diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..c9019da --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,81 @@ +name: CI + +on: + push: + branches: [main, develop] + pull_request: + branches: [main] + +jobs: + lint: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.12" + cache: "pip" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install ruff + + - name: Run ruff linter + run: ruff check src tests + + - name: Run ruff formatter check + run: ruff format --check src tests + + test: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.12" + cache: "pip" + + - name: Install dependencies + run: | + python -m pip install --upgrade pip + pip install -e ".[dev,viz]" + + - name: Run tests with coverage + run: | + pytest tests/ -v --tb=short --cov=src/samap --cov-report=xml --cov-report=term + + - name: Upload coverage + uses: codecov/codecov-action@v4 + with: + files: ./coverage.xml + fail_ci_if_error: false + + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.12" + cache: "pip" + + - name: Install build dependencies + run: | + python -m pip install --upgrade pip + pip install build + + - name: Build package + run: python -m build + + - name: Check build artifacts + run: | + ls -la dist/ + pip install dist/*.whl + python -c "import samap; print(samap.__version__)" diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml new file mode 100644 index 0000000..8fe08d1 --- /dev/null +++ b/.github/workflows/release.yml @@ -0,0 +1,47 @@ +name: Release to PyPI + +on: + push: + tags: + - "v*" + +jobs: + build: + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Set up Python + uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install build dependencies + run: | + python -m pip install --upgrade pip + pip install build + + - name: Build package + run: python -m build + + - name: Upload build artifacts + uses: actions/upload-artifact@v4 + with: + name: dist + path: dist/ + + publish: + needs: build + runs-on: ubuntu-latest + environment: pypi + permissions: + id-token: write + steps: + - name: Download build artifacts + uses: actions/download-artifact@v4 + with: + name: dist + path: dist/ + + - name: Publish to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..5a2a789 --- /dev/null +++ b/.gitignore @@ -0,0 +1,102 @@ +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +*.egg + +# PyInstaller +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ + +# Translations +*.mo +*.pot + +# Jupyter Notebook +.ipynb_checkpoints/ + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# ruff +.ruff_cache/ + +# IDE +.idea/ +.vscode/ +*.swp +*.swo +*~ + +# OS +.DS_Store +Thumbs.db + +# Project specific +*.h5 +*.hdf5 diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 0000000..40862ab --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,27 @@ +repos: + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: trailing-whitespace + - id: end-of-file-fixer + - id: check-yaml + - id: check-added-large-files + - id: check-merge-conflict + + - repo: https://github.com/astral-sh/ruff-pre-commit + rev: v0.2.0 + hooks: + - id: ruff + args: [--fix] + - id: ruff-format + + - repo: https://github.com/pre-commit/mirrors-mypy + rev: v1.8.0 + hooks: + - id: mypy + additional_dependencies: + - numpy + - pandas-stubs + args: + - --ignore-missing-imports + exclude: tests/ diff --git a/README.md b/README.md index ab56983..7855247 100755 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# SAMap -- version 1.0.15 +# SAMap -- version 2.0.2 # Citation Please cite the following paper if using SAMap: https://elifesciences.org/articles/66747 @@ -9,7 +9,7 @@ Tarashansky, Alexander J., et al. "Mapping single-cell atlases throughout Metazo ### pip -`pip install samap` +`pip install sc-samap` ### Manual installation Download Anacodna from here: diff --git a/SAMap_vignette.ipynb b/SAMap_vignette.ipynb index 148e2f0..0f978d6 100644 --- a/SAMap_vignette.ipynb +++ b/SAMap_vignette.ipynb @@ -6,9 +6,9 @@ "metadata": {}, "outputs": [], "source": [ - "from samap.mapping import SAMAP\n", + "from samap import SAMAP\n", "from samap.analysis import (get_mapping_scores, GenePairFinder,\n", - " sankey_plot, chord_plot, CellTypeTriangles, \n", + " sankey_plot, CellTypeTriangles, \n", " ParalogSubstitutions, FunctionalEnrichment,\n", " convert_eggnog_to_homologs, GeneTriangles)\n", "from samalg import SAM\n", @@ -469,7 +469,20 @@ "cell_type": "code", "execution_count": 6, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/alect/Desktop/sam-algorithm/src/samalg/sam.py:500: FutureWarning: `__version__` is deprecated, use `importlib.metadata.version('anndata')` instead.\n", + " if version.parse(str(anndata.__version__)) >= version.parse(\"0.7rc1\"):\n", + "/Users/alect/Desktop/sam-algorithm/src/samalg/sam.py:500: FutureWarning: `__version__` is deprecated, use `importlib.metadata.version('anndata')` instead.\n", + " if version.parse(str(anndata.__version__)) >= version.parse(\"0.7rc1\"):\n", + "/Users/alect/Desktop/sam-algorithm/src/samalg/sam.py:500: FutureWarning: `__version__` is deprecated, use `importlib.metadata.version('anndata')` instead.\n", + " if version.parse(str(anndata.__version__)) >= version.parse(\"0.7rc1\"):\n" + ] + } + ], "source": [ "sam1=SAM()\n", "sam1.load_data(fn1)\n", @@ -487,15 +500,15 @@ "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Not updating the manifold...\n", - "Not updating the manifold...\n", - "Not updating the manifold...\n", - "14355 `pl` gene symbols match between the datasets and the BLAST graph.\n", - "7605 `sc` gene symbols match between the datasets and the BLAST graph.\n", - "12637 `hy` gene symbols match between the datasets and the BLAST graph.\n" + "INFO: Not updating the manifold...\n", + "INFO: Not updating the manifold...\n", + "INFO: Not updating the manifold...\n", + "INFO: 14355 'pl' gene symbols match between the datasets and the BLAST graph.\n", + "INFO: 7605 'sc' gene symbols match between the datasets and the BLAST graph.\n", + "INFO: 12637 'hy' gene symbols match between the datasets and the BLAST graph.\n" ] } ], @@ -529,64 +542,61 @@ "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Prepping datasets for translation.\n", - "Translating feature spaces pairwise.\n", - "Projecting data into joint latent space. 3.2279748916625977\n", - "Correcting data with means. 4.532547950744629\n", - "Expanding neighbourhoods of species pl...\n", - "Expanding neighbourhoods of species sc...\n", - "Expanding neighbourhoods of species hy...\n", - "Indegree coarsening\n", - "0/1 (0, 3124)\n", - "Rescaling edge weights by expression correlations.\n", - "Concatenating SAM objects...\n", - "Iteration 1 complete.\n", - "Alignment scores:\n", + "INFO: Prepping datasets for translation.\n", + "INFO: Translating feature spaces pairwise.\n", + "INFO: Projecting data into joint latent space. 1.46s\n", + "INFO: Correcting data with means. 1.18s\n", + "INFO: Expanding neighbourhoods of species pl...\n", + "INFO: Expanding neighbourhoods of species sc...\n", + "INFO: Expanding neighbourhoods of species hy...\n", + "INFO: Indegree coarsening\n", + "INFO: Rescaling edge weights by expression correlations.\n", + "INFO: Concatenating SAM objects...\n", + "INFO: Iteration 1 complete.\n", + "INFO: Alignment scores:\n", " hy pl sc\n", - "hy 0.000000 0.435470 0.424640\n", - "pl 0.476524 0.000000 0.639555\n", - "sc 0.478394 0.663902 0.000000\n", - "Calculating gene-gene correlations in the homology graph...\n", - "Prepping datasets for translation.\n", - "Translating feature spaces pairwise.\n", - "Projecting data into joint latent space. 2.551313877105713\n", - "Correcting data with means. 2.6602261066436768\n", - "Expanding neighbourhoods of species pl...\n", - "Expanding neighbourhoods of species sc...\n", - "Expanding neighbourhoods of species hy...\n", - "Indegree coarsening\n", - "0/1 (0, 3124)\n", - "Rescaling edge weights by expression correlations.\n", - "Concatenating SAM objects...\n", - "Iteration 2 complete.\n", - "Alignment scores:\n", + "hy 0.000000 0.391416 0.382622\n", + "pl 0.445996 0.000000 0.601834\n", + "sc 0.455310 0.639204 0.000000\n", + "INFO: Calculating gene-gene correlations in the homology graph...\n", + "INFO: Prepping datasets for translation.\n", + "INFO: Translating feature spaces pairwise.\n", + "INFO: Projecting data into joint latent space. 1.23s\n", + "INFO: Correcting data with means. 1.05s\n", + "INFO: Expanding neighbourhoods of species pl...\n", + "INFO: Expanding neighbourhoods of species sc...\n", + "INFO: Expanding neighbourhoods of species hy...\n", + "INFO: Indegree coarsening\n", + "INFO: Rescaling edge weights by expression correlations.\n", + "INFO: Concatenating SAM objects...\n", + "INFO: Iteration 2 complete.\n", + "INFO: Alignment scores:\n", " hy pl sc\n", - "hy 0.000000 0.527345 0.488376\n", - "pl 0.582561 0.000000 0.705353\n", - "sc 0.555789 0.703715 0.000000\n", - "Calculating gene-gene correlations in the homology graph...\n", - "Prepping datasets for translation.\n", - "Translating feature spaces pairwise.\n", - "Projecting data into joint latent space. 2.362617015838623\n", - "Correcting data with means. 3.0483272075653076\n", - "Expanding neighbourhoods of species pl...\n", - "Expanding neighbourhoods of species sc...\n", - "Expanding neighbourhoods of species hy...\n", - "Indegree coarsening\n", - "0/1 (0, 3124)\n", - "Rescaling edge weights by expression correlations.\n", - "Concatenating SAM objects...\n", - "Iteration 3 complete.\n", - "Alignment scores:\n", + "hy 0.000000 0.476882 0.446729\n", + "pl 0.548278 0.000000 0.669231\n", + "sc 0.533270 0.681846 0.000000\n", + "INFO: Calculating gene-gene correlations in the homology graph...\n", + "INFO: Prepping datasets for translation.\n", + "INFO: Translating feature spaces pairwise.\n", + "INFO: Projecting data into joint latent space. 1.27s\n", + "INFO: Correcting data with means. 1.10s\n", + "INFO: Expanding neighbourhoods of species pl...\n", + "INFO: Expanding neighbourhoods of species sc...\n", + "INFO: Expanding neighbourhoods of species hy...\n", + "INFO: Indegree coarsening\n", + "INFO: Rescaling edge weights by expression correlations.\n", + "INFO: Concatenating SAM objects...\n", + "INFO: Iteration 3 complete.\n", + "INFO: Alignment scores:\n", " hy pl sc\n", - "hy 0.000000 0.549762 0.519417\n", - "pl 0.596325 0.000000 0.709699\n", - "sc 0.570683 0.709405 0.000000\n", - "Running UMAP on the stitched manifolds.\n", - "Elapsed time: 1.3108057181040447 minutes.\n" + "hy 0.000000 0.495094 0.474622\n", + "pl 0.564872 0.000000 0.675047\n", + "sc 0.546122 0.685110 0.000000\n", + "INFO: Running UMAP on the stitched manifolds.\n", + "INFO: Elapsed time: 0.64 minutes.\n" ] } ], @@ -786,11 +796,11 @@ " hy_t34367aep 73.5\n", " hy_t13960aep 70.3\n", " dtype: float64,\n", - " 'correlation': sc_Smp_102690 0.228268\n", - " sc_Smp_179320 0.871954\n", - " sc_Smp_198380 0.230778\n", - " hy_t34367aep 0.672766\n", - " hy_t13960aep 0.599172\n", + " 'correlation': sc_Smp_102690 0.225455\n", + " sc_Smp_179320 0.872515\n", + " sc_Smp_198380 0.236296\n", + " hy_t34367aep 0.655665\n", + " hy_t13960aep 0.601378\n", " dtype: float64}" ] }, @@ -811,7 +821,7 @@ { "data": { "text/plain": [ - "{'blast': 130.0, 'correlation': 0.8719536941498626}" + "{'blast': np.float64(130.0), 'correlation': np.float64(0.8725150463770156)}" ] }, "execution_count": 13, @@ -875,15 +885,15 @@ " \n", " \n", " \n", - " pl_Muscle: 13\n", " sc_Muscle\n", + " pl_Muscle: 13\n", " pl_Muscle: 14\n", - " pl_Neoblast: 0\n", " sc_Neoblast\n", + " pl_Neoblast: 22\n", " ...\n", - " sc_Intestine\n", " pl_Protonephridia: 26\n", - " pl_Protonephridia: 29\n", + " hy_i_nb4\n", + " hy_ecEp_bd\n", " sc_Gland\n", " sc_Neural_KK7\n", " \n", @@ -915,123 +925,123 @@ " \n", " \n", " 0\n", - " sc_Muscle\n", - " 0.982983\n", " pl_Muscle: 13\n", - " 0.982983\n", + " 0.979609\n", " sc_Muscle\n", - " 0.979713\n", + " 0.979609\n", + " sc_Muscle\n", + " 0.979485\n", + " pl_Neoblast: 22\n", + " 0.97269\n", " sc_Neoblast\n", - " 0.976192\n", - " pl_Neoblast: 0\n", - " 0.976192\n", + " 0.97269\n", " ...\n", - " pl_Cathepsin+ cells: 41\n", - " 0.152281\n", " sc_Parenchymal\n", - " 0.151101\n", - " sc_Flame cells\n", - " 0.145074\n", + " 0.121519\n", + " sc_Neoblast\n", + " 0.117416\n", + " pl_Epidermal: 11\n", + " 0.110585\n", " hy_i_zmg1\n", - " 0.081578\n", + " 0.07977\n", " pl_Neural: 1\n", - " 0.068333\n", + " 0.036137\n", " \n", " \n", " 1\n", - " hy_enEp_tent(pd)\n", - " 0.443094\n", " pl_Muscle: 14\n", - " 0.979713\n", + " 0.979485\n", + " hy_enEp_tent(pd)\n", + " 0.431635\n", " hy_enEp_tent(pd)\n", - " 0.51\n", + " 0.498208\n", + " pl_Neoblast: 0\n", + " 0.969821\n", " hy_i_SC\n", - " 0.662741\n", - " pl_Neoblast: 22\n", - " 0.975144\n", + " 0.62515\n", " ...\n", - " pl_Cathepsin+ cells: 17\n", - " 0.117137\n", " sc_Flame cells\n", - " 0.034998\n", - " hy_ecEp_bat2(mp)\n", - " 0.069005\n", + " 0.03699\n", + " pl_Neural: 1\n", + " 0.112005\n", + " sc_Tegument\n", + " 0.070849\n", " pl_Epidermal: 11\n", - " 0.066768\n", + " 0.068894\n", " pl_Neoblast: 0\n", - " 0.033106\n", + " 0.032044\n", " \n", " \n", " 2\n", - " hy_enEp_tent\n", - " 0.391651\n", " hy_enEp_tent(pd)\n", - " 0.915641\n", + " 0.905327\n", " hy_enEp_tent\n", - " 0.480479\n", + " 0.388224\n", + " hy_enEp_tent\n", + " 0.480113\n", + " hy_i_nb1\n", + " 0.780747\n", " hy_i_fmgl1\n", - " 0.642439\n", - " hy_i_SC\n", - " 0.805867\n", + " 0.132719\n", " ...\n", - " hy_enEp_SC2\n", - " 0.104744\n", " hy_i_nb3\n", - " 0.018667\n", + " 0.016521\n", " sc_Neural\n", - " 0.04483\n", + " 0.106921\n", + " pl_Epidermal: 24\n", + " 0.069311\n", " hy_i_zmg2\n", - " 0.066321\n", + " 0.063464\n", " hy_enEp_SC1\n", - " 0.028677\n", + " 0.029772\n", " \n", " \n", " 3\n", - " hy_enEp_foot\n", - " 0.158883\n", " hy_enEp_tent\n", - " 0.883223\n", + " 0.867443\n", " hy_enEp_foot\n", - " 0.234555\n", - " hy_i_nb1\n", - " 0.619087\n", + " 0.160652\n", + " hy_enEp_foot\n", + " 0.24675\n", + " hy_i_SC\n", + " 0.775236\n", " hy_i_nb1\n", - " 0.803724\n", + " 0.127893\n", " ...\n", - " hy_enEp_SC1\n", - " 0.099209\n", " sc_Neural\n", - " 0.01747\n", - " hy_ecEp_bat1(mp)\n", - " 0.037162\n", + " 0.01401\n", + " sc_Parenchymal\n", + " 0.050602\n", + " sc_Tegument_prog\n", + " 0.031709\n", " pl_Parapharyngeal: 12\n", - " 0.056032\n", - " pl_Muscle: 14\n", - " 0.026056\n", + " 0.058227\n", + " pl_Muscle: 13\n", + " 0.02699\n", " \n", " \n", " 4\n", - " hy_enEp_nem1(pd)\n", - " 0.055289\n", " pl_Muscle: 16\n", - " 0.837578\n", + " 0.836669\n", + " hy_enEp_nem1(pd)\n", + " 0.052999\n", " hy_enEp_nem1(pd)\n", - " 0.073166\n", + " 0.086924\n", + " hy_i_fmgl1\n", + " 0.718373\n", " hy_i_nc_gc_prog\n", - " 0.492698\n", - " pl_Neoblast: 5\n", - " 0.740004\n", + " 0.079645\n", " ...\n", - " hy_nan\n", - " 0.091858\n", " hy_i_nb2\n", - " 0.013353\n", - " hy_i_nem\n", - " 0.027602\n", + " 0.006867\n", + " pl_Parapharyngeal: 12\n", + " 0.043915\n", + " pl_Epidermal: 35\n", + " 0.008694\n", " pl_Epidermal: 3\n", - " 0.035933\n", - " pl_Muscle: 13\n", - " 0.025634\n", + " 0.036777\n", + " pl_Muscle: 14\n", + " 0.024752\n", " \n", " \n", "\n", @@ -1039,53 +1049,45 @@ "" ], "text/plain": [ - " pl_Muscle: 13 sc_Muscle \\\n", + " sc_Muscle pl_Muscle: 13 \\\n", " Cluster Alignment score Cluster Alignment score \n", - "0 sc_Muscle 0.982983 pl_Muscle: 13 0.982983 \n", - "1 hy_enEp_tent(pd) 0.443094 pl_Muscle: 14 0.979713 \n", - "2 hy_enEp_tent 0.391651 hy_enEp_tent(pd) 0.915641 \n", - "3 hy_enEp_foot 0.158883 hy_enEp_tent 0.883223 \n", - "4 hy_enEp_nem1(pd) 0.055289 pl_Muscle: 16 0.837578 \n", + "0 pl_Muscle: 13 0.979609 sc_Muscle 0.979609 \n", + "1 pl_Muscle: 14 0.979485 hy_enEp_tent(pd) 0.431635 \n", + "2 hy_enEp_tent(pd) 0.905327 hy_enEp_tent 0.388224 \n", + "3 hy_enEp_tent 0.867443 hy_enEp_foot 0.160652 \n", + "4 pl_Muscle: 16 0.836669 hy_enEp_nem1(pd) 0.052999 \n", "\n", - " pl_Muscle: 14 pl_Neoblast: 0 \\\n", + " pl_Muscle: 14 sc_Neoblast \\\n", " Cluster Alignment score Cluster Alignment score \n", - "0 sc_Muscle 0.979713 sc_Neoblast 0.976192 \n", - "1 hy_enEp_tent(pd) 0.51 hy_i_SC 0.662741 \n", - "2 hy_enEp_tent 0.480479 hy_i_fmgl1 0.642439 \n", - "3 hy_enEp_foot 0.234555 hy_i_nb1 0.619087 \n", - "4 hy_enEp_nem1(pd) 0.073166 hy_i_nc_gc_prog 0.492698 \n", - "\n", - " sc_Neoblast ... sc_Intestine \\\n", - " Cluster Alignment score ... Cluster \n", - "0 pl_Neoblast: 0 0.976192 ... pl_Cathepsin+ cells: 41 \n", - "1 pl_Neoblast: 22 0.975144 ... pl_Cathepsin+ cells: 17 \n", - "2 hy_i_SC 0.805867 ... hy_enEp_SC2 \n", - "3 hy_i_nb1 0.803724 ... hy_enEp_SC1 \n", - "4 pl_Neoblast: 5 0.740004 ... hy_nan \n", - "\n", - " pl_Protonephridia: 26 pl_Protonephridia: 29 \\\n", - " Alignment score Cluster Alignment score Cluster \n", - "0 0.152281 sc_Parenchymal 0.151101 sc_Flame cells \n", - "1 0.117137 sc_Flame cells 0.034998 hy_ecEp_bat2(mp) \n", - "2 0.104744 hy_i_nb3 0.018667 sc_Neural \n", - "3 0.099209 sc_Neural 0.01747 hy_ecEp_bat1(mp) \n", - "4 0.091858 hy_i_nb2 0.013353 hy_i_nem \n", - "\n", - " sc_Gland sc_Neural_KK7 \\\n", - " Alignment score Cluster Alignment score Cluster \n", - "0 0.145074 hy_i_zmg1 0.081578 pl_Neural: 1 \n", - "1 0.069005 pl_Epidermal: 11 0.066768 pl_Neoblast: 0 \n", - "2 0.04483 hy_i_zmg2 0.066321 hy_enEp_SC1 \n", - "3 0.037162 pl_Parapharyngeal: 12 0.056032 pl_Muscle: 14 \n", - "4 0.027602 pl_Epidermal: 3 0.035933 pl_Muscle: 13 \n", - "\n", - " \n", - " Alignment score \n", - "0 0.068333 \n", - "1 0.033106 \n", - "2 0.028677 \n", - "3 0.026056 \n", - "4 0.025634 \n", + "0 sc_Muscle 0.979485 pl_Neoblast: 22 0.97269 \n", + "1 hy_enEp_tent(pd) 0.498208 pl_Neoblast: 0 0.969821 \n", + "2 hy_enEp_tent 0.480113 hy_i_nb1 0.780747 \n", + "3 hy_enEp_foot 0.24675 hy_i_SC 0.775236 \n", + "4 hy_enEp_nem1(pd) 0.086924 hy_i_fmgl1 0.718373 \n", + "\n", + " pl_Neoblast: 22 ... pl_Protonephridia: 26 \\\n", + " Cluster Alignment score ... Cluster Alignment score \n", + "0 sc_Neoblast 0.97269 ... sc_Parenchymal 0.121519 \n", + "1 hy_i_SC 0.62515 ... sc_Flame cells 0.03699 \n", + "2 hy_i_fmgl1 0.132719 ... hy_i_nb3 0.016521 \n", + "3 hy_i_nb1 0.127893 ... sc_Neural 0.01401 \n", + "4 hy_i_nc_gc_prog 0.079645 ... hy_i_nb2 0.006867 \n", + "\n", + " hy_i_nb4 hy_ecEp_bd \\\n", + " Cluster Alignment score Cluster Alignment score \n", + "0 sc_Neoblast 0.117416 pl_Epidermal: 11 0.110585 \n", + "1 pl_Neural: 1 0.112005 sc_Tegument 0.070849 \n", + "2 sc_Neural 0.106921 pl_Epidermal: 24 0.069311 \n", + "3 sc_Parenchymal 0.050602 sc_Tegument_prog 0.031709 \n", + "4 pl_Parapharyngeal: 12 0.043915 pl_Epidermal: 35 0.008694 \n", + "\n", + " sc_Gland sc_Neural_KK7 \n", + " Cluster Alignment score Cluster Alignment score \n", + "0 hy_i_zmg1 0.07977 pl_Neural: 1 0.036137 \n", + "1 pl_Epidermal: 11 0.068894 pl_Neoblast: 0 0.032044 \n", + "2 hy_i_zmg2 0.063464 hy_enEp_SC1 0.029772 \n", + "3 pl_Parapharyngeal: 12 0.058227 pl_Muscle: 13 0.02699 \n", + "4 pl_Epidermal: 3 0.036777 pl_Muscle: 14 0.024752 \n", "\n", "[5 rows x 190 columns]" ] @@ -1167,11 +1169,11 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.012742\n", - " 0.006771\n", - " 0.001039\n", - " 0.001008\n", - " 0.067557\n", + " 0.011908\n", + " 0.004662\n", + " 0.0\n", + " 0.0\n", + " 0.065268\n", " \n", " \n", " pl_Cathepsin+ cells: 15\n", @@ -1191,11 +1193,11 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.003495\n", - " 0.000673\n", - " 0.000000\n", - " 0.000000\n", - " 0.021509\n", + " 0.003321\n", + " 0.001190\n", + " 0.0\n", + " 0.0\n", + " 0.019791\n", " \n", " \n", " pl_Cathepsin+ cells: 17\n", @@ -1215,11 +1217,11 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.007098\n", - " 0.004383\n", - " 0.000000\n", - " 0.000000\n", - " 0.050909\n", + " 0.007133\n", + " 0.003850\n", + " 0.0\n", + " 0.0\n", + " 0.052705\n", " \n", " \n", " pl_Cathepsin+ cells: 28\n", @@ -1239,11 +1241,11 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.002878\n", - " 0.001543\n", - " 0.000000\n", - " 0.000000\n", - " 0.015010\n", + " 0.002556\n", + " 0.001396\n", + " 0.0\n", + " 0.0\n", + " 0.028709\n", " \n", " \n", " pl_Cathepsin+ cells: 31\n", @@ -1263,11 +1265,11 @@ " 0.0\n", " 0.0\n", " 0.0\n", - " 0.004422\n", - " 0.003921\n", - " 0.000000\n", - " 0.000000\n", - " 0.004256\n", + " 0.004186\n", + " 0.003599\n", + " 0.0\n", + " 0.0\n", + " 0.012505\n", " \n", " \n", "\n", @@ -1318,18 +1320,18 @@ "pl_Cathepsin+ cells: 31 0.0 0.0 0.0 0.0 \n", "\n", " hy_i_smgc1 hy_i_smgc2 hy_i_zmg1 hy_i_zmg2 \\\n", - "pl_Cathepsin+ cells: 10 0.012742 0.006771 0.001039 0.001008 \n", - "pl_Cathepsin+ cells: 15 0.003495 0.000673 0.000000 0.000000 \n", - "pl_Cathepsin+ cells: 17 0.007098 0.004383 0.000000 0.000000 \n", - "pl_Cathepsin+ cells: 28 0.002878 0.001543 0.000000 0.000000 \n", - "pl_Cathepsin+ cells: 31 0.004422 0.003921 0.000000 0.000000 \n", + "pl_Cathepsin+ cells: 10 0.011908 0.004662 0.0 0.0 \n", + "pl_Cathepsin+ cells: 15 0.003321 0.001190 0.0 0.0 \n", + "pl_Cathepsin+ cells: 17 0.007133 0.003850 0.0 0.0 \n", + "pl_Cathepsin+ cells: 28 0.002556 0.001396 0.0 0.0 \n", + "pl_Cathepsin+ cells: 31 0.004186 0.003599 0.0 0.0 \n", "\n", " hy_nan \n", - "pl_Cathepsin+ cells: 10 0.067557 \n", - "pl_Cathepsin+ cells: 15 0.021509 \n", - "pl_Cathepsin+ cells: 17 0.050909 \n", - "pl_Cathepsin+ cells: 28 0.015010 \n", - "pl_Cathepsin+ cells: 31 0.004256 \n", + "pl_Cathepsin+ cells: 10 0.065268 \n", + "pl_Cathepsin+ cells: 15 0.019791 \n", + "pl_Cathepsin+ cells: 17 0.052705 \n", + "pl_Cathepsin+ cells: 28 0.028709 \n", + "pl_Cathepsin+ cells: 31 0.012505 \n", "\n", "[5 rows x 95 columns]" ] @@ -1386,5950 +1388,3895 @@ "outputs": [ { "data": { - "application/javascript": [ - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", + "text/html": [ + " \n", + " " - ], - "text/plain": [ - ":Sankey [source,target] (Value)" - ] - }, - "execution_count": 17, - "metadata": { - "application/vnd.holoviews_exec.v0+json": { - "id": "1002" - } - }, - "output_type": "execute_result" - } - ], - "source": [ - "sankey_plot(MappingTable, align_thr=0.05, species_order = ['pl','sc','hy'])" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [ - { - "data": { - "application/javascript": [ - "(function(root) {\n", - " function now() {\n", - " return new Date();\n", - " }\n", "\n", - " var force = true;\n", + "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n", + " return outOfRange(a.xyz, b.xyz, p.xyz);\n", + "}\n", "\n", - " if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n", - " root._bokeh_onload_callbacks = [];\n", - " root._bokeh_is_loading = undefined;\n", + "uniform vec3 clipBounds[2];\n", + "uniform float roughness\n", + " , fresnel\n", + " , kambient\n", + " , kdiffuse\n", + " , kspecular;\n", + "uniform sampler2D texture;\n", + "\n", + "varying vec3 f_normal\n", + " , f_lightDirection\n", + " , f_eyeDirection\n", + " , f_data;\n", + "varying vec4 f_color;\n", + "varying vec2 f_uv;\n", + "\n", + "void main() {\n", + " if (f_color.a == 0.0 ||\n", + " outOfRange(clipBounds[0], clipBounds[1], f_data)\n", + " ) discard;\n", + "\n", + " vec3 N = normalize(f_normal);\n", + " vec3 L = normalize(f_lightDirection);\n", + " vec3 V = normalize(f_eyeDirection);\n", + "\n", + " if(gl_FrontFacing) {\n", + " N = -N;\n", " }\n", "\n", - " if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n", - " root._bokeh_timeout = Date.now() + 5000;\n", - " root._bokeh_failed_load = false;\n", - " }\n", + " float specular = min(1.0, max(0.0, cookTorranceSpecular(L, V, N, roughness, fresnel)));\n", + " //float specular = max(0.0, beckmann(L, V, N, roughness)); // used in gl-surface3d\n", "\n", - " function run_callbacks() {\n", - " try {\n", - " root._bokeh_onload_callbacks.forEach(function(callback) {\n", - " if (callback != null)\n", - " callback();\n", - " });\n", - " } finally {\n", - " delete root._bokeh_onload_callbacks\n", - " }\n", - " console.debug(\"Bokeh: all callbacks have finished\");\n", - " }\n", + " float diffuse = min(kambient + kdiffuse * max(dot(N, L), 0.0), 1.0);\n", "\n", - " function load_libs(css_urls, js_urls, js_modules, callback) {\n", - " if (css_urls == null) css_urls = [];\n", - " if (js_urls == null) js_urls = [];\n", - " if (js_modules == null) js_modules = [];\n", + " vec4 surfaceColor = vec4(f_color.rgb, 1.0) * texture2D(texture, f_uv);\n", + " vec4 litColor = surfaceColor.a * vec4(diffuse * surfaceColor.rgb + kspecular * vec3(1,1,1) * specular, 1.0);\n", "\n", - " root._bokeh_onload_callbacks.push(callback);\n", - " if (root._bokeh_is_loading > 0) {\n", - " console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n", - " return null;\n", - " }\n", - " if (js_urls.length === 0 && js_modules.length === 0) {\n", - " run_callbacks();\n", - " return null;\n", - " }\n", - " console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n", - "\n", - " function on_load() {\n", - " 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url);\n", - " }\n", + "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n", + " return (outOfRange(a.x, b.x, p.x) ||\n", + " outOfRange(a.y, b.y, p.y));\n", + "}\n", "\n", - " for (var i = 0; i < css_urls.length; i++) {\n", - " var url = css_urls[i];\n", - " const element = document.createElement(\"link\");\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.rel = \"stylesheet\";\n", - " element.type = \"text/css\";\n", - " element.href = url;\n", - " console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n", - " document.body.appendChild(element);\n", - " }\n", + "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n", + " return (outOfRange(a.x, b.x, p.x) ||\n", + " outOfRange(a.y, b.y, p.y) ||\n", + " outOfRange(a.z, b.z, p.z));\n", + "}\n", "\n", - " var skip = [];\n", - " if (window.requirejs) {\n", - " window.requirejs.config({'packages': {}, 'paths': {'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@4.2.5/dist/gridstack-h5', 'notyf': 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#f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.card-button {\\n background-color: transparent;\\n margin-left: 0.5em;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n font-size: 1.4em;\\n font-weight: bold;\\n overflow-wrap: break-word;\\n}\\n.bk.card-header-row > .bk {\\n overflow-wrap: break-word;\\n text-align: center;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.panel-widget-box {\\n min-height: 20px;\\n background-color: #f5f5f5;\\n border: 1px solid #e3e3e3;\\n border-radius: 4px;\\n -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n overflow-x: hidden;\\n overflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n appearance: none;\\n -moz-appearance: none;\\n -webkit-appearance: none;\\n border: none;\\n height: 20px;\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n color: royalblue;\\n position: relative;\\n margin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n position: relative;\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n border-radius:3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n content:\\\" \\\";\\n position:absolute;\\n height: 20px;\\n top:0;\\n left:0;\\n right:0;\\n bottom:0;\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk-root .bk.loader {\\n overflow: hidden;\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled.primary div {\\n background-color: #007bff;\\n}\\n\\n.dot-filled.secondary div {\\n background-color: #6c757d;\\n}\\n\\n.dot-filled.success div {\\n background-color: #28a745;\\n}\\n\\n.dot-filled.danger div {\\n background-color: #dc3545;\\n}\\n\\n.dot-filled.warning div {\\n background-color: #ffc107;\\n}\\n\\n.dot-filled.info div {\\n background-color: #17a2b8;\\n}\\n\\n.dot-filled.dark div {\\n background-color: #343a40;\\n}\\n\\n.dot-filled.light div {\\n background-color: #f8f9fa;\\n}\\n\\n/* Slider editor */\\n.slider-edit .bk-input-group .bk-input {\\n border: 0;\\n border-radius: 0;\\n min-height: 0;\\n padding-left: 0;\\n padding-right: 0;\\n font-weight: bold;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper {\\n display: contents;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-up {\\n top: -6px;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-down {\\n bottom: 3px;\\n}\\n\\n/* JSON Pane */\\n.bk-root .json-formatter-row .json-formatter-string, .bk-root .json-formatter-row .json-formatter-stringifiable {\\n white-space: pre-wrap;\\n}\\n\\n.ql-bubble .ql-editor {\\n border: 1px solid #ccc;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\\n.markdown .codehilite {\\n padding: 1rem 1.25rem;\\n margin-top: 1rem;\\n margin-bottom: 1rem;\\n border-radius: 0.25rem;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link 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Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " const bokeh = factory();\n", - " bokeh.__bokeh__ = true;\n", - " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", - " root.Bokeh = bokeh;\n", - " }\n", - " const Bokeh = root.Bokeh;\n", - " Bokeh[bokeh.version] = bokeh;\n", - " })(this, function() {\n", - " let define;\n", - " const parent_require = typeof require 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null==this._interactive_timestamp?-1:Date.now()-this._interactive_timestamp}destructively_move(e){if(e===this)throw new Error(\"Attempted to overwrite a document with itself\");e.clear();const t=(0,g.copy)(this._roots);this.clear();for(const e of t)if(null!=e.document)throw new Error(`Somehow we didn't detach ${e}`);if(0!=this._all_models.size)throw new Error(`this._all_models still had stuff in it: ${this._all_models}`);for(const s of t)e.add_root(s);e.set_title(this._title)}_push_all_models_freeze(){this._all_models_freeze_count+=1}_pop_all_models_freeze(){this._all_models_freeze_count-=1,0===this._all_models_freeze_count&&this._recompute_all_models()}_invalidate_all_models(){_.logger.debug(\"invalidating document models\"),0===this._all_models_freeze_count&&this._recompute_all_models()}_recompute_all_models(){let e=new Set;for(const t of this._roots)e=p.union(e,t.references());const t=new Set(this._all_models.values()),s=p.difference(t,e),o=p.difference(e,t),n=new Map;for(const t of e)n.set(t.id,t);for(const e of s)e.detach_document();for(const e of o)e.attach_document(this);this._all_models=n}roots(){return this._roots}add_root(e,t){if(_.logger.debug(`Adding root: ${e}`),!(0,g.includes)(this._roots,e)){this._push_all_models_freeze();try{this._roots.push(e)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new z.RootAddedEvent(this,e,t))}}remove_root(e,t){const s=this._roots.indexOf(e);if(!(s<0)){this._push_all_models_freeze();try{this._roots.splice(s,1)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new z.RootRemovedEvent(this,e,t))}}title(){return this._title}set_title(e,t){e!==this._title&&(this._title=e,this._trigger_on_change(new z.TitleChangedEvent(this,e,t)))}get_model_by_id(e){var t;return null!==(t=this._all_models.get(e))&&void 0!==t?t:null}get_model_by_name(e){const t=[];for(const s of this._all_models.values())s instanceof M.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof z.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new z.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _instantiate_object(e,t,s,o){const n=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(o.get(t))(n)}static _instantiate_references_json(e,t,s){var o;const n=new Map;for(const i of e){const e=i.id,r=i.type,l=null!==(o=i.attributes)&&void 0!==o?o:{};let _=t.get(e);null==_&&(_=E._instantiate_object(e,r,l,s),null!=i.subtype&&_.set_subtype(i.subtype)),n.set(_.id,_)}return n}static _resolve_refs(e,t,s,o){function n(e){var i;if((0,f.is_ref)(e)){const o=null!==(i=t.get(e.id))&&void 0!==i?i:s.get(e.id);if(null!=o)return o;throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}if((0,u.is_NDArray_ref)(e)){const{buffer:t,dtype:s,shape:n}=(0,u.decode_NDArray)(e,o);return(0,m.ndarray)(t,{dtype:s,shape:n})}return(0,b.isArray)(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):(0,b.isPlainObject)(e)?function(e){const t={};for(const[s,o]of(0,v.entries)(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:i,attributes:r}of e){const e=!t.has(i),l=e?s.get(i):t.get(i),_=E._resolve_refs(r,t,s,o);l.setv(_,{silent:!0}),n.set(i,{instance:l,is_new:e})}const i=[],r=new Set;function l(e){if(e instanceof c.HasProps){if(n.has(e.id)&&!r.has(e.id)){r.add(e.id);const{instance:t,is_new:s}=n.get(e.id),{attributes:o}=t;for(const e of(0,v.values)(o))l(e);s&&(t.finalize(),i.push(t))}}else if((0,b.isArray)(e))for(const t of e)l(t);else if((0,b.isPlainObject)(e))for(const t of(0,v.values)(e))l(t)}for(const e of n.values())l(e.instance);for(const e of i)e.connect_signals()}static _event_for_attribute_change(e,t,s,o,n){if(o.get_model_by_id(e.id).property(t).syncable){const i={kind:\"ModelChanged\",model:{id:e.id},attr:t,new:s};return c.HasProps._json_record_references(o,s,n,{recursive:!0}),i}return null}static _events_to_sync_objects(e,t,s,o){const n=Object.keys(e.attributes),i=Object.keys(t.attributes),r=(0,g.difference)(n,i),l=(0,g.difference)(i,n),a=(0,g.intersection)(n,i),c=[];for(const e of r)_.logger.warn(`Server sent key ${e} but we don't seem to have it in our JSON`);for(const n of l){const i=t.attributes[n];c.push(E._event_for_attribute_change(e,n,i,s,o))}for(const n of a){const i=e.attributes[n],r=t.attributes[n];null==i&&null==r||(null==i||null==r?c.push(E._event_for_attribute_change(e,n,r,s,o)):\"data\"==n||(0,w.is_equal)(i,r)||c.push(E._event_for_attribute_change(e,n,r,s,o)))}return c.filter((e=>null!=e))}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),i=new Map,r=[];for(const t of e.roots.root_ids)i.set(t,n.get(t)),r.push(t);const l=o(s),_=new Map,a=[];for(const e of s.roots.root_ids)_.set(e,l.get(e)),a.push(e);if(r.sort(),a.sort(),(0,g.difference)(r,a).length>0||(0,g.difference)(a,r).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=E._events_to_sync_objects(n.get(e),l.get(e),t,c);h=h.concat(s)}const f=new d.Serializer({include_defaults:!1});return f.to_serializable([...c]),{references:[...f.definitions],events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=new d.Serializer({include_defaults:e}),s=t.to_serializable(this._roots);return{version:l.version,title:this._title,roots:{root_ids:s.map((e=>e.id)),references:[...t.definitions]}}}static from_json_string(e){const t=JSON.parse(e);return E.from_json(t)}static from_json(e){_.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${l.version}) / Python (${t})`;s||l.version.replace(/-(dev|rc)\\./,\"$1\")==t?_.logger.debug(o):(_.logger.warn(\"JS/Python version mismatch\"),_.logger.warn(o));const n=new r.ModelResolver;null!=e.defs&&(0,j.resolve_defs)(e.defs,n);const i=e.roots,a=i.root_ids,c=i.references,d=E._instantiate_references_json(c,new Map,n);E._initialize_references_json(c,new Map,d,new Map);const h=new E({resolver:n});h._push_all_models_freeze();for(const e of a){const t=d.get(e);null!=t&&h.add_root(t)}return h._pop_all_models_freeze(),h.set_title(e.title),h}replace_with_json(e){E.from_json(e).destructively_move(this)}create_json_patch_string(e){return JSON.stringify(this.create_json_patch(e))}create_json_patch(e){for(const t of e)if(t.document!=this)throw new Error(\"Cannot create a patch using events from a different document\");const t=new d.Serializer,s=t.to_serializable(e);for(const e of this._all_models.values())t.remove_def(e);return{events:s,references:[...t.definitions]}}apply_json_patch(e,t=new Map,s){const o=e.references,n=e.events,i=E._instantiate_references_json(o,this._all_models,this._resolver);t instanceof Map||(t=new Map(t));for(const e of n)switch(e.kind){case\"RootAdded\":case\"RootRemoved\":case\"ModelChanged\":{const t=e.model.id,s=this._all_models.get(t);if(null!=s)i.set(t,s);else if(!i.has(t))throw _.logger.warn(`Got an event for unknown model ${e.model}\"`),new Error(\"event model wasn't known\");break}}const r=new Map(this._all_models),l=new Map;for(const[e,t]of i)r.has(e)||l.set(e,t);E._initialize_references_json(o,r,l,t);for(const e of n)switch(e.kind){case\"MessageSent\":{const{msg_type:s,msg_data:o}=e;let n;if(void 0===o){if(1!=t.size)throw new Error(\"expected exactly one buffer\");{const[[,e]]=t;n=e}}else n=E._resolve_refs(o,r,l,t);this._trigger_on_message(s,n);break}case\"ModelChanged\":{const o=e.model.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot apply patch to ${o} which is not in the document`);const i=e.attr,_=E._resolve_refs(e.new,r,l,t);n.setv({[i]:_},{setter_id:s});break}case\"ColumnDataChanged\":{const o=e.column_source.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot stream to ${o} which is not in the document`);const i=E._resolve_refs(e.new,new Map,new Map,t);if(null!=e.cols)for(const e in n.data)e in i||(i[e]=n.data[e]);n.setv({data:i},{setter_id:s,check_eq:!1});break}case\"ColumnsStreamed\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot stream to ${t} which is not in the document`);if(!(o instanceof k.ColumnDataSource))throw new Error(\"Cannot stream to non-ColumnDataSource\");const n=e.data,i=e.rollover;o.stream(n,i,s);break}case\"ColumnsPatched\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot patch ${t} which is not in the document`);if(!(o instanceof k.ColumnDataSource))throw new Error(\"Cannot patch non-ColumnDataSource\");const n=e.patches;o.patch(n,s);break}case\"RootAdded\":{const t=e.model.id,o=i.get(t);this.add_root(o,s);break}case\"RootRemoved\":{const t=e.model.id,o=i.get(t);this.remove_root(o,s);break}case\"TitleChanged\":this.set_title(e.title,s);break;default:throw new Error(`Unknown patch event ${JSON.stringify(e)}`)}}}s.Document=E,E.__name__=\"Document\"},\n", - " function _(e,o,s,r,t){r();const l=e(1),i=e(8),d=e(13),n=e(14);s.overrides={};const a=new Map;s.Models=e=>{const 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extends((0,c.Signalable)()){constructor(e={}){var t,s;super(),this._subtype=void 0,this.document=null,this.destroyed=new c.Signal0(this,\"destroyed\"),this.change=new c.Signal0(this,\"change\"),this.transformchange=new c.Signal0(this,\"transformchange\"),this.exprchange=new c.Signal0(this,\"exprchange\"),this.properties={},this._watchers=new WeakMap,this._pending=!1,this._changing=!1;const n=e instanceof Map?e.get.bind(e):t=>e[t];this.id=null!==(t=n(\"id\"))&&void 0!==t?t:(0,u.uniqueId)();for(const[e,{type:t,default_value:s,options:r}]of(0,l.entries)(this._props)){let i;t instanceof _.PropertyAlias?Object.defineProperty(this.properties,e,{get:()=>this.properties[t.attr],configurable:!1,enumerable:!1}):(i=t instanceof h.Kind?new _.PrimitiveProperty(this,e,t,s,n(e),r):new t(this,e,h.Any,s,n(e),r),this.properties[e]=i)}null!==(s=n(\"__deferred__\"))&&void 0!==s&&s||(this.finalize(),this.connect_signals())}get is_syncable(){return!0}set type(e){console.warn(\"prototype.type = 'ModelName' 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r=Object.assign({},this.prototype._props);r[t]=Object.assign(Object.assign({},n),{default_value:e}),this.prototype._props=r}}toString(){return`${this.type}(${this.id})`}property(e){const t=this.properties[e];if(null!=t)return t;throw new Error(`unknown property ${this.type}.${e}`)}get attributes(){const e={};for(const t of this)e[t.attr]=t.get_value();return e}[m.clone](e){const t=new Map;for(const s of this)s.dirty&&t.set(s.attr,e.clone(s.get_value()));return new this.constructor(t)}[y.equals](e,t){for(const s of this){const n=e.property(s.attr);if(!t.eq(s.get_value(),n.get_value()))return!1}return!0}[v.pretty](e){const t=e.token,s=[];for(const n of this)if(n.dirty){const r=n.get_value();s.push(`${n.attr}${t(\":\")} ${e.to_string(r)}`)}return`${this.constructor.__qualified__}${t(\"(\")}${t(\"{\")}${s.join(`${t(\",\")} `)}${t(\"}\")}${t(\")\")}`}[d.serialize](e){const t=this.ref();e.add_ref(this,t);const s=this.struct();for(const t of 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n)e.change.emit();if(!r){if(!t.no_change)for(;this._pending;)this._pending=!1,this.change.emit();this._pending=!1,this._changing=!1}}setv(e,t={}){const s=(0,l.entries)(e);if(0==s.length)return;if(!0===t.silent){this._watchers=new WeakMap;for(const[e,t]of s)this.properties[e].set_value(t);return}const n=new Map,r=new Map;for(const[e,t]of s){const s=this.properties[e];n.set(s,t),r.set(s,s.get_value())}this._setv(n,t);const{document:i}=this;if(null!=i){const e=[];for(const[t,s]of r)e.push([t,s,t.get_value()]);for(const[,t,s]of e)if(this._needs_invalidate(t,s)){i._invalidate_all_models();break}this._push_changes(e,t)}}getv(e){return this.property(e).get_value()}ref(){return{id:this.id}}struct(){const e={type:this.type,id:this.id,attributes:{}};return null!=this._subtype&&(e.subtype=this._subtype),e}set_subtype(e){this._subtype=e}*[Symbol.iterator](){yield*(0,l.values)(this.properties)}*syncable_properties(){for(const e of this)e.syncable&&(yield e)}serializable_attributes(){const e={};for(const t of this.syncable_properties())e[t.attr]=t.get_value();return e}static _json_record_references(e,t,s,n){const{recursive:r}=n;if((0,a.is_ref)(t)){const n=e.get_model_by_id(t.id);null==n||s.has(n)||w._value_record_references(n,s,{recursive:r})}else if((0,f.isArray)(t))for(const n of t)w._json_record_references(e,n,s,{recursive:r});else if((0,f.isPlainObject)(t))for(const n of(0,l.values)(t))w._json_record_references(e,n,s,{recursive:r})}static _value_record_references(e,t,s){const{recursive:n}=s;if(e instanceof w){if(!t.has(e)&&(t.add(e),n))for(const s of e.syncable_properties()){const e=s.get_value();w._value_record_references(e,t,{recursive:n})}}else if((0,f.isArray)(e))for(const s of e)w._value_record_references(s,t,{recursive:n});else if((0,f.isPlainObject)(e))for(const s of(0,l.values)(e))w._value_record_references(s,t,{recursive:n})}references(){const e=new Set;return w._value_record_references(this,e,{recursive:!0}),e}_doc_attached(){}_doc_detached(){}attach_document(e){if(null!=this.document&&this.document!=e)throw new Error(\"models must be owned by only a single document\");this.document=e,this._doc_attached()}detach_document(){this._doc_detached(),this.document=null}_needs_invalidate(e,t){const s=new Set;w._value_record_references(t,s,{recursive:!1});const n=new Set;w._value_record_references(e,n,{recursive:!1});for(const e of s)if(!n.has(e))return!0;for(const e of n)if(!s.has(e))return!0;return!1}_push_changes(e,t={}){if(!this.is_syncable)return;const{document:s}=this;if(null==s)return;const{setter_id:n}=t,r=[];for(const[t,i,o]of e)t.syncable&&r.push(new g.ModelChangedEvent(s,this,t.attr,i,o,n));if(0!=r.length){let e;1==r.length?[e]=r:e=new g.DocumentEventBatch(s,r,n),s._trigger_on_change(e)}}on_change(e,t){for(const s of(0,f.isArray)(e)?e:[e])this.connect(s.change,t)}}s.HasProps=w,(o=w).prototype._props={},o.prototype._mixins=[]},\n", - " 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s.eq(this.shape,e.shape)&&s.arrays(this,e)}[q.serialize](e){return(0,d.encode_NDArray)(this)}}t.Int32NDArray=I,I.__name__=\"Int32NDArray\";class U extends Float32Array{constructor(e,s){super(e),this[p]=!0,this.dtype=\"float32\",this.shape=null!=s?s:x(e)?e.shape:[this.length],this.dimension=this.shape.length,null==this[A.equals]&&(this[A.equals]=(e,s)=>U.prototype[A.equals].call(this,e,s)),null==this[q.serialize]&&(this[q.serialize]=e=>U.prototype[q.serialize].call(this,e))}[(p=z,A.equals)](e,s){return s.eq(this.shape,e.shape)&&s.arrays(this,e)}[q.serialize](e){return(0,d.encode_NDArray)(this)}}t.Float32NDArray=U,U.__name__=\"Float32NDArray\";class w extends Float64Array{constructor(e,s){super(e),this[c]=!0,this.dtype=\"float64\",this.shape=null!=s?s:x(e)?e.shape:[this.length],this.dimension=this.shape.length,null==this[A.equals]&&(this[A.equals]=(e,s)=>w.prototype[A.equals].call(this,e,s)),null==this[q.serialize]&&(this[q.serialize]=e=>w.prototype[q.serialize].call(this,e))}[(c=z,A.equals)](e,s){return s.eq(this.shape,e.shape)&&s.arrays(this,e)}[q.serialize](e){return(0,d.encode_NDArray)(this)}}function x(e){return(0,y.isObject)(e)&&void 0!==e[z]}t.Float64NDArray=w,w.__name__=\"Float64NDArray\",t.is_NDArray=x,t.ndarray=function(e,s={}){let{dtype:t}=s;null==t&&(t=e instanceof ArrayBuffer||(0,y.isArray)(e)?\"float64\":(()=>{switch(!0){case e instanceof Uint8Array:return\"uint8\";case e instanceof Int8Array:return\"int8\";case e instanceof Uint16Array:return\"uint16\";case e instanceof Int16Array:return\"int16\";case e instanceof Uint32Array:return\"uint32\";case e instanceof Int32Array:return\"int32\";case e instanceof Float32Array:return\"float32\";case e instanceof Float64Array:return\"float64\";default:(0,_.unreachable)()}})());const{shape:i}=s;switch(t){case\"uint8\":return new D(e,i);case\"int8\":return new N(e,i);case\"uint16\":return new f(e,i);case\"int16\":return new m(e,i);case\"uint32\":return new g(e,i);case\"int32\":return new I(e,i);case\"float32\":return new U(e,i);case\"float64\":return new w(e,i)}}},\n", - " function _(e,r,t,i,s){i();const n=e(11),a=e(13),l=e(8);t.serialize=Symbol(\"serialize\");class o extends Error{}t.SerializationError=o,o.__name__=\"SerializationError\";class f{constructor(e){var r;this._references=new Map,this._definitions=new Map,this._refmap=new Map,this.include_defaults=null===(r=null==e?void 0:e.include_defaults)||void 0===r||r}get_ref(e){return this._references.get(e)}add_ref(e,r){(0,n.assert)(!this._references.has(e)),this._references.set(e,r)}add_def(e,r){const t=this.get_ref(e);(0,n.assert)(null!=t),this._definitions.set(e,r),this._refmap.set(t,r)}get 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d{constructor(e,t,s){super(e),this.msg_type=t,this.msg_data=s}[i.serialize](e){const t=this.msg_data,s=e.to_serializable(t);return{kind:\"MessageSent\",msg_type:this.msg_type,msg_data:s}}}s.MessageSentEvent=l,l.__name__=\"MessageSentEvent\";class _ extends d{constructor(e,t,s,n,o,i,r){super(e),this.model=t,this.attr=s,this.old=n,this.new_=o,this.setter_id=i,this.hint=r}[i.serialize](e){if(null!=this.hint)return e.to_serializable(this.hint);const t=this.new_,s=e.to_serializable(t);return this.model!=t&&e.remove_def(this.model),{kind:\"ModelChanged\",model:this.model.ref(),attr:this.attr,new:s}}}s.ModelChangedEvent=_,_.__name__=\"ModelChangedEvent\";class c extends d{constructor(e,t,s){super(e),this.column_source=t,this.patches=s}[i.serialize](e){return{kind:\"ColumnsPatched\",column_source:this.column_source,patches:this.patches}}}s.ColumnsPatchedEvent=c,c.__name__=\"ColumnsPatchedEvent\";class h extends d{constructor(e,t,s,n){super(e),this.column_source=t,this.data=s,this.rollover=n}[i.serialize](e){return{kind:\"ColumnsStreamed\",column_source:this.column_source,data:this.data,rollover:this.rollover}}}s.ColumnsStreamedEvent=h,h.__name__=\"ColumnsStreamedEvent\";class m extends d{constructor(e,t,s){super(e),this.title=t,this.setter_id=s}[i.serialize](e){return{kind:\"TitleChanged\",title:this.title}}}s.TitleChangedEvent=m,m.__name__=\"TitleChangedEvent\";class u extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}[i.serialize](e){return{kind:\"RootAdded\",model:e.to_serializable(this.model)}}}s.RootAddedEvent=u,u.__name__=\"RootAddedEvent\";class v extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}[i.serialize](e){return{kind:\"RootRemoved\",model:this.model.ref()}}}s.RootRemovedEvent=v,v.__name__=\"RootRemovedEvent\"},\n", - " function _(t,i,r,n,s){n();const e=t(8),o=t(13);r.pretty=Symbol(\"pretty\");class c{constructor(t){this.visited=new 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t.disconnect(e,this)}initialize(){this._has_finished=!1,this.is_root&&(this._stylesheet=r.stylesheet);for(const t of this.styles())this.stylesheet.append(t)}async lazy_initialize(){}remove(){this.disconnect_signals(),this.removed.emit()}toString(){return`${this.model.type}View(${this.model.id})`}serializable_state(){return{type:this.model.type}}get is_root(){return null==this.parent}has_finished(){return this._has_finished}get is_idle(){return this.has_finished()}connect_signals(){}disconnect_signals(){h.Signal.disconnect_receiver(this)}on_change(t,e){for(const s of(0,l.isArray)(t)?t:[t])this.connect(s.change,e)}cursor(t,e){return null}get stylesheet(){return this.is_root?this._stylesheet:this.root.stylesheet}styles(){return[_.default]}notify_finished(){this.is_root?!this._idle_notified&&this.has_finished()&&null!=this.model.document&&(this._idle_notified=!0,this.model.document.notify_idle(this.model)):this.root.notify_finished()}}s.View=d,d.__name__=\"View\"},\n", - " function 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null},n.extents=f,n.size=u,n.scroll_size=function(t){return{width:Math.ceil(t.scrollWidth),height:Math.ceil(t.scrollHeight)}},n.outer_size=function(t){const{margin:{left:e,right:n,top:i,bottom:o}}=f(t),{width:s,height:l}=u(t);return{width:Math.ceil(s+e+n),height:Math.ceil(l+i+o)}},n.content_size=function(t){const{left:e,top:n}=t.getBoundingClientRect(),{padding:i}=f(t);let o=0,s=0;for(const l of t.children){const t=l.getBoundingClientRect();o=Math.max(o,Math.ceil(t.left-e-i.left+t.width)),s=Math.max(s,Math.ceil(t.top-n-i.top+t.height))}return{width:o,height:s}},n.position=function(t,e,n){const{style:i}=t;if(i.left=`${e.x}px`,i.top=`${e.y}px`,i.width=`${e.width}px`,i.height=`${e.height}px`,null==n)i.margin=\"\";else{const{top:t,right:e,bottom:o,left:s}=n;i.margin=`${t}px ${e}px ${o}px ${s}px`}},n.children=function(t){return Array.from(t.children)};class p{constructor(t){this.el=t,this.classList=t.classList}get values(){const t=[];for(let e=0;e{document.addEventListener(\"DOMContentLoaded\",(()=>t()),{once:!0})}))}},\n", - " function _(o,i,t,e,r){e(),t.root=\"bk-root\",t.default=\".bk-root{position:relative;width:auto;height:auto;box-sizing:border-box;font-family:Helvetica, Arial, sans-serif;font-size:13px;}.bk-root .bk,.bk-root .bk:before,.bk-root .bk:after{box-sizing:inherit;margin:0;border:0;padding:0;background-image:none;font-family:inherit;font-size:100%;line-height:1.42857143;}.bk-root pre.bk{font-family:Courier, monospace;}\"},\n", - " function _(e,t,r,a,c){a();const n=e(1),l=e(46);c(\"Line\",l.Line),c(\"LineScalar\",l.LineScalar),c(\"LineVector\",l.LineVector);const i=e(49);c(\"Fill\",i.Fill),c(\"FillScalar\",i.FillScalar),c(\"FillVector\",i.FillVector);const s=e(50);c(\"Text\",s.Text),c(\"TextScalar\",s.TextScalar),c(\"TextVector\",s.TextVector);const o=e(51);c(\"Hatch\",o.Hatch),c(\"HatchScalar\",o.HatchScalar),c(\"HatchVector\",o.HatchVector);const u=(0,n.__importStar)(e(48)),V=e(47);c(\"VisualProperties\",V.VisualProperties),c(\"VisualUniforms\",V.VisualUniforms);class h{constructor(e){this._visuals=[];for(const[t,r]of e.model._mixins){const a=(()=>{switch(r){case u.Line:return new l.Line(e,t);case u.LineScalar:return new l.LineScalar(e,t);case u.LineVector:return new l.LineVector(e,t);case u.Fill:return new i.Fill(e,t);case u.FillScalar:return new i.FillScalar(e,t);case u.FillVector:return new i.FillVector(e,t);case u.Text:return new s.Text(e,t);case u.TextScalar:return new s.TextScalar(e,t);case u.TextVector:return new s.TextVector(e,t);case u.Hatch:return new o.Hatch(e,t);case u.HatchScalar:return new o.HatchScalar(e,t);case u.HatchVector:return new o.HatchVector(e,t);default:throw new Error(\"unknown visual\")}})();a instanceof V.VisualProperties&&a.update(),this._visuals.push(a),Object.defineProperty(this,t+a.type,{get:()=>a,configurable:!1,enumerable:!0})}}*[Symbol.iterator](){yield*this._visuals}}r.Visuals=h,h.__name__=\"Visuals\"},\n", - " function _(e,t,i,l,s){l();const a=e(1),n=e(47),h=(0,a.__importStar)(e(48)),o=e(22),_=e(8);function r(e){if((0,_.isArray)(e))return e;switch(e){case\"solid\":return[];case\"dashed\":return[6];case\"dotted\":return[2,4];case\"dotdash\":return[2,4,6,4];case\"dashdot\":return[6,4,2,4];default:return e.split(\" \").map(Number).filter(_.isInteger)}}i.resolve_line_dash=r;class u extends n.VisualProperties{get doit(){const e=this.line_color.get_value(),t=this.line_alpha.get_value(),i=this.line_width.get_value();return!(null==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.get_value(),alpha:this.line_alpha.get_value(),width:this.line_width.get_value(),join:this.line_join.get_value(),cap:this.line_cap.get_value(),dash:this.line_dash.get_value(),offset:this.line_dash_offset.get_value()}}set_value(e){const t=this.line_color.get_value(),i=this.line_alpha.get_value();e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.get_value(),e.lineJoin=this.line_join.get_value(),e.lineCap=this.line_cap.get_value(),e.lineDash=r(this.line_dash.get_value()),e.lineDashOffset=this.line_dash_offset.get_value()}}i.Line=u,u.__name__=\"Line\";class c extends n.VisualUniforms{get doit(){const e=this.line_color.value,t=this.line_alpha.value,i=this.line_width.value;return!(0==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.value,alpha:this.line_alpha.value,width:this.line_width.value,join:this.line_join.value,cap:this.line_cap.value,dash:this.line_dash.value,offset:this.line_dash_offset.value}}set_value(e){const t=this.line_color.value,i=this.line_alpha.value;e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.value,e.lineJoin=this.line_join.value,e.lineCap=this.line_cap.value,e.lineDash=r(this.line_dash.value),e.lineDashOffset=this.line_dash_offset.value}}i.LineScalar=c,c.__name__=\"LineScalar\";class d extends n.VisualUniforms{get doit(){const{line_color:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{line_alpha:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{line_width:i}=this;return!i.is_Scalar()||0!=i.value}apply(e,t){const{doit:i}=this;return i&&(this.set_vectorize(e,t),e.stroke()),i}values(e){return{color:this.line_color.get(e),alpha:this.line_alpha.get(e),width:this.line_width.get(e),join:this.line_join.get(e),cap:this.line_cap.get(e),dash:this.line_dash.get(e),offset:this.line_dash_offset.get(e)}}set_vectorize(e,t){const i=this.line_color.get(t),l=this.line_alpha.get(t),s=this.line_width.get(t),a=this.line_join.get(t),n=this.line_cap.get(t),h=this.line_dash.get(t),_=this.line_dash_offset.get(t);e.strokeStyle=(0,o.color2css)(i,l),e.lineWidth=s,e.lineJoin=a,e.lineCap=n,e.lineDash=r(h),e.lineDashOffset=_}}i.LineVector=d,d.__name__=\"LineVector\",u.prototype.type=\"line\",u.prototype.attrs=Object.keys(h.Line),c.prototype.type=\"line\",c.prototype.attrs=Object.keys(h.LineScalar),d.prototype.type=\"line\",d.prototype.attrs=Object.keys(h.LineVector)},\n", - " function _(t,s,o,i,r){i();class e{constructor(t,s=\"\"){this.obj=t,this.prefix=s;const o=this;this._props=[];for(const i of this.attrs){const r=t.model.properties[s+i];r.change.connect((()=>this.update())),o[i]=r,this._props.push(r)}}*[Symbol.iterator](){yield*this._props}update(){}}o.VisualProperties=e,e.__name__=\"VisualProperties\";class p{constructor(t,s=\"\"){this.obj=t,this.prefix=s;for(const o of this.attrs)Object.defineProperty(this,o,{get:()=>t[s+o]})}*[Symbol.iterator](){for(const t of this.attrs)yield this.obj.model.properties[this.prefix+t]}update(){}}o.VisualUniforms=p,p.__name__=\"VisualUniforms\"},\n", - " function _(e,l,t,a,c){a();const r=e(1),o=(0,r.__importStar)(e(18)),n=e(20),i=(0,r.__importStar)(e(21)),_=e(13);t.Line={line_color:[i.Nullable(i.Color),\"black\"],line_alpha:[i.Alpha,1],line_width:[i.Number,1],line_join:[n.LineJoin,\"bevel\"],line_cap:[n.LineCap,\"butt\"],line_dash:[i.Or(n.LineDash,i.Array(i.Number)),[]],line_dash_offset:[i.Number,0]},t.Fill={fill_color:[i.Nullable(i.Color),\"gray\"],fill_alpha:[i.Alpha,1]},t.Hatch={hatch_color:[i.Nullable(i.Color),\"black\"],hatch_alpha:[i.Alpha,1],hatch_scale:[i.Number,12],hatch_pattern:[i.Nullable(i.Or(n.HatchPatternType,i.String)),null],hatch_weight:[i.Number,1],hatch_extra:[i.Dict(i.AnyRef()),{}]},t.Text={text_color:[i.Nullable(i.Color),\"#444444\"],text_alpha:[i.Alpha,1],text_font:[o.Font,\"helvetica\"],text_font_size:[i.FontSize,\"16px\"],text_font_style:[n.FontStyle,\"normal\"],text_align:[n.TextAlign,\"left\"],text_baseline:[n.TextBaseline,\"bottom\"],text_line_height:[i.Number,1.2]},t.LineScalar={line_color:[o.ColorScalar,\"black\"],line_alpha:[o.NumberScalar,1],line_width:[o.NumberScalar,1],line_join:[o.LineJoinScalar,\"bevel\"],line_cap:[o.LineCapScalar,\"butt\"],line_dash:[o.LineDashScalar,[]],line_dash_offset:[o.NumberScalar,0]},t.FillScalar={fill_color:[o.ColorScalar,\"gray\"],fill_alpha:[o.NumberScalar,1]},t.HatchScalar={hatch_color:[o.ColorScalar,\"black\"],hatch_alpha:[o.NumberScalar,1],hatch_scale:[o.NumberScalar,12],hatch_pattern:[o.NullStringScalar,null],hatch_weight:[o.NumberScalar,1],hatch_extra:[o.AnyScalar,{}]},t.TextScalar={text_color:[o.ColorScalar,\"#444444\"],text_alpha:[o.NumberScalar,1],text_font:[o.FontScalar,\"helvetica\"],text_font_size:[o.FontSizeScalar,\"16px\"],text_font_style:[o.FontStyleScalar,\"normal\"],text_align:[o.TextAlignScalar,\"left\"],text_baseline:[o.TextBaselineScalar,\"bottom\"],text_line_height:[o.NumberScalar,1.2]},t.LineVector={line_color:[o.ColorSpec,\"black\"],line_alpha:[o.NumberSpec,1],line_width:[o.NumberSpec,1],line_join:[o.LineJoinSpec,\"bevel\"],line_cap:[o.LineCapSpec,\"butt\"],line_dash:[o.LineDashSpec,[]],line_dash_offset:[o.NumberSpec,0]},t.FillVector={fill_color:[o.ColorSpec,\"gray\"],fill_alpha:[o.NumberSpec,1]},t.HatchVector={hatch_color:[o.ColorSpec,\"black\"],hatch_alpha:[o.NumberSpec,1],hatch_scale:[o.NumberSpec,12],hatch_pattern:[o.NullStringSpec,null],hatch_weight:[o.NumberSpec,1],hatch_extra:[o.AnyScalar,{}]},t.TextVector={text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_font:[o.FontSpec,\"helvetica\"],text_font_size:[o.FontSizeSpec,\"16px\"],text_font_style:[o.FontStyleSpec,\"normal\"],text_align:[o.TextAlignSpec,\"left\"],text_baseline:[o.TextBaselineSpec,\"bottom\"],text_line_height:[o.NumberSpec,1.2]},t.attrs_of=function(e,l,t,a=!1){const c={};for(const r of(0,_.keys)(t)){const t=`${l}${r}`,o=e[t];c[a?t:r]=o}return c}},\n", - " function _(l,t,e,i,s){i();const a=l(1),o=l(47),r=(0,a.__importStar)(l(48)),_=l(22);class c extends o.VisualProperties{get doit(){const l=this.fill_color.get_value(),t=this.fill_alpha.get_value();return!(null==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.get_value(),alpha:this.fill_alpha.get_value()}}set_value(l){const t=this.fill_color.get_value(),e=this.fill_alpha.get_value();l.fillStyle=(0,_.color2css)(t,e)}}e.Fill=c,c.__name__=\"Fill\";class h extends o.VisualUniforms{get doit(){const l=this.fill_color.value,t=this.fill_alpha.value;return!(0==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.value,alpha:this.fill_alpha.value}}set_value(l){const t=this.fill_color.value,e=this.fill_alpha.value;l.fillStyle=(0,_.color2css)(t,e)}}e.FillScalar=h,h.__name__=\"FillScalar\";class u extends o.VisualUniforms{get doit(){const{fill_color:l}=this;if(l.is_Scalar()&&0==l.value)return!1;const{fill_alpha:t}=this;return!t.is_Scalar()||0!=t.value}apply(l,t,e){const{doit:i}=this;return i&&(this.set_vectorize(l,t),l.fill(e)),i}values(l){return{color:this.fill_color.get(l),alpha:this.fill_alpha.get(l)}}set_vectorize(l,t){const e=this.fill_color.get(t),i=this.fill_alpha.get(t);l.fillStyle=(0,_.color2css)(e,i)}}e.FillVector=u,u.__name__=\"FillVector\",c.prototype.type=\"fill\",c.prototype.attrs=Object.keys(r.Fill),h.prototype.type=\"fill\",h.prototype.attrs=Object.keys(r.FillScalar),u.prototype.type=\"fill\",u.prototype.attrs=Object.keys(r.FillVector)},\n", - " function _(t,e,l,s,_){s();const i=t(1),a=t(47),o=(0,i.__importStar)(t(48)),n=t(22);class h extends a.VisualProperties{get doit(){const t=this.text_color.get_value(),e=this.text_alpha.get_value();return!(null==t||0==e)}values(){return{color:this.text_color.get_value(),alpha:this.text_alpha.get_value(),font:this.text_font.get_value(),font_size:this.text_font_size.get_value(),font_style:this.text_font_style.get_value(),align:this.text_align.get_value(),baseline:this.text_baseline.get_value(),line_height:this.text_line_height.get_value()}}set_value(t){const e=this.text_color.get_value(),l=this.text_alpha.get_value();t.fillStyle=(0,n.color2css)(e,l),t.font=this.font_value(),t.textAlign=this.text_align.get_value(),t.textBaseline=this.text_baseline.get_value()}font_value(){return`${this.text_font_style.get_value()} ${this.text_font_size.get_value()} ${this.text_font.get_value()}`}}l.Text=h,h.__name__=\"Text\";class x extends a.VisualUniforms{get doit(){const t=this.text_color.value,e=this.text_alpha.value;return!(0==t||0==e)}values(){return{color:this.text_color.value,alpha:this.text_alpha.value,font:this.text_font.value,font_size:this.text_font_size.value,font_style:this.text_font_style.value,align:this.text_align.value,baseline:this.text_baseline.value,line_height:this.text_line_height.value}}set_value(t){const e=this.text_color.value,l=this.text_alpha.value,s=this.font_value(),_=this.text_align.value,i=this.text_baseline.value;t.fillStyle=(0,n.color2css)(e,l),t.font=s,t.textAlign=_,t.textBaseline=i}font_value(){return`${this.text_font_style.value} ${this.text_font_size.value} ${this.text_font.value}`}}l.TextScalar=x,x.__name__=\"TextScalar\";class u extends a.VisualUniforms{values(t){return{color:this.text_color.get(t),alpha:this.text_alpha.get(t),font:this.text_font.get(t),font_size:this.text_font_size.get(t),font_style:this.text_font_style.get(t),align:this.text_align.get(t),baseline:this.text_baseline.get(t),line_height:this.text_line_height.get(t)}}get doit(){const{text_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{text_alpha:e}=this;return!e.is_Scalar()||0!=e.value}set_vectorize(t,e){const l=this.text_color.get(e),s=this.text_alpha.get(e),_=this.font_value(e),i=this.text_align.get(e),a=this.text_baseline.get(e);t.fillStyle=(0,n.color2css)(l,s),t.font=_,t.textAlign=i,t.textBaseline=a}font_value(t){return`${this.text_font_style.get(t)} ${this.text_font_size.get(t)} ${this.text_font.get(t)}`}}l.TextVector=u,u.__name__=\"TextVector\",h.prototype.type=\"text\",h.prototype.attrs=Object.keys(o.Text),x.prototype.type=\"text\",x.prototype.attrs=Object.keys(o.TextScalar),u.prototype.type=\"text\",u.prototype.attrs=Object.keys(o.TextVector)},\n", - " function _(t,e,a,r,i){r();const h=t(1),s=t(47),n=t(52),c=(0,h.__importStar)(t(18)),_=(0,h.__importStar)(t(48));class l extends s.VisualProperties{constructor(){super(...arguments),this._update_iteration=0}update(){if(this._update_iteration++,this._hatch_image=null,!this.doit)return;const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_scale.get_value(),r=this.hatch_pattern.get_value(),i=this.hatch_weight.get_value(),h=t=>{this._hatch_image=t},s=this.hatch_extra.get_value()[r];if(null!=s){const r=s.get_pattern(t,e,a,i);if(r instanceof Promise){const{_update_iteration:t}=this;r.then((e=>{this._update_iteration==t&&(h(e),this.obj.request_render())}))}else h(r)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,r,t,e,a,i);h(c)}}get doit(){const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_pattern.get_value();return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){const e=this.pattern(t);t.fillStyle=null!=e?e:\"transparent\"}pattern(t){const e=this._hatch_image;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.get_value(),e=this.hatch_extra.get_value()[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.Hatch=l,l.__name__=\"Hatch\";class o extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const t=this.hatch_color.value,e=this.hatch_alpha.value,a=this.hatch_pattern.value;return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=this.hatch_color.value,a=this.hatch_alpha.value,r=this.hatch_scale.value,i=this.hatch_pattern.value,h=this.hatch_weight.value,s=e=>{this._hatch_image=new c.UniformScalar(e,t)},_=this.hatch_extra.value[i];if(null!=_){const t=_.get_pattern(e,a,r,h);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(s(t),this.obj.request_render())}))}else s(t)}else{const t=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(t,i,e,a,r,h);s(c)}}get doit(){return this._static_doit}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){var e;t.fillStyle=null!==(e=this.pattern(t))&&void 0!==e?e:\"transparent\"}pattern(t){const e=this._hatch_image.value;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.value,e=this.hatch_extra.value[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchScalar=o,o.__name__=\"HatchScalar\";class u extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const{hatch_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{hatch_alpha:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{hatch_pattern:a}=this;if(a.is_Scalar()){const t=a.value;if(\" \"==t||\"blank\"==t||null==t)return!1}return!0}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=(t,e,a,r,i,h)=>{const s=this.hatch_extra.value[t];if(null!=s){const t=s.get_pattern(e,a,r,i);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(h(t),this.obj.request_render())}))}else h(t)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,t,e,a,r,i);h(c)}};if(this.hatch_color.is_Scalar()&&this.hatch_alpha.is_Scalar()&&this.hatch_scale.is_Scalar()&&this.hatch_pattern.is_Scalar()&&this.hatch_weight.is_Scalar()){const a=this.hatch_color.value,r=this.hatch_alpha.value,i=this.hatch_scale.value;e(this.hatch_pattern.value,a,r,i,this.hatch_weight.value,(e=>{this._hatch_image=new c.UniformScalar(e,t)}))}else{const a=new Array(t);a.fill(null),this._hatch_image=new c.UniformVector(a);for(let r=0;r{a[r]=t}))}}}get doit(){return this._static_doit}apply(t,e,a){const{doit:r}=this;return r&&(this.set_vectorize(t,e),t.layer.undo_transform((()=>t.fill(a)))),r}set_vectorize(t,e){var a;t.fillStyle=null!==(a=this.pattern(t,e))&&void 0!==a?a:\"transparent\"}pattern(t,e){const a=this._hatch_image.get(e);return null==a?null:t.createPattern(a,this.repetition(e))}repetition(t){const e=this.hatch_pattern.get(t),a=this.hatch_extra.value[e];if(null==a)return\"repeat\";switch(a.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchVector=u,u.__name__=\"HatchVector\",l.prototype.type=\"hatch\",l.prototype.attrs=Object.keys(_.Hatch),o.prototype.type=\"hatch\",o.prototype.attrs=Object.keys(_.HatchScalar),u.prototype.type=\"hatch\",u.prototype.attrs=Object.keys(_.HatchVector)},\n", - " function _(e,o,a,s,r){s();const i=e(22);function l(e,o,a){e.moveTo(0,a+.5),e.lineTo(o,a+.5),e.stroke()}function n(e,o,a){e.moveTo(a+.5,0),e.lineTo(a+.5,o),e.stroke()}function t(e,o){e.moveTo(0,o),e.lineTo(o,0),e.stroke(),e.moveTo(0,0),e.lineTo(o,o),e.stroke()}a.hatch_aliases={\" \":\"blank\",\".\":\"dot\",o:\"ring\",\"-\":\"horizontal_line\",\"|\":\"vertical_line\",\"+\":\"cross\",'\"':\"horizontal_dash\",\":\":\"vertical_dash\",\"@\":\"spiral\",\"/\":\"right_diagonal_line\",\"\\\\\":\"left_diagonal_line\",x:\"diagonal_cross\",\",\":\"right_diagonal_dash\",\"`\":\"left_diagonal_dash\",v:\"horizontal_wave\",\">\":\"vertical_wave\",\"*\":\"criss_cross\"},a.get_pattern=function(e,o,s,r,c,k){return e.resize(c,c),e.prepare(),function(e,o,s,r,c,k){var _;const T=c,v=T/2,h=v/2,d=(0,i.color2css)(s,r);switch(e.strokeStyle=d,e.fillStyle=d,e.lineCap=\"square\",e.lineWidth=k,null!==(_=a.hatch_aliases[o])&&void 0!==_?_:o){case\"blank\":break;case\"dot\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.fill();break;case\"ring\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.stroke();break;case\"horizontal_line\":l(e,T,v);break;case\"vertical_line\":n(e,T,v);break;case\"cross\":l(e,T,v),n(e,T,v);break;case\"horizontal_dash\":l(e,v,v);break;case\"vertical_dash\":n(e,v,v);break;case\"spiral\":{const o=T/30;e.moveTo(v,v);for(let a=0;a<360;a++){const s=.1*a,r=v+o*s*Math.cos(s),i=v+o*s*Math.sin(s);e.lineTo(r,i)}e.stroke();break}case\"right_diagonal_line\":e.moveTo(.5-h,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(5*h+.5,0),e.stroke(),e.stroke();break;case\"left_diagonal_line\":e.moveTo(h+.5,T),e.lineTo(.5-h,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(5*h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.stroke();break;case\"diagonal_cross\":t(e,T);break;case\"right_diagonal_dash\":e.moveTo(h+.5,3*h+.5),e.lineTo(3*h+.5,h+.5),e.stroke();break;case\"left_diagonal_dash\":e.moveTo(h+.5,h+.5),e.lineTo(3*h+.5,3*h+.5),e.stroke();break;case\"horizontal_wave\":e.moveTo(0,h),e.lineTo(v,3*h),e.lineTo(T,h),e.stroke();break;case\"vertical_wave\":e.moveTo(h,0),e.lineTo(3*h,v),e.lineTo(h,T),e.stroke();break;case\"criss_cross\":t(e,T),l(e,T,v),n(e,T,v)}}(e.ctx,o,s,r,c,k),e.canvas}},\n", - " function _(e,t,s,n,c){var a;n();const i=e(14),r=e(8),l=e(13),o=e(26),_=e(19);class h extends i.HasProps{constructor(e){super(e)}get is_syncable(){return this.syncable}[o.equals](e,t){return t.eq(this.id,e.id)&&super[o.equals](e,t)}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,(()=>this._update_property_callbacks())),this.connect(this.properties.js_event_callbacks.change,(()=>this._update_event_callbacks())),this.connect(this.properties.subscribed_events.change,(()=>this._update_event_callbacks()))}_process_event(e){var t;for(const s of null!==(t=this.js_event_callbacks[e.event_name])&&void 0!==t?t:[])s.execute(e);null!=this.document&&this.subscribed_events.some((t=>t==e.event_name))&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):_.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of(0,l.entries)(this.js_property_callbacks)){const n=s.map((e=>()=>e.execute(this)));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){(0,l.isEmpty)(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if((0,r.isString)(e))return[...this.references()].filter((t=>t instanceof h&&t.name===e));if(e.prototype instanceof i.HasProps)return[...this.references()].filter((t=>t instanceof e));throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=h,a=h,h.__name__=\"Model\",a.define((({Any:e,Unknown:t,Boolean:s,String:n,Array:c,Dict:a,Nullable:i})=>({tags:[c(t),[]],name:[i(n),null],js_property_callbacks:[a(c(e)),{}],js_event_callbacks:[a(c(e)),{}],subscribed_events:[c(n),[]],syncable:[s,!0]})))},\n", - " function _(e,t,s,a,r){var c,n;a();const _=e(12),o=e(53),i=e(55),l=e(59),u=e(61),g=e(62),h=e(57),p=e(63),m=e(67);class x{constructor(e,t){this.x_scale=e,this.y_scale=t,this.x_source=this.x_scale.source_range,this.y_source=this.y_scale.source_range,this.ranges=[this.x_source,this.y_source],this.scales=[this.x_scale,this.y_scale]}map_to_screen(e,t){return[this.x_scale.v_compute(e),this.y_scale.v_compute(t)]}map_from_screen(e,t){return[this.x_scale.v_invert(e),this.y_scale.v_invert(t)]}}s.CoordinateTransform=x,x.__name__=\"CoordinateTransform\";class y extends o.Model{constructor(e){super(e)}get x_ranges(){return new Map([[\"default\",this.x_source]])}get y_ranges(){return new Map([[\"default\",this.y_source]])}_get_scale(e,t,s){if(e instanceof m.FactorRange!=t instanceof g.CategoricalScale)throw new Error(`Range ${e.type} is incompatible is Scale ${t.type}`);t instanceof u.LogScale&&e instanceof p.DataRange1d&&(e.scale_hint=\"log\");const a=t.clone();return a.setv({source_range:e,target_range:s}),a}get_transform(e){const{x_source:t,x_scale:s,x_target:a}=this,r=this._get_scale(t,s,a),{y_source:c,y_scale:n,y_target:_}=this,o=this._get_scale(c,n,_),i=new v({source_scale:r,source_range:r.source_range,target_scale:e.x_scale,target_range:e.x_target}),l=new v({source_scale:o,source_range:o.source_range,target_scale:e.y_scale,target_range:e.y_target});return new x(i,l)}}s.CoordinateMapping=y,c=y,y.__name__=\"CoordinateMapping\",c.define((({Ref:e})=>({x_source:[e(h.Range),()=>new p.DataRange1d],y_source:[e(h.Range),()=>new p.DataRange1d],x_scale:[e(i.Scale),()=>new l.LinearScale],y_scale:[e(i.Scale),()=>new l.LinearScale],x_target:[e(h.Range)],y_target:[e(h.Range)]})));class v extends i.Scale{constructor(e){super(e)}get s_compute(){const e=this.source_scale.s_compute,t=this.target_scale.s_compute;return s=>t(e(s))}get s_invert(){const e=this.source_scale.s_invert,t=this.target_scale.s_invert;return s=>e(t(s))}compute(e){return this.s_compute(e)}v_compute(e){const{s_compute:t}=this;return(0,_.map)(e,t)}invert(e){return this.s_invert(e)}v_invert(e){const{s_invert:t}=this;return(0,_.map)(e,t)}}s.CompositeScale=v,n=v,v.__name__=\"CompositeScale\",n.internal((({Ref:e})=>({source_scale:[e(i.Scale)],target_scale:[e(i.Scale)]})))},\n", - " function _(e,t,r,n,s){var _;n();const a=e(56),c=e(57),o=e(58),i=e(24);class u extends a.Transform{constructor(e){super(e)}compute(e){return this.s_compute(e)}v_compute(e){const t=new i.ScreenArray(e.length),{s_compute:r}=this;for(let n=0;n({source_range:[e(c.Range)],target_range:[e(o.Range1d)]})))},\n", - " function _(n,s,o,r,c){r();const e=n(53);class t extends e.Model{constructor(n){super(n)}}o.Transform=t,t.__name__=\"Transform\"},\n", - " function _(e,t,n,i,s){var r;i();const a=e(53);class l extends a.Model{constructor(e){super(e),this.have_updated_interactively=!1}get is_reversed(){return this.start>this.end}get is_valid(){return isFinite(this.min)&&isFinite(this.max)}get span(){return Math.abs(this.end-this.start)}}n.Range=l,r=l,l.__name__=\"Range\",r.define((({Number:e,Tuple:t,Or:n,Auto:i,Nullable:s})=>({bounds:[s(n(t(s(e),s(e)),i)),null],min_interval:[s(e),null],max_interval:[s(e),null]}))),r.internal((({Array:e,AnyRef:t})=>({plots:[e(t()),[]]})))},\n", - " function _(t,e,s,n,r){var a;n();const i=t(57);class _ extends i.Range{constructor(t){super(t)}_set_auto_bounds(){if(\"auto\"==this.bounds){const t=Math.min(this._reset_start,this._reset_end),e=Math.max(this._reset_start,this._reset_end);this.setv({bounds:[t,e]},{silent:!0})}}initialize(){super.initialize(),this._set_auto_bounds()}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}reset(){this._set_auto_bounds();const{_reset_start:t,_reset_end:e}=this;this.start!=t||this.end!=e?this.setv({start:t,end:e}):this.change.emit()}map(t){return new _({start:t(this.start),end:t(this.end)})}widen(t){let{start:e,end:s}=this;return this.is_reversed?(e+=t,s-=t):(e-=t,s+=t),new _({start:e,end:s})}}s.Range1d=_,a=_,_.__name__=\"Range1d\",a.define((({Number:t,Nullable:e})=>({start:[t,0],end:[t,1],reset_start:[e(t),null,{on_update(t,e){e._reset_start=null!=t?t:e.start}}],reset_end:[e(t),null,{on_update(t,e){e._reset_end=null!=t?t:e.end}}]})))},\n", - " function _(t,e,n,r,s){r();const a=t(60);class _ extends a.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e]=this._linear_compute_state();return n=>t*n+e}get s_invert(){const[t,e]=this._linear_compute_state();return n=>(n-e)/t}_linear_compute_state(){const t=this.source_range.start,e=this.source_range.end,n=this.target_range.start,r=(this.target_range.end-n)/(e-t);return[r,-r*t+n]}}n.LinearScale=_,_.__name__=\"LinearScale\"},\n", - " function _(n,c,o,s,e){s();const t=n(55);class u extends t.Scale{constructor(n){super(n)}}o.ContinuousScale=u,u.__name__=\"ContinuousScale\"},\n", - " function _(t,e,a,o,s){o();const r=t(60);class n extends r.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e,a,o]=this._compute_state();return s=>{if(0==a)return 0;{const r=(Math.log(s)-o)/a;return isFinite(r)?r*t+e:NaN}}}get s_invert(){const[t,e,a,o]=this._compute_state();return s=>{const r=(s-e)/t;return Math.exp(a*r+o)}}_get_safe_factor(t,e){let a=t<0?0:t,o=e<0?0:e;if(a==o)if(0==a)[a,o]=[1,10];else{const t=Math.log(a)/Math.log(10);a=10**Math.floor(t),o=Math.ceil(t)!=Math.floor(t)?10**Math.ceil(t):10**(Math.ceil(t)+1)}return[a,o]}_compute_state(){const t=this.source_range.start,e=this.source_range.end,a=this.target_range.start,o=this.target_range.end-a,[s,r]=this._get_safe_factor(t,e);let n,c;0==s?(n=Math.log(r),c=0):(n=Math.log(r)-Math.log(s),c=Math.log(s));return[o,a,n,c]}}a.LogScale=n,n.__name__=\"LogScale\"},\n", - " function _(t,e,c,a,s){a();const n=t(55),r=t(59),{_linear_compute_state:o}=r.LinearScale.prototype;class l extends n.Scale{constructor(t){super(t)}get s_compute(){const[t,e]=o.call(this),c=this.source_range;return a=>t*c.synthetic(a)+e}get s_invert(){const[t,e]=o.call(this);return c=>(c-e)/t}}c.CategoricalScale=l,l.__name__=\"CategoricalScale\"},\n", - " function _(t,i,n,e,a){e();const s=t(1);var l;const _=t(64),o=t(20),r=t(9),h=t(19),d=(0,s.__importStar)(t(65)),u=t(66);class g extends _.DataRange{constructor(t){super(t),this.have_updated_interactively=!1}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const{renderers:t,names:i}=this,n=(0,r.concat)(this.plots.map((t=>t.data_renderers)));return(0,u.compute_renderers)(0==t.length?\"auto\":t,n,i)}_compute_plot_bounds(t,i){let n=d.empty();for(const e of t){const t=i.get(e);null==t||!e.visible&&this.only_visible||(n=d.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=d.empty();let e=t.x1-t.x0;e<=0&&(e=1);let a=t.y1-t.y0;a<=0&&(a=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return el&&(\"start\"==this.follow?a=e+s*l:\"end\"==this.follow&&(e=a-s*l)),[e,a]}update(t,i,n,e){if(this.have_updated_interactively)return;const a=this.computed_renderers();let s=this._compute_plot_bounds(a,t);null!=e&&(s=this.adjust_bounds_for_aspect(s,e)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.entries(),i);let[o,r]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(r=this._initial_end):r=this._initial_end);let h=!1;\"auto\"==this.bounds&&(this.setv({bounds:[o,r]},{silent:!0}),h=!0);const[d,u]=[this.start,this.end];if(o!=d||r!=u){const t={};o!=d&&(t.start=o),r!=u&&(t.end=r),this.setv(t),h=!1}h&&this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=g,l=g,g.__name__=\"DataRange1d\",l.define((({Boolean:t,Number:i,Nullable:n})=>({start:[i],end:[i],range_padding:[i,.1],range_padding_units:[o.PaddingUnits,\"percent\"],flipped:[t,!1],follow:[n(o.StartEnd),null],follow_interval:[n(i),null],default_span:[i,2],only_visible:[t,!1]}))),l.internal((({Enum:t})=>({scale_hint:[t(\"log\",\"auto\"),\"auto\"]})))},\n", - " function _(e,n,a,r,s){var t;r();const c=e(57);class _ extends c.Range{constructor(e){super(e)}}a.DataRange=_,t=_,_.__name__=\"DataRange\",t.define((({String:e,Array:n,AnyRef:a})=>({names:[n(e),[]],renderers:[n(a()),[]]})))},\n", - " function _(t,i,e,h,r){h();const s=t(24),n=t(26),{min:x,max:y}=Math;e.empty=function(){return{x0:1/0,y0:1/0,x1:-1/0,y1:-1/0}},e.positive_x=function(){return{x0:Number.MIN_VALUE,y0:-1/0,x1:1/0,y1:1/0}},e.positive_y=function(){return{x0:-1/0,y0:Number.MIN_VALUE,x1:1/0,y1:1/0}},e.union=function(t,i){return{x0:x(t.x0,i.x0),x1:y(t.x1,i.x1),y0:x(t.y0,i.y0),y1:y(t.y1,i.y1)}};class o{constructor(t){if(null==t)this.x0=0,this.y0=0,this.x1=0,this.y1=0;else if(\"x0\"in t){const{x0:i,y0:e,x1:h,y1:r}=t;if(!(i<=h&&e<=r))throw new Error(`invalid bbox {x0: ${i}, y0: ${e}, x1: ${h}, y1: ${r}}`);this.x0=i,this.y0=e,this.x1=h,this.y1=r}else if(\"x\"in t){const{x:i,y:e,width:h,height:r}=t;if(!(h>=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}static from_rect({left:t,right:i,top:e,bottom:h}){return new o({x0:Math.min(t,i),y0:Math.min(e,h),x1:Math.max(t,i),y1:Math.max(e,h)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}[n.equals](t,i){return i.eq(this.x0,t.x0)&&i.eq(this.y0,t.y0)&&i.eq(this.x1,t.x1)&&i.eq(this.y1,t.y1)}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get size(){return{width:this.width,height:this.height}}get rect(){const{x0:t,y0:i,x1:e,y1:h}=this;return{p0:{x:t,y:i},p1:{x:e,y:i},p2:{x:e,y:h},p3:{x:t,y:h}}}get box(){const{x:t,y:i,width:e,height:h}=this;return{x:t,y:i,width:e,height:h}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}get area(){return this.width*this.height}relative(){const{width:t,height:i}=this;return new o({x:0,y:0,width:t,height:i})}translate(t,i){const{x:e,y:h,width:r,height:s}=this;return new o({x:t+e,y:i+h,width:r,height:s})}relativize(t,i){return[t-this.x,i-this.y]}contains(t,i){return this.x0<=t&&t<=this.x1&&this.y0<=i&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}grow_by(t){return new o({left:this.left-t,right:this.right+t,top:this.top-t,bottom:this.bottom+t})}shrink_by(t){return new o({left:this.left+t,right:this.right-t,top:this.top+t,bottom:this.bottom-t})}union(t){return new o({x0:x(this.x0,t.x0),y0:x(this.y0,t.y0),x1:y(this.x1,t.x1),y1:y(this.y1,t.y1)})}intersection(t){return this.intersects(t)?new o({x0:y(this.x0,t.x0),y0:y(this.y0,t.y0),x1:x(this.x1,t.x1),y1:x(this.y1,t.y1)}):null}intersects(t){return!(t.x1this.x1||t.y1this.y1)}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.bottom;for(let h=0;h0&&(r=r.filter((n=>(0,l.includes)(t,n.name)))),r}},\n", - " function _(t,n,e,i,s){var r;i();const a=t(57),o=t(20),g=t(21),p=t(24),c=t(9),l=t(8),u=t(11);function h(t,n,e=0){const i=new Map;for(let s=0;sa.get(t).value)));r.set(t,{value:l/s,mapping:a}),o+=s+n+p}return[r,(a.size-1)*n+g]}function _(t,n,e,i,s=0){var r;const a=new Map,o=new Map;for(const[n,e,i]of t){const t=null!==(r=o.get(n))&&void 0!==r?r:[];o.set(n,[...t,[e,i]])}let g=s,p=0;for(const[t,s]of o){const r=s.length,[o,l]=d(s,e,i,g);p+=l;const u=(0,c.sum)(s.map((([t])=>o.get(t).value)));a.set(t,{value:u/r,mapping:o}),g+=r+n+l}return[a,(o.size-1)*n+p]}e.Factor=(0,g.Or)(g.String,(0,g.Tuple)(g.String,g.String),(0,g.Tuple)(g.String,g.String,g.String)),e.FactorSeq=(0,g.Or)((0,g.Array)(g.String),(0,g.Array)((0,g.Tuple)(g.String,g.String)),(0,g.Array)((0,g.Tuple)(g.String,g.String,g.String))),e.map_one_level=h,e.map_two_levels=d,e.map_three_levels=_;class f extends a.Range{constructor(t){super(t)}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,(()=>this.reset())),this.connect(this.properties.factor_padding.change,(()=>this.reset())),this.connect(this.properties.group_padding.change,(()=>this.reset())),this.connect(this.properties.subgroup_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding_units.change,(()=>this.reset()))}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[n]=t,e=this._mapping.get(n);return null!=e?e.value:NaN}case 2:{const[n,e]=t,i=this._mapping.get(n);if(null!=i){const t=i.mapping.get(e);if(null!=t)return t.value}return NaN}case 3:{const[n,e,i]=t,s=this._mapping.get(n);if(null!=s){const t=s.mapping.get(e);if(null!=t){const n=t.mapping.get(i);if(null!=n)return n.value}}return NaN}default:(0,u.unreachable)()}}synthetic(t){if((0,l.isNumber)(t))return t;if((0,l.isString)(t))return this._lookup([t]);let n=0;const e=t[t.length-1];return(0,l.isNumber)(e)&&(n=e,t=t.slice(0,-1)),this._lookup(t)+n}v_synthetic(t){const n=t.length,e=new p.ScreenArray(n);for(let i=0;i{if((0,c.every)(this.factors,l.isString)){const t=this.factors,[n,e]=h(t,this.factor_padding);return{levels:1,mapping:n,tops:null,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&2==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])))){const t=this.factors,[n,e]=d(t,this.group_padding,this.factor_padding),i=[...n.keys()];return{levels:2,mapping:n,tops:i,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&3==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])&&(0,l.isString)(t[2])))){const t=this.factors,[n,e]=_(t,this.group_padding,this.subgroup_padding,this.factor_padding),i=[...n.keys()],s=[];for(const[t,e]of n)for(const n of e.mapping.keys())s.push([t,n]);return{levels:3,mapping:n,tops:i,mids:s,inside_padding:e}}(0,u.unreachable)()})();this._mapping=e,this.tops=i,this.mids=s;let a=0,o=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(o-a)*this.range_padding/2;a-=t,o+=t}else a-=this.range_padding,o+=this.range_padding;this.setv({start:a,end:o,levels:n},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,o]},{silent:!0})}}e.FactorRange=f,r=f,f.__name__=\"FactorRange\",r.define((({Number:t})=>({factors:[e.FactorSeq,[]],factor_padding:[t,0],subgroup_padding:[t,.8],group_padding:[t,1.4],range_padding:[t,0],range_padding_units:[o.PaddingUnits,\"percent\"],start:[t],end:[t]}))),r.internal((({Number:t,String:n,Array:e,Tuple:i,Nullable:s})=>({levels:[t],mids:[s(e(i(n,n))),null],tops:[s(e(n)),null]})))},\n", - " function _(t,e,s,a,i){a();const n=t(1);var _;const r=t(69),o=t(112),l=t(48),d=t(20),h=t(24),c=t(113),u=(0,n.__importStar)(t(18)),v=t(10);class p extends r.DataAnnotationView{async lazy_initialize(){await super.lazy_initialize();const{start:t,end:e}=this.model;null!=t&&(this.start=await(0,c.build_view)(t,{parent:this})),null!=e&&(this.end=await(0,c.build_view)(e,{parent:this}))}set_data(t){var e,s;super.set_data(t),null===(e=this.start)||void 0===e||e.set_data(t),null===(s=this.end)||void 0===s||s.set_data(t)}remove(){var t,e;null===(t=this.start)||void 0===t||t.remove(),null===(e=this.end)||void 0===e||e.remove(),super.remove()}map_data(){const{frame:t}=this.plot_view;\"data\"==this.model.start_units?(this._sx_start=this.coordinates.x_scale.v_compute(this._x_start),this._sy_start=this.coordinates.y_scale.v_compute(this._y_start)):(this._sx_start=t.bbox.xview.v_compute(this._x_start),this._sy_start=t.bbox.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(this._sx_end=this.coordinates.x_scale.v_compute(this._x_end),this._sy_end=this.coordinates.y_scale.v_compute(this._y_end)):(this._sx_end=t.bbox.xview.v_compute(this._x_end),this._sy_end=t.bbox.yview.v_compute(this._y_end));const{_sx_start:e,_sy_start:s,_sx_end:a,_sy_end:i}=this,n=e.length,_=this._angles=new h.ScreenArray(n);for(let t=0;t({x_start:[u.XCoordinateSpec,{field:\"x_start\"}],y_start:[u.YCoordinateSpec,{field:\"y_start\"}],start_units:[d.SpatialUnits,\"data\"],start:[e(t(o.ArrowHead)),null],x_end:[u.XCoordinateSpec,{field:\"x_end\"}],y_end:[u.YCoordinateSpec,{field:\"y_end\"}],end_units:[d.SpatialUnits,\"data\"],end:[e(t(o.ArrowHead)),()=>new o.OpenHead]})))},\n", - " function _(t,e,n,s,a){s();const o=t(1);var i;const c=t(40),r=t(70),_=t(75),l=t(78),h=(0,o.__importStar)(t(18));class d extends c.AnnotationView{constructor(){super(...arguments),this._initial_set_data=!1}connect_signals(){super.connect_signals();const t=()=>{this.set_data(this.model.source),this._rerender()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}_rerender(){this.request_render()}set_data(t){const e=this;for(const n of this.model)if(n instanceof h.VectorSpec||n instanceof h.ScalarSpec)if(n instanceof h.BaseCoordinateSpec){const s=n.array(t);e[`_${n.attr}`]=s}else{const s=n.uniform(t);e[`${n.attr}`]=s}this.plot_model.use_map&&(null!=e._x&&l.inplace.project_xy(e._x,e._y),null!=e._xs&&l.inplace.project_xsys(e._xs,e._ys));for(const t of this.visuals)t.update()}_render(){this._initial_set_data||(this.set_data(this.model.source),this._initial_set_data=!0),this.map_data(),this.paint(this.layer.ctx)}}n.DataAnnotationView=d,d.__name__=\"DataAnnotationView\";class u extends c.Annotation{constructor(t){super(t)}}n.DataAnnotation=u,i=u,u.__name__=\"DataAnnotation\",i.define((({Ref:t})=>({source:[t(r.ColumnarDataSource),()=>new _.ColumnDataSource]})))},\n", - " function _(t,e,n,s,a){var i;s();const r=t(71),l=t(15),c=t(19),o=t(73),h=t(8),u=t(9),g=t(13),d=t(72),_=t(74),m=t(29);class w extends r.DataSource{constructor(t){super(t),this.selection_manager=new o.SelectionManager(this)}get_array(t){let e=this.data[t];return null==e?this.data[t]=e=[]:(0,h.isArray)(e)||(this.data[t]=e=Array.from(e)),e}initialize(){super.initialize(),this._select=new l.Signal0(this,\"select\"),this.inspect=new l.Signal(this,\"inspect\"),this.streaming=new l.Signal0(this,\"streaming\"),this.patching=new l.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return(0,g.keys)(this.data)}get_length(t=!0){const e=(0,u.uniq)((0,g.values)(this.data).map((t=>(0,m.is_NDArray)(t)?t.shape[0]:t.length)));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return c.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=w,i=w,w.__name__=\"ColumnarDataSource\",i.define((({Ref:t})=>({selection_policy:[t(_.SelectionPolicy),()=>new _.UnionRenderers]}))),i.internal((({AnyRef:t})=>({inspected:[t(),()=>new d.Selection]})))},\n", - " function _(e,c,n,t,o){var a;t();const s=e(53),r=e(72);class l extends s.Model{constructor(e){super(e)}}n.DataSource=l,a=l,l.__name__=\"DataSource\",a.define((({Ref:e})=>({selected:[e(r.Selection),()=>new r.Selection]})))},\n", - " function _(i,e,s,t,n){var l;t();const c=i(53),d=i(9),h=i(13);class _ extends c.Model{constructor(i){super(i)}get_view(){return this.view}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices,this.view=i.view,this.selected_glyphs=i.selected_glyphs;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.image_indices=[],this.view=null,this.selected_glyphs=[]}map(i){return new _(Object.assign(Object.assign({},this.attributes),{indices:this.indices.map(i),multiline_indices:(0,h.to_object)((0,h.entries)(this.multiline_indices).map((([e,s])=>[i(Number(e)),s]))),image_indices:this.image_indices.map((e=>Object.assign(Object.assign({},e),{index:i(e.index)})))}))}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=(0,d.union)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=(0,d.intersection)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=(0,d.difference)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}}s.Selection=_,l=_,_.__name__=\"Selection\",l.define((({Int:i,Array:e,Dict:s})=>({indices:[e(i),[]],line_indices:[e(i),[]],multiline_indices:[s(e(i)),{}]}))),l.internal((({Int:i,Array:e,AnyRef:s,Struct:t,Nullable:n})=>({selected_glyphs:[e(s()),[]],view:[n(s()),null],image_indices:[e(t({index:i,dim1:i,dim2:i,flat_index:i})),[]]})))},\n", - " function _(e,t,o,s,c){s();const n=e(72);function i(e){return\"GlyphRenderer\"==e.model.type}function l(e){return\"GraphRenderer\"==e.model.type}class r{constructor(e){this.source=e,this.inspectors=new Map}select(e,t,o,s=\"replace\"){const c=[],n=[];for(const t of e)i(t)?c.push(t):l(t)&&n.push(t);let r=!1;for(const e of n){const c=e.model.selection_policy.hit_test(t,e);r=r||e.model.selection_policy.do_selection(c,e.model,o,s)}if(c.length>0){const e=this.source.selection_policy.hit_test(t,c);r=r||this.source.selection_policy.do_selection(e,this.source,o,s)}return r}inspect(e,t){let o=!1;if(i(e)){const s=e.hit_test(t);if(null!=s){o=!s.is_empty();const c=this.get_or_create_inspector(e.model);c.update(s,!0,\"replace\"),this.source.setv({inspected:c},{silent:!0}),this.source.inspect.emit([e.model,{geometry:t}])}}else if(l(e)){const s=e.model.inspection_policy.hit_test(t,e);o=o||e.model.inspection_policy.do_inspection(s,t,e,!1,\"replace\")}return o}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new n.Selection,this.inspectors.set(e,t)),t}}o.SelectionManager=r,r.__name__=\"SelectionManager\"},\n", - " function _(e,t,n,s,o){s();const r=e(53);class c extends r.Model{do_selection(e,t,n,s){return null!=e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=c,c.__name__=\"SelectionPolicy\";class l extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=l,l.__name__=\"IntersectRenderers\";class _ extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=_,_.__name__=\"UnionRenderers\"},\n", - " function _(t,n,e,s,o){s();const r=t(1);var l;const c=t(70),i=t(8),a=t(13),u=(0,r.__importStar)(t(76)),h=t(77),d=t(35);function f(t,n,e){if((0,i.isArray)(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if((0,i.isTypedArray)(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let l;t.length({data:[t(n),{}]})))},\n", - " function _(t,n,o,e,c){e(),o.concat=function(t,...n){let o=t.length;for(const t of n)o+=t.length;const e=new t.constructor(o);e.set(t,0);let c=t.length;for(const t of n)e.set(t,c),c+=t.length;return e}},\n", - " function _(n,o,t,e,f){function c(...n){const o=new Set;for(const t of n)for(const n of t)o.add(n);return o}e(),t.union=c,t.intersection=function(n,...o){const t=new Set;n:for(const e of n){for(const n of o)if(!n.has(e))continue n;t.add(e)}return t},t.difference=function(n,...o){const t=new Set(n);for(const n of c(...o))t.delete(n);return t}},\n", - " function _(n,t,e,o,r){o();const c=n(1),l=(0,c.__importDefault)(n(79)),i=(0,c.