/zjH20q/j799FPcd999IAgCt956Kx577DGb/S4Wu8MKQGuyatUqkwRgb28vrrrqKtTX1wMADh48iNOnT+ONN96w+5qngqIos08uFEWhuroaxcXFOHHiBMLCwlBYWIj169c7vVk0bfiblpZmdtqDLRmdQsLj8ZihBGv1atGRdvbK9bUXH1f1ISc6AHHBxoc3KIpCY2Mjk19tjQvp+Equp6fnhAhBZ6Cvrw9dXV1zTvzRn3F629caQyT2hCRJ3HfffQgJCcHzzz9vU8FKEAQWLFiAkydPIiYmBkuWLMHBgweRnp5us9/JYleMnvCc713vwrS1tSEvLw/+/v7485//jMsvvxxCoXDMhTYmJgZCodCBqzSOJRdEDoeDrKwsZGVl4ZlnnkF9fT1KSkqwZcsW+Pv7o6CgABs3bkRYWJhTbVvQ9hf2Sj0wBx8fHyQmJiIxMRFqtRoikQhVVVUAMOMUEkfk+tqLjVkRk36PoijU1tbCzc1tjPj7ol6M49X9+Ot16RZZtXA4HAQEBCAgIADz589nxPulS5cY8R4WFubQAare3l4IhULk5eU5pcixFePFHwBwuVwEBwcjODh4zBBJe3u7w5JIJoMkSTz00EPw8/OzufgDgHPnziE5ORnz5s0DAGzfvh1HjhxhBeAsZ+6cEcxgzZo16Ovrm/D1Z599dtKsxcjISHR2diIkJAQXL15EUVERampqYKzC6kxiyFpwOBykpaXhySefxB/+8Ae0tLSgpKQEO3fuhLu7OwoKClBYWIiIiAiHvn6RSMT0QTn7ZLOXlxfi4+MRHx/PTKjW1dXBYDCYnUJC5/ouWLAAwcHBNl6580CSJKqrq+Hj44N58+aNee/953w3hjQEOMZvjs1mtHjXaDQQiUSoqalxWGqMUChEX18f8vLynHp72toYE3/j4XA48Pf3h7+/P5KTk5khkqqqKmaIJCwszCEDIyRJ4ve//z24XC5eeuklu2xVC4VCxMbGMv+PiYnB2bNnbf57WRwLKwCN8MUXX5j9Mx4eHsyd46JFi5CUlITGxkbExMSgu7ubeVx3dzeioqKstlZnhMPhIDk5GY899hgeffRRdHR0oKysDLt27QJFUdi4cSOKiooQExNjVzHY3d2Nvr4+LFy40OW2wjw8PBATE4OYmBgmhaSpqYlJSpjKroS+IKanp7tcn+ZMIAgClZWVCA4ORnx8/ITvv3VDLigKVrWWofH09ERcXBzi4uKYoYTGxsYxx8vPz89m7396yjk3N5cVfybg7e3N3GzRx6upqQkajcYmSSSTQZIk9uzZA6VSiQMHDtitT3GuFCpYxsIKQCshFosRHBwMHo+H1tZWNDU1Yd68eQgODoafnx9+/PFHLFu2DO+99x7uvfdeRy/XbnA4HCQkJOCBBx7A/fffj97eXpSWluKOO+6ARqPBhg0bUFhYaDP7FWDk5Nba2orh4eFZUQ1xc3NDVFQUoqKimBSStrY2oykko6O+XNH+wlIMBgMqKiqm7HXkcjiTdMZYF3d3d0RHRyM6OppJtujo6MDw8DBjL2NNo/DOzk5IpdJJLW5mK7T4y8rKmtF7ffTxoo3du7q6MDQ0hMDAQAgEApsMkVAUheeeew79/f1499137TqkEhMTg66uLub/c6FQwcIOgZjNoUOHcO+990IsFiMwMBC5ubn47LPPUFpaiqeeegp8Ph88Hg/PPPMMNm7cCAC4cOECYwOzbt06vPrqq3P+7oqiKIhEIhw6dAhlZWWQy+XIz89HUVERFixYYLW/D0mSqK+vB4fDQWpq6qz+u49PIfHy8oJSqUReXt6s826cCr1ej/LycsTExCAyMtLRy5mU8Ubh/v7+zFCCpRf/9vZ2DAwMICsryyWmXK3FaPFnq75eWw6RUBSFv/71r2hoaMD7779v935Ng8GABQsW4NSpU4iOjsaSJUvwn//8BxkZGXZdB4vNYKeAWZwXqVSKw4cPo6ysDH19fbj22muxadOmGRkU03Yn/v7+Nq0wOiN9fX1obW2Fv78/hoaGnDKFxBbQgy4JCQkOs/axBNooXCQSQSaTwcfHx2xvSLrKnZmZOauP8XjsIf7GQw+RiMVixr7J0iESiqLwyiuv4MKFC/jwww8d1p5y4sQJ7N69GwRB4Oabb8YTTzzhkHWw2ARWALK4BgqFAkePHkVZWRk6OjqwZs0abNq0yWTjXuBng+fIyEhER0fbeMXOxfhc3/HiwhlSSGyBRqNBeXk55s+f7/Q2RFNhzBuSnig2ZuBMtzio1Wqkp6fPKfGnVCpRWVnp8Il+Y0kkpgyRUBSF119/HV9//TVKSkpmtUE3i0NhBSCL6zE4OIjjx4+jrKwMDQ0NWL16NYqKirBo0aJJL3S0wfO8efMQFhZm5xU7DlNyfcd713l5eSE8PNyuKSS2QKVSobKyEqmpqU7l62gNVCoV4w3J4XDG2AFRFIXm5mbodDqkp6fPqSq3s4i/8dBDJGKxeMohEoqi8Pbbb+PTTz9FWVmZ07sSsLg0rABkcW1UKhU++eQTlJaWorKyEqtWrUJRURGWLVvGiJ3z589j//79+Pvf/z7rhMBU0EbHBoPB5G1zcytNzgq9BZiRkQF/f39HL8emaDQaRlzo9XpwOBx4enrOuW1fZxV/4xndl1tbW4sTJ06gsLAQ69atw0cffYSysjIcOXLEYm9PFhYTYQUgy+xBo9Hg5MmTKC4uxk8//YTLLrsM8+bNw4EDB/D+++8jJyfH0Uu0GyRJora2Fh4eHkhOTra4CmTrFBJbMDg4iJqaGqcXAtaGoijU1dVBrVaDx+NBo9FMmACfrbiK+BuPVqvFyZMncejQIZw5cwY6nQ779u1DUVGRy2eqszg9rABkmZ3odDr86U9/wltvvYXIyEjk5uaiqKgIV1xxhUtVsizBVrm+arUaYrEYIpEIFEUxYtCZKhV0okt2dvacmnKmxR+fz8f8+fPB4XAmTIC7Wuatqbiq+BtNSUkJ3nrrLezduxeff/45PvnkE4SGhqKoqAgFBQWIiJg81YaFxUJYAcgyO3n99ddRWlqKkpIS+Pj4MA3V3377LfLy8lBUVISrrrpq1vXY0Lm+ERERNh10oVNIRCKRRSkktkAqlaKpqcklEl2sCR1r5+HhgaSkJKOVPpIkIZfLIRKJoFAoZs3Qz2wQf0eOHMFrr72G48ePj2lRaW1txZEjR3D06FE899xzWLFiheMWyTIbYQXgXKW4uBh79uxBXV0dzp07h8WLFzPf27t3L95++23weDy88soruPbaawEAFy9eZLwL8/Pz8fLLLzvdthJFUXj66afR0NCA9957b8JWJUEQ+O6771BaWoovv/wSmZmZKCoqwpo1a1y+YuQouxM6hUQkEjEN7uHh4ZOmkNgCOr81Nzd31ld4R0OSJGpqauDt7Y2kpCSTfsbY0A9tL+NKaTi0+MvMzHTZ7dITJ07ghRdewIkTJ+ZUHCOLU8AKwLlKXV0duFwubr/9drzwwguMAKytrcWOHTtw7tw59PT0YM2aNWhsbASPx8PSpUvx8ssvY/ny5cjPz8fvfvc7rFu3zsGvZCzl5eX417/+hRdffHHabS6SJHH27FmUlJTg5MmTmD9/PjZt2oRrrrnG5aoJzpLrS6eQiEQiqFQqJtUiICDAZmKwt7cX3d3dyM3NdSkBM1PoTGM/Pz8kJiZa9BwURTF9nhKJBHw+n6nmOnOf52wQfydPnsSzzz6LEydOIDQ01NHLYZl7sAJwrrNq1aoxAnDv3r0AgMcffxwAcO2112LPnj1ISEjAVVddhfr6egDAwYMHcfr0abzxxhuOWbiVIUkSly5dQnFxMT799FPEx8ejoKAA+fn5Tp+V66y5vgRBQCaTob+/n+lBoyOzrCUGx/sbzhVIkkRlZSWCgoKMZhpbilqtZoZ+aO86gUDgVNXx2SD+Tp8+jaeeegrHjx9HeHi4o5fDMjcxehKeO2dRlgkIhUIsX76c+X9MTAyEQiHc3NzG5KfSX58tcLlcLFq0CIsWLcJzzz2H6upqFBcXY8OGDQgPD0dBQQE2bNjgdNs0zpzry+PxGPNbugetr68PDQ0NVkkhaW9vh1wuR25urkv3sZkLQRCorKxEaGgoYmNjrfrcXl5eiI+PR3x8PHQ6HUQiERoaGqDT6RAaGgqBQGDXrf3x0N6Oriz+vv32W/zhD39gxR+LU8IKwFnCmjVr0NfXN+Hrzz77LAoLC43+jLHqL4fDmfTrsxEul4vs7GxkZ2fjj3/8I+rq6lBSUoLrrrsOAQEBKCwsxMaNGxEaGurQv4FUKkVzc7NLDD1wuVyEhIQgJCRkTApJU1OT2QMJdMqFUqlETk7OrJponQ6CIFBRUQGBQDDmhswWuLu7IyYmBjExMczWfltbG5RKJbO1HxgYaLfPgEqlQkVFhUuLvx9//BGPPvoojh075tSZ1CxzF1YAzhK++OILs38mJiYGXV1dzP+7u7sRFRWFmJgYdHd3T/j6bIfD4SA9PR1PPfUUnnzySTQ3N6O0tBQ7duyAh4cHCgoKUFhYiPDwcLuKwb6+PnR1dSEvL8/lhh44HA6CgoIQFBQ0ZiChtbWVGUgICwszuqVLm1sTBIGsrKxZexNiDIIgUF5ejsjISLt/9vh8PiIiIhAREcFs7ff09KC+vt4umdKzQfxduHAB999/P44ePWpz8c7CYilsD+AcYnwPYE1NDXbu3MkMgaxevRpNTU3g8XhYsmQJXn31VSxbtgz5+fm49957kZ+f7+BX4BgoikJHRwdKS0tx6NAhcDgcbNy4EUVFRYiOjrapMOnq6oJIJJp1fW/0QEJ/f7/RFBLa647H42HBggVzSvwZDAaUl5cjOjraqSpHJElCoVBALBZDJpPB19eXqeZa6705G8RfeXk57rjjDhw6dMjkaW0WFhvDDoHMVQ4dOoR7770XYrEYgYGByM3NxWeffQZgZIv4nXfeAZ/Px/79+5lJ3wsXLjA2MOvWrcOrr746py7Ck0FRFHp6ehgxqNVqsWHDBhQWFiIhIcFqfyOKotDW1oahoSFkZWXN+q1PpVLJ2MvweDwYDAYEBgbOOfGn1+tRXl6OuLg4p+4ZoygKQ0NDzESxh4cHkyltaZV6Noi/6upq3HrrrSguLkZKSoqjl8PCQsMKQBYWa0JRFEQiEcrKylBWVoaBgQHk5+ejqKiISWiw9Hnprc+0tLQ5JYDorU9aBDprCokt0Ov1uHTpkt29Ha3B+BhBeqLY1H5VWvy5cp5zXV0dfvOb3+DgwYPIyMhw9HJYWEbDCkAWFlsikUhw+PBhlJWVQSQS4dprr8WmTZvMEnHWyvV1RYwNPThjCoktoI29ExMTERYW5ujlzAiNRsOIQYIgpj1m9LRvenq6y4q/pqYm3Hjjjfjggw+QnZ3t6OWwsIyHFYAsLPZCLpfj448/RmlpKTo7O7F27Vps2rRpyu1cW+X6ugJ6vR4VFRVT9r05QwqJLdBqtSgvL0dycjJCQkIcvRyrotPpGLNw+piFhYXB398fHA5nVoi/trY27NixA++++y4WLlzo6OWwsBiDFYAsLI5gcHAQx48fR2lpKZqamrB69WoUFhZi0aJFjBiUSCT43e9+h71791rV7NcVsCTWzmAwQCqVor+/H0qlEiEhITZPIbEFGo0G5eXlDk91sQcEQTBicHh4GH5+flAoFMjKynIqU3Nz6OzsxLZt23DgwAEsXbrUJr9jz549OHDgAFMZfu6555iBvMmiPFlYxsEKQBYWR6NSqXDixAmUlJSgpqYGq1atwuWXX449e/bgvvvuw4033ujoJdoVjUaDioqKGVW/aKsSkUiEwcFBJoUkMDDQqYdnaPGXkpKCoKAgRy/HriiVSly6dAl+fn5QqVTw9/dn7GVcxehbKBTi+uuvx2uvvYZf/OIXNvs9e/bsga+vLx566KExX58qypOFZRxsEggLi6Px9vbGli1bsGXLFmg0Grz//vu46667kJycjEuXLiE+Ph4rV66cVZYvk0FnGs9UABlLIenv70dDQwP8/f0RHh5uU986S6Bfe2pqKgIDAx29HLuiVqtRVVWF7Oxs+Pv7g6IoDAwMQCQSobm5GT4+PszxdNbPQV9fH7Zt24b9+/fbVPxNxZEjR7B9+3Z4eHggMTERycnJOHfuHFasWOGQ9bC4Hs756WJhmQM0Nzfjtddew6effors7GycOnUKxcXFePDBB7F8+XIUFRXhiiuugJubm6OXanXojFdrT31OlUJC+9aFhoY6tEpCT7w6W56zPaCFb1paGnPcORwOAgMDERgYCIqiMDw8DJFIhIsXL8LNzY3xh/Tw8HDw6kcQiUS4/vrrsW/fPqxatcouv/O1117De++9h8WLF+PFF19EUFDQpFGeLCym4jy3xCwsU7Bnzx5ER0cjNzcXubm5OHHiBPO9vXv3Ijk5GSkpKYy/obNz5swZ3HDDDfjvf/+LxYsXw93dHevWrcPbb7+N8vJy7NixA8ePH8dll12GO+64A59++im0Wq2jl20VhoaGUFlZiaysLJs2/tMpJCkpKVi+fDni4uIwODiI8+fPo6KiAr29vTAYDDb7/cZQKpWM191cFn+TvXYOhwM/Pz8kJSVh2bJlSE1NhcFgQGVlJc6fP4+Ojg6o1Wo7r/xnpFIprr/+evzpT3/C2rVrrfa8a9asQWZm5oR/R44cwZ133omWlhYmGebBBx8EMHmUJwuLqbA9gCwuwWzqg1GpVMjPz8f777+P2NjYKR9LEAS+++47lJSU4KuvvkJWVhaKioqwZs0al/TFUygUqK+vR3Z2Nry9vR2yhulSSGzF8PAwqqqqkJWVBV9fX5v9HmfEFPE3HaMtgfR6PTMF7uPjYxfhI5fLsXnzZvz+979HQUGBzX+fMdrb27FhwwZUV1dj7969AIDHH38cAHDttddiz5497BYwizHYHkCW2Ycr9sF4e3vjq6++MumixePxcOWVV+LKK68ESZL48ccfUVJSgj//+c9ISUlBUVERrrnmGpcQFDKZDI2NjcjNzTXZINgWcDgc+Pr6wtfXF0lJSVCpVBCJRKioqACXy2XEoDXXODQ0hOrqamRnZ886D8PpsIb4AwAPDw/ExMQgJiYGer0eEokELS0tUKvVCA4OtukU+MDAALZu3YqHH37Y7uKvt7eXsUY6dOgQMjMzAQAFBQXYuXMnHnjgAfT09KCpqclmk8gssxNWALK4DLOpD8aSixSXy8XKlSuxcuVKkCSJn376CcXFxfjrX/+KxMREFBQUID8/3yn91MRiMdra2pCXl+c0vVw03t7eSEhIQEJCAmNiXF1dDYqiEBYWhvDw8BlVWwcHB1FTU8OKPytuebu5uSEyMhKRkZEgCAJSqRTd3d2oq6tDYGAgBAIBgoKCrDL4MzQ0hG3btuGee+7B5s2brbB683jkkUdQXl4ODoeDhIQEvPHGGwCAjIwMbN26Fenp6eDz+fj73//u1DsfLM4HuwXM4jSsWbMGfX19E77+7LPPYvny5QgNDQWHw8GTTz6J3t5evPPOO7j77ruxYsUK3HDDDQCAW265Bfn5+Q45UTsKkiRRVVWF4uJifPLJJ4iIiEBBQQE2bNjgFPYifX196OrqQm5urksNtOh0OohEIiaFJDQ0FAKBwKxq68DAAOrq6pCTk+OSW/YzwVbibypIkmQGf+RyOfz8/CAQCBASEmKROFIqldi2bRt27dqFm266yQYrZmGxC6wPIMvsgO2DmRyKolBXV4eSkhIcO3YMgYGBKCwsxIYNGxwSMSYUCtHX14ecnByntfQwBWMpJAKBAH5+fpNWc+l+R1b8OWbYhaIoDA4OQiQSQSqVwtPTk9neN+VGRK1WY9u2bdi+fTtuvfVWO6yYhcVmsAKQxXUZ3Qfzt7/9DWfPnsWHH36Impoa7Ny5kxkCWb16NZqamtitEIxcAJubm1FSUoKjR4/Cy8sLBQUFKCgoQHh4uM0b5zs7OyGVSpGdnT2rjocpKSTO0u/oCGiDa0eKv/HQgz8ikQgSiQQ8Hm/KXk+NRoOdO3eioKAAd955Jztdy+LqsAKQxXW58cYbJ/TB0ILw2WefxTvvvAM+n4/9+/dj3bp1Dl6t80FRFNrb21FaWorDhw+Dy+Vi48aNKCoqQlRUlFUvcBRFoa2tDcPDw8jMzHQqA2ZrYyyFxNPTE319fU7Z72hraPHn7AbXarWaqehSFIWffvoJK1euRFZWFnQ6HW688UasXr0a9913Hyv+WGYDrABkYWEZEWhCoRClpaU4dOgQdDodNmzYgMLCQiQkJMzogkdXHXU6HdLT0+fUxZMkSXR0dKCjowPu7u4ICAhg+s9mswimcRXxNx6dToe33noLhw4dgkQiQWBgIFasWIGXXnppThw3ljkBKwBZWFjGQlEU+vv7UVZWhrKyMgwODmL9+vUoKipCcnKyWQKOoijU19eDw+EgJSVlTok/YCQhor29nRl2GRgYQH9/P2QymdOkkNgKVxV/ozEYDLj11lvB5/OZXtqrr74amzZtwsqVK2flcWOZM7ACkIWFZWrEYjEOHz6MsrIyiMVirFu3DoWFhUhLS5tS0JEkidraWnh6eiIpKWnOib/+/n50dnYanXSmKApDQ0Po7++HVCqFl5cXIwZdaSp6MmaD+CMIAnfeeScSExPxxz/+ERwOB1qtFl9++SXKysrw448/YuvWrXjyyScdvVQWFktgBSALC4vpyOVyHD16FKWlpejq6sI111yDTZs2TejrU6vVeOutt7BhwwYkJiY6cMWOobe3F0KhELm5udNOOo8eRhCLxXBzc0N4eLjNU0hsxWwQfyRJ4ne/+x3CwsKwd+9eo9u+BEFAKBQiLi7OAStkYZkxrABkYWGxjMHBQRw7dgylpaVobm7GmjVrUFhYiPnz52PTpk1Yu3YtY8Uzl+jp6UFvb6/FNjd0ColYLLZZComtmC3i78EHH4SXlxfb88cym2EFIAsLy8wZHh7GJ598goMHD+L777/H5ZdfjjvvvBNLly6dU31S3d3dEIlEyMnJscrrplNIxGIxSJK0SgqJrZgt4u/xxx8HQRB47bXXWPHHMpthBSALC4t1kEqlKCgowN133w0fHx+UlJTg0qVLuPzyy1FYWIiVK1e6tPHzdHR1dUEikdjM49AaKSS2YraIvz179kChUODNN99kxR/LbIcVgCwsjuDTTz/FfffdB4IgcOutt+Kxxx5z9JJmRG9vLwoLC/HMM8+M8VzUarU4deoUSkpKcPbsWaxYsQJFRUW4/PLLZ8WwA01HRwfkcjmys7PtIhz0ej0kEglEIhHUarVJKSS2ghZ/KSkpThEzaAkUReHZZ59Fd3c3/vnPf86pqjXLnIUVgCws9oYgCCxYsAAnT55ETEwMlixZgoMHDyI9Pd3RS7OI/v5+rFu3Dn/7299w5ZVXTvo4vV6P06dPo7S0FN9++y0WL16MoqIirFq1yqXNkdvb2zEwMICsrCyHVI0IgmDE4PDwMIKDgxEeHj4mhcRWzBbx99e//hUNDQ14//33Z3WVmoVlFKwAZGGxN2fOnMGePXvw2WefAcCE7GJXgyAINDc3IyUlxeSfMRgM+O6771BSUoLTp08jOzsbRUVFWL16tVP2t01Ga2urU6WbjE8hCQwMhEAgQFBQkNXXp9VqcenSJZcXfy+//DJ++uknHDx4cFZVpVlYpsGoAGRvf1hYbIhQKERsbCzz/5iYGJw9e9aBK5oZPB7PLPEHAHw+H6tWrcKqVatAEAR+/PFHlJSU4M9//jNSUlJQVFSEa665Bj4+PjZa9cygKAotLS3QaDTIyspyGo9DHo+HsLAwhIWFgSRJyOVyiEQiNDY2wt/f32opJLNF/P3jH//A2bNnUVxczIo/FhawApCFxaYYq7A7i4BwBDweD5dddhkuu+wykCSJixcvori4GH/961+RmJiIgoICrFu3Dv7+/o5eKoCfo+30ej0yMjKc9thxuVyEhIQgJCQEFEUxKSTNzc0zSiGZLeLv7bffxpdffolDhw65pN8iC4stYAUgC4sNiYmJQVdXF/P/7u5uREVFOXBFzgOXy8WSJUuwZMkSPP/886isrERJSQny8/MRGRmJwsJCrF+/3mHCg6IoNDY2giTJaZNQnAkOh4PAwEAEBgYyKSQikQhtbW1mpZDMBvEHAO+99x6OHTuGI0eOuHT/KQuLtWF7AFlYbIjBYMCCBQtw6tQpREdHY8mSJfjPf/6DjIwMRy/NaaEoCrW1tSgpKcGxY8cQHByMwsJCbNiwAaGhoXZbQ319PbhcLhYsWOAy4m86hoeHIRKJIJFIwOfzIRAIIBAIJlTFtFotysvLMX/+fAQHBztotTPn3//+Nw4ePIhjx47B29vb0cthYXEU7BAIC4sjOHHiBHbv3g2CIHDzzTfjiSeecPSSXAaKotDU1ISSkhJ8/PHH8PLyQmFhITZu3Ijw8HCbCDOKolBXVwc3NzckJyfPGvE3nvEpJGFhYRAIBOBwOLNC/BUXF+Odd97B8ePHncI/kYXFgbACkIWFxXWhKAptbW0oLS3F4cOHwePxUFBQgMLCQkRFRVlFqFEUhZqaGnh6eiIpKWnWir/x0Ckk/f39GBoaQkREBBISEly2anbkyBH8/e9/x/HjxxEQEGDV5y4uLsaePXtQV1eHc+fOYfHixcz39u7di7fffhs8Hg+vvPIKrr32WgDAxYsXsWvXLqjVauTn5+Pll1+eM+8tFqeAFYAsLCyzA4qi0N3djdLSUhw6dAgGgwEbNmxAYWEh4uPjLbq4kiSJ6upq+Pr6Yt68eTZYtXNDb/smJCTAYDCgv78fer2eqQz6+Pi4hGg5ceIEXnzxRRw/ftwmFcy6ujpwuVzcfvvteOGFFxgBWFtbix07duDcuXPo6enBmjVr0NjYCB6Ph6VLl+Lll1/G8uXLkZ+fj9/97ndjTNRZWGwMawPDwsIyO+BwOIiNjcXu3btx3333oa+vD2VlZbj33nsxPDyM9evXo7Cw0OQtXJIkUVVVhYCAACQkJNj+BTgZxnr+oqOjmRSSlpYWh6eQmMLJkyfxl7/8BSdOnLDZ9nVaWprRrx85cgTbt2+Hh4cHEhMTkZycjHPnziEhIQGDg4NYsWIFAOCmm27C4cOHWQHI4nBYAcjCwuLScDgcREZG4u6778bdd98NsViMw4cP49FHH4VEIkF+fj4KCwuRmppqVLQYDAZUV1cjKCgI8fHxDngFjkWn003a8+fm5obIyEhERkYyKSQdHR12TyExha+++gp/+tOfcOLECbsNC41GKBRi+fLlzP9jYmIgFArh5uaGmJiYCV9nYXE0rABkYWGZVYSFheG2227DbbfdBplMhqNHj2LPnj0QCoW45pprsGnTJmRkZIDL5WJ4eBhFRUV4/PHHkZub6+il2x2dTodLly6ZNPDB4/EQHh6O8PBwkCQJqVQKoVCIuro6m6aQmMK3336LJ598EsePH4dAIJjx861ZswZ9fX0Tvv7ss8+isLDQ6M9M5vnJeoGyOCusAGRhYZm1BAcHY9euXdi1axcGBgZw7Ngx7Nu3Dy0tLVi1ahW+++47XHfddVi9erWjl2p3aPGXnJxs9nYpPTVMp5AoFAr09/dbPYXEFM6cOYNHH30Ux44dQ2RkpFWe84svvjD7Zybz/IyJiUF3d/eEr7OwOBpWALKwsMwJAgIC8Ktf/Qq/+tWv0NfXh7Vr1yIkJAT//e9/IRKJUFhYiCVLlpidluGKjBZ/ISEhM3ouLpeL4OBgBAcHMykkIpFoxikkpnDhwgU88MADOHr06JhtVkdQUFCAnTt34oEHHkBPTw+ampqwdOlS8Hg8+Pn54ccff8SyZcvw3nvv4d5773XoWllYAHYKmIWFZY4xODiIjRs34s4778T27duhVqvx2WefobS0FJcuXcLll1+OoqIirFixAnz+7LtHtqb4m4rRKSQSiQSenp4IDw83KYXEFMrLy3HHHXfg8OHDdp3aPnToEO69916IxWIEBgYiNzcXn332GYCRLeJ33nkHfD4f+/fvZwY9Lly4wNjArFu3Dq+++iq7DcxiT1gbGBYWlulJSEiAn58feDwe+Hw+Lly4AJlMhm3btqG9vR0JCQn46KOPXDIeTC6Xo6CgALt378bmzZsnfF+r1eKLL75ASUkJzp07h5UrV6KoqAi/+MUvrCJaHI29xJ8xTE0hMYXq6mrceuutKC4uRkpKig1Wy8Iyq2AFIAsLy/QkJCTgwoULYyYpH3nkEQQHB+Oxxx7D888/D7lcjn379jlwlZaxd+9eZGZmYuPGjdM+Vq/X4/Tp0ygpKcF3332HJUuWoKioCKtWrbJItDgaeto3KSnJ7uJvPKNTSDgcDiMGPT09p/3Zuro6/OY3v8GHH36I9PR0O6yWhcXlYQUgCwvL9BgTgCkpKTh9+jQiIyPR29uLVatWoaGhwYGrtC8GgwHfffcdiouL8fXXXyMnJwdFRUVYvXq1SaLF0Tiy8jcdGo0GYrEYIpEIJEkyxtPGUkgaGxtx00034YMPPkB2drYDVsvC4pKwApCFhWV6EhMTERQUBA6Hg9tvvx2//e1vERgYCIVCwTwmKCgIcrnccYt0IARB4MyZMygpKcGpU6eQlpaGwsJCXHPNNfDx8XH08ibgTJW/6dDpdIwYHBwcxIkTJ7B161bk5eWho6MDO3bswLvvvouFCxc6eqksLK4EKwBZWFimp6enB1FRURCJRFi7di1effVVFBQUsALQCCRJ4sKFCyguLsbnn3+OpKQkFBQUYN26dfDz83P08hjxN2/ePIeYI8+EoaEh/Pvf/8bRo0chFApBEASefvpp3HTTTewABQuLebACkIWFxTz27NkDX19fHDhwYE5vAZsCSZKoqKhASUkJPvnkE0RFRaGwsBDr169HYGCg3dfjyuJvNEKhENu2bcN1112Huro6VFdXY/Xq1di8eTNWrFjhEONpFhYXgxWALCwsU6NUKkGSJPz8/KBUKrF27Vo89dRTOHXqFEJCQpghEJlMhr/85S+OXq7TQlEUampqUFJSguPHjyM4OBhFRUVYv369XcTYbBF/fX192LJlC1566SWsWrUKwMik9qlTp1BaWorz58/j/vvvx29+8xvHLpSFxblhBSALC8vUtLa2YtOmTQBGBh927tyJJ554AlKpFFu3bkVnZyfi4uJQXFxsdnrEXIWiKDQ2NqKkpAQff/wxvL29UVRUhI0bN0IgEFh9O3O2iD+RSITNmzdj3759WLNmjdHHGAwGKBQKl36dLCx2gBWALCwsLI6Eoii0traitLQUhw8fhpubGwoKClBYWIjIyMgZi0G9Xo9Lly65vPiTSCTYvHkz/vjHPzJmyiwsLBbDCkAWFhYWZ4GiKHR3d6OkpASHDx+GwWDAhg0bsGnTJsTGxpotBmeL+JPL5bjuuuvwxBNPoKCgwNHLYWGZDbACkIWFhcUZoSgKvb29KCsrw6FDhzA8PIwNGzagsLAQSUlJ04pBWvwlJiYiLCzMTqu2PgMDA9i8eTMefPBBo0ktLCwsFsEKQBYWFhZXQCQS4fDhwygtLYVMJkN+fj4KCgqQmpo6QQyKxWJUVFQgJyfHpcXf0NAQtmzZgrvvvhvbt2939HJYWP6/vfsLqbv+4zj+Op7jLNAYLjTbKSodrqnDLfJPofZHN216jrtIdxrYjivUYHahmHWkFBKZ1FUZLDDQixycY9sYRFKRbCuWbszACSrTpVMzTVdQztTj7yJ+h19kv2ybO3q+z8eVfL4fPW/Foy8+3+/n8w4kBEAA2GhmZmZ06tQptbe3a3x8XHv37lV+fr7i4uL0008/ad++fXK5XLLb7f4u9ab9+uuvKigokNPpVFFRkb/LAQINARAANrKff/5Zp0+fVnt7uwYHB3Xjxg05nU69+uqrG/Y8vLm5ORUWFsrhcOjw4cP+LgcIRARAAAgEs7OzysnJUXp6uoaHh9Xf369nnnlGdrtdjz/++IYJgzdu3NALL7wgu92u0tJSOnwAa2PFN9bG+CsBACsoLi5WRESE4uPjfWMzMzPKysrStm3blJWV9aeWdQ0NDYqJiVFsbKw6Ojr8UfItu379unJzc/XGG2+osbFRbrdb3377rTIyMtTc3KyUlBRVVlbq3LlzWlpa8ne5f+v333/Xiy++qJycHMIf4AesAALYsM6cOaPQ0FAVFRWpt7dXklRVVaXw8HBf15LZ2VkdPXpUfX19cjgc6urq0vj4uDIzMzUwMCCz2ezn72L1/hv+qqqq/vaIlPn5eX3++efyeDzq7u7WE088of379+vJJ59UcHDwHa54ZQsLC3I6nUpNTVVlZSXhD1hb3AIGEHiuXr2q3NxcXwCMjY1dsW9xQ0ODJOn111+XJO3du1e1tbVKTU31W+3/1vnz5zU5ObnqDR8LCwv66quv5PF49PXXXyspKUl2u11PPfWUNm3atMbVrmxxcVEvvfSSdu7cKZfLRfgD1t6KbzLLna4CANbS5OSkoqKiJElRUVH68ccfJUljY2NKSUnxzbNarRobG/NLjTfrf+tfjeDgYO3Zs0d79uzR4uKizp49K7fbrZqaGiUmJsput+vZZ5/VXXfdtUYV/9nS0pJeeeUVbd++nfAH+BnPAAIwhJXudhgpgFgsFj399NP64IMP9N1336mkpETnzp1TRkaGnE6nTp48qd9++23NXn9paUnl5eXaunWramtrb+vP3u12Ky4uTkFBQbpw4YJv/OrVq7r77ruVmJioxMRElZaW+q5dvHhRCQkJiomJUXl5+Yq/H0AgYwUQQECJjIzUxMSE7xZwRESEpD9W/EZHR33zrl27pvvvv99fZfqV2WxWWlqa0tLS5PV61d3dLbfbraNHjyo6Olp2u13Z2dkKCwu7La/n9XpVUVGhzZs3q6Gh4bbvUo6Pj9cnn3yikpKSv1yLjo5WT0/PX8bLysr04YcfKiUlRc8995w+++wz+g7DUFgBBBBQbDabWlpaJEktLS2+5+VsNpuOHz+u+fl5DQ8Pa3BwUElJSf4sdV0ICgpScnKy3nnnHV26dEk1NTXq7+9Xdna2CgsL9fHHH+v69es3/fW9Xq+qq6sVHBysd999d02OqHn00UcVGxu76vkTExP65ZdflJqaKpPJpKKiIp08efK21wWsZ6wAAtiwHA6HOjs7NT09LavVqrq6OlVXV6ugoEDNzc168MEH5Xa7JUlxcXEqKCjQjh07ZLFY1NTUtKF2AN8JQUFB2r17t3bv3q36+nr19vbK4/HIZrPp3nvvVX5+vvbt26ctW7as6ut5vV699dZbmp+f17Fjx/xyPuHw8LB27dqle+65R2+//bbS0tI0NjYmq9Xqm7MRnwcFbhUBEMCG1dbWtuL4l19+ueK4y+WSy+Vay5IChslkUkJCghISElRbW6v+/n55PB49//zzCg0Nlc1mU15eniIiIlZ8nm95eVn19fWanp7WRx99dMvhLzMzUz/88MNfxuvr6/92V3RUVJRGRka0ZcsWXbx4Ufn5+bp8+bLhnwcFJAIgAOAfmEwmbd++XTU1NXK5XBoaGpLH49HBgwe1adMm5eXlKT8/X/fdd59MJpOWl5fV2Nio77//Xq2trbdlpfWLL774158TEhKikJAQSdJjjz2m6OhoDQwMyGq16tq1a755Rn4eFMZFAAQArJrJZFJ0dLRee+01VVVVaWRkRO3t7XI6nfJ6vcrNzdXMzIyGhobU1tYmi8V//2ampqYUHh4us9msoaEhDQ4O6pFHHlF4eLjCwsJ0/vx5JScnq7W1VUeOHPFbnYA/cBA0AOCWLS8va2JiQm1tbWpra9M333xzxw6bPnHihI4cOaKpqSlt3rxZiYmJ6ujoUHt7u958801ZLBaZzWbV1dUpLy9PknThwgUdOnRIc3NzysnJ0XvvvcdtYAQqOoEAAAAYzIoBkGNgAAAADIYACAAAYDAEQAAAAIMhAAKAHxUXFysiIkLx8fG+sdraWm3dutXXw/bTTz/1XWtoaFBMTIxiY2PV0dHhj5IBBAA2gQCAH505c0ahoaEqKipSb2+vpD8CYGhoqCorK/80t6+vTw6HQ11dXRofH1dmZqYGBgboaALg/2ETCACsN+np6QoPD1/V3FOnTunAgQMKCQnRww8/rJiYGHV1da1xhQACEQEQANah999/Xzt37lRxcbFmZ2clSWNjY3rggQd8c+hhC+BmEQABYJ0pKyvTlStX1NPTo6ioKFVUVEgSPWwB3DYEQABYZyIjI2U2mxUUFKSXX37Zd5vXarVqdHTUN48etgBuFgEQANaZiYkJ38cnTpzw7RC22Ww6fvy45ufnNTw8rMHBQSUlJfmrTAAbmP+6dAMA5HA41NnZqenpaVmtVtXV1amzs1M9PT0ymUx66KGHdOzYMUlSXFycCgoKtGPHDlksFjU1NbEDGMBN4RgYAACAwMUxMAAAACAAAgAAGA4BEAAAwGAIgAAAAAZDAAQAADAYAiAAAIDBEAABAAAMhgAIAABgMARAAAAAgyEAAgAAGAwBEAAAwGAIgAAAAAZDAAQAADAYAiAAAIDBEAABAAAMhgAIAABgMARAAAAAgyEAAgAAGAwBEAAAwGAIgAAAAAZDAAQAADAYAiAAAIDBEAABAAAMhgAIAABgMARAAAAAgyEAAgAAGIzlH66b7kgVAAAAuGNYAQQAADAYAiAAAIDBEAABAAAMhgAIAABgMARAAAAAgyEAAgAAGMx/AMAex4DHr1dpAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 5% error on radial distortion" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "param_error = 0.05\n", + "focal_length2 = focal_length#*(1+param_error) # np.random.normal(focal_length, focal_length*param_error)\n", + "principle_point2 = principle_point#*(1+param_error) # np.random.normal(principle_point, principle_point*param_error)\n", + "radial_distortion2 = radial_distortion*(1+param_error) # np.random.normal(radial_distortion, np.abs(radial_distortion)*param_error)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:26.511384732825423 max: 378.01580465147475\n", + "image 1 reprojection errors: average:24.263343179091372 max: 568.7827890898637\n", + "image 2 reprojection errors: average:24.92150383778915 max: 721.4168575965579\n", + "image 3 reprojection errors: average:23.925002124319143 max: 489.6881011422849\n", + "image 4 reprojection errors: average:27.368396161178776 max: 517.734072939231\n", + "image 5 reprojection errors: average:24.735638947862267 max: 684.4504984363251\n", + "image 6 reprojection errors: average:26.946181481137916 max: 542.0411179302149\n", + "image 7 reprojection errors: average:25.43422923307925 max: 712.6878967480803\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.8969e+06 2.71e+07 \n", + " 1 2 2.0056e+05 5.70e+06 6.35e+01 1.14e+06 \n", + " 2 3 1.7229e+05 2.83e+04 1.45e+00 1.23e+04 \n", + " 3 4 1.7208e+05 2.08e+02 1.16e+00 1.25e+04 \n", + " 4 5 1.7202e+05 5.90e+01 1.98e-01 2.39e+03 \n", + " 5 6 1.7200e+05 1.44e+01 9.40e-02 1.32e+03 \n", + " 6 7 1.7200e+05 6.66e+00 3.38e-02 7.72e+02 \n", + " 7 8 1.7200e+05 2.80e+00 1.93e-02 2.99e+02 \n", + " 8 9 1.7199e+05 2.05e+00 1.43e-02 4.28e+02 \n", + " 9 10 1.7199e+05 1.59e+00 1.23e-02 1.56e+02 \n", + " 10 11 1.7199e+05 1.30e+00 9.97e-03 3.09e+02 \n", + " 11 12 1.7199e+05 1.20e+00 1.01e-02 1.19e+02 \n", + " 12 13 1.7199e+05 1.18e+00 9.36e-03 2.50e+02 \n", + " 13 14 1.7199e+05 1.15e+00 9.74e-03 1.01e+02 \n", + " 14 15 1.7199e+05 1.13e+00 9.08e-03 2.21e+02 \n", + " 15 16 1.7198e+05 1.11e+00 9.48e-03 1.13e+02 \n", + " 16 17 1.7198e+05 1.09e+00 8.88e-03 2.10e+02 \n", + " 17 18 1.7198e+05 1.07e+00 9.27e-03 1.24e+02 \n", + " 18 19 1.7198e+05 1.04e+00 8.51e-03 1.70e+02 \n", + " 19 20 1.7198e+05 1.03e+00 9.09e-03 1.76e+02 \n", + " 20 21 1.7198e+05 1.02e+00 8.36e-03 1.40e+02 \n", + " 21 22 1.7198e+05 9.88e-01 8.73e-03 2.14e+02 \n", + " 22 23 1.7198e+05 7.70e-01 5.97e-03 1.09e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 23, initial cost 5.8969e+06, final cost 1.7198e+05, first-order optimality 1.09e+02.\n", + "mean reprojection error: 4.800226013227024\n", + "max reprojection error: 55.44595285253283\n", + "mean reconstruction error: 0.4754390724894953\n", + "max reconstruction error: 1.3606933924218323\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:27.925264662688868 max: 678.3540404454986\n", + "image 1 reprojection errors: average:26.23389248362247 max: 838.0683959410035\n", + "image 2 reprojection errors: average:25.998775800214247 max: 570.3406523829487\n", + "image 3 reprojection errors: average:26.46639354621687 max: 429.16719876329057\n", + "image 4 reprojection errors: average:27.67283603578831 max: 689.6058296118798\n", + "image 5 reprojection errors: average:25.26269435436887 max: 341.78831788372844\n", + "image 6 reprojection errors: average:24.310955909280935 max: 676.3145329346803\n", + "image 7 reprojection errors: average:24.36130665409135 max: 257.84555840091025\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 6.0911e+06 3.18e+07 \n", + " 1 2 2.3656e+05 5.85e+06 6.39e+01 1.58e+06 \n", + " 2 3 2.0126e+05 3.53e+04 1.65e+00 2.17e+04 \n", + " 3 4 2.0098e+05 2.80e+02 1.35e+00 2.01e+04 \n", + " 4 5 2.0091e+05 7.45e+01 1.94e-01 2.75e+03 \n", + " 5 6 2.0089e+05 1.68e+01 9.69e-02 2.15e+03 \n", + " 6 7 2.0088e+05 8.17e+00 3.49e-02 6.89e+02 \n", + " 7 8 2.0088e+05 3.68e+00 2.40e-02 5.91e+02 \n", + " 8 9 2.0088e+05 2.87e+00 1.66e-02 3.98e+02 \n", + " 9 10 2.0087e+05 2.80e+00 2.07e-02 4.07e+02 \n", + " 10 11 2.0087e+05 2.24e+00 1.27e-02 2.97e+02 \n", + " 11 12 2.0087e+05 2.04e+00 1.68e-02 3.24e+02 \n", + " 12 13 2.0087e+05 1.93e+00 1.13e-02 3.02e+02 \n", + " 13 14 2.0086e+05 1.78e+00 1.50e-02 2.52e+02 \n", + " 14 15 2.0086e+05 1.61e+00 9.72e-03 2.87e+02 \n", + " 15 16 2.0086e+05 1.39e+00 1.22e-02 1.78e+02 \n", + " 16 17 2.0086e+05 1.38e+00 8.99e-03 2.81e+02 \n", + " 17 18 2.0086e+05 1.38e+00 1.22e-02 1.45e+02 \n", + " 18 19 2.0086e+05 1.36e+00 8.88e-03 2.76e+02 \n", + " 19 20 2.0086e+05 1.34e+00 1.20e-02 1.42e+02 \n", + " 20 21 2.0085e+05 1.32e+00 8.78e-03 2.50e+02 \n", + " 21 22 2.0085e+05 1.29e+00 1.17e-02 1.37e+02 \n", + " 22 23 2.0085e+05 1.27e+00 8.63e-03 1.91e+02 \n", + " 23 24 2.0085e+05 1.15e+00 1.05e-02 1.25e+02 \n", + " 24 25 2.0085e+05 1.13e+00 7.89e-03 2.06e+02 \n", + " 25 26 2.0085e+05 1.04e+00 9.23e-03 1.34e+02 \n", + " 26 27 2.0085e+05 9.29e-01 6.17e-03 2.05e+02 \n", + " 27 28 2.0085e+05 4.19e-01 3.17e-03 8.47e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 28, initial cost 6.0911e+06, final cost 2.0085e+05, first-order optimality 8.47e+01.\n", + "mean reprojection error: 5.533969091338343\n", + "max reprojection error: 56.76504821623486\n", + "mean reconstruction error: 0.5012124540647189\n", + "max reconstruction error: 1.4768370623532858\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:25.957686131048664 max: 509.8624159728717\n", + "image 1 reprojection errors: average:26.13152197546778 max: 875.8377166532729\n", + "image 2 reprojection errors: average:27.747127478002593 max: 721.6196060311289\n", + "image 3 reprojection errors: average:27.6304694065223 max: 498.94241771072757\n", + "image 4 reprojection errors: average:27.536105391806007 max: 433.7621374465237\n", + "image 5 reprojection errors: average:27.102086214625523 max: 713.5792156300997\n", + "image 6 reprojection errors: average:25.380651245323858 max: 305.66274607625354\n", + "image 7 reprojection errors: average:25.929733103146873 max: 398.61967494617915\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 6.4124e+06 2.42e+07 \n", + " 1 2 2.9509e+05 6.12e+06 6.57e+01 1.52e+06 \n", + " 2 3 2.5873e+05 3.64e+04 1.63e+00 2.88e+04 \n", + " 3 4 2.5848e+05 2.48e+02 1.09e+00 2.70e+04 \n", + " 4 5 2.5841e+05 7.82e+01 1.82e-01 5.20e+03 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 5 6 2.5839e+05 1.88e+01 9.56e-02 3.57e+03 \n", + " 6 7 2.5838e+05 1.10e+01 4.19e-02 1.54e+03 \n", + " 7 8 2.5837e+05 5.70e+00 3.12e-02 1.03e+03 \n", + " 8 9 2.5837e+05 3.96e+00 1.81e-02 7.32e+02 \n", + " 9 10 2.5836e+05 3.78e+00 2.45e-02 6.17e+02 \n", + " 10 11 2.5836e+05 3.52e+00 1.64e-02 6.07e+02 \n", + " 11 12 2.5836e+05 3.59e+00 2.45e-02 4.56e+02 \n", + " 12 13 2.5835e+05 2.93e+00 1.29e-02 4.64e+02 \n", + " 13 14 2.5835e+05 2.96e+00 2.24e-02 3.68e+02 \n", + " 14 15 2.5835e+05 3.08e+00 1.39e-02 4.78e+02 \n", + " 15 16 2.5834e+05 2.43e+00 1.77e-02 2.46e+02 \n", + " 16 17 2.5834e+05 2.31e+00 1.18e-02 3.53e+02 \n", + " 17 18 2.5834e+05 2.29e+00 1.72e-02 2.41e+02 \n", + " 18 19 2.5834e+05 2.18e+00 1.12e-02 3.63e+02 \n", + " 19 20 2.5834e+05 1.84e+00 1.40e-02 2.11e+02 \n", + " 20 21 2.5833e+05 1.82e+00 1.02e-02 2.25e+02 \n", + " 21 22 2.5833e+05 1.84e+00 1.41e-02 2.11e+02 \n", + " 22 23 2.5833e+05 1.83e+00 1.02e-02 2.17e+02 \n", + " 23 24 2.5833e+05 1.80e+00 1.39e-02 2.06e+02 \n", + " 24 25 2.5833e+05 1.79e+00 1.01e-02 1.92e+02 \n", + " 25 26 2.5832e+05 1.74e+00 1.35e-02 1.97e+02 \n", + " 26 27 2.5832e+05 1.72e+00 9.95e-03 2.06e+02 \n", + " 27 28 2.5832e+05 1.69e+00 1.32e-02 1.88e+02 \n", + " 28 29 2.5832e+05 1.67e+00 9.77e-03 2.30e+02 \n", + " 29 30 2.5832e+05 1.64e+00 1.29e-02 1.86e+02 \n", + " 30 31 2.5832e+05 1.62e+00 9.55e-03 2.52e+02 \n", + " 31 32 2.5832e+05 1.30e+00 9.88e-03 1.71e+02 \n", + " 32 33 2.5831e+05 1.52e+00 9.95e-03 3.09e+02 \n", + " 33 34 2.5831e+05 1.03e+00 6.46e-03 1.54e+02 \n", + " 34 35 2.5831e+05 5.58e-01 3.58e-03 1.23e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 35, initial cost 6.4124e+06, final cost 2.5831e+05, first-order optimality 1.23e+02.\n", + "mean reprojection error: 6.639130322019802\n", + "max reprojection error: 62.02708302809169\n", + "mean reconstruction error: 0.5507963374722109\n", + "max reconstruction error: 1.7079757232455706\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:29.567308697739104 max: 630.1146481184453\n", + "image 1 reprojection errors: average:28.39738999546637 max: 530.7604292314593\n", + "image 2 reprojection errors: average:27.64800036643929 max: 768.0366764977256\n", + "image 3 reprojection errors: average:28.227287392944444 max: 754.6057499114276\n", + "image 4 reprojection errors: average:29.993284454160637 max: 1001.4046647419614\n", + "image 5 reprojection errors: average:27.91333402536985 max: 452.1232613602955\n", + "image 6 reprojection errors: average:28.21828273324991 max: 913.9431331919964\n", + "image 7 reprojection errors: average:29.34520299409795 max: 631.7329673713564\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 7.6234e+06 4.06e+07 \n", + " 1 2 5.8605e+05 7.04e+06 6.65e+01 2.77e+06 \n", + " 2 3 5.2613e+05 5.99e+04 2.00e+00 6.14e+04 \n", + " 3 4 5.2496e+05 1.18e+03 3.49e+00 2.98e+04 \n", + " 4 5 5.2475e+05 2.04e+02 2.97e-01 3.56e+03 \n", + " 5 6 5.2474e+05 1.64e+01 5.37e-02 7.72e+02 \n", + " 6 7 5.2473e+05 6.45e+00 2.28e-02 5.13e+02 \n", + " 7 8 5.2473e+05 3.46e+00 1.57e-02 2.66e+02 \n", + " 8 9 5.2472e+05 3.31e+00 1.64e-02 2.17e+02 \n", + " 9 10 5.2472e+05 3.20e+00 1.51e-02 2.25e+02 \n", + " 10 11 5.2472e+05 3.09e+00 1.59e-02 2.60e+02 \n", + " 11 12 5.2471e+05 2.95e+00 1.44e-02 2.38e+02 \n", + " 12 13 5.2471e+05 1.92e+00 9.45e-03 2.24e+02 \n", + " 13 14 5.2471e+05 1.09e+00 5.10e-03 1.97e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 14, initial cost 7.6234e+06, final cost 5.2471e+05, first-order optimality 1.97e+02.\n", + "mean reprojection error: 10.15880270245845\n", + "max reprojection error: 70.21930850062901\n", + "mean reconstruction error: 0.7130589979088843\n", + "max reconstruction error: 2.953417088808253\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 62, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length2, principle_point2, radial_distortion2) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.2" + }, + "pycharm": { + "stem_cell": { + "cell_type": "raw", + "metadata": { + "collapsed": false + }, + "source": [] + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/WCTE_RealPositions.ipynb b/WCTE_RealPositions.ipynb new file mode 100644 index 0000000..b108940 --- /dev/null +++ b/WCTE_RealPositions.ipynb @@ -0,0 +1,4062 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "import numpy as np\n", + "from scipy import linalg\n", + "from scipy.spatial.transform import Rotation as R\n", + "from mpl_toolkits.mplot3d import Axes3D\n", + "import matplotlib.pyplot as plt\n", + "import matplotlib.collections\n", + "import matplotlib.patches\n", + "import pg_fitter_tools as fit\n", + "import sk_geo_tools as geo\n", + "import cv2\n", + "from collections import Counter" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from IPython.core.display import display, HTML\n", + "display(HTML(\"\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "#%matplotlib notebook\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "def get_led_positions(led_count, mpmt_locations):\n", + " led_ring_radius = 24.\n", + " led_positions = {}\n", + " for k, v in mpmt_locations.items():\n", + " for i in range(led_count):\n", + " if abs(v[1]) > 100:\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count),0,np.cos(i*2*np.pi/led_count)])\n", + " else:\n", + " phi = np.arctan2(v[2], v[0])\n", + " led_positions[k+'-'+str(i)] = v+led_ring_radius*np.array([np.sin(i*2*np.pi/led_count)*np.sin(phi), np.cos(i*2*np.pi/led_count), -np.sin(i*2*np.pi/led_count)*np.cos(phi)])\n", + " return led_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def get_image_feature_locations(feature_positions, camera_matrix, distortion, camera_rotations, camera_translations, image_size):\n", + " image_feature_locations = {\n", + " i : {list(feature_positions.keys())[f]:v for f, v in enumerate(cv2.projectPoints(np.array(list(feature_positions.values())), r, t, camera_matrix, distortion)[0].reshape((-1,2)))\n", + " if v[0] > 0 and v[0] < image_size[0] and v[1] > 0 and v[1] < image_size[1]}\n", + " for i, (r, t) in enumerate(zip(camera_rotations, camera_translations))}\n", + " feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + " print(\"Feature in image counts:\", Counter(feature_counts.values()))\n", + " return image_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "def get_smeared_feature_locations(image_feature_locations, pixel_error, image_size):\n", + " smeared_feature_locations = {}\n", + " for k, i in image_feature_locations.items():\n", + " smeared_feature_locations[k] = {}\n", + " for j, f in i.items():\n", + " smeared = np.random.normal(f, pixel_error)\n", + " if(smeared[0] > 0 and smeared[0] < image_size[0] and smeared[1] > 0 and smeared[1] < image_size[1]):\n", + " smeared_feature_locations[k][j] = smeared\n", + " smeared_feature_counts = Counter([f for i in smeared_feature_locations.values() for f in i.keys()])\n", + " print(\"Smeared feature in image counts:\", Counter(smeared_feature_counts.values()))\n", + " return smeared_feature_locations" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "def setup_led_simulation(feature_positions, image_feature_locations, focal_length, principle_point, radial_distortion, seed_error=1):\n", + " seed_feature_positions = {}\n", + " for i, f in feature_positions.items():\n", + " seed_feature_positions[i] = np.random.normal(f, seed_error)\n", + " fitter = fit.PhotogrammetryFitter(image_feature_locations, seed_feature_positions, focal_length, principle_point, radial_distortion)\n", + " return fitter" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_images(image_feature_locations, image_size):\n", + " for i in image_feature_locations.values():\n", + " fig, ax = plt.subplots(figsize=(12,9))\n", + " coords = np.rint(np.stack(list(i.values())))\n", + " ax.scatter(coords[:,0], -coords[:,1], marker='s', s=0.2)\n", + " ax.set_xlim((0, image_size[0]))\n", + " ax.set_ylim((-image_size[1], 0))\n", + " ax.axes.xaxis.set_visible(False)\n", + " ax.axes.yaxis.set_visible(False)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "def run_led_fit(fitter, led_positions):\n", + " reco_cam_rotations, reco_cam_translations, reprojected_points = fitter.estimate_camera_poses()\n", + " reco_cam_rotations, reco_cam_translations, reco_locations = fitter.bundle_adjustment(reco_cam_rotations, reco_cam_translations)\n", + " \n", + " reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_locations)\n", + " print(\"mean reconstruction error:\", linalg.norm(reco_errors, axis=1).mean())\n", + " print(\"max reconstruction error:\", linalg.norm(reco_errors, axis=1).max())\n", + "\n", + " reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(reco_cam_rotations, reco_cam_translations)\n", + " cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + " cam_positions_translated = reco_cam_positions - translation\n", + " cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + " reco_led_positions = reco_positions_dict(reco_transformed, fitter.feature_index)\n", + " position_errors = linalg.norm(reco_errors, axis=1)\n", + "\n", + " return reco_led_positions, position_errors" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "def reco_positions_dict(reco_positions, feature_index):\n", + " return {f: reco_positions[i] for f, i in feature_index.items()}" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_centre_errors(reco_led_positions, mpmt_positions, led_count):\n", + " reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n", + " for k in mpmt_positions.keys()}\n", + " errors = np.array([linalg.norm(reco_mpmt_positions[k] - mpmt_positions[k]) for k in mpmt_positions.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "def get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_coun):\n", + " reco_orientations = {}\n", + " for k in mpmt_orientations.keys():\n", + " c, n = geo.fit_plane(np.array([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)]))\n", + " # flip normal if it is directed away from tank centre\n", + " if np.dot(n,c) > 0:\n", + " n = -n\n", + " reco_orientations[k] = n\n", + " errors = np.array([np.degrees(np.arccos(np.dot(reco_orientations[k], mpmt_orientations[k]))) for k in mpmt_orientations.keys()])\n", + " return errors" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "def make_fig(title=None, xlabel=None, ylabel=None, figsize=(8,6)):\n", + " fig, ax = plt.subplots(figsize=figsize)\n", + " ax.set_title(title)\n", + " ax.set_xlabel(xlabel)\n", + " ax.set_ylabel(ylabel)\n", + " fig.tight_layout()\n", + " return fig, ax" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_geometry(led_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter([l[0] for l in led_positions.values()], [l[2] for l in led_positions.values()], [l[1] for l in led_positions.values()], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_reconstruction(reco_positions, cam_positions):\n", + " fig = plt.figure(figsize=(12,9))\n", + " ax = fig.add_subplot(111, projection='3d')\n", + " ax.scatter(reco_positions[:,0], reco_positions[:,2], reco_positions[:,1], marker='*', label=\"LED\", s=1)\n", + " ax.scatter(cam_positions[:,0], cam_positions[:,2], cam_positions[:,1], marker='o', label=\"Camera\", s=60)\n", + " plt.legend(loc=0)\n", + " fig.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "pmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_PMT_locations.txt\", delimiter=\" \")\n", + "#mpmt_locations = {k: v for k, v in pmt_locations.items() if int(k)%19==0}\n", + "mpmt_locations = fit.read_3d_feature_locations(\"parameters/WCTE_16cShort_centrePMT_locations.txt\", delimiter=\" \")\n", + "mpmt_orientations = {k: np.array((0,-1,0)) if v[1]>100\n", + " else np.array((0,1,0)) if v[1]<-100\n", + " else np.array((-v[0],0,-v[2]))/np.sqrt(v[0]**2+v[2]**2)\n", + " for k, v in mpmt_locations.items()}\n", + "led_count = 12\n", + "led_positions = get_led_positions(led_count, mpmt_locations)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'19': array([160.01661746, 26.7375 , 31.8292842 ]),\n", + " '38': array([135.65553801, 26.7375 , 90.64213261]),\n", + " '57': array([ 90.64213261, 26.7375 , 135.65553801]),\n", + " '76': array([ 31.8292842 , 26.7375 , 160.01661746]),\n", + " '95': array([-31.8292842 , 26.7375 , 160.01661746]),\n", + " '114': array([-90.64213261, 26.7375 , 135.65553801]),\n", + " '133': array([-135.65553801, 26.7375 , 90.64213261]),\n", + " '152': array([-160.01661746, 26.7375 , 31.8292842 ]),\n", + " '171': array([-160.01661746, 26.7375 , -31.8292842 ]),\n", + " '190': array([-135.65553801, 26.7375 , 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0]),\n", + " '1197': array([0, 1, 0]),\n", + " '1216': array([0, 1, 0]),\n", + " '1235': array([0, 1, 0]),\n", + " '1254': array([0, 1, 0]),\n", + " '1273': array([0, 1, 0]),\n", + " '1292': array([0, 1, 0]),\n", + " '1311': array([0, 1, 0]),\n", + " '1330': array([-0.98078528, 0. , -0.19509032]),\n", + " '1349': array([-0.83146961, 0. , -0.55557023]),\n", + " '1368': array([-0.55557023, 0. , -0.83146961]),\n", + " '1387': array([-0.19509032, 0. , -0.98078528]),\n", + " '1406': array([ 0.19509032, 0. , -0.98078528]),\n", + " '1425': array([ 0.55557023, 0. , -0.83146961]),\n", + " '1444': array([ 0.83146961, 0. , -0.55557023]),\n", + " '1463': array([ 0.98078528, 0. , -0.19509032]),\n", + " '1482': array([0.98078528, 0. , 0.19509032]),\n", + " '1501': array([0.83146961, 0. , 0.55557023]),\n", + " '1520': array([0.55557023, 0. , 0.83146961]),\n", + " '1539': array([0.19509032, 0. , 0.98078528]),\n", + " '1558': array([-0.19509032, 0. , 0.98078528]),\n", + " '1577': array([-0.55557023, 0. , 0.83146961]),\n", + " '1596': array([-0.83146961, 0. , 0.55557023]),\n", + " '1615': array([-0.98078528, 0. , 0.19509032]),\n", + " '1634': array([ 0, -1, 0]),\n", + " '1653': array([ 0, -1, 0]),\n", + " '1672': array([ 0, -1, 0]),\n", + " '1691': array([ 0, -1, 0]),\n", + " '1710': array([ 0, -1, 0]),\n", + " '1729': array([ 0, -1, 0]),\n", + " '1748': array([ 0, -1, 0]),\n", + " '1767': array([ 0, -1, 0]),\n", + " '1786': array([ 0, -1, 0]),\n", + " '1805': array([ 0, -1, 0]),\n", + " '1824': array([ 0, -1, 0]),\n", + " '1843': array([ 0, -1, 0]),\n", + " '1862': array([ 0, -1, 0]),\n", + " '1881': array([ 0, -1, 0]),\n", + " '1900': array([ 0, -1, 0]),\n", + " '1919': array([ 0, -1, 0]),\n", + " '1938': array([ 0, -1, 0]),\n", + " '1957': array([ 0, -1, 0]),\n", + " '1976': array([ 0, -1, 0]),\n", + " '1995': array([ 0, -1, 0]),\n", + " '2014': array([ 0, -1, 0])}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mpmt_orientations" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [], + "source": [ + "pixel_errors = [1.0, 3.0, 5.0, 10.0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony A6000" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "focal_length = np.array([2925.84685880484, 2930.0351899542])\n", + "principle_point = np.array([3000, 2000])\n", + "radial_distortion = np.array([-0.251288719187471, 0.0622370807856553])#[-0.28009, 0.11246, -0.02736])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([6000, 4000])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "all_cam_positions = np.array([[97.47275687, 14.93703117, 99.94996814],\n", + " [29.15674544, 141.7448364, 147.4176074],\n", + " [44.82084089, 266.7725, -44.9380583],\n", + " [29.29952975, 16.2275, -28.97664714],\n", + " [-97.47275687 , 14.93703117, -99.94996814],\n", + " [99.94996814, 272.2629688, -97.47275687],\n", + " [99.94996814, 14.93703117, -97.47275687],\n", + " [-99.94996814, 14.93703117, 97.47275687],\n", + " [-29.15674544, 141.7448364, -147.4176074],\n", + " [-147.4176074, 141.7448364, 29.15674544],\n", + " [-99.94996814, 272.2629688, 97.47275687],\n", + " [97.47275687, 272.2629688, 99.94996814],\n", + " [147.4176074, 141.7448364, -29.15674544],\n", + " [-97.47275687, 272.2629688, -99.94996814]])\n", + "corner_cam_positions = all_cam_positions[(0,4,5,6,7,10,11,13),:]\n", + "cam_offsets = np.mean(corner_cam_positions, axis=0)\n", + "all_cam_positions = all_cam_positions - cam_offsets\n", + "corner_cam_positions = corner_cam_positions - cam_offsets" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "corner_cam_directions = [[-1, +1.9, -1],\n", + " [+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [-1, +1.9, +1],\n", + " [+1, +1.9, -1],\n", + " [+1, -1.9, -1],\n", + " [-1, -1.9, -1],\n", + " [+1, -1.9, +1]]" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "# camera_radial_position = 163.0\n", + "# camera_halfz_position = 168.0\n", + "# camera_positions = np.array([\n", + "# [ camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + "# [ camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + "# [-camera_radial_position/np.sqrt(2), camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + "# [-camera_radial_position/np.sqrt(2), camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + "# [ camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + "# [ camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)],\n", + "# [-camera_radial_position/np.sqrt(2), -camera_halfz_position, camera_radial_position/np.sqrt(2)],\n", + "# [-camera_radial_position/np.sqrt(2), -camera_halfz_position, -camera_radial_position/np.sqrt(2)]])\n", + "# camera_directions = [[-1, -1.9, -1],\n", + "# [-1, -1.9, 1],\n", + "# [ 1, -1.9, -1],\n", + "# [ 1, -1.9, 1],\n", + "# [-1, 1.9, -1],\n", + "# [-1, 1.9, 1],\n", + "# [ 1, 1.9, -1],\n", + "# [ 1, 1.9, 1]]\n", + "camera_positions = corner_cam_positions\n", + "camera_directions = corner_cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({4: 664, 6: 224, 5: 144, 8: 136, 3: 80, 7: 24})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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ROJThKzbAMtpNSjJm/mWPe/FsBquKJBc2KUMZNqEDLKPdpKTH3kbKxg9VBFgaKyhDQw2wjHYTYigZP1SxB0umIeArPe556PGa+aXX59/rdQPLlYwfqgiwIDqdflk9burt8Zr5pdfn3+t1R6Gvg3mqWCII0dknWFaPy4h7vGZ+6fX593rdUejrYJ4qsghCdLL2ANA6fR386VkWQQEWAADAQg4apirWedMqdftve90T9x6APQiwCMlGZlqlbv9tr3vi3v9N0EnL1G9KkeSCkGxkplXq9t/2uifu/d8kLaBl6jel2IMFAJ2StICWqd9sTZILAACATCS5AAAA2JgACwAAIBMBFkAjZMxqk+cKUBcBFpBSMohrgTTkbfJcAeoiwAJSSrEHcYK/ecZxTMMwSEPeGM+1Ddox6IcAC0gpxR7ERQ7+IjmdTunHjx+h0hHXNqiMWN6IzzWiiM/ud9ox6IeDhoGU0q9BXEQOiK1XbQd91lZefon+7LRj0A8BFhBe5OCPr9U2qKytvPwS/dlpx6AfDhoGAABYyEHDDYu+7rwnngVfiVQ/IpWlR9Huf7TyEIv6AQtN0zT75+3tbSKeYRimlNI0DEPponTPs+ArkerHK2W53W7TMAzT7XbbsGT1eeW+RKoL0xSvPMSifsShHY4lpfQ+fRIz2YPVgOjrznviWfCVSPXjlbJETyJQyiv3JVJdSCleeYhF/YhDO1wHe7Co0v1+T5fLJY3jKHUx7MR79zn3BdiL9iaW0HuwSqzttZ64bs4Tgf05j+lz7guU0eNYrsX2ptRz3PLfDRFglRgsG6CXk6NCv3Iobo8NMQC0yliuDaWe45b/bog9WCXW9lpPXE6O9cOvnCdi3TIAxPTK0rccYzlL7sorNSbf8t+1B4vdlWrMNKIAENP5fE7X6zUNw7DrR9BS/y5tCL0Hq3aWni1Tav1wi+uWv7OmbqrXAK/R9i73ytL/mv/dWvVaP5cyg5WBrx9EtaZuqtcAr9H20ir180/PZrBC7MGqnf1cRLWmbkaq15Z3AnNEaStaaXvhI/VzHjNYwGpbD2p8MQPm2LKtiBK8AXHYgwVBtLh+eesUq9bIA3Ns2Va0mBK8xf4IIhBgUVxvDXyLnfTWAVAtCUp6q8v0oaZ6vWVb0eKHnhb7IwhhmqbZP29vbxPtuN1u0zAM0+12K1qOYRimlNI0DEPRcuzl1fu+5nlFedat660u0wf1eh8l2uke+4Yer5ntpJTep09iJgFWx6J0mhq7edY8ryjPunXqMi1Sr/extp32nOaJ0h96Xm1oJsBSIfNZey89i32ZwQJo19p2OkrgEF2u/tDzYpoaCrBUyDhafBYCEQBqpP/alxnHeErc02cBVnXnYMm/H0eLz+Kx4TelJB04ANV4JPiIqMUU92vHQJGfV60ijeGcgwW/abETAICSnGXIHkqM4Z6dgyXAAqolIAaIT1tNqxw0DBSx5Rk6znCB/mzZptR05ldNajnLEHIRYAGb2jII2uPgTwMuWGbrd2bLNsVHGyCH6pJcAHXZMhnKHpuEI22ahRps/c5s2aa0mLwJ2J8ZrAB8IadltS8N2WOWDFqy9TuzZZtSe3sF3zHm3IcAKwBLEmAfr3QsBlywzCvvjEEf7MOYcx+WCAZgSQLsw3I/iMm7Cfsw5tyHACsAh83BPnQsEJN3E/ZhzLkPSwShYpbVLGO5H8Tk3VxG2w+xmcGCillWA9AfbT/EJsCCillWA9AfbT/EdpimafYfPh6P0/v7+4bFAQAAiO9wOPycpun48ff2YAEAAGQiwGJTNuICADUxdmEtARabcqAdxPHqoMFgYx73F9pg7MJaAiw2NY5jGobBRtzOGUDG8OqgwWBjHve3btopHoxdWEsWQTZV+4F29/s9XS6XNI6j81lWkFI4hlczj8lYNo/7WzftVD619521j10oTxZB+ML5fE7X6zUNw6CxXaH2zhZon3YqH30nvXiWRdAMFnzBl+U8fA0EotNO5aPvpHf2YMEXHh2ur5lEFHHPSMQyrRHxeiKWCX6n76R3ZrAAKhVxz0jEMq0R8XoilgmAXwRYAJWKuAwnYpnWiHg9EcsEwC+SXAAAACz0LMmFPVgAAACZCLAAAAAyCRdgyY4En/NuAAC8Zs9xVLgA65Ed6XK5lC4KhOLdAOAZH+Hga3uOo8JlEZQdCT7n3QDgGen74Wt7jqPCzWA5nO45X6f65t3oUyvvffTriF6+JVq6FuYbxzENw+AjXKe899/bcxwVbgaL53ydgv608t5Hv47o5VuipWthvsfgkT5572MRYFXEEjHoTyvvffTriF6+JVq6FmAe730sDhoGsrrf7+lyuaRxHC1nBKqmPQO+8uygYTNYQFaWKQCt0J4BrxBgAVlZpgC0QnsGvMISQQAAgIWeLREMl6YdAACgVgIs+ITzJADgdfpReibAYhO1N6yPjc2Xy6V0UQCgOi30o7WPZShHkgs2UXvmJRubAeB1LfSjtY9lKMcMFpsYxzENw1Btw3o6ndKPHz+ce0IxrX05jX490cu3VGvXQ31a6EdrH8tQjiyCAAGdz+d0vV7TMAxNfDmNfj3Ry7dUa9cDEJEsgtAIX6b70NqX0+jXE718S7V2PXxOfwAxmcGCyvgyDUBK+gMozQwWNKLkl2lfSwHiMFMJMZnBAmbztRTgT/f7PV0ulzSOY9UJHYDlns1gSdMOzNZC2l2AnKTyBj4SYAGzPdLuAvAPH56AjwRYAAAv8uEJ+EiSCwBWaz0BSuvXB0A+AixYaMlAy6CM3KLWqcc+lMvlku3vfPVat7hHW1xfLlHrBPVSp2ClaZpm/7y9vU3Qu2EYppTSNAxD1j+by+12m4ZhmG63227/Zg9eua9bPIsSdWqOSNe6xT2K/F7lvt5XrzXyPapVqXs6t0555vQupfQ+fRIzCbBgoSUdSonOZ8lgS+c43yuD2N4G+rkZ6M+T+3ojBbYtWvK8St3TuWX0zOmdAAs6UUPnXaMoM1iwNYHttlr6CBa9fLC1ZwGWg4ahYw7IBNiXdhfa8eygYUku6FrvG3kf6YV18nzU+7uRg3vIZ7S73g3aJ8CqmAZqvciZwehP7nd6zd+X+92I3l5Fyjy4RVmi33/6ou9dzzsd3GfrBp/92IMVi/0z61k/3p/Izzz3O73m74uSOGEvkRKSbFGWqPc/8vvIdjz39aK+071Jkly0p8YGqsYy05bInVLu9yPS+xapLJ+JVL4tyhLp+n4X+X2kD1Hfje/UWu7WPAuwJLlgV+fzOV2v1zQMQ/rx40fp4hRns/P+3HOIw/tYhvv+i3EJazxLcvGvEoVZQ6NQt3Ec//hv7x7r0FNKGvadPDaYA+V5H8vQ9/xiXNKOSDFCdQGWRqFukTvTEi+mhh2AvZXoeyINfn8XeVzCMpFihOoCLANStlLixdSwA7C3En1PpMEvbYoUI1QXYBmQspVILyYAtEQfy9YixQiSXAAAACz0LMmFg4YBAAAyEWDRHKebA0Ab9OnUSIBFcx4baS+XS+misLMWO+Karqmmsi5Vy7XVUk6YS59OlT47ffjZz9vb277HI9O9V04qd7p5v4ZhmFJK0zAMpYuSTU3XVFNZl6rl2mop5xLa9L4ZBxBZSul9+iRmqi6LIH15Ja1rpCwy7KvFLFU1XVNNZV2qlmurpZxLSO/dt1f6dHWG0mQRJLSoBxMCsA/9AEupM+zlWRZBARaf0jgBALzGOKoPzwIsSwT5lOl1AIDXGEf1TRbBTizNLDWOYxqGoal1/AAAe3hlHCULaDsEWJ1Ymub0sanUtPZ+NKwAbEH/sr9XxlFS0rfDEsFOtJhZqjWWEwCwBf1LHYzV2iHA6oTU5fFpWAHYgv6lDsZq7ZBFEAAAYKFnWQTtwQIAAMhEgEVXbPSlJjXV15rK+qoerhGA9QRYldHBryNDT5tafS9qqq81lfVVNV1jq+9Eq9fVO891PfcwFkkuKiMT0Do2+rap1feipvpaU1lfVdM1tvpOtHpdvfNc13MPg5mmafbP29vbRFm3220ahmG63W6li/KHqOWiD+of/KnVd6LV6+pdLc81cjkjl61lKaX36ZOYSRZBsjifz+l6vaZhGHw5AQCaY6zDR8+yCFoiSBY1LZ0BAFjKWIe5zGABAAAs5BwsAACAjQmwAAAAMukywGrtrIDWrgcAgL+1OOZr8Zq6THLR2lkBrV0PAAB/a3HM1+I1dRlgtZYFprXrAQDgby2O+Vq8pi6XCJ5Op/Tjx490Op1KFyWL1q4Hcoi+5CB6+XKq5VprKWcu0a83evmghBbHfC1eU5cBFkTTykDi1evY4vofSw4ul0u2vzOnrcq35l5uVQ+jP4uHLcvpuSyXu3yR2qcSWrkOqMI0TbN/3t7eJiC/YRimlNI0DEPpoqzy6nVscf23220ahmG63W7Z/s6ctirfmnu5VT2M/iwetiyn57Jc7vJFap9KaOU6IJKU0vv0ScwkwIIAog905nr1Olq5/gjW3EvPYTueS3m9t0+tXAdE8izAOvzz/+Y5Ho/T+/t75jk0AACAuhwOh5/TNB0//t4eLAAAgEwEWAHYeAoAwNaMOfchwAogeiYnaF3EDG94LlH1no0PambMuZPPNmY9+5HkYhs2nhJN5Dq5RdlkeHtdb5n3psmziZaNL+rziFou+qZe5pVkEaSkCC90hDLUInI632gp3aMNYvcWNZCJGvjtKVpA09u7ErVcEemfqZUAa0Mahu9F6GgilKEWket05LLlVMt11lLOnGq55lrKuVbU64xaroii9M+e2Tzu0y/PAixp2jM4n8/per2mYRjSjx8/ShcnpPv9ni6XSxrHMZ1Op27LAAD8KUr/bDw3j/v0y7M07f8qUZjWjOP4x3/52+l0Kv4SRigDAPCnKP2z8dw87tP3zGABAAAs5KBhAACAjQmwAAAAMhFgAQAAZLJ7gOUkd3rnHQAgAv0R/CnXO7F7FsHL5ZKu12tKKYXIGAN78w4AEIH+CP6U653YPcCS2pHeeQcAiEB/BH/K9U7svkTwcdaBg17pVcl3oNXlIDVdV01lXavWa6213K+o7VprK+8cJa/JmAz+lOudcNAwdKTV5SA1XVdNZV2r1muttdyvqO1aayvvHC1eE/ROgFWx+/2eLpdLGsfR1ydmaXU5SE3XVVNZ16r1Wmst9ytqu9bayjtHi9fEPowD4zpM0zT7Dx+Px+n9/X3D4rDE+XxO1+s1DcPgqxcAQEeMA8s7HA4/p2k6fvy9GayK+eoFANAn48C4HDRcMZtT82hx0zQARKTPzcc4MC4zWHTPBmMA2Ic+lx4IsOieKXYA2Ic+lx5IcgEAwKdkqoPnniW5sAcLMrK2HICWPJb0XS6X0kWBalgiCBlZWw5ASyzpg+WanMEyi0Ap4zimYRh0RAA0QaY6IqhtbN9kgGU6O77aXpS55dURAdCrmvr2mspKfWP7JpcIms6Or7aldLWVFwD2VlNfWVNZqW9s3+QMllmE+GpbSldbeX/X6le6Gq+rxjKvUfP11lz2V9R4vTWWeY6ar6umvrKmslLh2H6aptk/b29vE1CXYRimlNI0DEPpomRV43XVWOY1ar7emsv+ihqvt8Yyz9HqdUGLUkrv0ycxU5NLBIFfaptWn6vG66qxzGvUfL01l/0VNV5vjWWeo9Xrgp44aBgAAGAhBw0DAABsTIAFAACQiQALAIAq1JxlkX4IsKiahhYA+lHbgbP0SRZBquagQADohyyL1ECARdU0tADQj8eBsxCZAIuqaWgBAIjEHixCs8cKAFjC2IHSBFiEZjNrXjodgFi0y/kZO1CaAIvQxnFMwzCs2mOl8/qlhk7H8wJyit6m1NAu7yXXs8oxdoBVpmma/fP29jZBbYZhmFJK0zAMpYtS3O12m4ZhmG63W+miPLXV81p77Vveuxqey0c1ljm3Gu9B5Hq8Vdmi9wE11qOtRH9W8FFK6X36JGYSYNE8nVddog6ytuz4axxUbF3mHPVg63ffc8v7d0f9uMJ+PCtqI8DqhMYJPhf16/rWf/dWagheaggC9xa5Htd4P2EP3o24ngVYh3/+3zzH43F6f3/Ptz6R7M7nc7per2kYBunLgWrd7/d0uVzSOI7pdDoV+zsASjO2i+twOPycpun48ffOwWqMg3eBFuQ44845eUALjO3qYwYLAABgoWczWNK0s7voKXP5x5rn5BkDtdMGts9zYisCrBm8gHk586MOa56TZwzb0i9tTxvYPs9pG9qnJIvgHDWm4o1MNpw6rHlOWz3j2urO1uWVta1ea++9DIl/2qK8EdtA8vKcttHTuDlJ0/46LyDEUFujvXV5o5479FBz2xk9DX308u2ttvJCy2pu+5d6FmDJIjiDTFQQQ22ZlLYu79q/f+vyPZbfpJSqa0O3Lvvae791v+RdA15l3CyLIAAbqfkcqprLDsA+ZBEkNBsioT2Pr5g1Big1lx34nLEGe7FEkBBqXkoEAMRnrMFezGARwjiOaRiG3dfP+5oFAPsp2e+WGmvQH3uw6Nr5fE7X6zUNw+BrFgBsTL9LS57twbJEkK7JPAUA+9Hv0gMzWAAAAAvJIggAALAxARYAAEAmAiwAAIBMBFgAQBcczQHsQYDVMR0NUaiLwB4eB81eLpfSRaFz+r22CbA6tnVHo/Fgrt4GPS28Gy1cw1q134Pay/8KB80y19bvR2/9Xm+cg9Wxrc+ieDQeKSWHCfKl3s5FaeHdaOEa1qr9HtRe/lecTqdurpV1tn4/euv3eiPA6tjWHY3Gg7l6G/S08G60cA1r1X4Pai8/bGnr96O3fq83DhoGAABYyEHDAAAAGxNgAQAAZCLAYrEeM08BAHxkTMRnJLlgsR4zTwEAfGRMxGcEWCwm8xQAgDERn5NFEAAAYCFZBAEA2JU9SvRIgEUIURrgKOUAgBY89ihdLpfSRdHHsxt7sAghyibRKOUAgBZE2qOkj2cvAixCiNIARykHALTgdDqFCWb08exFkosN3e/3dLlc0jiO6XQ6lS4OAADMYhz7PUkuCoi07hiisRYeKEkbBF8zjn2dJYIbMhUNz1kLDzH0+pVaGwRfM459nRmsDT3WHffUYcFc4zimYRi6a7hb+WreynWs1cJ96PUrda9tEMxlHPs6M1hAEZE2Pu+pla/mrVzHWi3ch16/UvfaBgHbE2AB7KiVwWwr17FWC/dBoAGQlyyCAAAAC8kiCAAAsDEBVgNa2GQNAMDXjPnqYA9WA1rYZA0AwNeM+eogwGpAC5usAQD4mjFfHSS5AAAAWEiSCwAAgI0JsAAAADIRYAEAAGQiwApOOk5yU6cA4tAm92vLZ69elSXACu6RjvNyuWT/u718n2v9vqytUzoEoDaR260t+/kItOvPbfnsW69X4U3TNPvn7e1tYl+3220ahmG63W7Z/+5hGKaU0jQMQ/a/u2at35e1dWrL+9P6vQfKiNxubdnPR6Bdf27LZ996vYoipfQ+fRIzCbA65uX7nPvyNR3C32otNyxVa13XbpXj/tAyARbARvb4QlvbIKW28n6mtmvYo7xmI6hFbe8vdRJgUR2NI7WoaWC713vVwkB8r2vI9UwE+vBLC20Q8T0LsP61954vmOuxQTOllH78+FG4NPDc6XTavI6O4/jHf1+113uVq7wl7XUNuZ7JHuXdo65DDi20QdTr8E/wNc/xeJze3983LA78cr/f0+VySeM4ptPpVLo40ATvVTyeCUCdDofDz2majn/9XoAF9TEgA0BfAGU9C7AsEYQKWT4JgL4AYnLQMFRoHMc0DIO15UB3tj64tqaDcfUFEJMACyr02Ghew5KQGgZDNQ2ooGY53rXHrM3lcslYsv3+/pxq6gugJ5YIApvaeglLjr/fMhvYR453bevscLLPAWuZwQI2tfUSlhx//x7LbMySLZPrfrnv8+1xr3K8a1vP2pgVAlb77HCsZz8OGgZ4TQuHXu55yGyu+1XbYcEltVBHgWVaaLtKSg4ajkd6VehHC8uO9lxKmet+1XZYcEkt1FFgmRbarpA+i7qe/ZjBysvXwhh8vYF5vCvPuTfwPe9JPJ7JOunJDJaDhgsygxXD+XxO1+s1DcPg6w0AbER/S2ueHTQsyUVBtW6kbW3TuHNEAGB7rfa3rY2LWM8MFov5AgUAlBJtBZBxUb+ezWBJcsFikTZCR2tkAYBtRUvMEGlcRAzZlgiaHs0v6j2NtLTx0cheLpfSRQEAdhBtqWGkcdHvoo4je5BtBiva14QWuKff89UIAL7X0oqPR0DD14wjy8k2gxXta0IL3NPvRf1q9ApfmgDYSg0rPvSDeRlHliPJBV2o4cudTbIAbEU/CPlJckHXapgmt9wRgK3UsKxOP0grzGDRhRq+3AEAUA8HDdO1lvZqtcJae6AkbRCwFUsEgSJqWLYJtEsbBGzFDBZQRCvZjXwFpzet1PlW2iAgHgEWUEQryzZrSH28p1YG3x+1el2vaKXOt9IGAfFYIgiwgqxXf2p12VWr1/UKdR7gawIsgBVqSH28p1YH361e1yvUeYCvSdMOAACwkDTtAAAAGxNgAQAAZCLAAgAAyESABQAAkIkACwAAOuasv7wEWAWoxAAARNHKAeJRCLAKUIkBgFJ86OWjcRzTMAzO+stEgFWASkxKOjgAyvCh92s99s+PA8RPp1PpojThX6UL0KNHJe7F/X5Pl8sljePoxf3No4NLKXVVHwAo6/GB14fez+mfWcsMFptb+6Ws1S9JZjIBKKHl2YocYwb9M2uZwWJza7+UtfolqbeZTADYWo4xg/6Ztcxgsbm1X8p8SQJgS62ulOiRMUPbanlXmwywarn5zNPyUobeeDeBiCR9qMOcPsSYoW21vKtNLhFsdUkZz0mkUQfvJhCRpA910IdQy7vaZIBVy80nH41uHVp6NwX10M57YM9NHVrqQ3hNLe/qYZqm2X/4eDxO7+/vGxYHXtNKJ089zudzul6vaRiGKhp72IL3AOjZ4XD4OU3T8ePvm9yDRX+suWZvNlJ/rtV9dq1e11reA2rg/d2W+/s3AdYKKtQ23FdqIKj/XC0bkJdq9brW8h5Qg1bf3yjjpVbv7xpN7sHaS+l9P60uiyt9X4HXtbpHotXrgh60+v5GGS+1en/XsAdrhdIBTqtr30vfVwCA6IyXynu2B0uAVTEvFgAAlPEswLJEsGK1pKoEAIBeSHIBAACQiQALAomSEQiAduhbYF+WCEIgUTICAdAOfQvsywwWBOLQTgByi9y3mF2jRbII0h3ZFwEghlaPnKEPz7IImsGiO04cB+BVZlzyijy7Bq+yB4vuOHE8LzOCQE/sZ8rLkTO0SIBFdzTmeRlsAD3xkQ74jgALWMVgA+iJj3TAd+zBAlZ5DDa2XB5ozwMwl/aCr6gf7EGARXEaO76TKzHJXnVNnaYVe9blXP+WREZ8Rf1gF9M0zf55e3ubILdhGKaU0jQMQ+miENTtdpuGYZhut9uqv2evutZanc51/3vQ2r3asy7n+rdaewbkpX6QU0rpffokZhJgUZzG7nXu3TJ73a/WnktrAeOWWrtXe9bl1t6bLblXEIMACxrU2mCOmPYezOX+9wQJtEbbP4/3ka0JsKiOhvF7a++Re0xEuQePBqNEo+3eh3efrT0LsKRpJyznK31vbbpg95iIcqf+d5QA0axte6WKn8e7TykCLMLSMG7PPSai3INHg1Gi0fbuw7tPKYd/ZrfmOR6P0/v7+4bFAQAo536/p8vlksZx3PR8P6B+h8Ph5zRNx4+/dw4WsClnQgE1cU4SsJYlgsCm7PMCamL5HrCWGSxgU+M4pmEYDFagELPIyzz27VgeCLxKgAVsqpXByp6D1Jz/lsF1fXI/sz2XvKlvAAIs+JLBAg97DlJz/lv2k9Qn9zPbcxZZfSMlfSc4aBi+4JBCHvY82DPnv7X3gaStHoBa6/PfW81lJx995zzel/qlJwcNS9PeOelov+b+wDLn8zldr9c0DENTSU1avS7Ygr5zHu1K/Z6laZdFsHMyvH3NIYWwTKsZ2Fq9LtiCvnMe7Uq7zGB1zlcmAABYzgwWn/KVCQAA8pFFEAAAIBMBFgAAQCYCLAAAmuZsLvYkwCIUDSAAkJtDsNlT0QDLYJqPNIAAQG7jOKZhGKREZ7Y1cUrRLILOYOIjZ0IAALnJmsxSa+KUojNYvibw0aMBdCZXbGafAbSFkEvEd2lNnNL9QcMO2oXlzudzul6vaRgGXwSBbmkLIY9a3yUHDT9hmSIsZykngLYQcmntXTKDZQYLAABY6NkMVvdp2u35AQCoS8Q9O/DQfYBF3TSwRKEu0gP1nCgc60Jk3e/Bom720BGFukgP1HOiKLlnx/YSvmMGiyxKfdWU6p8oWq+LZi7maf0+tV7PqUfJLR5mz/hO90kuyKPW9JrAPN7xedwnetDSDM4r19LS9bOONO1s6pWp+hYaqBauAeZoLYXuVtwnetDSUtFXruUxewbPCLDI4pXGpoUGuoVrgDkMKOZxn+hBSx8SWroW4hBgUUwLjVoL1wAAS7T0IaGlayEOe7AAAAAWctAwAADAxgRYAAAAmQiwAAAAMhFgAQAAZCLAAgCADt3v93Q+n9P9fi9dlKZI0w4AAB1ynuc2zGAF4OsBAAB7G8cxDcPgPM/MBFgBPL4eXC6X0kUBAF7gYyk1ehy0fDqdShelKQKsAHw9oAYGDwDP+VgKPNiDFcDj6wFEZp02wHOPj6Q+lgICLGAWgweA53wsBR4EWMAsBg8AAN+zBwsAgKe23INrfy8tEmDRpa0adB0F0ANtXV+2TOAhOQgtskSQLm2VsEEiiP7c7/d0uVzSOI7S3NINbV1fttyDa38vLRJg0aWtGnQdRX8MNOmRtq4vW+7Btb+XFh2maZr9h4/H4/T+/r5hcQDq0sMMVg/XmJP7BdCHw+Hwc5qm48ffm8ECWKGHr69m6ZZxvwD6JsAC4EuWgy3jfgH0zRJBAACAhZ4tEZSmHQAAIBMBFgAAQCYCLAAAgEwEWAAAfOt+v6fz+Zzu93vpokBoAizIQKcDQOseRxBcLpenf0Z/CAIsmOW7DmNOpwMANRvHMQ3D8OURBPpDEGDBLN91GHM6HQDq1/MMzeNg9dPp9PTPtNof9vzcWU6ARXYtNkLfdRhzOp2WtfjMAT5jhuZrtfSHS/stz50l/lW6ALTn0QillNKPHz++/fP3+z1dLpc0jmPYBvnRYfC5pc8coFaPD22tzdD0Zmm/5bmzhACL7JY2Qgbn9dPxAL3wwa0NS/stz50lDtM0zf7Dx+Nxen9/37A49KiGGSwAgC0YB9XrcDj8nKbp+PH39mBRXC3rtQFYzh5N+Jr9Xe0RYHVOxwd/815APgaP8LVWMy/2zB6sztn/BH/zXkA+9mjC1+zvao8Aq3M6Pvib9wLyMXgEemOJYOfsf4K/7f1etLIksZXreKaV62vlOgCiEmABFJZ7j0qpAXTre21KXV/u59n6cwIozRJBgMJyL0kstYes9aWVpa4v9/Ns/TkBlOYcLIDGOFOlLZ4nxOF95HfOwQLohL2VbfE887MPrT5RnpkltswhwCKrCA1ghDIwn+cF7M0guT5Rnpkzq5hDgEVWERrACGVgvpzPS7AG7cr5fhsk1yfKMzOjzBySXJBVhM3TEcrAfDmflwOCoV05329nc9XHM6MmklwAzbD5GNrl/QaieZbkQoAFAACwkCyCAJnZ80XP1H+Az9mDBfAie77omfoP8DkzWAAvipLVqjW5Z0bMtGxD/Qf4nAAL4EWtp+stFZjkPmqh1NENrQd2rdd/gFdZIgjAp0otAct91EKpoxssoQPokwALgE+VCkxyn3dT6vwcZ/IB9MkSQQA+ZQnYOu4fNfpqaWvry14hFwEW7ECnBEANvtqzWGo/I9TGEkHI5H6/p8vlksZx/OuLtb0YANTgq6Wtlr3CPAIsyOSrIEqnBEANvtqzWGo/I9RGgAWZfBVE6ZQAAPogwIJMBFEAAEhyAQAAkIkACwCAbGTOpXcCLJhJhwFATUr1W9K50zsBFsy0d4choANgjVKBzjiOaRiGJjLn6ot5hSQXMNPeqdadnQXAGqWOCGkp6ZO+mFeYwWJzrXz9eXQYHw8R3kpLXwAB2F+OfquVPvwzc65NX8wrBFhsrte12Gs7pb0DOoCttDxIb13Lffica9MX8woBFpub8/Wnxc635U6pZS3WRShNe1ivlmdwWr42yrIHi83NWYvd4hrnUmvfWafFugilaQ/r1dJ+qo9avjbKEmARQoudr4a7Ti3WRShNewj05DBN0+w/fDwep/f39w2LAwAAEN/hcPg5TdPx4+/twQJgld72rfV2vQAsY4kgAKv0tm+tt+sFYBkBFgCr9LZvrbfrBWAZe7AAAAAWsgcLAABgYwIsAIBAJFKBugmwoHE6aoC6PBKpXC6X0kUBXiDJBTROxjOAukikAnUTYEHjdNQAdTmdTj6IQcUEWNA4HTUAwH7swQIAAMhEgAUA0CmJkCA/ARYUolMDYC/P+hwZCyE/e7CgENn9ANjLsz5HIiTIT4AFhTzr1O73e7pcLmkcx3Q6nUoUDYDGPOtzJEKC/A7TNM3+w8fjcXp/f9+wOMD5fE7X6zUNw6DTAwAI6nA4/Jym6fjx903swbKXhZaM45iGYbBcAwCgQk0sEbSXhZZYrgEAUK8mZrB88QfWMhMO2/OeAaXs2f40MYPliz+wlplw2J73DChlz/aniQALYC2pimF73jNKkJ2XlPZtf2QRBADIxGA+Htl52UrTWQRpmzX75XkGAPM8liFdLpfSReE/2avP3gRYhKezKs8z4Jleg+9er5vvGcyvl/v9euzVN6PIXuzBIjxr9svzDHim16QFvV4335N4az3vF7UTYBFe7s7K+vjlDBh4ptfgu9frhj14v6idJBd0x2ZXAADWepbkwgwW3fFlDACArQiw6I7lbgAAbEUWQQAAgEwEWAAAAJkIsAAAKuZcNohFgAWV0qECkJLD4CEaARZUSocK0K4lH9HGcUzDMMiOC0HIIgiVWpJu3uHKAHV5fERLKX2b+VZ2XIhFgAWVWtKhLumoASjPmY1QLwEWdEBHDVAXs1JQL3uwoAOPjtryQIB5JBICXiXAAjZjgAL9aO19l0gIeJUAC9hMawOU1gaQkFNr77vMfMCr7MECNtPa3i/JQuC51t53e6CAVx2maZr9h4/H4/T+/r5hcQDiku4eAHg4HA4/p2k6fvy9JYIAM0kWAlAnS7zZkwCLKmgYYT/et7zcTyivtT2CxGYPFlWw9wX2433Ly/2kZq0sjW5tjyCxmcGqgK+fsjnBnrxvebmf1KyVmR9LvP9kbLktSS4qcD6f0/V6TcMw+PpZqVa+AAJQTom+RP/VJmPLPJ4lubBEsAKmtetniRAAa5XoS6Srb5Ox5bYsEayAae367blEyLQ/wHw52sy92l3LTcnF2HJbAizYwZ4N2V7r5dcOKASCQAQ52sy92l2DYqiDJYLQmL2m/dcuVbFsEoggR5tpuRXwO0kugJes3fhs4zTE4F0EeM2zJBeWCAIvWbtUpeelLpZHEkkrabjRtpTgnvMZARZUSINety0GtOpEH7Z4zhIn/FL7eyRY3p97zqemaZr98/b2NsF3brfbNAzDdLvdShelWcMwTCmlaRiG0kVZRN34xxb3odY6wTKe87Zqv7/a2P25531LKb1Pn8RMklyQneQF26t1Q7W68Y8tzpWptU6wjOe8rdrvrzOr9uee85lFSS4Oh8P/SSn9r+2KQyP+W0rpf6SU/ndK6f8VLguxqBsAQCv+5zRN//3jLxcFWAAAADwnyQUAAEAmAiwAAIBMBFgAAACZCLAAAAAyEWABAABkIsACAADIRIAFAACQiQALAAAgEwEWAABAJv8/WEBZvDpTTjIAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:15.376666300026493 max: 109.64050368612064\n", + "image 1 reprojection errors: average:15.202131478994277 max: 69.51272526709528\n", + "image 2 reprojection errors: average:15.716292780251871 max: 181.94042863230572\n", + "image 3 reprojection errors: average:14.98964337813133 max: 100.1618742507683\n", + "image 4 reprojection errors: average:15.239792261548397 max: 145.3848426099025\n", + "image 5 reprojection errors: average:15.263250576431226 max: 110.38157697544744\n", + "image 6 reprojection errors: average:15.556337866603752 max: 122.50578466507639\n", + "image 7 reprojection errors: average:15.43842026045658 max: 138.9462934612739\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.1215e+06 1.51e+06 \n", + " 1 2 3.3796e+03 1.12e+06 6.26e+01 7.07e+04 \n", + " 2 3 2.7715e+03 6.08e+02 6.72e-01 3.57e+02 \n", + " 3 4 2.7662e+03 5.32e+00 4.16e-01 2.57e+02 \n", + " 4 5 2.7654e+03 7.54e-01 5.09e-02 4.90e+01 \n", + " 5 6 2.7654e+03 6.93e-02 9.00e-03 2.90e+01 \n", + " 6 7 2.7653e+03 3.19e-02 4.20e-03 1.60e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 1.1215e+06, final cost 2.7653e+03, first-order optimality 1.60e+01.\n", + "mean reprojection error: 0.8305711616581744\n", + "max reprojection error: 3.35073743596362\n", + "mean reconstruction error: 0.07653129593821141\n", + "max reconstruction error: 0.31426853210765976\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:15.0817217512262 max: 83.64747273269985\n", + "image 1 reprojection errors: average:16.024234523255913 max: 112.80789869769069\n", + "image 2 reprojection errors: average:15.626208031038457 max: 85.70800291007828\n", + "image 3 reprojection errors: average:15.50027502437788 max: 94.12028790868975\n", + "image 4 reprojection errors: average:15.86368993050673 max: 157.55466499963964\n", + "image 5 reprojection errors: average:15.374243218702185 max: 101.880862049147\n", + "image 6 reprojection errors: average:14.93893170377339 max: 88.28698545295501\n", + "image 7 reprojection errors: average:15.31078061073921 max: 97.94473794550262\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.0890e+06 1.94e+06 \n", + " 1 2 2.5606e+04 1.06e+06 6.15e+01 4.78e+04 \n", + " 2 3 2.5254e+04 3.52e+02 1.01e+00 2.09e+03 \n", + " 3 4 2.5232e+04 2.25e+01 5.50e-01 1.46e+03 \n", + " 4 5 2.5223e+04 8.32e+00 1.41e-01 3.35e+02 \n", + " 5 6 2.5221e+04 1.81e+00 5.69e-02 1.71e+02 \n", + " 6 7 2.5221e+04 8.13e-01 2.58e-02 8.45e+01 \n", + " 7 8 2.5220e+04 4.76e-01 1.77e-02 6.14e+01 \n", + " 8 9 2.5220e+04 4.81e-01 1.86e-02 6.94e+01 \n", + " 9 10 2.5219e+04 3.65e-01 1.17e-02 5.10e+01 \n", + " 10 11 2.5219e+04 1.00e-01 2.43e-03 1.20e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 1.0890e+06, final cost 2.5219e+04, first-order optimality 1.20e+01.\n", + "mean reprojection error: 2.5079388096761135\n", + "max reprojection error: 9.332125668493461\n", + "mean reconstruction error: 0.22927962542349026\n", + "max reconstruction error: 0.8683111418689335\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:15.922608482652592 max: 106.8623859387557\n", + "image 1 reprojection errors: average:16.484998666732356 max: 147.83242525318818\n", + "image 2 reprojection errors: average:16.30230250835252 max: 106.21747558998337\n", + "image 3 reprojection errors: average:16.361700271551772 max: 170.17355495278935\n", + "image 4 reprojection errors: average:16.073472910915953 max: 100.51536614827128\n", + "image 5 reprojection errors: average:16.410035363397697 max: 94.49800370613396\n", + "image 6 reprojection errors: average:16.506539570137356 max: 103.31262338665277\n", + "image 7 reprojection errors: average:16.161844294864093 max: 82.9915030254904\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.2191e+06 1.59e+06 \n", + " 1 2 6.8332e+04 1.15e+06 6.41e+01 5.92e+04 \n", + " 2 3 6.7787e+04 5.44e+02 7.63e-01 1.65e+03 \n", + " 3 4 6.7718e+04 6.93e+01 1.22e+00 1.79e+03 \n", + " 4 5 6.7698e+04 1.99e+01 1.70e-01 1.86e+02 \n", + " 5 6 6.7697e+04 1.79e+00 4.11e-02 9.96e+01 \n", + " 6 7 6.7696e+04 6.26e-01 1.34e-02 9.00e+01 \n", + " 7 8 6.7696e+04 2.28e-01 3.78e-03 1.29e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 8, initial cost 1.2191e+06, final cost 6.7696e+04, first-order optimality 1.29e+01.\n", + "mean reprojection error: 4.0983379203044725\n", + "max reprojection error: 15.75994255380696\n", + "mean reconstruction error: 0.38669485585313024\n", + "max reconstruction error: 1.4710154624395564\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:18.36971108890736 max: 81.58530447043105\n", + "image 1 reprojection errors: average:19.066551489850685 max: 195.758591709116\n", + "image 2 reprojection errors: average:18.326318201972956 max: 71.54414318652472\n", + "image 3 reprojection errors: average:17.738203440918724 max: 105.47925113446286\n", + "image 4 reprojection errors: average:18.379246664274195 max: 115.40830793631787\n", + "image 5 reprojection errors: average:18.50229706561002 max: 76.72097182181145\n", + "image 6 reprojection errors: average:18.307675879860035 max: 102.32779293459235\n", + "image 7 reprojection errors: average:19.32064538675488 max: 106.42193536309675\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.4727e+06 1.70e+06 \n", + " 1 2 2.7611e+05 1.20e+06 6.87e+01 6.07e+04 \n", + " 2 3 2.7551e+05 6.06e+02 1.33e+00 6.37e+03 \n", + " 3 4 2.7542e+05 9.14e+01 6.50e-01 3.46e+03 \n", + " 4 5 2.7537e+05 4.51e+01 2.72e-01 1.21e+03 \n", + " 5 6 2.7535e+05 2.30e+01 2.05e-01 8.44e+02 \n", + " 6 7 2.7533e+05 1.42e+01 1.05e-01 2.97e+02 \n", + " 7 8 2.7533e+05 8.04e+00 8.65e-02 3.06e+02 \n", + " 8 9 2.7532e+05 7.19e+00 6.82e-02 1.51e+02 \n", + " 9 10 2.7531e+05 6.41e+00 7.21e-02 2.46e+02 \n", + " 10 11 2.7531e+05 6.11e+00 6.15e-02 1.08e+02 \n", + " 11 12 2.7530e+05 5.12e+00 5.89e-02 2.46e+02 \n", + " 12 13 2.7530e+05 5.53e+00 6.04e-02 1.20e+02 \n", + " 13 14 2.7529e+05 5.30e+00 5.97e-02 2.61e+02 \n", + " 14 15 2.7529e+05 3.48e+00 3.57e-02 1.16e+02 \n", + " 15 16 2.7529e+05 1.13e+00 8.39e-03 7.17e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 16 17 2.7529e+05 1.15e+00 1.72e-02 1.53e+02 \n", + " 17 18 2.7528e+05 1.11e+00 8.15e-03 7.72e+01 \n", + " 18 19 2.7528e+05 1.35e+00 2.08e-02 1.85e+02 \n", + " 19 20 2.7528e+05 1.31e+00 8.68e-03 8.04e+01 \n", + " 20 21 2.7528e+05 1.38e+00 2.19e-02 1.90e+02 \n", + " 21 22 2.7528e+05 1.34e+00 8.67e-03 8.35e+01 \n", + " 22 23 2.7528e+05 1.42e+00 2.30e-02 1.95e+02 \n", + " 23 24 2.7528e+05 1.38e+00 8.68e-03 8.62e+01 \n", + " 24 25 2.7527e+05 1.46e+00 2.42e-02 1.99e+02 \n", + " 25 26 2.7527e+05 1.41e+00 8.70e-03 8.87e+01 \n", + " 26 27 2.7527e+05 1.50e+00 2.56e-02 2.04e+02 \n", + " 27 28 2.7527e+05 1.46e+00 8.74e-03 9.07e+01 \n", + " 28 29 2.7527e+05 1.55e+00 2.71e-02 2.09e+02 \n", + " 29 30 2.7527e+05 1.50e+00 8.80e-03 9.27e+01 \n", + " 30 31 2.7527e+05 1.38e+00 2.46e-02 2.01e+02 \n", + " 31 32 2.7526e+05 1.38e+00 8.51e-03 1.07e+02 \n", + " 32 33 2.7526e+05 1.26e+00 2.26e-02 1.93e+02 \n", + " 33 34 2.7526e+05 1.27e+00 8.26e-03 1.27e+02 \n", + " 34 35 2.7526e+05 1.19e+00 2.13e-02 1.87e+02 \n", + " 35 36 2.7526e+05 1.11e+00 7.31e-03 9.33e+01 \n", + " 36 37 2.7526e+05 3.51e-01 6.21e-03 1.07e+02 \n", + " 37 38 2.7526e+05 3.47e-01 3.93e-03 4.39e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 38, initial cost 1.4727e+06, final cost 2.7526e+05, first-order optimality 4.39e+01.\n", + "mean reprojection error: 8.244966455201748\n", + "max reprojection error: 35.77527247237545\n", + "mean reconstruction error: 0.761233133371262\n", + "max reconstruction error: 3.0636706088718864\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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jZ8+eHDhwgJycnCLl4uLiuOuuu0hJSaFv377s27cP8BKjl156iYMHD9K+fXuys7MBGD58OLNmzQLgd7/7HZdeeilJSUlMmTKl1LifeeYZunfvTnJyMqNHj+bEiROhGCZPnkyPHj1YuXJlkemHH36YTp060alTJ/7whz8AsH37dhITE7n99ttJSUlhx44dxbbbp08fJkyYQFpaGomJibz//vsMGTKEdu3ace+995Ya39ixY+nWrRsdO3YssJ2tW7dmypQppKSk0LlzZ7KyskrdByVxzvHWW29xww03ADBy5EheffXVIuVef/11+vXrR5MmTWjcuDH9+vVj8eLFBcp89dVXvPXWWxF7Wo4cOUJ6ejpJSUkMGzaMI0eOhJYtWbKE1NRUUlJSGDp0KIcPHwZg4cKFJCQk0KtXL8aPH88111xTrm0tjZIWEZGzyK5du7jwwgtD0/Hx8ezatatIua+//pqUlBTWrVtH7969mTp1aoHlDRs2ZMaMGWRkZPDCCy/w5Zdf8pOf/IQlS5awdetWVq9ezYYNG1i7di3Lly8vNp4tW7Ywf/583n33XTZs2ED16tV59tlnQzF06tSJzMxMevXqVWC6Tp06zJkzh8zMTFatWsWsWbNYv349ANnZ2YwYMYL169fTqlUrBgwYwO7duyO2f84557B8+XLGjBnDoEGDePTRR9m0aRNz585l//79Jcb361//mjVr1rBx40befvttNm7cGKq3adOmrFu3jrFjx/LQQw8VaTc7Ozt0uqbw48CBAwXK7t+/n0aNGlGjRo0Sj1k0x/aVV16hb9++NGjQoMj6f/rTn6hbty4bN27knnvuYe3atQB88cUXTJs2jaVLl7Ju3Tq6devGww8/zNGjRxk9ejSLFi1ixYoVocS2Iun0kIjIWcQ5V2RepF9xVKtWjWHDhgHw4x//mCFDhhQp069fPxYsWMC4ceP44IMPAO8b+ZIlS+jSpQsAhw8fZuvWraSlpUWM580332Tt2rVceumlgPdtv1mzZgBUr16d66+/PlQ2fHrFihUMHjyYevXqATBkyBDeeecdBg4cSKtWrejZs2dovYULFxa7PwYOHAhA586d6dixIy1atACgTZs27NixgxUrVhQb34svvsgTTzxBXl4eOTk5bN68maSkpFA8AF27duXll18u0m779u3ZsGFDsXGFi/aYRVPu+eef59Zbb43YzvLlyxk/fjwASUlJoW1ZtWoVmzdv5gc/+AEAx48fJzU1laysLNq0aRO6z8rw4cN54oknotqmU6WkRUTkLBIfH1/glMnOnTtp2bJlqetF+pA8efIkW7ZsoU6dOuTm5hIfH49zjl/+8peMHj06qnicc4wcOZLf/OY3RZbVrl27wHUr4dORPqDz5Scy0ahVqxbgJWn5z/On8/Lyio1v27ZtPPTQQ7z//vs0btyYjIyMAvccya+revXq5OXlFWk3Ozs7lBQWtmzZMho1ahSabtq0KQcOHCAvL48aNWoUe8zi4+NZtmxZaHrnzp306dMnNL1//35Wr17NK6+8Uuz+KC4Z6tevH88//3yB+fk9W5VJSYuISAXYnHMo6gtoo6mrQ4ui3fmnYuDAgcyYMYP09HQyMzNp2LBhqHch3MmTJ3nppZdIT0/nueeeo1evXkXKPPLIIyQmJvLAAw9w8803s3LlSq688kp+9atf8aMf/Yi4uDh27dpFzZo1Q70ThfXt25dBgwYxYcIEmjVrRm5uLl999RWtWrUqcTvS0tLIyMhg0qRJOOd45ZVXePrpp09tp5SguPgOHTpEvXr1aNiwIXv37mXRokUFEoTSlKWnxcy4/PLLQ8dj3rx5ES+kvfLKK7n77rv58ssvAa/XKzzZWrBgAddccw21a9eO2E5aWhrPPvssl19+OZs2bQqd7urZsyfjxo3jk08+oW3btnzzzTfs3LmThIQEPv30U7Zv307r1q2ZP39+1Nt/qs7IpCXSPRJ0jwMRqSwdWsYmwQjV16JBVHUOHz6cZcuW8cUXXxAfH8/UqVO55ZZbmDlzJgBjxoxhwIABLFy4kLZt21K3bl3mzJkTsa569erx0Ucf0bVrVxo2bFjkA+njjz9m9uzZrF69mvr165OWlsa0adOYOnUqW7ZsITXV++VUXFwczzzzTLFJS4cOHZg2bRpXXHEFJ0+epGbNmjz66KOlJi0pKSlkZGTQvXt3AG699Va6dOnC9u3bi5QdMGAAs2fPjqpHKdr4evbsSZcuXejYsSNt2rQJnTqpKNOnTyc9PZ17772XLl26cMsttwCwZs0aZs6cyezZs2nSpAm/+tWvQqeyJk+eXODC7BdeeIFJkyYV28bYsWMZNWoUSUlJJCcnh/bteeedx9y5cxk+fDjHjh0DYNq0aVxyySU89thj9O/fn6ZNm4bKVyQrqYst1rp16+Yq4zffwx5fWeCbSf7zWP38UESksC1btpCYmFjVYcRMXFxc6BciIsU5fPgwcXFxOOcYN24c7dq1Y8KECVGvH+l9Y2ZrnXPdIpU/Y389lJ+kzB+dGrNuVREREfnOrFmzSE5OpmPHjhw8eDDqa5lO1Rl5ekhERMpHvSwSjQkTJpSpZ6W8ztieFhERETmzKGkRERGRQFDSIiIiIoGga1pERGJt0STY82Fs62zeGa56MLZ1igSMelpERGJtz4exTVqiqO/o0aN0796d73//+0UG8AvnnGP8+PG0bduWpKQk1q1bV6ZQJk+ezNKlS8u0Tr64uLhTWk+8O/D26NGDdu3aMWzYMI4fP16kzIYNG0hNTaVjx44kJSVFvNnbT3/606iPQ58+faiM25SUhXpaREQqQvPOMOofsalrztWlFqlVqxZvvfUWcXFxfPvtt/Tq1YurrrqqwBg8AIsWLWLr1q1s3bqVzMxMxo4dS2ZmZtSh3H///WUOPxZOnDhR4Jb+hacjcc7hnKNateB/P584cSITJkwgPT2dMWPG8OSTTzJ27NgCZerWrctTTz1Fu3bt2L17N127duXKK68MDQmwZs2aIoMxBk3wj6SIiGBmoW/Q3377Ld9++23EcWRee+01RowYgZnRs2dPDhw4QE5OTpFycXFx3HXXXaSkpNC3b9/QCL4ZGRm89NJLHDx4kPbt25OdnQ14d+OdNWsWAL/73e+49NJLSUpKKrbHJ9wzzzxD9+7dSU5OZvTo0Zw4cSIUw+TJk+nRowcrV64sMv3www/TqVMnOnXqxB/+8AcAtm/fTmJiIrfffjspKSkFxlkqrE+fPkyYMIG0tDQSExN5//33GTJkCO3atePee+8tNb6xY8fSrVu3Ij1brVu3ZsqUKaSkpNC5c2eysrJK3Qclcc7x1ltvccMNNwAwcuRIXn311SLlLrnkEtq1awdAy5YtadasWei4nThxgv/+7//mt7/9bbHtHDlyhPT0dJKSkhg2bBhHjhwJLVuyZAmpqamkpKQwdOjQ0E/iFy5cSEJCAr169WL8+PFcc8015drW0ihpERE5Q5w4cYLk5GSaNWtGv3796NGjR5Eyu3bt4sILLwxNx8fHs2vXriLlvv76a1JSUli3bh29e/dm6tSpBZY3bNiQGTNmkJGRwQsvvMCXX37JT37yE5YsWcLWrVtZvXo1GzZsYO3atSxfvrzYmLds2cL8+fN599132bBhA9WrV+fZZ58NxdCpUycyMzPp1atXgek6deowZ84cMjMzWbVqFbNmzQoN4Jednc2IESNYv349rVq1YsCAAezevTti++eccw7Lly9nzJgxDBo0iEcffZRNmzYxd+5c9u/fX2J8v/71r1mzZg0bN27k7bffDo3VA94gh+vWrWPs2LE89NBDRdrNzs4mOTk54qNwb8j+/ftp1KgRNWrUKPGYhVu9ejXHjx/ne9/7HgAzZsxg4MCBEceZyvenP/2JunXrsnHjRu655x7Wrl0LwBdffMG0adNYunQp69ato1u3bjz88MMcPXqU0aNHs2jRIlasWBFKkCqSTg+JiJwhqlevzoYNGzhw4ACDBw9m06ZNdOrUqUCZSEO3ROqRqVatWmgU4h//+McMGTKkSJl+/fqxYMECxo0bxwcffAB438iXLFlCly5dAO8mdVu3biUtLS1izG+++SZr164NjZdz5MiR0DhF1atX5/rrry+wffnTK1asYPDgwaERnYcMGcI777zDwIEDadWqVYHTYgsXLozYNngDSAJ07tyZjh07hj7U27Rpw44dO1ixYkWx8b344os88cQT5OXlkZOTw+bNm0lKSgrFA9C1a1defvnlIu2WZcDEaI9ZvpycHG666SbmzZtHtWrV2L17NwsWLCgwAnQky5cvZ/z48QAkJSWFtmXVqlVs3rw5NL7S8ePHSU1NJSsrizZt2nDxxRcDXm/bE088EdU2nSolLSIiZ5hGjRrRp08fFi9eXCRpiY+PL3DKZOfOnVENJBjpQ/LkyZNs2bKFOnXqkJubS3x8PM45fvnLX0Z9O3fnHCNHjiwwGnG+2rVrF7huJXy6pHHz8hOZaNSqVQvwkrT85/nTeXl5xca3bds2HnroId5//30aN25MRkYGR48eLVJv9erVycvLK9JudnZ2KCksbNmyZaHrUMDrtTlw4AB5eXnUqFGjxGN26NAhrr76aqZNmxZK3NavXx8aoRngm2++oW3btnzyySdF1o90nJ1z9OvXj+eff77A/PyercqkpEVEpCLs+TCqC2ijrqt55xKL7Nu3j5o1a9KoUSOOHDnC0qVLmThxYpFyAwcOZMaMGaSnp5OZmUnDhg0jnjI4efIkL730Eunp6Tz33HP06tWrSJlHHnmExMREHnjgAW6++WZWrlzJlVdeya9+9St+9KMfERcXx65du6hZs2axozz37duXQYMGMWHCBJo1a0Zubi5fffVVqaM8p6WlkZGRwaRJk3DO8corr/D000+XuM6pKC6+Q4cOUa9ePRo2bMjevXtZtGgRffr0ibresvS0mBmXX3556HjMmzePQYMGFSl3/PhxBg8ezIgRIxg6dGho/tVXX82ePXtC03FxcRETlrS0NJ599lkuv/xyNm3aFDrd1bNnT8aNGxdKfL755ht27txJQkICn376Kdu3b6d169YRf60Ua0paRERirZQE45TqK6XOnJwcRo4cyYkTJzh58iQ33nhj6KLImTNnAjBmzBgGDBjAwoULadu2LXXr1mXOnDkR66tXrx4fffQRXbt2pWHDhkU+kD7++GNmz57N6tWrqV+/PmlpaUybNo2pU6eyZcsWUlNTAe8D8plnnik2aenQoQPTpk3jiiuu4OTJk9SsWZNHH3201KQlJSWFjIwMunfvDsCtt95Kly5d2L59e5GyAwYMYPbs2VH1KEUbX8+ePenSpQsdO3akTZs2oVMnFWX69Omkp6dz77330qVLF2655RbA+0XQzJkzmT17Ni+++CLLly9n//79zJ07F4C5c+eSnJwcVRtjx45l1KhRJCUlkZycHNq35513HnPnzmX48OEcO3YMgGnTpnHJJZfw2GOP0b9/f5o2bRoqX5GspC62WOvWrZurjN98D3t8JQDzR6dGnBYRibUtW7aQmJhY1WHETFxcnAZNlFIdPnyYuLg4nHOMGzeOdu3alWkAxUjvGzNb65zrFqm8fj0kIiIip2TWrFkkJyfTsWNHDh48GPW1TKdKp4dERKQI9bJINCZMmFCmnpXyUk+LiIiIBIKSFhEREQkEJS0iIiISCLqmRUQkxqavnk5WbvnGmyksoUkCE7sXve+KyNlEPS0iIjGWlZtFdm52zOrLzs2OKglq3bo1nTt3Jjk5mW7dIv5iFOcc48ePp23btiQlJbFu3boyxTJ58mSWLl1apnXy5Q/oKGW3bds2evToQbt27Rg2bBjHjx8vUuazzz6ja9euoV/z5N+fB7zhElJSUkhOTqZXr14Rby5XWJ8+faiM25SUhXpaREQqQPsm7ZnTP/KN28pq1OJRUZf95z//SdOmTYtdvmjRIrZu3crWrVvJzMxk7NixZGZmRl3//fffH3XZWDpx4kSBW/oXno7EOYdzjmrVgv/9fOLEiUyYMIH09HTGjBnDk08+ydixYwuUadGiBe+99x61atXi8OHDdOrUiYEDB9KyZUvGjh3La6+9RmJiIo899hjTpk0L3YAuSIJ/JEVEJGqvvfYaI0aMwMzo2bMnBw4cICcnp0i5uLg47rrrLlJSUujbt29oBN+MjAxeeuklDh48SPv27cnO9nqUhg8fzqxZswD43e9+x6WXXkpSUhJTpkwpNaZnnnmG7t27k5yczOjRozlx4kQohsmTJ9OjRw9WrlxZZPrhhx+mU6dOdOrUiT/84Q8AbN++ncTERG6//XZSUlIKjLNUWJ8+fZgwYQJpaWkkJiby/vvvM2TIENq1a8e9995banxjx46lW7dudOzYscB2tm7dmilTppCSkkLnzp3JyirfqULnHG+99RY33HADACNHjuTVV18tUu6cc84JjXl07NgxTp48GVpmZhw6dAiAgwcPRrw78JEjR0hPTycpKYlhw4Zx5MiR0LIlS5aQmppKSkoKQ4cODf0kfuHChSQkJNCrVy/Gjx8fugtzRVHSIiJyhjAzrrjiCrp27VrsaLu7du3iwgsvDE3Hx8eza9euIuW+/vprUlJSWLduHb1792bq1KkFljds2JAZM2aQkZHBCy+8wJdffslPfvITlixZwtatW1m9ejUbNmxg7dq1LF++vNiYt2zZwvz583n33XfZsGED1atX59lnnw3F0KlTJzIzM+nVq1eB6Tp16jBnzhwyMzNZtWoVs2bNCg3gl52dzYgRI1i/fj2tWrViwIAB7N69O2L755xzDsuXL2fMmDEMGjSIRx99lE2bNjF37lz2799fYny//vWvWbNmDRs3buTtt98OjdUD3iCH69atY+zYsTz00ENF2s3OziY5OTni48CBAwXK7t+/n0aNGlGjRo0SjxnAjh07SEpK4sILL2TixImh5GT27NkMGDCA+Ph4nn76aSZNmlRk3T/96U/UrVuXjRs3cs8997B27VoAvvjiC6ZNm8bSpUtZt24d3bp14+GHH+bo0aOMHj2aRYsWsWLFilBiW5F0ekhE5Azx7rvv0rJlSz7//HP69etHQkICaWlpBcpEGrol0si+1apVC41C/OMf/5ghQ4YUKdOvXz8WLFjAuHHj+OCDDwDvG/mSJUvo0qUL4N2kbuvWrUXiyPfmm2+ydu1aLr30UsD7tp8/TlH16tW5/vrrQ2XDp1esWMHgwYNDIzoPGTKEd955h4EDB9KqVavQCMfg9QYUZ+DAgQB07tyZjh07hgaPbNOmDTt27GDFihXFxvfiiy/yxBNPkJeXR05ODps3byYpKSkUD0DXrl15+eWXi7RblgEToz1mABdeeCEbN25k9+7dXHfdddxwww2cf/75PPLIIyxcuJAePXrwu9/9jjvvvJPZs2cXWHf58uWMHz8egKSkpNC2rFq1is2bN4fGVzp+/DipqalkZWXRpk0bLr74YsDrbSsuWY4VJS0iImeI/G/VzZo1Y/DgwaxevbpIshAfH1/glMnOnTujGkgw0ofkyZMn2bJlC3Xq1CE3N5f4+Hicc/zyl7+M+nbuzjlGjhzJb37zmyLLateuXeC6lfDpksbNy09kopF/OqVatWqh5/nTeXl5xca3bds2HnroId5//30aN25MRkYGR48eLVJv9erVycvLK9JudnZ2KCksbNmyZTRq1Cg03bRpUw4cOEBeXh41atSI6pi1bNmSjh078s4779C7d28++OADevToAcCwYcPo379/xPUiHWfnHP369eP5558vMD+/Z6syKWkREakA2bnZZbqAtrS62jdpX2KZr7/+mpMnT1K/fn2+/vprlixZwuTJk4uUGzhwIDNmzCA9PZ3MzEwaNmwY6l0Id/LkSV566SXS09N57rnn6NWrV5EyjzzyCImJiTzwwAPcfPPNrFy5kiuvvJJf/epX/OhHPyIuLo5du3ZRs2bNYkd57tu3L4MGDWLChAk0a9aM3Nxcvvrqq1JHeU5LSyMjI4NJkybhnOOVV17h6aefLnGdU1FcfIcOHaJevXo0bNiQvXv3smjRIvr06RN1vWXpaTEzLr/88tDxmDdvHoMGDSpSbufOnZx77rnUqVOHL7/8knfffZc777yTxo0bc/DgQT7++GMuueQS3njjjYiDe6alpfHss89y+eWXs2nTptDprp49ezJu3Dg++eQT2rZtyzfffMPOnTtJSEjg008/Zfv27bRu3brISOAVQUmLiEiMJTRJiGl97Zu0L7XOvXv3MnjwYADy8vL4r//6r9C36fyfvo4ZM4YBAwawcOFC2rZtS926dZkzJ/IvnOrVq8dHH31E165dadiwYZEPpI8//pjZs2ezevVq6tevT1paGtOmTWPq1Kls2bKF1NRUwLuY9plnnik2aenQoQPTpk3jiiuu4OTJk9SsWZNHH3201KQlJSWFjIwMunfvDsCtt95Kly5d2L59e5GyAwYMYPbs2VH1KEUbX8+ePenSpQsdO3akTZs2oVMnFWX69Omkp6dz77330qVLF2655RYA1qxZw8yZM5k9ezZbtmzhrrvuwsxwzvGLX/yCzp07A97Ahtdffz3VqlWjcePG/PnPfy7SxtixYxk1ahRJSUkkJyeH9u15553H3LlzGT58OMeOHQNg2rRpXHLJJTz22GP079+fpk2bhspXJCupiy3WunXr5irjN9/DHl8JwPzRqRGnRURibcuWLRG/vQZVXFycBk2UUh0+fJi4uDicc4wbN4527dqVaQDFSO8bM1vrnIt4oyH9ekhEREROyaxZs0I3szt48GDU1zKdKp0eEhGRItTLItGYMGFCmXpWyks9LSIiIhIISlpEREQkEJS0iIiISCDomhYRkRjb88ADHNtSvvFmCquVmEDzu++OaZ0iQaOeFhGRGDu2JYuj5RwkL9zRrKyokqCbb76ZZs2a0alTpwLzc3Nz6devH+3ataNfv358+eWXEddfvHgx7du3p23btjz44INlinHNmjWhW8CXVf4gjFJ2zjnGjx9P27ZtSUpKYt26dRHLXXbZZaGxjVq2bMl1110XWrZs2bLQL4B69+5daptz587ljjvuiNUmlIl6WkREKkDthARaPf1UTOr67KYRUZXLyMjgjjvuYMSIguUffPBB+vbty6RJk3jwwQd58MEHmT59eoEyJ06cYNy4cbzxxhvEx8dz6aWXMnDgQDp06BBV2926daNbt4i31qhQ+be2L2462vWCatGiRWzdupWtW7eSmZnJ2LFjyczMLFLunXfeCT2//vrrQ3fUPXDgALfffjuLFy/moosu4vPPP6+02E+FelpERM4QaWlpNGnSpMj81157jZEjRwIwcuRIXn311SJlVq9eTdu2bWnTpg3nnHMO6enpvPbaa0XKZWRkMGbMGC677DIuueQS/v73vwPet/VrrrkGgPHjx3P//fcD8Prrr5OWlsbJkydZu3YtvXv3pmvXrlx55ZXk5OSUuD3/+te/6N+/P127duWyyy4jy++9ysjI4M477+Tyyy9n4sSJRaY3bNhAz549SUpKYvDgwaGepT59+nD33XfTu3dv/vd//7fYdufOnct1113Htddey8UXX8yMGTN4+OGH6dKlCz179iQ3N7fE+P72t7/Ro0cPunTpwg9/+EP27t0LwH333cfNN99Mnz59aNOmDX/84x9L3P5ovPbaa4wYMQIzo2fPnhw4cKDE/frVV1/x1ltvhXpannvuOYYMGcJFF10EUOydi+fMmcMll1xC7969effdd0Pz9+3bx/XXX8+ll17KpZdeGlq2b98++vXrR0pKCqNHj6ZVq1Z88cUX5d5eJS0iIme4vXv3hsYXatGiRcRv07t27eLCCy8MTcfHx7Nr166I9W3fvp23336bf/zjH4wZM6bAQIHg9ezMnz+ff/7zn4wfP545c+Zw4sQJfvrTn/LSSy+xdu1abr75Zu65554S477tttv4v//7P9auXctDDz3E7bffHlr28ccfs3TpUn7/+98XmR4xYgTTp09n48aNdO7cmalTp4bWO3DgAG+//TZ33XUXM2fODA1xUNimTZt47rnnWL16Nffccw9169Zl/fr1pKam8tRTT5UYX69evVi1ahXr168nPT2d3/72t6F6s7KyeP3111m9ejVTp07l22+/LdL2sGHDQqdywh/57YYry3EDeOWVV+jbty8NGjQI7bcvv/ySPn360LVr14ht5OTkMGXKFN59913eeOMNNm/eHFr2s5/9jAkTJvD+++/zl7/8hVtvvRWAqVOn8p//+Z+sW7eOwYMH8+9//7vYmMoi+H1jIiJSbpGGdIk04i/AjTfeSLVq1WjXrh1t2rQJ9TDkq1u3LrNmzSItLY1HHnmE733ve2zatIlNmzbRr18/wDsdFWmgxnyHDx/mvffeY+jQoaF5+ePeAAwdOrTACND50wcPHuTAgQOhazNGjhxZoI7wkZXHjBlTbPuXX3459evXp379+jRs2JBrr70WgM6dO7Nx48YS49u5cyfDhg0jJyeH48ePc/HFF4fKXH311dSqVYtatWrRrFkz9u7dS3x8fIG2yzLwYFmOG8Dzzz8fSizAO022du1a3nzzTY4cOUJqaio9e/bkkksuCZXJzMykT58+nHfeeYC3Dz/++GMAli5dWiCJOXToEF999RUrVqzglVdeAaB///40btw46m0qSalJi5ldCDwFNAdOAk845/7XzJoA84HWwHbgRudc5Ku7RESkypx//vnk5OTQokULcnJyIp4CiI+PZ8eOHaHpnTt3FjvAYOEPxUgfkh9++CHnnnsuu3fvBrwP144dO7Jy5cqoYj558iSNGjUqdiTkevXqlThdnGjL1apVK/S8WrVqoelq1aqRl5dXYnw//elPufPOOxk4cCDLli3jvvvui1hv9erVycvLK7L+sGHDyM7OLjL/zjvvLHK9UlmO2/79+1m9enUomchfv2nTptSrV4969eqRlpbGBx98UCBpgeIToZMnT7Jy5Urq1KlTYH5FjWsYTU9LHnCXc26dmdUH1prZG0AG8KZz7kEzmwRMAiZWSJQiIgFzNCsr6gtoo6mrdsKpjxw9cOBA5s2bx6RJk5g3b17oIsxwl156KVu3bmXbtm1ccMEFvPDCCzz33HMR61uwYAEjR45k27ZtfPrpp7Rv355Vq1aFln/22Wf8/ve/Z/369QwYMIDrrruOLl26sG/fPlauXElqairffvstH3/8MR07dozYRoMGDbj44otZsGABQ4cOxTnHxo0b+f73v1/itjZs2JDGjRvzzjvvcNlll/H0009H9YuYsiopvoMHD3LBBRcAMG/evDLXXZaeloEDBzJjxgzS09PJzMykYcOGxfZgLViwgGuuuYbatWuH5g0aNIg77riDvLw8jh8/TmZmZpHb8vfo0YOf/exn7N+/nwYNGrBgwYLQcbjiiiuYMWMG//3f/w3Ahg0bSE5OplevXrz44otMnDiRJUuWFPuLtbIqNWlxzuUAOf7zr8xsC3ABMAjo4xebByzjDEtapq+eTlZu7H62mNAkgYndz6hdJCIR1Eo89QQjktoJCVHVOXz4cJYtW8YXX3xBfHw8U6dO5ZZbbmHSpEnceOONPPnkk1x00UUsWLAAgN27d3PrrbeycOFCatSowYwZM7jyyis5ceIEN998c7EJRfv27enduzd79+5l5syZBT4EnXPccsstPPTQQ7Rs2ZInn3ySjIwM3n//fV566SXGjx/PwYMHycvL4+c//3mxbQA8++yzjB07lmnTpvHtt9+Snp5eatICXqIwZswYvvnmG9q0acOcOXMilsu/nqWk00QlKS6+++67j6FDh3LBBRfQs2dPtm3bdkr1R2PAgAEsXLiQtm3bUrdu3QLbOmDAAGbPnh3qeXnhhReYNGlSgfUTExPp378/SUlJVKtWjVtvvbXIT+ZbtGjBfffdR2pqKi1atCAlJYUTJ04A8Mc//pFx48aRlJREXl4eaWlpzJw5kylTpjB8+HDmz59P7969adGiBfXr1y/39lpZunDMrDWwHOgE/Ns51yhs2ZfOuSInrczsNuA2gIsuuqjrZ599Vs6QSzfsca/7cf7o1IjT0Rq1eBTZudm0b9K+3DHl1zOnf+Q3j4gE25YtW0hMTKzqMCpcRkYG11xzDTfccENVhyKnsWPHjlG9enVq1KjBypUrGTt2bMRTaZHeN2a21jkX8ffzUV+Ia2ZxwF+AnzvnDpV0oU8459wTwBMA3bp1q5iTXBUoVonGqMWjYhCNiIjI6e/f//43N954IydPnuScc85h1qxZMak3qqTFzGriJSzPOude9mfvNbMWzrkcM2sBnN53pBERkXKbO3duVYcgAdCuXTvWr18f83pLvU+LeV0qTwJbnHMPhy36KzDSfz4SKHoXIhGRs0hF/WJC5Ex0Ku+XaG4u9wPgJuA/zWyD/xgAPAj0M7OtQD9/WkTkrFS7dm3279+vxEUkCs459u/fX+Ai7mhE8+uhFUBxF7D0LVNrIiJnqPj4eHbu3Mm+ffuqOhSRQKhdu3aRG+uVRnfEFRGJgZo1axa486mIxJ7GHhIREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEM7u+7QsmgR7Pix+ue39rtxV5b/hb3ZudswGTkxoksDE7hNjUpeIiEgQnN1Jy54PvUfzzsWXOf51yYlNlBKaJJS7jnzZudkxq0tERCQozu6kBbyEZdQ/Ii9bPMpLWGIwlEgse0Vi1VsjIiISJLqmRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCYQaVR1AZdmcc4hhj68EoEPLBky5tmMVRyQiIiJlcVYkLR1aNgg935xzqAojERERkVN1ViQt4b0q+b0tIiIiEiy6pkVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCGfFgIkiFWnPAw9wbEtWlbVfKzGB5nffXWXti4hUFvW0iJTTsS1ZHM2qmqTlaFZWlSZMIiKVST0tIjFQOyGBVk8/VentfnbTiEpvU0SkqqinRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEQqlJi5n92cw+N7NNYfPuM7NdZrbBfwyo2DBFRETkbBdNT8tcoH+E+Y8455L9x8LYhiUiIiJSUKkDJjrnlptZ60qIJWb21JjP0Wo7GLW4QZFl2885BOAts73ezMWjItaTnZtNe4A9H8Kcq0tvuHlnuOrBU4xaRERESlKea1ruMLON/umjxsUVMrPbzGyNma3Zt29fOZqL3tFqOzhqO8pdT/sm7Umo28JLRkqz50PvISIiIhWi1J6WYvwJ+H+A8//+Hrg5UkHn3BPAEwDdunVzp9hemdV2FzKn/5wi84c9vhKAOf1Tv+s9iVCuzKLpiREREZFTdko9Lc65vc65E865k8AsoHtswxIREREp6JSSFjNrETY5GNhUXFkRERGRWCj19JCZPQ/0AZqa2U5gCtDHzJLxTg9tB0ZXXIgiIiIi0f16aHiE2U9WQCwiIiIixdIdcUVERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEginOmCiFLJn6Rcc+/w4vDWi/JXlfgrHvy52cTrHAfjs913gnHrQpA0AtRITaH733eVvX0RE5DSkpCVGjn1+nKOfH6d28xhUdvxr73FOvdLL+Y5mZcWgYRERkdOXkpYYqt3sHFo9/VT5K5pztfd31D8iLr5v8SivWM7nfrmn+OymGPTwiIiInMZ0TYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEM6YAROn/u0jNu8+BMA3Lo+6tc6YTYsoOzebUXbcm1g8ivRcb5Tn/MEUo5XQJIGJ3SfGOjwREZGYO2M+2TfvPsTmnEN0aNGAurVqUPec6lUdUoVJaJLgPdnzYbnqyc7NjkE0IiIileOMSVoAOrRowPzRqYxa3KCqQ6lQoZ6ROVd7f/vP4bNnR3iz+s+Jup5RZeyVERERqUq6pkVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCGfUgImxMPVvH7F596HQdIeWDZhybccqjCh6R7Oy+OymEVGXT8/NAggNtlgetRITaH733eWu51TseeABjm3JqpK2wdvvtRMSqqx9EZGzhZKWQjbvPsTmnEN0aNGAzTmHSl/hNFErseo+NI9mVV3CAHBsS1aVJg61ExKqdP+LiJwtlLRE0KFFA+aPTmXY4yurOpSonUovx32LRwEwp/+ccrVdlt6dilI7IYFWTz9V1WGIiEgF0jUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUA4YwZM7L/sOZrv28FnKxqQnuuNOvzZs0UH8svwR27+bEUD2LPbm/nWiIjLC5QtxdHPj1O70bcw5+qSCzbvDFc9WGp9QXM0K6vKBk6syhGeRUSk8pwxSUvzfTtovu/f0KJTlbRfO74xtRp9W3KhPR9WTjCVrFZi1SYMtRMSqjwGERGpeGdM0gKw57yL6PL0U9y3eBQAc/rPKVLmfx5fCcD80anf9YqMeiri8gJlY6G0XpiAan733VUdgoiInAV0TYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCYRSkxYz+7OZfW5mm8LmNTGzN8xsq/+3ccWGKSIiIme7aHpa5gL9C82bBLzpnGsHvOlPi4iIiFSYUgdMdM4tN7PWhWYPAvr4z+cBy4CJsQysIm3OOcSwx1cyef9BAO73B0bMX9ahRYOqCi2wpq+eTlZuVkzqSmiSwMTugXk5iYhIJTnVUZ7Pd87lADjncsysWXEFzew24DaAiy666BSbi50OLUtOSDq0aFBqGSkqKzeL7Nxs2jdpX656snOzYxSRiIicaU41aYmac+4J4AmAbt26uYpurzRTru343cSchgDMH5VaRdGcWdo3ac+c/nPKVceoxaNiFI2IiJxpTvXXQ3vNrAWA//fz2IUkIiIiUtSpJi1/BUb6z0cCr8UmHBEREZHIovnJ8/PASqC9me00s1uAB4F+ZrYV6OdPi4iIiFSYaH49NLyYRX1jHIuIiIhIsXRHXBEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBEKFD5hYJXI/heNfw5yrSy6350No3rlyYgpvM5ZxRVNf885wlW5afKY6mpXFZzeNqLL2ayUm0Pzuu6usfRE5e5yZScvxr71HzVLKNe9cuUlLtG1FG1c0ZfZ8GF2bEki1EhOqtP2jWVlV2r6InF3OzKQF4Jx6kPGPqo6ioFj3dkRTX2m9MBJoVd3DUZU9PCJy9tE1LSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAOHMHTIyRzTmHGPb4ytB0h5YNmHJtxyqMKLayc7MZtXhUTOpp36R9DCISERGJTElLCTq0bFBgenPOoSqKpGIkNEmIWV3tm7SPaX0iIiKFKWkpQeEelfAelzPBxO4TqzoEERGRqOmaFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEgg1KjqAOQ0sWgS7Pmw9HLNO8NVD1ZoKNm52YxaPKpC2yirhCYJTOw+sarDEBE5qylpEc+eD71H884ll6lgCU0SKryNssrOza7qEEREBCUtEq55Zxj1j+KXz7m6wkM4HXszTrdeHxGRs5WuaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAKNcdcc1sO/AVcALIc851i0VQIiIiIoXF4jb+lzvnvohBPSIiIiLF0ukhERERCYTy9rQ4YImZOeBx59wTMYhJgm7RpOhGhG7eGa56sOLjkQp1NCuLz24aUWXt10pMoPndd1dZ+1I19jzwAMe2ZFVZ+3rdVY3yJi0/cM7tNrNmwBtmluWcWx5ewMxuA24DuOiii8rZnATCng+9R/POJZeRwKuVmFCl7R/NqroPLalax7ZkcTQri9oJlf8a1Ouu6pQraXHO7fb/fm5mrwDdgeWFyjwBPAHQrVs3V572JECad4ZR/yh++ZyrKy8WqTBV/U2zKnt4pOrVTkig1dNPVXq7et1VnVO+psXM6plZ/fznwBXAplgFJiIiIhKuPD0t5wOvmFl+Pc855xbHJCoRERGRQk45aXHOfQp8P4axiIiIiBRLP3kWERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQCjvKM9nnc05hxj2+MqIyzq0bMCUaztWckQiZ7ejWVlVNoBdrcSEKh80UuRsoqSlDDq0bFDsss05hyoxEhEBL2moKkezsqqsbZGzlZKWMiipF6W43hcRqThV2ctRVb07ImczXdMiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQNmHg22PMhzLm69DLNO1dOPFJu01dPJys3dqMMJzRJYGL3iTGrT0SkIihpOdNFm4g076ykJUCycrPIzs2mfZP25a4rOzc7BhGJiFQ8JS1nuqserOoIpIK0b9KeOf3nlLueUYtHxSAaEZGKp2taREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgpEVEREQCQUmLiIiIBIKSFhEREQkEJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIiIiIoGgARMrwNS/fcTm3YcKzOvQsgFTru1YRRHF0J4PYc7VpZeJ1YjRiyZ59ZWmeecKHRwyOzc7ZgMLJjRJYGL3iTGp60w1ffV0snKzYlJXRe7vo1lZfHbTiAqpOwhqJSbQ/O67qzoMOYsoaakAm3cfYnPOITq0aOBN5xwqZY2AiDYRad45dknLng9LT4KiSWrKIaFJQszqys7NjlldZ7Ks3Cyyc7Np36R9ueqpyP1dKzF2r4sgOpoVm6RSpCyUtFSQDi0aMH90KgDDHl9ZxdHESAX2ZJSoeWcY9Y/il5fW81NOsfyWHqvemrNB+ybtmdN/TrnqqMj9fbb3MJzNPUxSdXRNi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQlLSIiIhIIChpERERkUBQ0iIiIiKBoKRFREREAkFJi4iIiASCkhYREREJBCUtIiIiEghKWkRERCQQNGBiJdmcc6jAwIkdWjZgyrUdmfq3j9i8u/hRoPPLnZH2fFj6YIeljfBcFosmRTcidPPOVTc4ZIBNXz2drNzYjPwbixGew+uK1cCJCU0SYjqAZtAdzcqqsoETj2ZlUTuh6kbarsptPx3USkyokkFDlbRUgg4tGxSY3pzzXZKyefchNuccokOLBoVXK1DujBNtItK8c+ySlj0flp4ERZPUSERZuVkxSzbaN2lPQpPyfyDFoo582bnZMavrTFArseoSBoDaCQlVFkNVb3tVO5oVmy8np0JJSyUo3FMS3uMC0KFFA+aPTi2yXuFyZ5Sq6slo3hlG/aP45aX1/EiJ2jdpz5z+c6o6jJBY9orEqrfmTFEV37JPF2fztgNV2sOka1pEREQkEJS0iIiISCAoaREREZFAUNIiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhIISlpEREQkEJS0iIiISCCUK2kxs/5mlm1mn5jZpFgFJSIiIlLYKSctZlYdeBS4CugADDezDrEKTERERCRceQZM7A584pz7FMDMXgAGAZtjEVgQbc45xLDHVxY7avOplpUo7Pmw9MEOSxvhuZJk52aXe/C9WI2mHF7f6RaTiEhh5pw7tRXNbgD6O+du9advAno45+4oVO424DZ/sj1QUeO7NwW+qKC6pex0PE4/OianFx2P04uOx+mjlXPuvEgLytPTYhHmFcmAnHNPAE+Uo53ogjFb45zrVtHtSHR0PE4/OianFx2P04uORzCU50LcncCFYdPxwO7yhSMiIiISWXmSlveBdmZ2sZmdA6QDf41NWCIiIiIFnfLpIedcnpndAbwOVAf+7Jz7KGaRlV2Fn4KSMtHxOP3omJxedDxOLzoeAXDKF+KKiIiIVCbdEVdEREQCQUmLiIiIBELgkpbShg4wzx/95RvNLKUq4jxbRHE8+pjZQTPb4D8mV0WcZwsz+7OZfW5mm4pZrvdHJYrieOj9UYnM7EIz+6eZbTGzj8zsZxHK6D1yGgtU0hLl0AFXAe38x23Anyo1yLNIGYZyeMc5l+w/7q/UIM8+c4H+JSzX+6NyzaXk4wF6f1SmPOAu51wi0BMYp8+QYAlU0kLY0AHOueNA/tAB4QYBTznPKqCRmbWo7EDPEtEcD6lEzrnlQG4JRfT+qERRHA+pRM65HOfcOv/5V8AW4IJCxfQeOY0FLWm5ANgRNr2Toi+4aMpIbES7r1PN7AMzW2RmHSsnNCmG3h+nH70/qoCZtQa6AJmFFuk9chorz238q0I0QwdENbyAxEQ0+3od3jgSh81sAPAqXrerVA29P04ven9UATOLA/4C/Nw5d6jw4gir6D1ymghaT0s0QwdoeIHKU+q+ds4dcs4d9p8vBGqaWdPKC1EK0fvjNKL3R+Uzs5p4CcuzzrmXIxTRe+Q0FrSkJZqhA/4KjPCvAO8JHHTO5VR2oGeJUo+HmTU3M/Ofd8d7ze2v9Egln94fpxG9PyqXv6+fBLY45x4uppjeI6exQJ0eKm7oADMb4y+fCSwEBgCfAN8Ao6oq3jNdlMfjBmCsmeUBR4B0p9swVxgzex7oAzQ1s53AFKAm6P1RFaI4Hnp/VK4fADcBH5rZBn/e3cBFoPdIEOg2/iIiIhIIQTs9JCIiImcpJS0iIiISCEpaREREJBCUtIiIiEggKGkRERGRQFDSIoFjZoPNzJlZQjnryTCzGRVV3l/n7rJHFltm1trM/quq4yiOmd1nZr+o6jiiZWb3m9kPT3HdZP/Ot2UqZ2YDI42ifgrttzazI2E/9y28/JSPhZl9zx+p+nC5ghQpgZIWCaLhwAq8m9md7qo8aQFaAxGTFjMLxL2aTpc4zay6c26yc27pKVaRjHcPkDKVc8791Tn34Cm2Wdi/nHPJMaorxDlXIfWKhFPSIoHijxnyA+AWwpIWM+tjZsvM7CUzyzKzZ8PuNDrAn7fCzP5oZn+PUO95ZvYXM3vff/ygmBAuNLPFZpZtZlPC1v+xma32v2k+bmbVzexBoI4/71kz+x8zG++Xf8TM3vKf9zWzZ/znV5jZSjNbZ2YL/O3FzLqa2dtmttbMXjd/1Fl/m6f7bX9sZpdFiPlB4DI/jgl+j9ECM/sbsMTfd6F9YmYzzCyjpHYL7btrzSzTzNab2VIzO9+ff5+Z/dmP8dP8bfeX3ePvw6VA+0g72szmmtnDZvZPYLr/TX6xH8s7+T1tZna+mb1i3qCDH5jZf/jz7zSzTf7j58Ucz/D2+vrb8KEfdy1//nYzm2xmK4Chflw3lPW4mHfX6PuBYf6xGGZm3c3sPb/d98ysfTHlQr18ZtbKzN40s43+34vC9tcf/Xo+zY8xiu2OeCxK2N/fM7NV5r1P7jf1rEhlcs7poUdgHsCPgSf95+8BKf7zPsBBvHFCqgErgV5AbbwRWy/2yz0P/N1/ngHM8J8/B/Tyn1+Ed5vvwm1nADnAuUAdYBPQDUgE/gbU9Ms9Bozwnx8OW78nsMB//g6wGu/uqFOA0UBTYDlQzy8zEZjsl3kPOM+fPwzv7sMAy4Df+88HAEsjxN0nf5vDtmMn0KSY5TP8MsW2W6j+xnx3o8pbw+K5z1+/lr9t+/06uwIfAnWBBnh3Hv1FhHrnAn8HqvvTbwLt/Oc9gLf85/PxBr4D787MDcPaqAfEAR8BXUp4XeW/Ti7xp58Kq3M78D+F4rrhVI4LYa85f7oBUMN//kPgL8WUC03jvdZG+s9vBl4Ni2sB3uu/A/BJhO1sDWwKmy72WJSwv/8ODPefjyHsNV74Na+HHrF+nBZdriJlMBz4g//8BX96nT+92jm3E8C8c/atgcPAp865bX6Z54HbItT7Q6CDWWiA1wZmVt8591Whcm845/b7bbyMlxjl4f3zf99fvw7weYQ21gJdzaw+cMyPuxtwGTAeL6npALzr13MOXvLVHugEvOHPr46XPOV7Oaz+1hHajeQN51xuKWVKazdfPDDf72U4B9gWtuwfzrljwDEz+xw4H297X3HOfQNgZoXHDwu3wDl3wrwep/8AFoQdo1r+3/8ERgA4504AB82sl9/G134bL/vtri9hW7c55z72p+cB4/jutTa/mHXKe1waAvPMrB3eSMI1iykXLhUY4j9/Gvht2LJXnXMngc35PV6liHgsStnfqcB1/vPngIeiaEckJpS0SGCY2bl4H1CdzMzhfUg4M/sfv8ixsOIn8F7fkYaZj6QakOqcO1JKucLjXji/jXnOuV+WuKJz35rZdryxTN4DNgKXA98Dtvh/33DODQ9fz8w6Ax8551KLqTp/u/O3ORpfhz3Po+Cp4tr5TZfSbr7/Ax52zv3VzPrg9bAUjq1wfNGOH5IfZzXggIv+moloj3u05b+OMK+0/RPNcfl/wD+dc4PNrDVeD01Zhe/L8P0d7T6IdCzKur9FKoWuaZEguQF4yjnXyjnX2jl3Id63+l4lrJMFtPE/EMDrwo9kCXBH/oSZJRdTrp+ZNTGzOnjfNt/F60a/wcya+es2MbNWfvlvzSz82/Ny4Bf+33fwutc3OOccsAr4gZm19eupa2aXANnAeWaW6s+vaWYdS9jmwr4C6pew/DO8XqZaZtYQ6OvPj7bdhsAu//nIKOJZDgw2szp+r9O1pa3gnDsEbDOzoX4sZmbf9xe/CYz151c3swZ+G9f5+7AeMBhvfxcnC2idv+/xBtV7u5SwTuW4FD4W4fsuo4Ry4d7ju+u5foR3UfqpingsStnfq4Dr/edBuBheziBKWiRIhgOvFJr3F4r5ZQyA33NyO7DYv5ByL961L4WNB7r5FzduxksmIlmB1yW/Ae/6gzXOuc3AvXgXtW4E3gDyL1h9AthoZs/60+/4y1Y65/YCR/15OOf24X1wPe/XswpIcM4dx0vYppvZB37b/1HcNkewEcgz7yLVCYUXOud2AC/65Z7FP4VShnbvwzuN8A7wRWnBOOfW4Z1u2YB3/EpKJsL9CLjFj+UjYJA//2fA5Wb2Id6pmI5+G3PxrhvKBGY759ZD6NRh4ZiO4vWALfDrOQnMLGU7TuW4/BMvQdxgZsPwTu38xszexes5LK5cuPHAKP81cpO//aeklGNR3P7+OXCnma3Gey1Hej+JVAiN8ixnPDOLc84dNu/k/KPAVufcI1Udl0hl83sc/+6c61SOOuoCR5xzzszS8S7KHRS2/LBzLq780YoUpZ4WORv8xP92/RFed/zjVRuOSJU5ATSM1NtUBl2BDX5Pz+3AXfDdzeXwejNFKoR6WkRERCQQ1NMiIiIigaCkRURERAJBSYuIiIgEgpIWERERCQQlLSIiIhII/x/uh2OGAFZPwAAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "corner_4cam_positions = all_cam_positions[(0,4,5,10),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "corner_4cam_directions = [[-1, +1.9, -1],\n", + " [+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [+1, -1.9, -1],\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner_4cam_positions\n", + "camera_directions = corner_4cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1232\n", + "Feature in image counts: Counter({2: 776, 3: 308, 4: 148})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1232 features\n", + "image 0 reprojection errors: average:15.484589788583829 max: 80.78509801983431\n", + "image 1 reprojection errors: average:15.722812572576329 max: 121.31577374715337\n", + "image 2 reprojection errors: average:15.489355196558432 max: 135.22456030605278\n", + "image 3 reprojection errors: average:14.998362169162379 max: 88.51649209633774\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 5.4089e+05 9.35e+05 \n", + " 1 2 9.7842e+02 5.40e+05 6.12e+01 3.66e+04 \n", + " 2 3 7.7984e+02 1.99e+02 5.03e-01 2.17e+02 \n", + " 3 4 7.7811e+02 1.73e+00 2.99e-01 7.92e+01 \n", + " 4 5 7.7788e+02 2.30e-01 3.43e-02 3.91e+01 \n", + " 5 6 7.7786e+02 2.51e-02 5.68e-03 8.08e+00 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 6, initial cost 5.4089e+05, final cost 7.7786e+02, first-order optimality 8.08e+00.\n", + "mean reprojection error: 0.583563452282779\n", + "max reprojection error: 2.537971323870369\n", + "mean reconstruction error: 0.11113313400329004\n", + "max reconstruction error: 0.5017896436030329\n" + ] + }, + { + "ename": "KeyError", + "evalue": "'722-4'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mfitter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msetup_led_simulation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mled_positions_8a\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msmeared_feature_locations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfocal_length\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprinciple_point\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mradial_distortion\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mposition_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_led_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfitter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_positions_8a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m 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4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_mpmt_centre_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n\u001b[0m\u001b[1;32m 3\u001b[0m for k in mpmt_positions.keys()}\n\u001b[1;32m 4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m 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reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n\u001b[0m\u001b[1;32m 3\u001b[0m for k in mpmt_positions.keys()}\n\u001b[1;32m 4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: '722-4'" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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kqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6M1XASbJPkguTrEryqgnTt07y8STnJrkgySGLX1VJkqTpzBtwkiwDjgT2BXYDDkyy21ixlwDfqKo9gL2BtyXZdJHrKkmSNJVpenAeCKyqqouq6rfAccD+Y2UKuF2SAFsClwPXLGpNJUmSpjRNwNkeuGRkeHUbN+oI4D7ApcDXgZdV1XXjM0pyaJKVSVauWbNmLassSZI0t2kCTiaMq7HhxwPnAHcF9gSOSLLVTV5UdXRVraiqFcuXL19gVSVJkqYzTcBZDew4MrwDQ0/NqEOAE2uwCrgYuPfiVFGSJGlhpgk4ZwG7JtmlnTh8AHDSWJkfAI8GSHIn4F7ARYtZUUmSpGltPF+BqromyUuBU4BlwDFVdUGSF7XpRwFvBI5N8nWGQ1qHV9Vl67DekiRJs5o34ABU1SeAT4yNO2rk+aXA4xa3apIkSWvHKxlLkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3Zkq4CTZJ8mFSVYledUsZfZOck6SC5KcurjVlCRJmt7G8xVIsgw4EngssBo4K8lJVfWNkTLbAO8C9qmqHyS54zqqryRJ0rym6cF5ILCqqi6qqt8CxwH7j5V5BnBiVf0AoKp+urjVlCRJmt40AWd74JKR4dVt3Kh7Atsm+XySs5McNGlGSQ5NsjLJyjVr1qxdjSVJkuYxTcDJhHE1NrwxsBfwh8Djgb9Ics+bvKjq6KpaUVUrli9fvuDKSpIkTWPec3AYemx2HBneAbh0QpnLquoq4KokpwF7AN9elFpKkiQtwDQ9OGcBuybZJcmmwAHASWNl/h14RJKNk2wOPAj45uJWVZIkaTrz9uBU1TVJXgqcAiwDjqmqC5K8qE0/qqq+meRTwHnAdcB7qur8dVlxSZKk2aRq/HSapbFixYpauXLlelm2JEm6ZUhydlWtWOjrvJKxJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTtTBZwk+yS5MMmqJK+ao9wDklyb5KmLV0VJkqSFmTfgJFkGHAnsC+wGHJhkt1nKvRk4ZbErKUmStBDT9OA8EFhVVRdV1W+B44D9J5T7E+AE4KeLWD9JkqQFmybgbA9cMjK8uo27XpLtgScDR801oySHJlmZZOWaNWsWWldJkqSpTBNwMmFcjQ2/Azi8qq6da0ZVdXRVraiqFcuXL5+yipIkSQuz8RRlVgM7jgzvAFw6VmYFcFwSgDsA+yW5pqo+thiVlCRJWohpAs5ZwK5JdgF+CBwAPGO0QFXtMvM8ybHAyYYbSZK0vswbcKrqmiQvZfjvqGXAMVV1QZIXtelznncjSZK01KbpwaGqPgF8YmzcxGBTVQff/GpJkiStPa9kLEmSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHVnqoCTZJ8kFyZZleRVE6Y/M8l57XFGkj0Wv6qSJEnTmTfgJFkGHAnsC+wGHJhkt7FiFwN/UFX3A94IHL3YFZUkSZrWND04DwRWVdVFVfVb4Dhg/9ECVXVGVf28DZ4J7LC41ZQkSZreNAFne+CSkeHVbdxsngd8ctKEJIcmWZlk5Zo1a6avpSRJ0gJME3AyYVxNLJg8kiHgHD5pelUdXVUrqmrF8uXLp6+lJEnSAmw8RZnVwI4jwzsAl44XSnI/4D3AvlX1s8WpniRJ0sJN04NzFrBrkl2SbAocAJw0WiDJ3YATgWdX1bcXv5qSJEnTm7cHp6quSfJS4BRgGXBMVV2Q5EVt+lHA64DbA+9KAnBNVa1Yd9WWJEmaXaomnk6zzq1YsaJWrly5XpYtSZJuGZKcvTadJl7JWJIkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4EiSpO4YcCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5IkdceAI0mSumPAkSRJ3THgSJKk7hhwJElSdww4kiSpOwYcSZLUHQOOJEnqjgFHkiR1x4AjSZK6Y8CRJEndMeBIkqTuGHAkSVJ3DDiSJKk7BhxJktQdA44kSerOVAEnyT5JLkyyKsmrJkxPkne26ecluf/iV1WSJGk68wacJMuAI4F9gd2AA5PsNlZsX2DX9jgU+MdFrqckSdLUpunBeSCwqqouqqrfAscB+4+V2R94Xw3OBLZJcpdFrqskSdJUNp6izPbAJSPDq4EHTVFme+BHo4WSHMrQwwPwmyTnL6i2Wmp3AC5b35XQnGyjDZvts+GzjTZ891qbF00TcDJhXK1FGarqaOBogCQrq2rFFMvXemIbbfhsow2b7bPhs402fElWrs3rpjlEtRrYcWR4B+DStSgjSZK0JKYJOGcBuybZJcmmwAHASWNlTgIOav9N9WDgF1X1o/EZSZIkLYV5D1FV1TVJXgqcAiwDjqmqC5K8qE0/CvgEsB+wCvgVcMgUyz56rWutpWIbbfhsow2b7bPhs402fGvVRqm6yakykiRJt2heyViSJHXHgCNJkrqzzgOOt3nY8E3RRs9sbXNekjOS7LE+6nlrNV/7jJR7QJJrkzx1Keun6dooyd5JzklyQZJTl7qOt3ZTfM5tneTjSc5tbTTNuaRaJEmOSfLT2a6Pt1ZZoarW2YPhpOTvAr8DbAqcC+w2VmY/4JMM19J5MPDldVknH2vVRg8Ftm3P97WNNqz2GSn3nwwn/D91fdf71vSY8j20DfAN4G5t+I7ru963pseUbfQa4M3t+XLgcmDT9V33W8sD+H3g/sD5s0xfcFZY1z043uZhwzdvG1XVGVX18zZ4JsN1jrQ0pnkPAfwJcALw06WsnIDp2ugZwIlV9QOAqrKdltY0bVTA7ZIE2JIh4FyztNW89aqq0xi2+WwWnBXWdcCZ7RYOCy2jdWeh2/95DClaS2Pe9kmyPfBk4KglrJduMM176J7Atkk+n+TsJActWe0E07XREcB9GC5S+3XgZVV13dJUT1NYcFaY5lYNN8ei3eZB68zU2z/JIxkCzsPXaY00apr2eQdweFVdO/z41BKbpo02BvYCHg1sBnwpyZlV9e11XTkB07XR44FzgEcBdwc+k+QLVfXf67hums6Cs8K6Djje5mHDN9X2T3I/4D3AvlX1syWqm6ZrnxXAcS3c3AHYL8k1VfWxJamhpv2cu6yqrgKuSnIasAdgwFka07TRIcCbajjhY1WSi4F7A19ZmipqHgvOCuv6EJW3edjwzdtGSe4GnAg821+cS27e9qmqXapq56raGfg34MWGmyU1zefcvwOPSLJxks2BBwHfXOJ63ppN00Y/YOhhI8mdGO5gfdGS1lJzWXBWWKc9OLXubvOgRTJlG70OuD3wrtZLcE15990lMWX7aD2apo2q6ptJPgWcB1wHvKeqJv47rBbflO+jNwLHJvk6w+GQw6vqsvVW6VuZJB8C9gbukGQ18JfAJrD2WcFbNUiSpO54JWNJktQdA44kSeqOAUeSJHXHgCNJkrpjwJEkSd0x4OgWLcmTk1SSe9/M+Ryc5Ih1Vb695jULr9niSrJzkmes73rMJsnrk7xifddjWknekOQxa/naPZPst9BySZ44113lF7D8nZNcneScWaavdVskuXu7c/qVN6uS0s1gwNEt3YHA6QwX7trQrfeAA+zMcOPHm0iyrq9svig2lHomWVZVr6uqz67lLPZkuK7HgspV1UlV9aa1XOa471bVnos0r+tV1TqZr7QQBhzdYiXZEngYw/2xDhgZv3e7qeG/JflWkg+0OwSTZL827vQk70xy8oT5Lk9yQpKz2uNhs1RhxySfSnJhkr8cef2zknyl/YJ9d5JlSd4EbNbGfSDJK5Mc1sq/Pcl/tuePTvL+9vxxSb6U5KtJjm/rS5K9kpya4aaNp6TdUbet85vbsr+d5BET6vwmhivqnpPkT1tP1PFJPg58um2767dJkiOSHDzXcse23ROSfDnJ15J8tl0RdqY34JhWx4tm1r1N+/O2DT/LcPXYm0hybJK/S/JfwJtbD8GnWl2+MNODl+ROST6a5Nz2eGgb/3+SnN8eL5+lPUeX9+i2Dl9v9b5NG/+9JK9LcjrwtFavpy60XTJcTfcNwNNbWzw9yQOTnNGWe0aSe81S7vrewyQ7JflckvPa37uNbK93tvlcNFPHKdZ7YlvMsb3vnuTMDO+TN8QeG21IqsqHj1vkA3gW8M/t+RnA/dvzvYFfMNyrZCPgSww3CL0tw91od2nlPgSc3J4fDBzRnn8QeHh7fjfgmxOWfTDwI4YrPG8GnM9wT6j7AB8HNmnl3gUc1J5fOfL6BwPHt+dfYLjfzSYMV+98IcM9pU4DtmhlDme4ovQmbV2Xt/FPZ7gqK8Dngbe15/sBn51Q771n1nlkPVYD280y/YhWZtbljs1/W264gOjzR+rz+vb627R1+1mb514Md27eHNiK4Sqlr5gw32OBk4FlbfhzwK7t+YOA/2zPPwy8vD1fBmw9sowtgC2BC4Dfm2O/mtlP7tmG3zcyz+8Brxyr11PXpl0Y2efa8FbAxu35Y4ATZil3/TDDvvac9vy5wMdG6nU8w/6/G7BqwnruDJw/MjxrW8yxvU8GDmzPX8TIPj6+z/vwsdSPDaKrV1pLBzLcSRvguDb81Tb8lapaDZDhHIOdgSuBi6rq4lbmQ8ChE+b7GGC33HBn7q2S3K6qfjlW7jPVbjya5ESGEHUNwxfFWe31mwE/nbCMs4G9ktwO+E2r9wrgEcBhDAFoN+CLbT6bMgS1ewH3ZbjTMQxf4qP3YzlxZP47T1juJJ+pqsvnKTPfcmfsAHy49V5sClw8Mu0/quo3wG+S/BS4E8P6frSqfgWQZPz+QKOOr+GO6VsCDwWOH2mj27S/jwIOAqiqa4FfJHl4W8ZVbRkntuV+bY51vbhuuO/ae4GXcMO+9uFZXnNz22Vr4L1JdmW4S/Ims5Qb9RDgj9rzfwXeMjLtY1V1HfCNmZ60eUxsi3m290OAJ7XnHwTeOsVypCVhwNEtUpLbM3yZ3TdJMXyhVJJXtiK/GSl+LcO+HqazEfCQqrp6nnLj9zmptoz3VtWr53xh1f8k+R7D/VTOYLhH0SOBuzPchPHuDMHjwNHXJfld4IKqesgss55Z75l1nsZVI8+v4caHrm87s+h5ljvjH4C/q6qTkuzN0HMzXrfx+k17v5iZem4EXFHTn+MxbbtPW/6qCePm2z7TtMsbgf+qqicn2Zmh52ehRrfl6PaedhtMaouFbm9pg+A5OLqleirwvqraqYY7ae/I0Fvw8Dle8y3gd9qXBwyHESb5NPDSmYEke85S7rFJtkuyGcOv2C8ydOU/Nckd22u3S7JTK/8/SUZ/lZ8GvKL9/QJDF/85VVXAmcDDktyjzWfzJPcELgSWJ3lIG79Jkt3nWOdxvwRuN8f07zP0Xt0myda0uysvYLlbAz9sz58zRX1OA56cZLPWm/WE+V5QVf8NXJzkaa0uSbJHm/w54H+38cuSbNWW8aS2DbcAnsywvWfzLWDnmW0PPBs4dZ5qrU27jLfF6LY7eI5yo87ghvPPnslwwv3amtgW82zvM4GntOe3hBP9dStiwNEt1YHAR8fGncAs/yEE0HpkXgx8qp0k+hOGc3XGHQasaCdufoMheExyOsNhgXMYzpdYWVXfAF7LcMLuecBngJmTcY8GzkvygTb8hTbtS1X1E+DXbRxVtYbhS+5DbT5nAveuqt8yhLs3Jzm3Lfuhs63zBOcB12Q4AfdPxydW1SXAR1q5D9AO4yxgua9nOJTxBWDeOzFX1VcZDvmcw9B+cwWPUc8EntfqcgGwfxv/MuCRGe4IfTawe1vGsQznOX2Z4U7eX4PrD1+O1+nXDD1rx7f5XAfMedf2tWyX/2IIk+ckeTrD4aW/TfJFhh7J2cqNOgw4pO0jz27rv1bmaYvZtvfLgf+T5CsM+/Kk95O0Xng3cd2qJNmyqq7McDLBkcB3qurt67te0lJrPZknV9V9b8Y8NgeurqpKcgDDCcf7j0y/sqq2vPm1lRbOHhzd2ryg/Wq/gOGQwLvXb3Wk9eZaYOtJvVgLsBdwTutBejHwZ3DDhf4Yekml9cIeHEmS1B17cCRJUncMOJIkqTsGHEmS1B0DjiRJ6o4BR5Ikdef/AwGKbDVHKfd2AAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [], + "source": [ + "corner6_cam_positions = all_cam_positions[(4,5,6,7,10,11),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [], + "source": [ + "corner6_cam_directions = [[+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [-1, +1.9, +1],\n", + " [+1, +1.9, -1],\n", + " [+1, -1.9, -1],\n", + " [-1, -1.9, -1]]" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner6_cam_positions\n", + "camera_directions = corner6_cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({3: 708, 4: 196, 5: 150, 6: 142, 2: 76})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:15.228950797424705 max: 96.56510070201077\n", + "image 1 reprojection errors: average:15.161782116486421 max: 110.07189736159573\n", + "image 2 reprojection errors: average:15.351520057105907 max: 75.38681862942737\n", + "image 3 reprojection errors: average:15.119166183329087 max: 88.01161094537923\n", + "image 4 reprojection errors: average:15.16365420925013 max: 108.25721626785058\n", + "image 5 reprojection errors: average:15.952563038260042 max: 132.3325093063735\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 8.1236e+05 1.67e+06 \n", + " 1 2 1.9521e+03 8.10e+05 6.15e+01 3.19e+04 \n", + " 2 3 1.7700e+03 1.82e+02 1.08e+00 1.47e+03 \n", + " 3 4 1.7607e+03 9.32e+00 7.25e-01 9.78e+02 \n", + " 4 5 1.7569e+03 3.79e+00 1.50e-01 2.29e+02 \n", + " 5 6 1.7564e+03 5.54e-01 5.07e-02 7.15e+01 \n", + " 6 7 1.7560e+03 3.92e-01 3.91e-02 7.38e+01 \n", + " 7 8 1.7558e+03 2.31e-01 2.14e-02 2.09e+01 \n", + " 8 9 1.7556e+03 1.67e-01 1.86e-02 4.23e+01 \n", + " 9 10 1.7554e+03 1.49e-01 1.50e-02 1.60e+01 \n", + " 10 11 1.7553e+03 1.43e-01 1.66e-02 3.98e+01 \n", + " 11 12 1.7552e+03 1.40e-01 1.45e-02 1.64e+01 \n", + " 12 13 1.7550e+03 1.48e-01 1.78e-02 4.16e+01 \n", + " 13 14 1.7549e+03 1.43e-01 1.46e-02 1.60e+01 \n", + " 14 15 1.7547e+03 1.26e-01 1.53e-02 3.63e+01 \n", + " 15 16 1.7546e+03 9.10e-02 9.35e-03 1.06e+01 \n", + " 16 17 1.7546e+03 8.06e-02 1.13e-02 3.27e+01 \n", + " 17 18 1.7545e+03 7.52e-02 8.12e-03 1.01e+01 \n", + " 18 19 1.7544e+03 7.43e-02 1.08e-02 3.26e+01 \n", + " 19 20 1.7543e+03 7.00e-02 7.56e-03 9.72e+00 \n", + " 20 21 1.7543e+03 6.72e-02 1.01e-02 3.17e+01 \n", + " 21 22 1.7542e+03 6.51e-02 7.18e-03 9.60e+00 \n", + " 22 23 1.7541e+03 6.81e-02 1.05e-02 3.35e+01 \n", + " 23 24 1.7541e+03 6.48e-02 6.94e-03 9.50e+00 \n", + " 24 25 1.7540e+03 6.75e-02 1.07e-02 3.58e+01 \n", + " 25 26 1.7540e+03 6.10e-02 6.23e-03 8.85e+00 \n", + " 26 27 1.7539e+03 5.14e-02 8.34e-03 3.17e+01 \n", + " 27 28 1.7539e+03 4.70e-02 5.01e-03 8.17e+00 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 28, initial cost 8.1236e+05, final cost 1.7539e+03, first-order optimality 8.17e+00.\n", + "mean reprojection error: 0.7532275283608961\n", + "max reprojection error: 2.874303367276662\n", + "mean reconstruction error: 0.09497257101207475\n", + "max reconstruction error: 0.7665663062528056\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:15.342388587823544 max: 122.82865422267562\n", + "image 1 reprojection errors: average:16.043501254204937 max: 73.92372017165924\n", + "image 2 reprojection errors: average:15.267504271251447 max: 127.47606477213417\n", + "image 3 reprojection errors: average:14.914139893754673 max: 87.8431752746019\n", + "image 4 reprojection errors: average:15.583993959967998 max: 72.11001767981946\n", + "image 5 reprojection errors: average:15.532189422979288 max: 103.29708306757799\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 8.1092e+05 1.63e+06 \n", + " 1 2 1.6453e+04 7.94e+05 6.23e+01 5.05e+04 \n", + " 2 3 1.6109e+04 3.43e+02 1.42e+00 2.38e+03 \n", + " 3 4 1.6071e+04 3.83e+01 9.98e-01 1.82e+03 \n", + " 4 5 1.6051e+04 1.96e+01 3.06e-01 4.13e+02 \n", + " 5 6 1.6047e+04 4.90e+00 1.52e-01 2.56e+02 \n", + " 6 7 1.6043e+04 3.72e+00 9.15e-02 1.20e+02 \n", + " 7 8 1.6039e+04 3.36e+00 1.18e-01 1.10e+02 \n", + " 8 9 1.6037e+04 2.85e+00 7.15e-02 9.49e+01 \n", + " 9 10 1.6035e+04 1.63e+00 5.72e-02 7.18e+01 \n", + " 10 11 1.6034e+04 1.47e+00 4.62e-02 9.46e+01 \n", + " 11 12 1.6032e+04 1.37e+00 5.00e-02 6.85e+01 \n", + " 12 13 1.6031e+04 1.26e+00 4.02e-02 9.36e+01 \n", + " 13 14 1.6030e+04 1.22e+00 4.64e-02 6.79e+01 \n", + " 14 15 1.6029e+04 1.17e+00 3.82e-02 9.57e+01 \n", + " 15 16 1.6027e+04 1.17e+00 4.61e-02 6.74e+01 \n", + " 16 17 1.6026e+04 1.13e+00 3.71e-02 9.62e+01 \n", + " 17 18 1.6025e+04 9.69e-01 3.86e-02 5.97e+01 \n", + " 18 19 1.6024e+04 8.62e-01 3.01e-02 8.94e+01 \n", + " 19 20 1.6024e+04 8.42e-01 3.56e-02 6.19e+01 \n", + " 20 21 1.6023e+04 9.72e-01 3.57e-02 1.15e+02 \n", + " 21 22 1.6022e+04 7.08e-01 2.64e-02 4.70e+01 \n", + " 22 23 1.6021e+04 6.34e-01 2.66e-02 1.12e+02 \n", + " 23 24 1.6021e+04 5.97e-01 2.30e-02 4.80e+01 \n", + " 24 25 1.6020e+04 5.65e-01 2.38e-02 1.16e+02 \n", + " 25 26 1.6020e+04 5.60e-01 2.19e-02 4.96e+01 \n", + " 26 27 1.6019e+04 5.51e-01 2.32e-02 1.21e+02 \n", + " 27 28 1.6019e+04 4.09e-01 1.52e-02 3.60e+01 \n", + " 28 29 1.6018e+04 4.01e-01 1.94e-02 1.24e+02 \n", + " 29 30 1.6018e+04 3.80e-01 1.42e-02 3.37e+01 \n", + " 30 31 1.6017e+04 6.49e-01 3.44e-02 2.08e+02 \n", + " 31 32 1.6017e+04 5.15e-01 1.39e-02 2.18e+01 \n", + " 32 33 1.6016e+04 5.22e-01 3.13e-02 2.18e+02 \n", + " 33 34 1.6016e+04 5.07e-01 1.37e-02 2.05e+01 \n", + " 34 35 1.6015e+04 5.20e-01 3.20e-02 2.24e+02 \n", + " 35 36 1.6015e+04 5.07e-01 1.37e-02 1.94e+01 \n", + " 36 37 1.6014e+04 5.27e-01 3.31e-02 2.21e+02 \n", + " 37 38 1.6014e+04 5.11e-01 1.36e-02 1.82e+01 \n", + " 38 39 1.6013e+04 5.12e-01 3.29e-02 2.01e+02 \n", + " 39 40 1.6012e+04 5.01e-01 1.35e-02 1.73e+01 \n", + " 40 41 1.6012e+04 4.52e-01 2.95e-02 1.59e+02 \n", + " 41 42 1.6012e+04 4.53e-01 1.30e-02 1.79e+01 \n", + " 42 43 1.6011e+04 3.56e-01 2.30e-02 1.16e+02 \n", + " 43 44 1.6011e+04 3.80e-01 1.22e-02 2.19e+01 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 44 45 1.6010e+04 3.75e-01 2.36e-02 1.06e+02 \n", + " 45 46 1.6010e+04 3.69e-01 1.21e-02 2.11e+01 \n", + " 46 47 1.6010e+04 3.63e-01 2.32e-02 9.98e+01 \n", + " 47 48 1.6009e+04 3.58e-01 1.20e-02 2.05e+01 \n", + " 48 49 1.6009e+04 2.20e-01 1.34e-02 8.28e+01 \n", + " 49 50 1.6009e+04 2.57e-01 9.48e-03 3.50e+01 \n", + " 50 51 1.6009e+04 7.86e-02 2.90e-03 2.75e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 51, initial cost 8.1092e+05, final cost 1.6009e+04, first-order optimality 2.75e+01.\n", + "mean reprojection error: 2.276982408561192\n", + "max reprojection error: 8.649836025999104\n", + "mean reconstruction error: 0.2770247716168649\n", + "max reconstruction error: 1.386933879465432\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:16.128661171613665 max: 121.59067154442349\n", + "image 1 reprojection errors: average:16.46941187769987 max: 161.50799121580602\n", + "image 2 reprojection errors: average:15.988559689698846 max: 150.5470813926093\n", + "image 3 reprojection errors: average:16.175963348253234 max: 86.65889914788417\n", + "image 4 reprojection errors: average:15.978697552851306 max: 93.62267081654385\n", + "image 5 reprojection errors: average:16.442678519909204 max: 133.47778854921245\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 9.2394e+05 1.27e+06 \n", + " 1 2 4.4401e+04 8.80e+05 6.41e+01 6.93e+04 \n", + " 2 3 4.3756e+04 6.45e+02 1.50e+00 3.52e+03 \n", + " 3 4 4.3672e+04 8.38e+01 1.53e+00 2.19e+03 \n", + " 4 5 4.3631e+04 4.14e+01 3.62e-01 4.37e+02 \n", + " 5 6 4.3622e+04 8.89e+00 1.95e-01 1.93e+02 \n", + " 6 7 4.3615e+04 7.14e+00 1.16e-01 1.84e+02 \n", + " 7 8 4.3610e+04 4.32e+00 9.61e-02 8.39e+01 \n", + " 8 9 4.3607e+04 3.72e+00 7.09e-02 1.78e+02 \n", + " 9 10 4.3603e+04 3.29e+00 7.52e-02 7.81e+01 \n", + " 10 11 4.3600e+04 3.12e+00 6.22e-02 1.74e+02 \n", + " 11 12 4.3597e+04 3.12e+00 7.46e-02 7.85e+01 \n", + " 12 13 4.3595e+04 2.29e+00 4.27e-02 1.17e+02 \n", + " 13 14 4.3593e+04 2.05e+00 5.66e-02 7.62e+01 \n", + " 14 15 4.3591e+04 2.03e+00 3.96e-02 1.20e+02 \n", + " 15 16 4.3589e+04 1.79e+00 4.91e-02 7.16e+01 \n", + " 16 17 4.3587e+04 1.78e+00 3.67e-02 1.21e+02 \n", + " 17 18 4.3586e+04 1.63e+00 4.43e-02 6.82e+01 \n", + " 18 19 4.3584e+04 1.55e+00 3.30e-02 1.15e+02 \n", + " 19 20 4.3583e+04 1.51e+00 4.21e-02 6.83e+01 \n", + " 20 21 4.3581e+04 1.43e+00 3.03e-02 1.08e+02 \n", + " 21 22 4.3580e+04 1.39e+00 3.98e-02 6.75e+01 \n", + " 22 23 4.3579e+04 1.27e+00 2.68e-02 9.62e+01 \n", + " 23 24 4.3577e+04 1.09e+00 3.21e-02 5.94e+01 \n", + " 24 25 4.3576e+04 1.10e+00 2.50e-02 9.93e+01 \n", + " 25 26 4.3575e+04 1.17e+00 3.50e-02 6.24e+01 \n", + " 26 27 4.3574e+04 1.08e+00 2.37e-02 8.92e+01 \n", + " 27 28 4.3573e+04 1.10e+00 3.45e-02 6.27e+01 \n", + " 28 29 4.3572e+04 1.06e+00 2.30e-02 8.59e+01 \n", + " 29 30 4.3571e+04 1.25e+00 4.07e-02 7.00e+01 \n", + " 30 31 4.3570e+04 1.13e+00 2.22e-02 7.21e+01 \n", + " 31 32 4.3568e+04 1.12e+00 3.88e-02 6.87e+01 \n", + " 32 33 4.3567e+04 1.10e+00 2.19e-02 7.19e+01 \n", + " 33 34 4.3566e+04 1.10e+00 3.86e-02 6.75e+01 \n", + " 34 35 4.3565e+04 1.08e+00 2.17e-02 7.18e+01 \n", + " 35 36 4.3564e+04 1.08e+00 3.85e-02 6.63e+01 \n", + " 36 37 4.3563e+04 1.06e+00 2.14e-02 7.17e+01 \n", + " 37 38 4.3562e+04 1.06e+00 3.84e-02 6.50e+01 \n", + " 38 39 4.3561e+04 1.04e+00 2.12e-02 7.20e+01 \n", + " 39 40 4.3560e+04 1.04e+00 3.84e-02 6.39e+01 \n", + " 40 41 4.3559e+04 1.02e+00 2.09e-02 7.20e+01 \n", + " 41 42 4.3558e+04 9.42e-01 3.51e-02 6.15e+01 \n", + " 42 43 4.3557e+04 9.59e-01 2.05e-02 8.46e+01 \n", + " 43 44 4.3556e+04 7.97e-01 2.91e-02 6.02e+01 \n", + " 44 45 4.3555e+04 8.60e-01 1.97e-02 1.12e+02 \n", + " 45 46 4.3555e+04 6.66e-01 2.24e-02 6.02e+01 \n", + " 46 47 4.3554e+04 7.76e-01 1.91e-02 1.42e+02 \n", + " 47 48 4.3553e+04 5.22e-01 1.42e-02 5.09e+01 \n", + " 48 49 4.3553e+04 2.37e-01 4.33e-03 5.85e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 49, initial cost 9.2394e+05, final cost 4.3553e+04, first-order optimality 5.85e+01.