__importDefault)(n(80)),u=n(24),a=new i.default(\"GOOGLE\"),s=new i.default(\"WGS84\"),f=(0,l.default)(s,a);e.wgs84_mercator={compute:(n,t)=>isFinite(n)&&isFinite(t)?f.forward([n,t]):[NaN,NaN],invert:(n,t)=>isFinite(n)&&isFinite(t)?f.inverse([n,t]):[NaN,NaN]};const _={lon:[-20026376.39,20026376.39],lat:[-20048966.1,20048966.1]},p={lon:[-180,180],lat:[-85.06,85.06]},{min:g,max:h}=Math;function m(n,t){const o=g(n.length,t.length),r=(0,u.infer_type)(n,t),c=new r(o),l=new r(o);return e.inplace.project_xy(n,t,c,l),[c,l]}e.clip_mercator=function(n,t,e){const[o,r]=_[e];return[h(n,o),g(t,r)]},e.in_bounds=function(n,t){const[e,o]=p[t];return e2?void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name?\"number\"==typeof o.z?[o.x,o.y,o.z].concat(t.splice(3)):[o.x,o.y,t[2]].concat(t.splice(3)):[o.x,o.y].concat(t.splice(2)):[o.x,o.y]):(a=(0,c.default)(e,n,t,r),2===(i=Object.keys(t)).length||i.forEach((function(r){if(void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name){if(\"x\"===r||\"y\"===r||\"z\"===r)return}else if(\"x\"===r||\"y\"===r)return;a[r]=t[r]})),a)}function l(e){return e instanceof i.default?e:e.oProj?e.oProj:(0,i.default)(e)}t.default=function(e,n,t){e=l(e);var r,o=!1;return void 0===n?(n=e,e=u,o=!0):(void 0!==n.x||Array.isArray(n))&&(t=n,n=e,e=u,o=!0),n=l(n),t?f(e,n,t):(r={forward:function(t,r){return f(e,n,t,r)},inverse:function(t,r){return f(n,e,t,r)}},o&&(r.oProj=n),r)}},\n", - " function _(t,e,a,s,i){s();const l=t(1),u=(0,l.__importDefault)(t(81)),r=(0,l.__importDefault)(t(92)),d=(0,l.__importDefault)(t(93)),o=t(101),f=(0,l.__importDefault)(t(103)),p=(0,l.__importDefault)(t(104)),m=(0,l.__importDefault)(t(88)),n=t(105);function h(t,e){if(!(this instanceof h))return new h(t);e=e||function(t){if(t)throw t};var a=(0,u.default)(t);if(\"object\"==typeof a){var s=h.projections.get(a.projName);if(s){if(a.datumCode&&\"none\"!==a.datumCode){var i=(0,m.default)(f.default,a.datumCode);i&&(a.datum_params=a.datum_params||(i.towgs84?i.towgs84.split(\",\"):null),a.ellps=i.ellipse,a.datumName=i.datumName?i.datumName:a.datumCode)}a.k0=a.k0||1,a.axis=a.axis||\"enu\",a.ellps=a.ellps||\"wgs84\",a.lat1=a.lat1||a.lat0;var l=(0,o.sphere)(a.a,a.b,a.rf,a.ellps,a.sphere),d=(0,o.eccentricity)(l.a,l.b,l.rf,a.R_A),_=(0,n.getNadgrids)(a.nadgrids),c=a.datum||(0,p.default)(a.datumCode,a.datum_params,l.a,l.b,d.es,d.ep2,_);(0,r.default)(this,a),(0,r.default)(this,s),this.a=l.a,this.b=l.b,this.rf=l.rf,this.sphere=l.sphere,this.es=d.es,this.e=d.e,this.ep2=d.ep2,this.datum=c,this.init(),e(null,this)}else e(t)}else e(t)}h.projections=d.default,h.projections.start(),a.default=h},\n", - " function _(t,r,n,u,e){u();const f=t(1),i=(0,f.__importDefault)(t(82)),a=(0,f.__importDefault)(t(89)),o=(0,f.__importDefault)(t(84)),l=(0,f.__importDefault)(t(88));var C=[\"PROJECTEDCRS\",\"PROJCRS\",\"GEOGCS\",\"GEOCCS\",\"PROJCS\",\"LOCAL_CS\",\"GEODCRS\",\"GEODETICCRS\",\"GEODETICDATUM\",\"ENGCRS\",\"ENGINEERINGCRS\"];var d=[\"3857\",\"900913\",\"3785\",\"102113\"];n.default=function(t){if(!function(t){return\"string\"==typeof t}(t))return t;if(function(t){return t in i.default}(t))return i.default[t];if(function(t){return C.some((function(r){return t.indexOf(r)>-1}))}(t)){var r=(0,a.default)(t);if(function(t){var r=(0,l.default)(t,\"authority\");if(r){var n=(0,l.default)(r,\"epsg\");return n&&d.indexOf(n)>-1}}(r))return i.default[\"EPSG:3857\"];var n=function(t){var r=(0,l.default)(t,\"extension\");if(r)return(0,l.default)(r,\"proj4\")}(r);return n?(0,o.default)(n):r}return function(t){return\"+\"===t[0]}(t)?(0,o.default)(t):void 0}},\n", - " function _(t,r,i,e,n){e();const f=t(1),a=(0,f.__importDefault)(t(83)),l=(0,f.__importDefault)(t(84)),u=(0,f.__importDefault)(t(89));function o(t){var r=this;if(2===arguments.length){var i=arguments[1];\"string\"==typeof i?\"+\"===i.charAt(0)?o[t]=(0,l.default)(arguments[1]):o[t]=(0,u.default)(arguments[1]):o[t]=i}else if(1===arguments.length){if(Array.isArray(t))return t.map((function(t){Array.isArray(t)?o.apply(r,t):o(t)}));if(\"string\"==typeof t){if(t in o)return o[t]}else\"EPSG\"in t?o[\"EPSG:\"+t.EPSG]=t:\"ESRI\"in t?o[\"ESRI:\"+t.ESRI]=t:\"IAU2000\"in t?o[\"IAU2000:\"+t.IAU2000]=t:console.log(t);return}}(0,a.default)(o),i.default=o},\n", - " function _(t,l,G,S,e){S(),G.default=function(t){t(\"EPSG:4326\",\"+title=WGS 84 (long/lat) +proj=longlat +ellps=WGS84 +datum=WGS84 +units=degrees\"),t(\"EPSG:4269\",\"+title=NAD83 (long/lat) +proj=longlat +a=6378137.0 +b=6356752.31414036 +ellps=GRS80 +datum=NAD83 +units=degrees\"),t(\"EPSG:3857\",\"+title=WGS 84 / Pseudo-Mercator +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 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o.push(!0),t[o[0].toLowerCase()]=o[1],t}),{}),c={proj:\"projName\",datum:\"datumCode\",rf:function(t){u.rf=parseFloat(t)},lat_0:function(t){u.lat0=t*r.D2R},lat_1:function(t){u.lat1=t*r.D2R},lat_2:function(t){u.lat2=t*r.D2R},lat_ts:function(t){u.lat_ts=t*r.D2R},lon_0:function(t){u.long0=t*r.D2R},lon_1:function(t){u.long1=t*r.D2R},lon_2:function(t){u.long2=t*r.D2R},alpha:function(t){u.alpha=parseFloat(t)*r.D2R},gamma:function(t){u.rectified_grid_angle=parseFloat(t)},lonc:function(t){u.longc=t*r.D2R},x_0:function(t){u.x0=parseFloat(t)},y_0:function(t){u.y0=parseFloat(t)},k_0:function(t){u.k0=parseFloat(t)},k:function(t){u.k0=parseFloat(t)},a:function(t){u.a=parseFloat(t)},b:function(t){u.b=parseFloat(t)},r_a:function(){u.R_A=!0},zone:function(t){u.zone=parseInt(t,10)},south:function(){u.utmSouth=!0},towgs84:function(t){u.datum_params=t.split(\",\").map((function(t){return parseFloat(t)}))},to_meter:function(t){u.to_meter=parseFloat(t)},units:function(t){u.units=t;var n=(0,l.default)(f.default,t);n&&(u.to_meter=n.to_meter)},from_greenwich:function(t){u.from_greenwich=t*r.D2R},pm:function(t){var n=(0,l.default)(i.default,t);u.from_greenwich=(n||parseFloat(t))*r.D2R},nadgrids:function(t){\"@null\"===t?u.datumCode=\"none\":u.nadgrids=t},axis:function(t){var n=\"ewnsud\";3===t.length&&-1!==n.indexOf(t.substr(0,1))&&-1!==n.indexOf(t.substr(1,1))&&-1!==n.indexOf(t.substr(2,1))&&(u.axis=t)},approx:function(){u.approx=!0}};for(n in e)o=e[n],n in c?\"function\"==typeof(a=c[n])?a(o):u[a]=o:u[n]=o;return\"string\"==typeof u.datumCode&&\"WGS84\"!==u.datumCode&&(u.datumCode=u.datumCode.toLowerCase()),u}},\n", - " function _(S,_,P,R,I){R(),P.PJD_3PARAM=1,P.PJD_7PARAM=2,P.PJD_GRIDSHIFT=3,P.PJD_WGS84=4,P.PJD_NODATUM=5,P.SRS_WGS84_SEMIMAJOR=6378137,P.SRS_WGS84_SEMIMINOR=6356752.314,P.SRS_WGS84_ESQUARED=.0066943799901413165,P.SEC_TO_RAD=484813681109536e-20,P.HALF_PI=Math.PI/2,P.SIXTH=.16666666666666666,P.RA4=.04722222222222222,P.RA6=.022156084656084655,P.EPSLN=1e-10,P.D2R=.017453292519943295,P.R2D=57.29577951308232,P.FORTPI=Math.PI/4,P.TWO_PI=2*Math.PI,P.SPI=3.14159265359},\n", - " function _(o,r,a,e,s){e();var n={};a.default=n,n.greenwich=0,n.lisbon=-9.131906111111,n.paris=2.337229166667,n.bogota=-74.080916666667,n.madrid=-3.687938888889,n.rome=12.452333333333,n.bern=7.439583333333,n.jakarta=106.807719444444,n.ferro=-17.666666666667,n.brussels=4.367975,n.stockholm=18.058277777778,n.athens=23.7163375,n.oslo=10.722916666667},\n", - " function _(t,e,f,o,u){o(),f.default={ft:{to_meter:.3048},\"us-ft\":{to_meter:1200/3937}}},\n", - " function _(e,r,t,a,n){a();var o=/[\\s_\\-\\/\\(\\)]/g;t.default=function(e,r){if(e[r])return e[r];for(var t,a=Object.keys(e),n=r.toLowerCase().replace(o,\"\"),f=-1;++f0?90:-90),e.lat_ts=e.lat1)}(n),n}},\n", - " function _(t,e,r,i,s){i(),r.default=function(t){return new d(t).output()};var h=/\\s/,o=/[A-Za-z]/,n=/[A-Za-z84]/,a=/[,\\]]/,u=/[\\d\\.E\\-\\+]/;function d(t){if(\"string\"!=typeof t)throw new Error(\"not a string\");this.text=t.trim(),this.level=0,this.place=0,this.root=null,this.stack=[],this.currentObject=null,this.state=1}d.prototype.readCharicter=function(){var t=this.text[this.place++];if(4!==this.state)for(;h.test(t);){if(this.place>=this.text.length)return;t=this.text[this.place++]}switch(this.state){case 1:return this.neutral(t);case 2:return this.keyword(t);case 4:return this.quoted(t);case 5:return this.afterquote(t);case 3:return this.number(t);case-1:return}},d.prototype.afterquote=function(t){if('\"'===t)return this.word+='\"',void(this.state=4);if(a.test(t))return this.word=this.word.trim(),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in afterquote yet, index '+this.place)},d.prototype.afterItem=function(t){return\",\"===t?(null!==this.word&&this.currentObject.push(this.word),this.word=null,void(this.state=1)):\"]\"===t?(this.level--,null!==this.word&&(this.currentObject.push(this.word),this.word=null),this.state=1,this.currentObject=this.stack.pop(),void(this.currentObject||(this.state=-1))):void 0},d.prototype.number=function(t){if(!u.test(t)){if(a.test(t))return this.word=parseFloat(this.word),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in number yet, index '+this.place)}this.word+=t},d.prototype.quoted=function(t){'\"'!==t?this.word+=t:this.state=5},d.prototype.keyword=function(t){if(n.test(t))this.word+=t;else{if(\"[\"===t){var e=[];return e.push(this.word),this.level++,null===this.root?this.root=e:this.currentObject.push(e),this.stack.push(this.currentObject),this.currentObject=e,void(this.state=1)}if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in keyword yet, index '+this.place);this.afterItem(t)}},d.prototype.neutral=function(t){if(o.test(t))return this.word=t,void(this.state=2);if('\"'===t)return this.word=\"\",void(this.state=4);if(u.test(t))return this.word=t,void(this.state=3);if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in neutral yet, index '+this.place);this.afterItem(t)},d.prototype.output=function(){for(;this.place90&&a*o.R2D<-90&&h*o.R2D>180&&h*o.R2D<-180)return null;if(Math.abs(Math.abs(a)-o.HALF_PI)<=o.EPSLN)return null;if(this.sphere)i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0+this.a*this.k0*Math.log(Math.tan(o.FORTPI+.5*a));else{var e=Math.sin(a),r=(0,l.default)(this.e,a,e);i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0-this.a*this.k0*Math.log(r)}return t.x=i,t.y=s,t}function M(t){var i,s,h=t.x-this.x0,a=t.y-this.y0;if(this.sphere)s=o.HALF_PI-2*Math.atan(Math.exp(-a/(this.a*this.k0)));else{var e=Math.exp(-a/(this.a*this.k0));if(-9999===(s=(0,u.default)(this.e,e)))return null}return i=(0,n.default)(this.long0+h/(this.a*this.k0)),t.x=i,t.y=s,t}s.init=f,s.forward=_,s.inverse=M,s.names=[\"Mercator\",\"Popular Visualisation Pseudo Mercator\",\"Mercator_1SP\",\"Mercator_Auxiliary_Sphere\",\"merc\"],s.default={init:f,forward:_,inverse:M,names:s.names}},\n", - " function _(t,n,r,u,a){u(),r.default=function(t,n,r){var u=t*n;return r/Math.sqrt(1-u*u)}},\n", - " function _(t,n,u,a,f){a();const e=t(1),o=t(85),_=(0,e.__importDefault)(t(97));u.default=function(t){return Math.abs(t)<=o.SPI?t:t-(0,_.default)(t)*o.TWO_PI}},\n", - " function _(n,t,u,f,c){f(),u.default=function(n){return n<0?-1:1}},\n", - " function _(t,n,a,o,u){o();const c=t(85);a.default=function(t,n,a){var o=t*a,u=.5*t;return o=Math.pow((1-o)/(1+o),u),Math.tan(.5*(c.HALF_PI-n))/o}},\n", - " function _(t,a,n,r,f){r();const h=t(85);n.default=function(t,a){for(var n,r,f=.5*t,o=h.HALF_PI-2*Math.atan(a),u=0;u<=15;u++)if(n=t*Math.sin(o),o+=r=h.HALF_PI-2*Math.atan(a*Math.pow((1-n)/(1+n),f))-o,Math.abs(r)<=1e-10)return o;return-9999}},\n", - " function _(n,i,e,t,r){function a(){}function f(n){return n}t(),e.init=a,e.forward=f,e.inverse=f,e.names=[\"longlat\",\"identity\"],e.default={init:a,forward:f,inverse:f,names:e.names}},\n", - " function _(t,r,e,a,n){a();const f=t(1),i=t(85),u=(0,f.__importStar)(t(102)),c=(0,f.__importDefault)(t(88));e.eccentricity=function(t,r,e,a){var n=t*t,f=r*r,u=(n-f)/n,c=0;return a?(n=(t*=1-u*(i.SIXTH+u*(i.RA4+u*i.RA6)))*t,u=0):c=Math.sqrt(u),{es:u,e:c,ep2:(n-f)/f}},e.sphere=function(t,r,e,a,n){if(!t){var f=(0,c.default)(u.default,a);f||(f=u.WGS84),t=f.a,r=f.b,e=f.rf}return e&&!r&&(r=(1-1/e)*t),(0===e||Math.abs(t-r)3&&(0===s.datum_params[3]&&0===s.datum_params[4]&&0===s.datum_params[5]&&0===s.datum_params[6]||(s.datum_type=d.PJD_7PARAM,s.datum_params[3]*=d.SEC_TO_RAD,s.datum_params[4]*=d.SEC_TO_RAD,s.datum_params[5]*=d.SEC_TO_RAD,s.datum_params[6]=s.datum_params[6]/1e6+1))),r&&(s.datum_type=d.PJD_GRIDSHIFT,s.grids=r),s.a=_,s.b=t,s.es=u,s.ep2=p,s}},\n", - " function _(t,e,n,r,i){r();var u={};function l(t){if(0===t.length)return null;var e=\"@\"===t[0];return e&&(t=t.slice(1)),\"null\"===t?{name:\"null\",mandatory:!e,grid:null,isNull:!0}:{name:t,mandatory:!e,grid:u[t]||null,isNull:!1}}function o(t){return t/3600*Math.PI/180}function a(t,e,n){return String.fromCharCode.apply(null,new Uint8Array(t.buffer.slice(e,n)))}function d(t){return t.map((function(t){return[o(t.longitudeShift),o(t.latitudeShift)]}))}function g(t,e,n){return{name:a(t,e+8,e+16).trim(),parent:a(t,e+24,e+24+8).trim(),lowerLatitude:t.getFloat64(e+72,n),upperLatitude:t.getFloat64(e+88,n),lowerLongitude:t.getFloat64(e+104,n),upperLongitude:t.getFloat64(e+120,n),latitudeInterval:t.getFloat64(e+136,n),longitudeInterval:t.getFloat64(e+152,n),gridNodeCount:t.getInt32(e+168,n)}}function s(t,e,n,r){for(var i=e+176,u=[],l=0;l1&&console.log(\"Only single NTv2 subgrids are currently supported, subsequent sub grids are ignored\");var l=function(t,e,n){for(var r=176,i=[],u=0;ua.y||f>a.x||N1e-12&&Math.abs(n.y)>1e-12);if(d<0)return console.log(\"Inverse grid shift iterator failed to converge.\"),a;a.x=(0,u.default)(l.x+t.ll[0]),a.y=l.y+t.ll[1]}else isNaN(l.x)||(a.x=r.x+l.x,a.y=r.y+l.y);return a}function f(r,e){var t,a={x:r.x/e.del[0],y:r.y/e.del[1]},i=Math.floor(a.x),l=Math.floor(a.y),n=a.x-1*i,o=a.y-1*l,u={x:Number.NaN,y:Number.NaN};if(i<0||i>=e.lim[0])return u;if(l<0||l>=e.lim[1])return u;t=l*e.lim[0]+i;var d=e.cvs[t][0],s=e.cvs[t][1];t++;var y=e.cvs[t][0],f=e.cvs[t][1];t+=e.lim[0];var x=e.cvs[t][0],m=e.cvs[t][1];t--;var N=e.cvs[t][0],c=e.cvs[t][1],_=n*o,g=n*(1-o),v=(1-n)*(1-o),S=(1-n)*o;return u.x=v*d+g*y+S*N+_*x,u.y=v*s+g*f+S*c+_*m,u}t.default=function(r,e,t){if((0,o.compareDatums)(r,e))return t;if(r.datum_type===n.PJD_NODATUM||e.datum_type===n.PJD_NODATUM)return t;var a=r.a,i=r.es;if(r.datum_type===n.PJD_GRIDSHIFT){if(0!==s(r,!1,t))return;a=n.SRS_WGS84_SEMIMAJOR,i=n.SRS_WGS84_ESQUARED}var l=e.a,u=e.b,y=e.es;if(e.datum_type===n.PJD_GRIDSHIFT&&(l=n.SRS_WGS84_SEMIMAJOR,u=n.SRS_WGS84_SEMIMINOR,y=n.SRS_WGS84_ESQUARED),i===y&&a===l&&!d(r.datum_type)&&!d(e.datum_type))return t;if(t=(0,o.geodeticToGeocentric)(t,i,a),d(r.datum_type)&&(t=(0,o.geocentricToWgs84)(t,r.datum_type,r.datum_params)),d(e.datum_type)&&(t=(0,o.geocentricFromWgs84)(t,e.datum_type,e.datum_params)),t=(0,o.geocentricToGeodetic)(t,y,l,u),e.datum_type===n.PJD_GRIDSHIFT&&0!==s(e,!0,t))return;return t},t.applyGridShift=s},\n", - " function _(a,t,r,m,s){m();const u=a(85);r.compareDatums=function(a,t){return a.datum_type===t.datum_type&&(!(a.a!==t.a||Math.abs(a.es-t.es)>5e-11)&&(a.datum_type===u.PJD_3PARAM?a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]:a.datum_type!==u.PJD_7PARAM||a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]&&a.datum_params[3]===t.datum_params[3]&&a.datum_params[4]===t.datum_params[4]&&a.datum_params[5]===t.datum_params[5]&&a.datum_params[6]===t.datum_params[6]))},r.geodeticToGeocentric=function(a,t,r){var m,s,_,e,n=a.x,d=a.y,i=a.z?a.z:0;if(d<-u.HALF_PI&&d>-1.001*u.HALF_PI)d=-u.HALF_PI;else if(d>u.HALF_PI&&d<1.001*u.HALF_PI)d=u.HALF_PI;else{if(d<-u.HALF_PI)return{x:-1/0,y:-1/0,z:a.z};if(d>u.HALF_PI)return{x:1/0,y:1/0,z:a.z}}return n>Math.PI&&(n-=2*Math.PI),s=Math.sin(d),e=Math.cos(d),_=s*s,{x:((m=r/Math.sqrt(1-t*_))+i)*e*Math.cos(n),y:(m+i)*e*Math.sin(n),z:(m*(1-t)+i)*s}},r.geocentricToGeodetic=function(a,t,r,m){var s,_,e,n,d,i,p,P,y,z,M,o,A,c,x,h=1e-12,f=a.x,I=a.y,F=a.z?a.z:0;if(s=Math.sqrt(f*f+I*I),_=Math.sqrt(f*f+I*I+F*F),s/r1e-24&&A<30);return{x:c,y:Math.atan(M/Math.abs(z)),z:x}},r.geocentricToWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x+r[0],y:a.y+r[1],z:a.z+r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6];return{x:i*(a.x-d*a.y+n*a.z)+m,y:i*(d*a.x+a.y-e*a.z)+s,z:i*(-n*a.x+e*a.y+a.z)+_}}},r.geocentricFromWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x-r[0],y:a.y-r[1],z:a.z-r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6],p=(a.x-m)/i,P=(a.y-s)/i,y=(a.z-_)/i;return{x:p+d*P-n*y,y:-d*p+P+e*y,z:n*p-e*P+y}}}},\n", - " function _(e,a,i,r,s){r(),i.default=function(e,a,i){var r,s,n,c=i.x,d=i.y,f=i.z||0,u={};for(n=0;n<3;n++)if(!a||2!==n||void 0!==i.z)switch(0===n?(r=c,s=-1!==\"ew\".indexOf(e.axis[n])?\"x\":\"y\"):1===n?(r=d,s=-1!==\"ns\".indexOf(e.axis[n])?\"y\":\"x\"):(r=f,s=\"z\"),e.axis[n]){case\"e\":u[s]=r;break;case\"w\":u[s]=-r;break;case\"n\":u[s]=r;break;case\"s\":u[s]=-r;break;case\"u\":void 0!==i[s]&&(u.z=r);break;case\"d\":void 0!==i[s]&&(u.z=-r);break;default:return null}return u}},\n", - " function _(n,t,e,u,f){u(),e.default=function(n){var t={x:n[0],y:n[1]};return n.length>2&&(t.z=n[2]),n.length>3&&(t.m=n[3]),t}},\n", - " function _(e,i,n,t,r){function o(e){if(\"function\"==typeof Number.isFinite){if(Number.isFinite(e))return;throw new TypeError(\"coordinates must be finite numbers\")}if(\"number\"!=typeof e||e!=e||!isFinite(e))throw new TypeError(\"coordinates must be finite numbers\")}t(),n.default=function(e){o(e.x),o(e.y)}},\n", - " function _(e,i,s,t,o){t();const n=e(1);var l,a,r,_,c;const d=e(53),v=e(42),u=(0,n.__importStar)(e(45)),h=e(48),m=(0,n.__importStar)(e(18));class T extends v.View{initialize(){super.initialize(),this.visuals=new u.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.parent.canvas}set_data(e){const i=this;for(const s of this.model){if(!(s instanceof m.VectorSpec||s instanceof m.ScalarSpec))continue;const t=s.uniform(e);i[`${s.attr}`]=t}}}s.ArrowHeadView=T,T.__name__=\"ArrowHeadView\";class p extends d.Model{constructor(e){super(e)}}s.ArrowHead=p,l=p,p.__name__=\"ArrowHead\",l.define((()=>({size:[m.NumberSpec,25]})));class V extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,0),e.lineTo(.5*s,s)}render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.stroke()}}}s.OpenHeadView=V,V.__name__=\"OpenHeadView\";class f extends p{constructor(e){super(e)}}s.OpenHead=f,a=f,f.__name__=\"OpenHead\",a.prototype.default_view=V,a.mixins(h.LineVector);class w extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._normal(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._normal(e,i),e.stroke())}_normal(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.closePath()}}s.NormalHeadView=w,w.__name__=\"NormalHeadView\";class H extends p{constructor(e){super(e)}}s.NormalHead=H,r=H,H.__name__=\"NormalHead\",r.prototype.default_view=w,r.mixins([h.LineVector,h.FillVector]),r.override({fill_color:\"black\"});class z extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._vee(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._vee(e,i),e.stroke())}_vee(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.closePath()}}s.VeeHeadView=z,z.__name__=\"VeeHeadView\";class x extends p{constructor(e){super(e)}}s.VeeHead=x,_=x,x.__name__=\"VeeHead\",_.prototype.default_view=z,_.mixins([h.LineVector,h.FillVector]),_.override({fill_color:\"black\"});class g extends T{render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,0),e.lineTo(-.5*s,0),e.stroke()}}clip(e,i){}}s.TeeHeadView=g,g.__name__=\"TeeHeadView\";class b extends p{constructor(e){super(e)}}s.TeeHead=b,c=b,b.__name__=\"TeeHead\",c.prototype.default_view=g,c.mixins(h.LineVector)},\n", - " function _(n,e,t,i,o){i();const s=n(9);async function c(n,e,t){const i=new n(Object.assign(Object.assign({},t),{model:e}));return i.initialize(),await i.lazy_initialize(),i}t.build_view=async function(n,e={parent:null},t=(n=>n.default_view)){const i=await c(t(n),n,e);return i.connect_signals(),i},t.build_views=async function(n,e,t={parent:null},i=(n=>n.default_view)){const o=(0,s.difference)([...n.keys()],e);for(const e of o)n.get(e).remove(),n.delete(e);const a=[],f=e.filter((e=>!n.has(e)));for(const e of f){const o=await c(i(e),e,t);n.set(e,o),a.push(o)}for(const n of a)n.connect_signals();return a},t.remove_views=function(n){for(const[e,t]of n)t.remove(),n.delete(e)}},\n", - " function _(e,s,_,i,l){i();const t=e(1);var o;const r=e(115),p=(0,t.__importStar)(e(48));class h extends r.UpperLowerView{paint(e){e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);for(let s=this._upper_sx.length-1;s>=0;s--)e.lineTo(this._upper_sx[s],this._upper_sy[s]);e.closePath(),this.visuals.fill.apply(e),e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);this.visuals.line.apply(e),e.beginPath(),e.moveTo(this._upper_sx[0],this._upper_sy[0]);for(let s=0,_=this._upper_sx.length;s<_;s++)e.lineTo(this._upper_sx[s],this._upper_sy[s]);this.visuals.line.apply(e)}}_.BandView=h,h.__name__=\"BandView\";class n extends r.UpperLower{constructor(e){super(e)}}_.Band=n,o=n,n.__name__=\"Band\",o.prototype.default_view=h,o.mixins([p.Line,p.Fill]),o.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,i,s,o){s();const r=e(1);var n;const p=e(69),a=e(20),_=(0,r.__importStar)(e(18));class h extends p.DataAnnotationView{map_data(){const{frame:e}=this.plot_view,t=this.model.dimension,i=this.coordinates.x_scale,s=this.coordinates.y_scale,o=\"height\"==t?s:i,r=\"height\"==t?i:s,n=\"height\"==t?e.bbox.yview:e.bbox.xview,p=\"height\"==t?e.bbox.xview:e.bbox.yview;let a,_,h;a=\"data\"==this.model.properties.lower.units?o.v_compute(this._lower):n.v_compute(this._lower),_=\"data\"==this.model.properties.upper.units?o.v_compute(this._upper):n.v_compute(this._upper),h=\"data\"==this.model.properties.base.units?r.v_compute(this._base):p.v_compute(this._base);const[d,c]=\"height\"==t?[1,0]:[0,1],u=[a,h],l=[_,h];this._lower_sx=u[d],this._lower_sy=u[c],this._upper_sx=l[d],this._upper_sy=l[c]}}i.UpperLowerView=h,h.__name__=\"UpperLowerView\";class d extends _.CoordinateSpec{get dimension(){return\"width\"==this.obj.dimension?\"x\":\"y\"}get units(){var e;return null!==(e=this.spec.units)&&void 0!==e?e:\"data\"}}i.XOrYCoordinateSpec=d,d.__name__=\"XOrYCoordinateSpec\";class c extends p.DataAnnotation{constructor(e){super(e)}}i.UpperLower=c,n=c,c.__name__=\"UpperLower\",n.define((()=>({dimension:[a.Dimension,\"height\"],lower:[d,{field:\"lower\"}],upper:[d,{field:\"upper\"}],base:[d,{field:\"base\"}]})))},\n", - " function _(t,o,i,n,e){n();const s=t(1);var l;const r=t(40),a=(0,s.__importStar)(t(48)),c=t(20),h=t(65);i.EDGE_TOLERANCE=2.5;class b extends r.AnnotationView{constructor(){super(...arguments),this.bbox=new h.BBox}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{left:t,right:o,top:i,bottom:n}=this.model;if(null==t&&null==o&&null==i&&null==n)return;const{frame:e}=this.plot_view,s=this.coordinates.x_scale,l=this.coordinates.y_scale,r=(t,o,i,n,e)=>{let s;return s=null!=t?this.model.screen?t:\"data\"==o?i.compute(t):n.compute(t):e,s};this.bbox=h.BBox.from_rect({left:r(t,this.model.left_units,s,e.bbox.xview,e.bbox.left),right:r(o,this.model.right_units,s,e.bbox.xview,e.bbox.right),top:r(i,this.model.top_units,l,e.bbox.yview,e.bbox.top),bottom:r(n,this.model.bottom_units,l,e.bbox.yview,e.bbox.bottom)}),this._paint_box()}_paint_box(){const{ctx:t}=this.layer;t.save();const{left:o,top:i,width:n,height:e}=this.bbox;t.beginPath(),t.rect(o,i,n,e),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t),t.restore()}interactive_bbox(){const t=this.model.line_width+i.EDGE_TOLERANCE;return this.bbox.grow_by(t)}interactive_hit(t,o){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,o)}cursor(t,o){const{left:i,right:n,bottom:e,top:s}=this.bbox;return Math.abs(t-i)<3||Math.abs(t-n)<3?this.model.ew_cursor:Math.abs(o-e)<3||Math.abs(o-s)<3?this.model.ns_cursor:this.bbox.contains(t,o)?this.model.in_cursor:null}}i.BoxAnnotationView=b,b.__name__=\"BoxAnnotationView\";class u extends r.Annotation{constructor(t){super(t)}update({left:t,right:o,top:i,bottom:n}){this.setv({left:t,right:o,top:i,bottom:n,screen:!0})}}i.BoxAnnotation=u,l=u,u.__name__=\"BoxAnnotation\",l.prototype.default_view=b,l.mixins([a.Line,a.Fill,a.Hatch]),l.define((({Number:t,Nullable:o})=>({top:[o(t),null],top_units:[c.SpatialUnits,\"data\"],bottom:[o(t),null],bottom_units:[c.SpatialUnits,\"data\"],left:[o(t),null],left_units:[c.SpatialUnits,\"data\"],right:[o(t),null],right_units:[c.SpatialUnits,\"data\"],render_mode:[c.RenderMode,\"canvas\"]}))),l.internal((({Boolean:t,String:o,Nullable:i})=>({screen:[t,!1],ew_cursor:[i(o),null],ns_cursor:[i(o),null],in_cursor:[i(o),null]}))),l.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(t,e,i,o,n){o();const a=t(1);var r;const s=t(40),l=t(118),_=t(126),c=t(127),h=t(130),u=t(168),p=t(131),m=t(192),g=t(132),d=t(173),f=t(172),w=t(196),b=t(204),v=t(206),x=t(133),y=t(20),k=(0,a.__importStar)(t(48)),z=t(9),j=t(207),C=t(208),L=t(211),B=t(123),S=t(11),M=t(113),T=t(65),A=t(8);class O extends s.AnnotationView{get orientation(){return this._orientation}initialize(){super.initialize();const{ticker:t,formatter:e,color_mapper:i}=this.model;this._ticker=\"auto\"!=t?t:(()=>{switch(!0){case i instanceof w.LogColorMapper:return new u.LogTicker;case i instanceof w.ScanningColorMapper:return new u.BinnedTicker({mapper:i});case i instanceof w.CategoricalColorMapper:return new u.CategoricalTicker;default:return new u.BasicTicker}})(),this._formatter=\"auto\"!=e?e:(()=>{switch(!0){case this._ticker instanceof u.LogTicker:return new m.LogTickFormatter;case i instanceof w.CategoricalColorMapper:return new m.CategoricalTickFormatter;default:return new m.BasicTickFormatter}})(),this._major_range=(()=>{if(i instanceof w.CategoricalColorMapper){const{factors:t}=i;return new v.FactorRange({factors:t})}if(i instanceof f.ContinuousColorMapper){const{min:t,max:e}=i.metrics;return new v.Range1d({start:t,end:e})}(0,S.unreachable)()})(),this._major_scale=(()=>{if(i instanceof w.LinearColorMapper)return new b.LinearScale;if(i instanceof w.LogColorMapper)return new b.LogScale;if(i instanceof w.ScanningColorMapper){const{binning:t}=i.metrics;return new b.LinearInterpolationScale({binning:t})}if(i instanceof w.CategoricalColorMapper)return new b.CategoricalScale;(0,S.unreachable)()})(),this._minor_range=new v.Range1d({start:0,end:1}),this._minor_scale=new b.LinearScale;const o=k.attrs_of(this.model,\"major_label_\",k.Text,!0),n=k.attrs_of(this.model,\"major_tick_\",k.Line,!0),a=k.attrs_of(this.model,\"minor_tick_\",k.Line,!0),r=k.attrs_of(this.model,\"title_\",k.Text),s=i instanceof w.CategoricalColorMapper?c.CategoricalAxis:i instanceof w.LogColorMapper?c.LogAxis:c.LinearAxis;this._axis=new s(Object.assign(Object.assign(Object.assign({ticker:this._ticker,formatter:this._formatter,major_tick_in:this.model.major_tick_in,major_tick_out:this.model.major_tick_out,minor_tick_in:this.model.minor_tick_in,minor_tick_out:this.model.minor_tick_out,major_label_standoff:this.model.label_standoff,major_label_overrides:this.model.major_label_overrides,major_label_policy:this.model.major_label_policy,axis_line_color:null},o),n),a));const{title:_}=this.model;_&&(this._title=new l.Title(Object.assign({text:_,standoff:this.model.title_standoff},r)))}async lazy_initialize(){await super.lazy_initialize();const t=this,e={get parent(){return t.parent},get root(){return t.root},get frame(){return t._frame},get canvas_view(){return t.parent.canvas_view},request_layout(){t.parent.request_layout()}};this._axis_view=await(0,M.build_view)(this._axis,{parent:e}),null!=this._title&&(this._title_view=await(0,M.build_view)(this._title,{parent:e}))}remove(){var t;null===(t=this._title_view)||void 0===t||t.remove(),this._axis_view.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this._ticker.change,(()=>this.request_render())),this.connect(this._formatter.change,(()=>this.request_render())),this.connect(this.model.color_mapper.metrics_change,(()=>{const t=this._major_range,e=this._major_scale,{color_mapper:i}=this.model;if(i instanceof f.ContinuousColorMapper&&t instanceof v.Range1d){const{min:e,max:o}=i.metrics;t.setv({start:e,end:o})}if(i instanceof w.ScanningColorMapper&&e instanceof b.LinearInterpolationScale){const{binning:t}=i.metrics;e.binning=t}this._set_canvas_image(),this.plot_view.request_layout()}))}_set_canvas_image(){const{orientation:t}=this,e=(()=>{const{palette:e}=this.model.color_mapper;return\"vertical\"==t?(0,z.reversed)(e):e})(),[i,o]=\"vertical\"==t?[1,e.length]:[e.length,1],n=this._image=document.createElement(\"canvas\");n.width=i,n.height=o;const a=n.getContext(\"2d\"),r=a.getImageData(0,0,i,o),s=new w.LinearColorMapper({palette:e}).rgba_mapper.v_compute((0,z.range)(0,e.length));r.data.set(s),a.putImageData(r,0,0)}update_layout(){const{location:t,width:e,height:i,padding:o,margin:n}=this.model,[a,r]=(()=>{if(!(0,A.isString)(t))return[\"end\",\"start\"];switch(t){case\"top_left\":return[\"start\",\"start\"];case\"top\":case\"top_center\":return[\"start\",\"center\"];case\"top_right\":return[\"start\",\"end\"];case\"bottom_left\":return[\"end\",\"start\"];case\"bottom\":case\"bottom_center\":return[\"end\",\"center\"];case\"bottom_right\":return[\"end\",\"end\"];case\"left\":case\"center_left\":return[\"center\",\"start\"];case\"center\":case\"center_center\":return[\"center\",\"center\"];case\"right\":case\"center_right\":return[\"center\",\"end\"]}})(),s=this._orientation=(()=>{const{orientation:t}=this.model;return\"auto\"==t?null!=this.panel?this.panel.is_horizontal?\"horizontal\":\"vertical\":\"start\"==r||\"end\"==r||\"center\"==r&&\"center\"==a?\"vertical\":\"horizontal\":t})(),l=new C.NodeLayout,c=new C.VStack,h=new C.VStack,u=new C.HStack,p=new C.HStack;l.absolute=!0,c.absolute=!0,h.absolute=!0,u.absolute=!0,p.absolute=!0;const[m,g,d,f]=(()=>\"horizontal\"==s?[this._major_scale,this._minor_scale,this._major_range,this._minor_range]:[this._minor_scale,this._major_scale,this._minor_range,this._major_range])();this._frame=new _.CartesianFrame(m,g,d,f),l.on_resize((t=>this._frame.set_geometry(t)));const w=new L.BorderLayout;this._inner_layout=w,w.absolute=!0,w.center_panel=l,w.top_panel=c,w.bottom_panel=h,w.left_panel=u,w.right_panel=p;const b={left:o,right:o,top:o,bottom:o},v=(()=>{if(null==this.panel){if((0,A.isString)(t))return{left:n,right:n,top:n,bottom:n};{const[e,i]=t;return{left:e,right:n,top:n,bottom:i}}}if(!(0,A.isString)(t)){const[e,i]=t;return w.fixup_geometry=(t,o)=>{const n=t,a=this.layout.bbox,{width:r,height:s}=t;if(t=new T.BBox({left:a.left+e,bottom:a.bottom-i,width:r,height:s}),null!=o){const e=t.left-n.left,i=t.top-n.top,{left:a,top:r,width:s,height:l}=o;o=new T.BBox({left:a+e,top:r+i,width:s,height:l})}return[t,o]},{left:e,right:0,top:0,bottom:i}}w.fixup_geometry=(t,e)=>{const i=t;if(\"horizontal\"==s){const{top:e,width:i,height:o}=t;if(\"end\"==r){const{right:n}=this.layout.bbox;t=new T.BBox({right:n,top:e,width:i,height:o})}else if(\"center\"==r){const{hcenter:n}=this.layout.bbox;t=new T.BBox({hcenter:Math.round(n),top:e,width:i,height:o})}}else{const{left:e,width:i,height:o}=t;if(\"end\"==a){const{bottom:n}=this.layout.bbox;t=new T.BBox({left:e,bottom:n,width:i,height:o})}else if(\"center\"==a){const{vcenter:n}=this.layout.bbox;t=new T.BBox({left:e,vcenter:Math.round(n),width:i,height:o})}}if(null!=e){const o=t.left-i.left,n=t.top-i.top,{left:a,top:r,width:s,height:l}=e;e=new T.BBox({left:a+o,top:r+n,width:s,height:l})}return[t,e]}})();let x,y,k,z;if(w.padding=b,null!=this.panel?(x=\"max\",y=void 0,k=void 0,z=void 0):\"auto\"==(\"horizontal\"==s?e:i)?(x=\"fixed\",y=25*this.model.color_mapper.palette.length,k={percent:.3},z={percent:.8}):(x=\"fit\",y=void 0),\"horizontal\"==s){const t=\"auto\"==e?void 0:e,o=\"auto\"==i?25:i;w.set_sizing({width_policy:x,height_policy:\"min\",width:y,min_width:k,max_width:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"auto\"==e?\"fit\":\"fixed\",height_policy:\"fixed\",width:t,height:o})}else{const t=\"auto\"==e?25:e,o=\"auto\"==i?void 0:i;w.set_sizing({width_policy:\"min\",height_policy:x,height:y,min_height:k,max_height:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"fixed\",height_policy:\"auto\"==i?\"fit\":\"fixed\",width:t,height:o})}c.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),h.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),u.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),p.set_sizing({width_policy:\"min\",height_policy:\"fit\"});const{_title_view:S}=this;null!=S&&(\"horizontal\"==s?(S.panel=new B.Panel(\"above\"),S.update_layout(),c.children.push(S.layout)):(S.panel=new B.Panel(\"left\"),S.update_layout(),u.children.push(S.layout)));const{panel:M}=this,O=null!=M&&s==M.orientation?M.side:\"horizontal\"==s?\"below\":\"right\",R=(()=>{switch(O){case\"above\":return c;case\"below\":return h;case\"left\":return u;case\"right\":return p}})(),{_axis_view:F}=this;if(F.panel=new B.Panel(O),F.update_layout(),R.children.push(F.layout),null!=this.panel){const t=new j.Grid([{layout:w,row:0,col:0}]);t.absolute=!0,\"horizontal\"==s?t.set_sizing({width_policy:\"max\",height_policy:\"min\"}):t.set_sizing({width_policy:\"min\",height_policy:\"max\"}),this.layout=t}else this.layout=this._inner_layout;const{visible:I}=this.model;this.layout.sizing.visible=I,this._set_canvas_image()}_render(){var t;const{ctx:e}=this.layer;e.save(),this._paint_bbox(e,this._inner_layout.bbox),this._paint_image(e,this._inner_layout.center_panel.bbox),null===(t=this._title_view)||void 0===t||t.render(),this._axis_view.render(),e.restore()}_paint_bbox(t,e){const{x:i,y:o}=e;let{width:n,height:a}=e;i+n>=this.parent.canvas_view.bbox.width&&(n-=1),o+a>=this.parent.canvas_view.bbox.height&&(a-=1),t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(i,o,n,a)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}_paint_image(t,e){const{x:i,y:o,width:n,height:a}=e;t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this._image,i,o,n,a),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}serializable_state(){const t=super.serializable_state(),{children:e=[]}=t,i=(0,a.__rest)(t,[\"children\"]);return null!=this._title_view&&e.push(this._title_view.serializable_state()),e.push(this._axis_view.serializable_state()),Object.assign(Object.assign({},i),{children:e})}}i.ColorBarView=O,O.__name__=\"ColorBarView\";class R extends s.Annotation{constructor(t){super(t)}}i.ColorBar=R,r=R,R.__name__=\"ColorBar\",r.prototype.default_view=O,r.mixins([[\"major_label_\",k.Text],[\"title_\",k.Text],[\"major_tick_\",k.Line],[\"minor_tick_\",k.Line],[\"border_\",k.Line],[\"bar_\",k.Line],[\"background_\",k.Fill]]),r.define((({Alpha:t,Number:e,String:i,Tuple:o,Dict:n,Or:a,Ref:r,Auto:s,Nullable:l})=>({location:[a(y.Anchor,o(e,e)),\"top_right\"],orientation:[a(y.Orientation,s),\"auto\"],title:[l(i),null],title_standoff:[e,2],width:[a(e,s),\"auto\"],height:[a(e,s),\"auto\"],scale_alpha:[t,1],ticker:[a(r(h.Ticker),s),\"auto\"],formatter:[a(r(p.TickFormatter),s),\"auto\"],major_label_overrides:[n(a(i,r(x.BaseText))),{}],major_label_policy:[r(g.LabelingPolicy),()=>new g.NoOverlap],color_mapper:[r(d.ColorMapper)],label_standoff:[e,5],margin:[e,30],padding:[e,10],major_tick_in:[e,5],major_tick_out:[e,0],minor_tick_in:[e,0],minor_tick_out:[e,0]}))),r.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(t,e,i,s,l){s();const o=t(1);var a;const n=t(119),r=t(20),c=t(120),h=(0,o.__importStar)(t(48));class _ extends n.TextAnnotationView{_get_location(){const t=this.model.offset,e=this.model.standoff/2;let i,s;const{bbox:l}=this.layout;switch(this.panel.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":s=l.top+e;break;case\"middle\":s=l.vcenter;break;case\"bottom\":s=l.bottom-e}switch(this.model.align){case\"left\":i=l.left+t;break;case\"center\":i=l.hcenter;break;case\"right\":i=l.right-t}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=l.left+e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.right-e}switch(this.model.align){case\"left\":s=l.bottom-t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.top+t}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=l.right-e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.left+e}switch(this.model.align){case\"left\":s=l.top+t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.bottom-t}}return[i,s]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),s=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,s)}_get_size(){const{text:t}=this.model,e=new c.TextBox({text:t});e.visuals=this.visuals.text.values();const{width:i,height:s}=e.size();return{width:i,height:0==s?0:2+s+this.model.standoff}}}i.TitleView=_,_.__name__=\"TitleView\";class d extends n.TextAnnotation{constructor(t){super(t)}}i.Title=d,a=d,d.__name__=\"Title\",a.prototype.default_view=_,a.mixins([h.Text,[\"border_\",h.Line],[\"background_\",h.Fill]]),a.define((({Number:t,String:e})=>({text:[e,\"\"],vertical_align:[r.VerticalAlign,\"bottom\"],align:[r.TextAlign,\"left\"],offset:[t,0],standoff:[t,10]}))),a.prototype._props.text_align.options.internal=!0,a.prototype._props.text_baseline.options.internal=!0,a.override({text_font_size:\"13px\",text_font_style:\"bold\",text_line_height:1,background_fill_color:null,border_line_color:null})},\n", - " function _(e,t,s,i,l){var n;i();const o=e(40),a=e(43),r=e(20),d=e(120),u=e(123),c=e(11);class h extends o.AnnotationView{update_layout(){const{panel:e}=this;this.layout=null!=e?new u.SideLayout(e,(()=>this.get_size()),!0):void 0}initialize(){super.initialize(),\"css\"==this.model.render_mode&&(this.el=(0,a.div)(),this.plot_view.canvas_view.add_overlay(this.el))}remove(){null!=this.el&&(0,a.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),\"css\"==this.model.render_mode?this.connect(this.model.change,(()=>this.render())):this.connect(this.model.change,(()=>this.request_render()))}render(){this.model.visible||\"css\"!=this.model.render_mode||(0,a.undisplay)(this.el),super.render()}_canvas_text(e,t,s,i,l){const n=new d.TextBox({text:t});n.angle=l,n.position={sx:s,sy:i},n.visuals=this.visuals.text.values();const{background_fill:o,border_line:a}=this.visuals;if(o.doit||a.doit){const{p0:t,p1:s,p2:i,p3:l}=n.rect();e.beginPath(),e.moveTo(t.x,t.y),e.lineTo(s.x,s.y),e.lineTo(i.x,i.y),e.lineTo(l.x,l.y),e.closePath(),this.visuals.background_fill.apply(e),this.visuals.border_line.apply(e)}this.visuals.text.doit&&n.paint(e)}_css_text(e,t,s,i,l){const{el:n}=this;(0,c.assert)(null!=n),(0,a.undisplay)(n),n.textContent=t,this.visuals.text.set_value(e),n.style.position=\"absolute\",n.style.left=`${s}px`,n.style.top=`${i}px`,n.style.color=e.fillStyle,n.style.font=e.font,n.style.lineHeight=\"normal\",n.style.whiteSpace=\"pre\";const[o,r]=(()=>{switch(this.visuals.text.text_align.get_value()){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,u]=(()=>{switch(this.visuals.text.text_baseline.get_value()){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${r}, ${u})`;l&&(h+=`rotate(${l}rad)`),n.style.transformOrigin=`${o} ${d}`,n.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),n.style.backgroundColor=e.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),n.style.borderStyle=e.lineDash.length<2?\"solid\":\"dashed\",n.style.borderWidth=`${e.lineWidth}px`,n.style.borderColor=e.strokeStyle),(0,a.display)(n)}}s.TextAnnotationView=h,h.__name__=\"TextAnnotationView\";class _ extends o.Annotation{constructor(e){super(e)}}s.TextAnnotation=_,n=_,_.__name__=\"TextAnnotation\",n.define((()=>({render_mode:[r.RenderMode,\"canvas\"]})))},\n", - " function _(t,e,s,i,n){i();const h=t(65),o=t(121),r=t(9),a=t(8),c=t(122),_=t(22);s.text_width=(()=>{const t=document.createElement(\"canvas\").getContext(\"2d\");let e=\"\";return(s,i)=>(i!=e&&(e=i,t.font=i),t.measureText(s).width)})();class l{constructor(){this._position={sx:0,sy:0},this.font_size_scale=1,this.align=\"left\",this._base_font_size=13,this._x_anchor=\"left\",this._y_anchor=\"center\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}set position(t){this._position=t}get position(){return this._position}infer_text_height(){return\"ascent_descent\"}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new h.BBox({left:n,right:r,top:o,bottom:a})}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new c.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e.x),h(e.y)),t.lineTo(h(s.x),h(s.y)),t.lineTo(h(i.x),h(i.y)),t.lineTo(h(n.x),h(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e),h(s)),t.lineTo(h(e),h(s+n)),t.lineTo(h(e+i),h(s+n)),t.lineTo(h(e+i),h(s)),t.closePath(),t.stroke(),t.restore()}}s.GraphicsBox=l,l.__name__=\"GraphicsBox\";class x extends l{constructor({text:t}){super(),this.text=t}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const h=t.font,{font_size_scale:r,base_font_size:a}=this,c=(0,o.parse_css_font_size)(n);if(null!=c){let{value:t,unit:e}=c;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const l=`${i} ${n} ${h}`;this.font=l,this.color=(0,_.color2css)(e,s),this.line_height=t.line_height;const x=t.align;this._x_anchor=x;const u=t.baseline;this._y_anchor=(()=>{switch(u){case\"top\":return\"top\";case\"middle\":return\"center\";case\"bottom\":return\"bottom\";default:return\"baseline\"}})()}infer_text_height(){if(this.text.includes(\"\\n\"))return\"ascent_descent\";{function t(t){for(const e of new Set(t))if(!(\"0\"<=e&&e<=\"9\"))switch(e){case\",\":case\".\":case\"+\":case\"-\":case\"\\u2212\":case\"e\":continue;default:return!1}return!0}return t(this.text)?\"cap\":\"ascent_descent\"}}_text_line(t){var e;const s=null!==(e=this.text_height_metric)&&void 0!==e?e:this.infer_text_height(),i=(()=>{switch(s){case\"x\":case\"x_descent\":return t.x_height;case\"cap\":case\"cap_descent\":return t.cap_height;case\"ascent\":case\"ascent_descent\":return t.ascent}})(),n=(()=>{switch(s){case\"x\":case\"cap\":case\"ascent\":return 0;case\"x_descent\":case\"cap_descent\":case\"ascent_descent\":return t.descent}})();return{height:i+n,ascent:i,descent:n}}get nlines(){return this.text.split(\"\\n\").length}_size(){var t,e;const{font:i}=this,n=(0,o.font_metrics)(i),h=(this.line_height-1)*n.height,a=\"\"==this.text,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,i))),x=this._text_line(n).height*_,u=\"%\"==(null===(t=this.width)||void 0===t?void 0:t.unit)?this.width.value:1,p=\"%\"==(null===(e=this.height)||void 0===e?void 0:e.unit)?this.height.value:1;return{width:(0,r.max)(l)*u,height:a?0:(x+h*(_-1))*p,metrics:n}}_computed_position(t,e,s){const{width:i,height:n}=t,{sx:h,sy:o,x_anchor:r=this._x_anchor,y_anchor:c=this._y_anchor}=this.position;return{x:h-(()=>{if((0,a.isNumber)(r))return r*i;switch(r){case\"left\":return 0;case\"center\":return.5*i;case\"right\":return i}})(),y:o-(()=>{var t;if((0,a.isNumber)(c))return c*n;switch(c){case\"top\":return 0;case\"center\":return.5*n;case\"bottom\":return n;case\"baseline\":if(1!=s)return.5*n;switch(null!==(t=this.text_height_metric)&&void 0!==t?t:this.infer_text_height()){case\"x\":case\"x_descent\":return e.x_height;case\"cap\":case\"cap_descent\":return e.cap_height;case\"ascent\":case\"ascent_descent\":return e.ascent}}})()}}_rect(){const{width:t,height:e,metrics:s}=this._size(),i=this.text.split(\"\\n\").length,{x:n,y:o}=this._computed_position({width:t,height:e},s,i);return new h.BBox({x:n,y:o,width:t,height:e}).rect}paint(t){var e,i;const{font:n}=this,h=(0,o.font_metrics)(n),a=(this.line_height-1)*h.height,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,n))),x=this._text_line(h),u=x.height*_,p=\"%\"==(null===(e=this.width)||void 0===e?void 0:e.unit)?this.width.value:1,f=\"%\"==(null===(i=this.height)||void 0===i?void 0:i.unit)?this.height.value:1,g=(0,r.max)(l)*p,d=(u+a*(_-1))*f;t.save(),t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\";const{sx:b,sy:m}=this.position,{align:y}=this,{angle:w}=this;w&&(t.translate(b,m),t.rotate(w),t.translate(-b,-m));let{x:v,y:z}=this._computed_position({width:g,height:d},h,_);if(\"justify\"==y)for(let e=0;e<_;e++){let i=v;const h=c[e].split(\" \"),o=h.length,_=h.map((t=>(0,s.text_width)(t,n))),l=(g-(0,r.sum)(_))/(o-1);for(let e=0;e{switch(y){case\"left\":return 0;case\"center\":return.5*(g-l[e]);case\"right\":return g-l[e]}})();t.fillStyle=this.color,t.fillText(c[e],s,z+x.ascent),z+=x.height+a}t.restore()}}s.TextBox=x,x.__name__=\"TextBox\";class u extends l{constructor(t,e){super(),this.base=t,this.expo=e}get children(){return[this.base,this.expo]}set base_font_size(t){super.base_font_size=t,this.base.base_font_size=t,this.expo.base_font_size=t}set position(t){this._position=t;const e=this.base.size(),s=this.expo.size(),i=this._shift_scale()*e.height,n=Math.max(e.height,i+s.height);this.base.position={sx:0,x_anchor:\"left\",sy:n,y_anchor:\"bottom\"},this.expo.position={sx:e.width,x_anchor:\"left\",sy:i,y_anchor:\"bottom\"}}get position(){return this._position}set visuals(t){this.expo.font_size_scale=.7,this.base.visuals=t,this.expo.visuals=t}_shift_scale(){if(this.base instanceof x&&1==this.base.nlines){const{x_height:t,cap_height:e}=(0,o.font_metrics)(this.base.font);return t/e}return 2/3}infer_text_height(){return this.base.infer_text_height()}_rect(){const t=this.base.bbox(),e=this.expo.bbox(),s=t.union(e),{x:i,y:n}=this._computed_position();return s.translate(i,n).rect}_size(){const t=this.base.size(),e=this.expo.size();return{width:t.width+e.width,height:Math.max(t.height,this._shift_scale()*t.height+e.height)}}paint(t){t.save();const{angle:e}=this;if(e){const{sx:s,sy:i}=this.position;t.translate(s,i),t.rotate(e),t.translate(-s,-i)}const{x:s,y:i}=this._computed_position();t.translate(s,i),this.base.paint(t),this.expo.paint(t),t.restore()}paint_bbox(t){super.paint_bbox(t);const{x:e,y:s}=this._computed_position();t.save(),t.translate(e,s);for(const e of this.children)e.paint_bbox(t);t.restore()}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:h=this._y_anchor}=this.position;return{x:s-(()=>{if((0,a.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,a.isNumber)(h))return h*e;switch(h){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}}s.BaseExpo=u,u.__name__=\"BaseExpo\";class p{constructor(t){this.items=t}set base_font_size(t){for(const e of this.items)e.base_font_size=t}get length(){return this.items.length}set visuals(t){for(const e of this.items)e.visuals=t;const e={x:0,cap:1,ascent:2,x_descent:3,cap_descent:4,ascent_descent:5},s=(0,r.max_by)(this.items.map((t=>t.infer_text_height())),(t=>e[t]));for(const t of this.items)t.text_height_metric=s}set angle(t){for(const e of this.items)e.angle=t}max_size(){let t=0,e=0;for(const s of this.items){const i=s.size();t=Math.max(t,i.width),e=Math.max(e,i.height)}return{width:t,height:e}}}s.GraphicsBoxes=p,p.__name__=\"GraphicsBoxes\"},\n", - " function _(t,e,n,r,l){r();const a=t(11),c=(()=>{try{return\"undefined\"!=typeof OffscreenCanvas&&null!=new OffscreenCanvas(0,0).getContext(\"2d\")}catch(t){return!1}})()?(t,e)=>new OffscreenCanvas(t,e):(t,e)=>{const n=document.createElement(\"canvas\");return n.width=t,n.height=e,n},o=(()=>{const t=c(0,0).getContext(\"2d\");return e=>{t.font=e;const n=t.measureText(\"M\"),r=t.measureText(\"x\"),l=t.measureText(\"\\xc5\\u015ag|\"),c=l.fontBoundingBoxAscent,o=l.fontBoundingBoxDescent;if(null!=c&&null!=o)return{height:c+o,ascent:c,descent:o,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};const s=l.actualBoundingBoxAscent,u=l.actualBoundingBoxDescent;if(null!=s&&null!=u)return{height:s+u,ascent:s,descent:u,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};(0,a.unreachable)()}})(),s=(()=>{const t=c(0,0).getContext(\"2d\");return(e,n)=>{t.font=n;const r=t.measureText(e),l=r.actualBoundingBoxAscent,c=r.actualBoundingBoxDescent;if(null!=l&&null!=c)return{width:r.width,height:l+c,ascent:l,descent:c};(0,a.unreachable)()}})(),u=(()=>{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a=1)=>{e.font=l;const{width:c}=e.measureText(\"M\"),o=c*a,s=Math.ceil(o),u=Math.ceil(2*o),i=Math.ceil(1.5*o);n{let e=0;for(let n=0;n<=i;n++)for(let r=0;r{let e=t.length-4;for(let n=u;n>=i;n--)for(let r=0;r{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a,c=1)=>{e.font=a;const{width:o}=e.measureText(\"M\"),s=o*c,u=Math.ceil(s),i=Math.ceil(2*s),f=Math.ceil(1.5*s);(n{let e=0;for(let n=0;n<=f;n++)for(let r=0;r{let e=t.length-4;for(let n=i;n>=f;n--)for(let r=0;r{try{return o(\"normal 10px sans-serif\"),o}catch(t){return u}})(),h=(()=>{try{return s(\"A\",\"normal 10px sans-serif\"),s}catch(t){return i}})(),g=new Map;function d(t){let e=g.get(t);return null==e&&(e={font:f(t),glyphs:new Map},g.set(t,e)),e.font}n.font_metrics=d,n.glyph_metrics=function(t,e){let n=g.get(e);null==n&&(d(e),n=g.get(e));let r=n.glyphs.get(t);return null==r&&(r=h(t,e),n.glyphs.set(t,r)),r},n.parse_css_font_size=function(t){const e=t.match(/^\\s*(\\d+(\\.\\d+)?)(\\w+)\\s*$/);if(null!=e){const[,t,,n]=e,r=Number(t);if(isFinite(r))return{value:r,unit:n}}return null}},\n", - " function _(t,s,r,n,i){n();const{sin:e,cos:a}=Math;class h{constructor(t=1,s=0,r=0,n=1,i=0,e=0){this.a=t,this.b=s,this.c=r,this.d=n,this.e=i,this.f=e}toString(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return`matrix(${t}, ${s}, ${r}, ${n}, ${i}, ${e})`}static from_DOMMatrix(t){const{a:s,b:r,c:n,d:i,e,f:a}=t;return new h(s,r,n,i,e,a)}to_DOMMatrix(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new DOMMatrix([t,s,r,n,i,e])}clone(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new h(t,s,r,n,i,e)}get is_identity(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return 1==t&&0==s&&0==r&&1==n&&0==i&&0==e}apply_point(t){const[s,r]=this.apply(t.x,t.y);return{x:s,y:r}}apply_rect(t){return{p0:this.apply_point(t.p0),p1:this.apply_point(t.p1),p2:this.apply_point(t.p2),p3:this.apply_point(t.p3)}}apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this;return[r*t+i*s+a,n*t+e*s+h]}iv_apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this,c=t.length;for(let o=0;o{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=n&&\"fixed\"!=s)if(n==s){const n=t,s=_(t/e),r=_(h*e),g=h;Math.abs(i.width-n)+Math.abs(i.height-s)<=Math.abs(i.width-r)+Math.abs(i.height-g)?(t=n,h=s):(t=r,h=g)}else r(n,s)?h=_(t/e):t=_(h*e);else\"fixed\"==n?h=_(t/e):\"fixed\"==s&&(t=_(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,e=new s.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(e),r=this.clip_size(n,e),g=t(r.width),l=h(r.height),a=this.apply_aspect(e,{width:g,height:l});return Object.assign(Object.assign({},n),a)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new r.BBox({left:0,top:0,width:h,height:e});let s;if(null!=t.inner){const{left:i,top:n,right:g,bottom:l}=t.inner;s=new r.BBox({left:i,top:n,right:h-g,bottom:e-l})}this.set_geometry(n,s)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_size(i,t){function h(i,t,h,e){return null==h?h=0:(0,g.isNumber)(h)||(h=Math.round(h.percent*t)),null==e?e=1/0:(0,g.isNumber)(e)||(e=Math.round(e.percent*t)),a(h,l(i,e))}return{width:h(i.width,t.width,this.sizing.min_width,this.sizing.max_width),height:h(i.height,t.height,this.sizing.min_height,this.sizing.max_height)}}has_size_changed(){const{_dirty:i}=this;return this._dirty=!1,i}}h.Layoutable=o,o.__name__=\"Layoutable\";class d extends o{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;return{width:(()=>{const{width:h}=this.sizing;if(i.width==1/0)return null!=h?h:0;switch(t){case\"fixed\":return null!=h?h:0;case\"min\":return null!=h?l(i.width,h):0;case\"fit\":return null!=h?l(i.width,h):i.width;case\"max\":return null!=h?a(i.width,h):i.width}})(),height:(()=>{const{height:t}=this.sizing;if(i.height==1/0)return null!=t?t:0;switch(h){case\"fixed\":return null!=t?t:0;case\"min\":return null!=t?l(i.height,t):0;case\"fit\":return null!=t?l(i.height,t):i.height;case\"max\":return null!=t?a(i.height,t):i.height}})()}}}h.LayoutItem=d,d.__name__=\"LayoutItem\";class u extends o{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=u,u.__name__=\"ContentLayoutable\"},\n", - " function _(e,t,s,a,_){a();const r=e(62),n=e(61),g=e(58),i=e(63),c=e(67),h=e(65),l=e(13),o=e(11);class x{constructor(e,t,s,a,_={},r={},n={},g={}){this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=a,this.extra_x_ranges=_,this.extra_y_ranges=r,this.extra_x_scales=n,this.extra_y_scales=g,this._bbox=new h.BBox,(0,o.assert)(null==e.source_range&&null==e.target_range),(0,o.assert)(null==t.source_range&&null==t.target_range),this._configure_scales()}get bbox(){return this._bbox}_get_ranges(e,t){return new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s,a){var _;const g=new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e}))),h=new Map;for(const[t,l]of s){if(l instanceof c.FactorRange!=e instanceof r.CategoricalScale)throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&l instanceof i.DataRange1d&&(l.scale_hint=\"log\");const s=(null!==(_=g.get(t))&&void 0!==_?_:e).clone();s.setv({source_range:l,target_range:a}),h.set(t,s)}return h}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new g.Range1d({start:e.left,end:e.right}),this._y_target=new g.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this.extra_x_scales,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this.extra_y_scales,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}set_geometry(e){this._bbox=e,this._update_scales()}get x_target(){return this._x_target}get y_target(){return this._y_target}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return(0,l.to_object)(this.x_scales)}get yscales(){return(0,l.to_object)(this.y_scales)}}s.CartesianFrame=x,x.__name__=\"CartesianFrame\"},\n", - " function _(i,s,x,A,o){A(),o(\"Axis\",i(128).Axis),o(\"CategoricalAxis\",i(140).CategoricalAxis),o(\"ContinuousAxis\",i(143).ContinuousAxis),o(\"DatetimeAxis\",i(144).DatetimeAxis),o(\"LinearAxis\",i(145).LinearAxis),o(\"LogAxis\",i(162).LogAxis),o(\"MercatorAxis\",i(165).MercatorAxis)},\n", - " function _(t,e,i,s,a){s();const o=t(1);var l;const n=t(129),_=t(130),r=t(131),h=t(132),c=(0,o.__importStar)(t(48)),b=t(20),u=t(24),m=t(123),d=t(9),x=t(13),f=t(8),g=t(120),p=t(67),v=t(133),w=t(113),j=t(11),k=t(8),y=t(134),{abs:z}=Math;class M extends n.GuideRendererView{constructor(){super(...arguments),this._axis_label_view=null,this._major_label_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this._init_axis_label(),await this._init_major_labels()}async _init_axis_label(){const{axis_label:t}=this.model;if(null!=t){const e=(0,k.isString)(t)?(0,y.parse_delimited_string)(t):t;this._axis_label_view=await(0,w.build_view)(e,{parent:this})}else this._axis_label_view=null}async _init_major_labels(){const{major_label_overrides:t}=this.model;for(const[e,i]of(0,x.entries)(t)){const t=(0,k.isString)(i)?(0,y.parse_delimited_string)(i):i;this._major_label_views.set(e,await(0,w.build_view)(t,{parent:this}))}}update_layout(){this.layout=new m.SideLayout(this.panel,(()=>this.get_size()),!0),this.layout.on_resize((()=>this._coordinates=void 0))}get_size(){const{visible:t,fixed_location:e}=this.model;if(t&&null==e&&this.is_renderable){const{extents:t}=this;return{width:0,height:Math.round(t.tick+t.tick_label+t.axis_label)}}return{width:0,height:0}}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const{tick_coords:e,extents:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,i),this._draw_major_ticks(s,i,e),this._draw_minor_ticks(s,i,e),this._draw_major_labels(s,i,e),this._draw_axis_label(s,i,e),null===(t=this._paint)||void 0===t||t.call(this,s,i,e),s.restore()}connect_signals(){super.connect_signals();const{axis_label:t,major_label_overrides:e}=this.model.properties;this.on_change(t,(async()=>{var t;null===(t=this._axis_label_view)||void 0===t||t.remove(),await this._init_axis_label()})),this.on_change(e,(async()=>{for(const t of this._major_label_views.values())t.remove();await this._init_major_labels()})),this.connect(this.model.change,(()=>this.plot_view.request_layout()))}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[a,o]=this.coordinates.map_to_screen(i,s),[l,n]=this.normals,[_,r]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath();for(let e=0;e0?s+i+3:0}_draw_axis_label(t,e,i){if(null==this._axis_label_view||null!=this.model.fixed_location)return;const[s,a]=(()=>{const{bbox:t}=this.layout;switch(this.panel.side){case\"above\":return[t.hcenter,t.bottom];case\"below\":return[t.hcenter,t.top];case\"left\":return[t.right,t.vcenter];case\"right\":return[t.left,t.vcenter]}})(),[o,l]=this.normals,n=e.tick+e.tick_label+this.model.axis_label_standoff,{vertical_align:_,align:r}=this.panel.get_label_text_heuristics(\"parallel\"),h={sx:s+o*n,sy:a+l*n,x_anchor:r,y_anchor:_},c=this._axis_label_view.graphics();c.visuals=this.visuals.axis_label_text.values(),c.angle=this.panel.get_label_angle_heuristic(\"parallel\"),this.plot_view.base_font_size&&(c.base_font_size=this.plot_view.base_font_size),c.position=h,c.align=r,c.paint(t)}_draw_ticks(t,e,i,s,a){if(!a.doit)return;const[o,l]=e,[n,_]=this.coordinates.map_to_screen(o,l),[r,h]=this.normals,[c,b]=this.offsets,[u,m]=[r*(c-i),h*(b-i)],[d,x]=[r*(c+s),h*(b+s)];a.set_value(t),t.beginPath();for(let e=0;et.bbox())),M=(()=>{const[t]=this.ranges;return t.is_reversed?0==this.dimension?(t,e)=>z[t].left-z[e].right:(t,e)=>z[e].top-z[t].bottom:0==this.dimension?(t,e)=>z[e].left-z[t].right:(t,e)=>z[t].top-z[e].bottom})(),{major_label_policy:O}=this.model,T=O.filter(k,z,M),A=[...T.ones()];if(0!=A.length){const t=this.parent.canvas_view.bbox,e=e=>{const i=z[e];if(i.left<0){const t=-i.left,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sx:s.sx+t})}else if(i.right>t.width){const s=i.right-t.width,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sx:a.sx-s})}},i=e=>{const i=z[e];if(i.top<0){const t=-i.top,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sy:s.sy+t})}else if(i.bottom>t.height){const s=i.bottom-t.height,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sy:a.sy-s})}},s=A[0],a=A[A.length-1];0==this.dimension?(e(s),e(a)):(i(s),i(a))}for(const e of T){y[e].paint(t)}}_tick_extent(){return this.model.major_tick_out}_tick_label_extents(){const t=this.tick_coords.major,e=this.compute_labels(t[this.dimension]),i=this.model.major_label_orientation,s=this.model.major_label_standoff,a=this.visuals.major_label_text;return[this._oriented_labels_extent(e,i,s,a)]}get extents(){const t=this._tick_label_extents();return{tick:this._tick_extent(),tick_labels:t,tick_label:(0,d.sum)(t),axis_label:this._axis_label_extent()}}_oriented_labels_extent(t,e,i,s){if(0==t.length||!s.doit)return 0;const a=this.panel.get_label_angle_heuristic(e);t.visuals=s.values(),t.angle=a,t.base_font_size=this.plot_view.base_font_size;const o=t.max_size(),l=0==this.dimension?o.height:o.width;return l>0?i+l+3:0}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.format_graphics(t,this),{_major_label_views:i}=this,s=new Set;for(let a=0;az(l-n)?(t=r(_(a,o),l),s=_(r(a,o),n)):(t=_(a,o),s=r(a,o)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=[new Array(2),new Array(2)];return o[t][0]=Math.max(s,i.min),o[t][1]=Math.min(a,i.max),o[t][0]>o[t][1]&&(o[t][0]=o[t][1]=NaN),o[e][0]=this.loc,o[e][1]=this.loc,o}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=this.model.ticker.get_ticks(s,a,i,this.loc),l=o.major,n=o.minor,_=[[],[]],r=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(_[t].push(l[i]),_[e].push(this.loc));for(let i=0;ic||(r[t].push(n[i]),r[e].push(this.loc));return{major:_,minor:r}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if((0,f.isNumber)(t))return t;const[,e]=this.ranges;if(e instanceof p.FactorRange)return e.synthetic(t);(0,j.unreachable)()}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}remove(){var t;null===(t=this._axis_label_view)||void 0===t||t.remove();for(const t of this._major_label_views.values())t.remove();super.remove()}has_finished(){if(!super.has_finished())return!1;if(null!=this._axis_label_view&&!this._axis_label_view.has_finished())return!1;for(const t of this._major_label_views.values())if(!t.has_finished())return!1;return!0}}i.AxisView=M,M.__name__=\"AxisView\";class O extends n.GuideRenderer{constructor(t){super(t)}}i.Axis=O,l=O,O.__name__=\"Axis\",l.prototype.default_view=M,l.mixins([[\"axis_\",c.Line],[\"major_tick_\",c.Line],[\"minor_tick_\",c.Line],[\"major_label_\",c.Text],[\"axis_label_\",c.Text]]),l.define((({Any:t,Int:e,Number:i,String:s,Ref:a,Dict:o,Tuple:l,Or:n,Nullable:c,Auto:u})=>({bounds:[n(l(i,i),u),\"auto\"],ticker:[a(_.Ticker)],formatter:[a(r.TickFormatter)],axis_label:[c(n(s,a(v.BaseText))),null],axis_label_standoff:[e,5],major_label_standoff:[e,5],major_label_orientation:[n(b.TickLabelOrientation,i),\"horizontal\"],major_label_overrides:[o(n(s,a(v.BaseText))),{}],major_label_policy:[a(h.LabelingPolicy),()=>new h.AllLabels],major_tick_in:[i,2],major_tick_out:[i,6],minor_tick_in:[i,0],minor_tick_out:[i,4],fixed_location:[c(n(i,t)),null]}))),l.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})},\n", - " function _(e,r,d,n,i){var s;n();const _=e(41);class u extends _.RendererView{}d.GuideRendererView=u,u.__name__=\"GuideRendererView\";class c extends _.Renderer{constructor(e){super(e)}}d.GuideRenderer=c,s=c,c.__name__=\"GuideRenderer\",s.override({level:\"guide\"})},\n", - " function _(c,e,n,s,o){s();const r=c(53);class t extends r.Model{constructor(c){super(c)}}n.Ticker=t,t.__name__=\"Ticker\"},\n", - " function _(t,o,r,e,c){e();const n=t(53),a=t(120);class m extends n.Model{constructor(t){super(t)}format_graphics(t,o){return this.doFormat(t,o).map((t=>new a.TextBox({text:t})))}compute(t,o){return this.doFormat([t],null!=o?o:{loc:0})[0]}v_compute(t,o){return this.doFormat(t,null!=o?o:{loc:0})}}r.TickFormatter=m,m.__name__=\"TickFormatter\"},\n", - " function _(e,n,s,t,i){var c,r;t();const l=e(53),o=e(13),a=e(34),u=e(8),d=e(24);class _ extends l.Model{constructor(e){super(e)}}s.LabelingPolicy=_,_.__name__=\"LabelingPolicy\";class f extends _{constructor(e){super(e)}filter(e,n,s){return e}}s.AllLabels=f,f.__name__=\"AllLabels\";class m extends _{constructor(e){super(e)}filter(e,n,s){const{min_distance:t}=this;let i=null;for(const n of e)null!=i&&s(i,n)({min_distance:[e,5]})));class b extends _{constructor(e){super(e)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}get func(){const e=(0,a.use_strict)(this.code);return new d.GeneratorFunction(\"indices\",\"bboxes\",\"distance\",...this.names,e)}filter(e,n,s){const t=Object.create(null),i=this.func.call(t,e,n,s,...this.values);let c=i.next();if(c.done&&void 0!==c.value){const{value:n}=c;return n instanceof d.Indices?n:void 0===n?e:(0,u.isIterable)(n)?d.Indices.from_indices(e.size,n):d.Indices.all_unset(e.size)}{const n=[];do{n.push(c.value),c=i.next()}while(!c.done);return d.Indices.from_indices(e.size,n)}}}s.CustomLabelingPolicy=b,r=b,b.__name__=\"CustomLabelingPolicy\",r.define((({Unknown:e,String:n,Dict:s})=>({args:[s(e),{}],code:[n,\"\"]})))},\n", - " function _(e,s,t,n,a){var _;n();const x=e(53),c=e(42);class i extends c.View{}t.BaseTextView=i,i.__name__=\"BaseTextView\";class o extends x.Model{constructor(e){super(e)}}t.BaseText=o,_=o,o.__name__=\"BaseText\",_.define((({String:e})=>({text:[e]})))},\n", - " function _(n,e,t,i,r){i();const s=n(135),l=n(139),d=[{start:\"$$\",end:\"$$\",inline:!1},{start:\"\\\\[\",end:\"\\\\]\",inline:!1},{start:\"\\\\(\",end:\"\\\\)\",inline:!0}];t.parse_delimited_string=function(n){for(const e of d){const t=n.indexOf(e.start),i=t+e.start.length;if(0==t){const t=n.indexOf(e.end,i),r=t;if(t==n.length-e.end.length)return new s.TeX({text:n.slice(i,r),inline:e.inline});break}}return new l.PlainText({text:n})}},\n", - " function _(t,e,s,i,n){var o,r,a;i();const h=t(8),_=t(136),l=t(22),c=t(120),d=t(121),u=t(122),g=t(65),p=t(133),x=t(137);class m extends p.BaseTextView{constructor(){super(...arguments),this._position={sx:0,sy:0},this.align=\"left\",this._x_anchor=\"left\",this._y_anchor=\"center\",this._base_font_size=13,this.font_size_scale=1,this.svg_image=null}graphics(){return this}infer_text_height(){return\"ascent_descent\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}get has_image_loaded(){return null!=this.svg_image}_rect(){const{width:t,height:e}=this._size(),{x:s,y:i}=this._computed_position();return new g.BBox({x:s,y:i,width:t,height:e}).rect}set position(t){this._position=t}get position(){return this._position}get text(){return this.model.text}get provider(){return x.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>this.load_image())),\"loaded\"==this.provider.status&&await this.load_image()}connect_signals(){super.connect_signals(),this.on_change(this.model.properties.text,(()=>this.load_image()))}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const o=t.font,{font_size_scale:r,_base_font_size:a}=this,h=(0,d.parse_css_font_size)(n);if(null!=h){let{value:t,unit:e}=h;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const _=`${i} ${n} ${o}`;this.font=_,this.color=(0,l.color2css)(e,s)}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:o=this._y_anchor}=this.position;return{x:s-(()=>{if((0,h.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,h.isNumber)(o))return o*e;switch(o){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}get_text_dimensions(){return{width:(0,c.text_width)(this.model.text,this.font),height:(0,d.font_metrics)(this.font).height}}get_image_dimensions(){var t,e,s,i;const n=parseFloat(null!==(e=null===(t=this.svg_element.getAttribute(\"height\"))||void 0===t?void 0:t.replace(/([A-z])/g,\"\"))&&void 0!==e?e:\"0\"),o=parseFloat(null!==(i=null===(s=this.svg_element.getAttribute(\"width\"))||void 0===s?void 0:s.replace(/([A-z])/g,\"\"))&&void 0!==i?i:\"0\");return{width:(0,d.font_metrics)(this.font).x_height*o,height:(0,d.font_metrics)(this.font).x_height*n}}_size(){return this.has_image_loaded?this.get_image_dimensions():this.get_text_dimensions()}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new g.BBox({left:n,right:r,top:o,bottom:a})}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new u.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e.x),o(e.y)),t.lineTo(o(s.x),o(s.y)),t.lineTo(o(i.x),o(i.y)),t.lineTo(o(n.x),o(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e),o(s)),t.lineTo(o(e),o(s+n)),t.lineTo(o(e+i),o(s+n)),t.lineTo(o(e+i),o(s)),t.closePath(),t.stroke(),t.restore()}async load_image(){if(null==this.provider.MathJax)return null;const t=this._process_text(this.model.text);if(null==t)return this._has_finished=!0,null;const e=t.children[0];this.svg_element=e,e.setAttribute(\"font\",this.font),e.setAttribute(\"stroke\",this.color);const s=e.outerHTML,i=new Blob([s],{type:\"image/svg+xml\"}),n=URL.createObjectURL(i);try{this.svg_image=await(0,_.load_image)(n)}finally{URL.revokeObjectURL(n)}return this.parent.request_layout(),this.svg_image}paint(t){t.save();const{sx:e,sy:s}=this.position;this.angle&&(t.translate(e,s),t.rotate(this.angle),t.translate(-e,-s));const{x:i,y:n}=this._computed_position();if(null!=this.svg_image){const{width:e,height:s}=this.get_image_dimensions();t.drawImage(this.svg_image,i,n,e,s)}else t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\",t.fillText(this.model.text,i,n+(0,d.font_metrics)(this.font).ascent);t.restore(),this._has_finished||\"failed\"!=this.provider.status&&!this.has_image_loaded||(this._has_finished=!0,this.parent.notify_finished_after_paint())}}s.MathTextView=m,m.__name__=\"MathTextView\";class f extends p.BaseText{constructor(t){super(t)}}s.MathText=f,f.__name__=\"MathText\";class v extends m{_process_text(t){}}s.AsciiView=v,v.__name__=\"AsciiView\";class y extends f{constructor(t){super(t)}}s.Ascii=y,o=y,y.__name__=\"Ascii\",o.prototype.default_view=v;class w extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.mathml2svg(t.trim())}}s.MathMLView=w,w.__name__=\"MathMLView\";class b extends f{constructor(t){super(t)}}s.MathML=b,r=b,b.__name__=\"MathML\",r.prototype.default_view=w;class M extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.tex2svg(t,void 0,this.model.macros)}}s.TeXView=M,M.__name__=\"TeXView\";class T extends f{constructor(t){super(t)}}s.TeX=T,a=T,T.__name__=\"TeX\",a.prototype.default_view=M,a.define((({Boolean:t,Number:e,String:s,Dict:i,Tuple:n,Or:o})=>({macros:[i(o(s,n(s,e))),{}],inline:[t,!1]})))},\n", - " function _(i,e,t,s,o){s();const a=i(19);t.load_image=async function(i,e){return new n(i,e).promise};class n{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:s=1}=e;this.promise=new Promise(((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const s=`unable to load ${i} image after ${t} attempts`;if(a.logger.warn(s),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());a.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout((()=>this._image.src=i),s)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i}))}get finished(){return this._finished}get image(){if(this._finished)return this._image;throw new Error(\"not loaded yet\")}}t.ImageLoader=n,n.__name__=\"ImageLoader\"},\n", - " function _(t,e,a,s,n){var r=this&&this.__createBinding||(Object.create?function(t,e,a,s){void 0===s&&(s=a),Object.defineProperty(t,s,{enumerable:!0,get:function(){return e[a]}})}:function(t,e,a,s){void 0===s&&(s=a),t[s]=e[a]}),i=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),d=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var a in t)\"default\"!==a&&Object.prototype.hasOwnProperty.call(t,a)&&r(e,t,a);return i(e,t),e};s();const o=t(15),u=t(138);class c{constructor(){this.ready=new o.Signal0(this,\"ready\"),this.status=\"not_started\"}}a.MathJaxProvider=c,c.__name__=\"MathJaxProvider\";class h extends c{get MathJax(){return null}async fetch(){this.status=\"failed\"}}a.NoProvider=h,h.__name__=\"NoProvider\";class l extends c{get MathJax(){return\"undefined\"!=typeof MathJax?MathJax:null}async fetch(){const t=document.createElement(\"script\");t.src=\"https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-svg.js\",t.onload=()=>{this.status=\"loaded\",this.ready.emit()},t.onerror=()=>{this.status=\"failed\"},this.status=\"loading\",document.head.appendChild(t)}}a.CDNProvider=l,l.__name__=\"CDNProvider\";class _ extends c{get MathJax(){return this._mathjax}async fetch(){this.status=\"loading\";try{const e=await(0,u.load_module)(Promise.resolve().then((()=>d(t(519)))));this._mathjax=e,this.status=\"loaded\",this.ready.emit()}catch(t){this.status=\"failed\"}}}a.BundleProvider=_,_.__name__=\"BundleProvider\",a.default_provider=new _},\n", - " function _(n,r,o,t,c){t(),o.load_module=async function(n){try{return await n}catch(n){if((r=n)instanceof Error&&\"code\"in r&&\"MODULE_NOT_FOUND\"===n.code)return null;throw n}var r}},\n", - " function _(e,t,i,n,s){var a;n();const x=e(133),_=e(120);class l extends x.BaseTextView{initialize(){super.initialize(),this._has_finished=!0}graphics(){return new _.TextBox({text:this.model.text})}}i.PlainTextView=l,l.__name__=\"PlainTextView\";class r extends x.BaseText{constructor(e){super(e)}}i.PlainText=r,a=r,r.__name__=\"PlainText\",a.prototype.default_view=l},\n", - " function _(t,s,o,e,i){e();const r=t(1);var a;const l=t(128),_=t(141),n=t(142),p=(0,r.__importStar)(t(48)),c=t(20),h=t(120),m=t(8);class u extends l.AxisView{_paint(t,s,o){this._draw_group_separators(t,s,o)}_draw_group_separators(t,s,o){const[e]=this.ranges,[i,r]=this.computed_bounds;if(!e.tops||e.tops.length<2||!this.visuals.separator_line.doit)return;const a=this.dimension,l=(a+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&pnew h.GraphicsBoxes(t.map((t=>(0,m.isString)(t)?new h.TextBox({text:t}):t))),_=t=>l(this.model.formatter.doFormat(t,this));if(1==t.levels){const t=_(i.major);a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text])}else if(2==t.levels){const t=_(i.major.map((t=>t[1])));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=_(i.major.map((t=>t[2]))),s=i.mids.map((t=>t[1]));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(s),r.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}return a}get tick_coords(){const t=this.dimension,s=(t+1)%2,[o]=this.ranges,[e,i]=this.computed_bounds,r=this.model.ticker.get_ticks(e,i,o,this.loc),a={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return a.major[t]=r.major,a.major[s]=r.major.map((()=>this.loc)),3==o.levels&&(a.mids[t]=r.mids,a.mids[s]=r.mids.map((()=>this.loc))),o.levels>1&&(a.tops[t]=r.tops,a.tops[s]=r.tops.map((()=>this.loc))),a}}o.CategoricalAxisView=u,u.__name__=\"CategoricalAxisView\";class d extends l.Axis{constructor(t){super(t)}}o.CategoricalAxis=d,a=d,d.__name__=\"CategoricalAxis\",a.prototype.default_view=u,a.mixins([[\"separator_\",p.Line],[\"group_\",p.Text],[\"subgroup_\",p.Text]]),a.define((({Number:t,Or:s})=>({group_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"],subgroup_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"]}))),a.override({ticker:()=>new _.CategoricalTicker,formatter:()=>new n.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})},\n", - " function _(t,c,o,s,e){s();const r=t(130);class i extends r.Ticker{constructor(t){super(t)}get_ticks(t,c,o,s){var e,r;return{major:this._collect(o.factors,o,t,c),minor:[],tops:this._collect(null!==(e=o.tops)&&void 0!==e?e:[],o,t,c),mids:this._collect(null!==(r=o.mids)&&void 0!==r?r:[],o,t,c)}}_collect(t,c,o,s){const e=[];for(const r of t){const t=c.synthetic(r);t>o&&tnew _.DatetimeTicker,formatter:()=>new m.DatetimeTickFormatter})},\n", - " function _(e,i,s,n,r){var t;n();const a=e(143),o=e(146),c=e(147);class _ extends a.ContinuousAxisView{}s.LinearAxisView=_,_.__name__=\"LinearAxisView\";class u extends a.ContinuousAxis{constructor(e){super(e)}}s.LinearAxis=u,t=u,u.__name__=\"LinearAxis\",t.prototype.default_view=_,t.override({ticker:()=>new c.BasicTicker,formatter:()=>new o.BasicTickFormatter})},\n", - " function _(i,t,e,n,o){var r;n();const s=i(131),c=i(34);function _(i){let t=\"\";for(const e of i)t+=\"-\"==e?\"\\u2212\":e;return t}e.unicode_replace=_;class a extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 10**this.power_limit_high}_need_sci(i){if(!this.use_scientific)return!1;const{scientific_limit_high:t}=this,{scientific_limit_low:e}=this,n=i.length<2?0:Math.abs(i[1]-i[0])/1e4;for(const o of i){const i=Math.abs(o);if(!(i<=n)&&(i>=t||i<=e))return!0}return!1}_format_with_precision(i,t,e){return t?i.map((i=>_(i.toExponential(e)))):i.map((i=>_((0,c.to_fixed)(i,e))))}_auto_precision(i,t){const e=new Array(i.length),n=this.last_precision<=15;i:for(let o=this.last_precision;n?o<=15:o>=1;n?o++:o--){if(t){e[0]=i[0].toExponential(o);for(let t=1;t({precision:[n(t,e),\"auto\"],use_scientific:[i,!0],power_limit_high:[t,5],power_limit_low:[t,-3]})))},\n", - " function _(c,e,s,i,n){i();const r=c(148);class t extends r.AdaptiveTicker{constructor(c){super(c)}}s.BasicTicker=t,t.__name__=\"BasicTicker\"},\n", - " function _(t,i,a,s,e){var n;s();const r=t(149),_=t(9),l=t(10);class h extends r.ContinuousTicker{constructor(t){super(t)}get_min_interval(){return this.min_interval}get_max_interval(){var t;return null!==(t=this.max_interval)&&void 0!==t?t:1/0}initialize(){super.initialize();const t=(0,_.nth)(this.mantissas,-1)/this.base,i=(0,_.nth)(this.mantissas,0)*this.base;this.extended_mantissas=[t,...this.mantissas,i],this.base_factor=0===this.get_min_interval()?1:this.get_min_interval()}get_interval(t,i,a){const s=i-t,e=this.get_ideal_interval(t,i,a),n=Math.floor((0,l.log)(e/this.base_factor,this.base)),r=this.base**n*this.base_factor,h=this.extended_mantissas,m=h.map((t=>Math.abs(a-s/(t*r)))),v=h[(0,_.argmin)(m)]*r;return(0,l.clamp)(v,this.get_min_interval(),this.get_max_interval())}}a.AdaptiveTicker=h,n=h,h.__name__=\"AdaptiveTicker\",n.define((({Number:t,Array:i,Nullable:a})=>({base:[t,10],mantissas:[i(t),[1,2,5]],min_interval:[t,0],max_interval:[a(t),null]})))},\n", - " function _(t,n,i,s,e){var o;s();const r=t(130),c=t(9);class _ extends r.Ticker{constructor(t){super(t)}get_ticks(t,n,i,s){return 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c.AdaptiveTicker({mantissas:[1,2,4,6,8,12],base:24,min_interval:T.ONE_HOUR,max_interval:12*T.ONE_HOUR,num_minor_ticks:0}),new _.DaysTicker({days:(0,t.range)(1,32)}),new _.DaysTicker({days:(0,t.range)(1,31,3)}),new _.DaysTicker({days:[1,8,15,22]}),new _.DaysTicker({days:[1,15]}),new k.MonthsTicker({months:(0,t.range)(0,12,1)}),new k.MonthsTicker({months:(0,t.range)(0,12,2)}),new k.MonthsTicker({months:(0,t.range)(0,12,4)}),new k.MonthsTicker({months:(0,t.range)(0,12,6)}),new o.YearsTicker({})]})},\n", - " function _(t,e,i,r,s){var n;r();const _=t(149),a=t(9);class l extends _.ContinuousTicker{constructor(t){super(t)}get min_intervals(){return this.tickers.map((t=>t.get_min_interval()))}get max_intervals(){return this.tickers.map((t=>t.get_max_interval()))}get_min_interval(){return this.min_intervals[0]}get_max_interval(){return this.max_intervals[0]}get_best_ticker(t,e,i){const 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s=e(128),c=e(145),n=e(166),_=e(167);class x extends s.AxisView{}t.MercatorAxisView=x,x.__name__=\"MercatorAxisView\";class d extends c.LinearAxis{constructor(e){super(e)}}t.MercatorAxis=d,o=d,d.__name__=\"MercatorAxis\",o.prototype.default_view=x,o.override({ticker:()=>new _.MercatorTicker({dimension:\"lat\"}),formatter:()=>new n.MercatorTickFormatter({dimension:\"lat\"})})},\n", - " function _(r,t,e,o,n){var i;o();const c=r(146),s=r(20),a=r(78);class l extends c.BasicTickFormatter{constructor(r){super(r)}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n({dimension:[r(s.LatLon),null]})))},\n", - " function _(t,o,n,s,r){var e;s();const i=t(147),c=t(20),_=t(78);class a extends i.BasicTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,n,s){if(null==this.dimension)throw new Error(`${this}.dimension wasn't 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c.minor)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);m.push(o)}return{major:a,minor:m}}}n.MercatorTicker=a,e=a,a.__name__=\"MercatorTicker\",e.define((({Nullable:t})=>({dimension:[t(c.LatLon),null]})))},\n", - " function _(e,i,r,c,k){c(),k(\"AdaptiveTicker\",e(148).AdaptiveTicker),k(\"BasicTicker\",e(147).BasicTicker),k(\"CategoricalTicker\",e(141).CategoricalTicker),k(\"CompositeTicker\",e(156).CompositeTicker),k(\"ContinuousTicker\",e(149).ContinuousTicker),k(\"DatetimeTicker\",e(155).DatetimeTicker),k(\"DaysTicker\",e(157).DaysTicker),k(\"FixedTicker\",e(169).FixedTicker),k(\"LogTicker\",e(164).LogTicker),k(\"MercatorTicker\",e(167).MercatorTicker),k(\"MonthsTicker\",e(160).MonthsTicker),k(\"SingleIntervalTicker\",e(158).SingleIntervalTicker),k(\"Ticker\",e(130).Ticker),k(\"YearsTicker\",e(161).YearsTicker),k(\"BinnedTicker\",e(170).BinnedTicker)},\n", - " function _(r,t,e,i,n){var s;i();const _=r(149);class c extends _.ContinuousTicker{constructor(r){super(r)}get_ticks_no_defaults(r,t,e,i){return{major:this.ticks,minor:this.minor_ticks}}get_interval(r,t,e){return 0}get_min_interval(){return 0}get_max_interval(){return 0}}e.FixedTicker=c,s=c,c.__name__=\"FixedTicker\",s.define((({Number:r,Array:t})=>({ticks:[t(r),[]],minor_ticks:[t(r),[]]})))},\n", - " function _(e,n,t,r,i){var o;r();const a=e(130),s=e(171),c=e(12);class m extends a.Ticker{constructor(e){super(e)}get_ticks(e,n,t,r){const{binning:i}=this.mapper.metrics,o=Math.max(0,(0,c.left_edge_index)(e,i)),a=Math.min((0,c.left_edge_index)(n,i)+1,i.length-1),s=[];for(let e=o;e<=a;e++)s.push(i[e]);const{num_major_ticks:m}=this,_=[],h=\"auto\"==m?s.length:m,l=Math.max(1,Math.floor(s.length/h));for(let e=0;e({mapper:[n(s.ScanningColorMapper)],num_major_ticks:[t(e,r),8]})))},\n", - " function _(n,e,i,r,o){r();const t=n(172),a=n(12);class c extends t.ContinuousColorMapper{constructor(n){super(n)}cmap(n,e,i,r,o){if(no.binning[o.binning.length-1])return r;return e[(0,a.left_edge_index)(n,o.binning)]}}i.ScanningColorMapper=c,c.__name__=\"ScanningColorMapper\"},\n", - " function _(t,e,o,n,s){var l;n();const c=t(173),i=t(175),a=t(9),h=t(8);class r extends c.ColorMapper{constructor(t){super(t),this._scan_data=null}connect_signals(){super.connect_signals();const t=()=>{for(const[t]of this.domain)this.connect(t.view.change,(()=>this.update_data())),this.connect(t.data_source.selected.change,(()=>this.update_data()))};this.connect(this.properties.domain.change,(()=>t())),t()}update_data(){const{domain:t,palette:e}=this,o=[...this._collect(t)];this._scan_data=this.scan(o,e.length),this.metrics_change.emit(),this.change.emit()}get metrics(){return null==this._scan_data&&this.update_data(),this._scan_data}*_collect(t){for(const[e,o]of t)for(const t of(0,h.isArray)(o)?o:[o]){let o=e.data_source.get_column(t);o=e.view.indices.select(o);const n=e.view.masked,s=e.data_source.selected.indices;let l;if(null!=n&&s.length>0?l=(0,a.intersection)([...n],s):null!=n?l=[...n]:s.length>0&&(l=s),null!=l&&(o=(0,a.map)(l,(t=>o[t]))),o.length>0&&!(0,h.isNumber)(o[0]))for(const t of o)yield*t;else yield*o}}_v_compute(t,e,o,n){const{nan_color:s}=n;let{low_color:l,high_color:c}=n;null==l&&(l=o[0]),null==c&&(c=o[o.length-1]);const{domain:i}=this,h=(0,a.is_empty)(i)?t:[...this._collect(i)];this._scan_data=this.scan(h,o.length),this.metrics_change.emit();for(let n=0,i=t.length;n({high:[a(t),null],low:[a(t),null],high_color:[a(n),null],low_color:[a(n),null],domain:[c(l(o(i.GlyphRenderer),s(e,c(e)))),[]]})))},\n", - " function _(e,r,t,n,o){var a;n();const c=e(174),i=e(15),_=e(24),l=e(22),s=e(27);function p(e){return(0,l.encode_rgba)((0,l.color2rgba)(e))}function u(e){const r=new Uint32Array(e.length);for(let t=0,n=e.length;te))),r}get rgba_mapper(){const e=this,r=u(this.palette),t=this._colors(p);return{v_compute(n){const o=new _.ColorArray(n.length);return e._v_compute(n,o,r,t),new Uint8ClampedArray((0,s.to_big_endian)(o).buffer)}}}_colors(e){return{nan_color:e(this.nan_color)}}}t.ColorMapper=h,a=h,h.__name__=\"ColorMapper\",a.define((({Color:e,Array:r})=>({palette:[r(e)],nan_color:[e,\"gray\"]})))},\n", - " function _(r,e,n,s,o){s();const p=r(56);class t extends p.Transform{constructor(r){super(r)}compute(r){throw new Error(\"mapping single values is not supported\")}}n.Mapper=t,t.__name__=\"Mapper\"},\n", - " function _(e,t,i,s,l){var h;s();const n=e(176),o=e(177),a=e(186),c=e(187),_=e(189),r=e(179),d=e(70),p=e(190),g=e(24),u=e(12),y=e(13),m=e(113),v=e(67),f={fill:{},line:{}},w={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},b={fill:{fill_alpha:.2},line:{}},V={fill:{fill_alpha:.2},line:{}};class x extends n.DataRendererView{get glyph_view(){return this.glyph}async lazy_initialize(){var e;await super.lazy_initialize();const t=this.model.glyph;this.glyph=await this.build_glyph_view(t);const i=\"fill\"in this.glyph.visuals,s=\"line\"in this.glyph.visuals,l=Object.assign({},t.attributes);function h(e){const h=(0,y.clone)(l);return i&&(0,y.extend)(h,e.fill),s&&(0,y.extend)(h,e.line),new t.constructor(h)}function n(e,t){return t instanceof r.Glyph?t:h(\"auto\"==t?e:{fill:{},line:{}})}delete l.id;let{selection_glyph:o,nonselection_glyph:a,hover_glyph:c,muted_glyph:_}=this.model;o=n(f,o),this.selection_glyph=await this.build_glyph_view(o),a=n(b,a),this.nonselection_glyph=await this.build_glyph_view(a),null!=c&&(this.hover_glyph=await this.build_glyph_view(c)),_=n(V,_),this.muted_glyph=await this.build_glyph_view(_);const d=n(w,\"auto\");this.decimated_glyph=await this.build_glyph_view(d),this.selection_glyph.set_base(this.glyph),this.nonselection_glyph.set_base(this.glyph),null===(e=this.hover_glyph)||void 0===e||e.set_base(this.glyph),this.muted_glyph.set_base(this.glyph),this.decimated_glyph.set_base(this.glyph),this.set_data()}async build_glyph_view(e){return(0,m.build_view)(e,{parent:this})}remove(){var e;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),this.muted_glyph.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals();const e=()=>this.request_render(),t=()=>this.update_data();this.connect(this.model.change,e),this.connect(this.glyph.model.change,t),this.connect(this.selection_glyph.model.change,t),this.connect(this.nonselection_glyph.model.change,t),null!=this.hover_glyph&&this.connect(this.hover_glyph.model.change,t),this.connect(this.muted_glyph.model.change,t),this.connect(this.decimated_glyph.model.change,t),this.connect(this.model.data_source.change,t),this.connect(this.model.data_source.streaming,t),this.connect(this.model.data_source.patching,(e=>this.update_data(e))),this.connect(this.model.data_source.selected.change,e),this.connect(this.model.data_source._select,e),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,e),this.connect(this.model.properties.view.change,t),this.connect(this.model.view.properties.indices.change,t),this.connect(this.model.view.properties.masked.change,(()=>this.set_visuals())),this.connect(this.model.properties.visible.change,(()=>this.plot_view.invalidate_dataranges=!0));const{x_ranges:i,y_ranges:s}=this.plot_view.frame;for(const[,e]of i)e instanceof v.FactorRange&&this.connect(e.change,t);for(const[,e]of s)e instanceof v.FactorRange&&this.connect(e.change,t);const{transformchange:l,exprchange:h}=this.model.glyph;this.connect(l,t),this.connect(h,t)}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}update_data(e){this.set_data(e),this.request_render()}set_data(e){const t=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:i}=this;this.glyph.set_data(t,i,e),this.set_visuals(),this._update_masked_indices();const{lod_factor:s}=this.plot_model,l=this.all_indices.count;this.decimated=new g.Indices(l);for(let e=0;e!n||n.is_empty()?[]:n.selected_glyph?this.model.view.convert_indices_from_subset(i):n.indices.length>0?n.indices:Object.keys(n.multiline_indices).map((e=>parseInt(e))))()),d=(0,u.filter)(i,(e=>r.has(t[e]))),{lod_threshold:p}=this.plot_model;let g,y,m;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=p&&t.length>p?(i=[...this.decimated],g=this.decimated_glyph,y=this.decimated_glyph,m=this.selection_glyph):(g=this.model.muted?this.muted_glyph:this.glyph,y=this.nonselection_glyph,m=this.selection_glyph),null!=this.hover_glyph&&d.length){const e=new Set(i);for(const t of d)e.delete(t);i=[...e]}if(h.length){const e={};for(const t of h)e[t]=!0;const l=new Array,n=new Array;if(this.glyph instanceof o.LineView)for(const i of t)null!=e[i]?l.push(i):n.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):n.push(s);y.render(s,n),m.render(s,l),null!=this.hover_glyph&&(this.glyph instanceof o.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):this.hover_glyph.render(s,d))}else if(this.glyph instanceof o.LineView)this.hover_glyph&&d.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):g.render(s,t);else if(this.glyph instanceof a.PatchView||this.glyph instanceof c.HAreaView||this.glyph instanceof _.VAreaView)if(0==n.selected_glyphs.length||null==this.hover_glyph)g.render(s,t);else for(const e of n.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t);else g.render(s,i),this.hover_glyph&&d.length&&this.hover_glyph.render(s,d);s.restore()}draw_legend(e,t,i,s,l,h,n,o){0!=this.glyph.data_size&&(null==o&&(o=this.model.get_reference_point(h,n)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o))}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=x,x.__name__=\"GlyphRendererView\";class G extends n.DataRenderer{constructor(e){super(e)}initialize(){super.initialize(),this.view.source!=this.data_source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){if(null!=e){const i=this.data_source.get_column(e);if(null!=i)for(const[e,s]of Object.entries(this.view.indices_map))if(i[parseInt(e)]==t)return s}return 0}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=G,h=G,G.__name__=\"GlyphRenderer\",h.prototype.default_view=x,h.define((({Boolean:e,Auto:t,Or:i,Ref:s,Null:l,Nullable:h})=>({data_source:[s(d.ColumnarDataSource)],view:[s(p.CDSView),e=>new p.CDSView({source:e.data_source})],glyph:[s(r.Glyph)],hover_glyph:[h(s(r.Glyph)),null],nonselection_glyph:[i(s(r.Glyph),t,l),\"auto\"],selection_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted:[e,!1]})))},\n", - " function _(e,r,t,a,n){var s;a();const c=e(41);class _ extends c.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=_,_.__name__=\"DataRendererView\";class i extends c.Renderer{constructor(e){super(e)}get selection_manager(){return this.get_selection_manager()}}t.DataRenderer=i,s=i,i.__name__=\"DataRenderer\",s.override({level:\"glyph\"})},\n", - " function _(e,t,i,s,n){s();const l=e(1);var _;const r=e(178),o=e(184),a=(0,l.__importStar)(e(48)),h=(0,l.__importStar)(e(185)),c=e(72);class d extends r.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{LineGL:i}=await Promise.resolve().then((()=>(0,l.__importStar)(e(426))));this.glglyph=new i(t.regl_wrapper,this)}}_render(e,t,i){const{sx:s,sy:n}=null!=i?i:this;let l=null;const _=e=>null!=l&&e-l!=1;let r=!0;e.beginPath();for(const i of t){const t=s[i],o=n[i];isFinite(t+o)?r||_(i)?(e.moveTo(t,o),r=!1):e.lineTo(t,o):r=!0,l=i}this.visuals.line.set_value(e),e.stroke()}_hit_point(e){const t=new c.Selection,i={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.line_width.value/2);for(let e=0,l=this.sx.length-1;e({x:[c.XCoordinateSpec,{field:\"x\"}],y:[c.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,t,s,i,n){i();const r=e(1),a=(0,r.__importStar)(e(18)),o=(0,r.__importStar)(e(65)),_=(0,r.__importStar)(e(45)),l=e(42),c=e(53),h=e(19),d=e(24),u=e(8),f=e(180),p=e(12),g=e(26),y=e(181),x=e(67),v=e(72),{abs:b,ceil:m}=Math;class w extends l.View{constructor(){super(...arguments),this._index=null,this._data_size=null,this._nohit_warned=new Set}get renderer(){return this.parent}get has_webgl(){return null!=this.glglyph}get index(){const{_index:e}=this;if(null!=e)return e;throw new Error(`${this}.index_data() wasn't called`)}get data_size(){const{_data_size:e}=this;if(null!=e)return e;throw new Error(`${this}.set_data() wasn't called`)}initialize(){super.initialize(),this.visuals=new _.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.renderer.parent.canvas_view}render(e,t,s){var i;null!=this.glglyph&&(this.renderer.needs_webgl_blit=this.glglyph.render(e,t,null!==(i=this.base)&&void 0!==i?i:this),this.renderer.needs_webgl_blit)||this._render(e,t,null!=s?s:this.base)}has_finished(){return!0}notify_finished(){this.renderer.notify_finished()}_bounds(e){return e}bounds(){return this._bounds(this.index.bbox)}log_bounds(){const{x0:e,x1:t}=this.index.bounds(o.positive_x()),{y0:s,y1:i}=this.index.bounds(o.positive_y());return this._bounds({x0:e,y0:s,x1:t,y1:i})}get_anchor_point(e,t,[s,i]){switch(e){case\"center\":case\"center_center\":{const[e,n]=this.scenterxy(t,s,i);return{x:e,y:n}}default:return null}}scenterx(e,t,s){return this.scenterxy(e,t,s)[0]}scentery(e,t,s){return this.scenterxy(e,t,s)[1]}sdist(e,t,s,i=\"edge\",n=!1){const r=t.length,a=new d.ScreenArray(r),o=e.s_compute;if(\"center\"==i)for(let e=0;em(e))),a}draw_legend_for_index(e,t,s){}hit_test(e){switch(e.type){case\"point\":if(null!=this._hit_point)return this._hit_point(e);break;case\"span\":if(null!=this._hit_span)return this._hit_span(e);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(e);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(e)}return this._nohit_warned.has(e.type)||(h.logger.debug(`'${e.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(e.type)),null}_hit_rect_against_index(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.coordinates.x_scale.r_invert(t,s),[o,_]=this.renderer.coordinates.y_scale.r_invert(i,n),l=[...this.index.indices({x0:r,x1:a,y0:o,y1:_})];return new v.Selection({indices:l})}_project_data(){}*_iter_visuals(){for(const e of this.visuals)for(const t of e)(t instanceof a.VectorSpec||t instanceof a.ScalarSpec)&&(yield t)}set_base(e){e!=this&&e instanceof this.constructor&&(this.base=e)}_configure(e,t){Object.defineProperty(this,(0,u.isString)(e)?e:e.attr,Object.assign({configurable:!0,enumerable:!0},t))}set_visuals(e,t){var s;for(const s of this._iter_visuals()){const{base:i}=this;if(null!=i){const e=i.model.properties[s.attr];if(null!