\n", + "mean reprojection error: 3.751725891923626\n", + "max reprojection error: 13.455375307150806\n", + "mean reconstruction error: 0.47740445986802044\n", + "max reconstruction error: 2.1502824402420404\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:18.095532922662738 max: 97.53198030598877\n", + "image 1 reprojection errors: average:18.274859040776526 max: 153.01702225375607\n", + "image 2 reprojection errors: average:18.524135730520005 max: 94.98062182692085\n", + "image 3 reprojection errors: average:18.030235880859873 max: 128.69509456294188\n", + "image 4 reprojection errors: average:18.318485594193017 max: 132.57451701145095\n", + "image 5 reprojection errors: average:18.202145611736853 max: 110.07846555326284\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.0926e+06 2.04e+06 \n", + " 1 2 1.7957e+05 9.13e+05 7.16e+01 6.41e+04 \n", + " 2 3 1.7877e+05 7.99e+02 2.32e+00 5.78e+03 \n", + " 3 4 1.7857e+05 1.97e+02 1.45e+00 3.08e+03 \n", + " 4 5 1.7846e+05 1.12e+02 6.38e-01 9.32e+02 \n", + " 5 6 1.7840e+05 5.75e+01 5.29e-01 6.89e+02 \n", + " 6 7 1.7836e+05 4.73e+01 3.56e-01 4.16e+02 \n", + " 7 8 1.7832e+05 3.43e+01 3.31e-01 2.76e+02 \n", + " 8 9 1.7829e+05 3.01e+01 2.56e-01 3.43e+02 \n", + " 9 10 1.7827e+05 1.84e+01 1.73e-01 1.46e+02 \n", + " 10 11 1.7826e+05 1.65e+01 1.73e-01 2.99e+02 \n", + " 11 12 1.7824e+05 1.46e+01 1.41e-01 1.30e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 12 13 1.7823e+05 1.37e+01 1.51e-01 2.56e+02 \n", + " 13 14 1.7822e+05 1.30e+01 1.31e-01 1.31e+02 \n", + " 14 15 1.7820e+05 1.27e+01 1.44e-01 2.26e+02 \n", + " 15 16 1.7819e+05 1.22e+01 1.27e-01 1.34e+02 \n", + " 16 17 1.7818e+05 1.20e+01 1.39e-01 2.03e+02 \n", + " 17 18 1.7817e+05 9.53e+00 9.75e-02 1.21e+02 \n", + " 18 19 1.7816e+05 9.08e+00 1.18e-01 1.87e+02 \n", + " 19 20 1.7815e+05 8.57e+00 8.87e-02 1.14e+02 \n", + " 20 21 1.7814e+05 7.90e+00 1.03e-01 1.91e+02 \n", + " 21 22 1.7814e+05 7.21e+00 7.51e-02 1.31e+02 \n", + " 22 23 1.7813e+05 6.28e+00 8.26e-02 2.00e+02 \n", + " 23 24 1.7813e+05 5.68e+00 6.16e-02 1.30e+02 \n", + " 24 25 1.7812e+05 5.34e+00 7.29e-02 2.12e+02 \n", + " 25 26 1.7811e+05 5.04e+00 5.65e-02 1.25e+02 \n", + " 26 27 1.7811e+05 4.38e+00 6.07e-02 1.98e+02 \n", + " 27 28 1.7811e+05 4.30e+00 5.22e-02 1.19e+02 \n", + " 28 29 1.7810e+05 4.47e+00 6.31e-02 2.15e+02 \n", + " 29 30 1.7810e+05 4.64e+00 5.64e-02 1.23e+02 \n", + " 30 31 1.7809e+05 4.60e+00 6.39e-02 2.20e+02 \n", + " 31 32 1.7809e+05 4.50e+00 5.56e-02 1.19e+02 \n", + " 32 33 1.7808e+05 4.58e+00 6.47e-02 2.29e+02 \n", + " 33 34 1.7808e+05 4.15e+00 5.08e-02 1.06e+02 \n", + " 34 35 1.7808e+05 3.87e+00 5.73e-02 2.15e+02 \n", + " 35 36 1.7807e+05 3.84e+00 4.92e-02 1.03e+02 \n", + " 36 37 1.7807e+05 3.77e+00 5.62e-02 2.12e+02 \n", + " 37 38 1.7806e+05 3.74e+00 4.90e-02 1.02e+02 \n", + " 38 39 1.7806e+05 3.68e+00 5.52e-02 2.08e+02 \n", + " 39 40 1.7806e+05 3.65e+00 4.87e-02 1.01e+02 \n", + " 40 41 1.7805e+05 3.60e+00 5.43e-02 2.03e+02 \n", + " 41 42 1.7805e+05 3.56e+00 4.84e-02 1.00e+02 \n", + " 42 43 1.7805e+05 3.51e+00 5.33e-02 1.97e+02 \n", + " 43 44 1.7804e+05 3.45e+00 4.77e-02 9.83e+01 \n", + " 44 45 1.7804e+05 3.43e+00 5.27e-02 1.91e+02 \n", + " 45 46 1.7804e+05 3.35e+00 4.67e-02 9.67e+01 \n", + " 46 47 1.7803e+05 3.37e+00 5.24e-02 1.90e+02 \n", + " 47 48 1.7803e+05 3.33e+00 4.66e-02 9.56e+01 \n", + " 48 49 1.7803e+05 3.20e+00 4.98e-02 1.87e+02 \n", + " 49 50 1.7802e+05 3.19e+00 4.57e-02 1.02e+02 \n", + " 50 51 1.7802e+05 3.10e+00 4.79e-02 2.01e+02 \n", + " 51 52 1.7802e+05 3.10e+00 4.45e-02 1.14e+02 \n", + " 52 53 1.7801e+05 2.87e+00 4.27e-02 2.25e+02 \n", + " 53 54 1.7801e+05 3.02e+00 4.34e-02 1.33e+02 \n", + " 54 55 1.7801e+05 3.03e+00 4.28e-02 2.30e+02 \n", + " 55 56 1.7800e+05 2.87e+00 4.02e-02 1.34e+02 \n", + " 56 57 1.7800e+05 3.02e+00 4.36e-02 2.49e+02 \n", + " 57 58 1.7800e+05 2.99e+00 4.09e-02 1.32e+02 \n", + " 58 59 1.7800e+05 2.93e+00 4.27e-02 2.34e+02 \n", + " 59 60 1.7799e+05 2.05e+00 2.45e-02 1.05e+02 \n", + " 60 61 1.7799e+05 6.13e-01 6.14e-03 4.18e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 61, initial cost 1.0926e+06, final cost 1.7799e+05, first-order optimality 4.18e+01.\n", + "mean reprojection error: 7.6069260534659335\n", + "max reprojection error: 29.846203622929718\n", + "mean reconstruction error: 0.9417810000673973\n", + "max reconstruction error: 5.279652255991549\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [], + "source": [ + "wall_cam_positions = all_cam_positions[(1,2,3,8,9,12),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 29.15674544, -1.85516359, 147.4176074 ],\n", + " [ 44.82084089, 123.17250001, -44.9380583 ],\n", + " [ 29.29952975, -127.37249999, -28.97664714],\n", + " [ -29.15674544, -1.85516359, -147.4176074 ],\n", + " [-147.4176074 , -1.85516359, 29.15674544],\n", + " [ 147.4176074 , -1.85516359, -29.15674544]])" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wall_cam_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": {}, + "outputs": [], + "source": [ + "wall_cam_direcions = [[ 0, 0, -1],\n", + " [ 0, -1, 0],\n", + " [ 0, +1, 0],\n", + " [ 0, 0, +1],\n", + " [+1, 0, 0],\n", + " [-1, 0, 0]]" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "# camera_radial_position = 163.0\n", + "# camera_halfz_position = 168.0\n", + "# camera_positions = np.array([\n", + "# [0, -camera_halfz_position, 0],\n", + "# [0, camera_halfz_position, 0],\n", + "# [camera_radial_position, 0, 0],\n", + "# [-camera_radial_position, 0, 0],\n", + "# [0, 0, camera_radial_position],\n", + "# [0, 0, -camera_radial_position]])\n", + "# camera_directions = [[0, 1, 0],\n", + "# [0, -1, 0],\n", + "# [-1, 0, 0],\n", + "# [1, 0, 0],\n", + "# [0, 0, -1],\n", + "# [0, 0, 1]]\n", + "camera_positions = wall_cam_positions\n", + "camera_directions = wall_cam_direcions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([np.pi/2, 0, np.pi/2, 0, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1223\n", + "Feature in image counts: Counter({3: 715, 2: 273, 4: 204, 5: 31})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1223 features\n", + "image 0 reprojection errors: average:15.342952536661766 max: 66.8760788275862\n", + "image 1 reprojection errors: average:17.241562055924263 max: 67.26524606160376\n", + "image 2 reprojection errors: average:16.33529684763169 max: 69.07189540964276\n", + "image 3 reprojection errors: average:16.066497961784666 max: 72.96371831251166\n", + "image 4 reprojection errors: average:15.984364387008986 max: 61.56719760727543\n", + "image 5 reprojection errors: average:15.804475354774615 max: 67.02523038468682\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 6.5752e+05 9.65e+05 \n", + " 1 2 1.2642e+03 6.56e+05 6.11e+01 2.91e+04 \n", + " 2 3 1.1731e+03 9.10e+01 6.62e-01 5.52e+02 \n", + " 3 4 1.1710e+03 2.10e+00 2.23e-01 4.11e+02 \n", + " 4 5 1.1702e+03 8.61e-01 5.40e-02 9.96e+01 \n", + " 5 6 1.1699e+03 2.45e-01 3.10e-02 4.76e+01 \n", + " 6 7 1.1698e+03 1.70e-01 2.07e-02 3.09e+01 \n", + " 7 8 1.1696e+03 1.28e-01 1.83e-02 1.61e+01 \n", + " 8 9 1.1695e+03 1.12e-01 1.47e-02 2.27e+01 \n", + " 9 10 1.1694e+03 8.16e-02 1.11e-02 1.24e+01 \n", + " 10 11 1.1694e+03 4.80e-02 5.79e-03 1.50e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 11, initial cost 6.5752e+05, final cost 1.1694e+03, first-order optimality 1.50e+01.\n", + "mean reprojection error: 0.6836683552181272\n", + "max reprojection error: 2.8424111628158624\n", + "mean reconstruction error: 0.10285665508477058\n", + "max reconstruction error: 0.4227998410680015\n" + ] + }, + { + "ename": "KeyError", + "evalue": "'76-7'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0mfitter\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msetup_led_simulation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mled_positions_8a\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msmeared_feature_locations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfocal_length\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprinciple_point\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mradial_distortion\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mposition_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrun_led_fit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfitter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_positions_8a\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 13\u001b[0;31m \u001b[0mcentre_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_mpmt_centre_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_locations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 14\u001b[0m \u001b[0morientation_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mget_mpmt_orientation_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_orientations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[0max_led_pos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mposition_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbins\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mhisttype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'step'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlw\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1.5\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlabel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"{} pixel error: mean = {:.2f} cm\"\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mposition_errors_8a\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpixel_error\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmean\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36mget_mpmt_centre_errors\u001b[0;34m(reco_led_positions, mpmt_positions, led_count)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_mpmt_centre_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n\u001b[0m\u001b[1;32m 3\u001b[0m for k in mpmt_positions.keys()}\n\u001b[1;32m 4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_mpmt_centre_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n\u001b[0m\u001b[1;32m 3\u001b[0m for k in mpmt_positions.keys()}\n\u001b[1;32m 4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_mpmt_centre_errors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_led_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mled_count\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m reco_mpmt_positions = {k: np.mean([reco_led_positions[k + \"-\" + str(b)] for b in range(led_count)], axis=0)\n\u001b[0m\u001b[1;32m 3\u001b[0m for k in mpmt_positions.keys()}\n\u001b[1;32m 4\u001b[0m \u001b[0merrors\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mlinalg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreco_mpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mk\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmpmt_positions\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkeys\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mKeyError\u001b[0m: '76-7'" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Simulation with Sony a7R-IV" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "pycharm": { + "is_executing": false + } + }, + "outputs": [], + "source": [ + "focal_length = np.array([3526.4, 3622.6])\n", + "principle_point = np.array([4719.6, 3240.2])\n", + "radial_distortion = np.array([-0.1981, 0.0361])\n", + "tangential_distortion = np.array([0, 0])\n", + "camera_matrix = fit.build_camera_matrix(focal_length, principle_point)\n", + "distortion = fit.build_distortion_array(radial_distortion, tangential_distortion)\n", + "image_size = np.array([9504, 6336])\n", + "image_area = [[0,image_size[0]],[0,image_size[1]]]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 8 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [], + "source": [ + "all_cam_positions = np.array([[97.47275687, 14.93703117, 99.94996814],\n", + " [29.15674544, 141.7448364, 147.4176074],\n", + " [44.82084089, 266.7725, -44.9380583],\n", + " [29.29952975, 16.2275, -28.97664714],\n", + " [-97.47275687 , 14.93703117, -99.94996814],\n", + " [99.94996814, 272.2629688, -97.47275687],\n", + " [99.94996814, 14.93703117, -97.47275687],\n", + " [-99.94996814, 14.93703117, 97.47275687],\n", + " [-29.15674544, 141.7448364, -147.4176074],\n", + " [-147.4176074, 141.7448364, 29.15674544],\n", + " [-99.94996814, 272.2629688, 97.47275687],\n", + " [97.47275687, 272.2629688, 99.94996814],\n", + " [147.4176074, 141.7448364, -29.15674544],\n", + " [-97.47275687, 272.2629688, -99.94996814]])\n", + "corner_cam_positions = all_cam_positions[(0,4,5,6,7,10,11,13),:]\n", + "cam_offsets = np.mean(corner_cam_positions, axis=0)\n", + "all_cam_positions = all_cam_positions - cam_offsets\n", + "corner_cam_positions = corner_cam_positions - cam_offsets" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [], + "source": [ + "corner_cam_directions = [[-1, +1.9, -1],\n", + " [+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [-1, +1.9, +1],\n", + " [+1, +1.9, -1],\n", + " [+1, -1.9, -1],\n", + " [-1, -1.9, -1],\n", + " [+1, -1.9, +1]]" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner_cam_positions\n", + "camera_directions = corner_cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({4: 504, 8: 344, 7: 212, 6: 152, 5: 60})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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m27Vma0u9qtVusrU/wEHDACG8vr6W8/lcTqdTeXl5aV0cEtOWAPZx66BhARYAAMBCtwIse7AIyR4CbtE2YEyefSALe7AIyR4CbtE2YEyefSALARYh2dTLLdoGjMmzz1fsPSQSe7AAAEjteDyWy+VSpmkyw8lubu3BMoMFAEBqZjiJRIAFAEBqtc6GhBpkEQQAAKhEgAUAAFCJAAs24LwWAIAxCbCSMXBvZ0ndv5/Xcj6fdyjZctoRwH6i97nRywfZCLCSiT5w79mSuj+dTmWaprDZjLQjgP1E73OXlE8wFod7EZcsgslIQ9rOkrqPns1IOwLYT/Q+d0n53oOxUkro99wI3IvA5nm+++fp6WkGtnO9Xudpmubr9dq6KPCtEdrrCNdIP/Zor56JONyL9kopb/MnMdPh13+7z/Pz8/z29rZdtAeDcxI9r6+v5Xw+l9PpVF5eXloX50sjtNcRrpF+aK+wr8Ph8HOe5+ePf26JIAQSfRkJ28u05GOE9prpGjMF52wjU3uFnpnBAgjEIJm1zF4A7OvWDJYsgqwmew3U954gRXDFUtGzlwKMQoDFatHTztI3AT78rsfg3HNOFNoiSwwfYHlg1vO19H7aWX0CfOif53wb3knLaYvb6bE9Dp/kItOG8miin/UUiXZWn83c0D/P+Ta8k5bTFrfTY3scPsAa5YGxcb6tUdrZngT40D/P+Ta8k5bTFrfTY3uURXAQsksBAEA9sggOzn4pAIB4etyDNDoB1iB6zC61lo4MAIhCAo3+CLAYjo4MAPbl4+ZtVhn1Z/gkF4ynx82Un5HYBIAoeswUV4sEGv0RYDGcUToyLzOA2Eb6EDbKx00oxRJB6JYlB7SWYUlQhjLSr5GWrNsLzkgEWNApL7PYog3styhPhsHjFmUc4d5Shw9h0CdLBAEa2GIJ5yPLjbYoT4YlQVuU8ZG63GLJmOXCcY2yZB1GI8ACuhV5f0O0gf0W5ckweNyijI/U5UiBbuTnE+ARh3me7/7Lz8/P89vb24bFgf4ZVOzneDyWy+VSpmkKP9CvQdvKb6R7ONrzCfTncDj8nOf5+eOfm8GCnVmus5+oX+63kmHGiK+NdA9Hez5bGyl4h9YkuYCd2dT8tZob8iX6gLhqP5+SeXwtQ9IZ6IUACzb28aU/0qB/zYDHIABYY03fMVJQ5uMe7EeABRsbOWBYc+0GAWN7ZMA70mCZP63pO0bqnz9+3PO8wIbmeb775+npaQaWuV6v8zRN8/V6bV2U3Y187SPY4v5O0zSXUuZpmnb9f2/Rhvs28v3d4nmB0ZRS3uZPYiYBFsC/WTvg2mKgFn3wFy2giRbw7aH2NUdvc9TjXsPjBFgAd1g7oN5iID7a4D6i6NdYu42s/fei1xPAFm4FWNK0A/ybtamjt0g5HT2N9QgpxaNfY+02svbfc/wEwN8cNAxJOdPkb+oC2qr9DHqmf1EPEJuDhqEzvhj/TV1AW7Vn+jzTv6gHyEmABUm1XD4W7atq9KV0wDKe6V/UA+RkiSCw2PF4LJfLpUzT5Ksq0LVoH5SAOCwRBKrxVRUYhWV6wFICLGCx6JnVAGrxQQlY6n+0LgA84vX1tRyPx/L6+tq6KN/KVFYAfnn/oGR54P68N8lKgMWmtu4c35dunM/nTf79mjKVFYD+ZAtY9nhvZqsTcrBEkE1tvXY909KNTGUFoD/Z9pPt8d7MVifkIMBiU1t3jpn2AmUqKwD9yfahb4/3ZrY6IQdLBNmUtevrWLJAdlnacJZyQg3eyX9SJ2xBgMUfDDjas19rLD0+c1nacJZyLtVjm+Jz7jXEY4kgf7AeuT1LFsbS4zOXpQ1nKedSPbYpPudex+FQav4yz/PdP09PTzP9u16v8zRN8/V6bV2Urqnn/USv6+jlI5/IbSpy2TL6qj7V9b6maZpLKfM0Ta2Lwk5KKW/zJzGTAAsqWPMS0xHvR11DHJ7H/ayta4HZOuptPLcCLEsEoYI1SzR6XZoUkbqGODyP+1lb15YdriNbMO8kuSCE7Jt0T6dTmaZp0UssW+aizPcoW11DzzI/j9n6wbV1veadBvzt8Gt26z7Pz8/z29vbhsVhVMfjsVwulzJNk68/QblHwOj0g3lIOMEeDofDz3menz/+uSWChGDJSHzuETA6/WAeljnSkhksAAC6YgaLPZjBAgBgCBJO0JIkFwAAAJUIsAAAACoRYAEAAFQiwAIAAKhEgAXAJjIcypqhjADkIsACCKK3wf77OTTn87l1UW7KUMYlemtDABlJ0w4QRG8HY2Y4lDVDGZforQ0BZGQGCxhK5C/8p9OpTNPUzWD//RyayId8ZijjElHbUOTnDqA2ARYkY6DymMhLwnob7LO/qG0o8nOXhb4f8hBgkYIXy98iDFQy34+oX/ihZ5mfuyj9XYS+H7iPPVikYF/B3yLsGcl8P96/8AP7yfzcRenvIvT9kby+vpbz+VxOp1O4GVsQYJHCSC+W714aEQYqI90PYGxR+ruv+v4Rg40ogS98xhLBxKIsW9hDq30FLeo4wzKQqPs8AGrL0N+1em+0HIdkXna6xkhjvh6YwUrM15vttajjKF9LAcih1Xuj5TgkwmqOPRnz5WIGK7Hevt5E/DrToo7Xfi2NWH8A3G9tP95qlq23cUhk6jqXwzzPd//l5+fn+e3tbcPiMLLj8Vgul0uZpsnXmRXUH0Bu+vHHjbgfjXYOh8PPeZ6fP/65JYKEYWncY9QfQG768cdZSkcEZrAAWK3Xr8W9Xhf0zrPLnm7NYNmDBZBExH12tbOXrb3G2nUTNZtnxDYAkWTI+kj/BFhA11oPSGv+/oiD/tobr9deY+26ibqhvOZ1tn42ALo1z/PdP09PTzNAJtM0zaWUeZqmh/6d6/U6T9M0X6/XJr//kTJksvYaR6ibea57nWvaZs3fP8o9A/pVSnmbP4mZBFjAJqIMnmqVY22gFKUe4KM1bbPmB4Oa/9Zank/gEbcCLFkEgU1EyeRU6zDKtdm9RjsMkzzWtM2aWe4iZMyL0k8BfbEHCxoYYe9D1D0sa9k4DXWfgwjPVG/91C0jvHMgEmnaoQGHSQKwF+8c2IY07RDIKF9NaStCyvNRvpyvuc5R6ob2vHNgZ59tzLr1I8kFLdXajDzCpuYRrrFXrbPEPfL/bf1v1VT7GVlznTJMMhJtlB4VWQTJrtZgJOqAr6aM17j05dtrwB1h0D1CKu7az8ia64wQTG+l1fMZtb19JWOZ12h9ZAZsQYBFer0OqLeQ8RqXvnx7Dbgz3ruMeqvnaNfT6vmM9jzfI2OZ12h9ZAZsQYAFhGYGC/phBut+GcvckvoiklsBliyCAAAAC8kiCAAAsDEBFl2Q7hgA+uCdTnb/aF0AqOF8PpfL5VJKKQ5RBIDEvNPJToBFF94PT3SIIgDk5p1OdpJcAAAALCTJBQAAwMYEWAAAAJUIsGhChiBYJ+qzE7VcS0W9jqjlgiw8Q+xJgEUT7xmCzudz66IwmOwv2ajPTtRyLRX1OqKW617Znzvyy/4MkYssgjQhQxCtZE//G/XZiVqupaJeR9Ry3Sv7c0d+2Z8hcpFFEDb2+vpazudzOZ1O5eXlpXVxhud+wP48d7G4H1CHLILQSItlCZbj3Pby8lJ+/PhhUAE78tzd1qK/tlwOtmWJIGysxbIEy3EAcmjRX1suB9syg9WA2YWxtPhyezqdyjRNXp4AwbXor80ojssYdB8CrAZMzeeRtSPy8gTIIWt/nfX9ODpj0H1YItiAqfk8LLUDgD95P+ZkDLoPAVYD71+riE9HBAB/8n7MyRh0H9K0AwAALCRNOwAAwMYEWAyp5uZcG30B6In3GjxGgMWQambRkZGHvUUd/EQt1xIRryFimehb7feaNsxw5nm+++fp6WmGHlyv13mapvl6vYb6t9hP5vs2TdNcSpmnaWpdlN9ELdcSEa8hYpnulfk5G1nt+5a5DcNXSilv8ycxkyyCDKlmFh0ZeXLKnGI4avauqOVaIuI1RCzTvTI/ZyOr/V7L3IZhDVkEgSG9vr6W8/lcTqdTugM+IQvPGdCzW1kEBVgAAAALSdMOAACwMQEWdEKWJoDc9OPQB0kuoBM2kwPkph+HPpjBgh3s8VXydDqVaZpkaQJIao9+3CwZbE+SC9jB8Xgsl8ulTNPkqyQAzXgfQT23klxYIgg7cAYIABF4H8H2hlsiaGp8O+r2tvdDG50Dw1K9PFeRriNSWdbq4Rpow/voe56v/XRb1/M83/3z9PQ0ZzdN01xKmadpal2U7qjbv12v13mapvl6vbYuCitFuYe1nqs111OzDiL1Dz3UaZT6jPKcsJ57+Kcoz9cIstd1KeVt/iRmGi7A0pFsR93+LXuHEdGS9lWjLUa5hy0H5DXrIFL/0EOdRqnPR69n6XVEue6eROnrItHO9pO9rgVYsKPsHUZESwYBNQYMvd3D1jNYPVKnj1/P0mdVMFBfb20S9nQrwJJFEEjh9fW1nM/ncjqdvt07sOTvAu0sfVY920Akt7IICrDoipcvAOTj/U1GtwKs4bII0rfz+Vwul0s5n8+tiwKstDSrVLdZqGAg3t/0RIBFV06nU5mmqevzPQwmY2oVFERpDzXLsXSgVXNg1lt9Clb7MMJ9GeH9zUA+25h160eSC2ivx03erTdZt8g6WOs+RmkPLTMO9phOvlX7yJ4gpnVfspUo7RL4XZFFEGJZOxDocQDRevDQYlBZ6z5GaQ9RyvGoKNfRqn1kP+KgdV+ylUfuS5Q2DT26FWBJcgGNHI/HcrlcyjRN5cePH62L01Trzc2tfz/0pOXz5Fn+k3cNbEcWQQjGQACArXnXwHZkEWxohM2pLPfy8lJ+/Pjx6QtPmwGghq/eNWC8sQ0B1g6kHmUpbQaAexkks5bxxjb+0boAI3hPOSr1KPfSZgC41/sguZRinxWLGG9swx4sAIDE7LOCNm7twTKDBQCQ2Ps+KyAGe7AAAAAqEWABTWTalB2lrFHKsVS0ckcrz72ilDtKOb6TpZxAhz47ffjWz9PT056HI0Nq1+t1nqZpvl6vrYsS0jRNcyllnqapdVG+FaWsUcqxVLRyRyvPvaKUO0o5vpOlnC15T8FjSilv8ycxkwCL3+hs64n0co94XyOW6ZYoZY1SjqWilTtaee4VpdxRyvGdqOWMVK5I76keRLq37EOAVUnvD4/Otp5IbcV9BYghUn8c6T3Vg0j3dmvazi+3AixZBBfq/awJ5yHUEymr0z33VZpfgMfc049Ges9Gek/1INK93Vrv4+FHOQdrIYNQenU8HsvlcinTNOksAVbQjzIK4+FfnINVia899GqkL28AW9CPMgrj4a9J0w6deDQl8XtnOfKXKIBHPNqPSi0PfTCDBZ2wHhogN/049MEMFqn52ve30+lUpmmyNAUgKf3477zjyUqSC1KzoRgA+uQdT3S3klyYwSI1X/v6kOUrZZRyRinHElHKHKUcS0Qpc5RyfCVDGbmfdzxpfXY41q0fBw1vy6FtjCrL4YxRyhmlHEtEKXOUciwRpcxRyvGVDGWErRlP7qc4aDg+m1uJauvzLrKkNo5SzijlWCJKmaOUY4koZY5Sjq/sUUbn/xCd8WR79mAF8minrdNnK9bBA/yiP2RrxoN5OGg4gUcPbfPFgq1k+HINsAf9IVt7dDznEOD2BFgd0emzFZ01wC/6Q7ZmPJefJYIAAAALSdMOAACwMQEWmxrtTJLRrheAfoz0DhvpWtmfAItNvW/UPJ/PrYuyiz2v18sBGM1o/d7e1zvSO3uka2V/Aiw2Ndop7Hte70gvh1aDqhq/d8m/sffv20KLa1Bvy/+NrHU2Ur9Xyv7XO9I7e6RrpYHPTh++9fP09LTv8cgMyQnk9xmpnqZpmksp8zRN6X7vkn9j79+3hRbXoN6W/xtZ62ykfm+ex7vetdQTrZRS3uZPYiYBFuG0HugQT6uXZ43fu+Tf2Pv3baHFNai35f9GD3UG74wbaOVWgCVNO+E4gRwAuJdxA63cStMuwAIAAFjIOVhANa0TAnxl743+WbVIJNED9Xa/Xp7FyGUDgvps3eCtH3uwgHmOvd59z43+LfegPPq7WySSaL1np8bv37veRmljvfQpwFiKJBdALa0Hyl/Zc6N/y4HX3gP3FsFJbS2CRG1sv6QbW4lcNqAtARarZXi5ZCgj/ck8u9BC6zK3/v1raGOMJkO7y1BG9nErwJLkgm8dj8dyuVzKNE3lx48frYvzqQxlBAC+luF9nqGM7ONWkot/tCgMubyfch75tPMMZQQAvpbhfZ6hjLRlBusOzlcAAIA/jTxONoP1gPP5XC6XSymlmAoGAIB/MU7+k3Ow7nA6nco0TaaCKaU4EwWAsXjv8RXj5D8JsO7w8vJSfvz4Mdy0Z2QtO/v3LzXn83n3301bBhmMTPsfV+v3nrYXm3HynwRYpNSys4/ypcYLZ3+tBxn3at02Wv/+JSKUNUIZ7pGl/fckStto/d7T9kjns9ztt36cg0UUzqBof2jriLK0u9Zto/XvXyJCWSOU4R5Z2n9PsrSNrWl7RFVunIMlyQUpvU9Hj0ya2P1laXet20br379EhLJGKMM9srT/nmRpG1vT9shGmnYAAICFbqVptwcLWCXK3gCArejngDUEWMAqNh0DvdPPbUPgSu/swWIII58yvhV7A4De6ee24WBaemcGiyHc8xXSF7VlnHsB9E4/t8y979HWad9ha2awGMI9XyF9UQOA9e59j8oKSO/MYDGEe75C7v1FzYxZXhnuXYYykuM+ZSgjn9v73pmZgn/57HCsWz8OGoZ67j1A0gGL8WQ4/LN1GbO029blbH2f7pGhjKO5t926d7Ct4qBhiOXezdOWLsaTYeN76zJmabety9n6Pt0jQxlHc2+7de+gDQcNQ3AyIJJRlnabpZzw77RbiOHWQcMCLAAAgIVuBViSXAAAAFQiwILOyPgFkIt+u3/u8VgEWAPykPftnkOV19J2gFFt2f9t2W8Tg3s8FgHWgDzkfdvyHBJt53uCUDLSbr+3Zf/X+vwo9397re8xO/ssd/utH+dg9aH1uS+967l+e762WlqcO/PofVny/+/5u2rKUket6sd5Sd/ruf9z/2GdcuMcLAEWqUV84WUcYFNPi3vxaJtb8v/v+btqylJHrepHHxJHi3sR8f5HLBN8JMCiSxG/umUcYJNbltmZGv//WlnqyKAS/fkv6oEMbgVYzsEiNYct/qIeAPqgP/9FPZCBc7Do0svLS/nx48fwnW+WerhnI/Uom62XXOcodfJO3XxN/fyut34lS3++NfVAap9Na936sUQQ8vtuCdKWS5TuWfIxyrKQvfb0ZFySt+eeMPWTX4R+pWW/CrRT7MEC5vn7gcaWA5F7BhmjDET22tOTManEnnvC1E9+EfqVlv0q0I4AC5jn2ZfW0WScodmT+qEG/SqM6VaAJckFAADAQpJcAN3ItGEdWM+zDmT0j9YFAFjqfD6Xy+VSSinlx48fjUsDbMWzDmTU3QyWr13Qv9PpVKZpKqfTqXVRgA3t8awbN0BcWZ/P7gKs969d5/O5dVFgWFt3iM5HuS3ry2h07tvn9njWjRsgrqzPZ3dLBN+/cvmyDe1Y1tNO5Lp/fX0t5/O5nE6n3YPjlr/7HpHvW++MGyCurM9ndwHW+9cuoJ2sHWIPItd9yyAiegAT+b71zrgB4sr6fErTDsAuzGBBHp4Z+J407bCByPsmIpeNMbXcO2ffHhFF7qez7n2BCLpbIgh7irzsKHLZAIjdT1u2CusJsOABkV9AkcsGQOx+OuveF4jAHiygO/YOQB6eVyCrW3uwzGAB3Ym87Ab4necV6I0kF0B3TqdTmaYp5LKbPUTeON+qbOokrtGfV6A/lggCdOZ4PJbL5VKmaQo3I9CqbOoEgNqkaacbo3/the9EnhFoVTZ1Anl575ONGSzS8bU3LpvVgaz0X3H1+N7X3vogycXAenuII6e1HZ3N6kBW+q+4enzva299E2ANoLeH2NkccfX4EgTGoP+Kq8f3vvbWN0sEB9DbDBYAALQmycXA3r/8CK5gbHtvFI++MV19ALAFSwQBBrH3cuHoy5PVBwBbEGABDGLvNf/R9xioDwC2YA8W0DV7ECEWzyTQC3uwYFCj7/t4X5Z1Pp9bFyWFe9vLCO1KXWzDM6nNQO8sEYTOjb7vw7KsZe5tLyO0K3WxDc+kNgO9E2BB50YfzPR4fsqW7m0vI7QrdbENz2T8NmMZJzzGHix4kBcRAD05Ho/lcrmUaZqGD4bhK7f2YJnBggdZ6gFAT6LPsEF0klzAg06nU5mmyYsIIBGJJm57X8ZpVQasI8CCB3kR3WYAA0QlmyGwFUsEgc1YPglEZRkcsBUzWMBmRlo+abaO7EZrw1YfAFsxgwVsZqR0zGbryE4bBqjDDBbhjPYVlT7cO1unfbO3e9vcSDPO9EW/SjQCLMKx8Zhaar50v/u37l1upH2zt3vb3D1tuNYzZUBMTfpVorFEkHBsPKaWmkueav1b2jd7q9nmaj0HliNSk36VaARYCby+vpbz+VxOp9MQm3FH2rfDtmq+dGv9W9o3e6vZ5mo9BwbE1DRqvzra+DCTwzzPd//l5+fn+e3tbcPi8Jnj8Vgul0uZpmnIDgQAgN8ZH7Z3OBx+zvP8/PHP7cFKYKuNx9bA98l9BchFv92vLe+txDRxCbAS2OqsDptC+9TyvhokAFEs7Y9a9l+Z3sf6+WW2vLfOcgtsnue7f56enmZ+uV6v8zRN8/V6bV2U1Xq4hr1kqquWZZ2maS6lzNM03fX3M9XrntQL99JWblvaHy39+zVluo9r6inT9dXW27X3dj2PKqW8zZ/ETAKslVp2xDxmTefwyP0eqTNaeq2eo8+pF+6lrdy2tD9a8vd76NfXXsPe71BicS9/J8CqrIfOdVR7f33L3hlt2dZr/ts9PZM9XQvbitBWRnyOs/fr87zvNWS5r3zPvfydAAv+Ze/OIXtnlGUgUauc2e8X7K1mH5Glv+mhn+jhGqA1ARawSoSX8D1lqFXOLAM8iGLPGawtl/0BLHUrwHIOFtDEkgMS9zzrw8GNENfSvsA5QcCWbp2D9Y8WhQF4T11bSvl24PN+xsceZ328p70F4lnaF+zZd5CHD2lszTlYnYtwXkWEMhDPkgMSnfUBlLK8L+il79j6PTraezrKuWOj1ftQPls3eOvHHqx8IuwniVCGPW295t+eAoCxbP0e9Z7e5//9aLR671GR5GJMEdLnjhYQrO0w760nHTKR9Ph893hN5HZvm/Se3l7Nd7B6z0+AxcMM7O+ztsO8t351yOPa896PHPAvuaaI94Rx9fg8RuM55N8JsHiYTmVbLevXvc1hz8HTyAH/kmuKeE9oS18O4xBgATcZuOVgtiQe94SP9KeP09bJQoBF13TGj1F/bC1KG4tSDvqljT1OkEoWtwIsadrpQpSUq1n1ksq4Fqlz64vyjEYpR088L7/Tnz5uyTEeEJGDhumCwyT70/IgyCWHIHOfKM9olHL0pOXz4sDYPjnwnewEWHRBZ9yfloO2EQbhew9Mozyje5djhACg5fPiYwgQkQALCKnloC1KMLAlA9N9jFDPLZ+XET6GAPkIsICQRghyWjIw3Yd63pZ+Aojo8CsBxn2en5/nt7e3DYsDAAAQ3+Fw+DnP8/PHP5dFEAAAoBIBFkAiPabErn1N6giAluzBAkikx6QJta9JHQHQkhks2Jkv0TyixwM4a1+TOoI/effAfiS5gJ0dj8dyuVzKNE2+RAOwC+8eqC90kgtfVRiJL9E5Ze+nspe/F5nvQ+ay490Du5rn+e6fp6eneQvTNM2llHmapk3+feBz1+t1nqZpvl6vrYsSXvZ+Knv5e5H5PmQuewv6V4ir1vNZSnmbP4mZQiS5cBAjtGHj/P2y91PZy9+LzPchc9lb0L9CXFs/n/ZgwcBeX1/L+Xwup9OpvLy8tC4OQDf0r7zTFuKpdU9C78Fif9bSU0opLy8v5cePHyk6fG0WyNQPZOpf2db7bMn5fG5dFP5l6+dTgDUoDzvZjNpmMw0o2c+o7WLUfoDcJBgZT4g9WOzPWnqyGbXNjraPY+2yjdGW4IzWLt6N2g+Q2/tsCeMQYA3Kw042o7bZ0QaUawOH0QKO0drFu1H7AX4Z7UMKeVkiSCqjLoshj9ptdLR9HGuX0oy2BKd2u9C3koElomQhwCIVnSvRLWmjBrV/Whs4jBaI3mNJ+9K3ksFoH1LIyxJBUhl1WQx5LGmjoy1rY19L2pe+lQwsESULM1ik4is1e1s6y7Skjbb4GmvWrI0W9b6kfS3tW7UjgNscNAzwhePxWC6XS5mmqYsvp71dTxa91Xtv1wOwhoOGAVZYMguQ4au+PQxtZKj3Je03w/UAtGIGC6ASX/XJTPsFWObWDJYkFwCVSBRAZtovQB2WCAJD2mI5nyQs69S+FxmWaka0Rft1L9pzD2B/AixoJOJLL2KZtuLcnzhq3wv3No6R7kXU/nOkewBRWCIIjUQ8AylimUr5NXA5n8/ldDpV+7puOVQcte+FexvHFvdii/6ghqj9p+cBGpjn+e6fp6enGajjer3O0zTN1+u1dVH+ErFM8zzP0zTNpZR5mqbWRela1PufhfrbR9T+wP2H8ZRS3uZPYiYzWNBIxBPpI5aplP6+wPoC36eo9Re1va0VtT+I2n8C+xNgAeH1NnCJOhCPOnDNImr9RW1va/XWHwD9keQCYGdRD2ndKgtitM3/W5UnahbJqO0NoFcOGgZgU9EOsI1WHgByunXQsBksABZbMgsUbQZlSXmizb4BEJ8ZLAAWG2UWaJTrBGA5M1gAVBNtVmoro1zn3swMAj0zgwV0rbcU1dADM4NAD8xgAUN6T1F9Pp9bFwX4ly1mBreaFTPbBiwlwBqIlwS1ZBrIWOJV32h9yWjXu4ctUtpv9THFR5q2env+ersebpjn+e6fp6enmbymaZpLKfM0Ta2L8rDr9TpP0zRfr9fWRRnSVm2ppzaazZJnarT7tOR69U3tbFX3j/y72sPjeutverue0ZVS3uZPYiYB1kB66uh1UI+LOGjoqY1mI4i4TfDJWtrD43rrb3q7ntEJsOiKDupxXvwxtWrbnqk63D/+nfsCfRNgAb/Z88VvkHG/3gLfqPc+arnW6q3dbKm3ew+0cyvA+sfee76AGN43me/hfZN4KUVK5m+8J+PoJSlH1HsftVxr9dZuttTbvV/K0RWwPVkEYSdbZw7aIzPR2t8hk9/9tsiu1lLUex+1XGv11m62tPbeR+5jl5AVEbbnoGHYydYHa+5xcKfDQYFR9dLHmsGCem4dNGyJIOxk6yU8eywRsgwJHmeAm1Mvfeyey8NhVGawADpnQB+LmWCAPpjBAhjU6Jv6ozETDNA3SS6Aru2xaTy63hI6ZCchhecS6JsZLKBrZm/suSAezyXQMwEW0DXLsSAezyXQM0sEga5ZjhXbVkvFLEGLzXMJ9MwMFgDNbLVUzBI0AFoxgwUQzEizL1sl4BgpscdI7QUgAwEWXTPwaEO9P+Z99uV8Prcuyua2Wio20hK0kdrLFvRX7ah7eiXAomsGHm2o98eMNPvC47SXx2Trr/YISvYKfGrVvUCNcOZ5vvvn6elphq1dr9d5mqb5er2G+rda/p69rqOWbOUFxpWtv5qmaS6lzNM0pf4d81yv7vcqL3xUSnmbP4mZBFiEk7Gj3LrMGeuEdrINGEfnfrHEHu0lW5vMVl76cSvAkkWQcDKej7J1mTPWCe3IoJeL+8USexwcnu1w8mzlpX+HX8HXfZ6fn+e3t7cNiwPAo15fX8v5fC6n02mIJA/ZuV8AOR0Oh5/zPD//8ecCLAAA1vKRgFHdCrBkEYQPZCMah3sN2/F8jSNbJsZbtFlqEWBRVQ+dUy8vCr7nXsN2PF/jqHFUQITxgzZLLQIsqmrdOdXooJ0pMw73OpZHn98IAzT+5vkaR42DvVuPH0rRZqnos9SCt36kaec7rVOlSmdONq2fmUgefX49/3/TrshGmyWjIk17PyJvJm2dKlU6c7KRovtvjz6/nv+/aVdk03r8kEHk8R+/E2Al5MV5mw6abAQFf3v0+fX8/027gv4Y/+UhwErIixP6IShgC9oV9Mf4Lw/nYAEAACzkHCwACCZb5sNs5QVoQYAF7CL7wGxp+Vtfb+vfz31ap6Ze2k5al/dRngtgD/ZgAbvIvjl3aflbX2/r3899Wu+pWNpOWpf3UZ4LYA8CLGAX2QdmS8vf+npb/37u0zoZxdJ20rq8j/JcAHuQ5AIAIBlnIkF7klxAQvYLAD3Ql9WXfT8c9EyABYF5gdZnoBfLVvfDfd7OmrrVl9V3Op3KNE2WO0JA9mBBYPYL1Ldmk7ulONvZKumAZAbbWVO3+rL6su+Hg54JsCAwL9D61gz0DNa3s9XA24B+O2vqVl82Nh+pGI0kFwxJZ88S2gvAesfjsVwulzJNk0CbrtxKcmEGiyGZkWAJX98B1jOjzGgkuWBINgczOkkg9qGe4e+PVKOsAPDcI8DiLyN1CKN19r0bqe3WIqvbPtTzOp5pMvPcY4kgf7Fsjqy03eUs2dmHel7HM01mnnvMYPEXy+bIKlLbzfLlfY9Z3Oh1sUf5ssyWR7tXkZ5pWCrLc892ZBEEqEi2rL9Fr4vo5duTugBY7lYWQTNYABX1+uV9zQxH9LpYU75oMz21RL9XAJmYwQI25xyp/Mxw/KIe8tMfAbU4Bwtoxob1/Gza/kU95Kc/ArYmwAI2Z1Can8OWf1EP+emPgK1ZIggAALCQJBcAAAAbE2AB8K1es+ctpR7YmzYH+QiwICEvXPb2nhjgfD63LkpT6oG9aXOQjwALEvLC5RE9nmm1F2dnsTfPHuQjycVKztGgJe2PRzjLaV/qux59HxCJJBeVmUGgpfdU0SMNMMwC1OOL+L7Udz3evdCe9/H3BFgreWHCvgys6tkjQM/yAt6jnFE+iGS5J1/x7oX2vI+/56DhlRw2Cfvq4XDQkZY3vb+ASymh+8os5ayhh2v17oX2engfb02ABaTQw8CqhwHuvbK8gLOUs4aRrpX2RvqgNJoe3sdbk+SC4XkJsBdtDWLzjNYjuQsjuJXkwgwWwxtpVmFLBibf89UPYvM+qMeMKSMTYDE8L4E6DEyA7LwP6vFBiZHJIsjwomT4yk52r/Z6yBI3MvevPe8DoAYBFgxgpFTUI5M6Nzf3bxyCaeibJYIwAMv3xmB5U27u3zj0ydA3ARYMwMBtDPY85Ob+jUOfDH2zRBAGsGb5niUsAF9b209aUg19E2ABn7IfhK1tHcT7SMDWWvaT2jfEZYkgBNfqfClLWNja1vtQ7HNhay37Se0b4hJgQXCtXqL2g7C1rQenPhKwtZb9pPYNcR3meb77Lz8/P89vb28bFgf4qNUMFkA0vfWHvV0PjOZwOPyc5/n545/bg9Upa7P7sXYzdG9toLfrgT318vz0tje0t+vhMb08p1gi2C1rs+mtDfR0Pb5as7denp/elsX1dj08ppfnFAFWt3Ta9NYGeroeL1H21svz09ve0N6uh8f08pxiDxbA7sxgAa3of6Aee7CgIeuq+XcOGeVe+g5qs+8LtifAgh14oVGbgfcY9B3UdjqdyjRNlqHBhuzBgh1YV01t9nGNQd9BbfZ9wfbswQJIyD4KAGjLHiyAjtjHBWRiWTMjEWAxHJ08AOzLfkJGIsBiODp5iKfWhw8fUCAmyTUYiQCL4ejkP2dgSku1Pnz4gEJL+tHbLGtmJLIIMhwZlD4nKx0t1cqWJ+seLelHgVI2CrBkt4J8DExpqdaHDx9QaEk/CpSy0RJBSzQgn+zLN6IuzYlaLojYNiOWaYns/ShQxyYzWL7gAHuLujQnarkgYtuMWCaApTYJsCzRAPYW9cNO1HJBxLYZsUwA7+7dBnWY5/nuf/T5+Xl+e3urUT4AAIA0jsdjuVwuZZqm8uPHj3I4HH7O8/z88e/JIggAAPCNe2fZnYMFkFz2xAD8yT0FiOfeRDYCLIDkZG7tj3tKa4J8WM8SQXiAM9+IQGKA/rintCajI6xnBgse4CszETh7pz/R7una2QyzIHmdTqcyTZMgH1YQYMEDvIByM2iE+6z9mOQjVF7RgnzIRIAFD/ACys2gsa09AlXBcB1rPyb5CAWMyB4sYFhr97nYH1PHHns87COp4/1j0l7/H0BmAixgWAaNbe0RqAqGAdjbYZ7nu//y8/Pz/Pb2tmFxAAAA4jscDj/neX7++Of2YAFfsocF4Hf6xX2oZ7ISYJGaznd7EjoAj+gxW6d+cR/qmawEWB2K/FKqTee7vchZwB5p6yM9J9BSj9k6I/eLPRm1nr2fOjDP890/T09PM/FN0zSXUuZpmloXZXPX63Wepmm+Xq+ti0IDj7T1kZ4TYhmt31p7vaPVE7zzfsqjlPI2fxIzySLYoZGyZsnmNrZH2vpIz0kpv76Ins/ncjqdnNvW2Gip42XrhGVGez/1SBZBgAEcj8dyuVzKNE0GrY0JdgH6IIsgwMD23MuQcf/AnmV+n5kRXAH0yRJBgAHsudwq4xK4jGUGICYBFgBVZdw/kLHMAMRkiSAAn1q7bC7jEri1Zc64HPIRo10vwBoCLIA7jTa4jHwOURSj1VH06x3tGQViskQQCCN6drXR9ulYNve90eoo+vWO9owCMUnTDoQRPZV49AAQRucZBfZ0K027AAsIw+AIAMjCOVhAeBmTIwD0rqe9bT1dC3EJsNhVLx1bL9cBAN+JntxkiZ6uhbgEWOyql46tl+uAr/iQ8D11xAhOp1OZpilscpMleroW4pJFkN9svQcmegaqe/VyHfAVGdm+p44Ywfvy7R7scS32EyPA4jdbDxZ66aR7uQ74ig8J31tbRwZg+bmH3OLDCwIsfmNAxUcGEfmtvYc+JHxvbR0ZgOXnHnKLsRQCLH5jQMVHBhH5uYfxGIDl5x5yi7EUklwAX7IhOL8972HWpA97l9uRBPm5h8AtDhoGoJrj8Vgul0uZpinVF9ys5QagnVsHDVsiCEA1WZdNZS03APFYIghQSdblcTVlXTaVtdy1acMAjxNgAVTiAGqy67kNCx6BvVgiCOym95TvlpmRXc9tWDZNYC8CLGA3vQ9wpOYlu57bcM/BIxCLAAvYjQEO0ErPwSMQiz1YwG4kEqjDXpKxuN8AuZjBAkim96WW/M79BshFgAWQjKWWY3G/AXI5zPN8919+fn6e397eNiwOAABAfIfD4ec8z88f/9weLAB2t+e+InuYANiTAAuA3e15oG3Ph+dCTT5GQB0CLKjIywnuczqdyjRNu+wr2vN3wbuM7wMfI6AOSS6goozZvl5fX8v5fC6n00n6dHaz55lEzj+ihYzvAwlVoA4BFlSU8eWUcRAAEF3G94GPEVCHLIIwODNYAADL3coiaAYLBueLJQBAPZJcAAAAVCLAAqgoY+Yw0G4B6rFEEKAiSUPISLsFqEeABVBRxsxhoN0C1GOJIEBF70lDamVktHSLW2q2jdrtNiLPErAXARawK4OcZd6Xbp3P59ZFIRhtY5ks9aWPhPwEWNCJLC/lLIOcKE6nU5mmydIt/qBtLJOlvmr0kVneB9Are7AggBqH/WbZpG6vxzLOKeMWbWOZLPVVo4/M8j6AXgmwIIAaL8MsgUuWQQ5ACzX6yCzvA+iVJYIQQI2lKyNsUqdPtZczWR7F6LwPoC0zWBCAWR1GVns5k+VRALQkwAKgqdrLmSyPAqClwzzPd//l5+fn+e3tbcPiAAAAxHc4HH7O8/z88c/twQIAAKhEgAUAAFCJAAsAAKASARYA8Ckp7wGWE2ABrGTwSe/eU96fz+fWRQFIQ5p2gJWct0TvpLwHWE6ABbCSwSe9cwg6wHKWCAKs9D74fHl5aV0UGJrlukAkiw4aPhwO/08p5X9tVxwAgMX+r1LK/1FK+f9KKf9347IA4/g/53n+nx//cFGABQAAwG2WCAIAAFQiwAIAAKhEgAUAAFCJAAsAAKASARYAAEAlAiwAAIBKBFgAAACVCLAAAAAqEWABAABU8v8D73UY8GtkAewAAAAASUVORK5CYII=\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.264462402833644 max: 377.0328742850373\n", + "image 1 reprojection errors: average:21.694221695581575 max: 248.5391106616894\n", + "image 2 reprojection errors: average:21.46648375029394 max: 214.4193209393158\n", + "image 3 reprojection errors: average:21.728728432513453 max: 713.4642567776021\n", + "image 4 reprojection errors: average:23.010544507316624 max: 555.9822178943259\n", + "image 5 reprojection errors: average:21.76474491025006 max: 175.710935933977\n", + "image 6 reprojection errors: average:22.510237833250088 max: 564.9525615707422\n", + "image 7 reprojection errors: average:21.246286357455897 max: 268.11221735089924\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8700e+06 1.18e+07 \n", + " 1 2 2.1531e+04 3.85e+06 6.19e+01 1.04e+06 \n", + " 2 3 3.6035e+03 1.79e+04 1.13e+00 2.09e+04 \n", + " 3 4 3.5855e+03 1.81e+01 2.16e-01 2.56e+03 \n", + " 4 5 3.5838e+03 1.72e+00 3.40e-02 6.38e+02 \n", + " 5 6 3.5833e+03 4.35e-01 1.39e-02 3.26e+02 \n", + " 6 7 3.5831e+03 2.72e-01 8.80e-03 1.29e+02 \n", + " 7 8 3.5829e+03 1.91e-01 7.28e-03 1.06e+02 \n", + " 8 9 3.5827e+03 1.65e-01 6.17e-03 5.11e+01 \n", + " 9 10 3.5826e+03 1.41e-01 5.57e-03 7.05e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 3.8700e+06, final cost 3.5826e+03, first-order optimality 7.05e+01.\n", + "mean reprojection error: 0.8627700039771256\n", + "max reprojection error: 3.065881041660222\n", + "mean reconstruction error: 0.05077779033160973\n", + "max reconstruction error: 0.2411896069995061\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.736092527831087 max: 473.06001395021957\n", + "image 1 reprojection errors: average:21.99918119536144 max: 329.4595523669278\n", + "image 2 reprojection errors: average:22.38758648105242 max: 316.53304498905544\n", + "image 3 reprojection errors: average:21.633169894282073 max: 176.20839543366415\n", + "image 4 reprojection errors: average:22.1132323814833 max: 382.1037251657151\n", + "image 5 reprojection errors: average:22.57969095097145 max: 654.4855289535178\n", + "image 6 reprojection errors: average:22.359415805714885 max: 206.35285135130866\n", + "image 7 reprojection errors: average:22.845908475237774 max: 741.1278276208474\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.8543e+06 6.58e+06 \n", + " 1 2 5.2520e+04 3.80e+06 6.25e+01 1.02e+06 \n", + " 2 3 3.2016e+04 2.05e+04 1.11e+00 2.41e+04 \n", + " 3 4 3.1982e+04 3.44e+01 1.71e-01 3.22e+03 \n", + " 4 5 3.1976e+04 5.64e+00 5.57e-02 1.20e+03 \n", + " 5 6 3.1972e+04 3.67e+00 4.62e-02 7.36e+02 \n", + " 6 7 3.1970e+04 2.52e+00 2.92e-02 3.06e+02 \n", + " 7 8 3.1969e+04 1.25e+00 1.54e-02 1.98e+02 \n", + " 8 9 3.1967e+04 1.09e+00 1.66e-02 1.32e+02 \n", + " 9 10 3.1967e+04 9.68e-01 1.25e-02 1.39e+02 \n", + " 10 11 3.1966e+04 6.71e-01 1.02e-02 8.81e+01 \n", + " 11 12 3.1965e+04 6.52e-01 1.02e-02 1.28e+02 \n", + " 12 13 3.1965e+04 5.12e-01 7.69e-03 6.46e+01 \n", + " 13 14 3.1964e+04 5.10e-01 9.13e-03 1.27e+02 \n", + " 14 15 3.1964e+04 4.91e-01 7.45e-03 6.22e+01 \n", + " 15 16 3.1963e+04 4.88e-01 8.99e-03 1.27e+02 \n", + " 16 17 3.1963e+04 4.71e-01 7.21e-03 6.02e+01 \n", + " 17 18 3.1962e+04 4.66e-01 8.80e-03 1.28e+02 \n", + " 18 19 3.1962e+04 3.94e-01 5.90e-03 4.93e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 19, initial cost 3.8543e+06, final cost 3.1962e+04, first-order optimality 4.93e+01.\n", + "mean reprojection error: 2.5679150249597926\n", + "max reprojection error: 9.04509847406396\n", + "mean reconstruction error: 0.15051192345533668\n", + "max reconstruction error: 0.7660008115435512\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:23.360584846224295 max: 552.8120038883343\n", + "image 1 reprojection errors: average:22.515526458675605 max: 275.6338146187462\n", + "image 2 reprojection errors: average:21.368713789741193 max: 165.2596540070834\n", + "image 3 reprojection errors: average:23.15842538796967 max: 390.2233910306074\n", + "image 4 reprojection errors: average:21.949628582997676 max: 197.95563906776016\n", + "image 5 reprojection errors: average:21.590713526391312 max: 274.211028530515\n", + "image 6 reprojection errors: average:21.24189509529732 max: 173.62061563665003\n", + "image 7 reprojection errors: average:20.84250286924867 max: 243.02689931355297\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.2625e+06 7.70e+06 \n", + " 1 2 1.0362e+05 3.16e+06 6.18e+01 1.32e+06 \n", + " 2 3 8.6730e+04 1.69e+04 9.38e-01 4.31e+04 \n", + " 3 4 8.6665e+04 6.49e+01 3.48e-01 3.05e+03 \n", + " 4 5 8.6652e+04 1.25e+01 5.40e-02 5.24e+02 \n", + " 5 6 8.6648e+04 3.94e+00 3.66e-02 4.12e+02 \n", + " 6 7 8.6646e+04 2.71e+00 1.70e-02 1.69e+02 \n", + " 7 8 8.6644e+04 1.65e+00 1.70e-02 1.96e+02 \n", + " 8 9 8.6642e+04 1.47e+00 1.16e-02 1.55e+02 \n", + " 9 10 8.6641e+04 1.47e+00 1.62e-02 1.89e+02 \n", + " 10 11 8.6640e+04 1.34e+00 1.05e-02 1.39e+02 \n", + " 11 12 8.6638e+04 1.44e+00 1.70e-02 1.97e+02 \n", + " 12 13 8.6637e+04 1.29e+00 9.61e-03 1.16e+02 \n", + " 13 14 8.6635e+04 1.59e+00 2.06e-02 2.30e+02 \n", + " 14 15 8.6634e+04 1.27e+00 7.94e-03 6.65e+01 \n", + " 15 16 8.6633e+04 1.31e+00 1.92e-02 2.36e+02 \n", + " 16 17 8.6631e+04 1.25e+00 7.79e-03 6.15e+01 \n", + " 17 18 8.6630e+04 1.33e+00 2.03e-02 2.44e+02 \n", + " 18 19 8.6629e+04 1.27e+00 7.72e-03 5.60e+01 \n", + " 19 20 8.6628e+04 1.22e+00 1.92e-02 2.33e+02 \n", + " 20 21 8.6626e+04 1.12e+00 6.92e-03 4.51e+01 \n", + " 21 22 8.6625e+04 1.09e+00 1.81e-02 2.50e+02 \n", + " 22 23 8.6624e+04 1.07e+00 6.64e-03 4.93e+01 \n", + " 23 24 8.6623e+04 1.05e+00 1.76e-02 2.68e+02 \n", + " 24 25 8.6622e+04 1.03e+00 6.34e-03 5.18e+01 \n", + " 25 26 8.6621e+04 9.03e-01 1.53e-02 2.59e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 26 27 8.6620e+04 9.06e-01 5.87e-03 6.20e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 27, initial cost 3.2625e+06, final cost 8.6620e+04, first-order optimality 6.20e+01.\n", + "mean reprojection error: 4.239428688920704\n", + "max reprojection error: 14.81183633593874\n", + "mean reconstruction error: 0.25011290235774297\n", + "max reconstruction error: 1.2736186672016845\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "8 images with total of 1272 features\n", + "image 0 reprojection errors: average:23.77868769731182 max: 212.61223246648956\n", + "image 1 reprojection errors: average:23.97877768881696 max: 368.92023156153743\n", + "image 2 reprojection errors: average:23.2373559772466 max: 150.67143172973317\n", + "image 3 reprojection errors: average:24.500777451655722 max: 215.77527520567196\n", + "image 4 reprojection errors: average:24.098302922623464 max: 259.0542432221303\n", + "image 5 reprojection errors: average:24.451869185433324 max: 354.2270779128739\n", + "image 6 reprojection errors: average:24.279319764818606 max: 534.0462107117917\n", + "image 7 reprojection errors: average:23.379897428378335 max: 276.1006694300006\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.6784e+06 6.16e+06 \n", + " 1 2 3.5488e+05 3.32e+06 6.37e+01 5.32e+05 \n", + " 2 3 3.4589e+05 8.98e+03 1.09e+00 1.08e+04 \n", + " 3 4 3.4553e+05 3.68e+02 1.70e+00 8.99e+03 \n", + " 4 5 3.4543e+05 9.46e+01 2.82e-01 2.05e+03 \n", + " 5 6 3.4541e+05 2.61e+01 1.40e-01 1.08e+03 \n", + " 6 7 3.4539e+05 1.26e+01 6.69e-02 6.93e+02 \n", + " 7 8 3.4539e+05 4.00e+00 2.07e-02 2.50e+02 \n", + " 8 9 3.4539e+05 2.61e+00 1.72e-02 2.23e+02 \n", + " 9 10 3.4538e+05 2.47e+00 1.66e-02 1.64e+02 \n", + " 10 11 3.4538e+05 2.37e+00 1.60e-02 2.17e+02 \n", + " 11 12 3.4538e+05 2.06e+00 1.33e-02 2.71e+02 \n", + " 12 13 3.4538e+05 8.15e-01 4.24e-03 1.62e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 3.6784e+06, final cost 3.4538e+05, first-order optimality 1.62e+02.\n", + "mean reprojection error: 8.449306780257977\n", + "max reprojection error: 31.892610346765885\n", + "mean reconstruction error: 0.49416029797092004\n", + "max reconstruction error: 2.664382401654507\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 64, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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q3G43zp07BwCiGLTZbAkTIyiVhRJSwLkiCELhQUSIEAaDQXFfhJF1VBBSKNKgApBCQWpvv1xgWVasFSw2hYpNQgjGx8exsrKCQ4cOQa/XbxCUKpUKTqcTTqcTABCNRuHxeLC8vIyxsTGoVCo4HA44nU5YLBbZLD1oBJAiBeE7Kpx38fW68YJQiBCyLEsFIYWSBBWAlPMe4caRS8o3mUppAhFSvlarFT09PZKFm0ajQU1NDWpqagCsT4Bwu92YnZ2F1+uFTqcTI4Rms5nebBVMJUYAs53v6QSh4NnJsmxCypgKQgqFCkDKeUwhKd9kSmkDk68AXFlZwdDQEDo6OkQhly9arRZ1dXWoq6sDAASDQbjdbkxOTsLn88FkMomC0GAw0Jutwqi0zyNX0ZqqhlAQhMLv41PGVBBSzkeoAKScl0jx9ssFJUcACSEYGxuDy+USU75yYzAYYDAY0NjYCEIIAoEAXC4XRkdHEQwGYbFYxJSxTqdL+z40BVx8KvH4Fhq1TCUIY7GYWLZBBSHlfIQKQMp5RbK3nxziT3gfJQrAcDiM/v5+2Gy2nFK+hcAwDEwmE0wmE1paWkAIgdfrhdvtxunTpxGJRBI6jDUaTdHXVEwqTShUagpYzjWnEoTRaHSDIBQmlVBBSNmMUAFIOW9ITvnKeUFXYgpYSPl2dnaiurq6BCtLDcMwsFqtsFqt2LJlC3ieFzuMp6enwfO8KAip/yAlFcUWrQzDJHS2pxKEyXOMqSCkVDpUAFLOC/Lx9ssFJUUAS5HyLQSWZcXoHwDEYjFRELpcLoTDYYyPj4uWM6WIWubL+ZhOLQdCI0epSCUII5EIwuGweP0QBKEwx7jSjimFQgUgZVOTbA9RrJuIUmYBCylfu91espRvoajValRVVaGqqgqBQACjo6Mwm81YXFzEmTNnoNFoEixn6I32/KPcolWqIBRSxlQQUioBKgApm5ZCvf1yQQkRQKWkfAtB+Jxqa2tRW1sLYF3UCulin88HvV4vRhDjJ0NQpFFuMZUPSltzvCAUvouRSASRSATA+kNacg0hhaI0qACkbEqi0Sj8fj90Ol1JnsZL3b0avy1CCEZHR+HxeApK+SrpBhuPTqdDfX096uvrQQgRLWcmJibg9/thNpsTLGcomw/hIU6JxI+mAzYKwomJCWzdupUKQorioAKQsqkQGj0ET7o9e/aUZLulbgIRCIVCGBgYEFO+Sr1JygXDMDAajTAajWhqagIhBH6/Hy6XCyMjIwiHw6LljMPhyGg5c76itGiaFCppzcmCcGVlBVu3bt0QIUxuKqFQSg0VgJRNQ3zKt5SCDCiPf93y8jKGh4fR1dWFqqqqkm67WOR6HBmGgdlshtlsRmtrK3ieFy1nTp06hVgsJnYY2+32ireckYtKEVMClSQAkxEyEPERQkIIwuEwwuEwACoIKeWBCkDKpiDZ1FWlUpVUkJVSAPI8j1AohLNnz6Knp4dGueJgWRY2mw02mw1tbW3gOE7sMJ6cnAQhBHa7XRSE8YX95wu0c7l0pDrWqTwIkwWhMLZOpVKJXcYUitxQAUipaNJ5+5U6Aliq7YVCIfT394NhGNlTvkq4ycq9fZVKBafTCafTCWD9QcHj8cDlcmF8fBwqlUpMF1ut1vMi8qKEzzlXKnHNgLR1pxKEwkOeQPwcY6HLmEIpFCoAKRVLpnFuDMNsuhRwfMp3eHi4KF6GSqCYx1GtVqO6ulrsko5EInC73Zifn8fIyAi0Wi2cTiccDgfMZrNijoncVNp+VaoAFMpRcoEKQkqpoAKQUnEkj3NLdYHN5JVXDIoZAeR5HqOjo1hdXS1ayvd8vYFotVrU1dWhrq4OABAMBuHxeDA5OQmfzwej0ShGCI1GY8rjVGnHjqaAS4cc66aCkFIsqACkVBTCiCaO4zLau2yWJhAh5et0Os+bLt9yChSDwQCDwYCGhgYQQhAIBOB2uzE+Po5AIJDQYay0CSu5UGnnUaUKwHwigNlIJwiDwWBCBzIVhJRsUAFIqRhyGee2GVLAS0tLGBkZ2VRdvpUEwzAwmUwwmUxobm4GIQQ+nw9utxtDQ0OIRCLQ6/XieVkpc4xpBLB0FEMAJiNcC4XtpBKEwsg6Kggp8VABSFE8yY0eUi6olZwCLkXKV8koVaAwDAOLxQKLxSJazszOzmJ+fh6Dg4PgOC6hw1itVubltRLFVCWuGSjPulMJwvhxmAASTKmpIDx/UeYVikJ5mVKOcysEuSKAQsq3qqqq5ClfJdxky739XGBZFmazGVarFR0dHeA4Dh6PR5xSwjCMKAhtNtt5aTkjF0o4N/OhFBHAbKQThLFYTHyNIAjVajVYlq3IY03JHSoAKYpFiPpJSfmWGznWJqR8d+7cKdqWlBIlH1+l4g7G8KNBL97XEoXNoEFVVZWYro9Go/B4PFheXsbY2BjUarVYP2ixWMomDCpRTFXimgFlrjtVDWG8IGQYJiFlTAXh5oUKQIriyCflW8nwPI8zZ87A6/WelynfeMrdBJIr7kAMwSjBajAGmyFxyohGo0FNTQ1qamoAAOFweL2hZHIG0aAPOp1OtJwxmUz0JpsBJQopKSghApiNVIIwFothaWkJwWAQjY2NVBBuUqgApCiKTN5+m5FgMIj+/n5UV1fj0KFDOe1vpd4UlQpPCB46MY+uOjO6GyyS/mZrlR53H7Ci1WnI+lqdToeY3oZfz/rwmt1d6HBqxHSx3++HyWQSI4QGg6Fon20lnjeVIKRSIVzHKgnhuitEBRmGQTQaTZi0FF9DSAVh5UIFIEURSPH222wsLi7izJkzeaV86QW3OIwtBTDjDkkWgLlSZdKi3qpDs10Pg0ELg8GAxsZGEELg9/vhdrsxOjqKUCgEs9ksRgjljgpX2vlTiaIVWF93pV7LBNEdP8cYeMWKK14QJs8xrsTP6nyECkBK2ZHq7bdZiE/59vb25mUfIqRKN9uxKmcKmGUYvP/K9qIeU4NGhbuPtGz4OcMwMJvNMJvNaGlpAc/z8Pl8cLlcOHXqFGKxGKxWqxgh1Gg0Kd5dGpWUYheo1HO9UiOXQPq1pxKEkUgE4XBYvH4LglCYY1yJn935ABWAlLKSi7ffZkBI+dbU1OSc8o1H8Dms1JsLACDiB7t0GkzUD2KsBl/VAaC8+6NRKeN4siwLq9UKq9WKtrY28DyP1dVVuN1uTE1NgRCSYDmTS4dxJYqpSlwzULnrBqSL10yCEFg/lzUajZgyPh+u85UCFYCUslCqRg8lXYCFlO+uXbvgcDgKei+l7FO+sNPHoBn4ERg+Kn5GRG9H6MDbihKhIoRgYNaLrdVGmHXyXfaKFU1bDUZh0avBvvw5sywrRv+A9Q55j8cDl8uFs2fPgmXZBMuZin4wSEGlplIr+SGN5/m8vCzjBaHw/YhEIohEIgDWz+XkGkJKeaACkFJySuXtJ5hBl1ss8TyPkZER+P3+vFO+yZR60omcMK4xaE/cD95YC6Jer20jABDyQPf8V6GyXi/7Nj3BGH7ev4DdjRa8dl+9rO8t9/nlD8fwpccmsKXKgDv7mlO+Rq1Wo7q6GtXV1QDWb7Aej0d8yNBqtQmWM8ldnuX+TuRKJa4ZqNx1AwDHcQV7V8aPpgOoIFQaVABSSorQ6FGKlK8S0qTxKd/Ozk7Z9rfS7FLiUY/9FkRtANRJjQ16O5i1aVjXhgFcKus2HUYNbu9pRKNN+fN7jVoV+trs2Ntklfw3Wq0WtbW1qK2tBbBuKO52uzE9PQ2v1wuDwSA2lFSiKKnENQOVHwEsxhxjgApCpUAFIKUklMPbT87xbFKJv1HJmfJNphABSAgBTwAVW54bqmppGLypNvUvNUaYfGeLst3tNaaivK/cMAyDq3fWFPQeer0eDQ0NaGhoACEEwWBw3YNwfByrq6sYGhpCVVWVaDmjdCpVAFbquoHSzTEGEgWhkCGKF4TJXcYUeaACkFJ0eJ7H/Pw8VCoVbDZbyS6IpRaAgigjhMie8k23rXz47G/PgOMJPvrqjrLcnIhKCxAOQIr0EuFAWHkFSYwnUJdJ7MoBIQST7hBaHfq8Pi+GYWA0GmE0GtHU1IQXXngBLS0tWFtbw8jICMLhcEKHcTHO10KpVCGVbx2dEihH9DKVKTUhBOFwWGwqUalUYnRQ6DKm5EdlnpmUiiDe229tbQ1arRZ2u71k2xdqAEsFwzAIBAI4efIkamtrZU35ptqWsG8xjoc6h+7VbTVGLHgjZbtwci2HoZp4HMTSmPgLQsBEg/BYe9Eg07Z+e2oRx86t4n1XtMOir8zL3fOTq/jlwALe1NeMjtrCo5iC5Yzdbkdrayt4nofX64XL5cLMzAw4joPNZhMFoRIETCULwEpcN6CM9HUqQcjzPEKhkPgzQRAKEcJKPd7loPzfbMqmJDnlq1KpSp6OLXWjRDQaxfHjx9Hd3S17yjcZQQB6QzH82+/P4MhWJ67trpP0t7ccSt1YkA1vKCaLiOLaroRq5nkw/kUQYzXAsAAfA+ubB+/cAb+6reBtCLRVGXFixgujtrBi9nLS3WBBlOPRXiVPZDRZTLEsC5vNBpvNhvb2dnAcJ1rOTE5OAkBCh3GhjQFyrLlSqNTuZUAZAjAZKgjlhQpAiuyk8vZjWRYcx5V0HaVKAfM8j+HhYUQiEVxwwQUwmYpfayYIQIOGhV7Doq3KWNTtnZ734ScvzOKO3qaCo1DE6ETkyPuhPvU/UC2dAmFUAMMgtuUSxDpvBDk+KNOqgc46M/72VWbZ3q8cGLUqXLg1t0kxhaBSqeB0OsXpNLFYDG63G8vLyxgbG4NKpYLD4YDT6YTFYimJSKhUAahEESWVSlh7OkEYCAQwMjKCrq4uKggzQAUgRTbiU77JjR4sy4qjg0pFKVLAgUAA/f39qKurg9VqLVm6TBCAahWLj1zbWfTtNdp02FZjRINVnpFkxFyHaN+7EQ15wESDIHoboCmuiD1fSRZPuYoptVqNmpoa1NSsN6ZEIhG43W7Mzc1heHgYOp1OTBebzeai3GArVQBW6rqByhCAycTPMY5EImIQIBgMJjScUEG4DhWAFFnI5u1Xjo7cYm9zYWEBo6Oj6O7uht1uh9vtLtk+lrq+0WbQpPWkKwi9HURvl/99KQCAtVAM//HHs3hVVxWOxEURM930sjXNaLVa1NXVoa5uveRgYnEVX3n8LK5p9cBIgjAajaLljMFgkOUGW6lCqhJFlEClrz1+6oiwH0KEkArCdagApBSMlHFu5RCAxaoBFFK+wWAwoctXbm8+Qgj+PObCnkYr7MbE2a/F8AE8ny585ws6NQs1C5jipp9kOm9Gl/z44XMzeOsFLWh1Sqs51Gh1MJtN2La9GS0OPQKBANxuN0ZHRxEMBmGxWMQIoV6fnw9jpdbSVeq6gcoWgBzHpZ1jnE0QCjOMzwdBSAUgJW9y8fbbLBFAIeVbX1+Prq6uhIuD3KJsxR/B/w3MY8kbxusOJHbMKs0IOhTl8IVHxnHNrhocarWXezlpifEE33l6Cpdsc2JnfeG1gUr6DFKhU7P46LU7Nvw83U3NqldDp2Zh0klv9Giy6/H3cdswmUwwmUxobm5eb1TyeuF2uzE0NIRIJJLQYazRaDK88ytUcgSwEtcNVL4AlNKslEoQchyHWCwmvkYwpVar1WBZtmI/z1RQAUjJi1zHuZVLAMp5g56fn8fY2JiY8k21PTn3sdqswzsuaUs5vUJpApBlGMR4wB2IZX9xmSCEgAEQjHA4NeeVRQACxRkF94U/nsW1u2rQu8Uu63tno9aiw99dvV2292MYBlarFVarFVu2bAHP82KH8fT0NHieFwWh3W5PW0NbqUKqkkUUULlZASEFnCupmkriBSHDMAkRwkoXhFQAUnImFouJDR1Sx7mVwwZGLkHG8zyGhoYQDofR19eXNmpRDFG2tTp1x63SZgFr1Sw+cd3GSJNSODnrxf8cn8N7L2/HX1/RntPf/mJgAQwDXL9bms1OoQiejhyvHIEvFyzLitE/YP1aIgjCiYkJMAwj/t5msyVEZirxRlup6waUH93ORLoUcK6kEoTJ979KFoRUAFIkk5zyzeVEr9QawPiU786dOzPucymjcnJva3FxESMjIwkF/Eaj8rtyl30R/PdLc3hjTyNshvTpRIYBWJYBm8dEkGl3sJAlJhCIcPivxyfw1sPNqLGk7qjWqVl8/NXZxfTIoh/LvjCOtDtyvukQQjC04Mf2GiM0OZiIy41arUZVVRWqqqoArHtput1uLC4uYnR0FGq1Gg6HQxwLVmlUegSwUpGaAs6VzSYIqQCkSILneUSjUckp32TKEbEqNAUspHx3794Nm80maXul2ke5BCDP8zhz5gy8Xi8OHDiAaDQKl8uF0dFRhEIhxY8I84ZjiMR4BCJcRgG4q8GCXQ2WvLbxV5e25bm6jaz4I3AHophwBdMKQKk8+OIsIjGCI+25m45PukP45cACruisQk8JajaXvGGcWQrgSLs947VDo9GgtrYWtbXrs6LD4TDcbjcCgQAGBwdhNBrF89FkMin65gpUdgSwkimV8E4lCKPR6AZBKIyuU5ogpAKQkpF4bz8AeX+pKikFzHEchoeHs6Z8kylUlBFCcGJ6DdtqTFknbsghAMPhME6cOIGqqiocPHgQ0WgUWq0WJpMJLS0tG0aE8TwPu90Op9OZdSLEVx6fgFmnxlsOF8E6Jo72KiPem2NKNxMPHJvGhCuIj12zvSgX6ma7Hp+8rgMaVeHv/YErtyIU5cAwDNZCMTxwbAav21+Hemv2TtsWhx437q0ruoG4wIMvzmF2NYwDLVYYNNIjMzqdDvX19VhaWsK2bdsAQEwX+/1+mEymBMsZpVHJEUAlCZVcKVYEMBvC1CuBZEF4+vRpjI2N4c1vfnPJ15YKKgApaRFOXo7j8or6xVMpKWC/34/+/n40NjZmTfkmU+g+rgZj+MGxKeyst+Dui7ZkfG2hAtDlcuH06dPo6upCVVWV+F7xEYvkEWGxWAwejwcrKysYGxsT03PCRIj4Y7Xki2DFX1rjbzmYcAXB8cWL2jAMA61anvc2alXiiLtIjEeM4+ELS5u2wzIMOutKNyHlL460YNkXyUn8xSPYqej1ehiNRjQ1NYEQAr/fD7fbjZGREYTD4QTLGZ1OHtPyQqhUAVjJ9X+Aco57siCcmJjA0NBQGVeUCBWAlJRI8fbLhXJ1AecyfWRubg7j4+OSU77JFCrK7EYN7r5wC1oc2SMZ+W6LEIL+oVHMLCzjygsOib5swmec6T3VajWqq6tRXV0N4JX03PT0NLxeb0L94CdevaNkEQRCCPpnvehusGQ0MJbC36ewTElHjCf4wuMz6HYA2+VrnM2LarNW1kio3Bi1Ksm+gqlIlUplGAZmsxlmszkhYu12u3Hq1CnEYrGEDmOpkXw5qdQUcKWuW4DjuLJ83tkQotZKgQpASgK5ePvlQrlmAUsRSRzHiR5luaR8k5EjLbtTYp1aPtuKRqMYGBjAQ6NRmKxOvFpChGRsyY+Z1RAu3V614XdCeq6+vh6EkAQD4FAoBIvFIgrCXOoHQzGC+bWQpFQmAAwvrJsX37S3rqQzc1kGiMQIhpZLZ30T5dYfokrduBGJ8Tiz6MeuBvlGvbn8EfgjnKQHHimCJD5i3dbWBo7jxA7jyclJEEJgt9tFQViKFKFSIlG5UqnrFihXCjgbfr8fZrNyZpNTAUgRydXbLxeUagQdn/JtbW2tmDR3rgJwdXUVJ0+exNatW3HPdge8oaikff3t6WWEYxwu2ebM2gHt49Soa2hEc3PzhvpBjuPE1Fy2m+9PhqOwLE7gn27ohEpCRG9bjRG3H2pEl0y+flJhGQYfvrIZLpdL/CyKHTX5x1+fAQB8+vriz3+O58WpVTw+6oLVoJYk2KTwxccmEOF4fOaGzqzHLZ+IlEqlgtPphNO5/lAglDC4XC6Mj49DpVKJ56TVai2a4KnESFqlC0Clrt/v96OxsTH7C0sEFYAUABCjfnKlfJMpx0UwWw1goSnfVNtTmg0MIQTT09OYnp7Gvn37xPRDnVVafdTbL2xBlMtuwhuMcvj8I+OoMmnxd1dvS1k/uLq6mnDzFaKDVqs14f2va1ejtr1ekvgD1qNhB1py+/wCEQ4ji37sa7LIcm5+48lJMADeeXHm2s1CuWirA+WoztrfbEWVSYtme36j3FLxjota4Q3FJB1/OVKSEZ6Bw1klljBEIhG43W7Mz89jZGQEWq1WPCfNZvkinZWIUgWUVJQaAQwEAjQFTFEOxUr5KoF0ETkh5RuNRgtK+UrdXj4EIhx++sI0Xn+gCeYUHcFSBCDHcTh58iQYhkFfX19eF0StmoVWnf2cMGhUuHZXDXY1pI7CJfu9RSIRuFwuzM7OYmhoSLT3cDqdqDYw6Gm1gxCC35xaQovDgN2N+Vm4pOM3pxbxzFkP6q3tklPNmTBpVaKBczFYDUZh1atxza7aom0jE3qNCjtq5b1xNeUgJgsVgBxP8Olfn4FezeKTr+kAAGi1WtTV1aGubt3gOxQKwe12Y2pqSqxpFSKERqPxvBKElS4A850EUmx8Ph9NAVOUQaHefkonlSATUr5NTU1oaWmRdZ/ljACeXfbjxPQadjfZUs7WzbYtYT9bWlrQ3FxcKxaBKzurs77mqXEXdGoVDrXaEuoHg8EgXC4XxsbGEAgEcPr0aTgcDpxZ8GPKHZRdAF6zswbba0yoK9CLT/gM3txXvGO8Forhu89Mo7PWhFd3l0cAlptkAfiTF2ahYhm84UCDpL9XsQz2N1vRlUHE6vV6NDQ0oKGhAYQQvDixjP98ahq3d7gQCwdhNpvFCKHQPLVZqXQBKNckELmhNYCUsiOXt5/SSRZJs7OzmJiYwO7du2G1WouyPbkigDvrLfjYqzthN6aOTiaL20lXACqWQZPdgPn5eTG1XYz9LIRfDiyCZRkcan0lZcswDIxGI4xGI5qbm3Hs2DE0NTXB5XLhAqsHhOdw5kwETqdTtuJ9k06NvU2Zj81zE2481L+Aj1y9PaMvY7EfnKx6NQ612NCdJrpaKRBCEOWIpIhyqr+NP84DM16AgWQBCAC3H5Jee8UwDCZWY2A0euzc1QGDhoXP54Pb7RYbxqSYpFeqnYpSU6hSUer6A4EAFYCU8kEIgcvlAsdxG2qvNhuCSOI4DqdPn0YsFkNfX1/agfNybE+uTmeWZVBlTt85myw2f/zc9Pq82hYOoVAIvb29sqW2/eEYYjxJOWmDJwTf+PMkttcYcVVXTdb3+rurt2Wt7WMYBlarFVarVezm9Hg8cLvdOHv2rDhPVvAfLNYDTJQHQCC5FrGYXLJ9Y3czTwj+MLSMvi32tA8KSuKTvzqDcIzHP9/UCTaP6078teofb+iQc2kpef3+Brx+/ysC02KxwGKxoLW1FTzPY21tDW63W2xyiu8wLtY1plRUegRQqeunEUBK2RC8/dxuNziOk6XxQcmwLItIJCJGlORO+SZT6iaQh066oT7L4T1XbMOtB+owfPoU9Pp6dHV1ybqfn/ntKHie4N7X7tzwO5ZhwPEE056QpPfKNK4tHSqVakP9oNvtxuzsLLxeL/R6fcL8Yrn2/cKtDly4Nfcxa6Vifi2M35xaQjjG44Y9deVeTlYu73Dipam1vMRfMuV+cGVZFna7HXa7He3t7QkPKRMTE2AYBna7HbFYTLHRqEwoVUBJRanHnNYAUkpOcqOHSqVCLFY677LktZTq4r28vAyXy4W+vr6SpEKlNoHwPMGSLyK5EzcVDMPgzEoY5lAQy8vLmDkzjL69u+BwpBcshBA8c9aNrnozHEbpvnxv6m1CKJp+v/7fZW25LL1g4ov3hfpBt9uN8fFxBAKBBP9BJUyDKBYNVh3uuawtp2aKcnJFRzWu6MheJ1pJ8ITgW09OYXejBRdufeUhJRqNwuPxYHZ2Fi+++KI4NcfhcBQ1ai0XlS4AlWpkLVyflAIVgJucVN5+KpWq5KbMwCsRsmJ/MYWUbzgcFm1GSoHUCOB3njqHE9Or+NQNO+E0SRdiydv6wIXrN9OzZ8+ip6cnq9jxBKP40XPT2NNoxTsuaZO8rW6J5tTlIL5+UBgPJvgPCtMgNlNqLh6GYbC1ujSzfKUg13d7yh2EVa/OK1pcahgAZ5b8OOcKJESLNRoNqqurodfr0dvbK07NEaLWOp1OfEgxmUyKEyuVLgCB8keJUxEMBhU1s3rzXA0pGxAaPZK9/cphyhy/3WJeWHw+HwYGBtDc3Izq6mqcOnWqaNtKRupxvWFvPWosOjgKqNviOA6zs7Oor69HT0+PpIudw6jFuy9rR3MaI99ipLDn18L42hPn8KGrtsKkK/7lJlX9oOA/ODExUbL6wfONQCSGb/x5EnubrbiygCgfTwi++NhZ6NQq/NMN6c2uCSEYWw6grcpY8Pi/QmAYBv98Y+qaxnhBHD81B4AYtT537hx8Ph9MJpMYITQYDGUXL5tBACoRYaa1UqACcBOSzduvHGPZgPVarmIKz+QuXyHyWUz84Rj+8f+G8baLtsAuUUDVWfW4aZ/07kVhO74whzqrDh6PB6Ojo7DZbOjoyK0Yvqu+tNG8sysBrIZiWPFHSyIAk0meBiHUD87NzWF4eBh6vV4UhNnqByMxHp/+9Rm84UA99jdv7vrZXPmn34xiaN6HoxKsgDLBMgzu7GtGVZbI+JQ7hJ+8MIsrOqoyjv8jhODzj4yj2W7A7T3FmcCQbixfJhFlMBhgMBjQ2NgIQgj8fn/CGMV4y5lylDFQASg/SuwIpwJwkyHF26/YQiwdxYo8CilfjuMSunylzgIuhHCMhz8Sw9iSHz11qqJt79O/GkYoyuF9h61YmJ/Htm3bEAgEirItObmgzY6eVltZozTxJJv/Cv6D8fWDgiBMdeMNRjicmPFmFIA8Ifj2U1NosOlw/e7yN2cML/gQ4wi6ZfZSjMdh0GBnvRl7sljrSCGbPQ+wbiL9mt216KjNXFDPMAx4AsysSmtSkhOpKXGGYWA2m2E2m9HS0gKe5+Hz+RLKGOItZ+Tq7s8Ez/ObqlxCKSjNb5d+wpuEZG+/TCdauWoAixF5jE/5Njc3J+yznL586XCatPjSbfsAAC6Xq2jbe8dFLXj6xBCCATX6+vrgcrng9/uLsi05YRgGGpX0Cx7HE8T40j0pGwwGNDU1JdQPut1u8cZrs9lE/0GtWo3Pv35X1vdkGQYMgCiX/37Mrobw4AuzeN3+BrQ6C6sZ+u7TU+AJ8K83b+ziTsVHfz4EQoB/ualL8jY+9Kpt+S4PABDl+LSRtFSsGztLi8L+bYFryxWOJwhGOWiQXxSNZdmEMgae57G6uipOKSGEJNS1FqPbtZIjgELwQ2kQQhQXBaQCcBOQnPLNdvKXuwZQLmZmZnDu3Dns2bMnZWdVqfezWDYwq2trGD89gKO728VB4um2xfFEEb51+fKdp6dwbjKGI4dLv+34+sEtW7ZsqB9kGEaMDlqt1ow3yLdf1LrhZzwhki1Q/jSygj+OrIBlGLz3iva89wkAPnB0K7gSiupcmV8L47O/G8Vr99Xjsh1V5V5OwXz8F8MIRDl8+to2WUSUULcqdPjHYjF4PB64XC7RF1MQhDabTZZtVroAVOLaQ6GQohpAACoAKx7B2y+50SMTlS4AY7EYTp8+DUJIRmPnUj8FFuO4zs7O4it/HIHGWo1La15JJ6YSgL87tYBf9M8X1F1cKIEIB6M2/4jEoRYr4FGGgE2uH4xGo3C73Zifn8fIyAh0Op04ASJbuu++Z6YwMOvFZ27ohF6T/fi8/kADerbY0GDLzeLF5Y+AJ0B1nIl4bdy4OykPKP98o/TInxxY9WroNKoNdjY8IXh2woM9RUxdF4M7ehvx4tQa1Gxx0n1qtRrV1dWorl6vt4xEIvB4PFhcXMSZM2eg1WoTLGfyWYNSRZQUlOoB6Pf7YTLJO0+7UKgArFDiU76pGj0yUc4UcKECyefzob+/H62trWhqaiqqyHP5I7j/6Um869J2SaJGzgggx3EYGhpCNBrFX13XizPLwQThkGpbDTYDNGoWpgIEWCGs+CN44NgMDrfZcUF7fgbKB1vt4BaUeVnSaDSora1Fbe36PN5gMIjJyUm43W4cO3Ys46zYVocBp+d90Ekcg6ZVs9iRpb4tFf/yuzEQQvBvr0ufqlZaesyoVeHeFOnmJW8EfzqzgihHoKy4SWZ2N1qxu9EKn89XEhGl1WoTzstQKAS3243p6Wn4fL68jNIrWQAqde1KM4EGqACsSFJ5++VCpUYAp6enMTk5mTblKzdD816cWfRhyh1EZ93GLy4hBN956hzaq024srNGNgEYCATQ39+PhoYGtLa2gmEYNDkTnxxTNbjsabLiC2/YU/D288Vu0KDVacD2mtRPuTOeEFb8EUlF/kogxhN85OEh9G6x4daDGztIDQYDqqqqoNFo0N7eLhbuC7NihbScw+HAlZ3VuLLADlkpvP3Cloy1h0qrQcpEnVWHN/U2odasRb+7uNsKRTl866kpvOFAPeqt8hhrl8uMWK/Xo6GhAQ0NDQlG6WfPnhVHkcVbzqRCqVE0KSh17X6/H0ajcnw7ASoAK458Ur7JlMsGJl8BGIvFRD+/Ys7yTeZAix0Mw2BHTfov7YwnhIW1MK7srJFFWAtpnO7ubtjt9rSvK+XYOamoWAY376tP+/v/fPQswjEeX3j9roqoU1Qx62nI+bVw1tcyDCPOio2vHxS83oT6QTnrtFKR6kElHqVOSEhHi8NQkjV7QzGs+CMYXw7KJgCVEIlKZZTu8/ngdrsxMjKCcDicMDlHKGlQwtrzhed5xQpAGgGk5EU2b79cKNcXOx+B5PV6MTAwUJKUbzJPjq/gkdNLaLTpsaVqowhkGAafeE1Xwn/nK8p4nsfo6Ci8Xi96e3vFC3E6lCgAs/G3r9qGtVCsIsQfsH6MP58hlQqsewN+7skV3M7ZEhoY0tUPCgJfp9OJDSXlmASx7Isk1AkqmVIIwBqLDh+9ZntB52YwysEQV6ahRBEV/6DS2toKnufFyTkzMzPijPhgMFiWLJEccBynuOMOUAFIyZNCU75KIRcBSAjBzMxMyVK+UY7H5343ihv21oteZkfanagyadGSZnJGMvn6DobDYfT398PpdOLgwYOSvcMqTQBWm7WSRUexb/ocT8AyhdfDqVgGUW59KkWmDtZU9YNutxsTExMJaTmn07mhflBOCCEYX+XxnV+N4C2Hm3C4Lb9azWys+COYcgfzMswOx/iEWslSRS1zsaFJ5uxKAJ//wzjujDumlRBtZVkWNpsNNpsN7e3tYuR6ZWUFw8PDGzqMlRhZS0bJKWDaBELJiVgsJsnbrxKQKgCFlC/DMCVL+fI8wTmXH384vSgKQJNOjQMtdsnvEe87uO75BLBZIgoulwunT59GZ2en2NWX67bkopLPrVzgeIK/+d9T0KlZfPa10rzx0qFiGXz00mps3dqS098lT4IQ0nJC/WC8/6Dcxr+NZhYXWxzoypIuLoRfn1zEojeCnfUWyY0vAPCj52bw1Fk3/vH6TthfHpVYCUKqyqSFQatCs/2Vh0UlRgCzIUSuDQYDdu3aBZZl4fF4sLy8jLGxMahUKsWPUlTqcadNIBTJ5OrtVwlIEYBCynfLli1oamoq0coAnUaFL922r6AUUHxU7t9+PwpCCP72mtSj2gghmJiYwOLiIg4dOpRz1CdbBDAS4/GL/jlc010Hc4lGsCVHbvJ9jz+ci6KjOwqbsTgpShXLQM0y6Ntil/V9c/H5iydVWk7wH5ycnAQA2O12OJ3OgusHCSEwali88UBxv1uvP9CA1WA05/NhX7MVL06vwaJ/5ZxVqrFvPFa9Gp9LMtquBOGaDkFEpbKciR+lKJQyOBwOmM1mReyvkiOAVABSsiJlnFslkqn5JD7lu3fvXtm+KIJQknIMtQWKl3iBW2vRwR+OpXxdNBrFwMAAjEYjent787qhZxOAwws+/PbUIqrNOlzWUfzu09ElP77wyDjeeXFrQXNyx5cDGFzhcWJmDZfuqJYkqgZm1mDWq9Geok4zHZlsUvKhf2YNT4278abepgTxkg/Jxr/RaHSDz5tQtK+Um24yBo0qoR5OKrsaLJtGSCk1EiWFdGtPNUrR7XZjcnISPp8PRqNRPDcNBkNZPjelCsBAIICqKmUZnVMBqCCSx7kV++JR6gurSqUS9y2eWCyGkydPgmVZ2VO+Qqq0FBeEeFF215GNkyAAYG1tDYODg9i6dSvq69N3zOayrVTsarDg767pkFy/WCgOowZ6jSrBdDgfOutMuHOXFofb7AhEOHz/2DT2NVnT+goSQvCNJyehUbH4goQxbXIRifEJDwx2gwZaNVtwBDQVvijwq7Ewbj24HZ1aFUKhkBgd9Pl8MJlMYsNJtkhyqu98vpHLYhCKcvjBc7O4cU8tal4+l9Jdp56dcKPapMW2NLZDckAIwU9fmkOVUYujXbk9SFWqcAWkrz25lCEQCMDtdmNsbAzBYDDBcqaYta3xKHWOMbWBoaSFEIJoNAqO40oS9cslMiYXqVLAxU75CttMFoCEEIwvB7C1WpoxqhQyiTIhwjk1NYV9+/YVXAycTQCqWCavG2O+50SVSSuLAGMZBtUGFmqWgYphoWGZjI0jDMPgb45uLWj6SK785IVZ/OnMCj4TNzGj1WnA3UdyqwOUypIvAn84hrVQDEatCnq9Ho2NjeJN1+/3w+VyYXh4GOFwGDabTbzppqofjP98B2e9+OoT5/Dhq7eV7GEhE95QDK5ABNOeUEYBSAjB956dgVbF4N/f0F209TAMg8fPuKBimZwFYCVHAIHca4IZhoHJZILJZEJzc3PCbO342lZhhnE2p4N8UWoE0OfzlcS/NheoAFQAcnj75YowDaSUF6h4AUgIwfT0NKampmRN+abaZiqhdHLOi+89M4lbDjahV6ZOyLTzeTkuwcdQysUpEOHw7ScncOuhJtSl8CUrZhfw/x6fw5IvinddnDqKKRcr/ghCUX7DCDDh/FezDO6+MPsa2nJI/cpBd4MFz5x1w6JXwxMo/vY6ak3YXmNMGaVjGAZmsxlmszmhftDtdmNqagqEELFo32azbThnjFoVNCwDbQEdsHJSY9HhfVe0Qx1Xi5tKADIMg7971TaYdbnd6MeXA2ivyi01+bnX7cwrQloJtYvFJHm2Ns/zWFtbg8vlwvT0NHieTxCEckXtlCq8A4EArQGkvIKc3n65Uo5pIEINoJDyValUOHz4cFGf1tJ1y3bUmvGaPfXobpRvKkWqi73f70d/fz9aWlpy8jH0hWPwhznMroYkC0COJ7J47P3pjAt8DuLyvqenYNCqcNuhjdMyMvHp/zsDjif40q3dFXWj3N1oEaNOpbLikSpAkusHY7EY3G43lpaWMDo6CpVKhUgkAq/XC7PZjK3VRvzHLcWLoCUzuuSHRadGnTV9qUCyHUu6qHSrM7eI5fHpNXzl8Qm8ubcJl2aw7Ekmn1pGAFD552FZPg7Nohq8czu4pl5AXViJRCUjWMoIBvccx8Hj8Yh2SHKZpSs1AkhtYCgiwoieU6dOYffu3SW/AZZjHjDLsgiFQjh27Bja2trQ2JibYMh3m6kEoFbN4rId6VM6i94wPv2rIXz8us6UAkwK8/PzGB8fx+7du2G15iY0ay06fPja1B3EwEYB+JGHTsIdiOJLt+8tyM8MAP79DbmlcqM8QSyUuuElE++9vA2+CJcyulNJHodKFq9qtRo1NTWoqakBAKyurmJkZGRD/WCmsWByQQjB5x8Zh1bF4j9zEJ2EEMR44PS8Dzvr84+gdNWZcOPeOhxoya1JKcYT/Oj5GVy8zSmt0YgQaF76DppPPAiGAdRaLQAG0NkQuvJTII6t+e1ACSnF90+lUqGqqkpsjIg3Sx8dHYVarU6wnJH6PVOyAKQpYIoY9QPWa+DKcQMpdQSQEIKlpSWsrKzg8OHDJQuF57ufi94wAhEOC2vhnAUgz/MYHh5GMBhEb2+v7D5uwMbUds8WBx4dWcoo/iIxHu//6QBu7WnKKH5zTXe946L8UsXFLN6npEar1UKv16O7u1usH4wfC2a1WkVBmO28XfZF8A+/GsE9l7VJEmYMw+CeS9tgM+Z22yGE4NdjQYz1j+NT13eg0ZbfA5leo8L1u+ty/rsYx2NsKQAVw0gSgKrR30Fz6n/h09qg0uig1q3XujEhD/R//DiCN34L0JS/3lJpJJulh8NhuN1uzMzMwOv1Qq/XixHCTNNzlJoCpjYw5znJKd9yPqWUMgIYi8UwODgIQgiqq6tL+iXIdzrH7kYrvvOWgzn/Hc/zeO6551BbW4uurq6iivv4/Xr9wUa8/mDmiCrDrHdZPj/hzigAKYlwPAFPSFpxXUnRSuCViGV8/WBLS0tCjVZ8/WC6KRAxngCEIBhdv46sBqOwGTKLxu7G3CMghBBc2W5Er74WDRlSx8VCr1Hh767eJi2yTgg0J38CXmcBogziv/1EbwfjW4Rq6mlwW68s2noLRSndyzqdDvX19aivrxczZvHTc9JFr2kEUDpUAJYIpXn7lSoCKNietLW1wWaz4cyZM0XfZjzFmJghwPMEvnAM1pdvesvLywgEAujp6RFnwMY4Hv/xxzHsarDgut25274QQvD0uAt7m2wwx/nL5ZMm1ahYfDsPUVtq4veN4wkeG1nBRdsc0KepxYrxJKFpQG6+f2waMY7g7SkinT/tX8Fzk2v4asuWtOtTEoQQzPs4vPjsNN7U25RQM5pcoxWLxRKmQKjVavGGa7FYUG/V4b9u3wMAODGzhkeHV/CGg/UJ0zDkWrPdoEZfCfws0yG5DjDiBRtYAm+qBYn6geTTklVBtXRS0QJQiRE0hmFgNBphNBrR1NSUEL0+c+YMQqEQLBYLHA4HYrGYIgVgKBSCTqesGlAqAItMqb39pKJSqYoqAAkhmJqawszMjNjlW44B48UUuu/5ST8CEQ5ffeNeTE9OwO12i0aoAiqWASGAJ7DR/1AKs6shfP2JCVyyvQpvv7hN/HkxHiDK/VCSitPzPvzohVnwIHhVV82G34eiHO5/dhrba0w42lkcgdDdYIE3jam3UcOCAYri/1cMCCF4YjqMmbALN+2tyxixS54CEQ6HxQ5Or9cLk8kk1mhtrTJipSmCugJ9INOtWcq5GYpymPaEsL2cpQUqLQgYgPAAAZhkBcjHQDTKLn1QogBMJlX0WrCc8Xq9eOmll8QZxsUYp5gvSjuuVAAWkVJ7++VCpqkchSKkfDUaTYLtSbk6j4u1zXdevAWPDi/i5MAJWCwWHDp0CM8880zCaxiGwYeu3pH3Nhpterzniq3oqFVW7UixESKAO+vNuOeyNnTVpb5p6l42X85lCgjHE7CMdMHbm2Fk3Gt2OnBZi6bs3+3T8z6EopykBofXdhjR3L4ja7o2GZ1Oh4aGBjQ0NIimvy6XS4zANFqtcK/wsnu8SRWA//HoWYws+vGF1+0S5wiXHLUeXFMvVDPPg0CfuG6ynv0ZshxGtYR0ebmoBAGYDMuysNlssNlsWFpawoEDB+D1ekXDdEJIgiAsdYRQqWUiVAAWiVy8/cpRc1EsYRSf8k3u8i2HAExOlQYiHL7z5ATuvKC14AvwFgvQa1hCS8sOsXA5Gz99YQbuQBTvvKRN0usZhkHPFnl8CiuF+O+CimWwvzl9BzXDMHjrBbkZMN/3zDRULHL+OyXz1LgbPCHY02QFx5O0EUlC1n9XkyVSF4hw+NBDp/HGnkZcvM254ffxpr/xEZh4j7f4+cWF3HClXh/vPtKCgRlv+cTfy0T3vQWq+X6ofR5A+/J1IRYGE3Ij0HI5vjHIwnTmLD5xXfou/3JSiQIwGaGDON4OyePxwOVyYXx8HCqVSvy91Wotyf4qLQgEUAEoO/EpXynefukmVRQbuZtA4lO+6SZdFDvtnIpk0Tm84MWzEx7sb7Hj4u3SvcCCEQ6Gl6dNEEIwOTmJubk5HDhwIKfxPr8/vQieQLIALJS1YBQf/8VpfPTajrztbJREJMZDxTIF+R3WWrSw6DbXpe/OviZwhOA9Dw6C4wm+/sY9Bd1sWGa9tnLRG5b2+rgITHt7u3jDXVlZEesH87H0AKQbKtdadDjaVf4aK2LfgtDV/wr/I/8GZ3ACTFQNaPSI7r0T6H4D3rIQRH2KZhZCCCJcevFeKjaDAEwmuZwhEonA4/Fgfn4eIyMjRZ+vXer7nlQ211WwzBBCEIlEcmr0EIRYqQWgnNG4aDSKkydPbkj5JiN3Q8avB+fx0PE5fOm2vdClKdIW9lOIIuxrsuFzr+vOGgGJZzUYxXt/0o+eLXb81SVbxPR2b29vyn3NFLH46h37czJZFvjZ8TmYdSpctVNapFFgyh3Eii+CkUV/XgJw2ReBOxDFjtrS1S2la3AhhOCeBwehZhl85eXmg3y4YU/uViBKR5hLfFVnNRa9kbTnn9Roml6jwtff+MoxzrXRJlX9oNvtFusHhVpZoYMz1ZqWfRGccwXRalBGV2ouEEc7Jna+G0yDEyYtC2JwAqr1yGR3Q+pO0K89MYnxlQA+fX1H3ubTcrAZBWAyWq02wXImFAqJ03OE81OIEBqNhY8LDQaDipsDDFABKBtC1C/XcW7lSIsC68JTaEwphNXVVZw8eRLt7e1oaGjI+Fq5L+Kji35EOQJ1BnsGlmXxgxcX4Ym58YnXdEKjYlGfo4+YRaeGXqPCoUZDVhPrbDOWVSwD1YbWwOycW/GDYZicBeCuBgu+deeBrFEFQgjOnj0Lv9+Pqqoq0Qfu4f55hKI8tqUZRVZKGIZBZ50ZzfbKi2TOeEL4wh/H8cnrOmDRZ7/sCg8JuR7z1x/I/B0Ecv8eLvsiePDFWVzZUY2uPI2Yky09AoEA3G43RkdHxQ5OQRAK9YO/GlzEij+CW3fKN6+7lPA8j+cWGayECG7ep876rT/Sbsfsagh6GgEsOXq9fkN9q9vtxvj4uDjCTTg/9frcrz9KnAICUAFYMIWOcyvHRA6gcOEppEFnZ2fTpnyLzXuu3Jb1NQzDoMqogte3ccSUVFiWwT9cUYuJiQns2bMno5eTcFzlvoD+9dHtef0dwzBZ7Umi0Sj6+/thMplQV1cHj8eDqakpAMDhKhu0JitAyLqRYAnIdLP/m6OFT1HIpQnkxalV1Fl0G+YVC0gt7j6z6Ic7EMWiNyxJAL77x4MAgK+9Mf9IZyqE9X77qUkwDIO7j2SvgzTpVNCpWdlq6+LrB5ubmxPqB2dmZsT6wavabGD0TqjCXnAVKAAJIXh01APCsLh5X/ao8/4WG/bnOKWkGFSyAJSj2SL5/CSEwOfzwe12Y3h4WDRMFyKEUhqeqADchMjh7VcuAVjIdqPRKAYHB6HT6TKmfJUAy7I4us2Klpb8Cv55nsfp06cRjUbR19eXdWB5pY0x83q9GBgYwLZt21BdXY1oNCra2AijmVwuF55/fgJ6vR5OpxNOpzNt2k4uinkM73tmGhoVg7ccbs74uhhP8OXHJqDTsPhqhpSzlONw2Q4njmx1QKuSdsxqzFpZ5jonI0SnWYaBRuJaDBoV3nZhftNepJCqfnB1dRUulwueqQlwHCdOgci1flBueEIkR2V5nseHjrZBrdFWVASzkgVgMdbOMAwsFgssFgtaW1tFw3RhSgnHcQkdxqnuEcLYRaVBBWAeJHv7FdLdU2kRwNXVVQwODmLbtm2or8/d2FgqLn8EDmPh9hqF2N0EAgH09/ejoaEBra2tktZSSQJwdnYWExMTok9j8nFKHs0k2H4IabtcxoYpgbnVEJZ8EdiNatSas9eAqlkGH7xqK2rM2pxq4FKVADAMA51a+rn8jzd0Sn5tPvxFisgfxxM8dGIel++oQrVZPhuXXFGr1QkzYqemprC2tiaOBDMYDGJDSaYHkd8PLWFw1of3XdEmiwBz+SP46hPn8JrddRk70wV4nodOo4a6QjwiBTiOq1gBWIp6+njD9Pb2dnAcJz6wTExMgGEY2O12WCwWMZKY6xi4u+++G7/85S9RW1uLwcH1bIDL5cJtt92GiYkJtLW14cEHHxS7nP/lX/4F3/72t6FSqfDFL34R11xzjaTtUAGYI8kp30IvLOXojAVyF4CEEJw7dw5zc3PYv39/UZ9m3IEI3vPjfuxpsuLD1xZmlcCyrDh3ORcWFxdx5swZdHd3i5MRpEBQvMkjmRhb8uOZsy7c3tOcNXLE8zyOD54Gy0uLagoITvzxabuVlRVxbJgQHSzUViFXEb3kDcOsV2ctnP/U/51BOMbjm2/aK1nM7WqwgOMJ7ntmCnqNCm/qbcr4+ijH490/HkSL04BPvDp//8dikak+dcYTwi8GFhCJ8bgjy36WEpVKBZvNJqbjgsFgwoOIMAHC6XQmpOP+56V5RDn5vot6jQpaFQuLTprAUMpItVwphyuFXJSjoVKlUonXPmA9c+LxeDAwMIC//du/hcViQWdnp3gvknK9fetb34p77rkHb3nLW8Sf3XvvvTh69Cg+/OEP495778W9996Lz372szh16hR+/OMf4+TJk5idncVVV12FkZERSceBCsAcKMY4t2IaMmcil8hjfMr38OHDRX86tBs0ONBiw037G+AJRGHVq8HmmQ7LVejyPI/R0VGsra2ht7c3J0Pbf/q/Ybww5sN3OmPQ69dHxeW77lx54ZwHC2th8ISkbTIZXfThG4+P47Ddh36PFm++pDPhYpTL+RyftgNeuegtLCxgZGREtnRxjCdYC0bhNKX+HDie4H9PzMOoUeHOLCndT76mAyu+SM5j41Tseh3lHglzbDUqFizLoCnHRqNSwjAMeEIQjvEJornFocffX7sDzQ5lrT1eSMWPBIt/EHG73RgcHBTTcU6nE//5hp1gWVY2EWbUqvChV6WvOyaE4CtPnEODVYfX7W+o2FRqpa4bUMbaNRoNampqcOWVV+L555/H5OQkvva1r+HJJ59ET08PWlpacPToUVx55ZXYvXt3yvVeeumlmJiYSPjZww8/jMceewwAcNddd+Hyyy/HZz/7WTz88MO4/fbbodPp0N7eju3bt+PYsWM4cuRI1rVSASiBXL39ckHpKWCPx4OTJ0/KmvLN9mTMMAw+ePUO+MIxfORnJ9HuNOEDr8q/CUKqAAyHw+jv74fD4cChQ4dyvnHsbbLixNl5aFhgyhXAD5+bxh29zWhxFr/9/5ZDjeAJMkb/Hjk5jVNTy3jTgU4wqwzqbfLNbBUuejU16+PahC66sbExBINBWCyWhO7ibAgRwPc8OIhAhMPX37gnZTOLimVwtLMaDkP2S1m9VZfSf00K2SJ/8XxdYuPGqozTIKbcQQQiHDrrMqeZhOP6vWenEYryeMdFreI5wzBMSe1+pEIISXvNjX8QaWtrA8dxKQ1/Bf/BYooDhmHw4uQqWIbB6/Y3iD+TgpKihUoQUflSjghgNlpbW9Hd3Y3W1lZ86EMfwtmzZ/HHP/4R9957LwYHB/H1r39dklhbWFgQnTYaGhqwuLgIAJiZmcEFF1wgvq65uRkzMzOS1kYFYBby8fbLBaU2gQgp3/n5+ZzNjjORi/G1SatCT6sDl+6QbticantS0okulwunT59GZ2en6F2WKzfua8AWrH8phXRRtg7cQom3HUpX0y90bO81eHDL3X1w2szYV9RVIWFwe3yXp5AuFm7KNpttw80m/jv23svb8MxZT8bjaDdo8MGHTuMdF7Xgwq0bp1YokdPzPnzmN2fwFxe04GhX4TOMHxleRpQjkgQgwzC4dLsT51zBojSayE0u4kilUiXUD0YiEbjdbszOzsLr9YqRaSn+bvmIsq/fsTfh76Xw4Iuz+M3JJXzp1m6YUhiUT3uC+Orj5/CRa7bDXAIDc57nJZeFKA2lilfBSgYA2tvb8ba3vQ1ve9vbxOBSIaQ6z6Set5X5KZeIXMa55YsSI4DRaBQDAwPQ6/Xo6+uT9QuVTQDyPAFHCDSq9dTNXUcK6z7MFukkhGBiYgKLi4s4dOhQXh5P8Qj1azUWHd5/VX5Ry1y2lQ2O43Dy5EmoVCoclvmzlEpyl6eQLhbqLIUOT6fTueFBY2e9BTvrM6de1SxTKoca2Whx6LG12oRdDfLMeL71YCMiMemlDlurTdhanTnaNzTvwwPPzeATr94hGk2Xg0KiY1qtFnV1dairq0uoHxT83eL9B3W6V6LD33pqEk+Nu/GV23bn9BCXa3kBAGhVLMAgrZn9pCsIf4SDJxgtmQBUooiSghIjgMC6DUyqcaEMw0gW23V1dZibm0NDQwPm5ubE92tubhZtuwBgeno6rU9tMlQApqBQb79ckMuQOVfSCaNipHylbFe4yP/N/6yPsvrPWzeOsgpH14VyugtlKjKlgIXaRr1ej97eXlk+5/j9K3ZaJ5vpdCAQwIkTJ9DS0oLm5sT6uCVvGNVmafYUuU6ByIZGo0FVdTVMNic6taqEm3IwGATHcVheXkZDQ4OkdLHdqMF33lzsmKa8mHVqfPp6+WbBGrUqGLXZvxe5nJN/Gl3BxEoAwShXdgGY/N0MRDh4QzHUJaX0oxyPtVAMVSlqRpPrBwkhYmT61KlTiMViop2HCgQMUNBYthAn7bvz2n31eO2+9NfaC7c6SxrZrmQBqNS1+/3+grNoN954I+6//358+MMfxv3334+bbrpJ/Pkdd9yBD3zgA5idncWZM2fQ19cn6T2pAEyi2CnfZJSSAi5WyjeZVAKQEIK33PcCNCoWV3XVYNodTHncP/GLIQDAZ1/XnXU7ot9ZGsG5traGwcFBbN26VVahK4iyf//DKJ6f9ODbdx4oWho4U7fs0tISRkZGsHv3brFRQ2DGE8RPnp/BpTuq0bPFvuFvfzmwAKdJgwu3OuEJRPGj52dx6XYnuiU0QUjlnT8cQDjG4ztv3guDwYCmpiYxXXzixAkEg0H09/dnTRdTisfbLmzFWw43Q6ti8cfhZexvtqZtxikmqUTr/c9OIxDh8NdXtCcIrHf/eBChl8+rbMbvDMPAarXCarUm1A+63W7s0XqwbxeLiYmJvOoHeULwk+Eonlwbw0euKW4mQG6UKqKkoOQIYKYBAsm88Y1vxGOPPYbl5WU0NzfjU5/6FD784Q/j1ltvxbe//W20trbipz/9KQCgu7sbt956K3bt2gW1Wo3/+q//knwMqACMIxaLyeLtlwvl6gKOF0aRSASDg4MwGAyyp3wzbVdAONYOowZ39KU3bL56Zw2kTlH79K+GwTDA+y5p3CCSpqenMTU1VZQJJkLNYYNND5ZhijrYPV4A+sMxMQI0NjYGj8eTtou5zqLDhduc6EpRL0YIwU9fmoOKZXDhVicMWhX0GhYOU/pIHCEEZ1eCaK+S3u171+EmPDri2nCTZlkWWq0Wzc3NMJlMiMVicLvdYrpYp9OJ3cVyzOiUi9FFH56e8OC2g41ljZZlI5cIoJploGZVWAvFcHreB52axUXbSl9jKTyMx3PLgQYspejoft+V7Ric9eY19Sdd/eDc3ByGh4c3lCpkOo4sw2Cnk8UVe3Ib3ZiORW8Yvz65iDt6m/KeaCQVKgDlJ1cfwB/96Ecpf/7II4+k/PnHPvYxfOxjH8t5XVQAQn5vv1woVwRQ2Ech5bt9+3bU1WUfV1Qo6SJy33vroax/ezSHObjCfSF+exzH4dSpUyCEFG2CiZByvr23Gbf3ZrYlkWtbkRiPu7/3EnRqBn+9d921PlMXs1rF4oL21DdyhmHw76/fJd5kdGo2pWlwPH8ec+OrT5zDPZdtkZyqumR7FS7Znrq5J17Yzq5FYTXZ0flyd3Fyulio4XI6nWU1o14NcYhxpGi1iHJ2DOeKVa/GnYebJaWYi0Eq0Vpt1qY0q+5usKC7IXOk5cWpVfzno2fxuZt3otaSvitcqB8kBju279AgEg4lzIeN9x+Mrx8UONygRndjdsNoKfxhaBm/ObWES3dUob2quK4ClSwAldrAQkfBKRSe5zE/Pw+e51FdXV3yiEK5BCAhBOFwGENDQ0VN+SZT6AxiqXz8NV0A1r94PM/D7/ejv78fzc3NaG5uLtrnXMpJIMK2dGoWjVYNOnRraG7uLFjI55rm299sxWv31mFfkzw3OwGOJ/jt6SUYNCze3Lcupg0GAxoaG/GiS40ju+zQcCG4XC5MT0+XJV0sfNaHWm041JrfHNfx5QA++asRfOr6jpQ39+EFHx47s4LrumvR4ijMuiffulRrmvnF054gPIEYdstYHpCMsOaTs1501ZsL7lyOcQSMxFSCyx/BN5+cxN4mC27aWy92tgv1g263W6wftNlscDqdaceBFcLrDzTgyFYH2pzyWTelo5IFIMdxKcV4uck1BVwqzlsBGO/tFwwGEYvFRA+zUlKOFHAkEsHAwIAYCSvll71UAjB+e8FgEMePH09ZD1eM7ZVq/wQBODs7i1tbg9i791BOT5kvTHrQUWuGRZ+fGbSARa/GrYekdZ1JhRACFcvg+t21Gzofp90h/OC5GSx6w3jbha0JM2TLkS4u9H2F7t10XbwtDgMONNtQlyFalQtyHoe//8UIohyPB+7an9P7ekMxeIJRSYKWEIKhxSC++NQEbj3YIHrs5Utfmx19bXZJr3UYNbiio2pDVDG+fnDLli0px4GFw2F4PJ6CJ+MA65H4Ykf+BOgoOPnJNQVcKs5LAUgIQTQaBcdxYht2OBwuy1pKPQpOeGLdvn07wuFwyb/o2fY3FOXgD3OokmEWKc/zYqrwkksuKUmKsNAIYCTG410/OI63X7wFF23L7n945swZcBwHR9suPPDCIt56pFVSl7TLH8G//HoE3Y0WfOqGnXmvF1jvvDw558OeRossvnLxQqIhxUSNFoceH71mO7ZVJ94Q1Wp1ghl1suVH/OziXCa8FJuuejO+d9f+tL83alWSBUs2hHNzaN6Hz/5+DF9O4z0nlX+6oQOeQCxnUXnPg4OIcATfv2t/1i5ZQgg6aoy4o6cJl24vbQ0iwzC4WELdY/I4sHA4jBdffBHz8/MYGRkRH0YcDgdMJpNialdTUcmj4JQavaQRQIWQytuvXGlYoHQp4Hi/OyHlOzY2VvTtJpMtQnb3915ClOPx4Dt6C7pIhkIhnDhxAk6nE2azuWjijxCCSVcQLQ491kKcLClgfziGP5xeyigAQ6EQPB4PWlpasGPHDjxz1o1wDj5wTpMW77liqyydvePLATw97oLNoC5JlIJhGOyVkG5O7i4WLD9mZmbA8/x52V0sXPcGZtcQjHLwhrmCBGCz3YBme+5/97Frd2DSFZRkL0QIgUbN4sa9uZU2BKMcXppaxeE2R8kNr1UqFXQ6Hbq61ktRhIeRiYkJMRokCEalpSyVKqKkoNQIYCQSUdRDp8B5IwAzefupVCrEYrGyrKsUAlBI+ZpMpg1+d6UeQSSkvM8s+vCtP0/gk9fvhCGuuPxvXrUdU65AxjUFIlzGgvSVlRUMDQ1h586dsFqtcLlcsu5DPAMza3j4xBym3EGs+CP41OXVMBQQ0dWqWTz4zsweTsLUErPZjKamJjAMgyNbnTiSo1fYZR2FT6AAgG01Jph0KjRY5ZkhW4w6ymQz6krpLi4GDMPgDQca8IYDDTnvJ08ISJaRg1LoqDWhQ+LYuXyvUUPzPjwx5kajTY+2DA8ma6EYRpf8ONBsle1zT+5cjn8YIYTA5/Ml+A/abDY4HA44HI6yNzFUsgBU8tqVeE05LwRgNm8/tVpdtghgsWvGhJTvjh07NjiR5zKWTS6EbZ6YXYU7EEUwyiUIwEOtdhxqtaf9+ylXAP/56Dhet78BFyZFyAghGB8fx8rKCnp6eqDT6cDzfFGPb0edGdd010HDMvh5/zxM2vSj5ziegH95ykk+CF6NCwsLOHToEIaHh2UXSvE3W54Q/OT5WfS12bGtJv3NWs0yaLYXvzhdTjKli+O7i5WWLk6HVLNu4XzJ92Z01/dOAAC+nyFlLTf5CsDdjRZUm7Vosq8/mPCEgE3xPo+PrmBgxov2KiMcRnkyBZnmFzPMeqe+xWJJqB90u904d+7cuiXWy9HpdPWD/nAMT5/14IFj0/jGHXtltR5SsojKhhIjgEqa85zMpheAQtQv0zi3cqaAi3ViEEJw9uxZLC0t4eDBgzAYNt6ghf0uhwB8/YEmvHZfA9Q5iqFqsw5OowZNdgM4noiRCCHKaTab0dPTI17Ait2Vq9eo0NfmAAAcaLVjcnIyreB803eeB08IHnyHNJf2eGKxGE6ePAm1Wi1GcYuxb/HnYyjK46H+Bfx53I3/um23rNuRugapRDm+IH+05AjN2tpaxaSLP//IOF6YXMU379iTNZ1b6M2ovcqAGLfxnON4gjOLfnTWyV/flu+aNSpWbDJ5fNSFrz1xDl94/U7UJ0Wqj3ZWY3eDRTbxB+QmopLrB6PRKNxuNxYWFsT6QeH8M5lMeHRkBT8fWAADIBzji2I9pFTBkg2l1i8qVQRuWgGYyzi3cgrAYhAvhjKNOCt1R278NhmGgVqV+xfCoFXhI9d24JZvPgcVw+An7+gVvQxTRTnl+NLlIi4yibLeLXYs+yI5b1+wsGltbUVTU5P4c8F0Wi6Sj5VRq8LnX7cTThlvjFLJZb+++/QUfnt6CV+5bbcskyoYhpGcLs7n+Ec5Hp/45Qhef6AePRmi3VLZ02jBiem1hEh6sfj09Z0pfz6y6Mcjw8vQqllsrZa3DjTVzfNrT5wDAfBXl2yR9B5GLQsVy0Cn3niMDBpVxhRxPhRyw9doNKitrRWvZcFgEG63W6wfZBgDzCzBh67eAZu5NJ3BlYISO5iVuCaBTSkAeZ5HNBqVPM5tMwnATCnfZMqx3yzLFjz7mGEYbK8xodGmx+TkJGZnZzN6Gb60GMMjvxrCh67ekfNYtqF5Lz76s1P4yLUd6H050pdtbemO6d+8akdO2wYgio49e/bAat3Y+FBsz8FCfedKQVe9GX8cWUmws5GTTOnitbU1aLVacUqEkC7OlJLleIKx5QAeOj6fVQBGOR6eQBQ1GSxgrt5Zsz4lRwLFikRsrzFCp65FaxF86lKtWaNiwPGZz/1glMM3/jyJS7Y50NNqL2naWogA8mR9pnAhx9xgMMBgMKCxsVGsH9xW78bZ0RFEIhHRf1AJ9YPlRokp4EAgoEgTaGCTCcB4bz8AOYXgK10ASkn5JlPOCGCh/NMNnTh58iS83vWUaKYvPSEAAfJKEVr1GmhUrOTIklxROUIIRkdHsbq6mnakm9wRQKVwbjUGkz0GqZaNR9odONKeXZzLRXy6eG5uDl6vF4FAQEwXm6x2PDbNo6vJgSs6NwozvUaF771lX9byh7nVED740GlEYjx+8NYDih4xp1G9EvnzhmL4wP+cwt+/ege2yCAIUwnAt13YmvXvBAFe2ivcOsL38l9+OwoVy+DDV8szDzi+frC1tRU8z4v+g/H1gw6HQ5HlCqVAaalWpU4BATaRAEz29svlJFDCjbSQJ/NIJIL+/n5YLJaMKd9kKlUA+nw+9Pf3Y8uWLQkp0XQcrFPjwgu78tpWo12Pn7yjV/Lr5ajLE1L4Vqs140i3Uk4dKRXBKIcX5sJYwxreUJfdBzEXYjwByyBlI0C+MAwDvV6P1tbWhHRxZHQa3lkXToRmU3YXZ4tEe0Mx/HJwEdfsrAbLsLKJv1LUIi14w3AHojg555VNAOYjZDQqFn99RXva36drCpEDoRZNzbKotRSviYhlWVHwAev1gx6PR8wcaLVa8fxTuv/gZoUKwCKTytuvkiikG1ewBOno6Mh5kkm5UsCFCMDZ2VlMTExgz549ORtrDs178fGfn8YXbtkjObX51T+dRY1Zizccyi40gcT9C0Q4jCz4sL9F+vSRtbU1DA4OYvv27Qkp/PUiex8668zi+S3MApaTTAJh2hPE156YxEev2V60ubAGjQqXbTFgq8xj5QgheNN3X4KKZfDDvzgg63vHo1arwRptuOfaaqhYRqzfOnv2rGgGK9yQM3UXW/RqXLajCk02XUE+feVgW7URD7x1f8GiNcrxULFMUUTrb08t4ttPT+NLt3Sjziq/D5+QAv67q7fJ9p7nXEF85OEhfO7mnWJnczIajSahXCEUConRQZ/PB7PZLDaU6PXy2DZRMiMcdyVSWVeWJOJTvtkaPZRMPt24guXJ8vKy5JRvMpUUAeR5HkNDQ4hEIujr68ur1iUQ4UAAhKPropcQgtElP7bXpH8yXgtF4QtL94iMj8p99rcjeHHKg2+9+QDqJHjkzczMYHJyEvv27dvwxHhqzovfn16ERsWKlizFeNDJ9J7HJjw4NefD7GoI29PYwjxwbAY8IXjL4ea811BjUkMnc7qTYRiYdCrsqi/uhTgY5fDOHw7AolPhvrfs31C/JZhRDw4Ogud52O12cX5s8vVLqk9eLuQbTcsFhmFyrrVNxTefnIJGxaDHyMt+rlv0GqgYpmiNM8UQrSv+CGIv14SmE4DJ6PV6NDY2iuef3++Hy+XC8PAwwuFwwvxijUZT8vvB+YDP56MRQLnJ5u1XSeQaiQuHwxgYGMg55VvoduUgHwEYDAZx4sQJNDQ0YOfOnXl/1gdb7fjvOJPl49Or+N+XZnF7TzO6G1NHnP7umo6s7xt/sY+Pyr37sq14ccqD2iwzXAVxG41G0dvbm1LcdtaZoVWzCSm1YkQAM3Hj3npctqMqY1ewTs0gB72clV8OLKDWopNlFNp33rwv57/5/dASvvv0NO5/yz5JNaQGjQqXbHfiyo6N6ev4+bFtbW2IxWLweDxYXl7G6OhoydJ1lXKt3FFrRI1JC35pWfY1X7jVgQu3Fq9utBheegdbbHjw7YckvTYc48EACVFYhmFgNpthNpsT6gfdbjcmJydBCIHNZhO9UystoKLUcphAIEAjgHJSrJRvubx6chFihaR8k6mECODS0hJGRkbQ3d0Nu92e93ZTfbY76y24cW8DdtTm/+WMxHh88dEx7Ky34DV76hPqSeusOry6O/P4KmFkXV1dHbZs2ZL2/NOqWXTWJa6z1DWAapZBVZZmmFsONha8HWG/CCG475lpqFgGP3nbwYLfNx9+d3oZkRxG7AHA+zLUncWjVqtRXV2N6ur1iSxCuu7Zk2MwkaA4uzhbujgXlHqTTMWrutavby8sFve6HOV48ASyRp3zuZdEYrxstZ7v/++TAMPgKxn8O1PVDy4vL2NxcREvvPACNBqN2F1sNpsV/+CgVK89YfSfEqkoAZiLt1+uCCKsHG30KpUqqyiKn3Jx6NAhWeo3hLFspUSqACSE4MyZM1hbW0vbBSsVQVAkXxz0GlVWaxdCCNZCMdgMqaNeGhUDFcOIXcK5iDJBzO/cuVM0gc2FSmsC8Ydj0KrZnDwVv3xbN/QpvNuyIVeB/+du3lnwe0hFr9djhZjxpeOzeGNPK17dbE6ZLrbZbHlbXZT6JskTgs/9fhxHtjpw6fbcz3Gg+Gv+yuPnwBOC91+5dcPvpj1BfOh/T+Mrt+/JySg61wjasQkP7v3dKP7xhk50NxQ+n/vyjqqcXQ80Gg0cDgcsFgv27t2LUCgkRgeFNKYgCPMpOSo2SrSAAWgTiCzk6u2XK8I84HIIwGxCTEj5Wq3WhCkXhSJFeMrJWjCKh/qX0G3ILDrD4TD6+/vhcDgydsEmw6yMgj39MLA2C1K9A/zOmwBLgyg68zluvz21iOcm3Piry9pRbd6YymUYBu+/6hWLBykCN3mkW75ivpIEICEEb/neCahzjOYlT22QwlPjbnz+kXF8/nU7ZTf4LTaddWZcv7sWV3ZUwWrRpUwXj42NidEZpXd3EgI8e86Dl6ZXFSsAL93uRDTFdBMAGF0MIBTlMe0OFlUA1li063ZTMpiuE0Jw68uR+PhpSVKIX7der0dDQwMaGhrE+kG3242RkRGxflCIIGo0pTeLT0apU0CE5i8lUhECkOM4RCLrExSKVe9XznnAmVLAKysrGBoakiXlm4wcpsy58Nw5Dx4744K5lUdPmtcIRtadnZ1iaiwrhED1zJfAvvQ9gPAAwwBnH4X6he8gdsUnwLJ1eQulni12RGI8nEZpEchMoswXikGvBgYHB6HVaguq38y2LbmQK5LGMAwu3e6UNCWi0P2y6FRQsfI0IpQarZrF2y/a6HGXLl0sTIeQ2l1cigjgi1Or6J9Zw5v7mqFmGXzvLfugLWBMH1DcusUDGbr0L9vhxCXbnchBQ2HKHcSvT7lxbYf0m357lVGWMofT8z585fEJfPSa7Tg558WPXpjFvTd2ZTQSjyedcI2vH2xpaQHP8+K4xKmpKRBCEvwHyyHElDpxw+/3o6GhodzLSElFCECgeMJPoJxm0Km2TQjB2NgYXC6XbCnfVNsNhUKyv286LtlehS12LVYmhzf8jhCCiYkJLC4uZuxqfnR4CX8aWcbHrusUUxzM2Ueheul+EI0RYF+58BAuCtWjn4Jh18fA83vzWnO1WYcb90n/8sZHAM8s+vDn0RXcebgFX/jDGB4dXsRf72WwZ4c0/8JsFFsA8oTglm+9CL2GxQ/eWrh1SiZPNjnZ02TFgyWuGeQJAceTguYR50Jyd2e67uJUN+NiC8D1blUCYdKjuUAbmyhHMDjrxe5G6YLqS4+dxZ/OuPDAW/cX9CDAMAxynVj5lcfPoX9qFZe0Fy/q4w5E8dnfj+FdF7eiPS7KzWDd55JhgGqzFhqWzcmySWrkkmVZ2O12sS47OUKtVqvFB5JS1Q8qOQVMawALoBRdvkoSgEIK1G63y5ryTabUTSBaNYu2ahNWziWKlmg0isHBQej1+qxRscHZNYRjPFRx54Pqhe+AMGyC+Fv/hQaIBlE39wh4/hpZ9yUd8aLspalVrPgjIAAO1avx2MkwDu8/BIddui+g1G0VA/blm19y80kpqJTUtsBPX5xDOMbjzX1NRTMXTkem7uLkdHEpvu9C84Zc/HgkirPHh/C12/dItj+JvJzSLcf0lI9dux3PD03Abije7TUU5RDjeLgDUbTHNZx31Zvxn7d0A1gvn/jaG/fk9L75lsokR6jD4bAYHfR6vTCZTKL/YLHqB5WcAqYCUOGUWwAKF2Yh5ZtTCrSA7Za7CUQwPt66dSvq6+uz/v17rthorMqsnAHUaW4MKg3M3vGSCYp4UXbLwUZxpJs95sXP7rlYtm7O5G0VCym2E4QQ+MKcbLN44x/2ziz6Mbbsx9U7a2QXVnJ0XQrH/0CzFdOroaKJv2CUg07NSnr/TOlit9sNk8kEnudl7S5OZmEtjBqLVpbjcX27BgFrCxpt0g2b/+boVuBobtsZXfIjFOVzijSmwqxTo92uSSmkfvz8LEw6FW7Yk9kdIBsNNj3+7XW7CnqPVMhl/6LT6RLqBwOBAFwul1g/KHS4y1k/qOQUMBWABVCK8HE5BSDLsojFYhgdHS1qyjfVdkttAxMvWqanpzE1NYW9e/cW9gXRWoBoYGMEEAB4DpzBApRoP+OPaTQaRX9/P2w2Gw4ePCj7eayUJpD/ePQsHh1ZwTfv2Cv7VIUXplYRjq57msnJF/44jsfPuHDfnftgL7DwnmEYdNSZ0VGkSGmMJ/jx87MwalW47VDuNjvx6eLx8XGo1WqEQiEMDg6C4zgxMiNX7daiN4y3/6Afh1pt+ORrsvtoxrOwFoZewyZ03Tv0DK7el/3hsFD+7mdD4AnBQ+9MV6EsnXS1lqNLfjAMChaAxaIY/n8Mw8BkMsFkMiXUD7rdbkxPT8vW4a7kFDDtAlY45RSAPM9jcnISDQ0NRU35JlPqLmDgFdEyMDAAQkha4+Nc4LtfB/b5bwLqpGgGIQAIVpqvgiPNfnIvz4eVS5wJ+7e6uorBwUHs2LEjYaRbNsJRDv4IB6dJC184hv8bWMD1e+tT1vEUIuB5noCRab+v6qzG4KwX1WZ5oknxwva2gw0gkP8hsG+LHU+Nu2WLWhaLoXkf1CoGHbUmtEtooJGC0WhEdXV10bqLa8xaXLrDidflIdoeOjEPjYrB2y7c2AhTbD53806EovLcA9IJqb9/9Q5Z3r9YlMIAOr5+UJifnVw/KDyUWCwWyeegUs2raRdwBSDYwJSalZUVnD17Fna7HTt2lPbiUA4fQL/fj0AggNbWVjQ3N8tyY+f2vQns8P8BazOAzgSwaoCLgIkGwTf2wFfbB1sKocTzBJ/97Qi0ahYffJU8x55lWQQCAZw6dQr79+/P+cnvlm8+hxhP8Mt3X4CFtTBmV0NYWAuhvXrj++QbASSE4MavPAOWZfDzd1+Q898n015txGU7qjDjCaHVKW99D8Mwskf/AODibU5cvC0/W5JS8uGHh8AwkCUqlQqp3cUOhwM6nbToLsMw+NBV0mbg8oRgyh0SJ9y8ZnctDGXq3pbSoS4Vwa6s0iiHiEpVPyhEB71eL4xGY4L/YLrjqtQIIJ0EUiCl+CKp1WqEw+Gib0dAqA3zeDzo6OjA6upqybYtUOwU8JQrgAhHxNm1CwsLGB0dhV6vR0tLi3wb0tsQveX7UB37KtjTD4OJBEB0FsR67wJ/8K1gz6SuAWRZBloVi33N8jRl8DyP4eFhRKNRHDlyJK/I5gev2o6xZT9YlsHWaiPedUkb9JrUF+R8BeC6iTqDrSlEZT4wL//jFZCO3mx85oZOqHNtQ81ANhuYdN3Fp06dQiwWkz1d/PlHxvHoyAq+evsebHEa0OJQnsFwMi9OrcKkVWVsjirFzOVioIQ6Op1Oh/r6etTX1yfUD46OjiIUCiU8lMTXsCo5AkgFoMIpZQo4FAphYGBA7PL1eDxwu90l2XY8xd7nj//iNDgeuP+uAxgZGUEgEEBfXx+ee+45+TdmcIC77KPgLvk7IBYCNAaAedkmJsPM3A9eXXjkjxCCYCiEgf5+1NTUwO/3553WvrSjGpd2rD8JM1mG1QsC8MVJD/7hF6dx/1sPiRNJsiFH5E/ApFPjzsPNsr2fUmoblUB3gQ0JqZBsrJ7UXcxxHDweD1ZWVmRLF9/R0wSHQYMWR/FrnvNhLRTD3GpIFHuEEHzyVyNQMQweelf6qKySxEggwsGgYSV9PkrrpE1VPyg8lMzMzIj1gw6HA9FoFEaj8ozfo9Fo0ZqtCqViBGCxbwqlEoDLy8sYHh5GV1cXqqqqSrrtZIodAfz4dV1Y8wfx/PPPo7q6Gp2dncWP5rIqQJsY2ZK6n5EYD44nGUVXKq774pMIhsN46B0HYbPZsLCwkNPf54sgbM+tBhDlCELR0tRzzq6G8Jc/GsDHX70DvVvsJdlmsYnEeIwvB9BVv/FJPcYTzK+F0GxXfnQqG8nX0FyMoVUqFQwWOwamIrjp0HZEI+tWH+fOnYPP58srXdxk16c0vlYKD744ixVfFO+70gidel1E3XtTV1ZvvXLMpZ1fC+FzfxjHh67aKk7Q8YVj+H8/GUR3gwV/+6rsaXme5xUx1SMdLMvCZrPBZrMl1A+6XC4sLCxAq9UiGAzmXD94vlIxArDYFFuE8TyPsbExeDwe9PT0JFwgyyUAi71dOxvC/Eyi2C0HLMtKenh47deeBU8IfvOeCyW9r2BeXaONwadb97kihKTcljcUS2g4iHHrNUK5jGlKRngounl/I27en3t3aL4Iqd5IrHiCM5eHvVNzXqwEorikgJq+T/xqBP0za7jvzn2oTZqa0D+zhuPTa7hxT51sjS5yQgjBRx4eQnu1Ee+6eEvW1wo3xdd+/XkQQvDwX/ZK3tYvBxdw3zPTaHEY0LvFjsbGRtTVN+BHz8+gQ6uBMRRMSBc7HA7Y7XZFRZVy4baDjVjyRaCLswvaJWFWb7EigMEoh8/8ZhSv21eHg632hN+tBmOIcQSrwRjqres/M2lVMGpVuLJT2vVXaRHAbMTXDzIMA4vFAkIIZmZm4PV6YTAYEvwHSy0Iy/EgkAtUAL6MWq0uWhNIKBRCf38/nE4nenp6NpwQ5RKAxYqqEkJwZnQM9/x8Es3VVnzzyPqNOd53rZRfDKkRwNftb8CiV1odaCwWE0e63feuS8WLfap96p9exe9PL+K2nmY0v1zjdONXngEYBv93z5Ec9iSRYnx+HMdlTV832w34eQ6iIVdyPS/6Z9YQ40lBAvC9l7fhz6Mu1KQQeLvqzbDp1agyyRsZ+dmJeXz3mWk8+LaDCQIjVxiGwal5H04v+LMKwFR/mwvX765Di8OQMD6NZYBwjODcGoe+g20J6WKXyyVaz1RVVSl+dnEyFr06r07xXK9v3lAMEY5HVZYSDgbr19G5tY3Xqc66V0ygxdczDL56u3QzaCWlrnOF4zjo9XrYbLaE+kG3251QPygIwlKlZZUsAitGAFZqCjhVyjfVtkttxwIUp7kmEolgYGAAJpMJq1EW3nk/OJ5g2RfGP/xiCK/d3wDHy/sr9UkzyvGIxHiY8hwplakGMJ63X9wm6f18Ph/6+/vR1taGxsbskbctVUZ01VsSIkud9RaoC4j+AfJ+J4SmpLm5OahUKtGXq1zRm1z269ZDjSj0MDTa9Lg1jceeXqMSG5nk5OmzbsQ4Pqc5s6kghOB9V7RJSlHH34x+lqGGLR1GrQpH2h0JP2MYBm+7MLGpS6VSoaqqSrzmCZMhzp07h7NLXrRVm0VBmCldXKm1oLkKqf949CxiPMEnr9uRuUlHo8K/3rxTjiWmpNIFYPy1Kr5+sLm5OaF+UPDALPZ1LhaLKTqiWjECsNjILQB5nsfo6ChWV1c3pHyLve1ykex998QHOxB+Oepn1Wug07BoqzLCG2BzEoD/+KthRDge//LaXXmJVjlrHRcWFjA2Nobdu3fDarVK+hubQYPX7En0RPv3W3Ib0ZQKuQRgLBZDf38/jEYjDh8+DJ7nsbq6ipWVFYyPj8tS7J8Lub4/yzDIxSvmT2dWMLMawq0HGwsW4YXw2dfKdyOfdoex6I1KMqMuRzRCmAwxHTHgy48O464eMy60RMR0cbobsZKjJ5lI1wU8vxYCwKA+yTD9Tb1N8IdjKfe1lMegkgVgtrUn1w8mR6lVKlWC/6Acx0HJJtAAFYAicoqwbCnfZKRGqJQKIQRTU1OYnZ3FgQMHxE4srZoVU74GrQr/eeteAMALM7kJshv31mNuLZT3RXBwIYRmmwaF9KkSQnDmzBl4vV709vaWpFB6cHYN7//pAL715gPYUrWxu00OAej3+3HixAm0t7ejvr4e0WgUKpVKFHxAojdcIBCAxWJBVVWVrGOcSolVr8b8GiOL+BOOPyEE3jAHa5GNpf3hGO57Zhpvu7AF+pf98hiGwR19TZIiieWOqHU3WHD1zhpc1d2AGosOW7ZsSZkuFs6/ctRt5co3/jyJJ8dd+O6d+8TRd+l8AL/91BRYhsFHrtme8PN0HoTfe3Yao0t+fPzVO6BRFV+YVbIAzNUHMDlKHYlE4HK5MDs7C6/XC71eLzY1GY3GvM5DJVvAABUkAIt9EZBLAC4tLWFkZAQ7d+4Ub6DZUPoFLhOxWAwnT56ESqVCb2+vpC9grgbUPW2O7C9KQyDC4V8fn4eGBf7QuTWv94hEIujv74fdbi/KSLd0+MPrNanBKAd3IIKHj8/hDYeaYH45FV6oABTO1T179sBqtYoNLMn7x7Ma+NQ27N7dKKZRVlZWMDU1BQCwOxyorqqC1WqV5dgUu9zjQIsNB1psCMf4gmrvBBiGwad/fQbPnPXg+3ftL2qjyBNjbvx8YAG7Gy24bMcrJSW5iNlyXm+MWhU+cDTxe5gqXTy7uIxfPDeKLYYw+FgUc3NzWdPF5eIXgwvrk3XifpZOSL3lcDNyOfw6NQsG8jysSKGSBWCha9dqtQn+g8FgUHwoCQaDedUP0ghghVDoRVFI+a6trWVN+W4WhFq4LVu2oKmpSfLflXIGsVGrwnsurIOW4fNKpQhp7Y6ODtTU1BRplak53O7E7//6IgDA2JIfvkgM3lCsYAFICMH4+DhcLhd6e3uzXsyeP+fB8KIfDVYdLHq1mEYBgPFFL/7yx4N4c/caOs1hmEwmOJ1OVFVVKfo7cHreh/f/90l8+OrtuLyj8A71G/bU4cxiAI4C5wpn42hnFVrsenSmsKuRgnC+BCJcVisTgbnVEP44vIyb9zdI/ptC0Ol0CGts8KijOLzVCdfkMCKR7OnicvGLFA1R6a41qYyuYzzBZ383igu3OnDFyx6gAvnMfi6EShaAck4CYRgGRqMRRqMRzc3NCaboJ0+eFM9Docs9XeOcz+ejEcDNjpDyraqqwqFDhyoqoiekn3P90s/NzeHs2bPYs2dPznMOSykAAaDBpsd/H19AU9MqDiVZJ2RienoaU1NTCWntcrGtxoR7Lk/08ZJqbxNPLBbDwMAADAYDDh06JOlz72uzY1uNKWU3pMWghUajxs7tbehptcHv9xd1coQcBCIcVCygVrFosMkjUg+22PDAW/fL8l6Z0KjYgsyhCSGY90bwxOAqruiokjT+zBvmEOUIOL506eMdtSZUm7WwaAi8cxps2bIla7rYbDYr5trL8zwCUR6TCwHsasi8LpYBYhzB+HIQV3SUcJEpqGQBWMxayXSm6G63GxMTE2BZNmX9II0AyoRSvtjJ5JPyVRKCGJP6ped5HkNDQ4hEIujr68tr4kWpBeAWpx5HWgzYWS/txsnzPE6dOgWe59HX16cY4ZJMrhHAQCCAEydOYMuWLRm7l5MvpHqNCk321MegxqLDr/7qlQiI2WyG2WxGa2ureJEUhrxrtVrxZp2ppqbYKeBfDS4gHCP4xV9mr8+tVEJRDg++OIc39jRuqB1zGjXYVo0NjQjp6Kg1oaO2tDcxFcug2qxFOBxO+IzSdRdPTk6K0RbhHCt3BPq3p5cxNO9Ds6MNNkP6yDDLMPiH15RZ+b2MEkbBFUKpvs+p6gfdbjdmZ2dx6tQpfPvb38all16K6urqvIMHbW1tsFgsUKlUUKvVeP755+FyuXDbbbdhYmICbW1tePDBB+Fw5F8iVTECUGnwPJ/QFCCHp1A5Ot5yEWPBYBAnTpxAfX09du7cmfdaSy0AdWoV9tfrJaWvgsEg+vv7UV9fj9bWVkULhFyEkvCgsnv3bjF9m+r95BRfyRfJ5Joaq9UqNpPkOzovH67srIY/zEn6bFeDUbz5vuP45xs7sadJWte3EvjD8DK+f2wGzXY9rux8Ja1ICIFeo8LlHfLMvy422a6JQndxQ0MDCCHw+XwJEWi50sWRGI9AhIM9LsV/bMIDu1GTVhy/elcN9jVZM4o/pVHJEcByotVqUVdXh7q6OnR2dmLnzp34zW9+gwcffBATExNYXFzEVVddhaNHj6KhoUHy+z766KOorn7l+3vvvffi6NGj+PCHP4x7770X9957Lz772c/mvW4qAOOQmg4VREJ1dbVsKV+hCaWUN8L47WZDEBC7du2S/MSx5A3jtm89h4u2OfGPN+4CsH5Bj/IoqgD0hmI4NbeGw+3rEVmpgnNlZQVDQ0M57WOpCEU5hGN8ws0kWayFohxULJMQ8SGE4OzZs1heXi57barBYEBTUxOamprA8zzW1tawsrKCc+fOgWVZMXKTbpqKVObXwlC/HEFKRZVJiyqJAa35tTC84Rjuf3YaH7t2R9Fr/OTiqs5q1Ji1ONiibKEXbw6filweioVJEBaLRfZ08TefnEQoyuP9R9vBvvy9+/tfDEPFMvj1/+tL+TcmnRo7aivrFpvOvoYiHZZlsWvXLuzatQvV1dUIhUK47LLL8Ic//AF33nknPB4PLr74YnzoQx/KqXYeAB5++GE89thjAIC77roLl19++fkhAEsRiRHEUKYvwOLiIs6cOSN7yrdcAjCbOBIMgldXV3OOdK74I1gNRjE05xN/9rXHJ/D0iAufvNaO6hR/QwjBc+c8ONBiy9v24KM/O4n+mTU8+I4+1Fl1kvZxYmICS0tLsokkuaO5r/ny0+AIwaPvv1h832T7oO89MwkNy+IvLlqfBiFMK9HpdOjp6Uk4rx94dgqEENx5QfHnsPKE4CuPn8Ol253Y+3IUjWVZ2O122O12AK9YMExPT8PlckGnW//cqqqqsp5zD74wC7Nejeu6awEAd33vOBgAv7nncMFr76wz47/ffhCn532wGSrmcgm9RoXDKbrnhfPSH47lbawuF4+OrOBffjuK/7ylGzvTNLUU8j2SM1382n31WPSGRZsXhmHwudfthF1h0b3nznlQbdaiPc426uxKAP/821F8/nW7stoUVarvolLx+/2iHVxPTw8+/OEPIxgM4sknn4TBkNm4nWEYXH311WAYBu9617vwzne+EwsLC2IEsaGhAYuLiwWtr3KuaCVAEGGpvM2KkfJN3nY5vAAzRQDD4bBof5JPpLOr3oIXPnpFws8u2VGFwXMLSHcvPT3vxQ+PTSEU5XDpjlQSMTt/f10njk14UPdyjVOmZgmhKUKv128QSfkiCE4eDL771CSObHUWnD587xVbMeNJ9EJMjgD2tTlh1q2nuYR6v5aWFjQ3b3RAJISgVCX94RiPh08s4JHhZTz0ztTTJ+ItGKanpxEOhxGJRPDn5/th0RDxRm2z2VJ+RsHIK+fwR67enjGqlCvVZh0u2a7cjmZgPVXtDkTRlsIvMpm1MIdfn5jD7kYL+trsxV9cGhqsOqhVTMaoqpyCpJB0cZNdjya7PuFn+xRWEsATggeOzUCrZvG5uGkho0t+BCMcXP5I0X0qy0U638Vy4/f70dKSOCXHYDDgqquuyvq3Tz75JBobG7G4uIhXvepV6Orqkn19m/NsyBOVSpVyHrCQ8q2pqSlal2+u3nhybjeV8HS73Th16pTs9ie7G6344CV1aQVZR60Zdx1pTWjYmHYH4QlGsbtR2gW3zqrHDXtfmbyRbh9zHekmFUGYsSyLUJTD2WV/wQLwpv0b15d8Hu5/Od0npLLj6/1CUQ5qloH65ahqKSJ/AgaNCve9ZR/sEiNoLMtCp9NBY63BZx6eQ2+rFX/TZhWj74JBq9BMkjzCTQ5bl0rjd0PLCIQ5NDsMGT3jCCGw6FTorDOhs6683Yld9Wb837tTp08F4gXgsi8im8diMdPF5YJlGPzN0a0buvWv6qzG0c5qMXqZiUrYz1QotXaxECNo4Z5UW1uLm2++GceOHUNdXR3m5ubQ0NCAubk51NbWFrQ+5R2xMqJWqzeIsMXFRbz44ovo6OjA1q1bi/YFKdc4uGThKaRDR0ZGcPDgwaJ438ULspEFX0L0Rq1icaDFLk45AIBv/nkCDzw7BT5PG4pUk1bm5+fR39+PPXv2yCr+gFf2T8UyeO+V23DjPulFv7mQvF9Cvd/Y2Bh6enpE8UcIwTVffApX/eeTOb3//FoI13z5WZyYWSt4rU12fc4pxxqLFn1b7LjrglbU1NSgs7MTfX192L59fYrC6Ogojh07huHhYSwvL6d8eMuVaU8Q13z5WSz7IgW/Vyl5TXctrt1Vk1b8jSyuz+QmhEDFsrhom7MimhOEB6ljEx7c8u0X8cvBhaJsR0gX79ixA729vdi1axe0Wi0mJydx7NgxnDx5EnNzcwiHw0XZfjqGF3zwhaWf161Ow4aIKsMwksRfJSOnB6CcBAKBvASg3++H1+sV///vfvc77N69GzfeeCPuv/9+AMD999+Pm266qaD1VUwEsJQ1gMD6E8XIyAj8fn9RUr6Ztl1K4lPP8enQ3t7eoj1RCQLJE4jii4+OobPOjPdcsS3t6//6ym3whWNg83TDjxecQirf5/MVbaRbsW1MUm2H4zgMDg5Co9FsSGUzDIODrXY0x6WwlrxhGLQq0VQ6Ff4wB54Ay97cxNCfx1zoqjMXHK1hGQb/ctPGtEe8QWv83OKJiYmEMXb5RG6G5v2IcARnVwJFneghN0atKm2X+5lFP971owFcu7Ma1xXnWaRoCBHAzjoTdjeYcbDFBo4nWPKFUW/VZ3+DHBlfDuAvfzSAr9+xB+1x6eJkf8tSmFH7wzF895lpbHEa8FeXbCnKNjYLmy0CuLCwgJtvvhnA+n35jjvuwLXXXove3l7ceuut+Pa3v43W1lb89Kc/LWh9FSMAS4EgwoSUb21tLTo7O0suPkuJIAC9Xi8GBgbQ3t6eU5t6vtuMRCKwGzV4U18LOuMG2IejHH53ehFX76yF7uUooNOkhdOU/81YqAGMRCI4ceIEHA5HUUe6lVoABoNBHD9+HM3NzRvqTQT+/ZY94v/neYKHT8xBr1HhzYdTvx5YN5/+/XsOg+MJRhb92F5jzBpJWA1G8YlfjqDBpsMP3nqgoP2SgmDAKnRtJxf6WywWURBKeYg72lmFy3Y4JY/eKvdsXSlsrTbi9kMNuGFPHZbPjeR83s+vhbEWipXcCxB4pbbLZtDgS7fuBgA8fdaNFyZXcdvB9XnC6ZhbDUGjYnMS8iv+CHhC4A5E0f5yJQHDMBv8LVdXVxPSxQ6HA1VVVTCbzVgLRvHCQgwHeFLQCDeTTo039TSi1Zm5WUAuKuFcTodSI4A+ny8vI+itW7fixIkTG35eVVWFRx55RI6lAaACMAGVSgWXy5Wz3Ylc2y5HEwjLslhaWoLX68XevXtLMrYmPiJ3ZGtiJ/XJOS/+OLyMZocBB1rsG/6W5wm+/Ng4djdZcWVn9vT0wMwaPve7Edy9I4LnnnuuJCPd5PA5JIRg2hNKOTpKgGEYRCIRvPjii+ju7hY7arOvj8HVu2ozRv/iGVsO4InRFejVbNabkc2gwcdfvSNtV2exSS70F+YWDw4Ogud5UQxardaUEQOGYaBR5XbTZhgG40t+vDS9hhv31uXdvV4sVCyDd128HkFaRu7ZlMdGVrAajMIfjuFADrYyT591IxTlcUUBNZmpmkD2Nlpg0qqyCrs77z8OhmHw+/dI7wbv3WLHH957QcbXxEeZgVceOqampuD1enHGp8HJ5Riml9fQVluYDU8pvScruQOY53lFCkC/35/zpKxSUjECsNgnJs/zYh1RKVK+yZSjCYTjOCwsLIAQgt7e3pJZ0GTa171NVrz3iq1phQ/DrBeDPznmyioACSH44XNTGFnwYrEmhuuvvKgkI93kiAB+7fEJPHBsCl994z7sbd54EyGEYGpqCsFgEBdffDH0+tzSYa1O6cehvcoAvbpmQxdkOgq54QvEz6x1B6KStx1P/Pim9vZ2xGIxuFwuzM/PY2RkBAaDQbyRZ7NkyMZKIIooxxet1ipWYDRJIJ/z8qZ9dbjjuy/hh8/P4ud/2SO5dvDvfzEMQgo7H1KJEpNOLdoJZeLDV2+HUVuYGOcJyfqZJj90bHW54WBPwz0zjqVzr8yMdTgcihQpAkpNo0pBqRNMAoEAFYByUazUWiAQwMDAgGhFUWrxB5Q+BSzYhJhMJlit1pL6D2aKkKlVLNqr04fMGYbBp2/cmfb38ZxZ8MK36sY79pnQ6uBLNs9Xjgjg9XvXfce6Uoyv4zgOJ0+eBMuy0BuMIGxxi/k1quyRPzmJv+E/dmYFK74IbjvUWLC1i1qtRm1tLWpra0EIQSAQECP+kUgENpsNVVVVedV19W6xo3eLvaD1pWNw1ov+mTXctLdOFu++XB+mDRoVvnhLN16cWs2pceS+O/chyuV2vZ5yB9Fg04tit5Co1FVd+dlICawGo/ju09O4vMOJ/SkewlLBMAxsFjOaHCbs378/IV0s1KjGp4uVFHGrdAGoRHFNZwErnIWFBYyOjmLXrl0IBoMIhUJlWYdKpUI0Gi3JtoR93r17N/x+f8k720oxCi4YDGJx/CSu3VmNy/Zuw8BLzxd1e/HI8aDS4jDgH67f2AAhjONrbGxEc3Mzjtz7KNRPPYk/f/AS8WZbiFAqVf3ilDuIv/h+P37w1v2iX2MqLt9RBVcgIquvH7C+nyaTCSaTCS0tLeKNemVlBePj49BoNGJ00GQylfVGXW3WQKdmxZpYKfCEYGIliK3ViQ89+X62LQ5DxnKEdH+TCwtrYbz5vuPY22QR6/3KmZbUa1TQqpmcu6Xj15wqXex2u8V0sclkEn+faxQ/Hbd/50UAwI/vPpjT3yk1iiYFpYrXcgx3yAXlrqzI8DyP4eFhBINBMeUbjUbL0ogBrF8oii0+U3U2h0KhktceFlsACj543XF1nJlufNd9+WmsBaN44oOXyHKzKZaIcrlcOH36tFifSgjB5c0q+DQ2MAyDB56dBMMAf3FhaTsGAxEOL06t4nCbXXL928iCHzGex6Q7uEEAxh+/9e7W4kcfk2/UoVBIjNoIaRxhbnExOsczUW/V4/UHcmvM+q8/ncNPX5rDV27bjd2Nr0SRlVznVWvR4ub99bhxT534s3KuV6dm8e5L23L+u0xiRKfTiYbn8d3FQ0NDiEajsNlscDqdZUkXK1VESUGJEcBKaKqpKAEo1401EAigv78f9fX16OrqSnhaK5cALLYoCoVC4vzi+M7mYtcexrh1u5fquG69Yu1rvnNvI7H1tRRyo/GFYjC/bMCabf9c/vWIltQmDKHeb25uDocOHRIjBQzD4KbtWlx44T4AQM8WO9Q5NjDIwfxaGGNLfmyrNqLBJi2KcbSrGkcLTNEVE71ej8bGRsxzJvzdH07hq6+vhs/nxdTUFAAkzC1WoqB6/YF6RDm+7GbPucAwDN53RXvCzwo5vudcQdRatDDkEDmVA6lrztRdPDExkTAf22KxpH1PTyCKux84gb+6dAte1VWTc+RPgApA+WEYRpHXB4GKEoByIKQ/U3VNllMAFnPbQkSsq6tLnIspUEwBSAjBtV96Cp5AFL+65wjqXvbtKoYAFDwMDQZDziPd/vC+i/LeLiEET4+78PRZF+66oBXVZl3GBxVCCG74r2fAMMCfP3Rp1vfneR6nTp0CIQQ9PT0ZL3KpmkVKQVuVATXmBnEMXaGUKg0tBXcgCgJAozdia8t601E0GoXL5cLs7CxcLhe0Wi0YhkFVVZUsc6TloNGmxweObt3w81TiRM4JG3KTrwAMRDj8vH8erU4DboqbCiTnNtKRr5BKjkLHz8fOlC5WsQx4AngC64bRkRgPrZrF8elVfO2JSfzHG3aBYRjospRRKLWTVgo8zysy1aqU61g6lHfEikR8yrevry9lGmezCUBCCMbHx7GyspIQOUrebrEijwzDoKvOgkVfGDXm1BFA4QtSUPTt5ZFupfAwjOe7T53DN/48ge/ddQidtWY4jOs30UyzhxmGwbsubZPkaxgKhXDixAnU19ejtbUVDMPg+NQquhstirIaYRlmw/ipzcLRl8doxaPRaFBXV4e6ujpMT08jEokgFoslmARXVVXBZrMp8oYa/1374XMz+OoT5/Dl23YrbrYtkF6cRTkef/mjAdze04hXdW10AzBqVbiuuzZjfSmwPmnj90PLuLOvSbbJKHIJyvj52JnSxXa7HT971/qM7YmVAP7tkXHcdbgZT591wxWI4l9/P4ax5QC+evuetGbhAI0Ayk00Gi15uUiubM6rdhLpUr7JbCYBGIlEMDAwALPZnDEiVuzU85ffuC/jNj/ys1PgCcG/vm53Xu8/Pz+P8fFx7Nmzp+Tt9katCgwYNDkM2BFnZp1q9Fw8b5Ewh1eYxbxz504xInBydg3vfOAlvHZ/Az766s7Cd4BSMAzDQKfTIai1Y+fuJmhYwOPxYHl5GWNjY9BqtQlzi8udDkp+MLmg3YHfnV7Ctur8O+RjPMHvTi/hYItV9ukcmcTUmUU/vvyncykFILBuZJ4NnZqFhmVkfaAqhpCSmi5WG63Qq1nUW3W457I2vPvSNjx71o0pzzQMmuwRwEoVgEpcu9I7gIEKE4D5XDzn5+cxNjYmyShXrVbLMk80H+SMxK2urmJwcBDbt29HXV1dxteWQ/TGC0CTVoVAJPftn1vx46u/G8CN2zRFG+mWjdt6mnFbT/OGnxeawpyamsLMzAwOHjyY4E/XWWfG2y9uw41ZUlqVyLQniGVfFPubrYpKAUvBG+bw9h+fQJVZi4ff1YOqqiqx1CIYDIoTI4LBIKxWq9hMUo6UVbKg2lptxH1v2V/Qe3I8wcJaGKNLgZIIwMdHV9ZF53sOQ5XBG1FKJK6tyoh3yTxmrZhiZNkXwdmVAHpabSnTxa7ledzS5MXqzBhUwfXfX7Rt/V85111slBgBzHcKSCmpKAGYCzzPY2hoCOFwOG3KN5lyN4EUum2hWWBmZgYHDhyQ5HtXCkuWTNv8+Gs2Wp1kIxwO44/H+hHiGHTu2i1Z/IWiHPQlKAjP95jyPI/Tp0+D4zj09vZuuKCpVSzeeUmbTKtUFm++7zg4nuCx9x0p91JyghACi06Fuy9swaXb12+y3lAMfxxexjW7amAwGNDU1ISmpibwPI+1tTWsrKzg3Llzkov84xlfDuC+Z6bw8VfvUEwZgE7N4s19TRnFWL4QQjaIkrGlAADgyo70TUSBCIfvH5tGT6sNh1rtsq8rE8VsDPrBczOYWw2hu8GSkM7NJV2c7sGDCkB5yXcOcCnZlAIwPuW7c+dOyV/GcoghgULFp1CDxLIs+vr6JH8Zyh0BzBWPx4OTJ0/i+p4O/EUOI90Gl2N49A+jeNclbag2F7dQP58IVjgcxvHjx1FXV4ctW7aUPVVYar55x17MrYZEEVFJEUCGYXD3kVdmKrsDUfgjHLyhWMIDB8uysNvtYiYiucjfbDaLgnDOx8ETiGJ/0ui1/3lpDn8cWcHdR1rQVpV72rZY4qRYYjSVAPyLI+nnV7+yHgZqNncPPzngeR4EDB4ZWkLPFrusa7j7SAuWfJGMtXz5dhdXsgBU4tppClhmpFy4hJTv7t27YbPl1hVZzptuIULM5/NhYGAAra2taGpqyulvyxUBzPUGTwjB9PR0TtHNeBpMLKIqNaz64t8Qct0/QdSm6tI+X9hRa8KOWhN4QvC7kVU06GPY2MMqL/NrIXz7qSl86KptshpNtzoNuN3RmHGEGMcTvPH+Abx6Vw3eftEuEELg8/ngcrlw8uRJPDYZhlZvxBZzK2w2m3hze8/lbbi9pzFnk+VKJd/uTo2KxdsuzF5rWwwIIVgN8zg2vQqtmsUl2+X7Tlv06pwbrqR2F0ciEcU3LaSDRgDzo6IEYCY4jsPw8HBOKV8lkY8oAoC5uTmcPXs27yaIckY9BdaCUXCEiF20yXAch1OnTgFAytSoFGpMarymrz2vp8QpdxAsAzTZpd10szWBxDM9PY2pqSlJovb3pxbBsgyOpil63wwwAIIxHmc9xZ+K8/P+RfxqcBHX76mTvQM22/xYlgEWvWF8/9gM3n7Reoe3xWKBxWLBli1bsLM7Arfbg8XFRZw5cwZ6vV68ibc4ChtpWAnRZUIIYjzJKWL59T+fAwC86+LSGqEnw/M8qk0avOOiRtgMyrvFpksXz8/Pg+M4+P3+rOlipaFEAUhrAEuE3+9Hf38/Ghsbc0r5VjLxNY6FNEHkKzzl5PZvPw9CCH79ngs3/C5+9FlLS0ven60gylIJwBjHQ50hhfW/L82CAfDeK7dJ3la2Yyp8ftFoVHLKftoTRLHP7EIfCDie4H+Pz6HFYcAF7Y6c/55hGNy8uwoejyfvNUjlLYebcNkOJzpqS3+RZhgGT3xg4/kuYNBpYaivBeprAUCcWzw6OopQKJQwtzjXm/Sn/28ET4y58dt7+rIK1XLxw+dnEY7xuLyel/yd//6zMwCUIQBVKlVRvRUfG1lBe7URWwqc0R2fLuZ5HjqdDjqdLmcz6nKj1BQwjQDKSKqTT4iAdXd355zyTYdS3f0FgsEg+vv7UVdXtykE799ctR3h2Mb09/LyMoaHhyV1cGcjnbDheIL/+OMYTFoV/uqy1EnHN/Y25yS8sjX0hMNhnDhxAjU1NTl9fqUY8Vbow4CKZUAARLj0IpIQgtd85Tlc0G7HJ67rKGh7AoOzXnzzyUl87uadktO5eo0KnXW5X6Dn10K45Vsv4sG35TdxIR+MRiOMRiOam5vB87w4t3hiYiIhxWc2m7OeT78fWgZPskcpy0lPqw2jS34wiEn+fvzmnr4ir0oaxb5/RGI8PveHMWjVLB56Z0/W17sDUdgN6qxrEtLtUtLFDocjwaGg3FABmB8VJQDj4TgOQ0NDiEQistqACEJBaeFkgaWlJYyMjIjzYDcDySlNQgjGxsZwZnYFVx6WPtItE+kEoIploFez6NliT/u3tZbM2+d4gpemVrG3yQqtms0YARQsejo7O1FdXdgotIW1EE6tcEgfRyoPtx5szPh7hmHgCUbx29PLsgnAB56bwXPnPFgLxYo+1WJo3g+OJxhe8GN7YdnYvGBZFg6HQ/z+h8NhuFwuTE5OwufzwWKxiDdxrXbjscgUeVQKnXVmdNaZMT4+LllMSR2tWGyKLUa0ahafubETjRnGLv7zb0dh0qjw5Fk3XP4I/t9lbbh5X2b7qFTrTk4XC5HokZERhMNh2O12xaSLlRYI8fv9qK2tLfcyMqKMb0yOxKd8hQkJciE0YyhNABJCMDo6Co/Hk9OcWyXC8wQ/GY5A3ehGX1uiiBVGuj10JoI/z0SxvSuKHbXyCMB0ouyeKzKndgkhWPZFUJNGCE65g3j8zDK0agZ7m2xpBeDMzAwmJyfzamJJxQ1feQaRSAx3XMNl7ApUIk99MP34vXy6qD/9mg54gtGSjDS7bIcTf3r/EahZBjMzM0XfXjZ0Oh0aGhrQ0NAAQgi8Xi9cLhcGBwfB8zwcDgeqqqpgtSpv0kc2ih1Nm/GE8H8nF/HGnkbZBGQpMkj704x9jPEEx6dXMb8aAgDo1AzsRg36MjzgCmQTrgzDwGQywWQyoaWlRYxEx6eLhXNNyeniUkG7gGWGYZiipHzjKacXYLo6tUgkgv7+fthsNvT09FTUF2t4wYuPP3wan79lj9i5GOMJ+pc4TP92BP/zrsPia+NHur2t1QbNM5Noz8PqIhW5NGYk8/S4C0+OuXDn4RbUp3jqbnUY8IaDjWiwpZ51LIwhFOo15XpS/uk7+vDw4y9kdfjPFaWXQKRCq2azRmrlgmEYaFSZj885VxBrwSj2lHi8GsMwsFqtsFqtaGtrQywWg9vtxvz8PEZGRhAKhTAzMwOn01m0FB5PiGzp5WKfi/4IhxhPEOPkq4MuZzryqTEXHnxxDu+6uDXncy/XzFdyJDoSicDtdmNmZgZerxcGg0GMRCspXVwqaApYZoLBIBYXF4s6+aHcZtDJFw9hJFhHRwdqcvC9y5ViXWh/8OwUxpb9GF/yiwJQq2bxkcMGXHzBKzVUqUa65WMSnY5Cmhv2NNlAgLQRQJZl0Op8RajGR7AikQhOnDiBqqqqjGMI82FLlRF9DRpFCTaOJ1jxRwoWY4QQRDke7/3pSbxhfwOOdhWWLi81t3/nRRACPP3BC8v62ajVatTU1KCmpgaEEBw7dgw8zyek8IRmEjmyHi5/BL86uYjLd1TJYlWT6dyO8QRnlwPYUUATT0etSfYmIJ6X3rgiN71tdug1KnTVmxGO8fjOU5O45WCjpMh4ocJVq9WKM7JTpYsFM+pyTcEpNYFAgApAOTEYDNi3b+NsWTlRwjxgtVoNQgjOnTuH+fn5DSPB5EYQLMW4aL3v6HZc2lGNS3e84oX1sYdPYWkxgisvYsSbUSAQKKqwL0QAWvRqXLRNupeXsK21tTU8+2I/6lvbsXVrbv6MUlHa2LTXfuN5LKyF8fv3HM7bAFc4DwkBXppaw5nFgOIFoMsfwWooJkasv3XHXrgCUcUIc2D9uLIsi5aWFrS0tIgGwSsrKxgfH4darUZVVRWcTidMJlNea9drVNCpWBhkmriT6br09z8fwh9HVvDjuw9iawGzjOUmlXl1MbaRfFwWvWGEYzz62uzwhWMYXw7g+clVbK0x4Zqd2YMHckYuM6WLhSk4DocDTqcTVqu1oO+Jkq5/8dAUcAWiUqnKOg+Y4zixDk6n06Gvr6/oFxNhu8XYjtOkxVVdiYWwMY4HBwahUAinT5+G0+nEgQMHJF8EHh9ZxhOjK/jAVdthkFj7Vkq7G4Zh4PV6sbKygjFShzNTYXS3EbBFGJUlRQBe+8WnsK3GhP96Y3EfngDgE6/ege8fm5Fl+oFWzeLBtx1EjJTXpzITwrF/YsyFUJTHFqcBLMOguzF3T85M2whGednrPBmWxSd+P4uLtjnxxt4dCIVCYj1XIBBIaCaR+mBm1Kpw66HMTUC5kEkA/tWlbai16NBWpaz0YrFTwEPzPvzguRm85/K2hEj7v//xLGI8wb++tgsf/fkwCCH4l5u64DBK++yKue506eLZ2VkMDw8XlC5WYgcwQFPAslOKp2m1Wl3WCODa2hrGx8fR3t6OhoaGkmy31GbQn33dbjzzzDM4fvw4urq6cu+Gffk0yFaHlfAnBdQA5gLP85iamvr/7L13fCN3nT7+zKjLsiSruHd71163dd3NpvdKEggtBZIQCL2GescV7ntfwhX4wdHugC8cEA5CDSEcCUloIaRsshv3bq97k1WsLk37/eHMrCSrjLq07HOve91lLWlmpJn5PPN+v5/ngcfjwYUXXoj2IAu3n84K+QPEHdeOK4AdVyCpz2U5Dj9/ZQs3dppRksRw/FCDHkMiBs7jIZTUnl7dQ4Bm0WRQF1Q1LRLXHjHDT7FZsVb53cwuLO4gXt9bldHEEgLASyt7OLW6hzsGq6FUKlFdXY3q6mpwHAen0ylYgAAQFuh0Kzbx4A7QYWKMeASwwaDCA1dlOy8meWR7JIOPuYvMXn7vpQ3wUfvt5zsHq0EQiR0MQpFLIpXJdnEhijYBCIr8QkZREUAg+y2vfLaA/X4/5ubm0NfXl9Mnh1weM8dxAkHq6+sT/KaSwaWHTLj0UHKkMRckl5/3U6lUMBqNkEqlKJMiZsJJJiBmoTn96SuS/tyXlh34t6cWsO0K4P2XNaawZ5nBNe0m+On8zVSJAUEQUMkkGWt7RqK/Todlmy+j5A/Y3+8/ffiCA0SC/5tOp4NOp0NTUxMoigqr2KjVahgMBhiNxow5Eti9FH4xvIWemlJUahVQyyU5aadmGtGIFMWw+Pozy7i4pQwD9fq0Pr/FXIJ/vOmgfVLozGUqJuz5qqSl2y4uVALIV9ELGUVHALONfBBAhmEwNTWFQCCA9vb2nJeNc1UB5CPdCIKA0WiM6lGWLWS7BexyuTA2NobW1lbI5fKM2YNQDIsAxUITI/8zW5XNgXo9/vnmwzghciGhGBayOGkqySD0Bl+ikKKkeB2PMgJDiRyGkhjXCu2HbPwnkA1/F4TPDtZ4GMFj7wXTeJmoz1aKJK2zu368vBzE3cf3hVl8fNjU1BQoihLEJDqdLuXFWKeS4khlCQ6Z1bj6KydBAPjezYaCJv/REK0CSBIEAjSLhV1v2gQwWyiUVmqy7eJC2e9IeL3ejNh9ZRPnCWAEck0AvV4vRkZGUFNTk7f8YolEknUC6PV6MTo6ipqaGtTV1WFsbCylbV7zpb8AAJ76cGwfuWiIR3Knt1zYdQdwcWtqQgPemqinpwcajQZOpzNj3+ePX15HgGLwtgsboraRs1ER5zgOUgmJ6zvEmZhSDIufnt6EsUSG60S+JxbmdjxYs7hRLS3Mwe6CAuWD+uHXgbQtgKB9AADSa4Fk8zSC/W9H8JJPZWxTb3toBCwHvLG/Cmq5RIgPq6+vB8MwcDgc2N3dxcLCAuRyubBAq9XiW/ckQeDC5v2OwN9e14LyUgVY30bREcBohERCEvjENeKiJPOFfKqX4yFRu1ilUoGmadA0XVDq4kIOlOBRON+WSOSiBRwMBrP2+aHgg967urqg0+mwsLCQl/ZzouiydMGnl3R2dqKkVIunp3ZQkaOZPB7xKmVPT1lAMWzSBJDjOMzOzsLj8eDYsWPCzSeT5+jV7WZYPcGYM4SZ3JbX68Xw8DAYhoFGoxFafIkqtTIJCZNGjo6q9CvXd333FbAchx/cmj3Lo3yAYTk4/bTogXwxkL/4FZDWORBM+HwnQfsgP/1t0IduAFuZGeHP4+87hnWHP6oQRSKRwGg0wmjcV8r7fD7YbDYsLi7ihRU3/muMwk/uOoyGKpPoBfq23v3557Gx9YIkJfFQSLZMyaLQ9ztau3h9fR1bW1sYHh4GQRBh2cX5qgwWyzlQdAQw28iFCphlWczNzcHtdmNoaEhYYPM1f5itFjDHcZiem8e3X9jAPVd0Q6/X4zfjW/j6n87gjiNK1FQnv81kK3884h3j/Rc3gGaTI1EURWFkZAR6vf6AgjmTbdlKnTKq+XTotjJBAK1WK6anp9HR0QGlUgmv1wur1SqkSfBkMJYA4FoRNhNi8NA9vViz7AFwZeTzCgUXfP4v4Djgzw+cyNisoGzk+wfInwAmAPkr/w3/DV/KyLaMJXIYY7WhI6BSqVBTU4Oamho8bVkEh3XYnS7Yt9dAkmTYAp1okcznQrrlDKBUIUlKBAVkr5X65JQFtXolOqoKe64slyBJUphHbWlpAUVRsNls2NjYKAgz6kIngecJYASyrQL2+/0YHR2F0WhEf39/2AmS7UpcLGSDeFIUhbGxMTgYOf6wxmLkF1N48oMX4vLDZqhkEpgZa06PNd4MoEImQTJjZvy8X0tLCyoqKpLaVqaRCQK4srKCzc1NDA4OQiqVgqIolJaWorS0FI2NjWECgOnpaZSUlAgVn0zPcbZVaFClYrGxUTgEcNXuw/CaE9d3mFOec/zszW34+StbmROKcCxIvyPmnwmOBWE/k5ltJYA3yGDF5kNbxUHvwI9c2YyPXHlWqRsMBgVlscvlEirNBoMhqpgkXwSQYTn87JVNqGQk3n5hfVLvzQYBZFgO//GHM5BKSDz6rsGEr/dRDN778DjuPl6DKw4Xtodmugj9vmUyWUGYUXMcV7D+hKEoOgKY7ZtBNqtwfJWlvb1daJdEbpuiqKxsOx4yXQHkCVJzczPaykyof9mNhldtPNRyCa5oM2N+fi+nF0imqnJ8Ygk/7xdrW5HHxnEcxjdcaDKqYwo6UkE6BJBlWUxNTYFhGAwNDcV8AJHJZCgvL0d5eTk4joPH4wmrDoZmzWZq4RN7TBzH4Zej29ArpbiiLTsL3a47iECaSuRrj5gzViUFABAkOIUORGAv6p85ggRX1pS57cXB2LoTMzse1OiVKE1wbsvlclRWVqKyshIcx8HtdsNms2FychIMw4SJSfgHqXwQQAlJ4IYOc0ot+2zss4Qk8IXbOqBTRf9+AzSLP81ZccVhI2QSEhKCQJBhMb7hOucJYCwVcCJ1cTbbxcFgMGPq+Gyi6AhgtpENAshxHM6cOYPd3V0MDAxAqYze0pNIJPD7/Rndthhk8pgjBREcx0GnluFES7jdS669B0mSTItccxyHubk5uFyuhIkl0Y7NHWDw5/ldWFyluLI9c0Qg1WpjMBjE8PAwzGYzGhsbRS9YBEEIAoCGhgbQNA2bzYbNzU3MzMygpKQkbXuQZBZPgiCQJYtFAX11OvTVZT53PF0Ee++G/OVvAnQAE1wjmohNlBCvtoQlCgT77s3JfvTV6dBoVCckf5EgCEKoNPPnksPhEGajlUolfD4f/H5/Th0DeLSYU0txyFYLeNnmxXNnHPjYVc0HvuuRNSd+O2lBlVaB7hot5FIS37yjG//3iXmsO/yo0cceIyl2iLWBiVQXh3Y2Mt0uLoYUEOA8ATyATBNAvhVaUlKCwcHBuDeGYp4BZFkWMzMz8Pv9BwQRAYrFb8a38ebB2rBtFkoLOBEoisLo6Ci0Wu2Btn00RKvKlSqleF1vNQwZFAHwSPa4XC4XRkdHM5IvLZVKo1YH+YpOutVBH8XgpSVHWJRgJG7tqUzqM71BBmesXhyp1GTFuDlXCB7/AKSLv4fbtoHTgUPwk3IMErPgpCoE++4FW9mbk/2QS0lUaNOvdkilUphMJsEYnndIWFxcRDAYhE6nE3KLC0ntGYlkKoAcx+E3EztoNKrRmWC2r65MBfnKXtT0o746LcrUMjSFROLtuIOweoKYt3gSEsBiES1EA8uyKZ0PkZ0Nr9cLu92Oubk5+P3+tNrFbrf7PAEsRmSShO3t7WF8fBytra1RZ8Wyue1kQJJkWsKXQCCAkZERmEwmtLe3h91InluwYmPPj1teXaT/OLuLJye3cX+vJmnS6acY0b5lkUiV5LrdboyOjqK5uRmVleKIRqxtVcURc6SKZInt9vY2FhYWcPTo0Yz7TUarDtrtdmxtbWF2dlYwyE5UHQwl0A8+MY/Hxnfwg3t60ZWheLUzu16Mb7pQq1dmJLIuGsY3XPjIzyfx8/sHoM1gyz8MMjW8d/wSivGHcd2pn0EfsIM2XbDvA9h0ZXa2mUOo1WrI5XJ0d3eDIAght3hpaQkkSQq5xRqNpqDISzIVQA7A6LoLM9uehASwo6o0pgBEJiFxqDyccDQaVPjKm7ogF5GYVKheemLAMEza7dbQdnFtba3QLrbb7VhZWQGApNrFxRADBxQhAcz2hS6VStNWAfNpF+vr6+jt7RX9JJALP75Y203V+sZut2NycjLmXGNbhQZyKYnJrf2h/mfmduGnWEgkyRGyyU0nHn5pHfdd1IBGY/LmmqnMAO7s7GB+fh7d3d1JObpny6qIZTl4g0zYDKHYbXEch4WFBTgcjoQt7ExBKpXCbDbDbDYL1UF+3oumaaE6yM97RcMHLm/E4YqSjFjM8Gir1KBKp8gI+Yv13f9hdj++zeIKZI8AAoBMBarvbVD3vQ25Ma/KLfjKVGT7LhAIwGazYWVlRYjc4hfofLSLI8GvUy4/DVeAhqlEjh+f2sA1R8yoDKmWkgSBD1/ZBGnEHAPHcZi3eNFkUh/4WzL7oJCKe2+xE8BM++3Fahfzoy6J2sXnW8BFinQXb5qmMTk5CZIkcezYsaROzHypgFOpjvEkd2NjA/39/TFnJowaBX71nrNxU/9w036SwMbGBgJJEO3yUgU0CknKLdRkjpHjOMzPz2Nvby8lspQtAvjY6BZ2PUG89XidEAsmZls0TWN8fBxKpRIDAwNJP0Q5vBR+P2vFtUdMYTmtySC0OlhfXy9UB/l5L746GBkNWF6qwFuP1cb41NQgJYnYyRopINr3+d5LG3HfibqkLUQKEVZPEDqVLGUikgqWbT6UKiQxW5MKhQJVVVWoqqoCx3FwuVyw2WxZFSalgtu+dWpfUfyOfmzsBTBv8YQRQABRleHLNh9+cHINV7WbcWlr8nGZyaKYCWAu9j2yXcx7XYa2i0tLSyGXy2EymTJWAXziiSfwoQ99CAzD4B3veAc+9anMmbsD5wngAaRTYXS73RgbG0NdXR1qa5NftPLVAk52uwzDYGJiAiRJYmhoKCHJjTazkizpNGkU+MR1B/MvxULs9miaxujoKEpKSlIiS0D2COAlh4xYsnrDMmETbcvn82F4eBj19fWoqalJuI1ox+ujGFAMCz/FQpMhYVtkdZD3HZyamkIwGATHcbDb7XGrgzxYjkt6li+d6LrNPX/Cdr6EJAqO/PHnyZ6PgtNPh2XHxoI3yOCJiR3UGVS4tDX2HGYmwXIc/ji7C6VMgmYkvicTBAGtVgutVovGxsaoowfZ8oKjWQ5uPw19jAfTB29pw6rdB0OJHB++sgmyKO3YaOdvXZkKN/dUoKMyN55/xUwAc50FTBAE1Go11Gq10C52Op0YHx/Hxz/+cRAEgSNHjkCtVqeVTsIwDN73vvfhqaeeQm1tLYaGhnDLLbego6MjY8dSWHcoESikWY9Q8OrXrq4uaLXalD6jGEQg/GB2bW0t6urqcrLNTMDuo/HjcSc+1kTHtGHxeDwYGRlBU1MTqqqqUt5Wts7RaJmw8VrbfHu+o6NDaGWkgiqdEm8eqE75/YkQOn9TX18Pp9OJ+fn5MDUoPzsYqaDnOA69D/4ZADD66UtFbW/N4cMLZxy44rBRtLkxj++9sIYv/G4R/3VHNy5sTv07zSf+MGuFn2Lwxv5qoTIfC2q5BIMN+pyqSEmCwI2d5VDLJZgcTT5TO9rDBe8FFykmSZc4XPuVF0GzHH73weNhDxQUwyJAsxhq0GOoQQ8AUEgPEqxlmw8/enkdbz1WG/YdS0gCgznMDC5mApjvfSdJEnq9HhdffDGef/557Ozs4Itf/CJOnjyJgYEBNDc349prr8W1116LlhbxcYAnT55Ea2srmpv3fTRvv/12PProo3/dBLDQEKp+TXe2qtArgHykGx9dlw4yQQA5jsPJJTuGGspiRqXx2PMz8FIM7D4qKgHkyUZ3d3fKBD4fiFUBXFtbw9raWlzboUKFRCKBXC5HW1tb2AI+PT0NiqJQVlYGg8EAvV4v3PgjB+DjQauUQS2ToCRKZToRLj9sxB9mdzMmSMkl+HbqtUfM8AaZhOSPR1tF7ofZzaWZKTVHesExDCOISRYXFyGVSoXRg5KSg0bWifCpa1vwp3nbgWryt/6ygiDN4UNXxLdYUkpJyCVkVHKYS+SbRKWDXFcAE6G8vByHDx9GW1sb3v/+92N+fh5PPvkkHnjgASwvL+ORRx5BU1Nij8719fWwIkttbS1efPHFjO7reQIYA2Jk8T6fD6OjoygvLz+gfk0Fua6Kid0uLyCw2+1h0XXZ3KYY/GnOin94bAofvKIZb+iP3948VK7BW7o0B9peHMdhcXERNpstY8eWS0QSQP6BJBAIiGrPFyIiY/UiF3C73Q6LxYL5+XkolUo8fm8L9GXi56S0Silu7CrHltMP2643YbTWrjuIJasX/fU6NBhU+O7dvakeWkFALZdEzfT9a4BEIhHawcB+MpPNZsPS0hK8Xm+YmETMw3w0g2+O43BjZznsXirmmuCjGPzNo9P44OVNeOCq5qivySWKmQCyLFtw9zm3242qqioQBIFDhw7h0KFDeN/73geKosQrxKM82Ge6u1R0BDAXLWBejBGvd89Xw9Jtr0VuNx/xMfHUx6E+hgMDAxm7SbAgsOtJL/XkeGMZ3nVJI649Up7wtdEIJ03TGBsbg0qlyuix5RKhBJCiKPz2udNorjTg6NH4DyQUw+KpyR0cayqDKVODfTmARCIRvOL4YeyVTQt++vQYmko5dNQahPZeot/zmq+cBACM/O0lcWcIxzdd2HUF0Funy7rpdDYR+lBLs1xORR2FCqVSierqalRXV4PjODidTiGqDgDKysqw7JNj1sbgngtqRdtQNRrVaIwzMrnlDGBsw4Wnpy1458UNCT8v2z59DMMU5f0PKMx993q9UUUgyXQIa2trsbq6Kvz32toaqqszO4pTdAQwF+DzgKMRQF4h6nA4MDg4WBRxL4kQS30cGukm1gMvGliWA81yYeKF9/98FjaXD4900ykPy6vkEtx1TNwcYmSlzOPxYHR0FA0NDRm/qHIJ/rjcbjdePD2CMwE9Sgk9OhIsFkGaxa4niBWbr+AIoFgRDT+M3dJYh1afEkN1WkhpL3Z3d4XqIJ9KEm34/3t3H8W6w59QQHJJiwEUwxY0YdpxBWDSyEWJYcbWnZjccuPm7oq/2kpgNBAEAZ1OB51Oh6amJsH6w7W5hfV1F2annTCJ9LFMhCajGj++rz9mtFso9nwU3vq9Ybx5oBp3DcXudHAch4/8fBIXNJbh9sHk7mnFXAEsRALodrvTVgEPDQ1hbm4OZ86cQU1NDR5++GH88Ic/zNAe7uM8AYyCWDNxwWAQo6Oj0Ol0GBwcLFhBSrKIVh3b2NjA0tJS3MxbsXjHD17BstWLxz9wAnKpBDZPEHqlFHUqWUzyd2rFgboyFcozNAsUeoyZnGVMBIsrgF+PbeF1vdUxlYLpgDfIPXPmDI719eAwLYVJhLChRCHFnUO1oufAChkyCYnXdPFG6yrBj5JXFvPD/3zOLF8d7K/ToV9ExJuEJCAhC5co7bqD+P3MLvrqdHHn9fgqUnmpAotWb97nzgodvPXHLeXluDnEx3JqagoURYXlFvMtyGQ6OCaNuHETlUwCAoBKlvj32nUH8cTkzl8VAeQ4ruD2PVYFMBlIpVJ89atfxXXXXQeGYXDfffehs7MzQ3v46jYy+mk5QC5IVzQC6HA4MDExkZH4rEJD6PGGzpCFRrqlA+bVCiD76r3RE6Chkktw3Bz9BhikWfzi9DpKFFL87Q1taW8fOFvlXFxchNVqjTvv5w0yeMdDp/HpG9rQWZ2eICTIsOA4gM7CbCfHcbDZbPD5fDh27BjkcjmSkSZIU7RBKRbwVg387KDD4RCqgwqFQlAWZ9oaJNcwlMgw2KBPaOvCE8AKrSLp+Ly/VvB2QZE+lqHn08LCAuRyuSBMyvQaJZeSePTdQ3Ffs2r34b/+vIzP39YR5jP4/KINKrkUvbXx72OFOEcnFoVYiMmUEfSNN96IG2+8MQN7FB1FRwBzgVBCxHEclpeXsbW1FdfwuJjBV8f4SDez2ZwRUQuPb7+1DwzLQfHq/EydQY1/ee0RjI+PR329XErinZc0hVl0uPw0vv/CCu6+oD7p0HkAQpu0tLQ04bzfrnvfsPXxie2EBDBIs2Gt7UjU6FW476LEMz7JgvdipGkaDQ0NRSdeiYds+ChKJBKB8AEIswYJBAJh1cFiWwhJgkCrufBTB4oNFlcAt33rFN7QV4UPXRGu2ow8n3hj4DNnzsDtdmN6eloQk+Qit5hiXp0DZsIfNL9/ch0kQeBrb+6K+/5irgAWIjweT1LpUflCURLAbBnt8uAJIJ+gIJfLcezYsZxcILyvWy4vRoIgQNM0Xn755ZiRbulAKiEhjVhTQ1uy204/3AEGLSGLWENE3Nu6w4cdVwDrDh/akzRH9Xq9GB4ehlQqxZEjRxK+vt6gxlMfuijhfNRTUzv4m19O4r/v7kd3Te6sY/x+P0ZGRlBVVQW9Xp/SZ9AMi1+ObKK3VofW8vBWRSTxdwdo/HbSgguby7KSZ5wPhBq58tUcm82GxcVFyOVywRpErY4fO5gP0VaqSEVIwHEchtecqCtTiW5ZZhMsx2HbGcjJeahTyUAShCgbHJVKhZqaGpjNZkxMTKCyslKIquNjxYxGI0pLS0X9BizHweWnRccVNpvU+Owt7Qf+/TM3Hob0HM8CLkSczwIuYkgkErjdbszMzKCxsTGnIgGefObqYuQ4DisrKwgEArj44otzVuEMFZ58/U9nEKRZPPjajpg3x7YKDT513WEoRczBhGJ3dxczMzPo7OzE5OSk6PeJufFWaBUgCcSc7cuGcm9vbw/j4+M4cuQIDAYD1tbWUrLTIQkCQZrFusN/gABGe20uuyzZfsCLRLRqjtVqxfz8PPx+f8LqIAfgxTN2NBhVqNQWNkFO9nykWQ4zOx7seoK4pj3/oy+z2x48t2jHdR3mrJtTy6Uk/vSRE0m9Z3PPj3U3hz69Hnq9Hs3NzQgGg4Ky2OVyQaPRCNXBWGKSh06uY9nqxceubklLqFOhFTdDzbJsTiqVmUahPoCdrwAWMTweDzY2NjAwMJBzFs8TwHQMpcWCbyNKJBKo1eqctrdDK4Dvu7wZLj8tLE4cx+HBJ2bRaFDjruP7Kl+CIMIi5cbW9yAlSRyJ4eHGcRyWlpZgsViyptbuqdHh5Kcuj/o3nsRkkgBubGxgeXkZfX19QmUqVbJEkgTuFKmgVssluK039WSUdGDzBDGz7caxxrKcCVZUKhVqa2uFmCeHwyEYB8tkMoEs8r8BxwEbewE4A3RWCCDFsJCQRNJxd5FI5TyRSUjc0l0RNcIsH2gy7X/nYolNrvHYuAXbFho3hVz7crkclZWVqKysFEZRbDYbJicnwTBMmJiEf/C/pt2E0yt7ooQfmUCxVgCzbY+TKnw+X1GMixUlAcxWhYBhGExNTcHr9aKhoSEvJdx4nnyZBB/pxucWP/fcc1nfZihCL9ryUkWY2pcgCDAshyWbN+b7fzO+DQKISgAZhsH4+DhkMhkGBwdh9VAwycPPF47jEKRZYS4x08jkOcpxHGZnZ+H1ejE0NBT2pJ7ralmusWT1Yn0vAJrl8qJYJkkyzDiYn/Xiq4N8DNQNHQ2QyzJ/O+U4Dr8e34FcQuAmQemcOlJZLPNlFRPtvFZISbRXFm5r7Y1HzZhZ8MT8ngmCQGlpKUpLS9HQ0ACapvGdZxfxpz/M4AM9BNQhucWv6U7/9xaLYiWAhZYCwqMQlcnRUJQEMBvwer0YHR1FdXU19Ho9aJrOy37E8uTLJHJpg5Iq/uGmg/MsoXj3pU2Idov1+XwYHh4WiO3Wnh/ff3EVFzYbEHo5XvaFZ8FwHP70wMVZUcPyFc50b040TWNkZARarRa9vb0HFpZsEMB8P1WHHlNvnQ6d1dqCsSzhZ71qamoExbzH48HYyLBQHeRnBzPxHRIEgWajSvQsWDwU24NCPs9DmyeInw9v4ZbuiqSqjSVyEqYS8cuqVCrFr6b2wLAkjh8bOvCAodPpYDAYUFZWltUW7XkCmDnk+/6ZDM4TQJzNgeUJ0dbWFgKBQF72JZt5wHykm8PhiGqDUkwnbrQF0Wq1Ynp6Gp2dnYI4orxUgYtbDOiq1mJ85+xrbx+swSPDm1mzQskEMfN4PBgZGYlrxM2LhngMr+7B5adwySFTyttN5RzYcgbgDTJoNsUXTSQLkiCgkBbmOUmSJNRqNQwGAyoqKuD3+2G1WrGwsCAs3kajEWVlZWktUkdrM/OQVkzXN5Df/WU5QELsizGSeh/LJr3Pv37PWYuXUHESy7LY29uDzWbD46cX8ZNZCp+/oRo1FWZoNBoQBIEXl+zwBRlcfjj1653f72IkgIW638VyrRUlAczUF8uyLObm5uB2u8MIUTZJWCJka9sURWF0dFSwQYn8DjNVscoH7J4gXv9fz+Nd3TK89rLweT+SJHBhy0FV83svb8Z7L89eBme6Wcc8me3u7oZWG1thHPk7zmy7kM4EQarX1ktLDgQZFk1GVdrXZ7G2tZVKZVh1cG9vD1arFWfOnIFMJhNSSTJVHTzXkc9F1KSR474L65N+XyZbf7x6uKysDD9fBAipFVKZHCsrK4Kl1ReedYOUSNImgIWYpiEGhVoBLBYUJQHMBHjPO6PRiP7+/rAbjVQqzVsLOBsEkI90a2lpQUVF9LkSfrv5upi2nQG4A3SYFYwYMAyDF14ZR4BmwOqb8xbNF6AYTG+70V2tBUkSAomZ2nThLf99Cj+5f0jUsfGq7K2tLVHilcgK4JsGYkdFZRPXdphBM8lXP85VhC7ewL51D28z4/P5ctbaC0WxVCV4pLq/HMfh4VMbqNUrcUlrZi2tEiFbFamPX92Mj1/d/Or3UQuO4+ByufA3l1iwa7Pj5ZdfBiUvxVdfduEfbmpDW0VyCtRCraQlQiHut9/vLwoBCPBXSgD5OJ9Ynnf5rACmWzmKhNhIt0xvNxT8E1G8m/l7fzQMmuXwy3cfF33T9/l8GBkZQVdDDf58YV9OrUoiMbvjwXMLNpg0ctToVQIBtHqCADjYvVTCz2BZFpOTk+A4DkNDQ6JubJHVsnwt8AopWTBzeoUIpVKJ6upqVFdXh1UHl5aWIJVKw5TFxUTSgOwRy1SrabyIbM3hT/haTyD1LPJoyNZ3wX+mzRPEt55bxQcua4RWq0Xfq90BmqYxvLiFQNCGUyMTCFaVCGISMWSkEImUGBRiBTBTKSC5QFESwFQvMI7jcObMGVgsFgwMDECpjG7ZcC60gFmWxfT0NILBoKhIt2wSwI/9fD/x4wtv6D7wN/6G+dlbO2D3UqJ/W57Ed3R0CFWWfKK9UoMytQzVrxrU8t/nxa1GnPrbKxK+n69Il5eXo6GhQfT3UKzt0ngopmNKzYInvDoYCAQEmxmfzwetVivMDmayOpgtcvLIyBYkJJHxeLl09vctx2oTvsbupfCT0xvor9NhqEGf0nYikW0i9fLKHl5YtOOqNiMG6/XCv0ulUgwersXPDu9XB0OTboLBYFjFORphKtbxn0IkgG63+zwBLDRQFIWxsTGo1eqE1ZViJ4B8UkR5eTmOHDki6iaazWMO0ixOr+xheHUPvXVnB9pDF/oavUpUwkdoizQeiY+GbHjz8ZBJSNSGZLEmQ2KcTifGxsbQ1tYGkym5WZ5zUQVcbEj3u1IoFGHVQafTCavViuXlZUgkEmF2sKSkJCPzlZmGhCSgz4BKORLRBBUBmoU7QIfFRKYKrVKKFpM6ozF62b52rjhsREeVRnjQ/MOsFdU6BdoqNPAEaPzb04u494JaGNRyVFTVoLqmFhzLwOl0ClF1fMXZYDAI51SxVgALcb/PVwALDHt7e5iYmIirpgxFvglgOgpku92OycnJpCPdslkB/Lsb2/CJX0wgGJFTyW/zp69sYmTNiU9ddzhmqgaw/7THp3kMDQ1hxe7HL56dxzsvboRGRD4wf6PLxROj2O9za2sLi4uL6O3tTemmkQ0CWAjkr1gqgNHAsByemrag1aROmLISCd5XUK/X73tVBoNCq9jr9aZVHczWd5rpyh+PaGTqV2Pb8AYY3HWsBtI0fSElJIGr281gOQ6rdh/qytKf28omIVnc9aJSq0Ctfn8/WY7DN55dhkxC4qF7euGjWHiDDFasXvyf36xDJiEgl5AgCeDLb+oSvCz5ivPS0hI8Hg+0Wi38fn/OAggyiUKsAHq93qKIgQPOcQLIcRzW1tawtraGo0ePil5g800AUyFiHMdheXkZ29vbSVfG+O1m65grtEp8796BA/9+tk1qQpDmoFPFPh1D82/r6upAEATcARoMy4ES+X1xIODwBmEszf6AbiJixnEc5ufn4XQ6MTQ0lPKNt5japWLh9NOw+7Nvhp4tkARAMxwcvtSFZE9P78JPMbipqzxmdZAkSWF2UEx1MJ+VXYeXivtwFwqa5UAzbNT9vbbdhF13MCH5e37RBprlRIlAPvnLaTy3aMfD9/WlTQKzRQB9FIOHTq7BrJHjvZc2Ati3SPrszW2CJZZJI8e/v24/69zioVCrV+K3U5YD1dLQijPHccI5NTExAQBCbrFWqy2Ih8F4KMQK4PkWcJYh5qTkY84IgsCxY8eSekogSTJvi2oqRtA0TWNiYgJSqVS0eCDadnORQBIKnuzWlalwz4nYlgt8VZPPv+XRVa1FV3Vsi5RIPH6Gwl+cK7ig2YiB+rKwaLlMIx4xo2laGEeIVKAni3yeq9nCc4sOzO8yuDrfO5IiCIJIO8WhvFSODYc/7NwIrQ4C+5Ucm80WVsnhW3uFlOv6y5Et/PPjc/j67V043ph4XvfCz/8FAPC79xw9cG3oVDJRptiLVt9+Rp8IvOvieuhV0oxkC3McB7uPwZPPreKOweqMpaioZBK8obfqwD7GchZ4Q99+dOMFTfG/b4IgoNPpoFAoMDAwAIqiYLfbsbGxgZmZGcHn0mAwJF1UyAUKsWrp8XjOVwDzCY/Hg9HRUSENopiQbCUuU8eaDwIohuyurKxgY2MD/f39aUvrL6lXwKVU4VOPTOLywyb831s7kno/zbCijaNjfZ98BF9DQwOqq6uT2j6wHzavVUoF5WKhVgDTqTZdesiAEvdqhveouNBTo0VPTfyHG4VCgaqqKlRVVYFlWbhcLlitVqysrAgRdkajUTANzlcFsKdGC51KhhaTuKrILd0VmNnxAEh9HOGuIfF2SK3mEnz6+kMpbScSLMtiL8jBE6ThCdAZjdHrrE7O2iUVyGQylJeXo7y8HBzHwePxwGazYXp6GhRFheUWF0LrtRBbwG63+zwBzBf4maqurq64BrqFimQI4M7ODubn5zNyrPloe8cjnbwlCsuyGBoainmRL1m9eGx0E++9rDlhVqxJLcWFh41gIMGlSSZlvLBowytrDrz1WL3oecNIYsYrl0OTSpIBzbB4amoHarkEb+ivibmdfOOpaQt8QQav6a4AmcICrlFIUSov7NZToYEkSeh0Ouh0OjQ3Nwuzg8vLy0J1UKVS5eVcaTap8fsPXSD69f31OhwuL0kpVSPf4DgOrUYlLumqSvjaHVcgLAO90EAQBDQaDTQaDerr68EwDBwOB3Z3d7GwsJCV6MNkUYgt4PMVwCwj2onG53L6/f60ZqryDTFEjJ8f29vbw+Dg4IFIt1SQrwpgtG3y8346oxl/XAdaaA4lMR7yvvvcMp6Zt+IN/TWo0sVvUfDt0jdGMUv2Bpm4T+s1eiWmtiSi28aRx7a6uor19fWU5jN5SCUkrmo3Q6c8e24XIgGsKFVgzeFPifydR2Ygl8uF6iA/57WxsQGr1YrTp08fqA4WEspUUviC+/fAQtu3RBBLSJ6YtOCLv1/E/3nNYVFt8WxDzD1EIpEIM6cAhNziUPsivl2cqxGEQqwAer3esFGlQkZREsBIhNqetLe3Z+ymkY+WSSIRSDAYxNjYGLRabdRIt3S2m+8KIMty2NtzCCrmcRuHR0dn0VKuwTVHyqN+xieuO4y3XuBPSP747UW70T05uY3pLTfuu7AhZnWvzqDG2y5siPv5oYPuPDHj/RgpiopbyRSLGn14GzxdAmj3BqFVyhJWT3n4KAYPPjGPD17eCHOM6oWY9mU8FCKpLWbwc17A/nXe2NgIm80WFinGV3IK4cH5RPP+4ulwOM5ZAthXq8VAvQ7tFcVRKYoGlUoVFn3IW83wIwi8mKS0tDRrv2MhRtidt4HJIXZ3dzEzM5NxQ2CeEOV6mDoeEXM6nRgfH0drayvKy6MTolRBkiQoKnFaRaa3GUoAX/f1v4Cigvj5u09ApVLhQj2Lz7++C4fiWGmo5RLR8XGRsWk8emp08AYZlChSJ2ebe348OrKJi1uN6KreV89RFIVTp07BaDTG9WN8dGQTbRUaUT6IkUiHLPmCDC75/J9BEgRG//5KUe95acmBx8Z30FpegnuOF9d87V87+PNELpejsrISlZWVYSrQtbU1ABCqg7EWbqsnCKWUzGiCRqz9zSYBDND7tillItXJYiB2nyu0Cjx4S3vGthsKluNyXn0PFSjxIwg2mw1ra2twuVzQaDRCdTCTcZ2FaGDNP1QVA4qSAPKL3sLCAux2u6jM1GTB5wHnmgDGEkasr69jZWUlKTubZCCRSOD3J45OyiR4AshXyRiGRkN5mSD2kElIdEZR+T41tYM1uw/3nqhPaoGI1XKu1Cnx2t74ggxvkIHDS6E6hlLQrJGjv16PJqMawL7x+OrqKjo6OuKS9SDN4p9+PQ2SJPDy31wu+lh4pEMAVXIJemt1uEtEagKPi1oM+J97etFanr0n3GKr+hQLopETvjrIVwj5hXt1dTVqdZDjOFzzlRcBAKc/dYmobWRyf4H93PB3/M8ovvOWnphVaDH4xfAmfEEW956ozRhhyvZM2kvLDpTIJeioik4w9nwU/u8Tc7iouQxPTe/i3uO1GErQYs7GrGXkQ4bb7YbNZsPk5CQYhgkTk6TzfRVqC/j8DGAWwbIsTp06Ba1Wi8HBwey42+fJCzByu6GRbkNDQ1kjpPmaAQwEAnj55ZdhNpvx2AcvE/Vb/sfvF8CwHO6NYx0Ta3upHuNPT63DE2Rw/8UNkEVRAkslJI69eqPd2dnB5uYm6uvrE1Zq5VIS33xLX8oWFLGqmmLxg/sGk3q9hCRyokYsFpxrrerIhZtXFodWB982VIHGct2B9zIsh1+NbsFQIsdlh8Sb0MdCLAI4su7EjjuI0Q0XrmpLnQBe026GzUtltFqWzaolx3H496cXISEI/Oi+vpivk5IkNAopNvcC+Jen9ucMO2MQRiD7pJUgCJSWlqK0tBQNDQ2gaRoOhwM7OzuYm5uDQqEIE5Mkg0IVgZxvAWcRJEmivb09qyw7XwQw9ObBzzZWVFSIjnRLFakaUItBkGbx+xkLrm43h9mo7Lp88K+toaurK2oEWoBi8JlfT+O+ixrC2sAPv30IQSb5p9Z0PPNe21uFXXcwKvnjwWdNW61WNDY2ip6nGkwjhzQb83I0TYMkSRAEUXA310IEQRBY3PViz0ehr+4gMSoUJEtOCIKAVquFVqtFU1MTKIqC1WrFVVU+uFxLmJjYFRZuuVwOCUlAQpLQxzF0z8T+Xt1uwvFGPUpFqPHjwaSRw6RJX0AXimwSEoIg8Llb2qCURa94PT1twVPTu/joVc0oL1VgoF6Px8a20WyKT6py3UaVSqUwmUzCPZ/PLZ6fn4ff7w/LLU5U8CjECqDH4znfAs42SktLs/r0nc80EOCsZUik+XG2kIoBtVicWnHgS79bwDefXcKP7huEQibBb16axZf+tI13naiKmX9r91IYXXfiqcmdMAIoxoYlGtKpliUyoGUYBuPj45DL5RgYGMD6+rqwrV+8sg5vkMVbjteltO14yCQB5DhOGKrm951hGIEIprqwcRwHH8Wm7InmDTJQyciCbg3P7XjgDdC45/sj+OQ1zUm11cUgSLOQS9MnFul8hzKZLGp1cGxsDMB+dfDyRmPGFr9YBJAkCFFm0PlAtucW4807t1VocHJ5D2VqGWiWgzfI4G4Rc7r5rqKp1Wqo1WrU1tbu+yju7cFmswlpN/EU64WYW36+BXwOIF8EkOM4BAIBzM3NpWUZkiyy2QIeqNfj4lYD5nY8kJLA1NQU3E4XOIkMdWWxj69Sp8RDbxuAJsqw+eaeHz88uYa7L6gTPQeUrWP0+/0YHh5GTU0N6ur2SV4o2ZSSJEgiO99tpgggx3GgaRoEQQi2QizLgmEY4f/y10Oy1cE7/vsVTG+58cwDF0KbJHmnGBZPTllgLJGJivXKF645YoIvyOAffzOHl1f2MkoAX1qyY9MZwHUd5VCkQQIz+cAcrToYOfQfWh0Uu3+hi3m2F/eXlh1Ysnrxxv7kDdljIdtkykcxcPvpA/e8iQ0Xpnfc+OQ1zZje8uCpmV0sWDz4vyFRcfna52TAq4d5QSfvZxmqWOfFJHK5vCAJ4Hkj6Bwg21YR+SCANE1jfHxcMD/O5UWZzeOVS0n83Y3tCAaDOH369H6YfZUB7ZvLUEniX7yGkuiLB82wIIj9uSOxyAYBdDgcmJiYOFCpDVVV33I0sSlsqkj3OuCtavhB8MjoMf4cZFlWqBDy3yFN05BIJAnJ4Jv6q/B/Hp9HaQoqa5mExKHyEtRmIKYrmyAJAiUKKUY/fWlK71+weNBsim6m22QqQZDl0iJ/QHYJlUwmQ0VFBSoqKoShf6vVKtzP+CpOrHxZimHxq9Ft1JYpBV+8bBOTjz8yBYblcFtvlWgbpETItnn1159Zhi/I4G+uaw3b51+ObsFPsWgr1+Dbz63g8sMmtFdoRD1wFRIBjESkn6XL5YLNZhPOq0AgAIfDAa1WWzDH4Pf7CzI2LxqKlgBmG7kmgHykW319Pbxeb86farItAtnb28P4+DgOHz4Ms9mMZgCdegaBQCClz6szqPHA1a1JvSeSLD01uYMHn5jFj+8fSsmRn1dmR4upy9QDCs2w+NXoFnrrdGiOEqUVa67xS79bwH8/v4xnPnpJzApAPPIXbTsAhHmb0Oogy7JweAJQSEmoFLKw1wPAbb1VuK03dRIcb4A9m6AYNu7MZ6bwyuoe7n1oBHcN1eAT17Qc+Pv+rFpxGMsC4UP/jY2NYfmy09PTgiWI0WgUqoMyCQkJSUAfcq5mu7rzs3cMYM9HZYz8Afv7HI2I/Nefl0ESBN55cXLCtUjcOViNbVfgwD5/4poWUAwHmYTAG/ur0VurFT1yUcgEMBShVefGxkbQNI2TJ09ia2sLs7OzUCqVQtU53djQdFEM3ydwngDGhEQiAU3TOdlWZKTb6upqzkvb2RSBbGxsYHl5GX19fWEqr1wrjyO356MZcABIYn+xByBqwec4DjMzM/D5fDGV2ekITkJBEAQCNIvtPX9UAsjvTySkry4QqhgD48mQv2gIrQ7SDINnJnchJwlc024Uzt1iFpI8dHIN//70In5x/wBaRfpMporOqlK87mgl7hjMXCsyGvLVLovMl41VHby1pyKnLeBcikD2r7H0P79Kp4xqei+TkOAv9Qubk/PDLRYCGAmpVAqpVIr29vb9OWOfD1arFbOzswgEAtDr9YKYJFdCkUJsScdD0RLAbH/JUqk05eqUWPCRbk6nMyzSja8+5vKizIYIhGVZzM7OxiRK2SSd0RB5jLf0VOGWnv3K1LeeXQI44P5LGuN+BkVRGB0dhU6nQ29vb8zzMF17Fh4SksAdQ7HnyWJVGt9/RTPef0Vz1PfwrVz+ZpXutSSVSDDUaIRWKYVcLgkjl3ylMF0hSa7RbFSDAGCMMYKQScilJD5z0+Gsb6cQEFkdpGkaNptNqA6WlJQIcWPFtpgCBwmAy09DJZfgXWlW/rKJYiWAoftNEIQgJqmrqwPDMIKY5MyZM5BKpUJ1sKSkJKvnVTGdt0VLALONbLeAg8GgQCT6+/sPzF4xDJPTWKZMH28wGMTIyAgMBgPa2tqiq/myqDyOhnhpJ321OjAJKnYejwcjIyNobm5GZWVl3NfmKs4s2RsNL/YAMtumqDeEt1yitYrTEZLkGhe1GDDyt2fn+Vx+Om3bkXyjEBcmqVQaVh30eDxCddDv96OkpAQlJSU5n/FK9bsKJSUsx+FN3z4NCUng1+8ZyvQuZgznAgGMhEQiEcQiABAIBGC1WrG0tASPxxOWW5zJdbYQr7F4KO47WhaRTQLodDoxNjaGQ4cORTUKzocAJZOEhT8+ft4vFtJpATt9FLRJWkHEa8sOJnDL5yMHu7u7odUmzrnNh7F2PKTb8k0ViYQkxVAd3HEF8PwZOwbqdajV53e2KNv48akNvLLqxOdujf7QFg2PjW1DQhK4sTO9eEqCIKDRaKDRaNDQ0IClpSUEAgFsbm5iZmYGJSUlQruYT34K0iw++eg07r+wLmY6Rip46OQ6pCSBO4dqknpfKAEgCQIXNZellYudCxQrAUzGA1ChUKC6uhrV1dVC/CGvWgcQllucznfh8/mSNrPOJ4qWAGZ7AcsWCeOFA729vTHdwvNFADOBzc1NnDlz5sDxOX0USJIIs3RJlSSdXLLjHx+bwt/e0JaUNUgqbVmO47C8vIydnZ2kIgejEeptZwAahSTrGaqRyBf5i0QsIQlPCvnKpEQiSephZM3hw9i6C5cfNsaceUwHZWoZ2is0KNdkNm4y1xBTnfi3pxYAAJ+7tU3055LE2ZnTTIIkSeh0OsF3kK8O8nFiZWVloOWleOGMHVqlFP90U+YIoJQkoE8hIziSTP3dDYcytk/ZQq7HjTKFVIlraPwhb2HEi5RcLhfUarVQHUxWzet2u4smBQQoYgKYbfBZwJkCy7KYmpoCTdMJI93ybUKdCjiOw+zsLDweD44dO3bg+N7ynZex6wnijw9cApmEwA9eXIVezqFBmjwBbDSqYS5VoCWGKCIWkiWcLMtiYmICBEFgcHAwqZtNJAFkWA6/ndyGSibBGweiVxUWLB7c8e2X8PN3HUddWWYqTYVC/qIhVnXQ5XIB2B8j4F8T77uXEETSJMQbZESrJGUSEm0VhevrtWzzYcnqxSWthrixZmII4LMfvRAUk1wb66auCtGvTQah+xtZHaRpGna7HVarFZ85JoVZ68fGxkZYdTAdJFv5C0Wur7EgvW+JxQvYtpwBPDG5g7uGakSJ2v4aKoDxEClS8nq9sFqtmJ6eBkVRgphEr9cn3F4xxcAB5wlgTGSShIVGujU0NCS8QRRa+zAR+HlGvV6Pvr6+qMfnDjBg2H2bAgD4zcQ2CI7FJwaTv1mXlyrw/XsHkn5fMsrcQCCA4eFhVFZWor6+PiWVbOhvKCEJXNlmjuvLtWT1gmE5rNl9GSGAmRZ7ZBMkSeKO75wCRVH42FGgq6sLUqlU1OxgLGVkLMxsuzG77cZlh01JG1NHohCygGd33AhQLDLx66pkEhRKyEY8wiqVSmE2m2E2m9HWtl8dtNlsmJycBE3TQktPp9MVNLkRYzX06/FtfPeFNXzw8iZc0lJ24Dv5t6cWAAL4u+v3q41/mN3FH+dsuKbdhBoRIwu5joLLFLIRA0cQhDB3Wl9fD4Zh4HA4YLPZsLi4CJlMFpZbHPlbnK8A5gjF0gLmnyQ6OjoEd/NcbTsXcLlcGBsbQ2tra9R5Rh4DDXpwOPu7ffOuPlBBP5bmZ3O0p+JbwLxnYXt7O4zG1NInorWAaxOQuqvazTj1t1ektL1IZEvskU2MbzgBDujvvygsPSLW7GCqQhKdUop6gwqaFIypoyFXxPrP8zZ88KcT+MOHLghrT17THnvONhTFNqAudn9Dq4P19fVCdXBnZwdzc3NQqVTCoh2tpfejl9chk5B4Q1/6hu3JPBCwHIevP7MMhZTEuy9piPk6T4CBy0/jD7O76KrSHDDHP96kD/MFvLWnEn+et+Hbz6/hH0S0oFmWFZ3WUkjIReVSIpEIqnRgv5hjtVqxuLgIn88HrVYLvV4PuVwOg8GQkRi4z3zmM/jWt74lzM8/+OCDuPHGGwEAn/vc5/Dtb38bEokEX/7yl3Hdddelta2iJYDZRrokjOM4LC0tYWdnJ+lIt2IhgFtbW1hcXERPT0/Ck/6jV7fis4/PwO4Nokwth0YhQZCQJV3ppBkW0hTNecVUVvkZxkjPwmxsKxVYXAH4KAb1htj7xhOlTFb9WI57tYKb+Rsux3GYm5vD/9xiRGdn54Gn+kQm1Py1wv893qJg91K4/msn0VFVih++rS/jx5JNnFrdAwfATxdPdyAdpEpYQ6uDoS09fgQnsjr4zb+sggAyQgCTAUkQ0Kqk6EogXnnzQDVu6anAtjMQNRkp8gFALZdAq5JhqF4naj/+2lvAyUCpVKKmpgY1NTVgWRZOpxPz8/N4//vfD6lUio6ODqFzkc53+pGPfAQf+9jHwv5tcnISDz/8MCYmJrCxsYGrr74as7OzaX0H5wlgDKRDwvhIN7lcnlKkW74IIF+1SnTT5Rdsl8uFoaGhhDJ6P8Xgb385gR1XENvOAEbX9vC76V08cGVjUiRpweLBz06v465jdQmradEQj5SFejJGm2FMFtmygfnzvBUUw0YlgBzHweENQCOXZLzl+8TEDmiWwy098e1vkgXDMBgbG4NGo0F3d7eofY6cHYwkgvGqg3qVFBqlFG87kbms3lzhw1c04cNXNKX8/tBrm2E5UQkYvxnfhkouxRWHc5fDvObwweahUJKBimVkS4+maTgcDqE6qFQq8bXXVMNgSM48GQBW7T78YdaKtxyrEWYvY8Xc/b/nVnHIXIKr201hf3vbBXWitqWSSdBoFP9A+i+3tot+bbESwHzvN0mS0Ov1GBwcxAsvvIDNzU189atfxTPPPIPe3l50dnbi+uuvx7XXXouqqvQfLh599FHcfvvtUCgUaGpqQmtrK06ePIkTJ06kfgxp79U5ilRvPG63GydPnkR5eTk6OjpSOkFzbZDMQ4wvH0VROH36NAiCQH9/vygPJbmExBmrFzIpgVZzCVRyKUgCUMilSR2nVimFUkqKHt6PRKwZQJqm8corr4DjOPT39wvkz+4NprQdIHsE8LqOclzXcXDonuM4jK45cOUXn8MPTq5nvNV3uLwEDYbMWqD4/X6cOnUK5eXlaG1tTWmfSZKEVCqFXC6HXC6HTCYTrh+GYUBRFGiaFs4zgiDw7AMXim6bnkvgCeCfF2x4fGJHVI42QRAZmS1MBqdX9jCz7c5Krq5UKoXJZEJbWxuGhobQ0tKCUjmBreUFvPTSS5ifn4fNZhN1X/r6M8t46OQ6dt3x7xNSkoCEIETPm3Ich5eWHXB4o3uWZhr5JlKpIh8VwHioqqpCR0cH7rrrLoyMjOBv/uZvsL29jbe+9a04duwYVlZWRH/WV7/6VfT09OC+++6D3W4HsO8gUld39oGhtrYW6+vrae1z0VYAC3GWZXt7GwsLC0KkW6qIZ1icTSRqW7rdboyOjqKlpQUVFeKVfyRJ4HOv7cTkpgtSCYljjWU41lgmKFTFwlyqwIeuSi7/NxQEQRwguF6vFyMjI2hoaEB19dkorokNJ979wxG859Im3Hks+WpRtlrAsSxkGIZBrV4JlVyCwQZ9xrfbWp5ZFazL5cL4+Dja2toEs9Z0EdoqlslkB2xmisWEOtuo0yvhCzKiKoA3pOntlwpu6CwHywErZxayep8PrQ7y6RF2ux0WiwXz8/PgpAro9WWorzJHzZb92+tasWLzJcwRJ+JkAI+sO9FiUofZY7kDDH43s4t1hx+vPZrZins0nCeAmQM/A0gQBHp6etDT04NPfOIT8Hg8YWNgV199Nba2tg68/7Of/Sze85734O///u9BEAT+/u//Hh/96Efxne98J2pBIe0Up7TefR4Akm+JJkK+WsDxtsuT2+7ubpSWJu+3dUGzARc0hy/0uSbxFAs8MuOFq2QXlx42CQKdrq4u6HTh8zINRjWqdUoca9SntK1cJYFwHAeJRILJyUmYzWb88cMnCu6mGAmLxYKFhQX09PRkVTF3LphQZxIcx4EkSTQa1Um1E3MNfs6U399cQSKRwGQywWQygeM4XPOVF8EwbnzxCptgB2I0GqHX60GSJEqVUnRWH7wXbjn9IAkCJXIJHvj5FP72+tao1fM9H4Wnp3exWanB9SFEu1QpxVuO1cCUgxhCoHgJIMuyaY/qZBoejydq+EHkfe7pp58W9Xn3338/XvOa1wDYr/itrq4Kf1tbWwsrWqSCwvr2ihChFiiRkW6pIl8EMFrVKnQ2LhPkNp9QyiQgARg1cqysrGBzczOmQEejkOLH96ce35QLKx+ezPT19cHpdGJ3dxdnzpyBTCaDyWSC2Ry9cpFPrKysYGdnB/39/TlVHiYyoeb/f4lE8lddHSwkZKMFLBYEQeC9lzYgQLHo7a0R7EB2d3cxPz8PpVIppJLw1xj/wPfY2A4kxH6c4Irdh5eWHVEJoE4lwxv7qlBeevA6yGXiTLESwEKsAGbCB3Bzc1OYGXzkkUfQ1dUFALjllltw55134oEHHsDGxgbm5uZw7NixtLZVtAQwFzcG3jYk1sXB24UkijxLFvmsAIaSFpqmMTo6Co1GkzFym0+QJIkbm2WAfRUOhsHg4GDWbiDZrABGmjuTJImysjLBZsi254bdtl/dDAQCMBgMMJlMQuWCh8NL4YUzNlzZboY8C+reyH2emZkBTdPo7+/P+4KTqDpI07QoE+piwrlqA5Mt3NZbBW+Qwc9e2cSNneVhdiBerxfzazv4/dQEjug56PV66PV6EASB1/ZUgCQJGNQy/Pjt/SiJM7McmaGdDxQrASzE/fZ4PCl1yELxiU98AsPDwyAIAo2NjfjGN74BAOjs7MSb3vQmQWn8ta99Le31q2gJIJD9NhtPxKKdZGtra1hdXU3bLiTWdvMtAuHn/Zqbm1FZmf05lFyApmk4nU6YzWY0NjZmdXERWwF8edmO9z88ip/eP4S6ONYuPMQke/xx0QUJKcetfX1gGAY2mw3b29tCnirf5rJ6KHiCDAIUm1UCSNM0xsbGoNVq0dYmPmM2V4hnM3Ouzw7yCtW7j9XkPKIwEWIRwJltN+7/4Rh+fF9fUgbgqcDqCWLPR8HqCUItP0vW1Go1vvKSE8s2Bj9621Eg4MHu7i48Hg82FqdhNBrhJ43QFlgFPhoKkUiJwblaAXzooYdi/u3Tn/40Pv3pT6f1+aEorCu+wMATwNC2J8uymJycBMuyOHbsWFZOQDFq3GyAJy07OzuYn59Ped4v1/jBi6v4yal1/OydxyCXRr+RuVwujI6OQi6Xo6kpdSsNsQh9OHl5yY6FXQ/e0F9zYPDe4aPAcYCPSkwWxSZ7DDXqhcQViUQS5onmdruxu7uLkZERAECvwQBQPnAKTVaImd/vx+joKOrq6jJihZALxLKZiWZCXUyIRqiembfh//1lBaWK/bmzQkIsArhq94NlOey4g1kngLV6Je4+Xhs1ZvCzt7RhessNo0YJaJQoLS2Fz+fD4cOHYbVaMTs7i0AgEDY7KJFI4A0yeHp6F6/pLo8b3ZcrFGsWcKESwHSNoHOJ8wQwDiQSSVgesM/nw+joaMrxYMlsN18EcG1tDcFgEIODgxmd0dpw+DGy5sD1nRXC97Zq8+LBF/3410YnOqsPqqZphgXFcFAlsH05uWQHzXAxs2B5AUtPTw/GxsbSP5gIRFuoQv/bTzPgOCDa7l3dXo6rP5VYaZlMrFusGDmCIFBaWorS0lI0NTUhGAzCarViaWkJbrcbOp0OJpMJRqMxIzdWp9OJiYkJHDlyBHq9Pqn38uQ53yQrkgwCZ2cvWZYFRVHCf+d6Ed3z7TsF6JLIbov8Pi9tNeD/e30HhrKgHE8XsQjg1e2mA3562QJBEMLDVCTKSxVhCmB+f1UqFWpra1FbWxsWJbawsACFQoHnLVL8asaNGr0SAyLNmhOB5biUyWSxVgALcb8z0QLOJc4TwDiQSqUCEUsl0i1V5IMA0jSNnZ0dlJSUZGVG6xevbGBx141LD5mEVtNX/rgIi48FxUSvfn35D4sI0iw+ed2huETgy2/uifrvHMdhcXERdrs9awKWL/9+AT87vYHH3ndBzIX44tb0FqvQZI9M/i5yuRxVVVWoqqoCy7LY29s7ICQxmUwpjTjs7OxgcXERR48eTen9fQ/+CQAw/OnLk35vtsB/9/z/XVlZgcfjQUNDQ15axVf+xwsAgFOfukTU66ONy8gkJC47lDuT52SQ7xnAZBGNkERGifl8Pqi1FmjgB7U5jVl/WVh1MBJPTO7goZPr+O+3HI3Z3fjan5Ywu+MBxbD44hs6oYjxuljItdo6UyjECmAmouByiaImgLmYAaRpGmfOnIHFYkk60i2d7eaSAHo8HoyOjkKr1cJsNmflZnDnsRp87GcT+NXoFu4Y2vfV66zSQum3oTuKlQIAXNVmwo4rKCwCNMPiv55ZwgXNZRhsiE/C+YQJhUKRVdGBoUQOgkDcQW8A8ARorNp9aK8U/3QoZt4vU4gUkvh8Puzu7mJmZiaukCTaPq+srGB3dxcDAwNpke6yDNlgjKztoataK8r3Tgx4ZbzP58PAwIAwOsH/XqGJJNm0mfnY1S1J3f+KjVBF7i/HcXjujB11elVBiCciIaYipVKpcKipHoea6sGyLBwOh5AtK5PJBLKoVKlAEgT+PG9DkGYR72drMqrx/Bk75FISbMj5sGzzQauUokyd+BospvOCRyG2rt1u93kCeK6AIAjMz89Dq9VicHAwZydbLixEeFgsFszOzqK7uxt2uz1r29Wp5FDJJWE3o3tO1OOkZAssy8JPcxjbcOJYQxnIVxfqo3X6sM+QkAQCNIOZLXdcAujz+TAyMiK0YbKJtxyvw1uOJ45zuvnrL+zP/nzoImhEJALkkvxFg0qlQl1dnWCQG0tIEjomwLIsZmZmBGuadK6XTFX+Ti7Z8Y4fjOBtJ+rwkata0v48lmUxPj4OlUoVFl0nxoQ60zYzdwym5wFW6IhGWDccfljdwYIkgMkSbJIkYTAYBCN0n88Hm82GqZk5/HjSjSaTGh+5sA5lZYcgiSPSurGrHDd2hY+RsByHL/5+EQopiX997ZHUDqjAwbJswVUAg8FgTu2t0sV5AhgDbrcbm5ubqKysxJEjub2AcrHYcxyHM2fOwGq1YmhoCHK5HE6nM2sEUEIS+NodRw/8O092X1p24fczFtToVXFn2D56zaG427Hb7ZicnMxIq97qDkKvlmWkcvSNu3rx3IJNNPkTO+8XD//46xm8tGTH/77veFrnVCIhidFoRFlZGRYXF2EwGLKusE4GvbU63HtBHe4YSl/gQFEURkdHUV5eHhbJFA2FaEJd7BVAgiDwut6qqLO0hYAfvLwJj9uPjo7U3q9SqVBTU4Oamho8v3cGneUyOBwOYSTDaDTCYDBArVYn/B1JgsB9J+pgKCle39ZEKMQZQAAFuU+xUNQEMFs3M140UFVVVVQDnWJB0zTGx8ehUCiEFhaQnwg6ngCeaCpDXZkKtfqzLfZHXtlAiUKCa6Nk3wKAO0Bjw+HH4Yr9kvva2hrW1tbQ39+ftgGyn2Jw2zdehFxK4qkPXRT3dS4/DXOCOKhD5RocEhGnlinyB+zPD2V60Y8mJNnc3MTw8DCkUilUKhUsFgsMBkNBuPTLpSQeuDr9yh8vAGtubk7a81OMCTX/umzPDhYzAQQQU+iVabAch88+MY9jjXpcd0Tc700SgDKGYCRZvP/ycKcCv98Pq9WKhYUF+P1+6HQ64cErVhWspyb1ONJiQSGdz8X2gAUUOQHMNDiOw+zsLNxuN4aGhrC1tZUXNW42wWff1tfXo6YmvCqSy9Zz5DZVMglazOH+SfMWD0gCMQng4+PbWLF58c5LGrB2ZgGBQABDQ0MHbogMy+Hkkh1dUZTGsaCUSXD5YRNu6IyfeXzDV54HzXL44wMXp10pDJ0fywQJePET4sQB6cDn82FjYwN9fX3QarUZFZIUCng1c0dHx4HIwFQgxoQ6G4kkuYgmzCTytaD6KQa/HN3GH2et+MuiXTQBfGOPCbu72dknpVIpVAd5wZbVasWZM2cglUqF2UEx1cHzyB6KjQSeJ4CvIhgMYmRkBGVlZULqhUQigd/vz/euZQz8UH+07FsgP+rjeKTzY9e0xn3vDV0V2LB7MDM+irKyMrS3t0e9+BxeCqdXHEkTtH+6OXHr/59vOYKpLVda5C/f836pYnt7G0tLS+jt7RUqrpkQkhQS+Nzi0GPMJOKZUEc+EKRLCIttccrX/gZoFgGKxb+/rh0dVcmJtnKxv5GCLb/fD5vNhsXFRfh8Puh0OhgMBpSVlSWswnMcV3QPBjwKbb8LtSUdD0VNADN1scWKdAu1gckHMnVD4TgOS0tLsFgsGBwchEIRvV2ZzwpgNCQ8dsqP3cUJtLS0oKIidqXOqJHj9sFaaFVSvLSR2Rv1xa1GXNyauo1GMZI/juOwvLwMm82G/v7+mErfVIQkhYS1tTVsbW3lNLc4ngk1f96ei4kkPJx+Gm97aASfv+1I3uxJdCoZ7rkgefFYvgiAUqlEdXU1qqurw6qDS0tLQnXQYDCgpKTkwP2lWC1gChFerzftFJBco6gJYCawurqKtbW1qJFu+TJkBs4So3RVTgzDYHx8HDKZLKGSudAqgPHAq5d7enpEzWkaNfsLOG8dxP/fG77yPLprtPj313clvQ+RYFkOPooRHalVjOSPZVlMT08DAHp7e0UvHmKEJCaTCaWlpXn/HkJtXvr6+vKmNIzWKg4lhMnmFSd68Fl3+HHbt07h8687gktaDRk7jmSwuOvFljOAl5YcaEqxwuPwUnAF6JhismyBv47Fwumncd9DI3jr8Rrc2pOZuM3I6mAgEBBaxT6fD1qtVpgdlEqlRVm1Agqzmu12u4tu1OWvlgAyDIOpqam4kW75JID8ttNZfPh5v7q6OlF2KIVWAYyG0Gomr15OZXt8FYXlOIytO5Pd7ah4ZHgTniCNO4dqIX3VtiHWjSqTYo9cgaIojI2NwWAwoKGhIeV9jhSSUBSF3d1dLC8vhyWS5ENIwrIsJiYmoFAowmxe8o1oreLQrOJMtIoZdp9wuQN0gldmD0drSvH4+46hRC7B6VPrKX3/f5yzIkCzeFO/Mu77/RQDpSxz5D7ZappcQoAD4AvGvv8xLId7vz+Mo7VafCxEzESzHB5+eR1XHDahRh/bm1ahUIRVB51OJ6xWK5aXlyGRSKDT6cKqy8WCQiSuxRYDBxQ5AUz1hOV94qqrq1FXVxfzcwqBAKYKPrmks7NTdAxXPjKIJRKJaALIMAwmJiYgkUiiVjODNAu7N4gKbewbIkmSYbMjT8ZR+CaLyw4bsWr3CeSP31a0tgsfMVhoN7FY4FWwjY2NcdvtqUAmk6GqqgoGczlkJAGn0wmLxZJzIUkyNi/5gI9iQBKAQioRqn58FUeMCXWiRb7eoMKLH8/c9ZAKCIKAVoRVUjxce8QMH8UkrHb+fmYXV7bFJ1DJIFlSopRJ8PP7B+K+hiQAFsCKPXwW3eGl8OTULlx+Gu+5tFH4N30c02eSJKHX64X1IBAIYGtrC36/HydPnhRmBwtFwR8PhZgCUmwm0ECRE8BUkEykWzESQH4+a2dnJ+68X6xtZqsC6PRR+PXYFm7rqw576o4knaPrezhSWQpZhPGp3+/HyMgIqqqqUF9fH3Ubb/rWSwjQDH7xruMx84OzWeU0aRQwac5+3wRBhC0KxdjyBQCHw4GpqamMqWCjYc9H4YovPoehBj2+cddRYZHKlZCEJ7hNTU0oL0+czZwPXPT5ZwEAp//msrB/T2RCzT9s8ETxXIdaLoE6QTJPmVqGKp1CVEqGWGSjikYQBP7n3r4D/27SyPG5W9thfNXn7/czu/jBS+v45DUtaKsQR0IUCgVMJhNcLhc6OjqE6uDKygpIkhSUxdFmB/ONQkwB8Xg852cACxW88fHu7q5oYiSVSoWbZ66RClFJVCFLhGwSwJltN06vODDQUBZ2gwo9zrkdN/75f2fwmu5K3HPiLMnjRTrt7e1CpmYkOI7D517bgb8sWGOSP+AsKcsFQquNz87v4jvPLeOrb+qCXCopqBtqkGZj5oxubW1heXk5aypYHlqlFAQBXNsRbrmRaSEJw3KY3XHjSEgkX6ZtXrKF6zvKExIbIPrsoM/nw97eHiorK0FRVM5NqAsNarkEV7cn5+eYCNluS9Ish0DIjHFo5fJweQmajeqk5x75OfNo1UGbzYalpSV4PB5hdrBQqoOFmAJyngDmGGIXUZqmMTY2BqVSmRQxKqYKIN/WrqmpSbl9lc0WcH+9Hmq5BLuuQFQCGKRZ/Oz0Ogbr9bg5ZCB6Y2MDy8vLUUU6PJ5ftOLUyh7efmEDjiSwbcjlnCNPNjmOw7eeXcLcjgc0CygKiPz93a+m8OSUBY+//wIYQ7J3+VlLu92OgYGBrN/0CYLAqYjKViQihSQejwcWiwWjo6NgWVYgg/GEJP/0vzP41eg2fnhfPzqqSrG7u4v5+XkcPXoUarUaG3t+mDRyyONEb/HYcQVwasWBSw8ZUSIX9/3YvUFISRKlKbQ5H7w1+UQikiTh9XoxPj6OtrY26PV6wWYmldnBVbsP//PSOj56VfOBKn00UAyLb/1lBbcPVMOQoWznQkW25+je+T+jCDIcvn/PUZAR23no5DoohoVCSuCFM3Z0VpVCo0j8oBmLtCoUClRVVaGqqgosy8LlcoVVBw0GA4xGIzQaTV4eZguxBezxeIouOKKoCaAYuN1uobVTVVWV1HvzIYrgkQwBtNlsQosunfizbB6vhCTwjT8vwRNkMNCgF9rA/Dal5H5LtK9OB0OJHBzHYW5uTjDljkdAtEoZpCQRs4oVCoYjsOMKoCkHT2o8AWQYBv95ezcolhOtEM4VLmox4unpXehUZ/eLZVlMTU2BJMmklL65BEEQ0Gg00Gg0SQlJ3nFRAzQKKQ5XlByweXH6Kby8ZEdruUaU/xtB7EduERC/AD6/aIeEJHBdR27azHx1s6urS1icEkXUxSODPz61gV+ObOO1PZVor0zcahxec+Khk+uQSUjcf1H00Y1zBSzLwktz2Njzo1qXmblCAPj12DbOWL24c6gak1tukK86GLzn4XG0V2rw4Sua8OaBamy7Ath1U/j286sYqNNh3uLBofISvOvihrj7nOj6JkkSOp0OOp0Ozc3NCAaDAhl0u91hyuJYllCZRiGKQM7bwBQYtra2sLi4iO7u7pSYeT7bdGLasRzHYWVlBVtbWxgYGIBSmd5NJ1IgkWn8083t2HYGDswAUhQFkiTwqesOA9iv2I6OjqK0tBR9fX0Jf4fOai06RaZ8/HHFD4llB+816UURxkgk85RPEASCwSCkUikUMinET2PmDjd0luOGzrNkhBdCmEwm1NfXF1SrOh54IUlVVRU4jsPe3l5UIUm9QY2PX9OChYUFeDyeMJsXrVKGY01lMKjFVarMGkXSRO6CpjJIMxQXlghWqxVzc3Mx2/diTaj5v5Mkifdd1oibuirQViFuoRuo1+E/3tCJruriqoykApZl8fSiCxI5jXtP1GUsts5HseAAXN1uFtrWBEGAYTlMbboAAM0mNZpNanAch/de0oBmkxoP/nY+ocAlFSIll8vDrrXI2cFcVAcLsQLodrvPVwALASzLYm5uDh6PB0NDQzl7KskkElUAGYbB5OQkCILA0NBQwT0NRUOZWo6yiMU1surIW9c0NjYmXbEVg4vr1SA12pTI3/j6Hl5Z3cPr+2vizmLxYg+z2SxkLpvNZphMprRJejbh9XqFvNtCFUKIAUEQYfNMkUISlmVRUlKCrq6uA4tIZRwFeSaQqzbo5uamkIstdj4ylgl1qLJYTpJoKxcfN0YSBI416lM6hlzgnT8cxYrdjyfedyztz+I4Dtce1kOq1mY0s/iN/dHvg9+6q+fAv/FdFAD419cmHhlIt5JGEMSB6qDNZhOqg6WlpcLsYCbX4UIVgWRjzcomipoARrsJ8ZFuBoNBVPWoUBFvHs/v92N4eDihjU0xIJQA8grtWFF1mYBWKUWlKfqgdJDe349Y5LBEIYVUQkIWp4ITqvStqqpCdXU1vF4vLBYLJiYmQNM0jEYjzGYztFptwfx2drtdsA3SahNXU2mWhVTkDZjlODz04hpe010RNmeYK/BCksrKSoyMjAh5qSdPnoRarRbIeaEmkiQLfnazv78/5SpJIhPqaDYzxYgVuz9jXQ+WZWFQyWDIsQF1Osh0K1Uul6OyshKVlZVh1cG1tTUAEKqD6Rq+F6oI5LwNTI7BJzoA+3YVExMTByLd0kU+TDJjVQDtdjsmJyfTnvcrFPBEd3l5GVtbW0lb16SyPYpmcNNXn8dNXRV47+XNwt8efnkN4IC7T0SfVWoylaDJFLv1FcvmRa1Wo6GhAQ0NDaAoCjabDaurq3C5XNBqtTCbzXlV121ubmJ1dRV9fX2iKpSfeGQSf5zdxVMfPAGdKvFT/eSmC1/+wyLW7D58+obD0V/EL8JZus7sLg9+9IdhvGagBfU1la9uMjUhSTYQakr83IINTj+N6zuTq8JyHIfZ2VnQNI2jR49mbGGP1ypOJCSZ2HDhG39Zwedfd0RU1f2HL61jxe7DJ69pSfjaTCATlT8exWamDGR3li60OghAqA6urq6mXR0sxBaw1+s9TwDzhXiRbukgU5FsyUIikSAYDAr/zXEcVldXsbGxkZF5v0KCxWKBTqeL2coO0ixkkvi+eS8v21FXpkaFNj55JAgC4FjQLIcnp3bCCODxJkPK1QCxyR4ymQwVFRWoqKiIOqvGV6OyabkSus+Li4twOp3o7+8XTUD7anX405xVtJK1s6oUX3h9J/rro1R1fXaQOxMg7Iv7+6RvBFveCahTz1eOhMvlwvMvj0FnqoS8VC/8eyIhSa7I+Sure3jHD4bx4K1HcF1HOZx+GhySOw/5BBOVSoXDhw9nlYhEqw5GCkl4Ivjw6Q2cWtmDw0ehvDTxg903/7ICjkPOCGAmUYjChETI5T5HVgd5ZXEq1UGWZQvCjiYUbrf7vAgk1+Bn4TiOixnplg4yEcmWznaB/ZOdP8ahoaGs70uunmSDwSDm5uYglUrR1dUVdZs0w+It//0y5BISP7hvMOrn+CkGn/n1NBRSEj9/1/G42+SFLr/94IUH/ibWQDUSqSZ7xJpVm5qaAkVRMBgMMJvN0Ol0Gf89+HNKJpOht7c3qc+/Y6gGdwzViH49QRC4/LDp4B88FkjmngBIKVCyX+0iXBuQOJbAtlwDrjT9eRre5uXy471QKFWQxJnNihSS2OwO2Ky7WU8kKS9VgCQIwcMt2cofTdMYGRmB2WyOaZKeLcSqDvKk8FNXNeLdF9bAqBaXO/v4+44JkXTFBrFkamPPjxfO2PG6o5V5rxjmi0gRBAGtVgutVis8fPFk0OVyQaPRCNXBaKMZDMNktVOUCs63gPOAkZERGI3GrM3C5csLkFcB8wkYlZWVOVFl8i31bG/H5XJhdHQUtbW1cLlcwvYity2VkNAopLipK3ZYulImwadvaEODIfHCnGmlM1/5yESyR6jpMU3TsNlsWF9fx9TUFEpLS2E2m2E0GtO+YQeDQYyOjqKioiJ/kWccB8nKXwB5CSAPuWmqDADlBbnyFzAdtwFE6tWJ9fV1bGxsJCWE4PGhn47jLws2/OmBi3Do0CH4/f4wIUlZWRnMZnNGEklq9Eq89KlLU3pvIBDAyMgIGhoaMh7Rlwoiq4MyGQelXCpUB2maFl4T7XtTyc4SyXyTo2Qh9r75jWdXMLLmxGWHjBmdiXV4KZxaceCKNtMBn8BYYBimIGZfZTJZ1Org2NgYgIPVwUIVgZxXAecYyVYvkkW+CCBv4Hrq1CkcOXIEBoMhJ9vliWc2Ly7enqe3txcsy2Jvbw/AfiXv/h8MY6hBjw9eebYF9J27+xN+5olmcd9PppJAsh3rJpVKUV5ejvLycmGY2mKxCCHufKs42WqUx+PB2NgYWlpaMjonmzR8NsC/B0Sr8snUgGsT8OwCmuTVyBzHCTYvqQohOqtK8ZcFm6D2ViqVqK2tRW1tLRiGgd1uFxJJeCGJ0WiETC4XvfimC/63PHz4cM7uD8kgndnBc3me7mNXNWPZ5sso+bN7KfxlwYrnFh3oqNRgfNMNc6kCvbXxBV2F2LaOVh202Wxh1UGKogqObJ2fAcwDshlfxn9+Pgjg7u4u7HY7Tpw4kZN5MB68KCMbbQF+Yd7b2xPseTwej/D7KaQkSAJhpsSx8N3nVzBvceOfbz6S1EKRCbNrnvyFmuamixWbD1U6RdR0hchh6shqVGirON7N3GazYWZmRjAFnt12QaOUoUqrSOoYHvjZOJ5btOO5j1+cMtkhGCqB4IMAwQaTnIQLb2339PSk/Nu865JGvOuSxqh/k0gkQjuYF5Ls7u7i0T8P43MvevF3l5Xjmp66jAhJdt1B+CjmQMTX3t4eJicnwwyec4VUyZmY2UH+eoq3jUIlh2L3q1QpTdoXkeM4PDNvQ3uF5sCc86rdh2/9ZQVXHjbiPZc24PO/O4PhNSeONehEEcBCE1NEInJu2u12Y3p6GktLS1hZWRGqg/l2VTjfAj4HIZFIcpoHzKcw8G2mXJI/IHuEl6Zp/OdvXsK0ncMX7zoOmXT/pkNzAP3q9giCwPfuHRD1ef87tgWWA15YtAEEcKJZnGggXQIYKvbIFPlz+Cjc9d+nUKFV4Gf3DyV8fWQ1ymazYXNzE9PT09BoNCgtM6KmwhymrNvY2BB84RQKBTiOw+SWGzvOAP77hVV8486j6KkRZ6b93KIdHJBWpYuTawCO3f/fyDYvx4Hg2P3XJAGKojA2Ngaj0YiGhgawHIeRVQcaTSXQi1Arp4JQIQmlNkHy0inoNCqsrKxkROX9/KINQYZFrV4pnGv8XGO285mj4ZfDm/iXJ+fx83cOJTQZjofQ6mAoAeSr6hRFCQ9aoQ81ngCNm//rZdzcXYGPXNmU3sFkGNmspnmCDL71lxXU6JUH/P0qtQr01+lwtFaHMrUM/fU6UCyHv78xhuI+R/ucDRAEgdLSUpSUlKC+vh4KhQJ2ux0bGxvC/Y8nhLlubVMUVRDt9GRQ9AQw24xfKpXmrALIz/OUl5ejubkZk5OTOdluKLIRB+fz+TA8PAxGpoZMRQhVrq09P978/06hhKTxmzi876nJHXz3hRV8485eaF5Vnv7kVaL0jT8vgUByBJCiqJSOQ6zSN1noVTLcOVSLq9ujCCUSIDIf9/nZLTwzvo3O5VVoFPuVKq/Xi2AwiIGBAeFpnyD248imt9z47gurogfvV+0+fPzqFlzVnmb7WKEBp28C4VwDSiI+y2sFq60BlHrRH8fPyjY2NgqzcEGaxbzFC4rhMNSYfcukQ+UavBySZ8yrvHd394UkUqk06db9Ve1mUMzZebiNjQ2sr6+nNNeYCSjlEhAEoJRljjTwBIT/v8FgELOzsygvLz/QKpa/6sEpz1GaSjLIZmXS4g7iUHkJ3ntpeKwbxbD43otruLbdjDK1DBzHoUqrwKeubYlrVs+j2AggD16YKZPJwkZl3G43rFYrxsfH930Zc1gdLMSqdCIUPQHMNnLVAuY9DNvb22E0GhEMBvOSQ5xpAsj7FnZ2dmJ6cg9OixVbzgCqdEpoVTIYS+TQEvG3Z3EHwbBcmIKTv9jecVHsnMtoCPWNTAahYo9s3DDfc2lj2p9BEAQ6602QyBU41lgGn8+HsbExUBQFiUSC+fn5MOGCSiZBX50Oz338EtHbKFVIoZSTGSEAbO0xkGfcIJwbgEwJgAAoHzi1EWz9RaI/x+VyYXx8HEeOHBEU1cC+OOiGrnIoUkh9yQRCVd6tra0pCUn2F3EJOI7D0tISHA5HWgbP8cByXMKq7vUd5bg+iznGFEVhZGQEtbW1qKqqCjOh5u/Dv33vgDDLW0jkJdr+UAyLH5/awGC9Du2VqbfqZ7fd0Cgk0CrDK9lBmsXWXgATmy64AzTmLR48u2DH6VUnPnZ1c4xPi7/PxYBozhx8dbC0tBSNjY2CkI6vDpaUlMBoNGalOshxXFZjVLOF8wQwAXJBANfW1gQjXr4ykE/1caa2u7a2hrW1NcG38IZOJaQkgYpX/cDUcgl+9s5jePHFF+N+zp3HanHnsdqof5NGmZmLh2QJbrbFHpmGTiXD8SYDgsEgJiYmUFNTE1W4UFJSIggXkrkZ6tWyuIrspCBTgW29HoR7E8TeGsCy4PR1+/YvpLhbE59329PTE9WDq0Se21vcltOPitLoM5XRhCQ7OzsHhCSR9hbZMngORZBm8djYFhqNagzU6zP++WLAV3Gbm5sFgVJoq1gmkx2wmeH/f4lEkrWHM7GIVgEkCQIBmsOOK4j2NC6b6zrKo+ZOlyik+OS1LZCQBD7323kEaBYfvKJRdJ51sRJAMfsdKaTzeDxh1cGysjKhOpip76DQ14dIFD0BzPYXnk0ixrIspqenEQwGD3gYZqMVKwaZ2C7LspiZmUEwGAzzLazUKfHWC8J9ylKtyKWKZI6v0Mgfx3GgWA7yBKTX7XZjfHwchw4dgtG43xqPFC643W7s7u5iZGQEAGAymWA2m1FSUpLx49x1B/GRn43jS2/sQ4z/xAAA1ndJREFUOqh8JCXgtLXgtNEJfjzkux0aiclNF+7+7mncPliDj13TGve1sYQkY2NjYFlWiAssKSnBxMQE1Gp1Vg2eZRICcikpyqw5G+AVzW1tbXETjpIxoY61qHMch/+d2EF/nQ7VuswZ6kcjJRKSwNsvzK7VEj9S87GrWxCkWdEG7UDxEsBkbWBCZ3UbGhqE6uDm5qbwQMy3i1PxFyzEZBIxKHoCmG1IJBIEAoGMfy4/72c2m3HkyEEla77IRrqEl89iNhqNaG9vT3gcuT7OaITTG2QOzMtka94vHTw2tg0/zeKNfVUx94eviHV1dcVUpIW2SpqamhAMBrG7u4uFhQV4vV6hNVlWVpb04mD3BjG65sRFrQYhK/jlFQemt9w4teLAtUfSbx/yCSZutztr7dBU0GouQX+9HrceTc7AOnRxamxsFExxl5aWsLu7C41Gg8rKyqTV+Y+ObEIqIURVbAmCwM3dyZWobJ4gSIKAXp2ewMbpdGJiYiJpRXMiE+pY1cE9H43/+MMSGg0qfOuunrT2PRT5VicrpGTS4w7FSgB5EV6qiFUdnJycBMMwSVcHPR5P0aWAAOcJYEJkQwSyt7eH8fFxtLW1wWRKfvA/m0inAuh2uzE6OorW1laUl2dvTigdRB7fy8t2fPrRKXzmNe2Cl2Ahkj8A6KkpxZYzEHN/eOPjvr4+KBQKPDVlwa/Ht/CF13cKZCwa5HI5qqurUV1dDZZlYbfbsbu7i9nZWaE1aTKZRFXZVmw+bDkDCNAspPL9bV7TbkZfrQ4mTfpVOl4lL5FIkrJ54TgOS1YfasuUUa12MgG5lMQ37zqa9PtG1vbQZFIL810MSLihgt/vR0dHB5RKZZiQhK/WJhKSEK/+T7bwp9ldgCDwut7UE1vsdjtmZmZw9OjRtBNWElUHeRNqrVKCB29pQ4sps4kuhXKfSAbFSgAziWjVQbvdjq2tLczOzkKlUgmzg7Gqg8UYAwecAwSw2FrAGxsbWF5eznhmcaaQKgHc2dnB/Pw8uru7C86gMxSRx1etU0EuIVD7qqVFtsUe6aDRWIJG48GbDMdxmJ+fh9frDauI/Z/fzIJhOSTTYSdJUrjZhbYmR0dHwXGc0JrUaDRRr73uGi2OVJZCHlKJkJBEwoxmMaBpGqOjozAajUmn4uy6g3j+jA19tA5HRAzjr9l9eHHJgdt6sxvX5fRTePsPRqBRSPDHj+wLX56b28YL44u457J2VFbsPyDGE5KYTKao1dpbjmZoVjMGLjssPnEiGiwWCxYXF4UHlkwikQl1b/X+dRTaMs408l0RFIPzBPAgeLU+76zg8Xhgs9kwOTkJmqaF6mCo72oxegAC5wABzDYyRQD5ubhAIIChoaGCC7LmkezxchyHM2fOwGq1YnBwsCBmseLhAAHUK/HY+06EVQsKqeqXCAzDYHx8HGq1+kBF7HcfOoEgw6Zc8YrWmuQrUR6PB3q9HiaTCQaDQVhoSYKAXJr5787v92N0dDTlyDOTRo7LDplgLhV3fn7kZxM4s+vB5YczG9cVCa1Sho9d3YLjr9rU7O3tQWZfxpsuPoKaioPWRtGEJBaLRajW8nOFuchJNaTxvWxsbAgxfaF+ldlCZHUw9H95ohYtkSRV+CgGb/3uMAYbdPjUtfHnQfOJYozcA3JXbQ29B9bX1wvVwZ2dHYyPj+MLX/gCrrjiCrS1taVEAH/605/iM5/5DKampnDy5EkMDp7Nu//c5z6Hb3/725BIJPjyl7+M6667DgBw6tQp3HvvvfD5fLjxxhvxH//xHyl/H4XJQgoImSCAyc7FhSLXT5F8EogY8ORDJpNhYGAg4Y0zSLP4p/+dxuv7qtGfAaXhtjMAk0YeZg+TCNGygAtN7CEWgUAAo6OjqK6uRk1NzYG/y6VkWCUuXchkMlRVVQn2HA6HQ5gdVCqVAvlQKjM3WA/EtnlJBgRBJGVc/PU7ujG95c4q+eNx++D+b8dXxAb7Exs80ywLqQghiclkyltCAsNyeGxsCz01WjSbzlaul5eXYbPZ0NfXl5f5zWit4lBCSNM0CIKARCJJmQwqpSQIAjkR1fgoRshQTgXFcr/jkU+7ldDq4KFDh6DRaPDrX/8aDz74IDY3N/HJT34SN9xwAy666CJRDzZdXV34xS9+gXe9611h/z45OYmHH34YExMT2NjYwNVXX43Z2VlIJBK85z3vwTe/+U1ccMEFuPHGG/HEE0/ghhtuSO14UnpXAaHQW8BOp1PI60w2e5Xfdi6rhRKJBMFgMOHr/H4/hoeHUVNTg7o6cSq3mW0XRlb3UK1Tor9ej7kdN6yexNuKhj0fhXf/cBgt5hJ8/vVdot8XmQVcqPN+icArffOVA0uSJAwGg7BtnnxMTEyAYRihVZxuHFoim5dswaxRwNyaO0Xs+vo6Njc3RVXEdt1BPD29g0taTQKpjSUkWV1dFRJJTCYTjEZjzPuJ3RvEExMWvHmwOiN5xgQB+CkWKzYfmk0lQhSkz+fLiJ0Nx3H47guraDSocUVbarPU0VrFoVnF8fKK44EgCPz0HbHd7WmWw7rDjwZD4iSX77+4BqVMgjf1H5y1fG7Rhj/N2XD/RfUwaeSg0qj4FwsKpWpJkiT6+vrQ19eHoaEhPPfcc7j44ovxk5/8BB/+8IfR3NyM66+/Hrfffju02ugpS0eOHIn6748++ihuv/12KBQKNDU1obW1FSdPnkRjYyOcTidOnDgBALj77rvxy1/+8q+XAGYb6RDAzc1NLC0tobe3N6XFK9s5x9EgZgaQN60+cuRIUuTja388A1eARm/dfqbt55+aB8WweHsLl3SlU6uU4toj5bg2SVPa0OMrVPIXZFjIJSRWbD6MbzhxXUd5WJWTJ0Xd3d0FM3hcUlKCkpISNDQ0COSDj0PT6XQC+Uim4pNrmxeG5XByyY72Sg3KRPqoJYMgzeK3kzu4qMUgtE95g+e9vT3RFTGVnIRSJoFGEfu1MpkMlZWVqKysDEskWVpaEoQkJpMp7Pz5z2eW8OjoNo7WatFRlf4cL0kQQnWT4zhMTU2BJEl0dXVl5FrjAHzvhVVISCJlAhgJvjoolUqjmlCLsZkRg+G1Pby45MDreytRqY1dmZ7d8WDe4kFVDLuaJqMao+su6FRS7Pko/N1jM7i4xYA3D1SL2o9Cueclg0LML/Z4PDAYDLj55ptx8803C96djz/+OPx+f0wCGAvr6+u44IILhP+ura3F+vo6ZDIZamtrD/x7qjhPABNAKpUmnQXM//herzeteb9k2rGZQiLCm46I5R9uasOyzYfBBj0YlsObB2vQYFDDsjCW1EX93edXICUJvOey5LNA+RYwx3HC71pIQ9CPT+zgX347h2/edRTLNi/2fOGxdWtra0KlqFDnLXny4ZNqMUs50FqhhMNmxeLiIhQKhaBijdUq5udKnU5nTm1eggyLhV0PSAI43pT4wYblOKzafagvU4laSP00A6efxo4rCEOJHBzHYWZmBizLoqenR/R5WCKX4rVJWM3ESiSZm5uD3+8XhCTvuaQBFzYbcKQys8PsLMtifHwcJSUlaG5uzhjpIAkCD799IK32Z9zPT9KEOhl0VpVCI5cmbBH/y5PzoFkO/3RT9FzfKp0S775kPw2pREFg3uIFy3F4Y39VRqq4hYhC9Nzzer1hM4AEQaCtrQ1tbW24+uqrsbW1deA9n/3sZ3HrrbdG/bxobe5YnrnpXE9FTwBzke+XzMxBMBjE6OgoysrK0Nvbm9b+5SMNJFYFMBOk9scvr+FPs1bcd1EDGo1qPDNnxRv6FcI2xV7UAYpBOs6MDMMIcz6F9gRco99PSzGoZThcvj8ywJ+D/IJdSN538bDm8CFAszCUlcFsNODQoUPwer3Y3d3F5OQkKIoSWsX8E7LTR2HtzBwkEgmOHj2a099HJZPgtt5q0V5qi7tePL9owxWHTagtS9zK0ypluGOoBgTOzs9qNJqMkiIxiCUksdtnUaZWY2MjkDEhCa/cNplMqK+vT/yGJBGveiYG7gANghCXGBPPZoaiKOGhUkx1UCWToD0K0eY4DqdW99BqKoFeLcP/vbkNviAj6vyQkgTecVEdJjbd5yz5AwpTuex2u2POJz/99NNJf15tbS1WV1eF/15bW0N1dTVqa2uxtrZ24N9TRdETwGwjmRuzy+XC2NhYxnzw8kEAo7WdKYrC6OgotFptWqT2yckdbLmCeGZuF9d3duLNAyRay0swurl/nGLVgO+6NPnKHwDhaZ1hGJw+fVoY5i0kO56eGi1+9+ELw/6NYRiMjY1Bo9Ggu7u74EhrLFzSelDFqlarUV9fLyjqrFYr1tbW4HQ68e0pFq9sBvHN19aiv6016eN8asqCMrUMgw36lPc50hA8HuoNKkhJIyp14okSSRDC9VRRURHWzokHluNw4b8/i4taDPjC6ztFby8RxCSSpCok4cVvfK5vIeL133wJBEHgifdfkPjFIQitDgaDQUxOTqKxsREA0poddAcYPLdgh9UdxHUd5Uknlby+twqv7xX32mLMrgUKswLo8XhEz8KLwS233II777wTDzzwADY2NjA3NyekhZWWluKFF17A8ePH8f3vfx8f+MAHUt7OOUEAcx0nFg1bW1tYXFxET09PxvyA8jUDGEo6PR6PkM9ZWZmer9g7Lm7EjiuA91y2H1J+5NU5o1zE3vGzPAAwODiIQCAQ5qfGV6J0Ol1BESze/qS2tjatJ71ChFQqRUVFBSoqKuDz+XBs9xQmLQSCLiteecUltIoTKWJ52DxBOLzBuASQ4zj8cdaKyw4bsWT1orZMlTBaLxbkEhKNxuQeHvi826ampqQeEkmCAAfgLwu2JPdSPDIhJOERLde3EPHW47Upt5B9FAOCoTA8PBwWuxjLhFpMXnGpUorbB6uhV2XfGqcQK2liUIj7naoP4COPPIIPfOADsFgsuOmmm9Db24vf/va36OzsxJve9CZ0dHRAKpXia1/7mkB6//M//1OwgbnhhhtSFoAAAJGAOBXFI0IwGMwqAXzuuedw4YUXRv0b35pzu93o7u7OqKfVzMyM8ASeK3g8HszNzaG3t1cgSN3d3UkPsSaD4eFhtLa2Zs1IM5HYg2EYWK1WWCwWOJ1OlJaWwmw2i1rosgne/qStrU202OaJiW0opJKMDcXnAryiOTQH1u3xYmp5CxK/A8FgMGME/X/Ht/GZX8/gfZc1gSCA3lotjtbqMnUocRHtOJPBj19eB4eztjG5RKiQxGq1xhSSAGdzfdvb2w+0xRw+Cm4/LaplXsj40+wu/vXJOdx9mMP1xzri2hOFmlCHrlOCd2aeyAxFURgfH0dfX19etp8qbDYbbDYbWlsLx1/xk5/8JN74xjfiiiuuyPeuxELUm+Y5UQHMBaKpVENbo319fRmvHOWrBUzTNJaWlrC9vY3BwcGsm8pms9IpRuwhkUjCciGdTicsFgtOTi7iq8NBfP6mehyqr8q4v108WCwWLCwsJG1/8uAT8wCBvBHAAM1ASpKivRltNhtmZ2cPKJoX7BQm92S4sbsTBpUUVqsVGxsbmJqaQmlpqVCJSvaB6/LDRnzkqmbc3F0Bh49GRQ582oB95fzU1BS6u7tTftBpLS/JW6dDrJBEIpFgamoqZq7vU1MWBCgGdx6rLeo5NZOSA0MFcKy7O6E3ZSwT6lBlcSZNqMWiECtpYsB/X4WE81nAeUS2W8DR/Pj4eb+WlpaUkgmS2W6u4XK5oFQqMTQ0lJMLLRst4FTNnQmCgE6ng06nwzKjA8bnseGkEJyYAE3TQtUjm+a6Kysr2NnZCVP6/nneivJSBdoq4pOHH7ytH1JJfhZWjuPw09ObkEtIvEmEDcXm5iZWV1ejRoG1VWhQopDCWCIHSRAHCPru7i5WVlaEGTaxs5wlcinuHNqfuytVZr/NBoRHnqXzEDGQAfP0TCGakGR1dRVWqxVlZWVwOp2Qy+UHftcbO8vhDTI5IX97PgqlSmnS26IYFq/7xkvor9Ph/9zcfuDvTqcTzvV5/Pz+wZhkft3hxwM/G8f/94ZO1OjPVjsTmVBnymZGDIqVABaiDYzb7T4fBXeuIpIAbm9vC9WZbP7ouSaAgUAAIyMjIEkSnZ2dOZuFyzQBzFSyx5WHTbj8kAkksU8MedECPxOl0+lgNpvDotDS3e+ZmRnQNI3+/v6wm/OKzYfNPX9CAlgvwlg2WyAIAu0VJTAk8NAL0AyWzizB63ZiYGAg6nenlEnQaj74RB1K0FtaWg5k4xoMBphMJuj1+owsbukm8SRj8Fys4Cv4wWAQF110EWiajikkKVFIUaJIbdmhWRZSkb+pJ0jjkeFNNBhUuKItuRlE6avVa3fgoP2Xw+HA9PQ0jh49GveBY9vpR5Bhse0MhBHAUCTKK05VSCIWxUoAC1EE4vV6o1a8Cx3nCaAI8ESM4zjMz8/D6XRiaGgo6zd0iUQCiqISvzAD4BNL2traMDs7m/P4uVgEkGU50CwnOtIsk7FuBEEgtJgWKlpgWRZ7e3tCq1apVMJsNqdsn0HTNMbGxqDVatHW1nZgv28frEExdMwGG+LPtrEsi6/+5jQAAh95TX/aC1BkJcpms2F7exszMzMoKSkRfpNUrtUtpx9PTVlwU1dF0rm3vJehy+XKSuQZzbKQFIiNEZ/r29fXJ3zPmRCShGLN7sPvZ3ZxQ2c5zCLa9iVyKfrqdKJFOk4/hektNwbq9ZCQBH793uMHXmO1WjE/P4/e3l5QkOJPc1Zc2mqI+hv01+vxyLuOido2j3g2M0DmTKh5nCeAmcP5FnAekYs4uEAgIMwf9ff35+TGy2832+AVzHxiyezsbNa25fLTKJFLQL76lD254cTDo3u4/6Log/jf+PMZUAyHD17ZkvCzc5nsQZIkysrKhGF+j8cDi8WCsbExcBwntCVLSkoS7off78dDvzuNyzrr0dIY3RYkmbzjQgVPcvvrdKisrMr44iORSARrH47j4Ha7YbFYMDw8DIIgwkQLYs4NCUlAKiGSbiFyHIfp6WkAQE9PT8bPQ47j8KOX1iGXkHhzHgQhoUiU65tKIkk0aJRSKGUkFFISDh8lSiWbjLhnbseDiU0X2io00EX57J2dHSwtLaGvrw9yuRxf/O0cnp23odnUg7osCFpiVQdjmVCnci0VKwFkWbbgTPBTVQHnG+cEAcw2eCf7Q4cOpW2FkgyynQSS64qmn2Lwb0/OwqxRCIRu1e7DmpPGzI4HdVHGxvrq9Nh2JibB204/3v+jEXz06mYMNeY+G5ePQmtsbEQwGMTu7i4WFhbg9XpRVlYGs9mMsrKyAzdcp9OJP58axw+mWUz79/CFGAQwERxeCk9M7uDm7oqUW2yJ4A0yeGx0Czd2VaBUmdw2+PGCuro69OXAE44gCJSWlqK0tBTNzc2C7Q+fRcuLFqL9JjzMGgXuGEzu9+ANnktLS9HU1JSVhxCCIKBVSVEbo7WYDH47uYPFXS/efUlDUvsqNtfXTzF4dHQLVxw2obxUIUpIEu030atkeNNADa798vOgGA6Pv/84lBlMADlaq0WLuSQq+dvc3MTa2lpYhfNdFzfgRFMZavXJzXQGaRYBmk36+olVHXxicgcEgKvbjMJrxJK6QhRTiEEhVgCT8bEtJJwngAmws7MDm82Wc/IHZHcGkK/GqNXqnFU0lTIJ6spU6A15Mr+2oxzfe3YeD52y4Oreg1W+C5oTkzmGYUBRNDgAPir/zkVyuRzV1dWorq4Gy7JC0sLs7GxYW9Jut2NxcRFXHO+FtMKN/rrU7Uj2/BR8QQbeIJM1Arjno+AJMrB5g0ktYLz9yeHDh5PKjs4kFAoFampqUFNTc+A3UavVwm+STmWBoiiMjIygsrJStMFzqri1JzMk+p9/MwuWgxAnJgbJ5PpSDAdvkIHVEzwQexYrkYT/TfjqYOhIxd9cfwiPjW5llPwBgJQkoVcdJENra2vY2dlBX19fWMvaUCLH5YeTV9rf8/1XQDMcfvKOgYT33CDNRh19Ca0Ozu36MbzqxJPTNnzulkOQvup6MLnlQWd1KSRxCGEhiinEoNAql+nOCecT54QPIE3TGSdK/BOuw+GARqOBwWDISLpHMnA4HFhfX0dnZ+ac/4H9gdWRkRE0NDRENReO53uYLj76szEAwBfe0C3828mJeShlUvQcbkzqszI575cOAjQDT4BJOCfGtyV3dnawsbEBmqbR0NAAhdaATQ/QX6/LqTXGjisAQ4lM9GA9kPzNjrd56erqKsgWCZ9+YbFYsLu7CwAC8dBoNKKPtViMjyPh9FPwU2zCTFoe2cj1ZTkOLMcJ52FoIonVagXDMGklkqSKpaUlOBwOdHd3Z4woPTm1gzW7H/ddGD8Wb93hwycemcQdgzV4TXfswgPLcfjPZ5Ywu+PBl97QCY7j8MqqAz84uY439FZgoG7fvzWakGRnZwder1dIMCkWzMzMoLKyEjpdbvw7E4HjOFx66aUYHh7O967Ew7nrA5jpG0JodWxgYABLS0uCl1wukY0KoM1mw9TUFDo7OxP6V2UD772sGZHjbFVaxX5Lg+Xw+PgW+uvLUJ2gtVIo5A8AXv/Nl0EzHH7z/uNxCRzL7beKg8EgDAYDmpubYbVa8cRLM1i2ByH3mFFXVQG9Xp/143H5afxqdAstJnVSKslk9iuezUsirNh8uOM7p/DT+weTjsNKBqHpF01NTUL7/syZM/B4PGFtyVgkgK9wRjM+zhaembPiU7+cxM/fOYSqNL4frVIGsXG6fK6v2WwWYq8yUf340UvrYFgOd1+w/5mZTCRJBRzHYXFxER6PBz09PWdbrxyHn5zawJFKTcrm4dceEVdE0KtlUEglaDbFn40kCQLvu+xsNCZBEOiq0eH2QQI9NaWQS0lBSBLqPcgrtwupkiYWxdq6LkScEwQwk+Cjz5qamoT8ynz58WXaHmV1dRXr6+sYGBhI6EeWrbJ2SxRrD5IkQVEUKIbF5KYbQZrDbf2xfeRyKfYQg09c04IFi1cgfyzHHSCCniCN1/3XS2jWMPjkFTVobGwEQRCora3F3VXVcPmCYHwubG5uYnp6OutpJKVKKS5sNmTFNobjOKF60t/fD6lUCoblkhKyzFs8YFgOixZP2gTQE6ChlktEnSeR7XuHwwGLxYL5+fmoSm/eFiTXFc49PwUOAMPGbtJQDAtZijF3kYiW67ti8+H3Mxa8trcqreiy9koNPFEsV3hECkl4o/bl5eWwLONMqDA5jsPs7CwYhjmQu00SBPw0i4lNV9bTY0rkUnznrb0pvVchleB401k1fqQJNS8i8fl8wpx5rk2o00Ghta4piirK+T/gPAEMg8ViwdzcHLq6usKiz3JpxxKKTBFPlmUxPT0NmqYxNDSU8OLhiWeuLjJ+e0qZBO+9vAnKOJYvoeSvUG5Ylx4y4dJD+/8/zbJ46MU1lJcqcFPXWYNwgg4iGAzgaH05mpqawt4vk5AwaJSARikoWPlFbmlpCTKZTCAefC5ugGagkCb+fYIMGzPrtqMq875VLMtiZmYGHMcJ4gCO4/CDk6uQSUjBhDkRrmwz4YVPXJL2/vgpBld+6Xmo5RL84SPJjTWQJAmDwQCDwQCO47Bjd+KnJ5fRq9+AnOSgUqkEmxexecWZws3dlbg5TmtwbseNZ+ZteO3RShiTtLCJBN/ebmlpCYullEn2VdKSNB/AkjG4DvWB5PdNrJAkEfjZRolEgiNHjkR9YLj31SplMYIXiEilUmxvb8NqtaK7uztrNjPZQqGJQIrVAgY4RwhguhUgvuRvs9kwODh4YBBcIpHA7/entY1UkAkCyD+5m0wmoeokZru5JIChx6mJI2DgWxm5elplOQ63feMlHKksxedee0TUe6QkCbmERI3ubMtzb28Pk5OT+OU7ekW1CEMXudbWVvh8PlgsFkxNTYGiKMx6VdhjFXj7JS1QyWN/X94ggxu++gJazGp8563Zz/vkRyf0en3YuUYQBNRyCeoN4jzZMgmlTAKTRo77Lkxv4SYIAn7IoCzVoam9AvTeNtbX11FSUoLh4eGMm4KnizK1HCoZiRK5+H2hWRaPj+9gqFGPylf7wvFyfat0SrzlWH4JUaiQJJq4J5qQJBpYlsXExATUajWam5vxpzkrKrVKtFcW3txqutje3sbKykqYOXk2bGayhUJrAbvd7vMEsFjBL1oqlQoDAwNRTyw+HzfXSJcA8nF1hw4dSmownW8L5KqsTRBE3FZ3vub9SIIAB2Bh1xP3dTZPEL8a3cJbjtdCSpK469jZKtf29jaWlpbQ29ubcpVIpVKhvr4e9fX1oGkaqqUt/HlmE8OnXopLPFSy/Uzeq5JMQkgFoTYvVVFsXt7Ynz+/uv9930FT31TQYFDjbSfqsHTmDNxuN44fPy48LIWagisUCqFim2r022/Gt2H1BPHW46kRLJNGLrrayoNiOGw5A5jf8aBSq4TT6cTExETMXN9CA0mSMBqNMBqN4DgOXq9X8OaMTCQJvYcwDBP24MJyHP796QXISAK/fHdyZs6Fjq2tLcHSJnS0JNcm1Omg0FrAxeoBCPyVE8BEalgeUqk0LzOA6WQc7+zsYH5+PqW4umxk88YDv4hGA0/+QgPTc4lHRSwAvxrdwo9eXsdggx5d1fujAxzHCSa5mYwBk0ql6GmtRU9rbcI0EoIg8PsPZ0fNHYpCsHnJBViWxcz0NEiSDDN4jjQF54nHxMREygpWu5dCMpf+3I4bMgkpOvkiGlQyCe45UQcpSQjq7USRZ6li3eGHXi1FSZwKdjogCCLMm5OiKNhstgNCEr1ej4mJCZSXlwvWPSRB4PO3daBMXZxzXbGwsbGBzc1N9Pb2xp0rzoUJdTrgCwGFAq/Xe74CmE+kcjLwbYKurq6EcvJ8iUBSOa5E7WwxyPXxxiKckfN+hXDRRxusf9NADY7W6tD56kwdP3MJAL29vVm7QcZLI6FoBgajCdWV5UnZmSQLu92OmZmZgrV5yRT4KpFOp0s4SqFWq9HQ0ICGhgZQFAXLrhXzZ1YQ9Lmh1WoFcU+8KkZoFVkMnpmzgiQJvO1EfHuRRJBLyLDUi1RiDROBYlj87/gW1HLJgRay1ROEQS3L+Pkqk8mEGEd+xnZ7exsTExNQKpVgGAYejwdqtRoEQeBIZeKKZ5Bm8ZPT67j8kAm1SaaBuPw0Xlyy46o2U07ua+vr69ja2kJvb2/S1bNE1UGappM2oU4XhbAW8DjfAi4i8BmdVqsVQ0NDoghSvghgsuAXKYVCEbOdLQa5rgBG214ulb7f/ssy/nd8Bw/d2xfXRNniDuCR4U1c1WYOUzOr5RL0vWriTFEUxsbGYDAY0NCQXLpCugiteHz72TNwLXhwpe+snUmsNJJUsbW1hZWVFfT29ibV6iw241Te4Lmqqgo1Ncm1smUyGX63QiFAa/G2E51wvSruOXPmTFRxT6p400AN0v1ZGZbDyaklyHzWsNSLTEMmIXHtkXIYSsI/f3PPjzu/cxqXHzbiH29qy8q2gX3yoFKp4HA4BMEfLyThU2LEXCsMt29yveMKJE0Af/TyGp6asqDZpI5p9cJyHGjmYA76yNoevvP8Kv7ltUegEmGIvbq6it3d3ZTIXyRiVQdD1cX86wptdjBbcLvdRfvw+1dFAGmaxvj4eNIEqRgIoN/vx/DwsDAQnQ7itWTTBcdxoFkurIoWSQBzLfbg7UkSpQuo5RIoZZKocVEA4PP5MDo6isbGRlRUVER9Ta4w2GhAkNajp7EsbhpJKos839622+2CzYtYPD1twZLVi7svqIupTi4kzGzYsXVmBh2HW1I2eL7skAmbe35ISFKIQgP2z5fd3V1B3MO3inU6XdIEOdlosWj45E9O4c9Lbjx0b+ZGFmIhWqu6vFSBtooSvL4vu1GBvKq5tbUVRqMRAGIKSVQqlSAkiXzIUckkeOfFjSntwx2Dteip0aEpTsv+XT8cBcWw+O+39oadD+MbLviCDFiWA8dxeGrKgvbK0qiWTisrK7DZbHHj+tJBZHUw9H/5B71znQyenwHMM8TcLPl5v/r6+qSf4gudADocDkxMTKCjo0NoB6aDbGYQ/9uTc/BTLP7uxjaBePEEkJ/3c/qCUMokUWOQEsHuDWJy042LWsTPot17oh73imidlciluDvGUL7D4cDU1BQ6OjoKwqE+1Kcscjje7XbDYrHglVdeAUmSMJlMMJvNotoY0WxekoFBLcOanSgK8rdrd+J7fxhHV3M1LotD/hJ5HNYbVFEXZ5VKhbq6OtTV1YGmadhsNqyvr2NqairrPpCh4DPBb2iSodpUi5by/Ag+JCSB/7rzaFa34fP5MDIygra2tqj3ylhCEn6e02AwwGw2p51IUqqU4oKm+Pfqq9qMmNn2HNjOXcdqhREBV4DGN55dRpNRhc+/vivsdUtLS9jb2wszs84morWKQwkhTdMgCAISieScIoNer/c8ASxkWK1Wwaw1lcU5nwSQV8jGumDW19cFSX+mvMiy2QK+sNmA5xZtYQsmvz2+jfDAzychl5D4+h09SX/+l36/iPENF9orNWn7n4nF1tYWlpeX01L65goEQaC0tBSlpaVobm5GIBAQ/C/9fr+wwOl0ugPnHD9ioNVq0dTUlNIC2F+vR38M37cgw8IbZNIyFc4U7HY75mdmcPdlHagrj33PGF7dw4tLdtwxVAOtMvX9lkqlKC8vR3l5eVSzY6PJhOe2ONzaV5uycMIToA+MOITm+l55rAdXFVFrPll4PB6Mjo6is7MzzOc1FhIJSXiSbjAYslIxvX3wbCdnY88Pk0Z+4MHJ7qFwyFyCm7rDOw6Li4twu93o7u7OC9mK1ioObROn2iouNAEIsN8CLqb4x1CcMwQwmmKWb1Xt7OxgcHAw5YFm3sw2H+DJUeQFwnEcZmZm4Pf7MTQ0lNEqQVYJL0Fg3eHHusOHGr3q1X8i4PP54PV6oVKpcNkhY8pqxg9d0YyZbXdOyF9o4sXAwEDC3yBIs3D4KNG5q7mAQqEQ2l8Mw8Bms0VNI2EYBqOjo2FJEJnGVV96DiwHPPPARUmlhmQa29vbAqFPNNto1Mghl5IJxweSQTSz46fHVvDF329gamEVbx2siEnSY8HmCeLhl9fRX68XKk8sy2JsbAylpaUpE/pigcvlwvj4OLq7u1Ou1kQTkoSRdKMRZrNZEJJkCt4gg08/OgW9WoYvvqELLMfBRzEokUtRV6bEx65phV4txeaeH3M7bvjs23hsag///MbBgqm0hZpQh1YH+XVGrM1MoVnAAPsPFpHm/sWCc4YARoJhGIyPj0Mmk2FwsHAuhGTBk7FQcsEPpev1ehw9ejTjN+5sVgBr9UqoZKRQ5eEVvrW1tZiamgLDMLjQZER5uT4lsYChRI4TzZmzIuE4DvMWL1rM6rB4N5ZlhcqJ2Fbobd98CUGGxa/fezznLVCO48ABUbOKTy7ZoZRJ0FOzr1CNTCNZXFyEz+dDdXV1VrNuP3Z1C0bXnQL5y5ZYxOYJwhDjAWF1dRU7OzuiRRB1Zaq0lbeJoFQqcf1AKxSaMgzVa0F5nQJJ12g0AkmPt796tQyt5hIcLt9v80fL9c0GgjSbcJRjZtuN5xZteMux2oxF14WCj+vLtKVNvEQSvV6fMdGVWi7B63qr0PvqWMcDP5uAn2LwlTd3QyYhYdLsn8vffHYZy9s2XNukhE5fBgKFSehDq4MymSwpm5lCSwEBzreACw78nEcmBBH5RmQ1js8qbmlpyZrQIJsVwCZTCf71tv1ZldAnQH4Wig9+P3Mme+rVZLC468UTEzu4+ohJsIagKAqjo6MwmUyor68XTVL++eZ2nFpx5GX+7dvPrYADcP9FDQf+9olHJkFGeAbyVSiWZWGxWHD06FF4vd4wwUImZqFCcevRKtx6dL+6+PKyHadW9vDW43VQJ5FmkQi/HtvGZx+fxWdvbceK3YfXHt3PseU4DgsLC/B6vejr6yu4B0YpSeKaI6+2mUrOknSXywWLxYKVlZW485wkQeDajnIAZ9OB6urqUFkZO04uGn52egNrDh8+dEVzwt99ze7DW7/7Cu49UYt7LohNktfsPvgpFtkoQPJ+hskq1eNhasuFP8/bcMdgjSC+iZdIEk9IIha39Jz9nd48UI0XlxxhZJnjONzSwGLXpMHVx7pwexFVc5MxoS60FBDgvAikIMC3gPl5v87OzqxWK3KFUEUuf0Pp6enJqjM/SZJZzT6Ol+wRGvweeSMVW+3IJOoNKlzXYUajab9y4PV6MTo6ipaW5FWhfXU6wS4m1ygvVYBho48xfP32HiiiVGn4VmhfXx+USiWMRqMgWLBarcIsVDZi0HQqGaQSEnKpuIVsz0dh2eZDT0382a6eGi1qy1QoL5VjessNp4+GViERMmC7u7uLphVKEAS0Wi20Wi1aWloQCAQO5OKazWbo9Xph0YyV6ysWX/vTEliOw4euaE74WkOJHBKSQFtF/HvVVe1mXNWe+Rkq3m6nv78/JT/UWFBKJZCSBGSS6OdJtoUkJ5oNYV0OjuMwPT0NtYzE1ce6iub8jYZENjN+vx8EQYSRwnyjmLOAiQSzbfkZfEsBwWAQS0tL2NrawtGjRzP2tMfjueeew4kTJ3J+cY2Pj6O2thYOhwM7Ozvo7e3N6M0sGra2tuD1etHcnPgmnyxSjXULrXZYrVZIJBKhXZkr4YXdbhceLsQMkRcrQlNMenp64s42chwHh8MBi8UCm80mxKCZzeasmAjHwmOjWzhj9eLtF9UnJZLgZxsj84uLHQzDCA9PDocDJSUl0Gq12NzcxJEjR1J+OPYGGdAsm5bgJRfY2trC6uoqent7Yz4sWtwB3P+DEXzpjV1pJagkA15Isru7C6fTmbaQhBfxyGQytLa2njPnbzTwDy+NjY1C670Q8orvuecePPjgg2hvb8/L9kUi6olxzlQAp6enQVEUhoaGsnIiRJvFywVIksT8/DxUKlXOZhmzZQOTTqZvZLXD5/PBYrFgcnJSiNsym80oLS0V/bk+ioFSKi5hZHNzE6urq0I17FwFLy5iGEZUiglBEGFpJF/7/RzoLSsuMm+BZVmhJZnNNBIAuOaIGTYvlRT541uhNTU1caMgixESiURoO3Ich+3tbczMzEChUGBubi6sVZzM77Lfji+sGaxI8KkXkXm3kdh2BhCgWZzZ9aLRqMaq3YenpnbwlmN1KVlQiUE0Icnu7i6Wl5fDWvhihCQcxwlJJi0tLec0+eOv1VDvxtDqYOg4EV89zBUh9Hg8RZGVHQ3nDAFsaWnJKjmTSqWgaTqnBDAQCGBnZwdmsxkdHR05u8CzIQJJN9mD4zhQLCfMz6lUKtTX16O+vl6YG1xeXobb7RY1NxikWdz1ndPQqqT47t19cbe7uLgIp9OZtOlxsSHS5oXDvq9imfpgxXlx14MavRIKaTgZUCjk0GtUGBysBUVR+y3JhUW8/7c23NGlw50XNGRlnlMpk6BaJ56Y8HPCra2tSbdCHV4KL5yx4ap2c1ZEC5mG3W7H0tISjh07BpVKhWAwiO0dCx57cRq1yiDMRkPW5mw9QTopUh4tajEZ8JVrMakXXdVaPP7+C4T/XrP74AmyoFgWcmT/dw1Ve7e0tMDv98NqtWJ+fh5erzfufYxlWUxMTKCkpCQrnZpCQjAYxCuvvBJG/oDYJtSh60wuTKjPzwAWABQKRVa9+nLtBbi3t4fx8XFhliSXT3eZPlaO40DTNIDUn8re8/AogjSHb9119IBFiEwmQ3lFBX404cGJpmqYdQhLvSgvLz8wNyiXkihTy/CG/tiWJizLYnJyEjKZDL29vUX1hG1xB2AskUdV/UZDtGrY76ctGN9w4Z4L6qBXn/3unH4K935vGFqVFL9+7/Gwz3lHiMhEJpOhqqoK5ooKkL97Dn9YDeKalrO/i8lkAqMoxW8mrXjTQHVUopkN8JYgqZp2L+x6MLvjwWBDmaDATAfpkp54iJbrK5fLEVTosU34cbTJDLOCEq4XtVotpMSkO2qyavfhnu+9gjf1V+PdlzYmfL0nQOO133gJfbVa/NttnWF/81MMfvbKBm7srIiq4OYjPt1ud8qpF5GzddlAkGFjisCUSiVqampQU1MjzD/zM51KpVKo6Mrl8rBcagCwuAIYWdvDle1m0dd8MSAW+YtEIhNqsTYzqcDr9WZUXZ5LnDMEMNvIJQHc3NwUbto7Ozs5zeUFMlcBTKflG4nrjpTjD7O7Mf3hWI7Di0sODK858b17+sJSL3Z2drCysnJgbvDbb+2Nub1gMIjR0VFUVFQINhmTmy7UlikLfv7J4aXwPyfX0VGpEZSf8eDxeDA2NoZDhw6F3WQHGvQoUUihU4XfJrRKGe45UYdLW2PfkEMhJUk8+9GLhf/mf5fd3V1Mzq1ibZPGGSMNeUNV1oepeVVoT09PytvqrdWhrUIDTZzcaLHwUwyu/vLzqNWr8PDbB9L+vFCsr69jc3MzqqVNo1GNN/RVo1KngPRV0QLHcfB4PNjd3cXo6Cg4jhNGK1Jp4ZeXyiElCQw16kW9Xi2XQEIQONZ4MCFjz0fD5qGw5QwcIIAcx2Fubg4URR0Q8fx6bAsUw+F1vdmNlxODH7+8jl+ObOHLb+6CWRN/PjaakGR3dxfj4+NwuVzQarXQ689aZf1xzorJTRfqylRYsftxQVNZRuIB84lgMIjh4eGE5C8Suc4rZlm2aDtD54wIhGEYocqUDUxOTqKqqiojUWuxwN/I3G63MHy/srICgiCy6tUVCbfbjYWFBRw9mnosUzrkb8HiwR9md/G2E/VJGQK7AzTkEjLm/I7f74fFYoHFYgFN0zHnBnlCFKr09QYZfPPZZTQYVAWxmMQDx3F4edmBwxWamLnFPPgIu66urrzNsfDqVYvFkjCNJB3wquajR48mFKj8btqCf/rNLH793mNZJ/yX/X9/wT0X1OG+CzPnJ7i0tAS73Y6enp6UldnBYBBWqxUWiwUejwd6vR4mkwk+Ug2JhBSM3MXA5gnCT7Oo1qU+P0sxLKRk+L2EV8ASBIG2trYD95lv/HkJAPCuSxpT3q5oMK86J0iiny+nVhz4jz8s4v/d1ZvSjCEvWCorK4NKpQoTkmjLDJCotPjsk4tYsHjx/ssacXNPchY/hQS+8peqWj0WotnMAEi5OshxHC677DKcPn260DtEUXfuPAEUiZmZGSGsPRvgjVk1Gg0OHToknEzr6+ugKEoo9ecCXq8XMzMz6OuLPRsXD/HI3+MTO5jZduNDV8ROHvj3p+Yxve3Gl9/YdSC6KhLuAJ1SJYafG7RYLGFzgzwJj0aIVu0+GEvkGfWlyye2trawsrKCnp6eghG28GkkFosFe3t7KC0txSt2GfZoKd5zWXPKCSErKyuCn6GYp/Uv/W4BP31lE7953/GEJLqQwOf6BgIBdHR0ZIxAsywrqL2/+9IOpDIp3nVRnWi19zeeXQJFc3j/5ZlLTOBHNPItgiAcy5As/h6EbX5/v4xtYJuvAKfLzEO7xRXAvz45h1trA2iqqQjztg0VklitVkxaGWi1OlzaUQOjPnMenbkEX/lrbm7O2nrLI3RmkCeHAEQrizmOw6WXXorh4eGs7mcGcG6rgLONbLaAvV4vRkZG0NDQcECNKJFI4Pf7s7LdWEinBZxI7DG8tgeaPpjnGJr68KErmuGOklsaiV+ObOJnpzfx4K1HUG9Izgommt8gH+tmNBrhdruhVCrDWmd1ZYWd85sM/vWxYbg9XvzjG44lXSHyUwwefGIO77y4AbUZ/k5C2/T84nbasozNzR0Mv+JI2vqHN3j2+XxJGTx/+KoWfPiqlqT2neM4/GJ4C5cfNuYshzpy+7yfYWdnZ0YXf5IkYTAYYDAY8EBNI7xeLxifE+Pj46JU+K/vrUaAFn//fGR4E1vOAN51SUPUmTY+xo4XLOULhGUa0uHvg5NpwJXuEzNibxXSl/4LdN/bwBlb097GzJYTy9s2sIcOBhuECkl8KjPmNlZxs16F9ZUlzE3vC0lMJhPKysoKLkEjGnJJ/oDEJtQ0TQuvKQTPwUzjnCGA2X7SyRYB5I2ru7q6og6k51p8ks42xYg9Pn5NCz71yBT++fFZ/P0NhwHsK03//rEZ3DFYjYtajJBLSRik4Quow0fhhTN2XHfELPzWR/9/9s46Oo7z7OJ3QczSalfMthjMFHBiSK3YlpyYGyduyE3DnDbwOWkYGm4DTZoG6jQCQ2wHHHDYdgxiZtaCVlppeWfm+8OdiWAlLYM0v3N6eiKvdt/V7M7ced7nuTc6CMcbZBAFWnex5XA4kMvl4PP5uPjii6FWqyEWi3Hu3DmH+Q02ipW4o6gKb/0+Z9qtNZKiLG70pigKDQ0N4FF6xERHYkhLYsvbp7DnwnhsWxBt0nO0ydQ43iBDbIgPbrhgYrKIraAvbldfkgPg/OSuVCo1OY2Ejuvj8/nIyrK/QW6rTIW/fdWMiu4hPLresZ5gpub69iu0EAVa7s84pNaf71/z9wIQgvj4eKaa3tHRwRiDCwQChIWFMaLD3GEZDx4HHM7Y6EKCpFD4ximsSRPgguAhu8fYTQtpAK+2FJSPAPAcNQTgGwZK6wVebSkMK+4BOJYLB4PBAK/BNjy3IRnxMVNbFUUGeSMy2AeZybEI8OaPGSRpamoaM0jiKhX/0Tha/I3Hkt5BnU7nUL9TWzNjBKC94fF4Nt9i7ujoQG9vLxYsWDDpF9JennxTMTp9xBTM6ffjc7nw4HGQEfHb2LwHjwsu5/y/Tcbhyj58WStFmsifMW1NFPjipS1ZJq/TGARBMF5aOTk54HA4CAgIQEBAAGPNIJFIGNFB+3QZq3ToCBJDKj3CA8w/IUhGtDCQFOQq/ZQCkKIovP5dGzx5HLP7muh8bH9/f9y9YSE4HA6UOgM4APhmbK2mivzw4R/mI8IKIWEJPj4+TGSgsTSS0aJjdL+UPdsnCJJCWdcQcqIDkRjmiycL0pAb49i0F4PBgPLycgiFwikFUZtMhZJzPVidFm7RGt/+sR0f/dqFd67KQ3L4bwM046vpQ0NDkEqlaGlpgZeXF/OdMUd0rM+e2L/G5Zz/jh0814nNO+Y63buRM9gBjk4JKtDI5LCXPziKLnAU3RZvBev1epSVlSEuLs6k2M8wP0/csvI3S5jRgyQAmAGf6upqpgdaIBAgKCjI6VvFzhZ/xjAlok6hUDgsiMAezJgeQJIk7Rpf1tPTA61Wa5PtBroyQRAEMjMzpyzNDw4Ooru7G5mZmZM+xtZQFIVffvkFy5cvN+mxtpr0nQqlzoAWiQpZUaYbPU8HbX0SGRlpUmb0ZH2DtE/XByc7IR7W4eaLE+DtYb/tljd/aMMcoR8uTTU9Pot+r1FRUYiONq3S5y5QFIWhoSEmJcbDwwNqtZrxibQnjWIlDlX0Yl2mCBmRjh+iMSfXV0eQONtxXqxa0sda0zuMBw/VYd+1803+fNPTq1Kp1OoMaVokxMfH2y0H3Rw4kjrwyz8EFWj83MFRdMMwfzeoUPNaCYDf3mtCQgKEwukn+c2FvoEaPUhC30A5KmaTRq/X49y5c0hMTDQ7XtNZ0FXBf/7zn3jnnXdQU1Pj7CVNx8weArG3AOzv78fw8DBSUqzr6aC/2OHh4SZFTw0PD6O1tRU5OTlWva65/Pzzz9MKQEeJP3swMjKCqqqqCdYnpjI6p1gul8PPzw8e/iFQcnyxMNH056vrG0GYn4dFVUNTmczmZSaiVqtx7tw5BAcHQ6VS2T2NhCApdMrViA72drgptEajYWwybFk10egJu9zAjBcdgYGBjOiYbjBHq9WirKzM5lOhVqGUwOPnF0EFxgLjP1cUCc5wN/Qr7gF8zHOOcHQ1bPwgCZ1IIhAIzE6KMRd3FH80JSUlePvtt3HkyBF3SAKZ2UMg7tADODw8jIqKCsydO9fkD7szegBNwdpkD2cik8mYSV9/f3/oCRJv/diOBXFBWJpomhHseJ8u2m9wWNqLMwNtJvUNEiSFz6r74ePBM8ko1xJcweYFOC8qxMM6s4d1zIE2eM7MzGT6aek0ktbWViiVSpNSYsyBx+UwLQmNYiWu/7AMH+yeb9f3Cfwm6tPS0izO9TXGx6e70TOowc0rEyakvFgLn88fE4NGbxW3tbXBw8ODEerjvzN0aktqauoYGy7JiBafnOnBzkXRZpmIK7UGPHioDveuSTbLymYCfuEgBangyltA+Y+1huIM94AUZpkt/miha673nTWMTyShbZmam5uZRBJ7DJK4s/g7dOgQ3njjDXcRf5MyYwSgvbFWiPX39zPeeubExpjbj+cIbJHsYW8G1Xp48DgTYqi6u7vR09MzJhmBwwF6hzQYVJnu5q7SEXj/RCeumBcJYYCXRX2DPC4H2xdG28RQ2BhisRitra0ukV+c//pJGAgKX9y2FD5WVJcMJIn9ZX1YnhSK6ODf3hNt8JybmzvGlZ9OI4mMjBxTtbV16gUA9Ck0ICkKkhHtGAFIURR+aJJhrsgfEYHWHweFQoHq6mpkZ2ePOZfYIlFkaWIIfmmR21z8jYfD4SA4OBjBwcFISUkZM+Cj0+mYrWI+n4/KykqjqS0qHQEDQUGtJ2GOzGqVqdAgHsGZjiHrBCAAIuMKcMreB2eoA+B5A6AAQgsqOA5EWoFZz0VXdOfOnYvQUPsmkkyFl5eX0UQSWw6SuLP4+/zzz/HSSy/h6NGjNr35cgYzZguYoijodDq7Pb+lW7F0lqxcLkdubq7Z/RUGgwFnz57F4sWLzfo9a5lsC5hugnX1qt/fvm6GB4+DW//XFE37o6lUKmRlZY25k91f1ov3T3Ti4fy5mB8XbNLzS4a1+PeJTqxJn7qhfrq+QXtB+94lpWaAy+MjyMcDzRIlRrQGhw8pAOf7x062yfGHZdb15Cl1Brz+XRtyowNx2f9STmg/Q1MMnmno1AuJRAKpVAoATNXW1mkkOgOJV75tgTDQC1cvsW5qdbTQHV0pOz/g0YutC6Lc3q6IIAjIZDL09vZCKpUiNDQUkZGRNutPoygKg2o9Ar09LPaVHANpAEfeAo6kHuBwQAlSQYUkAVzzs6ltXdG1NfQgiVQqtXiQxJ3F39dff42//vWvOHLkiLutfWb3AALny+f2whJzZIIgUFlZCW9vb8ydO9eiCz5Jkjh58iSWLVtm9u9aw3gBaKt+P/GwFj82ybAxN2LKqV9rqesbga8nD3GhPsz0q6+vL1JSUiasfVCtx9d1UmzIFlnk0G8qxvoG6QqUrRqvaZsXvV6PjIwM/O61k6AAHLttGV473go9SeLOS81vSncl1HoCnjwueFwOOjo6IJVKmeQcSzGWRhIWFmYzoT6o0sPXkzfh80VRFC556WeE+3uh6IaFY/6NIKkxAoXO9TUmdAeUOnx8uhs7F8WMyW12V4aGhlBTU4Ps7GwQBMH0p/F4PKai7qr5q2o9gceONODGC+KRKJh+jbT4S09Ptyib2llYMkjizuLv+++/x0MPPYQjR464xBCSmczsHkB7Y+4WMP2ljomZaN5pDlwuF9OIdLtB9/fR4o8gCMYDyVJOtcnxXZMMF84JmzYP0xTkKh2CfTwmrCntfzYzWq0WFRUVU06/Bvt44Mp59o93m6xv0FZ+g6NtXubOnQsOh4NbVyZCpT//ub12eRz0hGu1E1iCjwePSWzRaDTIy8uzWqSN3vYiCAJnmnqw+50qXJPOg7e3D1ZnRkEYbrlQn0yU0Z9bycjYm9f6/hEcruzHriUxEAZ4TZnrCwChfp7408XOM0S2JXSVMy8vj/ku0P1pGo0GUqkU9fX10Gq1CA0NhUAgQHBwsMu0o0hHdGiWKHGybWBaAUj3cmZkZCAwMNBBK7QN43s66UGSjo4Oo4Mk7iz+fvrpJ/z5z392V/E3KTNKANJixR6YIwDlcjlqamqQkZFh1+xge0K/X/r/KYqyWvwBQHpEAD6rFuPXtkHkZ4kwrDHg/w7X4+ol0ciLDTbrudpkKjx0qA6b8iJw5byJnmD0pK+ze2qMYY3foDEms3kZnQd63vrD9dMApoOOAPP09LSLwTOPx0NYaCg8+B0IiohHY98QmvuH0NXZAT6fP61Qb5EqkRjma/K6jt+5YsLPgnz48PbgwteTxyTUzJs3zy5pDvaa+rUEiUSClpaWMT26o/H29mZuqunYwP7+ftTX10PP84EwXIDkGJHDrUxGExvig3/uyp3WakepVKKiosImA1pKrQFf1UmQnyVy+DQ6MP0gSVBQEORy+Zh8dXfh5MmTuPfee/Hpp5863XvS1swoAWhPTBWAXV1d6Orqwvz5893aIHK0AbUtJ30TwnyxIScCSxPOC2OSomAgSchU5lv4RAV7IyMyAEsSJopsetI3Ozvb5j1d9sDb25sxOab7Btvb2zEyMoLg4GAIhcJJtyNVKhUqKipsbgfiitCZ2WFhYYiPNy+FZFhjQIC3aae85HA/fHfXChhIEtIRAUQBXuBwOBOE+nhfu0bxCIrP9SI/U2hVr2VEoDf+dFECk+ubk5NjlwqX1kDg1eOtiAj0wi4r+xOtpb+/Hx0dHZg/f75JAu69k104WN6H0j2LwONw8PRnddB29uNyaS84HI7DrEyMEeg99fpHRkZQWVk5YZCHhqIoqPTEhCG2ySjvUuDbBhlSRQHM7oczGV1R12q1OHPmDHx9fdHW1obe3l6m9cXZw2nTcfbsWdxxxx04ePCgc1Nn7MSM6gHU6XR23S6dyhuPJElmWyI7O9umd+qmePLZmjNnziApKcnkCpQ5KDR6kOTk22JToSdI8LlTi9Guri709vYiNzfXJtOdliId0aG6R4EL54RZHN1GkiQGBwchFouN9g3SvVKZmZlmbyEpNPppL1SuBO2PFhsbi8hI87bs5Sod3vqxHfNjg7Em3TYVCGO+dsGhYejTeSIzKsiqqtroXF96O99evH+iE0sSQ/CnjyswR+iHN3bk2u21JqOnp4f5zpray7ntn6cxrCVw5E+LweFw0CpVwZPPQXSwD1OBkkqlUKvVY6xMnL1VTNsV5eTkTHpz+vhnDWiVqvDKtiyTRKCeINEzpEFsiI/F5xp7QG/7jja0tsUgiSMoLy/Hnj17UFJSgjlz5jh7OdYy83sA7bkFPBV6vR7l5eUICQlBWlqaS32IzYXu94uKikJ9fT0A209HPnesGSRJ4YmCdLPX9vK3LfDicXHrJUlG/72hoQFarRbz5893evj5Ly0DqOkbxvy4YJMrTwBwun0QL33Tgn9elQtvDx5CQ0MRGhrK9A1KJBKcO3cOBEHAYDAgKyvLbPFX3jWEo1Vi7FgUzfjYuSpqPYF/fNuEZJ4MF+SlWuSPFuTjgTSRP/JibNdnZczXTiKRQC+ToXbAy+IqB93LOV2ur624eulvlY1BlW3jLk2ho6MDMpkMeXl5Zn1n/3v92KGZ0f12xqxMbG3/Y8nW+dDQEGprayfYFY1nfZYIRWd74Gvi83vwuIgPda3vMR1lNz7NxM/PD35+foiPj2duorq7u1FbW+vURJLRVFdXY8+ePfjkk09mgviblBlVAdTr9Xb1zDNWiRsZGUFFRQWSk5Pt1hz6yy+/YMmSJXa/czU26avT6SCRSCAWi6HVapneNEuinGjq+kagJ0hkR5t/Mf7oVBeSw30nGDbTE9f+/v5ITk52CRGuI0go1AYI/M27yDz9RSO+bZDik+sXIsjH+Emwo6MD/f39CA8Px8DAgNl9gwqNHt81yLA2I9zunm/W0i0ewLNHq7BpcTJWZrhHjJ1KpWIsZgiCMDmNxNRc35lCa2srFAoFsrOzHVKZG23/090vAY8DRAjPi0FzkmI+OdONVqkKt12aZLKv5eDgIOrq6iZY+MxEaPEXHx9vcpSdMxNJRlNXV4fdu3fjP//5D7KyrMuadyFmvg2MowWgRCJh+szs6QZ+6tQpzJ8/3yqbi+kwJdmDvluTSCQYHh6etjfNUWg0GlRUVCAmJmZGNOmSFAUDQRm1pKGnX3U6HTIyMpi/u8FgYGxMTOkbdEUMJIl7S2uwZV4UliefF/h0L2dOTs60th/jbVNcBTqNRCKRQKlUIjg4GOHh4QgNDR1zbKbK9dUaCDzyaT1uvCAeyeGu39M6HbQvp1arHfM5diSb3jwFAHh9QwyausQ4XK/A9jwB4iKF06ZetEpV+LZBimuXm+ZrKZfLUV1bh6zsHAQHuP/xmwpLxJ8xRm/j2zORZDSNjY3YtWsXPvjgA+TmOr4Vwo7Mji1gez8/XR1ra2uDVCrFwoUL7d5nRg+g2EsAmhrrNnrLa3RvWkNDA/z9/SEUCk3K9bQldD9NWlqa205cj4fL4cCTP/EYEASB6upq+Pr6IjMzc8xx4vP5iIiIQERExIRjYw+/QXtgICic7RhC75AGy5ND0dvbywxUTfcd0xEkXv6mBbEhPti+0LWqhOPTSAYHB3Givhvd0josij3/vQkICEB1dfWkec19Ci1+aZEjItALd65ybx9HiqKY9pLxn2NHsjotHIHefERFRWGQE4BgWS+8AgIhk8mY1Av6ezN6Irl7UIMmiRJ/WGZahZa2tTkxHIqff+nFvWtcY4fCHthK/AFTJ5J4eVneYjEZbW1t2LVrF/71r3/NNPE3KTOqAmgwGOyam3vq1Cnk5OSgoaEBfD4faWlpDrlzPXfuHFJTU+1ifGqLZA+KojA8PAyxWAyZTAZPT0+mb9DUZAZLkEgkaG5utvukr1JrgCef6xR7BRqdToeKigpERESY5CupNRDw4vPG9A1KpVKT/QaVWgPe+KENG7MjMEdkn6lCnYHE379vxe8yRMzk4pBaDx8PHnq7OyGTyUw2eKb7Q5clhmDJFHnONb3D+NPHFXhzZy5S7fS+TOHFr5uhJ0jctCwCPT096O7uhq+vLyIiIhiT4/Hfx54hDQR+nnY1KwfOH3s/O8UT0hY+Xl5eRk3ZXQWKosZs45MkyWxHPnC0DWKFFv++Zt60fydaTObl5aFWrMaASo9LU93LBsVUaPEXFxdnd688Ww+SdHZ2YuvWrXjrrbewZMkSO6zY6cz8CqAjOHfuHKKjoxEXZ12klTlYm0NsDFslewDnK6OBgYEIDAxESkoKc+KsrKwERVFWDZF0ydUQBXpNEF8dHR0Qi8UmVYesgaQoXPPvc+DzuPj4ugUWPw9FUZCM6CAMMF8Qm2vz8tQXjfi2Xor/Xr8AIb6ejN9gUlKSURsTugI1+jNAUoCBpDCis98NFXA+z7VZqmQEYKA3n9niNsfgmcPh4A4TEk50hvMtIs42xL7pogQQFAWDWomBgQEsXrwYnp6ekEgkaGpqYiZXw8PDGZPjqCD7W2a0yVT48FQXNuVGIjPKtm0tJEmisrISgYGBSEy0jWm1gSTxfaMMSxNDp/XdM5VhjQFDaj1iQs4PKyQkJDDb+O3t7dgUOQJ1jB9UCjm8Q0MnbEdSFIURLQHNsJzJ4vb09ERerP1uhp2NI8UfYNtBkp6eHmzfvh2vvfbaTBV/kzKjKoD0VKQ9GBoawq+//or09PRJEyXsRXV1NaKjo22WEWlL8Tcd9BAJHbFFCw5ThkjkKh1eO96GzCh/XJEXxay9vr4eBoPBYb1DL3/TguRwX6zPjpj+wZPwQ5MMx//XM2ROAL0lNi/fNUjxzJdN+PRPS6bsiaNPnGKxmOkbNNab5ihIkkR1dTW8vb1dujpkKybL9QXOn8voydXBwUH4+/sjPDzc7tORSp0BJed6sTE7wqaRcgRBMP6Ntrx5bpWq8OGvXcjPFGKBiTne07H9nTPQESSKrl9o9PtDkiQz8T0wMDBhO/L5Y0040SLFnzI5uHCJaZ6GNBRFQakj4G+nCqw9MBgMOHfunMPE31SYO0jS19eHLVu24Pnnn8cll1zipFU7hJk/BGIvAdjT04P29nb4+PggMTHR4XmNdXV1zMnfWkzt97MHdMi7WCw2aYiEoiicbh/EXJE/gnw8YDAYUFlZiaCgIIfYY9gShUaPsx1DuDAlzORBBbFYjNbWVuTk5Nh9anA6v0GTnoOiUN0zjIzIALOHMWiDZ4FA4NDqurPo7+9He3u70Vzf8dAtFhKJhMnDtTY20JHQk80RERE2v3kmKQq9QxoIAybuElhKTe8wugbVWJtuWg/b+InvLhUPB+tH8NbupWa3wPzUPIBv6qW44YI4RAS6tkky4FrizxjjB0l++uknxMfHY926dVCr1bjiiivw1FNPYe3atc5eqr1hBaC50L5ySqUSOTk5aGxshEgkcnisWGNjI1OdsQZnir/xjBcc/v7+CA0TQCQMN9rzRU/6WmIC7I50dnZCLBYjJyfH7IrPiVY5+hQaFOREWHSMLe0brO8fwSdnurE+OwLzYk2/SdJqtSgvL0dcXNyE6deZSHd3N/r6+iw6tgCYbXyJRAK9Xo/Q0FCEh4c71EiXoihoDOS0FiiO3ho0hlpP4M0f2rB5XhRiQqwXzB+f7kZVjwJ/3TDR87WrqwsdHR0ICAjAyMgIAgMDmZt3UyZXJSNaHKuVYMv8KKf2HJuCq4u/8ZAkiS+++AL79+/HyZMnodVqsXHjRtx///2zwXJp5gtAkiSh15sfKWYM+q6V7mvjcDhoaGhg+nIcSXNzM/z8/Ky6OFIUxYhjV7MFoSgKz3xeh8a+IfwhFfD19oRQKGSGSBQKBaqrq5Genj7lNrhSZ8Dtn1Th6iUxuGiO+0WiKXUG+Hrw0NTUBI1Gg8zMTIuO1fNfNcFAULh/rW22UccLjsn6BvUEiUaxEinhfiYPKtD9jZbkNR+p7Ie/Nx8Xz7G+Mu4o6Fzf0WlBL33TAoG/B65abP5FyGAwYGBgABKJhEkjMUdwWMp7v3Sga1CDe1YnT2qGrNVqUVZWhqSkJLPPmToDiQPlvVibLmS2oiXDWnxdL8XWBVFmpV0MKHX4x/dtWJUmmOAfagm//9cZECSFfdcuGPP5p9NMaEPr0ebgAwMD4PD4EIaHQyS0TeX2bMcgis724qH8OSZHxtkKdxN/oxkcHMQVV1yBa665BjqdDkeOHMHg4CBWr16N9evXY8mSJU4PEbAD7BCIqSiVSpSXlyMxMXFMtckewximYM3rOrLfz1I4HA6WJodDpiaxYlkG1Go1M0Si0+mg1+uRlZU1bQ8kj8OBnqDQIVc7ZuE2pH1AhT/+pwIrozi4IjsUWVlZTLLNkNpgVj/WnZcmg/xfldcUdASJV79txdr0cKPm3KNzium+wdE5xXTfoAePi4xI0wcH6P7GrKwsi3w0K3sU4HI4biEAR/s3js/11RlI9A5pLXpePp8PoVAIoVA4RnC0tLRMa5UxojXgLwdr8ZffzTF7u/GClDB83yiD1yRCX61Wo7y8nBH2I1oDZEqdyWkV/cNa1PWNIEngh4XxwQCA90924qs6KZYlhZiVehHq54kH1801+fHT8eHu+QDG2o51dXVBLBaPSTPhcDgIDg5mzltX/+sMDIYe3LNAytxITTa5Spnw/e0f1kFPkA6PfnNn8adQKLBlyxbcfffd2LJlCwDg9ttvx/DwML766iu8++67qK2txXXXXefklToGtgI4DplMhrq6OmRnZ09oum9ra4OHh4fDh0A6OztBUZTZvVHuIP4mg6IoZtJXJBJBLJXhu1YlLpojwNz4SKuSSBxBz5AGQ2o90iNMEzbDKg02v3kS918SjUvzUpifl5zrQXXPMG67NAnBk6SCWIueIPHsl03IiAzApjzTt9fpbXy6wmFO3yBt8GxNKoKBJMEBxyXNn0dDkiRqa2vB5/Ptnus7mvG9aWFhYWOSYn5tk+O+/bW449IkFOTabutdqVSisrIS6enpTL/0C181Qakj8MBlc+BpwtYmRVFQaAzw9+Izx3dEa0CjWGlWe4EjoKPscnJypqwcvfJtC7w9uLjxgoQJlduAgACmcktyuLjtv5WYI/TD3atTJn0+Z2AwGFBWVoaYmBi3a9cYGRnBli1bsGfPHuzcudPZy3E0M38LmKIo6HQ6i3+3o6MDfX19yMvLM9q829nZCZIkER8fb+1SzaKnpwdardYs6wR3Fn8kSaK+vh4kSSI9PR1cLheSYS1eO96CXKEH5vppXCqJBADe+rENx2ql+PAP8+DF5+HZY03Q6gk8uG7utHfodLUkOTl5wlaZeFiL0+2DWJcpdOljaE7fIG3wnJuba3cTdWdD5/oGBgYiISHBacdQr9czKT6DimEIQkMQJhCA8PBHeKAX+Db6/tDG7OOrujKlDv0KrVkVYnegvb2d2dK39BxET67SN1JcLhevVxC4YI4A113oOqbf7iz+VCoVtm7diquvvhq7d+929nKcASsAJ4M2J6Uoasq+q97eXqjVaiQlJVm7VLPo6+uDUqlEcrJpJwNXGvYwF3oaNCQkZMIFU67SIcCbDz6Xa3SIhK4+OTKJhObpLxpxun0Qn9ywEFwOB4MqPZQ6wwTLF5KixghCehs0IyPD4dPl9sRY3yCdWzw4ODhttYSiKByrk2DlHIHdjY/tBd1HLBKJTDLvNofT7YM4UtWPh9bNNasCOqTW4+VvmpEV7onMID3kcjl8fHyY744xQU6QFLic6ZOW6M9yTk6OXY3ZTaFLrsbHZ7px88WJJmf1mktrayuGh4eRlZVl0xtQjUbDRAdqtdoxQz7OutF1Z/GnVquxY8cObN68GTfeeKOzl+Ms2B5AY9ATiEKhEPHx8VOe5NyhB9CVhz2mQ61Wo6KiAgkJCUZ7S0J8f7s4cblchIaGIjQ0dIxNRnt7Ozw8PMYMkTiCBy6bM+a/g309JvTtDWsM2PXeWVyWIcRNFyUwSSZ5eXluYedB3yyackMxvm9QKpWiqqoKOp0OIpEIcrl8Sr/Bk22DeOKzRvQNaXH1Uusm9DrlakQYMRO3JzqdjonEskef1FNfNGJAqcP1K8zzlfTz4sHXk4+8JBGSBH7nfeeUSkgkEpSXlwMABAIBY9xOUsCTnzci0JuP2y+d/MZXLpejvr7eZT7L7QMqKDUE1DrC5gKQoii0tLRArVbbXPwB5787MTExiImJAUEQePWrehjqmrAi3OAwP8jRuLP402q12LVrFwoKCnDDDTc4ezkux6yuACoUClRWViI1NdWkhAV6CyUtLc2aZZrNwMAA+vv7kZ6ePulj3HnLF/itejDdpK8p0L1PEokEFEVBIBBAKBRaVJUgKQr//KkdeTFBWJxgXdYwQVLY8vZpXL00BvND9Piyshv5y3MQFeIe4fBPf9EILoeD+9aa15dEkiSqqqrg6+uLxMTEMZORk/UN6gkSX9RIcGFKKIKs6H0cVOtR8I9TiAr2xr5rLU9yMQd6S3+yXF+bvIaewHcNUvzSKscflsUhIcw2MZE6nY6pPqlUKoSGhuLjeh0unCvCpWnGffGkUilzI+OoG67pMOdmZTwkRYEgKaM3DBRFobm5GVqtFhkZGQ45zz79RSMA4P61KWP8IGmTY0tTlkzBncWfTqfDNddcg5UrV+KOO+5wu2uijZn5W8DAecVvCn19fWhpaUFubq7JX57BwUF0d3cjMzPTmiWazdDQEDo7O5GVlWX0391d/PX396Otrc0uhsf0BU0sFpudRAKcHzTY8c5ZePI4+GgaATF+e9cYFEWhqakJ8mEVDnd7ITncD9dYWeGaistfPwkAOHKz9RFHz37ZBA8eB3euMr0vid4GDQ8PnzDEZKnfoLn8/btWrEkPxxyh/bN/R0ZGUFVVNWYAwl4MqfX4pWUAl6aFmzRYYS6mpJHQhtZ5eXkzpp9zxztnQFIU/nv9wjE/pye5DQYD0tPTnX6epU2O6ZSl8dGB1uLO4k+v1+Paa6/F4sWLcd999zn9WLkAs0MA6nQ6TPWe6Du4oaEhs41Yh4eHmWQGRzIyMoKWlhajr+vO4o+iKLS3t2NgYADZ2dlWb2mo9QT+8V0bdi6ONmprYSyJxJToM7lKB28PHnw8eEw6SYLAF+H+v1U7tr9z3hvsk+sXTHoMxked9Q9rEezjMamPmi2wpQA0F7q9wtRt0Mn6Bk0R68MaAwK8ndvRQlexs7Oz4e8/tdhU6QibZdc6AmNpJJ6enlCpVJg/37y4M1fn2WNNkI7o8OymDOZndAQlAKSmprrceXa8WKcr62FhYRYJc1r8RUdHu53xvsFgwI033oiMjAw8/PDDLnesnAQrAOkoMV9fX4vsGFQqFerr6zFv3jxbLNXq13XnYQ+SJFFXVwcASEtLs8kda59Cg79/14bLs0RYkjj1dq0xCxOhUDjtEIlGT+DJzxshDPDCLSt/m8r+y8FaNEuV+O91C43+nl6vR0VFBYRC4WxwnWesQCwxeAZ+yymWSCTTivXavmHs+7UbOxZFm2y7Y2vMsbVpFI/gw1Nd2LkoBqki+1cl7UFLSwv6+vrg7e0NnU7HiHVHppE4CoqiGBufOXPmWP3+5Codgnw8zPbvI0gKA0odwgOmjw4cGRlhItCAsX2d063fncUfQRC4+eabERsbi8cff3zGfRatYHYLQLVazUQSWerjp9PpUF5ejkWLFlm7TLPQarWorKzEwoW/iQt3HvbQ6/WorKxEaGjotIM3Zj83QYLPNV0M1/YN40BZL65ZIIBYIoV2WD7tEEnHgBph/h4mu+/Twy2WJCK4I9YaPI9nOr9BhUaPg+V9KMyNdEoV0Nxt0CG1Hv/5tQs7FsVM6u2oM5B4/qsmrEgOxcUulmrT1taGoaEhxvqErqyXt/TCm1AiNDjIojQStZ6AniAR6O061USKolBTUwMvLy8kJydbfa5S6QjctK8c4f5eeP7KyVuJTrTK8fHpbjy7KYOZgn/5mxY0SZR4fGOaWX2x4/s66a1iY/ZZBEGgrKwMUVFRbif+SJLEHXfcgZCQEDzzzDNud120M7NjCphOTxiNXC5HTU0NMjMzrRowcJUpYIIg3HLLF/itQT4pKQlC4eRh6yRFgQPzm7jNnfTslquhMZC493AbCJLCR39YDJ1WA7FYjMrKSqNDJHGhpven0TF2M83mZTKkUimamppsOg06fuKb7hs8d+4c0ze4OSccPk4Qf11dXejv78e8efNM3gYN8vHATRdN7enJ53FAkBQGVbaJtpwO8bAW139Yjneuyp20wkS3z2g0mjG+dzweDxyfIHwnlmFBXDiyo30hkUjQ2toKT09PpvpkLI1kNNv+eb737tObFtv8vEb+75pgTtWNbtnw9fVFUlKSTdbk68nD8qRQrJw7taj/pWUAaj0x5rK9ZUEUTrcPItDMz7mnpyeioqIQFRUFkiSZreKGhgb4+voyN1M8Hs+txd+9994LX19fVvyZwYyrAOr1epAkyfx3Z2cnuru7kZeXN+0JaDooisIvv/yC5cuXW7tMi1532bJlbtvvB5wfoqmtrTVJDN1VXAUA+Ntm44MvU6HQ6HFvaQ0eyU9FdLBpx/yXlgHU949g97KxgwrWDJHQNi/0tuBPzQM40TqAOy5Ndvn0iunoGdKAICnEhvwm8np6etDd3e1Qg2dz+gYlw1oE+XrYbGDCWK6vu/J9owyPHa3Ho+vTsCJ54pY93QNHURTS0tKMRpedahtEWoT/mOqUSqViqk/G0khG81lVP2RKHa5aYvsWicc/awAAPGRiJBw9uR4QEGCWAb8t6B5U460f23HN0lgkCfyg0OjtUhWlLYDo4zMyMoLQ0FAkJSXB39/fba4vJEniwQcfhFarxd///ndW/BlndlQAaegeM71ej0WLFtnkBO2sLwT9uu4s/vr6+phtMlMqQ+EBXlMO80z5WkNaqHQEmsQjJgvAZUmhWJY08cI3+u6Z3urq7Oycti+tq6sLfX19mD9/PiOGvmuUQmsg4ebaDwDwzx/bQQLYe3kqKIpixND8+fMdKoaM5RQbOz56ksLL37bC34s3wbPRXKbK9e2Uq/FlrRi7lsTaZTLXXlyYEorDf1piNNuX3gb18PCYtAeOw+EY7bv19fVFXFwc4uLimDSS8TnSISEh4PF4WJdlv1zZ6GBvmHo6IUkSlZWVCA4OdnjqEwB48rjw4HHhxeeiU67Gk583YmOOCOsybfv34XA48Pf3h4+PD2QyGVJSUsDn89Ha2gqlUjnh+LgiJEni0UcfxfDwMN5++22rxN+1116Lw4cPQygUoqrqfAFi7969ePvtt5nWnSeffBL5+fkAgKeeegrvvPMOeDweXnnlFVx22WXWvyEHMyMrgBqNBuXl5QgLC0NiYqJNxdLPP//slArgDz/8gOTkZKclXVjKaHGQnZ3tkLVTFAU9ScHDjF5Ac5lsiCQsLAzt7e1QqVTIzMx02ROntXQP0hVAb9TX14MgCCa2z9bQQ07mMP74+Pr6okPnh3lJEYgJM33wQqkzgMfhMJPa0+X6Hirvxan2Idy/NsXpU8m2gK6E+fv72/RcOvr4mJJG4igIgkBFRQXCwsLMzl63BzqCxMvftGDnomizDL9NZbKev/HHx9vbm9nKdyWvxyeffBIdHR147733rD7Xfv/99/D398fVV189RgD6+/vjnnvuGfPYmpoa7NixA6dOnUJPTw9Wr16NhoYGVz7fz44K4MjICMrKypCSkjJlj5m7QA97ZGdnQywWo62tDd7e3syQgivbL9AXSy6Xi9zcXIeV5jkcDjx59i2zGetL6+/vR11dHXg8HhISzge+jz8hNEuU+K5Rit3L4syeAnQlooO9mUqJr6+vTawx5Codtr9zBg/+bg4u+t/gg1ylw0vftOCKvEjkxpjeQzn++CiVSgSIxehprkF/G4/p65yuGv3csWZwOcAj+akm5fpenh2B1elCm1u8NIqVuOW/FXh3V55dhIAxaDFED2vZEmPHRyqVGk0jcdRuB0EQOHW2DDERrjOp78nj4t415hmvmwot/iIjIyf0/I0+PgCY41NVVTXtVr4joCgKL7zwApqbm/Hhhx/aRHhddNFFaGtrM+mxBw8exPbt2+Hl5YXExESkpKTg1KlTWLZsmdXrcCQzTgDSlSZbTB9OhiUVCUsYPewRGBiIwMBApKSkQKlUQiwWM03wtBi0tsfRltC2J+Hh4YiNjXW7LWtz4HA48Pb2xtDQEDPpO9kQyd+/b0OjWInN86NcZtpRT5D4rFqM/Cwh+CaKdGtsbTR6Al587oTPBEmdt7roHvzNzJ3P5YLH4VgV40ZvddFVrLNtMnC5atTW1k7bN3h5phCefK7Jub48Lscq8dev0KJ3SIO82LFit09xvuIqHdE5RADS7zciImKMawJBUib3r/YMaTCo0iMjcupz8ejjk5CQwPTdNjc3M2kktjQ4NgZBEPjl9DkUt3AwnwSutqP+a5OpEOjNR6ifcyudtPiLioqa9vF+fn7w8/NDfHw8s5Xf0dGB4eFhBAUFQSAQmD31bSkUReHVV19FeXk5Pv74Y7vvKr322mt4//33sXDhQrzwwgsICQlBd3c3li5dyjwmJiYG3d3ddl2HPZhxW8AGg8Guk7onTpywWU/hZJhj7qzRnJ9YpZusw8PDLY49sxUqlQoVFRVITk6eFbYntM1LYmLihKrz+CES38AQ8PxCkBEX7jKi+LNqMV78uhn3rEnG2vTpq+bmGjyPRqUj8PhnDUgW+OK6Ffbrr2oUK/Hx6W7cuSoJ/l6/XSC+rpfgr0cbcPfqZGzIjjDJb9Deub6jefyzBqh1BPauT3VodvFo9Ho9ysrKEBsbOyYB4mzHIP5ysA4vXJmJzKjJRR1BUnjy80Z82yCFtwcXh/+0xOJqt7E0EoFAMCE60Bpo37uoqCh8XKPGhpwIzBHa5/xJUhQe+bQOXnweHs43bSDF1pgr/qaCJEkMDQ1BKpVCJpPBy8vL5KlvS6AoCm+++SaOHz+O4uJim7cLtLW1Yf369cwWcH9/PwQCATgcDh5++GH09vbi3Xffxc0334xly5bhqquuAgBcd911yM/Px5VXXmnT9diQ2bEFbO+LKm3JYi8BSIs/giDA5U6skozH29ubabKmxUZjYyM0Gg1TeXJkmV4ul6Ourg6ZmZkIDAx0yGuaBEUBoACObS+q09m8GBsiEYvFOHGi2eQkEntzydwwePO5WJ48fdYxbfCcmpqKkBDzs5F9PLgI9OYbHbixJTKlDloDAQMx9h52SUIIrlocg4tSzmf08vl8iEQiiESiMX1PjY2N8PX1RXBwMHp6ejB37ly75fqO5rZLEjGg1DtN/NHiPjExccLNm78XHzweBz6eU6+NyzkfoXjxnFBcliGyqtWBx+Mxgo9utRi9+0GLDV9f87OQB9V6+PExRuzeZYEeOtMxiH6FFusyhdOeZ7kcDq5eEotgX+dU/20p/oDzW8UhISEICQnBnDlzmKnvmpoas9N8poOiKLz77rs4duwY9u/f75Be0dE3fDfccAPWr18P4HzFr7Ozk/m3rq4um/w9Hc2MqwASBMEYJNuDs2fPIj093eaZtYBtkz3oyoZYLGbG++mJLnuJwd7eXnR2diInJ8d1tqNHxOA1HgWv/UeA1IMKS4UhbSMokfn2MuOhPe9ycnLMvgARBIH9p9vgT6kRRA2PGSJxxb7OQZUebX0yqPtbTYo6c3coioJEIkFtbS08PT0ZPztT+gbdFY1Gg7KyMsyZM8chYtdaNBoNY2FSJ1YjLSYMidEik9JIjlT1458/teP3yQQuykm2ql/80SP1MBAUHtvgehFxo7G1+JsO+hoklUqhUCgQGBjIbBVbsm37/vvvo6SkBIcOHbLbd3B8BbC3t5fpj3zxxRdx8uRJfPzxx6iursbOnTuZIZBVq1ahsbGRHQKZ6djLDNrWsW7jKxsDAwPo6+tDfX09AgMDIRQKERoaapMPLEVRaGlpgUKhwPz58+3ak9ExoEZUsJdJvWqc4R54HH8cMGhA+YUDHB6g6ILHD8/AMG831PErceNHFViTLsBVi81r+unu7kZvb+8Ymxdz4HC5ONungzffAw/nL2UqG+3t7fDw8EB4eLhL9XU++1kNxPIhvLhjIfz9zK+2AOerQqb2GDobhUKB5uZmLFiwAP7+/ozYMKVv0B2h2zbS0tKsMsu3BUNqvUlJF97e3oiJiUGIMAL7WuvR3qrDBnSjtrYWgYGBTHXd2PkoXeiDQI4GizLmWj0s+MBlKTCQjukLtxSCIJieTkdVqkZfgyiKYraK29ra4OHhwVRvTRFz+/btw3//+18cPnzYbuJvx44dOH78OKRSKWJiYvDoo4/i+PHjKCsrA4fDQUJCAt58800AQGZmJrZu3YqMjAzw+Xy8/vrrriz+JmXGVQBJkoRebz/3/KqqKsTGxto01cGRyR70F1EsFkMmk5mcgTsZJEkyHmGW5Cubg3hYi4cP1WFBXBBuvDDB6GO+a5Bi3+kevLQlE/4n/waurAGU37gTPKEDRyWDZt2L2P1xMxYlBOPWlUkmrYFOQ1AqlcjKyrLqSz+k1sOLz2UsRmjUajUkEgnEYjFIknR6X2d3dzfq2roRHjcHObHnt33Fw1r4efLg52XaZ0alI7DpzVPIjAywyNzbkUyX6zu+bzAoKIi5oXJHE9qRkRFUVlbaLLqPRqHRY0CpR0LY9DcMJEXhlW9bEOLrieqeYexeFjvt8MhoavuGERXkjSAfD1AUBYVCAYlEAplMNuGGSqvV4oufziIyJg6L5loWC2ouaj2BjgG1U7KfafEnEoksjkG1NWq1mqneTpclXVJSgrfffhtHjhyx63DnDIetANoCHo9nsy1mc4Y9bAWHw0FwcDCCg4PH9NS0t7fD09OTERumVLV0Oh0qKiogEokcYpsQ7u+JjbkRWBwfPOlj6sUj0BEkuLohcMXVoAKMRBrxPAGSAL+/Eu/vvsDk1x8tdnNycqw+XpNVOXx8fCbt65zqRGlrKIpCa2srFAoFVi5dwIhdiqJw9XvnwONycOTmJWN+p0uuRniAJ7z4Y0Wtj8f5aV5jZsHOok2mwr9PdOKe1cmMkKVzfaeq7E7XN0iLDVfcyh8P3cOak5Nj8xuMXe+dg4EgceimJdNODlMU8HWdFFwuB4W5EWMSZkwhPeI3YcDhcBAUFISgoCCkpKQwN1TV1dXQ6/XQarX4TuwP72EFFs6Jcsh598Wvm1Hfr8TLW7Ic2v/niuIPOH+Oow3c6d7onp4eVFRU4B//+AdWr16NgoIC/Pzzz3jjjTdY8Wcn2AqgmTQ2NjJ3/NbgDPE3HSqVipko5nA4jBg0VgWhhwFSUlIgEDgvrJ6kKBwq78OypFCIAn8zKOUouuHx9cPGBSAAjqILRPYOEHN+Z9LrjLa1cZZBLH2ilEgkUCgUNqs8lXcNISHMd4wgpaO/SJJEWlrahOffX9aLyCBvLB0l6JQ6Ax490oDIQC/cuSrZ4vU4ip+aB3Coog/3rElGuL8Xk+ubm5trUTWc9rOjo+m4XC4jBqfqEa3tG0Z1zzCunBc55jzw6vEWSEZ0ePRy+/SWyeVy1NfXT1rpNAc9QeKxow3IiQ7AlvnnhUZN7zDaB9RYl2nauXLwfxVxHw/7bKVpNBqcO3cOQqEQ3QMjGBoeQUpkKAQCgc3aYSZDMqxFRY8Cq1Id54rgquJvKgiCwE8//YSDBw/im2++wcDAAO68805s3boVKSn28UOcJcyOCqCjpoCtwdb9frbC19cXCQkJSEhIgFarZZrgDQbDGC87+sJh6y0jS5Apdfi0sh/iES1uvCCB+TnlE3p+4pfQAzwjd9wUQPlHTPy5EehkGWM2L46E9nwUCoUTKk+WDpGMaA344GQXEsJ8ccvK85mntOGxv78/kpKSjH4+N+VNFNZ+nnwU5ERgrsh5FkTmsCI5FCuSQ5lK59DQEPLy8sDj8TCg1OGP+yrwytYsRASa1oc53m+Q7husr68fs801vm/wruJq6AkSG3JEYyqn0hEdKMo+5zSZTIampiabZKQDAJ/LAUUBat1vOewZkQFmbeMGm9D3ZylqtRrl5eVIT09HcHAwkpPHpl00NzfD29ubEey2njAND/BixZ8J8Hg8XHTRRdDpdDhz5gyKi4tx4sQJ3HXXXejq6sKqVauwfv16rFixwq0SsVyVGVcBpCgKOp3Obs/f3t4OHo83pRnsVLiq+JsKvV7PeNkpFApQFIX09HTGH8nZtEpViAjymlA54JV/BF7Tl6ACo4HR61QPgsPzgO6y54yLw1EMDw+jqqqKuXA4kob+EXx4qgv3rEme0jR69Fa+VCo1e4ikpncYMSHeCPT2YCqd0xkezxToXF+9Xj8myu5EqxwPHqzFX9bNscmFe7K+wZCQECi0BPoU2jHbmPaEThTKy8tzauyao6AHXNLT0yft3aYoCiqViqneAs5JI7EF7ir+aL777js89NBDOHr06BgbFrVajW+++QaHDx/GDTfcgPnz5ztxlW6H0Q8wKwDNpKurCwRBWBSNRPv7AXC7ZnF6+GFkZAQRERGQSqWMcS59IXO596RXw+PEK+CIqwG+FygOHxyDGvDwg/7C+0AFT30M6WEAS2xehjUGs7Ng6/tHoNIRmPe/FIiTrXIcKO/DfWuTEeJr2oW6rm8EPlwCHM2Q2UMk5lQ6h9R6NIqVWDhFP6arQ0cVenh4YM6cOWMu8iRFQaUj4OvJM9nHjqIo9Cq0iAqaWnQbyyl2VN9gb28vurq6kJeX55QeRYKk0DukQYyZPX405qYwKZVKVFRUmL1bQffeSiQSh6WR2AJa/AmFQre8gfvpp59w//334/Dhw27pq+fCzA4BCJw3M7UXvb29UKlUSE42vcfJFfv9zIEgCFRXV8Pb23vMhZIkScalXy6XIyAggNmGdJmReJIAR1wNbudJcAwqkKJskNGLAa+pp/G6u7vR09OD3Nxcs6skjeIR/OP7NuxcFGOWQNr81q8gKAqlNy6y6DNCUhQeOFADLz4Pf92QBmBiEomxIRKdgcQVb57CCqEeN63JNqnSeeNH5WgfUOG/1y10mqmtNRAEgcrKSgQFBU2a62su//qlAx+e6sLLW7KQFWWaCbqlfYOW0NXVBbFYjNzcXLO/nzoDCU8+F1oDMWHAxxyKznbjRMsg7l2bbPLWOs3Rqn68/VM73vp9LsL9vaZ9PD3dbKlvJUVRePjTOgR683Ht/BBIpVLI5XL4+fkhPDzcpmkktsDdxd/Jkydx11134dChQy6TxTyDmB09gPaGz+eb1QPo7uJPp9OhvLwckZGRE04qXC4XYWFhCAsLY6wXxGIxWlpa4OPjw9jLOPUkyeWBisgBEZFj0sNpT8ORkRHMnz/fIiEbFeSNOUJ/JAlMv4D/0CTDHy+MR0yIr8WfES6Hgz0XJIwZ5jCWRNLdfd4rjd6GpMCBSq2BFKEmb3M/tiEVld3Dbin+jOX6UhSFr+okmCP0N8m2xBhr0sLRJVebFSNmad/gaJRaw7R2PG1tbRgcHLRI/JV1DuHDU11YkRyKt39sxzObMpAdbVnKz6rUcIT4ekIUML2AGw9djfU2QYDSrRvWTDdzOBxwABhIakIaiUQiwblz5+wq2M2BIAgmm9sdxd+ZM2dwxx134ODBg6z4cyAzsgKo0+kwzfuymIGBAfT39yM9PX3ax7q7+BsZGUFVVZXZyQB0VYPuSePz+cw2pJeX+Sd+R2HM09BAknj/RBcuTRVYLAymg6Io3L+/Fh48Dp4omP5zZQvobciOjg7IZDKEhoYiIiLCLMFOURQ65GrEhzrvwmcuk+X66gkSDxyoha/nb9VTZ2Osb5A2N6ZF3GdV/fiqTjppRY2+oVGpVMjMzLRo+7J7UIM3vm/F5gVReORQPf6xM2fabW5nYk9rm/GMTiPRarUOtWmiocVfeHi4W4q/8vJy7NmzB6Wlpeykr/2YPVvA9hSAQ0ND6OzsRFbW1Ga27jjsMRq6/y0rK8vq2K/RxsYURTFi0Jl3zOMxGAyoqKhAWFjYmP5OpdaARz6tR05MAK5Zaj/7F7lKBw8eF/4mGivbgq6uLvT19SEnJwdarZYxB6cF+3RDJN83yrC/rBd7LkxAWoTrR8PRk6CT3dCIh7Xw9+LD19NF2hdGMbpvUC6Xw8fHB+Hh4dDw/VFSLsYdlyZNyA+mKAoNDQ0gCALp6enMOeiZLxuh0BjwxEbH3Gw4kqGhIdTW1hq1tiFICn85WItVaQKsTbf9ND9dYZdKpRgaGkJAQADCw8Mtjj4z9TXdWfxVV1fjuuuuwyeffIK0NNe48ZqhsALQFoyMjKC5uRm5ubmTPoaiKMYs2pUbhieD7n/LycmxecVOp9MxYlCn0zH2Mv7+/k4TyRqNBp/+eA5fdvPxys75E6aJR7QGePG5Ey6w7gptezI8PGw0zYQW7BKJBARBMGJw/DTksMaAX1oHsHKOAJ786f82ld0KxIf5TDnRbC/ofrCMjAybpviM5ut6CQ5X9uO5KzLsGnlnSt8gRVGora0Fj8ebkNDz4MFaUACedFC12VEMDg6irq5uUl9DkqKw7Z9n4Mnj4KNrF9h1LdOlkdgCkiRRXl4OgUDgltumdXV12L17N/bt24fMzExnL2emM3sEoF6vB0mS0z/QAtRqNWpra42OoLv7li9FUWhqaoJarUZmZqbdBzkMBgMzoKBUKhEaGgqhUIjg4GCH/e2Gh4dRXV2NcnUovm8dxqvbshHqN3OtMSiKQl1dHQAgLS1t2r/z6GlItVpt8RbXsMaAK9/6FSG+Hvjv9Quteg/mMjQ0hJqaGouHAUyl4I1TUOkIHL15ybQ3C0qtASQFsybFqf9NJo/v96M9O0dvQ9JG4cnJyW53HrKEgYEBNDQ0TOtraCBJcDkckye7xyMZ0ULg52n233T8TRX9PQoICLBs4MvNxV9jYyN27dqFDz74YMpiCovNYAWgLaCHIhYtWjTm5+4u/mjzX19fX6SkpDh8/SRJMv1OQ0NDDslXpbe5s7Oz4evrCwNJzZgqH82I1oCPTnXhmqWx8OCez7IOCAhAYmKi2cfY2iSSw5X9yIsJtNgCxBKmy/W1FdU9wxAFesLPi29SksX9+2tAAXh2Uwa65Gr4ePIQNs2Nx75fu3CybRD/d/ncSW2BtFotysrKQFEUKIoy2jfoaDR6Al58rt3OKaNNre3ZY9wsUeLlb1uxMUeE1WnGvSEVGj2eP9aMOy5NmvRG0pTezqlwd/HX1taG7du341//+hcWLLBvJZaFgZ0CtgV8Pn9CFrC7iz+tVouKigpERUU5zTh09DYWRVEYHByEWCxGY2Mj/P39GXsZW/XS9PT04MeaDqxZkgM/v/PbZh481z5u39ZL8WPzAB5cN8fkCsYPTQM4WN6H1HBf+I90ICIiwuJeofFJJENDQ8wxMsUaY322yOjP7YUpub6TIRnRokWiMim7WKUj8PZP7QgP8MSDv5tr0vPvWBgN4n8i7boPy8DjcHD0lqVT/s6SxBB0yNWTZkgbDAZUV1cjOjoaMTExY45RU1MT4zcoEAgcZgCt1hN48GAtEsJ8cdslSTZ/fqlUipaWFsybN8/u7yk21AcXpYRiQdzkLQQtEhXaZGrU9Y9geVKo0ceMz5IeGhqakEYiEAiMill3F3+dnZ3YsWMH3n77bVb8uQAzsgJoMBisjmubDIqi8Msvv2D58uXMf7vzsAc96Tt37lyEhho/YTkTiqIwPDzMDCh4enpCKBRaHNdET0X2yobwSSsf6ZEBuOmiRDus3Pb85WAttAYSz1+RYfLnTEeQqOoYgKavCXNSkhEebvs4KmuTSOyBKbm+aj0BDgBvIxW7y18/Ca2BxMGbFsHPc/qbjspuBWJCvE027B7NV3USBPt4WGWqrdfrUVZWhpiYGERGTozpG903KJVKmaxve9uXUBSFvUcasClXhLzYYJs+tysmmlAUBcX/TOAt2WYefYwoihqTRkJRlFuLv56eHmzZsgWvvvoqLrjgAmcvZ7Yxe7aA7SkAAeDnn3/G8uXL3X7YQyqVoqmpCdnZ2Xa3S7AVo+1l6KqhUCg0SWjQyQ88Hg+pqako61IgUeBr1wxSZ0MPPzgiyu5vXzejT6HF/12WANn/+ganGiKxBxRFoa2tDQqFwuiAy2juLa0GB8CzV0xsQO8e1KBJPIKL5wrsuFrbQFvbJCQkmJxVPbpv0FS/QVfibEMn6tu6sfmSBS5lxmxLxqeREAQBgUCAuXPnut31pq+vD5s3b8YLL7yASy65xNnLmY2wAtBW/Pzzz1iyZInbbvkC50vx/f39yMnJcZm7Z3PRaDTMRDEtNCaLPBtt8xIXF+eWx8xc6KlIW1j5mMJrx1vRKVfjmU0ZzM9sNURiCpPl+k7Gt/UScDmcaUUenYLhitDxfSkpKQgLC4NkWAuBv3lDCnRPWmevGHr1iEv0DU5Fb28vbvikAR7ePii5cZHFAx3uAr3tS/ewunIaiTEkEgmuuOIKPPXUU1i7dq1Vz3Xttdfi8OHDEAqFqKqqAnB+AGjbtm1oa2tDQkICPvnkE4SEnG/deOqpp/DOO++Ax+PhlVdewWWXXWb1+3FTWAFoCyiKwk8//cTkw7qbkKC9wXQ6HTIyMlzyBG8Jer2eEYMajYbZOgkMDGR6HMeb/7oyCo0eN35Ujr9uSDcrWYJGLBajtbUVubm5TtuGHY+1QyRTMVWurzU0SZR49dsWXL8i3uL0C3uhUqlQUVGBtLQ0BAcHo2dIgyc/a8SFc0KxbYF5vbxylQ6/f/csliaG4NblQojF4jF+g47sG5yKnp4e9Pb2Iiw+FUMaArkx9rH0cRVIkkRFRQVCQ0MRF3feh3R0GsnonRCBQOByOzkymQxXXHEF9u7di8svv9zq5/v+++/h7++Pq6++mhGA9913H0JDQ/HAAw/g6aefhlwuxzPPPIOamhrs2LEDp06dQk9PD1avXo2GhoYZc80zk9kzBGIvUUYPeyQmJqKurm7aqpOrQeefBgQETPAGc3c8PDzGRJ5JpVJ0dnZiaGgIer0eiYmJdul/sxcDSj00ehK1fcNmC0C6/23+/PkuVR2wdohkMujPdXBwMBISEmy65hBfD/h48hAe4HzxMxp6az8zMxOBgeeFqSjACxfNCcVKC7atg3w84MHnYk16OEJCQhASEjKmb7C8vNwmfYPNEiVOdwxiy/wosyt33d3d6O/vR15entUXcYqiIBnRQWhCJF1ltwLiYS0uTRU49JxpTPwB569vAQEBCAgIQFJSErOd39DQwNgACQQCh9ppGWNwcBBbtmzBgw8+aBPxBwAXXXQR2traxvzs4MGDOH78OADgmmuuwcqVK/HMM8/g4MGD2L59O7y8vJCYmIiUlBScOnUKy5Yts8laZgIzsgJIEMSESV1rMTbsYazqJBKJnGpqPBkajQYVFRWIiYlBVFSUs5fjEAYGBlBfX4+4uDgoFAoMyOUICgyESCRy2e2t0ZAUBQ6M39AYi2EbnWM8Xf+bs+gYUONfv3TgvrUpjF3K+IoGLRRNGSLR6/WoqKiYkOv7xg9tmCP0n9Suw52ho87s7Ws4HmN+g0Kh0Ky+wSc+b0DfkBbPX5kBLxMyfWk6OzshlUqRk5Njk8/1e7904EiVGM9uykDiNJnd95ZWQ09QeHFzpsPO65OJv+kgCAIDAwOMnZYj0kiMoVAocOWVV+KOO+7Ali1bbPrcbW1tWL9+PVMBDA4OxuDgIPPvISEhkMvluOWWW7B06VJcddVVAIDrrrsO69atw+bNm226Hjdh9lQAbc1kwx6jq060qXFrayuUSiVzcnRkJuRk0MHoaWlpTG/ETKenpwfd3d2YP38+vLy8IIqMxL0lNfDsIXCdpxzNzc1jbDFcqVJGM1WF5OcWOf7zaxf2XJiAnOhAkCSJuro6cLlc5OTkOP0zNxl1/cOQDGsxpNYzApCuaHQpgcdOS/DqlcmgtOdFzlRDJJPl+gJAfb8SLVLVjBGAf/+uFWo9iesWhjFpF46OUvTy8kJMTAxiYmJgMBgwMDCAzs5Os7zs7lmdDKWWMEv8tbe3Qy6XIzc312bDD2vSwzGo1iM2dPr2iL2Xp0JrIEEB+OhkJ5YmhSIl3H47PpaKP+B8lX20nRadRtLW1uaw6fyRkRFs3boVN998s83FnzkYK2656nnRWcxIAWjLg0wQhEnDHnw+HxEREYiIiGB6nbq6ulBbW4uQkBAIhUKEhIQ4/ANI+0s5IhjdFaBjzhQKBebPn89cjPhcLjx4HCxLEmLu3Mgx1iVnz56Fh4cHU3Ua779FURTuKqnGvJggXL3UNewXcqIDMagWYa7Qj9kCDQoKQkJCgkuf5FanhePiOWFGBYB4WAeCpKAHH4lxcYiLi2OGSJqbm6FWq5m0GE9PT1RUVBjN9eVwOHj+ygxwjN/0uiVHqs4POq3wl0ybduEI+Hz+hO18+lwzVd+gF59nlvhra2vD0NAQcnJybDr5Gh3sgzsuTTbpsX5efPh5nfd7/KJWgpq+EbvF6Fkj/sbD4XAQFBSEoKAgpKSkMGkkNTU10Ov1dpn8ViqV2L59O6677jrs3LnTJs85HSKRCL29vYiMjERvby8zCR8TE4POzk7mcV1dXbNm98tUZuQWMEmS0Ov1Vj2HrcydSZKEXC5Hf3+/wxIuaDo6OiAWi9160tccRlfBUlNTzTpmKpWK2c4HwFzc6Mm7a/59FjwuF+/uyrPH0i1Gr9ejvLycqUQDQPuACncXV+O17dmICLSNUOiSq/FdowzbFkbZNed2PN2Darz8bSseXjcXvh4cDAwMoLu7GzKZDGFhYYiOjjZrO7+8awgPHqrDh3+Y71b2Pz29/Whrb8PC+fY3PLYGW/oNtrS0QKlUIjMz02G2JzqChOcUaUD9Ci0CfUxLezEXkiRRWVmJkJAQq8XfdFibRmIMtVqN7du3Y+vWrbjhhhtsvOLfGL8FfO+99yIsLIwZAhkYGMCzzz6L6upq7Ny5kxkCWbVqFRobG12yNcYBsFvApkKLP4IgwOVaF2HE5XIRFhaGsLCwCQkXAQEBTMKFLT+UFEWhvr4eBoMB8+fPdzvPKEugbV5CQ0MRHx9v9jHz9fVFfHw84uPjmV6n2tpaGAwGhIWF4bUr5ji038oU1Go1KioqkJSUNGbApXtQAy1BQjysMyoA9QSJFqkKqSLT38+xOgl+bR/E5VkiBPs67vPULlNDqTVgQKVDQKgvPD09odFosGTJEuj1eiblwtQhkgaxEjoDCaXW4DYCsLe3F91dXVi0wLWGeozB4XDg7+8Pf39/JCYmMt+l+vp6k/sGKYpCXUMTtFoNcrOzHFbRPtEqx2vHW/Ho+lQkT7LFKwq0T9QcLf6Cg4PtLv4A69JIjKHVanHVVVehsLAQ119/vd3WvWPHDhw/fhxSqRQxMTF49NFH8cADD2Dr1q145513EBcXh6KiIgBAZmYmtm7dioyMDPD5fLz++uuzVfxNyoysAFIUBZ1OZ/HvOiLZg+7PoBMufHx8mC1Ia5p1DQYDsx1oSd6rO0IPuMTFxSEiIsKmz63X6yGVSiEWi8dsQTq7t5OeAs3IyEBQkHlWGMVne/B1nQT3XzYHCWGmVWV0BhJDGj3C/e2XtTodk+X6WjNEYgyNngCXw3EJ7z9TEk3cBbo1RiwWT1p1oigKTU1NeOp7CQIDA/HSliy7rUdPkHjpmxZcniVCRmQAmiVKPPF5A57ZlOHQz/lo8RcfH++w150MY2kkAoFg0uFGnU6Hq6++GpdccgnuuOOOWXHNcUNmjw+gpQLQWbFu46O0LI07o4VQbGys0TiomQgdZZeammr3ARd6wk4sFkOhUCA4OJjp7XRklVUul6O+vt7iBJdBtR7nOoZw8dwwu5rotkpVCPDmQ+Bv/ZYlnetrSuwX3etkaRLJ7Z9UgsPh2FV8mEJ7ezsGBgYsnnxV6gx46GAdNuZG4BIXSzShd0MkEgkGBgbg4+MDgUCAoaEhcDgc/DrkD08+F9sX2i+bXKMncFdxNTIiA3DLSufEQbqa+BuPTqdjtoqVSiVCQkIglUqxcOFCeHt7Q6/X49prr8XixYtx3333seLPdWEF4FSYOuzhCOi4M4lEMsY7bapyPG0N4YjIL1dhYGAADQ0NZgshiqJwpKofeTFBiAnxmf4XjECSJLOdL5fLbbadT1KUUVHWJlPh1eOtuHlxCKS9XcjNzTV5e8YZkBSF2z6pgiefg79daZ2QsqYKRls10UkkplRw95f1wpvPxbos55iG03Y+SqUSWVlZFt9c6AgS95RUY3VaODbm2LYyPhlqPQGtgTRre53uG6yuroZWq4Wvry8EAgGEQqFZfYNqPYE3f2jDzkUxJvn7AedFoAePCx7X8ed8Vxd/46H72f/v//4P3333HRITz4vmRYsW4cknn3T6dZNlSmaPAATO9ySYgq2GPeyFRqOBWCyGWCwGRVEThhOA86kPLS0tTDrJbKC3txednZ0WCSGlzoC7i6sRH+aLP182x+q1jN/O9/b2Ziq45vRsdcnVuLO4GreuTMRFc8ZOtn5TL8X7PzVjx1wuLl2S5/K9YABQ0a1AqK+HxSLbnFxfUxhfwXXFyLPRcXYZGRkudz6ajjuKqmAgSLy6LdvktVMUxaS4pKSkQKfTTfAbDAoJwwdlA9i+MAbRwca39VulKjzzZRO2LojCpamuVfEcDy3+6Ml9d0Ov12PPnj2QSqXQaDTw8PDA+vXrsWHDBsydO9fZy2OZCCsAx+Pq4m88dEO1WCyGwWCAQCAAQRBQKBTIyclxC1FgLbQoGBwctMoUtlOuRpifJ3w9bX/hp/vRRldwTelHk47ocOt/K3Hf2hTMi/2tr4+iKDQ3N0OlUk1bEaK/z67+WZ4OOrLQYDCYlOtryfPTFdyBgQGXyFalhRCPx3NIUg9FUfimQYoFscEI9p34nhvFSvh4cM0S8OVdQ1BoDLgwJWz6B/9vDeWVVfD39UFycvKE90z3DZa19OKFn+VYk+yHa5YnGBXtFEVhSG1AgDffKRU9U3F38UeSJG6//XaEhobimWeeAZfLRV9fH44cOYJDhw6hs7MTDz74IK688kpnL5XlN2aXANTpdEaNIGmc1e9nK7RaLSorK6FWq+Hh4eHSKSS2grZ54XA4SE1NdbnpZq2BQLNEhYzIAOZndAVXIpGAJMkx/WimQGfc8ng8k6xtbv+kEhSAV7ZmW/NWHIJKR+C+/TVYmz52i5IkSdTU1MDLywspKSkOEUK2HCKxBJIkUV1dDR8f40LIHvQpNPjD+2VYnBCMR9enjfk3iqJw838rwedy7PZZIkkSFZWVePmMGsEB/nhxmp7L7kE1PAwqDA7ImL5BV8opNgWSJFFVVYXAwEC3FX/33HMPvLy88OKLLxo9B6vVagwPDzN+fCwuAWsDQ+Pu4s9gMKC6uhphYWFISEhg7pJdMYXEVtDTzXTeqyu+r1e+bcXp9kG8sjWbsYvw9vZG3ChTY4lEgs9P1SCEb0Bc5Pkc6YCAAKPvhyAIVFRUICQkxGRrG08+F3rCPe7bvP43ZTv6Ps2eub6TMT5blR4ioZNI6H40U4dIzMVZFaGIQG88+Ls5yIwKmPBvHA4Hd16aDG8P+9xkMf1vQUGICvPE/LjpJ9mjg30A+EAoCDOaU2xJ36AjmQni7y9/+Qs4HM6k4g8AfHx8xrQosbgus64C6ErDHpZAe78lJCRMiL8Cfutz6u/vx/DwMJNCEhwc7HIVM1PRarUoLy936HQzQVL4tKIPF80JQ6ifadUFybAWpzsG8bsM4aSfrWGNAdd+UIaIQE88tFIEsViMkZERZjiBDnDX6XQoLy9HdHT0rHGvp3N9IyIiEB0dDblKB08eF35ezrtP1ev16O0XQy6T2sUGiCAIlJeXIzw8HLGxpqXMDKr1uObf5/B/+XMxPy54zL8ptQbcf6AGV+RF4tJU14zBs2XaBY2xnOLw8HCXuQmeCeLv0UcfxcDAAN566y2X6ZllMZnZVQHkcDhjBKC79fsZY2hoCDU1NVNO+o7OghydQlJfX4/AwECIRCKHpJDYCtrmZe7cuQgNDXXY63YPanCkqh8GksLm+aYJsPAAL6zLnHpyNMCbj5svTkBahD9Egd443KzB2Q4KDyeFore3F3V1dfDz84NCocDcuXNnzTYKneubkJAAoVAIiqJw1b/OgcsFPr1piVXPXdM7DLWewIJxYskUXv6uHS0SFf62OQseXDBJJLW1tVYPkRhLcTEFjZ6AzkCiUaKcIAD5PA4oClDrSbPX4wjoqrZAIDBZ8JrC6JxiekfEVsfJWmjxFxAQ4Jbij6IoPPXUU+jr68N7773Hir8ZxIytAOr1epDk+ZPgTBB//f39aGtrQ05OjkXl9fFN7/7+/hCJRDZPIbEltM1LVlaWw1M4KIpCs1SFmGBveNsh9onmteOtqO0bxmv/m5pUKBSoqKhAYGAglEol/Pz8IBQKIRAILDIC1hEkOAA8poi3cjZqtRrl5eUTRP7B8j4E+/BxsZUeduv/fhIkBRy92Xwh+V2DFPvL+/Di5swx543RPnYymQy+vr7McTJliIQWvPHx8UYr+TMRutopEokQHW2+v19VjwIJYb7wN6MibMxv0JF9g6PFH22b4k5QFIXnn38edXV1+OCDD9zejHwWM7uGQGgB6O79fhRFMYaw2dnZNplQtFcKiS2xxubFWWgNBD482YUr50UZnaqcjvG+hrYwCL/yrV/B4QDFNywyez2OgK7wpqenm51oYiqtUhW0BhJpEfa5iaD70ejjNN0QiVarRVlZGZKTkyEQOMeuRKkz4IMTXfj94hgEeNv/O28wGFBeXo7IyEiLWhqG1HrcXVKNJIEv/vI7y2xGjOUUCwQCs4ayzGEmiL9XXnkFp0+fxscffzwrXCZmMLNLABoMBhgMBrcWf/TUKwCkpaXZZduWPin29/dblUJiy/XQNi/Z2dkuI0hNoaZ3GC983YyrFsXgEjN9yOiki6kEr0qlYiaKORwOc5ymqgg/8VkDArz5uO2SJLPW4wiGhoZQW1trcaKJK9EkUSI+1AcePO6EJJLRQyQajQbl5eUOSa6ZinOdQ3jtu1bcsCIeSxPtuw6DwYCysjLExMRYFdV4olWOOUI/hJnYkzsd9uwbnAni74033sB3332H4uJit5myZpmU2SUABwYG4OHhAQ6H4zb9bqPR6/WorKxEaGioyROgtmC0yOByuQ61wyBJEvX19aAoym6C155QFIVehRbh/p5mbbl2dHRAKpUiJyfHZMGr0WggkUjQ1ScGRRgQIQy366SqrZHJZGhqakJubq7DrFbsRfegBg8fqsOK5BBct2JsosPoLGmlUgmdToeUlBRER0ebfZwoisIPTQNYEBdk9WAMQVKQjugg8Pe0q2eeXq9HWVkZ4uLiptzqJikKfQotooKc81mg+wYlEonVJuG0pY+/v7/bir933nkHn3/+OUpLS93++8kCYDYJQIqikJ+fD5VKhQ0bNqCwsBCRkZFucWEEfpv0TUxMdOoQwPgUkvDwcIhEIruM+LuDzYutoYPvNRoNMjMzzRa8FEXhj/+pAJcDPLwynIk7o22AAgMDXfLv2NfXh46Ojgm5vjKlDqG+Hi655qmgKAqf14ixOCFk0urU8PAwKisrERsbC4VCgaGhIVQMeSEjVoAV6TEmiYxWqQp/PdqAtRkCbF8YY/P3IB3RIdzECDVToPscExMTER4+9UTy01804lTbIP6+IxsRgc4VHOP7BulkH1P6Bt1d/AHA+++/j5KSEhw6dIi1c5k5zB4BCJz/End1daGkpASlpaUgCALr16/Hpk2bEBsb67IXmcHBQdTW1iIjI8NuPVGWoNPpGDFIp5CIRCKbbN05w+bF2dAGz3w+36rUh3+f6IAowAu/+9/0MV3JEIvFLmkD1NnZCbFYPCHXt0WqxOOfNaIwN8JhubWOYnBwEHV1dWOiGgmSxLXvnwUMOvwxk2PSEAlFUTjbOYRUkb9ZgxCm8P6JTnxytgd/uzITc0XW90rS4i8pKcmkPsdOuRqfV4tx3Yo4o1nYzmR0fyeASc3cafHn5+eHpCTXa7kwhX379uGjjz7Cp59+6vZtGSxjmF0CcDQURaGvrw+lpaUoLS3FyMgI1q9fj4KCAoe57ptCX18f2tvbLZ70dRR6vZ6JpNNoNEyP02SGxlOhVCpRWVnpcJsXZzLa4NmethC0DZBYLMbg4CACAgIgFAqdMvlNURRaW1sxPDyM7OzsCWJUR5B4+8d2XDkv0mEVIIKkIFPqILRh1Ws89GBPXl7ehK00ybAWvp48+HryzBoisQcdA2r865cO/Pl3c+Bp5cQ4PeSSkpKCsDDTIuHcBa1Wy2zpj+4bDAwMdHvxV1xcjH/+8584cuQIAgImmoOzuDWzVwCORywW48CBAygpKcHAwADy8/OxceNGpKWlOUUMuvPgg8FggEwmQ39/v9kpJHK5HPX19U6xeXEWtMFzTEyMQ6udFEVhaGiIsS2hJ78dkX07Otc3IyPDZW64nvmyEXV9I3hxc5ZFU9vTIZFI0NLSgry8PLMm2UfHBzoiicSWaDQalJWVzYobutHVdolEwsT4Octv0BoOHTqEV199FUeOHJnUY5bFrWEFoDEGBgZw8OBBlJSUoKenB5dddhkKCwst6smyhNFZr3PnznWJbTpLoVNIxGIxFArFlNuPdB9YTk7OrGkypv3u5syZ49TKyHjbEj6fz1ScbG25Y26ur44gza5A6Qwkbi+qQmFuBC7LML1ntlOuxk/NA9i2IMpkYdUzpMEb37fh/stS4Oc5+Y1aX18fOjs7kZeXZ5XA1uv1EEskeOnbNsT6kfhdxvnjRCfGmEpD/wjOdAxi+0Lzh09Mhf58p6Wl2V1E6AgSPzUN4OK5YU7dMqYoClVVVfD19UVoaOiYvkF6q9jVJ2g/++wzPPfcczh69KjNRXtCQgICAgLA4/HA5/Nx+vRpDAwMYNu2bWhra0NCQgI++eQTp07EzxJYATgdQ0ND+PTTT1FaWoqWlhasXr0ahYWFyMvLs4swo6Ov6BgoV7+7N4fx24+BgYEQCoUIDQ1FZ2cn5HK521U7rWF4eBhVVVXIzMxEYGCgs5czBrVazVQx6GEfW2Sqmpvr2yJV4rZPqnDzxYlYl2m6kCNICjd+VI60CH/cuyZl2scPqfUI8OZbJByO1Urw0a9deCR/LpIExnukuru70dfXN6HP0VIoisLGf5wCj8vB21cmQiKRYGhoaMx3arqK053FVRhU6fHGzhx48W1fnVKpVKioqBjj50iQFLgc2OW89lWdBB+e7MJtlyROSENxFBRFobq6mqn8jcbUvkFnc+zYMTzxxBM4evSoXTwpExIScPr06THPfd999yE0NBQPPPAAnn76acjlcjzzzDM2f22WMbAC0ByGh4dx9OhRlJSUoK6uDpdccgkKCwuxaNEim4hB+oSZnJw87YScu0NvP/b396O3txd8Ph8pKSkIDw93u60SS6D7wEYPAdgDtZ6Aj4WpJV/VSXCiVY57Lo2H9H/eaDqdjtl+9Pf3N+tCPj7X1xgURaG8S4GMqAB48rgYVOnxhw/O4fEN6ciMsk8P0ojWgG3/PIOYEG+8uTPX7N8nSAoaPQFfT57Rv0dHRwdkMhlycnJs+tlW6gzw4HLhyT9/7qG/U3Syz3Rb+mo9gWGNweJ+R52BxK73zuL6FfFYkz72fEX38WZkZDA3NyRFYds/z4DP5WDfdQsses2pUOsJVPcMIzcm0CkpN1OJv/FM1jfo7Jzi48eP45FHHsGRI0fslkZjTACmpqbi+PHjiIyMRG9vL1auXIn6+nq7vD4LAysALUWtVuOLL75AcXExysrKcNFFF6GwsBDLli2z6CQvl8tRV1fnktUge0FXgwICAiAQCCakkDiiF80Z0Fvd9k406ZSr8fChOmxdEIX8LPNP5tv+eRp6gkLxjQuZypjBYGAuXCqVCqGhoSb1d9JT3XSu72TU9Y3gyS8aUZATgSvnOaYfkqIo3FlcjR0Lo7Ak0XbbXdMNudgTY0kkdBXXVu0VeoLElrdPIysqAI9vTGd+PjIygsrKSmRlZU0YHNj+zhksiAsyqSrrTpgj/sYz3m/QnCquLfnxxx/xwAMP4PDhwxYls5hKYmIiQkJCwOFwsGfPHtx4440IDg7G4OAg85iQkBDI5XK7rYEFACsAbYNWq8VXX32FoqIi/Prrr1i+fDk2bdqEFStWmCRg6Iiz2dT7ptVqUVFRgejo6DEnm9EXLolE4vQUEltjicGzpaj1BO4srsLdq1IwR2j+NpOeIGEgqUkriOP7O4OCgpgL12ixM1mur9HnJCkcb5RiUXwwAr0n/+6o9QS8+VyXbZGg/Rx1Oh3S09Od3sdLm4SLxWK7DpHQ4i87O3vWDHFZI/6MPdfoKq6j+gZPnjyJO++8E59++iliY2Pt9joA0NPTg6ioKIjFYqxZswavvvoqNm7cyApAx8MKQFuj1+vx7bffori4GD/99BMWL16MgoICrFy5csIXmCRJnDx5Et7e3rOq943eHjJl8MGZKSS2hBYEWq0WGRkZThcEtoYkyTFGuf7+/ky1ifawNFbZJinK7L47rYHAjR9VINzfE89fmWmrt2AzKIpCXV0dOBwOUlNTGYGlM5Dw4Dk/fnJ0EolKpWK2H80dIhkP3dOak5Pjcn1t9sKW4s8YdE6xRCIBYJ++wTNnzuDWW2/FgQMH7GpBZYy9e/fC398fb7/9NrsF7HhYAWhPDAYDfvjhBxQVFeH7779HXl4eCgoKsGrVKlAUhauuugpJSUl49tlnnX5RcBTW2Lw4MoXEltBTr56enpgzZ86MPdYjWgPuLK7CXy6bgzBPAh0dHejv70dQUBCioqIQHh4+piKu1hPY8c4ZZEcH4q8b0sx6rbtKqnFFbgQuSHEtT7nJJpy1BgJ7PqpARJAXni7McPIqf4Ou4loyRDIaOsPZ3j2t4zGQJPb8pwJ50YG41cHZ1hRFoaamBt7e3nYRf+Oh+wYlEgk0Go1N+gbLy8uxZ88elJaWIiXF/tvySqUSJEkiICAASqUSa9aswSOPPIKvv/4aYWFhzBDIwMAAnn32WbuvZ5bDCkBHQRAEfv75Z5SUlOCLL76AVqvFJZdcgmeeecahJ0xn0t/fz5haW1vBM5ZCQg8muBIGgwEVFRUICwtDfHz89L/gxjSKlbinpBrXLo/Dimg+mpubkZubC4Igzh8riQTgcBEpEkIoFMLLywub3z6NrfOjsG2h8aEQd4IkSVRWViIwMNBo5Nee/5Rj6/worEpzzQEviqJwrqUPPnoFhgblJvfi0qkmubm5Dr8ZoygK139YjoggLzwxqg/REa9LC31nBAfYom+wuroa1113HYqKipCammrnFZ+npaUFmzZtAnD+3Lhz5048+OCDkMlk2Lp1Kzo6OhAXF4eioqIZ7xnpArAC0NE0NDRg+/bt2LVrF3p6evDll18iOTkZBQUF+N3vfjcj3dYpikJ7ezsGBgbs0vtGb2n19/dbnUJiS+joK1ePs+se1ODXNjkKciOs+ntRFAW1nsSgTIzuri7k5uaOaXu44cMy6AwEHrtEAKlUCoIgmMEEd98yJAgC5eXlEAgEiIuLs+q59ASJz6rFyM8Sgu/AVoFWqQoPf1qHNekCXL0k1qQhErqibyzVZKbibPFnbD3m9g3W1dVh9+7d2LdvHzIzXa+NgsUhsALQkXz33Xe4/fbb8f777yMnJwfA+apBeXk5ioqK8NlnnyEmJgYFBQXIz8+fEe7rFEWhvr4eBEE4pBmeIAimv2lkZMSsFBJbQlv6ONvg2RSe+qIR1T3DeG17NoJ9rJu67uzshEQiMSr0//VLBzoG1Pi/y89XG3Q6HXOsXEm4T4UxU2qDwYCysjJERUXZZHryWK0EL33TgjtXJWG1A6uFJEXh04p+XJASijC/scLB2BCJl5cXOjs7MW/ePLtOs7sSrib+jDG+b9Db2xsURTHXnMbGRuzatQsffPABcnPNtz1imTGwAtBRlJSU4IUXXkBJScmk1SDaQb64uBhHjhyBQCBAYWEhLr/8cpcXEcYgCAJVVVUICAhAYmKiU7ZJRk+pBgcHQyQSGU0hsSUKhQLV1dVuY+mj1BrQM6Q1a1K4WaLEgfJe3HpJEjx5XKstT8YLdzoxhraLIEgKByv6sHJOGEL9nDMNvuc/5egd0qDohoWMcTId4xcXF2cz3zSNnsCv7YNYnBBsF4Nma9Hr9WhtbUV3dze8vLwgEAhsMkQyGo2ewIHyPmzKi3CZv4E7iL/x6HQ6/Prrr3jsscfQ39+PhQsX4vTp0/jwww+xePFiZy+PxbmwAtBRdHR0ICwszOStLrpyVlxcjMOHD8Pf3x8bN27Ehg0bIBQKXf7kQ18Yx9u8OIvJUkjCwsJsKgZlMhkaGxsd3gzvaN74vg0/Ng/gla1ZCPH1QENDA1PltfazSZIkI9zpwQStZxCe+74P6zJFuHqpfW0qJuOTs934+NcelO5ZBOB8U35ZWRmSkpKmNG6nKMrlv6/mIJFI0Nrairy8PPB4PJsMkYzn+0YZ/vFDG269OBHLk53fC+aO4m88dXV1uOWWWxAWFoa2tjbGoWL16tUz+lzFMimsAHQHKIpCS0sLiouLcfDgQXh6emLDhg0oKChAZGSky52MzLF5cQajU0hGW5YIBAKrLlq9vb3oMtL7NhPRESSUWgOCvPlm5fqay+hjdbZNiuRwf8RFiSAQCJxqm2Sqt+EXNWL84/s2vLMrb8K26ojWAL9J0kOsQqcEZ7AN4HmACk0BOLa7wenu7cPLXzfhj2tzkCQcW902lkRC96KZa+iuJ0g09CsxV+TnlFSP0cwE8dfT04PNmzfjtddewwUXXACCIHDixAkcOnQIx44dQ2xsLP7+979PmtDDMiNhBaC7QVEUOjo6UFpaiv3794MkSaxfvx6FhYUukR08ODiI2tpaoykArghFURgeHmaa3S1NIWlvb2fivmaLn6O5ub7WQlEURkZGmGPl6enJDCY4UnArlUpUVFQgIyODybidDFoA/vuaeQga1V+pNRC47oNyBHrz8fcdObZZGKEH/8zb4NUeACgKHIoE5RMM/dLbQCZcbPXT9/X1obyhHe818nBZhhC7l00+7DJZEkl4eLjL2zaNhqIo1NbWwsPDwy43OI6gr68Pmzdvxt/+9jesXLnS6GPq6+uRkJAwa3o5WQCwAtC9oSgKvb29KC0tRWlpKVQqFdavX4+CggIkJSU5/GTV39+PtrY25Obmuu1EIC0wJBIJPDw8IBQKpxQYFEWhsbEROp1uRho8T4Zer0d5eTkiIyOdVjUYbRLO4XAYMWhPgUGbHdviBuf/DtdhXaYQS20UP8f/7nHwm74C5RMCcP93E6JXAXoV9Kv+CjL+Aoufu7e3F93d3cjLy4NcTSDI12PCMMyUvz8wjDuLq7ApiYvEQA7TN2hunrQjmQniTywW48orr8TTTz+NNWvWOHs5LK4FKwBnEmKxGPv370dJSQnkcjny8/NRUFAwJo3AXtAVsOzs7BmT3zs+hWS8DQZJkqiuroa3t7fbXiAswdRcX0ei1WqZKdXRvpC2jDobGhpCTU2NSyZdcAbb4Vm6G/AJnbjlq1MC3kHQbvkPYMHforu7G319fUzPnyWIh7W4q7ga1y2PwwVJQYyhsVKpZPKkbTlEYi0zQfzJZDJcccUVePTRR5Gfn+/s5bC4HqwAnKnIZDIcPHgQJSUl6Ovrw9q1a7Fp0yabV6koikJDQwMMBoNLZJ7aCzqFRCKRgCRJhIWFQSaTQSQSWe375k6Yk+vrLEZHnanVapskJgwMDKChocEpZsemwKsqhsfJV0H5GRHkFAVo5NBd8R6oIPMGaLq6uiAWi5Gbm2tVf+xk2CqJxJbMBPEnl8tx5ZVX4s9//jMKCgqcvRwW14QVgLOBwcFBfPrppygtLUVrayvWrFmDwsJC5ObmWiXYaJsXf39/p2w5O4vh4WGUl5eDx+ONqQy6WgqJrRkZGUFlZaXb2NsAvyUmiMViDA8PIzg4mLGXMfWzL5VK0dzcjLy8PJftkeJVfgyPU38H5WfcioajGYS24C1QIRMTSiajo6OD6Wt1hBiz5RCJNWtwd/GnUChw5ZVX4s4778TmzZudvRwW14UVgLON4eFhHDlyBCUlJaivr8ell16KwsJCLFy40CwxSNu8REVFzarJMdrgma6Aja82uYOZsSXQcV/Z2dkut/1pKiRJYnBwEGKxGHK5HAEBAYwV0GQCh44vzMvLc+nJbk5fBbw+uwOUd+jEbV6DFgAF7Y5SgGeakGpra8PQ0JBFno62gB4ioQ2NHTFEQos/Pp/vtpndIyMj2Lx5M2666Sbs2LHD2cthcW1YATibUavV+Oyzz1BSUoLy8nJcfPHFKCwsxNKlS6e843enlAtbQveATTYAMN7MODQ0FCKRyOEpJLaGroC50nCP1kBArSctTi6hKAoKhQJisRgymcxotamnpwc9PT3Iy8uzerJbodHjs2oxrpwXaZ94N4qC56d/AldWP1YEkgQ4ahn0i/8EInubSU9FG3pnZWW5TEuHsSQSWw6RUBSFuro68Hg8txV/SqUS27ZtwzXXXINrrrnG2cthcX1YAchyHq1Wi2PHjqGoqAhnzpzB8uXLUVhYiBUrVozZfvn6669RW1uLa665xi1sXmyFVCpFU1OTyT1gJEkyW490Com5W4+uQF9fHzo7O13O23DXe2dhICj859r5NrlYj7aX4fP54PP50Ol0mDdvnk22Pw+W9+GjX7vw8Lq5yI620/a5egCeXz8CrrgGAAWKwwEHHBgyt8Kw6MZpB0Bov1G1Wu3SE+101d1WQyQzQfyp1Wps374dW7duxQ033ODs5bC4B6wAZJmITqfDt99+i+LiYvz8889YvHgxCgsL0d3djVdffRWffPIJkpOTnb1Mh9HT04Pu7m6LRRC99djf32/XFBJbM1Wur7P5qVmGrkENti2wfftBQ0MDZDIZPDw8QFEU0+NpTVqCRk+gUaxEZlQAuPYUGBQFjqwBXEkdwPcEEb0I8BWY8GsUmpqaGDsjdxFB1g6RzATxp9VqsXPnTmzYsAE33XSTW74HFqfACkCWqTEYDPj+++/xyCOPoK2tDRdddBGuuOIKXHrppS6zHWgvKIpCe3s75HK5zRrhRze6y2Qym6WQ2BJrc33dFVoEabVapgKm0+mYrUedTsf0eLqyf5250JP8JEkiLS3Nbd+XuUMktPjjcrmYO3euW75vnU6HXbt2YdWqVbj99tvd8j2wOA1WALJMDUmSuOeeeyCVSvHmm2/i119/RUlJCb755htkZGSgsLAQa9asmXFZko6wtxmfQuLt7Q2RSGR2Comt12TLXF93gc7epihqUhFkMBiYHk9X9a8zF/p9A3CIX6ijmG6IZCaIP71ejz/84Q9YunQp7r33Xrd8DyxOhRWAtqCoqAh79+5FbW0tTp06hYULFwI4P0mXnp6O1NRUAMDSpUvxxhtvAADOnDmD3bt3Q61WIz8/Hy+//LLLfYHVajWuvvpqpKen49FHHx2zPpIkcerUKRQXF+PLL7/EnDlzUFhYiLVr17p9byBJkqiqqoKvr69Dsz/H96FNl0Jia0iStGuur6tCZ716enqa/L7pHk966zEoKIjZenSXiulMmHo1FXqIRCKRQK/XAwB8fX2RmZnpNsdrNAaDATfccAOysrLw0EMPzehjx2I3WAFoC2pra8HlcrFnzx48//zzYwTg+vXrUVVVNeF3Fi9ejJdffhlLly5Ffn4+brvtNqxbt87RS5+Se++9F6mpqbj++uunfBxJkigrK0NRURE+++wzxMXFoaCgAPn5+dNmpboaBoMB5eXlEAqFiI01zzTXloyPOaPFoL223QmCQEVFBUJCQhyS62tvKIrC+yc7ERvii0tTJ++Bo8W+v78/EhMTweFwoCdIeJgRc0ZRFORyOSQSCQYGBpht/bCwMJfrnaShRa+Xl5dDb3KcDS16NRoN+Hy+W1ZyCYLAn/70JyQkJOCxxx6z65o///xz3H777SAIAtdffz0eeOABu70Wi8NhBaAtWblypUkCsLe3F5dccgnq6uoAAPv27cPx48fx5ptvOnzNU0GSpNl3xxRFoaqqCkVFRTh69CjCw8NRUFCAyy+/3OUtY+iIs/j4eIhExg11ncFoCwySJG0ylDAaOtc3KioKUVFRNnlOZ0NRFLa/cwY8Lgf/uXaB0cfQojcsLIxJcznTMYinv2jC4xvTkCoyzdj7qn+dBUlR+OgP8wGA2daXyWTw9PSEUChEeHi4y0xR0xGGdIV7tkBvd3M4HGbblyRJDAwMQCwWM0Mk4eHhU3pDOhOSJHH77bcjLCwMTz/9tF2rlwRBYO7cuTh27BhiYmKwaNEi7Nu3DxkZGXZ7TRaHYlQAuuYtq5vS2tqKefPmITAwEI8//jguvPBCdHd3IyYmhnlMTEwMuru7nbhK41hycuFwOMjOzkZ2djYeffRR1NXVobi4GJs3b0ZgYCA2btyIDRs2IDw83KXutpVKJSorK10y4szb2xuxsbGIjY1lhhLq6+uZoQSRSGRx5q0r5vraAg6Hg7d+nztpJY+u9EZERIwxMg/x9YAHjwN/L9NPg0E+fAyq9czfPzAwEIGBgUhJSWH60MrLy43mSTsauuIZEBCAxETTU0HcHWPiDzh/jhMIBBAIBMwQiUQiQUtLCzNEIhAIXEK80/3YAQEBdhd/AHDq1CmkpKQgKSkJALB9+3YcPHiQFYAzHFYAGmH16tXo6+ub8PMnnnhi0qzFyMhIdHR0ICwsDGfOnEFhYSGqq6thrMLqSmLIVnA4HKSnp+Phhx/GQw89hObmZhQXF2Pnzp3w9PTExo0bUVBQgIiICKe+/+kMnl0JT09PREdHIzo6mvFDa25uZjJvRSKRySkk7pDraw1Bk5hE6/V6lJWVITY2FhEREWP+LUngN2nFcDJe354z6b/5+fnBz88PCQkJTCW3uroaBEEwQwmOihAkSZLZ5o+Pj3fIa7oCk4m/8XA4HAQHByM4OHiMeC8rK3NIEslUkCSJv/zlL+Byufjb3/7mkL7F7u7uMW0wMTExOHnypN1fl8W5sALQCF999ZXZv+Pl5cVkhy5YsADJycloaGhATEwMurq6mMd1dXXNmK23yeBwOEhJScEDDzyA+++/H+3t7SgtLcXu3btBURQ2bNiAwsJCxMTEOFQM0gbPeXl5TjmxW4OHhwciIyMRGRnJpJC0t7czKSRT9TUNDw+jqqrKrXJ9bYFWq0VZWRmSkpIQHh7u0NceXcnV6/WQSCRoamqCRqNBWFgYhEIhAgMD7fL5p7e7BQKBU3tbHc3oKWdzpn05HA78/f2Z3lBavNfW1kKv1zvUDogkSezduxdKpRJvv/22w4ZWZkuhgmUsrAC0ERKJhDEkbWlpQWNjI5KSkhAaGoqAgACcOHECS5Yswfvvv49bb73V2ct1GBwOBwkJCbjrrrtw5513ore3FyUlJfjjH/8IjUaD9evXo6CggGnKtxe0wfP8+fNdYovHGng8HkQiEUQiETOh2tPTg7q6ugkpJHSub05Ojtvm+lqCRqNBWVmZS1Q8PTw8mJ5LgiAgk8nQ2dmJ4eFhhISEMOLdFhd7giCYwabRrSczHdrSCLDe4ma8eJdKpWhtbR0zRBIUFGRzcUZRFJ588kn09/fjvffec+jEckxMDDo7O5n/ng2FChZ2CMRs9u/fj1tvvRUSiQTBwcHIy8vDF198gZKSEjzyyCPg8/ng8Xh49NFHsWHDBgDA6dOnGRuYdevW4dVXX531d1cURUEsFmP//v0oLS2FXC5Hfn4+CgsLberVRVHUmLB7V2z2thV0ColYLIZcLoenpyfUajXmz58/47wbp4LOr05LS0NwcLCzlzMpJElCLpdDLBaPSY0xNdliPARBoKysDJGRkbPq4k2LP4qi7OpvaM8hEoqi8Nxzz6G+vh4ffPCBwyfKDQYD5s6di6+//hrR0dFYtGgR/vOf/yAzM9Oh62CxG+wUMIvrIpPJcODAAZSWlqKvrw+XXXYZNm3aZJUxM70lRBsdu6MHmKX09vaira0NwcHBGBwchJ+fH0QikUvbldiCkZERVFZWukWP52iMJVvQqTGmGIUbDAaUlZUhOjoakZGRDlixa+Ao8WfsdekhEplMZtUQCUVReOWVV3D69Gl8/PHHTjOGP3r0KO644w4QBIFrr70WDz74oFPWwWIXWAHI4h4MDg7i0KFDKC0tRXt7O1avXo1NmzYhJyfHZBHnLINnV2B8rq+xFBLarsRZFxt7QA/4uPt2N0VRjFG4TCZjjMLDw8OZPuPR0IMucXFxLmVpZG+cJf6MrWN0EgmXy2WO13S9xhRF4Y033sB3332H4uJit29PYXFZWAHI4n4oFAocOXIEpaWlqK+vx6pVq1BYWIgFCxZMKgb1ej0qKiqcbvDsaCiKQktLC5RKJbKysib9+zg7hcQeyOVy1NfXIzc31+0GfKZDrVYzRuEURTHHy8fHB3q9HufOnZtx1j7T4cqZxuOTSCYbIqEoCu+88w4+//xzlJaWzvi8dRanwgpAFvdGpVLhs88+Q0lJCSoqKrBy5UoUFhZiyZIlTA9Oa2srHnjgAbz88ssTbD9mMvR2N0mSZuX6qtVq9Pf3OyyFxB7IZDI0NTUhNzfXrdZtCVqtljEK1+l00Ol0SEhIQGxsrEuJIHtCURQaGxtBEITLib/x0EMkEokENTU1+Oabb1BYWIjVq1fj448/RmlpKQ4ePDjjblpYXA5WALLMHDQaDY4dO4aioiKcPXsWK1aswIIFC/Dss8/i2Wefxe9+9ztnL9Fh0GkPPj4+Vm13j04hIQiCEYOuPEAiFovR1taGvLw8t65gmotWq8W5c+cQFhYGtVoNlUo1ZkLVlUWRNbiT+BuPWq3GkSNHcPDgQZw+fRoEQeBvf/sbNmzYwApAFnvDCkCWmYlOp8Prr7+OJ598EomJicjKykJhYSEuuuiiGS8KaM+30NBQmxr+0ikkdKXJ2hQSe9Db24vu7m7k5ubOqF7G6TBmcUMQBDOhqlAoJtgBzQTcWfyNpri4GP/85z+xd+9efPnll/jyyy+RkJCAwsJCt4jRZHFLWAHIMjM5cuQI9u7di9LSUkRGRjIN1T/88APmzZuHwsJCXHLJJTNue9BRub70NpZYLGZSSOxpZGwK9KBLbm7ujLb2GQ8t/lJTUxESEmL0MePtgAICApgJVXf9W80U8Xfw4EG89tprOHLkyBiLorq6Ohw4cACHDx/Giy++iEWLFjlvkSwzEVYAzlaKioqwd+9e1NbW4tSpU1i4cCHzb0899RTeeecd8Hg8vPLKK7jssssAAGfOnGG8C/Pz8/Hyyy+75En33Xffxfvvv4/S0tIJhr8EQeDHH39ESUkJvvnmG6YyuHr1apfe1jQFZ+X60kbG/f39JqWQ2IO2tjYMDg7OeF/H8dBxfub4G1IUBYVCAYlE4rYT4BRFoampCXq93qz+Vlfj6NGjeP7553H06FGnm5OzzDpYAThbqa2tBZfLxZ49e/D8888zArCmpgY7duzAqVOn0NPTg9WrV6OhoQE8Hg+LFy/Gyy+/jKVLlyI/Px+33XYb1q1b5+R3Mpauri7ce++9ePfdd6ftoSFJEidPnkRxcTGOHTuGOXPmYNOmTVi7dq3D8lltBW107OyUi/HGuPbedqQoislCzszMnDFbm6ZAH/OMjAyr4vyUSiUzUczj8Rgx6KrV8Zki/o4dO4YnnngCR48ehUAgcPZyWGYfrACc7axcuXKMAHzqqacAAH/+858BAJdddhn27t2LhIQEXHLJJairqwMA7Nu3D8ePH8ebb77pnIXbGJIkce7cORQVFeHzzz9HfHw8Nm7ciPz8fAQFBTl7eVPiqrm+xrYdRSKRxakW46FtP2hTb3cVApagVCpRUVFhc3NrjUbDiEGSJBm7ElfxUJwp4u/48eN45JFHcOTIkVnl08jiUhj98szcSACWaenu7sbSpUuZ/46JiUF3dzc8PDzG5IjSP58pcLlcLFiwAAsWLMCTTz6JqqoqFBUVYf369RCJRNi4cSPWr1/vcts0rpzry+VyERoaitDQ0DGpFk1NTfDz82NSLSxJIaEoCjU1NfDw8HBrIWAJdLJJdna2zSvV3t7eiIuLQ1xcHDP009DQAK1Wy4jBgIAAp/y9Z4r4++GHH/DQQw+x4o/FJWEF4Axh9erV6Ovrm/DzJ554AgUFBUZ/x1j1l8PhTPrzmQiXy0VOTg5ycnLw2GOPoba2FsXFxbjiiisQFBSEgoICbNiwAQKBwKl/A6lUiubmZuTl5bnsdh0Nh8NBcHAwgoODmVSL/v5+tLW1md2DRie6+Pn5ISkpacZ+Do1BV3sdIfg9PT0RHR2N6OhoGAwGyGQytLe3O6XPc6aIvxMnTuD+++/H4cOHZ1U8H4v7wArAGcJXX31l9u/ExMSgs7OT+e+uri5ERUUhJiYGXV1dE34+0+FwOMjIyMAjjzyChx9+GE1NTSgpKcGOHTvg5eWFjRs3oqCgACKRyKEXpd7eXnR1dWHevHluZ2vD4XAQEBCAgIAApKSkMD1o586dmzaFxF4WN+6AQqFATU0NcnNzHT6wxOfzIRKJIBKJmD7P3t5e1NXVITAwEEKhEGFhYXbr85wJ4u/06dO48847cejQoTG7KSwsrgTbAziLGN8DWF1djZ07dzJDIKtWrUJjYyN4PB4WLVqEV199FUuWLEF+fj5uvfVW5OfnO/kdOAeKotDe3o6SkhLs378fHA4HGzZsQGFhIaKjo+16kRqf6zuToCPOxGLxhBQSg8GA8vJyiESiWXcBHRoaQm1trcvF2lEUxfR5DgwMWL21b+z5m5ubodVqkZGR4bbir6ysDH/84x+xf/9+JCcnO3s5LCwAOwQye9m/fz9uvfVWSCQSBAcHIy8vD1988QWA81vE7777Lvh8Pl566SVm0vf06dOMDcy6devw6quvuu0J2ZZQFIWenh5GDGq1Wqxfvx4FBQVISEiw2d/I1FzfmYJWq2XEoMFggE6nQ2xsLBISEpy9NIdC93m6mvgbD721T2dKe3p6Mlv7llSpZ4r4q6qqwvXXX4+ioiKkpqY6ezksLDSsAGRhsSUURUEsFqO0tBSlpaUYGhpCfn4+CgsLMWfOHIsvYpbm+s4EdDodzp49i+DgYKjVaiaFRCgUwt/ff0b/LQYGBtDQ0OAWfZ7jUalUzEQxXc0NDw83ScTOFPFXW1uLP/zhD9i3bx8yMzOdvRwWltGwApCFxZ5IpVIcOHAApaWlEIvFuOyyy7Bp0yazRJytcn3dETrlYs6cOUwclsFgYCLpXCWFxB7IZDI0NTUhLy8PXl5ezl6OVdDVXIlEAoPBMMZeZvwxmynir7GxEbt27cKHH36InJwcZy+HhWU8rABkYXEUcrkcn376KUpKStDR0YE1a9Zg06ZNyM7OnnQ7dzYPPdBGx1OlXNApJGKxGMPDw05JIbEHUqkULS0tyMvLc7shn+mYKkYQwIwQf62trdixYwfee+89zJ8/39nLYWExBisAWVicgUKhwJEjR1BSUoLGxkasWrUKBQUFWLBgASMGJRIJbrvtNjz77LOIjY118oodC+11Z4659fgUkqCgIIhEIrulkNgLsViMtrY2zJs3z22i2SxlvIDncrnw8PBw6zznjo4ObNu2DW+//TYWL15sl9fYu3cv3n77bYSHhwMAnnzySWYgb7IoTxaWcbACkIXF2ahUKhw9ehTFxcWorq7GypUrsXz5cjz22GO4++67sXPnTmcv0aEoFApUV1dbZXRsLIWEtipxZWHR39+Pjo4O5OXlzXjxN56mpiYMDQ3B19cXg4ODbnPMRtPd3Y0tW7bgtddewwUXXGC319m7dy/8/f1xzz33jPn5VFGeLCzjYJNAWFicja+vLzZv3ozNmzdDo9Hg3//+N2699VakpKTg9OnTiImJwfLly2ec5YsxRk+8WuN1Nz6FRKFQoL+/H83NzTa3KrEVvb296O7uxrx581xqXY6gubkZGo0G8+fPZ4znFQoFxGIxWlpa4OPjwxwzVxXGfX192LZtG1566SW7ir+pOHjwILZv3w4vLy8kJiYiJSUFp06dwrJly5yyHhb3Y3adeVhYXIiGhgb8/e9/x7Fjx5CZmYmvv/4aRUVFuPvuu7F06VIUFhbioosuctmLoDXIZDI0NjbafOKVw+EgKCgIQUFBVqeQ2Iuenh709vYiLy9vVoo/tVqNzMxMpudv9DEzZhYeHh4OoVDoMsMxYrEYW7ZswTPPPIOVK1c65DVfe+01vP/++1i4cCFeeOEFhISETBrlycJiKu7TLMMyq9m7dy+io6ORl5eHvLw8HD16lPm3p556CikpKUhNTWX8DV2dH3/8Eddccw2KioqYhI9169bhnXfeQVlZGXbs2IEjR45gxYoV+OMf/4jPP/8cWq3W2cu2CWKxGM3NzZg/f75d7U7oFJKUlBQsXboUc+bMgVarxblz53D27Fl0dXU5/G/a1dWFvr4+VvxNMvDB4XDg7++PpKQkLF68GOnp6SBJEpWVlfj111/R1tYGlUrl4JX/hkwmw5YtW/DXv/4Va9assdnzrl69GllZWRP+d/DgQdx0001obm5GWVkZIiMjcffddwOYPMqThcVU2B5AFrdgJvXBjIyMYMOGDfjwww8RHR095WMJgsCPP/6I4uJifPvtt8jOzkZhYSFWr17t0kbBk0HH2jm7781YCompvnWW0tnZCalUipycHJf+fNoDU8TfdOh0OsZexhn+kHK5HFdeeSX+8pe/YOPGjXZ/PWO0tbVh/fr1qKqqwlNPPQUA+POf/wwAuOyyy7B37152C5jFGGwPIMvMwx37YPz9/fHNN9+YdNHi8Xi4+OKLcfHFF4MkSZw4cQLFxcV4/PHHkZqaisLCQqxdu9biAQpH0tXVhf7+fpfoe/Px8UF8fDzi4+MZ37qamhoQBMFsOfr5+dns9drb2yGXy5Gbm+tWU8q2oKWlxWrxBwCenp6IiYlBTEwMDAYDpFIpWltboVQqGXuZoKAgu4jBoaEhbN26Fffee6/DxV9vby8iIyMBnE91ysrKAgBs3LgRO3fuxF133YWenh40NjbabRKZZWbCCkAWt2Em9cFYcpHicrlYvnw5li9fDpIkcfbsWRQVFeG5555DYmIiNm7ciPz8fJOtVBwJLYDy8vJcrvrl5eWF2NhYxMbGQqfTQSqVoqGhwWZVptbWVgwPDyMnJ2dWij+VSmW1+BsPn89HREQEIiIiQBAEBgYG0N3djdraWgQFBUEoFCI0NNQmf+/h4WFs27YNt9xyC6688kobrN487rvvPpSVlYHD4SAhIQFvvvkmACAzMxNbt25FRkYG+Hw+Xn/9dZf7brG4NuwWMIvLsHr1avT19U34+RNPPIGlS5dCIBCAw+Hg4YcfRm9vL959913cfPPNWLZsGa666ioAwHXXXYf8/HynnKidBd0jVVRUhM8++wwRERHYuHEj1q9fj5CQEKeuzZ0zjekqk1gshkqlsiiFhH7vmZmZbvXebcHo4+6o3jTaEkgikWBgYAD+/v6MvYwlVWelUolt27Zh9+7duPrqq+2wYhYWh8D6ALLMDNg+mMmhKAq1tbUoLi7G4cOHERwcjIKCAqxfv54xknXkWhobG6HX69066QGYaGIcEhICkUg0aQoJHXGm0WhsXv1yB5wh/sZDURSGh4chFoshlUqZKXCBQGBS4oparca2bduwfft2XH/99Q5YMQuL3WAFIIv7MroP5sUXX8TJkyfx8ccfo7q6Gjt37mSGQFatWoXGxkZ2KwTnL4BNTU0oLi7GoUOH4OPjg40bN2Ljxo0QiUR2vTDTQpTH42Hu3LkzSgBNl0JCC1+DwWBWDvRMwRXEnzFoexmJRAIej8f0ehqbRNdoNNi5cyc2btyIm266yaXeBwuLBbACkMV92bVr14Q+GFoQPvHEE3j33XfB5/Px0ksvYd26dU5eretBURTa2tpQUlKCAwcOgMvlYsOGDSgsLERUVJRNL3AkSaK6uho+Pj5ITk6e0RdPiqIgl8vHpJDo9Xp4eXnNSvHX2tqKkZERl9/y1mg0kEgkEIvFIAgCZ86cwfLly5GbmwudToddu3Zh1apVuP3222fdMWSZkbACkIWF5bxo6e7uRklJCfbv3w+dTof169ejoKAACQkJVl3wCIJAZWUlgoODkZCQYLtFuwEkSaKiogIajQYURblsCom9oIdd3K3XU6fT4V//+hf279+P/v5+BAUFYenSpXjppZfc6n2wsEwBKwBZWFjGQlEU+vv7UVpaitLSUigUClx++eUoLCxESkqKWWKQIAiUl5cjPDwcsbGxdly160FRFGpqauDp6YmUlBQA5/0e6f4zT09PiEQip6eQ2At3FX+jMRgMuP7665n+wIqKCqxcuRJXXHEFLrjgglkh4llmLKwAZGFhmRqJRIIDBw6gtLQUEokE69atQ0FBwbTbmXq9HmVlZYiJiWG25mcLFEUxW95JSUlG/07j+8+EQqFLxZtZw0wQfwRB4KabbkJiYiIee+wxcDgc6HQ6fPvtt9i/fz9++uknXHHFFXj00UedvVQWFktgBSALC4vpyOVyHDp0CCUlJejs7MTatWuxadOmCRf63t5efPzxx/j9738PoVDoxBU7HpIkUVVVxcSXmQKdQiKRSEBRFCMG3THZZSaIP5IkcdtttyE8PBxPPfWU0fdBEAR6enpmXWWbZcbACkAWFhbLUCgUOHz4MEpKStDU1ITVq1ejoKAAoaGh2Lx5Mx588MFZ5b0I/Oa/GBQUZHG/I51CQg8j2COFxF60tbVBoVC4vfi7++674ePjg7/97W9u+z5YWKaBFYAsLCzWMzIygs8++wz//ve/ceLECaxfvx67du3C4sWLZ439Dj3wERoairi4OJs8p16vh0QiQX9/v1Oybs1hpoi/P//5zyAIAq+99prbvg8WFhNgBSALC4ttqKurw/bt2/H6669DKpWiuLgY586dw4UXXoiCggIsX758xjbNEwSBiooKCAQCu20J2iKFxF7MFPG3d+9eDA4O4q233nLb98HCYiKsAGRhcQaff/45br/9dhAEgeuvvx4PPPCAs5dkFWVlZbjmmmvw0UcfMcH0wPntzK+//hrFxcU4efIkli1bhsLCQlx44YUzZvKVIAiUlZUhIiIC0dHRDnvN8SkkQqEQISEhDheDM0H8URSFJ554Al1dXfjXv/41a6rWLLMaVgCysDgagiAwd+5cHDt2DDExMVi0aBH27duHjIwMZy/NIqqqqrBr1y4UFRUxdifG0Ov1OH78OEpKSvDDDz9g4cKFKCwsxMqVK9128tVgMKC8vBxRUVFOm3QmSRJyuRz9/f1MColQKERoaKjdBVlbWxuGhoaQnZ3t1uLvueeeQ319PT744IMZW6VmYRkHKwBZWBzNL7/8gr179+KLL74AgAnZxe6GRqPBwMAAoqKiTP4dg8GAH3/8EcXFxTh+/DhycnJQWFiIVatWuc3kq16vR3l5OWJiYhAREeHs5QA4L2YGBwfR39/PpJAIhUKEhYXZvKo1U8Tfyy+/jLNnz2Lfvn0zpirNwmICRgUge/vDwmJHuru7x/SJxcTE4OTJk05ckXV4e3ubJf4AgM/nY+XKlVi5ciUIgsCJEydQXFyMxx9/HKmpqSgsLMTatWtddvKV9jiMi4uDSCRy9nIYOBwOQkJCEBISAoqioFAoIBaL0dLSAh8fH4hEIpukkLS3t88I8fePf/wDJ0+eRFFRESv+WFjACkAWFrtirMLu7CZ+Z8Lj8bBixQqsWLECJEnizJkzKCoqwnPPPYfExERs3LgR69atQ2BgoLOXCuB8TFhZWRkSExMRHh7u7OVMCofDQVBQEIKCgpCSksKkkLS3tzMpJAKBgEm5MJX29nYMDg66vfh755138M0332D//v1m/w1YWGYqrABkYbEjMTEx6OzsZP67q6vL7AraTIXL5WLRokVYtGgRnn76aVRUVKC4uBj5+fmIjIxEQUEBLr/8coSEhDhlfTqdDufOnUNycjIEAoFT1mAJHA4HAQEBCAgIQHJyMpNCUlZWZlYKyUwQfwDw/vvv4/Dhwzh48KDb9p+ysNgDtgeQhcWOGAwGzJ07F19//TWio6OxaNEi/Oc//0FmZqazl+ay0Lm6xcXFOHz4MEJDQ1FQUID169c7TIhptVqUlZUhJSUFYWFhDnlNR6BWqyGRSCAWi6dMIZkp4u+jjz7Cvn37cPjwYfj6+jp7OSwszoIdAmFhcQZHjx7FHXfcAYIgcO211+LBBx909pLcBoqi0NjYiOLiYnz66afw8fFBQUEBNmzYAJFIZJftdI1Gg7KyMqSmpjqt+ugItFotIwYNBgOTQiKVSmeE+CsqKsK7776LI0eOwN/f39nLYWFxJqwAZGFhcV8oikJraytKSkpw4MAB8Hg8bNy4EQUFBYiKirKJGFSr1SgvL0daWhqCg4OtX7SbQKeQtLe3Q6PRMNPOrphCYgoHDx7E66+/jiNHjiAoKMimz11UVIS9e/eitrYWp06dwsKFC5l/e+qpp/DOO++Ax+PhlVdewWWXXQYAOHPmDHbv3g21Wo38/Hy8/PLLbvl3ZXFbWAHIwsIyM6AoCl1dXSgpKcH+/fthMBiwfv16FBQUID4+3qKLq0qlQkVFBdLT020uGtyBjo4ODAwMICMjAwMDAxCLxVAqlUwKSVBQkFuIlqNHj+KFF17AkSNHEBoaavPnr62tBZfLxZ49e/D8888zArCmpgY7duzAqVOn0NPTg9WrV6OhoQE8Hg+LFy/Gyy+/jKVLlyI/Px+33XYb1q1bZ/O1sbBMAmsDw8LCMjPgcDiIjY3FHXfcgdtvvx19fX0oLS3FrbfeipGREVx++eUoKChASkqKSaJFqVSioqICmZmZLjOB7Eho8ZeTkwMul4uIiAhEREQwKSRdXV2ora11agqJKRw7dgzPPvssjh49ahfxBwDp6elGf37w4EFs374dXl5eSExMREpKCk6dOoWEhAQoFAosW7YMAHD11VfjwIEDrABkcTqsAGRhYXFrOBwOIiMjcfPNN+Pmm2+GRCLBgQMHcP/990MqlSI/Px8FBQVIS0szKlpkMhkaGhqQlZWFgIAAJ7wD5zJe/I1m9NQwnULS19eH+vp6h6aQmMK3336Lv/71rzh69KhTpra7u7uxdOlS5r9jYmLQ3d0NDw8PxMTETPg5C4uzYQUgCwvLjCI8PBw33HADbrjhBgwMDODQoUPYu3cvuru7sXbtWmzatAmZmZngcrk4deoUbrrpJnz55Zes+JtGxHG5XISFhSEsLIxJIRGLxWhsbLRrCokp/PDDD3j44Ydx5MgRCIVCq59v9erV6Ovrm/DzJ554AgUFBUZ/ZzLPT9YLlMVVYQUgCwvLjCU0NBS7d+/G7t27MTQ0hMOHD+OZZ55Bc3MzFi5ciG+//RYfffTRjLJ6MZXOzk6Txd94pkshEQqFCA8Pd0jW7i+//IL7778fhw8ftllG81dffWX270zm+RkTE4Ourq4JP2dhcTbOr9uzsLCwOICgoCD8/ve/R2lpKV555RV88803yM3NxZ49e/DnP/8ZJ06cAEEQzl6mQ+js7IRUKrVI/I2HTiGZM2cOlixZgqSkJKhUKpw5cwbnzp1Dd3c3dDqdjVY+ltOnT+Ouu+7CwYMHx2yzOoONGzfi448/hlarRWtrKxobG7F48WJERkYiICAAJ06cAEVReP/99yetIrKwOBJ2CpiFhWVW8fPPP+OWW27B/v37ER8fD7VajS+++AIlJSU4d+4cLrzwQhQWFmLZsmUOqWA5Glr85ebm2r13j04hkUgkZqWQmEJZWRn++Mc/4sCBA0hKSrLBak1j//79uPXWWyGRSBAcHIy8vDx88cUXAM5vEb/77rvg8/l46aWXmEGP06dPMzYw69atw6uvvspuA7M4EtYGhoWFZXoSEhIQEBAAHo8HPp+P06dPY2BgANu2bUNbWxsSEhLwySefuKVJ8vfff4+77roLBw4cMFox0mq1+Oqrr1BcXIxTp05h+fLlKCwsxAUXXAAPDw8nrNi2OFL8jUej0UAsFk+bQmIKVVVVuP7661FUVITU1FQ7rJaFZUbBCkAWFpbpSUhIwOnTp8dMUt53330IDQ3FAw88gKeffhpyuRzPPPOME1dpPhRF4ZZbbsFDDz1kUq+YXq/H8ePHUVxcjB9//BGLFi1CYWEhVq5cCU9PTwes2LY4U/yNZ7IUEj8/v2l/t7a2Fn/4wx/w8ccfIyMjwwGrZWFxe1gByMLCMj3GBGBqaiqOHz+OyMhI9Pb2YuXKlaivr3fiKh2LwWDAjz/+iKKiInz33XfIzc1FYWEhVq1aBW9vb2cvb1pcSfyNh04hEYvF0Gg0EAgEEIlERlNIGhoacPXVV+PDDz9ETk6Ok1bMwuJ2sAKQhYVlehITExmj3z179uDGG29EcHAwBgcHmceEhIRALpc7b5FOhCAI/PLLLyguLsbXX3+N9PR0FBQUYO3atSZVsBxNV1cXJBIJcnJynGLRYg4GgwEymQz9/f2Qy+UoKirCpk2bsHLlSnR0dGDHjh147733MH/+fGcvlYXFnWAFIAsLy/T09PQgKioKYrEYa9aswauvvoqNGzeyAtAIJEni9OnTKCoqwpdffonk5GRs3LgR69b9f3t3H1Nl3cdx/HN4kOWgGDYMRZdBgwQKaYlaaA9QPsA5IIpgCwTnU07+0ZEbzqDFGK6HP8w2bTaxFW4c4BBZYbExZ61QF2zgBiwo5EGRMCsTTM65/3Cd+y65y1I5nHO9X3+x6/zkfMcYvned67p+yybFcwXdKf7+bGRkRDU1NaqpqVFbW5scDocKCgq0ceNGj7w5B7iDCEAA/0xRUZH8/f31zjvvGPoj4Jtht9vV0tIiq9WqTz75RDNmzJDFYtGKFSsUGBg44fO4c/z9r76+PmVkZCgnJ0ft7e364osvFB8fr5UrV+qZZ55xy+sxgQlGAAL4a5cvX5bdbldAQIAuX76spKQk7d69Ww0NDZo2bZrzJpDh4WHt2bPH1eNOWg6HQ21tbbJarTp69KiCgoKUmpqqFStWTMg2ZZ4Sf+fOndOqVav0xhtv6Mknn5T034/gq6ur1dDQoPXr1ys/P9+1gwKTGwEI4K91dXUpLS1N0vXrsdauXavCwkL98MMPysjIUE9Pj2bPnq3KykoFBQW5eFr34HA41NHRIavVqrq6Ok2dOlWpqalKSUlRcHDwbX8eXG9vrwYHB/XII4+4dfwNDg4qPT1dZWVlSkxMHHfN77uQ3HPPPRM8HeBWCEAAcCWHw6Guri5VVVXJZrPJ19dXZrNZFotFISEhtxyDnhJ/Q0NDSk9P1yuvvOJ8mDKAf40ABIDJwuFwqLe3V1arVTabTdeuXVNycrLS0tI0a9asfxyDnhJ/Fy9e1MqVK1VYWCiz2ezqcQBPQAACwGTkcDg0MDCg6upq1dTU6JdfflFycrIsFovCwsL+Ngb7+vp0/vx5t4+/S5cuKT09Xdu3b1d6erqrxwE8BQEIAO5gcHBQNptNVVVVGh4e1vLly2U2mxUZGXlDDP6+rd28efPcOv5+/vlnrVq1Slu3blVmZqarxwE8CQEIAO5meHhYtbW1qqqqUn9/v5577jmlpqYqKipKe/fulc1m00cffTQpH0J9sy5fvqyMjAzl5uYqOzvb1eMAnoYABAB3dunSJdXV1amqqkptbW3y8/PTm2++qQULFky6Ld5u1pUrV7RmzRplZWVp/fr1rh4H8EQEIAB4gkOHDum9997TunXr9OGHH6q9vV1PP/20LBaLHnvsMbeJwZGREa1du1YWi0WbN2++7Y/EASDp/wSge/yVAIBx5OXlKTg4WNHR0c5jw8PDSkpK0oMPPqikpKQ/bFlXWlqq8PBwRUREqL6+3hUj37Ly8nJVVFSorq5OL7zwgiorK/X1119ryZIlOnjwoBYsWKAdO3boxIkTGhsbc/W4/9fVq1eVk5OjZcuWEX+AC3AGEIDbOn78uPz9/ZWdna3W1lZJUkFBgYKCgpy7lly8eFFlZWU6c+aMsrKy1NTUpP7+fiUmJqqjo8OtbpwoLy/X+++/L5vNpqlTp467ZnR0VJ999pmsVqtOnjypRYsWKS0tTY8//rh8fX0neOLx/fbbb8rNzdXChQu1Y8cO4g+4szgDCMCzLF68+IYdSWpra5WTkyNJysnJkc1mcx7PzMyUn5+f5syZo/DwcDU1NU30yLfEz8/vL+Pv9zXJyck6dOiQmpubtXr1atlsNi1atEhbt27VsWPHdPXq1Qmc+o+uXbumDRs2KC4ujvgDXIgABOBRzp8/r5CQEElSSEiIBgcHJV1/Vt6sWbOc60JDQ9XX1+eSGf+tzMzMv4y/P/P19dWzzz6rAwcOqKWlRdnZ2Tp27JieeOIJbdy4UUePHtXIyMgdnPiPxsbG9OKLLyoyMlKFhYXEH+BCBCAAQxjvchcjBYiPj4+eeuopvf3222ppadGmTZt04sQJLVmyRLm5ubLZbPr111/v2PuPjY0pPz9fM2fOVFFR0W392VdWVioqKkpeXl46deqU8/h3332nu+66S7GxsYqNjdXmzZudr50+fVoxMTEKDw9Xfn7+uL8fgCfzcfUAAHA7TZ8+XQMDAwoJCdHAwICCg4MlXT/jd/bsWee63t5ezZgxw1VjupS3t7cSEhKUkJAgu92ukydPqrKyUmVlZQoLC5PFYtHSpUsVEBBwW97Pbrdr+/btCgwMVGlp6W2/Szk6OlrV1dXatGnTDa+FhYWpubn5huNbtmzRgQMHtGDBAi1fvlyffvop+w7DUDgDCMCjmM1mlZeXS7p+04TFYnEeP3LkiEZHR9Xd3a3Ozk7Nnz/flaNOCl5eXoqPj9drr72mb775Rrt27VJ7e7uWLl2qNWvW6IMPPtCPP/74r7+/3W7Xzp075evrq9dff/2OPKLmoYceUkRExE2vHxgY0E8//aSFCxfKZDIpOzvbea0oYBScAQTgtrKystTY2KihoSGFhoaquLhYO3fuVEZGhg4ePKjZs2ersrJSkhQVFaWMjAzNnTtXPj4+2rdvn1vdATwRvLy8FBcXp7i4OJWUlKi1tVVWq1Vms1n33nuvUlNTtWLFCk2bNu2mvp/dbtfLL7+s0dFR7d+/3yXPJ+zu7ta8efN0991369VXX1VCQoL6+voUGhrqXOOO14MCt4oABOC2Kioqxj3e0NAw7vHCwkIVFhbeyZE8hslkUkxMjGJiYlRUVKT29nZZrVatXr1a/v7+MpvNSklJUXBw8LjX8zkcDpWUlGhoaEjvvvvuLcdfYmKizp07d8PxkpIS51nePwsJCVFPT4+mTZum06dPKzU1VW1tbYa/HhSQCEAAwN8wmUyKjIzUrl27VFhYqK6uLlmtVj3//POaMmWKUlJSlJqaqvvuu08mk0kOh0N79uzR999/r8OHD9+WM62ff/75P/43fn5+8vPzkyQ9+uijCgsLU0dHh0JDQ9Xb2+tcZ+TrQWFcBCAA4KaZTCaFhYXppZdeUkFBgXp6elRVVaXc3FzZ7XYlJydreHhYXV1dqqiokI+P6/6buXDhgoKCguTt7a2uri51dnbqgQceUFBQkAICAvTVV18pPj5ehw8f1rZt21w2J+AK7AQCALhlDodDAwMDqqioUEVFhb788ktNmTJlQt67pqZG27Zt04ULFxQYGKjY2FjV19erqqpKu3fvlo+Pj7y9vVVcXKyUlBRJ0qlTp7Ru3TpduXJFy5Yt0969e/kYGJ5q3F9sAhAAAMBzsRUcAAAACEAAAADDIQABAAAMhgAEABfJy8tTcHCwoqOjnceKioo0c+ZM5/61H3/8sfO10tJShYeHKyIiQvX19a4YGYCH4CYQAHCR48ePy9/fX9nZ2WptbZV0PQD9/f21Y8eOP6w9c+aMsrKy1NTUpP7+fiUmJqqjo4PdTAD8HW4CAYDJZPHixQoKCrqptbW1tcrMzJSfn5/mzJmj8PBwNTU13eEJAXgqAhAAJpm33npLDz/8sPLy8nTx4kVJUl9fn2bNmuVcw/61AG4FAQgAk8iWLVv07bffqrm5WSEhIdq+fbsksX8tgNuKAASASWT69Ony9vaWl5eXNmzY4PyYNzQ0VGfPnnWuY/9aALeCAASASWRgYMD5dU1NjfMOYbPZrCNHjmh0dFTd3d3q7OzU/PnzXTUmADfnul26AcDgsrKy1NjYqKGhIYWGhqq4uFiNjY1qbm6WyWTS/fffr/3790uSoqKilJGRoblz58rHx0f79u3jDmAA/xqPgQEAAPBcPAYGAAAABCAAAIDhEIAAAAAGQwACAAAYDAEIAABgMAQgAACAwRCAAAAABkMAAgAAGAwBCAAAYDAEIAAAgMEQgAAAAAZDAAIAABgMAQgAAGAwBCAAAIDBEIAAAAAGQwACAAAYDAEIAABgMAQgAACAwRCAAAAABkMAAgAAGAwBCAAAYDAEIAAAgMEQgAAAAAZDAAIAABgMAQgAAGAwBCAAAIDB+PzN66YJmQIAAAAThjOAAAAABkMAAgAAGAwBCAAAYDAEIAAAgMEQgAAAAAZDAAIAABjMfwCdrDd6Uu3BxwAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "corner_4cam_positions = all_cam_positions[(0,4,5,10),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [], + "source": [ + "corner_4cam_directions = [[-1, +1.9, -1],\n", + " [+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [+1, -1.9, -1],\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner_4cam_positions\n", + "camera_directions = corner_4cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0])#, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({2: 546, 4: 462, 3: 264})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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m27Vma0u9qtVusrU/wEHDACG8vr6W8/lcTqdTeXl5aV0cEtOWAPZx66BhARYAAMBCtwIse7AIyR4CbtE2YEyefSALe7AIyR4CbtE2YEyefSALARYh2dTLLdoGjMmzz1fsPSQSe7AAAEjteDyWy+VSpmkyw8lubu3BMoMFAEBqZjiJRIAFAEBqtc6GhBpkEQQAAKhEgAUAAFCJAAs24LwWAIAxCbCSMXBvZ0ndv5/Xcj6fdyjZctoRwH6i97nRywfZCLCSiT5w79mSuj+dTmWaprDZjLQjgP1E73OXlE8wFod7EZcsgslIQ9rOkrqPns1IOwLYT/Q+d0n53oOxUkro99wI3IvA5nm+++fp6WkGtnO9Xudpmubr9dq6KPCtEdrrCNdIP/Zor56JONyL9kopb/MnMdPh13+7z/Pz8/z29rZdtAeDcxI9r6+v5Xw+l9PpVF5eXloX50sjtNcRrpF+aK+wr8Ph8HOe5+ePf26JIAQSfRkJ28u05GOE9prpGjMF52wjU3uFnpnBAgjEIJm1zF4A7OvWDJYsgqwmew3U954gRXDFUtGzlwKMQoDFatHTztI3AT78rsfg3HNOFNoiSwwfYHlg1vO19H7aWX0CfOif53wb3knLaYvb6bE9Dp/kItOG8miin/UUiXZWn83c0D/P+Ta8k5bTFrfTY3scPsAa5YGxcb6tUdrZngT40D/P+Ta8k5bTFrfTY3uURXAQsksBAEA9sggOzn4pAIB4etyDNDoB1iB6zC61lo4MAIhCAo3+CLAYjo4MAPbl4+ZtVhn1Z/gkF4ynx82Un5HYBIAoeswUV4sEGv0RYDGcUToyLzOA2Eb6EDbKx00oxRJB6JYlB7SWYUlQhjLSr5GWrNsLzkgEWNApL7PYog3styhPhsHjFmUc4d5Shw9h0CdLBAEa2GIJ5yPLjbYoT4YlQVuU8ZG63GLJmOXCcY2yZB1GI8ACuhV5f0O0gf0W5ckweNyijI/U5UiBbuTnE+ARh3me7/7Lz8/P89vb24bFgf4ZVOzneDyWy+VSpmkKP9CvQdvKb6R7ONrzCfTncDj8nOf5+eOfm8GCnVmus5+oX+63kmHGiK+NdA9Hez5bGyl4h9YkuYCd2dT8tZob8iX6gLhqP5+SeXwtQ9IZ6IUACzb28aU/0qB/zYDHIABYY03fMVJQ5uMe7EeABRsbOWBYc+0GAWN7ZMA70mCZP63pO0bqnz9+3PO8wIbmeb775+npaQaWuV6v8zRN8/V6bV2U3Y187SPY4v5O0zSXUuZpmnb9f2/Rhvs28v3d4nmB0ZRS3uZPYiYBFsC/WTvg2mKgFn3wFy2giRbw7aH2NUdvc9TjXsPjBFgAd1g7oN5iID7a4D6i6NdYu42s/fei1xPAFm4FWNK0A/ybtamjt0g5HT2N9QgpxaNfY+02svbfc/wEwN8cNAxJOdPkb+oC2qr9DHqmf1EPEJuDhqEzvhj/TV1AW7Vn+jzTv6gHyEmABUm1XD4W7atq9KV0wDKe6V/UA+RkiSCw2PF4LJfLpUzT5Ksq0LVoH5SAOCwRBKrxVRUYhWV6wFICLGCx6JnVAGrxQQlY6n+0LgA84vX1tRyPx/L6+tq6KN/KVFYAfnn/oGR54P68N8lKgMWmtu4c35dunM/nTf79mjKVFYD+ZAtY9nhvZqsTcrBEkE1tvXY909KNTGUFoD/Z9pPt8d7MVifkIMBiU1t3jpn2AmUqKwD9yfahb4/3ZrY6IQdLBNmUtevrWLJAdlnacJZyQg3eyX9SJ2xBgMUfDDjas19rLD0+c1nacJZyLtVjm+Jz7jXEY4kgf7AeuT1LFsbS4zOXpQ1nKedSPbYpPudex+FQav4yz/PdP09PTzP9u16v8zRN8/V6bV2Urqnn/USv6+jlI5/IbSpy2TL6qj7V9b6maZpLKfM0Ta2Lwk5KKW/zJzGTAAsqWPMS0xHvR11DHJ7H/ayta4HZOuptPLcCLEsEoYI1SzR6XZoUkbqGODyP+1lb15YdriNbMO8kuSCE7Jt0T6dTmaZp0UssW+aizPcoW11DzzI/j9n6wbV1veadBvzt8Gt26z7Pz8/z29vbhsVhVMfjsVwulzJNk68/QblHwOj0g3lIOMEeDofDz3menz/+uSWChGDJSHzuETA6/WAeljnSkhksAAC6YgaLPZjBAgBgCBJO0JIkFwAAAJUIsAAAACoRYAEAAFQiwAIAAKhEgAXAJjIcypqhjADkIsACCKK3wf77OTTn87l1UW7KUMYlemtDABlJ0w4QRG8HY2Y4lDVDGZforQ0BZGQGCxhK5C/8p9OpTNPUzWD//RyayId8ZijjElHbUOTnDqA2ARYkY6DymMhLwnob7LO/qG0o8nOXhb4f8hBgkYIXy98iDFQy34+oX/ihZ5mfuyj9XYS+H7iPPVikYF/B3yLsGcl8P96/8AP7yfzcRenvIvT9kby+vpbz+VxOp1O4GVsQYJHCSC+W714aEQYqI90PYGxR+ruv+v4Rg40ogS98xhLBxKIsW9hDq30FLeo4wzKQqPs8AGrL0N+1em+0HIdkXna6xkhjvh6YwUrM15vttajjKF9LAcih1Xuj5TgkwmqOPRnz5WIGK7Hevt5E/DrToo7Xfi2NWH8A3G9tP95qlq23cUhk6jqXwzzPd//l5+fn+e3tbcPiMLLj8Vgul0uZpsnXmRXUH0Bu+vHHjbgfjXYOh8PPeZ6fP/65JYKEYWncY9QfQG768cdZSkcEZrAAWK3Xr8W9Xhf0zrPLnm7NYNmDBZBExH12tbOXrb3G2nUTNZtnxDYAkWTI+kj/BFhA11oPSGv+/oiD/tobr9deY+26ibqhvOZ1tn42ALo1z/PdP09PTzNAJtM0zaWUeZqmh/6d6/U6T9M0X6/XJr//kTJksvYaR6ibea57nWvaZs3fP8o9A/pVSnmbP4mZBFjAJqIMnmqVY22gFKUe4KM1bbPmB4Oa/9Zank/gEbcCLFkEgU1EyeRU6zDKtdm9RjsMkzzWtM2aWe4iZMyL0k8BfbEHCxoYYe9D1D0sa9k4DXWfgwjPVG/91C0jvHMgEmnaoQGHSQKwF+8c2IY07RDIKF9NaStCyvNRvpyvuc5R6ob2vHNgZ59tzLr1I8kFLdXajDzCpuYRrrFXrbPEPfL/bf1v1VT7GVlznTJMMhJtlB4VWQTJrtZgJOqAr6aM17j05dtrwB1h0D1CKu7az8ia64wQTG+l1fMZtb19JWOZ12h9ZAZsQYBFer0OqLeQ8RqXvnx7Dbgz3ruMeqvnaNfT6vmM9jzfI2OZ12h9ZAZsQYAFhGYGC/phBut+GcvckvoiklsBliyCAAAAC8kiCAAAsDEBFl2Q7hgA+uCdTnb/aF0AqOF8PpfL5VJKKQ5RBIDEvNPJToBFF94PT3SIIgDk5p1OdpJcAAAALCTJBQAAwMYEWAAAAJUIsGhChiBYJ+qzE7VcS0W9jqjlgiw8Q+xJgEUT7xmCzudz66IwmOwv2ajPTtRyLRX1OqKW617Znzvyy/4MkYssgjQhQxCtZE//G/XZiVqupaJeR9Ry3Sv7c0d+2Z8hcpFFEDb2+vpazudzOZ1O5eXlpXVxhud+wP48d7G4H1CHLILQSItlCZbj3Pby8lJ+/PhhUAE78tzd1qK/tlwOtmWJIGysxbIEy3EAcmjRX1suB9syg9WA2YWxtPhyezqdyjRNXp4AwbXor80ojssYdB8CrAZMzeeRtSPy8gTIIWt/nfX9ODpj0H1YItiAqfk8LLUDgD95P+ZkDLoPAVYD71+riE9HBAB/8n7MyRh0H9K0AwAALCRNOwAAwMYEWAyp5uZcG30B6In3GjxGgMWQambRkZGHvUUd/EQt1xIRryFimehb7feaNsxw5nm+++fp6WmGHlyv13mapvl6vYb6t9hP5vs2TdNcSpmnaWpdlN9ELdcSEa8hYpnulfk5G1nt+5a5DcNXSilv8ycxkyyCDKlmFh0ZeXLKnGI4avauqOVaIuI1RCzTvTI/ZyOr/V7L3IZhDVkEgSG9vr6W8/lcTqdTugM+IQvPGdCzW1kEBVgAAAALSdMOAACwMQEWdEKWJoDc9OPQB0kuoBM2kwPkph+HPpjBgh3s8VXydDqVaZpkaQJIao9+3CwZbE+SC9jB8Xgsl8ulTNPkqyQAzXgfQT23klxYIgg7cAYIABF4H8H2hlsiaGp8O+r2tvdDG50Dw1K9PFeRriNSWdbq4Rpow/voe56v/XRb1/M83/3z9PQ0ZzdN01xKmadpal2U7qjbv12v13mapvl6vbYuCitFuYe1nqs111OzDiL1Dz3UaZT6jPKcsJ57+Kcoz9cIstd1KeVt/iRmGi7A0pFsR93+LXuHEdGS9lWjLUa5hy0H5DXrIFL/0EOdRqnPR69n6XVEue6eROnrItHO9pO9rgVYsKPsHUZESwYBNQYMvd3D1jNYPVKnj1/P0mdVMFBfb20S9nQrwJJFEEjh9fW1nM/ncjqdvt07sOTvAu0sfVY920Akt7IICrDoipcvAOTj/U1GtwKs4bII0rfz+Vwul0s5n8+tiwKstDSrVLdZqGAg3t/0RIBFV06nU5mmqevzPQwmY2oVFERpDzXLsXSgVXNg1lt9Clb7MMJ9GeH9zUA+25h160eSC2ivx03erTdZt8g6WOs+RmkPLTMO9phOvlX7yJ4gpnVfspUo7RL4XZFFEGJZOxDocQDRevDQYlBZ6z5GaQ9RyvGoKNfRqn1kP+KgdV+ylUfuS5Q2DT26FWBJcgGNHI/HcrlcyjRN5cePH62L01Trzc2tfz/0pOXz5Fn+k3cNbEcWQQjGQACArXnXwHZkEWxohM2pLPfy8lJ+/Pjx6QtPmwGghq/eNWC8sQ0B1g6kHmUpbQaAexkks5bxxjb+0boAI3hPOSr1KPfSZgC41/sguZRinxWLGG9swx4sAIDE7LOCNm7twTKDBQCQ2Ps+KyAGe7AAAAAqEWABTWTalB2lrFHKsVS0ckcrz72ilDtKOb6TpZxAhz47ffjWz9PT056HI0Nq1+t1nqZpvl6vrYsS0jRNcyllnqapdVG+FaWsUcqxVLRyRyvPvaKUO0o5vpOlnC15T8FjSilv8ycxkwCL3+hs64n0co94XyOW6ZYoZY1SjqWilTtaee4VpdxRyvGdqOWMVK5I76keRLq37EOAVUnvD4/Otp5IbcV9BYghUn8c6T3Vg0j3dmvazi+3AixZBBfq/awJ5yHUEymr0z33VZpfgMfc049Ges9Gek/1INK93Vrv4+FHOQdrIYNQenU8HsvlcinTNOksAVbQjzIK4+FfnINVia899GqkL28AW9CPMgrj4a9J0w6deDQl8XtnOfKXKIBHPNqPSi0PfTCDBZ2wHhogN/049MEMFqn52ve30+lUpmmyNAUgKf3477zjyUqSC1KzoRgA+uQdT3S3klyYwSI1X/v6kOUrZZRyRinHElHKHKUcS0Qpc5RyfCVDGbmfdzxpfXY41q0fBw1vy6FtjCrL4YxRyhmlHEtEKXOUciwRpcxRyvGVDGWErRlP7qc4aDg+m1uJauvzLrKkNo5SzijlWCJKmaOUY4koZY5Sjq/sUUbn/xCd8WR79mAF8minrdNnK9bBA/yiP2RrxoN5OGg4gUcPbfPFgq1k+HINsAf9IVt7dDznEOD2BFgd0emzFZ01wC/6Q7ZmPJefJYIAAAALSdMOAACwMQEWmxrtTJLRrheAfoz0DhvpWtmfAItNvW/UPJ/PrYuyiz2v18sBGM1o/d7e1zvSO3uka2V/Aiw2Ndop7Hte70gvh1aDqhq/d8m/sffv20KLa1Bvy/+NrHU2Ur9Xyv7XO9I7e6RrpYHPTh++9fP09LTv8cgMyQnk9xmpnqZpmksp8zRN6X7vkn9j79+3hRbXoN6W/xtZ62ykfm+ex7vetdQTrZRS3uZPYiYBFuG0HugQT6uXZ43fu+Tf2Pv3baHFNai35f9GD3UG74wbaOVWgCVNO+E4gRwAuJdxA63cStMuwAIAAFjIOVhANa0TAnxl743+WbVIJNED9Xa/Xp7FyGUDgvps3eCtH3uwgHmOvd59z43+LfegPPq7WySSaL1np8bv37veRmljvfQpwFiKJBdALa0Hyl/Zc6N/y4HX3gP3FsFJbS2CRG1sv6QbW4lcNqAtARarZXi5ZCgj/ck8u9BC6zK3/v1raGOMJkO7y1BG9nErwJLkgm8dj8dyuVzKNE3lx48frYvzqQxlBAC+luF9nqGM7ONWkot/tCgMubyfch75tPMMZQQAvpbhfZ6hjLRlBusOzlcAAIA/jTxONoP1gPP5XC6XSymlmAoGAIB/MU7+k3Ow7nA6nco0TaaCKaU4EwWAsXjv8RXj5D8JsO7w8vJSfvz4Mdy0Z2QtO/v3LzXn83n3301bBhmMTPsfV+v3nrYXm3HynwRYpNSys4/ypcYLZ3+tBxn3at02Wv/+JSKUNUIZ7pGl/fckStto/d7T9kjns9ztt36cg0UUzqBof2jriLK0u9Zto/XvXyJCWSOU4R5Z2n9PsrSNrWl7RFVunIMlyQUpvU9Hj0ya2P1laXet20br379EhLJGKMM9srT/nmRpG1vT9shGmnYAAICFbqVptwcLWCXK3gCArejngDUEWMAqNh0DvdPPbUPgSu/swWIII58yvhV7A4De6ee24WBaemcGiyHc8xXSF7VlnHsB9E4/t8y979HWad9ha2awGMI9XyF9UQOA9e59j8oKSO/MYDGEe75C7v1FzYxZXhnuXYYykuM+ZSgjn9v73pmZgn/57HCsWz8OGoZ67j1A0gGL8WQ4/LN1GbO029blbH2f7pGhjKO5t926d7Ct4qBhiOXezdOWLsaTYeN76zJmabety9n6Pt0jQxlHc2+7de+gDQcNQ3AyIJJRlnabpZzw77RbiOHWQcMCLAAAgIVuBViSXAAAAFQiwILOyPgFkIt+u3/u8VgEWAPykPftnkOV19J2gFFt2f9t2W8Tg3s8FgHWgDzkfdvyHBJt53uCUDLSbr+3Zf/X+vwo9397re8xO/ssd/utH+dg9aH1uS+967l+e762WlqcO/PofVny/+/5u2rKUket6sd5Sd/ruf9z/2GdcuMcLAEWqUV84WUcYFNPi3vxaJtb8v/v+btqylJHrepHHxJHi3sR8f5HLBN8JMCiSxG/umUcYJNbltmZGv//WlnqyKAS/fkv6oEMbgVYzsEiNYct/qIeAPqgP/9FPZCBc7Do0svLS/nx48fwnW+WerhnI/Uom62XXOcodfJO3XxN/fyut34lS3++NfVAap9Na936sUQQ8vtuCdKWS5TuWfIxyrKQvfb0ZFySt+eeMPWTX4R+pWW/CrRT7MEC5vn7gcaWA5F7BhmjDET22tOTManEnnvC1E9+EfqVlv0q0I4AC5jn2ZfW0WScodmT+qEG/SqM6VaAJckFAADAQpJcAN3ItGEdWM+zDmT0j9YFAFjqfD6Xy+VSSinlx48fjUsDbMWzDmTU3QyWr13Qv9PpVKZpKqfTqXVRgA3t8awbN0BcWZ/P7gKs969d5/O5dVFgWFt3iM5HuS3ry2h07tvn9njWjRsgrqzPZ3dLBN+/cvmyDe1Y1tNO5Lp/fX0t5/O5nE6n3YPjlr/7HpHvW++MGyCurM9ndwHW+9cuoJ2sHWIPItd9yyAiegAT+b71zrgB4sr6fErTDsAuzGBBHp4Z+J407bCByPsmIpeNMbXcO2ffHhFF7qez7n2BCLpbIgh7irzsKHLZAIjdT1u2CusJsOABkV9AkcsGQOx+OuveF4jAHiygO/YOQB6eVyCrW3uwzGAB3Ym87Ab4necV6I0kF0B3TqdTmaYp5LKbPUTeON+qbOokrtGfV6A/lggCdOZ4PJbL5VKmaQo3I9CqbOoEgNqkaacbo3/the9EnhFoVTZ1Anl575ONGSzS8bU3LpvVgaz0X3H1+N7X3vogycXAenuII6e1HZ3N6kBW+q+4enzva299E2ANoLeH2NkccfX4EgTGoP+Kq8f3vvbWN0sEB9DbDBYAALQmycXA3r/8CK5gbHtvFI++MV19ALAFSwQBBrH3cuHoy5PVBwBbEGABDGLvNf/R9xioDwC2YA8W0DV7ECEWzyTQC3uwYFCj7/t4X5Z1Pp9bFyWFe9vLCO1KXWzDM6nNQO8sEYTOjb7vw7KsZe5tLyO0K3WxDc+kNgO9E2BB50YfzPR4fsqW7m0vI7QrdbENz2T8NmMZJzzGHix4kBcRAD05Ho/lcrmUaZqGD4bhK7f2YJnBggdZ6gFAT6LPsEF0klzAg06nU5mmyYsIIBGJJm57X8ZpVQasI8CCB3kR3WYAA0QlmyGwFUsEgc1YPglEZRkcsBUzWMBmRlo+abaO7EZrw1YfAFsxgwVsZqR0zGbryE4bBqjDDBbhjPYVlT7cO1unfbO3e9vcSDPO9EW/SjQCLMKx8Zhaar50v/u37l1upH2zt3vb3D1tuNYzZUBMTfpVorFEkHBsPKaWmkueav1b2jd7q9nmaj0HliNSk36VaARYCby+vpbz+VxOp9MQm3FH2rfDtmq+dGv9W9o3e6vZ5mo9BwbE1DRqvzra+DCTwzzPd//l5+fn+e3tbcPi8Jnj8Vgul0uZpmnIDgQAgN8ZH7Z3OBx+zvP8/PHP7cFKYKuNx9bA98l9BchFv92vLe+txDRxCbAS2OqsDptC+9TyvhokAFEs7Y9a9l+Z3sf6+WW2vLfOcgtsnue7f56enmZ+uV6v8zRN8/V6bV2U1Xq4hr1kqquWZZ2maS6lzNM03fX3M9XrntQL99JWblvaHy39+zVluo9r6inT9dXW27X3dj2PKqW8zZ/ETAKslVp2xDxmTefwyP0eqTNaeq2eo8+pF+6lrdy2tD9a8vd76NfXXsPe71BicS9/J8CqrIfOdVR7f33L3hlt2dZr/ts9PZM9XQvbitBWRnyOs/fr87zvNWS5r3zPvfydAAv+Ze/OIXtnlGUgUauc2e8X7K1mH5Glv+mhn+jhGqA1ARawSoSX8D1lqFXOLAM8iGLPGawtl/0BLHUrwHIOFtDEkgMS9zzrw8GNENfSvsA5QcCWbp2D9Y8WhQF4T11bSvl24PN+xsceZ328p70F4lnaF+zZd5CHD2lszTlYnYtwXkWEMhDPkgMSnfUBlLK8L+il79j6PTraezrKuWOj1ftQPls3eOvHHqx8IuwniVCGPW295t+eAoCxbP0e9Z7e5//9aLR671GR5GJMEdLnjhYQrO0w760nHTKR9Ph893hN5HZvm/Se3l7Nd7B6z0+AxcMM7O+ztsO8t351yOPa896PHPAvuaaI94Rx9fg8RuM55N8JsHiYTmVbLevXvc1hz8HTyAH/kmuKeE9oS18O4xBgATcZuOVgtiQe94SP9KeP09bJQoBF13TGj1F/bC1KG4tSDvqljT1OkEoWtwIsadrpQpSUq1n1ksq4Fqlz64vyjEYpR088L7/Tnz5uyTEeEJGDhumCwyT70/IgyCWHIHOfKM9olHL0pOXz4sDYPjnwnewEWHRBZ9yfloO2EQbhew9Mozyje5djhACg5fPiYwgQkQALCKnloC1KMLAlA9N9jFDPLZ+XET6GAPkIsICQRghyWjIw3Yd63pZ+Aojo8CsBxn2en5/nt7e3DYsDAAAQ3+Fw+DnP8/PHP5dFEAAAoBIBFkAiPabErn1N6giAluzBAkikx6QJta9JHQHQkhks2Jkv0TyixwM4a1+TOoI/effAfiS5gJ0dj8dyuVzKNE2+RAOwC+8eqC90kgtfVRiJL9E5Ze+nspe/F5nvQ+ay490Du5rn+e6fp6eneQvTNM2llHmapk3+feBz1+t1nqZpvl6vrYsSXvZ+Knv5e5H5PmQuewv6V4ir1vNZSnmbP4mZQiS5cBAjtGHj/P2y91PZy9+LzPchc9lb0L9CXFs/n/ZgwcBeX1/L+Xwup9OpvLy8tC4OQDf0r7zTFuKpdU9C78Fif9bSU0opLy8v5cePHyk6fG0WyNQPZOpf2db7bMn5fG5dFP5l6+dTgDUoDzvZjNpmMw0o2c+o7WLUfoDcJBgZT4g9WOzPWnqyGbXNjraPY+2yjdGW4IzWLt6N2g+Q2/tsCeMQYA3Kw042o7bZ0QaUawOH0QKO0drFu1H7AX4Z7UMKeVkiSCqjLoshj9ptdLR9HGuX0oy2BKd2u9C3koElomQhwCIVnSvRLWmjBrV/Whs4jBaI3mNJ+9K3ksFoH1LIyxJBUhl1WQx5LGmjoy1rY19L2pe+lQwsESULM1ik4is1e1s6y7Skjbb4GmvWrI0W9b6kfS3tW7UjgNscNAzwhePxWC6XS5mmqYsvp71dTxa91Xtv1wOwhoOGAVZYMguQ4au+PQxtZKj3Je03w/UAtGIGC6ASX/XJTPsFWObWDJYkFwCVSBRAZtovQB2WCAJD2mI5nyQs69S+FxmWaka0Rft1L9pzD2B/AixoJOJLL2KZtuLcnzhq3wv3No6R7kXU/nOkewBRWCIIjUQ8AylimUr5NXA5n8/ldDpV+7puOVQcte+FexvHFvdii/6ghqj9p+cBGpjn+e6fp6enGajjer3O0zTN1+u1dVH+ErFM8zzP0zTNpZR5mqbWRela1PufhfrbR9T+wP2H8ZRS3uZPYiYzWNBIxBPpI5aplP6+wPoC36eo9Re1va0VtT+I2n8C+xNgAeH1NnCJOhCPOnDNImr9RW1va/XWHwD9keQCYGdRD2ndKgtitM3/W5UnahbJqO0NoFcOGgZgU9EOsI1WHgByunXQsBksABZbMgsUbQZlSXmizb4BEJ8ZLAAWG2UWaJTrBGA5M1gAVBNtVmoro1zn3swMAj0zgwV0rbcU1dADM4NAD8xgAUN6T1F9Pp9bFwX4ly1mBreaFTPbBiwlwBqIlwS1ZBrIWOJV32h9yWjXu4ctUtpv9THFR5q2env+ersebpjn+e6fp6enmbymaZpLKfM0Ta2L8rDr9TpP0zRfr9fWRRnSVm2ppzaazZJnarT7tOR69U3tbFX3j/y72sPjeutverue0ZVS3uZPYiYB1kB66uh1UI+LOGjoqY1mI4i4TfDJWtrD43rrb3q7ntEJsOiKDupxXvwxtWrbnqk63D/+nfsCfRNgAb/Z88VvkHG/3gLfqPc+arnW6q3dbKm3ew+0cyvA+sfee76AGN43me/hfZN4KUVK5m+8J+PoJSlH1HsftVxr9dZuttTbvV/K0RWwPVkEYSdbZw7aIzPR2t8hk9/9tsiu1lLUex+1XGv11m62tPbeR+5jl5AVEbbnoGHYydYHa+5xcKfDQYFR9dLHmsGCem4dNGyJIOxk6yU8eywRsgwJHmeAm1Mvfeyey8NhVGawADpnQB+LmWCAPpjBAhjU6Jv6ozETDNA3SS6Aru2xaTy63hI6ZCchhecS6JsZLKBrZm/suSAezyXQMwEW0DXLsSAezyXQM0sEga5ZjhXbVkvFLEGLzXMJ9MwMFgDNbLVUzBI0AFoxgwUQzEizL1sl4BgpscdI7QUgAwEWXTPwaEO9P+Z99uV8Prcuyua2Wio20hK0kdrLFvRX7ah7eiXAomsGHm2o98eMNPvC47SXx2Trr/YISvYKfGrVvUCNcOZ5vvvn6elphq1dr9d5mqb5er2G+rda/p69rqOWbOUFxpWtv5qmaS6lzNM0pf4d81yv7vcqL3xUSnmbP4mZBFiEk7Gj3LrMGeuEdrINGEfnfrHEHu0lW5vMVl76cSvAkkWQcDKej7J1mTPWCe3IoJeL+8USexwcnu1w8mzlpX+HX8HXfZ6fn+e3t7cNiwPAo15fX8v5fC6n02mIJA/ZuV8AOR0Oh5/zPD//8ecCLAAA1vKRgFHdCrBkEYQPZCMah3sN2/F8jSNbJsZbtFlqEWBRVQ+dUy8vCr7nXsN2PF/jqHFUQITxgzZLLQIsqmrdOdXooJ0pMw73OpZHn98IAzT+5vkaR42DvVuPH0rRZqnos9SCt36kaec7rVOlSmdONq2fmUgefX49/3/TrshGmyWjIk17PyJvJm2dKlU6c7KRovtvjz6/nv+/aVdk03r8kEHk8R+/E2Al5MV5mw6abAQFf3v0+fX8/027gv4Y/+UhwErIixP6IShgC9oV9Mf4Lw/nYAEAACzkHCwACCZb5sNs5QVoQYAF7CL7wGxp+Vtfb+vfz31ap6Ze2k5al/dRngtgD/ZgAbvIvjl3aflbX2/r3899Wu+pWNpOWpf3UZ4LYA8CLGAX2QdmS8vf+npb/37u0zoZxdJ20rq8j/JcAHuQ5AIAIBlnIkF7klxAQvYLAD3Ql9WXfT8c9EyABYF5gdZnoBfLVvfDfd7OmrrVl9V3Op3KNE2WO0JA9mBBYPYL1Ldmk7ulONvZKumAZAbbWVO3+rL6su+Hg54JsCAwL9D61gz0DNa3s9XA24B+O2vqVl82Nh+pGI0kFwxJZ88S2gvAesfjsVwulzJNk0CbrtxKcmEGiyGZkWAJX98B1jOjzGgkuWBINgczOkkg9qGe4e+PVKOsAPDcI8DiLyN1CKN19r0bqe3WIqvbPtTzOp5pMvPcY4kgf7Fsjqy03eUs2dmHel7HM01mnnvMYPEXy+bIKlLbzfLlfY9Z3Oh1sUf5ssyWR7tXkZ5pWCrLc892ZBEEqEi2rL9Fr4vo5duTugBY7lYWQTNYABX1+uV9zQxH9LpYU75oMz21RL9XAJmYwQI25xyp/Mxw/KIe8tMfAbU4Bwtoxob1/Gza/kU95Kc/ArYmwAI2Z1Can8OWf1EP+emPgK1ZIggAALCQJBcAAAAbE2AB8K1es+ctpR7YmzYH+QiwICEvXPb2nhjgfD63LkpT6oG9aXOQjwALEvLC5RE9nmm1F2dnsTfPHuQjycVKztGgJe2PRzjLaV/qux59HxCJJBeVmUGgpfdU0SMNMMwC1OOL+L7Udz3evdCe9/H3BFgreWHCvgys6tkjQM/yAt6jnFE+iGS5J1/x7oX2vI+/56DhlRw2Cfvq4XDQkZY3vb+ASymh+8os5ayhh2v17oX2engfb02ABaTQw8CqhwHuvbK8gLOUs4aRrpX2RvqgNJoe3sdbk+SC4XkJsBdtDWLzjNYjuQsjuJXkwgwWwxtpVmFLBibf89UPYvM+qMeMKSMTYDE8L4E6DEyA7LwP6vFBiZHJIsjwomT4yk52r/Z6yBI3MvevPe8DoAYBFgxgpFTUI5M6Nzf3bxyCaeibJYIwAMv3xmB5U27u3zj0ydA3ARYMwMBtDPY85Ob+jUOfDH2zRBAGsGb5niUsAF9b209aUg19E2ABn7IfhK1tHcT7SMDWWvaT2jfEZYkgBNfqfClLWNja1vtQ7HNhay37Se0b4hJgQXCtXqL2g7C1rQenPhKwtZb9pPYNcR3meb77Lz8/P89vb28bFgf4qNUMFkA0vfWHvV0PjOZwOPyc5/n545/bg9Upa7P7sXYzdG9toLfrgT318vz0tje0t+vhMb08p1gi2C1rs+mtDfR0Pb5as7denp/elsX1dj08ppfnFAFWt3Ta9NYGeroeL1H21svz09ve0N6uh8f08pxiDxbA7sxgAa3of6Aee7CgIeuq+XcOGeVe+g5qs+8LtifAgh14oVGbgfcY9B3UdjqdyjRNlqHBhuzBgh1YV01t9nGNQd9BbfZ9wfbswQJIyD4KAGjLHiyAjtjHBWRiWTMjEWAxHJ08AOzLfkJGIsBiODp5iKfWhw8fUCAmyTUYiQCL4ejkP2dgSku1Pnz4gEJL+tHbLGtmJLIIMhwZlD4nKx0t1cqWJ+seLelHgVI2CrBkt4J8DExpqdaHDx9QaEk/CpSy0RJBSzQgn+zLN6IuzYlaLojYNiOWaYns/ShQxyYzWL7gAHuLujQnarkgYtuMWCaApTYJsCzRAPYW9cNO1HJBxLYZsUwA7+7dBnWY5/nuf/T5+Xl+e3urUT4AAIA0jsdjuVwuZZqm8uPHj3I4HH7O8/z88e/JIggAAPCNe2fZnYMFkFz2xAD8yT0FiOfeRDYCLIDkZG7tj3tKa4J8WM8SQXiAM9+IQGKA/rintCajI6xnBgse4CszETh7pz/R7una2QyzIHmdTqcyTZMgH1YQYMEDvIByM2iE+6z9mOQjVF7RgnzIRIAFD/ACys2gsa09AlXBcB1rPyb5CAWMyB4sYFhr97nYH1PHHns87COp4/1j0l7/H0BmAixgWAaNbe0RqAqGAdjbYZ7nu//y8/Pz/Pb2tmFxAAAA4jscDj/neX7++Of2YAFfsocF4Hf6xX2oZ7ISYJGaznd7EjoAj+gxW6d+cR/qmawEWB2K/FKqTee7vchZwB5p6yM9J9BSj9k6I/eLPRm1nr2fOjDP890/T09PM/FN0zSXUuZpmloXZXPX63Wepmm+Xq+ti0IDj7T1kZ4TYhmt31p7vaPVE7zzfsqjlPI2fxIzySLYoZGyZsnmNrZH2vpIz0kpv76Ins/ncjqdnNvW2Gip42XrhGVGez/1SBZBgAEcj8dyuVzKNE0GrY0JdgH6IIsgwMD23MuQcf/AnmV+n5kRXAH0yRJBgAHsudwq4xK4jGUGICYBFgBVZdw/kLHMAMRkiSAAn1q7bC7jEri1Zc64HPIRo10vwBoCLIA7jTa4jHwOURSj1VH06x3tGQViskQQCCN6drXR9ulYNve90eoo+vWO9owCMUnTDoQRPZV49AAQRucZBfZ0K027AAsIw+AIAMjCOVhAeBmTIwD0rqe9bT1dC3EJsNhVLx1bL9cBAN+JntxkiZ6uhbgEWOyql46tl+uAr/iQ8D11xAhOp1OZpilscpMleroW4pJFkN9svQcmegaqe/VyHfAVGdm+p44Ywfvy7R7scS32EyPA4jdbDxZ66aR7uQ74ig8J31tbRwZg+bmH3OLDCwIsfmNAxUcGEfmtvYc+JHxvbR0ZgOXnHnKLsRQCLH5jQMVHBhH5uYfxGIDl5x5yi7EUklwAX7IhOL8972HWpA97l9uRBPm5h8AtDhoGoJrj8Vgul0uZpinVF9ys5QagnVsHDVsiCEA1WZdNZS03APFYIghQSdblcTVlXTaVtdy1acMAjxNgAVTiAGqy67kNCx6BvVgiCOym95TvlpmRXc9tWDZNYC8CLGA3vQ9wpOYlu57bcM/BIxCLAAvYjQEO0ErPwSMQiz1YwG4kEqjDXpKxuN8AuZjBAkim96WW/M79BshFgAWQjKWWY3G/AXI5zPN8919+fn6e397eNiwOAABAfIfD4ec8z88f/9weLAB2t+e+InuYANiTAAuA3e15oG3Ph+dCTT5GQB0CLKjIywnuczqdyjRNu+wr2vN3wbuM7wMfI6AOSS6goozZvl5fX8v5fC6n00n6dHaz55lEzj+ihYzvAwlVoA4BFlSU8eWUcRAAEF3G94GPEVCHLIIwODNYAADL3coiaAYLBueLJQBAPZJcAAAAVCLAAqgoY+Yw0G4B6rFEEKAiSUPISLsFqEeABVBRxsxhoN0C1GOJIEBF70lDamVktHSLW2q2jdrtNiLPErAXARawK4OcZd6Xbp3P59ZFIRhtY5ks9aWPhPwEWNCJLC/lLIOcKE6nU5mmydIt/qBtLJOlvmr0kVneB9Are7AggBqH/WbZpG6vxzLOKeMWbWOZLPVVo4/M8j6AXgmwIIAaL8MsgUuWQQ5ACzX6yCzvA+iVJYIQQI2lKyNsUqdPtZczWR7F6LwPoC0zWBCAWR1GVns5k+VRALQkwAKgqdrLmSyPAqClwzzPd//l5+fn+e3tbcPiAAAAxHc4HH7O8/z88c/twQIAAKhEgAUAAFCJAAsAAKASARYA8Ckp7wGWE2ABrGTwSe/eU96fz+fWRQFIQ5p2gJWct0TvpLwHWE6ABbCSwSe9cwg6wHKWCAKs9D74fHl5aV0UGJrlukAkiw4aPhwO/08p5X9tVxwAgMX+r1LK/1FK+f9KKf9347IA4/g/53n+nx//cFGABQAAwG2WCAIAAFQiwAIAAKhEgAUAAFCJAAsAAKASARYAAEAlAiwAAIBKBFgAAACVCLAAAAAqEWABAABU8v8D73UY8GtkAewAAAAASUVORK5CYII=\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "4 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.195833113096693 max: 482.1907827262405\n", + "image 1 reprojection errors: average:21.980512812067968 max: 188.90291200650978\n", + "image 2 reprojection errors: average:21.680381989110735 max: 157.71544954422495\n", + "image 3 reprojection errors: average:21.61669072994175 max: 329.2322411858199\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6145e+06 1.08e+07 \n", + " 1 2 4.6790e+03 1.61e+06 6.11e+01 6.80e+05 \n", + " 2 3 1.1913e+03 3.49e+03 2.11e+00 1.02e+04 \n", + " 3 4 1.1883e+03 2.95e+00 1.27e-01 1.10e+03 \n", + " 4 5 1.1877e+03 6.74e-01 3.33e-02 1.75e+02 \n", + " 5 6 1.1874e+03 2.65e-01 1.94e-02 4.78e+01 \n", + " 6 7 1.1873e+03 1.26e-01 6.89e-03 3.20e+01 \n", + " 7 8 1.1872e+03 8.68e-02 7.73e-03 4.19e+01 \n", + " 8 9 1.1871e+03 7.50e-02 4.97e-03 2.88e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.6145e+06, final cost 1.1871e+03, first-order optimality 2.88e+01.