=e&&(0,g.is_equal)(s.get_value(),e.get_value())){this._configure(s,{get:()=>i[`${s.attr}`]});continue}}const n=s.uniform(e).select(t);this._configure(s,{value:n})}for(const e of this.visuals)e.update();null===(s=this.glglyph)||void 0===s||s.set_visuals_changed()}set_data(e,t,s){var i;const{x_source:n,y_source:r}=this.renderer.coordinates,o=new Set(this._iter_visuals());this._data_size=t.count;for(const s of this.model)if((s instanceof a.VectorSpec||s instanceof a.ScalarSpec)&&!o.has(s))if(s instanceof a.BaseCoordinateSpec){const i=s.array(e);let o=t.select(i);const _=\"x\"==s.dimension?n:r;if(_ instanceof x.FactorRange)if(s instanceof a.CoordinateSpec)o=_.v_synthetic(o);else if(s instanceof a.CoordinateSeqSpec)for(let e=0;e{const s=new Uint32Array(r);for(let a=0;a>1;t[s]>i?e=s:n=s+1}return t[n]}class r extends d.default{get boxes(){return this._boxes}search_indices(i,t,n,e){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let s=this._boxes.length-4;const d=[],x=new o.Indices(this.numItems);for(;void 0!==s;){const o=Math.min(s+4*this.nodeSize,h(s,this._levelBounds));for(let h=s;h>2],r=this._boxes[h+0],l=this._boxes[h+1],a=this._boxes[h+2],_=this._boxes[h+3];na||t>_||(s<4*this.numItems?x.set(o):d.push(o)))}s=d.pop()}return x}}r.__name__=\"_FlatBush\";class l{constructor(i){this.index=null,i>0&&(this.index=new r(i))}add_rect(i,t,n,e){var s;isFinite(i+t+n+e)?null===(s=this.index)||void 0===s||s.add(i,t,n,e):this.add_empty()}add_point(i,t){var n;isFinite(i+t)?null===(n=this.index)||void 0===n||n.add(i,t,i,t):this.add_empty()}add_empty(){var i;null===(i=this.index)||void 0===i||i.add(1/0,1/0,-1/0,-1/0)}finish(){var i;null===(i=this.index)||void 0===i||i.finish()}_normalize(i){let{x0:t,y0:n,x1:e,y1:s}=i;return t>e&&([t,e]=[e,t]),n>s&&([n,s]=[s,n]),{x0:t,y0:n,x1:e,y1:s}}get bbox(){if(null==this.index)return(0,x.empty)();{const{minX:i,minY:t,maxX:n,maxY:e}=this.index;return{x0:i,y0:t,x1:n,y1:e}}}indices(i){if(null==this.index)return new o.Indices(0);{const{x0:t,y0:n,x1:e,y1:s}=this._normalize(i);return this.index.search_indices(t,n,e,s)}}bounds(i){const t=(0,x.empty)();if(null==this.index)return t;const{boxes:n}=this.index;for(const e of this.indices(i)){const s=n[4*e+0],d=n[4*e+1],o=n[4*e+2],x=n[4*e+3];s>=i.x0&&st.x1&&(t.x1=o),d>=i.y0&&dt.y1&&(t.y1=x)}return t}}n.SpatialIndex=l,l.__name__=\"SpatialIndex\"},\n", - " function _(t,s,i,e,h){e();const n=(0,t(1).__importDefault)(t(183)),o=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class r{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got v${i>>4} data when expected v3.`);const[e]=new Uint16Array(t,2,1),[h]=new Uint32Array(t,4,1);return new r(h,e,o[15&i],t)}constructor(t,s=16,i=Float64Array,e){if(void 0===t)throw new Error(\"Missing required argument: numItems.\");if(isNaN(t)||t<=0)throw new Error(`Unpexpected numItems value: ${t}.`);this.numItems=+t,this.nodeSize=Math.min(Math.max(+s,2),65535);let h=t,r=h;this._levelBounds=[4*h];do{h=Math.ceil(h/this.nodeSize),r+=h,this._levelBounds.push(4*r)}while(1!==h);this.ArrayType=i||Float64Array,this.IndexArrayType=r<16384?Uint16Array:Uint32Array;const a=o.indexOf(this.ArrayType),_=4*r*this.ArrayType.BYTES_PER_ELEMENT;if(a<0)throw new Error(`Unexpected typed array class: ${i}.`);e&&e instanceof ArrayBuffer?(this.data=e,this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=4*r,this.minX=this._boxes[this._pos-4],this.minY=this._boxes[this._pos-3],this.maxX=this._boxes[this._pos-2],this.maxY=this._boxes[this._pos-1]):(this.data=new ArrayBuffer(8+_+r*this.IndexArrayType.BYTES_PER_ELEMENT),this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=0,this.minX=1/0,this.minY=1/0,this.maxX=-1/0,this.maxY=-1/0,new Uint8Array(this.data,0,2).set([251,48+a]),new Uint16Array(this.data,2,1)[0]=s,new Uint32Array(this.data,4,1)[0]=t),this._queue=new n.default}add(t,s,i,e){const h=this._pos>>2;return this._indices[h]=h,this._boxes[this._pos++]=t,this._boxes[this._pos++]=s,this._boxes[this._pos++]=i,this._boxes[this._pos++]=e,tthis.maxX&&(this.maxX=i),e>this.maxY&&(this.maxY=e),h}finish(){if(this._pos>>2!==this.numItems)throw new Error(`Added ${this._pos>>2} items when expected ${this.numItems}.`);if(this.numItems<=this.nodeSize)return 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c.point_in_poly(t.sx,t.sy,this.sx,this.sy)&&(s.add_to_selected_glyphs(this.model),s.view=this),s}}e.PatchView=p,p.__name__=\"PatchView\";class d extends _.XYGlyph{constructor(t){super(t)}}e.Patch=d,n=d,d.__name__=\"Patch\",n.prototype.default_view=p,n.mixins([h.LineScalar,h.FillScalar,h.HatchScalar])},\n", - " function _(t,s,e,i,n){i();const h=t(1);var r;const a=t(188),_=(0,h.__importStar)(t(185)),o=(0,h.__importStar)(t(18)),l=t(72);class c extends a.AreaView{_index_data(t){const{min:s,max:e}=Math,{data_size:i}=this;for(let n=0;n=0;s--)t.lineTo(n[s],h[s]);t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t)}_hit_point(t){const s=this.sy.length,e=new l.Selection;for(let i=0,n=s-1;i({x1:[o.XCoordinateSpec,{field:\"x1\"}],x2:[o.XCoordinateSpec,{field:\"x2\"}],y:[o.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,a,r,_,s){_();const n=e(1);var c;const i=e(179),l=e(184),t=(0,n.__importStar)(e(48));class o extends i.GlyphView{draw_legend_for_index(e,a,r){(0,l.generic_area_scalar_legend)(this.visuals,e,a)}}r.AreaView=o,o.__name__=\"AreaView\";class d extends i.Glyph{constructor(e){super(e)}}r.Area=d,c=d,d.__name__=\"Area\",c.mixins([t.FillScalar,t.HatchScalar])},\n", - " function _(t,s,e,i,n){i();const h=t(1);var r;const a=t(188),_=(0,h.__importStar)(t(185)),o=(0,h.__importStar)(t(18)),l=t(72);class c extends a.AreaView{_index_data(t){const{min:s,max:e}=Math,{data_size:i}=this;for(let n=0;n=0;s--)t.lineTo(i[s],h[s]);t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t)}scenterxy(t){return[this.sx[t],(this.sy1[t]+this.sy2[t])/2]}_hit_point(t){const s=this.sx.length,e=new l.Selection;for(let i=0,n=s-1;i({x:[o.XCoordinateSpec,{field:\"x\"}],y1:[o.YCoordinateSpec,{field:\"y1\"}],y2:[o.YCoordinateSpec,{field:\"y2\"}]})))},\n", - " function _(e,i,s,t,n){var c;t();const o=e(53),r=e(24),u=e(191),_=e(70);class a extends o.Model{constructor(e){super(e)}initialize(){super.initialize(),this.compute_indices()}connect_signals(){super.connect_signals(),this.connect(this.properties.filters.change,(()=>this.compute_indices()));const e=()=>{const e=()=>this.compute_indices();null!=this.source&&(this.connect(this.source.change,e),this.source instanceof _.ColumnarDataSource&&(this.connect(this.source.streaming,e),this.connect(this.source.patching,e)))};let i=null!=this.source;i?e():this.connect(this.properties.source.change,(()=>{i||(e(),i=!0)}))}compute_indices(){var e;const{source:i}=this;if(null==i)return;const s=null!==(e=i.get_length())&&void 0!==e?e:1,t=r.Indices.all_set(s);for(const e of this.filters)t.intersect(e.compute_indices(i));this.indices=t,this._indices=[...t],this.indices_map_to_subset()}indices_map_to_subset(){this.indices_map={};for(let e=0;ethis._indices[e]))}convert_selection_to_subset(e){return e.map((e=>this.indices_map[e]))}convert_indices_from_subset(e){return e.map((e=>this._indices[e]))}}s.CDSView=a,c=a,a.__name__=\"CDSView\",c.define((({Array:e,Ref:i})=>({filters:[e(i(u.Filter)),[]],source:[i(_.ColumnarDataSource)]}))),c.internal((({Int:e,Dict:i,Ref:s,Nullable:t})=>({indices:[s(r.Indices)],indices_map:[i(e),{}],masked:[t(s(r.Indices)),null]})))},\n", - " function _(e,t,n,s,c){s();const o=e(53);class r extends o.Model{constructor(e){super(e)}}n.Filter=r,r.__name__=\"Filter\"},\n", - " function _(t,r,a,e,c){e(),c(\"BasicTickFormatter\",t(146).BasicTickFormatter),c(\"CategoricalTickFormatter\",t(142).CategoricalTickFormatter),c(\"DatetimeTickFormatter\",t(150).DatetimeTickFormatter),c(\"FuncTickFormatter\",t(193).FuncTickFormatter),c(\"LogTickFormatter\",t(163).LogTickFormatter),c(\"MercatorTickFormatter\",t(166).MercatorTickFormatter),c(\"NumeralTickFormatter\",t(194).NumeralTickFormatter),c(\"PrintfTickFormatter\",t(195).PrintfTickFormatter),c(\"TickFormatter\",t(131).TickFormatter)},\n", - " function _(t,e,n,s,r){var c;s();const 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_(r,o,a,p,e){p(),e(\"CategoricalColorMapper\",r(197).CategoricalColorMapper),e(\"CategoricalMarkerMapper\",r(199).CategoricalMarkerMapper),e(\"CategoricalPatternMapper\",r(200).CategoricalPatternMapper),e(\"ContinuousColorMapper\",r(172).ContinuousColorMapper),e(\"ColorMapper\",r(173).ColorMapper),e(\"LinearColorMapper\",r(201).LinearColorMapper),e(\"LogColorMapper\",r(202).LogColorMapper),e(\"ScanningColorMapper\",r(171).ScanningColorMapper),e(\"EqHistColorMapper\",r(203).EqHistColorMapper)},\n", - " function _(t,o,r,a,e){var c;a();const s=t(198),l=t(173),n=t(67);class _ extends l.ColorMapper{constructor(t){super(t)}_v_compute(t,o,r,{nan_color:a}){(0,s.cat_v_compute)(t,this.factors,r,o,this.start,this.end,a)}}r.CategoricalColorMapper=_,c=_,_.__name__=\"CategoricalColorMapper\",c.define((({Number:t,Nullable:o})=>({factors:[n.FactorSeq],start:[t,0],end:[o(t),null]})))},\n", - " function _(n,t,e,l,i){l();const c=n(12),u=n(8);function f(n,t){if(n.length!=t.length)return!1;for(let 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Array(t.length);return(0,c.cat_v_compute)(t,this.factors,this.patterns,e,this.start,this.end,this.default_value),e}}a.CategoricalPatternMapper=o,s=o,o.__name__=\"CategoricalPatternMapper\",s.define((({Number:t,Array:e,Nullable:a})=>({factors:[l.FactorSeq],patterns:[e(u.HatchPatternType)],start:[t,0],end:[a(t),null],default_value:[u.HatchPatternType,\" \"]})))},\n", - " function _(n,r,o,t,a){t();const e=n(172),i=n(12);class s extends e.ContinuousColorMapper{constructor(n){super(n)}scan(n,r){const o=null!=this.low?this.low:(0,i.min)(n),t=null!=this.high?this.high:(0,i.max)(n);return{max:t,min:o,norm_factor:1/(t-o),normed_interval:1/r}}cmap(n,r,o,t,a){const e=r.length-1;if(n==a.max)return r[e];const i=(n-a.min)*a.norm_factor,s=Math.floor(i/a.normed_interval);return s<0?o:s>e?t:r[s]}}o.LinearColorMapper=s,s.__name__=\"LinearColorMapper\"},\n", - " function _(o,t,n,r,l){r();const a=o(172),s=o(12);class e extends a.ContinuousColorMapper{constructor(o){super(o)}scan(o,t){const n=null!=this.low?this.low:(0,s.min)(o),r=null!=this.high?this.high:(0,s.max)(o);return{max:r,min:n,scale:t/(Math.log(r)-Math.log(n))}}cmap(o,t,n,r,l){const a=t.length-1;if(o>l.max)return r;if(o==l.max)return t[a];if(oa&&(e=a),t[e]}}n.LogColorMapper=e,e.__name__=\"LogColorMapper\"},\n", - " function _(e,n,s,t,l){var i;t();const r=e(171),o=e(12),c=e(9);class a extends r.ScanningColorMapper{constructor(e){super(e)}scan(e,n){let s=null!=this.low?this.low:(0,o.min)(e);const t=null!=this.high?this.high:(0,o.max)(e),l=this.bins,i=(0,c.linspace)(s,t,l+1),r=(0,o.bin_counts)(e,i);let a=0;for(let e=0;e1&&(f=1-n)}const d=(0,c.linspace)(f,1,n+1),g=(0,o.interpolate)(d,p,_);return this.rescale_discrete_levels?s=g[0]:g[0]=s,g[g.length-1]=t,{min:s,max:t,binning:g}}}s.EqHistColorMapper=a,i=a,a.__name__=\"EqHistColorMapper\",i.define((({Boolean:e,Int:n})=>({bins:[n,65536],rescale_discrete_levels:[e,!1]})))},\n", - " function _(a,e,l,c,n){c(),n(\"CategoricalScale\",a(62).CategoricalScale),n(\"ContinuousScale\",a(60).ContinuousScale),n(\"LinearScale\",a(59).LinearScale),n(\"LinearInterpolationScale\",a(205).LinearInterpolationScale),n(\"LogScale\",a(61).LogScale),n(\"Scale\",a(55).Scale)},\n", - " function _(e,r,n,t,a){var i;t();const s=e(55),o=e(59),c=e(12);class _ extends s.Scale{constructor(e){super(e)}connect_signals(){super.connect_signals();const{source_range:e,target_range:r}=this.properties;this.on_change([e,r],(()=>{this.linear_scale=new o.LinearScale({source_range:this.source_range,target_range:this.target_range})}))}get s_compute(){throw new Error(\"not implemented\")}get s_invert(){throw new Error(\"not implemented\")}compute(e){return e}v_compute(e){const{binning:r}=this,{start:n,end:t}=this.source_range,a=n,i=t,s=r.length,o=(t-n)/(s-1),_=new Float64Array(s);for(let e=0;e{if(ei)return i;const n=(0,c.left_edge_index)(e,r);if(-1==n)return a;if(n>=s-1)return i;const t=r[n],o=(e-t)/(r[n+1]-t),l=_[n];return l+o*(_[n+1]-l)}));return this.linear_scale.v_compute(l)}invert(e){return e}v_invert(e){return new Float64Array(e)}}n.LinearInterpolationScale=_,i=_,_.__name__=\"LinearInterpolationScale\",i.internal((({Arrayable:e,Ref:r})=>({binning:[e],linear_scale:[r(o.LinearScale),e=>new o.LinearScale({source_range:e.source_range,target_range:e.target_range})]})))},\n", - " function _(a,n,e,g,R){g(),R(\"DataRange\",a(64).DataRange),R(\"DataRange1d\",a(63).DataRange1d),R(\"FactorRange\",a(67).FactorRange),R(\"Range\",a(57).Range),R(\"Range1d\",a(58).Range1d)},\n", - " function _(a,o,i,t,e){t();var n=a(124);e(\"Sizeable\",n.Sizeable),e(\"SizingPolicy\",n.SizingPolicy);var c=a(125);e(\"Layoutable\",c.Layoutable),e(\"LayoutItem\",c.LayoutItem);var r=a(208);e(\"HStack\",r.HStack),e(\"VStack\",r.VStack);var l=a(209);e(\"Grid\",l.Grid),e(\"Row\",l.Row),e(\"Column\",l.Column);var S=a(210);e(\"ContentBox\",S.ContentBox),e(\"VariadicBox\",S.VariadicBox)},\n", - " function _(t,e,h,i,r){i();const n=t(125),o=t(65);class s extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}}h.Stack=s,s.__name__=\"Stack\";class c extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e+=i.width,h=Math.max(h,i.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.top:0;let i=this.absolute?t.left:0;const{height:r}=t;for(const t of this.children){const{width:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({left:i,width:e,top:h,height:r})),i+=e}}}h.HStack=c,c.__name__=\"HStack\";class a extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e=Math.max(e,i.width),h+=i.height}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.left:0;let i=this.absolute?t.top:0;const{width:r}=t;for(const t of this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({top:i,height:e,left:h,width:r})),i+=e}}}h.VStack=a,a.__name__=\"VStack\";class l extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}_measure(t){const{width_policy:e,height_policy:h}=this.sizing,{min:i,max:r}=Math;let n=0,o=0;for(const e of this.children){const{width:h,height:i}=e.measure(t);n=r(n,h),o=r(o,i)}return{width:(()=>{const{width:h}=this.sizing;if(t.width==1/0)return\"fixed\"==e&&null!=h?h:n;switch(e){case\"fixed\":return null!=h?h:n;case\"min\":return n;case\"fit\":return null!=h?i(t.width,h):t.width;case\"max\":return null!=h?r(t.width,h):t.width}})(),height:(()=>{const{height:e}=this.sizing;if(t.height==1/0)return\"fixed\"==h&&null!=e?e:o;switch(h){case\"fixed\":return null!=e?e:o;case\"min\":return o;case\"fit\":return null!=e?i(t.height,e):t.height;case\"max\":return null!=e?r(t.height,e):t.height}})()}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t:t.relative(),{left:i,right:r,top:n,bottom:s}=h,c=Math.round(h.vcenter),a=Math.round(h.hcenter);for(const e of this.children){const{margin:h,halign:l,valign:d}=e.sizing,{width:u,height:g,inner:_}=e.measure(t),w=(()=>{switch(`${d}_${l}`){case\"start_start\":return new o.BBox({left:i+h.left,top:n+h.top,width:u,height:g});case\"start_center\":return new o.BBox({hcenter:a,top:n+h.top,width:u,height:g});case\"start_end\":return new o.BBox({right:r-h.right,top:n+h.top,width:u,height:g});case\"center_start\":return new o.BBox({left:i+h.left,vcenter:c,width:u,height:g});case\"center_center\":return new o.BBox({hcenter:a,vcenter:c,width:u,height:g});case\"center_end\":return new o.BBox({right:r-h.right,vcenter:c,width:u,height:g});case\"end_start\":return new o.BBox({left:i+h.left,bottom:s-h.bottom,width:u,height:g});case\"end_center\":return new o.BBox({hcenter:a,bottom:s-h.bottom,width:u,height:g});case\"end_end\":return new o.BBox({right:r-h.right,bottom:s-h.bottom,width:u,height:g})}})(),m=null==_?w:new o.BBox({left:w.left+_.left,top:w.top+_.top,right:w.right-_.right,bottom:w.bottom-_.bottom});e.set_geometry(w,m)}}}h.NodeLayout=l,l.__name__=\"NodeLayout\"},\n", - " function _(t,i,s,e,o){e();const n=t(124),l=t(125),r=t(8),h=t(65),c=t(9),{max:a,round:g}=Math;class p{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}p.__name__=\"DefaultMap\";class f{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=a(this._nrows,s+1),this._ncols=a(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter((({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1)).map((({data:t})=>t))}row(t){return this._items.filter((({span:i})=>i.r0<=t&&t<=i.r1)).map((({data:t})=>t))}col(t){return this._items.filter((({span:i})=>i.c0<=t&&t<=i.c1)).map((({data:t})=>t))}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new f;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}f.__name__=\"Container\";class _ extends l.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0}*[Symbol.iterator](){for(const{layout:t}of this.items)yield t}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}_init(){var t,i,s,e;super._init();const o=new f;for(const{layout:t,row:i,col:s,row_span:e,col_span:n}of this.items)if(t.sizing.visible){const l=i,r=s,h=i+(null!=e?e:1)-1,c=s+(null!=n?n:1)-1;o.add({r0:l,c0:r,r1:h,c1:c},t)}const{nrows:n,ncols:l}=o,h=new Array(n);for(let s=0;s{var t;const i=(0,r.isPlainObject)(this.rows)?null!==(t=this.rows[s])&&void 0!==t?t:this.rows[\"*\"]:this.rows;return null==i?{policy:\"auto\"}:(0,r.isNumber)(i)?{policy:\"fixed\",height:i}:(0,r.isString)(i)?{policy:i}:i})(),n=null!==(t=e.align)&&void 0!==t?t:\"auto\";if(\"fixed\"==e.policy)h[s]={policy:\"fixed\",height:e.height,align:n};else if(\"min\"==e.policy)h[s]={policy:\"min\",align:n};else if(\"fit\"==e.policy||\"max\"==e.policy)h[s]={policy:e.policy,flex:null!==(i=e.flex)&&void 0!==i?i:1,align:n};else{if(\"auto\"!=e.policy)throw new Error(\"unrechable\");(0,c.some)(o.row(s),(t=>t.is_height_expanding()))?h[s]={policy:\"max\",flex:1,align:n}:h[s]={policy:\"min\",align:n}}}const a=new Array(l);for(let t=0;t{var i;const s=(0,r.isPlainObject)(this.cols)?null!==(i=this.cols[t])&&void 0!==i?i:this.cols[\"*\"]:this.cols;return null==s?{policy:\"auto\"}:(0,r.isNumber)(s)?{policy:\"fixed\",width:s}:(0,r.isString)(s)?{policy:s}:s})(),n=null!==(s=i.align)&&void 0!==s?s:\"auto\";if(\"fixed\"==i.policy)a[t]={policy:\"fixed\",width:i.width,align:n};else if(\"min\"==i.policy)a[t]={policy:\"min\",align:n};else if(\"fit\"==i.policy||\"max\"==i.policy)a[t]={policy:i.policy,flex:null!==(e=i.flex)&&void 0!==e?e:1,align:n};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");(0,c.some)(o.col(t),(t=>t.is_width_expanding()))?a[t]={policy:\"max\",flex:1,align:n}:a[t]={policy:\"min\",align:n}}}const[g,p]=(0,r.isNumber)(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:o,nrows:n,ncols:l,rows:h,cols:a,rspacing:g,cspacing:p}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:(0,c.sum)(t)+(s-1)*o,width:(0,c.sum)(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:e,rows:o,cols:l,rspacing:r,cspacing:h}=this._state,c=new Array(s);for(let t=0;t{const{r0:e,c0:f,r1:d,c1:u}=i,w=(d-e)*r,m=(u-f)*h;let y=0;for(let i=e;i<=d;i++)y+=t(i,f).height;y+=w;let x=0;for(let i=f;i<=u;i++)x+=t(e,i).width;x+=m;const b=s.measure({width:x,height:y});_.add(i,{layout:s,size_hint:b});const z=new n.Sizeable(b).grow_by(s.sizing.margin);z.height-=w,z.width-=m;const v=[];for(let t=e;t<=d;t++){const i=o[t];\"fixed\"==i.policy?z.height-=i.height:v.push(t)}if(z.height>0){const t=g(z.height/v.length);for(const i of v)c[i]=a(c[i],t)}const j=[];for(let t=f;t<=u;t++){const i=l[t];\"fixed\"==i.policy?z.width-=i.width:j.push(t)}if(z.width>0){const t=g(z.width/j.length);for(const i of j)p[i]=a(p[i],t)}}));return{size:this._measure_totals(c,p),row_heights:c,col_widths:p,size_hints:_}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:l}=this._state,r=this._measure_cells(((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}}));let h;h=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:r.size.height;let c,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}c=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:r.size.width;let f=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:_,col_widths:d,size_hints:u}=this._measure_cells(((t,i)=>({width:r.col_widths[i],height:r.row_heights[t]})));return{size:this._measure_totals(_,d),row_heights:_,col_widths:d,size_hints:u}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:l,col_widths:r,size_hints:c}=this._measure_grid(t),f=this._state.rows.map(((t,i)=>Object.assign(Object.assign({},t),{top:0,height:l[i],get bottom(){return this.top+this.height}}))),_=this._state.cols.map(((t,i)=>Object.assign(Object.assign({},t),{left:0,width:r[i],get right(){return this.left+this.width}}))),d=c.map(((t,i)=>Object.assign(Object.assign({},i),{outer:new h.BBox,inner:new h.BBox})));for(let i=0,e=this.absolute?t.top:0;i{const{layout:r,size_hint:c}=l,{sizing:a}=r,{width:p,height:d}=c,u=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=_[e].width;return s}(i,e),w=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=f[e].height;return s}(t,s),m=i==e&&\"auto\"!=_[i].align?_[i].align:a.halign,y=t==s&&\"auto\"!=f[t].align?f[t].align:a.valign;let x=_[i].left;\"start\"==m?x+=a.margin.left:\"center\"==m?x+=g((u-p)/2):\"end\"==m&&(x+=u-a.margin.right-p);let b=f[t].top;\"start\"==y?b+=a.margin.top:\"center\"==y?b+=g((w-d)/2):\"end\"==y&&(b+=w-a.margin.bottom-d),l.outer=new h.BBox({left:x,top:b,width:p,height:d})}));const u=f.map((()=>({start:new p((()=>0)),end:new p((()=>0))}))),w=_.map((()=>({start:new p((()=>0)),end:new p((()=>0))})));d.foreach((({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:l}=o;null!=l&&(u[t].start.apply(n.top,(t=>a(t,l.top))),u[s].end.apply(f[s].bottom-n.bottom,(t=>a(t,l.bottom))),w[i].start.apply(n.left,(t=>a(t,l.left))),w[e].end.apply(_[e].right-n.right,(t=>a(t,l.right))))})),d.foreach((({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:l}=o,r=t=>{const i=this.absolute?l:l.relative(),s=i.left+t.left,e=i.top+t.top,o=i.right-t.right,n=i.bottom-t.bottom;return new h.BBox({left:s,top:e,right:o,bottom:n})};if(null!=n.inner){let h=r(n.inner);if(!1!==n.align){const o=u[t].start.get(l.top),n=u[s].end.get(f[s].bottom-l.bottom),c=w[i].start.get(l.left),a=w[e].end.get(_[e].right-l.right);try{h=r({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=h}else o.inner=l})),d.foreach(((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)}))}}s.Grid=_,_.__name__=\"Grid\";class d extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:0,col:i}))),this.rows=\"fit\"}}s.Row=d,d.__name__=\"Row\";class u extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:i,col:0}))),this.cols=\"fit\"}}s.Column=u,u.__name__=\"Column\"},\n", - " function _(e,t,s,n,i){n();const a=e(125),c=e(124),o=e(43);class r extends a.ContentLayoutable{constructor(e){super(),this.content_size=(0,o.unsized)(e,(()=>new c.Sizeable((0,o.size)(e))))}_content_size(){return this.content_size}}s.ContentBox=r,r.__name__=\"ContentBox\";class _ extends a.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new c.Sizeable(e).bounded_to(this.sizing.size);return(0,o.sized)(this.el,t,(()=>{const e=new c.Sizeable((0,o.content_size)(this.el)),{border:t,padding:s}=(0,o.extents)(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)}))}}s.VariadicBox=_,_.__name__=\"VariadicBox\";class h extends _{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=h,h.__name__=\"CachedVariadicBox\"},\n", - " function _(t,e,i,h,o){h();const s=t(124),r=t(125),n=t(65);class g extends r.Layoutable{constructor(){super(...arguments),this.min_border={left:0,top:0,right:0,bottom:0},this.padding={left:0,top:0,right:0,bottom:0}}*[Symbol.iterator](){yield this.top_panel,yield this.bottom_panel,yield this.left_panel,yield this.right_panel,yield this.center_panel}_measure(t){t=new s.Sizeable({width:\"fixed\"==this.sizing.width_policy||t.width==1/0?this.sizing.width:t.width,height:\"fixed\"==this.sizing.height_policy||t.height==1/0?this.sizing.height:t.height});const e=this.left_panel.measure({width:0,height:t.height}),i=Math.max(e.width,this.min_border.left)+this.padding.left,h=this.right_panel.measure({width:0,height:t.height}),o=Math.max(h.width,this.min_border.right)+this.padding.right,r=this.top_panel.measure({width:t.width,height:0}),n=Math.max(r.height,this.min_border.top)+this.padding.top,g=this.bottom_panel.measure({width:t.width,height:0}),a=Math.max(g.height,this.min_border.bottom)+this.padding.bottom,d=new s.Sizeable(t).shrink_by({left:i,right:o,top:n,bottom:a}),l=this.center_panel.measure(d);return{width:i+l.width+o,height:n+l.height+a,inner:{left:i,right:o,top:n,bottom:a},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const i=this.left_panel.measure({width:0,height:t.height}),h=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:r,top:g,right:a,bottom:d}=e;this.top_panel.set_geometry(new n.BBox({left:r,right:a,bottom:g,height:o.height})),this.bottom_panel.set_geometry(new n.BBox({left:r,right:a,top:d,height:s.height})),this.left_panel.set_geometry(new n.BBox({top:g,bottom:d,right:r,width:i.width})),this.right_panel.set_geometry(new n.BBox({top:g,bottom:d,left:a,width:h.width}))}}i.BorderLayout=g,g.__name__=\"BorderLayout\"},\n", - " function _(t,e,i,s,l){s();const n=t(1);var o;const a=t(119),_=t(10),d=t(20),h=t(120),r=t(123),u=(0,n.__importStar)(t(48));class c extends a.TextAnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new r.SideLayout(t,(()=>this.get_size()),!1):void 0}_get_size(){const{text:t}=this.model,e=new h.TextBox({text:t}),{angle:i,angle_units:s}=this.model;e.angle=(0,_.resolve_angle)(i,s),e.visuals=this.visuals.text.values();const{width:l,height:n}=e.size();return{width:l,height:n}}_render(){const{angle:t,angle_units:e}=this.model,i=(0,_.resolve_angle)(t,e),s=null!=this.layout?this.layout:this.plot_view.frame,l=this.coordinates.x_scale,n=this.coordinates.y_scale;let o=\"data\"==this.model.x_units?l.compute(this.model.x):s.bbox.xview.compute(this.model.x),a=\"data\"==this.model.y_units?n.compute(this.model.y):s.bbox.yview.compute(this.model.y);o+=this.model.x_offset,a-=this.model.y_offset;(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,this.model.text,o,a,i)}}i.LabelView=c,c.__name__=\"LabelView\";class x extends a.TextAnnotation{constructor(t){super(t)}}i.Label=x,o=x,x.__name__=\"Label\",o.prototype.default_view=c,o.mixins([u.Text,[\"border_\",u.Line],[\"background_\",u.Fill]]),o.define((({Number:t,String:e,Angle:i})=>({x:[t],x_units:[d.SpatialUnits,\"data\"],y:[t],y_units:[d.SpatialUnits,\"data\"],text:[e,\"\"],angle:[i,0],angle_units:[d.AngleUnits,\"rad\"],x_offset:[t,0],y_offset:[t,0]}))),o.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,s,i,l){i();const o=t(1);var a;const r=t(69),n=(0,o.__importStar)(t(48)),d=t(20),_=t(43),c=t(120),h=(0,o.__importStar)(t(18)),u=t(11);class v extends r.DataAnnotationView{set_data(t){var e;if(super.set_data(t),null===(e=this.els)||void 0===e||e.forEach((t=>(0,_.remove)(t))),\"css\"==this.model.render_mode){const t=this.els=[...this.text].map((()=>(0,_.div)({style:{display:\"none\"}})));for(const e of t)this.plot_view.canvas_view.add_overlay(e)}else delete this.els}remove(){var t;null===(t=this.els)||void 0===t||t.forEach((t=>(0,_.remove)(t))),super.remove()}_rerender(){\"css\"==this.model.render_mode?this.render():this.request_render()}map_data(){const{x_scale:t,y_scale:e}=this.coordinates,s=null!=this.layout?this.layout:this.plot_view.frame;this.sx=\"data\"==this.model.x_units?t.v_compute(this._x):s.bbox.xview.v_compute(this._x),this.sy=\"data\"==this.model.y_units?e.v_compute(this._y):s.bbox.yview.v_compute(this._y)}paint(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer;for(let s=0,i=this.text.length;s{switch(this.visuals.text.text_align.get(e)){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,c]=(()=>{switch(this.visuals.text.text_baseline.get(e)){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${n}, ${c})`;o&&(h+=`rotate(${o}rad)`),a.style.transformOrigin=`${r} ${d}`,a.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_vectorize(t,e),a.style.backgroundColor=t.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_vectorize(t,e),a.style.borderStyle=t.lineDash.length<2?\"solid\":\"dashed\",a.style.borderWidth=`${t.lineWidth}px`,a.style.borderColor=t.strokeStyle),(0,_.display)(a)}}s.LabelSetView=v,v.__name__=\"LabelSetView\";class x extends r.DataAnnotation{constructor(t){super(t)}}s.LabelSet=x,a=x,x.__name__=\"LabelSet\",a.prototype.default_view=v,a.mixins([n.TextVector,[\"border_\",n.LineVector],[\"background_\",n.FillVector]]),a.define((()=>({x:[h.XCoordinateSpec,{field:\"x\"}],y:[h.YCoordinateSpec,{field:\"y\"}],x_units:[d.SpatialUnits,\"data\"],y_units:[d.SpatialUnits,\"data\"],text:[h.StringSpec,{field:\"text\"}],angle:[h.AngleSpec,0],x_offset:[h.NumberSpec,{value:0}],y_offset:[h.NumberSpec,{value:0}],render_mode:[d.RenderMode,\"canvas\"]}))),a.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,i,l,s){l();const n=t(1);var o;const h=t(40),a=t(215),_=t(20),r=(0,n.__importStar)(t(48)),d=t(15),c=t(123),g=t(121),m=t(65),b=t(9),f=t(8),u=t(11);class x extends h.AnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new c.SideLayout(t,(()=>this.get_size())):void 0}cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.model.border_line_color?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.item_change,(()=>this.request_render()))}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:l,label_width:s}=this.model;this.max_label_height=(0,b.max)([(0,g.font_metrics)(this.visuals.label_text.font_value()).height,l,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,(0,b.max)([n.measureText(e).width,s]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?(0,g.font_metrics)(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const o=Math.max((0,b.max)([...this.text_widths.values()]),0),h=this.model.margin,{legend_padding:a}=this,_=this.model.spacing,{label_standoff:r}=this.model;let d,c;if(\"vertical\"==this.model.orientation)d=t.length*this.max_label_height+Math.max(t.length-1,0)*_+2*a+this.title_height,c=(0,b.max)([o+i+r+2*a,this.title_width+2*a]);else{let e=2*a+Math.max(t.length-1,0)*_;for(const[,t]of this.text_widths)e+=(0,b.max)([t,s])+i+r;c=(0,b.max)([this.title_width+2*a,e]),d=this.max_label_height+this.title_height+2*a}const x=null!=this.layout?this.layout:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if((0,f.isString)(v))switch(v){case\"top_left\":y=p.start+h,k=w.start+h;break;case\"top\":case\"top_center\":y=(p.end+p.start)/2-c/2,k=w.start+h;break;case\"top_right\":y=p.end-h-c,k=w.start+h;break;case\"bottom_right\":y=p.end-h-c,k=w.end-h-d;break;case\"bottom\":case\"bottom_center\":y=(p.end+p.start)/2-c/2,k=w.end-h-d;break;case\"bottom_left\":y=p.start+h,k=w.end-h-d;break;case\"left\":case\"center_left\":y=p.start+h,k=(w.end+w.start)/2-d/2;break;case\"center\":case\"center_center\":y=(p.end+p.start)/2-c/2,k=(w.end+w.start)/2-d/2;break;case\"right\":case\"center_right\":y=p.end-h-c,k=(w.end+w.start)/2-d/2}else if((0,f.isArray)(v)&&2==v.length){const[t,e]=v;y=x.bbox.xview.compute(t),k=x.bbox.yview.compute(e)-d}else(0,u.unreachable)();return new m.BBox({left:y,top:k,width:c,height:d})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=i=s;const a=this.compute_legend_bbox(),_=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop();for(const c of d){const d=a.x+h,g=a.y+i+this.title_height;let b,f;[b,f]=_?[a.width-2*s,this.max_label_height]:[this.text_widths.get(c)+l+o,this.max_label_height];if(new m.BBox({left:d,top:g,width:b,height:f}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of r.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of r.renderers)t.muted=!t.muted}return!0}_?i+=this.max_label_height+n:h+=this.text_widths.get(c)+l+o+n}}return!1}_render(){if(0==this.model.items.length)return;if(!(0,b.some)(this.model.items,(t=>t.visible)))return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.apply(t),this.visuals.border_line.apply(t)}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=s,a=s;const _=\"vertical\"==this.model.orientation;for(const r of this.model.items){if(!r.visible)continue;const d=r.get_labels_list_from_label_prop(),c=r.get_field_from_label_prop();if(0==d.length)continue;const g=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return(0,b.every)(r.renderers,(t=>t.visible));case\"mute\":return(0,b.every)(r.renderers,(t=>!t.muted))}})();for(const m of d){const d=e.x+h,b=e.y+a+this.title_height,f=d+i,u=b+l;_?a+=this.max_label_height+n:h+=this.text_widths.get(m)+i+o+n,this.visuals.label_text.set_value(t),t.fillText(m,f+o,b+this.max_label_height/2);for(const e of r.renderers){const i=this.plot_view.renderer_view(e);null==i||i.draw_legend(t,d,f,b,u,c,m,r.index)}if(!g){let l,n;[l,n]=_?[e.width-2*s,this.max_label_height]:[this.text_widths.get(m)+i+o,this.max_label_height],t.beginPath(),t.rect(d,b,l,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){const{title:i}=this.model;i&&this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(i,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=x,x.__name__=\"LegendView\";class p extends h.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new d.Signal0(this,\"item_change\")}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=p,o=p,p.__name__=\"Legend\",o.prototype.default_view=x,o.mixins([[\"label_\",r.Text],[\"title_\",r.Text],[\"inactive_\",r.Fill],[\"border_\",r.Line],[\"background_\",r.Fill]]),o.define((({Number:t,String:e,Array:i,Tuple:l,Or:s,Ref:n,Nullable:o})=>({orientation:[_.Orientation,\"vertical\"],location:[s(_.LegendLocation,l(t,t)),\"top_right\"],title:[o(e),null],title_standoff:[t,5],label_standoff:[t,5],glyph_height:[t,20],glyph_width:[t,20],label_height:[t,20],label_width:[t,20],margin:[t,10],padding:[t,10],spacing:[t,3],items:[i(n(a.LegendItem)),[]],click_policy:[_.LegendClickPolicy,\"none\"]}))),o.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(e,r,l,n,t){n();const i=e(1);var s;const o=e(53),a=e(175),_=e(70),u=e(216),d=(0,i.__importStar)(e(18)),c=e(19),f=e(9);class h extends o.Model{constructor(e){super(e)}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!(0,f.includes)(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,(()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()}));this._check_data_sources_on_renderers()||c.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||c.logger.error(`Bad column name on label: ${this.label}`)}get_field_from_label_prop(){const{label:e}=this;return(0,u.isField)(e)?e.field:null}get_labels_list_from_label_prop(){if(!this.visible)return[];if((0,u.isValue)(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof _.ColumnarDataSource){const l=r.get_column(e);return null!=l?(0,f.uniq)(Array.from(l)):[\"Invalid field\"]}}return[]}}l.LegendItem=h,s=h,h.__name__=\"LegendItem\",s.define((({Boolean:e,Int:r,Array:l,Ref:n,Nullable:t})=>({label:[d.NullStringSpec,null],renderers:[l(n(a.GlyphRenderer)),[]],index:[t(r),null],visible:[e,!0]})))},\n", - " function _(i,n,e,t,u){t();const c=i(8);e.isValue=function(i){return(0,c.isPlainObject)(i)&&\"value\"in i},e.isField=function(i){return(0,c.isPlainObject)(i)&&\"field\"in i},e.isExpr=function(i){return(0,c.isPlainObject)(i)&&\"expr\"in i}},\n", - " function _(t,n,e,s,i){s();const o=t(1);var a;const l=t(40),c=(0,o.__importStar)(t(48)),r=t(20);class _ extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{xs:t,ys:n}=this.model;if(t.length!=n.length)return;const e=t.length;if(e<3)return;const{frame:s}=this.plot_view,{ctx:i}=this.layer,o=this.coordinates.x_scale,a=this.coordinates.y_scale,{screen:l}=this.model;function c(t,n,e,s){return l?t:\"data\"==n?e.v_compute(t):s.v_compute(t)}const r=c(t,this.model.xs_units,o,s.bbox.xview),_=c(n,this.model.ys_units,a,s.bbox.yview);i.beginPath();for(let t=0;t({xs:[n(t),[]],xs_units:[r.SpatialUnits,\"data\"],ys:[n(t),[]],ys_units:[r.SpatialUnits,\"data\"]}))),a.internal((({Boolean:t})=>({screen:[t,!1]}))),a.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,n,o,i){o();const s=e(1);var l;const r=e(40),c=(0,s.__importStar)(e(48));class a extends r.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{gradient:e,y_intercept:t}=this.model;if(null==e||null==t)return;const{frame:n}=this.plot_view,o=this.coordinates.x_scale,i=this.coordinates.y_scale;let s,l,r,c;if(0==e)s=i.compute(t),l=s,r=n.bbox.left,c=r+n.bbox.width;else{s=n.bbox.top,l=s+n.bbox.height;const a=(i.invert(s)-t)/e,_=(i.invert(l)-t)/e;r=o.compute(a),c=o.compute(_)}const{ctx:a}=this.layer;a.save(),a.beginPath(),this.visuals.line.set_value(a),a.moveTo(r,s),a.lineTo(c,l),a.stroke(),a.restore()}}n.SlopeView=a,a.__name__=\"SlopeView\";class _ extends r.Annotation{constructor(e){super(e)}}n.Slope=_,l=_,_.__name__=\"Slope\",l.prototype.default_view=a,l.mixins(c.Line),l.define((({Number:e,Nullable:t})=>({gradient:[t(e),null],y_intercept:[t(e),null]}))),l.override({line_color:\"black\"})},\n", - " function _(e,t,i,o,n){o();const s=e(1);var l;const a=e(40),r=(0,s.__importStar)(e(48)),c=e(20);class d extends a.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_paint(this)))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,o=this.coordinates.y_scale,n=(t,i)=>\"data\"==this.model.location_units?t.compute(e):this.model.for_hover?e:i.compute(e);let s,l,a,r;\"width\"==this.model.dimension?(a=n(o,t.bbox.yview),l=t.bbox.left,r=t.bbox.width,s=this.model.line_width):(a=t.bbox.top,l=n(i,t.bbox.xview),r=this.model.line_width,s=t.bbox.height);const{ctx:c}=this.layer;c.save(),c.beginPath(),this.visuals.line.set_value(c),c.moveTo(l,a),\"width\"==this.model.dimension?c.lineTo(l+r,a):c.lineTo(l,a+s),c.stroke(),c.restore()}}i.SpanView=d,d.__name__=\"SpanView\";class _ extends a.Annotation{constructor(e){super(e)}}i.Span=_,l=_,_.__name__=\"Span\",l.prototype.default_view=d,l.mixins(r.Line),l.define((({Number:e,Nullable:t})=>({render_mode:[c.RenderMode,\"canvas\"],location:[t(e),null],location_units:[c.SpatialUnits,\"data\"],dimension:[c.Dimension,\"width\"]}))),l.internal((({Boolean:e})=>({for_hover:[e,!1]}))),l.override({line_color:\"black\"})},\n", - " function _(i,e,t,o,l){var s;o();const a=i(40),_=i(221),n=i(113),r=i(43),h=i(123),b=i(65);class v extends a.AnnotationView{constructor(){super(...arguments),this._invalidate_toolbar=!0,this._previous_bbox=new b.BBox}update_layout(){this.layout=new h.SideLayout(this.panel,(()=>this.get_size()),!0)}initialize(){super.initialize(),this.el=(0,r.div)(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){await super.lazy_initialize(),this._toolbar_view=await(0,n.build_view)(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push((i=>this._toolbar_view.set_visibility(i)))}remove(){this._toolbar_view.remove(),(0,r.remove)(this.el),super.remove()}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{bbox:i}=this.layout;this._previous_bbox.equals(i)||((0,r.position)(this.el,i),this._previous_bbox=i,this._invalidate_toolbar=!0),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",(0,r.empty)(this.el),this.el.appendChild(this._toolbar_view.el),this._toolbar_view.layout.bbox=i,this._toolbar_view.render(),this._invalidate_toolbar=!1),(0,r.display)(this.el)}_get_size(){const{tools:i,logo:e}=this.model.toolbar;return{width:30*i.length+(null!=e?25:0)+15,height:30}}}t.ToolbarPanelView=v,v.__name__=\"ToolbarPanelView\";class d extends a.Annotation{constructor(i){super(i)}}t.ToolbarPanel=d,s=d,d.__name__=\"ToolbarPanel\",s.prototype.default_view=v,s.define((({Ref:i})=>({toolbar:[i(_.Toolbar)]})))},\n", - " function _(t,e,s,i,o){var c;i();const n=t(8),a=t(9),l=t(13),r=t(222),_=t(223),u=t(232),p=t(233);function v(t){switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null}function h(t){return\"tap\"==t||\"pan\"==t}s.Drag=r.Tool,s.Inspection=r.Tool,s.Scroll=r.Tool,s.Tap=r.Tool;class f extends p.ToolbarBase{constructor(t){super(t)}connect_signals(){super.connect_signals();const{tools:t,active_drag:e,active_inspect:s,active_scroll:i,active_tap:o,active_multi:c}=this.properties;this.on_change([t,e,s,i,o,c],(()=>this._init_tools()))}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof u.InspectTool){let t=!1;for(const e of this.inspectors)e!=this.active_inspect?e.active=!1:t=!0;t||(this.active_inspect=null)}else if((0,n.isArray)(this.active_inspect)){const t=(0,a.intersection)(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)(0,a.includes)(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of(0,l.values)(this.gestures)){t.tools=(0,a.sort_by)(t.tools,(t=>t.default_order));for(const e of t.tools)this.connect(e.properties.active.change,(()=>this._active_change(e)))}for(const[e,s]of(0,l.entries)(this.gestures)){const i=v(e);if(i){const o=this[i];\"auto\"==o?0!=s.tools.length&&h(e)&&t(s.tools[0]):null!=o&&((0,a.includes)(this.tools,o)?t(o):this[i]=null)}}}}s.Toolbar=f,c=f,f.__name__=\"Toolbar\",c.prototype.default_view=p.ToolbarBaseView,c.define((({Or:t,Ref:e,Auto:i,Null:o})=>({active_drag:[t(e(s.Drag),i,o),\"auto\"],active_inspect:[t(e(s.Inspection),i,o),\"auto\"],active_scroll:[t(e(s.Scroll),i,o),\"auto\"],active_tap:[t(e(s.Tap),i,o),\"auto\"],active_multi:[t(e(_.GestureTool),i,o),\"auto\"]})))},\n", - " function _(t,e,n,o,s){var i;o();const a=t(42),r=t(9),l=t(53);class c extends a.View{get plot_view(){return this.parent}get plot_model(){return this.parent.model}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>{this.model.active?this.activate():this.deactivate()}))}activate(){}deactivate(){}}n.ToolView=c,c.__name__=\"ToolView\";class _ extends l.Model{constructor(t){super(t)}get synthetic_renderers(){return[]}_get_dim_limits([t,e],[n,o],s,i){const a=s.bbox.h_range;let l;\"width\"==i||\"both\"==i?(l=[(0,r.min)([t,n]),(0,r.max)([t,n])],l=[(0,r.max)([l[0],a.start]),(0,r.min)([l[1],a.end])]):l=[a.start,a.end];const c=s.bbox.v_range;let _;return\"height\"==i||\"both\"==i?(_=[(0,r.min)([e,o]),(0,r.max)([e,o])],_=[(0,r.max)([_[0],c.start]),(0,r.min)([_[1],c.end])]):_=[c.start,c.end],[l,_]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}n.Tool=_,i=_,_.__name__=\"Tool\",i.prototype._known_aliases=new Map,i.define((({String:t,Nullable:e})=>({description:[e(t),null]}))),i.internal((({Boolean:t})=>({active:[t,!1]})))},\n", - " function _(e,o,t,s,n){s();const u=e(224),_=e(231);class l extends u.ButtonToolView{}t.GestureToolView=l,l.__name__=\"GestureToolView\";class i extends u.ButtonTool{constructor(e){super(e),this.button_view=_.OnOffButtonView}}t.GestureTool=i,i.__name__=\"GestureTool\"},\n", - " function _(t,e,o,s,i){s();const n=t(1);var l;const r=(0,n.__importDefault)(t(225)),a=t(226),u=t(222),h=t(43),_=t(34),d=t(8),c=t(9),m=(0,n.__importStar)(t(227)),p=m,v=(0,n.__importDefault)(t(228)),f=(0,n.__importDefault)(t(229)),g=t(230);class b extends a.DOMView{initialize(){super.initialize();const t=this.model.menu;if(null!=t){const e=this.parent.model.toolbar_location,o=\"left\"==e||\"above\"==e,s=this.parent.model.horizontal?\"vertical\":\"horizontal\";this._menu=new g.ContextMenu(o?(0,c.reversed)(t):t,{orientation:s,prevent_hide:t=>t.target==this.el})}this._hammer=new r.default(this.el,{touchAction:\"auto\",inputClass:r.default.TouchMouseInput}),this.connect(this.model.change,(()=>this.render())),this._hammer.on(\"tap\",(t=>{var e;(null===(e=this._menu)||void 0===e?void 0:e.is_open)?this._menu.hide():t.target==this.el&&this._clicked()})),this._hammer.on(\"press\",(()=>this._pressed())),this.el.addEventListener(\"keydown\",(t=>{t.keyCode==h.Keys.Enter&&this._clicked()}))}remove(){var t;this._hammer.destroy(),null===(t=this._menu)||void 0===t||t.remove(),super.remove()}styles(){return[...super.styles(),m.default,v.default,f.default]}css_classes(){return super.css_classes().concat(p.toolbar_button)}render(){(0,h.empty)(this.el);const t=this.model.computed_icon;(0,d.isString)(t)&&((0,_.startsWith)(t,\"data:image\")?this.el.style.backgroundImage=`url(\"${t}\")`:this.el.classList.add(t)),this.el.title=this.model.tooltip,this.el.tabIndex=0,null!=this._menu&&this.root.el.appendChild(this._menu.el)}_pressed(){var t;const e=(()=>{switch(this.parent.model.toolbar_location){case\"right\":return{left_of:this.el};case\"left\":return{right_of:this.el};case\"above\":return{below:this.el};case\"below\":return{above:this.el}}})();null===(t=this._menu)||void 0===t||t.toggle(e)}}o.ButtonToolButtonView=b,b.__name__=\"ButtonToolButtonView\";class w extends u.ToolView{}o.ButtonToolView=w,w.__name__=\"ButtonToolView\";class y extends u.Tool{constructor(t){super(t)}_get_dim_tooltip(t){const{description:e,tool_name:o}=this;return null!=e?e:\"both\"==t?o:`${o} (${\"width\"==t?\"x\":\"y\"}-axis)`}get tooltip(){var t;return null!==(t=this.description)&&void 0!==t?t:this.tool_name}get computed_icon(){return this.icon}get menu(){return null}}o.ButtonTool=y,l=y,y.__name__=\"ButtonTool\",l.internal((({Boolean:t})=>({disabled:[t,!1]})))},\n", - " function _(t,e,i,n,r){\n", - " /*! 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i,n,s=e[0].toUpperCase()+e.slice(1),a=0;a1&&!i.firstMultiple?i.firstMultiple=H(e):1===s&&(i.firstMultiple=!1);var o=i.firstInput,a=i.firstMultiple,h=a?a.center:o.center,l=e.center=L(n);e.timeStamp=c(),e.deltaTime=e.timeStamp-o.timeStamp,e.angle=G(h,l),e.distance=j(h,l),function(t,e){var i=e.center,n=t.offsetDelta||{},r=t.prevDelta||{},s=t.prevInput||{};1!==e.eventType&&4!==s.eventType||(r=t.prevDelta={x:s.deltaX||0,y:s.deltaY||0},n=t.offsetDelta={x:i.x,y:i.y});e.deltaX=r.x+(i.x-n.x),e.deltaY=r.y+(i.y-n.y)}(i,e),e.offsetDirection=V(e.deltaX,e.deltaY);var p=U(e.deltaTime,e.deltaX,e.deltaY);e.overallVelocityX=p.x,e.overallVelocityY=p.y,e.overallVelocity=u(p.x)>u(p.y)?p.x:p.y,e.scale=a?(f=a.pointers,v=n,j(v[0],v[1],W)/j(f[0],f[1],W)):1,e.rotation=a?function(t,e){return G(e[1],e[0],W)+G(t[1],t[0],W)}(a.pointers,n):0,e.maxPointers=i.prevInput?e.pointers.length>i.prevInput.maxPointers?e.pointers.length:i.prevInput.maxPointers:e.pointers.length,function(t,e){var i,n,s,o,a=t.lastInterval||e,h=e.timeStamp-a.timeStamp;if(8!=e.eventType&&(h>25||a.velocity===r)){var c=e.deltaX-a.deltaX,l=e.deltaY-a.deltaY,p=U(h,c,l);n=p.x,s=p.y,i=u(p.x)>u(p.y)?p.x:p.y,o=V(c,l),t.lastInterval=e}else i=a.velocity,n=a.velocityX,s=a.velocityY,o=a.direction;e.velocity=i,e.velocityX=n,e.velocityY=s,e.direction=o}(i,e);var f,v;var d=t.element;_(e.srcEvent.target,d)&&(d=e.srcEvent.target);e.target=d}(t,i),t.emit(\"hammer.input\",i),t.recognize(i),t.session.prevInput=i}function H(t){for(var e=[],i=0;i=u(e)?t<0?2:4:e<0?8:16}function j(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return Math.sqrt(n*n+r*r)}function G(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return 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e=nt[t.type];if(1===e&&(this.started=!0),this.started){var i=at.call(this,t,e);12&e&&i[0].length-i[1].length==0&&(this.started=!1),this.callback(this.manager,e,{pointers:i[0],changedPointers:i[1],pointerType:N,srcEvent:t})}}});var ht={touchstart:1,touchmove:2,touchend:4,touchcancel:8},ut=\"touchstart touchmove touchend touchcancel\";function ct(){this.evTarget=ut,this.targetIds={},q.apply(this,arguments)}function lt(t,e){var i=P(t.touches),n=this.targetIds;if(3&e&&1===i.length)return n[i[0].identifier]=!0,[i,i];var r,s,o=P(t.changedTouches),a=[],h=this.target;if(s=i.filter((function(t){return _(t.target,h)})),1===e)for(r=0;r-1&&n.splice(t,1)}),2500)}}function dt(t){for(var e=t.srcEvent.clientX,i=t.srcEvent.clientY,n=0;n-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){var e=this,i=this.state;function n(i){e.manager.emit(i,t)}i<8&&n(e.options.event+Dt(i)),n(e.options.event),t.additionalEvent&&n(t.additionalEvent),i>=8&&n(e.options.event+Dt(i))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=bt},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return Ot.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=xt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(Mt,Ot,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(zt,Pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[yt]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distancee.time;if(this._input=t,!n||!i||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return bt},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Nt,Ot,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(Xt,Ot,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return Rt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&Y&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(Yt,Pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[Et]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance .bk-divider{cursor:default;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-context-menu.bk-horizontal > .bk-divider{width:1px;margin:5px 0;}.bk-root .bk-context-menu.bk-vertical > .bk-divider{height:1px;margin:0 5px;}.bk-root .bk-context-menu > :not(.bk-divider){border:1px solid transparent;}.bk-root .bk-context-menu > :not(.bk-divider).bk-active{border-color:#26aae1;}.bk-root .bk-context-menu > :not(.bk-divider):hover{background-color:#f9f9f9;}.bk-root .bk-context-menu > :not(.bk-divider):focus,.bk-root .bk-context-menu > :not(.bk-divider):focus-visible{outline:1px dotted #26aae1;outline-offset:-1px;}.bk-root .bk-context-menu > :not(.bk-divider)::-moz-focus-inner{border:0;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child{border-top-left-radius:4px;border-bottom-left-radius:4px;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child{border-top-right-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child{border-top-left-radius:4px;border-top-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child{border-bottom-left-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-menu{position:absolute;left:0;width:100%;z-index:100;cursor:pointer;font-size:12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;box-shadow:0 6px 12px rgba(0, 0, 0, 0.175);}.bk-root .bk-menu.bk-above{bottom:100%;}.bk-root .bk-menu.bk-below{top:100%;}.bk-root .bk-menu > .bk-divider{height:1px;margin:7.5px 0;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-menu > :not(.bk-divider){padding:6px 12px;}.bk-root .bk-menu > :not(.bk-divider):hover,.bk-root .bk-menu > :not(.bk-divider).bk-active{background-color:#e6e6e6;}.bk-root .bk-caret{display:inline-block;vertical-align:middle;width:0;height:0;margin:0 5px;}.bk-root .bk-caret.bk-down{border-top:4px solid;}.bk-root .bk-caret.bk-up{border-bottom:4px solid;}.bk-root .bk-caret.bk-down,.bk-root .bk-caret.bk-up{border-right:4px solid transparent;border-left:4px solid transparent;}.bk-root .bk-caret.bk-left{border-right:4px solid;}.bk-root .bk-caret.bk-right{border-left:4px solid;}.bk-root .bk-caret.bk-left,.bk-root .bk-caret.bk-right{border-top:4px solid transparent;border-bottom:4px solid transparent;}\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),l=t(43),h=t(9),r=(0,s.__importStar)(t(229));class d{constructor(t,e={}){var i,n;this.items=t,this.el=(0,l.div)(),this._open=!1,this._item_click=t=>{var e;null===(e=t.handler)||void 0===e||e.call(t),this.hide()},this._on_mousedown=t=>{var e;const{target:i}=t;i instanceof Node&&this.el.contains(i)||(null===(e=this.prevent_hide)||void 0===e?void 0:e.call(this,t))||this.hide()},this._on_keydown=t=>{t.keyCode==l.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},this.orientation=null!==(i=e.orientation)&&void 0!==i?i:\"vertical\",this.reversed=null!==(n=e.reversed)&&void 0!==n&&n,this.prevent_hide=e.prevent_hide,(0,l.undisplay)(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){(0,l.remove)(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=(()=>{if(\"left_of\"in t){const{left:e,top:i}=t.left_of.getBoundingClientRect();return{right:e,top:i}}if(\"right_of\"in t){const{top:e,right:i}=t.right_of.getBoundingClientRect();return{left:i,top:e}}if(\"below\"in t){const{left:e,bottom:i}=t.below.getBoundingClientRect();return{left:e,top:i}}if(\"above\"in t){const{left:e,top:i}=t.above.getBoundingClientRect();return{left:e,bottom:i}}return t})(),n=e.getBoundingClientRect();this.el.style.left=null!=i.left?i.left-n.left+\"px\":\"\",this.el.style.top=null!=i.top?i.top-n.top+\"px\":\"\",this.el.style.right=null!=i.right?n.right-i.right+\"px\":\"\",this.el.style.bottom=null!=i.bottom?n.bottom-i.bottom+\"px\":\"\"}}render(){var t;(0,l.empty)(this.el,!0),(0,l.classes)(this.el).add(\"bk-context-menu\",`bk-${this.orientation}`);const e=this.reversed?(0,h.reversed)(this.items):this.items;for(const i of e){let e;if(null==i)e=(0,l.div)({class:r.divider});else{if(null!=i.if&&!i.if())continue;if(null!=i.content)e=i.content;else{const n=null!=i.icon?(0,l.div)({class:[\"bk-menu-icon\",i.icon]}):null,o=[(null===(t=i.active)||void 0===t?void 0:t.call(i))?\"bk-active\":null,i.class];e=(0,l.div)({class:o,title:i.tooltip,tabIndex:0},n,i.label,i.content),e.addEventListener(\"click\",(()=>{this._item_click(i)})),e.addEventListener(\"keydown\",(t=>{t.keyCode==l.Keys.Enter&&this._item_click(i)}))}}this.el.appendChild(e)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),(0,l.display)(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),(0,l.undisplay)(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=d,d.__name__=\"ContextMenu\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),c=t(224),l=(0,s.__importStar)(t(227)),a=t(43);class _ extends c.ButtonToolButtonView{render(){super.render(),(0,a.classes)(this.el).toggle(l.active,this.model.active)}_clicked(){const{active:t}=this.model;this.model.active=!t}}i.OnOffButtonView=_,_.__name__=\"OnOffButtonView\"},\n", - " function _(e,o,t,n,s){var c;n();const l=e(224),_=e(231);class i extends l.ButtonToolView{}t.InspectToolView=i,i.__name__=\"InspectToolView\";class a extends l.ButtonTool{constructor(e){super(e),this.event_type=\"move\"}}t.InspectTool=a,c=a,a.__name__=\"InspectTool\",c.prototype.button_view=_.OnOffButtonView,c.define((({Boolean:e})=>({toggleable:[e,!0]}))),c.override({active:!0})},\n", - " function _(t,o,e,l,i){l();const s=t(1);var n,a;const r=t(19),c=t(43),h=t(113),_=t(226),u=t(20),v=t(9),d=t(234),p=t(13),b=t(8),g=t(235),f=t(65),m=t(53),w=t(222),y=t(223),T=t(238),z=t(239),x=t(232),B=t(230),C=(0,s.__importStar)(t(227)),k=C,L=(0,s.__importStar)(t(240)),M=L;class S extends m.Model{constructor(t){super(t)}get visible(){var t;return!this.autohide||null!==(t=this._visible)&&void 0!==t&&t}}e.ToolbarViewModel=S,n=S,S.__name__=\"ToolbarViewModel\",n.define((({Boolean:t})=>({autohide:[t,!1]}))),n.internal((({Boolean:t,Nullable:o})=>({_visible:[o(t),null]})));class $ extends _.DOMView{constructor(){super(...arguments),this.layout={bbox:new f.BBox}}initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new S({autohide:this.model.autohide});const{toolbar_location:t}=this.model,o=\"left\"==t||\"above\"==t,e=this.model.horizontal?\"vertical\":\"horizontal\";this._overflow_menu=new B.ContextMenu([],{orientation:e,reversed:o})}async lazy_initialize(){await super.lazy_initialize(),await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,(async()=>{await this._build_tool_button_views(),this.render()})),this.connect(this.model.properties.autohide.change,(()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()})),this.connect(this._toolbar_view_model.properties._visible.change,(()=>this._on_visible_change()))}styles(){return[...super.styles(),C.default,L.default]}remove(){(0,h.remove_views)(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await(0,h.build_views)(this._tool_button_views,t,{parent:this},(t=>t.button_view))}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const{visible:t}=this._toolbar_view_model;(0,c.classes)(this.el).toggle(k.toolbar_hidden,!t)}render(){(0,c.empty)(this.el),this.el.classList.add(k.toolbar),this.el.classList.add(k[this.model.toolbar_location]),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change();const{horizontal:t}=this.model;let o=0;if(null!=this.model.logo){const e=\"grey\"===this.model.logo?M.grey:null,l=(0,c.a)({href:\"https://bokeh.org/\",target:\"_blank\",class:[M.logo,M.logo_small,e]});this.el.appendChild(l);const{width:i,height:s}=l.getBoundingClientRect();o+=t?i:s}for(const[,t]of this._tool_button_views)t.render();const e=[],l=t=>this._tool_button_views.get(t).el,{gestures:i}=this.model;for(const t of(0,p.values)(i))e.push(t.tools.map(l));e.push(this.model.actions.map(l)),e.push(this.model.inspectors.filter((t=>t.toggleable)).map(l));const s=e.filter((t=>0!=t.length)),n=()=>(0,c.div)({class:k.divider}),{bbox:a}=this.layout;let r=!1;this.root.el.appendChild(this._overflow_menu.el);const h=(0,c.div)({class:k.tool_overflow,tabIndex:0},t?\"\\u22ee\":\"\\u22ef\"),_=()=>{const t=(()=>{switch(this.model.toolbar_location){case\"right\":return{left_of:h};case\"left\":return{right_of:h};case\"above\":return{below:h};case\"below\":return{above:h}}})();this._overflow_menu.toggle(t)};h.addEventListener(\"click\",(()=>{_()})),h.addEventListener(\"keydown\",(t=>{t.keyCode==c.Keys.Enter&&_()}));for(const e of(0,d.join)(s,n))if(r)this._overflow_menu.items.push({content:e,class:t?k.right:k.above});else{this.el.appendChild(e);const{width:l,height:i}=e.getBoundingClientRect();if(o+=t?l:i,r=t?o>a.width-15:o>a.height-15,r){this.el.removeChild(e),this.el.appendChild(h);const{items:t}=this._overflow_menu;t.splice(0,t.length),t.push({content:e})}}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}export(t,o=!0){const e=\"png\"==t?\"canvas\":\"svg\",l=new g.CanvasLayer(e,o);return l.resize(0,0),l}}function V(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=$,$.__name__=\"ToolbarBaseView\";class A extends m.Model{constructor(t){super(t)}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map((t=>t.id)));return(0,v.some)(t,(t=>!e.has(t.id)))},o=this.tools.filter((t=>t instanceof x.InspectTool));t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter((t=>t instanceof z.HelpTool));t(this.help,e)&&(this.help=e);const l=this.tools.filter((t=>t instanceof T.ActionTool));t(this.actions,l)&&(this.actions=l);const i=(t,o)=>{t in this.gestures||r.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},s={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof y.GestureTool&&t.event_type)if((0,b.isString)(t.event_type))s[t.event_type].tools.push(t),i(t.event_type,t);else{s.multi.tools.push(t);for(const o of t.event_type)i(o,t)}for(const o of Object.keys(s)){const e=this.gestures[o];t(e.tools,s[o].tools)&&(e.tools=s[o].tools),e.active&&(0,v.every)(e.tools,(t=>t.id!=e.active.id))&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=(0,b.isString)(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(r.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,r.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=A,a=A,A.__name__=\"ToolbarBase\",a.prototype.default_view=$,a.define((({Boolean:t,Array:o,Ref:e,Nullable:l})=>({tools:[o(e(w.Tool)),[]],logo:[l(u.Logo),\"normal\"],autohide:[t,!1]}))),a.internal((({Array:t,Struct:o,Ref:e,Nullable:l})=>{const i=o({tools:t(e(y.GestureTool)),active:l(e(w.Tool))});return{gestures:[o({pan:i,scroll:i,pinch:i,tap:i,doubletap:i,press:i,pressup:i,rotate:i,move:i,multi:i}),V],actions:[t(e(T.ActionTool)),[]],inspectors:[t(e(x.InspectTool)),[]],help:[t(e(z.HelpTool)),[]],toolbar_location:[u.Location,\"right\"]}}))},\n", - " function _(n,o,e,t,f){t();const r=n(9);function*i(n,o){const e=n.length;if(o>e)return;const t=(0,r.range)(o);for(yield t.map((o=>n[o]));;){let f;for(const n of(0,r.reversed)((0,r.range)(o)))if(t[n]!=n+e-o){f=n;break}if(null==f)return;t[f]+=1;for(const n of(0,r.range)(f+1,o))t[n]=t[n-1]+1;yield t.map((o=>n[o]))}}e.enumerate=function*(n){let o=0;for(const e of n)yield[e,o++]},e.join=function*(n,o){let e=!0;for(const t of n)e?e=!1:null!=o&&(yield o()),yield*t},e.combinations=i,e.subsets=function*(n){for(const o of(0,r.range)(n.length+1))yield*i(n,o)}},\n", - " function _(t,e,s,i,n){i();const o=t(236),a=t(65),r=t(43);function h(t){!function(t){void 0===t.lineDash&&Object.defineProperty(t,\"lineDash\",{get:()=>t.getLineDash(),set:e=>t.setLineDash(e)})}(t),function(t){t.setImageSmoothingEnabled=e=>{t.imageSmoothingEnabled=e,t.mozImageSmoothingEnabled=e,t.oImageSmoothingEnabled=e,t.webkitImageSmoothingEnabled=e,t.msImageSmoothingEnabled=e},t.getImageSmoothingEnabled=()=>{const e=t.imageSmoothingEnabled;return null==e||e}}(t),function(t){t.ellipse||(t.ellipse=function(e,s,i,n,o,a,r,h=!1){const l=.551784;t.translate(e,s),t.rotate(o);let c=i,g=n;h&&(c=-i,g=-n),t.moveTo(-c,0),t.bezierCurveTo(-c,g*l,-c*l,g,0,g),t.bezierCurveTo(c*l,g,c,g*l,c,0),t.bezierCurveTo(c,-g*l,c*l,-g,0,-g),t.bezierCurveTo(-c*l,-g,-c,-g*l,-c,0),t.rotate(-o),t.translate(-e,-s)})}(t)}const 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t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}this._clear_webgl()}}_clear_webgl(){const{webgl:e}=this;if(null!=e){const{regl_wrapper:t,canvas:i}=e;t.clear(i.width,i.height)}}compose(){const e=this.create_layer(),{width:t,height:i}=this.bbox;return e.resize(t,i),e.ctx.drawImage(this.primary.canvas,0,0),e.ctx.drawImage(this.overlays.canvas,0,0),e}create_layer(){const{output_backend:e,hidpi:t}=this.model;return new y.CanvasLayer(e,t)}to_blob(){return this.compose().to_blob()}}i.CanvasView=x,x.__name__=\"CanvasView\";class z extends h.HasProps{constructor(e){super(e)}}i.Canvas=z,l=z,z.__name__=\"Canvas\",l.prototype.default_view=x,l.internal((({Boolean:e})=>({hidpi:[e,!0],output_backend:[p.OutputBackend,\"canvas\"]})))},\n", - " function _(t,e,s,n,i){n();const r=t(1),a=(0,r.__importDefault)(t(225)),_=t(15),h=t(19),o=t(43),l=(0,r.__importStar)(t(251)),c=t(252),p=t(9),u=t(8),v=t(27),d=t(230);class g{constructor(t){this.canvas_view=t,this.pan_start=new _.Signal(this,\"pan:start\"),this.pan=new _.Signal(this,\"pan\"),this.pan_end=new _.Signal(this,\"pan:end\"),this.pinch_start=new _.Signal(this,\"pinch:start\"),this.pinch=new _.Signal(this,\"pinch\"),this.pinch_end=new _.Signal(this,\"pinch:end\"),this.rotate_start=new _.Signal(this,\"rotate:start\"),this.rotate=new _.Signal(this,\"rotate\"),this.rotate_end=new _.Signal(this,\"rotate:end\"),this.tap=new _.Signal(this,\"tap\"),this.doubletap=new _.Signal(this,\"doubletap\"),this.press=new _.Signal(this,\"press\"),this.pressup=new _.Signal(this,\"pressup\"),this.move_enter=new _.Signal(this,\"move:enter\"),this.move=new _.Signal(this,\"move\"),this.move_exit=new _.Signal(this,\"move:exit\"),this.scroll=new _.Signal(this,\"scroll\"),this.keydown=new _.Signal(this,\"keydown\"),this.keyup=new _.Signal(this,\"keyup\"),this.hammer=new a.default(this.hit_area,{touchAction:\"auto\",inputClass:a.default.TouchMouseInput}),this._prev_move=null,this._curr_pan=null,this._curr_pinch=null,this._curr_rotate=null,this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",(t=>this._mouse_move(t))),this.hit_area.addEventListener(\"mouseenter\",(t=>this._mouse_enter(t))),this.hit_area.addEventListener(\"mouseleave\",(t=>this._mouse_exit(t))),this.hit_area.addEventListener(\"contextmenu\",(t=>this._context_menu(t))),this.hit_area.addEventListener(\"wheel\",(t=>this._mouse_wheel(t))),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new d.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}get hit_area(){return this.canvas_view.events_el}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",(t=>this._doubletap(t))),this.hammer.on(\"tap\",(t=>this._tap(t))),this.hammer.on(\"press\",(t=>this._press(t))),this.hammer.on(\"pressup\",(t=>this._pressup(t))),this.hammer.get(\"pan\").set({direction:a.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",(t=>this._pan_start(t))),this.hammer.on(\"pan\",(t=>this._pan(t))),this.hammer.on(\"panend\",(t=>this._pan_end(t))),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",(t=>this._pinch_start(t))),this.hammer.on(\"pinch\",(t=>this._pinch(t))),this.hammer.on(\"pinchend\",(t=>this._pinch_end(t))),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",(t=>this._rotate_start(t))),this.hammer.on(\"rotate\",(t=>this._rotate(t))),this.hammer.on(\"rotateend\",(t=>this._rotate_end(t)))}register_tool(t){const e=t.model.event_type;null!=e&&((0,u.isString)(e)?this._register_tool(t,e):e.forEach(((e,s)=>this._register_tool(t,e,s<1))))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},a=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n))),null!=n._doubletap&&n.connect(this.doubletap,r(n._doubletap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(`unsupported event_type: ${e}`)}s&&(null!=n._keydown&&n.connect(this.keydown,a(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,a(n._keyup.bind(n))),v.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(h.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e,s){var n;const i=t.get_renderer_views();for(const t of(0,p.reversed)(i))if(null===(n=t.interactive_hit)||void 0===n?void 0:n.call(t,e,s))return t;return null}set_cursor(t=\"default\"){this.hit_area.style.cursor=t}_hit_test_frame(t,e,s){return t.frame.bbox.contains(e,s)}_hit_test_canvas(t,e,s){return t.layout.bbox.contains(e,s)}_hit_test_plot(t,e){for(const s of this.canvas_view.plot_views)if(s.layout.bbox.relative().contains(t,e))return s;return null}_trigger(t,e,s){var n;const{sx:i,sy:r}=e,a=this._hit_test_plot(i,r),_=t=>{const[s,n]=[i,r];return Object.assign(Object.assign({},e),{sx:s,sy:n})};if(\"panstart\"==e.type||\"pan\"==e.type||\"panend\"==e.type){let n;if(\"panstart\"==e.type&&null!=a?(this._curr_pan={plot_view:a},n=a):\"pan\"==e.type&&null!=this._curr_pan?n=this._curr_pan.plot_view:\"panend\"==e.type&&null!=this._curr_pan?(n=this._curr_pan.plot_view,this._curr_pan=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"pinchstart\"==e.type||\"pinch\"==e.type||\"pinchend\"==e.type){let n;if(\"pinchstart\"==e.type&&null!=a?(this._curr_pinch={plot_view:a},n=a):\"pinch\"==e.type&&null!=this._curr_pinch?n=this._curr_pinch.plot_view:\"pinchend\"==e.type&&null!=this._curr_pinch?(n=this._curr_pinch.plot_view,this._curr_pinch=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"rotatestart\"==e.type||\"rotate\"==e.type||\"rotateend\"==e.type){let n;if(\"rotatestart\"==e.type&&null!=a?(this._curr_rotate={plot_view:a},n=a):\"rotate\"==e.type&&null!=this._curr_rotate?n=this._curr_rotate.plot_view:\"rotateend\"==e.type&&null!=this._curr_rotate?(n=this._curr_rotate.plot_view,this._curr_rotate=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"mouseenter\"==e.type||\"mousemove\"==e.type||\"mouseleave\"==e.type){const h=null===(n=this._prev_move)||void 0===n?void 0:n.plot_view;if(null!=h&&(\"mouseleave\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(h,this.move_exit,{type:\"mouseleave\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&(\"mouseenter\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(a,this.move_enter,{type:\"mouseenter\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&\"mousemove\"==e.type){const e=_();this.__trigger(a,t,e,s)}this._prev_move={sx:i,sy:r,plot_view:a}}else if(null!=a){const e=_();this.__trigger(a,t,e,s)}}__trigger(t,e,s,n){var i,r,a;const _=t.model.toolbar.gestures,h=e.name.split(\":\")[0],o=this._hit_test_renderers(t,s.sx,s.sy),l=this._hit_test_canvas(t,s.sx,s.sy);switch(h){case\"move\":{const n=_.move.active;null!=n&&this.trigger(e,s,n.id);const r=t.model.toolbar.inspectors.filter((t=>t.active));let a=\"default\";null!=o?(a=null!==(i=o.cursor(s.sx,s.sy))&&void 0!==i?i:a,(0,p.is_empty)(r)||(e=this.move_exit)):this._hit_test_frame(t,s.sx,s.sy)&&((0,p.is_empty)(r)||(a=\"crosshair\")),this.set_cursor(a),t.set_toolbar_visibility(l),r.map((t=>this.trigger(e,s,t.id)));break}case\"tap\":{const{target:i}=n;if(null!=i&&i!=this.hit_area)return;if(null===(r=null==o?void 0:o.on_hit)||void 0===r||r.call(o,s.sx,s.sy),this._hit_test_frame(t,s.sx,s.sy)){const t=_.tap.active;null!=t&&this.trigger(e,s,t.id)}break}case\"doubletap\":if(this._hit_test_frame(t,s.sx,s.sy)){const t=null!==(a=_.doubletap.active)&&void 0!==a?a:_.tap.active;null!=t&&this.trigger(e,s,t.id)}break;case\"scroll\":{const t=_[v.is_mobile?\"pinch\":\"scroll\"].active;null!=t&&(n.preventDefault(),n.stopPropagation(),this.trigger(e,s,t.id));break}case\"pan\":{const t=_.pan.active;null!=t&&(n.preventDefault(),this.trigger(e,s,t.id));break}default:{const t=_[h].active;null!=t&&this.trigger(e,s,t.id)}}this._trigger_bokeh_event(t,s)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t,e){const s=(()=>{const{sx:s,sy:n}=e,i=t.frame.x_scale.invert(s),r=t.frame.y_scale.invert(n);switch(e.type){case\"wheel\":return new l.MouseWheel(s,n,i,r,e.delta);case\"mousemove\":return new l.MouseMove(s,n,i,r);case\"mouseenter\":return new l.MouseEnter(s,n,i,r);case\"mouseleave\":return new l.MouseLeave(s,n,i,r);case\"tap\":return new l.Tap(s,n,i,r);case\"doubletap\":return new l.DoubleTap(s,n,i,r);case\"press\":return new l.Press(s,n,i,r);case\"pressup\":return new l.PressUp(s,n,i,r);case\"pan\":return new l.Pan(s,n,i,r,e.deltaX,e.deltaY);case\"panstart\":return new l.PanStart(s,n,i,r);case\"panend\":return new l.PanEnd(s,n,i,r);case\"pinch\":return new l.Pinch(s,n,i,r,e.scale);case\"pinchstart\":return new l.PinchStart(s,n,i,r);case\"pinchend\":return new l.PinchEnd(s,n,i,r);case\"rotate\":return new l.Rotate(s,n,i,r,e.rotation);case\"rotatestart\":return new l.RotateStart(s,n,i,r);case\"rotateend\":return new l.RotateEnd(s,n,i,r);default:return}})();null!=s&&t.model.trigger_event(s)}_get_sxy(t){const{pageX:e,pageY:s}=function(t){return\"undefined\"!=typeof TouchEvent&&t instanceof TouchEvent}(t)?(0!=t.touches.length?t.touches:t.changedTouches)[0]:t,{left:n,top:i}=(0,o.offset)(this.hit_area);return{sx:e-n,sy:s-i}}_pan_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{deltaX:t.deltaX,deltaY:t.deltaY,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_pinch_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{scale:t.scale,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_rotate_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{rotation:t.rotation,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_tap_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_move_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_scroll_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t)),{delta:(0,c.getDeltaY)(t),shiftKey:t.shiftKey,ctrlKey:t.ctrlKey})}_key_event(t){return{type:t.type,keyCode:t.keyCode}}_pan_start(t){const e=this._pan_event(t);e.sx-=t.deltaX,e.sy-=t.deltaY,this._trigger(this.pan_start,e,t.srcEvent)}_pan(t){this._trigger(this.pan,this._pan_event(t),t.srcEvent)}_pan_end(t){this._trigger(this.pan_end,this._pan_event(t),t.srcEvent)}_pinch_start(t){this._trigger(this.pinch_start,this._pinch_event(t),t.srcEvent)}_pinch(t){this._trigger(this.pinch,this._pinch_event(t),t.srcEvent)}_pinch_end(t){this._trigger(this.pinch_end,this._pinch_event(t),t.srcEvent)}_rotate_start(t){this._trigger(this.rotate_start,this._rotate_event(t),t.srcEvent)}_rotate(t){this._trigger(this.rotate,this._rotate_event(t),t.srcEvent)}_rotate_end(t){this._trigger(this.rotate_end,this._rotate_event(t),t.srcEvent)}_tap(t){this._trigger(this.tap,this._tap_event(t),t.srcEvent)}_doubletap(t){this._trigger(this.doubletap,this._tap_event(t),t.srcEvent)}_press(t){this._trigger(this.press,this._tap_event(t),t.srcEvent)}_pressup(t){this._trigger(this.pressup,this._tap_event(t),t.srcEvent)}_mouse_enter(t){this._trigger(this.move_enter,this._move_event(t),t)}_mouse_move(t){this._trigger(this.move,this._move_event(t),t)}_mouse_exit(t){this._trigger(this.move_exit,this._move_event(t),t)}_mouse_wheel(t){this._trigger(this.scroll,this._scroll_event(t),t)}_context_menu(t){!this.menu.is_open&&this.menu.can_open&&t.preventDefault();const{sx:e,sy:s}=this._get_sxy(t);this.menu.toggle({left:e,top:s})}_key_down(t){this.trigger(this.keydown,this._key_event(t))}_key_up(t){this.trigger(this.keyup,this._key_event(t))}}s.UIEventBus=g,g.__name__=\"UIEventBus\"},\n", 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c{constructor(e){super(),this.item=e}_to_json(){const{item:e}=this;return Object.assign(Object.assign({},super._to_json()),{item:e})}};s.MenuItemClick=u,u.__name__=\"MenuItemClick\",s.MenuItemClick=u=a([o(\"menu_item_click\")],u);class d extends c{}s.UIEvent=d,d.__name__=\"UIEvent\";let m=class extends d{};s.LODStart=m,m.__name__=\"LODStart\",s.LODStart=m=a([o(\"lodstart\")],m);let h=class extends d{};s.LODEnd=h,h.__name__=\"LODEnd\",s.LODEnd=h=a([o(\"lodend\")],h);let p=class extends d{constructor(e,t,s,n){super(),this.x0=e,this.x1=t,this.y0=s,this.y1=n}_to_json(){const{x0:e,x1:t,y0:s,y1:n}=this;return Object.assign(Object.assign({},super._to_json()),{x0:e,x1:t,y0:s,y1:n})}};s.RangesUpdate=p,p.__name__=\"RangesUpdate\",s.RangesUpdate=p=a([o(\"rangesupdate\")],p);let x=class extends d{constructor(e,t){super(),this.geometry=e,this.final=t}_to_json(){const{geometry:e,final:t}=this;return Object.assign(Object.assign({},super._to_json()),{geometry:e,final:t})}};s.SelectionGeometry=x,x.__name__=\"SelectionGeometry\",s.SelectionGeometry=x=a([o(\"selectiongeometry\")],x);let j=class extends d{};s.Reset=j,j.__name__=\"Reset\",s.Reset=j=a([o(\"reset\")],j);class y extends d{constructor(e,t,s,n){super(),this.sx=e,this.sy=t,this.x=s,this.y=n}_to_json(){const{sx:e,sy:t,x:s,y:n}=this;return Object.assign(Object.assign({},super._to_json()),{sx:e,sy:t,x:s,y:n})}}s.PointEvent=y,y.__name__=\"PointEvent\";let g=class extends y{constructor(e,t,s,n,_,a){super(e,t,s,n),this.delta_x=_,this.delta_y=a}_to_json(){const{delta_x:e,delta_y:t}=this;return Object.assign(Object.assign({},super._to_json()),{delta_x:e,delta_y:t})}};s.Pan=g,g.__name__=\"Pan\",s.Pan=g=a([o(\"pan\")],g);let P=class extends y{constructor(e,t,s,n,_){super(e,t,s,n),this.scale=_}_to_json(){const{scale:e}=this;return Object.assign(Object.assign({},super._to_json()),{scale:e})}};s.Pinch=P,P.__name__=\"Pinch\",s.Pinch=P=a([o(\"pinch\")],P);let O=class extends y{constructor(e,t,s,n,_){super(e,t,s,n),this.rotation=_}_to_json(){const{rotation:e}=this;return Object.assign(Object.assign({},super._to_json()),{rotation:e})}};s.Rotate=O,O.__name__=\"Rotate\",s.Rotate=O=a([o(\"rotate\")],O);let b=class extends y{constructor(e,t,s,n,_){super(e,t,s,n),this.delta=_}_to_json(){const{delta:e}=this;return Object.assign(Object.assign({},super._to_json()),{delta:e})}};s.MouseWheel=b,b.__name__=\"MouseWheel\",s.MouseWheel=b=a([o(\"wheel\")],b);let v=class extends y{};s.MouseMove=v,v.__name__=\"MouseMove\",s.MouseMove=v=a([o(\"mousemove\")],v);let E=class extends y{};s.MouseEnter=E,E.__name__=\"MouseEnter\",s.MouseEnter=E=a([o(\"mouseenter\")],E);let R=class extends y{};s.MouseLeave=R,R.__name__=\"MouseLeave\",s.MouseLeave=R=a([o(\"mouseleave\")],R);let M=class extends y{};s.Tap=M,M.__name__=\"Tap\",s.Tap=M=a([o(\"tap\")],M);let f=class extends y{};s.DoubleTap=f,f.__name__=\"DoubleTap\",s.DoubleTap=f=a([o(\"doubletap\")],f);let S=class extends y{};s.Press=S,S.__name__=\"Press\",s.Press=S=a([o(\"press\")],S);let D=class extends y{};s.PressUp=D,D.__name__=\"PressUp\",s.PressUp=D=a([o(\"pressup\")],D);let k=class extends y{};s.PanStart=k,k.__name__=\"PanStart\",s.PanStart=k=a([o(\"panstart\")],k);let L=class extends y{};s.PanEnd=L,L.__name__=\"PanEnd\",s.PanEnd=L=a([o(\"panend\")],L);let U=class extends y{};s.PinchStart=U,U.__name__=\"PinchStart\",s.PinchStart=U=a([o(\"pinchstart\")],U);let C=class extends y{};s.PinchEnd=C,C.__name__=\"PinchEnd\",s.PinchEnd=C=a([o(\"pinchend\")],C);let T=class extends y{};s.RotateStart=T,T.__name__=\"RotateStart\",s.RotateStart=T=a([o(\"rotatestart\")],T);let B=class extends y{};s.RotateEnd=B,B.__name__=\"RotateEnd\",s.RotateEnd=B=a([o(\"rotateend\")],B)},\n", - " function _(t,e,n,l,o){\n", - " /*!\n", - " * jQuery 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function _(e,n,t,o,r){var i;o();const l=e(254);class u extends l.Expression{constructor(e){super(e)}_v_compute(e){var n;const t=new Float64Array(null!==(n=e.get_length())&&void 0!==n?n:0),o=e.data[this.field],r=this.include_zero?1:0;t[0]=this.include_zero?0:o[0];for(let e=1;e({field:[n],include_zero:[e,!1]})))},\n", - " function _(i,n,l,t,e){var a;t();const u=i(254),r=i(9);class s extends u.ScalarExpression{constructor(i){super(i)}_compute(i){var n,l;const t=null!==(n=i.data[this.field])&&void 0!==n?n:[];return Math.min(null!==(l=this.initial)&&void 0!==l?l:1/0,(0,r.min)(t))}}l.Minimum=s,a=s,s.__name__=\"Minimum\",a.define((({Number:i,String:n,Nullable:l})=>({field:[n],initial:[l(i),null]})))},\n", - " function _(i,a,n,l,t){var e;l();const u=i(254),r=i(9);class s extends u.ScalarExpression{constructor(i){super(i)}_compute(i){var a,n;const l=null!==(a=i.data[this.field])&&void 0!==a?a:[];return Math.max(null!==(n=this.initial)&&void 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_=e(178),o=e(184),d=e(48),u=e(24),h=e(20),c=(0,n.__importStar)(e(18)),l=e(10),g=e(72),p=e(12);class x extends _.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,u.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,u.to_screen)(this.outer_radius),this.max_souter_radius=(0,p.max)(this.souter_radius)}_render(e,s,t){const{sx:i,sy:r,start_angle:n,end_angle:a,sinner_radius:_,souter_radius:o}=null!=t?t:this,d=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],u=r[t],h=_[t],c=o[t],l=n.get(t),g=a.get(t);if(!isFinite(s+u+h+c+l+g))continue;const p=g-l;e.translate(s,u),e.rotate(l),e.beginPath(),e.moveTo(c,0),e.arc(0,0,c,0,p,d),e.rotate(p),e.lineTo(h,0),e.arc(0,0,h,0,-p,!d),e.closePath(),e.rotate(-p-l),e.translate(-s,-u),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t)}}_hit_point(e){const{sx:s,sy:t}=e,i=this.renderer.xscale.invert(s),r=this.renderer.yscale.invert(t),n=s-this.max_souter_radius,a=s+this.max_souter_radius,[_,o]=this.renderer.xscale.r_invert(n,a),d=t-this.max_souter_radius,u=t+this.max_souter_radius,[h,c]=this.renderer.yscale.r_invert(d,u),p=[];for(const e of this.index.indices({x0:_,x1:o,y0:h,y1:c})){const s=this.souter_radius[e]**2,t=this.sinner_radius[e]**2,[n,a]=this.renderer.xscale.r_compute(i,this._x[e]),[_,o]=this.renderer.yscale.r_compute(r,this._y[e]),d=(n-a)**2+(_-o)**2;d<=s&&d>=t&&p.push(e)}const x=\"anticlock\"==this.model.direction,m=[];for(const e of p){const i=Math.atan2(t-this.sy[e],s-this.sx[e]);(0,l.angle_between)(-i,-this.start_angle.get(e),-this.end_angle.get(e),x)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,o.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=(this.sinner_radius[e]+this.souter_radius[e])/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.AnnularWedgeView=x,x.__name__=\"AnnularWedgeView\";class m extends _.XYGlyph{constructor(e){super(e)}}t.AnnularWedge=m,a=m,m.__name__=\"AnnularWedge\",a.prototype.default_view=x,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],inner_radius:[c.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[c.DistanceSpec,{field:\"outer_radius\"}],start_angle:[c.AngleSpec,{field:\"start_angle\"}],end_angle:[c.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(s,e,i,r,t){r();const n=s(1);var a;const u=s(178),o=s(24),_=s(48),d=(0,n.__importStar)(s(18)),h=s(27),c=s(72);class l extends u.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,o.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,o.to_screen)(this.outer_radius)}_render(s,e,i){const{sx:r,sy:t,sinner_radius:n,souter_radius:a}=null!=i?i:this;for(const i of e){const e=r[i],u=t[i],o=n[i],_=a[i];if(isFinite(e+u+o+_)){if(s.beginPath(),h.is_ie)for(const i of[!1,!0])s.moveTo(e,u),s.arc(e,u,o,0,Math.PI,i),s.moveTo(e+_,u),s.arc(e,u,_,Math.PI,0,!i);else s.arc(e,u,o,0,2*Math.PI,!0),s.moveTo(e+_,u),s.arc(e,u,_,2*Math.PI,0,!1);this.visuals.fill.apply(s,i),this.visuals.hatch.apply(s,i),this.visuals.line.apply(s,i)}}}_hit_point(s){const{sx:e,sy:i}=s,r=this.renderer.xscale.invert(e),t=this.renderer.yscale.invert(i);let n,a,u,o;if(\"data\"==this.model.properties.outer_radius.units)n=r-this.max_outer_radius,u=r+this.max_outer_radius,a=t-this.max_outer_radius,o=t+this.max_outer_radius;else{const s=e-this.max_outer_radius,r=e+this.max_outer_radius;[n,u]=this.renderer.xscale.r_invert(s,r);const t=i-this.max_outer_radius,_=i+this.max_outer_radius;[a,o]=this.renderer.yscale.r_invert(t,_)}const _=[];for(const s of this.index.indices({x0:n,x1:u,y0:a,y1:o})){const e=this.souter_radius[s]**2,i=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(r,this._x[s]),[u,o]=this.renderer.yscale.r_compute(t,this._y[s]),d=(n-a)**2+(u-o)**2;d<=e&&d>=i&&_.push(s)}return new c.Selection({indices:_})}draw_legend_for_index(s,{x0:e,y0:i,x1:r,y1:t},n){const a=n+1,u=new Array(a);u[n]=(e+r)/2;const o=new Array(a);o[n]=(i+t)/2;const _=.5*Math.min(Math.abs(r-e),Math.abs(t-i)),d=new Array(a);d[n]=.4*_;const h=new Array(a);h[n]=.8*_,this._render(s,[n],{sx:u,sy:o,sinner_radius:d,souter_radius:h})}}i.AnnulusView=l,l.__name__=\"AnnulusView\";class x extends u.XYGlyph{constructor(s){super(s)}}i.Annulus=x,a=x,x.__name__=\"Annulus\",a.prototype.default_view=l,a.mixins([_.LineVector,_.FillVector,_.HatchVector]),a.define((({})=>({inner_radius:[d.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[d.DistanceSpec,{field:\"outer_radius\"}]})))},\n", - " function _(e,i,s,t,n){t();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),_=e(24),o=e(20),u=(0,r.__importStar)(e(18));class h extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,_.to_screen)(this.radius)}_render(e,i,s){if(this.visuals.line.doit){const{sx:t,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of i){const i=t[s],l=n[s],_=r[s],o=a.get(s),u=c.get(s);isFinite(i+l+_+o+u)&&(e.beginPath(),e.arc(i,l,_,o,u,d),this.visuals.line.set_vectorize(e,s),e.stroke())}}}draw_legend_for_index(e,i,s){(0,d.generic_line_vector_legend)(this.visuals,e,i,s)}}s.ArcView=h,h.__name__=\"ArcView\";class g extends c.XYGlyph{constructor(e){super(e)}}s.Arc=g,a=g,g.__name__=\"Arc\",a.prototype.default_view=h,a.mixins(l.LineVector),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[u.DistanceSpec,{field:\"radius\"}],start_angle:[u.AngleSpec,{field:\"start_angle\"}],end_angle:[u.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(e,t,i,n,s){n();const o=e(1);var c;const r=e(48),a=e(179),_=e(184),d=e(78),l=(0,o.__importStar)(e(18));function x(e,t,i,n,s,o,c,r){const a=[],_=[[],[]];for(let _=0;_<=2;_++){let d,l,x;if(0===_?(l=6*e-12*i+6*s,d=-3*e+9*i-9*s+3*c,x=3*i-3*e):(l=6*t-12*n+6*o,d=-3*t+9*n-9*o+3*r,x=3*n-3*t),Math.abs(d)<1e-12){if(Math.abs(l)<1e-12)continue;const e=-x/l;0({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx0:[l.XCoordinateSpec,{field:\"cx0\"}],cy0:[l.YCoordinateSpec,{field:\"cy0\"}],cx1:[l.XCoordinateSpec,{field:\"cx1\"}],cy1:[l.YCoordinateSpec,{field:\"cy1\"}]}))),c.mixins(r.LineVector)},\n", - " function _(s,i,e,t,r){t();const a=s(1);var n;const h=s(178),d=s(48),l=s(24),_=s(20),c=(0,a.__importStar)(s(185)),u=(0,a.__importStar)(s(18)),o=s(9),x=s(12),m=s(72);class p extends h.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:i}=this.renderer.plot_view.canvas_view;if(null!=i&&i.regl_wrapper.has_webgl){const{CircleGL:e}=await Promise.resolve().then((()=>(0,a.__importStar)(s(423))));this.glglyph=new e(i.regl_wrapper,this)}}get use_radius(){return!(this.radius.is_Scalar()&&isNaN(this.radius.value))}_set_data(s){super._set_data(s);const i=(()=>{if(this.use_radius)return 2*this.max_radius;{const{size:s}=this;return s.is_Scalar()?s.value:(0,x.max)(s.array)}})();this._configure(\"max_size\",{value:i})}_map_data(){if(this.use_radius)if(\"data\"==this.model.properties.radius.units)switch(this.model.radius_dimension){case\"x\":this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius);break;case\"y\":this.sradius=this.sdist(this.renderer.yscale,this._y,this.radius);break;case\"max\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.max(s,i[e])));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.min(s,i[e])));break}}else this.sradius=(0,l.to_screen)(this.radius);else{const s=l.ScreenArray.from(this.size);this.sradius=(0,x.map)(s,(s=>s/2))}}_mask_data(){const{frame:s}=this.renderer.plot_view,i=s.x_target,e=s.y_target;let t,r;return this.use_radius&&\"data\"==this.model.properties.radius.units?(t=i.map((s=>this.renderer.xscale.invert(s))).widen(this.max_radius),r=e.map((s=>this.renderer.yscale.invert(s))).widen(this.max_radius)):(t=i.widen(this.max_size).map((s=>this.renderer.xscale.invert(s))),r=e.widen(this.max_size).map((s=>this.renderer.yscale.invert(s)))),this.index.indices({x0:t.start,x1:t.end,y0:r.start,y1:r.end})}_render(s,i,e){const{sx:t,sy:r,sradius:a}=null!=e?e:this;for(const e of i){const i=t[e],n=r[e],h=a[e];isFinite(i+n+h)&&(s.beginPath(),s.arc(i,n,h,0,2*Math.PI,!1),this.visuals.fill.apply(s,e),this.visuals.hatch.apply(s,e),this.visuals.line.apply(s,e))}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e),{hit_dilation:a}=this.model;let n,h,d,l;if(this.use_radius&&\"data\"==this.model.properties.radius.units)n=t-this.max_radius*a,h=t+this.max_radius*a,d=r-this.max_radius*a,l=r+this.max_radius*a;else{const s=i-this.max_size*a,t=i+this.max_size*a;[n,h]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size*a,_=e+this.max_size*a;[d,l]=this.renderer.yscale.r_invert(r,_)}const _=this.index.indices({x0:n,x1:h,y0:d,y1:l}),c=[];if(this.use_radius&&\"data\"==this.model.properties.radius.units)for(const s of _){const i=(this.sradius[s]*a)**2,[e,n]=this.renderer.xscale.r_compute(t,this._x[s]),[h,d]=this.renderer.yscale.r_compute(r,this._y[s]);(e-n)**2+(h-d)**2<=i&&c.push(s)}else for(const s of _){const t=(this.sradius[s]*a)**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&c.push(s)}return new m.Selection({indices:c})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new m.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new m.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=(0,o.range)(0,this.sx.length),r=[];for(let s=0,a=t.length;s({angle:[u.AngleSpec,0],size:[u.ScreenSizeSpec,{value:4}],radius:[u.NullDistanceSpec,null],radius_dimension:[_.RadiusDimension,\"x\"],hit_dilation:[s,1]})))},\n", - " function _(e,l,s,i,_){var p;i();const t=e(274);class a extends t.EllipseOvalView{}s.EllipseView=a,a.__name__=\"EllipseView\";class n extends t.EllipseOval{constructor(e){super(e)}}s.Ellipse=n,p=n,n.__name__=\"Ellipse\",p.prototype.default_view=a},\n", - " function _(t,s,e,i,h){i();const n=t(1),r=t(275),a=(0,n.__importStar)(t(185)),l=t(24),_=t(72),o=(0,n.__importStar)(t(18));class d extends r.CenterRotatableView{_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"):this.sw=(0,l.to_screen)(this.width),\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"):this.sh=(0,l.to_screen)(this.height)}_render(t,s,e){const{sx:i,sy:h,sw:n,sh:r,angle:a}=null!=e?e:this;for(const e of s){const s=i[e],l=h[e],_=n[e],o=r[e],d=a.get(e);isFinite(s+l+_+o+d)&&(t.beginPath(),t.ellipse(s,l,_/2,o/2,d,0,2*Math.PI),this.visuals.fill.apply(t,e),this.visuals.hatch.apply(t,e),this.visuals.line.apply(t,e))}}_hit_point(t){let s,e,i,h,n,r,l,o,d;const{sx:c,sy:p}=t,w=this.renderer.xscale.invert(c),x=this.renderer.yscale.invert(p);\"data\"==this.model.properties.width.units?(s=w-this.max_width,e=w+this.max_width):(r=c-this.max_width,l=c+this.max_width,[s,e]=this.renderer.xscale.r_invert(r,l)),\"data\"==this.model.properties.height.units?(i=x-this.max_height,h=x+this.max_height):(o=p-this.max_height,d=p+this.max_height,[i,h]=this.renderer.yscale.r_invert(o,d));const m=this.index.indices({x0:s,x1:e,y0:i,y1:h}),y=[];for(const t of m)n=a.point_in_ellipse(c,p,this.angle.get(t),this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),n&&y.push(t);return new _.Selection({indices:y})}draw_legend_for_index(t,{x0:s,y0:e,x1:i,y1:h},n){const r=n+1,a=new Array(r);a[n]=(s+i)/2;const l=new Array(r);l[n]=(e+h)/2;const _=this.sw[n]/this.sh[n],d=.8*Math.min(Math.abs(i-s),Math.abs(h-e)),c=new Array(r),p=new Array(r);_>1?(c[n]=d,p[n]=d/_):(c[n]=d*_,p[n]=d);const w=new o.UniformScalar(0,r);this._render(t,[n],{sx:a,sy:l,sw:c,sh:p,angle:w})}}e.EllipseOvalView=d,d.__name__=\"EllipseOvalView\";class c extends r.CenterRotatable{constructor(t){super(t)}}e.EllipseOval=c,c.__name__=\"EllipseOval\"},\n", - " function _(e,t,i,a,n){a();const s=e(1);var r;const h=e(178),o=e(48),_=(0,s.__importStar)(e(18));class c extends h.XYGlyphView{get max_w2(){return\"data\"==this.model.properties.width.units?this.max_width/2:0}get max_h2(){return\"data\"==this.model.properties.height.units?this.max_height/2:0}_bounds({x0:e,x1:t,y0:i,y1:a}){const{max_w2:n,max_h2:s}=this;return{x0:e-n,x1:t+n,y0:i-s,y1:a+s}}}i.CenterRotatableView=c,c.__name__=\"CenterRotatableView\";class l extends h.XYGlyph{constructor(e){super(e)}}i.CenterRotatable=l,r=l,l.__name__=\"CenterRotatable\",r.mixins([o.LineVector,o.FillVector,o.HatchVector]),r.define((({})=>({angle:[_.AngleSpec,0],width:[_.DistanceSpec,{field:\"width\"}],height:[_.DistanceSpec,{field:\"height\"}]})))},\n", - " function _(t,e,s,i,r){i();const h=t(1);var a;const n=t(277),_=t(24),o=(0,h.__importStar)(t(18));class l extends n.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:s}=await Promise.resolve().then((()=>(0,h.__importStar)(t(427))));this.glglyph=new s(e.regl_wrapper,this)}}scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){const e=this._left[t],s=this._right[t],i=this._y[t],r=this.height.get(t)/2;return[Math.min(e,s),Math.max(e,s),i+r,i-r]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new _.ScreenArray(t),this.sbottom=new _.ScreenArray(t);for(let e=0;e({left:[o.XCoordinateSpec,{value:0}],y:[o.YCoordinateSpec,{field:\"y\"}],height:[o.NumberSpec,{value:1}],right:[o.XCoordinateSpec,{field:\"right\"}]})))},\n", - " function _(t,e,s,r,i){var n;r();const a=t(48),h=t(179),o=t(184),c=t(72);class _ extends h.GlyphView{get_anchor_point(t,e,s){const r=Math.min(this.sleft[e],this.sright[e]),i=Math.max(this.sright[e],this.sleft[e]),n=Math.min(this.stop[e],this.sbottom[e]),a=Math.max(this.sbottom[e],this.stop[e]);switch(t){case\"top_left\":return{x:r,y:n};case\"top\":case\"top_center\":return{x:(r+i)/2,y:n};case\"top_right\":return{x:i,y:n};case\"bottom_left\":return{x:r,y:a};case\"bottom\":case\"bottom_center\":return{x:(r+i)/2,y:a};case\"bottom_right\":return{x:i,y:a};case\"left\":case\"center_left\":return{x:r,y:(n+a)/2};case\"center\":case\"center_center\":return{x:(r+i)/2,y:(n+a)/2};case\"right\":case\"center_right\":return{x:i,y:(n+a)/2}}}_index_data(t){const{min:e,max:s}=Math,{data_size:r}=this;for(let i=0;i(0,n.__importStar)(e(425))));this.glglyph=new s(t.regl_wrapper,this)}}scenterxy(e){return[this.sx[e],this.sy[e]]}_set_data(){const{orientation:e,size:t,aspect_scale:s}=this.model,{q:i,r}=this,n=this.q.length;this._x=new Float64Array(n),this._y=new Float64Array(n);const{_x:a,_y:l}=this,o=Math.sqrt(3);if(\"pointytop\"==e)for(let e=0;e({r:[c.NumberSpec,{field:\"r\"}],q:[c.NumberSpec,{field:\"q\"}],scale:[c.NumberSpec,1],size:[e,1],aspect_scale:[e,1],orientation:[_.HexTileOrientation,\"pointytop\"]}))),a.override({line_color:null})},\n", - " function _(e,a,t,_,r){var n;_();const s=e(280),o=e(173),i=e(201);class p extends s.ImageBaseView{connect_signals(){super.connect_signals(),this.connect(this.model.color_mapper.change,(()=>this._update_image()))}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}t.ImageView=p,p.__name__=\"ImageView\";class m extends s.ImageBase{constructor(e){super(e)}}t.Image=m,n=m,m.__name__=\"Image\",n.prototype.default_view=p,n.define((({Ref:e})=>({color_mapper:[e(o.ColorMapper),()=>new i.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})))},\n", - " function _(e,t,i,s,a){s();const h=e(1);var n;const r=e(178),_=e(24),d=(0,h.__importStar)(e(18)),l=e(72),g=e(9),o=e(29),c=e(11);class m extends r.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_render(e,t,i){const{image_data:s,sx:a,sy:h,sw:n,sh:r,global_alpha:_}=null!=i?i:this,d=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1);const l=_.is_Scalar();l&&(e.globalAlpha=_.value);for(const i of t){const t=s[i],_=a[i],d=h[i],g=n[i],o=r[i],c=this.global_alpha.get(i);if(null==t||!isFinite(_+d+g+o+c))continue;l||(e.globalAlpha=c);const m=d;e.translate(0,m),e.scale(1,-1),e.translate(0,-m),e.drawImage(t,0|_,0|d,g,o),e.translate(0,m),e.scale(1,-1),e.translate(0,-m)}e.setImageSmoothingEnabled(d)}_set_data(e){this._set_width_heigh_data();for(let t=0,i=this.image.length;t({image:[d.NDArraySpec,{field:\"image\"}],dw:[d.DistanceSpec,{field:\"dw\"}],dh:[d.DistanceSpec,{field:\"dh\"}],global_alpha:[d.NumberSpec,{value:1}],dilate:[e,!1]})))},\n", - " function _(e,a,t,r,_){var n;r();const s=e(280),m=e(8);class i extends s.ImageBaseView{_flat_img_to_buf8(e){let a;return a=(0,m.isArray)(e)?new Uint32Array(e):e,new Uint8ClampedArray(a.buffer)}}t.ImageRGBAView=i,i.__name__=\"ImageRGBAView\";class g extends s.ImageBase{constructor(e){super(e)}}t.ImageRGBA=g,n=g,g.__name__=\"ImageRGBA\",n.prototype.default_view=i},\n", - " function _(e,t,s,r,a){r();const i=e(1);var n;const o=e(178),c=e(24),_=e(20),h=(0,i.__importStar)(e(18)),l=e(12),d=e(136);class m extends o.XYGlyphView{constructor(){super(...arguments),this._images_rendered=!1,this._set_data_iteration=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_index_data(e){const{data_size:t}=this;for(let s=0;s{this._set_data_iteration==r&&(this.image[a]=e,this.renderer.request_render())},attempts:t+1,timeout:s})}const a=\"data\"==this.model.properties.w.units,i=\"data\"==this.model.properties.h.units,n=this._x.length,o=new c.ScreenArray(a?2*n:n),_=new c.ScreenArray(i?2*n:n),{anchor:h}=this.model;function m(e,t){switch(h){case\"top_left\":case\"bottom_left\":case\"left\":case\"center_left\":return[e,e+t];case\"top\":case\"top_center\":case\"bottom\":case\"bottom_center\":case\"center\":case\"center_center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"right\":case\"center_right\":return[e-t,e]}}function g(e,t){switch(h){case\"top_left\":case\"top\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"left\":case\"center_left\":case\"center\":case\"center_center\":case\"right\":case\"center_right\":return[e+t/2,e-t/2]}}if(a)for(let e=0;e({url:[h.StringSpec,{field:\"url\"}],anchor:[_.Anchor,\"top_left\"],global_alpha:[h.NumberSpec,{value:1}],angle:[h.AngleSpec,0],w:[h.NullDistanceSpec,null],h:[h.NullDistanceSpec,null],dilate:[e,!1],retry_attempts:[t,0],retry_timeout:[t,0]})))},\n", - " function _(e,t,s,i,n){i();const o=e(1);var r;const l=e(78),_=e(48),c=(0,o.__importStar)(e(185)),h=(0,o.__importStar)(e(18)),a=e(12),d=e(13),x=e(179),y=e(184),g=e(72);class p extends x.GlyphView{_project_data(){l.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s0&&o.set(e,s)}return new g.Selection({indices:[...o.keys()],multiline_indices:(0,d.to_object)(o)})}get_interpolation_hit(e,t,s){const i=this._xs.get(e),n=this._ys.get(e),o=i[t],r=n[t],l=i[t+1],_=n[t+1];return(0,y.line_interpolation)(this.renderer,s,o,r,l,_)}draw_legend_for_index(e,t,s){(0,y.generic_line_vector_legend)(this.visuals,e,t,s)}scenterxy(){throw new Error(`${this}.scenterxy() is not implemented`)}}s.MultiLineView=p,p.__name__=\"MultiLineView\";class u extends x.Glyph{constructor(e){super(e)}}s.MultiLine=u,r=u,u.__name__=\"MultiLine\",r.prototype.default_view=p,r.define((({})=>({xs:[h.XCoordinateSeqSpec,{field:\"xs\"}],ys:[h.YCoordinateSeqSpec,{field:\"ys\"}]}))),r.mixins(_.LineVector)},\n", - " function _(t,e,s,n,i){n();const o=t(1);var r;const l=t(181),h=t(179),a=t(184),_=t(12),c=t(12),d=t(48),x=(0,o.__importStar)(t(185)),y=(0,o.__importStar)(t(18)),f=t(72),g=t(11);class p extends h.GlyphView{_project_data(){}_index_data(t){const{min:e,max:s}=Math,{data_size:n}=this;for(let i=0;i1&&c.length>1)for(let s=1,n=i.length;s1){let r=!1;for(let t=1;t({xs:[y.XCoordinateSeqSeqSeqSpec,{field:\"xs\"}],ys:[y.YCoordinateSeqSeqSeqSpec,{field:\"ys\"}]}))),r.mixins([d.LineVector,d.FillVector,d.HatchVector])},\n", - " function _(a,e,l,s,_){var t;s();const i=a(274),n=a(12);class p extends i.EllipseOvalView{_map_data(){super._map_data(),(0,n.mul)(this.sw,.75)}}l.OvalView=p,p.__name__=\"OvalView\";class v extends i.EllipseOval{constructor(a){super(a)}}l.Oval=v,t=v,v.__name__=\"Oval\",t.prototype.default_view=p},\n", - " function _(e,t,s,i,n){i();const r=e(1);var a;const o=e(179),c=e(184),_=e(12),h=e(48),l=(0,r.__importStar)(e(185)),d=(0,r.__importStar)(e(18)),y=e(72),p=e(11),x=e(78);class f extends o.GlyphView{_project_data(){x.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s({xs:[d.XCoordinateSeqSpec,{field:\"xs\"}],ys:[d.YCoordinateSeqSpec,{field:\"ys\"}]}))),a.mixins([h.LineVector,h.FillVector,h.HatchVector])},\n", - " function _(t,e,i,o,r){o();const s=t(1);var a;const n=t(277),l=(0,s.__importStar)(t(18));class _ extends n.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:i}=await Promise.resolve().then((()=>(0,s.__importStar)(t(427))));this.glglyph=new i(e.regl_wrapper,this)}}scenterxy(t){return[this.sleft[t]/2+this.sright[t]/2,this.stop[t]/2+this.sbottom[t]/2]}_lrtb(t){return[this._left[t],this._right[t],this._top[t],this._bottom[t]]}}i.QuadView=_,_.__name__=\"QuadView\";class p extends n.Box{constructor(t){super(t)}}i.Quad=p,a=p,p.__name__=\"Quad\",a.prototype.default_view=_,a.define((({})=>({right:[l.XCoordinateSpec,{field:\"right\"}],bottom:[l.YCoordinateSpec,{field:\"bottom\"}],left:[l.XCoordinateSpec,{field:\"left\"}],top:[l.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,t,i,n,s){n();const c=e(1);var o;const r=e(48),a=e(78),_=e(179),d=e(184),l=(0,c.__importStar)(e(18));function x(e,t,i){if(t==(e+i)/2)return[e,i];{const n=(e-t)/(e-2*t+i),s=e*(1-n)**2+2*t*(1-n)*n+i*n**2;return[Math.min(e,i,s),Math.max(e,i,s)]}}class y extends _.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{_x0:t,_x1:i,_y0:n,_y1:s,_cx:c,_cy:o,data_size:r}=this;for(let a=0;a({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx:[l.XCoordinateSpec,{field:\"cx\"}],cy:[l.YCoordinateSpec,{field:\"cy\"}]}))),o.mixins(r.LineVector)},\n", - " function _(e,t,s,i,n){i();const l=e(1);var a;const r=e(178),o=e(184),h=e(48),_=e(24),c=(0,l.__importStar)(e(18));class g extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.length.units?this.slength=this.sdist(this.renderer.xscale,this._x,this.length):this.slength=(0,_.to_screen)(this.length);const{width:e,height:t}=this.renderer.plot_view.frame.bbox,s=2*(e+t),{slength:i}=this;for(let e=0,t=i.length;e({length:[c.DistanceSpec,0],angle:[c.AngleSpec,0]})))},\n", - " function _(t,e,s,i,r){var n,h=this&&this.__createBinding||(Object.create?function(t,e,s,i){void 0===i&&(i=s),Object.defineProperty(t,i,{enumerable:!0,get:function(){return e[s]}})}:function(t,e,s,i){void 0===i&&(i=s),t[i]=e[s]}),a=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),l=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var s in t)\"default\"!==s&&Object.prototype.hasOwnProperty.call(t,s)&&h(e,t,s);return a(e,t),e};i();const o=t(275),c=t(184),_=t(24),d=t(12),f=t(72);class y extends o.CenterRotatableView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null==e?void 0:e.regl_wrapper.has_webgl){const{RectGL:s}=await Promise.resolve().then((()=>l(t(429))));this.glglyph=new s(e.regl_wrapper,this)}}_map_data(){if(\"data\"==this.model.properties.width.units)[this.sw,this.sx0]=this._map_dist_corner_for_data_side_length(this._x,this.width,this.renderer.xscale);else{this.sw=(0,_.to_screen)(this.width);const t=this.sx.length;this.sx0=new _.ScreenArray(t);for(let e=0;e({dilate:[t,!1]})))},\n", - " function _(e,t,r,a,s){a();const i=e(1);var n;const l=e(292),_=e(293),c=(0,i.__importStar)(e(18));class o extends l.MarkerView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null!=t&&t.regl_wrapper.has_webgl){const{MultiMarkerGL:r}=await Promise.resolve().then((()=>(0,i.__importStar)(e(428))));this.glglyph=new r(t.regl_wrapper,this)}}_render(e,t,r){const{sx:a,sy:s,size:i,angle:n,marker:l}=null!=r?r:this;for(const r of t){const t=a[r],c=s[r],o=i.get(r),g=n.get(r),w=l.get(r);if(!isFinite(t+c+o+g)||null==w)continue;const p=o/2;e.beginPath(),e.translate(t,c),g&&e.rotate(g),_.marker_funcs[w](e,r,p,this.visuals),g&&e.rotate(-g),e.translate(-t,-c)}}draw_legend_for_index(e,{x0:t,x1:r,y0:a,y1:s},i){const n=i+1,l=this.marker.get(i),_=Object.assign(Object.assign({},this._get_legend_args({x0:t,x1:r,y0:a,y1:s},i)),{marker:new c.UniformScalar(l,n)});this._render(e,[i],_)}}r.ScatterView=o,o.__name__=\"ScatterView\";class g extends l.Marker{constructor(e){super(e)}}r.Scatter=g,n=g,g.__name__=\"Scatter\",n.prototype.default_view=o,n.define((()=>({marker:[c.MarkerSpec,{value:\"circle\"}]})))},\n", - " function _(e,t,s,n,i){n();const r=e(1);var a;const c=e(178),o=e(48),_=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),l=e(9),x=e(72);class d extends c.XYGlyphView{_render(e,t,s){const{sx:n,sy:i,size:r,angle:a}=null!=s?s:this;for(const s of t){const t=n[s],c=i[s],o=r.get(s),_=a.get(s);if(!isFinite(t+c+o+_))continue;const h=o/2;e.beginPath(),e.translate(t,c),_&&e.rotate(_),this._render_one(e,s,h,this.visuals),_&&e.rotate(-_),e.translate(-t,-c)}}_mask_data(){const{x_target:e,y_target:t}=this.renderer.plot_view.frame,s=e.widen(this.max_size).map((e=>this.renderer.xscale.invert(e))),n=t.widen(this.max_size).map((e=>this.renderer.yscale.invert(e)));return this.index.indices({x0:s.start,x1:s.end,y0:n.start,y1:n.end})}_hit_point(e){const{sx:t,sy:s}=e,{max_size:n}=this,{hit_dilation:i}=this.model,r=t-n*i,a=t+n*i,[c,o]=this.renderer.xscale.r_invert(r,a),_=s-n*i,h=s+n*i,[l,d]=this.renderer.yscale.r_invert(_,h),y=this.index.indices({x0:c,x1:o,y0:l,y1:d}),g=[];for(const e of y){const n=this.size.get(e)/2*i;Math.abs(this.sx[e]-t)<=n&&Math.abs(this.sy[e]-s)<=n&&g.push(e)}return new x.Selection({indices:g})}_hit_span(e){const{sx:t,sy:s}=e,n=this.bounds(),i=this.max_size/2;let r,a,c,o;if(\"h\"==e.direction){c=n.y0,o=n.y1;const e=t-i,s=t+i;[r,a]=this.renderer.xscale.r_invert(e,s)}else{r=n.x0,a=n.x1;const e=s-i,t=s+i;[c,o]=this.renderer.yscale.r_invert(e,t)}const _=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_rect(e){const{sx0:t,sx1:s,sy0:n,sy1:i}=e,[r,a]=this.renderer.xscale.r_invert(t,s),[c,o]=this.renderer.yscale.r_invert(n,i),_=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_poly(e){const{sx:t,sy:s}=e,n=(0,l.range)(0,this.sx.length),i=[];for(let e=0,r=n.length;e({size:[h.ScreenSizeSpec,{value:4}],angle:[h.AngleSpec,0],hit_dilation:[e,1]})))},\n", - " function _(l,o,n,t,i){t();const e=Math.sqrt(3),a=Math.sqrt(5),c=(a+1)/4,p=Math.sqrt((5-a)/8),r=(a-1)/4,h=Math.sqrt((5+a)/8);function u(l,o){l.rotate(Math.PI/4),s(l,o),l.rotate(-Math.PI/4)}function f(l,o){const n=o*e,t=n/3;l.moveTo(-n/2,-t),l.lineTo(0,0),l.lineTo(n/2,-t),l.lineTo(0,0),l.lineTo(0,o)}function s(l,o){l.moveTo(0,o),l.lineTo(0,-o),l.moveTo(-o,0),l.lineTo(o,0)}function T(l,o){l.moveTo(0,o),l.lineTo(o/1.5,0),l.lineTo(0,-o),l.lineTo(-o/1.5,0),l.closePath()}function y(l,o){const n=o*e,t=n/3;l.moveTo(-o,t),l.lineTo(o,t),l.lineTo(0,t-n),l.closePath()}function v(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function d(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function _(l,o,n,t){!function(l,o){l.beginPath(),l.arc(0,0,o/4,0,2*Math.PI,!1),l.closePath()}(l,n),t.line.set_vectorize(l,o),l.fillStyle=l.strokeStyle,l.fill()}function P(l,o,n,t){!function(l,o){const n=o/2,t=e*n;l.moveTo(o,0),l.lineTo(n,-t),l.lineTo(-n,-t),l.lineTo(-o,0),l.lineTo(-n,t),l.lineTo(n,t),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function m(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function q(l,o,n,t){!function(l,o){const n=Math.sqrt(5-2*a)*o;l.moveTo(0,-o),l.lineTo(n*r,n*h-o),l.lineTo(n*(1+r),n*h-o),l.lineTo(n*(1+r-c),n*(h+p)-o),l.lineTo(n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(0,2*n*h-o),l.lineTo(-n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(-n*(1+r-c),n*(h+p)-o),l.lineTo(-n*(1+r),n*h-o),l.lineTo(-n*r,n*h-o),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function M(l,o,n,t){y(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}n.marker_funcs={asterisk:function(l,o,n,t){s(l,n),u(l,n),t.line.apply(l,o)},circle:v,circle_cross:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},circle_dot:function(l,o,n,t){v(l,o,n,t),_(l,o,n,t)},circle_y:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),f(l,n),l.stroke())},circle_x:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),u(l,n),l.stroke())},cross:function(l,o,n,t){s(l,n),t.line.apply(l,o)},diamond:d,diamond_dot:function(l,o,n,t){d(l,o,n,t),_(l,o,n,t)},diamond_cross:function(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(0,n),l.lineTo(0,-n),l.moveTo(-n/1.5,0),l.lineTo(n/1.5,0),l.stroke())},dot:_,hex:P,hex_dot:function(l,o,n,t){P(l,o,n,t),_(l,o,n,t)},inverted_triangle:function(l,o,n,t){l.rotate(Math.PI),y(l,n),l.rotate(-Math.PI),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},plus:function(l,o,n,t){const i=3*n/8,e=[i,i,n,n,i,i,-i,-i,-n,-n,-i,-i],a=[n,i,i,-i,-i,-n,-n,-i,-i,i,i,n];l.beginPath();for(let o=0;o<12;o++)l.lineTo(e[o],a[o]);l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square:m,square_cross:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},square_dot:function(l,o,n,t){m(l,o,n,t),_(l,o,n,t)},square_pin:function(l,o,n,t){const i=3*n/8;l.moveTo(-n,-n),l.quadraticCurveTo(0,-i,n,-n),l.quadraticCurveTo(i,0,n,n),l.quadraticCurveTo(0,i,-n,n),l.quadraticCurveTo(-i,0,-n,-n),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square_x:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(-n,n),l.lineTo(n,-n),l.moveTo(-n,-n),l.lineTo(n,n),l.stroke())},star:q,star_dot:function(l,o,n,t){q(l,o,n,t),_(l,o,n,t)},triangle:M,triangle_dot:function(l,o,n,t){M(l,o,n,t),_(l,o,n,t)},triangle_pin:function(l,o,n,t){const i=n*e,a=i/3,c=3*a/8;l.moveTo(-n,a),l.quadraticCurveTo(0,c,n,a),l.quadraticCurveTo(e*c/2,c/2,0,a-i),l.quadraticCurveTo(-e*c/2,c/2,-n,a),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},dash:function(l,o,n,t){!function(l,o){l.moveTo(-o,0),l.lineTo(o,0)}(l,n),t.line.apply(l,o)},x:function(l,o,n,t){u(l,n),t.line.apply(l,o)},y:function(l,o,n,t){f(l,n),t.line.apply(l,o)}}},\n", - " function _(e,t,s,i,n){i();const r=e(1);var o;const _=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),c=e(48),a=e(78),d=e(179),x=e(184),l=e(72);class y extends d.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{min:t,max:s}=Math,{_x0:i,_x1:n,_y0:r,_y1:o,data_size:_}=this;for(let h=0;h<_;h++){const _=i[h],c=n[h],a=r[h],d=o[h];e.add_rect(t(_,c),t(a,d),s(_,c),s(a,d))}}_render(e,t,s){if(this.visuals.line.doit){const{sx0:i,sy0:n,sx1:r,sy1:o}=null!=s?s:this;for(const s of t){const t=i[s],_=n[s],h=r[s],c=o[s];isFinite(t+_+h+c)&&(e.beginPath(),e.moveTo(t,_),e.lineTo(h,c),this.visuals.line.set_vectorize(e,s),e.stroke())}}}_hit_point(e){const{sx:t,sy:s}=e,i={x:t,y:s},[n,r]=this.renderer.xscale.r_invert(t-2,t+2),[o,h]=this.renderer.yscale.r_invert(s-2,s+2),c=this.index.indices({x0:n,y0:o,x1:r,y1:h}),a=[];for(const e of c){const t=Math.max(2,this.line_width.get(e)/2)**2,s={x:this.sx0[e],y:this.sy0[e]},n={x:this.sx1[e],y:this.sy1[e]};_.dist_to_segment_squared(i,s,n)({x0:[h.XCoordinateSpec,{field:\"x0\"}],y0:[h.YCoordinateSpec,{field:\"y0\"}],x1:[h.XCoordinateSpec,{field:\"x1\"}],y1:[h.YCoordinateSpec,{field:\"y1\"}]}))),o.mixins(c.LineVector)},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const l=t(178),a=(0,o.__importStar)(t(48)),c=t(296);class r extends l.XYGlyphView{_set_data(){const{tension:t,closed:e}=this.model;[this._xt,this._yt]=(0,c.catmullrom_spline)(this._x,this._y,20,t,e)}_map_data(){const{x_scale:t,y_scale:e}=this.renderer.coordinates;this.sxt=t.v_compute(this._xt),this.syt=e.v_compute(this._yt)}_render(t,e,s){const{sxt:i,syt:n}=null!=s?s:this;let o=!0;t.beginPath();const _=i.length;for(let e=0;e<_;e++){const s=i[e],_=n[e];isFinite(s+_)?o?(t.moveTo(s,_),o=!1):t.lineTo(s,_):o=!0}this.visuals.line.set_value(t),t.stroke()}}s.SplineView=r,r.__name__=\"SplineView\";class h extends l.XYGlyph{constructor(t){super(t)}}s.Spline=h,_=h,h.__name__=\"Spline\",_.prototype.default_view=r,_.mixins(a.LineScalar),_.define((({Boolean:t,Number:e})=>({tension:[e,.5],closed:[t,!1]})))},\n", - " function _(n,t,e,o,s){o();const c=n(24),l=n(11);e.catmullrom_spline=function(n,t,e=10,o=.5,s=!1){(0,l.assert)(n.length==t.length);const r=n.length,f=s?r+1:r,w=(0,c.infer_type)(n,t),i=new w(f+2),u=new w(f+2);i.set(n,1),u.set(t,1),s?(i[0]=n[r-1],u[0]=t[r-1],i[f]=n[0],u[f]=t[0],i[f+1]=n[1],u[f+1]=t[1]):(i[0]=n[0],u[0]=t[0],i[f+1]=n[r-1],u[f+1]=t[r-1]);const g=new w(4*(e+1));for(let n=0,t=0;n<=e;n++){const o=n/e,s=o**2,c=o*s;g[t++]=2*c-3*s+1,g[t++]=-2*c+3*s,g[t++]=c-2*s+o,g[t++]=c-s}const h=new w((f-1)*(e+1)),_=new w((f-1)*(e+1));for(let n=1,t=0;n1&&(e.stroke(),o=!1)}o?(e.lineTo(t,r),e.lineTo(a,c)):(e.beginPath(),e.moveTo(s[n],i[n]),o=!0),l=n}e.lineTo(s[a-1],i[a-1]),e.stroke()}}draw_legend_for_index(e,t,n){(0,r.generic_line_scalar_legend)(this.visuals,e,t)}}n.StepView=f,f.__name__=\"StepView\";class u extends a.XYGlyph{constructor(e){super(e)}}n.Step=u,l=u,u.__name__=\"Step\",l.prototype.default_view=f,l.mixins(c.LineScalar),l.define((()=>({mode:[_.StepMode,\"before\"]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const h=t(178),l=t(48),r=(0,o.__importStar)(t(185)),a=(0,o.__importStar)(t(18)),c=t(121),x=t(11),u=t(72);class f extends h.XYGlyphView{_rotate_point(t,e,s,i,n){return[(t-s)*Math.cos(n)-(e-i)*Math.sin(n)+s,(t-s)*Math.sin(n)+(e-i)*Math.cos(n)+i]}_text_bounds(t,e,s,i){return[[t,t+s,t+s,t,t],[e,e,e-i,e-i,e]]}_render(t,e,s){const{sx:i,sy:n,x_offset:o,y_offset:_,angle:h,text:l}=null!=s?s:this;this._sys=[],this._sxs=[];for(const s of e){const e=this._sxs[s]=[],r=this._sys[s]=[],a=i[s],x=n[s],u=o.get(s),f=_.get(s),p=h.get(s),g=l.get(s);if(isFinite(a+x+u+f+p)&&null!=g&&this.visuals.text.doit){const i=`${g}`;t.save(),t.translate(a+u,x+f),t.rotate(p),this.visuals.text.set_vectorize(t,s);const n=this.visuals.text.font_value(s),{height:o}=(0,c.font_metrics)(n),_=this.text_line_height.get(s)*o;if(-1==i.indexOf(\"\\n\")){t.fillText(i,0,0);const s=a+u,n=x+f,o=t.measureText(i).width,[h,l]=this._text_bounds(s,n,o,_);e.push(h),r.push(l)}else{const n=i.split(\"\\n\"),o=_*n.length,h=this.text_baseline.get(s);let l;switch(h){case\"top\":l=0;break;case\"middle\":l=-o/2+_/2;break;case\"bottom\":l=-o+_;break;default:l=0,console.warn(`'${h}' baseline not supported with multi line text`)}for(const s of n){t.fillText(s,0,l);const i=a+u,n=l+x+f,o=t.measureText(s).width,[h,c]=this._text_bounds(i,n,o,_);e.push(h),r.push(c),l+=_}}t.restore()}}}_hit_point(t){const{sx:e,sy:s}=t,i=[];for(let t=0;t({text:[a.NullStringSpec,{field:\"text\"}],angle:[a.AngleSpec,0],x_offset:[a.NumberSpec,0],y_offset:[a.NumberSpec,0]})))},\n", - " function _(t,e,s,i,r){i();const h=t(1);var o;const a=t(277),n=t(24),_=(0,h.__importStar)(t(18));class l extends a.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:s}=await Promise.resolve().then((()=>(0,h.__importStar)(t(427))));this.glglyph=new s(e.regl_wrapper,this)}}scenterxy(t){return[this.sx[t],(this.stop[t]+this.sbottom[t])/2]}_lrtb(t){const e=this.width.get(t)/2,s=this._x[t],i=this._top[t],r=this._bottom[t];return[s-e,s+e,Math.max(i,r),Math.min(i,r)]}_map_data(){this.sx=this.renderer.xscale.v_compute(this._x),this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"),this.stop=this.renderer.yscale.v_compute(this._top),this.sbottom=this.renderer.yscale.v_compute(this._bottom);const t=this.sx.length;this.sleft=new n.ScreenArray(t),this.sright=new n.ScreenArray(t);for(let e=0;e({x:[_.XCoordinateSpec,{field:\"x\"}],bottom:[_.YCoordinateSpec,{value:0}],width:[_.NumberSpec,{value:1}],top:[_.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,s,t,i,n){i();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),h=e(24),o=e(20),_=(0,r.__importStar)(e(18)),u=e(10),g=e(72),x=e(12);class p extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,h.to_screen)(this.radius),this.max_sradius=(0,x.max)(this.sradius)}_render(e,s,t){const{sx:i,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=t?t:this,d=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],l=n[t],h=r[t],o=a.get(t),_=c.get(t);isFinite(s+l+h+o+_)&&(e.beginPath(),e.arc(s,l,h,o,_,d),e.lineTo(s,l),e.closePath(),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t))}}_hit_point(e){let s,t,i,n,r;const{sx:a,sy:c}=e,d=this.renderer.xscale.invert(a),l=this.renderer.yscale.invert(c);t=a-this.max_sradius,i=a+this.max_sradius;const[h,o]=this.renderer.xscale.r_invert(t,i);n=c-this.max_sradius,r=c+this.max_sradius;const[_,x]=this.renderer.yscale.r_invert(n,r),p=[];for(const e of this.index.indices({x0:h,x1:o,y0:_,y1:x})){const a=this.sradius[e]**2;[t,i]=this.renderer.xscale.r_compute(d,this._x[e]),[n,r]=this.renderer.yscale.r_compute(l,this._y[e]),s=(t-i)**2+(n-r)**2,s<=a&&p.push(e)}const y=\"anticlock\"==this.model.direction,m=[];for(const e of p){const s=Math.atan2(c-this.sy[e],a-this.sx[e]);(0,u.angle_between)(-s,-this.start_angle.get(e),-this.end_angle.get(e),y)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,d.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=this.sradius[e]/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.WedgeView=p,p.__name__=\"WedgeView\";class y extends c.XYGlyph{constructor(e){super(e)}}t.Wedge=y,a=y,y.__name__=\"Wedge\",a.prototype.default_view=p,a.mixins([l.LineVector,l.FillVector,l.HatchVector]),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[_.DistanceSpec,{field:\"radius\"}],start_angle:[_.AngleSpec,{field:\"start_angle\"}],end_angle:[_.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(t,_,r,o,a){o();const e=t(1);(0,e.__exportStar)(t(302),r),(0,e.__exportStar)(t(303),r),(0,e.__exportStar)(t(304),r)},\n", - " function _(e,t,d,n,s){n();const o=e(53),r=e(12),_=e(9),i=e(72);class c extends o.Model{constructor(e){super(e)}_hit_test(e,t,d){if(!t.model.visible)return null;const n=d.glyph.hit_test(e);return null==n?null:d.model.view.convert_selection_from_subset(n)}}d.GraphHitTestPolicy=c,c.__name__=\"GraphHitTestPolicy\";class a extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.edge_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;return s.update(e,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{edge_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.edge_view.model);return r.update(e,n,s),d.edge_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!r.is_empty()}}d.EdgesOnly=a,a.__name__=\"EdgesOnly\";class l extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,d,n),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{node_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.node_view.model);return r.update(e,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.node_view.model.data_source.inspect.emit([d.node_view.model,{geometry:t}]),!r.is_empty()}}d.NodesOnly=l,l.__name__=\"NodesOnly\";class u extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}get_linked_edges(e,t,d){let n=[];\"selection\"==d?n=e.selected.indices.map((t=>e.data.index[t])):\"inspection\"==d&&(n=e.inspected.indices.map((t=>e.data.index[t])));const s=[];for(let e=0;e(0,r.indexOf)(e.data.index,t)));return new i.Selection({indices:o})}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,d,n);const o=t.node_renderer.data_source.selected,r=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(r,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const o=d.edge_view.model.data_source.selection_manager.get_or_create_inspector(d.edge_view.model);o.update(e,n,s),d.edge_view.model.data_source.setv({inspected:o},{silent:!0});const r=d.node_view.model.data_source.selection_manager.get_or_create_inspector(d.node_view.model),_=this.get_linked_nodes(d.node_view.model.data_source,d.edge_view.model.data_source,\"inspection\");return r.update(_,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!o.is_empty()}}d.EdgesAndLinkedNodes=m,m.__name__=\"EdgesAndLinkedNodes\"},\n", - " function _(e,o,t,r,n){var s;r();const a=e(53),d=e(260);class _ extends a.Model{constructor(e){super(e)}get node_coordinates(){return new u({layout:this})}get edge_coordinates(){return new i({layout:this})}}t.LayoutProvider=_,_.__name__=\"LayoutProvider\";class c extends d.CoordinateTransform{constructor(e){super(e)}}t.GraphCoordinates=c,s=c,c.__name__=\"GraphCoordinates\",s.define((({Ref:e})=>({layout:[e(_)]})));class u extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_node_coordinates(e);return{x:o,y:t}}}t.NodeCoordinates=u,u.__name__=\"NodeCoordinates\";class i extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_edge_coordinates(e);return{x:o,y:t}}}t.EdgeCoordinates=i,i.__name__=\"EdgeCoordinates\"},\n", - " function _(t,a,l,e,n){var o;e();const r=t(303);class u extends r.LayoutProvider{constructor(t){super(t)}get_node_coordinates(t){var a;const l=null!==(a=t.data.index)&&void 0!==a?a:[],e=l.length,n=new Float64Array(e),o=new Float64Array(e);for(let t=0;t({graph_layout:[l(a(t,t)),{}]})))},\n", - " function _(i,d,n,r,G){r(),G(\"Grid\",i(306).Grid)},\n", - " function _(i,e,n,s,t){s();const r=i(1);var o;const d=i(127),_=i(129),a=i(130),l=(0,r.__importStar)(i(48)),h=i(8);class c extends _.GuideRendererView{_render(){const i=this.layer.ctx;i.save(),this._draw_regions(i),this._draw_minor_grids(i),this._draw_grids(i),i.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;const[e,n]=this.grid_coords(\"major\",!1);for(let s=0;sn[1]&&(t=n[1]);else{[s,t]=n;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,t]=i.computed_bounds)}return[s,t]}grid_coords(i,e=!0){const n=this.model.dimension,s=(n+1)%2,[t,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const _=[[],[]],a=this.model.get_ticker();if(null==a)return _;const l=a.get_ticks(o,d,t,r.min)[i],h=t.min,c=t.max,u=r.min,m=r.max;e||(l[0]!=h&&l.splice(0,0,h),l[l.length-1]!=c&&l.push(c));for(let i=0;i({bounds:[r(t(i,i),e),\"auto\"],dimension:[n(0,1),0],axis:[o(s(d.Axis)),null],ticker:[o(s(a.Ticker)),null]}))),o.override({level:\"underlay\",band_fill_color:null,band_fill_alpha:0,grid_line_color:\"#e5e5e5\",minor_grid_line_color:null})},\n", - " function _(o,a,x,B,e){B(),e(\"Box\",o(308).Box),e(\"Column\",o(310).Column),e(\"GridBox\",o(311).GridBox),e(\"HTMLBox\",o(312).HTMLBox),e(\"LayoutDOM\",o(309).LayoutDOM),e(\"Panel\",o(313).Panel),e(\"Row\",o(314).Row),e(\"Spacer\",o(315).Spacer),e(\"Tabs\",o(316).Tabs),e(\"WidgetBox\",o(319).WidgetBox)},\n", - " function _(e,n,s,t,c){var i;t();const o=e(309);class r extends o.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,(()=>this.rebuild()))}get child_models(){return this.model.children}}s.BoxView=r,r.__name__=\"BoxView\";class a extends o.LayoutDOM{constructor(e){super(e)}}s.Box=a,i=a,a.__name__=\"Box\",i.define((({Number:e,Array:n,Ref:s})=>({children:[n(s(o.LayoutDOM)),[]],spacing:[e,0]})))},\n", - " function _(t,i,e,s,o){var l;s();const n=t(53),h=t(20),a=t(43),r=t(19),_=t(8),c=t(22),u=t(121),d=t(113),p=t(226),m=t(207),g=t(44),w=t(235);class f extends p.DOMView{constructor(){super(...arguments),this._offset_parent=null,this._viewport={}}get is_layout_root(){return this.is_root||!(this.parent instanceof f)}get base_font_size(){const t=getComputedStyle(this.el).fontSize,i=(0,u.parse_css_font_size)(t);if(null!=i){const{value:t,unit:e}=i;if(\"px\"==e)return t}return null}initialize(){super.initialize(),this.el.style.position=this.is_layout_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this.build_child_views()}remove(){for(const t of this.child_views)t.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_layout_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval((()=>{const t=this.el.offsetParent;this._offset_parent!=t&&(this._offset_parent=t,null!=t&&(this.compute_viewport(),this.invalidate_layout()))}),250));const t=this.model.properties;this.on_change([t.width,t.height,t.min_width,t.min_height,t.max_width,t.max_height,t.margin,t.width_policy,t.height_policy,t.sizing_mode,t.aspect_ratio,t.visible],(()=>this.invalidate_layout())),this.on_change([t.background,t.css_classes],(()=>this.invalidate_render()))}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map((t=>this._child_views.get(t)))}async build_child_views(){await(0,d.build_views)(this._child_views,this.child_models,{parent:this})}render(){super.render(),(0,a.empty)(this.el);const{background:t}=this.model;this.el.style.backgroundColor=null!=t?(0,c.color2css)(t):\"\",(0,a.classes)(this.el).clear().add(...this.css_classes());for(const t of this.child_views)this.el.appendChild(t.el),t.render()}update_layout(){for(const t of this.child_views)t.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const t=this.is_layout_root?this.layout.sizing.margin:void 0;(0,a.position)(this.el,this.layout.bbox,t);for(const t of this.child_views)t.update_position()}after_layout(){for(const t of this.child_views)t.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(t){t.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build(),this.notify_finished()}build(){if(!this.is_layout_root)throw new Error(`${this.toString()} is not a root layout`);return this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const t=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),r.logger.debug(`layout computed in ${Date.now()-t} ms`)}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const t of this.child_views)if(!t.has_finished())return!1;return!0}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:t,height_policy:i,aspect_ratio:e}=this.model;\"auto\"==t&&(t=this._width_policy()),\"auto\"==i&&(i=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)t=i=\"fixed\";else if(\"stretch_both\"==s)t=i=\"max\";else if(\"stretch_width\"==s)t=\"max\";else if(\"stretch_height\"==s)i=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":t=\"max\",i=\"min\";break;case\"scale_height\":t=\"min\",i=\"max\";break;case\"scale_both\":t=\"max\",i=\"max\"}const o={width_policy:t,height_policy:i},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:h,height:a}=this.model;null!=h&&(o.width=h),null!=a&&(o.height=a);const{max_width:r,max_height:c}=this.model;null!=r&&(o.max_width=r),null!=c&&(o.max_height=c),\"auto\"==e&&null!=h&&null!=a?o.aspect=h/a:(0,_.isNumber)(e)&&(o.aspect=e);const{margin:u}=this.model;if(null!=u)if((0,_.isNumber)(u))o.margin={top:u,right:u,bottom:u,left:u};else if(2==u.length){const[t,i]=u;o.margin={top:t,right:i,bottom:t,left:i}}else{const[t,i,e,s]=u;o.margin={top:t,right:i,bottom:e,left:s}}o.visible=this.model.visible;const{align:d}=this.model;return(0,_.isArray)(d)?[o.halign,o.valign]=d:o.halign=o.valign=d,o}_viewport_size(){return(0,a.undisplayed)(this.el,(()=>{let t=this.el;for(;t=t.parentElement;){if(t.classList.contains(g.root))continue;if(t==document.body){const{margin:{left:t,right:i,top:e,bottom:s}}=(0,a.extents)(document.body);return{width:Math.ceil(document.documentElement.clientWidth-t-i),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:i,right:e,top:s,bottom:o}}=(0,a.extents)(t),{width:l,height:n}=t.getBoundingClientRect(),h=Math.ceil(l-i-e),r=Math.ceil(n-s-o);if(h>0||r>0)return{width:h>0?h:void 0,height:r>0?r:void 0}}return{}}))}export(t,i=!0){const e=\"png\"==t?\"canvas\":\"svg\",s=new w.CanvasLayer(e,i),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(t,i),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map((t=>t.serializable_state()))})}}e.LayoutDOMView=f,f.__name__=\"LayoutDOMView\";class y extends n.Model{constructor(t){super(t)}}e.LayoutDOM=y,l=y,y.__name__=\"LayoutDOM\",l.define((t=>{const{Boolean:i,Number:e,String:s,Auto:o,Color:l,Array:n,Tuple:a,Or:r,Null:_,Nullable:c}=t,u=a(e,e),d=a(e,e,e,e);return{width:[c(e),null],height:[c(e),null],min_width:[c(e),null],min_height:[c(e),null],max_width:[c(e),null],max_height:[c(e),null],margin:[c(r(e,u,d)),[0,0,0,0]],width_policy:[r(m.SizingPolicy,o),\"auto\"],height_policy:[r(m.SizingPolicy,o),\"auto\"],aspect_ratio:[r(e,o,_),null],sizing_mode:[c(h.SizingMode),null],visible:[i,!0],disabled:[i,!1],align:[r(h.Align,a(h.Align,h.Align)),\"start\"],background:[c(l),null],css_classes:[n(s),[]]}}))},\n", - " function _(o,s,t,i,e){var n;i();const a=o(308),l=o(209);class u extends a.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Column(o),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}t.ColumnView=u,u.__name__=\"ColumnView\";class _ extends a.Box{constructor(o){super(o)}}t.Column=_,n=_,_.__name__=\"Column\",n.prototype.default_view=u,n.define((({Any:o})=>({rows:[o,\"auto\"]})))},\n", - " function _(s,o,t,i,e){var n;i();const l=s(309),a=s(209);class r extends l.LayoutDOMView{connect_signals(){super.connect_signals();const{children:s,rows:o,cols:t,spacing:i}=this.model.properties;this.on_change([s,o,t,i],(()=>this.rebuild()))}get child_models(){return this.model.children.map((([s])=>s))}_update_layout(){this.layout=new a.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[s,o,t,i,e]of this.model.children){const n=this._child_views.get(s);this.layout.items.push({layout:n.layout,row:o,col:t,row_span:i,col_span:e})}this.layout.set_sizing(this.box_sizing())}}t.GridBoxView=r,r.__name__=\"GridBoxView\";class c extends l.LayoutDOM{constructor(s){super(s)}}t.GridBox=c,n=c,c.__name__=\"GridBox\",n.prototype.default_view=r,n.define((({Any:s,Int:o,Number:t,Tuple:i,Array:e,Ref:n,Or:a,Opt:r})=>({children:[e(i(n(l.LayoutDOM),o,o,r(o),r(o))),[]],rows:[s,\"auto\"],cols:[s,\"auto\"],spacing:[a(t,i(t,t)),0]})))},\n", - " function _(t,e,o,s,n){s();const _=t(309),i=t(207);class a extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new i.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=a,a.__name__=\"HTMLBoxView\";class u extends _.LayoutDOM{constructor(t){super(t)}}o.HTMLBox=u,u.__name__=\"HTMLBox\"},\n", - " function _(e,n,l,a,o){var t;a();const s=e(53),c=e(309);class d extends s.Model{constructor(e){super(e)}}l.Panel=d,t=d,d.__name__=\"Panel\",t.define((({Boolean:e,String:n,Ref:l})=>({title:[n,\"\"],child:[l(c.LayoutDOM)],closable:[e,!1],disabled:[e,!1]})))},\n", - " function _(o,s,t,i,e){var a;i();const n=o(308),l=o(209);class _ extends n.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Row(o),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}t.RowView=_,_.__name__=\"RowView\";class c extends n.Box{constructor(o){super(o)}}t.Row=c,a=c,c.__name__=\"Row\",a.prototype.default_view=_,a.define((({Any:o})=>({cols:[o,\"auto\"]})))},\n", - " function _(e,t,a,s,_){var o;s();const i=e(309),n=e(207);class u extends i.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new n.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=u,u.__name__=\"SpacerView\";class c extends i.LayoutDOM{constructor(e){super(e)}}a.Spacer=c,o=c,c.__name__=\"Spacer\",o.prototype.default_view=u},\n", - " function _(e,t,s,i,l){i();const h=e(1);var a;const o=e(207),d=e(43),r=e(9),c=e(10),n=e(20),_=e(309),p=e(313),b=(0,h.__importStar)(e(317)),m=b,u=(0,h.__importStar)(e(318)),g=u,v=(0,h.__importStar)(e(229)),w=v;class f extends _.LayoutDOMView{constructor(){super(...arguments),this._scroll_index=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,(()=>this.rebuild())),this.connect(this.model.properties.active.change,(()=>this.on_active_change()))}styles(){return[...super.styles(),u.default,v.default,b.default]}get child_models(){return this.model.tabs.map((e=>e.child))}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends o.ContentBox{_measure(e){const l=(0,d.size)(s),h=(0,d.children)(i).slice(0,3).map((e=>(0,d.size)(e))),{width:a,height:o}=super._measure(e);if(t){const t=l.width+(0,r.sum)(h.map((e=>e.width)));return{width:e.width!=1/0?e.width:t,height:o}}{const t=l.height+(0,r.sum)(h.map((e=>e.height)));return{width:a,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let l=1,h=1;switch(e){case\"above\":l-=1;break;case\"below\":l+=1;break;case\"left\":h-=1;break;case\"right\":h+=1}const a={layout:this.header,row:l,col:h},c=this.child_views.map((e=>({layout:e.layout,row:1,col:1})));this.layout=new o.Grid([a,...c]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",(0,d.position)(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=(0,d.size)(this.scroll_el),i=(0,d.scroll_size)(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxWidth=\"\",(0,d.undisplay)(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxHeight=\"\",(0,d.undisplay)(this.scroll_el))}const{child_views:l}=this;for(const e of l)(0,d.hide)(e.el);const h=l[this.model.active];null!=h&&(0,d.show)(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs.map(((t,s)=>{const i=(0,d.div)({class:[m.tab,s==e?m.active:null]},t.title);if(i.addEventListener(\"click\",(e=>{this.model.disabled||e.target==e.currentTarget&&this.change_active(s)})),t.closable){const e=(0,d.div)({class:m.close});e.addEventListener(\"click\",(e=>{if(e.target==e.currentTarget){this.model.tabs=(0,r.remove_at)(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}})),i.appendChild(e)}return(this.model.disabled||t.disabled)&&i.classList.add(m.disabled),i}));this.headers_el=(0,d.div)({class:[m.headers]},t),this.wrapper_el=(0,d.div)({class:m.headers_wrapper},this.headers_el),this.left_el=(0,d.div)({class:[g.btn,g.btn_default],disabled:\"\"},(0,d.div)({class:[w.caret,m.left]})),this.right_el=(0,d.div)({class:[g.btn,g.btn_default]},(0,d.div)({class:[w.caret,m.right]})),this.left_el.addEventListener(\"click\",(()=>this.do_scroll(\"left\"))),this.right_el.addEventListener(\"click\",(()=>this.do_scroll(\"right\"))),this.scroll_el=(0,d.div)({class:g.btn_group},this.left_el,this.right_el);const s=this.model.tabs_location;this.header_el=(0,d.div)({class:[m.tabs_header,m[s]]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}do_scroll(e){const t=this.model.tabs.length;\"left\"==e?this._scroll_index-=1:\"right\"==e?this._scroll_index+=1:this._scroll_index=e,this._scroll_index=(0,c.clamp)(this._scroll_index,0,t-1),0==this._scroll_index?this.left_el.setAttribute(\"disabled\",\"\"):this.left_el.removeAttribute(\"disabled\"),this._scroll_index==t-1?this.right_el.setAttribute(\"disabled\",\"\"):this.right_el.removeAttribute(\"disabled\");const s=(0,d.children)(this.headers_el).slice(0,this._scroll_index).map((e=>e.getBoundingClientRect())),i=this.model.tabs_location;if(\"above\"==i||\"below\"==i){const e=-(0,r.sum)(s.map((e=>e.width)));this.headers_el.style.left=`${e}px`}else{const e=-(0,r.sum)(s.map((e=>e.height)));this.headers_el.style.top=`${e}px`}}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=(0,d.children)(this.headers_el);for(const e of t)e.classList.remove(m.active);t[e].classList.add(m.active);const{child_views:s}=this;for(const e of s)(0,d.hide)(e.el);(0,d.show)(s[e].el)}}s.TabsView=f,f.__name__=\"TabsView\";class x extends _.LayoutDOM{constructor(e){super(e)}}s.Tabs=x,a=x,x.__name__=\"Tabs\",a.prototype.default_view=f,a.define((({Int:e,Array:t,Ref:s})=>({tabs:[t(s(p.Panel)),[]],tabs_location:[n.Location,\"above\"],active:[e,0]})))},\n", - " function _(e,r,b,o,t){o(),b.root=\"bk-root\",b.tabs_header=\"bk-tabs-header\",b.btn_group=\"bk-btn-group\",b.btn=\"bk-btn\",b.headers_wrapper=\"bk-headers-wrapper\",b.above=\"bk-above\",b.right=\"bk-right\",b.below=\"bk-below\",b.left=\"bk-left\",b.headers=\"bk-headers\",b.tab=\"bk-tab\",b.active=\"bk-active\",b.close=\"bk-close\",b.disabled=\"bk-disabled\",b.default='.bk-root .bk-tabs-header{display:flex;flex-wrap:nowrap;align-items:center;overflow:hidden;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-tabs-header .bk-btn-group{height:auto;margin-right:5px;}.bk-root .bk-tabs-header .bk-btn-group > .bk-btn{flex-grow:0;height:auto;padding:4px 4px;}.bk-root .bk-tabs-header .bk-headers-wrapper{flex-grow:1;overflow:hidden;color:#666666;}.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper{border-bottom:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper{border-left:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper{border-top:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper{border-right:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-above,.bk-root .bk-tabs-header.bk-below{flex-direction:row;}.bk-root .bk-tabs-header.bk-above .bk-headers,.bk-root .bk-tabs-header.bk-below .bk-headers{flex-direction:row;}.bk-root .bk-tabs-header.bk-left,.bk-root .bk-tabs-header.bk-right{flex-direction:column;}.bk-root .bk-tabs-header.bk-left .bk-headers,.bk-root .bk-tabs-header.bk-right .bk-headers{flex-direction:column;}.bk-root .bk-tabs-header .bk-headers{position:relative;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-tabs-header .bk-tab{padding:4px 8px;border:solid transparent;white-space:nowrap;cursor:pointer;}.bk-root .bk-tabs-header .bk-tab:hover{background-color:#f2f2f2;}.bk-root .bk-tabs-header .bk-tab.bk-active{color:#4d4d4d;background-color:white;border-color:#e6e6e6;}.bk-root .bk-tabs-header .bk-tab .bk-close{margin-left:10px;}.bk-root .bk-tabs-header .bk-tab.bk-disabled{cursor:not-allowed;pointer-events:none;opacity:0.65;}.bk-root .bk-tabs-header.bk-above .bk-tab{border-width:3px 1px 0px 1px;border-radius:4px 4px 0 0;}.bk-root .bk-tabs-header.bk-right .bk-tab{border-width:1px 3px 1px 0px;border-radius:0 4px 4px 0;}.bk-root .bk-tabs-header.bk-below .bk-tab{border-width:0px 1px 3px 1px;border-radius:0 0 4px 4px;}.bk-root .bk-tabs-header.bk-left .bk-tab{border-width:1px 0px 1px 3px;border-radius:4px 0 0 4px;}.bk-root .bk-close{display:inline-block;width:10px;height:10px;vertical-align:middle;background-image:url(\\'data:image/svg+xml;utf8, \\');}.bk-root .bk-close:hover{background-image:url(\\'data:image/svg+xml;utf8, \\');}'},\n", - " function _(o,b,r,t,e){t(),r.root=\"bk-root\",r.btn=\"bk-btn\",r.active=\"bk-active\",r.btn_default=\"bk-btn-default\",r.btn_primary=\"bk-btn-primary\",r.btn_success=\"bk-btn-success\",r.btn_warning=\"bk-btn-warning\",r.btn_danger=\"bk-btn-danger\",r.btn_light=\"bk-btn-light\",r.btn_group=\"bk-btn-group\",r.vertical=\"bk-vertical\",r.horizontal=\"bk-horizontal\",r.dropdown_toggle=\"bk-dropdown-toggle\",r.default=\".bk-root .bk-btn{height:100%;display:inline-block;text-align:center;vertical-align:middle;white-space:nowrap;cursor:pointer;padding:6px 12px;font-size:12px;border:1px solid transparent;border-radius:4px;outline:0;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-btn:hover,.bk-root .bk-btn:focus{text-decoration:none;}.bk-root .bk-btn:active,.bk-root .bk-btn.bk-active{background-image:none;box-shadow:inset 0 3px 5px rgba(0, 0, 0, 0.125);}.bk-root .bk-btn[disabled]{cursor:not-allowed;pointer-events:none;opacity:0.65;box-shadow:none;}.bk-root .bk-btn-default{color:#333;background-color:#fff;border-color:#ccc;}.bk-root .bk-btn-default:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-default.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-default[disabled],.bk-root .bk-btn-default[disabled]:hover,.bk-root .bk-btn-default[disabled]:focus,.bk-root .bk-btn-default[disabled]:active,.bk-root .bk-btn-default[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-primary{color:#fff;background-color:#428bca;border-color:#357ebd;}.bk-root .bk-btn-primary:hover{background-color:#3681c1;border-color:#2c699e;}.bk-root .bk-btn-primary.bk-active{background-color:#3276b1;border-color:#285e8e;}.bk-root .bk-btn-primary[disabled],.bk-root .bk-btn-primary[disabled]:hover,.bk-root .bk-btn-primary[disabled]:focus,.bk-root .bk-btn-primary[disabled]:active,.bk-root .bk-btn-primary[disabled].bk-active{background-color:#506f89;border-color:#357ebd;}.bk-root .bk-btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c;}.bk-root .bk-btn-success:hover{background-color:#4eb24e;border-color:#409240;}.bk-root .bk-btn-success.bk-active{background-color:#47a447;border-color:#398439;}.bk-root .bk-btn-success[disabled],.bk-root .bk-btn-success[disabled]:hover,.bk-root .bk-btn-success[disabled]:focus,.bk-root .bk-btn-success[disabled]:active,.bk-root .bk-btn-success[disabled].bk-active{background-color:#667b66;border-color:#4cae4c;}.bk-root .bk-btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236;}.bk-root .bk-btn-warning:hover{background-color:#eea43b;border-color:#e89014;}.bk-root .bk-btn-warning.bk-active{background-color:#ed9c28;border-color:#d58512;}.bk-root .bk-btn-warning[disabled],.bk-root .bk-btn-warning[disabled]:hover,.bk-root .bk-btn-warning[disabled]:focus,.bk-root .bk-btn-warning[disabled]:active,.bk-root .bk-btn-warning[disabled].bk-active{background-color:#c89143;border-color:#eea236;}.bk-root .bk-btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a;}.bk-root .bk-btn-danger:hover{background-color:#d5433e;border-color:#bd2d29;}.bk-root .bk-btn-danger.bk-active{background-color:#d2322d;border-color:#ac2925;}.bk-root .bk-btn-danger[disabled],.bk-root .bk-btn-danger[disabled]:hover,.bk-root .bk-btn-danger[disabled]:focus,.bk-root .bk-btn-danger[disabled]:active,.bk-root .bk-btn-danger[disabled].bk-active{background-color:#a55350;border-color:#d43f3a;}.bk-root .bk-btn-light{color:#333;background-color:#fff;border-color:#ccc;border-color:transparent;}.bk-root .bk-btn-light:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-light.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-light[disabled],.bk-root .bk-btn-light[disabled]:hover,.bk-root .bk-btn-light[disabled]:focus,.bk-root .bk-btn-light[disabled]:active,.bk-root .bk-btn-light[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-group{height:100%;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-btn-group:not(.bk-vertical),.bk-root .bk-btn-group.bk-horizontal{flex-direction:row;}.bk-root .bk-btn-group.bk-vertical{flex-direction:column;}.bk-root .bk-btn-group > .bk-btn{flex-grow:1;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn + .bk-btn{margin-left:-1px;}.bk-root .bk-btn-group.bk-vertical > .bk-btn + .bk-btn{margin-top:-1px;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:first-child:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:first-child:not(:last-child){border-bottom-left-radius:0;border-bottom-right-radius:0;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:not(:first-child):last-child{border-bottom-left-radius:0;border-top-left-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:not(:first-child):last-child{border-top-left-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group > .bk-btn:not(:first-child):not(:last-child){border-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn{width:100%;}.bk-root .bk-btn-group .bk-dropdown-toggle{flex:0 0 0;padding:6px 6px;}\"},\n", - " function _(e,t,o,n,_){var i;n();const s=e(310);class d extends s.ColumnView{}o.WidgetBoxView=d,d.__name__=\"WidgetBoxView\";class a extends s.Column{constructor(e){super(e)}}o.WidgetBox=a,i=a,a.__name__=\"WidgetBox\",i.prototype.default_view=d},\n", - " function _(t,a,i,e,M){e();var T=t(135);M(\"MathText\",T.MathText),M(\"Ascii\",T.Ascii),M(\"MathML\",T.MathML),M(\"TeX\",T.TeX),M(\"PlainText\",t(139).PlainText)},\n", - " function _(r,o,t,e,n){e(),n(\"CustomJSTransform\",r(322).CustomJSTransform),n(\"Dodge\",r(323).Dodge),n(\"Interpolator\",r(325).Interpolator),n(\"Jitter\",r(326).Jitter),n(\"LinearInterpolator\",r(327).LinearInterpolator),n(\"StepInterpolator\",r(328).StepInterpolator),n(\"Transform\",r(56).Transform)},\n", - " function _(r,t,s,n,e){var a;n();const u=r(56),o=r(13),m=r(34);class _ extends u.Transform{constructor(r){super(r)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}_make_transform(r,t){return new Function(...this.names,r,(0,m.use_strict)(t))}get scalar_transform(){return this._make_transform(\"x\",this.func)}get vector_transform(){return this._make_transform(\"xs\",this.v_func)}compute(r){return this.scalar_transform(...this.values,r)}v_compute(r){return this.vector_transform(...this.values,r)}}s.CustomJSTransform=_,a=_,_.__name__=\"CustomJSTransform\",a.define((({Unknown:r,String:t,Dict:s})=>({args:[s(r),{}],func:[t,\"\"],v_func:[t,\"\"]})))},\n", - " function _(e,n,r,o,s){var t;o();const u=e(324);class a extends u.RangeTransform{constructor(e){super(e)}_compute(e){return e+this.value}}r.Dodge=a,t=a,a.__name__=\"Dodge\",t.define((({Number:e})=>({value:[e,0]})))},\n", - " function _(e,n,t,r,a){var s;r();const c=e(56),o=e(57),i=e(67),u=e(24),h=e(8),l=e(11);class g extends c.Transform{constructor(e){super(e)}v_compute(e){let n;this.range instanceof i.FactorRange?n=this.range.v_synthetic(e):(0,h.isArrayableOf)(e,h.isNumber)?n=e:(0,l.unreachable)();const t=new((0,u.infer_type)(n))(n.length);for(let e=0;e({range:[n(e(o.Range)),null]})))},\n", - " function _(t,e,r,n,s){var o;n();const i=t(56),a=t(70),h=t(24),l=t(9),d=t(8);class c extends i.Transform{constructor(t){super(t),this._sorted_dirty=!0}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._sorted_dirty=!0))}v_compute(t){const e=new((0,h.infer_type)(t))(t.length);for(let r=0;ro*(e[t]-e[r]))),this._x_sorted=new((0,h.infer_type)(e))(n),this._y_sorted=new((0,h.infer_type)(r))(n);for(let t=0;t({x:[o(r,s(e))],y:[o(r,s(e))],data:[i(n(a.ColumnarDataSource)),null],clip:[t,!0]})))},\n", - " function _(t,s,e,i,r){i();const n=t(1);var o;const a=t(324),u=t(67),h=t(20),c=t(8),m=t(12),f=(0,n.__importStar)(t(10)),_=t(11);class p extends a.RangeTransform{constructor(t){super(t)}v_compute(t){var s;let e;this.range instanceof u.FactorRange?e=this.range.v_synthetic(t):(0,c.isArrayableOf)(t,c.isNumber)?e=t:(0,_.unreachable)();const i=e.length;(null===(s=this.previous_offsets)||void 0===s?void 0:s.length)!=i&&(this.previous_offsets=new Array(i),this.previous_offsets=(0,m.map)(this.previous_offsets,(()=>this._compute())));const r=this.previous_offsets;return(0,m.map)(e,((t,s)=>r[s]+t))}_compute(){switch(this.distribution){case\"uniform\":return this.mean+(f.random()-.5)*this.width;case\"normal\":return f.rnorm(this.mean,this.width)}}}e.Jitter=p,o=p,p.__name__=\"Jitter\",o.define((({Number:t})=>({mean:[t,0],width:[t,1],distribution:[h.Distribution,\"uniform\"]})))},\n", - " function _(t,s,_,r,e){r();const i=t(9),o=t(325);class n extends o.Interpolator{constructor(t){super(t)}compute(t){if(this.sort(!1),this.clip){if(tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}if(t==this._x_sorted[0])return this._y_sorted[0];const s=(0,i.find_last_index)(this._x_sorted,(s=>sthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}let e;switch(this.mode){case\"after\":e=(0,d.find_last_index)(this._x_sorted,(e=>t>=e));break;case\"before\":e=(0,d.find_index)(this._x_sorted,(e=>t<=e));break;case\"center\":{const s=(0,d.map)(this._x_sorted,(e=>Math.abs(e-t))),r=(0,d.min)(s);e=(0,d.find_index)(s,(t=>r===t));break}default:throw new Error(`unknown mode: ${this.mode}`)}return-1!=e?this._y_sorted[e]:NaN}}s.StepInterpolator=h,_=h,h.__name__=\"StepInterpolator\",_.define((()=>({mode:[n.StepMode,\"after\"]})))},\n", - " function _(p,o,t,a,n){a(),n(\"MapOptions\",p(330).MapOptions),n(\"GMapOptions\",p(330).GMapOptions),n(\"GMapPlot\",p(330).GMapPlot),n(\"Plot\",p(331).Plot)},\n", - " function _(e,t,n,o,a){var s,p,_;o();const i=e(331),r=e(53),l=e(58),c=e(336);a(\"GMapPlotView\",c.GMapPlotView);class d extends r.Model{constructor(e){super(e)}}n.MapOptions=d,s=d,d.__name__=\"MapOptions\",s.define((({Int:e,Number:t})=>({lat:[t],lng:[t],zoom:[e,12]})));class u extends d{constructor(e){super(e)}}n.GMapOptions=u,p=u,u.__name__=\"GMapOptions\",p.define((({Boolean:e,Int:t,String:n})=>({map_type:[n,\"roadmap\"],scale_control:[e,!1],styles:[n],tilt:[t,45]})));class M extends i.Plot{constructor(e){super(e),this.use_map=!0}}n.GMapPlot=M,_=M,M.__name__=\"GMapPlot\",_.prototype.default_view=c.GMapPlotView,_.define((({String:e,Ref:t})=>({map_options:[t(u)],api_key:[e],api_version:[e,\"weekly\"]}))),_.override({x_range:()=>new l.Range1d,y_range:()=>new l.Range1d})},\n", - " function _(e,t,r,n,i){n();const o=e(1);var a;const s=(0,o.__importStar)(e(48)),l=(0,o.__importStar)(e(18)),_=e(15),c=e(20),h=e(9),d=e(13),u=e(8),g=e(309),p=e(128),f=e(306),b=e(40),w=e(118),y=e(59),m=e(221),x=e(57),v=e(55),A=e(75),S=e(41),R=e(176),D=e(175),L=e(63),P=e(332);i(\"PlotView\",P.PlotView);class k extends g.LayoutDOM{constructor(e){super(e),this.use_map=!1}_doc_attached(){super._doc_attached(),this._push_changes([[this.properties.inner_height,null,this.inner_height],[this.properties.inner_width,null,this.inner_width]])}initialize(){super.initialize(),this.reset=new _.Signal0(this,\"reset\");for(const e of(0,d.values)(this.extra_x_ranges).concat(this.x_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}for(const e of(0,d.values)(this.extra_y_ranges).concat(this.y_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}}add_layout(e,t=\"center\"){const r=this.properties[t].get_value();this.setv({[t]:[...r,e]})}remove_layout(e){const t=t=>{(0,h.remove_by)(t,(t=>t==e))};t(this.left),t(this.right),t(this.above),t(this.below),t(this.center)}get data_renderers(){return this.renderers.filter((e=>e instanceof R.DataRenderer))}add_renderers(...e){this.renderers=this.renderers.concat(e)}add_glyph(e,t=new A.ColumnDataSource,r={}){const n=new D.GlyphRenderer(Object.assign(Object.assign({},r),{data_source:t,glyph:e}));return this.add_renderers(n),n}add_tools(...e){this.toolbar.tools=this.toolbar.tools.concat(e)}get panels(){return[...this.side_panels,...this.center]}get side_panels(){const{above:e,below:t,left:r,right:n}=this;return(0,h.concat)([e,t,r,n])}}r.Plot=k,a=k,k.__name__=\"Plot\",a.prototype.default_view=P.PlotView,a.mixins([[\"outline_\",s.Line],[\"background_\",s.Fill],[\"border_\",s.Fill]]),a.define((({Boolean:e,Number:t,String:r,Array:n,Dict:i,Or:o,Ref:a,Null:s,Nullable:_})=>({toolbar:[a(m.Toolbar),()=>new m.Toolbar],toolbar_location:[_(c.Location),\"right\"],toolbar_sticky:[e,!0],plot_width:[l.Alias(\"width\")],plot_height:[l.Alias(\"height\")],frame_width:[_(t),null],frame_height:[_(t),null],title:[o(a(w.Title),r,s),\"\",{convert:e=>(0,u.isString)(e)?new w.Title({text:e}):e}],title_location:[_(c.Location),\"above\"],above:[n(o(a(b.Annotation),a(p.Axis))),[]],below:[n(o(a(b.Annotation),a(p.Axis))),[]],left:[n(o(a(b.Annotation),a(p.Axis))),[]],right:[n(o(a(b.Annotation),a(p.Axis))),[]],center:[n(o(a(b.Annotation),a(f.Grid))),[]],renderers:[n(a(S.Renderer)),[]],x_range:[a(x.Range),()=>new L.DataRange1d],y_range:[a(x.Range),()=>new L.DataRange1d],x_scale:[a(v.Scale),()=>new y.LinearScale],y_scale:[a(v.Scale),()=>new y.LinearScale],extra_x_ranges:[i(a(x.Range)),{}],extra_y_ranges:[i(a(x.Range)),{}],extra_x_scales:[i(a(v.Scale)),{}],extra_y_scales:[i(a(v.Scale)),{}],lod_factor:[t,10],lod_interval:[t,300],lod_threshold:[_(t),2e3],lod_timeout:[t,500],hidpi:[e,!0],output_backend:[c.OutputBackend,\"canvas\"],min_border:[_(t),5],min_border_top:[_(t),null],min_border_left:[_(t),null],min_border_bottom:[_(t),null],min_border_right:[_(t),null],inner_width:[t,0],inner_height:[t,0],outer_width:[t,0],outer_height:[t,0],match_aspect:[e,!1],aspect_scale:[t,1],reset_policy:[c.ResetPolicy,\"standard\"]}))),a.override({width:600,height:600,outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"})},\n", - " function _(e,t,i,s,a){s();const n=e(1),o=e(126),l=e(249),r=e(309),_=e(40),h=e(118),d=e(128),u=e(220),c=e(251),p=e(113),v=e(45),g=e(19),b=e(251),m=e(333),y=e(8),w=e(9),f=e(235),x=e(208),z=e(211),k=e(209),q=e(123),M=e(65),R=e(334),V=e(335),S=e(28);class O extends r.LayoutDOMView{constructor(){super(...arguments),this._outer_bbox=new M.BBox,this._inner_bbox=new M.BBox,this._needs_paint=!0,this._needs_layout=!1,this._invalidated_painters=new Set,this._invalidate_all=!0,this._needs_notify=!1}get canvas(){return this.canvas_view}get state(){return this._state_manager}set invalidate_dataranges(e){this._range_manager.invalidate_dataranges=e}renderer_view(e){const t=this.renderer_views.get(e);if(null==t)for(const[,t]of this.renderer_views){const i=t.renderer_view(e);if(null!=i)return i}return t}get is_paused(){return null!=this._is_paused&&0!==this._is_paused}get child_models(){return[]}pause(){null==this._is_paused?this._is_paused=1:this._is_paused+=1}unpause(e=!1){if(null==this._is_paused)throw new Error(\"wasn't paused\");this._is_paused-=1,0!=this._is_paused||e||this.request_paint(\"everything\")}notify_finished_after_paint(){this._needs_notify=!0}request_render(){this.request_paint(\"everything\")}request_paint(e){this.invalidate_painters(e),this.schedule_paint()}invalidate_painters(e){if(\"everything\"==e)this._invalidate_all=!0;else if((0,y.isArray)(e))for(const t of e)this._invalidated_painters.add(t);else this._invalidated_painters.add(e)}schedule_paint(){if(!this.is_paused){const e=this.throttled_paint();this._ready=this._ready.then((()=>e))}}request_layout(){this._needs_layout=!0,this.request_paint(\"everything\")}reset(){\"standard\"==this.model.reset_policy&&(this.state.clear(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){(0,p.remove_views)(this.renderer_views),(0,p.remove_views)(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.lod_started=!1,this.visuals=new v.Visuals(this),this._initial_state={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.renderer_views=new Map,this.tool_views=new Map,this.frame=new o.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges,this.model.extra_x_scales,this.model.extra_y_scales),this._range_manager=new R.RangeManager(this),this._state_manager=new V.StateManager(this,this._initial_state),this.throttled_paint=(0,m.throttle)((()=>this.repaint()),1e3/60);const{title_location:e,title:t}=this.model;null!=e&&null!=t&&(this._title=t instanceof h.Title?t:new h.Title({text:t}));const{toolbar_location:i,toolbar:s}=this.model;null!=i&&null!=s&&(this._toolbar=new u.ToolbarPanel({toolbar:s}),s.toolbar_location=i)}async lazy_initialize(){await super.lazy_initialize();const{hidpi:e,output_backend:t}=this.model,i=new l.Canvas({hidpi:e,output_backend:t});this.canvas_view=await(0,p.build_view)(i,{parent:this}),this.canvas_view.plot_views=[this],await this.build_renderer_views(),await this.build_tool_views(),this._range_manager.update_dataranges(),this.unpause(!0),g.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){var e,t,i,s,a;this.layout=new z.BorderLayout,this.layout.set_sizing(this.box_sizing());const n=(0,w.copy)(this.model.above),o=(0,w.copy)(this.model.below),l=(0,w.copy)(this.model.left),r=(0,w.copy)(this.model.right),d=e=>{switch(e){case\"above\":return n;case\"below\":return o;case\"left\":return l;case\"right\":return r}},{title_location:c,title:p}=this.model;null!=c&&null!=p&&d(c).push(this._title);const{toolbar_location:v,toolbar:g}=this.model;if(null!=v&&null!=g){const e=d(v);let t=!0;if(this.model.toolbar_sticky)for(let i=0;i{var i;const s=this.renderer_view(t);return s.panel=new q.Panel(e),null===(i=s.update_layout)||void 0===i||i.call(s),s.layout},m=(e,t)=>{const i=\"above\"==e||\"below\"==e,s=[];for(const a of t)if((0,y.isArray)(a)){const t=a.map((t=>{const s=b(e,t);if(t instanceof u.ToolbarPanel){const e=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[e]:\"min\"}))}return s}));let n;i?(n=new k.Row(t),n.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(n=new k.Column(t),n.set_sizing({width_policy:\"min\",height_policy:\"max\"})),n.absolute=!0,s.push(n)}else s.push(b(e,a));return s},f=null!==(e=this.model.min_border)&&void 0!==e?e:0;this.layout.min_border={left:null!==(t=this.model.min_border_left)&&void 0!==t?t:f,top:null!==(i=this.model.min_border_top)&&void 0!==i?i:f,right:null!==(s=this.model.min_border_right)&&void 0!==s?s:f,bottom:null!==(a=this.model.min_border_bottom)&&void 0!==a?a:f};const M=new x.NodeLayout,R=new x.VStack,V=new x.VStack,S=new x.HStack,O=new x.HStack;M.absolute=!0,R.absolute=!0,V.absolute=!0,S.absolute=!0,O.absolute=!0,M.children=this.model.center.filter((e=>e instanceof _.Annotation)).map((e=>{var t;const i=this.renderer_view(e);return null===(t=i.update_layout)||void 0===t||t.call(i),i.layout})).filter((e=>null!=e));const{frame_width:P,frame_height:j}=this.model;M.set_sizing(Object.assign(Object.assign({},null!=P?{width_policy:\"fixed\",width:P}:{width_policy:\"fit\"}),null!=j?{height_policy:\"fixed\",height:j}:{height_policy:\"fit\"})),M.on_resize((e=>this.frame.set_geometry(e))),R.children=(0,w.reversed)(m(\"above\",n)),V.children=m(\"below\",o),S.children=(0,w.reversed)(m(\"left\",l)),O.children=m(\"right\",r),R.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),V.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),S.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.center_panel=M,this.layout.top_panel=R,this.layout.bottom_panel=V,this.layout.left_panel=S,this.layout.right_panel=O}get axis_views(){const e=[];for(const[,t]of this.renderer_views)t instanceof d.AxisView&&e.push(t);return e}set_toolbar_visibility(e){for(const t of this.visibility_callbacks)t(e)}update_range(e,t){this.pause(),this._range_manager.update(e,t),this.unpause()}reset_range(){this.update_range(null),this.trigger_ranges_update_event()}trigger_ranges_update_event(){const{x_range:e,y_range:t}=this.model;this.model.trigger_event(new b.RangesUpdate(e.start,e.end,t.start,t.end))}get_selection(){const e=new Map;for(const t of this.model.data_renderers){const{selected:i}=t.selection_manager.source;e.set(t,i)}return e}update_selection(e){for(const t of this.model.data_renderers){const i=t.selection_manager.source;if(null!=e){const s=e.get(t);null!=s&&i.selected.update(s,!0)}else i.selection_manager.clear()}}reset_selection(){this.update_selection(null)}_invalidate_layout(){(()=>{var e;for(const t of this.model.side_panels){const i=this.renderer_views.get(t);if(null===(e=i.layout)||void 0===e?void 0:e.has_size_changed())return this.invalidate_painters(i),!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map((e=>this.renderer_views.get(e)))}*_compute_renderers(){const{above:e,below:t,left:i,right:s,center:a,renderers:n}=this.model;yield*n,yield*e,yield*t,yield*i,yield*s,yield*a,null!=this._title&&(yield this._title),null!=this._toolbar&&(yield this._toolbar);for(const e of this.model.toolbar.tools)null!=e.overlay&&(yield e.overlay),yield*e.synthetic_renderers}async build_renderer_views(){this.computed_renderers=[...this._compute_renderers()],await(0,p.build_views)(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const e=this.model.toolbar.tools;(await(0,p.build_views)(this.tool_views,e,{parent:this})).map((e=>this.canvas_view.ui_event_bus.register_tool(e)))}connect_signals(){super.connect_signals();const{x_ranges:e,y_ranges:t}=this.frame;for(const[,t]of e)this.connect(t.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));for(const[,e]of t)this.connect(e.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));const{above:i,below:s,left:a,right:n,center:o,renderers:l}=this.model.properties;this.on_change([i,s,a,n,o,l],(async()=>await this.build_renderer_views())),this.connect(this.model.toolbar.properties.tools.change,(async()=>{await this.build_renderer_views(),await this.build_tool_views()})),this.connect(this.model.change,(()=>this.request_paint(\"everything\"))),this.connect(this.model.reset,(()=>this.reset()))}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,e]of this.renderer_views)if(!e.has_finished())return!1;return!0}after_layout(){var e;super.after_layout();for(const[,t]of this.renderer_views)t instanceof _.AnnotationView&&(null===(e=t.after_layout)||void 0===e||e.call(t));if(this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this._range_manager.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:e,height:t}=this.layout.bbox;this.canvas_view.resize(e,t),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}const{inner_bbox:t}=this.layout;this._inner_bbox.equals(t)||(this._inner_bbox=t,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){this.is_paused||(this.model.visible&&(g.logger.trace(`${this.toString()}.paint()`),this._actual_paint()),this._needs_notify&&(this._needs_notify=!1,this.notify_finished()))}_actual_paint(){var e;const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint(\"everything\")}),this.model.lod_timeout):t.interactive_stop()}this._range_manager.invalidate_dataranges&&(this._range_manager.update_dataranges(),this._invalidate_layout());let i=!1,s=!1;if(this._invalidate_all)i=!0,s=!0;else for(const e of this._invalidated_painters){const{level:t}=e.model;if(\"overlay\"!=t?i=!0:s=!0,i&&s)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const a=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:o}=this.canvas_view;i&&(n.prepare(),this.canvas_view.prepare_webgl(a),this._map_hook(n.ctx,a),this._paint_empty(n.ctx,a),this._paint_outline(n.ctx,a),this._paint_levels(n.ctx,\"image\",a,!0),this._paint_levels(n.ctx,\"underlay\",a,!0),this._paint_levels(n.ctx,\"glyph\",a,!0),this._paint_levels(n.ctx,\"guide\",a,!1),this._paint_levels(n.ctx,\"annotation\",a,!1),n.finish()),(s||S.settings.wireframe)&&(o.prepare(),this._paint_levels(o.ctx,\"overlay\",a,!1),S.settings.wireframe&&this._paint_layout(o.ctx,this.layout),o.finish()),null==this._initial_state.range&&(this._initial_state.range=null!==(e=this._range_manager.compute_initial())&&void 0!==e?e:void 0),this._needs_paint=!1}_paint_levels(e,t,i,s){for(const a of this.computed_renderers){if(a.level!=t)continue;const n=this.renderer_views.get(a);e.save(),(s||n.needs_clip)&&(e.beginPath(),e.rect(...i),e.clip()),n.render(),e.restore(),n.has_webgl&&n.needs_webgl_blit&&this.canvas_view.blit_webgl(e)}}_paint_layout(e,t){const{x:i,y:s,width:a,height:n}=t.bbox;e.strokeStyle=\"blue\",e.strokeRect(i,s,a,n);for(const a of t)e.save(),t.absolute||e.translate(i,s),this._paint_layout(e,a),e.restore()}_map_hook(e,t){}_paint_empty(e,t){const[i,s,a,n]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,_]=t;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(e),e.fillRect(i,s,a,n),e.clearRect(o,l,r,_)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fillRect(o,l,r,_))}_paint_outline(e,t){if(this.visuals.outline_line.doit){e.save(),this.visuals.outline_line.set_value(e);let[i,s,a,n]=t;i+a==this.layout.bbox.width&&(a-=1),s+n==this.layout.bbox.height&&(n-=1),e.strokeRect(i,s,a,n),e.restore()}}to_blob(){return this.canvas_view.to_blob()}export(e,t=!0){const i=\"png\"==e?\"canvas\":\"svg\",s=new f.CanvasLayer(i,t),{width:a,height:n}=this.layout.bbox;s.resize(a,n);const{canvas:o}=this.canvas_view.compose();return s.ctx.drawImage(o,0,0),s}serializable_state(){const e=super.serializable_state(),{children:t}=e,i=(0,n.__rest)(e,[\"children\"]),s=this.get_renderer_views().map((e=>e.serializable_state())).filter((e=>null!=e.bbox));return Object.assign(Object.assign({},i),{children:[...null!=t?t:[],...s]})}}i.PlotView=O,O.__name__=\"PlotView\"},\n", - " function _(t,n,e,o,u){o(),e.throttle=function(t,n){let e=null,o=0,u=!1;return function(){return new Promise(((r,i)=>{const l=function(){o=Date.now(),e=null,u=!1;try{t(),r()}catch(t){i(t)}},a=Date.now(),c=n-(a-o);c<=0&&!u?(null!=e&&clearTimeout(e),u=!0,requestAnimationFrame(l)):e||u?r():e=setTimeout((()=>requestAnimationFrame(l)),c)}))}}},\n", - " function _(t,n,e,a,s){a();const o=t(63),r=t(19);class l{constructor(t){this.parent=t,this.invalidate_dataranges=!0}get frame(){return this.parent.frame}update(t,n){const{x_ranges:e,y_ranges:a}=this.frame;if(null==t){for(const[,t]of e)t.reset();for(const[,t]of a)t.reset();this.update_dataranges()}else{const s=[];for(const[n,a]of e)s.push([a,t.xrs.get(n)]);for(const[n,e]of a)s.push([e,t.yrs.get(n)]);(null==n?void 0:n.scrolling)&&this._update_ranges_together(s),this._update_ranges_individually(s,n)}}reset(){this.update(null)}_update_dataranges(t){const n=new Map,e=new Map;let a=!1;for(const[,n]of t.x_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const[,n]of t.y_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const t of this.parent.model.data_renderers){const s=this.parent.renderer_view(t);if(null==s)continue;const o=s.glyph_view.bounds();if(null!=o&&n.set(t,o),a){const n=s.glyph_view.log_bounds();null!=n&&e.set(t,n)}}let s=!1,l=!1;const i=t.x_target.span,d=t.y_target.span;let u;!1!==this.parent.model.match_aspect&&0!=i&&0!=d&&(u=1/this.parent.model.aspect_scale*(i/d));for(const[,a]of t.x_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,0,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}for(const[,a]of t.y_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,1,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}if(s&&l){r.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,n]of t.x_ranges)n.bounds=null;for(const[,n]of t.y_ranges)n.bounds=null}}update_dataranges(){this._update_dataranges(this.frame);for(const t of this.parent.model.renderers){const{coordinates:n}=t;null!=n&&this._update_dataranges(n)}null!=this.compute_initial()&&(this.invalidate_dataranges=!1)}compute_initial(){let t=!0;const{x_ranges:n,y_ranges:e}=this.frame,a=new Map,s=new Map;for(const[e,s]of n){const{start:n,end:o}=s;if(null==n||null==o||isNaN(n+o)){t=!1;break}a.set(e,{start:n,end:o})}if(t)for(const[n,a]of e){const{start:e,end:o}=a;if(null==e||null==o||isNaN(e+o)){t=!1;break}s.set(n,{start:e,end:o})}return t?{xrs:a,yrs:s}:(r.logger.warn(\"could not set initial ranges\"),null)}_update_ranges_together(t){let n=1;for(const[e,a]of t)n=Math.min(n,this._get_weight_to_constrain_interval(e,a));if(n<1)for(const[e,a]of t)a.start=n*a.start+(1-n)*e.start,a.end=n*a.end+(1-n)*e.end}_update_ranges_individually(t,n){const e=!!(null==n?void 0:n.panning),a=!!(null==n?void 0:n.scrolling);let s=!1;for(const[n,o]of t){if(!a){const t=this._get_weight_to_constrain_interval(n,o);t<1&&(o.start=t*o.start+(1-t)*n.start,o.end=t*o.end+(1-t)*n.end)}if(null!=n.bounds&&\"auto\"!=n.bounds){const[t,r]=n.bounds,l=Math.abs(o.end-o.start);n.is_reversed?(null!=t&&t>o.end&&(s=!0,o.end=t,(e||a)&&(o.start=t+l)),null!=r&&ro.start&&(s=!0,o.start=t,(e||a)&&(o.end=t+l)),null!=r&&r0&&r0&&r>a&&(s=(a-o)/(r-o)),s=Math.max(0,Math.min(1,s))}return s}}e.RangeManager=l,l.__name__=\"RangeManager\"},\n", - " function _(t,i,s,e,n){e();const h=t(15);class a{constructor(t,i){this.parent=t,this.initial_state=i,this.changed=new h.Signal0(this.parent,\"state_changed\"),this.history=[],this.index=-1}_do_state_change(t){const i=null!=this.history[t]?this.history[t].state:this.initial_state;return null!=i.range&&this.parent.update_range(i.range),null!=i.selection&&this.parent.update_selection(i.selection),i}push(t,i){const{history:s,index:e}=this,n=null!=s[e]?s[e].state:{},h=Object.assign(Object.assign(Object.assign({},this.initial_state),n),i);this.history=this.history.slice(0,this.index+1),this.history.push({type:t,state:h}),this.index=this.history.length-1,this.changed.emit()}clear(){this.history=[],this.index=-1,this.changed.emit()}undo(){if(this.can_undo){this.index-=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}redo(){if(this.can_redo){this.index+=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}get can_undo(){return this.index>=0}get can_redo(){return this.indexm.emit();const s=encodeURIComponent,o=document.createElement(\"script\");o.type=\"text/javascript\",o.src=`https://maps.googleapis.com/maps/api/js?v=${s(e)}&key=${s(t)}&callback=_bokeh_gmaps_callback`,document.body.appendChild(o)}(t,e)}m.connect((()=>this.request_paint(\"everything\")))}this.unpause()}remove(){(0,p.remove)(this.map_el),super.remove()}update_range(t,e){var s,o;if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null,e);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(null!==(s=t.sdx)&&void 0!==s?s:0,null!==(o=t.sdy)&&void 0!==o?o:0),super.update_range(t,e);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t,e);const s=t.factor<0?-1:1,o=this.map.getZoom();if(null!=o){const t=o+s;if(t>=2){this.map.setZoom(t);const[e,s]=this._get_projected_bounds();s-e<0&&this.map.setZoom(o)}}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=(0,p.div)({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",(()=>this._set_bokeh_ranges())),t.event.addListener(this.map,\"bounds_changed\",(()=>this._set_bokeh_ranges())),t.event.addListenerOnce(this.map,\"tilesloaded\",(()=>this._render_finished())),this.connect(this.model.properties.map_options.change,(()=>this._update_options())),this.connect(this.model.map_options.properties.styles.change,(()=>this._update_styles())),this.connect(this.model.map_options.properties.lat.change,(()=>this._update_center(\"lat\"))),this.connect(this.model.map_options.properties.lng.change,(()=>this._update_center(\"lng\"))),this.connect(this.model.map_options.properties.zoom.change,(()=>this._update_zoom())),this.connect(this.model.map_options.properties.map_type.change,(()=>this._update_map_type())),this.connect(this.model.map_options.properties.scale_control.change,(()=>this._update_scale_control())),this.connect(this.model.map_options.properties.tilt.change,(()=>this._update_tilt()))}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,o]=this._get_latlon_bounds(),[i,a]=l.wgs84_mercator.compute(t,s),[n,p]=l.wgs84_mercator.compute(e,o);return[i,n,a,p]}_set_bokeh_ranges(){const[t,e,s,o]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:o})}_update_center(t){var e;const s=null===(e=this.map.getCenter())||void 0===e?void 0:e.toJSON();null!=s&&(s[t]=this.model.map_options[t],this.map.setCenter(s),this._set_bokeh_ranges())}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,o,i]=e;this.map_el.style.top=`${s}px`,this.map_el.style.left=`${t}px`,this.map_el.style.width=`${o}px`,this.map_el.style.height=`${i}px`}}_paint_empty(t,e){const s=this.layout.bbox.width,o=this.layout.bbox.height,[i,a,n,p]=e;t.clearRect(0,0,s,o),t.beginPath(),t.moveTo(0,0),t.lineTo(0,o),t.lineTo(s,o),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(i,a),t.lineTo(i+n,a),t.lineTo(i+n,a+p),t.lineTo(i,a+p),t.lineTo(i,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=(0,_.color2css)(this.model.border_fill_color),t.fill())}}s.GMapPlotView=d,d.__name__=\"GMapPlotView\"},\n", - " function _(t,_,n,o,r){o();(0,t(1).__exportStar)(t(132),n)},\n", - " function _(e,r,d,n,R){n(),R(\"GlyphRenderer\",e(175).GlyphRenderer),R(\"GraphRenderer\",e(339).GraphRenderer),R(\"GuideRenderer\",e(129).GuideRenderer);var G=e(41);R(\"Renderer\",G.Renderer),R(\"RendererGroup\",G.RendererGroup)},\n", - " function _(e,r,i,n,t){var o;n();const s=e(176),d=e(175),a=e(303),p=e(302),l=e(113),_=e(178),h=e(283),y=e(286);class c extends s.DataRendererView{get glyph_view(){return this.node_view.glyph}async lazy_initialize(){await super.lazy_initialize(),this.apply_coordinates();const{parent:e}=this,{edge_renderer:r,node_renderer:i}=this.model;this.edge_view=await(0,l.build_view)(r,{parent:e}),this.node_view=await(0,l.build_view)(i,{parent:e})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,(()=>{this.apply_coordinates(),this.edge_view.set_data(),this.node_view.set_data(),this.request_render()}))}apply_coordinates(){const{edge_renderer:e,node_renderer:r}=this.model;if(!(e.glyph instanceof h.MultiLine||e.glyph instanceof y.Patches))throw new Error(`${this}.edge_renderer.glyph must be a MultiLine glyph`);if(!(r.glyph instanceof _.XYGlyph))throw new Error(`${this}.node_renderer.glyph must be a XYGlyph glyph`);const i=this.model.layout_provider.edge_coordinates,n=this.model.layout_provider.node_coordinates;e.glyph.properties.xs.internal=!0,e.glyph.properties.ys.internal=!0,r.glyph.properties.x.internal=!0,r.glyph.properties.y.internal=!0,e.glyph.xs={expr:i.x},e.glyph.ys={expr:i.y},r.glyph.x={expr:n.x},r.glyph.y={expr:n.y}}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}renderer_view(e){if(e instanceof d.GlyphRenderer){if(e==this.edge_view.model)return this.edge_view;if(e==this.node_view.model)return this.node_view}return super.renderer_view(e)}}i.GraphRendererView=c,c.__name__=\"GraphRendererView\";class g extends s.DataRenderer{constructor(e){super(e)}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}i.GraphRenderer=g,o=g,g.__name__=\"GraphRenderer\",o.prototype.default_view=c,o.define((({Ref:e})=>({layout_provider:[e(a.LayoutProvider)],node_renderer:[e(d.GlyphRenderer)],edge_renderer:[e(d.GlyphRenderer)],selection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly],inspection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly]})))},\n", - " function _(e,t,n,o,c){o();(0,e(1).__exportStar)(e(74),n),c(\"Selection\",e(72).Selection)},\n", - " function _(a,e,S,o,r){o(),r(\"ServerSentDataSource\",a(342).ServerSentDataSource),r(\"AjaxDataSource\",a(344).AjaxDataSource),r(\"ColumnDataSource\",a(75).ColumnDataSource),r(\"ColumnarDataSource\",a(70).ColumnarDataSource),r(\"CDSView\",a(190).CDSView),r(\"DataSource\",a(71).DataSource),r(\"GeoJSONDataSource\",a(345).GeoJSONDataSource),r(\"WebDataSource\",a(343).WebDataSource)},\n", - " function _(e,t,i,a,s){a();const n=e(343);class r extends n.WebDataSource{constructor(e){super(e),this.initialized=!1}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{var t;this.load_data(JSON.parse(e.data),this.mode,null!==(t=this.max_size)&&void 0!==t?t:void 0)}}}}i.ServerSentDataSource=r,r.__name__=\"ServerSentDataSource\"},\n", - " function _(e,t,a,n,r){var s;n();const l=e(75),o=e(20);class c extends l.ColumnDataSource{constructor(e){super(e)}get_column(e){const t=this.data[e];return null!=t?t:[]}get_length(){var e;return null!==(e=super.get_length())&&void 0!==e?e:0}initialize(){super.initialize(),this.setup()}load_data(e,t,a){const{adapter:n}=this;let r;switch(r=null!=n?n.execute(this,{response:e}):e,t){case\"replace\":this.data=r;break;case\"append\":{const e=this.data;for(const t of this.columns()){const n=Array.from(e[t]),s=Array.from(r[t]),l=n.concat(s);r[t]=null!=a?l.slice(-a):l}this.data=r;break}}}}a.WebDataSource=c,s=c,c.__name__=\"WebDataSource\",s.define((({Any:e,Int:t,String:a,Nullable:n})=>({max_size:[n(t),null],mode:[o.UpdateMode,\"replace\"],adapter:[n(e),null],data_url:[a]})))},\n", - " function _(t,e,i,s,a){var n;s();const r=t(343),o=t(20),l=t(19),d=t(13);class h extends r.WebDataSource{constructor(t){super(t),this.interval=null,this.initialized=!1}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),null!=this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=null,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",(()=>this.do_load(s,t,null!=e?e:void 0))),s.addEventListener(\"error\",(()=>this.do_error(s))),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of(0,d.entries)(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){l.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=h,n=h,h.__name__=\"AjaxDataSource\",n.define((({Boolean:t,Int:e,String:i,Dict:s,Nullable:a})=>({polling_interval:[a(e),null],content_type:[i,\"application/json\"],http_headers:[s(i),{}],method:[o.HTTPMethod,\"POST\"],if_modified:[t,!1]})))},\n", - " function _(e,t,o,r,n){var s;r();const a=e(70),i=e(19),l=e(9),c=e(13);function _(e){return null!=e?e:NaN}const{hasOwnProperty:g}=Object.prototype;class u extends a.ColumnarDataSource{constructor(e){super(e)}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,(()=>this._update_data()))}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return(0,l.range)(0,e).map((e=>[]))}_get_new_nan_array(e){return(0,l.range)(0,e).map((e=>NaN))}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of(0,c.entries)(s))g.call(t,e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=_(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=_(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const s=n.reduce(r);for(let e=0;e({geojson:[e]}))),s.internal((({Dict:e,Arrayable:t})=>({data:[e(t),{}]})))},\n", - " function _(e,r,T,o,S){o(),S(\"BBoxTileSource\",e(347).BBoxTileSource),S(\"MercatorTileSource\",e(348).MercatorTileSource),S(\"QUADKEYTileSource\",e(351).QUADKEYTileSource),S(\"TileRenderer\",e(352).TileRenderer),S(\"TileSource\",e(349).TileSource),S(\"TMSTileSource\",e(355).TMSTileSource),S(\"WMTSTileSource\",e(353).WMTSTileSource)},\n", - " function _(e,t,r,o,l){var i;o();const n=e(348);class s extends n.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars);let l,i,n,s;return this.use_latlon?[i,s,l,n]=this.get_tile_geographic_bounds(e,t,r):[i,s,l,n]=this.get_tile_meter_bounds(e,t,r),o.replace(\"{XMIN}\",i.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",l.toString()).replace(\"{YMAX}\",n.toString())}}r.BBoxTileSource=s,i=s,s.__name__=\"BBoxTileSource\",i.define((({Boolean:e})=>({use_latlon:[e,!1]})))},\n", - " function _(t,e,i,_,s){var r;_();const o=t(349),n=t(9),l=t(350);class u extends o.TileSource{constructor(t){super(t)}initialize(){super.initialize(),this._resolutions=(0,n.range)(this.min_zoom,this.max_zoom+1).map((t=>this.get_resolution(t)))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=u,r=u,u.__name__=\"MercatorTileSource\",r.define((({Boolean:t})=>({snap_to_zoom:[t,!1],wrap_around:[t,!0]}))),r.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})},\n", - " function _(e,t,r,i,n){var l;i();const a=e(53),s=e(13);class c extends a.Model{constructor(e){super(e)}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._clear_cache()))}string_lookup_replace(e,t){let r=e;for(const[e,i]of(0,s.entries)(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map((e=>parseInt(e)));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,l]=t,a=(n-r)/2+r,s=(l-i)/2+i;e.sort((function(e,t){return Math.sqrt((a-e[0])**2+(s-e[1])**2)-Math.sqrt((a-t[0])**2+(s-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=c,l=c,c.__name__=\"TileSource\",l.define((({Number:e,String:t,Dict:r,Nullable:i})=>({url:[t,\"\"],tile_size:[e,256],max_zoom:[e,30],min_zoom:[e,0],extra_url_vars:[r(t),{}],attribution:[t,\"\"],x_origin_offset:[e],y_origin_offset:[e],initial_resolution:[i(e),null]})))},\n", - " function _(t,e,r,n,o){n();const c=t(78);function _(t,e){return c.wgs84_mercator.compute(t,e)}function g(t,e){return c.wgs84_mercator.invert(t,e)}r.geographic_to_meters=_,r.meters_to_geographic=g,r.geographic_extent_to_meters=function(t){const[e,r,n,o]=t,[c,g]=_(e,r),[i,u]=_(n,o);return[c,g,i,u]},r.meters_extent_to_geographic=function(t){const[e,r,n,o]=t,[c,_]=g(e,r),[i,u]=g(n,o);return[c,_,i,u]}},\n", - " function _(e,t,r,s,_){s();const o=e(348);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const s=this.string_lookup_replace(this.url,this.extra_url_vars),[_,o,c]=this.tms_to_wmts(e,t,r),i=this.tile_xyz_to_quadkey(_,o,c);return s.replace(\"{Q}\",i)}}r.QUADKEYTileSource=c,c.__name__=\"QUADKEYTileSource\"},\n", - " function _(t,e,i,s,_){s();const n=t(1);var a;const o=t(349),r=t(353),h=t(41),l=t(58),d=t(43),m=t(136),c=t(9),u=t(8),p=(0,n.__importStar)(t(354));class g extends h.RendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.tile_source.change,(()=>this.request_render()))}remove(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el),super.remove()}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el);const{attribution:t}=this.model.tile_source;if((0,u.isString)(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=(0,d.div)({class:p.tile_attribution,style:{position:\"absolute\",right:`${s}px`,bottom:`${_}px`,\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof l.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof l.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const n=this.model.tile_source.tile_xyz_to_quadkey(t,e,i),a=this.model.tile_source.tile_xyz_to_key(t,e,i);if(this.model.tile_source.tiles.has(a))return;const[o,r,h]=this.model.tile_source.normalize_xyz(t,e,i),l=this.model.tile_source.get_image_url(o,r,h),d={img:void 0,tile_coords:[t,e,i],normalized_coords:[o,r,h],quadkey:n,cache_key:a,bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]};this.model.tile_source.tiles.set(a,d),this._tiles.push(d),new m.ImageLoader(l,{loaded:t=>{Object.assign(d,{img:t,loaded:!0}),_?(d.finished=!0,this.notify_finished()):this.request_render()},failed(){d.finished=!0}})}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0==this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,o=t,r=i,h=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,o,r,n,a),this.map_canvas.setImageSmoothingEnabled(h),e.finished=!0}}_set_rect(){const t=this.plot_model.outline_line_width,e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,o=i,r=!0),r&&(this.x_range.setv({start:s[0],end:s[2]}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const h=t.get_tiles_by_extent(s,o),l=[],d=[],m=[],u=[];for(const e of h){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),o=t.tiles.get(a);if(null!=o&&o.loaded)d.push(a);else if(this.model.render_parents){const[e,a,o]=t.get_closest_parent_by_tile_xyz(i,s,n),r=t.tile_xyz_to_key(e,a,o),h=t.tiles.get(r);if(null!=h&&h.loaded&&!(0,c.includes)(m,r)&&m.push(r),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&u.push(e)}}}null==o&&l.push(e)}this._render_tiles(m),this._render_tiles(u),this._render_tiles(d),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout((()=>this._fetch_tiles(l)),65)}}i.TileRendererView=g,g.__name__=\"TileRendererView\";class b extends h.Renderer{constructor(t){super(t)}}i.TileRenderer=b,a=b,b.__name__=\"TileRenderer\",a.prototype.default_view=g,a.define((({Boolean:t,Number:e,Ref:i})=>({alpha:[e,1],smoothing:[t,!0],tile_source:[i(o.TileSource),()=>new r.WMTSTileSource],render_parents:[t,!0]}))),a.override({level:\"image\"})},\n", - " function _(t,e,r,o,s){o();const c=t(348);class i extends c.MercatorTileSource{constructor(t){super(t)}get_image_url(t,e,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,i]=this.tms_to_wmts(t,e,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",i.toString())}}r.WMTSTileSource=i,i.__name__=\"WMTSTileSource\"},\n", - " function _(t,o,i,b,r){b(),i.root=\"bk-root\",i.tile_attribution=\"bk-tile-attribution\",i.default=\".bk-root .bk-tile-attribution a{color:black;}\"},\n", - " function _(e,r,t,c,o){c();const i=e(348);class l extends i.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=l,l.__name__=\"TMSTileSource\"},\n", - " function _(e,t,u,a,r){a(),r(\"CanvasTexture\",e(357).CanvasTexture),r(\"ImageURLTexture\",e(359).ImageURLTexture),r(\"Texture\",e(358).Texture)},\n", - " function _(t,e,n,c,s){var r;c();const o=t(358),a=t(34);class u extends o.Texture{constructor(t){super(t)}get func(){const t=(0,a.use_strict)(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),c}}n.CanvasTexture=u,r=u,u.__name__=\"CanvasTexture\",r.define((({String:t})=>({code:[t]})))},\n", - " function _(e,t,n,r,o){var i;r();const s=e(53),u=e(20);class c extends s.Model{constructor(e){super(e)}}n.Texture=c,i=c,c.__name__=\"Texture\",i.define((()=>({repetition:[u.TextureRepetition,\"repeat\"]})))},\n", - " function _(e,t,i,r,n){var a;r();const s=e(358),o=e(136);class u extends s.Texture{constructor(e){super(e)}initialize(){super.initialize(),this._loader=new o.ImageLoader(this.url)}get_pattern(e,t,i){const{_loader:r}=this;return this._loader.finished?r.image:r.promise}}i.ImageURLTexture=u,a=u,u.__name__=\"ImageURLTexture\",a.define((({String:e})=>({url:[e]})))},\n", - " function _(o,l,T,e,t){e(),t(\"ActionTool\",o(238).ActionTool),t(\"CustomAction\",o(361).CustomAction),t(\"HelpTool\",o(239).HelpTool),t(\"RedoTool\",o(362).RedoTool),t(\"ResetTool\",o(363).ResetTool),t(\"SaveTool\",o(364).SaveTool),t(\"UndoTool\",o(365).UndoTool),t(\"ZoomInTool\",o(366).ZoomInTool),t(\"ZoomOutTool\",o(369).ZoomOutTool),t(\"ButtonTool\",o(224).ButtonTool),t(\"EditTool\",o(370).EditTool),t(\"BoxEditTool\",o(371).BoxEditTool),t(\"FreehandDrawTool\",o(372).FreehandDrawTool),t(\"PointDrawTool\",o(373).PointDrawTool),t(\"PolyDrawTool\",o(374).PolyDrawTool),t(\"PolyTool\",o(375).PolyTool),t(\"PolyEditTool\",o(376).PolyEditTool),t(\"BoxSelectTool\",o(377).BoxSelectTool),t(\"BoxZoomTool\",o(379).BoxZoomTool),t(\"GestureTool\",o(223).GestureTool),t(\"LassoSelectTool\",o(380).LassoSelectTool),t(\"LineEditTool\",o(382).LineEditTool),t(\"PanTool\",o(384).PanTool),t(\"PolySelectTool\",o(381).PolySelectTool),t(\"RangeTool\",o(385).RangeTool),t(\"SelectTool\",o(378).SelectTool),t(\"TapTool\",o(386).TapTool),t(\"WheelPanTool\",o(387).WheelPanTool),t(\"WheelZoomTool\",o(388).WheelZoomTool),t(\"CrosshairTool\",o(389).CrosshairTool),t(\"CustomJSHover\",o(390).CustomJSHover),t(\"HoverTool\",o(391).HoverTool),t(\"InspectTool\",o(232).InspectTool),t(\"Tool\",o(222).Tool),t(\"ToolProxy\",o(394).ToolProxy),t(\"Toolbar\",o(221).Toolbar),t(\"ToolbarBase\",o(233).ToolbarBase),t(\"ProxyToolbar\",o(395).ProxyToolbar),t(\"ToolbarBox\",o(395).ToolbarBox)},\n", - " function _(t,o,e,s,n){var c;s();const i=t(238);class u extends i.ActionToolButtonView{css_classes(){return super.css_classes().concat(\"bk-toolbar-button-custom-action\")}}e.CustomActionButtonView=u,u.__name__=\"CustomActionButtonView\";class l extends i.ActionToolView{doit(){var t;null===(t=this.model.callback)||void 0===t||t.execute(this.model)}}e.CustomActionView=l,l.__name__=\"CustomActionView\";class a extends i.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=u}}e.CustomAction=a,c=a,a.__name__=\"CustomAction\",c.prototype.default_view=l,c.define((({Any:t,String:o,Nullable:e})=>({callback:[e(t)],icon:[o]}))),c.override({description:\"Perform a Custom Action\"})},\n", - " function _(e,o,t,i,s){var n;i();const l=e(238),_=e(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_redo))}doit(){const e=this.plot_view.state.redo();null!=(null==e?void 0:e.range)&&this.plot_view.trigger_ranges_update_event()}}t.RedoToolView=d,d.__name__=\"RedoToolView\";class a extends l.ActionTool{constructor(e){super(e),this.tool_name=\"Redo\",this.icon=_.tool_icon_redo}}t.RedoTool=a,n=a,a.__name__=\"RedoTool\",n.prototype.default_view=d,n.override({disabled:!0}),n.register_alias(\"redo\",(()=>new a))},\n", - " function _(e,o,t,s,i){var _;s();const n=e(238),l=e(228);class c extends n.ActionToolView{doit(){this.plot_view.reset()}}t.ResetToolView=c,c.__name__=\"ResetToolView\";class r extends n.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=l.tool_icon_reset}}t.ResetTool=r,_=r,r.__name__=\"ResetTool\",_.prototype.default_view=c,_.register_alias(\"reset\",(()=>new r))},\n", - " function _(e,o,t,a,i){var s;a();const c=e(238),n=e(228);class l extends c.ActionToolView{async copy(){const e=await this.plot_view.to_blob(),o=new ClipboardItem({[e.type]:Promise.resolve(e)});await navigator.clipboard.write([o])}async save(e){const o=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(o),t.download=e,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(e=\"save\"){switch(e){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=l,l.__name__=\"SaveToolView\";class r extends c.ActionTool{constructor(e){super(e),this.tool_name=\"Save\",this.icon=n.tool_icon_save}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=r,s=r,r.__name__=\"SaveTool\",s.prototype.default_view=l,s.register_alias(\"save\",(()=>new r))},\n", - " function _(o,e,t,n,i){var s;n();const l=o(238),_=o(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_undo))}doit(){const o=this.plot_view.state.undo();null!=(null==o?void 0:o.range)&&this.plot_view.trigger_ranges_update_event()}}t.UndoToolView=d,d.__name__=\"UndoToolView\";class a extends l.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=_.tool_icon_undo}}t.UndoTool=a,s=a,a.__name__=\"UndoTool\",s.prototype.default_view=d,s.override({disabled:!0}),s.register_alias(\"undo\",(()=>new a))},\n", - " function _(o,n,e,i,s){var t;i();const _=o(367),m=o(228);class a extends _.ZoomBaseToolView{}e.ZoomInToolView=a,a.__name__=\"ZoomInToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=m.tool_icon_zoom_in}}e.ZoomInTool=l,t=l,l.__name__=\"ZoomInTool\",t.prototype.default_view=a,t.register_alias(\"zoom_in\",(()=>new l({dimensions:\"both\"}))),t.register_alias(\"xzoom_in\",(()=>new l({dimensions:\"width\"}))),t.register_alias(\"yzoom_in\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(o,t,e,i,s){var n;i();const a=o(238),_=o(20),l=o(368);class m extends a.ActionToolView{doit(){var o;const t=this.plot_view.frame,e=this.model.dimensions,i=\"width\"==e||\"both\"==e,s=\"height\"==e||\"both\"==e,n=(0,l.scale_range)(t,this.model.sign*this.model.factor,i,s);this.plot_view.state.push(\"zoom_out\",{range:n}),this.plot_view.update_range(n,{scrolling:!0,maintain_focus:this.model.maintain_focus}),null===(o=this.model.document)||void 0===o||o.interactive_start(this.plot_model),this.plot_view.trigger_ranges_update_event()}}e.ZoomBaseToolView=m,m.