\n", + "mean reprojection error: 0.6659023325181292\n", + "max reprojection error: 3.0204378979976183\n", + "mean reconstruction error: 0.07717277843476102\n", + "max reconstruction error: 0.3774148540928275\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "4 images with total of 1272 features\n", + "image 0 reprojection errors: average:21.765970980859443 max: 276.70870850256534\n", + "image 1 reprojection errors: average:21.96311703346684 max: 317.85655182152817\n", + "image 2 reprojection errors: average:21.01296455326584 max: 319.52640359210204\n", + "image 3 reprojection errors: average:20.652028860588956 max: 170.51436060266448\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.5357e+06 3.49e+06 \n", + " 1 2 1.4257e+04 1.52e+06 6.19e+01 4.28e+05 \n", + " 2 3 1.0869e+04 3.39e+03 8.07e-01 7.28e+03 \n", + " 3 4 1.0836e+04 3.33e+01 8.26e-01 7.28e+03 \n", + " 4 5 1.0828e+04 7.87e+00 9.95e-02 9.28e+02 \n", + " 5 6 1.0827e+04 1.37e+00 4.29e-02 6.92e+02 \n", + " 6 7 1.0826e+04 6.34e-01 1.33e-02 1.74e+02 \n", + " 7 8 1.0826e+04 3.88e-01 1.50e-02 1.64e+02 \n", + " 8 9 1.0826e+04 3.56e-01 9.54e-03 7.69e+01 \n", + " 9 10 1.0825e+04 1.37e-01 4.59e-03 3.67e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 1.5357e+06, final cost 1.0825e+04, first-order optimality 3.67e+01.\n", + "mean reprojection error: 2.0316679585410555\n", + "max reprojection error: 8.133508077856309\n", + "mean reconstruction error: 0.22627791078478332\n", + "max reconstruction error: 1.2494971296175976\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "4 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.669269841620803 max: 265.14591392216255\n", + "image 1 reprojection errors: average:21.511001710751813 max: 197.97823971843354\n", + "image 2 reprojection errors: average:22.249435756098315 max: 178.5624381572415\n", + "image 3 reprojection errors: average:22.506645125459386 max: 458.6795937143421\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7192e+06 6.26e+06 \n", + " 1 2 3.9218e+04 1.68e+06 6.35e+01 1.20e+06 \n", + " 2 3 2.8743e+04 1.05e+04 1.07e+00 3.11e+04 \n", + " 3 4 2.8708e+04 3.48e+01 3.14e-01 3.35e+03 \n", + " 4 5 2.8698e+04 1.03e+01 8.85e-02 6.02e+02 \n", + " 5 6 2.8691e+04 6.08e+00 9.69e-02 4.04e+02 \n", + " 6 7 2.8687e+04 4.51e+00 4.78e-02 1.71e+02 \n", + " 7 8 2.8684e+04 2.80e+00 4.83e-02 2.23e+02 \n", + " 8 9 2.8682e+04 2.34e+00 3.02e-02 1.40e+02 \n", + " 9 10 2.8680e+04 1.87e+00 3.39e-02 1.95e+02 \n", + " 10 11 2.8678e+04 1.62e+00 2.24e-02 1.21e+02 \n", + " 11 12 2.8677e+04 1.45e+00 2.78e-02 1.92e+02 \n", + " 12 13 2.8676e+04 1.33e+00 1.92e-02 1.16e+02 \n", + " 13 14 2.8675e+04 8.39e-01 1.51e-02 1.26e+02 \n", + " 14 15 2.8674e+04 1.01e+00 1.89e-02 1.57e+02 \n", + " 15 16 2.8673e+04 7.99e-01 1.21e-02 9.45e+01 \n", + " 16 17 2.8672e+04 1.34e+00 3.14e-02 2.51e+02 \n", + " 17 18 2.8670e+04 1.21e+00 1.36e-02 7.85e+01 \n", + " 18 19 2.8670e+04 8.08e-01 1.92e-02 1.88e+02 \n", + " 19 20 2.8669e+04 5.37e-01 6.24e-03 3.42e+01 \n", + " 20 21 2.8668e+04 6.93e-01 2.04e-02 2.25e+02 \n", + " 21 22 2.8668e+04 6.31e-01 6.43e-03 2.65e+01 \n", + " 22 23 2.8667e+04 7.33e-01 2.29e-02 2.43e+02 \n", + " 23 24 2.8666e+04 6.92e-01 6.62e-03 2.32e+01 \n", + " 24 25 2.8665e+04 7.98e-01 2.58e-02 2.62e+02 \n", + " 25 26 2.8665e+04 7.50e-01 6.86e-03 2.03e+01 \n", + " 26 27 2.8664e+04 7.85e-01 2.60e-02 2.50e+02 \n", + " 27 28 2.8663e+04 7.28e-01 6.95e-03 2.02e+01 \n", + " 28 29 2.8663e+04 5.44e-01 1.78e-02 1.87e+02 \n", + " 29 30 2.8662e+04 5.17e-01 6.42e-03 2.50e+01 \n", + " 30 31 2.8662e+04 3.92e-01 1.23e-02 1.47e+02 \n", + " 31 32 2.8661e+04 4.02e-01 6.14e-03 2.73e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 32, initial cost 1.7192e+06, final cost 2.8661e+04, first-order optimality 2.73e+01.\n", + "mean reprojection error: 3.2810786776158927\n", + "max reprojection error: 13.697677051247968\n", + "mean reconstruction error: 0.36818248519896435\n", + "max reconstruction error: 1.6619614990017917\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "4 images with total of 1272 features\n", + "image 0 reprojection errors: average:24.774101956804113 max: 253.2340317235348\n", + "image 1 reprojection errors: average:25.391846930160337 max: 389.55113091903155\n", + "image 2 reprojection errors: average:23.701998036106502 max: 413.7416581449505\n", + "image 3 reprojection errors: average:24.995591656742235 max: 140.12396653426424\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.9667e+06 8.52e+06 \n", + " 1 2 1.1750e+05 1.85e+06 6.88e+01 5.87e+05 \n", + " 2 3 1.1239e+05 5.11e+03 1.35e+00 1.11e+04 \n", + " 3 4 1.1218e+05 2.08e+02 1.82e+00 1.61e+04 \n", + " 4 5 1.1210e+05 7.65e+01 3.44e-01 2.02e+03 \n", + " 5 6 1.1209e+05 1.05e+01 1.26e-01 1.89e+03 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 6 7 1.1209e+05 6.61e+00 5.50e-02 8.13e+02 \n", + " 7 8 1.1208e+05 2.69e+00 2.74e-02 3.38e+02 \n", + " 8 9 1.1208e+05 2.06e+00 2.47e-02 3.18e+02 \n", + " 9 10 1.1208e+05 2.11e+00 2.22e-02 1.91e+02 \n", + " 10 11 1.1208e+05 1.70e+00 1.79e-02 2.21e+02 \n", + " 11 12 1.1208e+05 1.21e+00 1.22e-02 1.30e+02 \n", + " 12 13 1.1207e+05 8.70e-01 9.95e-03 1.62e+02 \n", + " 13 14 1.1207e+05 8.13e-01 9.40e-03 1.23e+02 \n", + " 14 15 1.1207e+05 1.17e+00 1.46e-02 2.58e+02 \n", + " 15 16 1.1207e+05 8.17e-01 7.06e-03 7.62e+01 \n", + " 16 17 1.1207e+05 7.67e-01 1.14e-02 2.59e+02 \n", + " 17 18 1.1207e+05 7.49e-01 6.66e-03 7.33e+01 \n", + " 18 19 1.1207e+05 7.56e-01 1.14e-02 2.75e+02 \n", + " 19 20 1.1207e+05 7.41e-01 6.57e-03 7.04e+01 \n", + " 20 21 1.1207e+05 7.53e-01 1.15e-02 2.95e+02 \n", + " 21 22 1.1207e+05 7.38e-01 6.51e-03 6.75e+01 \n", + " 22 23 1.1207e+05 7.51e-01 1.17e-02 3.17e+02 \n", + " 23 24 1.1207e+05 7.36e-01 6.45e-03 6.47e+01 \n", + " 24 25 1.1207e+05 7.50e-01 1.19e-02 3.42e+02 \n", + " 25 26 1.1206e+05 7.35e-01 6.40e-03 6.19e+01 \n", + " 26 27 1.1206e+05 7.51e-01 1.21e-02 3.71e+02 \n", + " 27 28 1.1206e+05 7.36e-01 6.36e-03 5.92e+01 \n", + " 28 29 1.1206e+05 7.33e-01 1.20e-02 3.96e+02 \n", + " 29 30 1.1206e+05 6.99e-01 6.01e-03 5.71e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 30, initial cost 1.9667e+06, final cost 1.1206e+05, first-order optimality 5.71e+01.\n", + "mean reprojection error: 6.478621284247045\n", + "max reprojection error: 27.90784150844781\n", + "mean reconstruction error: 0.7401618010520424\n", + "max reconstruction error: 3.1150285479397852\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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XXAHA+PHjee2114qVe+eddxg6dCgtWrTg1FNPZejQobz99tuAd63KkSNe797hw4dp27ZtsfXz8vL49a9/TUpKCqmpqTz66KOh/Zk+fTr9+/enV69erFu3jmHDhnHWWWcxd+7ccu1bWZTMiIhIMbt376Zdu3ah6YSEBHbv3l2s3Pfff09aWhrr1q3jvPPOY9asWYWWN2vWjDlz5pCens4LL7zAwYMHueGGG1i6dCnbtm1j1apVbNiwgbVr1/Lxxx+XGE9GRgYvvvgin332GRs2bKB27do8++yzoRi6devGypUrGTBgQKHphg0bsmDBAlauXMmKFSt44oknWL9+PQBZWVmMGzeO9evX0759e0aMGMGePXsibr9evXp8/PHHTJ48mVGjRvHYY4+xefNmFi5cyIEDB0qN77777mPNmjVs3LiRjz76iI0bN4bqbdmyJevWrWPKlCk89NBDxbablZVF9+7dI74OHTpUqOyBAwdo3rw5derUKfUzK+2znT9/PiNGjCAhIYGnn36aadOmFVt/3rx5bN++nfXr17Nx40auueaa0LJ27dqxfPlyBg4cGEpoV6xYwYwZMyK2a0XRBcAiIlKM16NfWKQ7TGrVqsWYMWMA+MUvfsHo0aOLlRk6dCgvv/wyN910E1988QUAS5cuZenSpfTo0QOAo0ePsm3bNgYNGhQxnvfff5+1a9fSu3dvAH744QdatWoFQO3atbn88stDZcOnP/30Uy677DIaNWoEwOjRo/nkk08YOXIk7du3p1+/fqH1lixZUmJ7jBw5EoCUlBSSk5Np06YNAB07dmTnzp18+umnJcb30ksvMW/ePHJzc8nOzmbLli2kpqaG4gHo2bMnr776arHtdunShQ0bNpQYV7hoP7PSyj3yyCMsWbKEvn378uCDD3L77bczf/78QmXfe+89Jk+eHEqawnv5wtvp6NGjNGnShCZNmtCgQQMOHTpE8+bNo9qXWCmZERGRYhISEgqdetm1a1fEUw5FRfryzM/PJyMjg4YNG5KTk0NCQgLOOe68804mTZoUVTzOOcaPH8/vf//7YssaNGhA7dq1I05H+uIuUJDgRKN+/fqAl7wVvC+Yzs3NLTG+7du389BDD7F69WpOPfVU0tPTCz0/paCu2rVrk5ubW2y7WVlZoWSxqGXLlhVKDlq2bMmhQ4fIzc2lTp06JX5mCQkJLFu2LDS9a9cuBg8ezP79+/niiy/o27cvAGPGjGH48OHF1nfOlXjrdFntFC9KZkREKtGW7COMeXx5hdXVtU3TCqlr5MiRzJkzh7Fjx7Jy5UqaNWsW6o0Il5+fzyuvvMLYsWN57rnnGDBgQLEyjzzyCElJSdx///1cd911LF++nGHDhvG73/2Oa665hsaNG7N7927q1q0b6s0oasiQIYwaNYrbbruNVq1akZOTw3fffUf79u1L3Y9BgwaRnp7OtGnTcM6xePFinn766RNrlFKUFN+RI0do1KgRzZo1Y9++fbz11lsMHjw46npj6ZkxM84///zQ57Fo0SJGjRpVrNywYcOYPn06Bw8eBLxest///vc0bdqUw4cPs3XrVs4++2zeffddkpKSiq1/wQUXMHfuXAYPHkydOnXIyckp8xqseFMyU+CtabB3U3RlW6fAhQ/ENx4Rqfa6tq2YxCNUX5umUdV59dVXs2zZMr799lsSEhKYNWsW119/fegizcmTJzNixAiWLFlCp06dOOWUU1iwYEHEuho1asSXX35Jz549adasGS+++GKh5Vu3bmX+/PmsWrWKJk2aMGjQIO69915mzZpFRkYG/fv3B7yLeJ955pkSk5muXbty7733csEFF5Cfn0/dunV57LHHykxm0tLSSE9Pp0+fPgBMnDiRHj16sGPHjmJlR4wYwfz586PqgYo2vn79+tGjRw+Sk5Pp2LEj5557bsx1x2L27NmMHTuWu+66ix49enD99dcDsGbNGubOncv8+fNp0aIFv/vd70KnxGbMmBFKRp544gkuv/xyatWqxamnnsqf//znYtuYOHEiW7duJTU1lbp163LDDTdw8803x3W/ymKldcGdLL169XJr1qyp3CAWXOQlM61TSi9XUGbCmycnLhGpVjIyMiL+txtUjRs35ujRo5UdhlRDkX5XzGytc65X0bLqmQkXTZKy4KKTE4uIiIhERbdmi4jICVOvjFQFSmZEREQk0JTMiIiISKApmREREZFA0wXAIiKVJZZHQkRLj46QGkg9MyIilWXvpopNZqKo79ixY/Tp04dzzjmn2MCH4Zxz3HrrrXTq1InU1FTWrVsXUygzZszgvffei2mdAo0bNz6h9cR74nDfvn3p3LkzY8aM4fjx48XKbNiwgf79+5OcnExqamqhZwNdf/31nHPOOaSmpnLFFVcE5gJv9cyIiFSminxuVRSPjqhfvz4ffPABjRs35qeffmLAgAFceOGFhcYoAnjrrbfYtm0b27ZtY+XKlUyZMoWVK1dGHco999wTc/gVIS8vr9DQBkWnI3HO4ZyjVq3g/38/depUbrvtNsaOHcvkyZN58sknmTJlSqEyp5xyCk899RSdO3dmz5499OzZk2HDhtG8eXMeeeQRmjb1Hrx4++23M2fOnIiDTVY1wf/kREQkamYW6vn46aef+OmnnyKOs/P6668zbtw4zIx+/fpx6NAhsrOzi5Vr3Lgxd9xxB2lpaQwZMoT9+/cDhEZMPnz4MF26dCErKwvwnj78xBNPAPDggw/Su3dvUlNTS+whCvfMM8/Qp08funfvzqRJk8jLywvFMGPGDPr27cvy5cuLTT/88MN069aNbt268cc//hGAHTt2kJSUxI033khaWlqhcaiKGjx4MLfddhuDBg0iKSmJ1atXM3r0aDp37sxdd91VZnxTpkyhV69exXrCOnTowMyZM0lLSyMlJYXMzMwy26A0zjk++OADrrjiCgDGjx/Pa6+9Vqzc2WefTefOnQFo27YtrVq1Cn1uBYmMc44ffvgh4rGRl5fHr3/9a1JSUkhNTeXRRx8N7c/06dPp378/vXr1Yt26dQwbNoyzzjor9HTpeFEyIyJSw+Tl5dG9e3datWrF0KFDQwMLhtu9ezft2rULTSckJLB79+5i5b7//nvS0tJYt24d5513HrNmzSq0vFmzZsyZM4f09HReeOEFDh48yA033MDSpUvZtm0bq1atYsOGDaxdu5aPP/64xJgzMjJ48cUX+eyzz9iwYQO1a9fm2WefDcXQrVs3Vq5cyYABAwpNN2zYkAULFrBy5UpWrFjBE088wfr16wFvEMdx48axfv162rdvz4gRI9izZ0/E7derV4+PP/6YyZMnM2rUKB577DE2b97MwoULOXDgQKnx3XfffaxZs4aNGzfy0UcfsXHjxlC9LVu2ZN26dUyZMoWHHnqo2HazsrLo3r17xNehQ4cKlT1w4ADNmzcPjWZd0mcWbtWqVRw/fpyzzjorNG/ChAm0bt2azMxMbrnllmLrzJs3j+3bt7N+/Xo2btzINddcE1rWrl07li9fzsCBA0MJ7YoVK5gxY0apcZSXTjOJiNQwtWvXZsOGDRw6dIjLLruMzZs3061bt0JlIg11E+m/9Fq1aoVGdf7FL37B6NGji5UZOnQoL7/8MjfddBNffPEF4A1uuHTpUnr06AF4D9/btm0bgwYNihjz+++/z9q1a0PjCf3www+hcZxq167N5ZdfXmj/CqY//fRTLrvsstAI2aNHj+aTTz5h5MiRtG/fvtDptSVLlkTcNngDbwKkpKSQnJwcGnSzY8eO7Ny5k08//bTE+F566SXmzZtHbm4u2dnZbNmyhdTU1FA8AD179uTVV18ttt1YBpqM9jMrkJ2dzbXXXsuiRYsKnWJbsGABeXl53HLLLbz44otMmDCh0HrvvfcekydPDiVN4YNMhrfT0aNHadKkCU2aNKFBgwYcOnSo0CjfFUnJjIhIDdW8eXMGDx7M22+/XSyZSUhIKHTqZdeuXVENwBjpyzM/P5+MjAwaNmxITk4OCQkJOOe48847mTRpUlSxOucYP348v//974sta9CgQaHrYsKnSxt/sCDBiUb9+vUBL3kreF8wnZubW2J827dv56GHHmL16tWceuqppKenc+zYsWL11q5dm9zc3GLbzcrKCiWLRS1btqxQctCyZUsOHTpEbm4uderUKfUzO3LkCBdddBH33ntvseulCuIZM2YMDz74YLFkxjlXYpJUVjvFi5IZEZHKtHdTxY35FsVgufv376du3bo0b96cH374gffee4+pU6cWKzdy5EjmzJnD2LFjWblyJc2aNQv1RoTLz8/nlVdeYezYsTz33HMMGDCgWJlHHnmEpKQk7r//fq677jqWL1/OsGHD+N3vfsc111xD48aN2b17N3Xr1i1x1OwhQ4YwatQobrvtNlq1akVOTg7fffddmaNmDxo0iPT0dKZNm4ZzjsWLF/P000+Xus6JKCm+I0eO0KhRI5o1a8a+fft46623GDx4cNT1xtIzY2acf/75oc9j0aJFjBo1qli548ePc9lllzFu3DiuvPLK0HznHH//+9/p1KkTzjneeOMNEhMTi61/wQUXMHfuXAYPHkydOnXIyckp1DtTGZTMnIho/vjoWQ8iUpYyEo8Tqq+MOrOzsxk/fjx5eXnk5+dz1VVXcfHFFwOELtKcPHkyI0aMYMmSJXTq1IlTTjmFBQsWRKyvUaNGfPnll/Ts2ZNmzZoVus0XYOvWrcyfP59Vq1bRpEkTBg0axL333susWbPIyMigf//+gHcR7zPPPFNiMtO1a1fuvfdeLrjgAvLz86lbty6PPfZYmclMWloa6enp9OnTB4CJEyfSo0cPduzYUazsiBEjmD9/flQ9UNHG169fP3r06EFycjIdO3bk3HPPjbnuWMyePZuxY8dy11130aNHD66//noA1qxZw9y5c5k/fz4vvfQSH3/8MQcOHGDhwoUALFy4kNTUVMaPH8+RI0dwznHOOefwP//zP8W2MXHiRLZu3Upqaip169blhhtu4Oabb47rfpXFSuuCO1l69erl1qxZU7lBFCQnZd0iGc1Drgr+O6qo2y1FpNrIyMggKSmpssOoMI0bNw7Ms0gkWCL9rpjZWudcr6Jl1TMTq2h6Wyqqy1hERETKpFuzRUTkhKlXRqoCJTMiIiISaEpmREREJNCUzIiIiEig6QJgEZFKMnvVbDJzyjceT1GJLRKZ2qf4c2NEqjP1zIiIVJLMnEyycrIqrL6snKyokqMOHTqQkpJC9+7d6dWr2F2ugPcAtVtvvZVOnTqRmprKunXrYoplxowZvPfeezGtU6BgIEyJ3fbt2+nbty+dO3dmzJgxHD9+vFiZr7/+mp49e9K9e3eSk5MLDQI5cODA0NhPbdu25dJLLz2J0Z849cyIiFSiLi26sGB45AfSxWrC2xPKLuT78MMPadmyZYnL33rrLbZt28a2bdtYuXIlU6ZMYeXKlVHXf88990RdtiLl5eUVGtqg6HQkzjmcc4XGJwqqqVOncttttzF27FgmT57Mk08+yZQpUwqVadOmDZ9//jn169fn6NGjdOvWjZEjR9K2bVs++eSTULnLL7884hOEq6Lgf3IiIlLhXn/9dcaNG4eZ0a9fPw4dOkR2dnaxco0bN+aOO+4gLS2NIUOGsH//foDQiMmHDx+mS5cuZGV5PVBXX301TzzxBAAPPvggvXv3JjU1lZkzZ5YZ0zPPPEOfPn3o3r07kyZNIi8vLxTDjBkz6Nu3L8uXLy82/fDDD9OtWze6devGH//4RwB27NhBUlISN954I2lpaYXGoSpq8ODB3HbbbQwaNIikpCRWr17N6NGj6dy5M3fddVeZ8U2ZMoVevXqRnJxcaD87dOjAzJkzSUtLIyUlhczM8p1ydM7xwQcfcMUVVwAwfvx4XnvttWLl6tWrFxo36ccffyQ/P79Yme+++44PPvggYs9MXl4ev/71r0lJSSE1NZVHH300tD/Tp0+nf//+9OrVi3Xr1jFs2DDOOuusQr0/8aBkRkSkhjEzLrjgAnr27Mm8efMiltm9ezft2rULTSckJLB79+5i5b7//nvS0tJYt24d5513HrNmzSq0vFmzZsyZM4f09HReeOEFDh48yA033MDSpUvZtm0bq1atYsOGDaxdu5aPP/64xJgzMjJ48cUX+eyzz9iwYQO1a9fm2WefDcXQrVs3Vq5cyYABAwpNN2zYkAULFrBy5UpWrFjBE088wfr16wFvEMdx48axfv162rdvz4gRI9izZ0/E7derV4+PP/6YyZMnM2rUKB577DE2b97MwoULOXDgQKnx3XfffaxZs4aNGzfy0UcfsXHjxlC9LVu2ZN26dUyZMoWHHnqo2HazsrJCp32Kvg4dOlSo7IEDB2jevHloNOuSPjOAnTt3kpqaSrt27Zg6dWqxIRwWL17MkCFDaNq0abF1582bx/bt21m/fj0bN27kmmuuCS1r164dy5cvZ+DAgaGEdsWKFcyYMSNiHBVFp5lERGqYzz77jLZt2/LNN98wdOhQEhMTGTRoUKEykYa6iTRScq1atUKjOv/iF79g9OjRxcoMHTqUl19+mZtuuokvvvgCgKVLl7J06VJ69OgBeA/f27ZtW7E4Crz//vusXbuW3r17A/DDDz+ExnGqXbs2l19+eahs+PSnn37KZZddFhohe/To0XzyySeMHDmS9u3bFxoxesmSJRG3Dd7AmwApKSkkJyeHBt3s2LEjO3fu5NNPPy0xvpdeeol58+aRm5tLdnY2W7ZsITU1NRQPQM+ePXn11VeLbTeWgSaj/czASzo2btzInj17uPTSS7niiiv42c9+Flr+/PPPM3HixIjrvvfee0yePDmUNIUPMhneTkePHqVJkyY0adKEBg0acOjQoUKjfFckJTMiIjVMwX/hrVq14rLLLmPVqlXFkoiEhIRCp1527doV1QCMkb488/PzycjIoGHDhuTk5JCQkIBzjjvvvJNJkyZFFbNzjvHjx/P73/++2LIGDRoUui4mfLq08QcLEpxoFJyWqVWrVuh9wXRubm6J8W3fvp2HHnqI1atXc+qpp5Kens6xY8eK1Vu7dm1yc3OLbTcrKyuULBa1bNmyQslBy5YtOXToELm5udSpUyeqz6xt27YkJyfzySefhE5PHThwgFWrVrF48eKI6zjnSkySymqneFEyIyJSibJysmK6cLesurq06FJqme+//578/HyaNGnC999/z9KlSyOeAhg5ciRz5sxh7NixrFy5kmbNmoV6I8Ll5+fzyiuvMHbsWJ577jkGDBhQrMwjjzxCUlIS999/P9dddx3Lly9n2LBh/O53v+Oaa66hcePG7N69m7p165Y4avaQIUMYNWoUt912G61atSInJ4fvvvuuzFGzBw0aRHp6OtOmTcM5x+LFi3n66adLXedElBTfkSNHaNSoEc2aNWPfvn289dZbDB48OOp6Y+mZMTPOP//80OexaNGiiBfw7tq1i9NOO42GDRty8OBBPvvsM26//fbQ8pdffpmLL76YBg0aRNzOBRdcwNy5cxk8eDB16tQhJyenUO9MZVAyIyJSSRJbJFZofV1adCmzzn379nHZZZcBkJuby7//+78zfPhwgNBFmpMnT2bEiBEsWbKETp06ccopp7BgQeQ7rho1asSXX35Jz549adasGS+++GKh5Vu3bmX+/PmsWrWKJk2aMGjQIO69915mzZpFRkYG/fv3B7yLeJ955pkSk5muXbty7733csEFF5Cfn0/dunV57LHHykxm0tLSSE9Pp0+fPgBMnDiRHj16sGPHjmJlR4wYwfz586PqgYo2vn79+tGjRw+Sk5Pp2LEj5557bsx1x2L27NmMHTuWu+66ix49enD99dcDsGbNGubOncv8+fPJyMjgjjvuwMxwzoUu5i3wwgsvMG3atBK3MXHiRLZu3Upqaip169blhhtu4Oabb47rfpXFSuuCO1l69erl1qxZE/ftzHrjS7bsORKa7tq2KTMvSfYmCka6nvBm+TdUkXWJSLWSkZFBUlJSZYdRYRo3bqzBJiUuIv2umNla51yxhyPVqJ6ZLXuOsCX7CF3bNGVL9pGyVxAREZEqr8bdmt21TVNenNSfrm2K324mIiKxUa+MVAU1LpkRERGR6qXMZMbM2pnZh2aWYWZfmtn/9effbWa7zWyD/xoRts6dZvaVmWWZ2bB47oCIiIjUbNFcM5ML3OGcW2dmTYC1Zvauv+wR51yhRxaaWVdgLJAMtAXeM7OznXN5FRm4iIiICESRzDjnsoFs//13ZpYBnFHKKqOAF5xzPwLbzewroA+wvALiFRGpNvbefz8/ZpRvPJ6i6icl0nr69AqtU6Sqi+maGTPrAPQACoZOvdnMNprZn83sVH/eGUD4iF27iJD8mNkvzWyNma0pGJhMRKQm+TEjk2PlHFww3LHMzKiSo+uuu45WrVrRrVu3QvNzcnIYOnQonTt3ZujQoRw8eDDi+m+//TZdunShU6dOPPDAAzHFuGbNGm699daY1ilQMNaPxM45x6233kqnTp1ITU1l3bp1EcsNHDgwNPZT27Ztiw00uXr1amrXrl3lPoeob802s8bAX4BfOeeOmNn/AP8PcP7PPwDXAZGecVzsYTbOuXnAPPCeMxN76CIiwdcgMZH2Tz9VIXV9fe24qMqlp6dz8803M25c4fIPPPAAQ4YMYdq0aTzwwAM88MADzJ49u1CZvLw8brrpJt59910SEhLo3bs3I0eOpGvXrlFtu1evXvTqVewxIXFX8Ij/kqajXS+o3nrrLbZt28a2bdtYuXIlU6ZMYeXKlcXKffLJJ6H3l19+eaEnCOfl5TF16lSGDat6l8JG1TNjZnXxEplnnXOvAjjn9jnn8pxz+cATeKeSwOuJaRe2egIQeRjSSrYl+whjHl/OmMeXs+PA95UdjojISTFo0KCIj59//fXXGT9+PADjx4/ntddeK1Zm1apVdOrUiY4dO1KvXj3Gjh3L66+/Xqxceno6kydPZuDAgZx99tn87W9/A7zxhC6++GIAbr31Vu655x4A3nnnHQYNGkR+fj5r167lvPPOo2fPngwbNozs7OxS9+fvf/87w4cPp2fPngwcOJBMv7crPT2d22+/nfPPP5+pU6cWm96wYQP9+vUjNTWVyy67LNQTNXjwYKZPn855553Hf/3Xf5W43YULF3LppZdyySWXcOaZZzJnzhwefvhhevToQb9+/cjJySk1vjfeeIO+ffvSo0cPfv7zn7Nv3z4A7r77bq677joGDx5Mx44d+e///u9S9z8ar7/+OuPGjcPM6NevH4cOHSq1Xb/77js++OCDQj0zjz76KJdffnmJT2kGr9cuLS2Nc845hyFDhoT2Z/z48VxwwQV06NCBV199ld/85jekpKQwfPhwfvrpp3LvXzR3MxnwJJDhnHs4bH74IB2XAZv9938FxppZfTM7E+gMrCp3pBWsa9umoWfNbMk+wvfH4zcAlohIEOzbty80/lKbNm345ptvipXZvXs37dr96//VhIQEdu/eHbG+HTt28NFHH/Hmm28yefLkQgMsgtcT9OKLL/Lhhx9y6623smDBAvLy8rjlllt45ZVXWLt2Lddddx2//e1vS437l7/8JY8++ihr167loYce4sYbbwwt27p1K++99x5/+MMfik2PGzeO2bNns3HjRlJSUpg1a1ZovUOHDvHRRx9xxx13MHfu3NBQD0Vt3ryZ5557jlWrVvHb3/6WU045hfXr19O/f3+eeuqpUuMbMGAAK1asYP369YwdO5b//M//DNWbmZnJO++8w6pVq5g1a1bEL/wxY8aETgmFvwq2Gy6Wzw1g8eLFDBkyhKZNm4bWX7x4MZMnTy5xnf3793PDDTfwl7/8hS+++IKXX345tOzvf/87b775Jq+//jq/+MUvOP/889m0aRMNGzbkzTfL/7T8aPrOzgWuBTaZ2QZ/3nTgajPrjncKaQcwCcA596WZvQRswbsT6qaqeCdTaBgDYMzjy+FAJQYjIhIQkYbAKWkE5auuuopatWrRuXNnOnbsGOqRKHDKKafwxBNPMGjQIB555BHOOussNm/ezObNmxk6dCjgndqINMBlgaNHj/L5559z5ZVXhub9+OOPofdXXnlloRG1C6YPHz7MoUOHOO+88wCvJyq8jvCRqkv7Aj///PNp0qQJTZo0oVmzZlxyySUApKSksHHjxlLj27VrF2PGjCE7O5vjx49z5plnhspcdNFF1K9fn/r169OqVSv27dtHQkJCoW0XHQerNLF8bgDPP/88EydODE3/6le/Yvbs2YXasqgVK1YwaNCg0H6E9/5deOGF1K1bl5SUFPLy8kLjgaWkpEQcJytW0dzN9CmRr4NZUso69wH3lSMuERE5yX72s5+RnZ1NmzZtyM7Ojng6ISEhgZ07/3WPx65du0ocmLHol2WkL89NmzZx2mmnsWePdzWCc47k5GSWL4/uBtj8/HyaN29e4sjSjRo1KnW6JNGWq1+/fuh9rVq1QtO1atUiNze31PhuueUWbr/9dkaOHMmyZcu4++67I9Zbu3ZtcnOLnz0YM2YMWVlZxebffvvtxa6HiuVzO3DgAKtWrWLx4sWheWvWrGHs2LEAfPvttyxZsoQ6deoUOg3lnCsxQQpvl7p164bKFbRTeQX/qiYRkQA7lpkZ9YW70dTVIPHER+IeOXIkixYtYtq0aSxatKjQxZ8FevfuzbZt29i+fTtnnHEGL7zwAs8991zE+l5++WXGjx/P9u3b+cc//kGXLl1YsWJFaPnXX3/NH/7wB9avX8+IESO49NJL6dGjB/v372f58uX079+fn376ia1bt5KcnBxxG02bNuXMM8/k5Zdf5sorr8Q5x8aNGznnnHNK3ddmzZpx6qmn8sknnzBw4ECefvrpUC9NRSotvsOHD3PGGd7NvosWLYq57lh6ZkaOHMmcOXMYO3YsK1eupFmzZiX2eL388stcfPHFNGjQIDRv+/btoffp6elcfPHFxe506t+/PzfddBPbt2/nzDPPJCcnJ+K1WfGg4QxERCpJ/aTEciUfRTVITKR+Utn1XX311fTv35+srCwSEhJ48sknAZg2bRrvvvsunTt35t1332XatGkA7NmzhxEjvIe816lThzlz5jBs2DCSkpK46qqrSkw0unTpwnnnnceFF17I3LlzC305Oue4/vrreeihh2jbti1PPvkkEydOJD8/n1deeYWpU6dyzjnn0L17dz7//PNS9+fZZ5/lySef5JxzziE5OTniBcmRLFq0iP/4j/8gNTWVDRs2MGPGjIjlSrtmJholxXf33Xdz5ZVXMnDgQFq2bHnC9UdjxIgRdOzYkU6dOnHDDTfwpz/9qdCygp4xgBdeeIGrr7465m2cfvrpzJs3j9GjR3POOecUOlUXbxbpPNrJ1qtXL7dmzZq4b2fM41635YuT+hebP+PAf5DcphlMKP+FSCy4yPtZEXWJSLWSkZFBUlJSZYcRdwX/vV9xxRWVHYoEVKTfFTNb65wrdm+/TjPFwWw7SCbH4e0JMa2X2CKRqX2mxikqERGR6knJTBxkcpwsjtMlhnWycopfxCUiElQLFy6s7BCkBlEyEyddqMeC4QuiLj8hxl4cEQmu0u76EJHIt5KXRhcAi4icRA0aNODAgQMx/7EWqSmccxw4cKDQBeNlUc+MiMhJlJCQwK5du9AAuyIla9CgQbGHBJZGyYyIyElUt27dQk96FZHy02kmERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFA06jZAbL3/vv5MSMzbvXXT0qk9fTpcatfREQkHtQzEyA/ZmRyLDM+ycyxzMy4JkoiIiLxop6ZgGmQmEj7p5+q8Hq/vnZchdcpIiJyMqhnRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAKtTmUHEASzV80mMycz6vJZHKcL9eIYkYiIiBRQz0wUMnMyycrJirp8F+qRqGRGRETkpFDPTJS6tOjCguELoiu84KL4BiMiIiIh6pkRERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaEpmREREJNDKfM6MmbUDngJaA/nAPOfcf5lZC+BFoAOwA7jKOXfQX+dO4HogD7jVOfdOXKKvyvZuiu55M61T4MIH4h+PiIhINRXNQ/NygTucc+vMrAmw1szeBdKB951zD5jZNGAaMNXMugJjgWSgLfCemZ3tnMuLzy5UQa1Toiu3d1N84xAREakBykxmnHPZQLb//jszywDOAEYBg/1ii4BlwFR//gvOuR+B7Wb2FdAHWF7RwVdZ0fa06EnBIiIi5RbTNTNm1gHoAawEfuYnOgUJTyu/2BnAzrDVdvnzRERERCpc1MmMmTUG/gL8yjl3pLSiEea5CPX90szWmNma/fv3RxuGiIiISCFRDTRpZnXxEplnnXOv+rP3mVkb51y2mbUBvvHn7wLaha2eAOwpWqdzbh4wD6BXr17Fkp0g2nv//fyYkRnDCn6zfDCOsTneel8/O67E4scyM2mQmFieEEVERKqdaO5mMuBJIMM593DYor8C44EH/J+vh81/zswexrsAuDOwqiKDrqp+zMgsV8Lxz9wfyMwpJRlqBd803MkHb08AILFFIlP7TD2hbYmIiFQX0fTMnAtcC2wysw3+vOl4ScxLZnY98L/AlQDOuS/N7CVgC96dUDfVpDuZGiQm0v7pp6IrXHAB8ISneGHV7NITmSKycrJOIDoREZHqJ5q7mT4l8nUwAENKWOc+4L5yxFXjxNrDMsHvnREREanp9ARgERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0KIZaFJqiGOZmXx97bi41V8/KZHW06fHrX4REamZlMz4/nk8jy+zD3PP48vp2rYpMy9JruyQTqr6SYlxrf9YZvQjgouIiMRCyQzQtW1TTjlQG4At2UcqOZrKEe8ek3j2+IiISM2mZAa8XphvmwHQ9XjTSo5GREREYqELgEVERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAq1OZQcgNcexzEy+vnZc3Oqvn5RI6+nT41a/iIhUTUpm5KSon5QY1/qPZWbGtX4REam6lMzISRHvHpN49viIiEjVpmtmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBFqZyYyZ/dnMvjGzzWHz7jaz3Wa2wX+NCFt2p5l9ZWZZZjYsXoGLiIiIQHQ9MwuB4RHmP+Kc6+6/lgCYWVdgLJDsr/MnM6tdUcGKiIiIFFVmMuOc+xjIibK+UcALzrkfnXPbga+APuWIT0RERKRU5blm5mYz2+ifhjrVn3cGsDOszC5/XjFm9kszW2Nma/bv31+OMERERKQmO9Fk5n+As4DuQDbwB3++RSjrIlXgnJvnnOvlnOt1+umnn2AYIiIiUtOdUDLjnNvnnMtzzuUDT/CvU0m7gHZhRROAPeULUURERKRkJ5TMmFmbsMnLgII7nf4KjDWz+mZ2JtAZWFW+EEVERERKVuao2Wb2PDAYaGlmu4CZwGAz6453CmkHMAnAOfelmb0EbAFygZucc3lxiVxERESEKJIZ59zVEWY/WUr5+4D7yhOUiIiISLT0BGAREREJtDJ7ZiTO9m6CBReVXqZ1Clz4wMmJR0REJGCUzFSm1illl9m7qcRFWTlZTHh7QkybTGyRyNQ+U2NaR0REpCpTMlOZoultKaHXJrFFYsyby8rJinkdERGRqk7JTECdSO9KrL04IiIiQaALgEVERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmRGREREAk3JjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBpmQmgi3ZRxjz+HJmvfFlZYciIiIiZdCo2UV0bdsU8BIaERERqfqUzBQx85JkAMY8vrySIxEREZFo6DSTiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCrdo/NG/WG1+yZY/3NN8t2Ufo2qZpJUckIiIiFanaJzNb9hzh4uz/Jq3eTqgHjb6rAwsaFS+4dxO0Tjn5AYqIiEi5VPtkBiCt3k6S7X9LT1ZapyiZERERCaAakcwAXqIy4c3KjkJEREQqmC4AFhERkUBTMiMiIiKBpmRGREREAq3mXDMTZvaq2WTmZJZaZkc973buCW83JSsniy4tupyM0ERERCRGNbJnJjMnk6ycrKjLd2nRhcQWiXGMSERERE5UjeyZAS9BWTB8QYnLxzy+HIAFw/ufrJBERETkBNTInhkRERGpPpTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAKtxt7NJNXPscxMvr52XFzqrp+USOvp0+NSt4iIlI+SGakW6ifF7zlAxzJLf8CiiIhULiUzUi3Es9ckXr09IiJSMXTNjIiIiASakhkREREJNCUzIiIiEmhKZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBVmYyY2Z/NrNvzGxz2LwWZvaumW3zf54atuxOM/vKzLLMbFi8AhcRERGB6HpmFgLDi8ybBrzvnOsMvO9PY2ZdgbFAsr/On8ysdoVFKyIiIlJEmcmMc+5jIKfI7FHAIv/9IuDSsPkvOOd+dM5tB74C+lRMqCIiIiLFneg1Mz9zzmUD+D9b+fPPAHaGldvlzyvGzH5pZmvMbM3+/ftPMAwRERGp6Sr6AmCLMM9FKuicm+ec6+Wc63X66adXcBgiIiJSU5zoQJP7zKyNcy7bzNoA3/jzdwHtwsolAHvKE2Bl2pJ9hDGPLwega9umzLwkuZIjKr+snCwmvD0h6vKJLRKZ2mdqHCMSEREpnxNNZv4KjAce8H++Hjb/OTN7GGgLdAZWlTfIytC1bdPQ+y3ZRyoxkoqT2CIxpvJZOVlxikRERKTilJnMmNnzwGCgpZntAmbiJTEvmdn1wP8CVwI45740s5eALUAucJNzLi9OscdVeC9MQe9M0MXawxJLD46IiEhlKTOZcc5dXcKiISWUvw+4rzxBiYiIiERLTwAWERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQFMyIyIiIoGmZEZEREQCTcmMiIiIBFqZA02KCBzLzOTra8fFrf76SYm0nj49bvWLiFRnSmZEylA/KTGu9R/LzIxr/SIi1Z2SGZEyxLvHJJ49PiIiNYGumREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREREZFAUzIjIiIigaZkRkRERAJNyYyIiIgEmgaajNKW7COMeXw5AF3bNmXmJcmVHJGIiIiAkpmodG3bNPR+S/aRSoxEREREilIyE4XwXpiC3pmTau8mWHBR2eVap8CFD8Q/HhERkSpEyUxV1zolunJ7N8U3DhERkSpKyUxVF21PSzQ9NyIiItWQ7mYSERGRQFPPjJQqKyeLCW9PiGmdxBaJTO0zNU4RVU/HMjP5+tpxcam7flIiradPj0vdIiJVgZIZKVFii8SY18nKyYpDJNVb/aTY2zlaxzIz41a3iEhVoWRGSnQivSux9uIIce01iVdvj4hIVaJrZkRERCTQlMyIiIhIoCmZERERkUBTMiMiIiKBVuMuAN57//2M/exLAL5+NvaLI9P9sZm+/rRpsWXHMjNpkBi/O1NERESkuBrXM/NjRiatdv8zLnU3SEyM6222IiIiUlyN65kB+OaMU3jhlmQWDF8Q87q/8QeafHFS/4oOS0RERE5AjeuZERERkepFyYyIiIgEmpIZERERCbQaec1MtbV3Eyy4qPQyrVPgwgdOTjwiIiIngZKZ6qJ1Stll9m6KfxwiIiInmZKZ6iKa3payem1EREQCSMmMVLisnKyYRs9ObJF4QiN0i4iIgJIZqWCJLWJ7aGBWTlacIhERkZpCyYxUqFh7WGLpwREREYlEt2aLiIhIoJWrZ8bMdgDfAXlArnOul5m1AF4EOgA7gKuccwfLF6aIiIhIZBXRM3O+c667c66XPz0NeN851xl4358WERERiYt4nGYaBSzy3y8CLo3DNkRERESA8iczDlhqZmvN7Jf+vJ8557IB/J+tIq1oZr80szVmtmb//v3lDENERERqqvLezXSuc26PmbUC3jWzzGhXdM7NA+YB9OrVy5UzDhEREamhytUz45zb4//8BlgM9AH2mVkbAP/nN+UNUkRERKQkJ5zMmFkjM2tS8B64ANgM/BUY7xcbD7xe3iBFRERESlKe00w/AxabWUE9zznn3jaz1cBLZnY98L/AleUPU0RERCSyE05mnHP/AM6JMP8AMKQ8QYmIiIhES8MZiFRzxzIz+fracXGrv35SIq2nT49b/SIiZVEyI1KN1U+KbeDPWB3LjPoGRhGRuFEycwK2ZB9hzOPLAejatikzL0mu5IhEIot3j0k8e3xERKKlZCZGXds2Db3fkn2kEiMRERERUDITs/BemILeGREREak8SmZqmr2bYMFFZZdrnQIXPhD/eERERMpJyUxN0jolunJ7N8U3DhERkQqkZKYmibanJZqeGxERkSqivKNmi4iIiFQq9cyUk27TFhERqVxKZspBt2mLiIhUPiUz5aDbtEVERCqfkhkRKReN/SQilU3JjFS6rJwsJrw9IaZ1ElskMrXP1DhFJNHS2E8iUhUomZHIonm4XgU8WC+xRexfhlk5WeXaplQcjf0kIlWBkhkpLpqH61XQg/VOpHdlwtsTYu7NUU+OiEj1pWRGioumt6USH6wXa2+OenJERKo3JTMSOLH2sMR6PY6IiASLngAsIiIigaZkRkRERAJNp5lEpEqL53Ns9AwbkepByYyIVFnxfI6NnmEjUn0omRGRKiuevSZ6ho1I9aFrZkRERCTQ1DNTgbZkHwkNONm1bdNCA1GKiIhIfCiZqSBd2zYNvd+SfaQSIzmJohnyACpk2IPy0vhPEokGyRSpHpTMVJDwXpiC3plqLZohD6DChj0oD43/JJFokEyR6kPJjJyYaHtaKnHYgwInOv6TVG8aJFOk+lAyI1ICDWYpIhIMSmZEItBgliIiwaFkRiQCDWYpIhIces6MiIiIBJqSGREREQk0JTMiIiISaEpmREREJNCUzIiIiEigKZkRERGRQNOt2RJ/0YzhVAXGbxIRkWBSMiPxFc0YTlVg/CYREQkuJTNxsiX7CGMeX07Xtk0LDUJZ40TT21IFxm+qCBr+QESkciiZiYOubZsCXkIjNYOGPxARqTxKZuKgoCdmzOPLQz00RdX4HptqRsMfyMm29/77+TEjM271109KjNvI4kGOXaomJTNxVNBDU5R6bERqhmOZmXx97bi41P3P1asBOKV37wqv+1hm/BINgB8zMjmWmUmDxNh6NKMR79ilalIyE0cl9bxE6qkRkeqlflLFf1GHO6V377j1QMQrAQvXIDGR9k8/VeH1nozYpepRMiNSSWK9YBh00XCQ6DSHyMmjZEakEsR6wTDoomERkZIomRGpBCfSu6KLhuVkiuf1PvG6XkZqLiUzUjVE85Rg0JOCRU6CeF/v0yAxMa7biGciBrpbqipSMiOVL5qnBIOeFCxykgT5izreiZjulqqalMxUkpKePxOuxjyLJtqelgUXaZwnESlVvBMx3S1VNSmZqQQlPX8mnJ5FE4HGeYrJ7FWzycyJ/b9I3TElIkGjZKYSRNPbUvTpwTWml6Y0FTnO01vTokt8AtzLk5mTSVZOFl1adIl6Hd0xJSJBpGSmigrvvSnopZn1xpds2XOkUJkan+BEEs2pqK8/9X62H1B6PVVRtImY7aNLvUYsGL4g6qp1x5SIBFHckhkzGw78F1AbmO+cC+a/t5UkPEkp6J3ZsucIW7KP0LVNU52GKkm0FxO3H1B2r0tVHc177ybvVda+Hv/+5MQjIlLJ4pLMmFlt4DFgKLALWG1mf3XObYnH9mqSrm2a8uKk/joNVZKAnhKKVlZOFhPsOLRpBa1blV52706iP8FUZBvVoIdG1/5IEMV7EM54q6zb1uPVM9MH+Mo59w8AM3sBGAUomTlBBT0xXdt4p5/CT0Ot3J5TKTHVCNE+/+YkSLSDwHGvx6VeozLLd6EeidSLbRsn8GTiqmjNvjWVHYJUY0EdQDTeCmKvDOacq/hKza4AhjvnJvrT1wJ9nXM3h5X5JfBLf7ILEK8rD1sC38ap7upKbRYbtVfs1GaxUXvFTm0Wm6C0V3vn3OlFZ8arZ8YizCuUNTnn5gHz4rT9fwVitsY51yve26lO1GaxUXvFTm0WG7VX7NRmsQl6e9WKU727gHZh0wnAnjhtS0RERGqweCUzq4HOZnammdUDxgJ/jdO2REREpAaLy2km51yumd0MvIN3a/afnXNfxmNbUYj7qaxqSG0WG7VX7NRmsVF7xU5tFptAt1dcLgAWEREROVnidZpJRERE5KRQMiMiIiKBVm2SGTMbbmZZZvaVmU2LsNzM7L/95RvNLK0y4qwqomivwWZ22Mw2+K8ZlRFnVWFmfzazb8xscwnLdXwVEUWb6RgLY2btzOxDM8swsy/N7P9GKKPjLEyUbabjzGdmDcxslZl94bfXrAhlgnmMOecC/8K7yPjvQEegHvAF0LVImRHAW3jPwOkHrKzsuKt4ew0G/lbZsVaVFzAISAM2l7Bcx1fsbaZjrHB7tAHS/PdNgK36O1Yhbabj7F9tYUBj/31dYCXQr0iZQB5j1aVnJjR8gnPuOFAwfEK4UcBTzrMCaG5mbU52oFVENO0lYZxzHwOljRuh46uIKNpMwjjnsp1z6/z33wEZwBlFiuk4CxNlm4nPP26O+pN1/VfRu4ACeYxVl2TmDGBn2PQuih/Q0ZSpKaJti/5+d+RbZqZRLEun4+vE6BiLwMw6AD3w/nMOp+OsBKW0Geg4CzGz2ma2AfgGeNc5Vy2OsXgNZ3CylTl8QpRlaopo2mId3hgYR81sBPAa0DnegQWYjq/Y6RiLwMwaA38BfuWcO1J0cYRVavxxVkab6TgL45zLA7qbWXNgsZl1c86FX9cWyGOsuvTMRDN8goZY+Jcy28I5d6SgO9I5twSoa2YtT16IgaPjK0Y6xoozs7p4X8rPOudejVBEx1kRZbWZjrPInHOHgGXA8CKLAnmMVZdkJprhE/4KjPOv1O4HHHbOZZ/sQKuIMtvLzFqbmfnv++AdKwdOeqTBoeMrRjrGCvPb4kkgwzn3cAnFdJyFiabNdJz9i5md7vfIYGYNgZ8DmUWKBfIYqxanmVwJwyeY2WR/+VxgCd5V2l8B/wQmVFa8lS3K9roCmGJmucAPwFjnX+peE5nZ83h3RbQ0s13ATLyL53R8lSCKNtMxVti5wLXAJv+aBoDpwL+BjrMSRNNmOs7+pQ2wyMxq4yV1Lznn/lYdvis1nIGIiIgEWnU5zSQiIiI1lJIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKApmREBzCzPH1H3S/+x57ebWS1/WS8z++9S1u1gZv9+8qIttv1b/VGDn43zdn5lZqfEqe5KbcOTycyWmFlz/3Vj2Py2ZvZKBW1jh5ltMrNeFVDXg2a218x+XRGxicSDbs0WAczsqHOusf++FfAc8JlzbmYU6w4Gfu2cuziuQZa8/UzgQufc9iLz6zjncitwOzuAXs65byMsq+0/Jv1E6x5MOdqwvNuvDP5YQn9zznWLQ907KOGzOsH67gaOOuceqoj6RCqaemZEinDOfQP8ErjZfwrmYDP7G4CZnef34Gwws/Vm1gR4ABjoz7vN72X4xMzW+a//46872MyWmdkrZpZpZs+GPZm0t5l97vcKrTKzJuYNCPegma02s41mNqlorGY2F+gI/NXf9t1mNs/MlgJPmVl7M3vfX/99M/s3f72FZvY/Zvahmf3D368/+z08CyNs51agLfChmX3ozztqZveY2Uq8gfx2mP+YeL83a5n/vpFf92q/zSKN0F60DRuY2QK/d2G9mZ0fIabBfvzP4T00rcT2MrPf+HV9YWYP+PO6m9kKv+xiMzu1tOPCb9unzewDM9tmZjf4883f7mZ/G2P8+W3M7GN/nzab2UB/fkE7PQCc5S9/0D9uNvtlIu6/maWb2atm9rYfw3+WFnNY7JGOr3Qze83M3jCz7WZ2s3k9kuv9dmkRTd0iVYJzTi+9avwL77/OovMOAj/De4rt3/x5bwDn+u8b4z1FO7Tcn38K0MB/3xlY478fDBzGG+ukFrAcGADUA/4B9PbLNfXr/SVwlz+vPrAGODNCnDuAlv77u4G1QMOweMf7768DXvPfLwRewBtUbhRwBEjx41oLdC9tO/60A64qIY5ewDL//f3AL/z3zYGtQKMidRdtwzuABf77ROB/C9q0yDrfF7RJSe0FXAh8DpziL2vh/9wInOe/vwf4YxnHyN3AF0BDoCXeyMJtgcuBd/Gepv0zP9Y2/j781l+3NtAkvJ2ADsDmsPpD0yXtP5COd6w086e/BtqVcUyUdHyl4z3ltQlwOt6xOdkv8wjeoI3h+/7ryv491Uuvkl7qmREpWaTRYz8DHvZ7Kpq7yKdx6gJPmNkm4GWga9iyVc65Xc65fGAD3hdYFyDbObcaQgPj5QIX4I2RsgFYCZxGdKP9/tU594P/vj/eKTOAp/GSpwJvOOccsAnY55zb5Mf1pR9XWfLwBvgrywXANH8/luF9Cf9bGesM8OPFOZeJ96V9doRyq9y/Tq+V1F4/x0sM/unXl2NmzfA+v4/8dRcBg6LYl9edcz847/TNh0AfP9bnnXN5zrl9wEdAb7wx0CaYd4omxTn3XRT1R7P/7zvnDjvnjgFbgPZl1FXS8QXwoXPuO+fcfrxk5g1//iaiOwZEqoRqMTaTSEUzs454X9bfAEkF851zD5jZm3hjl6wws59HWP02YB9wDl5Px7GwZT+Gvc/D+x00vF6OYmEAtzjn3okx/O9LWRa+nYJY8ovElU90fxuOucLXqeTyr1PXDcLmG3C5cy4rijrD14lG+L5GbC8zG07k9j0RRetxlBCrc+5jMxsEXAQ8bWYPOueeinI7pe1/pGOorLpK2v+in3v4MaHvBwkM9cyIFGFmpwNzgTl+z0X4srP8HozZeKcxEoHv8LrqCzTD+084H28QvNplbDITaGtmvf1tNDGzOngDgU4xs7r+/LPNrFGMu/M53qjoANcAn8a4frii+1nUDqCn//7ysPnvALeYha4P6hFF3R/jxYuZnY3Xk1NWMlRSey0FrjP/Tiwza+GcOwwcLLiOBe9z+ihSpUWM8q9nOQ3vNNdqP9Yx/jU7p+P18Kwys/bAN865J/BGdk4rY5/Dncj+l6Sk40uk2tABLeJp6J+eqIvXw/A08HCEcr/yL8bMw+vifwvvv9hcM/sC71qUPwF/MbMr8U5FlNZTgnPuuH/R6KNm1hBvZN+fA/PxuvrX+YnAfuDSGPfrVuDPZvYf/vrlGQF3HvCWmWU754pdkAvMAp40s+l4p3kK/D/gj8BGfz92AEXvWtpI8Tac65+qywXSnXM/UrqI7eWce9vMugNrzOw43qjA04Hx/jZOwbumZAKAmd2Dd53TXyNsYxXwJl5y8f+cc3vMbDHe6bwv8HpAfuOc22tm44H/MLOfgKPAuPCKnHMHzOwz/6Lft4DHwhZH3H8/H4xJKceXSLWhW7NFRKJgAbo92XRrttQwOs0kIlL97Afetwp6aB7wC8roYRSpTOqZERERkUBTz4yIiIgEmpIZERERCTQlMyIiIhJoSmZEREQk0JTMiIiISKD9/9p9iBjuIIYOAAAAAElFTkSuQmCC\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera corner configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [], + "source": [ + "corner6_cam_positions = all_cam_positions[(4,5,6,7,10,11),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [], + "source": [ + "corner6_cam_directions = [[+1, +1.9, +1],\n", + " [-1, -1.9, +1],\n", + " [-1, +1.9, +1],\n", + " [+1, +1.9, -1],\n", + " [+1, -1.9, -1],\n", + " [-1, -1.9, -1]]" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [], + "source": [ + "camera_positions = corner6_cam_positions\n", + "camera_directions = corner6_cam_directions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([0.0, 0.0, 0.0, 0.0, 0.0, 0.0])#[np.pi/2, np.pi/2, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({3: 519, 6: 397, 5: 235, 4: 121})\n" + ] + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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nV2awAKim1OyLWR0ASjODBQxppJmMFpWafTGrA0AtZrCArpnJgHjsvQF68GgG6x81CgOwl9sMhpkMiON2tl9KyYcPoDuWCAJds4naMknisYQT6JkAC6Bzt9mC8/lcuygkAW9KPnwAfbNEEKBzlknGYnkcQN/MYMFOSn+13uOruC/vbTJbEIvlcW3SxwJLmcGCnZT+ar3HV3Ff3mG7W8BLW3rpY2VwhPLMYMFOSn+13uOr+LO/w1fZcUW991HLRXnP3vvIfewa9mTCDuZ5Xvzz8vIyA6w1TdOcUpqnaapdlPAul8s8TdN8uVxqFyWLqPc+arme1Vu7Kam3e7+WtgL5pJSu852YyRJBGNSey0QkWViut2WYUe991HI9q7d2U1Jv934tS1RhB/eirkc/ZrDa1tNXq56upZbRv+JGVatte6bycP/4K/cF+pYezGAJsAbS04C6p2upZcuLv9SgwWCknjXP1Gj3ac316pv6s6W9aw/b9dbf9HY9oxNg0dVD3dO1tKjUoMFgpB5BxGOCzzaUqvst7V172K63/qa36xmdAAvIpqUZLAOc/Ear09Gut1WlBq7uf1291X9v1zO6RwHW4fP/W+Z4PM7X6zXb/i+A0t7e3tL7+3uapsnGbgiiRJId5zsBezscDj/meT7+/ueyCAJdGz1jGERUIuuh7HhAFA4aBrp2G3T5op3XKAf1jnKde9vjQF2AWgRYAKx2m4E4n8/f/t1oQcqa8qy5Tpbz4QPomSWCAKy2ZulltENw15THElMA1hJgAbDamv0u0YKUNeWxrweAtSwRBNhZtCVzN6XKFW05WLTylBa1vQH0SoAFsLOo+3qilqsVUQMZ9xVgXwIsILyoA9dnRc2gFrVcrYgayPR2X3vrD4D+CLCgkoiDhIhlSinuwPVZUZeoRS1XK6IGMr3d16j9QdT+E9ifAAsqiThIiFimlMoMXA2G4sh9L2rd294CmRxK3IuogWzU/lNfB/uTRRAqiZZZLaWYZUqpTCa3aKnDR5b7Xri3cZS4F1EzO0btPz0PsD8BFlQScZAQsUylRB0MjSj3vXBv4xjpXkTtP0e6BxDFYZ7nxX/5eDzO1+u1YHEA2vXx8ZHO53M6nU6WidEc7RdgncPh8GOe5+Pvf24GCyATS3FomfYLkIckFwBfWLNBPOrm+7+y4b2OFup9Tftt4XoAarFEEOALb29v6f39PU3T1MVX/d6upxW91Xtv1wPwjEdLBM1gAXyh5KxUjVmAFmbZelSj3ku2L+0I4DEzWDTFJmyiW9NGzQJQ0pr2pW8FWE+SC7pgEzbRrWmj0idT0pr2pW+lBT4E0AoBFk0xICW6NW006rk5NT07gDLw+rs17UvfSgt8CKAVlggCBDZa4PDsssnRlluO1i4gJe2eeCS54BdS7NKaUdvs7Yvt+XyuXZRdPJs8YbSkC6O1i5tR+wE+3WZlBVdEZ4ngoEyz05pR2+xoS7eeXTY52nLL0drFzaj9AG0z8zYeAdagRn05065R2+xogQPLjNouRu0HaJsPA+OxRHBQptlJqa3lNtos0FI/0FL/SlmjLWFuQennM0SApROCOkbdx/GM1vup1svfi5bvQ8tlr0H/yk1LHwZGUfr5DLFE0NQp1GG5zXKt91Otl78XLd+Hlsteg/4V4ir9fIYIsHRCjCTSZtdR93E8o/V+qvXy96Ll+9By2WuI1r9GevdAbaWfT+dgwc5GO68HgPq8eyA/52BBEDa7skWP+2ByX5M6gr/z7oH9mMECaEiPX6FzX5M6AmAPj2awQuzBAmCZHvfB5L4mdQRATWawAAAAVrIHCwAAoDABFsCAJE3Yh3oGGI8ACwjJwLSs0qfY80k9l6WfACISYAEh1RyYjjBok7J5HyPUc83nRQALRCTAogsjDIhHU3NgOsKg7XaK/evr6y6/L8ozunc59q7nGmo+LyMEsEB7pGmnC7cXfErJGTGduA1Ma5ASO78oz2iUcvSk5vNSs5+gnI+Pj3Q+n9PpdOr64wT9EmDRBQPibbzMfmXQll+UZzRKOXriefmV/nQ7H0JonSWCdGGEZTgljbAkrgd7Lm/L/buiPKO5y9HyPaEM/el2ln7SvHmeF/+8vLzMjOtyuczTNM2Xy6V2UbpUs37d2zZM0zSnlOZpmsL8rh7bzpprinhPqEtfDuNIKV3nOzGTAKtzOTtbL/dlnq3zkQe0LLPnvV/6u3rsF9ZcU8R7wriefR61reXUFX8lwBpUzsHPs53KaJ1R6RdcjwNa2tXj893jNdG2pW2y9Ac+YoyriEOANagID+9oHXfpOo9wTwHYT+n36GjvlS3Xa2UQfyXAoprROm6WWdMutCFgZPrAvKIENu5r+x4FWIfP/2+Z4/E4X6/XHLk1gMG9vb2l9/f3NE3Tt2l41/xdoF9rU6BLmc492gW5HA6HH/M8H3//c2nagSrWpOHdM2WvVNiwzp7PzNoU6FKmc0+UYyPolwALCmt9wF6q/GtecEv+bq5yGpDBOjmfme+e47UfW0p9nGm9XwcKu7du8NGPPVj0YO81z1HWej+rlfLnKqc18bDOiJv+WynnV/R1sF2S5CIvHVO7nnkxRsk4VEPJZBQ566b1ev6rnq6FsnprK61cTyvl/MqeQWIP9cUn9/JXAqzMevh6NapnOgf3e5m19aRe71MvLKWtPFbzg08L9jzbUjvth3v5KwFWZj10xD1cw15aqquaZTWgyUO9sJS28lhLH3xauo97rwJpXW/X3tv1bCXA4m98heiT+wrQ1geflvptA+x1Wrq3rPcowPrHTrk02KDUeQ23rEp7pL5mP+4rwM/so6X+fk4t9ds166lFJe+t87zictBwAxyyCgDAXxkf1ueg4YbtechqBM4XIZecbUm7hHzPgecJthttfNiUe+sGH/3Yg8UerFcml5xtyTlbtCriOVX6eXLSr1JLsgeLVrS0Fp3YcralXP/W+XxO7+/vKaVkSQe7yNnmcj0H+nly0q8SjT1YABks3WxsUzJ70zbpnbZLLY/2YAmwADKw2ZjWacMA60hyAexupI3sNhvTutHa8Ej9E7AvM1hAMb6IA1Hpn4CtHs1gSXIBFGMjOxCV/gkoxQwWbGRzLQDAeOzBgkJu6WHP53PtogDAZvanwTaWCMJGlpkA0BPnSsE2ZrBgo9fX1/THH3+EXR44+pfI0a9/raX1NUK9qgtKid5mRssoCdnN87z45+XlZQbaMk3TnFKap2mqXZQqRr/+tZbW1wj1qi7KuFwu8zRN8+VyqV2UarQZ6ENK6TrfiZksEYTOjb6EcfTrX2tpfY1Qr+qiDMvPtBnonSyCAMBuZF4FeiGLIMDg9t73EX2fifqoI/q+VYCtLBEEGMTeS7OiLwVTHwCUIMACGMTe+z6i7zNRHwCUYA/WAKx3BwCAvOzBGthtWcr5fK5dFDpnjwnQKv0Xe9Le+ibAGkBvBwbqlOISzAOt0n/F1eN7X3vrmz1YA7hlbOqFjeJx2WMCtEr/FVeP733trW9msGhObzNyPZF+OYbIX3trlU2d8B39V1w9vve1t75JcgHQmbe3t/T+/p6maQr3tbdW2dQJALlJcgEMY/QZgchfe2uVTZ3ENfrzCvTHDBbQHTMC0A7PK9CqRzNYklwA3bF5GNrheQV6Y4kgbBB5aUvkspVm8zC0Y+TndeR+GnomwIINIp9jEblsAMTupwV/8DxLBGGDyEtbIpcNgNj9dI9nT8FeJLkAYBcfHx/pfD6n0+m0+3Kwmr8bWuSZge9J0w7sxtKSeiLXfc3lUJGXYqUU+771Tt3fN/LeONiquwBLRwn1RR/M9ixy3dc87yn6WVOR71vv1D3E1eq4vrs9WNYMQ32R9xX0LnLd376Ij/a7l4h833qn7iGuVsf13e3BsmYY+uc5hzF41mFs0fuAR3uwuguwgP69vb2l9/f3NE1TU1+0gHU860BkjwKs7pYIAv2zpAfG4FkHWmQGC/hF9Ol4AIAIpGkHUkrfZ+QpmVGr1WxALatV51t+75r/duv1tVg/xPPd/XS/YTDzPC/+eXl5mYG2TdM0p5TmaZru/v+Xy2Wepmm+XC67/+7Svz+SNde5pU6W1HkJW37vmv926/W1WD97tZ1WLLnG0vXw3f2s1c6AslJK1/lOzCTAgsHUHHAt+d2jDET2CiJq3e8tv3fPAKLF+tkzAG3BkmssXQ/f3c8RAl0YkQALOtbTy7una/mKWQiepe38KsIMFjCmRwGWJBc0TUKGT1IZA/TBe+2TeqAFklzQpZIJGZ5VYzPz6XRK0zRJZTyoPRM9jJpUYq86kgyBGu+1iO0u4vsdFrs3rfXoxxJBoom47KPnPQ8R6zuaGnW0Z6KHEZNKrP3v90rwkZNnO44W+5AStElakOzB4kanVVbP9RvxJRxNjTraM9HDiEkl1v73eyX4yMmz/b2e+/aerw1KEmDxJy/SvpV8UXoJf08d0SLt9nsl353qv3/ucZ8eBVj/2HtJIvXd9unYr9On27r1lFL2hBevr6+SaHxDHdEi7fZ7Jd+dJfttYnCPxyLAGpAXad8E0AD5lXx36rf75x6PRZp2AACAlaRph0ZFTJ8LAMB9AiyoZGng5CwQnlE7MK/9+5eqXc7av582aTcQ3L3MF49+ZBGEfJZmpJJ5KJ4W7kntbKG1f/9StctZ+/cv0UJ7H433B8SQZBGEWJZueJWUJJ4WskHV3lBd+/cvVbuctX//Ei2099EsbTfuHdQhyQX8t4+Pj3Q+n9PpdEqvr6+1i0Ng2goj0d7btfe901YYzaMkFwIshrCk0397e0vv7+9pmiZf+gBgpaXvUYEYvXgUYFkiyBCWLJNoYakOAERl6SJ8kkWQIZxOpzRN05ed/m2vk69py8hiBfROP7fO0vfokncytMwSQeApllQCvdPPAV+xRBDIypJKoHf6OeAZZrAAAABWejSDZQ8WTbIuXh3wWO22Ufv3rxGhrBHKQEzaxif1QHPunT786Ofl5WW/o5HhC0tPsS/hcrnM0zTNl8tl99/9VzXrYFRR7v13areN2r9/jQhljVCGJVpp/z1ppW2Uph6IKqV0ne/ETPZg0aSa6+KjpJe1N2B/Ue79d2q3jdq/f40IZY1QhiVaaf89idI2ap9bFaUeYCl7sGCl2i8a6nHvGZn2Py7ZFOG+R3uwBFgLeKkAAKMyDuIrI7cPado3sCwCABjV7QBhuMc4+e9kEVxg9BPHZe8BAOCe0cfJ9wiwFrh9uRlt2vPm9mXifD7XLspDgkAAaF8L7/MWyrin0cfJ91giyLdayN5jehoA2tfC+7yFMlKXGSy+1cKXCdPT1FDzK2aLX1Brl7n273+GNsZoWnift1BGKrt3ONajHwcNA/Mc+8DRNWXbeh01D7/c+rvXXnuOe177sNAcv3/vehuljfXSpwBjSQ8OGhZgAavVHih/ZU3Z9g5Sctp74F4jOMmtRpCoje3zLJYUuWxAXQIsIJvaA+Wv9PLVvLQaM1g9UG/L9fIsRi4bUNejAMtBwwAAACs9OmhYkgvCsbEaxra2D9BnwNj0AUQjwCKcFs7dYl+1Xp45fu+af2Pv31dCjt+/tg/I0Wf0UG8jtLXa94mYjBsI5966wUc/9mCxB+vdlxmpnmptMs/xe/fe6F97Q36LmfrmuY96G6Gt1b5Pexupn99CPVFLkuSCGkbr9Pa83pEGGrXaUY7fu/dG/9rPXO3f/6za5dbW4v7Omvbu50eq35GulXIeBViSXFDU29tben9/T9M0DXHa+Z7X+/Hxkc7nczqdTqEPgQbgOXv38yO9s0e6Vsp5lOTiHzUKwzhup5yPctr5ntf7+vrqpQDQsb37+ZHe2SNdK/szgwUAALCSNO0AAACFCbA6In0tAEDbjOfaJ8DqiHMgKEVnD/BJf0hpxnPtE2AFsrXTPp1OaZomGzbJTmcP8El/SGlbx3M+AtQnwApka6d9yzYkZTe5lQ7eW3kZRClnlHKsEaXMUcqxRpQyRynHV/Yoo4+ZlLZ1POcjQAD3Dsd69OOg4bIceseoWjk0OUo5o5RjjShljlKONaKUOUo5vtJCGaE048n9pAcHDTsHKxDnGq3nsN0+tHIeSZRyRinHGlHKHKUca0Qpc5RyfKWFMrKcd/xzjCfrcw4WTXMSOwD0yTue6JyDRZeshf+phf0RADymH/+VdzytMoMFnfClD6Bt+nFoy6MZLHuwoBP2HgC0TT8OfbBEEDqxNa2rpSkA22ztRx23An0QYK1kEEqvnJsBsI1+lFEYD39NgLVS752nB6ZPS+6rzcQA2yzpR71n+zXSve19PLzZvcOxHv04aLj/w9sc0phPpLbivgLEEKk/jvSe6kGke1uatvMpPThoWIDFLzww+UTqaCPe14hleiRKWaOUY61o5Y5WnqWilDtKOb4TtZyRyhXpPdWDSPeWfQiwYGc62q+19GKPUtYo5VgrWrmjlWepKOWOUo7vtFLOmrynYJtHAZY07VDILRsU97WUjjhKWaOUY61o5Y5WnqWilDtKOb7TSjlr8p6CMhw0DAAAsNKjg4ZlEQQAAMhEgAUBjZTqFYBtvDMgFgHWDnR8rOV8CQCW8s7gWcaoZUhysYNbx5dSspmURWzOBmAp7wyeZYxahgBrBzo+1pLZCYClvDN4ljFqGZYI7uDW8b2+vtYuCoGYlgegNO8avmKMWoYACyqxZv6n2gOA2r8felLzefIs/513DexPgAWVnE6nNE3T6mn5HgcQtQcAOX7/2vuS6z5GaQ9RyrFVlOuo1T5y/N6az3PtvqSULffl2XcNsME8z4t/Xl5eZqCuaZrmlNI8TVPtomRzuVzmaZrmy+XS7O9fe19y3cco7SFnOdbej5ztp7f6rNEuaz7PtfuSUqK0S+BXKaXrfCdmEmDRlV5frn81wjW2qFZQEKU91AxyagZ3pdRqH1Gun1+NcF9GuEb68yjAOnz+f8scj8f5er1mnUGDnN7e3tL7+3uapklGJWjUx8dHOp/P6XQ6Ldp4vfbvA/F4f9Oiw+HwY57n4+9/Lk07XZFuFNq3NuW0FNXQPu9veiLJBV2RbrRfazZ5R0lUAHytVnIYfopSp97f9ESABQVEeWH1ZE12sBpZAaN75np6q4PcatZplHuztRxrn9VeswTWpE7/LsrzRcPubcx69NNDkgubKMtRtz/J+JTfmvZVIytgKbmeq2eup8fkETnLUrNOo7TPreWQhKM+dfp3UZ6vEbTe/pIsgp88NOWo259a7zCIcw9zPVfPXE+P6c9zlqVmnUZpn1HKATlp1/uJ9G54hgDrv3loylG3kF8vz1Wk64hUFoCRtd4fPwqwpGmHHUgjDUAE3keQz6M07ZJcwA5sIgbgO3skV/A+gvKcgwU72ON8D18lAdp2C35SSsXOdnPeFJQnwIId7HEQ6h4vZgDK2SP4cTA3lCfAgk74KgnQNsEP9EGABZ3wYgYAqE+SCwAAgEwEWMCQ9sjWBaPznAEjEmAxJC99Wk5VHLX9Ri3XGhGvIWKZlmr5OSOfltswPOXe6cOPfl5eXvY+IBmKmKZpTinN0zRt/rdaP4V8VC3ft5ztN6eo5Voj4jVELNNSLT9nI8t931puw/CVlNJ1vhMzSXLBkHJm3JMevU0tJwWJmjEyarnWiHgNEcu0VMvP2chyv9dabsPwjMNn8LXM8Xicr9drweJAexzwC0BPvNdgmcPh8GOe5+Pf/lyABQAAsM6jAEuSCwAAgEwEWPAFmY8A4O+8H+ExAVYFOqV2SDEMAH/n/dgmY9B9yCJYgaxz7ZD5CAD+zvuxTcag+zCDVcHpdErTNOmUGnBLMdxaFiVfqADa0Gp/3er7cXTGoPsQYFWgUxpLjZenpRsAbajRX7ca1LGdMeg+LBGEwmpMx1u6AdCGGv21ZWJQlhksKKzGdLwvVI/5cgv789w9VqO/HnGZmDbIngRYVDFSRyfYiaX15ZNRn52o5Vor6nVELddSrT93vRnxvaQNsidLBKnC8gRqaX35ZNRnJ2q51op6HVHLtVTrzx3t0wbZkwCLKnR01HL7ctuqqM9O1HKtFfU6opZrqdafO9qnDbKnwzzPi//y8Xicr9drweIAAADEdzgcfszzfPz9z+3BAgAAyESABQAAkIkAiy60nmELAPjknU7rJLmgC61n2AIAPnmn0zoBFl1oPcMWAPDJO53WySIIAACwkiyCAEDX7N0BIhBgASGsHRjlGkgZkEF+tZ7P296d8/m86ffuSR+0jvqiCfM8L/55eXmZoZbL5TJP0zRfLpcQ/05kLV7jNE1zSmmepqnI3y/97+TS4r37StTriVquZ0W7nlrPZ7R6WCJaH1RKrnszSn3RhpTSdb4TMwmwaEavA+oSWrzGtS/fXgPunPfu2WvLWSdR22Lucj1TZz3Xc6/PZwkjXOM852ujo9QXbRBg0Twv7OVGuMZeRRh0RwjySstdrmfqbIR6hhttlB4JsCAQLxr2EGEGaxS1Z7DgK9oalPEowJKmHSp4e3tL7+/vaZomhygCUJR3DpQhTTsEcjqd0jRNXR+iKNMTEN0o/dQI7xyIRIAFFby+vqY//vgjvb6+1i5KMS2mS/7KKAMx+ErO5yDCM9VbP/XICO8ciESABRQR5YtprkHcswOxCINIuOeZtpkzIIkQ3ETpp4DO3NuY9ehHkgugNbVTA8sUt06UxBxR67p2lsmcvz9qHQMslWQRBEZUexBXe0BcWoR051v+u73+vVwE7ABxPAqw/lFr5gxgD7e9Bz38/tsypkjLmW7LvFJKWa7z2WvMXTcR6zqlvOWq/WwA9EqadgCe9vHxkc7nczqdTjbQA9Xpk9iTNO2EJxnANuqPGmQng3z049tFSJ4ClggSRu6lRqNRfwBt049vF3V5L2Mxg9Ww3r50RUyX21IdR6w/AJZrrR+P+I7sdVY9Yl3zmD1YDXt7e0vv7+9pmiZfugqpUcfWjwOwRq33hnHIftR1TI/2YFki2DDT4OXVqGNLRADiaOGjV633Rs1xSAv3JSdjvraYwaIJI3WkLVxrC2UEyKGFmYMR++QW7gv9M4NF00aa1fnubJoIL9KR7gcwtigzB1/1/SOeaRblvsA9AiyaoCP9KUJw0/L9iBCgwmhafu6iBC8R+v5IotwXuEeARRN0pD9FCG5avh8GKfQsaiDjudsuQt8PLCNNOzSm1xS0e4mcBrm3NLwtXE8LZVwj6iGrkZ+7Vuj7oR1msIChRJ596+0rfwvX00IZ14g6yxH5uQPITYAFEETUwfGzWrieFsq4hkAGoD5p2gEAAFZ6lKbdHiwAAIBMBFgAAACZCLAAAAAyEWABAABkIsACAADIRIAFAEBXejtEnLYIsAhBRxifewSMTj/Yjtsh4ufzuXZRGJCDhgnh1hGmlBySGZR7BIxulH7w4+Mjnc/ndDqd0uvra+3iPKW3Q8RpixksQjidTmmapmY7whG+arZ+jwC2aq0ffPbd1MPsz+vra/rjjz+aDRBpmwCLEFrvCJ95GbUWlLV8j1qra+hZy89ja/3gs4FSa4EkRCPA4m9afvnV8szLqIcvhK1Q1xCH53E/zwZKrQWSURg/cSPA4m+8/NZ75mXkC+F+ote1lzK5RW5T0Z/H1nx1rwVK+zJ+4k/zPC/+eXl5menf5XKZp2maL5dL7aIMyz0YyzRNc0ppnqapdlGyaaUNt1LOtXpsU9znXsfRa3/CYyml63wnZpJFkL+5ffGinlEyVfGpx2xXrbThVsq5Vo9tivvc6ziMn7gRYEFAXphj6fGl3EobbqWca/XYprjPvd6mh5T0xGMPFkVF3gewtzV1Yd08rWulDbdSTsihtXfyHuW1b4oSzGBRVOnlNy19eep1KRIAbWjtPbRHeXudxaYuARZFle64WnpZ6MQBqKm199Ae5bXEkhIOnwkwljkej/P1ei1YHFinpRksAAD6cTgcfszzfPz9z+3Bomn2T9TR2jp+gGfp74C1LBEEVmtpaSbAFvo7YC0BFrBaa+v4AZ6lvwPWskQQGlVz2Uq0pZmW8EBfIj3TNfu7SPUALGcGCxpl2cpP6gL64pn+pB6gTWawoFGn0ylN02TZSspbF74Yw3q5nxv92yf1AG0SYEGjoi3TqylnXdy+GJ/P51X/XYnATLDHd3K3kWf/vWefm0f0b5/UA7RJgAXwF89+Mc49wCz1b+Y0QgAY/Rpzt5Fn/z0zLQB/Mc/z4p+Xl5cZgL+7XC7zNE3z5XIJ/W/mNE3TnFKap2nK9m9uueYS9VXiGnPKfc3R2xz5uNewXUrpOt+JmQRYUNjIL7GRr30E0QKaaAEf8Y18f6N/PIAWCLCgkpFfYs9c+8gDHuLNYNGOZ+7/yP2z5wW2exRgSdMOhY18SOUz1y4t8dhum/r3/m9p3zN9x0j988fHRzqfz+l0OqXX11fPCxR0+Ay+ljkej/P1ei1YHOjf7y85fqV+YAy5n3V9x9fe3t7S+/t7mqZJYAWZHA6HH/M8H3//czNYsDMzNF/L+VXVgAviyt0XmpH52kizdVCbNO2wM+mM9xM9zXlu0VOK872R7qG+cF/O1IL9CLBgZ15y+4k8gCsxkN4SUI40sC9tS12W+CgQ9d7qC4FeWSIIdCvykqESS0W3LAEqUZ4WlmiWKOOWuiyxjMuyZIB9CbAAKigxkN4SUI46sI8W6Jb4KGDvTVwtfIQA1pNFEDrlxU1tLbTBFspIv2T2g7bJIgiDaWH2gL5FXqJ500IZ6ddIs4s+ZjASARbDGaWTH+nFDdCikQJ8H/0YiQCL4YzSyY/04gYgNh/9Hhvlw+9IBFiD8PD+pJMHgH356PfYKB9+RyLAGoSH9yedPAAQhQ+//RFgDcLDCwAQjw+//fkftQtQW9QT7nO7PbyjLw+sZZR2BkB83klE0mN7HD7Aui2dO5/PtYtCx7Sz/HrskIFfec7L8E5aT1ssp8f2OPwSQUvnnidxxnLaWX72FUL/POdleCetpy2W02N7PMzzvPgvH4/H+Xq9FiwOLXECPTUJ8KF/nnOi0Ba553A4/Jjn+fi3Pxdg8SydDeTnueJZ2g7Avh4FWMMvEeR5st5Afpah8CxtByCG4ZNcQCQ20XI6ndI0TU2sRR+hvbZ0jS21Hcpoqb1CzywRhEDsa6MlI7TXEa6RfmivsK9HSwTNYEEgvkDTkhHa6wjXSD/2aK9myeJwL+ISYDXGw1TPHnW/14HQ2hE5jHCA+QjXSHl79bnPttc15evxzKJWuRdxSXLRGJuY61lT99GzeWlHAPuJ3ueuKV+PZxa1yr2IS4DVGA9TPWvqPvrLVDsC2E/0PndN+WQQjsO9iEuSCygg+gwWAADbOAcLduSrEgDAmCS5AAAAyESABQAAkIkACwCApjl+hEgEWABAeAbQfMWZUEQiwCIkL1Ie0TZgTAbQfOV0OqVpmsKmwmcssggSUvRzpKhH24AxRT9Lirpk7yUSARYheZHyiLYBYzKABlrhoGEA6IiDzgH28eigYXuwAAKwt4xc7FUCqEuABYMzsI+htUHxSO2mtWu12T+GXO2mtfYH2IMFzcq1DEjSiBha21s2Urtp7VrtVYohV7tprf0BAixoVq6XbmsD+161Nigeqd2MdK3kk6vdaH/QHkkuoFE2sgMA1PMoyYUZLGhUazMeAAAjkOQCAAAgEwEWAABAJgIsAACATARYAAAAmQiwYFAOrwQo71Ffqw+GfgmwoHOPXuK3c7TO53OlkuVjoAJ96emZftTX9tQHA7+Spr0C5xexp0cHEvd0eGWuQ5eBGHp6ph/1tT31wfTB+DQfAVYFPb04iO/RS7ync7QMVKAvPT3Tj/ra1vpgg+/+GZ/mY4lgBafTKU3T1MWLY1QtLV+5vcR7fiGOcI2QU/Q+zDO9n6VtwZLGGEo+u8anGc3zvPjn5eVlJp7L5TJP0zRfLpfaRRnGNE1zSmmepunLv+feMM/aAfEs7cPon/dZWzy7saSUrvOdmMkSwQ6Y0t3f0uUr7g0paQfE09MSPLZZ2hZyLWm01HAbz24j7kVdj37MYMXkq9I6e9aXe8M8l2sHkdtX5LL9rmRZt/7bLdUjLGEGhp6kBzNYAiyGo3OnF1vbcsnBe0vPWcmybv23W6pHWMJHA3ryKMCyRJDhmF6nF1vbcsmliy09ZyXLuvXfbqkeYYnWsifCMw6fwdcyx+Nxvl6vBYsDwF7shQCA5x0Ohx/zPB9//3Np2oGhRE9PvSepsNmL5w4YiQALGIqzXOB5zwZKnrs+CJRhGQEWMJQtBykaXDC6ZwMlB5iWtVffJFCGZSS5gJX22rdif0wZWzZYO8+K0T2bdENig7L26pskXYFlBFiw0l4vMoP5eEoNLgTT5FaqTQmUYtor8HH/YRkBFqy014vMl8J4Sg0uBNOfcgQFgtVP2tRYBD4QiwALVtrrReaFOY6WgumSAUyOoKBkYNFS8NZSmwLojQALoLKWgunohxOXDCxamhVqqU0B9EaABcBiJQOYHEFBycDCrBAASxzmeV78l4/H43y9XgsWBwAAIL7D4fBjnufj73/uHCwAAIBMBFgAABk4jBxISYAF/MYAAeA5t0Qo5/P5zz/Tp8J4BFgwqEcv/XsDBAC+dzqd0jRNvyRC0afCeGQRhEE9SjktUxrAc+5lsdSnwnhkEYRBtXRoKgBANI+yCJrBgkE5iBQAID97sAAAKpEEA/ojwIKOlXxxGxQAIyjd10mCAf0RYEHHSr64DQqgbT6SLFO6r7uXeTAS7QTWE2DBRpFfPiVf3NEHBVFEbh+MzUeSZZ7t65Y++7f9sFGTDWkn8IR5nhf/vLy8zMCvpmmaU0rzNE21i/K0y+UyT9M0Xy6X2kXpTg/tgz557stq6dn/qi1oJ/BYSuk634mZZBGEjb4646SVVOiPzsRiO2fgtKOV5zUXmUTLaunZ/+odoJ3AegIs2Oirl08rgUtLA4HWjDY4aTlIaeV5pQ0tPfveAZCXAAsKauWl1dJAgNhaDlJaeV4hN+8AyOvwuXxwmePxOF+v14LFAaBlLc9gAcAah8PhxzzPx9//3AwWANn4Eg7A6KRpBwAAyESAVYmzcQAA2mdMx+8EWJW0enCfToSttCGgBn0PpbQ6prvHc5KHPViVtJqtquUMYcSgDQE16HsopdUx3T2ekzwEWJW0uhG8p06EOrQhoAZ9D6W0Oqa7x3OShzTtAAAAKz1K024PFgAAQCYCLACAJ0kKAPxOgAV8yeAB4NO9/rCnDHJAHgIs4Eu/Dx4EXMCo7gVTp9MpTdMkKQDwJ1kEgS/9nlFICldgVPcyrPWUQQ7IwwwW8KXb4OH19TWl5GvtGmb7iE4bXef3/hDgHjNYwCq+1i5nto/otFGA/ARYAIU4sJHotFGA/CwRBCjEcqL2jLZkThsdz2htHGoQYAFNMChoQ+v3ScrtNrTezmrSxqE8SwShgo+Pj3Q+n9PpdPLleCF7RdrQ+n2yZK4NrbezmrRxKE+ABRUYHKxnUNCG1u+TJC5taL2dbbXlI502DuUd5nle/JePx+N8vV4LFgfGYAYLgGe9vb2l9/f3NE2TYAkqOhwOP+Z5Pv7+5/ZgQQVbNpbbewAwNucRQmyWCEJjLC8EGJtlfhCbAAsaM/reAwCAyARY0BhfLgEA4rIHCwDgv9nnCmxlBgsA4L/Z5wpsZQYLyMrXXyCqJf2TDH3AVgIsIKvb19/z+fzw7wjCgBqW9E9bjtEASEmABWS25OvvkkEOMJY9PryYnWqbj3O0QoAFZLXk62/JQU4rL+BWykkfWmhve3x4MTvVNh/naIUkF3Th4+Mjnc/ndDqdvDgbUDLVfCsb1FspJ31oob0544/vaCO0QoBFF1oYPLCPVl7ArZSTPrTQ3pzxx3e0EVphiSBdsK6em1aWALVSzr9qYZlZaa3WQYvtjTJabcPQEjNYdMFXLSjPTLE6oH3aMJQnwIJK7BujNS0sMytNHdA6bRjKO8zzvPgvH4/H+Xq9FiwOjOPt7S29v7+naZp8RQTojI9o0L/D4fBjnufj739uBgsq8RURoF+W4sG4JLmASiJuOrf5GRhJyT5P8iUYlwAL+FOpQxwFbsBfPdMnlOhHSh5cG/Ej2lb6clhGgAX8qdQX19yDmCiDM+A5z/QJJYIhs0zrlAxIoSvzPC/+eXl5mYGfLpfLPE3TfLlcahcltNz1NE3TnFKap2kq+t9Eo73RSxt45jp6ufaWuQfwq5TSdb4TMwmwYIMeBu0tGnVwlqO99VAPrcpR9/qcfXhOgCUeBViyCMIGMgHWseZg6b+mSm49k1eO9iazWT056r63PidqKnPPCbCFAAs2WDPQH0HEwVJPA6Uc7a23AXpLctR9b31O1OfTcwJs4aBhIJuIhydHDPqAT55PoGWPDhoWYAHZGCwBAKN4FGBZIghk09vyJQCAtZyDBQAAkIkACwAAIBMBFgAAQCYCLAAAgEyaC7A+Pj7S29tb+vj4qF0UAACAXzSXRTDqoYQAAADNBVhOVwcAAKJqLsByzg4AABBVc3uwAAAAohJgAQAAZCLAAniSrKa0bGn71c6BEeTs65rbgwUQxdKsph8fH+l8PqfT6ZReX1/3Kh58aWn7lb0XGEHOvk6ABfCkpVlNDVCJaGn7lb0XGEHOvu4wz/Piv3w8Hufr9br5lwKMxAwWrdOGAf7ucDj8mOf5+Puf24MF8KSl67Vvx0s8OzC1B4Z79mwXt1nY8/lc/HcBtM4SQYAn7bX0zxJD7tmzXVgmCLCcGSyAJ51OpzRNU/FB516/h7bs2S5qzsKawQVaYw8W0Lxn94fYVwL7eHt7S+/v72maptWzbVv+W4CSHu3BskQQaN6zS6UsvYN9bFliaHki0BpLBIHmPbtUarSld5ZaxRDlPuxZji1LDLcuTwTYmwALaN6zA7A9B24RBtUywcUQ5T5EKccaEZ4jgO8IsIAmtTbQijCYHW3GLqoo9+FeOaI/VxGeI4Dv2IMFNCny/ql7yTMi7CO5zdhRV5T7cK8ckZ+rlGI8RwDfEWABTYo80Lo3SI0yqIavRH6uUvIcAW2Qph0gM+nf++S+AvBXj9K024MFkFnvWc+i79Mpxf4f9jTqcwY9EGABsMqogUaU5BTUs2fQM+pzBj0QYEGnfP3sX617PGqgUXNm0vMcw55Bz6jPGfRAkgvo1F7ZwOxLqadWxjeJBvZ3u9f/+te/0r/927953irZMwmI5wzaJcCCTu01EIie1rlHt6D2P/7jP1JKcTO+RdfSx4HbPf7Xv/7leatI0AMsYYkgdGqv5UyWsezvFtT+13/9VxPJNKIub2tpj8vtef7P//zPrp63qG0DYAszWMAmLX3RbWnG4ivRzyr6XdRZztbqMaW2nrclorYNgC0EWMAwehnMtTbIjhrItFaPPYraNgC2sEQQGIbljMvlXLp1b7lqjaVhpX+n5W7r9X5mHDAmARYwDIO55UrvT6qx/6nHaxqJAPZ76ghiEGABzTOoyC/HbN9X96XGbOJXvzNHGzJDWpYA9nvqCIKY53nxz8vLywzUcblc5mma5svlUrso4UzTNKeU5mmaaheleTnbWUv3JXdZPa/5qdPvqSPYV0rpOt+JmSS5gEb0kqChBBvl88nZzlq6L7nL6nnNT1KS76kjiEGABY1oabC6N4OKfHK2s5buS+6yel4BxnX4nN1a5ng8ztfrtWBxAAAA4jscDj/meT7+/ueSXAAAAGQiwAIAAMhEgAUA/MmxBwDbSHIBAPxJBkSAbcxgARQy4kxAL9fcy3U8w4HJANuYwQIoZMSZgF6uuZfreMbvKes/Pj7S+XxOp9Mpvb6+ViwZQBsEWACZ/D4QHfEspF6uuZfryGHkYBPgGc7BAsjk7e0tvb+/p2maDETphhksgPsenYNlBgsgE7Me9Oj3JYMAfE2ABZCJgSgAIIsgAEMbOWMgAPmt2oN1OBz+n5TS/ylXHADY3f+dUvqfKaX/L6X0vyuXBYB2/F/zPP+v3/9wVYAFAADAY5YIAgAAZCLAAgAAyESABQAAkIkACwAAIBMBFgAAQCYCLAAAgEwEWAAAAJkIsAAAADIRYAEAAGTy/wM1xtHmfLy0GQAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:21.521537117432654 max: 228.75899826216641\n", + "image 1 reprojection errors: average:22.094526537115975 max: 207.5519265500523\n", + "image 2 reprojection errors: average:21.04955820055219 max: 194.2499535622554\n", + "image 3 reprojection errors: average:21.704116103157226 max: 401.9243028649641\n", + "image 4 reprojection errors: average:21.712405338524015 max: 269.3266754377959\n", + "image 5 reprojection errors: average:21.507903823649407 max: 236.6415247235926\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.3892e+06 3.60e+06 \n", + " 1 2 6.0334e+03 2.38e+06 6.11e+01 3.52e+05 \n", + " 2 3 2.3980e+03 3.64e+03 8.85e-01 3.60e+03 \n", + " 3 4 2.3872e+03 1.08e+01 4.56e-01 1.32e+03 \n", + " 4 5 2.3851e+03 2.14e+00 6.30e-02 1.63e+02 \n", + " 5 6 2.3849e+03 1.63e-01 8.01e-03 6.49e+01 \n", + " 6 7 2.3848e+03 7.85e-02 4.83e-03 2.78e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 7, initial cost 2.3892e+06, final cost 2.3848e+03, first-order optimality 2.78e+01.