__name__=\"ZoomBaseToolView\";class h extends a.ActionTool{constructor(o){super(o),this.maintain_focus=!0}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.ZoomBaseTool=h,n=h,h.__name__=\"ZoomBaseTool\",n.define((({Percent:o})=>({factor:[o,.1],dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(n,t,o,r,s){r();const c=n(10);function e(n,t,o){const[r,s]=[n.start,n.end],c=null!=o?o:(s+r)/2;return[r-(r-c)*t,s-(s-c)*t]}function a(n,[t,o]){const r=new Map;for(const[s,c]of n){const[n,e]=c.r_invert(t,o);r.set(s,{start:n,end:e})}return r}o.scale_highlow=e,o.get_info=a,o.scale_range=function(n,t,o=!0,r=!0,s){t=(0,c.clamp)(t,-.9,.9);const l=o?t:0,[u,i]=e(n.bbox.h_range,l,null!=s?s.x:void 0),_=a(n.x_scales,[u,i]),f=r?t:0,[g,x]=e(n.bbox.v_range,f,null!=s?s.y:void 0);return{xrs:_,yrs:a(n.y_scales,[g,x]),factor:t}}},\n", - " function _(o,e,t,i,s){var n;i();const _=o(367),a=o(228);class m extends _.ZoomBaseToolView{}t.ZoomOutToolView=m,m.__name__=\"ZoomOutToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=a.tool_icon_zoom_out}}t.ZoomOutTool=l,n=l,l.__name__=\"ZoomOutTool\",n.prototype.default_view=m,n.define((({Boolean:o})=>({maintain_focus:[o,!0]}))),n.register_alias(\"zoom_out\",(()=>new l({dimensions:\"both\"}))),n.register_alias(\"xzoom_out\",(()=>new l({dimensions:\"width\"}))),n.register_alias(\"yzoom_out\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(e,t,s,o,n){var r;o();const i=e(9),c=e(8),a=e(11),_=e(175),l=e(223);class d extends l.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,a.unreachable)():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,s){if(!this.plot_view.frame.bbox.contains(e,t))return null;const o=this.plot_view.renderer_view(s);if(null==o)return null;return[o.coordinates.x_scale.invert(e),o.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,s=t.selected.indices;s.sort();for(const e of t.columns()){const o=t.get_array(e);for(let e=0;e({custom_icon:[n(t),null],empty_value:[e],renderers:[s(o(_.GlyphRenderer)),[]]})))},\n", - " function _(e,t,s,i,_){var o;i();const n=e(43),a=e(20),d=e(370),l=e(228);class r extends d.EditToolView{_tap(e){null==this._draw_basepoint&&null==this._basepoint&&this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)if(e.keyCode===n.Keys.Backspace)this._delete_selected(t);else if(e.keyCode==n.Keys.Esc){t.data_source.selection_manager.clear()}}_set_extent([e,t],[s,i],_,o=!1){const n=this.model.renderers[0],a=this.plot_view.renderer_view(n);if(null==a)return;const d=n.glyph,l=n.data_source,[r,h]=a.coordinates.x_scale.r_invert(e,t),[p,u]=a.coordinates.y_scale.r_invert(s,i),[c,m]=[(r+h)/2,(p+u)/2],[f,b]=[h-r,u-p],[y,x]=[d.x.field,d.y.field],[w,v]=[d.width.field,d.height.field];if(_)this._pop_glyphs(l,this.model.num_objects),y&&l.get_array(y).push(c),x&&l.get_array(x).push(m),w&&l.get_array(w).push(f),v&&l.get_array(v).push(b),this._pad_empty_columns(l,[y,x,w,v]);else{const e=l.data[y].length-1;y&&(l.data[y][e]=c),x&&(l.data[x][e]=m),w&&(l.data[w][e]=f),v&&(l.data[v][e]=b)}this._emit_cds_changes(l,!0,!1,o)}_update_box(e,t=!1,s=!1){if(null==this._draw_basepoint)return;const i=[e.sx,e.sy],_=this.plot_view.frame,o=this.model.dimensions,n=this.model._get_dim_limits(this._draw_basepoint,i,_,o);if(null!=n){const[e,i]=n;this._set_extent(e,i,t,s)}}_doubletap(e){this.model.active&&(null!=this._draw_basepoint?(this._update_box(e,!1,!0),this._draw_basepoint=null):(this._draw_basepoint=[e.sx,e.sy],this._select_event(e,\"append\",this.model.renderers),this._update_box(e,!0,!1)))}_move(e){this._update_box(e,!1,!1)}_pan_start(e){if(e.shiftKey){if(null!=this._draw_basepoint)return;this._draw_basepoint=[e.sx,e.sy],this._update_box(e,!0,!1)}else{if(null!=this._basepoint)return;this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy]}}_pan(e,t=!1,s=!1){if(e.shiftKey){if(null==this._draw_basepoint)return;this._update_box(e,t,s)}else{if(null==this._basepoint)return;this._drag_points(e,this.model.renderers)}}_pan_end(e){if(this._pan(e,!1,!0),e.shiftKey)this._draw_basepoint=null;else{this._basepoint=null;for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0)}}}s.BoxEditToolView=r,r.__name__=\"BoxEditToolView\";class h extends d.EditTool{constructor(e){super(e),this.tool_name=\"Box Edit Tool\",this.icon=l.tool_icon_box_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=1}}s.BoxEditTool=h,o=h,h.__name__=\"BoxEditTool\",o.prototype.default_view=r,o.define((({Int:e})=>({dimensions:[a.Dimensions,\"both\"],num_objects:[e,0]})))},\n", - " function _(e,t,a,s,r){var _;s();const d=e(43),o=e(8),n=e(370),i=e(228);class l extends n.EditToolView{_draw(e,t,a=!1){if(!this.model.active)return;const s=this.model.renderers[0],r=this._map_drag(e.sx,e.sy,s);if(null==r)return;const[_,d]=r,n=s.data_source,i=s.glyph,[l,h]=[i.xs.field,i.ys.field];if(\"new\"==t)this._pop_glyphs(n,this.model.num_objects),l&&n.get_array(l).push([_]),h&&n.get_array(h).push([d]),this._pad_empty_columns(n,[l,h]);else if(\"add\"==t){if(l){const e=n.data[l].length-1;let t=n.get_array(l)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[l][e]=t),t.push(_)}if(h){const e=n.data[h].length-1;let t=n.get_array(h)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[h][e]=t),t.push(d)}}this._emit_cds_changes(n,!0,!0,a)}_pan_start(e){this._draw(e,\"new\")}_pan(e){this._draw(e,\"add\")}_pan_end(e){this._draw(e,\"add\",!0)}_tap(e){this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===d.Keys.Esc?t.data_source.selection_manager.clear():e.keyCode===d.Keys.Backspace&&this._delete_selected(t)}}a.FreehandDrawToolView=l,l.__name__=\"FreehandDrawToolView\";class h extends n.EditTool{constructor(e){super(e),this.tool_name=\"Freehand Draw Tool\",this.icon=i.tool_icon_freehand_draw,this.event_type=[\"pan\",\"tap\"],this.default_order=3}}a.FreehandDrawTool=h,_=h,h.__name__=\"FreehandDrawTool\",_.prototype.default_view=l,_.define((({Int:e})=>({num_objects:[e,0]}))),_.register_alias(\"freehand_draw\",(()=>new h))},\n", - " function _(e,t,s,o,a){var i;o();const n=e(43),_=e(370),r=e(228);class d extends _.EditToolView{_tap(e){if(this._select_event(e,this._select_mode(e),this.model.renderers).length||!this.model.add)return;const t=this.model.renderers[0],s=this._map_drag(e.sx,e.sy,t);if(null==s)return;const o=t.glyph,a=t.data_source,[i,n]=[o.x.field,o.y.field],[_,r]=s;this._pop_glyphs(a,this.model.num_objects),i&&a.get_array(i).push(_),n&&a.get_array(n).push(r),this._pad_empty_columns(a,[i,n]),a.change.emit(),a.data=a.data,a.properties.data.change.emit()}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===n.Keys.Backspace?this._delete_selected(t):e.keyCode==n.Keys.Esc&&t.data_source.selection_manager.clear()}_pan_start(e){this.model.drag&&(this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy])}_pan(e){this.model.drag&&null!=this._basepoint&&this._drag_points(e,this.model.renderers)}_pan_end(e){if(this.model.drag){this._pan(e);for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0);this._basepoint=null}}}s.PointDrawToolView=d,d.__name__=\"PointDrawToolView\";class l extends _.EditTool{constructor(e){super(e),this.tool_name=\"Point Draw Tool\",this.icon=r.tool_icon_point_draw,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=2}}s.PointDrawTool=l,i=l,l.__name__=\"PointDrawTool\",i.prototype.default_view=d,i.define((({Boolean:e,Int:t})=>({add:[e,!0],drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,t,s,i,a){var r;i();const o=e(43),n=e(8),d=e(375),_=e(228);class h extends d.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._initialized=!1}_tap(e){this._drawing?this._draw(e,\"add\",!0):this._select_event(e,this._select_mode(e),this.model.renderers)}_draw(e,t,s=!1){const i=this.model.renderers[0],a=this._map_drag(e.sx,e.sy,i);if(this._initialized||this.activate(),null==a)return;const[r,o]=this._snap_to_vertex(e,...a),d=i.data_source,_=i.glyph,[h,l]=[_.xs.field,_.ys.field];if(\"new\"==t)this._pop_glyphs(d,this.model.num_objects),h&&d.get_array(h).push([r,r]),l&&d.get_array(l).push([o,o]),this._pad_empty_columns(d,[h,l]);else if(\"edit\"==t){if(h){const e=d.data[h][d.data[h].length-1];e[e.length-1]=r}if(l){const e=d.data[l][d.data[l].length-1];e[e.length-1]=o}}else if(\"add\"==t){if(h){const e=d.data[h].length-1;let t=d.get_array(h)[e];const s=t[t.length-1];t[t.length-1]=r,(0,n.isArray)(t)||(t=Array.from(t),d.data[h][e]=t),t.push(s)}if(l){const e=d.data[l].length-1;let t=d.get_array(l)[e];const s=t[t.length-1];t[t.length-1]=o,(0,n.isArray)(t)||(t=Array.from(t),d.data[l][e]=t),t.push(s)}}this._emit_cds_changes(d,!0,!1,s)}_show_vertices(){if(!this.model.active)return;const e=[],t=[];for(let s=0;sthis._show_vertices()))}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=h,h.__name__=\"PolyDrawToolView\";class l extends d.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}}s.PolyDrawTool=l,r=l,l.__name__=\"PolyDrawTool\",r.prototype.default_view=h,r.define((({Boolean:e,Int:t})=>({drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,r,t,s,o){var _;s();const d=e(8),i=e(370);class l extends i.EditToolView{_set_vertices(e,r){const t=this.model.vertex_renderer.glyph,s=this.model.vertex_renderer.data_source,[o,_]=[t.x.field,t.y.field];o&&((0,d.isArray)(e)?s.data[o]=e:t.x={value:e}),_&&((0,d.isArray)(r)?s.data[_]=r:t.y={value:r}),this._emit_cds_changes(s,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,r,t){if(this.model.vertex_renderer){const s=this._select_event(e,\"replace\",[this.model.vertex_renderer]),o=this.model.vertex_renderer.data_source,_=this.model.vertex_renderer.glyph,[d,i]=[_.x.field,_.y.field];if(s.length){const e=o.selected.indices[0];d&&(r=o.data[d][e]),i&&(t=o.data[i][e]),o.selection_manager.clear()}}return[r,t]}}t.PolyToolView=l,l.__name__=\"PolyToolView\";class n extends i.EditTool{constructor(e){super(e)}}t.PolyTool=n,_=n,n.__name__=\"PolyTool\",_.define((({AnyRef:e})=>({vertex_renderer:[e()]})))},\n", - " function _(e,t,s,r,i){var _;r();const d=e(43),n=e(8),l=e(375),a=e(228);class c extends l.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._cur_index=null}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this.model.renderers[0],s=()=>this._update_vertices(t),r=null==t?void 0:t.data_source,i=this._select_event(e,\"replace\",this.model.renderers);if(!i.length)return this._set_vertices([],[]),this._selected_renderer=null,this._drawing=!1,this._cur_index=null,void(null!=r&&r.disconnect(r.properties.data.change,s));null!=r&&r.connect(r.properties.data.change,s),this._cur_index=i[0].data_source.selected.indices[0],this._update_vertices(i[0])}_update_vertices(e){const t=e.glyph,s=e.data_source,r=this._cur_index,[i,_]=[t.xs.field,t.ys.field];if(this._drawing)return;if(null==r&&(i||_))return;let d,l;i&&null!=r?(d=s.data[i][r],(0,n.isArray)(d)||(s.data[i][r]=d=Array.from(d))):d=t.xs.value,_&&null!=r?(l=s.data[_][r],(0,n.isArray)(l)||(s.data[_][r]=l=Array.from(l))):l=t.ys.value,this._selected_renderer=e,this._set_vertices(d,l)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===d.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==d.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=c,c.__name__=\"PolyEditToolView\";class o extends l.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=a.tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}}s.PolyEditTool=o,_=o,o.__name__=\"PolyEditTool\",_.prototype.default_view=c},\n", - " function _(e,t,o,s,i){var l;s();const n=e(378),_=e(116),c=e(20),r=e(228);class a extends n.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.state.push(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const n={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(n,i,l)}}o.BoxSelectToolView=a,a.__name__=\"BoxSelectToolView\";const h=()=>new _.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends n.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=r.tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}o.BoxSelectTool=m,l=m,m.__name__=\"BoxSelectTool\",l.prototype.default_view=a,l.define((({Boolean:e,Ref:t})=>({dimensions:[c.Dimensions,\"both\"],select_every_mousemove:[e,!1],overlay:[t(_.BoxAnnotation),h],origin:[c.BoxOrigin,\"corner\"]}))),l.register_alias(\"box_select\",(()=>new m)),l.register_alias(\"xbox_select\",(()=>new m({dimensions:\"width\"}))),l.register_alias(\"ybox_select\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(e,t,s,n,r){var o;n();const c=e(223),i=e(175),a=e(339),l=e(176),d=e(66),_=e(20),h=e(43),p=e(251),u=e(15),m=e(11);class v extends c.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect((()=>this._clear()))}get computed_renderers(){const{renderers:e,names:t}=this.model,s=this.plot_model.data_renderers;return(0,d.compute_renderers)(e,s,t)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof i.GlyphRenderer)n=s.data_source;else{if(!(s instanceof a.GraphRenderer))continue;n=s.node_renderer.data_source}const r=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...r,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,m.unreachable)():this.model.mode}_keyup(e){e.keyCode==h.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();const e=this.computed_renderers.map((e=>this.plot_view.renderer_view(e)));this.plot_view.request_paint(e)}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,r]of n){const n=r[0].get_selection_manager(),o=[];for(const e of r){const t=this.plot_view.renderer_view(e);null!=t&&o.push(t)}n.select(o,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let r;switch(e.type){case\"point\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:o,sy0:c,sy1:i}=e,[a,l]=s.r_invert(t,o),[d,_]=n.r_invert(c,i);r=Object.assign(Object.assign({},e),{x0:a,y0:d,x1:l,y1:_});break}case\"poly\":{const{sx:t,sy:o}=e,c=s.v_invert(t),i=n.v_invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new p.SelectionGeometry(r,t))}}s.SelectToolView=v,v.__name__=\"SelectToolView\";class b extends c.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new u.Signal0(this,\"clear\")}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=b,o=b,b.__name__=\"SelectTool\",o.define((({String:e,Array:t,Ref:s,Or:n,Auto:r})=>({renderers:[n(t(s(l.DataRenderer)),r),\"auto\"],names:[t(e),[]],mode:[_.SelectionMode,\"replace\"]})))},\n", - " function _(t,o,e,s,i){var n;s();const _=t(223),a=t(116),l=t(20),r=t(228);class h extends _.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew a.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=r.tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.BoxZoomTool=m,n=m,m.__name__=\"BoxZoomTool\",n.prototype.default_view=h,n.define((({Boolean:t,Ref:o})=>({dimensions:[l.Dimensions,\"both\"],overlay:[o(a.BoxAnnotation),c],match_aspect:[t,!1],origin:[l.BoxOrigin,\"corner\"]}))),n.register_alias(\"box_zoom\",(()=>new m({dimensions:\"both\"}))),n.register_alias(\"xbox_zoom\",(()=>new m({dimensions:\"width\"}))),n.register_alias(\"ybox_zoom\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(s,e,t,o,_){var l;o();const i=s(378),a=s(217),c=s(381),n=s(43),h=s(228);class r extends i.SelectToolView{constructor(){super(...arguments),this.sxs=[],this.sys=[]}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_overlay()}_keyup(s){s.keyCode==n.Keys.Enter&&this._clear_overlay()}_pan_start(s){this.sxs=[],this.sys=[];const{sx:e,sy:t}=s;this._append_overlay(e,t)}_pan(s){const[e,t]=this.plot_view.frame.bbox.clip(s.sx,s.sy);this._append_overlay(e,t),this.model.select_every_mousemove&&this._do_select(this.sxs,this.sys,!1,this._select_mode(s))}_pan_end(s){const{sxs:e,sys:t}=this;this._clear_overlay(),this._do_select(e,t,!0,this._select_mode(s)),this.plot_view.state.push(\"lasso_select\",{selection:this.plot_view.get_selection()})}_append_overlay(s,e){const{sxs:t,sys:o}=this;t.push(s),o.push(e),this.model.overlay.update({xs:t,ys:o})}_clear_overlay(){this.sxs=[],this.sys=[],this.model.overlay.update({xs:this.sxs,ys:this.sys})}_do_select(s,e,t,o){const _={type:\"poly\",sx:s,sy:e};this._select(_,t,o)}}t.LassoSelectToolView=r,r.__name__=\"LassoSelectToolView\";class y extends i.SelectTool{constructor(s){super(s),this.tool_name=\"Lasso Select\",this.icon=h.tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}}t.LassoSelectTool=y,l=y,y.__name__=\"LassoSelectTool\",l.prototype.default_view=r,l.define((({Boolean:s,Ref:e})=>({select_every_mousemove:[s,!0],overlay:[e(a.PolyAnnotation),c.DEFAULT_POLY_OVERLAY]}))),l.register_alias(\"lasso_select\",(()=>new y))},\n", - " function _(e,t,s,l,o){var i;l();const a=e(378),_=e(217),c=e(43),n=e(9),h=e(228);class y extends a.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==c.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.state.push(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:(0,n.copy)(this.data.sx),ys:(0,n.copy)(this.data.sy)}))}_do_select(e,t,s,l){const o={type:\"poly\",sx:e,sy:t};this._select(o,s,l)}}s.PolySelectToolView=y,y.__name__=\"PolySelectToolView\";s.DEFAULT_POLY_OVERLAY=()=>new _.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class d extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=h.tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}}s.PolySelectTool=d,i=d,d.__name__=\"PolySelectTool\",i.prototype.default_view=y,i.define((({Ref:e})=>({overlay:[e(_.PolyAnnotation),s.DEFAULT_POLY_OVERLAY]}))),i.register_alias(\"poly_select\",(()=>new d))},\n", - " function _(e,t,s,i,r){var n;i();const _=e(20),d=e(383),o=e(228);class l extends d.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const s of t){1==this._select_event(e,\"replace\",[s]).length&&(this._selected_renderer=s)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[s,i]=[t.x.field,t.y.field],r=e.get_array(s),n=e.get_array(i);this._set_intersection(r,n)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const s=this._select_mode(e);if(0==this._select_event(e,s,[t]).length)return}const s=this._select_mode(e);this._select_event(e,s,[t]),this._select_event(e,s,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,i]=[e.x.field,e.y.field];if(s&&i){const e=t.data[s],r=t.data[i];this._selected_renderer.data_source.data[s]=e,this._selected_renderer.data_source.data[i]=r}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}s.LineEditToolView=l,l.__name__=\"LineEditToolView\";class h extends d.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=o.tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}s.LineEditTool=h,n=h,h.__name__=\"LineEditTool\",n.prototype.default_view=l,n.define((()=>({dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(e,i,n,t,s){var o;t();const r=e(8),_=e(370);class d extends _.EditToolView{_set_intersection(e,i){const n=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,o]=[n.x.field,n.y.field];s&&((0,r.isArray)(e)?t.data[s]=e:n.x={value:e}),o&&((0,r.isArray)(i)?t.data[o]=i:n.y={value:i}),this._emit_cds_changes(t,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}n.LineToolView=d,d.__name__=\"LineToolView\";class a extends _.EditTool{constructor(e){super(e)}}n.LineTool=a,o=a,a.__name__=\"LineTool\",o.define((({AnyRef:e})=>({intersection_renderer:[e()]})))},\n", - " function _(t,s,n,e,i){e();const o=t(1);var a;const _=t(223),l=t(20),r=(0,o.__importStar)(t(228));function h(t,s,n){const e=new Map;for(const[i,o]of t){const[t,a]=o.r_invert(s,n);e.set(i,{start:t,end:a})}return e}n.update_ranges=h;class d extends _.GestureToolView{_pan_start(t){var s;this.last_dx=0,this.last_dy=0;const{sx:n,sy:e}=t,i=this.plot_view.frame.bbox;if(!i.contains(n,e)){const t=i.h_range,s=i.v_range;(nt.end)&&(this.v_axis_only=!0),(es.end)&&(this.h_axis_only=!0)}null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan(t){var s;this._update(t.deltaX,t.deltaY),null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.state.push(\"pan\",{range:this.pan_info}),this.plot_view.trigger_ranges_update_event()}_update(t,s){const n=this.plot_view.frame,e=t-this.last_dx,i=s-this.last_dy,o=n.bbox.h_range,a=o.start-e,_=o.end-e,l=n.bbox.v_range,r=l.start-i,d=l.end-i,p=this.model.dimensions;let c,u,m,v,x,g;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,u=o.end,m=0):(c=a,u=_,m=-e),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(v=l.start,x=l.end,g=0):(v=r,x=d,g=-i),this.last_dx=t,this.last_dy=s;const{x_scales:w,y_scales:y}=n,f=h(w,c,u),b=h(y,v,x);this.pan_info={xrs:f,yrs:b,sdx:m,sdy:g},this.plot_view.update_range(this.pan_info,{panning:!0})}}n.PanToolView=d,d.__name__=\"PanToolView\";class p extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}n.PanTool=p,a=p,p.__name__=\"PanTool\",a.prototype.default_view=d,a.define((()=>({dimensions:[l.Dimensions,\"both\",{on_update(t,s){switch(t){case\"both\":s.icon=r.tool_icon_pan;break;case\"width\":s.icon=r.tool_icon_xpan;break;case\"height\":s.icon=r.tool_icon_ypan}}}]}))),a.register_alias(\"pan\",(()=>new p({dimensions:\"both\"}))),a.register_alias(\"xpan\",(()=>new p({dimensions:\"width\"}))),a.register_alias(\"ypan\",(()=>new p({dimensions:\"height\"})))},\n", - " function _(e,t,i,s,n){var l;s();const a=e(116),r=e(58),o=e(19),_=e(223),h=e(228);function d(e){switch(e){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return e}}function u(e,t,i,s){if(null==t)return!1;const n=i.compute(t);return Math.abs(e-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const e=s.invert(t);(en.top)&&(l=!1)}return l}function g(e,t,i){let s=0;return e>=i.start&&e<=i.end&&(s+=1),t>=i.start&&t<=i.end&&(s+=1),s}function y(e,t,i,s){const n=t.compute(e),l=t.invert(n+i);return l>=s.start&&l<=s.end?l:e}function f(e,t,i){return e>t.start?(t.end=e,i):(t.end=t.start,t.start=e,d(i))}function v(e,t,i){return e=o&&(e.start=a,e.end=r)}i.flip_side=d,i.is_near=u,i.is_inside=c,i.sides_inside=g,i.compute_value=y,i.update_range_end_side=f,i.update_range_start_side=v,i.update_range=m;class p extends _.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,(()=>this.model.update_overlay_from_ranges())),null!=this.model.y_range&&this.connect(this.model.y_range.change,(()=>this.model.update_overlay_from_ranges()))}_pan_start(e){this.last_dx=0,this.last_dy=0;const t=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,n=s.x_scale,l=s.y_scale,r=this.model.overlay,{left:o,right:_,top:h,bottom:d}=r,g=this.model.overlay.line_width+a.EDGE_TOLERANCE;null!=t&&this.model.x_interaction&&(u(e.sx,o,n,g)?this.side=1:u(e.sx,_,n,g)?this.side=2:c(e.sx,e.sy,n,l,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&u(e.sy,d,l,g)&&(this.side=4),0==this.side&&u(e.sy,h,l,g)?this.side=5:c(e.sx,e.sy,n,l,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(e){const t=this.plot_view.frame,i=e.deltaX-this.last_dx,s=e.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=t.x_scale,r=t.y_scale;if(null!=n)if(3==this.side||7==this.side)m(n,a,i,t.x_range);else if(1==this.side){const e=y(n.start,a,i,t.x_range);this.side=v(e,n,this.side)}else if(2==this.side){const e=y(n.end,a,i,t.x_range);this.side=f(e,n,this.side)}if(null!=l)if(6==this.side||7==this.side)m(l,r,s,t.y_range);else if(4==this.side){const e=y(l.start,r,s,t.y_range);this.side=v(e,l,this.side)}else if(5==this.side){const e=y(l.end,r,s,t.y_range);this.side=f(e,l,this.side)}this.last_dx=e.deltaX,this.last_dy=e.deltaY}_pan_end(e){this.side=0,this.plot_view.trigger_ranges_update_event()}}i.RangeToolView=p,p.__name__=\"RangeToolView\";const x=()=>new a.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class w extends _.GestureTool{constructor(e){super(e),this.tool_name=\"Range Tool\",this.icon=h.tool_icon_range,this.event_type=\"pan\",this.default_order=1}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,o.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=w,l=w,w.__name__=\"RangeTool\",l.prototype.default_view=p,l.define((({Boolean:e,Ref:t,Nullable:i})=>({x_range:[i(t(r.Range1d)),null],x_interaction:[e,!0],y_range:[i(t(r.Range1d)),null],y_interaction:[e,!0],overlay:[t(a.BoxAnnotation),x]})))},\n", - " function _(e,t,s,o,i){var l;o();const a=e(378),n=e(20),c=e(228);class _ extends a.SelectToolView{_tap(e){\"tap\"==this.model.gesture&&this._handle_tap(e)}_doubletap(e){\"doubletap\"==this.model.gesture&&this._handle_tap(e)}_handle_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const{callback:o}=this.model;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,l]of i){const i=l[0].get_selection_manager(),a=l.map((e=>this.plot_view.renderer_view(e))).filter((e=>null!=e));if(i.select(a,e,t,s)&&null!=o){const t=a[0].coordinates.x_scale.invert(e.sx),s=a[0].coordinates.y_scale.invert(e.sy),l={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,l)}}this._emit_selection_event(e),this.plot_view.state.push(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_view(t);if(null==s)continue;const i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),l=s.coordinates.y_scale.invert(e.sy),a={geometries:Object.assign(Object.assign({},e),{x:t,y:l}),source:i.source};o.execute(this.model,a)}}}}s.TapToolView=_,_.__name__=\"TapToolView\";class r extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=c.tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}}s.TapTool=r,l=r,r.__name__=\"TapTool\",l.prototype.default_view=_,l.define((({Any:e,Enum:t,Nullable:s})=>({behavior:[n.TapBehavior,\"select\"],gesture:[t(\"tap\",\"doubletap\"),\"tap\"],callback:[s(e)]}))),l.register_alias(\"click\",(()=>new r({behavior:\"inspect\"}))),l.register_alias(\"tap\",(()=>new r)),l.register_alias(\"doubletap\",(()=>new r({gesture:\"doubletap\"})))},\n", - " function _(e,t,s,n,i){var a;n();const o=e(223),l=e(20),_=e(228),r=e(384);class h extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){var t;const{frame:s}=this.plot_view,n=s.bbox.h_range,i=s.bbox.v_range,[a,o]=[n.start,n.end],[l,_]=[i.start,i.end];let h,d,p,c;switch(this.model.dimension){case\"height\":{const t=Math.abs(_-l);h=a,d=o,p=l-t*e,c=_-t*e;break}case\"width\":{const t=Math.abs(o-a);h=a-t*e,d=o-t*e,p=l,c=_;break}}const{x_scales:g,y_scales:u}=s,w={xrs:(0,r.update_ranges)(g,h,d),yrs:(0,r.update_ranges)(u,p,c),factor:e};this.plot_view.state.push(\"wheel_pan\",{range:w}),this.plot_view.update_range(w,{scrolling:!0}),null===(t=this.model.document)||void 0===t||t.interactive_start(this.plot_model,(()=>this.plot_view.trigger_ranges_update_event()))}}s.WheelPanToolView=h,h.__name__=\"WheelPanToolView\";class d extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=_.tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}get tooltip(){return this._get_dim_tooltip(this.dimension)}}s.WheelPanTool=d,a=d,d.__name__=\"WheelPanTool\",a.prototype.default_view=h,a.define((()=>({dimension:[l.Dimension,\"width\"]}))),a.internal((({Number:e})=>({speed:[e,.001]}))),a.register_alias(\"xwheel_pan\",(()=>new d({dimension:\"width\"}))),a.register_alias(\"ywheel_pan\",(()=>new d({dimension:\"height\"})))},\n", - " function _(e,o,t,s,i){var n;s();const l=e(223),_=e(368),h=e(20),a=e(27),r=e(228);class m extends l.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:n}=e;let l;l=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:l,ctrlKey:i,shiftKey:n})}_scroll(e){var o;const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,{sx:n,sy:l}=e,h=this.model.dimensions,a=(\"width\"==h||\"both\"==h)&&s.startthis.plot_view.trigger_ranges_update_event()))}}t.WheelZoomToolView=m,m.__name__=\"WheelZoomToolView\";class d extends l.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Zoom\",this.icon=r.tool_icon_wheel_zoom,this.event_type=a.is_mobile?\"pinch\":\"scroll\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}t.WheelZoomTool=d,n=d,d.__name__=\"WheelZoomTool\",n.prototype.default_view=m,n.define((({Boolean:e,Number:o})=>({dimensions:[h.Dimensions,\"both\"],maintain_focus:[e,!0],zoom_on_axis:[e,!0],speed:[o,1/600]}))),n.register_alias(\"wheel_zoom\",(()=>new d({dimensions:\"both\"}))),n.register_alias(\"xwheel_zoom\",(()=>new d({dimensions:\"width\"}))),n.register_alias(\"ywheel_zoom\",(()=>new d({dimensions:\"height\"})))},\n", - " function _(i,e,s,t,o){var n;t();const l=i(232),a=i(219),h=i(20),r=i(13),_=i(228);class c extends l.InspectToolView{_move(i){if(!this.model.active)return;const{sx:e,sy:s}=i;this.plot_view.frame.bbox.contains(e,s)?this._update_spans(e,s):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,e){const s=this.model.dimensions;\"width\"!=s&&\"both\"!=s||(this.model.spans.width.location=e),\"height\"!=s&&\"both\"!=s||(this.model.spans.height.location=i)}}s.CrosshairToolView=c,c.__name__=\"CrosshairToolView\";class p extends l.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=_.tool_icon_crosshair}get tooltip(){return this._get_dim_tooltip(this.dimensions)}get synthetic_renderers(){return(0,r.values)(this.spans)}}s.CrosshairTool=p,n=p,p.__name__=\"CrosshairTool\",(()=>{function i(i,e){return new a.Span({for_hover:!0,dimension:e,location_units:\"screen\",level:\"overlay\",line_color:i.line_color,line_width:i.line_width,line_alpha:i.line_alpha})}n.prototype.default_view=c,n.define((({Alpha:i,Number:e,Color:s})=>({dimensions:[h.Dimensions,\"both\"],line_color:[s,\"black\"],line_width:[e,1],line_alpha:[i,1]}))),n.internal((({Struct:e,Ref:s})=>({spans:[e({width:s(a.Span),height:s(a.Span)}),e=>({width:i(e,\"width\"),height:i(e,\"height\")})]}))),n.register_alias(\"crosshair\",(()=>new p))})()},\n", - " function _(e,s,t,r,n){var o;r();const a=e(53),u=e(13),c=e(34);class i extends a.Model{constructor(e){super(e)}get values(){return(0,u.values)(this.args)}_make_code(e,s,t,r){return new Function(...(0,u.keys)(this.args),e,s,t,(0,c.use_strict)(r))}format(e,s,t){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,e,s,t)}}t.CustomJSHover=i,o=i,i.__name__=\"CustomJSHover\",o.define((({Unknown:e,String:s,Dict:t})=>({args:[t(e),{}],code:[s,\"\"]})))},\n", - " function _(e,t,n,s,i){s();const o=e(1);var r;const l=e(232),a=e(390),c=e(241),_=e(175),d=e(339),p=e(176),h=e(177),u=e(283),m=e(186),y=e(187),f=e(189),x=(0,o.__importStar)(e(185)),v=e(152),w=e(43),g=e(22),b=e(13),k=e(234),C=e(8),S=e(113),T=e(20),$=e(228),R=e(15),A=e(66),M=(0,o.__importStar)(e(242)),V=e(392);function G(e,t,n,s,i,o){const r={x:i[e],y:o[e]},l={x:i[e+1],y:o[e+1]};let a,c;if(\"span\"==t.type)\"h\"==t.direction?(a=Math.abs(r.x-n),c=Math.abs(l.x-n)):(a=Math.abs(r.y-s),c=Math.abs(l.y-s));else{const e={x:n,y:s};a=x.dist_2_pts(r,e),c=x.dist_2_pts(l,e)}return adelete this._template_el)),this.on_change([e,t,n],(async()=>await this._update_ttmodels()))}async _update_ttmodels(){const{_ttmodels:e,computed_renderers:t}=this;e.clear();const{tooltips:n}=this.model;if(null!=n)for(const t of this.computed_renderers){const s=new c.Tooltip({custom:(0,C.isString)(n)||(0,C.isFunction)(n),attachment:this.model.attachment,show_arrow:this.model.show_arrow});t instanceof _.GlyphRenderer?e.set(t,s):t instanceof d.GraphRenderer&&(e.set(t.node_renderer,s),e.set(t.edge_renderer,s))}const s=await(0,S.build_views)(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of s)e.render();const i=[...function*(){for(const e of t)e instanceof _.GlyphRenderer?yield e:e instanceof d.GraphRenderer&&(yield e.node_renderer,yield e.edge_renderer)}()],o=this._slots.get(this._update);if(null!=o){const e=new Set(i.map((e=>e.data_source)));R.Signal.disconnect_receiver(this,o,e)}for(const e of i)this.connect(e.data_source.inspect,this._update)}get computed_renderers(){const{renderers:e,names:t}=this.model,n=this.plot_model.data_renderers;return(0,A.compute_renderers)(e,n,t)}get ttmodels(){return this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:n}=e;this.plot_view.frame.bbox.contains(t,n)?this._inspect(t,n):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let n;if(\"mouse\"==this.model.mode)n={type:\"point\",sx:e,sy:t};else{n={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){const t=e.get_selection_manager(),s=this.plot_view.renderer_view(e);null!=s&&t.inspect(s,n)}this._emit_callback(n)}_update([e,{geometry:t}]){var n,s;if(!this.model.active)return;if(\"point\"!=t.type&&\"span\"!=t.type)return;if(!(e instanceof _.GlyphRenderer))return;if(\"ignore\"==this.model.muted_policy&&e.muted)return;const i=this.ttmodels.get(e);if(null==i)return;const o=e.get_selection_manager(),r=o.inspectors.get(e),l=e.view.convert_selection_to_subset(r);if(r.is_empty()&&null==r.view)return void i.clear();const a=o.source,c=this.plot_view.renderer_view(e);if(null==c)return;const{sx:d,sy:p}=t,x=c.coordinates.x_scale,v=c.coordinates.y_scale,g=x.invert(d),k=v.invert(p),{glyph:C}=c,S=[];if(C instanceof m.PatchView){const[t,n]=[d,p],s={x:g,y:k,sx:d,sy:p,rx:t,ry:n,name:e.name};S.push([t,n,this._render_tooltips(a,-1,s)])}if(C instanceof y.HAreaView)for(const t of l.line_indices){const n=C._x1,s=C._x2,i=C._y,[o,r]=[d,p],c={index:t,x:g,y:k,sx:d,sy:p,data_x1:n,data_x2:s,data_y:i,rx:o,ry:r,indices:l.line_indices,name:e.name};S.push([o,r,this._render_tooltips(a,t,c)])}if(C instanceof f.VAreaView)for(const t of l.line_indices){const n=C._x,s=C._y1,i=C._y2,[o,r]=[d,p],c={index:t,x:g,y:k,sx:d,sy:p,data_x:n,data_y1:s,data_y2:i,rx:o,ry:r,indices:l.line_indices,name:e.name};S.push([o,r,this._render_tooltips(a,t,c)])}if(C instanceof h.LineView)for(const n of l.line_indices){let s,i,o=C._x[n+1],r=C._y[n+1],c=n;switch(this.model.line_policy){case\"interp\":[o,r]=C.get_interpolation_hit(n,t),s=x.compute(o),i=v.compute(r);break;case\"prev\":[[s,i],c]=H(C.sx,C.sy,n);break;case\"next\":[[s,i],c]=H(C.sx,C.sy,n+1);break;case\"nearest\":[[s,i],c]=G(n,t,d,p,C.sx,C.sy),o=C._x[c],r=C._y[c];break;default:[s,i]=[d,p]}const _={index:c,x:g,y:k,sx:d,sy:p,data_x:o,data_y:r,rx:s,ry:i,indices:l.line_indices,name:e.name};S.push([s,i,this._render_tooltips(a,c,_)])}for(const t of r.image_indices){const n={index:t.index,x:g,y:k,sx:d,sy:p,name:e.name},s=this._render_tooltips(a,t,n);S.push([d,p,s])}for(const i of l.indices)if(C instanceof u.MultiLineView&&!(0,b.isEmpty)(l.multiline_indices))for(const n of l.multiline_indices[i.toString()]){let s,o,r,c=C._xs.get(i)[n],h=C._ys.get(i)[n],u=n;switch(this.model.line_policy){case\"interp\":[c,h]=C.get_interpolation_hit(i,n,t),s=x.compute(c),o=v.compute(h);break;case\"prev\":[[s,o],u]=H(C.sxs.get(i),C.sys.get(i),n);break;case\"next\":[[s,o],u]=H(C.sxs.get(i),C.sys.get(i),n+1);break;case\"nearest\":[[s,o],u]=G(n,t,d,p,C.sxs.get(i),C.sys.get(i)),c=C._xs.get(i)[u],h=C._ys.get(i)[u];break;default:throw new Error(\"shouldn't have happened\")}r=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([i])[0]:i;const m={index:r,x:g,y:k,sx:d,sy:p,data_x:c,data_y:h,segment_index:u,indices:l.multiline_indices,name:e.name};S.push([s,o,this._render_tooltips(a,r,m)])}else{const t=null===(n=C._x)||void 0===n?void 0:n[i],o=null===(s=C._y)||void 0===s?void 0:s[i];let r,c,h;if(\"snap_to_data\"==this.model.point_policy){let e=C.get_anchor_point(this.model.anchor,i,[d,p]);if(null==e&&(e=C.get_anchor_point(\"center\",i,[d,p]),null==e))continue;r=e.x,c=e.y}else[r,c]=[d,p];h=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([i])[0]:i;const u={index:h,x:g,y:k,sx:d,sy:p,data_x:t,data_y:o,indices:l.indices,name:e.name};S.push([r,c,this._render_tooltips(a,h,u)])}if(0==S.length)i.clear();else{const{content:e}=i;(0,w.empty)(i.content);for(const[,,t]of S)null!=t&&e.appendChild(t);const[t,n]=S[S.length-1];i.setv({position:[t,n]},{check_eq:!1})}}_emit_callback(e){const{callback:t}=this.model;if(null!=t)for(const n of this.computed_renderers){if(!(n instanceof _.GlyphRenderer))continue;const s=this.plot_view.renderer_view(n);if(null==s)continue;const{x_scale:i,y_scale:o}=s.coordinates,r=i.invert(e.sx),l=o.invert(e.sy),a=n.data_source.inspected;t.execute(this.model,{geometry:Object.assign({x:r,y:l},e),renderer:n,index:a})}}_create_template(e){const t=(0,w.div)({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[n]of e){const e=(0,w.div)({style:{display:\"table-row\"}});t.appendChild(e);const s=(0,w.div)({style:{display:\"table-cell\"},class:M.tooltip_row_label},0!=n.length?`${n}: `:\"\");e.appendChild(s);const i=(0,w.span)();i.dataset.value=\"\";const o=(0,w.span)({class:M.tooltip_color_block},\" \");o.dataset.swatch=\"\",(0,w.undisplay)(o);const r=(0,w.div)({style:{display:\"table-cell\"},class:M.tooltip_row_value},i,o);e.appendChild(r)}return t}_render_template(e,t,n,s,i){const o=e.cloneNode(!0),r=o.querySelectorAll(\"[data-value]\"),l=o.querySelectorAll(\"[data-swatch]\"),a=/\\$color(\\[.*\\])?:(\\w*)/,c=/\\$swatch:(\\w*)/;for(const[[,e],o]of(0,k.enumerate)(t)){const t=e.match(c),_=e.match(a);if(null!=t||null!=_){if(null!=t){const[,e]=t,i=n.get_column(e);if(null==i)r[o].textContent=`${e} unknown`;else{const e=(0,C.isNumber)(s)?i[s]:null;null!=e&&(l[o].style.backgroundColor=(0,g.color2css)(e),(0,w.display)(l[o]))}}if(null!=_){const[,e=\"\",t]=_,i=n.get_column(t);if(null==i){r[o].textContent=`${t} unknown`;continue}const a=e.indexOf(\"hex\")>=0,c=e.indexOf(\"swatch\")>=0,d=(0,C.isNumber)(s)?i[s]:null;if(null==d){r[o].textContent=\"(null)\";continue}r[o].textContent=a?(0,g.color2hex)(d):(0,g.color2css)(d),c&&(l[o].style.backgroundColor=(0,g.color2css)(d),(0,w.display)(l[o]))}}else{const t=(0,v.replace_placeholders)(e.replace(\"$~\",\"$data_\"),n,s,this.model.formatters,i);if((0,C.isString)(t))r[o].textContent=t;else for(const e of t)r[o].appendChild(e)}}return o}_render_tooltips(e,t,n){var s;const{tooltips:i}=this.model;if((0,C.isString)(i)){const s=(0,v.replace_placeholders)({html:i},e,t,this.model.formatters,n);return(0,w.div)(s)}if((0,C.isFunction)(i))return i(e,n);if(i instanceof V.Template)return this._template_view.update(e,t,n),this._template_view.el;if(null!=i){const o=null!==(s=this._template_el)&&void 0!==s?s:this._template_el=this._create_template(i);return this._render_template(o,i,e,t,n)}return null}}n.HoverToolView=z,z.__name__=\"HoverToolView\";class P extends l.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=$.tool_icon_hover}}n.HoverTool=P,r=P,P.__name__=\"HoverTool\",r.prototype.default_view=z,r.define((({Any:e,Boolean:t,String:n,Array:s,Tuple:i,Dict:o,Or:r,Ref:l,Function:c,Auto:_,Nullable:d})=>({tooltips:[d(r(l(V.Template),n,s(i(n,n)),c())),[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[o(r(l(a.CustomJSHover),v.FormatterType)),{}],renderers:[r(s(l(p.DataRenderer)),_),\"auto\"],names:[s(n),[]],mode:[T.HoverMode,\"mouse\"],muted_policy:[T.MutedPolicy,\"show\"],point_policy:[T.PointPolicy,\"snap_to_data\"],line_policy:[T.LinePolicy,\"nearest\"],show_arrow:[t,!0],anchor:[T.Anchor,\"center\"],attachment:[T.TooltipAttachment,\"horizontal\"],callback:[d(e)]}))),r.register_alias(\"hover\",(()=>new P))},\n", - " function _(e,t,s,n,a){n();const l=e(1);var i,_,o,r,c,d,p,u,m,w,f,h,x;const v=e(53),y=e(309),V=e(393);a(\"Styles\",V.Styles);const g=e(43),T=e(42),b=e(226),R=e(113),D=e(8),M=e(13),S=(0,l.__importStar)(e(242)),O=e(152);class C extends b.DOMView{}s.DOMNodeView=C,C.__name__=\"DOMNodeView\";class z extends v.Model{constructor(e){super(e)}}s.DOMNode=z,z.__name__=\"DOMNode\",z.__module__=\"bokeh.models.dom\";class P extends C{render(){super.render(),this.el.textContent=this.model.content}_createElement(){return document.createTextNode(\"\")}}s.TextView=P,P.__name__=\"TextView\";class A extends z{constructor(e){super(e)}}s.Text=A,i=A,A.__name__=\"Text\",i.prototype.default_view=P,i.define((({String:e})=>({content:[e,\"\"]})));class N extends C{}s.PlaceholderView=N,N.__name__=\"PlaceholderView\",N.tag_name=\"span\";class E extends z{constructor(e){super(e)}}s.Placeholder=E,_=E,E.__name__=\"Placeholder\",_.define((({})=>({})));class G extends N{update(e,t,s){this.el.textContent=t.toString()}}s.IndexView=G,G.__name__=\"IndexView\";class I extends E{constructor(e){super(e)}}s.Index=I,o=I,I.__name__=\"Index\",o.prototype.default_view=G,o.define((({})=>({})));class k extends N{update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ValueRefView=k,k.__name__=\"ValueRefView\";class $ extends E{constructor(e){super(e)}}s.ValueRef=$,r=$,$.__name__=\"ValueRef\",r.prototype.default_view=k,r.define((({String:e})=>({field:[e]})));class B extends k{render(){super.render(),this.value_el=(0,g.span)(),this.swatch_el=(0,g.span)({class:S.tooltip_color_block},\" \"),this.el.appendChild(this.value_el),this.el.appendChild(this.swatch_el)}update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ColorRefView=B,B.__name__=\"ColorRefView\";class L extends ${constructor(e){super(e)}}s.ColorRef=L,c=L,L.__name__=\"ColorRef\",c.prototype.default_view=B,c.define((({Boolean:e})=>({hex:[e,!0],swatch:[e,!0]})));class j extends C{constructor(){super(...arguments),this.child_views=new Map}async lazy_initialize(){await super.lazy_initialize();const e=this.model.children.filter((e=>e instanceof v.Model));await(0,R.build_views)(this.child_views,e,{parent:this})}render(){super.render();const{style:e}=this.model;if(null!=e)if(e instanceof V.Styles)for(const t of e){const e=t.get_value();if((0,D.isString)(e)){const s=t.attr.replace(/_/g,\"-\");this.el.style.hasOwnProperty(s)&&this.el.style.setProperty(s,e)}}else for(const[t,s]of(0,M.entries)(e)){const e=t.replace(/_/g,\"-\");this.el.style.hasOwnProperty(e)&&this.el.style.setProperty(e,s)}for(const e of this.model.children)if((0,D.isString)(e)){const t=document.createTextNode(e);this.el.appendChild(t)}else{this.child_views.get(e).renderTo(this.el)}}}s.DOMElementView=j,j.__name__=\"DOMElementView\";class q extends z{constructor(e){super(e)}}s.DOMElement=q,d=q,q.__name__=\"DOMElement\",d.define((({String:e,Array:t,Dict:s,Or:n,Nullable:a,Ref:l})=>({style:[a(n(l(V.Styles),s(e))),null],children:[t(n(e,l(z),l(y.LayoutDOM))),[]]})));class F extends T.View{}s.ActionView=F,F.__name__=\"ActionView\";class H extends v.Model{constructor(e){super(e)}}s.Action=H,p=H,H.__name__=\"Action\",H.__module__=\"bokeh.models.dom\",p.define((({})=>({})));class J extends j{constructor(){super(...arguments),this.action_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await(0,R.build_views)(this.action_views,this.model.actions,{parent:this})}remove(){(0,R.remove_views)(this.action_views),super.remove()}update(e,t,s={}){!function n(a){for(const l of a.child_views.values())l instanceof N?l.update(e,t,s):l instanceof j&&n(l)}(this);for(const n of this.action_views.values())n.update(e,t,s)}}s.TemplateView=J,J.__name__=\"TemplateView\",J.tag_name=\"div\";class K extends q{}s.Template=K,u=K,K.__name__=\"Template\",u.prototype.default_view=J,u.define((({Array:e,Ref:t})=>({actions:[e(t(H)),[]]})));class Q extends j{}s.SpanView=Q,Q.__name__=\"SpanView\",Q.tag_name=\"span\";class U extends q{}s.Span=U,m=U,U.__name__=\"Span\",m.prototype.default_view=Q;class W extends j{}s.DivView=W,W.__name__=\"DivView\",W.tag_name=\"div\";class X extends q{}s.Div=X,w=X,X.__name__=\"Div\",w.prototype.default_view=W;class Y extends j{}s.TableView=Y,Y.__name__=\"TableView\",Y.tag_name=\"table\";class Z extends q{}s.Table=Z,f=Z,Z.__name__=\"Table\",f.prototype.default_view=Y;class ee extends j{}s.TableRowView=ee,ee.__name__=\"TableRowView\",ee.tag_name=\"tr\";class te extends q{}s.TableRow=te,h=te,te.__name__=\"TableRow\",h.prototype.default_view=ee;const se=e(41),ne=e(234);class ae extends F{update(e,t,s){for(const[e,s]of(0,ne.enumerate)(this.model.groups))e.visible=t==s}}s.ToggleGroupView=ae,ae.__name__=\"ToggleGroupView\";class le extends H{constructor(e){super(e)}}s.ToggleGroup=le,x=le,le.__name__=\"ToggleGroup\",x.prototype.default_view=ae,x.define((({Array:e,Ref:t})=>({groups:[e(t(se.RendererGroup)),[]]})))},\n", - " function _(l,n,u,_,e){var t;_();const o=l(53);class r extends 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- " function _(t,o,e,n,s){var i;n();const l=t(15),c=t(53),r=t(224),a=t(232),u=t(234);class h extends c.Model{constructor(t){super(t)}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof a.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new l.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,(()=>this.doit())),this.connect(this.properties.active.change,(()=>this.set_active()));for(const t of this.tools)this.connect(t.properties.active.change,(()=>{this.active=t.active}))}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,n]of(0,u.enumerate)(t))if(null==e)o.push(null);else{const t=()=>{var t,o,e;for(const s of this.tools)null===(e=null===(o=null===(t=s.menu)||void 0===t?void 0:t[n])||void 0===o?void 0:o.handler)||void 0===e||e.call(o)};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=h,i=h,h.__name__=\"ToolProxy\",i.define((({Boolean:t,Array:o,Ref:e})=>({tools:[o(e(r.ButtonTool)),[]],active:[t,!1],disabled:[t,!1]})))},\n", - " function _(o,t,s,e,i){var n,r;e();const l=o(20),c=o(9),h=o(13),a=o(233),_=o(221),p=o(394),u=o(309),f=o(207);class y extends a.ToolbarBase{constructor(o){super(o)}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},e=[],i=[];for(const o of this.help)(0,c.includes)(i,o.redirect)||(e.push(o),i.push(o.redirect));this._proxied_tools.push(...e),this.help=e;for(const[o,t]of(0,h.entries)(this.gestures)){o in s||(s[o]={});for(const e of t.tools)e.type in s[o]||(s[o][e.type]=[]),s[o][e.type].push(e)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const n=(o,t=!1)=>{const s=new p.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of(0,h.keys)(s)){const t=this.gestures[o];t.tools=[];for(const e of(0,h.keys)(s[o])){const i=s[o][e];if(i.length>0)if(\"multi\"==o)for(const o of i){const s=n([o]);t.tools.push(s),this.connect(s.properties.active.change,(()=>this._active_change(s)))}else{const o=n(i);t.tools.push(o),this.connect(o.properties.active.change,(()=>this._active_change(o)))}}}this.actions=[];for(const[o,s]of(0,h.entries)(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(n([o]));else s.length>0&&this.actions.push(n(s));this.inspectors=[];for(const t of(0,h.values)(o))t.length>0&&this.inspectors.push(n(t,!0));for(const[o,t]of(0,h.entries)(this.gestures))0!=t.tools.length&&(t.tools=(0,c.sort_by)(t.tools,(o=>o.default_order)),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=y,n=y,y.__name__=\"ProxyToolbar\",n.define((({Array:o,Ref:t})=>({toolbars:[o(t(_.Toolbar)),[]]})));class d extends u.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new f.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}after_layout(){super.after_layout();const o=this.child_views[0];o.layout.bbox=this.layout.bbox,o.render()}}s.ToolbarBoxView=d,d.__name__=\"ToolbarBoxView\";class b extends u.LayoutDOM{constructor(o){super(o)}}s.ToolbarBox=b,r=b,b.__name__=\"ToolbarBox\",r.prototype.default_view=d,r.define((({Ref:o})=>({toolbar:[o(a.ToolbarBase)],toolbar_location:[l.Location,\"right\"]})))},\n", - " function _(e,n,r,t,o){t();const s=e(1),u=e(53),c=(0,s.__importStar)(e(21)),a=e(8),l=e(13);r.resolve_defs=function(e,n){var r,t,o,s;function i(e){return null!=e.module?`${e.module}.${e.name}`:e.name}function f(e){if((0,a.isString)(e))switch(e){case\"Any\":return c.Any;case\"Unknown\":return c.Unknown;case\"Boolean\":return c.Boolean;case\"Number\":return c.Number;case\"Int\":return c.Int;case\"String\":return c.String;case\"Null\":return c.Null}else switch(e[0]){case\"Nullable\":{const[,n]=e;return c.Nullable(f(n))}case\"Or\":{const[,...n]=e;return c.Or(...n.map(f))}case\"Tuple\":{const[,n,...r]=e;return c.Tuple(f(n),...r.map(f))}case\"Array\":{const[,n]=e;return c.Array(f(n))}case\"Struct\":{const[,...n]=e,r=n.map((([e,n])=>[e,f(n)]));return 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function(n,e,o=[],i=!1){const u=new Map;async function f(i){let d;const f=n.roots().indexOf(i),r=o[f];null!=r?d=r:e.classList.contains(l.BOKEH_ROOT)?d=e:(d=(0,a.div)({class:l.BOKEH_ROOT}),e.appendChild(d));const w=await(0,s.build_view)(i,{parent:null});return w instanceof c.DOMView&&w.renderTo(d),u.set(i,w),t.index[i.id]=w,w}for(const e of n.roots())await f(e);return i&&(window.document.title=n.title()),n.on_change((n=>{n instanceof d.RootAddedEvent?f(n.model):n instanceof d.RootRemovedEvent?function(n){const e=u.get(n);null!=e&&(e.remove(),u.delete(n),delete t.index[n.id])}(n.model):i&&n instanceof d.TitleChangedEvent&&(window.document.title=n.title)})),[...u.values()]}},\n", - " function _(o,e,n,t,r){t();const l=o(43),d=o(44);function u(o){let e=document.getElementById(o);if(null==e)throw new Error(`Error rendering Bokeh model: could not find #${o} HTML tag`);if(!document.body.contains(e))throw new Error(`Error rendering Bokeh model: element #${o} must be under `);if(\"SCRIPT\"==e.tagName){const o=(0,l.div)({class:n.BOKEH_ROOT});(0,l.replaceWith)(e,o),e=o}return e}n.BOKEH_ROOT=d.root,n._resolve_element=function(o){const{elementid:e}=o;return null!=e?u(e):document.body},n._resolve_root_elements=function(o){const e=[];if(null!=o.root_ids&&null!=o.roots)for(const n of o.root_ids)e.push(u(o.roots[n]));return e}},\n", - " function _(n,o,t,s,e){s();const c=n(400),r=n(19),a=n(397);t._get_ws_url=function(n,o){let t,s=\"ws:\";return\"https:\"==window.location.protocol&&(s=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),`${s}//${t.host}${n}/ws`};const i={};t.add_document_from_session=async function(n,o,t,s=[],e=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=(0,c.parse_token)(o).session_id;n in i||(i[n]={});const e=i[n];return s in e||(e[s]=(0,c.pull_session)(n,o,t)),e[s]}(n,o,l)}catch(n){const t=(0,c.parse_token)(o).session_id;throw r.logger.error(`Failed to load Bokeh session ${t}: ${n}`),n}return(0,a.add_document_standalone)(d.document,t,s,e)}},\n", - " function _(e,s,n,t,o){t();const r=e(19),i=e(5),c=e(401),l=e(402),_=e(403);n.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",n.DEFAULT_TOKEN=\"eyJzZXNzaW9uX2lkIjogImRlZmF1bHQifQ\";let h=0;function a(e){let s=e.split(\".\")[0];const n=s.length%4;return 0!=n&&(s+=\"=\".repeat(4-n)),JSON.parse(atob(s.replace(/_/g,\"/\").replace(/-/g,\"+\")))}n.parse_token=a;class d{constructor(e=n.DEFAULT_SERVER_WEBSOCKET_URL,s=n.DEFAULT_TOKEN,t=null){this.url=e,this.token=s,this.args_string=t,this._number=h++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_replies=new Map,this._pending_messages=[],this._receiver=new l.Receiver,this.id=a(s).session_id.split(\".\")[0],r.logger.debug(`Creating websocket ${this._number} to '${this.url}' session '${this.id}'`)}async connect(){if(this.closed_permanently)throw new Error(\"Cannot connect() a closed ClientConnection\");if(null!=this.socket)throw new Error(\"Already connected\");this._current_handler=null,this._pending_replies.clear(),this._pending_messages=[];try{let e=`${this.url}`;return null!=this.args_string&&this.args_string.length>0&&(e+=`?${this.args_string}`),this.socket=new WebSocket(e,[\"bokeh\",this.token]),new Promise(((e,s)=>{this.socket.binaryType=\"arraybuffer\",this.socket.onopen=()=>this._on_open(e,s),this.socket.onmessage=e=>this._on_message(e),this.socket.onclose=e=>this._on_close(e,s),this.socket.onerror=()=>this._on_error(s)}))}catch(e){throw r.logger.error(`websocket creation failed to url: ${this.url}`),r.logger.error(` - ${e}`),e}}close(){this.closed_permanently||(r.logger.debug(`Permanently closing websocket connection ${this._number}`),this.closed_permanently=!0,null!=this.socket&&this.socket.close(1e3,`close method called on ClientConnection ${this._number}`),this.session._connection_closed())}_schedule_reconnect(e){setTimeout((()=>{this.closed_permanently||r.logger.info(`Websocket connection ${this._number} disconnected, will not attempt to reconnect`)}),e)}send(e){if(null==this.socket)throw new Error(`not connected so cannot send ${e}`);e.send(this.socket)}async send_with_reply(e){const s=await new Promise(((s,n)=>{this._pending_replies.set(e.msgid(),{resolve:s,reject:n}),this.send(e)}));if(\"ERROR\"===s.msgtype())throw new Error(`Error reply ${s.content.text}`);return s}async _pull_doc_json(){const e=c.Message.create(\"PULL-DOC-REQ\",{}),s=await this.send_with_reply(e);if(!(\"doc\"in s.content))throw new Error(\"No 'doc' field in PULL-DOC-REPLY\");return s.content.doc}async _repull_session_doc(e,s){var n;r.logger.debug(this.session?\"Repulling session\":\"Pulling session for first time\");try{const n=await this._pull_doc_json();if(null==this.session)if(this.closed_permanently)r.logger.debug(\"Got new document after connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=i.Document.from_json(n),t=i.Document._compute_patch_since_json(n,s);if(t.events.length>0){r.logger.debug(`Sending ${t.events.length} changes from model construction back to server`);const e=c.Message.create(\"PATCH-DOC\",{},t);this.send(e)}this.session=new _.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],r.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),r.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),r.logger.error(`Failed to repull session ${e}`),s(e instanceof Error?e:`${e}`)}}_on_open(e,s){r.logger.info(`Websocket connection ${this._number} is now open`),this._current_handler=n=>{this._awaiting_ack_handler(n,e,s)}}_on_message(e){null==this._current_handler&&r.logger.error(\"Got a message with no current handler set\");try{this._receiver.consume(e.data)}catch(e){this._close_bad_protocol(`${e}`)}const s=this._receiver.message;if(null!=s){const e=s.problem();null!=e&&this._close_bad_protocol(e),this._current_handler(s)}}_on_close(e,s){r.logger.info(`Lost websocket ${this._number} connection, ${e.code} (${e.reason})`),this.socket=null,this._pending_replies.forEach((e=>e.reject(\"Disconnected\"))),this._pending_replies.clear(),this.closed_permanently||this._schedule_reconnect(2e3),s(new Error(`Lost websocket connection, ${e.code} (${e.reason})`))}_on_error(e){r.logger.debug(`Websocket error on socket ${this._number}`);const s=\"Could not open websocket\";r.logger.error(`Failed to connect to Bokeh server: ${s}`),e(new Error(s))}_close_bad_protocol(e){r.logger.error(`Closing connection: ${e}`),null!=this.socket&&this.socket.close(1002,e)}_awaiting_ack_handler(e,s,n){\"ACK\"===e.msgtype()?(this._current_handler=e=>this._steady_state_handler(e),this._repull_session_doc(s,n)):this._close_bad_protocol(\"First message was not an ACK\")}_steady_state_handler(e){const s=e.reqid(),n=this._pending_replies.get(s);n?(this._pending_replies.delete(s),n.resolve(e)):this.session?this.session.handle(e):\"PATCH-DOC\"!=e.msgtype()&&this._pending_messages.push(e)}}n.ClientConnection=d,d.__name__=\"ClientConnection\",n.pull_session=function(e,s,n){return new d(e,s,n).connect()}},\n", - " function _(e,s,t,r,n){r();const i=e(34);class a{constructor(e,s,t){this.header=e,this.metadata=s,this.content=t,this.buffers=new Map}static assemble(e,s,t){const r=JSON.parse(e),n=JSON.parse(s),i=JSON.parse(t);return new a(r,n,i)}assemble_buffer(e,s){const t=null!=this.header.num_buffers?this.header.num_buffers:0;if(t<=this.buffers.size)throw new Error(`too many buffers received, expecting ${t}`);const{id:r}=JSON.parse(e);this.buffers.set(r,s)}static create(e,s,t={}){const r=a.create_header(e);return new a(r,s,t)}static create_header(e){return{msgid:(0,i.uniqueId)(),msgtype:e}}complete(){return null!=this.header&&null!=this.metadata&&null!=this.content&&(null==this.header.num_buffers||this.buffers.size==this.header.num_buffers)}send(e){if((null!=this.header.num_buffers?this.header.num_buffers:0)>0)throw new Error(\"BokehJS only supports receiving buffers, not sending\");const s=JSON.stringify(this.header),t=JSON.stringify(this.metadata),r=JSON.stringify(this.content);e.send(s),e.send(t),e.send(r)}msgid(){return this.header.msgid}msgtype(){return this.header.msgtype}reqid(){return this.header.reqid}problem(){return\"msgid\"in this.header?\"msgtype\"in this.header?null:\"No msgtype in header\":\"No msgid in header\"}}t.Message=a,a.__name__=\"Message\"},\n", - " function _(e,t,s,_,r){_();const i=e(401),h=e(8);class 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this.request_server_info()}_document_changed(e){if(e.setter_id===this.id)return;const t=e instanceof c.DocumentEventBatch?e.events:[e],n=this.document.create_json_patch(t),s=i.Message.create(\"PATCH-DOC\",{},n);this._connection.send(s)}_handle_patch(e){this.document.apply_json_patch(e.content,e.buffers,this.id)}_handle_ok(e){_.logger.trace(`Unhandled OK reply to ${e.reqid()}`)}_handle_error(e){_.logger.error(`Unhandled ERROR reply to ${e.reqid()}: ${e.content.text}`)}}n.ClientSession=r,r.__name__=\"ClientSession\"},\n", - " function _(e,o,t,n,r){n();const s=e(1),l=e(5),i=e(402),a=e(19),c=e(43),g=e(13),f=e(397),u=e(398),m=(0,s.__importDefault)(e(44)),p=(0,s.__importDefault)(e(240)),d=(0,s.__importDefault)(e(405));function _(e,o){o.buffers.length>0?e.consume(o.buffers[0].buffer):e.consume(o.content.data);const t=e.message;null!=t&&this.apply_json_patch(t.content,t.buffers)}function b(e,o){if(\"undefined\"!=typeof Jupyter&&null!=Jupyter.notebook.kernel){a.logger.info(`Registering Jupyter comms for target ${e}`);const t=Jupyter.notebook.kernel.comm_manager;try{t.register_target(e,(t=>{a.logger.info(`Registering Jupyter comms for target ${e}`);const n=new i.Receiver;t.on_msg(_.bind(o,n))}))}catch(e){a.logger.warn(`Jupyter comms failed to register. push_notebook() will not function. 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(exception reported: ${e})`)}}else if(\"undefined\"!=typeof google&&null!=google.colab.kernel){a.logger.info(`Registering Google Colab comms for target ${e}`);const t=google.colab.kernel.comms;try{t.registerTarget(e,(async t=>{var n,r,l;a.logger.info(`Registering Google Colab comms for target ${e}`);const c=new i.Receiver;try{for(var g,f=(0,s.__asyncValues)(t.messages);!(g=await f.next()).done;){const e=g.value,t={data:e.data},n=[];for(const o of null!==(l=e.buffers)&&void 0!==l?l:[])n.push(new DataView(o));const r={content:t,buffers:n};_.bind(o)(c,r)}}catch(e){n={error:e}}finally{try{g&&!g.done&&(r=f.return)&&await r.call(f)}finally{if(n)throw n.error}}}))}catch(e){a.logger.warn(`Google Colab comms failed to register. push_notebook() will not function. (exception reported: ${e})`)}}else console.warn(\"Jupyter notebooks comms not available. push_notebook() will not function. If running JupyterLab ensure the latest @bokeh/jupyter_bokeh extension is installed. 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t.def(e.shared.vao+\".currentVAO?\"+e.shared.vao+\".currentVAO.instances:-1\")}));return null}var d=l(hr,!0),m=function(){if(mr in r){var e=r[mr];return a.primitive=e,_.commandParameter(e,ie,\"invalid primitve\",t.commandStr),an((function(t,r){return ie[e]}))}if(mr in n){var o=n[mr];return on(o,(function(e,t){var r=e.constants.primTypes,n=e.invoke(t,o);return _.optional((function(){e.assert(t,n+\" in \"+r,\"invalid primitive, must be one of \"+Object.keys(ie))})),t.def(r,\"[\",n,\"]\")}))}return u?nn(s)?s.value?an((function(e,t){return t.def(e.ELEMENTS,\".primType\")})):an((function(){return 4})):new rn(s.thisDep,s.contextDep,s.propDep,(function(e,t){var r=e.ELEMENTS;return t.def(r,\"?\",r,\".primType:\",4)})):i?new rn(f.thisDep,f.contextDep,f.propDep,(function(e,t){return t.def(e.shared.vao+\".currentVAO?\"+e.shared.vao+\".currentVAO.primitive:4\")})):null}(),p=function(){if(pr in r){var e=0|r[pr];return a.count=e,_.command(\"number\"==typeof e&&e>=0,\"invalid vertex 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t.def(e.shared.vao,\".currentVAO?\",e.shared.vao,\".currentVAO.count:-1\")}));return m}return null}(),h=l(br,!1);return{elements:s,primitive:m,count:p,instances:h,offset:d,vao:f,vaoActive:i,elementsActive:u,static:a}}(e,d),A=function(e,t){var r=e.static,n=e.dynamic,i={};return k.forEach((function(e){var o=E(e);function f(t,a){if(e in r){var f=t(r[e]);i[o]=an((function(){return f}))}else if(e in n){var u=n[e];i[o]=on(u,(function(e,t){return a(e,t,e.invoke(t,u))}))}}switch(e){case Nt:case It:case Vt:case er:case Mt:case ir:case Xt:case Kt:case Jt:case Gt:return f((function(r){return _.commandType(r,\"boolean\",e,t.commandStr),r}),(function(t,r,n){return _.optional((function(){t.assert(r,\"typeof \"+n+'===\"boolean\"',\"invalid flag \"+e,t.commandStr)})),n}));case Wt:return f((function(r){return _.commandParameter(r,$r,\"invalid \"+e,t.commandStr),$r[r]}),(function(t,r,n){var a=t.constants.compareFuncs;return _.optional((function(){t.assert(r,n+\" in \"+a,\"invalid \"+e+\", must be one of 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_.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"blend.color must be a 4d array\")})),V(4,(function(e){return t.def(\"+\",r,\"[\",e,\"]\")}))}));case tr:return f((function(e){return _.commandType(e,\"number\",o,t.commandStr),0|e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"',\"invalid stencil.mask\")})),t.def(r,\"|0\")}));case rr:return f((function(r){_.commandType(r,\"object\",o,t.commandStr);var n=r.cmp||\"keep\",a=r.ref||0,i=\"mask\"in r?r.mask:-1;return _.commandParameter(n,$r,e+\".cmp\",t.commandStr),_.commandType(a,\"number\",e+\".ref\",t.commandStr),_.commandType(i,\"number\",e+\".mask\",t.commandStr),[$r[n],a,i]}),(function(e,t,r){var n=e.constants.compareFuncs;return _.optional((function(){function a(){e.assert(t,Array.prototype.join.call(arguments,\"\"),\"invalid stencil.func\")}a(r+\"&&typeof \",r,'===\"object\"'),a('!(\"cmp\" in ',r,\")||(\",r,\".cmp in \",n,\")\")})),[t.def('\"cmp\" in 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_.commandType(r,\"number\",o+\".factor\",t.commandStr),_.commandType(n,\"number\",o+\".units\",t.commandStr),[r,n]}),(function(t,r,n){return _.optional((function(){t.assert(r,n+\"&&typeof \"+n+'===\"object\"',\"invalid \"+e)})),[r.def(n,\".factor|0\"),r.def(n,\".units|0\")]}));case qt:return f((function(e){var r=0;return\"front\"===e?r=Hr:\"back\"===e&&(r=Nr),_.command(!!r,o,t.commandStr),r}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"front\"||'+r+'===\"back\"',\"invalid cull.face\")})),t.def(r,'===\"front\"?',Hr,\":\",Nr)}));case Yt:return f((function(e){return _.command(\"number\"==typeof e&&e>=a.lineWidthDims[0]&&e<=a.lineWidthDims[1],\"invalid line width, must be a positive number between \"+a.lineWidthDims[0]+\" and \"+a.lineWidthDims[1],t.commandStr),e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"&&'+r+\">=\"+a.lineWidthDims[0]+\"&&\"+r+\"<=\"+a.lineWidthDims[1],\"invalid line width\")})),r}));case Qt:return f((function(e){return _.commandParameter(e,Zr,o,t.commandStr),Zr[e]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"cw\"||'+r+'===\"ccw\"',\"invalid frontFace, must be one of cw,ccw\")})),t.def(r+'===\"cw\"?2304:'+qr)}));case Ht:return f((function(e){return _.command(me(e)&&4===e.length,\"color.mask must be length 4 array\",t.commandStr),e.map((function(e){return!!e}))}),(function(e,t,r){return _.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"invalid color.mask\")})),V(4,(function(e){return\"!!\"+r+\"[\"+e+\"]\"}))}));case Zt:return f((function(e){_.command(\"object\"==typeof e&&e,o,t.commandStr);var r=\"value\"in e?e.value:1,n=!!e.invert;return _.command(\"number\"==typeof r&&r>=0&&r<=1,\"sample.coverage.value must be a number between 0 and 1\",t.commandStr),[r,n]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+\"&&typeof \"+r+'===\"object\"',\"invalid sample.coverage\")})),[t.def('\"value\" in 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t=x[e];t&&(A[e]=t)}O(fr),O(E(or));var T=Object.keys(A).length>0,D={framebuffer:y,draw:w,shader:S,state:A,dirty:T,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(D.profile=function(e){var t,r=e.static,n=e.dynamic;if(ur in r){var a=!!r[ur];(t=an((function(e,t){return a}))).enable=a}else if(ur in n){var i=n[ur];t=on(i,(function(e,t){return e.invoke(t,i)}))}return t}(e),D.uniforms=function(e,t){var r=e.static,n=e.dynamic,a={};return Object.keys(r).forEach((function(e){var n,i=r[e];if(\"number\"==typeof i||\"boolean\"==typeof i)n=an((function(){return i}));else if(\"function\"==typeof i){var o=i._reglType;\"texture2d\"===o||\"textureCube\"===o?n=an((function(e){return e.link(i)})):\"framebuffer\"===o||\"framebufferCube\"===o?(_.command(i.color.length>0,'missing color attachment for framebuffer sent to uniform \"'+e+'\"',t.commandStr),n=an((function(e){return e.link(i.color[0])}))):_.commandRaise('invalid data for uniform \"'+e+'\"',t.commandStr)}else me(i)?n=an((function(t){return t.global.def(\"[\",V(i.length,(function(r){return _.command(\"number\"==typeof i[r]||\"boolean\"==typeof i[r],\"invalid uniform \"+e,t.commandStr),i[r]})),\"]\")})):_.commandRaise('invalid or missing data for uniform \"'+e+'\"',t.commandStr);n.value=i,a[e]=n})),Object.keys(n).forEach((function(e){var t=n[e];a[e]=on(t,(function(e,r){return e.invoke(r,t)}))})),a}(f,d),D.drawVAO=D.scopeVAO=w.vao,!D.drawVAO&&S.program&&!h&&n.angle_instanced_arrays&&w.static.elements){var j=!0,C=S.program.attributes.map((function(e){var r=t.static[e];return j=j&&!!r,r}));if(j&&C.length>0){var z=c.getVAO(c.createVAO({attributes:C,elements:w.static.elements}));D.drawVAO=new rn(null,null,null,(function(e,t){return e.link(z)})),D.useVAO=!0}}return h?D.useVAO=!0:D.attributes=function(e,t){var n=e.static,a=e.dynamic,o={};return Object.keys(n).forEach((function(e){var a=n[e],f=r.id(e),u=new b;if(en(a))u.state=1,u.buffer=i.getBuffer(i.create(a,Sr,!1,!0)),u.type=0;else{var s=i.getBuffer(a);if(s)u.state=1,u.buffer=s,u.type=0;else if(_.command(\"object\"==typeof a&&a,\"invalid data for attribute \"+e,t.commandStr),\"constant\"in a){var c=a.constant;u.buffer=\"null\",u.state=2,\"number\"==typeof c?u.x=c:(_.command(me(c)&&c.length>0&&c.length<=4,\"invalid constant for attribute \"+e,t.commandStr),Bt.forEach((function(e,t){t=0,'invalid offset for attribute \"'+e+'\"',t.commandStr);var d=0|a.stride;_.command(d>=0&&d<256,'invalid stride for attribute \"'+e+'\", must be integer betweeen [0, 255]',t.commandStr);var m=0|a.size;_.command(!(\"size\"in a)||m>0&&m<=4,'invalid size for attribute \"'+e+'\", must be 1,2,3,4',t.commandStr);var p=!!a.normalized,h=0;\"type\"in a&&(_.commandParameter(a.type,X,\"invalid type for attribute \"+e,t.commandStr),h=X[a.type]);var v=0|a.divisor;_.optional((function(){\"divisor\"in a&&(_.command(0===v||g,'cannot specify divisor for attribute \"'+e+'\", instancing not supported',t.commandStr),_.command(v>=0,'invalid divisor for 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a=this._map.get(e);if(null==a){const s=(0,n.gcd)(t);if(s>1){t=(0,o.map)(t,(t=>t/s)),a=this._get_or_create(t);const[r,n,_]=a;a=[r,n,s],this._map.set(e,a)}else{const[r,n]=this._create_texture(t);a=[r,n,s],this._map.set(e,a)}}return a}get(t){return t.length%2==1&&(t=(0,_.concat)([t,t])),this._get_or_create(t)}}a.DashCache=c,c.__name__=\"DashCache\"},\n", - " 414: function _(n,t,e,r,o){function u(n,t){let e,r;n>t?(e=n,r=t):(e=t,r=n);let o=e%r;for(;0!=o;)e=r,r=o,o=e%r;return r}r(),e.gcd=function(n){let t=n[0];for(let e=1;e= 0.0 ? 1.0 : -1.0;\\n}\\n\\nvoid main()\\n{\\n if (a_show_curr < 0.5) {\\n // Line segment has non-finite value at one or both ends, do not render.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n const float min_miter_factor_round_join_mesh = sqrt(2.0);\\n\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n vec2 segment_along = normalize(a_point_end - a_point_start); // unit vector.\\n v_segment_length = length(a_point_end - a_point_start);\\n vec2 segment_right = right_vector(segment_along); // unit vector.\\n vec2 xy;\\n\\n bool miter_too_large_start = false;\\n bool miter_too_large_end = false;\\n\\n v_coords.y = a_position.y*halfwidth; // Overwritten later for end points.\\n\\n bool has_start_cap = a_show_prev < 0.5;\\n bool has_end_cap = a_show_next < 0.5;\\n\\n vec2 point_normal_start;\\n float cos_theta_start;\\n float turn_right_start;\\n if (has_start_cap)\\n point_normal_start = segment_right;\\n else {\\n vec2 prev_right = right_vector(normalize(a_point_start - a_point_prev));\\n point_normal_start = normalize(segment_right + prev_right);\\n cos_theta_start = dot(segment_right, point_normal_start); // Always +ve\\n turn_right_start = sign_no_zero(dot(segment_right, a_point_prev - a_point_start));\\n }\\n\\n vec2 point_normal_end;\\n float cos_theta_end;\\n float turn_right_end;\\n if (has_end_cap)\\n point_normal_end = segment_right;\\n else {\\n vec2 next_right = right_vector(normalize(a_point_next - a_point_end));\\n point_normal_end = normalize(segment_right + next_right);\\n cos_theta_end = dot(segment_right, point_normal_end); // Always +ve\\n turn_right_end = sign_no_zero(dot(segment_right, a_point_next - a_point_end));\\n }\\n\\n float miter_factor_start = 1.0 / dot(segment_right, point_normal_start);\\n float miter_factor_end = 1.0 / dot(segment_right, point_normal_end);\\n if (join_type == miter_join) {\\n // If miter too large, use bevel join instead.\\n miter_too_large_start = (miter_factor_start > u_miter_limit);\\n miter_too_large_end = (miter_factor_end > u_miter_limit);\\n }\\n\\n float sign_at_start = -sign(a_position.x); // +ve at segment start, -ve end.\\n vec2 point = sign_at_start > 0.0 ? a_point_start : a_point_end;\\n vec2 adjacent_point =\\n sign_at_start > 0.0 ? (has_start_cap ? a_point_start : a_point_prev)\\n : (has_end_cap ? a_point_end : a_point_next);\\n\\n if ( (has_start_cap && sign_at_start > 0.0) ||\\n (has_end_cap && sign_at_start < 0.0) ) {\\n // Cap.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (cap_type == butt_cap)\\n xy -= sign_at_start*0.5*u_antialias*segment_along;\\n else\\n xy -= sign_at_start*halfwidth*segment_along;\\n }\\n else { // Join.\\n // +ve if turning to right, -ve if to left.\\n float turn_sign = sign_at_start > 0.0 ? turn_right_start : turn_right_end;\\n\\n vec2 adjacent_right = sign_at_start*normalize(right_vector(point - adjacent_point));\\n vec2 point_right = normalize(segment_right + adjacent_right);\\n float miter_factor = sign_at_start > 0.0 ? miter_factor_start : miter_factor_end;\\n bool miter_too_large = sign_at_start > 0.0 ? miter_too_large_start : miter_too_large_end;\\n\\n if (abs(a_position.x) > 1.5) {\\n // Outer point, meets prev/next segment.\\n float factor; // multiplied by halfwidth...\\n\\n if (join_type == bevel_join || (join_type == miter_join && miter_too_large))\\n factor = 1.0 / miter_factor; // cos_theta.\\n else if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh)\\n factor = 1.0;\\n else // miter, or round (small angle only).\\n factor = miter_factor;\\n\\n xy = point - point_right*(halfwidth*turn_sign*factor);\\n v_coords.y = turn_sign*halfwidth*factor / miter_factor;\\n }\\n else if (turn_sign*a_position.y < 0.0) {\\n // Inner point, meets prev/next segment.\\n float len = halfwidth*miter_factor;\\n float segment_len = v_segment_length;\\n float adjacent_len = distance(point, adjacent_point);\\n\\n if (len <= min(segment_len, adjacent_len))\\n // Normal behaviour.\\n xy = point - point_right*(len*a_position.y);\\n else\\n // For short wide line segments the inner point using the above\\n // calculation can be outside of the line. Here clipping it.\\n xy = point + segment_right*(halfwidth*turn_sign);\\n }\\n else {\\n // Point along outside edge.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh) {\\n xy = line_intersection(xy, segment_along,\\n point - turn_sign*point_right*halfwidth,\\n right_vector(point_right));\\n }\\n }\\n }\\n\\n vec2 pos = xy + 0.5; // Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n\\n v_coords.x = dot(xy - a_point_start, segment_along);\\n v_flags = float(int(has_start_cap) +\\n 2*int(has_end_cap) +\\n 4*int(miter_too_large_start) +\\n 8*int(miter_too_large_end));\\n v_cos_theta_turn_right_start = cos_theta_start*turn_right_start;\\n v_cos_theta_turn_right_end = cos_theta_end*turn_right_end;\\n\\n#ifdef DASHED\\n v_length_so_far = a_length_so_far;\\n#endif\\n}\\n\"},\n", - " 416: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\nuniform float u_linewidth;\\nuniform float u_antialias;\\nuniform float u_line_join;\\nuniform float u_line_cap;\\nuniform vec4 u_line_color;\\n#ifdef DASHED\\nuniform sampler2D u_dash_tex;\\nuniform vec4 u_dash_tex_info;\\nuniform float u_dash_scale;\\nuniform float u_dash_offset;\\n#endif\\n\\nvarying float v_segment_length;\\nvarying vec2 v_coords;\\nvarying float v_flags;\\nvarying float v_cos_theta_turn_right_start;\\nvarying float v_cos_theta_turn_right_end;\\n#ifdef DASHED\\nvarying float v_length_so_far;\\n#endif\\n\\nfloat cross_z(in vec2 v0, in vec2 v1)\\n{\\n return v0.x*v1.y - v0.y*v1.x;\\n}\\n\\nfloat point_line_side(in vec2 point, in vec2 start, in vec2 end)\\n{\\n // +ve if point to right of line.\\n // Alternatively could do dot product with right_vector.\\n return cross_z(point - start, end - start);\\n}\\n\\nfloat point_line_distance(in vec2 point, in vec2 start, in vec2 end)\\n{\\n return point_line_side(point, start, end) / distance(start, end);\\n}\\n\\nvec2 right_vector(in vec2 v)\\n{\\n return vec2(v.y, -v.x);\\n}\\n\\nfloat bevel_join_distance(in float sign_start, in float halfwidth)\\n{\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n float distance_along = sign_start > 0.0 ? 0.0 : v_segment_length;\\n\\n // In v_coords reference frame (x is along segment, y across).\\n vec2 line_start = vec2(distance_along, halfwidth*turn_right);\\n float sin_alpha = cos_theta;\\n float cos_alpha = sqrt(1.0 - sin_alpha*sin_alpha);\\n vec2 line_along = vec2(-sign_start*turn_right*sin_alpha, -cos_alpha);\\n\\n return halfwidth + sign_start*point_line_distance(\\n v_coords, line_start, line_start+line_along);\\n}\\n\\nfloat cap(in int cap_type, in float x, in float y)\\n{\\n // x is distance along segment in direction away from end of segment,\\n // y is distance across segment.\\n if (cap_type == butt_cap)\\n return max(0.5*u_linewidth - x, abs(y));\\n else if (cap_type == square_cap)\\n return max(-x, abs(y));\\n else // cap_type == round_cap\\n return distance(vec2(min(x, 0.0), y), vec2(0.0, 0.0));\\n}\\n\\nfloat distance_to_alpha(in float dist)\\n{\\n return 1.0 - smoothstep(0.5*(u_linewidth - u_antialias),\\n 0.5*(u_linewidth + u_antialias), dist);\\n}\\n\\n#ifdef DASHED\\nfloat dash_distance(in float x)\\n{\\n // x is in direction of v_coords.x, i.e. along segment.\\n float tex_length = u_dash_tex_info.x;\\n float tex_offset = u_dash_tex_info.y;\\n float tex_dist_min = u_dash_tex_info.z;\\n float tex_dist_max = u_dash_tex_info.w;\\n\\n // Apply offset.\\n x += v_length_so_far - u_dash_scale*tex_offset + u_dash_offset;\\n\\n // Interpolate within texture to obtain distance to dash.\\n float dist = texture2D(u_dash_tex,\\n vec2(x / (tex_length*u_dash_scale), 0.0)).a;\\n\\n // Scale distance within min and max limits.\\n dist = tex_dist_min + dist*(tex_dist_max - tex_dist_min);\\n\\n return u_dash_scale*dist;\\n}\\n\\nfloat clip_dash_distance(in float x, in float offset, in float sign_along)\\n{\\n // Return clipped dash distance, sign_along is +1.0 if looking forward\\n // into next segment and -1.0 if looking backward into previous segment.\\n float half_antialias = 0.5*u_antialias;\\n\\n if (sign_along*x > half_antialias) {\\n // Outside antialias region, use usual dash distance.\\n return dash_distance(offset + x);\\n }\\n else {\\n // Inside antialias region.\\n // Dash distance at edge of antialias region clipped to half_antialias.\\n float edge_dist = min(dash_distance(offset + sign_along*half_antialias), half_antialias);\\n\\n // Physical distance from dash distance at edge of antialias region.\\n return edge_dist + sign_along*x - half_antialias;\\n }\\n}\\n\\nmat2 rotation_matrix(in float sign_start)\\n{\\n // Rotation matrix for v_coords from this segment to prev or next segment.\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n\\n float sin_theta = sqrt(1.0 - cos_theta*cos_theta)*sign_start*turn_right;\\n float cos_2theta = 2.0*cos_theta*cos_theta - 1.0;\\n float sin_2theta = 2.0*sin_theta*cos_theta;\\n return mat2(cos_2theta, -sin_2theta, sin_2theta, cos_2theta);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n float half_antialias = 0.5*u_antialias;\\n\\n // Extract flags.\\n int flags = int(v_flags + 0.5);\\n bool miter_too_large_end = (flags / 8 > 0);\\n flags -= 8*int(miter_too_large_end);\\n bool miter_too_large_start = (flags / 4 > 0);\\n flags -= 4*int(miter_too_large_start);\\n bool has_end_cap = (flags / 2 > 0);\\n flags -= 2*int(has_end_cap);\\n bool has_start_cap = flags > 0;\\n\\n float dist = v_coords.y; // For straight segment, and miter join.\\n\\n // Along-segment coords with respect to end of segment, +ve inside segment\\n // so equivalent to v_coords.x at start of segment.\\n float end_coords_x = v_segment_length - v_coords.x;\\n\\n if (v_coords.x <= half_antialias) {\\n // At start of segment, either cap or join.\\n if (has_start_cap)\\n dist = cap(cap_type, v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(0.0, 0.0));\\n else if (join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_start))\\n dist = max(abs(dist), bevel_join_distance(1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n else if (end_coords_x <= half_antialias) {\\n // At end of segment, either cap or join.\\n if (has_end_cap)\\n dist = cap(cap_type, end_coords_x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(v_segment_length, 0));\\n else if ((join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_end)))\\n dist = max(abs(dist), bevel_join_distance(-1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n\\n float alpha = distance_to_alpha(abs(dist));\\n\\n#ifdef DASHED\\n if (u_dash_tex_info.x >= 0.0) {\\n // Dashes in straight segments (outside of joins) are easily calculated.\\n dist = dash_distance(v_coords.x);\\n\\n if (!has_start_cap && cap_type == butt_cap) {\\n if (v_coords.x < half_antialias) {\\n // Outer of start join rendered solid color or not at all\\n // depending on whether corner point is in dash or gap, with\\n // antialiased ends.\\n if (dash_distance(0.0) > 0.0) {\\n // Corner is solid color.\\n dist = max(dist, min(half_antialias, -v_coords.x));\\n // Avoid visible antialiasing band between corner and dash.\\n dist = max(dist, dash_distance(half_antialias));\\n }\\n else {\\n // Use large negative value so corner not colored.\\n dist = -halfwidth;\\n\\n if (v_coords.x > -half_antialias) {\\n // Consider antialias region of dash after start region.\\n float edge_dist = min(dash_distance(half_antialias), half_antialias);\\n dist = max(dist, edge_dist + v_coords.x - half_antialias);\\n }\\n }\\n }\\n\\n vec2 prev_coords = rotation_matrix(1.0)*v_coords;\\n\\n if (abs(prev_coords.y) < halfwidth && prev_coords.x < half_antialias) {\\n // Extend dashes across from end of previous segment, with antialiased end.\\n float new_dist = clip_dash_distance(prev_coords.x, 0.0, -1.0);\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(prev_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n if (!has_end_cap && cap_type == butt_cap) {\\n if (end_coords_x < half_antialias) {\\n // Similar for end join.\\n if (dash_distance(v_segment_length) > 0.0) {\\n // Corner is solid color.\\n dist = max(dist, min(half_antialias, -end_coords_x));\\n // Avoid visible antialiasing band between corner and dash.\\n dist = max(dist, dash_distance(v_segment_length - half_antialias));\\n }\\n else {\\n // Use large negative value so corner not colored.\\n dist = -halfwidth;\\n\\n if (end_coords_x > -half_antialias) {\\n // Consider antialias region of dash before end region.\\n float edge_dist = min(dash_distance(v_segment_length - half_antialias),\\n half_antialias);\\n dist = max(dist, edge_dist + end_coords_x - half_antialias);\\n }\\n }\\n }\\n\\n vec2 next_coords = rotation_matrix(-1.0)*(v_coords - vec2(v_segment_length, 0.0));\\n\\n if (abs(next_coords.y) < halfwidth && next_coords.x > -half_antialias) {\\n // Extend dashes across from next segment, with antialiased end.\\n float new_dist = clip_dash_distance(next_coords.x, v_segment_length, 1.0);\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(next_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n dist = cap(cap_type, dist, v_coords.y);\\n\\n float dash_alpha = distance_to_alpha(dist);\\n alpha = min(alpha, dash_alpha);\\n }\\n#endif\\n\\n alpha = u_line_color.a*alpha;\\n gl_FragColor = vec4(u_line_color.rgb*alpha, alpha); // Premultiplied alpha.\\n}\\n\"},\n", - " 417: function _(n,i,e,t,a){t();e.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_width;\\nattribute float a_height;\\nattribute float a_angle; // In radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_line_cap;\\nattribute float a_line_join;\\nattribute float a_show;\\n#ifdef HATCH\\nattribute float a_hatch_pattern;\\nattribute float a_hatch_scale;\\nattribute float a_hatch_weight;\\nattribute vec4 a_hatch_color;\\n#endif\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\nuniform float u_size_hint;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size; // 2D size for rects compared to 1D for markers.\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_cap;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\nvoid main()\\n{\\n if (a_show < 0.5) {\\n // Do not show this rect.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n v_size = vec2(a_width, a_height);\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n v_line_cap = a_line_cap;\\n v_line_join = a_line_join;\\n\\n if (v_linewidth < 1.0) {\\n // Linewidth less than 1 is implemented as 1 but with reduced alpha.\\n v_line_color.a *= v_linewidth;\\n v_linewidth = 1.0;\\n }\\n\\n#ifdef HATCH\\n v_hatch_pattern = a_hatch_pattern;\\n v_hatch_scale = a_hatch_scale;\\n v_hatch_weight = a_hatch_weight;\\n v_hatch_color = a_hatch_color;\\n#endif\\n\\n vec2 enclosing_size;\\n // Need extra size of (v_linewidth+u_antialias) if edge of marker parallel to\\n // edge of bounding box. If symmetric spike towards edge then multiply by\\n // 1/cos(theta) where theta is angle between spike and bbox edges.\\n int size_hint = int(u_size_hint + 0.5);\\n if (size_hint == 1) // Dash\\n enclosing_size = vec2(v_size.x + v_linewidth + u_antialias,\\n v_linewidth + u_antialias);\\n else if (size_hint == 2) // Dot\\n enclosing_size = 0.25*v_size + u_antialias;\\n else if (size_hint == 3) // Diamond\\n enclosing_size = vec2(v_size.x*(2.0/3.0) + (v_linewidth + u_antialias)*1.20185,\\n v_size.y + (v_linewidth + u_antialias)*1.80278);\\n else if (size_hint == 4) // Hex\\n enclosing_size = v_size + (v_linewidth + u_antialias)*vec2(2.0/sqrt(3.0), 1.0);\\n else if (size_hint == 5) // Square pin\\n enclosing_size = v_size + (v_linewidth + u_antialias)*3.1;\\n else if (size_hint == 6) // Triangle\\n enclosing_size = vec2(v_size.x + (v_linewidth + u_antialias)*sqrt(3.0),\\n v_size.y*(2.0/sqrt(3.0)) + (v_linewidth + u_antialias)*2.0);\\n else if (size_hint == 7) // Triangle pin\\n enclosing_size = v_size + (v_linewidth + u_antialias)*vec2(4.8, 6.0);\\n else if (size_hint == 8) // Star\\n enclosing_size = vec2(v_size.x*0.95106 + (v_linewidth + u_antialias)*3.0,\\n v_size.y + (v_linewidth + u_antialias)*3.2);\\n else\\n enclosing_size = v_size + v_linewidth + u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used for\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n#ifdef HATCH\\n // Coordinates for hatching in unrotated frame of reference.\\n v_hatch_coords = pos - 0.5;\\n#endif\\n pos += 0.5; // Make up for Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // 0 to 1.\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 418: function _(n,i,e,t,a){t();e.default=\"\\nprecision mediump float;\\n\\nconst float SQRT2 = sqrt(2.0);\\nconst float SQRT3 = sqrt(3.0);\\nconst float PI = 3.14159265358979323846;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\n#ifdef HATCH\\nconst int hatch_dot = 1;\\nconst int hatch_ring = 2;\\nconst int hatch_horizontal_line = 3;\\nconst int hatch_vertical_line = 4;\\nconst int hatch_cross = 5;\\nconst int hatch_horizontal_dash = 6;\\nconst int hatch_vertical_dash = 7;\\nconst int hatch_spiral = 8;\\nconst int hatch_right_diagonal_line = 9;\\nconst int hatch_left_diagonal_line = 10;\\nconst int hatch_diagonal_cross = 11;\\nconst int hatch_right_diagonal_dash = 12;\\nconst int hatch_left_diagonal_dash = 13;\\nconst int hatch_horizontal_wave = 14;\\nconst int hatch_vertical_wave = 15;\\nconst int hatch_criss_cross = 16;\\n#endif\\n\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_cap;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\n// Lines within the marker (dot, cross, x and y) are added at the end as they are\\n// on top of the fill rather than astride it.\\n#if defined(USE_CIRCLE_DOT) || defined(USE_DIAMOND_DOT) || defined(USE_DOT) || defined(USE_HEX_DOT) || defined(USE_SQUARE_DOT) || defined(USE_STAR_DOT) || defined(USE_TRIANGLE_DOT)\\n #define APPEND_DOT\\n#endif\\n\\n#if defined(USE_CIRCLE_CROSS) || defined(USE_SQUARE_CROSS)\\n #define APPEND_CROSS\\n#endif\\n\\n#ifdef USE_DIAMOND_CROSS\\n #define APPEND_CROSS_2\\n#endif\\n\\n#ifdef USE_CIRCLE_X\\n #define APPEND_X\\n #define APPEND_X_LEN (0.5*v_size.x)\\n#endif\\n\\n#ifdef USE_SQUARE_X\\n #define APPEND_X\\n #define APPEND_X_LEN (v_size.x/SQRT2)\\n#endif\\n\\n#ifdef USE_CIRCLE_Y\\n #define APPEND_Y\\n#endif\\n\\n#if defined(USE_ASTERISK) || defined(USE_CROSS) || defined(USE_DASH) || defined(USE_DOT) || defined(USE_X) || defined(USE_Y)\\n // No fill.\\n #define LINE_ONLY\\n#endif\\n\\n#if defined(LINE_ONLY) || defined(APPEND_CROSS) || defined(APPEND_CROSS_2) || defined(APPEND_X) || defined(APPEND_Y)\\nfloat end_cap_distance(in vec2 p, in vec2 end_point, in vec2 unit_direction, in int line_cap)\\n{\\n vec2 offset = p - end_point;\\n if (line_cap == butt_cap)\\n return dot(offset, unit_direction) + 0.5*v_linewidth;\\n else if (line_cap == square_cap)\\n return dot(offset, unit_direction);\\n else if (line_cap == round_cap && dot(offset, unit_direction) > 0.0)\\n return length(offset);\\n else\\n // Default is outside of line and should be -0.5*(v_linewidth+u_antialias) or less,\\n // so here avoid the multiplication.\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if !(defined(LINE_ONLY) || defined(USE_SQUARE_PIN) || defined(USE_TRIANGLE_PIN))\\n// For line join at a vec2 corner where 2 line segments meet, consider bevel points which are the 2\\n// points obtained by moving half a linewidth away from the corner point in the directions normal to\\n// the line segments. The line through these points is the bevel line, characterised by a vec2\\n// unit_normal and offset distance from the corner point. Edge of bevel join straddles this line,\\n// round join occurs outside of this line centred on the corner point. In general\\n// offset = (linewidth/2)*sin(alpha/2)\\n// where alpha is the angle between the 2 line segments at the corner.\\nfloat line_join_distance_no_miter(\\n in vec2 p, in vec2 corner, in vec2 unit_normal, in float offset, in int line_join)\\n{\\n // Simplified version of line_join_distance ignoring miter which most markers do implicitly\\n // as they are composed of straight line segments.\\n float dist_outside = dot((p - corner), unit_normal) - offset;\\n\\n if (line_join == bevel_join && dist_outside > -0.5*u_antialias)\\n return dist_outside + 0.5*v_linewidth;\\n else if (dist_outside > 0.0) // round_join\\n return distance(p, corner);\\n else\\n // Default is outside of line and should be -0.5*(v_linewidth+u_antialias) or less,\\n // so here avoid the multiplication.\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if defined(USE_SQUARE_PIN) || defined(USE_TRIANGLE_PIN)\\n// Line join distance including miter but only one-sided check as assuming use of symmetry in\\n// calling function.\\nfloat line_join_distance_incl_miter(\\n in vec2 p, in vec2 corner, in vec2 unit_normal, in float offset, in int line_join,\\n vec2 miter_unit_normal)\\n{\\n float dist_outside = dot((p - corner), unit_normal) - offset;\\n\\n if (line_join == miter_join && dist_outside > 0.0)\\n return dot((p - corner), miter_unit_normal);\\n else if (line_join == bevel_join && dist_outside > -0.5*u_antialias)\\n return dist_outside + 0.5*v_linewidth;\\n else if (dist_outside > 0.0) // round_join\\n return distance(p, corner);\\n else\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if defined(APPEND_CROSS) || defined(APPEND_X) || defined(USE_ASTERISK) || defined(USE_CROSS) || defined(USE_X)\\nfloat one_cross(in vec2 p, in int line_cap, in float len)\\n{\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(len, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#ifdef APPEND_CROSS_2\\nfloat one_cross_2(in vec2 p, in int line_cap, in vec2 lengths)\\n{\\n // Cross with different length in x and y directions.\\n p = abs(p);\\n bool switch_xy = (p.y > p.x);\\n p = switch_xy ? p.yx : p.xy;\\n float len = switch_xy ? lengths.y : lengths.x;\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(len, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#if defined(APPEND_Y) || defined(USE_Y)\\nfloat one_y(in vec2 p, in int line_cap, in float len)\\n{\\n p = vec2(abs(p.x), -p.y);\\n\\n // End point of line to right is (1/2, 1/3)*len*SQRT3.\\n // Unit vector along line is (1/2, 1/3)*k where k = 6/SQRT13.\\n const float k = 6.0/sqrt(13.0);\\n vec2 unit_along = vec2(0.5*k, k/3.0);\\n vec2 end_point = vec2(0.5*len*SQRT3, len*SQRT3/3.0);\\n float dist = max(abs(dot(p, vec2(-unit_along.y, unit_along.x))),\\n end_cap_distance(p, end_point, unit_along, line_cap));\\n\\n if (p.y < 0.0) {\\n // Vertical line.\\n float vert_dist = max(p.x,\\n end_cap_distance(p, vec2(0.0, -len), vec2(0.0, -1.0), line_cap));\\n dist = min(dist, vert_dist);\\n }\\n return dist;\\n}\\n#endif\\n\\n// One marker_distance function per marker type.\\n// Distance is zero on edge of marker, +ve outside and -ve inside.\\n\\n#ifdef USE_ASTERISK\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n vec2 p_diag = vec2((p.x + p.y)/SQRT2, (p.x - p.y)/SQRT2);\\n float len = 0.5*v_size.x;\\n return min(one_cross(p, line_cap, len), // cross\\n one_cross(p_diag, line_cap, len)); // x\\n}\\n#endif\\n\\n#if defined(USE_CIRCLE) || defined(USE_CIRCLE_CROSS) || defined(USE_CIRCLE_DOT) || defined(USE_CIRCLE_X) || defined(USE_CIRCLE_Y)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return length(p) - 0.5*v_size.x;\\n}\\n#endif\\n\\n#ifdef USE_CROSS\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return one_cross(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n#ifdef USE_DASH\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n p = abs(p);\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(0.5*v_size.x, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#if defined(USE_DIAMOND) || defined(USE_DIAMOND_CROSS) || defined(USE_DIAMOND_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // Only need to consider +ve quadrant, the 2 end points are (2r/3, 0) and (0, r)\\n // where r = radius = v_size.x/2.\\n // Line has outward-facing unit normal vec2(1, 2/3)/k where k = SQRT13/3\\n // hence vec2(3, 2)/SQRT13, and distance from origin of 2r/(3k) = 2r/SQRT13.\\n p = abs(p);\\n float r = 0.5*v_size.x;\\n const float SQRT13 = sqrt(13.0);\\n float dist = dot(p, vec2(3.0, 2.0))/SQRT13 - 2.0*r/SQRT13;\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, r), vec2(0.0, 1.0), v_linewidth/SQRT13, line_join));\\n\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r*2.0/3.0, 0.0), vec2(1.0, 0.0), v_linewidth*(1.5/SQRT13), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_DOT\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Dot is always appended.\\n return v_linewidth+u_antialias;\\n}\\n#endif\\n\\n#if defined(USE_HEX) || defined(USE_HEX_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // A regular hexagon has v_size.x == v.size_y = r where r is the length of\\n // each of the 3 sides of the 6 equilateral triangles that comprise the hex.\\n // Only consider +ve quadrant, the 3 corners are at (0, h), (rx/2, h), (rx, 0)\\n // where rx = 0.5*v_size.x, ry = 0.5*v_size.y and h = ry*SQRT3/2.\\n // Sloping line has outward normal vec2(h, rx/2). Length of this is\\n // len = sqrt(h**2 + rx**2/4) to give unit normal (h, rx/2)/len and distance\\n // from origin of this line is rx*h/len.\\n p = abs(p);\\n float rx = v_size.x/2.0;\\n float h = v_size.y*(SQRT3/4.0);\\n float len_normal = sqrt(h*h + 0.25*rx*rx);\\n vec2 unit_normal = vec2(h, 0.5*rx) / len_normal;\\n float dist = max(dot(p, unit_normal) - rx*h/len_normal, // Distance from sloping line.\\n p.y - h); // Distance from horizontal line.\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(rx, 0.0), vec2(1.0, 0.0), 0.5*v_linewidth*unit_normal.x, line_join));\\n\\n unit_normal = normalize(unit_normal + vec2(0.0, 1.0)); // At (rx/2, h) corner.\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.5*rx, h), unit_normal, 0.5*v_linewidth*unit_normal.y, line_join));\\n }\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_PLUS\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // Only need to consider one octant, the +ve quadrant with x >= y.\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n\\n // 3 corners are (r, 0), (r, 3r/8) and (3r/8, 3r/8).\\n float r = 0.5*v_size.x;\\n p = p - vec2(r, 0.375*r); // Distance with respect to outside corner\\n float dist = max(p.x, p.y);\\n\\n if (line_join != miter_join) {\\n // Outside corner\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, 0.0), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n\\n // Inside corner\\n dist = min(dist, -line_join_distance_no_miter(\\n p, vec2(-5.0*r/8.0, 0.0), vec2(-1.0/SQRT2, -1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_SQUARE) || defined(USE_SQUARE_CROSS) || defined(USE_SQUARE_DOT) || defined(USE_SQUARE_X)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n vec2 p2 = abs(p) - v_size/2.0; // Offset from corner\\n float dist = max(p2.x, p2.y);\\n\\n if (line_join != miter_join)\\n dist = max(dist, line_join_distance_no_miter(\\n p2, vec2(0.0, 0.0), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_PIN\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n // p is in octant between y=0 and y=x.\\n // Quadratic bezier curve passes through (r, r), (11r/16, 0) and (r, -r).\\n // Circular arc that passes through the same points has center at\\n // x = r + 231r/160 = 2.44275r and y = 0 and hence radius is\\n // x - 11r/16 = 1.75626 precisely.\\n float r = 0.5*v_size.x;\\n float center_x = r*2.44375;\\n float radius = r*1.75626;\\n float dist = radius - distance(p, vec2(center_x, 0.0));\\n\\n // Magic number is 0.5*sin(atan(8/5) - pi/4)\\n dist = max(dist, line_join_distance_incl_miter(\\n p, vec2(r, r), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth*0.1124297533493792, line_join,\\n vec2(8.0/sqrt(89.0), -5.0/sqrt(89.0))));\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_STAR) || defined(USE_STAR_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n const float SQRT5 = sqrt(5.0);\\n const float COS72 = 0.25*(SQRT5 - 1.0);\\n const float SIN72 = sqrt((5.0+SQRT5) / 8.0);\\n\\n float angle = atan(p.x, p.y); // In range -pi to +pi clockwise from +y direction.\\n angle = mod(angle, 0.4*PI) - 0.2*PI; // In range -pi/5 to +pi/5 clockwise from +y direction.\\n p = length(p)*vec2(cos(angle), abs(sin(angle))); // (x,y) in pi/10 (36 degree) sector.\\n\\n // 2 corners are at (r, 0) and (r-a*SIN72, a*COS72) where a = r sqrt(5-2*sqrt(5)).\\n // Line has outward-facing unit normal vec2(COS72, SIN72) and distance from\\n // origin of dot(vec2(r, 0), vec2(COS72, SIN72)) = r*COS72\\n float r = 0.5*v_size.x;\\n float a = r*sqrt(5.0 - 2.0*SQRT5);\\n float dist = dot(p, vec2(COS72, SIN72)) - r*COS72;\\n\\n if (line_join != miter_join) {\\n // Outside corner\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r, 0.0), vec2(1.0, 0.0), v_linewidth*(0.5*COS72), line_join));\\n\\n // Inside corner\\n const float COS36 = sqrt(0.5 + COS72/2.0);\\n const float SIN36 = sqrt(0.5 - COS72/2.0);\\n dist = min(dist, -line_join_distance_no_miter(\\n p, vec2(r-a*SIN72, a*COS72), vec2(-COS36, -SIN36), v_linewidth*(0.5*COS36), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_TRIANGLE) || defined(USE_TRIANGLE_DOT) || defined(USE_INVERTED_TRIANGLE)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // For normal triangle 3 corners are at (-r, a), (r, a), (0, a-h)=(0, -2h/3)\\n // given r = radius = v_size.x/2, h = SQRT3*r, a = h/3.\\n // Sloping line has outward-facing unit normal vec2(h, -r)/2r = vec2(SQRT3, -1)/2\\n // and distance from origin of a. Horizontal line has outward-facing unit normal\\n // vec2(0, 1) and distance from origin of a.\\n float r = 0.5*v_size.x;\\n float a = r*SQRT3/3.0;\\n\\n // Only need to consider +ve x.\\n#ifdef USE_INVERTED_TRIANGLE\\n p = vec2(abs(p.x), -p.y);\\n#else\\n p = vec2(abs(p.x), p.y);\\n#endif\\n\\n float dist = max(0.5*dot(p, vec2(SQRT3, -1.0)) - a, // Distance from sloping line.\\n p.y - a); // Distance from horizontal line.\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, -(2.0/SQRT3)*r), vec2(0.0, -1.0), v_linewidth*0.25, line_join));\\n\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r, a), vec2(SQRT3/2.0, 0.5), v_linewidth*0.25, line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_PIN\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n float angle = atan(p.x, -p.y); // In range -pi to +pi.\\n angle = mod(angle, PI*2.0/3.0) - PI/3.0; // In range -pi/3 to pi/3.\\n p = length(p)*vec2(cos(angle), abs(sin(angle))); // (x,y) in range 0 to pi/3.\\n // Quadratic bezier curve passes through (a, r), ((a+b)/2, 0) and (a, -r) where\\n // a = r/SQRT3, b = 3a/8 = r SQRT3/8. Circular arc that passes through the same points has\\n // center at (a+x, 0) and radius x+c where c = (a-b)/2 and x = (r**2 - c**2) / (2c).\\n // Ignore r factor until the end so can use const.\\n const float a = 1.0/SQRT3;\\n const float b = SQRT3/8.0;\\n const float c = (a-b)/2.0;\\n const float x = (1.0 - c*c) / (2.0*c);\\n const float center_x = x + a;\\n const float radius = x + c;\\n float r = 0.5*v_size.x;\\n float dist = r*radius - distance(p, vec2(r*center_x, 0.0));\\n\\n // Magic number is 0.5*sin(atan(8*sqrt(3)/5) - pi/3)\\n dist = max(dist, line_join_distance_incl_miter(\\n p, vec2(a*r, r), vec2(0.5, 0.5*SQRT3), v_linewidth*0.0881844526878324, line_join,\\n vec2(8.0*SQRT3, -5.0)/sqrt(217.0)));\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_X\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n p = vec2((p.x + p.y)/SQRT2, (p.x - p.y)/SQRT2);\\n return one_cross(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n#ifdef USE_Y\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return one_y(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n// Convert distance from edge of marker to fraction in range 0 to 1, depending\\n// on antialiasing width.\\nfloat distance_to_fraction(in float dist)\\n{\\n return 1.0 - smoothstep(-0.5*u_antialias, 0.5*u_antialias, dist);\\n}\\n\\n// Return fraction from 0 (no fill color) to 1 (full fill color).\\nfloat fill_fraction(in float dist)\\n{\\n return distance_to_fraction(dist);\\n}\\n\\n// Return fraction in range 0 (no line color) to 1 (full line color).\\nfloat line_fraction(in float dist)\\n{\\n return distance_to_fraction(abs(dist) - 0.5*v_linewidth);\\n}\\n\\n// Return fraction (in range 0 to 1) of a color, with premultiplied alpha.\\nvec4 fractional_color(in vec4 color, in float fraction)\\n{\\n color.a *= fraction;\\n color.rgb *= color.a;\\n return color;\\n}\\n\\n// Blend colors that have premultiplied alpha.\\nvec4 blend_colors(in vec4 src, in vec4 dest)\\n{\\n return (1.0 - src.a)*dest + src;\\n}\\n\\n#ifdef APPEND_DOT\\nfloat dot_fraction(in vec2 p)\\n{\\n // Assuming v_size.x == v_size.y\\n float radius = 0.125*v_size.x;\\n float dot_distance = max(length(p) - radius, -0.5*u_antialias);\\n return fill_fraction(dot_distance);\\n}\\n#endif\\n\\n#ifdef HATCH\\n// Wrap coordinate(s) by removing integer part to give distance from center of\\n// repeat, in the range -0.5 to +0.5.\\nfloat wrap(in float x)\\n{\\n return fract(x) - 0.5;\\n}\\n\\nvec2 wrap(in vec2 xy)\\n{\\n return fract(xy) - 0.5;\\n}\\n\\n// Return fraction from 0 (no hatch color) to 1 (full hatch color).\\nfloat hatch_fraction(in vec2 coords, in int hatch_pattern)\\n{\\n float scale = v_hatch_scale; // Hatch repeat distance.\\n\\n // Coordinates and linewidth/halfwidth are scaled to hatch repeat distance.\\n coords = coords / scale;\\n float halfwidth = 0.5*v_hatch_weight / scale; // Half the hatch linewidth.\\n\\n // Default is to return fraction of zero, i.e. no pattern.\\n float dist = u_antialias;\\n\\n if (hatch_pattern == hatch_dot) {\\n const float dot_radius = 0.25;\\n dist = length(wrap(coords)) - dot_radius;\\n }\\n else if (hatch_pattern == hatch_ring) {\\n const float ring_radius = 0.25;\\n dist = abs(length(wrap(coords)) - ring_radius) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_line) {\\n dist = abs(wrap(coords.y)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_line) {\\n dist = abs(wrap(coords.x)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_cross) {\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_dash) {\\n // Dashes have square caps.\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.y)),\\n abs(wrap(coords.x) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_dash) {\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.x)),\\n abs(wrap(coords.y) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_spiral) {\\n vec2 wrap2 = wrap(coords);\\n float angle = wrap(atan(wrap2.y, wrap2.x) / (2.0*PI));\\n // Canvas spiral radius increases by scale*pi/15 each rotation.\\n const float dr = PI/15.0;\\n float radius = length(wrap2);\\n // At any angle, spiral lines are equally spaced dr apart.\\n // Find distance to nearest of these lines.\\n float frac = fract((radius - dr*angle) / dr); // 0 to 1.\\n dist = dr*(abs(frac - 0.5));\\n dist = min(dist, radius) - halfwidth; // Consider center point also.\\n }\\n else if (hatch_pattern == hatch_right_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x + coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x - coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_diagonal_cross) {\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_right_diagonal_dash) {\\n float across = coords.x + coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x - coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_dash) {\\n float across = coords.x - coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x + coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_wave) {\\n float wrapx = wrap(coords.x);\\n float wrapy = wrap(coords.y - 0.25 + abs(wrapx));\\n dist = abs(wrapy) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_wave) {\\n float wrapy = wrap(coords.y);\\n float wrapx = wrap(coords.x - 0.25 + abs(wrapy));\\n dist = abs(wrapx) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_criss_cross) {\\n float plus = min(abs(wrap(coords.x)), abs(wrap(coords.y)));\\n\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n float X = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2;\\n\\n dist = min(plus, X) - halfwidth;\\n }\\n\\n return distance_to_fraction(dist*scale);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int line_cap = int(v_line_cap + 0.5);\\n int line_join = int(v_line_join + 0.5);\\n#ifdef HATCH\\n int hatch_pattern = int(v_hatch_pattern + 0.5);\\n#endif\\n\\n float dist = marker_distance(v_coords, line_cap, line_join);\\n\\n#ifdef LINE_ONLY\\n vec4 color = vec4(0.0, 0.0, 0.0, 0.0);\\n#else\\n float fill_frac = fill_fraction(dist);\\n vec4 color = fractional_color(v_fill_color, fill_frac);\\n#endif\\n\\n#if defined(HATCH) && !defined(LINE_ONLY)\\n if (hatch_pattern > 0 && fill_frac > 0.0) {\\n float hatch_frac = hatch_fraction(v_hatch_coords, hatch_pattern);\\n vec4 hatch_color = fractional_color(v_hatch_color, hatch_frac*fill_frac);\\n color = blend_colors(hatch_color, color);\\n }\\n#endif\\n\\n float line_frac = line_fraction(dist);\\n\\n#ifdef APPEND_DOT\\n line_frac = max(line_frac, dot_fraction(v_coords));\\n#endif\\n#ifdef APPEND_CROSS\\n line_frac = max(line_frac, line_fraction(one_cross(v_coords, line_cap, 0.5*v_size.x)));\\n#endif\\n#ifdef APPEND_CROSS_2\\n vec2 lengths = vec2(v_size.x/3.0, v_size.x/2.0);\\n line_frac = max(line_frac, line_fraction(one_cross_2(v_coords, line_cap, lengths)));\\n#endif\\n#ifdef APPEND_X\\n vec2 p = vec2((v_coords.x + v_coords.y)/SQRT2, (v_coords.x - v_coords.y)/SQRT2);\\n line_frac = max(line_frac, line_fraction(one_cross(p, line_cap, APPEND_X_LEN)));\\n#endif\\n#ifdef APPEND_Y\\n line_frac = max(line_frac, line_fraction(one_y(v_coords, line_cap, 0.5*v_size.x)));\\n#endif\\n\\n if (line_frac > 0.0) {\\n vec4 line_color = fractional_color(v_line_color, line_frac);\\n color = blend_colors(line_color, color);\\n }\\n\\n gl_FragColor = color;\\n}\\n\"},\n", - " 419: function _(t,_,i,h,e){h();const s=t(420),a=t(421),r=t(422);class l extends s.BaseGLGlyph{constructor(t,_){super(t,_),this.glyph=_,this._antialias=1.5,this._show_all=!1}_draw_one_marker_type(t,_,i){const h={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[_.width,_.height],pixel_ratio:_.pixel_ratio,center:i._centers,width:i._widths,height:i._heights,angle:i._angles,size_hint:(0,r.marker_type_to_size_hint)(t),nmarkers:i.nvertices,antialias:this._antialias,linewidth:this._linewidths,line_color:this._line_rgba,fill_color:this._fill_rgba,line_cap:this._line_caps,line_join:this._line_joins,show:this._show};if(this._have_hatch){const _=Object.assign(Object.assign({},h),{hatch_pattern:this._hatch_patterns,hatch_scale:this._hatch_scales,hatch_weight:this._hatch_weights,hatch_color:this._hatch_rgba});this.regl_wrapper.marker_hatch(t)(_)}else this.regl_wrapper.marker_no_hatch(t)(h)}_set_visuals(){const t=this._get_visuals(),_=t.fill,i=t.line;if(null==this._linewidths&&(this._linewidths=new a.Float32Buffer(this.regl_wrapper),this._line_caps=new a.Uint8Buffer(this.regl_wrapper),this._line_joins=new a.Uint8Buffer(this.regl_wrapper),this._line_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper),this._fill_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper)),this._linewidths.set_from_prop(i.line_width),this._line_caps.set_from_line_cap(i.line_cap),this._line_joins.set_from_line_join(i.line_join),this._line_rgba.set_from_color(i.line_color,i.line_alpha),this._fill_rgba.set_from_color(_.fill_color,_.fill_alpha),this._have_hatch=t.hatch.doit,this._have_hatch){const _=t.hatch;null==this._hatch_patterns&&(this._hatch_patterns=new a.Uint8Buffer(this.regl_wrapper),this._hatch_scales=new a.Float32Buffer(this.regl_wrapper),this._hatch_weights=new a.Float32Buffer(this.regl_wrapper),this._hatch_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper)),this._hatch_patterns.set_from_hatch_pattern(_.hatch_pattern),this._hatch_scales.set_from_prop(_.hatch_scale),this._hatch_weights.set_from_prop(_.hatch_weight),this._hatch_rgba.set_from_color(_.hatch_color,_.hatch_alpha)}}}i.BaseMarkerGL=l,l.__name__=\"BaseMarkerGL\",l.missing_point=-1e4},\n", - " 420: function _(e,t,s,i,h){i();class a{constructor(e,t){this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1,this.regl_wrapper=e}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,s){if(0==t.length)return!0;const{width:i,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:i,height:h};return this.draw(t,s,a),!0}}s.BaseGLGlyph=a,a.__name__=\"BaseGLGlyph\"},\n", - " 421: function _(r,t,a,e,s){e();const i=r(422),_=r(22);class n{constructor(r){this.regl_wrapper=r,this.is_scalar=!0}get_sized_array(r){return null!=this.array&&this.array.length==r||(this.array=this.new_array(r)),this.array}is_normalized(){return!1}get length(){return null!=this.array?this.array.length:0}set_from_array(r){const t=r.length,a=this.get_sized_array(t);for(let e=0;e0}_set_data(){const s=this.glyph.sx.length,i=s-1;this._is_closed=s>2&&this.glyph.sx[0]==this.glyph.sx[s-1]&&this.glyph.sy[0]==this.glyph.sy[s-1]&&isFinite(this.glyph.sx[0])&&isFinite(this.glyph.sy[0]),null==this._points&&(this._points=new o.Float32Buffer(this.regl_wrapper));const t=this._points.get_sized_array(2*(s+2));for(let i=1;is/255)),this._linewidth=s.line_width.value,this._linewidth<1&&(this._color[3]*=this._linewidth,this._linewidth=1),this._line_dash=(0,a.resolve_line_dash)(s.line_dash.value),this._is_dashed()&&([this._dash_tex_info,this._dash_tex,this._dash_scale]=this.regl_wrapper.get_dash(this._line_dash),this._dash_offset=s.line_dash_offset.value)}}t.LineGL=r,r.__name__=\"LineGL\"},\n", - " 427: function _(s,t,i,e,r){e();const h=s(421),a=s(424);class n extends a.SingleMarkerGL{constructor(s,t){super(s,t),this.glyph=t}draw(s,t,i){this._draw_impl(s,i,t.glglyph,\"square\")}_get_visuals(){return this.glyph.visuals}_set_data(){const s=this.nvertices;null==this._centers&&(this._centers=new h.Float32Buffer(this.regl_wrapper),this._widths=new h.Float32Buffer(this.regl_wrapper),this._heights=new h.Float32Buffer(this.regl_wrapper),this._angles=new h.Float32Buffer(this.regl_wrapper),this._angles.set_from_scalar(0));const t=this._centers.get_sized_array(2*s),i=this._heights.get_sized_array(s),e=this._widths.get_sized_array(s);for(let r=0;r1||s.length<_){this._show_all=!1,n.fill(0),r=0;for(const e of s)1!=h&&i._marker_types.get(e)!=t||(n[e]=255,r++)}else this._show_all&&a==_||(this._show_all=!0,n.fill(255));this._show.update(),0!=r&&this._draw_one_marker_type(t,e,i)}}_get_visuals(){return this.glyph.visuals}_set_data(){const s=this.nvertices;null==this._centers&&(this._centers=new r.Float32Buffer(this.regl_wrapper),this._widths=new r.Float32Buffer(this.regl_wrapper),this._heights=this._widths,this._angles=new r.Float32Buffer(this.regl_wrapper));const t=this._centers.get_sized_array(2*s);for(let e=0;ethis.render()))}remove(){null!=this.icon_view&&this.icon_view.remove(),super.remove()}styles(){return[...super.styles(),d.default]}_render_button(...t){return(0,c.button)({type:\"button\",disabled:this.model.disabled,class:[h.btn,h[`btn_${this.model.button_type}`]]},...t)}render(){super.render(),this.button_el=this._render_button(this.model.label),this.button_el.addEventListener(\"click\",(()=>this.click())),null!=this.icon_view&&(\"\"!=this.model.label?(0,c.prepend)(this.button_el,this.icon_view.el,(0,c.nbsp)()):(0,c.prepend)(this.button_el,this.icon_view.el),this.icon_view.render()),this.group_el=(0,c.div)({class:h.btn_group},this.button_el),this.el.appendChild(this.group_el)}click(){}}n.AbstractButtonView=b,b.__name__=\"AbstractButtonView\";class p extends _.Control{constructor(t){super(t)}}n.AbstractButton=p,o=p,p.__name__=\"AbstractButton\",o.define((({String:t,Ref:e,Nullable:n})=>({label:[t,\"Button\"],icon:[n(e(a.AbstractIcon)),null],button_type:[r.ButtonType,\"default\"]})))},\n", - " 442: function _(t,e,o,s,n){s();const i=t(512),l=t(43);class c extends i.WidgetView{connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.disabled,(()=>{for(const t of this.controls())(0,l.toggle_attribute)(t,\"disabled\",this.model.disabled)}))}}o.ControlView=c,c.__name__=\"ControlView\";class r extends i.Widget{constructor(t){super(t)}}o.Control=r,r.__name__=\"Control\"},\n", - " 512: function _(i,e,t,n,o){var r;n();const s=i(312);class _ extends s.HTMLBoxView{get orientation(){return\"horizontal\"}get default_size(){return this.model.default_size}_width_policy(){return\"horizontal\"==this.orientation?super._width_policy():\"fixed\"}_height_policy(){return\"horizontal\"==this.orientation?\"fixed\":super._height_policy()}box_sizing(){const i=super.box_sizing();return\"horizontal\"==this.orientation?null==i.width&&(i.width=this.default_size):null==i.height&&(i.height=this.default_size),i}}t.WidgetView=_,_.__name__=\"WidgetView\";class h extends s.HTMLBox{constructor(i){super(i)}}t.Widget=h,r=h,h.__name__=\"Widget\",r.define((({Number:i})=>({default_size:[i,300]}))),r.override({margin:[5,5,5,5]})},\n", - " 444: function _(c,t,s,n,e){n();const o=c(53),_=c(226);class a extends _.DOMView{}s.AbstractIconView=a,a.__name__=\"AbstractIconView\";class r extends o.Model{constructor(c){super(c)}}s.AbstractIcon=r,r.__name__=\"AbstractIcon\"},\n", - " 445: function _(e,t,n,s,i){s();const h=e(1);var o;const _=e(446),u=e(43),r=e(10),c=(0,h.__importStar)(e(229)),a=c;class l extends _.TextInputView{constructor(){super(...arguments),this._open=!1,this._last_value=\"\",this._hover_index=0}styles(){return[...super.styles(),c.default]}render(){super.render(),this.input_el.addEventListener(\"keydown\",(e=>this._keydown(e))),this.input_el.addEventListener(\"keyup\",(e=>this._keyup(e))),this.menu=(0,u.div)({class:[a.menu,a.below]}),this.menu.addEventListener(\"click\",(e=>this._menu_click(e))),this.menu.addEventListener(\"mouseover\",(e=>this._menu_hover(e))),this.el.appendChild(this.menu),(0,u.undisplay)(this.menu)}change_input(){this._open&&this.menu.children.length>0?(this.model.value=this.menu.children[this._hover_index].textContent,this.input_el.focus(),this._hide_menu()):this.model.restrict||super.change_input()}_update_completions(e){(0,u.empty)(this.menu);for(const t of e){const e=(0,u.div)(t);this.menu.appendChild(e)}e.length>0&&this.menu.children[0].classList.add(a.active)}_show_menu(){if(!this._open){this._open=!0,this._hover_index=0,this._last_value=this.model.value,(0,u.display)(this.menu);const e=t=>{const{target:n}=t;n instanceof HTMLElement&&!this.el.contains(n)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,(0,u.undisplay)(this.menu))}_menu_click(e){e.target!=e.currentTarget&&e.target instanceof Element&&(this.model.value=e.target.textContent,this.input_el.focus(),this._hide_menu())}_menu_hover(e){if(e.target!=e.currentTarget&&e.target instanceof Element){let t=0;for(t=0;t0&&(this.menu.children[this._hover_index].classList.remove(a.active),this._hover_index=(0,r.clamp)(e,0,t-1),this.menu.children[this._hover_index].classList.add(a.active))}_keydown(e){}_keyup(e){switch(e.keyCode){case u.Keys.Enter:this.change_input();break;case u.Keys.Esc:this._hide_menu();break;case u.Keys.Up:this._bump_hover(this._hover_index-1);break;case u.Keys.Down:this._bump_hover(this._hover_index+1);break;default:{const e=this.input_el.value;if(e.lengthe:e=>e.toLowerCase();for(const n of this.model.completions)s(n).startsWith(s(e))&&t.push(n);this._update_completions(t),0==t.length?this._hide_menu():this._show_menu()}}}}n.AutocompleteInputView=l,l.__name__=\"AutocompleteInputView\";class d extends _.TextInput{constructor(e){super(e)}}n.AutocompleteInput=d,o=d,d.__name__=\"AutocompleteInput\",o.prototype.default_view=l,o.define((({Boolean:e,Int:t,String:n,Array:s})=>({completions:[s(n),[]],min_characters:[t,2],case_sensitive:[e,!0],restrict:[e,!0]})))},\n", - " 446: function _(t,e,n,p,_){p();const u=t(1);var i;const s=t(447),r=t(43),x=(0,u.__importStar)(t(449));class a extends s.TextLikeInputView{_render_input(){this.input_el=(0,r.input)({type:\"text\",class:x.input})}}n.TextInputView=a,a.__name__=\"TextInputView\";class c extends s.TextLikeInput{constructor(t){super(t)}}n.TextInput=c,i=c,c.__name__=\"TextInput\",i.prototype.default_view=a},\n", - " 447: function _(e,t,n,i,l){var s;i();const h=e(448);class a extends h.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>this.input_el.value=this.model.value)),this.connect(this.model.properties.value_input.change,(()=>this.input_el.value=this.model.value_input)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.max_length.change,(()=>{const{max_length:e}=this.model;null!=e?this.input_el.maxLength=e:this.input_el.removeAttribute(\"maxLength\")}))}render(){var e;super.render(),this._render_input();const{input_el:t}=this;t.name=null!==(e=this.model.name)&&void 0!==e?e:\"\",t.value=this.model.value,t.disabled=this.model.disabled,t.placeholder=this.model.placeholder,null!=this.model.max_length&&(t.maxLength=this.model.max_length),t.addEventListener(\"change\",(()=>this.change_input())),t.addEventListener(\"input\",(()=>this.change_input_value())),this.group_el.appendChild(t)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_value(){this.model.value_input=this.input_el.value,super.change_input()}}n.TextLikeInputView=a,a.__name__=\"TextLikeInputView\";class u extends h.InputWidget{constructor(e){super(e)}}n.TextLikeInput=u,s=u,u.__name__=\"TextLikeInput\",s.define((({Int:e,String:t,Nullable:n})=>({value:[t,\"\"],value_input:[t,\"\"],placeholder:[t,\"\"],max_length:[n(e),null]})))},\n", - " 448: function _(e,t,n,s,l){s();const i=e(1);var o;const r=e(442),_=e(43),p=(0,i.__importStar)(e(449)),a=p;class c extends r.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,(()=>{this.label_el.textContent=this.model.title}))}styles(){return[...super.styles(),p.default]}render(){super.render();const{title:e}=this.model;this.label_el=(0,_.label)({style:{display:0==e.length?\"none\":\"\"}},e),this.group_el=(0,_.div)({class:a.input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}n.InputWidgetView=c,c.__name__=\"InputWidgetView\";class d extends r.Control{constructor(e){super(e)}}n.InputWidget=d,o=d,d.__name__=\"InputWidget\",o.define((({String:e})=>({title:[e,\"\"]})))},\n", - " 449: function _(o,p,t,n,i){n(),t.root=\"bk-root\",t.input=\"bk-input\",t.input_group=\"bk-input-group\",t.inline=\"bk-inline\",t.spin_wrapper=\"bk-spin-wrapper\",t.spin_btn=\"bk-spin-btn\",t.spin_btn_up=\"bk-spin-btn-up\",t.spin_btn_down=\"bk-spin-btn-down\",t.default='.bk-root .bk-input{display:inline-block;width:100%;flex-grow:1;min-height:31px;padding:0 12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;}.bk-root .bk-input:focus{border-color:#66afe9;outline:0;box-shadow:inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);}.bk-root .bk-input::placeholder,.bk-root .bk-input:-ms-input-placeholder,.bk-root .bk-input::-moz-placeholder,.bk-root .bk-input::-webkit-input-placeholder{color:#999;opacity:1;}.bk-root .bk-input[disabled]{cursor:not-allowed;background-color:#eee;opacity:1;}.bk-root select:not([multiple]).bk-input,.bk-root select:not([size]).bk-input{height:auto;appearance:none;-webkit-appearance:none;background-image:url(\\'data:image/svg+xml;utf8,\\');background-position:right 0.5em center;background-size:8px 6px;background-repeat:no-repeat;}.bk-root select[multiple].bk-input,.bk-root select[size].bk-input,.bk-root textarea.bk-input{height:auto;}.bk-root .bk-input-group{width:100%;height:100%;display:inline-flex;flex-wrap:nowrap;align-items:start;flex-direction:column;white-space:nowrap;}.bk-root .bk-input-group.bk-inline{flex-direction:row;}.bk-root .bk-input-group.bk-inline > *:not(:first-child){margin-left:5px;}.bk-root .bk-input-group input[type=\"checkbox\"] + span,.bk-root .bk-input-group input[type=\"radio\"] + span{position:relative;top:-2px;margin-left:3px;}.bk-root .bk-input-group > .bk-spin-wrapper{display:inherit;width:inherit;height:inherit;position:relative;overflow:hidden;padding:0;vertical-align:middle;}.bk-root .bk-input-group > .bk-spin-wrapper input{padding-right:20px;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn{position:absolute;display:block;height:50%;min-height:0;min-width:0;width:30px;padding:0;margin:0;right:0;border:none;background:none;cursor:pointer;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before{content:\"\";display:inline-block;transform:translateY(-50%);border-left:5px solid transparent;border-right:5px solid transparent;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up{top:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before{border-bottom:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before{border-bottom-color:grey;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down{bottom:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before{border-top:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before{border-top-color:grey;}'},\n", - " 450: function _(t,e,n,o,c){var s;o();const u=t(441),r=t(251);class i extends u.AbstractButtonView{click(){this.model.trigger_event(new r.ButtonClick),super.click()}}n.ButtonView=i,i.__name__=\"ButtonView\";class _ extends u.AbstractButton{constructor(t){super(t)}}n.Button=_,s=_,_.__name__=\"Button\",s.prototype.default_view=i,s.override({label:\"Button\"})},\n", - " 451: function _(t,e,o,c,a){c();const s=t(1);var n;const i=t(452),r=t(43),u=(0,s.__importStar)(t(318));class _ extends i.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach(((e,o)=>{(0,r.classes)(e).toggle(u.active,t.has(o))}))}}o.CheckboxButtonGroupView=_,_.__name__=\"CheckboxButtonGroupView\";class h extends i.ButtonGroup{constructor(t){super(t)}}o.CheckboxButtonGroup=h,n=h,h.__name__=\"CheckboxButtonGroup\",n.prototype.default_view=_,n.define((({Int:t,Array:e})=>({active:[e(t),[]]})))},\n", - " 452: function _(t,e,n,s,i){s();const o=t(1);var r;const a=t(453),l=t(20),d=t(43),u=(0,o.__importStar)(t(318)),_=u;class c extends a.OrientedControlView{get default_size(){return\"horizontal\"==this.orientation?this.model.default_size:void 0}*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,(()=>this.render())),this.on_change(t.labels,(()=>this.render())),this.on_change(t.active,(()=>this._update_active()))}styles(){return[...super.styles(),u.default]}render(){super.render(),this._buttons=this.model.labels.map(((t,e)=>{const n=(0,d.div)({class:[_.btn,_[`btn_${this.model.button_type}`]],disabled:this.model.disabled},t);return n.addEventListener(\"click\",(()=>this.change_active(e))),n})),this._update_active();const t=\"horizontal\"==this.model.orientation?_.horizontal:_.vertical,e=(0,d.div)({class:[_.btn_group,t]},this._buttons);this.el.appendChild(e)}}n.ButtonGroupView=c,c.__name__=\"ButtonGroupView\";class h extends a.OrientedControl{constructor(t){super(t)}}n.ButtonGroup=h,r=h,h.__name__=\"ButtonGroup\",r.define((({String:t,Array:e})=>({labels:[e(t),[]],button_type:[l.ButtonType,\"default\"]})))},\n", - " 453: function _(n,t,e,o,r){var i;o();const a=n(442),l=n(20);class s extends a.ControlView{get orientation(){return this.model.orientation}}e.OrientedControlView=s,s.__name__=\"OrientedControlView\";class _ extends a.Control{constructor(n){super(n)}}e.OrientedControl=_,i=_,_.__name__=\"OrientedControl\",i.define((()=>({orientation:[l.Orientation,\"horizontal\"]})))},\n", - " 454: function _(e,t,n,i,s){i();const o=e(1);var a;const c=e(455),l=e(43),d=e(9),p=(0,o.__importStar)(e(449));class r extends c.InputGroupView{render(){super.render();const e=(0,l.div)({class:[p.input_group,this.model.inline?p.inline:null]});this.el.appendChild(e);const{active:t,labels:n}=this.model;this._inputs=[];for(let i=0;ithis.change_active(i))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),(0,d.includes)(t,i)&&(s.checked=!0);const o=(0,l.label)(s,(0,l.span)(n[i]));e.appendChild(o)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}n.CheckboxGroupView=r,r.__name__=\"CheckboxGroupView\";class h extends c.InputGroup{constructor(e){super(e)}}n.CheckboxGroup=h,a=h,h.__name__=\"CheckboxGroup\",a.prototype.default_view=r,a.define((({Boolean:e,Int:t,String:n,Array:i})=>({active:[i(t),[]],labels:[i(n),[]],inline:[e,!1]})))},\n", - " 455: function _(n,t,e,s,o){s();const r=n(1),u=n(442),c=(0,r.__importDefault)(n(449));class _ extends u.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}styles(){return[...super.styles(),c.default]}}e.InputGroupView=_,_.__name__=\"InputGroupView\";class i extends u.Control{constructor(n){super(n)}}e.InputGroup=i,i.__name__=\"InputGroup\"},\n", - " 456: function _(e,t,i,n,o){n();const s=e(1);var l;const r=e(448),c=e(43),a=e(22),d=(0,s.__importStar)(e(449));class h extends r.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.color.change,(()=>this.input_el.value=(0,a.color2hexrgb)(this.model.color))),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled))}render(){super.render(),this.input_el=(0,c.input)({type:\"color\",class:d.input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}i.ColorPickerView=h,h.__name__=\"ColorPickerView\";class p extends r.InputWidget{constructor(e){super(e)}}i.ColorPicker=p,l=p,p.__name__=\"ColorPicker\",l.prototype.default_view=h,l.define((({Color:e})=>({color:[e,\"#000000\"]})))},\n", - " 457: function _(e,t,i,n,s){n();const a=e(1);var l;const o=(0,a.__importDefault)(e(458)),d=e(448),r=e(43),c=e(20),u=e(8),h=(0,a.__importStar)(e(449)),_=(0,a.__importDefault)(e(459));function p(e){const t=[];for(const i of e)if((0,u.isString)(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class m extends d.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.setDate(this.model.value)})),this.connect(t.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",this.model.min_date)})),this.connect(i.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",this.model.max_date)})),this.connect(n.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",this.model.disabled_dates)})),this.connect(s.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",this.model.enabled_dates)})),this.connect(a.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",this.model.position)})),this.connect(l.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",this.model.inline)}))}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),_.default]}render(){var e,t;null==this._picker&&(super.render(),this.input_el=(0,r.input)({type:\"text\",class:h.input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=(0,o.default)(this.input_el,{defaultDate:this.model.value,minDate:null!==(e=this.model.min_date)&&void 0!==e?e:void 0,maxDate:null!==(t=this.model.max_date)&&void 0!==t?t:void 0,inline:this.model.inline,position:this.model.position,disable:p(this.model.disabled_dates),enable:p(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=m,m.__name__=\"DatePickerView\";class v extends d.InputWidget{constructor(e){super(e)}}i.DatePicker=v,l=v,v.__name__=\"DatePicker\",l.prototype.default_view=m,l.define((({Boolean:e,String:t,Array:i,Tuple:n,Or:s,Nullable:a})=>{const l=i(s(t,n(t,t)));return{value:[t],min_date:[a(t),null],max_date:[a(t),null],disabled_dates:[l,[]],enabled_dates:[l,[]],position:[c.CalendarPosition,\"auto\"],inline:[e,!1]}}))},\n", - " 458: function _(e,n,t,a,i){\n", - " /* flatpickr v4.6.6, @license MIT */var o,r;o=this,r=function(){\"use strict\";\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation.\n", - " \n", - " Permission to use, copy, modify, and/or distribute this software for any\n", - " purpose with or without fee is hereby granted.\n", - " \n", - " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", - " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", - " AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n", - " INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n", - " LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n", - " OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n", - " PERFORMANCE OF THIS SOFTWARE.\n", - " ***************************************************************************** */var e=function(){return e=Object.assign||function(e){for(var n,t=1,a=arguments.length;t\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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i.setDate(i.getDate()-i.getDay()+t.firstDayOfWeek),i},Y:function(e,n){e.setFullYear(parseFloat(n))},Z:function(e,n){return new Date(n)},d:function(e,n){e.setDate(parseFloat(n))},h:function(e,n){e.setHours(parseFloat(n))},i:function(e,n){e.setMinutes(parseFloat(n))},j:function(e,n){e.setDate(parseFloat(n))},l:p,m:function(e,n){e.setMonth(parseFloat(n)-1)},n:function(e,n){e.setMonth(parseFloat(n)-1)},s:function(e,n){e.setSeconds(parseFloat(n))},u:function(e,n){return new Date(parseFloat(n))},w:p,y:function(e,n){e.setFullYear(2e3+parseFloat(n))}},D={D:\"(\\\\w+)\",F:\"(\\\\w+)\",G:\"(\\\\d\\\\d|\\\\d)\",H:\"(\\\\d\\\\d|\\\\d)\",J:\"(\\\\d\\\\d|\\\\d)\\\\w+\",K:\"\",M:\"(\\\\w+)\",S:\"(\\\\d\\\\d|\\\\d)\",U:\"(.+)\",W:\"(\\\\d\\\\d|\\\\d)\",Y:\"(\\\\d{4})\",Z:\"(.+)\",d:\"(\\\\d\\\\d|\\\\d)\",h:\"(\\\\d\\\\d|\\\\d)\",i:\"(\\\\d\\\\d|\\\\d)\",j:\"(\\\\d\\\\d|\\\\d)\",l:\"(\\\\w+)\",m:\"(\\\\d\\\\d|\\\\d)\",n:\"(\\\\d\\\\d|\\\\d)\",s:\"(\\\\d\\\\d|\\\\d)\",u:\"(.+)\",w:\"(\\\\d\\\\d|\\\\d)\",y:\"(\\\\d{2})\"},w={Z:function(e){return e.toISOString()},D:function(e,n,t){return n.weekdays.shorthand[w.w(e,n,t)]},F:function(e,n,t){return h(w.n(e,n,t)-1,!1,n)},G:function(e,n,t){return o(w.h(e,n,t))},H:function(e){return o(e.getHours())},J:function(e,n){return void 0!==n.ordinal?e.getDate()+n.ordinal(e.getDate()):e.getDate()},K:function(e,n){return n.amPM[r(e.getHours()>11)]},M:function(e,n){return h(e.getMonth(),!0,n)},S:function(e){return 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n=g(e),t=V(n),a=n===w.input||n===w.altInput||w.element.contains(n)||e.path&&e.path.indexOf&&(~e.path.indexOf(w.input)||~e.path.indexOf(w.altInput)),i=\"blur\"===e.type?a&&e.relatedTarget&&!V(e.relatedTarget):!a&&!t&&!V(e.relatedTarget),o=!w.config.ignoredFocusElements.some((function(e){return e.contains(n)}));i&&o&&(void 0!==w.timeContainer&&void 0!==w.minuteElement&&void 0!==w.hourElement&&\"\"!==w.input.value&&void 0!==w.input.value&&T(),w.close(),w.config&&\"range\"===w.config.mode&&1===w.selectedDates.length&&(w.clear(!1),w.redraw()))}}function Q(e){if(!(!e||w.config.minDate&&ew.config.maxDate.getFullYear())){var n=e,t=w.currentYear!==n;w.currentYear=n||w.currentYear,w.config.maxDate&&w.currentYear===w.config.maxDate.getFullYear()?w.currentMonth=Math.min(w.config.maxDate.getMonth(),w.currentMonth):w.config.minDate&&w.currentYear===w.config.minDate.getFullYear()&&(w.currentMonth=Math.max(w.config.minDate.getMonth(),w.currentMonth)),t&&(w.redraw(),pe(\"onYearChange\"),K())}}function X(e,n){void 0===n&&(n=!0);var t=w.parseDate(e,void 0,n);if(w.config.minDate&&t&&M(t,w.config.minDate,void 0!==n?n:!w.minDateHasTime)<0||w.config.maxDate&&t&&M(t,w.config.maxDate,void 0!==n?n:!w.maxDateHasTime)>0)return!1;if(0===w.config.enable.length&&0===w.config.disable.length)return!0;if(void 0===t)return!1;for(var a=w.config.enable.length>0,i=a?w.config.enable:w.config.disable,o=0,r=void 0;o=r.from.getTime()&&t.getTime()<=r.to.getTime())return a}return!a}function ee(e){return void 0!==w.daysContainer&&-1===e.className.indexOf(\"hidden\")&&-1===e.className.indexOf(\"flatpickr-disabled\")&&w.daysContainer.contains(e)}function ne(e){e.target!==w._input||e.relatedTarget&&V(e.relatedTarget)||w.setDate(w._input.value,!0,e.target===w.altInput?w.config.altFormat:w.config.dateFormat)}function te(e){var n=g(e),t=w.config.wrap?p.contains(n):n===w._input,a=w.config.allowInput,i=w.isOpen&&(!a||!t),o=w.config.inline&&t&&!a;if(13===e.keyCode&&t){if(a)return 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d.AbstractRangeSliderView{}r.DatetimeRangeSliderView=_,_.__name__=\"DatetimeRangeSliderView\";class c extends d.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,t){return(0,o.isString)(t)?(0,s.default)(e,t):t.compute(e)}}r.DatetimeRangeSlider=c,n=c,c.__name__=\"DatetimeRangeSlider\",n.prototype.default_view=_,n.override({format:\"%d %b %Y %H:%M:%S\",step:36e5})},\n", - " 467: function _(e,t,s,r,i){var _;r();const n=e(468);class a extends n.MarkupView{render(){super.render(),this.model.render_as_text?this.markup_el.textContent=this.model.text:this.markup_el.innerHTML=this.has_math_disabled()?this.model.text:this.process_tex()}}s.DivView=a,a.__name__=\"DivView\";class d extends n.Markup{constructor(e){super(e)}}s.Div=d,_=d,d.__name__=\"Div\",_.prototype.default_view=a,_.define((({Boolean:e})=>({render_as_text:[e,!1]})))},\n", - " 468: function _(t,e,s,i,r){i();const a=t(1);var n;const o=t(210),d=t(43),h=t(137),l=t(512),_=(0,a.__importStar)(t(469));class u extends l.WidgetView{get provider(){return h.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>{this.contains_tex_string()&&this.rerender()}))}after_layout(){super.after_layout(),\"loading\"===this.provider.status&&(this._has_finished=!1)}rerender(){this.layout.invalidate_cache(),this.render(),this.root.compute_layout()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>{this.rerender()}))}styles(){return[...super.styles(),_.default]}_update_layout(){this.layout=new o.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render();const 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r.InputWidgetView{constructor(){super(...arguments),this._last_height=null}connect_signals(){super.connect_signals(),this.connect(this.model.properties.disabled.change,(()=>this.set_disabled()));const{value:e,max_items:t,option_limit:i,search_option_limit:l,delete_button:s,placeholder:o,options:n,name:h,title:a}=this.model.properties;this.on_change([e,t,i,l,s,o,n,h,a],(()=>this.render()))}styles(){return[...super.styles(),d.default]}_update_layout(){this.layout=new c.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render(),this.input_el=(0,a.select)({multiple:!0,class:_.input,name:this.model.name,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el);const e=new Set(this.model.value),t=this.model.options.map((t=>{let i,l;return(0,u.isString)(t)?i=l=t:[i,l]=t,{value:i,label:l,selected:e.has(i)}})),i=this.model.solid?\"solid\":\"light\",l=`choices__item ${i}`,s=`choices__button 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i=e.split(this.options.tokenSeparator),n=0,s=i.length;n0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1?arguments[1]:void 0,i=this.list,n={},s=[];if(\"string\"==typeof i[0]){for(var r=0,o=i.length;r1)throw new Error(\"Key weight has to be > 0 and <= 1\");p=p.name}else a[p]={weight:1};this._analyze({key:p,value:this.options.getFn(h,p),record:h,index:c},{resultMap:n,results:s,tokenSearchers:e,fullSearcher:t})}return{weights:a,results:s}}},{key:\"_analyze\",value:function(e,t){var i=e.key,n=e.arrayIndex,s=void 0===n?-1:n,r=e.value,o=e.record,c=e.index,l=t.tokenSearchers,h=void 0===l?[]:l,u=t.fullSearcher,d=void 0===u?[]:u,p=t.resultMap,m=void 0===p?{}:p,f=t.results,v=void 0===f?[]:f;if(null!=r){var g=!1,_=-1,b=0;if(\"string\"==typeof r){this._log(\"\\nKey: \".concat(\"\"===i?\"-\":i));var y=d.search(r);if(this._log('Full text: \"'.concat(r,'\", score: ').concat(y.score)),this.options.tokenize){for(var E=r.split(this.options.tokenSeparator),I=[],S=0;S-1&&(P=(P+_)/2),this._log(\"Score average:\",P);var D=!this.options.tokenize||!this.options.matchAllTokens||b>=h.length;if(this._log(\"\\nCheck Matches: \".concat(D)),(g||y.isMatch)&&D){var M=m[c];M?M.output.push({key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}):(m[c]={item:o,output:[{key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}]},v.push(m[c]))}}else if(a(r))for(var N=0,F=r.length;N-1&&(o.arrayIndex=r.arrayIndex),t.matches.push(o)}}})),this.options.includeScore&&s.push((function(e,t){t.score=e.score}));for(var r=0,o=e.length;ri)return s(e,this.pattern,n);var o=this.options,a=o.location,c=o.distance,l=o.threshold,h=o.findAllMatches,u=o.minMatchCharLength;return r(e,this.pattern,this.patternAlphabet,{location:a,distance:c,threshold:l,findAllMatches:h,minMatchCharLength:u})}}])&&n(t.prototype,i),a&&n(t,a),e}();e.exports=a},function(e,t){var i=/[\\-\\[\\]\\/\\{\\}\\(\\)\\*\\+\\?\\.\\\\\\^\\$\\|]/g;e.exports=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:/ +/g,s=new RegExp(t.replace(i,\"\\\\$&\").replace(n,\"|\")),r=e.match(s),o=!!r,a=[];if(o)for(var c=0,l=r.length;c=P;N-=1){var F=N-1,j=i[e.charAt(F)];if(j&&(E[F]=1),M[N]=(M[N+1]<<1|1)&j,0!==T&&(M[N]|=(O[N+1]|O[N])<<1|1|O[N+1]),M[N]&L&&(C=n(t,{errors:T,currentLocation:F,expectedLocation:v,distance:l}))<=_){if(_=C,(b=F)<=v)break;P=Math.max(1,2*v-b)}}if(n(t,{errors:T+1,currentLocation:v,expectedLocation:v,distance:l})>_)break;O=M}return{isMatch:b>=0,score:0===C?.001:C,matchedIndices:s(E,f)}}},function(e,t){e.exports=function(e,t){var i=t.errors,n=void 0===i?0:i,s=t.currentLocation,r=void 0===s?0:s,o=t.expectedLocation,a=void 0===o?0:o,c=t.distance,l=void 0===c?100:c,h=n/e.length,u=Math.abs(a-r);return l?h+u/l:u?1:h}},function(e,t){e.exports=function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,i=[],n=-1,s=-1,r=0,o=e.length;r=t&&i.push([n,s]),n=-1)}return e[r-1]&&r-n>=t&&i.push([n,r-1]),i}},function(e,t){e.exports=function(e){for(var t={},i=e.length,n=0;n/g,\"&rt;\").replace(/-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!0),i})):e;case\"REMOVE_ITEM\":return t.choiceId>-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!1),i})):e;case\"FILTER_CHOICES\":return e.map((function(e){var i=e;return i.active=t.results.some((function(e){var t=e.item,n=e.score;return t.id===i.id&&(i.score=n,!0)})),i}));case\"ACTIVATE_CHOICES\":return e.map((function(e){var i=e;return i.active=t.active,i}));case\"CLEAR_CHOICES\":return v;default:return e}},general:_}),A=function(e,t){var i=e;if(\"CLEAR_ALL\"===t.type)i=void 0;else if(\"RESET_TO\"===t.type)return O(t.state);return C(i,t)};function L(e,t){for(var i=0;i\"'+I(e)+'\"'},maxItemText:function(e){return\"Only \"+e+\" values can be added\"},valueComparer:function(e,t){return e===t},fuseOptions:{includeScore:!0},callbackOnInit:null,callbackOnCreateTemplates:null,classNames:{containerOuter:\"choices\",containerInner:\"choices__inner\",input:\"choices__input\",inputCloned:\"choices__input--cloned\",list:\"choices__list\",listItems:\"choices__list--multiple\",listSingle:\"choices__list--single\",listDropdown:\"choices__list--dropdown\",item:\"choices__item\",itemSelectable:\"choices__item--selectable\",itemDisabled:\"choices__item--disabled\",itemChoice:\"choices__item--choice\",placeholder:\"choices__placeholder\",group:\"choices__group\",groupHeading:\"choices__heading\",button:\"choices__button\",activeState:\"is-active\",focusState:\"is-focused\",openState:\"is-open\",disabledState:\"is-disabled\",highlightedState:\"is-highlighted\",selectedState:\"is-selected\",flippedState:\"is-flipped\",loadingState:\"is-loading\",noResults:\"has-no-results\",noChoices:\"has-no-choices\"}},D=\"showDropdown\",M=\"hideDropdown\",N=\"change\",F=\"choice\",j=\"search\",K=\"addItem\",R=\"removeItem\",H=\"highlightItem\",B=\"highlightChoice\",V=\"ADD_CHOICE\",G=\"FILTER_CHOICES\",q=\"ACTIVATE_CHOICES\",U=\"CLEAR_CHOICES\",z=\"ADD_GROUP\",W=\"ADD_ITEM\",X=\"REMOVE_ITEM\",$=\"HIGHLIGHT_ITEM\",J=46,Y=8,Z=13,Q=65,ee=27,te=38,ie=40,ne=33,se=34,re=\"text\",oe=\"select-one\",ae=\"select-multiple\",ce=function(){function e(e){var t=e.element,i=e.type,n=e.classNames,s=e.position;this.element=t,this.classNames=n,this.type=i,this.position=s,this.isOpen=!1,this.isFlipped=!1,this.isFocussed=!1,this.isDisabled=!1,this.isLoading=!1,this._onFocus=this._onFocus.bind(this),this._onBlur=this._onBlur.bind(this)}var t=e.prototype;return t.addEventListeners=function(){this.element.addEventListener(\"focus\",this._onFocus),this.element.addEventListener(\"blur\",this._onBlur)},t.removeEventListeners=function(){this.element.removeEventListener(\"focus\",this._onFocus),this.element.removeEventListener(\"blur\",this._onBlur)},t.shouldFlip=function(e){if(\"number\"!=typeof e)return!1;var t=!1;return\"auto\"===this.position?t=!window.matchMedia(\"(min-height: \"+(e+1)+\"px)\").matches:\"top\"===this.position&&(t=!0),t},t.setActiveDescendant=function(e){this.element.setAttribute(\"aria-activedescendant\",e)},t.removeActiveDescendant=function(){this.element.removeAttribute(\"aria-activedescendant\")},t.open=function(e){this.element.classList.add(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"true\"),this.isOpen=!0,this.shouldFlip(e)&&(this.element.classList.add(this.classNames.flippedState),this.isFlipped=!0)},t.close=function(){this.element.classList.remove(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"false\"),this.removeActiveDescendant(),this.isOpen=!1,this.isFlipped&&(this.element.classList.remove(this.classNames.flippedState),this.isFlipped=!1)},t.focus=function(){this.isFocussed||this.element.focus()},t.addFocusState=function(){this.element.classList.add(this.classNames.focusState)},t.removeFocusState=function(){this.element.classList.remove(this.classNames.focusState)},t.enable=function(){this.element.classList.remove(this.classNames.disabledState),this.element.removeAttribute(\"aria-disabled\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"0\"),this.isDisabled=!1},t.disable=function(){this.element.classList.add(this.classNames.disabledState),this.element.setAttribute(\"aria-disabled\",\"true\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"-1\"),this.isDisabled=!0},t.wrap=function(e){!function(e,t){void 0===t&&(t=document.createElement(\"div\")),e.nextSibling?e.parentNode.insertBefore(t,e.nextSibling):e.parentNode.appendChild(t),t.appendChild(e)}(e,this.element)},t.unwrap=function(e){this.element.parentNode.insertBefore(e,this.element),this.element.parentNode.removeChild(this.element)},t.addLoadingState=function(){this.element.classList.add(this.classNames.loadingState),this.element.setAttribute(\"aria-busy\",\"true\"),this.isLoading=!0},t.removeLoadingState=function(){this.element.classList.remove(this.classNames.loadingState),this.element.removeAttribute(\"aria-busy\"),this.isLoading=!1},t._onFocus=function(){this.isFocussed=!0},t._onBlur=function(){this.isFocussed=!1},e}();function le(e,t){for(var i=0;i0?this.element.scrollTop+o-s:e.offsetTop;requestAnimationFrame((function(){i._animateScroll(a,t)}))}},t._scrollDown=function(e,t,i){var n=(i-e)/t,s=n>1?n:1;this.element.scrollTop=e+s},t._scrollUp=function(e,t,i){var n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function de(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},be=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ye=function(e,t){return{type:$,id:e,highlighted:t}},Ee=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},Ie=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function Se(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ye(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ye(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(be(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(be(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(be(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1,p=\"[data-choice-selectable]\";if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(p);else{var m=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=m?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(m,p,d):this.dropdown.element.querySelector(p)}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(we&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(Ee({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(Ee({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;r{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value})),this.connect(this.model.properties.low.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&e{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&e>l&&(this.model.value=l)})),this.connect(this.model.properties.high.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder))}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",(()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}}))}render(){super.render(),this.input_el=(0,r.input)({type:\"text\",class:_.input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.input_el.addEventListener(\"focusout\",(()=>this.input_el.value=this.format_value)),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter((e=>m.test(e))):\"float\"==this.model.mode&&this._set_input_filter((e=>c.test(e)))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!=this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=v,v.__name__=\"NumericInputView\";class g extends o.InputWidget{constructor(e){super(e)}_formatter(e,t){return(0,d.isString)(t)?h.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):`${e}`}}l.NumericInput=g,u=g,g.__name__=\"NumericInput\",u.prototype.default_view=v,u.define((({Number:e,String:t,Enum:l,Ref:i,Or:n,Nullable:s})=>({value:[s(e),null],placeholder:[t,\"\"],mode:[l(\"int\",\"float\"),\"int\"],format:[s(n(t,i(a.TickFormatter))),null],low:[s(e),null],high:[s(e),null]})))},\n", - " 479: function _(e,t,r,s,n){var a;s();const o=e(468),_=e(43);class p extends o.MarkupView{render(){super.render();const e=(0,_.pre)({style:{overflow:\"auto\"}},this.model.text);this.markup_el.appendChild(e)}}r.PreTextView=p,p.__name__=\"PreTextView\";class u extends o.Markup{constructor(e){super(e)}}r.PreText=u,a=u,u.__name__=\"PreText\",a.prototype.default_view=p},\n", - " 480: function _(t,o,e,a,i){a();const n=t(1);var u;const s=t(452),c=t(43),_=(0,n.__importStar)(t(318));class r extends s.ButtonGroupView{change_active(t){this.model.active!==t&&(this.model.active=t)}_update_active(){const{active:t}=this.model;this._buttons.forEach(((o,e)=>{(0,c.classes)(o).toggle(_.active,t===e)}))}}e.RadioButtonGroupView=r,r.__name__=\"RadioButtonGroupView\";class l extends s.ButtonGroup{constructor(t){super(t)}}e.RadioButtonGroup=l,u=l,l.__name__=\"RadioButtonGroup\",u.prototype.default_view=r,u.define((({Int:t,Nullable:o})=>({active:[o(t),null]})))},\n", - " 481: function _(e,n,i,t,a){t();const s=e(1);var l;const o=e(43),d=e(34),p=e(455),r=(0,s.__importStar)(e(449));class u extends p.InputGroupView{render(){super.render();const e=(0,o.div)({class:[r.input_group,this.model.inline?r.inline:null]});this.el.appendChild(e);const n=(0,d.uniqueId)(),{active:i,labels:t}=this.model;this._inputs=[];for(let a=0;athis.change_active(a))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),a==i&&(s.checked=!0);const l=(0,o.label)(s,(0,o.span)(t[a]));e.appendChild(l)}}change_active(e){this.model.active=e}}i.RadioGroupView=u,u.__name__=\"RadioGroupView\";class c extends p.InputGroup{constructor(e){super(e)}}i.RadioGroup=c,l=c,c.__name__=\"RadioGroup\",l.prototype.default_view=u,l.define((({Boolean:e,Int:n,String:i,Array:t,Nullable:a})=>({active:[a(n),null],labels:[t(i),[]],inline:[e,!1]})))},\n", - " 482: function _(e,r,t,a,i){a();var n;const o=(0,e(1).__importStar)(e(153)),s=e(461),_=e(8);class d extends s.AbstractRangeSliderView{}t.RangeSliderView=d,d.__name__=\"RangeSliderView\";class c extends s.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,r){return(0,_.isString)(r)?o.format(e,r):r.compute(e)}}t.RangeSlider=c,n=c,c.__name__=\"RangeSlider\",n.prototype.default_view=d,n.override({format:\"0[.]00\"})},\n", - " 483: function _(e,t,n,s,i){s();const l=e(1);var u;const a=e(43),o=e(8),p=e(13),_=e(448),r=(0,l.__importStar)(e(449));class c extends _.InputWidgetView{constructor(){super(...arguments),this._known_values=new Set}connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,(()=>{this._update_value()})),this.on_change(t,(()=>{(0,a.empty)(this.input_el),(0,a.append)(this.input_el,...this.options_el()),this._update_value()}))}options_el(){const{_known_values:e}=this;function t(t){return t.map((t=>{let n,s;return(0,o.isString)(t)?n=s=t:[n,s]=t,e.add(n),(0,a.option)({value:n},s)}))}e.clear();const{options:n}=this.model;return(0,o.isArray)(n)?t(n):(0,p.entries)(n).map((([e,n])=>(0,a.optgroup)({label:e},t(n))))}render(){super.render(),this.input_el=(0,a.select)({class:r.input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;this._known_values.has(e)?this.input_el.value=e:this.input_el.removeAttribute(\"value\")}}n.SelectView=c,c.__name__=\"SelectView\";class h extends _.InputWidget{constructor(e){super(e)}}n.Select=h,u=h,h.__name__=\"Select\",u.prototype.default_view=c,u.define((({String:e,Array:t,Tuple:n,Dict:s,Or:i})=>{const l=t(i(e,n(e,e)));return{value:[e,\"\"],options:[i(l,s(l)),[]]}}))},\n", - " 484: function _(e,t,r,i,a){i();var o;const s=(0,e(1).__importStar)(e(153)),_=e(461),n=e(8);class c extends _.AbstractSliderView{}r.SliderView=c,c.__name__=\"SliderView\";class d extends _.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}_formatter(e,t){return(0,n.isString)(t)?s.format(e,t):t.compute(e)}}r.Slider=d,o=d,d.__name__=\"Slider\",o.prototype.default_view=c,o.override({format:\"0[.]00\"})},\n", - " 485: function _(e,t,i,n,s){var l;n();const o=e(478),r=e(43),{min:a,max:h,floor:_,abs:u}=Math;function d(e){return _(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class p extends o.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._handles={interval:void 0,timeout:void 0},this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,(()=>{for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled)}))}render(){super.render(),this.wrapper_el=(0,r.div)({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",(e=>this._btn_mouse_down(e))),e.addEventListener(\"mouseup\",(()=>this._btn_mouse_up())),e.addEventListener(\"mouseleave\",(()=>this._btn_mouse_leave()));this.input_el.addEventListener(\"keydown\",(e=>this._input_key_down(e))),this.input_el.addEventListener(\"keyup\",(()=>this.model.value_throttled=this.model.value)),this.input_el.addEventListener(\"wheel\",(e=>this._input_mouse_wheel(e))),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,o=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),o&&e.apply(l,s)}}((()=>{this.model.value_throttled=this.model.value}),this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model,n=d;return h(n(u(null!=e?e:0)),n(u(null!=t?t:0)),n(u(i)))}remove(){this._stop_incrementation(),super.remove()}_start_incrementation(e){clearInterval(this._handles.interval),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(e)),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(2*e)),this._interval/10))}this.increment(e)};this._handles.interval=setInterval((()=>i(e*t)),this._interval)}_stop_incrementation(){clearTimeout(this._handles.timeout),this._handles.timeout=void 0,clearInterval(this._handles.interval),this._handles.interval=void 0,this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._handles.timeout=setTimeout((()=>this._start_incrementation(t)),this._interval)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case r.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case r.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case r.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case r.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?a(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?h(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=p,p.__name__=\"SpinnerView\";class m extends o.NumericInput{constructor(e){super(e)}}i.Spinner=m,l=m,m.__name__=\"Spinner\",l.prototype.default_view=p,l.define((({Number:e,Nullable:t})=>({value_throttled:[t(e),null],step:[e,1],page_step_multiplier:[e,10],wheel_wait:[e,100]}))),l.override({mode:\"float\"})},\n", - " 486: function _(e,t,s,n,i){n();const o=e(1);var r;const c=e(447),l=e(43),p=(0,o.__importStar)(e(449));class _ extends c.TextLikeInputView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.rows.change,(()=>this.input_el.rows=this.model.rows)),this.connect(this.model.properties.cols.change,(()=>this.input_el.cols=this.model.cols))}_render_input(){this.input_el=(0,l.textarea)({class:p.input})}render(){super.render(),this.input_el.cols=this.model.cols,this.input_el.rows=this.model.rows}}s.TextAreaInputView=_,_.__name__=\"TextAreaInputView\";class a extends c.TextLikeInput{constructor(e){super(e)}}s.TextAreaInput=a,r=a,a.__name__=\"TextAreaInput\",r.prototype.default_view=_,r.define((({Int:e})=>({cols:[e,20],rows:[e,2]}))),r.override({max_length:500})},\n", - " 487: function _(e,t,s,c,i){c();const o=e(1);var a;const n=e(441),l=e(43),_=(0,o.__importStar)(e(318));class r extends n.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._update_active()))}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){(0,l.classes)(this.button_el).toggle(_.active,this.model.active)}}s.ToggleView=r,r.__name__=\"ToggleView\";class g extends n.AbstractButton{constructor(e){super(e)}}s.Toggle=g,a=g,g.__name__=\"Toggle\",a.prototype.default_view=r,a.define((({Boolean:e})=>({active:[e,!1]}))),a.override({label:\"Toggle\"})},\n", - " }, 439, {\"models/widgets/main\":439,\"models/widgets/index\":440,\"models/widgets/abstract_button\":441,\"models/widgets/control\":442,\"models/widgets/widget\":512,\"models/widgets/abstract_icon\":444,\"models/widgets/autocomplete_input\":445,\"models/widgets/text_input\":446,\"models/widgets/text_like_input\":447,\"models/widgets/input_widget\":448,\"styles/widgets/inputs.css\":449,\"models/widgets/button\":450,\"models/widgets/checkbox_button_group\":451,\"models/widgets/button_group\":452,\"models/widgets/oriented_control\":453,\"models/widgets/checkbox_group\":454,\"models/widgets/input_group\":455,\"models/widgets/color_picker\":456,\"models/widgets/date_picker\":457,\"styles/widgets/flatpickr.css\":459,\"models/widgets/date_range_slider\":460,\"models/widgets/abstract_slider\":461,\"styles/widgets/sliders.css\":463,\"styles/widgets/nouislider.css\":464,\"models/widgets/date_slider\":465,\"models/widgets/datetime_range_slider\":466,\"models/widgets/div\":467,\"models/widgets/markup\":468,\"styles/clearfix.css\":469,\"models/widgets/dropdown\":470,\"models/widgets/file_input\":471,\"models/widgets/multiselect\":472,\"models/widgets/paragraph\":473,\"models/widgets/password_input\":474,\"models/widgets/multichoice\":475,\"styles/widgets/choices.css\":477,\"models/widgets/numeric_input\":478,\"models/widgets/pretext\":479,\"models/widgets/radio_button_group\":480,\"models/widgets/radio_group\":481,\"models/widgets/range_slider\":482,\"models/widgets/selectbox\":483,\"models/widgets/slider\":484,\"models/widgets/spinner\":485,\"models/widgets/textarea_input\":486,\"models/widgets/toggle\":487}, {});});\n", - "\n", - " /* END bokeh-widgets.min.js */\n", - " },\n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-tables.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2022, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.4.3\");\n", - " })(this, function(Bokeh, version) {\n", - " let define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 488: function _(t,e,o,r,s){r();const _=(0,t(1).__importStar)(t(489));o.Tables=_;(0,t(7).register_models)(_)},\n", - " 489: function _(g,a,r,e,t){e();const o=g(1);(0,o.__exportStar)(g(490),r),(0,o.__exportStar)(g(493),r),t(\"DataTable\",g(496).DataTable),t(\"TableColumn\",g(514).TableColumn),t(\"TableWidget\",g(513).TableWidget);var n=g(516);t(\"AvgAggregator\",n.AvgAggregator),t(\"MinAggregator\",n.MinAggregator),t(\"MaxAggregator\",n.MaxAggregator),t(\"SumAggregator\",n.SumAggregator);var A=g(517);t(\"GroupingInfo\",A.GroupingInfo),t(\"DataCube\",A.DataCube)},\n", - " 490: function _(e,t,i,s,a){s();const r=e(1);var l,n,u,d,o,p,_,c,h;const E=e(43),V=e(226),m=e(53),f=e(491),v=(0,r.__importStar)(e(492));class w extends V.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(v.cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",(e=>{switch(e.keyCode){case E.Keys.Left:case E.Keys.Right:case E.Keys.Up:case E.Keys.Down:case E.Keys.PageUp:case E.Keys.PageDown:e.stopImmediatePropagation()}}))}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[f.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=w,w.__name__=\"CellEditorView\";class g extends m.Model{}i.CellEditor=g,g.__name__=\"CellEditor\";class x extends w{get emptyValue(){return\"\"}_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=x,x.__name__=\"StringEditorView\";class y extends g{}i.StringEditor=y,l=y,y.__name__=\"StringEditor\",l.prototype.default_view=x,l.define((({String:e,Array:t})=>({completions:[t(e),[]]})));class I extends w{_createInput(){return(0,E.textarea)()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=I,I.__name__=\"TextEditorView\";class b extends g{}i.TextEditor=b,n=b,b.__name__=\"TextEditor\",n.prototype.default_view=I;class N extends w{_createInput(){return(0,E.select)()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild((0,E.option)({value:e},e));this.focus()}}i.SelectEditorView=N,N.__name__=\"SelectEditorView\";class C extends g{}i.SelectEditor=C,u=C,C.__name__=\"SelectEditor\",u.prototype.default_view=N,u.define((({String:e,Array:t})=>({options:[t(e),[]]})));class D extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.PercentEditorView=D,D.__name__=\"PercentEditorView\";class S extends g{}i.PercentEditor=S,d=S,S.__name__=\"PercentEditor\",d.prototype.default_view=D;class k extends w{_createInput(){return(0,E.input)({type:\"checkbox\"})}renderEditor(){this.focus()}loadValue(e){this.defaultValue=!!e[this.args.column.field],this.inputEl.checked=this.defaultValue}serializeValue(){return this.inputEl.checked}}i.CheckboxEditorView=k,k.__name__=\"CheckboxEditorView\";class z extends g{}i.CheckboxEditor=z,o=z,z.__name__=\"CheckboxEditor\",o.prototype.default_view=k;class P extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseInt(this.getValue(),10))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid integer\"}:super.validateValue(e)}}i.IntEditorView=P,P.__name__=\"IntEditorView\";class T extends g{}i.IntEditor=T,p=T,T.__name__=\"IntEditor\",p.prototype.default_view=P,p.define((({Int:e})=>({step:[e,1]})));class K extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseFloat(this.getValue()))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid number\"}:super.validateValue(e)}}i.NumberEditorView=K,K.__name__=\"NumberEditorView\";class A extends g{}i.NumberEditor=A,_=A,A.__name__=\"NumberEditor\",_.prototype.default_view=K,_.define((({Number:e})=>({step:[e,.01]})));class M extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.TimeEditorView=M,M.__name__=\"TimeEditorView\";class O extends g{}i.TimeEditor=O,c=O,O.__name__=\"TimeEditor\",c.prototype.default_view=M;class F extends 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require([\"gridstack\"], function(GridStack) {\n", - "\twindow.GridStack = GridStack\n", - "\ton_load()\n", - " })\n", - " require([\"notyf\"], function() {\n", - "\ton_load()\n", - " })\n", - " root._bokeh_is_loading = css_urls.length + 2;\n", - " } else {\n", - " root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length;\n", - " } if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/gridstack/gridstack@4.2.5/dist/gridstack-h5.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n", - " var urls = ['https://cdn.holoviz.org/panel/0.14.3/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n", - " for (var i = 0; i < urls.length; i++) {\n", - " skip.push(urls[i])\n", - " }\n", - " } for (var i = 0; i < js_urls.length; i++) {\n", - " var url = js_urls[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " for (var i = 0; i < js_modules.length; i++) {\n", - " var url = js_modules[i];\n", - " if (skip.indexOf(url) >= 0) {\n", - "\tif (!window.requirejs) {\n", - "\t on_load();\n", - "\t}\n", - "\tcontinue;\n", - " }\n", - " var element = document.createElement('script');\n", - " element.onload = on_load;\n", - " element.onerror = on_error;\n", - " element.async = false;\n", - " element.src = url;\n", - " element.type = \"module\";\n", - " console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n", - " document.head.appendChild(element);\n", - " }\n", - " if (!js_urls.length && !js_modules.length) {\n", - " on_load()\n", + "attribute vec3 position;\n", + "attribute vec4 color;\n", + "attribute vec2 glyph;\n", + "attribute vec4 id;\n", + "\n", + "uniform mat4 model, view, projection;\n", + "uniform vec2 screenSize;\n", + "uniform vec3 clipBounds[2];\n", + "uniform float highlightScale, pixelRatio;\n", + "uniform vec4 highlightId;\n", + "\n", + "varying vec4 interpColor;\n", + "varying vec4 pickId;\n", + "varying vec3 dataCoordinate;\n", + "\n", + "void main() {\n", + " if (outOfRange(clipBounds[0], clipBounds[1], position)) {\n", + "\n", + " gl_Position = vec4(0,0,0,0);\n", + " } else {\n", + " float scale = pixelRatio;\n", + " if(distance(highlightId.bgr, id.bgr) < 0.001) {\n", + " scale *= highlightScale;\n", " }\n", - " };\n", "\n", - " function inject_raw_css(css) {\n", - " const element = document.createElement(\"style\");\n", - " element.appendChild(document.createTextNode(css));\n", - " document.body.appendChild(element);\n", + " vec4 worldPosition = model * vec4(position, 1.0);\n", + " vec4 viewPosition = view * worldPosition;\n", + " vec4 clipPosition = projection * viewPosition;\n", + " clipPosition /= clipPosition.w;\n", + "\n", + " gl_Position = clipPosition + vec4(screenSize * scale * vec2(glyph.x, -glyph.y), 0.0, 0.0);\n", + " interpColor = color;\n", + " pickId = id;\n", + " dataCoordinate = position;\n", " }\n", + "}`]),f=l([`precision highp float;\n", + "#define GLSLIFY 1\n", + "\n", + "bool outOfRange(float a, float b, float p) {\n", + " return ((p > max(a, b)) || \n", + " (p < min(a, b)));\n", + "}\n", + "\n", + "bool outOfRange(vec2 a, vec2 b, vec2 p) {\n", + " return (outOfRange(a.x, b.x, p.x) ||\n", + " outOfRange(a.y, b.y, p.y));\n", + "}\n", + "\n", + "bool outOfRange(vec3 a, vec3 b, vec3 p) {\n", + " return (outOfRange(a.x, b.x, p.x) ||\n", + " outOfRange(a.y, b.y, p.y) ||\n", + " outOfRange(a.z, b.z, p.z));\n", + "}\n", + "\n", + "bool outOfRange(vec4 a, vec4 b, vec4 p) {\n", + " return outOfRange(a.xyz, b.xyz, p.xyz);\n", + "}\n", + "\n", + "attribute vec3 position;\n", + "attribute vec4 color;\n", + "attribute vec2 glyph;\n", + "attribute vec4 id;\n", + "\n", + "uniform float highlightScale;\n", + "uniform vec4 highlightId;\n", + "uniform vec3 axes[2];\n", + "uniform mat4 model, view, projection;\n", + "uniform vec2 screenSize;\n", + "uniform vec3 clipBounds[2];\n", + "uniform float scale, pixelRatio;\n", "\n", - " var js_urls = [];\n", - " var js_modules = [];\n", - " var css_urls = [];\n", - " var inline_js = [ function(Bokeh) {\n", - " inject_raw_css(\".bk.debugger-card {\\n border: 1px solid rgba(0,0,0,1);\\n color: rgba(255,255,255,1);\\n background-color: rgba(0,0,0,1);\\n border-radius: 0rem;\\n}\\n.bk.debugger-card-header {\\n align-items: center;\\n text-align: left;\\n background-color: rgba(0, 0, 0, 1)!important;\\n color: rgba(255, 255, 255, 1);\\n border-radius: 0rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.debugger-card-button {\\n background-color: transparent;\\n color: rgba(255, 255, 255, 1);\\n margin-left: 0.5em;\\n}\\n.bk.debugger-card-title {\\n align-items: center;\\n text-align: left;\\n color: rgba(255, 255, 255, 1);\\n font-size: 1em;\\n overflow-wrap: break-word;\\n}\\n\\n/* Special debugger buttons for clearing and saving */\\n.bk button.special_btn {\\n width: 25px;\\n height: 25px;\\n background-color: black;\\n color: white;\\n display: inline-block;\\n}\\n\\n\\n.bk button.special_btn .tooltiptext {\\n visibility: hidden;\\n width: 100px;\\n background-color: darkgray;\\n color: #fff;\\n text-align: center;\\n border-radius: 6px;\\n padding: 5px 0;\\n\\n /* Position the tooltip */\\n position: relative;\\n z-index: 1;\\n top: 100%;\\n left: 100%;\\n margin-left: -100px;\\n display: block;\\n}\\n\\n.bk button.special_btn:hover .tooltiptext {\\n visibility: visible;\\n}\\n\\n\\n\\n.bk button.clear_btn:hover .shown { display: none;}\\n.bk button.clear_btn:hover:before { content: \\\"\\u2611\\\"; }\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.alert {\\n padding: 0.75rem 1.25rem;\\n border: 1px solid transparent;\\n border-radius: 0.25rem;\\n /* Don't set margin because that will not render correctly! */\\n /* margin-bottom: 1rem; */\\n margin-top: 15px;\\n margin-bottom: 15px;\\n}\\n.bk.alert a {\\n color: rgb(11, 46, 19); /* #002752; */\\n font-weight: 700;\\n text-decoration: rgb(11, 46, 19);\\n text-decoration-color: rgb(11, 46, 19);\\n text-decoration-line: none;\\n text-decoration-style: solid;\\n text-decoration-thickness: auto;\\n }\\n.bk.alert a:hover {\\n color: rgb(11, 46, 19);\\n font-weight: 700;\\n text-decoration: underline;\\n}\\n\\n.bk.alert-primary {\\n color: #004085;\\n background-color: #cce5ff;\\n border-color: #b8daff;\\n}\\n.bk.alert-primary hr {\\n border-top-color: #9fcdff;\\n}\\n\\n.bk.alert-secondary {\\n color: #383d41;\\n background-color: #e2e3e5;\\n border-color: #d6d8db;\\n }\\n.bk.alert-secondary hr {\\n border-top-color: #c8cbcf;\\n}\\n\\n.bk.alert-success {\\n color: #155724;\\n background-color: #d4edda;\\n border-color: #c3e6cb;\\n }\\n\\n.bk.alert-success hr {\\n border-top-color: #b1dfbb;\\n}\\n\\n.bk.alert-info {\\n color: #0c5460;\\n background-color: #d1ecf1;\\n border-color: #bee5eb;\\n }\\n.bk.alert-info hr {\\n border-top-color: #abdde5;\\n}\\n\\n.bk.alert-warning {\\n color: #856404;\\n background-color: #fff3cd;\\n border-color: #ffeeba;\\n }\\n\\n.bk.alert-warning hr {\\n border-top-color: #ffe8a1;\\n}\\n\\n.bk.alert-danger {\\n color: #721c24;\\n background-color: #f8d7da;\\n border-color: #f5c6cb;\\n}\\n.bk.alert-danger hr {\\n border-top-color: #f1b0b7;\\n}\\n\\n.bk.alert-light {\\n color: #818182;\\n background-color: #fefefe;\\n border-color: #fdfdfe;\\n }\\n.bk.alert-light hr {\\n border-top-color: #ececf6;\\n}\\n\\n.bk.alert-dark {\\n color: #1b1e21;\\n background-color: #d6d8d9;\\n border-color: #c6c8ca;\\n }\\n.bk.alert-dark hr {\\n border-top-color: #b9bbbe;\\n}\\n\\n\\n/* adjf\\u00e6l */\\n\\n.bk.alert-primary a {\\n color: #002752;\\n}\\n\\n.bk.alert-secondary a {\\n color: #202326;\\n}\\n\\n\\n.bk.alert-success a {\\n color: #0b2e13;\\n}\\n\\n\\n.bk.alert-info a {\\n color: #062c33;\\n}\\n\\n\\n.bk.alert-warning a {\\n color: #533f03;\\n}\\n\\n\\n.bk.alert-danger a {\\n color: #491217;\\n}\\n\\n.bk.alert-light a {\\n color: #686868;\\n}\\n\\n.bk.alert-dark a {\\n color: #040505;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.card {\\n border: 1px solid rgba(0,0,0,.125);\\n border-radius: 0.25rem;\\n}\\n.bk.accordion {\\n border: 1px solid rgba(0,0,0,.125);\\n}\\n.bk.card-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0.25rem;\\n display: inline-flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.accordion-header {\\n align-items: center;\\n background-color: rgba(0, 0, 0, 0.03);\\n border-radius: 0;\\n display: flex;\\n justify-content: start;\\n width: 100%;\\n}\\n.bk.card-button {\\n background-color: transparent;\\n margin-left: 0.5em;\\n}\\n.bk.card-header-row {\\n position: relative !important;\\n}\\n.bk.card-title {\\n align-items: center;\\n font-size: 1.4em;\\n font-weight: bold;\\n overflow-wrap: break-word;\\n}\\n.bk.card-header-row > .bk {\\n overflow-wrap: break-word;\\n text-align: center;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.panel-widget-box {\\n min-height: 20px;\\n background-color: #f5f5f5;\\n border: 1px solid #e3e3e3;\\n border-radius: 4px;\\n -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n box-shadow: inset 0 1px 1px rgba(0,0,0,.05);\\n overflow-x: hidden;\\n overflow-y: hidden;\\n}\\n\\n.scrollable {\\n overflow: scroll;\\n}\\n\\nprogress {\\n appearance: none;\\n -moz-appearance: none;\\n -webkit-appearance: none;\\n border: none;\\n height: 20px;\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n color: royalblue;\\n position: relative;\\n margin: 0 0 1.5em;\\n}\\n\\nprogress[value]::-webkit-progress-bar {\\n background-color: whiteSmoke;\\n border-radius: 3px;\\n box-shadow: 0 2px 3px rgba(0,0,0,.5) inset;\\n}\\n\\nprogress[value]::-webkit-progress-value {\\n position: relative;\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress.active:not([value])::before {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress[value]::-moz-progress-bar {\\n background-size: 35px 20px, 100% 100%, 100% 100%;\\n border-radius:3px;\\n}\\n\\nprogress:not([value])::-moz-progress-bar {\\n border-radius:3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\nprogress.active:not([value])::-moz-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.active:not([value])::-webkit-progress-bar {\\n background-position: 10%;\\n animation-name: stripes;\\n animation-duration: 3s;\\n animation-timing-function: linear;\\n animation-iteration-count: infinite;\\n}\\n\\nprogress.primary[value]::-webkit-progress-value { background-color: #007bff; }\\nprogress.primary:not([value])::before { background-color: #007bff; }\\nprogress.primary:not([value])::-webkit-progress-bar { background-color: #007bff; }\\nprogress.primary::-moz-progress-bar { background-color: #007bff; }\\n\\nprogress.secondary[value]::-webkit-progress-value { background-color: #6c757d; }\\nprogress.secondary:not([value])::before { background-color: #6c757d; }\\nprogress.secondary:not([value])::-webkit-progress-bar { background-color: #6c757d; }\\nprogress.secondary::-moz-progress-bar { background-color: #6c757d; }\\n\\nprogress.success[value]::-webkit-progress-value { background-color: #28a745; }\\nprogress.success:not([value])::before { background-color: #28a745; }\\nprogress.success:not([value])::-webkit-progress-bar { background-color: #28a745; }\\nprogress.success::-moz-progress-bar { background-color: #28a745; }\\n\\nprogress.danger[value]::-webkit-progress-value { background-color: #dc3545; }\\nprogress.danger:not([value])::before { background-color: #dc3545; }\\nprogress.danger:not([value])::-webkit-progress-bar { background-color: #dc3545; }\\nprogress.danger::-moz-progress-bar { background-color: #dc3545; }\\n\\nprogress.warning[value]::-webkit-progress-value { background-color: #ffc107; }\\nprogress.warning:not([value])::before { background-color: #ffc107; }\\nprogress.warning:not([value])::-webkit-progress-bar { background-color: #ffc107; }\\nprogress.warning::-moz-progress-bar { background-color: #ffc107; }\\n\\nprogress.info[value]::-webkit-progress-value { background-color: #17a2b8; }\\nprogress.info:not([value])::before { background-color: #17a2b8; }\\nprogress.info:not([value])::-webkit-progress-bar { background-color: #17a2b8; }\\nprogress.info::-moz-progress-bar { background-color: #17a2b8; }\\n\\nprogress.light[value]::-webkit-progress-value { background-color: #f8f9fa; }\\nprogress.light:not([value])::before { background-color: #f8f9fa; }\\nprogress.light:not([value])::-webkit-progress-bar { background-color: #f8f9fa; }\\nprogress.light::-moz-progress-bar { background-color: #f8f9fa; }\\n\\nprogress.dark[value]::-webkit-progress-value { background-color: #343a40; }\\nprogress.dark:not([value])::-webkit-progress-bar { background-color: #343a40; }\\nprogress.dark:not([value])::before { background-color: #343a40; }\\nprogress.dark::-moz-progress-bar { background-color: #343a40; }\\n\\nprogress:not([value])::-webkit-progress-bar {\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\nprogress:not([value])::before {\\n content:\\\" \\\";\\n position:absolute;\\n height: 20px;\\n top:0;\\n left:0;\\n right:0;\\n bottom:0;\\n border-radius: 3px;\\n background: linear-gradient(-45deg, transparent 33%, rgba(0, 0, 0, 0.2) 33%, rgba(0, 0, 0, 0.2) 66%, transparent 66%) left/2.5em 1.5em;\\n}\\n\\n@keyframes stripes {\\n from {background-position: 0%}\\n to {background-position: 100%}\\n}\\n\\n.bk-root .bk.loader {\\n overflow: hidden;\\n}\\n\\n.bk.loader::after {\\n content: \\\"\\\";\\n border-radius: 50%;\\n -webkit-mask-image: radial-gradient(transparent 50%, rgba(0, 0, 0, 1) 54%);\\n width: 100%;\\n height: 100%;\\n left: 0;\\n top: 0;\\n position: absolute;\\n}\\n\\n.bk-root .bk.loader.dark::after {\\n background: #0f0f0f;\\n}\\n\\n.bk-root .bk.loader.light::after {\\n background: #f0f0f0;\\n}\\n\\n.bk-root .bk.loader.spin::after {\\n animation: spin 2s linear infinite;\\n}\\n\\n.bk-root div.bk.loader.spin.primary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #dc3545 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.warning-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.dark-light::after {\\n background: linear-gradient(135deg, #f0f0f0 50%, transparent 50%), linear-gradient(45deg, #f0f0f0 50%, #343a40 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.primary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #007bff 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.secondary-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #6c757d 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.success-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #28a745 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.danger-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #dc3545 50%)\\n}\\n\\n.bk-root div.bk.loader.spin.warning-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #ffc107 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.info-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #17a2b8 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.light-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #f8f9fa 50%);\\n}\\n\\n.bk-root div.bk.loader.spin.dark-dark::after {\\n background: linear-gradient(135deg, #0f0f0f 50%, transparent 50%), linear-gradient(45deg, #0f0f0f 50%, #343a40 50%);\\n}\\n\\n/* Safari */\\n@-webkit-keyframes spin {\\n 0% { -webkit-transform: rotate(0deg); }\\n 100% { -webkit-transform: rotate(360deg); }\\n}\\n\\n@keyframes spin {\\n 0% { transform: rotate(0deg); }\\n 100% { transform: rotate(360deg); }\\n}\\n\\n.dot div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n background-color: #fff;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled div {\\n height: 100%;\\n width: 100%;\\n border: 1px solid #000 !important;\\n border-radius: 50%;\\n display: inline-block;\\n}\\n\\n.dot-filled.primary div {\\n background-color: #007bff;\\n}\\n\\n.dot-filled.secondary div {\\n background-color: #6c757d;\\n}\\n\\n.dot-filled.success div {\\n background-color: #28a745;\\n}\\n\\n.dot-filled.danger div {\\n background-color: #dc3545;\\n}\\n\\n.dot-filled.warning div {\\n background-color: #ffc107;\\n}\\n\\n.dot-filled.info div {\\n background-color: #17a2b8;\\n}\\n\\n.dot-filled.dark div {\\n background-color: #343a40;\\n}\\n\\n.dot-filled.light div {\\n background-color: #f8f9fa;\\n}\\n\\n/* Slider editor */\\n.slider-edit .bk-input-group .bk-input {\\n border: 0;\\n border-radius: 0;\\n min-height: 0;\\n padding-left: 0;\\n padding-right: 0;\\n font-weight: bold;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper {\\n display: contents;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-up {\\n top: -6px;\\n}\\n\\n.slider-edit .bk-input-group .bk-spin-wrapper .bk.bk-spin-btn-down {\\n bottom: 3px;\\n}\\n\\n/* JSON Pane */\\n.bk-root .json-formatter-row .json-formatter-string, .bk-root .json-formatter-row .json-formatter-stringifiable {\\n white-space: pre-wrap;\\n}\\n\\n.ql-bubble .ql-editor {\\n border: 1px solid #ccc;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".codehilite .hll { background-color: #ffffcc }\\n.codehilite { background: #f8f8f8; }\\n.codehilite .c { color: #408080; font-style: italic } /* Comment */\\n.codehilite .err { border: 1px solid #FF0000 } /* Error */\\n.codehilite .k { color: #008000; font-weight: bold } /* Keyword */\\n.codehilite .o { color: #666666 } /* Operator */\\n.codehilite .ch { color: #408080; font-style: italic } /* Comment.Hashbang */\\n.codehilite .cm { color: #408080; font-style: italic } /* Comment.Multiline */\\n.codehilite .cp { color: #BC7A00 } /* Comment.Preproc */\\n.codehilite .cpf { color: #408080; font-style: italic } /* Comment.PreprocFile */\\n.codehilite .c1 { color: #408080; font-style: italic } /* Comment.Single */\\n.codehilite .cs { color: #408080; font-style: italic } /* Comment.Special */\\n.codehilite .gd { color: #A00000 } /* Generic.Deleted */\\n.codehilite .ge { font-style: italic } /* Generic.Emph */\\n.codehilite .gr { color: #FF0000 } /* Generic.Error */\\n.codehilite .gh { color: #000080; font-weight: bold } /* Generic.Heading */\\n.codehilite .gi { color: #00A000 } /* Generic.Inserted */\\n.codehilite .go { color: #888888 } /* Generic.Output */\\n.codehilite .gp { color: #000080; font-weight: bold } /* Generic.Prompt */\\n.codehilite .gs { font-weight: bold } /* Generic.Strong */\\n.codehilite .gu { color: #800080; font-weight: bold } /* Generic.Subheading */\\n.codehilite .gt { color: #0044DD } /* Generic.Traceback */\\n.codehilite .kc { color: #008000; font-weight: bold } /* Keyword.Constant */\\n.codehilite .kd { color: #008000; font-weight: bold } /* Keyword.Declaration */\\n.codehilite .kn { color: #008000; font-weight: bold } /* Keyword.Namespace */\\n.codehilite .kp { color: #008000 } /* Keyword.Pseudo */\\n.codehilite .kr { color: #008000; font-weight: bold } /* Keyword.Reserved */\\n.codehilite .kt { color: #B00040 } /* Keyword.Type */\\n.codehilite .m { color: #666666 } /* Literal.Number */\\n.codehilite .s { color: #BA2121 } /* Literal.String */\\n.codehilite .na { color: #7D9029 } /* Name.Attribute */\\n.codehilite .nb { color: #008000 } /* Name.Builtin */\\n.codehilite .nc { color: #0000FF; font-weight: bold } /* Name.Class */\\n.codehilite .no { color: #880000 } /* Name.Constant */\\n.codehilite .nd { color: #AA22FF } /* Name.Decorator */\\n.codehilite .ni { color: #999999; font-weight: bold } /* Name.Entity */\\n.codehilite .ne { color: #D2413A; font-weight: bold } /* Name.Exception */\\n.codehilite .nf { color: #0000FF } /* Name.Function */\\n.codehilite .nl { color: #A0A000 } /* Name.Label */\\n.codehilite .nn { color: #0000FF; font-weight: bold } /* Name.Namespace */\\n.codehilite .nt { color: #008000; font-weight: bold } /* Name.Tag */\\n.codehilite .nv { color: #19177C } /* Name.Variable */\\n.codehilite .ow { color: #AA22FF; font-weight: bold } /* Operator.Word */\\n.codehilite .w { color: #bbbbbb } /* Text.Whitespace */\\n.codehilite .mb { color: #666666 } /* Literal.Number.Bin */\\n.codehilite .mf { color: #666666 } /* Literal.Number.Float */\\n.codehilite .mh { color: #666666 } /* Literal.Number.Hex */\\n.codehilite .mi { color: #666666 } /* Literal.Number.Integer */\\n.codehilite .mo { color: #666666 } /* Literal.Number.Oct */\\n.codehilite .sa { color: #BA2121 } /* Literal.String.Affix */\\n.codehilite .sb { color: #BA2121 } /* Literal.String.Backtick */\\n.codehilite .sc { color: #BA2121 } /* Literal.String.Char */\\n.codehilite .dl { color: #BA2121 } /* Literal.String.Delimiter */\\n.codehilite .sd { color: #BA2121; font-style: italic } /* Literal.String.Doc */\\n.codehilite .s2 { color: #BA2121 } /* Literal.String.Double */\\n.codehilite .se { color: #BB6622; font-weight: bold } /* Literal.String.Escape */\\n.codehilite .sh { color: #BA2121 } /* Literal.String.Heredoc */\\n.codehilite .si { color: #BB6688; font-weight: bold } /* Literal.String.Interpol */\\n.codehilite .sx { color: #008000 } /* Literal.String.Other */\\n.codehilite .sr { color: #BB6688 } /* Literal.String.Regex */\\n.codehilite .s1 { color: #BA2121 } /* Literal.String.Single */\\n.codehilite .ss { color: #19177C } /* Literal.String.Symbol */\\n.codehilite .bp { color: #008000 } /* Name.Builtin.Pseudo */\\n.codehilite .fm { color: #0000FF } /* Name.Function.Magic */\\n.codehilite .vc { color: #19177C } /* Name.Variable.Class */\\n.codehilite .vg { color: #19177C } /* Name.Variable.Global */\\n.codehilite .vi { color: #19177C } /* Name.Variable.Instance */\\n.codehilite .vm { color: #19177C } /* Name.Variable.Magic */\\n.codehilite .il { color: #666666 } /* Literal.Number.Integer.Long */\\n\\n.markdown h1 { margin-block-start: 0.34em }\\n.markdown h2 { margin-block-start: 0.42em }\\n.markdown h3 { margin-block-start: 0.5em }\\n.markdown h4 { margin-block-start: 0.67em }\\n.markdown h5 { margin-block-start: 0.84em }\\n.markdown h6 { margin-block-start: 1.17em }\\n.markdown ul { padding-inline-start: 2em }\\n.markdown ol { padding-inline-start: 2em }\\n.markdown strong { font-weight: 600 }\\n.markdown a { color: -webkit-link }\\n.markdown a { color: -moz-hyperlinkText }\\n\\n.markdown .codehilite {\\n padding: 1rem 1.25rem;\\n margin-top: 1rem;\\n margin-bottom: 1rem;\\n border-radius: 0.25rem;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-row,\\n.json-formatter-row a,\\n.json-formatter-row a:hover {\\n color: black;\\n text-decoration: none;\\n}\\n.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-row .json-formatter-string,\\n.json-formatter-row .json-formatter-stringifiable {\\n color: green;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-row .json-formatter-number {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-boolean {\\n color: red;\\n}\\n.json-formatter-row .json-formatter-null {\\n color: #855A00;\\n}\\n.json-formatter-row .json-formatter-undefined {\\n color: #ca0b69;\\n}\\n.json-formatter-row .json-formatter-function {\\n color: #FF20ED;\\n}\\n.json-formatter-row .json-formatter-date {\\n background-color: rgba(0, 0, 0, 0.05);\\n}\\n.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: blue;\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-bracket {\\n color: blue;\\n}\\n.json-formatter-row .json-formatter-key {\\n color: #00008B;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n.json-formatter-dark.json-formatter-row {\\n font-family: monospace;\\n}\\n.json-formatter-dark.json-formatter-row,\\n.json-formatter-dark.json-formatter-row a,\\n.json-formatter-dark.json-formatter-row a:hover {\\n color: white;\\n text-decoration: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-row {\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty {\\n opacity: 0.5;\\n margin-left: 1rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty:after {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-object:after {\\n content: \\\"No properties\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-children.json-formatter-empty.json-formatter-array:after {\\n content: \\\"[]\\\";\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-string,\\n.json-formatter-dark.json-formatter-row .json-formatter-stringifiable {\\n color: #31F031;\\n white-space: pre;\\n word-wrap: break-word;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-number {\\n color: #66C2FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-boolean {\\n color: #EC4242;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-null {\\n color: #EEC97D;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-undefined {\\n color: #ef8fbe;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-function {\\n color: #FD48CB;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-date {\\n background-color: rgba(255, 255, 255, 0.05);\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-url {\\n text-decoration: underline;\\n color: #027BFF;\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-bracket {\\n color: #9494FF;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-key {\\n color: #23A0DB;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler-link {\\n cursor: pointer;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler {\\n line-height: 1.2rem;\\n font-size: 0.7rem;\\n vertical-align: middle;\\n opacity: 0.6;\\n cursor: pointer;\\n padding-right: 0.2rem;\\n}\\n.json-formatter-dark.json-formatter-row .json-formatter-toggler:after {\\n display: inline-block;\\n transition: transform 100ms ease-in;\\n content: \\\"\\\\25BA\\\";\\n}\\n.json-formatter-dark.json-formatter-row > a > .json-formatter-preview-text {\\n opacity: 0;\\n transition: opacity 0.15s ease-in;\\n font-style: italic;\\n}\\n.json-formatter-dark.json-formatter-row:hover > a > .json-formatter-preview-text {\\n opacity: 0.6;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-toggler-link .json-formatter-toggler:after {\\n transform: rotate(90deg);\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > .json-formatter-children:after {\\n display: inline-block;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open > a > .json-formatter-preview-text {\\n display: none;\\n}\\n.json-formatter-dark.json-formatter-row.json-formatter-open.json-formatter-empty:after {\\n display: block;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\".bk.pn-loading {\\n overflow: hidden;\\n}\\n.bk.pn-loading:before {\\n position: absolute;\\n height: 100%;\\n width: 100%;\\n content: '';\\n z-index: 1000;\\n background-color: rgb(255,255,255,0.50);\\n border-color: lightgray;\\n background-repeat: no-repeat;\\n background-position: center;\\n background-size: auto 50%;\\n border-width: 1px;\\n cursor: progress;\\n}\\n.bk.pn-loading.arcs:hover:before {\\n cursor: progress;\\n}\\n.bk.pn-loading .pn-loading-msg {\\n position: absolute;\\n top: 72%;\\n font-size: 2em;\\n color: black;\\n width: 100%;\\n text-align: center;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\"table.panel-df {\\n margin-left: auto;\\n margin-right: auto;\\n border: none;\\n border-collapse: collapse;\\n border-spacing: 0;\\n color: black;\\n font-size: 12px;\\n table-layout: fixed;\\n width: 100%;\\n}\\n\\n.panel-df tr, .panel-df th, .panel-df td {\\n text-align: right;\\n vertical-align: middle;\\n padding: 0.5em 0.5em !important;\\n line-height: normal;\\n white-space: normal;\\n max-width: none;\\n border: none;\\n}\\n\\n.panel-df tbody {\\n display: table-row-group;\\n vertical-align: middle;\\n border-color: inherit;\\n}\\n\\n.panel-df tbody tr:nth-child(odd) {\\n background: #f5f5f5;\\n}\\n\\n.panel-df thead {\\n border-bottom: 1px solid black;\\n vertical-align: bottom;\\n}\\n\\n.panel-df tr:hover {\\n background: lightblue !important;\\n cursor: pointer;\\n}\\n\");\n", - " }, function(Bokeh) {\n", - " inject_raw_css(\"\\n .bk.pn-loading.arc:before {\\n background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n background-size: auto calc(min(50%, 400px));\\n }\\n \");\n", - " }, function(Bokeh) {\n", - " /* BEGIN bokeh.