\n", + "mean reprojection error: 0.8062567047996868\n", + "max reprojection error: 2.8782678127190735\n", + "mean reconstruction error: 0.05934584184939325\n", + "max reconstruction error: 0.23782823768220313\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:21.942779276381504 max: 236.41667991417424\n", + "image 1 reprojection errors: average:22.37978573477711 max: 434.02035149793255\n", + "image 2 reprojection errors: average:22.101527652771175 max: 233.23964800037638\n", + "image 3 reprojection errors: average:22.231637302531094 max: 346.346421669916\n", + "image 4 reprojection errors: average:21.48268254139276 max: 250.12116060589744\n", + "image 5 reprojection errors: average:21.620840605803767 max: 421.0821453460319\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.5522e+06 6.50e+06 \n", + " 1 2 2.7511e+04 2.52e+06 6.22e+01 4.24e+05 \n", + " 2 3 2.1716e+04 5.79e+03 8.77e-01 4.59e+03 \n", + " 3 4 2.1669e+04 4.67e+01 7.59e-01 3.42e+03 \n", + " 4 5 2.1658e+04 1.16e+01 1.17e-01 6.42e+02 \n", + " 5 6 2.1655e+04 2.78e+00 5.11e-02 3.54e+02 \n", + " 6 7 2.1653e+04 1.59e+00 2.83e-02 1.62e+02 \n", + " 7 8 2.1652e+04 8.73e-01 1.67e-02 8.49e+01 \n", + " 8 9 2.1652e+04 7.05e-01 1.61e-02 6.75e+01 \n", + " 9 10 2.1651e+04 7.04e-01 1.49e-02 8.66e+01 \n", + " 10 11 2.1651e+04 4.65e-01 9.75e-03 5.24e+01 \n", + " 11 12 2.1650e+04 3.21e-01 6.56e-03 8.00e+01 \n", + " 12 13 2.1650e+04 2.73e-01 6.08e-03 4.82e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 13, initial cost 2.5522e+06, final cost 2.1650e+04, first-order optimality 4.82e+01.\n", + "mean reprojection error: 2.430619663053812\n", + "max reprojection error: 8.376542118503291\n", + "mean reconstruction error: 0.17885374447677432\n", + "max reconstruction error: 0.771862098234976\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.593682962216494 max: 200.59445513860547\n", + "image 1 reprojection errors: average:22.441377129926277 max: 306.85165470838893\n", + "image 2 reprojection errors: average:22.83081169716057 max: 210.35463316786604\n", + "image 3 reprojection errors: average:22.920588190134715 max: 333.78910840485014\n", + "image 4 reprojection errors: average:23.02501712084041 max: 855.2523964177373\n", + "image 5 reprojection errors: average:22.405875593312956 max: 296.4891313693352\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.8621e+06 1.38e+07 \n", + " 1 2 7.3627e+04 2.79e+06 6.31e+01 1.66e+06 \n", + " 2 3 5.8452e+04 1.52e+04 1.05e+00 5.38e+04 \n", + " 3 4 5.8385e+04 6.70e+01 4.56e-01 1.02e+04 \n", + " 4 5 5.8367e+04 1.80e+01 8.29e-02 8.89e+02 \n", + " 5 6 5.8360e+04 6.30e+00 7.03e-02 4.32e+02 \n", + " 6 7 5.8355e+04 5.09e+00 3.80e-02 2.03e+02 \n", + " 7 8 5.8351e+04 4.23e+00 5.18e-02 3.11e+02 \n", + " 8 9 5.8347e+04 3.67e+00 2.96e-02 2.01e+02 \n", + " 9 10 5.8345e+04 2.86e+00 3.63e-02 2.61e+02 \n", + " 10 11 5.8342e+04 2.18e+00 1.71e-02 1.69e+02 \n", + " 11 12 5.8341e+04 1.22e+00 1.53e-02 1.73e+02 \n", + " 12 13 5.8340e+04 1.33e+00 1.43e-02 1.98e+02 \n", + " 13 14 5.8339e+04 1.27e+00 1.54e-02 1.69e+02 \n", + " 14 15 5.8338e+04 9.93e-01 1.03e-02 1.43e+02 \n", + " 15 16 5.8337e+04 8.19e-01 1.08e-02 1.41e+02 \n", + " 16 17 5.8336e+04 7.84e-01 8.84e-03 1.37e+02 \n", + " 17 18 5.8335e+04 7.40e-01 9.90e-03 1.34e+02 \n", + " 18 19 5.8335e+04 7.09e-01 8.18e-03 1.29e+02 \n", + " 19 20 5.8334e+04 6.86e-01 9.36e-03 1.29e+02 \n", + " 20 21 5.8333e+04 6.65e-01 7.80e-03 1.23e+02 \n", + " 21 22 5.8333e+04 6.66e-01 9.28e-03 1.28e+02 \n", + " 22 23 5.8332e+04 6.48e-01 7.61e-03 1.18e+02 \n", + " 23 24 5.8331e+04 6.55e-01 9.32e-03 1.29e+02 \n", + " 24 25 5.8331e+04 6.36e-01 7.46e-03 1.13e+02 \n", + " 25 26 5.8330e+04 6.47e-01 9.43e-03 1.31e+02 \n", + " 26 27 5.8329e+04 6.10e-01 7.05e-03 1.02e+02 \n", + " 27 28 5.8329e+04 6.09e-01 9.20e-03 1.28e+02 \n", + " 28 29 5.8328e+04 5.91e-01 6.85e-03 9.53e+01 \n", + " 29 30 5.8328e+04 5.98e-01 9.24e-03 1.28e+02 \n", + " 30 31 5.8327e+04 6.01e-01 7.00e-03 9.63e+01 \n", + " 31 32 5.8326e+04 6.31e-01 9.85e-03 1.34e+02 \n", + " 32 33 5.8326e+04 5.46e-01 6.04e-03 7.38e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 33, initial cost 2.8621e+06, final cost 5.8326e+04, first-order optimality 7.38e+01.\n", + "mean reprojection error: 3.9906164944734175\n", + "max reprojection error: 15.618583503188447\n", + "mean reconstruction error: 0.307195500751489\n", + "max reconstruction error: 1.3359731802359165\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:24.781651232290653 max: 232.74034746710714\n", + "image 1 reprojection errors: average:24.22181734355406 max: 282.06070723308943\n", + "image 2 reprojection errors: average:25.06360566074307 max: 285.04279024326013\n", + "image 3 reprojection errors: average:24.46168205561923 max: 307.4811863804454\n", + "image 4 reprojection errors: average:24.838949795292468 max: 824.9761466326689\n", + "image 5 reprojection errors: average:24.653101002576875 max: 517.5896576475868\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 3.2164e+06 1.62e+07 \n", + " 1 2 2.5067e+05 2.97e+06 6.62e+01 1.65e+06 \n", + " 2 3 2.2939e+05 2.13e+04 1.63e+00 5.17e+04 \n", + " 3 4 2.2886e+05 5.29e+02 2.59e+00 2.79e+04 \n", + " 4 5 2.2871e+05 1.44e+02 3.38e-01 1.12e+03 \n", + " 5 6 2.2869e+05 2.06e+01 1.48e-01 8.51e+02 \n", + " 6 7 2.2868e+05 9.83e+00 3.52e-02 1.58e+02 \n", + " 7 8 2.2868e+05 3.14e+00 2.20e-02 2.13e+02 \n", + " 8 9 2.2868e+05 2.23e+00 1.34e-02 1.15e+02 \n", + " 9 10 2.2868e+05 2.11e+00 1.76e-02 2.57e+02 \n", + " 10 11 2.2867e+05 2.02e+00 1.25e-02 1.23e+02 \n", + " 11 12 2.2867e+05 1.96e+00 1.68e-02 2.77e+02 \n", + " 12 13 2.2867e+05 1.90e+00 1.20e-02 1.22e+02 \n", + " 13 14 2.2867e+05 1.89e+00 1.65e-02 2.83e+02 \n", + " 14 15 2.2867e+05 1.84e+00 1.17e-02 1.18e+02 \n", + " 15 16 2.2866e+05 1.83e+00 1.64e-02 2.85e+02 \n", + " 16 17 2.2866e+05 1.79e+00 1.15e-02 1.13e+02 \n", + " 17 18 2.2866e+05 1.40e+00 1.24e-02 2.13e+02 \n", + " 18 19 2.2866e+05 1.40e+00 1.02e-02 1.21e+02 \n", + " 19 20 2.2866e+05 1.41e+00 1.26e-02 2.26e+02 \n", + " 20 21 2.2866e+05 1.41e+00 1.03e-02 1.21e+02 \n", + " 21 22 2.2865e+05 1.39e+00 1.25e-02 2.24e+02 \n", + " 22 23 2.2865e+05 1.37e+00 1.02e-02 1.15e+02 \n", + " 23 24 2.2865e+05 1.36e+00 1.23e-02 2.24e+02 \n", + " 24 25 2.2865e+05 1.34e+00 1.00e-02 1.17e+02 \n", + " 25 26 2.2865e+05 1.32e+00 1.21e-02 2.20e+02 \n", + " 26 27 2.2865e+05 1.30e+00 9.87e-03 1.17e+02 \n", + " 27 28 2.2865e+05 1.28e+00 1.18e-02 2.20e+02 \n", + " 28 29 2.2865e+05 1.23e+00 9.31e-03 1.07e+02 \n", + " 29 30 2.2864e+05 1.08e+00 9.81e-03 2.50e+02 \n", + " 30 31 2.2864e+05 1.18e+00 9.26e-03 1.70e+02 \n", + " 31 32 2.2864e+05 1.16e+00 9.85e-03 2.51e+02 \n", + " 32 33 2.2864e+05 1.16e+00 9.01e-03 1.86e+02 \n", + " 33 34 2.2864e+05 1.13e+00 9.48e-03 2.57e+02 \n", + " 34 35 2.2864e+05 7.29e-01 4.90e-03 1.17e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 35, initial cost 3.2164e+06, final cost 2.2864e+05, first-order optimality 1.17e+02.\n", + "mean reprojection error: 7.898026068621451\n", + "max reprojection error: 26.86533328464151\n", + "mean reconstruction error: 0.6076257745630586\n", + "max reconstruction error: 3.3284979242909634\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 6 camera configuration A" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [], + "source": [ + "wall_cam_positions = all_cam_positions[(1,2,3,8,9,12),:]" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 29.15674544, -1.85516359, 147.4176074 ],\n", + " [ 44.82084089, 123.17250001, -44.9380583 ],\n", + " [ 29.29952975, -127.37249999, -28.97664714],\n", + " [ -29.15674544, -1.85516359, -147.4176074 ],\n", + " [-147.4176074 , -1.85516359, 29.15674544],\n", + " [ 147.4176074 , -1.85516359, -29.15674544]])" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wall_cam_positions" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [], + "source": [ + "wall_cam_direcions = [[ 0, 0, -1],\n", + " [ 0, -1, 0],\n", + " [ 0, +1, 0],\n", + " [ 0, 0, +1],\n", + " [+1, 0, 0],\n", + " [-1, 0, 0]]" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [], + "source": [ + "# camera_radial_position = 163.0\n", + "# camera_halfz_position = 168.0\n", + "# camera_positions = np.array([\n", + "# [0, -camera_halfz_position, 0],\n", + "# [0, camera_halfz_position, 0],\n", + "# [camera_radial_position, 0, 0],\n", + "# [-camera_radial_position, 0, 0],\n", + "# [0, 0, camera_radial_position],\n", + "# [0, 0, -camera_radial_position]])\n", + "# camera_directions = [[0, 1, 0],\n", + "# [0, -1, 0],\n", + "# [-1, 0, 0],\n", + "# [1, 0, 0],\n", + "# [0, 0, -1],\n", + "# [0, 0, 1]]\n", + "camera_positions = wall_cam_positions\n", + "camera_directions = wall_cam_direcions\n", + "camera_directions = camera_directions / linalg.norm(camera_directions, axis=1, keepdims=True)\n", + "camera_rolls = np.array([np.pi/2, 0, np.pi/2, 0, np.pi/2, np.pi/2])\n", + "camera_rotations, camera_translations = fit.camera_poses(camera_positions, camera_directions, camera_rolls)\n", + "camera_count = camera_positions.shape[0]\n", + "simulator = fit.PhotogrammetrySimulator(led_positions, focal_length, principle_point, camera_rotations, camera_translations, radial_distortion, tangential_distortion)" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total number of features: 1272\n", + "Number of features in more than one image: 1272\n", + "Feature in image counts: Counter({3: 679, 4: 431, 5: 123, 2: 39})\n" + ] + }, + { + "data": { + "image/png": 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WTX0Hyxmswtlz35dhGEKM0Qr1zmo7vwMl6+V5er41LSmQ6eXa85o5YzlsESycLQh9qW2bUytsvYLteJ6O49r3zZyxHLYIFs7rfgAAfmLOuL+pLYICLAAAgIWcwQIAAMhMgAUVcYAVAKBsAiyoiAxRAP2yyAZ1kEUQKiJDFEC/ZImDOgiwoCLSuAP0yyIb1MEWQQCKNbUlylYpelTix42B/yTAAqhY6wHI1LnDls4jtnKvAPhNgEU3TGJoUesByDAMIcb4H1uipn5eo1f3Sn8FUC9nsOiGw8G0aOpMRitnNabOHbZ0HvHVvdJf0bL7/R7GcQzDMNjuSJO8waIbLa14H6W1VfUW6jN1JsNZjXq8ulct9FctPF//1lp9jtTKG3aY4g0W3Whpxfso766ql7pa6S0BpWqhv2rt+WqtPkdq5Q07TBFgAbO9OyiWOjExyEM+pT5f7y74lFqfGrWwgADfOaWUZv/y+XxOj8cjY3GAFk1NaEp9swXUb6p/uVwu4Xq9hhijST6wyul0+pVSOn/9uTNYcJCe9vNPnQeyDx/IZap/aeF82xI9jTVQClsE4SClbpvbky03QC5T/Utv29OMNbA/ARYcRHDR30QH2I/+5TdjDezPGSwAAICFnMECdmG/P1Ab/RawJQEWfzHIsJbEFUBt9FvAlpzB4i8Ow7KW/f5AbfRbbMknSPAGi7/0lr6W7U2lZOdYNb2dXlrWmuoWQn3l7YF+iy15I4oAi78YZP5mIrQ/13yepdeppgF/aVlrqlsIy8vrmfiZa0RJLFYTUkqz/318fCToSYwxhRBSjPHoovyP2+2WYozpdrsdXZQsSrzmJVp6nWpqN0vLWlPdUlpeXs/Ez1yjY9T27MHWQgiP9CJmEmDBN94ZPHIPOK1PJI4esI/++3PVUk7Wq+FeH13Go//+HkqsY+vjEfxEgAU7yT3glDjItsSEAZbz3ORX4thiPKJ3UwGWLIKwsdzZqJ7n5MhDNjFYznOTX+5r/E4WYeMRvHb6HXzNcz6f0+PxyFgcAAD2JrU4LHc6nX6llM5ffy6LILCIbF1Aj1rv+2QRhu3YIggs4mPUQI/0fcBcAixgEWctgB7p+4C5bBEEFrGNpF17bIE6aptVy3VjH/o+YC4BFrAJk8ttHXE9n1ugxnGs+m8c9XePqptnb1uuJ7CWLYLAJno7n5A749YR13OPLVBHbbNquW4520qPmeV668uA7QmwgE30dj4h9yTsiOu5xzdtjvpuTst1y9lWegw2euvLgO3ZIghsIsf5hJK36gzDEGKM2T8oXfpbg5Lv0Vq11C1nW8ndztfIdX9qefaAcvnQMFCsy+USrtdriDFWv3re6larlu7RVy3WraV22OL9Aeoy9aFhWwSBYrW0VafVrVYt3aOvWqxbS+2wxfsDtMEbLIAdtPTmgHpphwDbmXqDJcACAABYaCrAkuQCAABgIwIsAACAjQiwaNaaFL61pGf+txrLDMDf9OVQPwEWzXpmyxrHcdf/7VFyltmAD/BHzj6xxvGntwVN+Ik07TRrTQrfGtP/5ixzS6mdAdbK2SfWOP6suR7GF1okwKJZn5+fb3fWa/63R8lZ5hoHfIBccvaJNY4/vS1owk+kaQcAAFhImnaysX8aAAB+E2CxWo0HcgEAvmMBmXcJsFhtGIYQY7R/unMGIqB2+jH+zQIy7xJgsdrzQO7n5+fRReFAuQYiEx7gq1z9ggk1/2YBmXfJIghsIlcmKCl8ga9y9Qsy2vFvNWZ0pAzeYEEn5qz4rlkVzvUm0woi8FWufmFtP5a7nwXqIE07dOJyuYTr9RpijJMrcnN+B4DX9LPQF2naIbPSVyXnrPh6W8RSpbf7d7VaL/LSzwIheIMFm7EqyU/u93sYxzEMw9BMUphW232L9Wqx/ZGHtgLzTL3BkuSCKtTQ2TsczU9aTNjRartvsV4ttj/y0FZgHQEWVaihs5dtiJ+0OGlvtd23WK8W2x951NBWalh4pV/OYFEFe9ZpQQ3fjMt99uios02t1muJGtofZaihrfhmGSUTYFGFGjp7+tPipD33pOWoSVGL9aohqINcLLxSMlsEAd6Ue+vqEVtjc28NOmrrUYv1yt0+bMGiZC1u46UdsggCvCn3BNQEl+/kbh8tZlIE2NJUFkEBFlAkwQUcyzMI8D0fGgaq4gAzHKuGs6/OoQElEmABWayd+DjADPxk7UKMAA3IQZILIIu1B/AdYAZ+sja5SA3fWATqI8ACsqjhQ5VA3dYuxOingBwkuYAOOKwOALAtSS6gUXPOEEgYQQj1nDdZWs5W60WbtAPoQEpp9r+Pj48ElCXGmEIIKcY4+Tu32y3FGNPtdtuxZOxhyb2d01ZKsLScrdbLc9umue3A/YfyhRAe6UXMJMCCyrUyCJdYjxLL9NWSSXsN9UlpeTlbrVfpgWMt1700c69b6fcfEGABhZiaXJQ4mSixTF+Z5Lar9Htb4vMxdc1Kv5av1Fhm6M1UgCWLILCrqbTIJWbzKrFMX0ln367S722Jz8dU/1JjOvbS7z8wTYAF7GpqUlbiZKLEMkEpSnw+pvqXEoNBoF3StMMOpEkHAGiLNO1wIGnSASiFVPGQlwALdjAMQ4gxFr09xYALsF4NfalFP8jLGSzYQYlnFb6q8RA4QGlq6EudSYO8BFhsylmjehlwAdaroS+tYdEPaibJBZu6XC7her2GGKPOGwCoioVilpDkgl3UcNaoNjXs5wdgX8aGPJxPYwu2CLIp2w62V8N+fgD2ZWzIo4YtnpTPGywonLeCzPVqRbv2Ve6p8rdYr9rrxL6MDXk8F4ptD2SVlNLsfx8fHwlyut1uKcaYbrfb0UWhY7W2wxhjCiGkGOO3P6vJVPlbrFetdar1eaFN2iN7CiE80ouYSYBFUWqdYDBfDYNfre3w1bWt4Xp/Z6r8Ldar1jrV8rzUen1Zppb2SBsEWFTBANiOqXtZw+CnHcJ8tTwvU31PLeVnHveTPU0FWNK0A1lMpeyXAhc4wlTf4/MiwLum0rTLIghkMZWJSaZJ4AhTfY+sccDWvMECAABYyIeGAQAAMhNgAYfz/R9gK/oT4GgCLGDSXhOVcRzD9XoN4zhm/TtA+/bsTwRzwCuSXACTnhOVEELWxBQOmQNb2bM/2auPBOoiwAIm7TVRkVkQ2Mqe/YnFIeAVWQQBAAAWkkUQyMIZBKA1+jVgDQEWsIoEFcdaOhGsYeKoTnXUqWX6NWCVlNLsfx8fHwl43+12SzHGdLvdji7KZlqs07+VXr8YYwohpBhjlt8/gjqVX6fSn4u1Wq8fsI0QwiO9iJkEWLCj0idN/KfS79nSiWANE0d1Kr9OpT8XvFZ6u4LaTAVYklzAju73exjHMQzDED4/P48uDjO4Z/CfPBd1ulwu4Xq9hhijzK2wgakkFwIsKJDJCwBLzBk3jC2wrakAy3ewoEA+XgnAEnPGDd8chH3IIggFGoYhxBi7/XilDGoAy/Q+bkBJbBEEiuOcADCXbW/AUWwRBKrxXIG1Egv8xJZqoDQCLKA4zgkAc1mQAUrjDBbASjnPjB1xHq21+uzxd/eul3OKfzwXZGwPBErhDRbASjm3KB2x/am1+uzxd/euV86/50wTwDoCLBYz+MLfcm5ROmL7U2v12ePv7l2vnH/PmSZ4zfyHuWQRZDEZ3vpiQOEnLbaRFus0V891h++Y//DVVBZBZ7BYzLc2+vJczR7H8eiiNKHFszMttpHW6rSk3TnT9LMWn2N+Zv7DbCml2f8+Pj4S0Jfb7ZZijOl2u836Od+LMaYQQooxHl2UzbTYFlqrU4vtbg9T7cD1BFJKKYTwSC9iJgEWxWptgtMaE4z3aNccQbt7z1Q/53qWxf3gKFMBliQXFMtB67L59sx7fOOLI2h375nq51zPspgvUBoBFsUygS+bCQbQOv1cHcwXKI0sggAAAAvJIggAAJCZAAsokjTIwE/0E0CJnMECiuTQMvAT/QRQIm+wIDMrrO/xQUfgJ/qJdYxPkIckF5DZ5XIJ1+s1xBitsAJQDOMTrDOV5MIWQchM+lgASmR8gjxsEYTMnt9R+fz8XPy/tX0DgClrx4g14xMwzRssKJgD3ABMMUZAmbp4g+UtALVygBuAKcYIWtTCvL2LJBcOcQIAQPlqmrd3neTCIU4AAChfC/P2LrYIOsQJy7Xwih4gN30lbKuFeXsXARaw3PPw9DiO3/6eycUyLV4vdSpfa/XZw9xrNrevBDqSUpr97+PjI1G32+2WYozpdrsdXRQKN7etxBhTCCHFGHcqWd1avF7qVL7W6rOHudfMuMoS2ktbQgiP9CJm6uIMFn9I6cpcz1f0P2lhr/SeWrxe6lS+1uqzh7nXbG5fCSGYh/WiiyyC/HG/38M4jmEYhqr3ttIubRRYSr9BLbTVtkxlEXQGqzMtHBykbTWeZ8h5vuWIszOt1WePv+s+HavGfoM+mYd14tW+wal/zmBRKnua21Hjvcx5vuWIszOt1WePv+s+HavGfoNp7ie1CM5g0TJ7mttR43mGnOdbjjg701p99vi77tOxauw3mGZMp3bOYNGEI/Y020cNQA/2Hu+Mr9Ri6gyWAAvedLlcwvV6DTFGK2wANMt4B69JclG42g4U83vrTIyxmi00APAO4129zC+PIcAqhAxI9Tk6E5BOE6B9JfT1R493vM/88hgCrEJYHWKprTrNEgZvgNZs1beaILOG+eUxZBEshAxILLVVli/ZmgC2t1XfWltGR8pifnkMb7DoXq1vcLbaspFjdavWawr0KUeftVXfWuv2POMAPRNg0b3et1/kGLyXXNPSB+HWyld6fUJos04hLCtn6XVqrXw5xoFaA6Ot9D620rlXXx+e+vfx8bHv55FhB74Yv70l1zTGmEIIKca4Q8mWa618pdcnpTbrlNKycpZep9bKZxzYnmtKD0IIj/QiZhJgQcNqGOBKL2Nr5Su9Pim1WaeUlpWz9Dop3zZqKSfw2lSA5UPD0LDSPg55v9/DOI5hGIZut80AxymtDyqtjwaWmfrQsCyC0LDSsk/JWAgcqbQ+qLQ+GtiGAAsaVlp6VpMJ4Eil9UGl9dHANmwRBAAAWGhqi6A07QAAABsRYAEAAGxEgAUAALARARYAAMBGBFgAAAAbEWABAABsRIAF8C/3+z1cLpdwv9+PLspir8pec31CmC6/epWl1nID5OBDwwD/Mo5juF6vIYRQ3QdAX5W95vqEMF1+9SpLreUGyEGABfAvwzD89X9r8qrsNdcnhOnyq1dZai03QA6nlNLsXz6fz+nxeGQsDtCy+/0exnEMwzCEz8/Po4sDdEYfBGzpdDr9Simdv/7cGyxgN7YRAUfSBwF7kOQCGlbawfNhGEKM0TYi4BCl9UGl9dHANmwRhIZdLpdwvV5DjNFqLUBh9NFQt6ktgt5g0b2WVxBLW619peXrDxyjln6lhj76XbXcA8jBGyy6ZwVxe0sOkrv+wNaW9iuSX2xP304PJLmACb2nF84xsVhykLz36w9sb2m/kiP5Re9Bm76dnnmDBZ3LscrY+8QCqEuOPssbHGifM1iFs1eZpbZqMznOAHx+foZ//vlHcAVUIUeftVXfan7AGtrPMbzBKoSVLpbSZgDap69nDe0nL2+wCtdyJqFWHb0qpM3kdfT9hRp4TvIroa93n+tVQvvpUkpp9r+Pj48E/BZjTCGEFGM8uihkUMP9vd1uKcaYbrdblt8/inq99/tHqOE5YT33GV4LITzSi5hJgEUTjpiI1DD54X013N+lk55aJknq9d7vH6GG54T19r7P2hW1mAqwpGmnCTlS7P7keSiaNtVwf5emQa4lbbJ6vff7R6jhOWG9ve/zEWM6bEmSC5ogLXg73EtgKf1GW9xPajGV5EKABRRFxiNgKf0GcARZBAkhyARE+WQ8ApbSb1AL87A+CLA689zXPI7j0UWhEVsPFj5SDCyVo98wESYH87A+SHLRmRoOTVMXh5GBFunbyME8rA/eYHXG2wHmmrt6a2sO0KK5fZs3XSxhHtYHARbw0txtDL0OFiZV9KDndj63b7PlC/iqiwCr5wEC3uXN1PdyT6qO6rdy/91W67XX39j7bwoefqavhG01MW9/9fXhqX8fHx/7fh55IzHGFEJIMcajiwI04na7pRhjut1uWf77R/Vbuf9uq/Xa62/s/Tdzt3OAr2qat4cQHulFzNRFkgsHCoGtPbcP5XJUv5X777Zar73+xt5/M3c7B/iqhXm7Dw1DwXzNvh3uJSXQDtvifsKxfGgYKuT8QztavZdN7JWf0GLdWm2HvXI/oUxdbBGEI61ZYWzhNTm/tXovW/5WUIt1a7Ud9mrt/fQGDPKwRRAyu1wu4Xq9hhhjM5M0eGp5gtZy3SAE4xOsZYsgHEQK3/e0uD2rRS1/B63lurVCP7GO8Qny8AYLKJKVVeAn+gngSFNvsJzBAorkrAjwE/0EUCJvsAAAABZyBgsAACAzARYAANWS7ITSCLAolg4TgCMZh+rgg8uURoBFsXSYZTPxAFpnHKqDdPOURoBFsXSYZZgKpEw8gNZNjUMWmMrim3WURoDFYnsNLDrMMkwFUgJgoHVT45AFpj4JrJnLd7BY7DmwhBB82LEDU9+ZeU48AHrj+1t9Mv9hLgEWixlY+iKQAvibfrFP5j/M5UPDAAAAC/nQMAAAQGYCLAAAgI0IsIDitJSpqaW60I6W2mVLdQHaIMACitNSCuSW6vJV6xPbluvXUrtsqS5AG2QRhALd7/cwjmMYhqHL74C1lKmppbp81XrK4pbr11K7bKkua/Q+bkBJZBGEAl0ul3C9XkOMsbmJXe1MYv5o/Vq0Xr8lXIvyGTdgf7IIQkWGYQgxxu5XZEuUezvSkdvSlv7t57eAlky41S+P3H/XNrzyGTegICml2f8+Pj4S8L7b7ZZijOl2ux1dFN6U+x7GGFMIIcUYs/z3j/7b6lfn39V3tcF9hG2FEB7pRczkDBbsqOUzHb14vtXI5cjzJHv8bfWr8+/mbvfswxgE+3AGC3bkHANA+Vrtq1utFxxl6gyWAAtYxYANtEbCCGCOqQDLFkFgFVtOgNZI/Q6sIcACVjERAVrjzBmwhjTtwKQ5qZ/fSWUN0IIjPzsAlEuABUza69s3JUxSSigD1K6E52jPMvg+GPCKAAuYtNeHK0uYpJRQhjlKmMCyv1ruewnP0Z5l8HFf4KVXH8ea+udDw0AOJXz8soQyzPHOB2VrqdvTO+VtvY5HfqB5iRLuQwllAPoQJj40LE07QEXeSYtfW8rpd8rbeh19DgGgPNK0AzTgnexmtWV6fKe8rddRVjuAeniDBWRhxR2ogb4KeJc3WMCufIAYqIG+CtiaLIJAFlPZtWrJhga0ZarvkQmwLcYYSmCLIMWwTaMPtSUjANqg7+mD+8yebBGkeLZp9KG2ZARAG/Q9fXCfKYE3WBTDG6zXXBcAvjI2wPGm3mA5g0UxnmmIDRR/e77ZG8fx6KIAUAhjQx7OcLEFWwTZlBW17dnuAMBXxoY8HFdgCwIsNqVj2p4PjALwlbEhD4ErW7BFkE1Jd1uvnrZF9FRXKEFPz1xPdW2R4wpsQYDFpnRM9eppP38rdX01kTO5q9PUfWvlfrbyzM3RU12BCSml2f8+Pj4SsNztdksxxnS73Y4uyqQayriVVuoaY0whhBRj/PZnNZu6V63cw6ep+9bK/Wztfn2nhrrWUEaoQQjhkV7ETAIs2EErkyTK8mqS1NrEqfXA46mXQJIytPb8wFGmAixJLmAHDs2Sw6tD7q0dfJ96dlp7pqbuW2v3kzK09vxAaXxoGAAAYCEfGgYAAMhMgAUAALARARZUrpU0zgD8oW+HegmwoHJzvrlioAYow9z+2Pe0oF6yCELl5mSDeg7UIQQZyQAONLc/lukP6iXAgsrNSeNsoAYow9z+WIp+qJc07QAAAAtJ0w4A7M4ZUKA3AiygSyZ9sA/JGoDeCLCALtU26XsnIBRElq+H+zoMQ4gxOgMKdEOABXSptknfOwFhbUHkUw9Bx1MP9/WZrOHz8/PoogDsQhZBoEu1Zeh6JxNkrdkj3/msQK2fIujpvgL0QhZBAIpyv9/DOI5hGIbZbz3e+d8AwBpTWQQFWAAAVMWiCiWQpp2q1Xq+AgDYXm1nEemLAIsq6EgBYB81LGrWlqiIvkhyQRVqONRtuwIALaghaUxtiYroiwCLKtTQkdYwIAHAT2pY1ISS2SIIG7FdoS01bJGBEnhW/phzLWq4Xr5dBusIsGAjpQ9IrQz8e9nj3J/rTU57tS9nZP+Ycy1cL+hASmn2v4+PjwTUKcaYQggpxrjqd3pxu91SjDHdbrdsf6OE671HPY/4WyWU4ej67tW+jq5nSeZcC9cL2hFCeKQXMZMACzph4C9PCdd7zyCvhICyp/qW0L4AWjYVYElyAZ2YkyikhmQiLSnheu95mL2Eg/M91beE9gU1kx2Yd51+B1/znM/n9Hg8MhaHGumAwHNAO7Rl+O1yuYTr9RpijBYreOl0Ov1KKZ2//lySC1ZzYBf6eg56TM7RU517asvwHdmBeZctgqx29DYYKEFPz0GP33zrqc49tWX4jm22vMsWQQAW6XELWY91BuB7tggCsInSv/mWQ491ZlpPW0bnWnNNXE9aI8CiWTr77bgeAH/kPKdWa3+75po490drnMGiWWvOTNR43iLnFqYarwdALjnPqdXa3665Js790RoBFs3qrbPPOSjXeD0AcsmZ/KDW/nbNNZFMgtZIcgGNcAgfAGA/U0kuvMGCRlgBBAA4niQXAAAAGxFgAQAAbESABQAAsBEBFgAAwEYEWAAAABsRYAEAAGxEgAUAALARARYAAMBGBFgAAAAbEWABvOl+v4fL5RLu9/vRRYEstPE/XAtgLgEWsIhJxh/jOIbr9RrGcTy6KJCFNv6HawHMJcACFjHJ+GMYhhBjDMMwHF2U3fQcYPdY9x7b+BTXApjrlFKa/cvn8zk9Ho+MxQFKd7/fwziOYRiG8Pn5eXRxNtFinXK5XC7her2GGGP4559/ji7Ornqu+1KeKaAHp9PpV0rp/PXn3mABi3x+foZ//vmnqUnTnm/lan8L0vMqfu1137PtedNdn9r7JihKSmn2v4+PjwR873a7pRhjut1uVf73e7TnNY0xphBCijFm/1vf0Y72U8q13rPtlVLnluS+pu+2D/eanoUQHulFzCTAgm+8M3DknsSUMkHnPaVMRvZuR6XU+4iylPLMlnQPWC53O3q3fZTSvuEIUwHW/zroxRlU4bnNJYQw+8zFc/tQrm1Euf/75PXcYnm0vdvRO89SK2Up5Zktpe3xntzt6N32UUr7hpJIcgHfcFAbtlHSs1RSWQCo11SSCwEWAABsxCJOP2QR5EcyCAEArCOLJgIs/ocOAYAjWOCjJbV/0oH1JLngfzioSgtszYD6lJQEBdaSUAYBFv9Dh0ALTNSgPhb4gJbYIgg0pfatGbZK8a6a285zgc9b5+3V3C6gVgIsOIhBL4/aJ2rvnoXUntrx7r10jpZXtAvYny2CcBBb2Xjl3a1SrbSnNWfoWjl/9+69tM2OV7QL2J8ACw5i0OOVd89CttKe1gSKrQSZ795L52h5RbuA/dkiCAepcSubbWjlqrE9vbLmDF3t5++eWrmXrdH/AXOdUkqzf/l8PqfH45GxOEDJLpdLuF6vIcZoRRToiv5vO61s54XT6fQrpXT++nNbBOmGDn29VrahASyl/9tOK9t5YYoAi27o0Nezlx/olf5vO4JVWifAohs6dAA4nmCV1gmw6IYOHQCA3GQRBAAA2IgAC6iOdMnQF888UBMBFlTEJOO3Z8KScRyPLgqwA8/8b8YAqIMzWFARmRB/k7AE+uKZ/80YAHUQYEFFTDJ+k7AE/tb6d/48878ZA6AOtghCRZ6TjBYnUPxtaiuQLUL9+u7e20LXB2MA1EGABVCgqQlzbxPp74KK3oLN7+79MAwhxujNBkABbBEsXOvbPoDXprYC9bZF6LszJ72dR/nu3ttCB5gzlkOAVbjeJhDAb1MT5t4m0t8FFb0Fm73de5Yzwe6bOWM5BFiF620C0TuDI/ztu6BCwAF/M8HumzljOQRYhTOB6IvBEYB3mWD3zZyxHJJcQEFKO6jeWxIBgCVK6yNlGYQyeIMFBSlt9ckbNYBp+kjgFQEWMMl2E4Bp+kjglVNKafYvn8/n9Hg8MhYHAACgfKfT6VdK6fz1585gAQBFK+2sE8B3BFhAdUy2oC/Ps07jOB5dFIAfOYMFVMfBcuiLs05ATbzBAqpTWjp7IK8e0497Uw/1EmBB5XochFuZbPV479iXNlYv2yKhXk0HWAYWemAQrteae6d/68eae61/qFfvb+r1cVQtpTT738fHR6pJjDGFEFKM8eiikNntdksxxnS73Y4uyu56rnvt1ty7Vvu3Ndek1Wdhzb1u9ZrQvlb7OJYruR8LITzSi5ip6QCr5BvCtnTE9KbV/m3Ns9xqP9DqvW6d+7aO68dTyX37VIDVdBbB5zkN2ifD1Pvu93sYxzEMw1D9maaetNq/rXmWW+0HWr3XrZPtdB3tnqca+/bT7+BrnvP5nB6PR8biAHu7XC7her2GGKPBDGAjFq+gfafT6VdK6fz1500nuQB+1vtBaoAcfsp2KokDtEuABY37aRBvJeU5QE1keGyHYJmvBFh8S6dRP4M4UIPexhu7B9phnOWrppNcsJ5DuvWr8XDoGs49QJ16G28kcWhHb+MsPxNg8S2dRv16G8R7m6RBK4w31Kq3cZaf2SLIt5zPoTZHbbvpbXsT7TqqLRtvtqEvguN5gwUFsb1tvaNWEr05oxXact3cPzieN1hQEAdl61XqgXWr2eUq9d6U2paZx/2D4wmwoCAGxuOsneyWur3p6KC91CAihOPLdvS9mbK2LR99XXtXal8EPbFFEArioOxxWt1Wc3TigJKv69FlO/re5HL0dQU4mgALILQ72T06aC/5uh5dtqPvTS5HX1fokTPcZTmllGb/8vl8To/HI2NxeMVDAwCwndbmVpfLJVyv1xBjbHLhplSn0+lXSun89efOYFWg1H36S9mXD/Xx3H7P9YE6tTK3enKGuyy2CFagle0W9uVDfTy333N9oE6tzK2eWt1yXCsBVgVaeWha68ygB57b77k+UKdW5laUyRksAACAhZzBAgAAyEyABQAAsBEBFgAAwEYEWAAAABsRYAEAAGxEgAUAALARARYAAEW53+/hcrmE+/1+dFFgMR8aBgCgKOM4huv1GkIIPghMdbzBoglWugCgHcMwhBhjGIbh6KLAYt5g0QQrXQDQjs/PT+M51fIGiyZY6QKA1+zygH0JsGjCc6Xr8/Pz6KLMYrADYC/PXR7jOB5dFOiCAAsOYLA7lgAX9ue5O45dHrAvZ7DgAM9BzmB3DGf2YH9bPHf3+z2M4xiGYahmx0IJnGeCfQmw4AAGu/dtMcES4ML+tnjuLI4ANRBgAVXZYoIlwIX9bfHcWRwBaiDAAqpiggX9sjgC1ECSC6AqR2aM7OmQfk913UIv16uXegKs4Q0WwEw9nf/oqa5b6OV69VJP6iYZCkcTYFEMHSKl62l7Yk913UIv16uXelI3CwEc7ZRSmv3L5/M5PR6PjMWhZ5fLJVyv1xBj1CHCmyxU1Mu9g214ltjL6XT6lVI6f/25M1gUw4cQYb2SPmJdy3mdUspZ0r1rVSn3mryOPKsLIdgiSEFkh+qDlcW8StrCVcs2nVLKWdK9a1Up9xpomwAL2JUJTl4lLVTUEjCUUs6S7l2rSrnXQNucwQJ25Q0WANCCqTNY3mABu7JKDwC0TJILAAB2TQIi4QgtE2DRhb06cgMGALXaM5OlrJm0TIBFF/bqyA0YhCDQpk7aLXt+LsWnWWiZM1h0Ya/MUTJUEYJMiexvi+Qx2i17npF1HpeWCbDowl4duQGDELYJtGVbZIktgiMLRADbEGABbGyLQNvbBJbYIjiyQASwDWewAArU4/mErc4A9XiW6BkcedsJcDwBFkCBepwwb5UkRrIZ2FePixrwHQEWTDBgwL62emvX49s/tqX/X8aiBvzNGSyY4AzMfBIysIWtzgA5S8Ra+v9lJEiBvwmwYIIBYz6TEaAl+v9lLGrA304ppdm/fD6f0+PxyFgcoEbeYAEAvTmdTr9SSuevP2/iDJa90nCsHhMyAAC80sQWQduTAACAEjTxBkvGKAAA6E+JO9maeIPlcCUAAPSnxJ1sTQRYAABAf0rM+tnEFkGAkpS4XQF+ot0CNSox0ZYAC2Bjz+0K4zhO/o7JLHv7qc3NabcA/MwWQYCNzdmuUOKecdr2U5srcZsNQI0EWAAbm5N4x2SWvf3U5iSMAtiGLYIAByhxz3iJftrWZqvlfNocwD4EWAAU66dzQc4NAVMswHAUARZF0AkCr/z0IXkfmic341O9LMBwFGewKIID/3W63+9hHMcwDINtR2Tx07kg54bIzfhUL2ddOYoAiyLoBOtk4gG0zvhULwswHOWUUpr9y+fzOT0ej4zFAWriDRYA0KvT6fQrpXT++nNvsIC3WR0EAPibJBcAAAAbEWABAABsRIAFAACwEQEWAADARgRYAMAsProL8DMBFsACJpj07Pntu3Ecjy4KQLEEWAALmGBSo60WBoZhCDFGH90F+IbvYAEs8JxYbjHB9KFm9vJcGAghrPp2nW/fAfxMgAWwwJYTzK0mvfCTLRcGAPieLYIAB7Hdir08Fwa8KX3N2UpgSwIsIAsTlp+Z9P5tyzaj/bGEs5XAlmwRBLKw/Y2ltmwz2h9L2EIJbEmABWRhwsJSW7YZ7Y8lJO8AtnRKKc3+5fP5nB6PR8biAAAAlO90Ov1KKZ2//twZLAAAgI0IsACAXUlCArRMgAV0w6QOyrB11j7PNlASARZQpBwTJqmYoQxbfwPOsw2URBZBoEg50mzLLAdl2Dprn2cbKIksgkCR7vd7GMcxDMPgQ7wAQHFkEQSq8lzhFlzBf3LmCKBcAiyASphU8+TMEUC5BFgAlTCp3k/pwezWSSIA2I4kFwCVKP0gf0vn5nIkWdnS1kkiANiOAAugEqVPqksPSpYoPZgFoFwCLAA20VJQUnowC0C5nMECYBMyP36v9HNdAGxDgAXQIZP9/UlSAtAHWwQBOtTSealatLSFEoBpAiyADpns78+5LoA+CLAAOmSyDwB5OIMFAACwEQEWAADARgRYrCITGQDQA3Me5nIGi1VkIgMAemDOw1wCLFaRiQwA6IE5D3OdUkqzf/l8PqfH45GxOAAA9bnf72EcxzAMQ/j8/Dy6OMAOTqfTr5TS+evPncECXrLXHGhRrr7tuX1sHMdN/7tAfQRYwEu5JgsCN+BIufq2YRhCjNH2McAZLOC1XHvNHRIGjpSrb/PxbuDJGSxgV84pAAAtmDqD5Q0WsCurvABAy5zBAgAA2IgACwCgUBIDQX0EWFAxAy/Qi177O+nfoT4CLKhYzwNvr5Mt6FWv/Z3071AfSS6gYrnSDddAunfoS6/9ncRAUB9p2oEqSfcOABxJmnagKVZ1AYASOYMFAAdwjhCgTQIsgE6Y0Jel16QNAK0TYAEUIncAZEJflpzZ4QTTAMdxBgugELkzI/aaha1UOc8RyrIJcBwBFkAhcgdAEoP0QzANcBxbBAEK8QyAaks73/p2tBrrV2tbAmiBN1gArNL6drTW6wfAtrzBAmCVnMkaStB6/Y5W4xtCgO8IsICmmbzl1/p2tNbrdzTZLfelT4T8BFiwM4PbvkzeoGzeEO5Lnwj5OYMFO3OeY1+yqcE27vd7GMcxDMOw6ds82S33pU+E/ARYsDOD275yTt5yTTihRBaH2iCghfwEWLAzg1s7TDjpicUhgHkEWABvMuGkJxaHAOY5pZTm//Lp9H9DCP8nX3EAAACq8P+mlP731x8uCrAAAACYJk07AADARgRYAAAAGxFgAQAAbESABQAAsBEBFgAAwEYEWAAAABsRYAEAAGxEgAUAALARARYAAMBG/n8BzitkRUlioQAAAABJRU5ErkJggg==\n", 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\n", 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\n", 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "image_feature_locations = simulator.get_image_feature_locations(area_restrict = image_area, min_feature_count = 2)\n", + "feature_counts = Counter([f for i in image_feature_locations.values() for f in i.keys()])\n", + "feature_counts_counts = Counter(feature_counts.values())\n", + "print(\"Total number of features: \", len(led_positions))\n", + "print(\"Number of features in more than one image: \", sum(feature_counts_counts.values()))\n", + "print(\"Feature in image counts:\", feature_counts_counts)\n", + "simulator.show_images(image_feature_locations, area=image_area)" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "camera_orientations, camera_positions = fit.camera_world_poses(camera_rotations, camera_translations)\n", + "plot_geometry(led_positions, camera_positions)" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "=== Gaussian errors on feature image locations: 1.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:20.858704238950686 max: 164.51857526493566\n", + "image 1 reprojection errors: average:23.08158645127888 max: 218.2245004661737\n", + "image 2 reprojection errors: average:22.853147989360476 max: 101.36027530142324\n", + "image 3 reprojection errors: average:22.394074617717934 max: 236.518025867157\n", + "image 4 reprojection errors: average:22.058503659399516 max: 147.68489513962896\n", + "image 5 reprojection errors: average:21.558179984640816 max: 191.75728957345015\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.7060e+06 4.26e+06 \n", + " 1 2 3.1045e+03 1.70e+06 6.14e+01 3.00e+05 \n", + " 2 3 1.6239e+03 1.48e+03 1.78e+00 3.12e+03 \n", + " 3 4 1.6169e+03 7.07e+00 3.27e-01 4.50e+02 \n", + " 4 5 1.6150e+03 1.91e+00 7.19e-02 9.60e+01 \n", + " 5 6 1.6145e+03 4.98e-01 3.22e-02 5.20e+01 \n", + " 6 7 1.6142e+03 2.17e-01 1.31e-02 4.95e+01 \n", + " 7 8 1.6141e+03 9.76e-02 6.53e-03 2.54e+01 \n", + " 8 9 1.6141e+03 7.02e-02 5.30e-03 3.91e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.7060e+06, final cost 1.6141e+03, first-order optimality 3.91e+01.\n", + "mean reprojection error: 0.7362571661903533\n", + "max reprojection error: 2.8984207989238793\n", + "mean reconstruction error: 0.06509631789198089\n", + "max reconstruction error: 0.3663931155363071\n", + "=== Gaussian errors on feature image locations: 3.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:20.823468029437308 max: 173.4674826856074\n", + "image 1 reprojection errors: average:23.699870683530364 max: 163.495742578979\n", + "image 2 reprojection errors: average:22.06797204532011 max: 184.53344869030482\n", + "image 3 reprojection errors: average:22.967660083801007 max: 189.48573756681873\n", + "image 4 reprojection errors: average:22.441012605828426 max: 182.39869742899972\n", + "image 5 reprojection errors: average:20.980883238022 max: 128.04201566093667\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 1.6743e+06 5.29e+06 \n", + " 1 2 1.5452e+04 1.66e+06 6.18e+01 1.75e+05 \n", + " 2 3 1.4405e+04 1.05e+03 9.64e-01 4.71e+03 \n", + " 3 4 1.4349e+04 5.62e+01 1.02e+00 1.60e+03 \n", + " 4 5 1.4333e+04 1.56e+01 1.67e-01 3.81e+02 \n", + " 5 6 1.4332e+04 1.37e+00 3.28e-02 1.50e+02 \n", + " 6 7 1.4331e+04 4.89e-01 9.98e-03 1.01e+02 \n", + " 7 8 1.4331e+04 2.94e-01 8.89e-03 5.11e+01 \n", + " 8 9 1.4331e+04 2.44e-01 6.10e-03 7.85e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 9, initial cost 1.6743e+06, final cost 1.4331e+04, first-order optimality 7.85e+01.\n", + "mean reprojection error: 2.2030817660174904\n", + "max reprojection error: 7.795772078064718\n", + "mean reconstruction error: 0.19736314893868795\n", + "max reconstruction error: 0.9076175329989111\n", + "=== Gaussian errors on feature image locations: 5.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.62274178792073 max: 234.79610889483814\n", + "image 1 reprojection errors: average:24.645921005585986 max: 242.31072945060583\n", + "image 2 reprojection errors: average:24.11432631790437 max: 195.3568895482822\n", + "image 3 reprojection errors: average:23.568656435555926 max: 232.85354784940125\n", + "image 4 reprojection errors: average:23.12435736107767 max: 234.7212647672052\n", + "image 5 reprojection errors: average:22.680846795897473 max: 171.94992236472285\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0113e+06 3.62e+06 \n", + " 1 2 4.3396e+04 1.97e+06 6.33e+01 3.57e+05 \n", + " 2 3 4.0392e+04 3.00e+03 1.36e+00 7.38e+03 \n", + " 3 4 4.0288e+04 1.04e+02 1.24e+00 1.74e+03 \n", + " 4 5 4.0256e+04 3.23e+01 2.15e-01 2.44e+02 \n", + " 5 6 4.0252e+04 3.80e+00 5.01e-02 1.44e+02 \n", + " 6 7 4.0251e+04 1.13e+00 1.69e-02 1.11e+02 \n", + " 7 8 4.0251e+04 7.12e-01 1.18e-02 9.65e+01 \n", + " 8 9 4.0250e+04 5.62e-01 9.85e-03 1.09e+02 \n", + " 9 10 4.0250e+04 4.07e-01 6.09e-03 9.19e+01 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 10, initial cost 2.0113e+06, final cost 4.0250e+04, first-order optimality 9.19e+01.\n", + "mean reprojection error: 3.686614014894297\n", + "max reprojection error: 14.452198424577757\n", + "mean reconstruction error: 0.3209318688489082\n", + "max reconstruction error: 1.6142655069273937\n", + "=== Gaussian errors on feature image locations: 10.0 ===\n", + "6 images with total of 1272 features\n", + "image 0 reprojection errors: average:22.78921934919311 max: 98.26149818915943\n", + "image 1 reprojection errors: average:25.709113336274978 max: 139.01870287491323\n", + "image 2 reprojection errors: average:24.461345124073695 max: 223.5331129021383\n", + "image 3 reprojection errors: average:24.86970448586711 max: 317.5239113770566\n", + "image 4 reprojection errors: average:23.996469521035717 max: 215.95955750869106\n", + "image 5 reprojection errors: average:23.898124139694108 max: 157.9741373887714\n", + " Iteration Total nfev Cost Cost reduction Step norm Optimality \n", + " 0 1 2.0233e+06 5.75e+06 \n", + " 1 2 1.6508e+05 1.86e+06 6.61e+01 4.02e+05 \n", + " 2 3 1.6229e+05 2.78e+03 1.66e+00 1.34e+04 \n", + " 3 4 1.6200e+05 2.96e+02 1.65e+00 4.83e+03 \n", + " 4 5 1.6186e+05 1.32e+02 3.73e-01 8.63e+02 \n", + " 5 6 1.6185e+05 1.77e+01 1.16e-01 4.85e+02 \n", + " 6 7 1.6183e+05 1.17e+01 7.34e-02 4.22e+02 \n", + " 7 8 1.6183e+05 6.97e+00 4.74e-02 2.45e+02 \n", + " 8 9 1.6182e+05 6.08e+00 4.39e-02 3.22e+02 \n", + " 9 10 1.6182e+05 5.92e+00 4.23e-02 2.50e+02 \n", + " 10 11 1.6181e+05 5.87e+00 4.26e-02 3.24e+02 \n", + " 11 12 1.6180e+05 5.44e+00 3.84e-02 2.37e+02 \n", + " 12 13 1.6180e+05 4.06e+00 2.89e-02 2.42e+02 \n", + " 13 14 1.6179e+05 5.36e+00 4.55e-02 3.18e+02 \n", + " 14 15 1.6179e+05 4.10e+00 2.37e-02 1.59e+02 \n", + " 15 16 1.6179e+05 3.80e+00 3.68e-02 3.09e+02 \n", + " 16 17 1.6178e+05 3.70e+00 2.23e-02 1.49e+02 \n", + " 17 18 1.6178e+05 3.63e+00 3.59e-02 3.14e+02 \n", + " 18 19 1.6178e+05 3.46e+00 2.12e-02 1.34e+02 \n", + " 19 20 1.6177e+05 3.38e+00 3.45e-02 3.21e+02 \n", + " 20 21 1.6177e+05 3.37e+00 2.12e-02 1.31e+02 \n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " 21 22 1.6177e+05 2.94e+00 2.99e-02 2.99e+02 \n", + " 22 23 1.6176e+05 2.88e+00 1.94e-02 1.29e+02 \n", + " 23 24 1.6176e+05 2.71e+00 2.75e-02 3.42e+02 \n", + " 24 25 1.6176e+05 2.93e+00 2.00e-02 1.58e+02 \n", + " 25 26 1.6176e+05 1.88e+00 1.65e-02 2.93e+02 \n", + " 26 27 1.6175e+05 1.64e+00 1.17e-02 1.61e+02 \n", + " 27 28 1.6175e+05 1.24e+00 1.02e-02 2.42e+02 \n", + " 28 29 1.6175e+05 1.22e+00 9.93e-03 1.67e+02 \n", + " 29 30 1.6175e+05 1.22e+00 1.02e-02 2.71e+02 \n", + " 30 31 1.6175e+05 1.22e+00 9.90e-03 1.75e+02 \n", + " 31 32 1.6175e+05 1.21e+00 1.01e-02 3.02e+02 \n", + " 32 33 1.6175e+05 1.19e+00 9.74e-03 1.81e+02 \n", + " 33 34 1.6175e+05 1.18e+00 9.96e-03 3.37e+02 \n", + " 34 35 1.6174e+05 1.17e+00 9.62e-03 1.87e+02 \n", + " 35 36 1.6174e+05 1.16e+00 9.82e-03 3.79e+02 \n", + " 36 37 1.6174e+05 9.40e-01 7.37e-03 1.51e+02 \n", + " 37 38 1.6174e+05 9.34e-01 8.71e-03 4.49e+02 \n", + " 38 39 1.6174e+05 8.40e-01 6.32e-03 1.27e+02 \n", + " 39 40 1.6174e+05 7.79e-01 7.44e-03 5.06e+02 \n", + " 40 41 1.6174e+05 7.33e-01 5.52e-03 1.09e+02 \n", + "`xtol` termination condition is satisfied.\n", + "Function evaluations 41, initial cost 2.0233e+06, final cost 1.6174e+05, first-order optimality 1.09e+02.\n", + "mean reprojection error: 7.388796281598879\n", + "max reprojection error: 26.37898922941176\n", + "mean reconstruction error: 0.6361120217026041\n", + "max reconstruction error: 2.8221227087668894\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 86, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "fig_led_pos, ax_led_pos = make_fig(\"Reconstructed LED position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_pos, ax_mpmt_pos = make_fig(\"Reconstructed mPMT position error with {} cameras\".format(camera_count), \"Distance from true to reco. position [cm]\")\n", + "fig_mpmt_ang, ax_mpmt_ang = make_fig(\"Reconstructed mPMT orientation error with {} cameras\".format(camera_count), \"Angle between true and reco. orientation [deg]\")\n", + "position_errors_8a = {}\n", + "centre_errors_8a = {}\n", + "orientation_errors_8a = {}\n", + "for pixel_error in [1.0, 3.0, 5.0, 10.0]:\n", + " print(\"=== Gaussian errors on feature image locations:\", pixel_error, \"===\")\n", + " smeared_feature_locations = simulator.get_image_feature_locations(area_restrict=image_area, min_feature_count=2, pixel_error=pixel_error)\n", + " led_positions_8a = {k: v for k, v in led_positions.items() if np.any([k in i.keys() for i in smeared_feature_locations.values()])}\n", + " fitter = setup_led_simulation(led_positions_8a, smeared_feature_locations, focal_length, principle_point, radial_distortion) \n", + " reco_led_positions, position_errors_8a[pixel_error] = run_led_fit(fitter, led_positions_8a)\n", + " centre_errors_8a[pixel_error] = get_mpmt_centre_errors(reco_led_positions, mpmt_locations, led_count)\n", + " orientation_errors_8a[pixel_error] = get_mpmt_orientation_errors(reco_led_positions, mpmt_orientations, led_count)\n", + " ax_led_pos.hist(position_errors_8a[pixel_error], bins=20, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, position_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_pos.hist(centre_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} cm\".format(pixel_error, centre_errors_8a[pixel_error].mean()))\n", + " ax_mpmt_ang.hist(orientation_errors_8a[pixel_error], bins=15, histtype='step', lw=1.5, label=\"{} pixel error: mean = {:.2f} deg\".format(pixel_error, orientation_errors_8a[pixel_error].mean()))\n", + "ax_led_pos.legend(loc='upper right')\n", + "ax_mpmt_pos.legend(loc='upper right')\n", + "ax_mpmt_ang.legend(loc='upper right')" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "reco_errors, reco_transformed, scale, R, translation, _ = fit.kabsch_errors(led_positions, reco_led_positions)\n", + "\n", + "reco_cam_orientations, reco_cam_positions = fit.camera_world_poses(fitter.camera_rotations, fitter.camera_translations)\n", + "cam_orientations_transformed = np.matmul(R, reco_cam_orientations)\n", + "cam_positions_translated = reco_cam_positions - translation\n", + "cam_positions_transformed = scale*R.dot(cam_positions_translated.transpose()).transpose()\n", + "\n", + "plot_reconstruction(reco_transformed, cam_positions_transformed)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.2" + }, + "pycharm": { + "stem_cell": { + "cell_type": "raw", + "metadata": { + "collapsed": false + }, + "source": [] + } + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/parameters/WCTE_16cShort_PMT_locations.txt b/parameters/WCTE_16cShort_PMT_locations.txt new file mode 100644 index 0000000..fbce0f5 --- /dev/null +++ b/parameters/WCTE_16cShort_PMT_locations.txt @@ -0,0 +1,2014 @@ +1 165.261390445 10.279512936 32.87253441 +2 163.655993447 12.484465107 40.943410139 +3 162.480761278 18.508506468 46.851701234 +4 162.050596449 26.7375 49.014285867 +5 162.480761278 34.966493532 46.851701234 +6 163.655993447 40.990534893 40.943410139 +7 165.261390445 43.195487064 32.87253441 +8 166.866787443 40.990534893 24.801658681 +9 168.042019612 34.966493532 18.893367586 +10 168.472184441 26.7375 16.730782952 +11 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b/parameters/WCTE_16c_centrePMT_locations.txt new file mode 100644 index 0000000..a388e0e --- /dev/null +++ b/parameters/WCTE_16c_centrePMT_locations.txt @@ -0,0 +1,122 @@ +19 160.016617465 58.78 31.8292842 +38 135.65553801 58.78 90.642132614 +57 90.642132614 58.78 135.65553801 +76 31.8292842 58.78 160.016617465 +95 -31.8292842 58.78 160.016617465 +114 -90.642132614 58.78 135.65553801 +133 -135.65553801 58.78 90.642132614 +152 -160.016617465 58.78 31.8292842 +171 -160.016617465 58.78 -31.8292842 +190 -135.65553801 58.78 -90.642132614 +209 -90.642132614 58.78 -135.65553801 +228 -31.8292842 58.78 -160.016617465 +247 31.8292842 58.78 -160.016617465 +266 90.642132614 58.78 -135.65553801 +285 135.65553801 58.78 -90.642132614 +304 160.016617465 58.78 -31.8292842 +323 160.016617465 0 31.8292842 +342 135.65553801 0 90.642132614 +361 90.642132614 0 135.65553801 +380 31.8292842 0 160.016617465 +399 -31.8292842 0 160.016617465 +418 -90.642132614 0 135.65553801 +437 -135.65553801 0 90.642132614 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-168.051528333 0 +1539 58 -168.051528333 58 +1558 58 -168.051528333 116 +1577 116 -168.051528333 -58 +1596 116 -168.051528333 0 +1615 116 -168.051528333 58 +1634 160.016617465 117.56 31.8292842 +1653 135.65553801 117.56 90.642132614 +1672 90.642132614 117.56 135.65553801 +1691 31.8292842 117.56 160.016617465 +1710 -31.8292842 117.56 160.016617465 +1729 -90.642132614 117.56 135.65553801 +1748 -135.65553801 117.56 90.642132614 +1767 -160.016617465 117.56 31.8292842 +1786 -160.016617465 117.56 -31.8292842 +1805 -135.65553801 117.56 -90.642132614 +1824 -90.642132614 117.56 -135.65553801 +1843 -31.8292842 117.56 -160.016617465 +1862 31.8292842 117.56 -160.016617465 +1881 90.642132614 117.56 -135.65553801 +1900 135.65553801 117.56 -90.642132614 +1919 160.016617465 117.56 -31.8292842 +1938 -116 168.051528333 -58 +1957 -116 168.051528333 0 +1976 -116 168.051528333 58 +1995 -58 168.051528333 -116 +2014 -58 168.051528333 -58 +2033 -58 168.051528333 0 +2052 -58 168.051528333 58 +2071 -58 168.051528333 116 +2090 0 168.051528333 -116 +2109 0 168.051528333 -58 +2128 0 168.051528333 0 +2147 0 168.051528333 58 +2166 0 168.051528333 116 +2185 58 168.051528333 -116 +2204 58 168.051528333 -58 +2223 58 168.051528333 0 +2242 58 168.051528333 58 +2261 58 168.051528333 116 +2280 116 168.051528333 -58 +2299 116 168.051528333 0 +2318 116 168.051528333 58 diff --git a/pg_fitter_tools.py b/pg_fitter_tools.py index 3dde55a..1e02a25 100644 --- a/pg_fitter_tools.py +++ b/pg_fitter_tools.py @@ -110,53 +110,97 @@ def fit_errors(self, params, fit_cam=False, max_error=None): return errors return np.minimum(errors, max_error) + def fit_errors_curvefit(self, x_dummy, *args, fit_cam=False, max_error=None): + params=np.array(args) + if fit_cam: + offset = 4+self.distortion.shape[0] + camera_matrix = build_camera_matrix(params[:2],params[2:4]) + distortion = params[4:offset].reshape((-1,1)) + else: + offset = 0 + camera_matrix = self.camera_matrix + distortion = self.distortion + camera_rotations = params[offset:offset+self.nimages*3].reshape((-1, 3)) + camera_translations = params[offset+self.nimages*3:offset+self.nimages*6].reshape((-1, 3)) + feature_locations = params[offset+self.nimages*6:].reshape((-1, 3)) + errors = self.reprojection_errors(camera_rotations, camera_translations, feature_locations, camera_matrix, distortion) + if max_error is None: + return errors + return np.minimum(errors, max_error) + + def bundle_adjustment(self, camera_rotations, camera_translations, xtol=1e-6, method='trf', use_sparsity = True, - max_error = None, fit_cam = False): + max_error = None, fit_cam = False, return_opt = False, curve_fit=False): x0 = np.concatenate((camera_rotations.flatten(), camera_translations.flatten(), self.seed_feature_locations.flatten())) if fit_cam: x0 = np.concatenate((self.camera_matrix[(0,1,0,1),(0,1,2,2)], self.distortion.flatten(), x0)) initial_errors = self.fit_errors(x0, max_error, fit_cam) - if method == 'lm' or use_sparsity == False: - res = opt.least_squares(self.fit_errors, x0, verbose=2, method=method, xtol=xtol) + if curve_fit: + x_dummy = initial_errors + y_values = np.zeros(initial_errors.shape) + self.opt_result = opt.curve_fit(self.fit_errors_curvefit, x_dummy, y_values, x0, method=method) else: - jac_sparsity = lil_matrix((initial_errors.shape[0], x0.shape[0]), dtype=int) - row = 0 - offset = 0 - if fit_cam: - offset = 4+self.distortion.shape[0] - jac_sparsity[:,:offset] = 1 - for i in range(self.nimages): - for j in np.where(np.any(self.image_feature_locations[i] != 0, axis=1))[0]: - jac_sparsity[row:row+2, offset+3*i:offset+3*(i+1)] = 1 - jac_sparsity[row:row+2, offset+3*(self.nimages+i):offset+3*(self.nimages+i+1)] = 1 - jac_sparsity[row:row+2, offset+6*self.nimages+3*j:offset+6*self.nimages+3*(j+1)] = 1 - row += 2 -# print(jac_sparsity.shape, row) -# print(list(jac_sparsity.sum(axis=0))) -# print(list(jac_sparsity.sum(axis=1))) - res = opt.least_squares(self.fit_errors, x0, verbose=2, method=method, xtol=xtol, jac_sparsity=jac_sparsity, - kwargs={"max_error":max_error, "fit_cam": fit_cam}) - errors = linalg.norm(self.fit_errors(res.x, fit_cam=fit_cam).reshape((-1, 2)), axis=1) + if method == 'lm' or use_sparsity == False: + self.opt_result = opt.least_squares(self.fit_errors, x0, verbose=2, method=method, xtol=xtol) + else: + jac_sparsity = lil_matrix((initial_errors.shape[0], x0.shape[0]), dtype=int) + row = 0 + offset = 0 + if fit_cam: + offset = 4+self.distortion.shape[0] + jac_sparsity[:,:offset] = 1 + for i in range(self.nimages): + for j in np.where(np.any(self.image_feature_locations[i] != 0, axis=1))[0]: + jac_sparsity[row:row+2, offset+3*i:offset+3*(i+1)] = 1 + jac_sparsity[row:row+2, offset+3*(self.nimages+i):offset+3*(self.nimages+i+1)] = 1 + jac_sparsity[row:row+2, offset+6*self.nimages+3*j:offset+6*self.nimages+3*(j+1)] = 1 + row += 2 + # print(jac_sparsity.shape, row) + # print(list(jac_sparsity.sum(axis=0))) + # print(list(jac_sparsity.sum(axis=1))) + self.opt_result = opt.least_squares(self.fit_errors, x0, verbose=2, method=method, xtol=xtol, jac_sparsity=jac_sparsity, + kwargs={"max_error":max_error, "fit_cam": fit_cam}) + errors = linalg.norm(self.fit_errors(self.opt_result.x, fit_cam=fit_cam).reshape((-1, 2)), axis=1) if not self.quiet: print("mean reprojection error:", np.mean(errors), ) print("max reprojection error:", max(errors)) if fit_cam: - camera_matrix = build_camera_matrix(res.x[:2],res.x[2:4]) + camera_matrix = build_camera_matrix(self.opt_result.x[:2],self.opt_result.x[2:4]) offset = 4+self.distortion.shape[0] - distortion = res.x[4:offset].reshape((-1,1)) + distortion = self.opt_result.x[4:offset].reshape((-1,1)) else: offset = 0 - self.camera_rotations = res.x[offset:offset+self.nimages*3].reshape((-1, 3)) - self.camera_translations = res.x[offset+self.nimages*3:offset+self.nimages*6].reshape((-1, 3)) - self.reco_locations = res.x[offset+self.nimages*6:].reshape((-1, 3)) + self.camera_rotations = self.opt_result.x[offset:offset+self.nimages*3].reshape((-1, 3)) + self.camera_translations = self.opt_result.x[offset+self.nimages*3:offset+self.nimages*6].reshape((-1, 3)) + self.reco_locations = self.opt_result.x[offset+self.nimages*6:].reshape((-1, 3)) reco_locations = {f: self.reco_locations[i] for f, i in self.feature_index.items()} + result = self.camera_rotations, self.camera_translations, reco_locations if fit_cam: - return self.camera_rotations, self.camera_translations, reco_locations, camera_matrix, distortion - else: - return self.camera_rotations, self.camera_translations, reco_locations - + result = *result, camera_matrix, distortion + if return_opt: + result = *result, self.opt_result + return result + + def bundle_adjustment_curvefit(self, camera_rotations, camera_translations, method='trf', xtol=1e-6): + x0 = np.concatenate((camera_rotations.flatten(), + camera_translations.flatten(), + self.seed_feature_locations.flatten())) + initial_errors = self.fit_errors(x0) + x_dummy = initial_errors + y_values = np.zeros(initial_errors.shape) + self.opt_result = opt.curve_fit(self.fit_errors_curvefit, x_dummy, y_values, x0, verbose=2, method=method, xtol=xtol) + errors = linalg.norm(self.fit_errors(self.opt_result[0]).reshape((-1, 2)), axis=1) + if not self.quiet: + print("mean reprojection error:", np.mean(errors), ) + print("max reprojection error:", max(errors)) + self.camera_rotations = self.opt_result[0][:self.nimages*3].reshape((-1, 3)) + self.camera_translations = self.opt_result[0][self.nimages*3:self.nimages*6].reshape((-1, 3)) + self.reco_locations = self.opt_result[0][self.nimages*6:].reshape((-1, 3)) + reco_locations = {f: self.reco_locations[i] for f, i in self.feature_index.items()} + return self.camera_rotations, self.camera_translations, reco_locations, self.opt_result + def fit(self): camera_rotations, camera_translations = self.estimate_camera_poses() return self.bundle_adjustment(camera_rotations, camera_translations) diff --git a/results/full_ring_relabelled_2/SK_ring_cameras_relabelled.txt b/results/full_ring_relabelled_2/SK_ring_cameras_relabelled.txt index ea180d8..5998ef3 100644 --- a/results/full_ring_relabelled_2/SK_ring_cameras_relabelled.txt +++ b/results/full_ring_relabelled_2/SK_ring_cameras_relabelled.txt @@ -1,52 +1,52 @@ CameraID/C:CameraPosition[3]/D:CameraOrientation[3][3]/D -755 -970.5092180137706 564.3784382127312 293.3823327623795 0.4522776906126593 -0.015743884031937203 -0.8917382018785944 0.8918348214011813 -0.0017601765219726097 0.45235777114462655 -0.008691484936539286 -0.9998745080729884 0.013244855431355135 -756 -889.7590320221931 700.2124696144455 295.5607796822613 0.5611808064680818 -0.0016323186867720006 -0.8276916321840755 0.8276929365557922 0.00024795829279654737 0.5611812018344292 -0.0007107935583411163 -0.9999986370252661 0.0014902080819712117 -757 -797.1598304414227 789.0560040424572 295.65999522152237 0.6824136051335139 -0.008630399791837695 -0.7309153081774347 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1973.7003063845013 2009.211176967734 2250.705808941928 2025.845946621428 1233.360711104229 2032.7815639739326 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3.372249974079294 2.3093692725215242 2.2667404395392223 1.2707080114380989 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -02222-00 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2735 1994 3169 1975 2270 2034 1231 2009 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 -384.0 1646.0 212.0 -384.5761096757854 1647.4146375233004 212.11634373109285 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2734.542400103081 1991.25976366044 3166.1433056805063 1978.6936934461958 2274.5299826511778 2032.177133280707 1229.3248781620205 2009.973986531194 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.7781815747544503 4.669483237950136 4.882989442572795 1.9377004244782576 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -03650-00 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2926 2009 1885 2025 1896 2022 2292 2080 1129 2057 0 0 -1666.0 284.0 212.0 -1666.1194114088414 283.910153435889 211.69729375937425 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2924.777660220091 2010.9879291053503 1883.858935649156 2023.6970042139533 1896.6867605180212 2021.7268931273397 2293.717881084848 2081.1437687284433 1128.7473841720407 2055.426478855413 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2.3336616433079187 1.7320005401912435 0.7390719674070862 2.063812570424925 1.5936698368854485 0.0 -06457-00 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3440 1287 2241 1298 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 907.0 -1426.0 357.0 907.692425003944 -1428.2965625772797 358.28878930716775 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 3440.874352555176 1287.6207006036755 2240.0054808518316 1297.4542298390793 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0722693831988357 1.1344308725633965 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -00747-00 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2249 703 1193 776 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1408.0 935.0 491.0 1408.832399589781 934.0757866361133 492.2941864591914 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2249.681018884021 710.1480401667603 1192.018780482565 768.6323200794709 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 7.180408410808679 7.432731607744422 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -02630-00 3 0 0 0 0 0 0 0 0 3342 2007 2169 1999 1259 1976 0 0 0 0 0 0 0 0 0 0 0 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