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2022, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " const bokeh = factory();\n", - " bokeh.__bokeh__ = true;\n", - " if (typeof root.Bokeh === \"undefined\" || typeof root.Bokeh.__bokeh__ === \"undefined\") {\n", - " root.Bokeh = bokeh;\n", - " }\n", - " const Bokeh = root.Bokeh;\n", - " Bokeh[bokeh.version] = bokeh;\n", - " })(this, function() {\n", - " let define;\n", - " const parent_require = typeof require === \"function\" && require\n", - " return (function(modules, entry, aliases, externals) {\n", - " if (aliases === undefined) aliases = {};\n", - " if (externals === undefined) externals = {};\n", - "\n", - " const cache = {};\n", - "\n", - " const normalize = function(name) {\n", - " if (typeof name === \"number\")\n", - " return name;\n", - "\n", - " if (name === \"bokehjs\")\n", - " return entry;\n", - "\n", - " if (!externals[name]) {\n", - " const prefix = \"@bokehjs/\"\n", - " if (name.slice(0, prefix.length) === prefix)\n", - " name = name.slice(prefix.length)\n", - " }\n", - "\n", - " const alias = aliases[name]\n", - " if (alias != null)\n", - " return alias;\n", - "\n", - " const trailing = name.length > 0 && name[name.lenght-1] === \"/\";\n", - " const index = aliases[name + (trailing ? \"\" : \"/\") + \"index\"];\n", - " if (index != null)\n", - " return index;\n", - "\n", - " return name;\n", - " }\n", - "\n", - " const require = function(name) {\n", - " let mod = cache[name];\n", - " if (!mod) {\n", - " const id = normalize(name);\n", - "\n", - " mod = cache[id];\n", - " if (!mod) {\n", - " if (!modules[id]) {\n", - " if (externals[id] === false || (externals[id] == true && parent_require)) {\n", - " try {\n", - " mod = {exports: externals[id] ? parent_require(id) : {}};\n", - " cache[id] = cache[name] = mod;\n", - " return mod.exports;\n", - " } catch (e) {}\n", - " }\n", - "\n", - " const err = new Error(\"Cannot find module '\" + name + \"'\");\n", - " err.code = 'MODULE_NOT_FOUND';\n", - " throw err;\n", - " }\n", - "\n", - " mod = {exports: {}};\n", - " cache[id] = cache[name] = mod;\n", - "\n", - " function __esModule() {\n", - " Object.defineProperty(mod.exports, \"__esModule\", {value: true});\n", - " }\n", - "\n", - " function __esExport(name, value) {\n", - " Object.defineProperty(mod.exports, name, {\n", - " enumerable: true, get: function () { return value; }\n", - " });\n", - " }\n", - "\n", - " modules[id].call(mod.exports, require, mod, mod.exports, __esModule, __esExport);\n", - " } else {\n", - " cache[name] = mod;\n", - " }\n", - " }\n", - "\n", - " return mod.exports;\n", - " }\n", - " require.resolve = function(name) {\n", - " return \"\"\n", - " }\n", - "\n", - " const main = require(entry);\n", - " main.require = require;\n", - "\n", - " if (typeof Proxy !== \"undefined\") {\n", - " // allow Bokeh.loader[\"@bokehjs/module/name\"] syntax\n", - " main.loader = new Proxy({}, {\n", - " get: function(_obj, module) {\n", - " return require(module);\n", - " }\n", - " });\n", - " }\n", - "\n", - " main.register_plugin = function(plugin_modules, plugin_entry, plugin_aliases, plugin_externals) {\n", - " if (plugin_aliases === undefined) plugin_aliases = {};\n", - " if (plugin_externals === undefined) plugin_externals = {};\n", - "\n", - " for (let name in plugin_modules) {\n", - " modules[name] = plugin_modules[name];\n", - " }\n", - "\n", - " for (let name in plugin_aliases) {\n", - " aliases[name] = 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e)n.set(t.id,t);for(const e of s)e.detach_document();for(const e of o)e.attach_document(this);this._all_models=n}roots(){return this._roots}add_root(e,t){if(_.logger.debug(`Adding root: ${e}`),!(0,g.includes)(this._roots,e)){this._push_all_models_freeze();try{this._roots.push(e)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new z.RootAddedEvent(this,e,t))}}remove_root(e,t){const s=this._roots.indexOf(e);if(!(s<0)){this._push_all_models_freeze();try{this._roots.splice(s,1)}finally{this._pop_all_models_freeze()}this._trigger_on_change(new z.RootRemovedEvent(this,e,t))}}title(){return this._title}set_title(e,t){e!==this._title&&(this._title=e,this._trigger_on_change(new z.TitleChangedEvent(this,e,t)))}get_model_by_id(e){var t;return null!==(t=this._all_models.get(e))&&void 0!==t?t:null}get_model_by_name(e){const t=[];for(const s of this._all_models.values())s instanceof M.Model&&s.name==e&&t.push(s);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(`Multiple models are named '${e}'`)}}on_message(e,t){const s=this._message_callbacks.get(e);null==s?this._message_callbacks.set(e,new Set([t])):s.add(t)}remove_on_message(e,t){var s;null===(s=this._message_callbacks.get(e))||void 0===s||s.delete(t)}_trigger_on_message(e,t){const s=this._message_callbacks.get(e);if(null!=s)for(const e of s)e(t)}on_change(e,t=!1){this._callbacks.has(e)||this._callbacks.set(e,t)}remove_on_change(e){this._callbacks.delete(e)}_trigger_on_change(e){for(const[t,s]of this._callbacks)if(!s&&e instanceof z.DocumentEventBatch)for(const s of e.events)t(s);else t(e)}_notify_change(e,t,s,o,n){this._trigger_on_change(new z.ModelChangedEvent(this,e,t,s,o,null==n?void 0:n.setter_id,null==n?void 0:n.hint))}static _instantiate_object(e,t,s,o){const n=Object.assign(Object.assign({},s),{id:e,__deferred__:!0});return new(o.get(t))(n)}static _instantiate_references_json(e,t,s){var o;const n=new Map;for(const i of e){const e=i.id,r=i.type,l=null!==(o=i.attributes)&&void 0!==o?o:{};let _=t.get(e);null==_&&(_=E._instantiate_object(e,r,l,s),null!=i.subtype&&_.set_subtype(i.subtype)),n.set(_.id,_)}return n}static _resolve_refs(e,t,s,o){function n(e){var i;if((0,f.is_ref)(e)){const o=null!==(i=t.get(e.id))&&void 0!==i?i:s.get(e.id);if(null!=o)return o;throw new Error(`reference ${JSON.stringify(e)} isn't known (not in Document?)`)}if((0,u.is_NDArray_ref)(e)){const{buffer:t,dtype:s,shape:n}=(0,u.decode_NDArray)(e,o);return(0,m.ndarray)(t,{dtype:s,shape:n})}return(0,b.isArray)(e)?function(e){const t=[];for(const s of e)t.push(n(s));return t}(e):(0,b.isPlainObject)(e)?function(e){const t={};for(const[s,o]of(0,v.entries)(e))t[s]=n(o);return t}(e):e}return n(e)}static _initialize_references_json(e,t,s,o){const n=new Map;for(const{id:i,attributes:r}of e){const e=!t.has(i),l=e?s.get(i):t.get(i),_=E._resolve_refs(r,t,s,o);l.setv(_,{silent:!0}),n.set(i,{instance:l,is_new:e})}const i=[],r=new Set;function l(e){if(e instanceof 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i=e.attributes[n],r=t.attributes[n];null==i&&null==r||(null==i||null==r?c.push(E._event_for_attribute_change(e,n,r,s,o)):\"data\"==n||(0,w.is_equal)(i,r)||c.push(E._event_for_attribute_change(e,n,r,s,o)))}return c.filter((e=>null!=e))}static _compute_patch_since_json(e,t){const s=t.to_json(!1);function o(e){const t=new Map;for(const s of e.roots.references)t.set(s.id,s);return t}const n=o(e),i=new Map,r=[];for(const t of e.roots.root_ids)i.set(t,n.get(t)),r.push(t);const l=o(s),_=new Map,a=[];for(const e of s.roots.root_ids)_.set(e,l.get(e)),a.push(e);if(r.sort(),a.sort(),(0,g.difference)(r,a).length>0||(0,g.difference)(a,r).length>0)throw new Error(\"Not implemented: computing add/remove of document roots\");const c=new Set;let h=[];for(const e of t._all_models.keys())if(n.has(e)){const s=E._events_to_sync_objects(n.get(e),l.get(e),t,c);h=h.concat(s)}const f=new d.Serializer({include_defaults:!1});return f.to_serializable([...c]),{references:[...f.definitions],events:h}}to_json_string(e=!0){return JSON.stringify(this.to_json(e))}to_json(e=!0){const t=new d.Serializer({include_defaults:e}),s=t.to_serializable(this._roots);return{version:l.version,title:this._title,roots:{root_ids:s.map((e=>e.id)),references:[...t.definitions]}}}static from_json_string(e){const t=JSON.parse(e);return E.from_json(t)}static from_json(e){_.logger.debug(\"Creating Document from JSON\");const t=e.version,s=-1!==t.indexOf(\"+\")||-1!==t.indexOf(\"-\"),o=`Library versions: JS (${l.version}) / Python (${t})`;s||l.version.replace(/-(dev|rc)\\./,\"$1\")==t?_.logger.debug(o):(_.logger.warn(\"JS/Python version mismatch\"),_.logger.warn(o));const n=new r.ModelResolver;null!=e.defs&&(0,j.resolve_defs)(e.defs,n);const i=e.roots,a=i.root_ids,c=i.references,d=E._instantiate_references_json(c,new Map,n);E._initialize_references_json(c,new Map,d,new Map);const h=new E({resolver:n});h._push_all_models_freeze();for(const e of a){const t=d.get(e);null!=t&&h.add_root(t)}return h._pop_all_models_freeze(),h.set_title(e.title),h}replace_with_json(e){E.from_json(e).destructively_move(this)}create_json_patch_string(e){return JSON.stringify(this.create_json_patch(e))}create_json_patch(e){for(const t of e)if(t.document!=this)throw new Error(\"Cannot create a patch using events from a different document\");const t=new d.Serializer,s=t.to_serializable(e);for(const e of this._all_models.values())t.remove_def(e);return{events:s,references:[...t.definitions]}}apply_json_patch(e,t=new Map,s){const o=e.references,n=e.events,i=E._instantiate_references_json(o,this._all_models,this._resolver);t instanceof Map||(t=new Map(t));for(const e of n)switch(e.kind){case\"RootAdded\":case\"RootRemoved\":case\"ModelChanged\":{const t=e.model.id,s=this._all_models.get(t);if(null!=s)i.set(t,s);else if(!i.has(t))throw _.logger.warn(`Got an event for unknown model ${e.model}\"`),new Error(\"event model wasn't known\");break}}const r=new Map(this._all_models),l=new Map;for(const[e,t]of i)r.has(e)||l.set(e,t);E._initialize_references_json(o,r,l,t);for(const e of n)switch(e.kind){case\"MessageSent\":{const{msg_type:s,msg_data:o}=e;let n;if(void 0===o){if(1!=t.size)throw new Error(\"expected exactly one buffer\");{const[[,e]]=t;n=e}}else n=E._resolve_refs(o,r,l,t);this._trigger_on_message(s,n);break}case\"ModelChanged\":{const o=e.model.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot apply patch to ${o} which is not in the document`);const i=e.attr,_=E._resolve_refs(e.new,r,l,t);n.setv({[i]:_},{setter_id:s});break}case\"ColumnDataChanged\":{const o=e.column_source.id,n=this._all_models.get(o);if(null==n)throw new Error(`Cannot stream to ${o} which is not in the document`);const i=E._resolve_refs(e.new,new Map,new Map,t);if(null!=e.cols)for(const e in n.data)e in i||(i[e]=n.data[e]);n.setv({data:i},{setter_id:s,check_eq:!1});break}case\"ColumnsStreamed\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot stream to ${t} which is not in the document`);if(!(o instanceof k.ColumnDataSource))throw new Error(\"Cannot stream to non-ColumnDataSource\");const n=e.data,i=e.rollover;o.stream(n,i,s);break}case\"ColumnsPatched\":{const t=e.column_source.id,o=this._all_models.get(t);if(null==o)throw new Error(`Cannot patch ${t} which is not in the document`);if(!(o instanceof k.ColumnDataSource))throw new Error(\"Cannot patch non-ColumnDataSource\");const n=e.patches;o.patch(n,s);break}case\"RootAdded\":{const t=e.model.id,o=i.get(t);this.add_root(o,s);break}case\"RootRemoved\":{const t=e.model.id,o=i.get(t);this.remove_root(o,s);break}case\"TitleChanged\":this.set_title(e.title,s);break;default:throw new Error(`Unknown patch event ${JSON.stringify(e)}`)}}}s.Document=E,E.__name__=\"Document\"},\n", - " function _(e,o,s,r,t){r();const l=e(1),i=e(8),d=e(13),n=e(14);s.overrides={};const a=new Map;s.Models=e=>{const 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extends((0,c.Signalable)()){constructor(e={}){var t,s;super(),this._subtype=void 0,this.document=null,this.destroyed=new c.Signal0(this,\"destroyed\"),this.change=new c.Signal0(this,\"change\"),this.transformchange=new c.Signal0(this,\"transformchange\"),this.exprchange=new c.Signal0(this,\"exprchange\"),this.properties={},this._watchers=new WeakMap,this._pending=!1,this._changing=!1;const n=e instanceof Map?e.get.bind(e):t=>e[t];this.id=null!==(t=n(\"id\"))&&void 0!==t?t:(0,u.uniqueId)();for(const[e,{type:t,default_value:s,options:r}]of(0,l.entries)(this._props)){let i;t instanceof _.PropertyAlias?Object.defineProperty(this.properties,e,{get:()=>this.properties[t.attr],configurable:!1,enumerable:!1}):(i=t instanceof h.Kind?new _.PrimitiveProperty(this,e,t,s,n(e),r):new t(this,e,h.Any,s,n(e),r),this.properties[e]=i)}null!==(s=n(\"__deferred__\"))&&void 0!==s&&s||(this.finalize(),this.connect_signals())}get is_syncable(){return!0}set type(e){console.warn(\"prototype.type = 'ModelName' 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r=Object.assign({},this.prototype._props);r[t]=Object.assign(Object.assign({},n),{default_value:e}),this.prototype._props=r}}toString(){return`${this.type}(${this.id})`}property(e){const t=this.properties[e];if(null!=t)return t;throw new Error(`unknown property ${this.type}.${e}`)}get attributes(){const e={};for(const t of this)e[t.attr]=t.get_value();return e}[m.clone](e){const t=new Map;for(const s of this)s.dirty&&t.set(s.attr,e.clone(s.get_value()));return new this.constructor(t)}[y.equals](e,t){for(const s of this){const n=e.property(s.attr);if(!t.eq(s.get_value(),n.get_value()))return!1}return!0}[v.pretty](e){const t=e.token,s=[];for(const n of this)if(n.dirty){const r=n.get_value();s.push(`${n.attr}${t(\":\")} ${e.to_string(r)}`)}return`${this.constructor.__qualified__}${t(\"(\")}${t(\"{\")}${s.join(`${t(\",\")} `)}${t(\"}\")}${t(\")\")}`}[d.serialize](e){const t=this.ref();e.add_ref(this,t);const s=this.struct();for(const t of this)t.syncable&&(e.include_defaults||t.dirty)&&(s.attributes[t.attr]=e.to_serializable(t.get_value()));return e.add_def(this,s),t}finalize(){for(const e of this){if(!(e instanceof _.VectorSpec||e instanceof _.ScalarSpec))continue;const t=e.get_value();if(null!=t){const{transform:e,expr:s}=t;null!=e&&this.connect(e.change,(()=>this.transformchange.emit())),null!=s&&this.connect(s.change,(()=>this.exprchange.emit()))}}this.initialize()}initialize(){}connect_signals(){}disconnect_signals(){c.Signal.disconnectReceiver(this)}destroy(){this.disconnect_signals(),this.destroyed.emit()}clone(){return(new m.Cloner).clone(this)}changed_for(e){const t=this._watchers.get(e);return this._watchers.set(e,!1),null==t||t}_setv(e,t){const s=t.check_eq,n=[],r=this._changing;this._changing=!0;for(const[t,r]of e)!1!==s&&(0,p.is_equal)(t.get_value(),r)||(t.set_value(r),n.push(t));n.length>0&&(this._watchers=new WeakMap,this._pending=!0);for(const e of n)e.change.emit();if(!r){if(!t.no_change)for(;this._pending;)this._pending=!1,this.change.emit();this._pending=!1,this._changing=!1}}setv(e,t={}){const s=(0,l.entries)(e);if(0==s.length)return;if(!0===t.silent){this._watchers=new WeakMap;for(const[e,t]of s)this.properties[e].set_value(t);return}const n=new Map,r=new Map;for(const[e,t]of s){const s=this.properties[e];n.set(s,t),r.set(s,s.get_value())}this._setv(n,t);const{document:i}=this;if(null!=i){const e=[];for(const[t,s]of r)e.push([t,s,t.get_value()]);for(const[,t,s]of e)if(this._needs_invalidate(t,s)){i._invalidate_all_models();break}this._push_changes(e,t)}}getv(e){return this.property(e).get_value()}ref(){return{id:this.id}}struct(){const e={type:this.type,id:this.id,attributes:{}};return null!=this._subtype&&(e.subtype=this._subtype),e}set_subtype(e){this._subtype=e}*[Symbol.iterator](){yield*(0,l.values)(this.properties)}*syncable_properties(){for(const e of this)e.syncable&&(yield e)}serializable_attributes(){const e={};for(const t of this.syncable_properties())e[t.attr]=t.get_value();return e}static _json_record_references(e,t,s,n){const{recursive:r}=n;if((0,a.is_ref)(t)){const n=e.get_model_by_id(t.id);null==n||s.has(n)||w._value_record_references(n,s,{recursive:r})}else if((0,f.isArray)(t))for(const n of t)w._json_record_references(e,n,s,{recursive:r});else if((0,f.isPlainObject)(t))for(const n of(0,l.values)(t))w._json_record_references(e,n,s,{recursive:r})}static _value_record_references(e,t,s){const{recursive:n}=s;if(e instanceof w){if(!t.has(e)&&(t.add(e),n))for(const s of e.syncable_properties()){const e=s.get_value();w._value_record_references(e,t,{recursive:n})}}else if((0,f.isArray)(e))for(const s of e)w._value_record_references(s,t,{recursive:n});else if((0,f.isPlainObject)(e))for(const s of(0,l.values)(e))w._value_record_references(s,t,{recursive:n})}references(){const e=new Set;return w._value_record_references(this,e,{recursive:!0}),e}_doc_attached(){}_doc_detached(){}attach_document(e){if(null!=this.document&&this.document!=e)throw new Error(\"models must be owned by only a single document\");this.document=e,this._doc_attached()}detach_document(){this._doc_detached(),this.document=null}_needs_invalidate(e,t){const s=new Set;w._value_record_references(t,s,{recursive:!1});const n=new Set;w._value_record_references(e,n,{recursive:!1});for(const e of s)if(!n.has(e))return!0;for(const e of n)if(!s.has(e))return!0;return!1}_push_changes(e,t={}){if(!this.is_syncable)return;const{document:s}=this;if(null==s)return;const{setter_id:n}=t,r=[];for(const[t,i,o]of e)t.syncable&&r.push(new g.ModelChangedEvent(s,this,t.attr,i,o,n));if(0!=r.length){let e;1==r.length?[e]=r:e=new g.DocumentEventBatch(s,r,n),s._trigger_on_change(e)}}on_change(e,t){for(const s of(0,f.isArray)(e)?e:[e])this.connect(s.change,t)}}s.HasProps=w,(o=w).prototype._props={},o.prototype._mixins=[]},\n", - " function _(n,t,e,l,s){l();const i=n(16),o=n(9);class c{constructor(n,t){this.sender=n,this.name=t}connect(n,t=null){u.has(this.sender)||u.set(this.sender,[]);const e=u.get(this.sender);if(null!=g(e,this,n,t))return!1;const l=null!=t?t:n;a.has(l)||a.set(l,[]);const s=a.get(l),i={signal:this,slot:n,context:t};return e.push(i),s.push(i),!0}disconnect(n,t=null){const e=u.get(this.sender);if(null==e||0===e.length)return!1;const l=g(e,this,n,t);if(null==l)return!1;const s=null!=t?t:n,i=a.get(s);return l.signal=null,d(e),d(i),!0}emit(n){var t;const e=null!==(t=u.get(this.sender))&&void 0!==t?t:[];for(const{signal:t,slot:l,context:s}of e)t===this&&l.call(s,n,this.sender)}}e.Signal=c,c.__name__=\"Signal\";class r extends c{emit(){super.emit(void 0)}}e.Signal0=r,r.__name__=\"Signal0\",function(n){function t(n,t){const e=u.get(n);if(null==e||0===e.length)return;const l=a.get(t);if(null!=l&&0!==l.length){for(const t of 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e in l.named_colors}},\n", - " function _(r,t,n,a,o){a(),n.GeneratorFunction=Object.getPrototypeOf((function*(){})).constructor,n.ColorArray=Uint32Array,n.RGBAArray=Uint8ClampedArray,n.infer_type=function(r,t){return r instanceof Float64Array||r instanceof Array||t instanceof Float64Array||t instanceof Array?Float64Array:Float32Array},n.ScreenArray=Float32Array,n.to_screen=function(r){return r instanceof Float32Array?r:Float32Array.from(r)},o(\"Indices\",r(25).BitSet)},\n", - " function _(t,s,r,e,i){var n;e();const o=t(26),a=t(11);class _{constructor(t,s=0){this.size=t,this[n]=\"BitSet\",this._count=null,this._nwords=Math.ceil(t/32),0==s||1==s?(this._array=new Uint32Array(this._nwords),1==s&&this._array.fill(4294967295)):((0,a.assert)(s.length==this._nwords,\"Initializer size mismatch\"),this._array=s)}clone(){return new _(this.size,new Uint32Array(this._array))}[(n=Symbol.toStringTag,o.equals)](t,s){if(!s.eq(this.size,t.size))return!1;const{_nwords:r}=this,e=this.size%r,i=0==e?r:r-1;for(let s=0;s>>5,r=31&t;return!!(this._array[s]>>r&1)}set(t,s=!0){this._check_bounds(t),this._count=null;const r=t>>>5,e=31&t;s?this._array[r]|=1<>>t&1&&(e+=1)}return e}*ones(){const{_array:t,_nwords:s,size:r}=this;for(let e=0,i=0;i>>t&1&&(yield e);else e+=32}}*zeros(){const{_array:t,_nwords:s,size:r}=this;for(let e=0,i=0;i>>t&1||(yield e);else e+=32}}_check_size(t){(0,a.assert)(this.size==t.size,\"Size mismatch\")}add(t){this._check_size(t);for(let s=0;s{if(a(t)&&a(e))return t[r.equals](e,this);switch(n){case\"[object Array]\":case\"[object Uint8Array]\":case\"[object Int8Array]\":case\"[object Uint16Array]\":case\"[object Int16Array]\":case\"[object Uint32Array]\":case\"[object Int32Array]\":case\"[object Float32Array]\":case\"[object Float64Array]\":return this.arrays(t,e);case\"[object Map]\":return this.maps(t,e);case\"[object Set]\":return this.sets(t,e);case\"[object Object]\":if(t.constructor==e.constructor&&(null==t.constructor||t.constructor===Object))return this.objects(t,e);case\"[object Function]\":if(t.constructor==e.constructor&&t.constructor===Function)return this.eq(`${t}`,`${e}`)}if(t instanceof Node)return this.nodes(t,e);throw Error(`can't compare objects of type ${n}`)})();return s.pop(),o.pop(),u}numbers(t,e){return Object.is(t,e)}arrays(t,e){const{length:r}=t;if(r!=e.length)return!1;for(let n=0;n{const n=navigator.userAgent;return n.includes(\"MSIE\")||n.includes(\"Trident\")||n.includes(\"Edge\")})(),e.is_mobile=\"undefined\"!=typeof window&&(\"ontouchstart\"in window||navigator.maxTouchPoints>0),e.is_little_endian=(()=>{const n=new ArrayBuffer(4),i=new Uint8Array(n);new Uint32Array(n)[1]=168496141;let e=!0;return 10==i[4]&&11==i[5]&&12==i[6]&&13==i[7]&&(e=!1),e})(),e.BYTE_ORDER=e.is_little_endian?\"little\":\"big\",e.to_big_endian=function(n){if(e.is_little_endian){const i=new 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d{constructor(e,t,s){super(e),this.msg_type=t,this.msg_data=s}[i.serialize](e){const t=this.msg_data,s=e.to_serializable(t);return{kind:\"MessageSent\",msg_type:this.msg_type,msg_data:s}}}s.MessageSentEvent=l,l.__name__=\"MessageSentEvent\";class _ extends d{constructor(e,t,s,n,o,i,r){super(e),this.model=t,this.attr=s,this.old=n,this.new_=o,this.setter_id=i,this.hint=r}[i.serialize](e){if(null!=this.hint)return e.to_serializable(this.hint);const t=this.new_,s=e.to_serializable(t);return this.model!=t&&e.remove_def(this.model),{kind:\"ModelChanged\",model:this.model.ref(),attr:this.attr,new:s}}}s.ModelChangedEvent=_,_.__name__=\"ModelChangedEvent\";class c extends d{constructor(e,t,s){super(e),this.column_source=t,this.patches=s}[i.serialize](e){return{kind:\"ColumnsPatched\",column_source:this.column_source,patches:this.patches}}}s.ColumnsPatchedEvent=c,c.__name__=\"ColumnsPatchedEvent\";class h extends d{constructor(e,t,s,n){super(e),this.column_source=t,this.data=s,this.rollover=n}[i.serialize](e){return{kind:\"ColumnsStreamed\",column_source:this.column_source,data:this.data,rollover:this.rollover}}}s.ColumnsStreamedEvent=h,h.__name__=\"ColumnsStreamedEvent\";class m extends d{constructor(e,t,s){super(e),this.title=t,this.setter_id=s}[i.serialize](e){return{kind:\"TitleChanged\",title:this.title}}}s.TitleChangedEvent=m,m.__name__=\"TitleChangedEvent\";class u extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}[i.serialize](e){return{kind:\"RootAdded\",model:e.to_serializable(this.model)}}}s.RootAddedEvent=u,u.__name__=\"RootAddedEvent\";class v extends d{constructor(e,t,s){super(e),this.model=t,this.setter_id=s}[i.serialize](e){return{kind:\"RootRemoved\",model:this.model.ref()}}}s.RootRemovedEvent=v,v.__name__=\"RootRemovedEvent\"},\n", - " function _(t,i,r,n,s){n();const e=t(8),o=t(13);r.pretty=Symbol(\"pretty\");class c{constructor(t){this.visited=new 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l.Renderer{constructor(t){super(t)}}i.Annotation=a,o=a,a.__name__=\"Annotation\",o.override({level:\"annotation\"})},\n", - " function _(e,i,t,n,s){n();const r=e(1);var o,a;const _=e(42),l=(0,r.__importStar)(e(45)),d=e(20),h=e(53),u=e(54);class c extends h.Model{constructor(e){super(e)}}t.RendererGroup=c,o=c,c.__name__=\"RendererGroup\",o.define((({Boolean:e})=>({visible:[e,!0]})));class p extends _.View{get coordinates(){const{_coordinates:e}=this;return null!=e?e:this._coordinates=this._initialize_coordinates()}initialize(){super.initialize(),this.visuals=new l.Visuals(this),this.needs_webgl_blit=!1}connect_signals(){super.connect_signals();const{x_range_name:e,y_range_name:i}=this.model.properties;this.on_change([e,i],(()=>this._initialize_coordinates()));const{group:t}=this.model;null!=t&&this.on_change(t.properties.visible,(()=>{this.model.visible=t.visible}))}_initialize_coordinates(){const{coordinates:e}=this.model,{frame:i}=this.plot_view;if(null!=e)return e.get_transform(i);{const{x_range_name:e,y_range_name:t}=this.model,n=i.x_scales.get(e),s=i.y_scales.get(t);return new u.CoordinateTransform(n,s)}}get plot_view(){return this.parent}get plot_model(){return this.parent.model}get layer(){const{overlays:e,primary:i}=this.canvas;return\"overlay\"==this.model.level?e:i}get canvas(){return this.plot_view.canvas_view}request_render(){this.request_paint()}request_paint(){this.plot_view.request_paint(this)}request_layout(){this.plot_view.request_layout()}notify_finished(){this.plot_view.notify_finished()}notify_finished_after_paint(){this.plot_view.notify_finished_after_paint()}get needs_clip(){return!1}get has_webgl(){return!1}render(){this.model.visible&&this._render(),this._has_finished=!0}renderer_view(e){}}t.RendererView=p,p.__name__=\"RendererView\";class g extends h.Model{constructor(e){super(e)}}t.Renderer=g,a=g,g.__name__=\"Renderer\",a.define((({Boolean:e,String:i,Ref:t,Nullable:n})=>({group:[n(t(c)),null],level:[d.RenderLevel,\"image\"],visible:[e,!0],x_range_name:[i,\"default\"],y_range_name:[i,\"default\"],coordinates:[n(t(u.CoordinateMapping)),null]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1),h=t(15),r=t(43),l=t(8),_=(0,o.__importDefault)(t(44));class d{constructor(t){this.removed=new h.Signal0(this,\"removed\"),this._ready=Promise.resolve(void 0),this._slots=new WeakMap,this._idle_notified=!1;const{model:e,parent:s}=t;this.model=e,this.parent=s,this.root=null==s?this:s.root,this.removed.emit()}get ready(){return this._ready}connect(t,e){let s=this._slots.get(e);return null==s&&(s=(t,s)=>{const i=Promise.resolve(e.call(this,t,s));this._ready=this._ready.then((()=>i))},this._slots.set(e,s)),t.connect(s,this)}disconnect(t,e){return t.disconnect(e,this)}initialize(){this._has_finished=!1,this.is_root&&(this._stylesheet=r.stylesheet);for(const t of this.styles())this.stylesheet.append(t)}async lazy_initialize(){}remove(){this.disconnect_signals(),this.removed.emit()}toString(){return`${this.model.type}View(${this.model.id})`}serializable_state(){return{type:this.model.type}}get is_root(){return null==this.parent}has_finished(){return this._has_finished}get is_idle(){return this.has_finished()}connect_signals(){}disconnect_signals(){h.Signal.disconnect_receiver(this)}on_change(t,e){for(const s of(0,l.isArray)(t)?t:[t])this.connect(s.change,e)}cursor(t,e){return null}get stylesheet(){return this.is_root?this._stylesheet:this.root.stylesheet}styles(){return[_.default]}notify_finished(){this.is_root?!this._idle_notified&&this.has_finished()&&null!=this.model.document&&(this._idle_notified=!0,this.model.document.notify_idle(this.model)):this.root.notify_finished()}}s.View=d,d.__name__=\"View\"},\n", - " function _(t,e,n,i,o){i();const s=t(8),l=t(13),r=t=>(e={},...n)=>{const i=document.createElement(t);i.classList.add(\"bk\"),(0,s.isPlainObject)(e)||(n=[e,...n],e={});for(let[t,n]of(0,l.entries)(e))if(null!=n&&(!(0,s.isBoolean)(n)||n))if(\"class\"===t&&((0,s.isString)(n)&&(n=n.split(/\\s+/)),(0,s.isArray)(n)))for(const t of n)null!=t&&i.classList.add(t);else if(\"style\"===t&&(0,s.isPlainObject)(n))for(const[t,e]of(0,l.entries)(n))i.style[t]=e;else if(\"data\"===t&&(0,s.isPlainObject)(n))for(const[t,e]of(0,l.entries)(n))i.dataset[t]=e;else i.setAttribute(t,n);function o(t){if((0,s.isString)(t))i.appendChild(document.createTextNode(t));else if(t instanceof Node)i.appendChild(t);else if(t instanceof NodeList||t instanceof HTMLCollection)for(const e of t)i.appendChild(e);else if(null!=t&&!1!==t)throw new Error(`expected a DOM element, string, false or null, got ${JSON.stringify(t)}`)}for(const t of n)if((0,s.isArray)(t))for(const e of t)o(e);else o(t);return i};function a(t){const e=t.parentNode;null!=e&&e.removeChild(t)}function c(t,...e){const n=t.firstChild;for(const i of e)t.insertBefore(i,n)}function d(t,e){var n,i,o;const s=Element.prototype;return(null!==(o=null!==(i=null!==(n=s.matches)&&void 0!==n?n:s.webkitMatchesSelector)&&void 0!==i?i:s.mozMatchesSelector)&&void 0!==o?o:s.msMatchesSelector).call(t,e)}function h(t){return parseFloat(t)||0}function f(t){const e=getComputedStyle(t);return{border:{top:h(e.borderTopWidth),bottom:h(e.borderBottomWidth),left:h(e.borderLeftWidth),right:h(e.borderRightWidth)},margin:{top:h(e.marginTop),bottom:h(e.marginBottom),left:h(e.marginLeft),right:h(e.marginRight)},padding:{top:h(e.paddingTop),bottom:h(e.paddingBottom),left:h(e.paddingLeft),right:h(e.paddingRight)}}}function u(t){const e=t.getBoundingClientRect();return{width:Math.ceil(e.width),height:Math.ceil(e.height)}}n.createElement=function(t,e,...n){return r(t)(e,...n)},n.div=r(\"div\"),n.span=r(\"span\"),n.canvas=r(\"canvas\"),n.link=r(\"link\"),n.style=r(\"style\"),n.a=r(\"a\"),n.p=r(\"p\"),n.i=r(\"i\"),n.pre=r(\"pre\"),n.button=r(\"button\"),n.label=r(\"label\"),n.input=r(\"input\"),n.select=r(\"select\"),n.option=r(\"option\"),n.optgroup=r(\"optgroup\"),n.textarea=r(\"textarea\"),n.createSVGElement=function(t,e,...n){const i=document.createElementNS(\"http://www.w3.org/2000/svg\",t);for(const[t,n]of(0,l.entries)(null!=e?e:{}))null==n||(0,s.isBoolean)(n)&&!n||i.setAttribute(t,n);function o(t){if((0,s.isString)(t))i.appendChild(document.createTextNode(t));else if(t instanceof Node)i.appendChild(t);else if(t instanceof NodeList||t instanceof HTMLCollection)for(const e of t)i.appendChild(e);else if(null!=t&&!1!==t)throw new Error(`expected a DOM element, string, false or null, got ${JSON.stringify(t)}`)}for(const t of n)if((0,s.isArray)(t))for(const e of t)o(e);else o(t);return i},n.nbsp=function(){return document.createTextNode(\"\\xa0\")},n.append=function(t,...e){for(const n of e)t.appendChild(n)},n.remove=a,n.removeElement=a,n.replaceWith=function(t,e){const n=t.parentNode;null!=n&&n.replaceChild(e,t)},n.prepend=c,n.empty=function(t,e=!1){let n;for(;n=t.firstChild;)t.removeChild(n);if(e&&t instanceof Element)for(const e of t.attributes)t.removeAttributeNode(e)},n.display=function(t){t.style.display=\"\"},n.undisplay=function(t){t.style.display=\"none\"},n.show=function(t){t.style.visibility=\"\"},n.hide=function(t){t.style.visibility=\"hidden\"},n.offset=function(t){const e=t.getBoundingClientRect();return{top:e.top+window.pageYOffset-document.documentElement.clientTop,left:e.left+window.pageXOffset-document.documentElement.clientLeft}},n.matches=d,n.parent=function(t,e){let n=t;for(;n=n.parentElement;)if(d(n,e))return n;return null},n.extents=f,n.size=u,n.scroll_size=function(t){return{width:Math.ceil(t.scrollWidth),height:Math.ceil(t.scrollHeight)}},n.outer_size=function(t){const{margin:{left:e,right:n,top:i,bottom:o}}=f(t),{width:s,height:l}=u(t);return{width:Math.ceil(s+e+n),height:Math.ceil(l+i+o)}},n.content_size=function(t){const{left:e,top:n}=t.getBoundingClientRect(),{padding:i}=f(t);let o=0,s=0;for(const l of t.children){const t=l.getBoundingClientRect();o=Math.max(o,Math.ceil(t.left-e-i.left+t.width)),s=Math.max(s,Math.ceil(t.top-n-i.top+t.height))}return{width:o,height:s}},n.position=function(t,e,n){const{style:i}=t;if(i.left=`${e.x}px`,i.top=`${e.y}px`,i.width=`${e.width}px`,i.height=`${e.height}px`,null==n)i.margin=\"\";else{const{top:t,right:e,bottom:o,left:s}=n;i.margin=`${t}px ${e}px ${o}px ${s}px`}},n.children=function(t){return Array.from(t.children)};class p{constructor(t){this.el=t,this.classList=t.classList}get values(){const t=[];for(let e=0;e{document.addEventListener(\"DOMContentLoaded\",(()=>t()),{once:!0})}))}},\n", - " function _(o,i,t,e,r){e(),t.root=\"bk-root\",t.default=\".bk-root{position:relative;width:auto;height:auto;box-sizing:border-box;font-family:Helvetica, Arial, sans-serif;font-size:13px;}.bk-root .bk,.bk-root .bk:before,.bk-root .bk:after{box-sizing:inherit;margin:0;border:0;padding:0;background-image:none;font-family:inherit;font-size:100%;line-height:1.42857143;}.bk-root pre.bk{font-family:Courier, monospace;}\"},\n", - " function _(e,t,r,a,c){a();const n=e(1),l=e(46);c(\"Line\",l.Line),c(\"LineScalar\",l.LineScalar),c(\"LineVector\",l.LineVector);const i=e(49);c(\"Fill\",i.Fill),c(\"FillScalar\",i.FillScalar),c(\"FillVector\",i.FillVector);const s=e(50);c(\"Text\",s.Text),c(\"TextScalar\",s.TextScalar),c(\"TextVector\",s.TextVector);const o=e(51);c(\"Hatch\",o.Hatch),c(\"HatchScalar\",o.HatchScalar),c(\"HatchVector\",o.HatchVector);const u=(0,n.__importStar)(e(48)),V=e(47);c(\"VisualProperties\",V.VisualProperties),c(\"VisualUniforms\",V.VisualUniforms);class h{constructor(e){this._visuals=[];for(const[t,r]of e.model._mixins){const a=(()=>{switch(r){case u.Line:return new l.Line(e,t);case u.LineScalar:return new l.LineScalar(e,t);case u.LineVector:return new l.LineVector(e,t);case u.Fill:return new i.Fill(e,t);case u.FillScalar:return new i.FillScalar(e,t);case u.FillVector:return new i.FillVector(e,t);case u.Text:return new s.Text(e,t);case u.TextScalar:return new s.TextScalar(e,t);case u.TextVector:return new s.TextVector(e,t);case u.Hatch:return new o.Hatch(e,t);case u.HatchScalar:return new o.HatchScalar(e,t);case u.HatchVector:return new o.HatchVector(e,t);default:throw new Error(\"unknown visual\")}})();a instanceof V.VisualProperties&&a.update(),this._visuals.push(a),Object.defineProperty(this,t+a.type,{get:()=>a,configurable:!1,enumerable:!0})}}*[Symbol.iterator](){yield*this._visuals}}r.Visuals=h,h.__name__=\"Visuals\"},\n", - " function _(e,t,i,l,s){l();const a=e(1),n=e(47),h=(0,a.__importStar)(e(48)),o=e(22),_=e(8);function r(e){if((0,_.isArray)(e))return e;switch(e){case\"solid\":return[];case\"dashed\":return[6];case\"dotted\":return[2,4];case\"dotdash\":return[2,4,6,4];case\"dashdot\":return[6,4,2,4];default:return e.split(\" \").map(Number).filter(_.isInteger)}}i.resolve_line_dash=r;class u extends n.VisualProperties{get doit(){const e=this.line_color.get_value(),t=this.line_alpha.get_value(),i=this.line_width.get_value();return!(null==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.get_value(),alpha:this.line_alpha.get_value(),width:this.line_width.get_value(),join:this.line_join.get_value(),cap:this.line_cap.get_value(),dash:this.line_dash.get_value(),offset:this.line_dash_offset.get_value()}}set_value(e){const t=this.line_color.get_value(),i=this.line_alpha.get_value();e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.get_value(),e.lineJoin=this.line_join.get_value(),e.lineCap=this.line_cap.get_value(),e.lineDash=r(this.line_dash.get_value()),e.lineDashOffset=this.line_dash_offset.get_value()}}i.Line=u,u.__name__=\"Line\";class c extends n.VisualUniforms{get doit(){const e=this.line_color.value,t=this.line_alpha.value,i=this.line_width.value;return!(0==e||0==t||0==i)}apply(e){const{doit:t}=this;return t&&(this.set_value(e),e.stroke()),t}values(){return{color:this.line_color.value,alpha:this.line_alpha.value,width:this.line_width.value,join:this.line_join.value,cap:this.line_cap.value,dash:this.line_dash.value,offset:this.line_dash_offset.value}}set_value(e){const t=this.line_color.value,i=this.line_alpha.value;e.strokeStyle=(0,o.color2css)(t,i),e.lineWidth=this.line_width.value,e.lineJoin=this.line_join.value,e.lineCap=this.line_cap.value,e.lineDash=r(this.line_dash.value),e.lineDashOffset=this.line_dash_offset.value}}i.LineScalar=c,c.__name__=\"LineScalar\";class d extends n.VisualUniforms{get doit(){const{line_color:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{line_alpha:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{line_width:i}=this;return!i.is_Scalar()||0!=i.value}apply(e,t){const{doit:i}=this;return i&&(this.set_vectorize(e,t),e.stroke()),i}values(e){return{color:this.line_color.get(e),alpha:this.line_alpha.get(e),width:this.line_width.get(e),join:this.line_join.get(e),cap:this.line_cap.get(e),dash:this.line_dash.get(e),offset:this.line_dash_offset.get(e)}}set_vectorize(e,t){const i=this.line_color.get(t),l=this.line_alpha.get(t),s=this.line_width.get(t),a=this.line_join.get(t),n=this.line_cap.get(t),h=this.line_dash.get(t),_=this.line_dash_offset.get(t);e.strokeStyle=(0,o.color2css)(i,l),e.lineWidth=s,e.lineJoin=a,e.lineCap=n,e.lineDash=r(h),e.lineDashOffset=_}}i.LineVector=d,d.__name__=\"LineVector\",u.prototype.type=\"line\",u.prototype.attrs=Object.keys(h.Line),c.prototype.type=\"line\",c.prototype.attrs=Object.keys(h.LineScalar),d.prototype.type=\"line\",d.prototype.attrs=Object.keys(h.LineVector)},\n", - " function _(t,s,o,i,r){i();class e{constructor(t,s=\"\"){this.obj=t,this.prefix=s;const o=this;this._props=[];for(const i of this.attrs){const r=t.model.properties[s+i];r.change.connect((()=>this.update())),o[i]=r,this._props.push(r)}}*[Symbol.iterator](){yield*this._props}update(){}}o.VisualProperties=e,e.__name__=\"VisualProperties\";class p{constructor(t,s=\"\"){this.obj=t,this.prefix=s;for(const o of this.attrs)Object.defineProperty(this,o,{get:()=>t[s+o]})}*[Symbol.iterator](){for(const t of this.attrs)yield this.obj.model.properties[this.prefix+t]}update(){}}o.VisualUniforms=p,p.__name__=\"VisualUniforms\"},\n", - " function _(e,l,t,a,c){a();const r=e(1),o=(0,r.__importStar)(e(18)),n=e(20),i=(0,r.__importStar)(e(21)),_=e(13);t.Line={line_color:[i.Nullable(i.Color),\"black\"],line_alpha:[i.Alpha,1],line_width:[i.Number,1],line_join:[n.LineJoin,\"bevel\"],line_cap:[n.LineCap,\"butt\"],line_dash:[i.Or(n.LineDash,i.Array(i.Number)),[]],line_dash_offset:[i.Number,0]},t.Fill={fill_color:[i.Nullable(i.Color),\"gray\"],fill_alpha:[i.Alpha,1]},t.Hatch={hatch_color:[i.Nullable(i.Color),\"black\"],hatch_alpha:[i.Alpha,1],hatch_scale:[i.Number,12],hatch_pattern:[i.Nullable(i.Or(n.HatchPatternType,i.String)),null],hatch_weight:[i.Number,1],hatch_extra:[i.Dict(i.AnyRef()),{}]},t.Text={text_color:[i.Nullable(i.Color),\"#444444\"],text_alpha:[i.Alpha,1],text_font:[o.Font,\"helvetica\"],text_font_size:[i.FontSize,\"16px\"],text_font_style:[n.FontStyle,\"normal\"],text_align:[n.TextAlign,\"left\"],text_baseline:[n.TextBaseline,\"bottom\"],text_line_height:[i.Number,1.2]},t.LineScalar={line_color:[o.ColorScalar,\"black\"],line_alpha:[o.NumberScalar,1],line_width:[o.NumberScalar,1],line_join:[o.LineJoinScalar,\"bevel\"],line_cap:[o.LineCapScalar,\"butt\"],line_dash:[o.LineDashScalar,[]],line_dash_offset:[o.NumberScalar,0]},t.FillScalar={fill_color:[o.ColorScalar,\"gray\"],fill_alpha:[o.NumberScalar,1]},t.HatchScalar={hatch_color:[o.ColorScalar,\"black\"],hatch_alpha:[o.NumberScalar,1],hatch_scale:[o.NumberScalar,12],hatch_pattern:[o.NullStringScalar,null],hatch_weight:[o.NumberScalar,1],hatch_extra:[o.AnyScalar,{}]},t.TextScalar={text_color:[o.ColorScalar,\"#444444\"],text_alpha:[o.NumberScalar,1],text_font:[o.FontScalar,\"helvetica\"],text_font_size:[o.FontSizeScalar,\"16px\"],text_font_style:[o.FontStyleScalar,\"normal\"],text_align:[o.TextAlignScalar,\"left\"],text_baseline:[o.TextBaselineScalar,\"bottom\"],text_line_height:[o.NumberScalar,1.2]},t.LineVector={line_color:[o.ColorSpec,\"black\"],line_alpha:[o.NumberSpec,1],line_width:[o.NumberSpec,1],line_join:[o.LineJoinSpec,\"bevel\"],line_cap:[o.LineCapSpec,\"butt\"],line_dash:[o.LineDashSpec,[]],line_dash_offset:[o.NumberSpec,0]},t.FillVector={fill_color:[o.ColorSpec,\"gray\"],fill_alpha:[o.NumberSpec,1]},t.HatchVector={hatch_color:[o.ColorSpec,\"black\"],hatch_alpha:[o.NumberSpec,1],hatch_scale:[o.NumberSpec,12],hatch_pattern:[o.NullStringSpec,null],hatch_weight:[o.NumberSpec,1],hatch_extra:[o.AnyScalar,{}]},t.TextVector={text_color:[o.ColorSpec,\"#444444\"],text_alpha:[o.NumberSpec,1],text_font:[o.FontSpec,\"helvetica\"],text_font_size:[o.FontSizeSpec,\"16px\"],text_font_style:[o.FontStyleSpec,\"normal\"],text_align:[o.TextAlignSpec,\"left\"],text_baseline:[o.TextBaselineSpec,\"bottom\"],text_line_height:[o.NumberSpec,1.2]},t.attrs_of=function(e,l,t,a=!1){const c={};for(const r of(0,_.keys)(t)){const t=`${l}${r}`,o=e[t];c[a?t:r]=o}return c}},\n", - " function _(l,t,e,i,s){i();const a=l(1),o=l(47),r=(0,a.__importStar)(l(48)),_=l(22);class c extends o.VisualProperties{get doit(){const l=this.fill_color.get_value(),t=this.fill_alpha.get_value();return!(null==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.get_value(),alpha:this.fill_alpha.get_value()}}set_value(l){const t=this.fill_color.get_value(),e=this.fill_alpha.get_value();l.fillStyle=(0,_.color2css)(t,e)}}e.Fill=c,c.__name__=\"Fill\";class h extends o.VisualUniforms{get doit(){const l=this.fill_color.value,t=this.fill_alpha.value;return!(0==l||0==t)}apply(l,t){const{doit:e}=this;return e&&(this.set_value(l),l.fill(t)),e}values(){return{color:this.fill_color.value,alpha:this.fill_alpha.value}}set_value(l){const t=this.fill_color.value,e=this.fill_alpha.value;l.fillStyle=(0,_.color2css)(t,e)}}e.FillScalar=h,h.__name__=\"FillScalar\";class u extends o.VisualUniforms{get doit(){const{fill_color:l}=this;if(l.is_Scalar()&&0==l.value)return!1;const{fill_alpha:t}=this;return!t.is_Scalar()||0!=t.value}apply(l,t,e){const{doit:i}=this;return i&&(this.set_vectorize(l,t),l.fill(e)),i}values(l){return{color:this.fill_color.get(l),alpha:this.fill_alpha.get(l)}}set_vectorize(l,t){const e=this.fill_color.get(t),i=this.fill_alpha.get(t);l.fillStyle=(0,_.color2css)(e,i)}}e.FillVector=u,u.__name__=\"FillVector\",c.prototype.type=\"fill\",c.prototype.attrs=Object.keys(r.Fill),h.prototype.type=\"fill\",h.prototype.attrs=Object.keys(r.FillScalar),u.prototype.type=\"fill\",u.prototype.attrs=Object.keys(r.FillVector)},\n", - " function _(t,e,l,s,_){s();const i=t(1),a=t(47),o=(0,i.__importStar)(t(48)),n=t(22);class h extends a.VisualProperties{get doit(){const t=this.text_color.get_value(),e=this.text_alpha.get_value();return!(null==t||0==e)}values(){return{color:this.text_color.get_value(),alpha:this.text_alpha.get_value(),font:this.text_font.get_value(),font_size:this.text_font_size.get_value(),font_style:this.text_font_style.get_value(),align:this.text_align.get_value(),baseline:this.text_baseline.get_value(),line_height:this.text_line_height.get_value()}}set_value(t){const e=this.text_color.get_value(),l=this.text_alpha.get_value();t.fillStyle=(0,n.color2css)(e,l),t.font=this.font_value(),t.textAlign=this.text_align.get_value(),t.textBaseline=this.text_baseline.get_value()}font_value(){return`${this.text_font_style.get_value()} ${this.text_font_size.get_value()} ${this.text_font.get_value()}`}}l.Text=h,h.__name__=\"Text\";class x extends a.VisualUniforms{get doit(){const t=this.text_color.value,e=this.text_alpha.value;return!(0==t||0==e)}values(){return{color:this.text_color.value,alpha:this.text_alpha.value,font:this.text_font.value,font_size:this.text_font_size.value,font_style:this.text_font_style.value,align:this.text_align.value,baseline:this.text_baseline.value,line_height:this.text_line_height.value}}set_value(t){const e=this.text_color.value,l=this.text_alpha.value,s=this.font_value(),_=this.text_align.value,i=this.text_baseline.value;t.fillStyle=(0,n.color2css)(e,l),t.font=s,t.textAlign=_,t.textBaseline=i}font_value(){return`${this.text_font_style.value} ${this.text_font_size.value} ${this.text_font.value}`}}l.TextScalar=x,x.__name__=\"TextScalar\";class u extends a.VisualUniforms{values(t){return{color:this.text_color.get(t),alpha:this.text_alpha.get(t),font:this.text_font.get(t),font_size:this.text_font_size.get(t),font_style:this.text_font_style.get(t),align:this.text_align.get(t),baseline:this.text_baseline.get(t),line_height:this.text_line_height.get(t)}}get doit(){const{text_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{text_alpha:e}=this;return!e.is_Scalar()||0!=e.value}set_vectorize(t,e){const l=this.text_color.get(e),s=this.text_alpha.get(e),_=this.font_value(e),i=this.text_align.get(e),a=this.text_baseline.get(e);t.fillStyle=(0,n.color2css)(l,s),t.font=_,t.textAlign=i,t.textBaseline=a}font_value(t){return`${this.text_font_style.get(t)} ${this.text_font_size.get(t)} ${this.text_font.get(t)}`}}l.TextVector=u,u.__name__=\"TextVector\",h.prototype.type=\"text\",h.prototype.attrs=Object.keys(o.Text),x.prototype.type=\"text\",x.prototype.attrs=Object.keys(o.TextScalar),u.prototype.type=\"text\",u.prototype.attrs=Object.keys(o.TextVector)},\n", - " function _(t,e,a,r,i){r();const h=t(1),s=t(47),n=t(52),c=(0,h.__importStar)(t(18)),_=(0,h.__importStar)(t(48));class l extends s.VisualProperties{constructor(){super(...arguments),this._update_iteration=0}update(){if(this._update_iteration++,this._hatch_image=null,!this.doit)return;const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_scale.get_value(),r=this.hatch_pattern.get_value(),i=this.hatch_weight.get_value(),h=t=>{this._hatch_image=t},s=this.hatch_extra.get_value()[r];if(null!=s){const r=s.get_pattern(t,e,a,i);if(r instanceof Promise){const{_update_iteration:t}=this;r.then((e=>{this._update_iteration==t&&(h(e),this.obj.request_render())}))}else h(r)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,r,t,e,a,i);h(c)}}get doit(){const t=this.hatch_color.get_value(),e=this.hatch_alpha.get_value(),a=this.hatch_pattern.get_value();return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){const e=this.pattern(t);t.fillStyle=null!=e?e:\"transparent\"}pattern(t){const e=this._hatch_image;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.get_value(),e=this.hatch_extra.get_value()[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.Hatch=l,l.__name__=\"Hatch\";class o extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const t=this.hatch_color.value,e=this.hatch_alpha.value,a=this.hatch_pattern.value;return!(null==t||0==e||\" \"==a||\"blank\"==a||null==a)}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=this.hatch_color.value,a=this.hatch_alpha.value,r=this.hatch_scale.value,i=this.hatch_pattern.value,h=this.hatch_weight.value,s=e=>{this._hatch_image=new c.UniformScalar(e,t)},_=this.hatch_extra.value[i];if(null!=_){const t=_.get_pattern(e,a,r,h);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(s(t),this.obj.request_render())}))}else s(t)}else{const t=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(t,i,e,a,r,h);s(c)}}get doit(){return this._static_doit}apply(t,e){const{doit:a}=this;return a&&(this.set_value(t),t.layer.undo_transform((()=>t.fill(e)))),a}set_value(t){var e;t.fillStyle=null!==(e=this.pattern(t))&&void 0!==e?e:\"transparent\"}pattern(t){const e=this._hatch_image.value;return null==e?null:t.createPattern(e,this.repetition())}repetition(){const t=this.hatch_pattern.value,e=this.hatch_extra.value[t];if(null==e)return\"repeat\";switch(e.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchScalar=o,o.__name__=\"HatchScalar\";class u extends s.VisualUniforms{constructor(){super(...arguments),this._static_doit=!1,this._update_iteration=0}_compute_static_doit(){const{hatch_color:t}=this;if(t.is_Scalar()&&0==t.value)return!1;const{hatch_alpha:e}=this;if(e.is_Scalar()&&0==e.value)return!1;const{hatch_pattern:a}=this;if(a.is_Scalar()){const t=a.value;if(\" \"==t||\"blank\"==t||null==t)return!1}return!0}update(){this._update_iteration++;const t=this.hatch_color.length;if(this._hatch_image=new c.UniformScalar(null,t),this._static_doit=this._compute_static_doit(),!this._static_doit)return;const e=(t,e,a,r,i,h)=>{const s=this.hatch_extra.value[t];if(null!=s){const t=s.get_pattern(e,a,r,i);if(t instanceof Promise){const{_update_iteration:e}=this;t.then((t=>{this._update_iteration==e&&(h(t),this.obj.request_render())}))}else h(t)}else{const s=this.obj.canvas.create_layer(),c=(0,n.get_pattern)(s,t,e,a,r,i);h(c)}};if(this.hatch_color.is_Scalar()&&this.hatch_alpha.is_Scalar()&&this.hatch_scale.is_Scalar()&&this.hatch_pattern.is_Scalar()&&this.hatch_weight.is_Scalar()){const a=this.hatch_color.value,r=this.hatch_alpha.value,i=this.hatch_scale.value;e(this.hatch_pattern.value,a,r,i,this.hatch_weight.value,(e=>{this._hatch_image=new c.UniformScalar(e,t)}))}else{const a=new Array(t);a.fill(null),this._hatch_image=new c.UniformVector(a);for(let r=0;r{a[r]=t}))}}}get doit(){return this._static_doit}apply(t,e,a){const{doit:r}=this;return r&&(this.set_vectorize(t,e),t.layer.undo_transform((()=>t.fill(a)))),r}set_vectorize(t,e){var a;t.fillStyle=null!==(a=this.pattern(t,e))&&void 0!==a?a:\"transparent\"}pattern(t,e){const a=this._hatch_image.get(e);return null==a?null:t.createPattern(a,this.repetition(e))}repetition(t){const e=this.hatch_pattern.get(t),a=this.hatch_extra.value[e];if(null==a)return\"repeat\";switch(a.repetition){case\"repeat\":return\"repeat\";case\"repeat_x\":return\"repeat-x\";case\"repeat_y\":return\"repeat-y\";case\"no_repeat\":return\"no-repeat\"}}}a.HatchVector=u,u.__name__=\"HatchVector\",l.prototype.type=\"hatch\",l.prototype.attrs=Object.keys(_.Hatch),o.prototype.type=\"hatch\",o.prototype.attrs=Object.keys(_.HatchScalar),u.prototype.type=\"hatch\",u.prototype.attrs=Object.keys(_.HatchVector)},\n", - " function _(e,o,a,s,r){s();const i=e(22);function l(e,o,a){e.moveTo(0,a+.5),e.lineTo(o,a+.5),e.stroke()}function n(e,o,a){e.moveTo(a+.5,0),e.lineTo(a+.5,o),e.stroke()}function t(e,o){e.moveTo(0,o),e.lineTo(o,0),e.stroke(),e.moveTo(0,0),e.lineTo(o,o),e.stroke()}a.hatch_aliases={\" \":\"blank\",\".\":\"dot\",o:\"ring\",\"-\":\"horizontal_line\",\"|\":\"vertical_line\",\"+\":\"cross\",'\"':\"horizontal_dash\",\":\":\"vertical_dash\",\"@\":\"spiral\",\"/\":\"right_diagonal_line\",\"\\\\\":\"left_diagonal_line\",x:\"diagonal_cross\",\",\":\"right_diagonal_dash\",\"`\":\"left_diagonal_dash\",v:\"horizontal_wave\",\">\":\"vertical_wave\",\"*\":\"criss_cross\"},a.get_pattern=function(e,o,s,r,c,k){return e.resize(c,c),e.prepare(),function(e,o,s,r,c,k){var _;const T=c,v=T/2,h=v/2,d=(0,i.color2css)(s,r);switch(e.strokeStyle=d,e.fillStyle=d,e.lineCap=\"square\",e.lineWidth=k,null!==(_=a.hatch_aliases[o])&&void 0!==_?_:o){case\"blank\":break;case\"dot\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.fill();break;case\"ring\":e.arc(v,v,v/2,0,2*Math.PI,!0),e.stroke();break;case\"horizontal_line\":l(e,T,v);break;case\"vertical_line\":n(e,T,v);break;case\"cross\":l(e,T,v),n(e,T,v);break;case\"horizontal_dash\":l(e,v,v);break;case\"vertical_dash\":n(e,v,v);break;case\"spiral\":{const o=T/30;e.moveTo(v,v);for(let a=0;a<360;a++){const s=.1*a,r=v+o*s*Math.cos(s),i=v+o*s*Math.sin(s);e.lineTo(r,i)}e.stroke();break}case\"right_diagonal_line\":e.moveTo(.5-h,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(5*h+.5,0),e.stroke(),e.stroke();break;case\"left_diagonal_line\":e.moveTo(h+.5,T),e.lineTo(.5-h,0),e.stroke(),e.moveTo(3*h+.5,T),e.lineTo(h+.5,0),e.stroke(),e.moveTo(5*h+.5,T),e.lineTo(3*h+.5,0),e.stroke(),e.stroke();break;case\"diagonal_cross\":t(e,T);break;case\"right_diagonal_dash\":e.moveTo(h+.5,3*h+.5),e.lineTo(3*h+.5,h+.5),e.stroke();break;case\"left_diagonal_dash\":e.moveTo(h+.5,h+.5),e.lineTo(3*h+.5,3*h+.5),e.stroke();break;case\"horizontal_wave\":e.moveTo(0,h),e.lineTo(v,3*h),e.lineTo(T,h),e.stroke();break;case\"vertical_wave\":e.moveTo(h,0),e.lineTo(3*h,v),e.lineTo(h,T),e.stroke();break;case\"criss_cross\":t(e,T),l(e,T,v),n(e,T,v)}}(e.ctx,o,s,r,c,k),e.canvas}},\n", - " function _(e,t,s,n,c){var a;n();const i=e(14),r=e(8),l=e(13),o=e(26),_=e(19);class h extends i.HasProps{constructor(e){super(e)}get is_syncable(){return this.syncable}[o.equals](e,t){return t.eq(this.id,e.id)&&super[o.equals](e,t)}initialize(){super.initialize(),this._js_callbacks=new Map}connect_signals(){super.connect_signals(),this._update_property_callbacks(),this.connect(this.properties.js_property_callbacks.change,(()=>this._update_property_callbacks())),this.connect(this.properties.js_event_callbacks.change,(()=>this._update_event_callbacks())),this.connect(this.properties.subscribed_events.change,(()=>this._update_event_callbacks()))}_process_event(e){var t;for(const s of null!==(t=this.js_event_callbacks[e.event_name])&&void 0!==t?t:[])s.execute(e);null!=this.document&&this.subscribed_events.some((t=>t==e.event_name))&&this.document.event_manager.send_event(e)}trigger_event(e){null!=this.document&&(e.origin=this,this.document.event_manager.trigger(e))}_update_event_callbacks(){null!=this.document?this.document.event_manager.subscribed_models.add(this):_.logger.warn(\"WARNING: Document not defined for updating event callbacks\")}_update_property_callbacks(){const e=e=>{const[t,s=null]=e.split(\":\");return null!=s?this.properties[s][t]:this[t]};for(const[t,s]of this._js_callbacks){const n=e(t);for(const e of s)this.disconnect(n,e)}this._js_callbacks.clear();for(const[t,s]of(0,l.entries)(this.js_property_callbacks)){const n=s.map((e=>()=>e.execute(this)));this._js_callbacks.set(t,n);const c=e(t);for(const e of n)this.connect(c,e)}}_doc_attached(){(0,l.isEmpty)(this.js_event_callbacks)&&0==this.subscribed_events.length||this._update_event_callbacks()}_doc_detached(){this.document.event_manager.subscribed_models.delete(this)}select(e){if((0,r.isString)(e))return[...this.references()].filter((t=>t instanceof h&&t.name===e));if(e.prototype instanceof i.HasProps)return[...this.references()].filter((t=>t instanceof e));throw new Error(\"invalid selector\")}select_one(e){const t=this.select(e);switch(t.length){case 0:return null;case 1:return t[0];default:throw new Error(\"found more than one object matching given selector\")}}}s.Model=h,a=h,h.__name__=\"Model\",a.define((({Any:e,Unknown:t,Boolean:s,String:n,Array:c,Dict:a,Nullable:i})=>({tags:[c(t),[]],name:[i(n),null],js_property_callbacks:[a(c(e)),{}],js_event_callbacks:[a(c(e)),{}],subscribed_events:[c(n),[]],syncable:[s,!0]})))},\n", - " function _(e,t,s,a,r){var c,n;a();const _=e(12),o=e(53),i=e(55),l=e(59),u=e(61),g=e(62),h=e(57),p=e(63),m=e(67);class x{constructor(e,t){this.x_scale=e,this.y_scale=t,this.x_source=this.x_scale.source_range,this.y_source=this.y_scale.source_range,this.ranges=[this.x_source,this.y_source],this.scales=[this.x_scale,this.y_scale]}map_to_screen(e,t){return[this.x_scale.v_compute(e),this.y_scale.v_compute(t)]}map_from_screen(e,t){return[this.x_scale.v_invert(e),this.y_scale.v_invert(t)]}}s.CoordinateTransform=x,x.__name__=\"CoordinateTransform\";class y extends o.Model{constructor(e){super(e)}get x_ranges(){return new Map([[\"default\",this.x_source]])}get y_ranges(){return new Map([[\"default\",this.y_source]])}_get_scale(e,t,s){if(e instanceof m.FactorRange!=t instanceof g.CategoricalScale)throw new Error(`Range ${e.type} is incompatible is Scale ${t.type}`);t instanceof u.LogScale&&e instanceof p.DataRange1d&&(e.scale_hint=\"log\");const a=t.clone();return a.setv({source_range:e,target_range:s}),a}get_transform(e){const{x_source:t,x_scale:s,x_target:a}=this,r=this._get_scale(t,s,a),{y_source:c,y_scale:n,y_target:_}=this,o=this._get_scale(c,n,_),i=new v({source_scale:r,source_range:r.source_range,target_scale:e.x_scale,target_range:e.x_target}),l=new v({source_scale:o,source_range:o.source_range,target_scale:e.y_scale,target_range:e.y_target});return new x(i,l)}}s.CoordinateMapping=y,c=y,y.__name__=\"CoordinateMapping\",c.define((({Ref:e})=>({x_source:[e(h.Range),()=>new p.DataRange1d],y_source:[e(h.Range),()=>new p.DataRange1d],x_scale:[e(i.Scale),()=>new l.LinearScale],y_scale:[e(i.Scale),()=>new l.LinearScale],x_target:[e(h.Range)],y_target:[e(h.Range)]})));class v extends i.Scale{constructor(e){super(e)}get s_compute(){const e=this.source_scale.s_compute,t=this.target_scale.s_compute;return s=>t(e(s))}get s_invert(){const e=this.source_scale.s_invert,t=this.target_scale.s_invert;return s=>e(t(s))}compute(e){return this.s_compute(e)}v_compute(e){const{s_compute:t}=this;return(0,_.map)(e,t)}invert(e){return this.s_invert(e)}v_invert(e){const{s_invert:t}=this;return(0,_.map)(e,t)}}s.CompositeScale=v,n=v,v.__name__=\"CompositeScale\",n.internal((({Ref:e})=>({source_scale:[e(i.Scale)],target_scale:[e(i.Scale)]})))},\n", - " function _(e,t,r,n,s){var _;n();const a=e(56),c=e(57),o=e(58),i=e(24);class u extends a.Transform{constructor(e){super(e)}compute(e){return this.s_compute(e)}v_compute(e){const t=new i.ScreenArray(e.length),{s_compute:r}=this;for(let n=0;n({source_range:[e(c.Range)],target_range:[e(o.Range1d)]})))},\n", - " function _(n,s,o,r,c){r();const e=n(53);class t extends e.Model{constructor(n){super(n)}}o.Transform=t,t.__name__=\"Transform\"},\n", - " function _(e,t,n,i,s){var r;i();const a=e(53);class l extends a.Model{constructor(e){super(e),this.have_updated_interactively=!1}get is_reversed(){return this.start>this.end}get is_valid(){return isFinite(this.min)&&isFinite(this.max)}get span(){return Math.abs(this.end-this.start)}}n.Range=l,r=l,l.__name__=\"Range\",r.define((({Number:e,Tuple:t,Or:n,Auto:i,Nullable:s})=>({bounds:[s(n(t(s(e),s(e)),i)),null],min_interval:[s(e),null],max_interval:[s(e),null]}))),r.internal((({Array:e,AnyRef:t})=>({plots:[e(t()),[]]})))},\n", - " function _(t,e,s,n,r){var a;n();const i=t(57);class _ extends i.Range{constructor(t){super(t)}_set_auto_bounds(){if(\"auto\"==this.bounds){const t=Math.min(this._reset_start,this._reset_end),e=Math.max(this._reset_start,this._reset_end);this.setv({bounds:[t,e]},{silent:!0})}}initialize(){super.initialize(),this._set_auto_bounds()}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}reset(){this._set_auto_bounds();const{_reset_start:t,_reset_end:e}=this;this.start!=t||this.end!=e?this.setv({start:t,end:e}):this.change.emit()}map(t){return new _({start:t(this.start),end:t(this.end)})}widen(t){let{start:e,end:s}=this;return this.is_reversed?(e+=t,s-=t):(e-=t,s+=t),new _({start:e,end:s})}}s.Range1d=_,a=_,_.__name__=\"Range1d\",a.define((({Number:t,Nullable:e})=>({start:[t,0],end:[t,1],reset_start:[e(t),null,{on_update(t,e){e._reset_start=null!=t?t:e.start}}],reset_end:[e(t),null,{on_update(t,e){e._reset_end=null!=t?t:e.end}}]})))},\n", - " function _(t,e,n,r,s){r();const a=t(60);class _ extends a.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e]=this._linear_compute_state();return n=>t*n+e}get s_invert(){const[t,e]=this._linear_compute_state();return n=>(n-e)/t}_linear_compute_state(){const t=this.source_range.start,e=this.source_range.end,n=this.target_range.start,r=(this.target_range.end-n)/(e-t);return[r,-r*t+n]}}n.LinearScale=_,_.__name__=\"LinearScale\"},\n", - " function _(n,c,o,s,e){s();const t=n(55);class u extends t.Scale{constructor(n){super(n)}}o.ContinuousScale=u,u.__name__=\"ContinuousScale\"},\n", - " function _(t,e,a,o,s){o();const r=t(60);class n extends r.ContinuousScale{constructor(t){super(t)}get s_compute(){const[t,e,a,o]=this._compute_state();return s=>{if(0==a)return 0;{const r=(Math.log(s)-o)/a;return isFinite(r)?r*t+e:NaN}}}get s_invert(){const[t,e,a,o]=this._compute_state();return s=>{const r=(s-e)/t;return Math.exp(a*r+o)}}_get_safe_factor(t,e){let a=t<0?0:t,o=e<0?0:e;if(a==o)if(0==a)[a,o]=[1,10];else{const t=Math.log(a)/Math.log(10);a=10**Math.floor(t),o=Math.ceil(t)!=Math.floor(t)?10**Math.ceil(t):10**(Math.ceil(t)+1)}return[a,o]}_compute_state(){const t=this.source_range.start,e=this.source_range.end,a=this.target_range.start,o=this.target_range.end-a,[s,r]=this._get_safe_factor(t,e);let n,c;0==s?(n=Math.log(r),c=0):(n=Math.log(r)-Math.log(s),c=Math.log(s));return[o,a,n,c]}}a.LogScale=n,n.__name__=\"LogScale\"},\n", - " function _(t,e,c,a,s){a();const n=t(55),r=t(59),{_linear_compute_state:o}=r.LinearScale.prototype;class l extends n.Scale{constructor(t){super(t)}get s_compute(){const[t,e]=o.call(this),c=this.source_range;return a=>t*c.synthetic(a)+e}get s_invert(){const[t,e]=o.call(this);return c=>(c-e)/t}}c.CategoricalScale=l,l.__name__=\"CategoricalScale\"},\n", - " function _(t,i,n,e,a){e();const s=t(1);var l;const _=t(64),o=t(20),r=t(9),h=t(19),d=(0,s.__importStar)(t(65)),u=t(66);class g extends _.DataRange{constructor(t){super(t),this.have_updated_interactively=!1}initialize(){super.initialize(),this._initial_start=this.start,this._initial_end=this.end,this._initial_range_padding=this.range_padding,this._initial_range_padding_units=this.range_padding_units,this._initial_follow=this.follow,this._initial_follow_interval=this.follow_interval,this._initial_default_span=this.default_span,this._plot_bounds=new Map}get min(){return Math.min(this.start,this.end)}get max(){return Math.max(this.start,this.end)}computed_renderers(){const{renderers:t,names:i}=this,n=(0,r.concat)(this.plots.map((t=>t.data_renderers)));return(0,u.compute_renderers)(0==t.length?\"auto\":t,n,i)}_compute_plot_bounds(t,i){let n=d.empty();for(const e of t){const t=i.get(e);null==t||!e.visible&&this.only_visible||(n=d.union(n,t))}return n}adjust_bounds_for_aspect(t,i){const n=d.empty();let e=t.x1-t.x0;e<=0&&(e=1);let a=t.y1-t.y0;a<=0&&(a=1);const s=.5*(t.x1+t.x0),l=.5*(t.y1+t.y0);return el&&(\"start\"==this.follow?a=e+s*l:\"end\"==this.follow&&(e=a-s*l)),[e,a]}update(t,i,n,e){if(this.have_updated_interactively)return;const a=this.computed_renderers();let s=this._compute_plot_bounds(a,t);null!=e&&(s=this.adjust_bounds_for_aspect(s,e)),this._plot_bounds.set(n,s);const[l,_]=this._compute_min_max(this._plot_bounds.entries(),i);let[o,r]=this._compute_range(l,_);null!=this._initial_start&&(\"log\"==this.scale_hint?this._initial_start>0&&(o=this._initial_start):o=this._initial_start),null!=this._initial_end&&(\"log\"==this.scale_hint?this._initial_end>0&&(r=this._initial_end):r=this._initial_end);let h=!1;\"auto\"==this.bounds&&(this.setv({bounds:[o,r]},{silent:!0}),h=!0);const[d,u]=[this.start,this.end];if(o!=d||r!=u){const t={};o!=d&&(t.start=o),r!=u&&(t.end=r),this.setv(t),h=!1}h&&this.change.emit()}reset(){this.have_updated_interactively=!1,this.setv({range_padding:this._initial_range_padding,range_padding_units:this._initial_range_padding_units,follow:this._initial_follow,follow_interval:this._initial_follow_interval,default_span:this._initial_default_span},{silent:!0}),this.change.emit()}}n.DataRange1d=g,l=g,g.__name__=\"DataRange1d\",l.define((({Boolean:t,Number:i,Nullable:n})=>({start:[i],end:[i],range_padding:[i,.1],range_padding_units:[o.PaddingUnits,\"percent\"],flipped:[t,!1],follow:[n(o.StartEnd),null],follow_interval:[n(i),null],default_span:[i,2],only_visible:[t,!1]}))),l.internal((({Enum:t})=>({scale_hint:[t(\"log\",\"auto\"),\"auto\"]})))},\n", - " function _(e,n,a,r,s){var t;r();const c=e(57);class _ extends c.Range{constructor(e){super(e)}}a.DataRange=_,t=_,_.__name__=\"DataRange\",t.define((({String:e,Array:n,AnyRef:a})=>({names:[n(e),[]],renderers:[n(a()),[]]})))},\n", - " function _(t,i,e,h,r){h();const s=t(24),n=t(26),{min:x,max:y}=Math;e.empty=function(){return{x0:1/0,y0:1/0,x1:-1/0,y1:-1/0}},e.positive_x=function(){return{x0:Number.MIN_VALUE,y0:-1/0,x1:1/0,y1:1/0}},e.positive_y=function(){return{x0:-1/0,y0:Number.MIN_VALUE,x1:1/0,y1:1/0}},e.union=function(t,i){return{x0:x(t.x0,i.x0),x1:y(t.x1,i.x1),y0:x(t.y0,i.y0),y1:y(t.y1,i.y1)}};class o{constructor(t){if(null==t)this.x0=0,this.y0=0,this.x1=0,this.y1=0;else if(\"x0\"in t){const{x0:i,y0:e,x1:h,y1:r}=t;if(!(i<=h&&e<=r))throw new Error(`invalid bbox {x0: ${i}, y0: ${e}, x1: ${h}, y1: ${r}}`);this.x0=i,this.y0=e,this.x1=h,this.y1=r}else if(\"x\"in t){const{x:i,y:e,width:h,height:r}=t;if(!(h>=0&&r>=0))throw new Error(`invalid bbox {x: ${i}, y: ${e}, width: ${h}, height: ${r}}`);this.x0=i,this.y0=e,this.x1=i+h,this.y1=e+r}else{let i,e,h,r;if(\"width\"in t)if(\"left\"in t)i=t.left,e=i+t.width;else if(\"right\"in t)e=t.right,i=e-t.width;else{const h=t.width/2;i=t.hcenter-h,e=t.hcenter+h}else i=t.left,e=t.right;if(\"height\"in t)if(\"top\"in t)h=t.top,r=h+t.height;else if(\"bottom\"in t)r=t.bottom,h=r-t.height;else{const i=t.height/2;h=t.vcenter-i,r=t.vcenter+i}else h=t.top,r=t.bottom;if(!(i<=e&&h<=r))throw new Error(`invalid bbox {left: ${i}, top: ${h}, right: ${e}, bottom: ${r}}`);this.x0=i,this.y0=h,this.x1=e,this.y1=r}}static from_rect({left:t,right:i,top:e,bottom:h}){return new o({x0:Math.min(t,i),y0:Math.min(e,h),x1:Math.max(t,i),y1:Math.max(e,h)})}equals(t){return this.x0==t.x0&&this.y0==t.y0&&this.x1==t.x1&&this.y1==t.y1}[n.equals](t,i){return i.eq(this.x0,t.x0)&&i.eq(this.y0,t.y0)&&i.eq(this.x1,t.x1)&&i.eq(this.y1,t.y1)}toString(){return`BBox({left: ${this.left}, top: ${this.top}, width: ${this.width}, height: ${this.height}})`}get left(){return this.x0}get top(){return this.y0}get right(){return this.x1}get bottom(){return this.y1}get p0(){return[this.x0,this.y0]}get p1(){return[this.x1,this.y1]}get x(){return this.x0}get y(){return this.y0}get width(){return this.x1-this.x0}get height(){return this.y1-this.y0}get size(){return{width:this.width,height:this.height}}get rect(){const{x0:t,y0:i,x1:e,y1:h}=this;return{p0:{x:t,y:i},p1:{x:e,y:i},p2:{x:e,y:h},p3:{x:t,y:h}}}get box(){const{x:t,y:i,width:e,height:h}=this;return{x:t,y:i,width:e,height:h}}get h_range(){return{start:this.x0,end:this.x1}}get v_range(){return{start:this.y0,end:this.y1}}get ranges(){return[this.h_range,this.v_range]}get aspect(){return this.width/this.height}get hcenter(){return(this.left+this.right)/2}get vcenter(){return(this.top+this.bottom)/2}get area(){return this.width*this.height}relative(){const{width:t,height:i}=this;return new o({x:0,y:0,width:t,height:i})}translate(t,i){const{x:e,y:h,width:r,height:s}=this;return new o({x:t+e,y:i+h,width:r,height:s})}relativize(t,i){return[t-this.x,i-this.y]}contains(t,i){return this.x0<=t&&t<=this.x1&&this.y0<=i&&i<=this.y1}clip(t,i){return tthis.x1&&(t=this.x1),ithis.y1&&(i=this.y1),[t,i]}grow_by(t){return new o({left:this.left-t,right:this.right+t,top:this.top-t,bottom:this.bottom+t})}shrink_by(t){return new o({left:this.left+t,right:this.right-t,top:this.top+t,bottom:this.bottom-t})}union(t){return new o({x0:x(this.x0,t.x0),y0:x(this.y0,t.y0),x1:y(this.x1,t.x1),y1:y(this.y1,t.y1)})}intersection(t){return this.intersects(t)?new o({x0:y(this.x0,t.x0),y0:y(this.y0,t.y0),x1:x(this.x1,t.x1),y1:x(this.y1,t.y1)}):null}intersects(t){return!(t.x1this.x1||t.y1this.y1)}get xview(){return{compute:t=>this.left+t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.left;for(let h=0;hthis.bottom-t,v_compute:t=>{const i=new s.ScreenArray(t.length),e=this.bottom;for(let h=0;h0&&(r=r.filter((n=>(0,l.includes)(t,n.name)))),r}},\n", - " function _(t,n,e,i,s){var r;i();const a=t(57),o=t(20),g=t(21),p=t(24),c=t(9),l=t(8),u=t(11);function h(t,n,e=0){const i=new Map;for(let s=0;sa.get(t).value)));r.set(t,{value:l/s,mapping:a}),o+=s+n+p}return[r,(a.size-1)*n+g]}function _(t,n,e,i,s=0){var r;const a=new Map,o=new Map;for(const[n,e,i]of t){const t=null!==(r=o.get(n))&&void 0!==r?r:[];o.set(n,[...t,[e,i]])}let g=s,p=0;for(const[t,s]of o){const r=s.length,[o,l]=d(s,e,i,g);p+=l;const u=(0,c.sum)(s.map((([t])=>o.get(t).value)));a.set(t,{value:u/r,mapping:o}),g+=r+n+l}return[a,(o.size-1)*n+p]}e.Factor=(0,g.Or)(g.String,(0,g.Tuple)(g.String,g.String),(0,g.Tuple)(g.String,g.String,g.String)),e.FactorSeq=(0,g.Or)((0,g.Array)(g.String),(0,g.Array)((0,g.Tuple)(g.String,g.String)),(0,g.Array)((0,g.Tuple)(g.String,g.String,g.String))),e.map_one_level=h,e.map_two_levels=d,e.map_three_levels=_;class f extends a.Range{constructor(t){super(t)}get min(){return this.start}get max(){return this.end}initialize(){super.initialize(),this._init(!0)}connect_signals(){super.connect_signals(),this.connect(this.properties.factors.change,(()=>this.reset())),this.connect(this.properties.factor_padding.change,(()=>this.reset())),this.connect(this.properties.group_padding.change,(()=>this.reset())),this.connect(this.properties.subgroup_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding.change,(()=>this.reset())),this.connect(this.properties.range_padding_units.change,(()=>this.reset()))}reset(){this._init(!1),this.change.emit()}_lookup(t){switch(t.length){case 1:{const[n]=t,e=this._mapping.get(n);return null!=e?e.value:NaN}case 2:{const[n,e]=t,i=this._mapping.get(n);if(null!=i){const t=i.mapping.get(e);if(null!=t)return t.value}return NaN}case 3:{const[n,e,i]=t,s=this._mapping.get(n);if(null!=s){const t=s.mapping.get(e);if(null!=t){const n=t.mapping.get(i);if(null!=n)return n.value}}return NaN}default:(0,u.unreachable)()}}synthetic(t){if((0,l.isNumber)(t))return t;if((0,l.isString)(t))return this._lookup([t]);let n=0;const e=t[t.length-1];return(0,l.isNumber)(e)&&(n=e,t=t.slice(0,-1)),this._lookup(t)+n}v_synthetic(t){const n=t.length,e=new p.ScreenArray(n);for(let i=0;i{if((0,c.every)(this.factors,l.isString)){const t=this.factors,[n,e]=h(t,this.factor_padding);return{levels:1,mapping:n,tops:null,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&2==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])))){const t=this.factors,[n,e]=d(t,this.group_padding,this.factor_padding),i=[...n.keys()];return{levels:2,mapping:n,tops:i,mids:null,inside_padding:e}}if((0,c.every)(this.factors,(t=>(0,l.isArray)(t)&&3==t.length&&(0,l.isString)(t[0])&&(0,l.isString)(t[1])&&(0,l.isString)(t[2])))){const t=this.factors,[n,e]=_(t,this.group_padding,this.subgroup_padding,this.factor_padding),i=[...n.keys()],s=[];for(const[t,e]of n)for(const n of e.mapping.keys())s.push([t,n]);return{levels:3,mapping:n,tops:i,mids:s,inside_padding:e}}(0,u.unreachable)()})();this._mapping=e,this.tops=i,this.mids=s;let a=0,o=this.factors.length+r;if(\"percent\"==this.range_padding_units){const t=(o-a)*this.range_padding/2;a-=t,o+=t}else a-=this.range_padding,o+=this.range_padding;this.setv({start:a,end:o,levels:n},{silent:t}),\"auto\"==this.bounds&&this.setv({bounds:[a,o]},{silent:!0})}}e.FactorRange=f,r=f,f.__name__=\"FactorRange\",r.define((({Number:t})=>({factors:[e.FactorSeq,[]],factor_padding:[t,0],subgroup_padding:[t,.8],group_padding:[t,1.4],range_padding:[t,0],range_padding_units:[o.PaddingUnits,\"percent\"],start:[t],end:[t]}))),r.internal((({Number:t,String:n,Array:e,Tuple:i,Nullable:s})=>({levels:[t],mids:[s(e(i(n,n))),null],tops:[s(e(n)),null]})))},\n", - " function _(t,e,s,a,i){a();const n=t(1);var _;const r=t(69),o=t(112),l=t(48),d=t(20),h=t(24),c=t(113),u=(0,n.__importStar)(t(18)),v=t(10);class p extends r.DataAnnotationView{async lazy_initialize(){await super.lazy_initialize();const{start:t,end:e}=this.model;null!=t&&(this.start=await(0,c.build_view)(t,{parent:this})),null!=e&&(this.end=await(0,c.build_view)(e,{parent:this}))}set_data(t){var e,s;super.set_data(t),null===(e=this.start)||void 0===e||e.set_data(t),null===(s=this.end)||void 0===s||s.set_data(t)}remove(){var t,e;null===(t=this.start)||void 0===t||t.remove(),null===(e=this.end)||void 0===e||e.remove(),super.remove()}map_data(){const{frame:t}=this.plot_view;\"data\"==this.model.start_units?(this._sx_start=this.coordinates.x_scale.v_compute(this._x_start),this._sy_start=this.coordinates.y_scale.v_compute(this._y_start)):(this._sx_start=t.bbox.xview.v_compute(this._x_start),this._sy_start=t.bbox.yview.v_compute(this._y_start)),\"data\"==this.model.end_units?(this._sx_end=this.coordinates.x_scale.v_compute(this._x_end),this._sy_end=this.coordinates.y_scale.v_compute(this._y_end)):(this._sx_end=t.bbox.xview.v_compute(this._x_end),this._sy_end=t.bbox.yview.v_compute(this._y_end));const{_sx_start:e,_sy_start:s,_sx_end:a,_sy_end:i}=this,n=e.length,_=this._angles=new h.ScreenArray(n);for(let t=0;t({x_start:[u.XCoordinateSpec,{field:\"x_start\"}],y_start:[u.YCoordinateSpec,{field:\"y_start\"}],start_units:[d.SpatialUnits,\"data\"],start:[e(t(o.ArrowHead)),null],x_end:[u.XCoordinateSpec,{field:\"x_end\"}],y_end:[u.YCoordinateSpec,{field:\"y_end\"}],end_units:[d.SpatialUnits,\"data\"],end:[e(t(o.ArrowHead)),()=>new o.OpenHead]})))},\n", - " function _(t,e,n,s,a){s();const o=t(1);var i;const c=t(40),r=t(70),_=t(75),l=t(78),h=(0,o.__importStar)(t(18));class d extends c.AnnotationView{constructor(){super(...arguments),this._initial_set_data=!1}connect_signals(){super.connect_signals();const t=()=>{this.set_data(this.model.source),this._rerender()};this.connect(this.model.change,t),this.connect(this.model.source.streaming,t),this.connect(this.model.source.patching,t),this.connect(this.model.source.change,t)}_rerender(){this.request_render()}set_data(t){const e=this;for(const n of this.model)if(n instanceof h.VectorSpec||n instanceof h.ScalarSpec)if(n instanceof h.BaseCoordinateSpec){const s=n.array(t);e[`_${n.attr}`]=s}else{const s=n.uniform(t);e[`${n.attr}`]=s}this.plot_model.use_map&&(null!=e._x&&l.inplace.project_xy(e._x,e._y),null!=e._xs&&l.inplace.project_xsys(e._xs,e._ys));for(const t of this.visuals)t.update()}_render(){this._initial_set_data||(this.set_data(this.model.source),this._initial_set_data=!0),this.map_data(),this.paint(this.layer.ctx)}}n.DataAnnotationView=d,d.__name__=\"DataAnnotationView\";class u extends c.Annotation{constructor(t){super(t)}}n.DataAnnotation=u,i=u,u.__name__=\"DataAnnotation\",i.define((({Ref:t})=>({source:[t(r.ColumnarDataSource),()=>new _.ColumnDataSource]})))},\n", - " function _(t,e,n,s,a){var i;s();const r=t(71),l=t(15),c=t(19),o=t(73),h=t(8),u=t(9),g=t(13),d=t(72),_=t(74),m=t(29);class w extends r.DataSource{constructor(t){super(t),this.selection_manager=new o.SelectionManager(this)}get_array(t){let e=this.data[t];return null==e?this.data[t]=e=[]:(0,h.isArray)(e)||(this.data[t]=e=Array.from(e)),e}initialize(){super.initialize(),this._select=new l.Signal0(this,\"select\"),this.inspect=new l.Signal(this,\"inspect\"),this.streaming=new l.Signal0(this,\"streaming\"),this.patching=new l.Signal(this,\"patching\")}get_column(t){const e=this.data[t];return null!=e?e:null}columns(){return(0,g.keys)(this.data)}get_length(t=!0){const e=(0,u.uniq)((0,g.values)(this.data).map((t=>(0,m.is_NDArray)(t)?t.shape[0]:t.length)));switch(e.length){case 0:return null;case 1:return e[0];default:{const n=\"data source has columns of inconsistent lengths\";if(t)return c.logger.warn(n),e.sort()[0];throw new Error(n)}}}get length(){var t;return null!==(t=this.get_length())&&void 0!==t?t:0}clear(){const t={};for(const e of this.columns())t[e]=new this.data[e].constructor(0);this.data=t}}n.ColumnarDataSource=w,i=w,w.__name__=\"ColumnarDataSource\",i.define((({Ref:t})=>({selection_policy:[t(_.SelectionPolicy),()=>new _.UnionRenderers]}))),i.internal((({AnyRef:t})=>({inspected:[t(),()=>new d.Selection]})))},\n", - " function _(e,c,n,t,o){var a;t();const s=e(53),r=e(72);class l extends s.Model{constructor(e){super(e)}}n.DataSource=l,a=l,l.__name__=\"DataSource\",a.define((({Ref:e})=>({selected:[e(r.Selection),()=>new r.Selection]})))},\n", - " function _(i,e,s,t,n){var l;t();const c=i(53),d=i(9),h=i(13);class _ extends c.Model{constructor(i){super(i)}get_view(){return this.view}get selected_glyph(){return this.selected_glyphs.length>0?this.selected_glyphs[0]:null}add_to_selected_glyphs(i){this.selected_glyphs.push(i)}update(i,e=!0,s=\"replace\"){switch(s){case\"replace\":this.indices=i.indices,this.line_indices=i.line_indices,this.multiline_indices=i.multiline_indices,this.image_indices=i.image_indices,this.view=i.view,this.selected_glyphs=i.selected_glyphs;break;case\"append\":this.update_through_union(i);break;case\"intersect\":this.update_through_intersection(i);break;case\"subtract\":this.update_through_subtraction(i)}}clear(){this.indices=[],this.line_indices=[],this.multiline_indices={},this.image_indices=[],this.view=null,this.selected_glyphs=[]}map(i){return new _(Object.assign(Object.assign({},this.attributes),{indices:this.indices.map(i),multiline_indices:(0,h.to_object)((0,h.entries)(this.multiline_indices).map((([e,s])=>[i(Number(e)),s]))),image_indices:this.image_indices.map((e=>Object.assign(Object.assign({},e),{index:i(e.index)})))}))}is_empty(){return 0==this.indices.length&&0==this.line_indices.length&&0==this.image_indices.length}update_through_union(i){this.indices=(0,d.union)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_intersection(i){this.indices=(0,d.intersection)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}update_through_subtraction(i){this.indices=(0,d.difference)(this.indices,i.indices),this.selected_glyphs=(0,d.union)(i.selected_glyphs,this.selected_glyphs),this.line_indices=(0,d.union)(i.line_indices,this.line_indices),this.view=i.view,this.multiline_indices=(0,h.merge)(i.multiline_indices,this.multiline_indices)}}s.Selection=_,l=_,_.__name__=\"Selection\",l.define((({Int:i,Array:e,Dict:s})=>({indices:[e(i),[]],line_indices:[e(i),[]],multiline_indices:[s(e(i)),{}]}))),l.internal((({Int:i,Array:e,AnyRef:s,Struct:t,Nullable:n})=>({selected_glyphs:[e(s()),[]],view:[n(s()),null],image_indices:[e(t({index:i,dim1:i,dim2:i,flat_index:i})),[]]})))},\n", - " function _(e,t,o,s,c){s();const n=e(72);function i(e){return\"GlyphRenderer\"==e.model.type}function l(e){return\"GraphRenderer\"==e.model.type}class r{constructor(e){this.source=e,this.inspectors=new Map}select(e,t,o,s=\"replace\"){const c=[],n=[];for(const t of e)i(t)?c.push(t):l(t)&&n.push(t);let r=!1;for(const e of n){const c=e.model.selection_policy.hit_test(t,e);r=r||e.model.selection_policy.do_selection(c,e.model,o,s)}if(c.length>0){const e=this.source.selection_policy.hit_test(t,c);r=r||this.source.selection_policy.do_selection(e,this.source,o,s)}return r}inspect(e,t){let o=!1;if(i(e)){const s=e.hit_test(t);if(null!=s){o=!s.is_empty();const c=this.get_or_create_inspector(e.model);c.update(s,!0,\"replace\"),this.source.setv({inspected:c},{silent:!0}),this.source.inspect.emit([e.model,{geometry:t}])}}else if(l(e)){const s=e.model.inspection_policy.hit_test(t,e);o=o||e.model.inspection_policy.do_inspection(s,t,e,!1,\"replace\")}return o}clear(e){this.source.selected.clear(),null!=e&&this.get_or_create_inspector(e.model).clear()}get_or_create_inspector(e){let t=this.inspectors.get(e);return null==t&&(t=new n.Selection,this.inspectors.set(e,t)),t}}o.SelectionManager=r,r.__name__=\"SelectionManager\"},\n", - " function _(e,t,n,s,o){s();const r=e(53);class c extends r.Model{do_selection(e,t,n,s){return null!=e&&(t.selected.update(e,n,s),t._select.emit(),!t.selected.is_empty())}}n.SelectionPolicy=c,c.__name__=\"SelectionPolicy\";class l extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_intersection(t);return e}return null}}n.IntersectRenderers=l,l.__name__=\"IntersectRenderers\";class _ extends c{hit_test(e,t){const n=[];for(const s of t){const t=s.hit_test(e);null!=t&&n.push(t)}if(n.length>0){const e=n[0];for(const t of n)e.update_through_union(t);return e}return null}}n.UnionRenderers=_,_.__name__=\"UnionRenderers\"},\n", - " function _(t,n,e,s,o){s();const r=t(1);var l;const c=t(70),i=t(8),a=t(13),u=(0,r.__importStar)(t(76)),h=t(77),d=t(35);function f(t,n,e){if((0,i.isArray)(t)){const s=t.concat(n);return null!=e&&s.length>e?s.slice(-e):s}if((0,i.isTypedArray)(t)){const s=t.length+n.length;if(null!=e&&s>e){const o=s-e,r=t.length;let l;t.length({data:[t(n),{}]})))},\n", - " function _(t,n,o,e,c){e(),o.concat=function(t,...n){let o=t.length;for(const t of n)o+=t.length;const e=new t.constructor(o);e.set(t,0);let c=t.length;for(const t of n)e.set(t,c),c+=t.length;return e}},\n", - " function _(n,o,t,e,f){function c(...n){const o=new Set;for(const t of n)for(const n of t)o.add(n);return o}e(),t.union=c,t.intersection=function(n,...o){const t=new Set;n:for(const e of n){for(const n of o)if(!n.has(e))continue n;t.add(e)}return t},t.difference=function(n,...o){const t=new Set(n);for(const n of c(...o))t.delete(n);return t}},\n", - " function _(n,t,e,o,r){o();const c=n(1),l=(0,c.__importDefault)(n(79)),i=(0,c.__importDefault)(n(80)),u=n(24),a=new i.default(\"GOOGLE\"),s=new i.default(\"WGS84\"),f=(0,l.default)(s,a);e.wgs84_mercator={compute:(n,t)=>isFinite(n)&&isFinite(t)?f.forward([n,t]):[NaN,NaN],invert:(n,t)=>isFinite(n)&&isFinite(t)?f.inverse([n,t]):[NaN,NaN]};const _={lon:[-20026376.39,20026376.39],lat:[-20048966.1,20048966.1]},p={lon:[-180,180],lat:[-85.06,85.06]},{min:g,max:h}=Math;function m(n,t){const o=g(n.length,t.length),r=(0,u.infer_type)(n,t),c=new r(o),l=new r(o);return e.inplace.project_xy(n,t,c,l),[c,l]}e.clip_mercator=function(n,t,e){const[o,r]=_[e];return[h(n,o),g(t,r)]},e.in_bounds=function(n,t){const[e,o]=p[t];return e2?void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name?\"number\"==typeof o.z?[o.x,o.y,o.z].concat(t.splice(3)):[o.x,o.y,t[2]].concat(t.splice(3)):[o.x,o.y].concat(t.splice(2)):[o.x,o.y]):(a=(0,c.default)(e,n,t,r),2===(i=Object.keys(t)).length||i.forEach((function(r){if(void 0!==e.name&&\"geocent\"===e.name||void 0!==n.name&&\"geocent\"===n.name){if(\"x\"===r||\"y\"===r||\"z\"===r)return}else if(\"x\"===r||\"y\"===r)return;a[r]=t[r]})),a)}function l(e){return e instanceof i.default?e:e.oProj?e.oProj:(0,i.default)(e)}t.default=function(e,n,t){e=l(e);var r,o=!1;return void 0===n?(n=e,e=u,o=!0):(void 0!==n.x||Array.isArray(n))&&(t=n,n=e,e=u,o=!0),n=l(n),t?f(e,n,t):(r={forward:function(t,r){return f(e,n,t,r)},inverse:function(t,r){return f(n,e,t,r)}},o&&(r.oProj=n),r)}},\n", - " function _(t,e,a,s,i){s();const l=t(1),u=(0,l.__importDefault)(t(81)),r=(0,l.__importDefault)(t(92)),d=(0,l.__importDefault)(t(93)),o=t(101),f=(0,l.__importDefault)(t(103)),p=(0,l.__importDefault)(t(104)),m=(0,l.__importDefault)(t(88)),n=t(105);function h(t,e){if(!(this instanceof h))return new h(t);e=e||function(t){if(t)throw t};var a=(0,u.default)(t);if(\"object\"==typeof a){var s=h.projections.get(a.projName);if(s){if(a.datumCode&&\"none\"!==a.datumCode){var i=(0,m.default)(f.default,a.datumCode);i&&(a.datum_params=a.datum_params||(i.towgs84?i.towgs84.split(\",\"):null),a.ellps=i.ellipse,a.datumName=i.datumName?i.datumName:a.datumCode)}a.k0=a.k0||1,a.axis=a.axis||\"enu\",a.ellps=a.ellps||\"wgs84\",a.lat1=a.lat1||a.lat0;var l=(0,o.sphere)(a.a,a.b,a.rf,a.ellps,a.sphere),d=(0,o.eccentricity)(l.a,l.b,l.rf,a.R_A),_=(0,n.getNadgrids)(a.nadgrids),c=a.datum||(0,p.default)(a.datumCode,a.datum_params,l.a,l.b,d.es,d.ep2,_);(0,r.default)(this,a),(0,r.default)(this,s),this.a=l.a,this.b=l.b,this.rf=l.rf,this.sphere=l.sphere,this.es=d.es,this.e=d.e,this.ep2=d.ep2,this.datum=c,this.init(),e(null,this)}else e(t)}else e(t)}h.projections=d.default,h.projections.start(),a.default=h},\n", - " function _(t,r,n,u,e){u();const f=t(1),i=(0,f.__importDefault)(t(82)),a=(0,f.__importDefault)(t(89)),o=(0,f.__importDefault)(t(84)),l=(0,f.__importDefault)(t(88));var C=[\"PROJECTEDCRS\",\"PROJCRS\",\"GEOGCS\",\"GEOCCS\",\"PROJCS\",\"LOCAL_CS\",\"GEODCRS\",\"GEODETICCRS\",\"GEODETICDATUM\",\"ENGCRS\",\"ENGINEERINGCRS\"];var d=[\"3857\",\"900913\",\"3785\",\"102113\"];n.default=function(t){if(!function(t){return\"string\"==typeof t}(t))return t;if(function(t){return t in i.default}(t))return i.default[t];if(function(t){return C.some((function(r){return t.indexOf(r)>-1}))}(t)){var r=(0,a.default)(t);if(function(t){var r=(0,l.default)(t,\"authority\");if(r){var n=(0,l.default)(r,\"epsg\");return n&&d.indexOf(n)>-1}}(r))return i.default[\"EPSG:3857\"];var n=function(t){var r=(0,l.default)(t,\"extension\");if(r)return(0,l.default)(r,\"proj4\")}(r);return n?(0,o.default)(n):r}return function(t){return\"+\"===t[0]}(t)?(0,o.default)(t):void 0}},\n", - " function _(t,r,i,e,n){e();const f=t(1),a=(0,f.__importDefault)(t(83)),l=(0,f.__importDefault)(t(84)),u=(0,f.__importDefault)(t(89));function o(t){var r=this;if(2===arguments.length){var i=arguments[1];\"string\"==typeof i?\"+\"===i.charAt(0)?o[t]=(0,l.default)(arguments[1]):o[t]=(0,u.default)(arguments[1]):o[t]=i}else if(1===arguments.length){if(Array.isArray(t))return t.map((function(t){Array.isArray(t)?o.apply(r,t):o(t)}));if(\"string\"==typeof t){if(t in o)return o[t]}else\"EPSG\"in t?o[\"EPSG:\"+t.EPSG]=t:\"ESRI\"in t?o[\"ESRI:\"+t.ESRI]=t:\"IAU2000\"in t?o[\"IAU2000:\"+t.IAU2000]=t:console.log(t);return}}(0,a.default)(o),i.default=o},\n", - " function _(t,l,G,S,e){S(),G.default=function(t){t(\"EPSG:4326\",\"+title=WGS 84 (long/lat) +proj=longlat +ellps=WGS84 +datum=WGS84 +units=degrees\"),t(\"EPSG:4269\",\"+title=NAD83 (long/lat) +proj=longlat +a=6378137.0 +b=6356752.31414036 +ellps=GRS80 +datum=NAD83 +units=degrees\"),t(\"EPSG:3857\",\"+title=WGS 84 / Pseudo-Mercator +proj=merc +a=6378137 +b=6378137 +lat_ts=0.0 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o.push(!0),t[o[0].toLowerCase()]=o[1],t}),{}),c={proj:\"projName\",datum:\"datumCode\",rf:function(t){u.rf=parseFloat(t)},lat_0:function(t){u.lat0=t*r.D2R},lat_1:function(t){u.lat1=t*r.D2R},lat_2:function(t){u.lat2=t*r.D2R},lat_ts:function(t){u.lat_ts=t*r.D2R},lon_0:function(t){u.long0=t*r.D2R},lon_1:function(t){u.long1=t*r.D2R},lon_2:function(t){u.long2=t*r.D2R},alpha:function(t){u.alpha=parseFloat(t)*r.D2R},gamma:function(t){u.rectified_grid_angle=parseFloat(t)},lonc:function(t){u.longc=t*r.D2R},x_0:function(t){u.x0=parseFloat(t)},y_0:function(t){u.y0=parseFloat(t)},k_0:function(t){u.k0=parseFloat(t)},k:function(t){u.k0=parseFloat(t)},a:function(t){u.a=parseFloat(t)},b:function(t){u.b=parseFloat(t)},r_a:function(){u.R_A=!0},zone:function(t){u.zone=parseInt(t,10)},south:function(){u.utmSouth=!0},towgs84:function(t){u.datum_params=t.split(\",\").map((function(t){return parseFloat(t)}))},to_meter:function(t){u.to_meter=parseFloat(t)},units:function(t){u.units=t;var n=(0,l.default)(f.default,t);n&&(u.to_meter=n.to_meter)},from_greenwich:function(t){u.from_greenwich=t*r.D2R},pm:function(t){var n=(0,l.default)(i.default,t);u.from_greenwich=(n||parseFloat(t))*r.D2R},nadgrids:function(t){\"@null\"===t?u.datumCode=\"none\":u.nadgrids=t},axis:function(t){var n=\"ewnsud\";3===t.length&&-1!==n.indexOf(t.substr(0,1))&&-1!==n.indexOf(t.substr(1,1))&&-1!==n.indexOf(t.substr(2,1))&&(u.axis=t)},approx:function(){u.approx=!0}};for(n in e)o=e[n],n in c?\"function\"==typeof(a=c[n])?a(o):u[a]=o:u[n]=o;return\"string\"==typeof u.datumCode&&\"WGS84\"!==u.datumCode&&(u.datumCode=u.datumCode.toLowerCase()),u}},\n", - " function _(S,_,P,R,I){R(),P.PJD_3PARAM=1,P.PJD_7PARAM=2,P.PJD_GRIDSHIFT=3,P.PJD_WGS84=4,P.PJD_NODATUM=5,P.SRS_WGS84_SEMIMAJOR=6378137,P.SRS_WGS84_SEMIMINOR=6356752.314,P.SRS_WGS84_ESQUARED=.0066943799901413165,P.SEC_TO_RAD=484813681109536e-20,P.HALF_PI=Math.PI/2,P.SIXTH=.16666666666666666,P.RA4=.04722222222222222,P.RA6=.022156084656084655,P.EPSLN=1e-10,P.D2R=.017453292519943295,P.R2D=57.29577951308232,P.FORTPI=Math.PI/4,P.TWO_PI=2*Math.PI,P.SPI=3.14159265359},\n", - " function _(o,r,a,e,s){e();var n={};a.default=n,n.greenwich=0,n.lisbon=-9.131906111111,n.paris=2.337229166667,n.bogota=-74.080916666667,n.madrid=-3.687938888889,n.rome=12.452333333333,n.bern=7.439583333333,n.jakarta=106.807719444444,n.ferro=-17.666666666667,n.brussels=4.367975,n.stockholm=18.058277777778,n.athens=23.7163375,n.oslo=10.722916666667},\n", - " function _(t,e,f,o,u){o(),f.default={ft:{to_meter:.3048},\"us-ft\":{to_meter:1200/3937}}},\n", - " function _(e,r,t,a,n){a();var o=/[\\s_\\-\\/\\(\\)]/g;t.default=function(e,r){if(e[r])return e[r];for(var t,a=Object.keys(e),n=r.toLowerCase().replace(o,\"\"),f=-1;++f0?90:-90),e.lat_ts=e.lat1)}(n),n}},\n", - " function _(t,e,r,i,s){i(),r.default=function(t){return new d(t).output()};var h=/\\s/,o=/[A-Za-z]/,n=/[A-Za-z84]/,a=/[,\\]]/,u=/[\\d\\.E\\-\\+]/;function d(t){if(\"string\"!=typeof t)throw new Error(\"not a string\");this.text=t.trim(),this.level=0,this.place=0,this.root=null,this.stack=[],this.currentObject=null,this.state=1}d.prototype.readCharicter=function(){var t=this.text[this.place++];if(4!==this.state)for(;h.test(t);){if(this.place>=this.text.length)return;t=this.text[this.place++]}switch(this.state){case 1:return this.neutral(t);case 2:return this.keyword(t);case 4:return this.quoted(t);case 5:return this.afterquote(t);case 3:return this.number(t);case-1:return}},d.prototype.afterquote=function(t){if('\"'===t)return this.word+='\"',void(this.state=4);if(a.test(t))return this.word=this.word.trim(),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in afterquote yet, index '+this.place)},d.prototype.afterItem=function(t){return\",\"===t?(null!==this.word&&this.currentObject.push(this.word),this.word=null,void(this.state=1)):\"]\"===t?(this.level--,null!==this.word&&(this.currentObject.push(this.word),this.word=null),this.state=1,this.currentObject=this.stack.pop(),void(this.currentObject||(this.state=-1))):void 0},d.prototype.number=function(t){if(!u.test(t)){if(a.test(t))return this.word=parseFloat(this.word),void this.afterItem(t);throw new Error(\"havn't handled \\\"\"+t+'\" in number yet, index '+this.place)}this.word+=t},d.prototype.quoted=function(t){'\"'!==t?this.word+=t:this.state=5},d.prototype.keyword=function(t){if(n.test(t))this.word+=t;else{if(\"[\"===t){var e=[];return e.push(this.word),this.level++,null===this.root?this.root=e:this.currentObject.push(e),this.stack.push(this.currentObject),this.currentObject=e,void(this.state=1)}if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in keyword yet, index '+this.place);this.afterItem(t)}},d.prototype.neutral=function(t){if(o.test(t))return this.word=t,void(this.state=2);if('\"'===t)return this.word=\"\",void(this.state=4);if(u.test(t))return this.word=t,void(this.state=3);if(!a.test(t))throw new Error(\"havn't handled \\\"\"+t+'\" in neutral yet, index '+this.place);this.afterItem(t)},d.prototype.output=function(){for(;this.place90&&a*o.R2D<-90&&h*o.R2D>180&&h*o.R2D<-180)return null;if(Math.abs(Math.abs(a)-o.HALF_PI)<=o.EPSLN)return null;if(this.sphere)i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0+this.a*this.k0*Math.log(Math.tan(o.FORTPI+.5*a));else{var e=Math.sin(a),r=(0,l.default)(this.e,a,e);i=this.x0+this.a*this.k0*(0,n.default)(h-this.long0),s=this.y0-this.a*this.k0*Math.log(r)}return t.x=i,t.y=s,t}function M(t){var i,s,h=t.x-this.x0,a=t.y-this.y0;if(this.sphere)s=o.HALF_PI-2*Math.atan(Math.exp(-a/(this.a*this.k0)));else{var e=Math.exp(-a/(this.a*this.k0));if(-9999===(s=(0,u.default)(this.e,e)))return null}return i=(0,n.default)(this.long0+h/(this.a*this.k0)),t.x=i,t.y=s,t}s.init=f,s.forward=_,s.inverse=M,s.names=[\"Mercator\",\"Popular Visualisation Pseudo Mercator\",\"Mercator_1SP\",\"Mercator_Auxiliary_Sphere\",\"merc\"],s.default={init:f,forward:_,inverse:M,names:s.names}},\n", - " function _(t,n,r,u,a){u(),r.default=function(t,n,r){var u=t*n;return r/Math.sqrt(1-u*u)}},\n", - " function _(t,n,u,a,f){a();const e=t(1),o=t(85),_=(0,e.__importDefault)(t(97));u.default=function(t){return Math.abs(t)<=o.SPI?t:t-(0,_.default)(t)*o.TWO_PI}},\n", - " function _(n,t,u,f,c){f(),u.default=function(n){return n<0?-1:1}},\n", - " function _(t,n,a,o,u){o();const c=t(85);a.default=function(t,n,a){var o=t*a,u=.5*t;return o=Math.pow((1-o)/(1+o),u),Math.tan(.5*(c.HALF_PI-n))/o}},\n", - " function _(t,a,n,r,f){r();const h=t(85);n.default=function(t,a){for(var n,r,f=.5*t,o=h.HALF_PI-2*Math.atan(a),u=0;u<=15;u++)if(n=t*Math.sin(o),o+=r=h.HALF_PI-2*Math.atan(a*Math.pow((1-n)/(1+n),f))-o,Math.abs(r)<=1e-10)return o;return-9999}},\n", - " function _(n,i,e,t,r){function a(){}function f(n){return n}t(),e.init=a,e.forward=f,e.inverse=f,e.names=[\"longlat\",\"identity\"],e.default={init:a,forward:f,inverse:f,names:e.names}},\n", - " function _(t,r,e,a,n){a();const f=t(1),i=t(85),u=(0,f.__importStar)(t(102)),c=(0,f.__importDefault)(t(88));e.eccentricity=function(t,r,e,a){var n=t*t,f=r*r,u=(n-f)/n,c=0;return a?(n=(t*=1-u*(i.SIXTH+u*(i.RA4+u*i.RA6)))*t,u=0):c=Math.sqrt(u),{es:u,e:c,ep2:(n-f)/f}},e.sphere=function(t,r,e,a,n){if(!t){var f=(0,c.default)(u.default,a);f||(f=u.WGS84),t=f.a,r=f.b,e=f.rf}return e&&!r&&(r=(1-1/e)*t),(0===e||Math.abs(t-r)3&&(0===s.datum_params[3]&&0===s.datum_params[4]&&0===s.datum_params[5]&&0===s.datum_params[6]||(s.datum_type=d.PJD_7PARAM,s.datum_params[3]*=d.SEC_TO_RAD,s.datum_params[4]*=d.SEC_TO_RAD,s.datum_params[5]*=d.SEC_TO_RAD,s.datum_params[6]=s.datum_params[6]/1e6+1))),r&&(s.datum_type=d.PJD_GRIDSHIFT,s.grids=r),s.a=_,s.b=t,s.es=u,s.ep2=p,s}},\n", - " function _(t,e,n,r,i){r();var u={};function l(t){if(0===t.length)return null;var e=\"@\"===t[0];return e&&(t=t.slice(1)),\"null\"===t?{name:\"null\",mandatory:!e,grid:null,isNull:!0}:{name:t,mandatory:!e,grid:u[t]||null,isNull:!1}}function o(t){return t/3600*Math.PI/180}function a(t,e,n){return String.fromCharCode.apply(null,new Uint8Array(t.buffer.slice(e,n)))}function d(t){return t.map((function(t){return[o(t.longitudeShift),o(t.latitudeShift)]}))}function g(t,e,n){return{name:a(t,e+8,e+16).trim(),parent:a(t,e+24,e+24+8).trim(),lowerLatitude:t.getFloat64(e+72,n),upperLatitude:t.getFloat64(e+88,n),lowerLongitude:t.getFloat64(e+104,n),upperLongitude:t.getFloat64(e+120,n),latitudeInterval:t.getFloat64(e+136,n),longitudeInterval:t.getFloat64(e+152,n),gridNodeCount:t.getInt32(e+168,n)}}function s(t,e,n,r){for(var i=e+176,u=[],l=0;l1&&console.log(\"Only single NTv2 subgrids are currently supported, subsequent sub grids are ignored\");var l=function(t,e,n){for(var r=176,i=[],u=0;ua.y||f>a.x||N1e-12&&Math.abs(n.y)>1e-12);if(d<0)return console.log(\"Inverse grid shift iterator failed to converge.\"),a;a.x=(0,u.default)(l.x+t.ll[0]),a.y=l.y+t.ll[1]}else isNaN(l.x)||(a.x=r.x+l.x,a.y=r.y+l.y);return a}function f(r,e){var t,a={x:r.x/e.del[0],y:r.y/e.del[1]},i=Math.floor(a.x),l=Math.floor(a.y),n=a.x-1*i,o=a.y-1*l,u={x:Number.NaN,y:Number.NaN};if(i<0||i>=e.lim[0])return u;if(l<0||l>=e.lim[1])return u;t=l*e.lim[0]+i;var d=e.cvs[t][0],s=e.cvs[t][1];t++;var y=e.cvs[t][0],f=e.cvs[t][1];t+=e.lim[0];var x=e.cvs[t][0],m=e.cvs[t][1];t--;var N=e.cvs[t][0],c=e.cvs[t][1],_=n*o,g=n*(1-o),v=(1-n)*(1-o),S=(1-n)*o;return u.x=v*d+g*y+S*N+_*x,u.y=v*s+g*f+S*c+_*m,u}t.default=function(r,e,t){if((0,o.compareDatums)(r,e))return t;if(r.datum_type===n.PJD_NODATUM||e.datum_type===n.PJD_NODATUM)return t;var a=r.a,i=r.es;if(r.datum_type===n.PJD_GRIDSHIFT){if(0!==s(r,!1,t))return;a=n.SRS_WGS84_SEMIMAJOR,i=n.SRS_WGS84_ESQUARED}var l=e.a,u=e.b,y=e.es;if(e.datum_type===n.PJD_GRIDSHIFT&&(l=n.SRS_WGS84_SEMIMAJOR,u=n.SRS_WGS84_SEMIMINOR,y=n.SRS_WGS84_ESQUARED),i===y&&a===l&&!d(r.datum_type)&&!d(e.datum_type))return t;if(t=(0,o.geodeticToGeocentric)(t,i,a),d(r.datum_type)&&(t=(0,o.geocentricToWgs84)(t,r.datum_type,r.datum_params)),d(e.datum_type)&&(t=(0,o.geocentricFromWgs84)(t,e.datum_type,e.datum_params)),t=(0,o.geocentricToGeodetic)(t,y,l,u),e.datum_type===n.PJD_GRIDSHIFT&&0!==s(e,!0,t))return;return t},t.applyGridShift=s},\n", - " function _(a,t,r,m,s){m();const u=a(85);r.compareDatums=function(a,t){return a.datum_type===t.datum_type&&(!(a.a!==t.a||Math.abs(a.es-t.es)>5e-11)&&(a.datum_type===u.PJD_3PARAM?a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]:a.datum_type!==u.PJD_7PARAM||a.datum_params[0]===t.datum_params[0]&&a.datum_params[1]===t.datum_params[1]&&a.datum_params[2]===t.datum_params[2]&&a.datum_params[3]===t.datum_params[3]&&a.datum_params[4]===t.datum_params[4]&&a.datum_params[5]===t.datum_params[5]&&a.datum_params[6]===t.datum_params[6]))},r.geodeticToGeocentric=function(a,t,r){var m,s,_,e,n=a.x,d=a.y,i=a.z?a.z:0;if(d<-u.HALF_PI&&d>-1.001*u.HALF_PI)d=-u.HALF_PI;else if(d>u.HALF_PI&&d<1.001*u.HALF_PI)d=u.HALF_PI;else{if(d<-u.HALF_PI)return{x:-1/0,y:-1/0,z:a.z};if(d>u.HALF_PI)return{x:1/0,y:1/0,z:a.z}}return n>Math.PI&&(n-=2*Math.PI),s=Math.sin(d),e=Math.cos(d),_=s*s,{x:((m=r/Math.sqrt(1-t*_))+i)*e*Math.cos(n),y:(m+i)*e*Math.sin(n),z:(m*(1-t)+i)*s}},r.geocentricToGeodetic=function(a,t,r,m){var s,_,e,n,d,i,p,P,y,z,M,o,A,c,x,h=1e-12,f=a.x,I=a.y,F=a.z?a.z:0;if(s=Math.sqrt(f*f+I*I),_=Math.sqrt(f*f+I*I+F*F),s/r1e-24&&A<30);return{x:c,y:Math.atan(M/Math.abs(z)),z:x}},r.geocentricToWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x+r[0],y:a.y+r[1],z:a.z+r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6];return{x:i*(a.x-d*a.y+n*a.z)+m,y:i*(d*a.x+a.y-e*a.z)+s,z:i*(-n*a.x+e*a.y+a.z)+_}}},r.geocentricFromWgs84=function(a,t,r){if(t===u.PJD_3PARAM)return{x:a.x-r[0],y:a.y-r[1],z:a.z-r[2]};if(t===u.PJD_7PARAM){var m=r[0],s=r[1],_=r[2],e=r[3],n=r[4],d=r[5],i=r[6],p=(a.x-m)/i,P=(a.y-s)/i,y=(a.z-_)/i;return{x:p+d*P-n*y,y:-d*p+P+e*y,z:n*p-e*P+y}}}},\n", - " function _(e,a,i,r,s){r(),i.default=function(e,a,i){var r,s,n,c=i.x,d=i.y,f=i.z||0,u={};for(n=0;n<3;n++)if(!a||2!==n||void 0!==i.z)switch(0===n?(r=c,s=-1!==\"ew\".indexOf(e.axis[n])?\"x\":\"y\"):1===n?(r=d,s=-1!==\"ns\".indexOf(e.axis[n])?\"y\":\"x\"):(r=f,s=\"z\"),e.axis[n]){case\"e\":u[s]=r;break;case\"w\":u[s]=-r;break;case\"n\":u[s]=r;break;case\"s\":u[s]=-r;break;case\"u\":void 0!==i[s]&&(u.z=r);break;case\"d\":void 0!==i[s]&&(u.z=-r);break;default:return null}return u}},\n", - " function _(n,t,e,u,f){u(),e.default=function(n){var t={x:n[0],y:n[1]};return n.length>2&&(t.z=n[2]),n.length>3&&(t.m=n[3]),t}},\n", - " function _(e,i,n,t,r){function o(e){if(\"function\"==typeof Number.isFinite){if(Number.isFinite(e))return;throw new TypeError(\"coordinates must be finite numbers\")}if(\"number\"!=typeof e||e!=e||!isFinite(e))throw new TypeError(\"coordinates must be finite numbers\")}t(),n.default=function(e){o(e.x),o(e.y)}},\n", - " function _(e,i,s,t,o){t();const n=e(1);var l,a,r,_,c;const d=e(53),v=e(42),u=(0,n.__importStar)(e(45)),h=e(48),m=(0,n.__importStar)(e(18));class T extends v.View{initialize(){super.initialize(),this.visuals=new u.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.parent.canvas}set_data(e){const i=this;for(const s of this.model){if(!(s instanceof m.VectorSpec||s instanceof m.ScalarSpec))continue;const t=s.uniform(e);i[`${s.attr}`]=t}}}s.ArrowHeadView=T,T.__name__=\"ArrowHeadView\";class p extends d.Model{constructor(e){super(e)}}s.ArrowHead=p,l=p,p.__name__=\"ArrowHead\",l.define((()=>({size:[m.NumberSpec,25]})));class V extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,0),e.lineTo(.5*s,s)}render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.stroke()}}}s.OpenHeadView=V,V.__name__=\"OpenHeadView\";class f extends p{constructor(e){super(e)}}s.OpenHead=f,a=f,f.__name__=\"OpenHead\",a.prototype.default_view=V,a.mixins(h.LineVector);class w extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._normal(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._normal(e,i),e.stroke())}_normal(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.closePath()}}s.NormalHeadView=w,w.__name__=\"NormalHeadView\";class H extends p{constructor(e){super(e)}}s.NormalHead=H,r=H,H.__name__=\"NormalHead\",r.prototype.default_view=w,r.mixins([h.LineVector,h.FillVector]),r.override({fill_color:\"black\"});class z extends T{clip(e,i){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.moveTo(.5*s,s),e.lineTo(.5*s,-2),e.lineTo(-.5*s,-2),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.lineTo(.5*s,s)}render(e,i){this.visuals.fill.doit&&(this.visuals.fill.set_vectorize(e,i),this._vee(e,i),e.fill()),this.visuals.line.doit&&(this.visuals.line.set_vectorize(e,i),this._vee(e,i),e.stroke())}_vee(e,i){const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,s),e.lineTo(0,0),e.lineTo(-.5*s,s),e.lineTo(0,.5*s),e.closePath()}}s.VeeHeadView=z,z.__name__=\"VeeHeadView\";class x extends p{constructor(e){super(e)}}s.VeeHead=x,_=x,x.__name__=\"VeeHead\",_.prototype.default_view=z,_.mixins([h.LineVector,h.FillVector]),_.override({fill_color:\"black\"});class g extends T{render(e,i){if(this.visuals.line.doit){this.visuals.line.set_vectorize(e,i);const s=this.size.get(i);e.beginPath(),e.moveTo(.5*s,0),e.lineTo(-.5*s,0),e.stroke()}}clip(e,i){}}s.TeeHeadView=g,g.__name__=\"TeeHeadView\";class b extends p{constructor(e){super(e)}}s.TeeHead=b,c=b,b.__name__=\"TeeHead\",c.prototype.default_view=g,c.mixins(h.LineVector)},\n", - " function _(n,e,t,i,o){i();const s=n(9);async function c(n,e,t){const i=new n(Object.assign(Object.assign({},t),{model:e}));return i.initialize(),await i.lazy_initialize(),i}t.build_view=async function(n,e={parent:null},t=(n=>n.default_view)){const i=await c(t(n),n,e);return i.connect_signals(),i},t.build_views=async function(n,e,t={parent:null},i=(n=>n.default_view)){const o=(0,s.difference)([...n.keys()],e);for(const e of o)n.get(e).remove(),n.delete(e);const a=[],f=e.filter((e=>!n.has(e)));for(const e of f){const o=await c(i(e),e,t);n.set(e,o),a.push(o)}for(const n of a)n.connect_signals();return a},t.remove_views=function(n){for(const[e,t]of n)t.remove(),n.delete(e)}},\n", - " function _(e,s,_,i,l){i();const t=e(1);var o;const r=e(115),p=(0,t.__importStar)(e(48));class h extends r.UpperLowerView{paint(e){e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);for(let s=this._upper_sx.length-1;s>=0;s--)e.lineTo(this._upper_sx[s],this._upper_sy[s]);e.closePath(),this.visuals.fill.apply(e),e.beginPath(),e.moveTo(this._lower_sx[0],this._lower_sy[0]);for(let s=0,_=this._lower_sx.length;s<_;s++)e.lineTo(this._lower_sx[s],this._lower_sy[s]);this.visuals.line.apply(e),e.beginPath(),e.moveTo(this._upper_sx[0],this._upper_sy[0]);for(let s=0,_=this._upper_sx.length;s<_;s++)e.lineTo(this._upper_sx[s],this._upper_sy[s]);this.visuals.line.apply(e)}}_.BandView=h,h.__name__=\"BandView\";class n extends r.UpperLower{constructor(e){super(e)}}_.Band=n,o=n,n.__name__=\"Band\",o.prototype.default_view=h,o.mixins([p.Line,p.Fill]),o.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,i,s,o){s();const r=e(1);var n;const p=e(69),a=e(20),_=(0,r.__importStar)(e(18));class h extends p.DataAnnotationView{map_data(){const{frame:e}=this.plot_view,t=this.model.dimension,i=this.coordinates.x_scale,s=this.coordinates.y_scale,o=\"height\"==t?s:i,r=\"height\"==t?i:s,n=\"height\"==t?e.bbox.yview:e.bbox.xview,p=\"height\"==t?e.bbox.xview:e.bbox.yview;let a,_,h;a=\"data\"==this.model.properties.lower.units?o.v_compute(this._lower):n.v_compute(this._lower),_=\"data\"==this.model.properties.upper.units?o.v_compute(this._upper):n.v_compute(this._upper),h=\"data\"==this.model.properties.base.units?r.v_compute(this._base):p.v_compute(this._base);const[d,c]=\"height\"==t?[1,0]:[0,1],u=[a,h],l=[_,h];this._lower_sx=u[d],this._lower_sy=u[c],this._upper_sx=l[d],this._upper_sy=l[c]}}i.UpperLowerView=h,h.__name__=\"UpperLowerView\";class d extends _.CoordinateSpec{get dimension(){return\"width\"==this.obj.dimension?\"x\":\"y\"}get units(){var e;return null!==(e=this.spec.units)&&void 0!==e?e:\"data\"}}i.XOrYCoordinateSpec=d,d.__name__=\"XOrYCoordinateSpec\";class c extends p.DataAnnotation{constructor(e){super(e)}}i.UpperLower=c,n=c,c.__name__=\"UpperLower\",n.define((()=>({dimension:[a.Dimension,\"height\"],lower:[d,{field:\"lower\"}],upper:[d,{field:\"upper\"}],base:[d,{field:\"base\"}]})))},\n", - " function _(t,o,i,n,e){n();const s=t(1);var l;const r=t(40),a=(0,s.__importStar)(t(48)),c=t(20),h=t(65);i.EDGE_TOLERANCE=2.5;class b extends r.AnnotationView{constructor(){super(...arguments),this.bbox=new h.BBox}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{left:t,right:o,top:i,bottom:n}=this.model;if(null==t&&null==o&&null==i&&null==n)return;const{frame:e}=this.plot_view,s=this.coordinates.x_scale,l=this.coordinates.y_scale,r=(t,o,i,n,e)=>{let s;return s=null!=t?this.model.screen?t:\"data\"==o?i.compute(t):n.compute(t):e,s};this.bbox=h.BBox.from_rect({left:r(t,this.model.left_units,s,e.bbox.xview,e.bbox.left),right:r(o,this.model.right_units,s,e.bbox.xview,e.bbox.right),top:r(i,this.model.top_units,l,e.bbox.yview,e.bbox.top),bottom:r(n,this.model.bottom_units,l,e.bbox.yview,e.bbox.bottom)}),this._paint_box()}_paint_box(){const{ctx:t}=this.layer;t.save();const{left:o,top:i,width:n,height:e}=this.bbox;t.beginPath(),t.rect(o,i,n,e),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t),t.restore()}interactive_bbox(){const t=this.model.line_width+i.EDGE_TOLERANCE;return this.bbox.grow_by(t)}interactive_hit(t,o){if(null==this.model.in_cursor)return!1;return this.interactive_bbox().contains(t,o)}cursor(t,o){const{left:i,right:n,bottom:e,top:s}=this.bbox;return Math.abs(t-i)<3||Math.abs(t-n)<3?this.model.ew_cursor:Math.abs(o-e)<3||Math.abs(o-s)<3?this.model.ns_cursor:this.bbox.contains(t,o)?this.model.in_cursor:null}}i.BoxAnnotationView=b,b.__name__=\"BoxAnnotationView\";class u extends r.Annotation{constructor(t){super(t)}update({left:t,right:o,top:i,bottom:n}){this.setv({left:t,right:o,top:i,bottom:n,screen:!0})}}i.BoxAnnotation=u,l=u,u.__name__=\"BoxAnnotation\",l.prototype.default_view=b,l.mixins([a.Line,a.Fill,a.Hatch]),l.define((({Number:t,Nullable:o})=>({top:[o(t),null],top_units:[c.SpatialUnits,\"data\"],bottom:[o(t),null],bottom_units:[c.SpatialUnits,\"data\"],left:[o(t),null],left_units:[c.SpatialUnits,\"data\"],right:[o(t),null],right_units:[c.SpatialUnits,\"data\"],render_mode:[c.RenderMode,\"canvas\"]}))),l.internal((({Boolean:t,String:o,Nullable:i})=>({screen:[t,!1],ew_cursor:[i(o),null],ns_cursor:[i(o),null],in_cursor:[i(o),null]}))),l.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(t,e,i,o,n){o();const a=t(1);var r;const s=t(40),l=t(118),_=t(126),c=t(127),h=t(130),u=t(168),p=t(131),m=t(192),g=t(132),d=t(173),f=t(172),w=t(196),b=t(204),v=t(206),x=t(133),y=t(20),k=(0,a.__importStar)(t(48)),z=t(9),j=t(207),C=t(208),L=t(211),B=t(123),S=t(11),M=t(113),T=t(65),A=t(8);class O extends s.AnnotationView{get orientation(){return this._orientation}initialize(){super.initialize();const{ticker:t,formatter:e,color_mapper:i}=this.model;this._ticker=\"auto\"!=t?t:(()=>{switch(!0){case i instanceof w.LogColorMapper:return new u.LogTicker;case i instanceof w.ScanningColorMapper:return new u.BinnedTicker({mapper:i});case i instanceof w.CategoricalColorMapper:return new u.CategoricalTicker;default:return new u.BasicTicker}})(),this._formatter=\"auto\"!=e?e:(()=>{switch(!0){case this._ticker instanceof u.LogTicker:return new m.LogTickFormatter;case i instanceof w.CategoricalColorMapper:return new m.CategoricalTickFormatter;default:return new m.BasicTickFormatter}})(),this._major_range=(()=>{if(i instanceof w.CategoricalColorMapper){const{factors:t}=i;return new v.FactorRange({factors:t})}if(i instanceof f.ContinuousColorMapper){const{min:t,max:e}=i.metrics;return new v.Range1d({start:t,end:e})}(0,S.unreachable)()})(),this._major_scale=(()=>{if(i instanceof w.LinearColorMapper)return new b.LinearScale;if(i instanceof w.LogColorMapper)return new b.LogScale;if(i instanceof w.ScanningColorMapper){const{binning:t}=i.metrics;return new b.LinearInterpolationScale({binning:t})}if(i instanceof w.CategoricalColorMapper)return new b.CategoricalScale;(0,S.unreachable)()})(),this._minor_range=new v.Range1d({start:0,end:1}),this._minor_scale=new b.LinearScale;const o=k.attrs_of(this.model,\"major_label_\",k.Text,!0),n=k.attrs_of(this.model,\"major_tick_\",k.Line,!0),a=k.attrs_of(this.model,\"minor_tick_\",k.Line,!0),r=k.attrs_of(this.model,\"title_\",k.Text),s=i instanceof w.CategoricalColorMapper?c.CategoricalAxis:i instanceof w.LogColorMapper?c.LogAxis:c.LinearAxis;this._axis=new s(Object.assign(Object.assign(Object.assign({ticker:this._ticker,formatter:this._formatter,major_tick_in:this.model.major_tick_in,major_tick_out:this.model.major_tick_out,minor_tick_in:this.model.minor_tick_in,minor_tick_out:this.model.minor_tick_out,major_label_standoff:this.model.label_standoff,major_label_overrides:this.model.major_label_overrides,major_label_policy:this.model.major_label_policy,axis_line_color:null},o),n),a));const{title:_}=this.model;_&&(this._title=new l.Title(Object.assign({text:_,standoff:this.model.title_standoff},r)))}async lazy_initialize(){await super.lazy_initialize();const t=this,e={get parent(){return t.parent},get root(){return t.root},get frame(){return t._frame},get canvas_view(){return t.parent.canvas_view},request_layout(){t.parent.request_layout()}};this._axis_view=await(0,M.build_view)(this._axis,{parent:e}),null!=this._title&&(this._title_view=await(0,M.build_view)(this._title,{parent:e}))}remove(){var t;null===(t=this._title_view)||void 0===t||t.remove(),this._axis_view.remove(),super.remove()}connect_signals(){super.connect_signals(),this.connect(this._ticker.change,(()=>this.request_render())),this.connect(this._formatter.change,(()=>this.request_render())),this.connect(this.model.color_mapper.metrics_change,(()=>{const t=this._major_range,e=this._major_scale,{color_mapper:i}=this.model;if(i instanceof f.ContinuousColorMapper&&t instanceof v.Range1d){const{min:e,max:o}=i.metrics;t.setv({start:e,end:o})}if(i instanceof w.ScanningColorMapper&&e instanceof b.LinearInterpolationScale){const{binning:t}=i.metrics;e.binning=t}this._set_canvas_image(),this.plot_view.request_layout()}))}_set_canvas_image(){const{orientation:t}=this,e=(()=>{const{palette:e}=this.model.color_mapper;return\"vertical\"==t?(0,z.reversed)(e):e})(),[i,o]=\"vertical\"==t?[1,e.length]:[e.length,1],n=this._image=document.createElement(\"canvas\");n.width=i,n.height=o;const a=n.getContext(\"2d\"),r=a.getImageData(0,0,i,o),s=new w.LinearColorMapper({palette:e}).rgba_mapper.v_compute((0,z.range)(0,e.length));r.data.set(s),a.putImageData(r,0,0)}update_layout(){const{location:t,width:e,height:i,padding:o,margin:n}=this.model,[a,r]=(()=>{if(!(0,A.isString)(t))return[\"end\",\"start\"];switch(t){case\"top_left\":return[\"start\",\"start\"];case\"top\":case\"top_center\":return[\"start\",\"center\"];case\"top_right\":return[\"start\",\"end\"];case\"bottom_left\":return[\"end\",\"start\"];case\"bottom\":case\"bottom_center\":return[\"end\",\"center\"];case\"bottom_right\":return[\"end\",\"end\"];case\"left\":case\"center_left\":return[\"center\",\"start\"];case\"center\":case\"center_center\":return[\"center\",\"center\"];case\"right\":case\"center_right\":return[\"center\",\"end\"]}})(),s=this._orientation=(()=>{const{orientation:t}=this.model;return\"auto\"==t?null!=this.panel?this.panel.is_horizontal?\"horizontal\":\"vertical\":\"start\"==r||\"end\"==r||\"center\"==r&&\"center\"==a?\"vertical\":\"horizontal\":t})(),l=new C.NodeLayout,c=new C.VStack,h=new C.VStack,u=new C.HStack,p=new C.HStack;l.absolute=!0,c.absolute=!0,h.absolute=!0,u.absolute=!0,p.absolute=!0;const[m,g,d,f]=(()=>\"horizontal\"==s?[this._major_scale,this._minor_scale,this._major_range,this._minor_range]:[this._minor_scale,this._major_scale,this._minor_range,this._major_range])();this._frame=new _.CartesianFrame(m,g,d,f),l.on_resize((t=>this._frame.set_geometry(t)));const w=new L.BorderLayout;this._inner_layout=w,w.absolute=!0,w.center_panel=l,w.top_panel=c,w.bottom_panel=h,w.left_panel=u,w.right_panel=p;const b={left:o,right:o,top:o,bottom:o},v=(()=>{if(null==this.panel){if((0,A.isString)(t))return{left:n,right:n,top:n,bottom:n};{const[e,i]=t;return{left:e,right:n,top:n,bottom:i}}}if(!(0,A.isString)(t)){const[e,i]=t;return w.fixup_geometry=(t,o)=>{const n=t,a=this.layout.bbox,{width:r,height:s}=t;if(t=new T.BBox({left:a.left+e,bottom:a.bottom-i,width:r,height:s}),null!=o){const e=t.left-n.left,i=t.top-n.top,{left:a,top:r,width:s,height:l}=o;o=new T.BBox({left:a+e,top:r+i,width:s,height:l})}return[t,o]},{left:e,right:0,top:0,bottom:i}}w.fixup_geometry=(t,e)=>{const i=t;if(\"horizontal\"==s){const{top:e,width:i,height:o}=t;if(\"end\"==r){const{right:n}=this.layout.bbox;t=new T.BBox({right:n,top:e,width:i,height:o})}else if(\"center\"==r){const{hcenter:n}=this.layout.bbox;t=new T.BBox({hcenter:Math.round(n),top:e,width:i,height:o})}}else{const{left:e,width:i,height:o}=t;if(\"end\"==a){const{bottom:n}=this.layout.bbox;t=new T.BBox({left:e,bottom:n,width:i,height:o})}else if(\"center\"==a){const{vcenter:n}=this.layout.bbox;t=new T.BBox({left:e,vcenter:Math.round(n),width:i,height:o})}}if(null!=e){const o=t.left-i.left,n=t.top-i.top,{left:a,top:r,width:s,height:l}=e;e=new T.BBox({left:a+o,top:r+n,width:s,height:l})}return[t,e]}})();let x,y,k,z;if(w.padding=b,null!=this.panel?(x=\"max\",y=void 0,k=void 0,z=void 0):\"auto\"==(\"horizontal\"==s?e:i)?(x=\"fixed\",y=25*this.model.color_mapper.palette.length,k={percent:.3},z={percent:.8}):(x=\"fit\",y=void 0),\"horizontal\"==s){const t=\"auto\"==e?void 0:e,o=\"auto\"==i?25:i;w.set_sizing({width_policy:x,height_policy:\"min\",width:y,min_width:k,max_width:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"auto\"==e?\"fit\":\"fixed\",height_policy:\"fixed\",width:t,height:o})}else{const t=\"auto\"==e?25:e,o=\"auto\"==i?void 0:i;w.set_sizing({width_policy:\"min\",height_policy:x,height:y,min_height:k,max_height:z,halign:r,valign:a,margin:v}),w.center_panel.set_sizing({width_policy:\"fixed\",height_policy:\"auto\"==i?\"fit\":\"fixed\",width:t,height:o})}c.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),h.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),u.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),p.set_sizing({width_policy:\"min\",height_policy:\"fit\"});const{_title_view:S}=this;null!=S&&(\"horizontal\"==s?(S.panel=new B.Panel(\"above\"),S.update_layout(),c.children.push(S.layout)):(S.panel=new B.Panel(\"left\"),S.update_layout(),u.children.push(S.layout)));const{panel:M}=this,O=null!=M&&s==M.orientation?M.side:\"horizontal\"==s?\"below\":\"right\",R=(()=>{switch(O){case\"above\":return c;case\"below\":return h;case\"left\":return u;case\"right\":return p}})(),{_axis_view:F}=this;if(F.panel=new B.Panel(O),F.update_layout(),R.children.push(F.layout),null!=this.panel){const t=new j.Grid([{layout:w,row:0,col:0}]);t.absolute=!0,\"horizontal\"==s?t.set_sizing({width_policy:\"max\",height_policy:\"min\"}):t.set_sizing({width_policy:\"min\",height_policy:\"max\"}),this.layout=t}else this.layout=this._inner_layout;const{visible:I}=this.model;this.layout.sizing.visible=I,this._set_canvas_image()}_render(){var t;const{ctx:e}=this.layer;e.save(),this._paint_bbox(e,this._inner_layout.bbox),this._paint_image(e,this._inner_layout.center_panel.bbox),null===(t=this._title_view)||void 0===t||t.render(),this._axis_view.render(),e.restore()}_paint_bbox(t,e){const{x:i,y:o}=e;let{width:n,height:a}=e;i+n>=this.parent.canvas_view.bbox.width&&(n-=1),o+a>=this.parent.canvas_view.bbox.height&&(a-=1),t.save(),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(t),t.fillRect(i,o,n,a)),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}_paint_image(t,e){const{x:i,y:o,width:n,height:a}=e;t.save(),t.setImageSmoothingEnabled(!1),t.globalAlpha=this.model.scale_alpha,t.drawImage(this._image,i,o,n,a),this.visuals.bar_line.doit&&(this.visuals.bar_line.set_value(t),t.strokeRect(i,o,n,a)),t.restore()}serializable_state(){const t=super.serializable_state(),{children:e=[]}=t,i=(0,a.__rest)(t,[\"children\"]);return null!=this._title_view&&e.push(this._title_view.serializable_state()),e.push(this._axis_view.serializable_state()),Object.assign(Object.assign({},i),{children:e})}}i.ColorBarView=O,O.__name__=\"ColorBarView\";class R extends s.Annotation{constructor(t){super(t)}}i.ColorBar=R,r=R,R.__name__=\"ColorBar\",r.prototype.default_view=O,r.mixins([[\"major_label_\",k.Text],[\"title_\",k.Text],[\"major_tick_\",k.Line],[\"minor_tick_\",k.Line],[\"border_\",k.Line],[\"bar_\",k.Line],[\"background_\",k.Fill]]),r.define((({Alpha:t,Number:e,String:i,Tuple:o,Dict:n,Or:a,Ref:r,Auto:s,Nullable:l})=>({location:[a(y.Anchor,o(e,e)),\"top_right\"],orientation:[a(y.Orientation,s),\"auto\"],title:[l(i),null],title_standoff:[e,2],width:[a(e,s),\"auto\"],height:[a(e,s),\"auto\"],scale_alpha:[t,1],ticker:[a(r(h.Ticker),s),\"auto\"],formatter:[a(r(p.TickFormatter),s),\"auto\"],major_label_overrides:[n(a(i,r(x.BaseText))),{}],major_label_policy:[r(g.LabelingPolicy),()=>new g.NoOverlap],color_mapper:[r(d.ColorMapper)],label_standoff:[e,5],margin:[e,30],padding:[e,10],major_tick_in:[e,5],major_tick_out:[e,0],minor_tick_in:[e,0],minor_tick_out:[e,0]}))),r.override({background_fill_color:\"#ffffff\",background_fill_alpha:.95,bar_line_color:null,border_line_color:null,major_label_text_font_size:\"11px\",major_tick_line_color:\"#ffffff\",minor_tick_line_color:null,title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(t,e,i,s,l){s();const o=t(1);var a;const n=t(119),r=t(20),c=t(120),h=(0,o.__importStar)(t(48));class _ extends n.TextAnnotationView{_get_location(){const t=this.model.offset,e=this.model.standoff/2;let i,s;const{bbox:l}=this.layout;switch(this.panel.side){case\"above\":case\"below\":switch(this.model.vertical_align){case\"top\":s=l.top+e;break;case\"middle\":s=l.vcenter;break;case\"bottom\":s=l.bottom-e}switch(this.model.align){case\"left\":i=l.left+t;break;case\"center\":i=l.hcenter;break;case\"right\":i=l.right-t}break;case\"left\":switch(this.model.vertical_align){case\"top\":i=l.left+e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.right-e}switch(this.model.align){case\"left\":s=l.bottom-t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.top+t}break;case\"right\":switch(this.model.vertical_align){case\"top\":i=l.right-e;break;case\"middle\":i=l.hcenter;break;case\"bottom\":i=l.left+e}switch(this.model.align){case\"left\":s=l.top+t;break;case\"center\":s=l.vcenter;break;case\"right\":s=l.bottom-t}}return[i,s]}_render(){const{text:t}=this.model;if(null==t||0==t.length)return;this.model.text_baseline=this.model.vertical_align,this.model.text_align=this.model.align;const[e,i]=this._get_location(),s=this.panel.get_label_angle_heuristic(\"parallel\");(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,t,e,i,s)}_get_size(){const{text:t}=this.model,e=new c.TextBox({text:t});e.visuals=this.visuals.text.values();const{width:i,height:s}=e.size();return{width:i,height:0==s?0:2+s+this.model.standoff}}}i.TitleView=_,_.__name__=\"TitleView\";class d extends n.TextAnnotation{constructor(t){super(t)}}i.Title=d,a=d,d.__name__=\"Title\",a.prototype.default_view=_,a.mixins([h.Text,[\"border_\",h.Line],[\"background_\",h.Fill]]),a.define((({Number:t,String:e})=>({text:[e,\"\"],vertical_align:[r.VerticalAlign,\"bottom\"],align:[r.TextAlign,\"left\"],offset:[t,0],standoff:[t,10]}))),a.prototype._props.text_align.options.internal=!0,a.prototype._props.text_baseline.options.internal=!0,a.override({text_font_size:\"13px\",text_font_style:\"bold\",text_line_height:1,background_fill_color:null,border_line_color:null})},\n", - " function _(e,t,s,i,l){var n;i();const o=e(40),a=e(43),r=e(20),d=e(120),u=e(123),c=e(11);class h extends o.AnnotationView{update_layout(){const{panel:e}=this;this.layout=null!=e?new u.SideLayout(e,(()=>this.get_size()),!0):void 0}initialize(){super.initialize(),\"css\"==this.model.render_mode&&(this.el=(0,a.div)(),this.plot_view.canvas_view.add_overlay(this.el))}remove(){null!=this.el&&(0,a.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),\"css\"==this.model.render_mode?this.connect(this.model.change,(()=>this.render())):this.connect(this.model.change,(()=>this.request_render()))}render(){this.model.visible||\"css\"!=this.model.render_mode||(0,a.undisplay)(this.el),super.render()}_canvas_text(e,t,s,i,l){const n=new d.TextBox({text:t});n.angle=l,n.position={sx:s,sy:i},n.visuals=this.visuals.text.values();const{background_fill:o,border_line:a}=this.visuals;if(o.doit||a.doit){const{p0:t,p1:s,p2:i,p3:l}=n.rect();e.beginPath(),e.moveTo(t.x,t.y),e.lineTo(s.x,s.y),e.lineTo(i.x,i.y),e.lineTo(l.x,l.y),e.closePath(),this.visuals.background_fill.apply(e),this.visuals.border_line.apply(e)}this.visuals.text.doit&&n.paint(e)}_css_text(e,t,s,i,l){const{el:n}=this;(0,c.assert)(null!=n),(0,a.undisplay)(n),n.textContent=t,this.visuals.text.set_value(e),n.style.position=\"absolute\",n.style.left=`${s}px`,n.style.top=`${i}px`,n.style.color=e.fillStyle,n.style.font=e.font,n.style.lineHeight=\"normal\",n.style.whiteSpace=\"pre\";const[o,r]=(()=>{switch(this.visuals.text.text_align.get_value()){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,u]=(()=>{switch(this.visuals.text.text_baseline.get_value()){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${r}, ${u})`;l&&(h+=`rotate(${l}rad)`),n.style.transformOrigin=`${o} ${d}`,n.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),n.style.backgroundColor=e.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_value(e),n.style.borderStyle=e.lineDash.length<2?\"solid\":\"dashed\",n.style.borderWidth=`${e.lineWidth}px`,n.style.borderColor=e.strokeStyle),(0,a.display)(n)}}s.TextAnnotationView=h,h.__name__=\"TextAnnotationView\";class _ extends o.Annotation{constructor(e){super(e)}}s.TextAnnotation=_,n=_,_.__name__=\"TextAnnotation\",n.define((()=>({render_mode:[r.RenderMode,\"canvas\"]})))},\n", - " function _(t,e,s,i,n){i();const h=t(65),o=t(121),r=t(9),a=t(8),c=t(122),_=t(22);s.text_width=(()=>{const t=document.createElement(\"canvas\").getContext(\"2d\");let e=\"\";return(s,i)=>(i!=e&&(e=i,t.font=i),t.measureText(s).width)})();class l{constructor(){this._position={sx:0,sy:0},this.font_size_scale=1,this.align=\"left\",this._base_font_size=13,this._x_anchor=\"left\",this._y_anchor=\"center\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}set position(t){this._position=t}get position(){return this._position}infer_text_height(){return\"ascent_descent\"}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new h.BBox({left:n,right:r,top:o,bottom:a})}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new c.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e.x),h(e.y)),t.lineTo(h(s.x),h(s.y)),t.lineTo(h(i.x),h(i.y)),t.lineTo(h(n.x),h(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:h}=Math;t.moveTo(h(e),h(s)),t.lineTo(h(e),h(s+n)),t.lineTo(h(e+i),h(s+n)),t.lineTo(h(e+i),h(s)),t.closePath(),t.stroke(),t.restore()}}s.GraphicsBox=l,l.__name__=\"GraphicsBox\";class x extends l{constructor({text:t}){super(),this.text=t}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const h=t.font,{font_size_scale:r,base_font_size:a}=this,c=(0,o.parse_css_font_size)(n);if(null!=c){let{value:t,unit:e}=c;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const l=`${i} ${n} ${h}`;this.font=l,this.color=(0,_.color2css)(e,s),this.line_height=t.line_height;const x=t.align;this._x_anchor=x;const u=t.baseline;this._y_anchor=(()=>{switch(u){case\"top\":return\"top\";case\"middle\":return\"center\";case\"bottom\":return\"bottom\";default:return\"baseline\"}})()}infer_text_height(){if(this.text.includes(\"\\n\"))return\"ascent_descent\";{function t(t){for(const e of new Set(t))if(!(\"0\"<=e&&e<=\"9\"))switch(e){case\",\":case\".\":case\"+\":case\"-\":case\"\\u2212\":case\"e\":continue;default:return!1}return!0}return t(this.text)?\"cap\":\"ascent_descent\"}}_text_line(t){var e;const s=null!==(e=this.text_height_metric)&&void 0!==e?e:this.infer_text_height(),i=(()=>{switch(s){case\"x\":case\"x_descent\":return t.x_height;case\"cap\":case\"cap_descent\":return t.cap_height;case\"ascent\":case\"ascent_descent\":return t.ascent}})(),n=(()=>{switch(s){case\"x\":case\"cap\":case\"ascent\":return 0;case\"x_descent\":case\"cap_descent\":case\"ascent_descent\":return t.descent}})();return{height:i+n,ascent:i,descent:n}}get nlines(){return this.text.split(\"\\n\").length}_size(){var t,e;const{font:i}=this,n=(0,o.font_metrics)(i),h=(this.line_height-1)*n.height,a=\"\"==this.text,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,i))),x=this._text_line(n).height*_,u=\"%\"==(null===(t=this.width)||void 0===t?void 0:t.unit)?this.width.value:1,p=\"%\"==(null===(e=this.height)||void 0===e?void 0:e.unit)?this.height.value:1;return{width:(0,r.max)(l)*u,height:a?0:(x+h*(_-1))*p,metrics:n}}_computed_position(t,e,s){const{width:i,height:n}=t,{sx:h,sy:o,x_anchor:r=this._x_anchor,y_anchor:c=this._y_anchor}=this.position;return{x:h-(()=>{if((0,a.isNumber)(r))return r*i;switch(r){case\"left\":return 0;case\"center\":return.5*i;case\"right\":return i}})(),y:o-(()=>{var t;if((0,a.isNumber)(c))return c*n;switch(c){case\"top\":return 0;case\"center\":return.5*n;case\"bottom\":return n;case\"baseline\":if(1!=s)return.5*n;switch(null!==(t=this.text_height_metric)&&void 0!==t?t:this.infer_text_height()){case\"x\":case\"x_descent\":return e.x_height;case\"cap\":case\"cap_descent\":return e.cap_height;case\"ascent\":case\"ascent_descent\":return e.ascent}}})()}}_rect(){const{width:t,height:e,metrics:s}=this._size(),i=this.text.split(\"\\n\").length,{x:n,y:o}=this._computed_position({width:t,height:e},s,i);return new h.BBox({x:n,y:o,width:t,height:e}).rect}paint(t){var e,i;const{font:n}=this,h=(0,o.font_metrics)(n),a=(this.line_height-1)*h.height,c=this.text.split(\"\\n\"),_=c.length,l=c.map((t=>(0,s.text_width)(t,n))),x=this._text_line(h),u=x.height*_,p=\"%\"==(null===(e=this.width)||void 0===e?void 0:e.unit)?this.width.value:1,f=\"%\"==(null===(i=this.height)||void 0===i?void 0:i.unit)?this.height.value:1,g=(0,r.max)(l)*p,d=(u+a*(_-1))*f;t.save(),t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\";const{sx:b,sy:m}=this.position,{align:y}=this,{angle:w}=this;w&&(t.translate(b,m),t.rotate(w),t.translate(-b,-m));let{x:v,y:z}=this._computed_position({width:g,height:d},h,_);if(\"justify\"==y)for(let e=0;e<_;e++){let i=v;const h=c[e].split(\" \"),o=h.length,_=h.map((t=>(0,s.text_width)(t,n))),l=(g-(0,r.sum)(_))/(o-1);for(let e=0;e{switch(y){case\"left\":return 0;case\"center\":return.5*(g-l[e]);case\"right\":return g-l[e]}})();t.fillStyle=this.color,t.fillText(c[e],s,z+x.ascent),z+=x.height+a}t.restore()}}s.TextBox=x,x.__name__=\"TextBox\";class u extends l{constructor(t,e){super(),this.base=t,this.expo=e}get children(){return[this.base,this.expo]}set base_font_size(t){super.base_font_size=t,this.base.base_font_size=t,this.expo.base_font_size=t}set position(t){this._position=t;const e=this.base.size(),s=this.expo.size(),i=this._shift_scale()*e.height,n=Math.max(e.height,i+s.height);this.base.position={sx:0,x_anchor:\"left\",sy:n,y_anchor:\"bottom\"},this.expo.position={sx:e.width,x_anchor:\"left\",sy:i,y_anchor:\"bottom\"}}get position(){return this._position}set visuals(t){this.expo.font_size_scale=.7,this.base.visuals=t,this.expo.visuals=t}_shift_scale(){if(this.base instanceof x&&1==this.base.nlines){const{x_height:t,cap_height:e}=(0,o.font_metrics)(this.base.font);return t/e}return 2/3}infer_text_height(){return this.base.infer_text_height()}_rect(){const t=this.base.bbox(),e=this.expo.bbox(),s=t.union(e),{x:i,y:n}=this._computed_position();return s.translate(i,n).rect}_size(){const t=this.base.size(),e=this.expo.size();return{width:t.width+e.width,height:Math.max(t.height,this._shift_scale()*t.height+e.height)}}paint(t){t.save();const{angle:e}=this;if(e){const{sx:s,sy:i}=this.position;t.translate(s,i),t.rotate(e),t.translate(-s,-i)}const{x:s,y:i}=this._computed_position();t.translate(s,i),this.base.paint(t),this.expo.paint(t),t.restore()}paint_bbox(t){super.paint_bbox(t);const{x:e,y:s}=this._computed_position();t.save(),t.translate(e,s);for(const e of this.children)e.paint_bbox(t);t.restore()}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:h=this._y_anchor}=this.position;return{x:s-(()=>{if((0,a.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,a.isNumber)(h))return h*e;switch(h){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}}s.BaseExpo=u,u.__name__=\"BaseExpo\";class p{constructor(t){this.items=t}set base_font_size(t){for(const e of this.items)e.base_font_size=t}get length(){return this.items.length}set visuals(t){for(const e of this.items)e.visuals=t;const e={x:0,cap:1,ascent:2,x_descent:3,cap_descent:4,ascent_descent:5},s=(0,r.max_by)(this.items.map((t=>t.infer_text_height())),(t=>e[t]));for(const t of this.items)t.text_height_metric=s}set angle(t){for(const e of this.items)e.angle=t}max_size(){let t=0,e=0;for(const s of this.items){const i=s.size();t=Math.max(t,i.width),e=Math.max(e,i.height)}return{width:t,height:e}}}s.GraphicsBoxes=p,p.__name__=\"GraphicsBoxes\"},\n", - " function _(t,e,n,r,l){r();const a=t(11),c=(()=>{try{return\"undefined\"!=typeof OffscreenCanvas&&null!=new OffscreenCanvas(0,0).getContext(\"2d\")}catch(t){return!1}})()?(t,e)=>new OffscreenCanvas(t,e):(t,e)=>{const n=document.createElement(\"canvas\");return n.width=t,n.height=e,n},o=(()=>{const t=c(0,0).getContext(\"2d\");return e=>{t.font=e;const n=t.measureText(\"M\"),r=t.measureText(\"x\"),l=t.measureText(\"\\xc5\\u015ag|\"),c=l.fontBoundingBoxAscent,o=l.fontBoundingBoxDescent;if(null!=c&&null!=o)return{height:c+o,ascent:c,descent:o,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};const s=l.actualBoundingBoxAscent,u=l.actualBoundingBoxDescent;if(null!=s&&null!=u)return{height:s+u,ascent:s,descent:u,cap_height:n.actualBoundingBoxAscent,x_height:r.actualBoundingBoxAscent};(0,a.unreachable)()}})(),s=(()=>{const t=c(0,0).getContext(\"2d\");return(e,n)=>{t.font=n;const r=t.measureText(e),l=r.actualBoundingBoxAscent,c=r.actualBoundingBoxDescent;if(null!=l&&null!=c)return{width:r.width,height:l+c,ascent:l,descent:c};(0,a.unreachable)()}})(),u=(()=>{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a=1)=>{e.font=l;const{width:c}=e.measureText(\"M\"),o=c*a,s=Math.ceil(o),u=Math.ceil(2*o),i=Math.ceil(1.5*o);n{let e=0;for(let n=0;n<=i;n++)for(let r=0;r{let e=t.length-4;for(let n=u;n>=i;n--)for(let r=0;r{const t=document.createElement(\"canvas\"),e=t.getContext(\"2d\");let n=-1,r=-1;return(l,a,c=1)=>{e.font=a;const{width:o}=e.measureText(\"M\"),s=o*c,u=Math.ceil(s),i=Math.ceil(2*s),f=Math.ceil(1.5*s);(n{let e=0;for(let n=0;n<=f;n++)for(let r=0;r{let e=t.length-4;for(let n=i;n>=f;n--)for(let r=0;r{try{return o(\"normal 10px sans-serif\"),o}catch(t){return u}})(),h=(()=>{try{return s(\"A\",\"normal 10px sans-serif\"),s}catch(t){return i}})(),g=new Map;function d(t){let e=g.get(t);return null==e&&(e={font:f(t),glyphs:new Map},g.set(t,e)),e.font}n.font_metrics=d,n.glyph_metrics=function(t,e){let n=g.get(e);null==n&&(d(e),n=g.get(e));let r=n.glyphs.get(t);return null==r&&(r=h(t,e),n.glyphs.set(t,r)),r},n.parse_css_font_size=function(t){const e=t.match(/^\\s*(\\d+(\\.\\d+)?)(\\w+)\\s*$/);if(null!=e){const[,t,,n]=e,r=Number(t);if(isFinite(r))return{value:r,unit:n}}return null}},\n", - " function _(t,s,r,n,i){n();const{sin:e,cos:a}=Math;class h{constructor(t=1,s=0,r=0,n=1,i=0,e=0){this.a=t,this.b=s,this.c=r,this.d=n,this.e=i,this.f=e}toString(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return`matrix(${t}, ${s}, ${r}, ${n}, ${i}, ${e})`}static from_DOMMatrix(t){const{a:s,b:r,c:n,d:i,e,f:a}=t;return new h(s,r,n,i,e,a)}to_DOMMatrix(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new DOMMatrix([t,s,r,n,i,e])}clone(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return new h(t,s,r,n,i,e)}get is_identity(){const{a:t,b:s,c:r,d:n,e:i,f:e}=this;return 1==t&&0==s&&0==r&&1==n&&0==i&&0==e}apply_point(t){const[s,r]=this.apply(t.x,t.y);return{x:s,y:r}}apply_rect(t){return{p0:this.apply_point(t.p0),p1:this.apply_point(t.p1),p2:this.apply_point(t.p2),p3:this.apply_point(t.p3)}}apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this;return[r*t+i*s+a,n*t+e*s+h]}iv_apply(t,s){const{a:r,b:n,c:i,d:e,e:a,f:h}=this,c=t.length;for(let o=0;o{const h={max:4,fit:3,min:2,fixed:1};return h[i]>h[t]};if(\"fixed\"!=n&&\"fixed\"!=s)if(n==s){const n=t,s=_(t/e),r=_(h*e),g=h;Math.abs(i.width-n)+Math.abs(i.height-s)<=Math.abs(i.width-r)+Math.abs(i.height-g)?(t=n,h=s):(t=r,h=g)}else r(n,s)?h=_(t/e):t=_(h*e);else\"fixed\"==n?h=_(t/e):\"fixed\"==s&&(t=_(h*e))}return{width:t,height:h}}measure(i){if(!this.sizing.visible)return{width:0,height:0};const t=i=>\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:i,h=i=>\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:i,e=new s.Sizeable(i).shrink_by(this.sizing.margin).map(t,h),n=this._measure(e),r=this.clip_size(n,e),g=t(r.width),l=h(r.height),a=this.apply_aspect(e,{width:g,height:l});return Object.assign(Object.assign({},n),a)}compute(i={}){const t=this.measure({width:null!=i.width&&this.is_width_expanding()?i.width:1/0,height:null!=i.height&&this.is_height_expanding()?i.height:1/0}),{width:h,height:e}=t,n=new r.BBox({left:0,top:0,width:h,height:e});let s;if(null!=t.inner){const{left:i,top:n,right:g,bottom:l}=t.inner;s=new r.BBox({left:i,top:n,right:h-g,bottom:e-l})}this.set_geometry(n,s)}get xview(){return this.bbox.xview}get yview(){return this.bbox.yview}clip_size(i,t){function h(i,t,h,e){return null==h?h=0:(0,g.isNumber)(h)||(h=Math.round(h.percent*t)),null==e?e=1/0:(0,g.isNumber)(e)||(e=Math.round(e.percent*t)),a(h,l(i,e))}return{width:h(i.width,t.width,this.sizing.min_width,this.sizing.max_width),height:h(i.height,t.height,this.sizing.min_height,this.sizing.max_height)}}has_size_changed(){const{_dirty:i}=this;return this._dirty=!1,i}}h.Layoutable=o,o.__name__=\"Layoutable\";class d extends o{_measure(i){const{width_policy:t,height_policy:h}=this.sizing;return{width:(()=>{const{width:h}=this.sizing;if(i.width==1/0)return null!=h?h:0;switch(t){case\"fixed\":return null!=h?h:0;case\"min\":return null!=h?l(i.width,h):0;case\"fit\":return null!=h?l(i.width,h):i.width;case\"max\":return null!=h?a(i.width,h):i.width}})(),height:(()=>{const{height:t}=this.sizing;if(i.height==1/0)return null!=t?t:0;switch(h){case\"fixed\":return null!=t?t:0;case\"min\":return null!=t?l(i.height,t):0;case\"fit\":return null!=t?l(i.height,t):i.height;case\"max\":return null!=t?a(i.height,t):i.height}})()}}}h.LayoutItem=d,d.__name__=\"LayoutItem\";class u extends o{_measure(i){const t=this._content_size(),h=i.bounded_to(this.sizing.size).bounded_to(t);return{width:(()=>{switch(this.sizing.width_policy){case\"fixed\":return null!=this.sizing.width?this.sizing.width:t.width;case\"min\":return t.width;case\"fit\":return h.width;case\"max\":return Math.max(t.width,h.width)}})(),height:(()=>{switch(this.sizing.height_policy){case\"fixed\":return null!=this.sizing.height?this.sizing.height:t.height;case\"min\":return t.height;case\"fit\":return h.height;case\"max\":return Math.max(t.height,h.height)}})()}}}h.ContentLayoutable=u,u.__name__=\"ContentLayoutable\"},\n", - " function _(e,t,s,a,_){a();const r=e(62),n=e(61),g=e(58),i=e(63),c=e(67),h=e(65),l=e(13),o=e(11);class x{constructor(e,t,s,a,_={},r={},n={},g={}){this.in_x_scale=e,this.in_y_scale=t,this.x_range=s,this.y_range=a,this.extra_x_ranges=_,this.extra_y_ranges=r,this.extra_x_scales=n,this.extra_y_scales=g,this._bbox=new h.BBox,(0,o.assert)(null==e.source_range&&null==e.target_range),(0,o.assert)(null==t.source_range&&null==t.target_range),this._configure_scales()}get bbox(){return this._bbox}_get_ranges(e,t){return new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e})))}_get_scales(e,t,s,a){var _;const g=new Map((0,l.entries)(Object.assign(Object.assign({},t),{default:e}))),h=new Map;for(const[t,l]of s){if(l instanceof c.FactorRange!=e instanceof r.CategoricalScale)throw new Error(`Range ${l.type} is incompatible is Scale ${e.type}`);e instanceof n.LogScale&&l instanceof i.DataRange1d&&(l.scale_hint=\"log\");const s=(null!==(_=g.get(t))&&void 0!==_?_:e).clone();s.setv({source_range:l,target_range:a}),h.set(t,s)}return h}_configure_frame_ranges(){const{bbox:e}=this;this._x_target=new g.Range1d({start:e.left,end:e.right}),this._y_target=new g.Range1d({start:e.bottom,end:e.top})}_configure_scales(){this._configure_frame_ranges(),this._x_ranges=this._get_ranges(this.x_range,this.extra_x_ranges),this._y_ranges=this._get_ranges(this.y_range,this.extra_y_ranges),this._x_scales=this._get_scales(this.in_x_scale,this.extra_x_scales,this._x_ranges,this._x_target),this._y_scales=this._get_scales(this.in_y_scale,this.extra_y_scales,this._y_ranges,this._y_target)}_update_scales(){this._configure_frame_ranges();for(const[,e]of this._x_scales)e.target_range=this._x_target;for(const[,e]of this._y_scales)e.target_range=this._y_target}set_geometry(e){this._bbox=e,this._update_scales()}get x_target(){return this._x_target}get y_target(){return this._y_target}get x_ranges(){return this._x_ranges}get y_ranges(){return this._y_ranges}get x_scales(){return this._x_scales}get y_scales(){return this._y_scales}get x_scale(){return this._x_scales.get(\"default\")}get y_scale(){return this._y_scales.get(\"default\")}get xscales(){return(0,l.to_object)(this.x_scales)}get yscales(){return(0,l.to_object)(this.y_scales)}}s.CartesianFrame=x,x.__name__=\"CartesianFrame\"},\n", - " function _(i,s,x,A,o){A(),o(\"Axis\",i(128).Axis),o(\"CategoricalAxis\",i(140).CategoricalAxis),o(\"ContinuousAxis\",i(143).ContinuousAxis),o(\"DatetimeAxis\",i(144).DatetimeAxis),o(\"LinearAxis\",i(145).LinearAxis),o(\"LogAxis\",i(162).LogAxis),o(\"MercatorAxis\",i(165).MercatorAxis)},\n", - " function _(t,e,i,s,a){s();const o=t(1);var l;const n=t(129),_=t(130),r=t(131),h=t(132),c=(0,o.__importStar)(t(48)),b=t(20),u=t(24),m=t(123),d=t(9),x=t(13),f=t(8),g=t(120),p=t(67),v=t(133),w=t(113),j=t(11),k=t(8),y=t(134),{abs:z}=Math;class M extends n.GuideRendererView{constructor(){super(...arguments),this._axis_label_view=null,this._major_label_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this._init_axis_label(),await this._init_major_labels()}async _init_axis_label(){const{axis_label:t}=this.model;if(null!=t){const e=(0,k.isString)(t)?(0,y.parse_delimited_string)(t):t;this._axis_label_view=await(0,w.build_view)(e,{parent:this})}else this._axis_label_view=null}async _init_major_labels(){const{major_label_overrides:t}=this.model;for(const[e,i]of(0,x.entries)(t)){const t=(0,k.isString)(i)?(0,y.parse_delimited_string)(i):i;this._major_label_views.set(e,await(0,w.build_view)(t,{parent:this}))}}update_layout(){this.layout=new m.SideLayout(this.panel,(()=>this.get_size()),!0),this.layout.on_resize((()=>this._coordinates=void 0))}get_size(){const{visible:t,fixed_location:e}=this.model;if(t&&null==e&&this.is_renderable){const{extents:t}=this;return{width:0,height:Math.round(t.tick+t.tick_label+t.axis_label)}}return{width:0,height:0}}get is_renderable(){const[t,e]=this.ranges;return t.is_valid&&e.is_valid}_render(){var t;if(!this.is_renderable)return;const{tick_coords:e,extents:i}=this,s=this.layer.ctx;s.save(),this._draw_rule(s,i),this._draw_major_ticks(s,i,e),this._draw_minor_ticks(s,i,e),this._draw_major_labels(s,i,e),this._draw_axis_label(s,i,e),null===(t=this._paint)||void 0===t||t.call(this,s,i,e),s.restore()}connect_signals(){super.connect_signals();const{axis_label:t,major_label_overrides:e}=this.model.properties;this.on_change(t,(async()=>{var t;null===(t=this._axis_label_view)||void 0===t||t.remove(),await this._init_axis_label()})),this.on_change(e,(async()=>{for(const t of this._major_label_views.values())t.remove();await this._init_major_labels()})),this.connect(this.model.change,(()=>this.plot_view.request_layout()))}get needs_clip(){return null!=this.model.fixed_location}_draw_rule(t,e){if(!this.visuals.axis_line.doit)return;const[i,s]=this.rule_coords,[a,o]=this.coordinates.map_to_screen(i,s),[l,n]=this.normals,[_,r]=this.offsets;this.visuals.axis_line.set_value(t),t.beginPath();for(let e=0;e0?s+i+3:0}_draw_axis_label(t,e,i){if(null==this._axis_label_view||null!=this.model.fixed_location)return;const[s,a]=(()=>{const{bbox:t}=this.layout;switch(this.panel.side){case\"above\":return[t.hcenter,t.bottom];case\"below\":return[t.hcenter,t.top];case\"left\":return[t.right,t.vcenter];case\"right\":return[t.left,t.vcenter]}})(),[o,l]=this.normals,n=e.tick+e.tick_label+this.model.axis_label_standoff,{vertical_align:_,align:r}=this.panel.get_label_text_heuristics(\"parallel\"),h={sx:s+o*n,sy:a+l*n,x_anchor:r,y_anchor:_},c=this._axis_label_view.graphics();c.visuals=this.visuals.axis_label_text.values(),c.angle=this.panel.get_label_angle_heuristic(\"parallel\"),this.plot_view.base_font_size&&(c.base_font_size=this.plot_view.base_font_size),c.position=h,c.align=r,c.paint(t)}_draw_ticks(t,e,i,s,a){if(!a.doit)return;const[o,l]=e,[n,_]=this.coordinates.map_to_screen(o,l),[r,h]=this.normals,[c,b]=this.offsets,[u,m]=[r*(c-i),h*(b-i)],[d,x]=[r*(c+s),h*(b+s)];a.set_value(t),t.beginPath();for(let e=0;et.bbox())),M=(()=>{const[t]=this.ranges;return t.is_reversed?0==this.dimension?(t,e)=>z[t].left-z[e].right:(t,e)=>z[e].top-z[t].bottom:0==this.dimension?(t,e)=>z[e].left-z[t].right:(t,e)=>z[t].top-z[e].bottom})(),{major_label_policy:O}=this.model,T=O.filter(k,z,M),A=[...T.ones()];if(0!=A.length){const t=this.parent.canvas_view.bbox,e=e=>{const i=z[e];if(i.left<0){const t=-i.left,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sx:s.sx+t})}else if(i.right>t.width){const s=i.right-t.width,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sx:a.sx-s})}},i=e=>{const i=z[e];if(i.top<0){const t=-i.top,{position:s}=y[e];y[e].position=Object.assign(Object.assign({},s),{sy:s.sy+t})}else if(i.bottom>t.height){const s=i.bottom-t.height,{position:a}=y[e];y[e].position=Object.assign(Object.assign({},a),{sy:a.sy-s})}},s=A[0],a=A[A.length-1];0==this.dimension?(e(s),e(a)):(i(s),i(a))}for(const e of T){y[e].paint(t)}}_tick_extent(){return this.model.major_tick_out}_tick_label_extents(){const t=this.tick_coords.major,e=this.compute_labels(t[this.dimension]),i=this.model.major_label_orientation,s=this.model.major_label_standoff,a=this.visuals.major_label_text;return[this._oriented_labels_extent(e,i,s,a)]}get extents(){const t=this._tick_label_extents();return{tick:this._tick_extent(),tick_labels:t,tick_label:(0,d.sum)(t),axis_label:this._axis_label_extent()}}_oriented_labels_extent(t,e,i,s){if(0==t.length||!s.doit)return 0;const a=this.panel.get_label_angle_heuristic(e);t.visuals=s.values(),t.angle=a,t.base_font_size=this.plot_view.base_font_size;const o=t.max_size(),l=0==this.dimension?o.height:o.width;return l>0?i+l+3:0}get normals(){return this.panel.normals}get dimension(){return this.panel.dimension}compute_labels(t){const e=this.model.formatter.format_graphics(t,this),{_major_label_views:i}=this,s=new Set;for(let a=0;az(l-n)?(t=r(_(a,o),l),s=_(r(a,o),n)):(t=_(a,o),s=r(a,o)),[t,s]}}get rule_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=[new Array(2),new Array(2)];return o[t][0]=Math.max(s,i.min),o[t][1]=Math.min(a,i.max),o[t][0]>o[t][1]&&(o[t][0]=o[t][1]=NaN),o[e][0]=this.loc,o[e][1]=this.loc,o}get tick_coords(){const t=this.dimension,e=(t+1)%2,[i]=this.ranges,[s,a]=this.computed_bounds,o=this.model.ticker.get_ticks(s,a,i,this.loc),l=o.major,n=o.minor,_=[[],[]],r=[[],[]],[h,c]=[i.min,i.max];for(let i=0;ic||(_[t].push(l[i]),_[e].push(this.loc));for(let i=0;ic||(r[t].push(n[i]),r[e].push(this.loc));return{major:_,minor:r}}get loc(){const{fixed_location:t}=this.model;if(null!=t){if((0,f.isNumber)(t))return t;const[,e]=this.ranges;if(e instanceof p.FactorRange)return e.synthetic(t);(0,j.unreachable)()}const[,e]=this.ranges;switch(this.panel.side){case\"left\":case\"below\":return e.start;case\"right\":case\"above\":return e.end}}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box})}remove(){var t;null===(t=this._axis_label_view)||void 0===t||t.remove();for(const t of this._major_label_views.values())t.remove();super.remove()}has_finished(){if(!super.has_finished())return!1;if(null!=this._axis_label_view&&!this._axis_label_view.has_finished())return!1;for(const t of this._major_label_views.values())if(!t.has_finished())return!1;return!0}}i.AxisView=M,M.__name__=\"AxisView\";class O extends n.GuideRenderer{constructor(t){super(t)}}i.Axis=O,l=O,O.__name__=\"Axis\",l.prototype.default_view=M,l.mixins([[\"axis_\",c.Line],[\"major_tick_\",c.Line],[\"minor_tick_\",c.Line],[\"major_label_\",c.Text],[\"axis_label_\",c.Text]]),l.define((({Any:t,Int:e,Number:i,String:s,Ref:a,Dict:o,Tuple:l,Or:n,Nullable:c,Auto:u})=>({bounds:[n(l(i,i),u),\"auto\"],ticker:[a(_.Ticker)],formatter:[a(r.TickFormatter)],axis_label:[c(n(s,a(v.BaseText))),null],axis_label_standoff:[e,5],major_label_standoff:[e,5],major_label_orientation:[n(b.TickLabelOrientation,i),\"horizontal\"],major_label_overrides:[o(n(s,a(v.BaseText))),{}],major_label_policy:[a(h.LabelingPolicy),()=>new h.AllLabels],major_tick_in:[i,2],major_tick_out:[i,6],minor_tick_in:[i,0],minor_tick_out:[i,4],fixed_location:[c(n(i,t)),null]}))),l.override({axis_line_color:\"black\",major_tick_line_color:\"black\",minor_tick_line_color:\"black\",major_label_text_font_size:\"11px\",major_label_text_align:\"center\",major_label_text_baseline:\"alphabetic\",axis_label_text_font_size:\"13px\",axis_label_text_font_style:\"italic\"})},\n", - " function _(e,r,d,n,i){var s;n();const _=e(41);class u extends _.RendererView{}d.GuideRendererView=u,u.__name__=\"GuideRendererView\";class c extends _.Renderer{constructor(e){super(e)}}d.GuideRenderer=c,s=c,c.__name__=\"GuideRenderer\",s.override({level:\"guide\"})},\n", - " function _(c,e,n,s,o){s();const r=c(53);class t extends r.Model{constructor(c){super(c)}}n.Ticker=t,t.__name__=\"Ticker\"},\n", - " function _(t,o,r,e,c){e();const n=t(53),a=t(120);class m extends n.Model{constructor(t){super(t)}format_graphics(t,o){return this.doFormat(t,o).map((t=>new a.TextBox({text:t})))}compute(t,o){return this.doFormat([t],null!=o?o:{loc:0})[0]}v_compute(t,o){return this.doFormat(t,null!=o?o:{loc:0})}}r.TickFormatter=m,m.__name__=\"TickFormatter\"},\n", - " function _(e,n,s,t,i){var c,r;t();const l=e(53),o=e(13),a=e(34),u=e(8),d=e(24);class _ extends l.Model{constructor(e){super(e)}}s.LabelingPolicy=_,_.__name__=\"LabelingPolicy\";class f extends _{constructor(e){super(e)}filter(e,n,s){return e}}s.AllLabels=f,f.__name__=\"AllLabels\";class m extends _{constructor(e){super(e)}filter(e,n,s){const{min_distance:t}=this;let i=null;for(const n of e)null!=i&&s(i,n)({min_distance:[e,5]})));class b extends _{constructor(e){super(e)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}get func(){const e=(0,a.use_strict)(this.code);return new d.GeneratorFunction(\"indices\",\"bboxes\",\"distance\",...this.names,e)}filter(e,n,s){const t=Object.create(null),i=this.func.call(t,e,n,s,...this.values);let c=i.next();if(c.done&&void 0!==c.value){const{value:n}=c;return n instanceof d.Indices?n:void 0===n?e:(0,u.isIterable)(n)?d.Indices.from_indices(e.size,n):d.Indices.all_unset(e.size)}{const n=[];do{n.push(c.value),c=i.next()}while(!c.done);return d.Indices.from_indices(e.size,n)}}}s.CustomLabelingPolicy=b,r=b,b.__name__=\"CustomLabelingPolicy\",r.define((({Unknown:e,String:n,Dict:s})=>({args:[s(e),{}],code:[n,\"\"]})))},\n", - " function _(e,s,t,n,a){var _;n();const x=e(53),c=e(42);class i extends c.View{}t.BaseTextView=i,i.__name__=\"BaseTextView\";class o extends x.Model{constructor(e){super(e)}}t.BaseText=o,_=o,o.__name__=\"BaseText\",_.define((({String:e})=>({text:[e]})))},\n", - " function _(n,e,t,i,r){i();const s=n(135),l=n(139),d=[{start:\"$$\",end:\"$$\",inline:!1},{start:\"\\\\[\",end:\"\\\\]\",inline:!1},{start:\"\\\\(\",end:\"\\\\)\",inline:!0}];t.parse_delimited_string=function(n){for(const e of d){const t=n.indexOf(e.start),i=t+e.start.length;if(0==t){const t=n.indexOf(e.end,i),r=t;if(t==n.length-e.end.length)return new s.TeX({text:n.slice(i,r),inline:e.inline});break}}return new l.PlainText({text:n})}},\n", - " function _(t,e,s,i,n){var o,r,a;i();const h=t(8),_=t(136),l=t(22),c=t(120),d=t(121),u=t(122),g=t(65),p=t(133),x=t(137);class m extends p.BaseTextView{constructor(){super(...arguments),this._position={sx:0,sy:0},this.align=\"left\",this._x_anchor=\"left\",this._y_anchor=\"center\",this._base_font_size=13,this.font_size_scale=1,this.svg_image=null}graphics(){return this}infer_text_height(){return\"ascent_descent\"}set base_font_size(t){null!=t&&(this._base_font_size=t)}get base_font_size(){return this._base_font_size}get has_image_loaded(){return null!=this.svg_image}_rect(){const{width:t,height:e}=this._size(),{x:s,y:i}=this._computed_position();return new g.BBox({x:s,y:i,width:t,height:e}).rect}set position(t){this._position=t}get position(){return this._position}get text(){return this.model.text}get provider(){return x.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>this.load_image())),\"loaded\"==this.provider.status&&await this.load_image()}connect_signals(){super.connect_signals(),this.on_change(this.model.properties.text,(()=>this.load_image()))}set visuals(t){const e=t.color,s=t.alpha,i=t.font_style;let n=t.font_size;const o=t.font,{font_size_scale:r,_base_font_size:a}=this,h=(0,d.parse_css_font_size)(n);if(null!=h){let{value:t,unit:e}=h;t*=r,\"em\"==e&&a&&(t*=a,e=\"px\"),n=`${t}${e}`}const _=`${i} ${n} ${o}`;this.font=_,this.color=(0,l.color2css)(e,s)}_computed_position(){const{width:t,height:e}=this._size(),{sx:s,sy:i,x_anchor:n=this._x_anchor,y_anchor:o=this._y_anchor}=this.position;return{x:s-(()=>{if((0,h.isNumber)(n))return n*t;switch(n){case\"left\":return 0;case\"center\":return.5*t;case\"right\":return t}})(),y:i-(()=>{if((0,h.isNumber)(o))return o*e;switch(o){case\"top\":return 0;case\"center\":return.5*e;case\"bottom\":return e;case\"baseline\":return.5*e}})()}}size(){const{width:t,height:e}=this._size(),{angle:s}=this;if(s){const i=Math.cos(Math.abs(s)),n=Math.sin(Math.abs(s));return{width:Math.abs(t*i+e*n),height:Math.abs(t*n+e*i)}}return{width:t,height:e}}get_text_dimensions(){return{width:(0,c.text_width)(this.model.text,this.font),height:(0,d.font_metrics)(this.font).height}}get_image_dimensions(){var t,e,s,i;const n=parseFloat(null!==(e=null===(t=this.svg_element.getAttribute(\"height\"))||void 0===t?void 0:t.replace(/([A-z])/g,\"\"))&&void 0!==e?e:\"0\"),o=parseFloat(null!==(i=null===(s=this.svg_element.getAttribute(\"width\"))||void 0===s?void 0:s.replace(/([A-z])/g,\"\"))&&void 0!==i?i:\"0\");return{width:(0,d.font_metrics)(this.font).x_height*o,height:(0,d.font_metrics)(this.font).x_height*n}}_size(){return this.has_image_loaded?this.get_image_dimensions():this.get_text_dimensions()}bbox(){const{p0:t,p1:e,p2:s,p3:i}=this.rect(),n=Math.min(t.x,e.x,s.x,i.x),o=Math.min(t.y,e.y,s.y,i.y),r=Math.max(t.x,e.x,s.x,i.x),a=Math.max(t.y,e.y,s.y,i.y);return new g.BBox({left:n,right:r,top:o,bottom:a})}rect(){const t=this._rect(),{angle:e}=this;if(e){const{sx:s,sy:i}=this.position,n=new u.AffineTransform;return n.translate(s,i),n.rotate(e),n.translate(-s,-i),n.apply_rect(t)}return t}paint_rect(t){const{p0:e,p1:s,p2:i,p3:n}=this.rect();t.save(),t.strokeStyle=\"red\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e.x),o(e.y)),t.lineTo(o(s.x),o(s.y)),t.lineTo(o(i.x),o(i.y)),t.lineTo(o(n.x),o(n.y)),t.closePath(),t.stroke(),t.restore()}paint_bbox(t){const{x:e,y:s,width:i,height:n}=this.bbox();t.save(),t.strokeStyle=\"blue\",t.lineWidth=1,t.beginPath();const{round:o}=Math;t.moveTo(o(e),o(s)),t.lineTo(o(e),o(s+n)),t.lineTo(o(e+i),o(s+n)),t.lineTo(o(e+i),o(s)),t.closePath(),t.stroke(),t.restore()}async load_image(){if(null==this.provider.MathJax)return null;const t=this._process_text(this.model.text);if(null==t)return this._has_finished=!0,null;const e=t.children[0];this.svg_element=e,e.setAttribute(\"font\",this.font),e.setAttribute(\"stroke\",this.color);const s=e.outerHTML,i=new Blob([s],{type:\"image/svg+xml\"}),n=URL.createObjectURL(i);try{this.svg_image=await(0,_.load_image)(n)}finally{URL.revokeObjectURL(n)}return this.parent.request_layout(),this.svg_image}paint(t){t.save();const{sx:e,sy:s}=this.position;this.angle&&(t.translate(e,s),t.rotate(this.angle),t.translate(-e,-s));const{x:i,y:n}=this._computed_position();if(null!=this.svg_image){const{width:e,height:s}=this.get_image_dimensions();t.drawImage(this.svg_image,i,n,e,s)}else t.fillStyle=this.color,t.font=this.font,t.textAlign=\"left\",t.textBaseline=\"alphabetic\",t.fillText(this.model.text,i,n+(0,d.font_metrics)(this.font).ascent);t.restore(),this._has_finished||\"failed\"!=this.provider.status&&!this.has_image_loaded||(this._has_finished=!0,this.parent.notify_finished_after_paint())}}s.MathTextView=m,m.__name__=\"MathTextView\";class f extends p.BaseText{constructor(t){super(t)}}s.MathText=f,f.__name__=\"MathText\";class v extends m{_process_text(t){}}s.AsciiView=v,v.__name__=\"AsciiView\";class y extends f{constructor(t){super(t)}}s.Ascii=y,o=y,y.__name__=\"Ascii\",o.prototype.default_view=v;class w extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.mathml2svg(t.trim())}}s.MathMLView=w,w.__name__=\"MathMLView\";class b extends f{constructor(t){super(t)}}s.MathML=b,r=b,b.__name__=\"MathML\",r.prototype.default_view=w;class M extends m{_process_text(t){var e;return null===(e=this.provider.MathJax)||void 0===e?void 0:e.tex2svg(t,void 0,this.model.macros)}}s.TeXView=M,M.__name__=\"TeXView\";class T extends f{constructor(t){super(t)}}s.TeX=T,a=T,T.__name__=\"TeX\",a.prototype.default_view=M,a.define((({Boolean:t,Number:e,String:s,Dict:i,Tuple:n,Or:o})=>({macros:[i(o(s,n(s,e))),{}],inline:[t,!1]})))},\n", - " function _(i,e,t,s,o){s();const a=i(19);t.load_image=async function(i,e){return new n(i,e).promise};class n{constructor(i,e={}){this._image=new Image,this._finished=!1;const{attempts:t=1,timeout:s=1}=e;this.promise=new Promise(((o,n)=>{this._image.crossOrigin=\"anonymous\";let r=0;this._image.onerror=()=>{if(++r==t){const s=`unable to load ${i} image after ${t} attempts`;if(a.logger.warn(s),null==this._image.crossOrigin)return void(null!=e.failed&&e.failed());a.logger.warn(`attempting to load ${i} without a cross origin policy`),this._image.crossOrigin=null,r=0}setTimeout((()=>this._image.src=i),s)},this._image.onload=()=>{this._finished=!0,null!=e.loaded&&e.loaded(this._image),o(this._image)},this._image.src=i}))}get finished(){return this._finished}get image(){if(this._finished)return this._image;throw new Error(\"not loaded yet\")}}t.ImageLoader=n,n.__name__=\"ImageLoader\"},\n", - " function _(t,e,a,s,n){var r=this&&this.__createBinding||(Object.create?function(t,e,a,s){void 0===s&&(s=a),Object.defineProperty(t,s,{enumerable:!0,get:function(){return e[a]}})}:function(t,e,a,s){void 0===s&&(s=a),t[s]=e[a]}),i=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),d=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var 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l.AxisView{_paint(t,s,o){this._draw_group_separators(t,s,o)}_draw_group_separators(t,s,o){const[e]=this.ranges,[i,r]=this.computed_bounds;if(!e.tops||e.tops.length<2||!this.visuals.separator_line.doit)return;const a=this.dimension,l=(a+1)%2,_=[[],[]];let n=0;for(let t=0;ti&&pnew h.GraphicsBoxes(t.map((t=>(0,m.isString)(t)?new h.TextBox({text:t}):t))),_=t=>l(this.model.formatter.doFormat(t,this));if(1==t.levels){const t=_(i.major);a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text])}else if(2==t.levels){const t=_(i.major.map((t=>t[1])));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}else if(3==t.levels){const t=_(i.major.map((t=>t[2]))),s=i.mids.map((t=>t[1]));a.push([t,r.major,this.model.major_label_orientation,this.visuals.major_label_text]),a.push([l(s),r.mids,this.model.subgroup_label_orientation,this.visuals.subgroup_text]),a.push([l(i.tops),r.tops,this.model.group_label_orientation,this.visuals.group_text])}return a}get tick_coords(){const t=this.dimension,s=(t+1)%2,[o]=this.ranges,[e,i]=this.computed_bounds,r=this.model.ticker.get_ticks(e,i,o,this.loc),a={major:[[],[]],mids:[[],[]],tops:[[],[]],minor:[[],[]]};return a.major[t]=r.major,a.major[s]=r.major.map((()=>this.loc)),3==o.levels&&(a.mids[t]=r.mids,a.mids[s]=r.mids.map((()=>this.loc))),o.levels>1&&(a.tops[t]=r.tops,a.tops[s]=r.tops.map((()=>this.loc))),a}}o.CategoricalAxisView=u,u.__name__=\"CategoricalAxisView\";class d extends l.Axis{constructor(t){super(t)}}o.CategoricalAxis=d,a=d,d.__name__=\"CategoricalAxis\",a.prototype.default_view=u,a.mixins([[\"separator_\",p.Line],[\"group_\",p.Text],[\"subgroup_\",p.Text]]),a.define((({Number:t,Or:s})=>({group_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"],subgroup_label_orientation:[s(c.TickLabelOrientation,t),\"parallel\"]}))),a.override({ticker:()=>new _.CategoricalTicker,formatter:()=>new n.CategoricalTickFormatter,separator_line_color:\"lightgrey\",separator_line_width:2,group_text_font_style:\"bold\",group_text_font_size:\"11px\",group_text_color:\"grey\",subgroup_text_font_style:\"bold\",subgroup_text_font_size:\"11px\"})},\n", - " function _(t,c,o,s,e){s();const r=t(130);class i extends r.Ticker{constructor(t){super(t)}get_ticks(t,c,o,s){var e,r;return{major:this._collect(o.factors,o,t,c),minor:[],tops:this._collect(null!==(e=o.tops)&&void 0!==e?e:[],o,t,c),mids:this._collect(null!==(r=o.mids)&&void 0!==r?r:[],o,t,c)}}_collect(t,c,o,s){const e=[];for(const r of t){const t=c.synthetic(r);t>o&&tnew _.DatetimeTicker,formatter:()=>new m.DatetimeTickFormatter})},\n", - " function _(e,i,s,n,r){var t;n();const a=e(143),o=e(146),c=e(147);class _ extends a.ContinuousAxisView{}s.LinearAxisView=_,_.__name__=\"LinearAxisView\";class u extends a.ContinuousAxis{constructor(e){super(e)}}s.LinearAxis=u,t=u,u.__name__=\"LinearAxis\",t.prototype.default_view=_,t.override({ticker:()=>new c.BasicTicker,formatter:()=>new o.BasicTickFormatter})},\n", - " function _(i,t,e,n,o){var r;n();const s=i(131),c=i(34);function _(i){let t=\"\";for(const e of i)t+=\"-\"==e?\"\\u2212\":e;return t}e.unicode_replace=_;class a extends s.TickFormatter{constructor(i){super(i),this.last_precision=3}get scientific_limit_low(){return 10**this.power_limit_low}get scientific_limit_high(){return 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Date(t)),s=(0,r.last_month_no_later_than)(new Date(e));s.setUTCMonth(s.getUTCMonth()+1);const o=[],a=n;for(;o.push((0,r.copy_date)(a)),a.setUTCMonth(a.getUTCMonth()+1),!(a>s););return o}(t,e),a=this.days,i=this.interval,_=(0,c.concat)(o.map((t=>((t,e)=>{const n=t.getUTCMonth(),s=[];for(const o of a){const a=(0,r.copy_date)(t);a.setUTCDate(o),new Date(a.getTime()+e/2).getUTCMonth()==n&&s.push(a)}return s})(t,i))));return{major:_.map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.DaysTicker=_,a=_,_.__name__=\"DaysTicker\",a.define((({Int:t,Array:e})=>({days:[e(t),[]]}))),a.override({num_minor_ticks:0})},\n", - " function _(e,n,t,r,i){var a;r();const l=e(149);class s extends l.ContinuousTicker{constructor(e){super(e)}get_interval(e,n,t){return this.interval}get_min_interval(){return this.interval}get_max_interval(){return this.interval}}t.SingleIntervalTicker=s,a=s,s.__name__=\"SingleIntervalTicker\",a.define((({Number:e})=>({interval:[e]})))},\n", - " function _(t,n,e,_,E){function N(t){return new Date(t.getTime())}function O(t){const n=N(t);return n.setUTCDate(1),n.setUTCHours(0),n.setUTCMinutes(0),n.setUTCSeconds(0),n.setUTCMilliseconds(0),n}_(),e.ONE_MILLI=1,e.ONE_SECOND=1e3,e.ONE_MINUTE=60*e.ONE_SECOND,e.ONE_HOUR=60*e.ONE_MINUTE,e.ONE_DAY=24*e.ONE_HOUR,e.ONE_MONTH=30*e.ONE_DAY,e.ONE_YEAR=365*e.ONE_DAY,e.copy_date=N,e.last_month_no_later_than=O,e.last_year_no_later_than=function(t){const n=O(t);return n.setUTCMonth(0),n}},\n", - " function _(t,e,n,a,r){var s;a();const i=t(158),o=t(159),l=t(9);class _ extends i.SingleIntervalTicker{constructor(t){super(t)}initialize(){super.initialize();const t=this.months;t.length>1?this.interval=(t[1]-t[0])*o.ONE_MONTH:this.interval=12*o.ONE_MONTH}get_ticks_no_defaults(t,e,n,a){const r=function(t,e){const n=(0,o.last_year_no_later_than)(new Date(t)),a=(0,o.last_year_no_later_than)(new Date(e));a.setUTCFullYear(a.getUTCFullYear()+1);const r=[],s=n;for(;r.push((0,o.copy_date)(s)),s.setUTCFullYear(s.getUTCFullYear()+1),!(s>a););return r}(t,e),s=this.months;return{major:(0,l.concat)(r.map((t=>s.map((e=>{const n=(0,o.copy_date)(t);return n.setUTCMonth(e),n}))))).map((t=>t.getTime())).filter((n=>t<=n&&n<=e)),minor:[]}}}n.MonthsTicker=_,s=_,_.__name__=\"MonthsTicker\",s.define((({Int:t,Array:e})=>({months:[e(t),[]]})))},\n", - " function _(e,t,a,i,r){i();const n=e(147),_=e(158),s=e(159);class c extends _.SingleIntervalTicker{constructor(e){super(e)}initialize(){super.initialize(),this.interval=s.ONE_YEAR,this.basic_ticker=new n.BasicTicker({num_minor_ticks:0})}get_ticks_no_defaults(e,t,a,i){const r=(0,s.last_year_no_later_than)(new Date(e)).getUTCFullYear(),n=(0,s.last_year_no_later_than)(new Date(t)).getUTCFullYear();return{major:this.basic_ticker.get_ticks_no_defaults(r,n,a,i).major.map((e=>Date.UTC(e,0,1))).filter((a=>e<=a&&a<=t)),minor:[]}}}a.YearsTicker=c,c.__name__=\"YearsTicker\"},\n", - " function _(e,o,i,s,t){var n;s();const r=e(143),_=e(163),c=e(164);class a extends r.ContinuousAxisView{}i.LogAxisView=a,a.__name__=\"LogAxisView\";class u extends r.ContinuousAxis{constructor(e){super(e)}}i.LogAxis=u,n=u,u.__name__=\"LogAxis\",n.prototype.default_view=a,n.override({ticker:()=>new c.LogTicker,formatter:()=>new _.LogTickFormatter})},\n", - " function _(e,t,n,o,r){var i;o();const a=e(131),s=e(146),c=e(164),l=e(120),{abs:u,log:x,round:_}=Math;class p extends a.TickFormatter{constructor(e){super(e)}initialize(){super.initialize(),this.basic_formatter=new s.BasicTickFormatter}format_graphics(e,t){var n,o;if(0==e.length)return[];const r=null!==(o=null===(n=this.ticker)||void 0===n?void 0:n.base)&&void 0!==o?o:10,i=this._exponents(e,r);return null==i?this.basic_formatter.format_graphics(e,t):i.map((e=>{if(u(e)u(e)({ticker:[n(t(c.LogTicker)),null],min_exponent:[e,0]})))},\n", - " function _(t,o,e,s,n){var r;s();const i=t(148),a=t(9);class c extends i.AdaptiveTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,e,s){const n=this.num_minor_ticks,r=[],i=this.base,c=Math.log(t)/Math.log(i),f=Math.log(o)/Math.log(i),l=f-c;let h;if(isFinite(l))if(l<2){const e=this.get_interval(t,o,s),i=Math.floor(t/e),c=Math.ceil(o/e);if(h=(0,a.range)(i,c+1).filter((t=>0!=t)).map((t=>t*e)).filter((e=>t<=e&&e<=o)),n>0&&h.length>0){const t=e/n,o=(0,a.range)(0,n).map((o=>o*t));for(const t of o.slice(1))r.push(h[0]-t);for(const t of h)for(const e of o)r.push(t+e)}}else{const t=Math.ceil(.999999*c),o=Math.floor(1.000001*f),e=Math.ceil((o-t)/9);if(h=(0,a.range)(t-1,o+1,e).map((t=>i**t)),n>0&&h.length>0){const t=i**e/n,o=(0,a.range)(1,n+1).map((o=>o*t));for(const t of o)r.push(h[0]/t);r.push(h[0]);for(const t of h)for(const e of o)r.push(t*e)}}else h=[];return{major:h.filter((e=>t<=e&&e<=o)),minor:r.filter((e=>t<=e&&e<=o))}}}e.LogTicker=c,r=c,c.__name__=\"LogTicker\",r.override({mantissas:[1,5]})},\n", - " function _(e,r,t,i,a){var o;i();const s=e(128),c=e(145),n=e(166),_=e(167);class x extends s.AxisView{}t.MercatorAxisView=x,x.__name__=\"MercatorAxisView\";class d extends c.LinearAxis{constructor(e){super(e)}}t.MercatorAxis=d,o=d,d.__name__=\"MercatorAxis\",o.prototype.default_view=x,o.override({ticker:()=>new _.MercatorTicker({dimension:\"lat\"}),formatter:()=>new n.MercatorTickFormatter({dimension:\"lat\"})})},\n", - " function _(r,t,e,o,n){var i;o();const c=r(146),s=r(20),a=r(78);class l extends c.BasicTickFormatter{constructor(r){super(r)}doFormat(r,t){if(null==this.dimension)throw new Error(\"MercatorTickFormatter.dimension not configured\");if(0==r.length)return[];const e=r.length,o=new Array(e);if(\"lon\"==this.dimension)for(let n=0;n({dimension:[r(s.LatLon),null]})))},\n", - " function _(t,o,n,s,r){var e;s();const i=t(147),c=t(20),_=t(78);class a extends i.BasicTicker{constructor(t){super(t)}get_ticks_no_defaults(t,o,n,s){if(null==this.dimension)throw new Error(`${this}.dimension wasn't configured`);return[t,o]=(0,_.clip_mercator)(t,o,this.dimension),\"lon\"==this.dimension?this._get_ticks_lon(t,o,n,s):this._get_ticks_lat(t,o,n,s)}_get_ticks_lon(t,o,n,s){const[r]=_.wgs84_mercator.invert(t,n),[e,i]=_.wgs84_mercator.invert(o,n),c=super.get_ticks_no_defaults(r,e,n,s),a=[];for(const t of c.major)if((0,_.in_bounds)(t,\"lon\")){const[o]=_.wgs84_mercator.compute(t,i);a.push(o)}const m=[];for(const t of c.minor)if((0,_.in_bounds)(t,\"lon\")){const[o]=_.wgs84_mercator.compute(t,i);m.push(o)}return{major:a,minor:m}}_get_ticks_lat(t,o,n,s){const[,r]=_.wgs84_mercator.invert(n,t),[e,i]=_.wgs84_mercator.invert(n,o),c=super.get_ticks_no_defaults(r,i,n,s),a=[];for(const t of c.major)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);a.push(o)}const m=[];for(const t of c.minor)if((0,_.in_bounds)(t,\"lat\")){const[,o]=_.wgs84_mercator.compute(e,t);m.push(o)}return{major:a,minor:m}}}n.MercatorTicker=a,e=a,a.__name__=\"MercatorTicker\",e.define((({Nullable:t})=>({dimension:[t(c.LatLon),null]})))},\n", - " function _(e,i,r,c,k){c(),k(\"AdaptiveTicker\",e(148).AdaptiveTicker),k(\"BasicTicker\",e(147).BasicTicker),k(\"CategoricalTicker\",e(141).CategoricalTicker),k(\"CompositeTicker\",e(156).CompositeTicker),k(\"ContinuousTicker\",e(149).ContinuousTicker),k(\"DatetimeTicker\",e(155).DatetimeTicker),k(\"DaysTicker\",e(157).DaysTicker),k(\"FixedTicker\",e(169).FixedTicker),k(\"LogTicker\",e(164).LogTicker),k(\"MercatorTicker\",e(167).MercatorTicker),k(\"MonthsTicker\",e(160).MonthsTicker),k(\"SingleIntervalTicker\",e(158).SingleIntervalTicker),k(\"Ticker\",e(130).Ticker),k(\"YearsTicker\",e(161).YearsTicker),k(\"BinnedTicker\",e(170).BinnedTicker)},\n", - " function _(r,t,e,i,n){var s;i();const _=r(149);class c extends _.ContinuousTicker{constructor(r){super(r)}get_ticks_no_defaults(r,t,e,i){return{major:this.ticks,minor:this.minor_ticks}}get_interval(r,t,e){return 0}get_min_interval(){return 0}get_max_interval(){return 0}}e.FixedTicker=c,s=c,c.__name__=\"FixedTicker\",s.define((({Number:r,Array:t})=>({ticks:[t(r),[]],minor_ticks:[t(r),[]]})))},\n", - " function _(e,n,t,r,i){var o;r();const a=e(130),s=e(171),c=e(12);class m extends a.Ticker{constructor(e){super(e)}get_ticks(e,n,t,r){const{binning:i}=this.mapper.metrics,o=Math.max(0,(0,c.left_edge_index)(e,i)),a=Math.min((0,c.left_edge_index)(n,i)+1,i.length-1),s=[];for(let e=o;e<=a;e++)s.push(i[e]);const{num_major_ticks:m}=this,_=[],h=\"auto\"==m?s.length:m,l=Math.max(1,Math.floor(s.length/h));for(let e=0;e({mapper:[n(s.ScanningColorMapper)],num_major_ticks:[t(e,r),8]})))},\n", - " function _(n,e,i,r,o){r();const t=n(172),a=n(12);class c extends t.ContinuousColorMapper{constructor(n){super(n)}cmap(n,e,i,r,o){if(no.binning[o.binning.length-1])return r;return e[(0,a.left_edge_index)(n,o.binning)]}}i.ScanningColorMapper=c,c.__name__=\"ScanningColorMapper\"},\n", - " function _(t,e,o,n,s){var l;n();const c=t(173),i=t(175),a=t(9),h=t(8);class r extends c.ColorMapper{constructor(t){super(t),this._scan_data=null}connect_signals(){super.connect_signals();const t=()=>{for(const[t]of this.domain)this.connect(t.view.change,(()=>this.update_data())),this.connect(t.data_source.selected.change,(()=>this.update_data()))};this.connect(this.properties.domain.change,(()=>t())),t()}update_data(){const{domain:t,palette:e}=this,o=[...this._collect(t)];this._scan_data=this.scan(o,e.length),this.metrics_change.emit(),this.change.emit()}get metrics(){return null==this._scan_data&&this.update_data(),this._scan_data}*_collect(t){for(const[e,o]of t)for(const t of(0,h.isArray)(o)?o:[o]){let o=e.data_source.get_column(t);o=e.view.indices.select(o);const n=e.view.masked,s=e.data_source.selected.indices;let l;if(null!=n&&s.length>0?l=(0,a.intersection)([...n],s):null!=n?l=[...n]:s.length>0&&(l=s),null!=l&&(o=(0,a.map)(l,(t=>o[t]))),o.length>0&&!(0,h.isNumber)(o[0]))for(const t of o)yield*t;else yield*o}}_v_compute(t,e,o,n){const{nan_color:s}=n;let{low_color:l,high_color:c}=n;null==l&&(l=o[0]),null==c&&(c=o[o.length-1]);const{domain:i}=this,h=(0,a.is_empty)(i)?t:[...this._collect(i)];this._scan_data=this.scan(h,o.length),this.metrics_change.emit();for(let n=0,i=t.length;n({high:[a(t),null],low:[a(t),null],high_color:[a(n),null],low_color:[a(n),null],domain:[c(l(o(i.GlyphRenderer),s(e,c(e)))),[]]})))},\n", - " function _(e,r,t,n,o){var a;n();const c=e(174),i=e(15),_=e(24),l=e(22),s=e(27);function p(e){return(0,l.encode_rgba)((0,l.color2rgba)(e))}function u(e){const r=new Uint32Array(e.length);for(let t=0,n=e.length;te))),r}get rgba_mapper(){const e=this,r=u(this.palette),t=this._colors(p);return{v_compute(n){const o=new _.ColorArray(n.length);return e._v_compute(n,o,r,t),new Uint8ClampedArray((0,s.to_big_endian)(o).buffer)}}}_colors(e){return{nan_color:e(this.nan_color)}}}t.ColorMapper=h,a=h,h.__name__=\"ColorMapper\",a.define((({Color:e,Array:r})=>({palette:[r(e)],nan_color:[e,\"gray\"]})))},\n", - " function _(r,e,n,s,o){s();const p=r(56);class t extends p.Transform{constructor(r){super(r)}compute(r){throw new Error(\"mapping single values is not supported\")}}n.Mapper=t,t.__name__=\"Mapper\"},\n", - " function _(e,t,i,s,l){var h;s();const n=e(176),o=e(177),a=e(186),c=e(187),_=e(189),r=e(179),d=e(70),p=e(190),g=e(24),u=e(12),y=e(13),m=e(113),v=e(67),f={fill:{},line:{}},w={fill:{fill_alpha:.3,fill_color:\"grey\"},line:{line_alpha:.3,line_color:\"grey\"}},b={fill:{fill_alpha:.2},line:{}},V={fill:{fill_alpha:.2},line:{}};class x extends n.DataRendererView{get glyph_view(){return this.glyph}async lazy_initialize(){var e;await super.lazy_initialize();const t=this.model.glyph;this.glyph=await this.build_glyph_view(t);const i=\"fill\"in this.glyph.visuals,s=\"line\"in this.glyph.visuals,l=Object.assign({},t.attributes);function h(e){const h=(0,y.clone)(l);return i&&(0,y.extend)(h,e.fill),s&&(0,y.extend)(h,e.line),new t.constructor(h)}function n(e,t){return t instanceof r.Glyph?t:h(\"auto\"==t?e:{fill:{},line:{}})}delete l.id;let{selection_glyph:o,nonselection_glyph:a,hover_glyph:c,muted_glyph:_}=this.model;o=n(f,o),this.selection_glyph=await this.build_glyph_view(o),a=n(b,a),this.nonselection_glyph=await this.build_glyph_view(a),null!=c&&(this.hover_glyph=await this.build_glyph_view(c)),_=n(V,_),this.muted_glyph=await this.build_glyph_view(_);const d=n(w,\"auto\");this.decimated_glyph=await this.build_glyph_view(d),this.selection_glyph.set_base(this.glyph),this.nonselection_glyph.set_base(this.glyph),null===(e=this.hover_glyph)||void 0===e||e.set_base(this.glyph),this.muted_glyph.set_base(this.glyph),this.decimated_glyph.set_base(this.glyph),this.set_data()}async build_glyph_view(e){return(0,m.build_view)(e,{parent:this})}remove(){var e;this.glyph.remove(),this.selection_glyph.remove(),this.nonselection_glyph.remove(),null===(e=this.hover_glyph)||void 0===e||e.remove(),this.muted_glyph.remove(),this.decimated_glyph.remove(),super.remove()}connect_signals(){super.connect_signals();const e=()=>this.request_render(),t=()=>this.update_data();this.connect(this.model.change,e),this.connect(this.glyph.model.change,t),this.connect(this.selection_glyph.model.change,t),this.connect(this.nonselection_glyph.model.change,t),null!=this.hover_glyph&&this.connect(this.hover_glyph.model.change,t),this.connect(this.muted_glyph.model.change,t),this.connect(this.decimated_glyph.model.change,t),this.connect(this.model.data_source.change,t),this.connect(this.model.data_source.streaming,t),this.connect(this.model.data_source.patching,(e=>this.update_data(e))),this.connect(this.model.data_source.selected.change,e),this.connect(this.model.data_source._select,e),null!=this.hover_glyph&&this.connect(this.model.data_source.inspect,e),this.connect(this.model.properties.view.change,t),this.connect(this.model.view.properties.indices.change,t),this.connect(this.model.view.properties.masked.change,(()=>this.set_visuals())),this.connect(this.model.properties.visible.change,(()=>this.plot_view.invalidate_dataranges=!0));const{x_ranges:i,y_ranges:s}=this.plot_view.frame;for(const[,e]of i)e instanceof v.FactorRange&&this.connect(e.change,t);for(const[,e]of s)e instanceof v.FactorRange&&this.connect(e.change,t);const{transformchange:l,exprchange:h}=this.model.glyph;this.connect(l,t),this.connect(h,t)}_update_masked_indices(){const e=this.glyph.mask_data();return this.model.view.masked=e,e}update_data(e){this.set_data(e),this.request_render()}set_data(e){const t=this.model.data_source;this.all_indices=this.model.view.indices;const{all_indices:i}=this;this.glyph.set_data(t,i,e),this.set_visuals(),this._update_masked_indices();const{lod_factor:s}=this.plot_model,l=this.all_indices.count;this.decimated=new g.Indices(l);for(let e=0;e!n||n.is_empty()?[]:n.selected_glyph?this.model.view.convert_indices_from_subset(i):n.indices.length>0?n.indices:Object.keys(n.multiline_indices).map((e=>parseInt(e))))()),d=(0,u.filter)(i,(e=>r.has(t[e]))),{lod_threshold:p}=this.plot_model;let g,y,m;if(null!=this.model.document&&this.model.document.interactive_duration()>0&&!e&&null!=p&&t.length>p?(i=[...this.decimated],g=this.decimated_glyph,y=this.decimated_glyph,m=this.selection_glyph):(g=this.model.muted?this.muted_glyph:this.glyph,y=this.nonselection_glyph,m=this.selection_glyph),null!=this.hover_glyph&&d.length){const e=new Set(i);for(const t of d)e.delete(t);i=[...e]}if(h.length){const e={};for(const t of h)e[t]=!0;const l=new Array,n=new Array;if(this.glyph instanceof o.LineView)for(const i of t)null!=e[i]?l.push(i):n.push(i);else for(const s of i)null!=e[t[s]]?l.push(s):n.push(s);y.render(s,n),m.render(s,l),null!=this.hover_glyph&&(this.glyph instanceof o.LineView?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):this.hover_glyph.render(s,d))}else if(this.glyph instanceof o.LineView)this.hover_glyph&&d.length?this.hover_glyph.render(s,this.model.view.convert_indices_from_subset(d)):g.render(s,t);else if(this.glyph instanceof a.PatchView||this.glyph instanceof c.HAreaView||this.glyph instanceof _.VAreaView)if(0==n.selected_glyphs.length||null==this.hover_glyph)g.render(s,t);else for(const e of n.selected_glyphs)e==this.glyph.model&&this.hover_glyph.render(s,t);else g.render(s,i),this.hover_glyph&&d.length&&this.hover_glyph.render(s,d);s.restore()}draw_legend(e,t,i,s,l,h,n,o){0!=this.glyph.data_size&&(null==o&&(o=this.model.get_reference_point(h,n)),this.glyph.draw_legend_for_index(e,{x0:t,x1:i,y0:s,y1:l},o))}hit_test(e){if(!this.model.visible)return null;const t=this.glyph.hit_test(e);return null==t?null:this.model.view.convert_selection_from_subset(t)}}i.GlyphRendererView=x,x.__name__=\"GlyphRendererView\";class G extends n.DataRenderer{constructor(e){super(e)}initialize(){super.initialize(),this.view.source!=this.data_source&&(this.view.source=this.data_source,this.view.compute_indices())}get_reference_point(e,t){if(null!=e){const i=this.data_source.get_column(e);if(null!=i)for(const[e,s]of Object.entries(this.view.indices_map))if(i[parseInt(e)]==t)return s}return 0}get_selection_manager(){return this.data_source.selection_manager}}i.GlyphRenderer=G,h=G,G.__name__=\"GlyphRenderer\",h.prototype.default_view=x,h.define((({Boolean:e,Auto:t,Or:i,Ref:s,Null:l,Nullable:h})=>({data_source:[s(d.ColumnarDataSource)],view:[s(p.CDSView),e=>new p.CDSView({source:e.data_source})],glyph:[s(r.Glyph)],hover_glyph:[h(s(r.Glyph)),null],nonselection_glyph:[i(s(r.Glyph),t,l),\"auto\"],selection_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted_glyph:[i(s(r.Glyph),t,l),\"auto\"],muted:[e,!1]})))},\n", - " function _(e,r,t,a,n){var s;a();const c=e(41);class _ extends c.RendererView{get xscale(){return this.coordinates.x_scale}get yscale(){return this.coordinates.y_scale}}t.DataRendererView=_,_.__name__=\"DataRendererView\";class i extends c.Renderer{constructor(e){super(e)}get selection_manager(){return this.get_selection_manager()}}t.DataRenderer=i,s=i,i.__name__=\"DataRenderer\",s.override({level:\"glyph\"})},\n", - " function _(e,t,i,s,n){s();const l=e(1);var _;const r=e(178),o=e(184),a=(0,l.__importStar)(e(48)),h=(0,l.__importStar)(e(185)),c=e(72);class d extends r.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null==t?void 0:t.regl_wrapper.has_webgl){const{LineGL:i}=await Promise.resolve().then((()=>(0,l.__importStar)(e(426))));this.glglyph=new i(t.regl_wrapper,this)}}_render(e,t,i){const{sx:s,sy:n}=null!=i?i:this;let l=null;const _=e=>null!=l&&e-l!=1;let r=!0;e.beginPath();for(const i of t){const t=s[i],o=n[i];isFinite(t+o)?r||_(i)?(e.moveTo(t,o),r=!1):e.lineTo(t,o):r=!0,l=i}this.visuals.line.set_value(e),e.stroke()}_hit_point(e){const t=new c.Selection,i={x:e.sx,y:e.sy};let s=9999;const n=Math.max(2,this.line_width.value/2);for(let e=0,l=this.sx.length-1;e({x:[c.XCoordinateSpec,{field:\"x\"}],y:[c.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,t,s,i,n){i();const r=e(1),a=(0,r.__importStar)(e(18)),o=(0,r.__importStar)(e(65)),_=(0,r.__importStar)(e(45)),l=e(42),c=e(53),h=e(19),d=e(24),u=e(8),f=e(180),p=e(12),g=e(26),y=e(181),x=e(67),v=e(72),{abs:b,ceil:m}=Math;class w extends l.View{constructor(){super(...arguments),this._index=null,this._data_size=null,this._nohit_warned=new Set}get renderer(){return this.parent}get has_webgl(){return null!=this.glglyph}get index(){const{_index:e}=this;if(null!=e)return e;throw new Error(`${this}.index_data() wasn't called`)}get data_size(){const{_data_size:e}=this;if(null!=e)return e;throw new Error(`${this}.set_data() wasn't called`)}initialize(){super.initialize(),this.visuals=new _.Visuals(this)}request_render(){this.parent.request_render()}get canvas(){return this.renderer.parent.canvas_view}render(e,t,s){var i;null!=this.glglyph&&(this.renderer.needs_webgl_blit=this.glglyph.render(e,t,null!==(i=this.base)&&void 0!==i?i:this),this.renderer.needs_webgl_blit)||this._render(e,t,null!=s?s:this.base)}has_finished(){return!0}notify_finished(){this.renderer.notify_finished()}_bounds(e){return e}bounds(){return this._bounds(this.index.bbox)}log_bounds(){const{x0:e,x1:t}=this.index.bounds(o.positive_x()),{y0:s,y1:i}=this.index.bounds(o.positive_y());return this._bounds({x0:e,y0:s,x1:t,y1:i})}get_anchor_point(e,t,[s,i]){switch(e){case\"center\":case\"center_center\":{const[e,n]=this.scenterxy(t,s,i);return{x:e,y:n}}default:return null}}scenterx(e,t,s){return this.scenterxy(e,t,s)[0]}scentery(e,t,s){return this.scenterxy(e,t,s)[1]}sdist(e,t,s,i=\"edge\",n=!1){const r=t.length,a=new d.ScreenArray(r),o=e.s_compute;if(\"center\"==i)for(let e=0;em(e))),a}draw_legend_for_index(e,t,s){}hit_test(e){switch(e.type){case\"point\":if(null!=this._hit_point)return this._hit_point(e);break;case\"span\":if(null!=this._hit_span)return this._hit_span(e);break;case\"rect\":if(null!=this._hit_rect)return this._hit_rect(e);break;case\"poly\":if(null!=this._hit_poly)return this._hit_poly(e)}return this._nohit_warned.has(e.type)||(h.logger.debug(`'${e.type}' selection not available for ${this.model.type}`),this._nohit_warned.add(e.type)),null}_hit_rect_against_index(e){const{sx0:t,sx1:s,sy0:i,sy1:n}=e,[r,a]=this.renderer.coordinates.x_scale.r_invert(t,s),[o,_]=this.renderer.coordinates.y_scale.r_invert(i,n),l=[...this.index.indices({x0:r,x1:a,y0:o,y1:_})];return new v.Selection({indices:l})}_project_data(){}*_iter_visuals(){for(const e of this.visuals)for(const t of e)(t instanceof a.VectorSpec||t instanceof a.ScalarSpec)&&(yield t)}set_base(e){e!=this&&e instanceof this.constructor&&(this.base=e)}_configure(e,t){Object.defineProperty(this,(0,u.isString)(e)?e:e.attr,Object.assign({configurable:!0,enumerable:!0},t))}set_visuals(e,t){var s;for(const s of this._iter_visuals()){const{base:i}=this;if(null!=i){const e=i.model.properties[s.attr];if(null!=e&&(0,g.is_equal)(s.get_value(),e.get_value())){this._configure(s,{get:()=>i[`${s.attr}`]});continue}}const n=s.uniform(e).select(t);this._configure(s,{value:n})}for(const e of this.visuals)e.update();null===(s=this.glglyph)||void 0===s||s.set_visuals_changed()}set_data(e,t,s){var i;const{x_source:n,y_source:r}=this.renderer.coordinates,o=new Set(this._iter_visuals());this._data_size=t.count;for(const s of this.model)if((s instanceof a.VectorSpec||s instanceof a.ScalarSpec)&&!o.has(s))if(s instanceof a.BaseCoordinateSpec){const i=s.array(e);let o=t.select(i);const _=\"x\"==s.dimension?n:r;if(_ instanceof x.FactorRange)if(s instanceof a.CoordinateSpec)o=_.v_synthetic(o);else if(s instanceof a.CoordinateSeqSpec)for(let e=0;e{const s=new Uint32Array(r);for(let a=0;a>1;t[s]>i?e=s:n=s+1}return t[n]}class r extends d.default{get boxes(){return this._boxes}search_indices(i,t,n,e){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let s=this._boxes.length-4;const d=[],x=new o.Indices(this.numItems);for(;void 0!==s;){const o=Math.min(s+4*this.nodeSize,h(s,this._levelBounds));for(let h=s;h>2],r=this._boxes[h+0],l=this._boxes[h+1],a=this._boxes[h+2],_=this._boxes[h+3];na||t>_||(s<4*this.numItems?x.set(o):d.push(o)))}s=d.pop()}return x}}r.__name__=\"_FlatBush\";class l{constructor(i){this.index=null,i>0&&(this.index=new r(i))}add_rect(i,t,n,e){var s;isFinite(i+t+n+e)?null===(s=this.index)||void 0===s||s.add(i,t,n,e):this.add_empty()}add_point(i,t){var n;isFinite(i+t)?null===(n=this.index)||void 0===n||n.add(i,t,i,t):this.add_empty()}add_empty(){var i;null===(i=this.index)||void 0===i||i.add(1/0,1/0,-1/0,-1/0)}finish(){var i;null===(i=this.index)||void 0===i||i.finish()}_normalize(i){let{x0:t,y0:n,x1:e,y1:s}=i;return t>e&&([t,e]=[e,t]),n>s&&([n,s]=[s,n]),{x0:t,y0:n,x1:e,y1:s}}get bbox(){if(null==this.index)return(0,x.empty)();{const{minX:i,minY:t,maxX:n,maxY:e}=this.index;return{x0:i,y0:t,x1:n,y1:e}}}indices(i){if(null==this.index)return new o.Indices(0);{const{x0:t,y0:n,x1:e,y1:s}=this._normalize(i);return this.index.search_indices(t,n,e,s)}}bounds(i){const t=(0,x.empty)();if(null==this.index)return t;const{boxes:n}=this.index;for(const e of this.indices(i)){const s=n[4*e+0],d=n[4*e+1],o=n[4*e+2],x=n[4*e+3];s>=i.x0&&st.x1&&(t.x1=o),d>=i.y0&&dt.y1&&(t.y1=x)}return t}}n.SpatialIndex=l,l.__name__=\"SpatialIndex\"},\n", - " function _(t,s,i,e,h){e();const n=(0,t(1).__importDefault)(t(183)),o=[Int8Array,Uint8Array,Uint8ClampedArray,Int16Array,Uint16Array,Int32Array,Uint32Array,Float32Array,Float64Array];class r{static from(t){if(!(t instanceof ArrayBuffer))throw new Error(\"Data must be an instance of ArrayBuffer.\");const[s,i]=new Uint8Array(t,0,2);if(251!==s)throw new Error(\"Data does not appear to be in a Flatbush format.\");if(i>>4!=3)throw new Error(`Got v${i>>4} data when expected v3.`);const[e]=new Uint16Array(t,2,1),[h]=new Uint32Array(t,4,1);return new r(h,e,o[15&i],t)}constructor(t,s=16,i=Float64Array,e){if(void 0===t)throw new Error(\"Missing required argument: numItems.\");if(isNaN(t)||t<=0)throw new Error(`Unpexpected numItems value: ${t}.`);this.numItems=+t,this.nodeSize=Math.min(Math.max(+s,2),65535);let h=t,r=h;this._levelBounds=[4*h];do{h=Math.ceil(h/this.nodeSize),r+=h,this._levelBounds.push(4*r)}while(1!==h);this.ArrayType=i||Float64Array,this.IndexArrayType=r<16384?Uint16Array:Uint32Array;const a=o.indexOf(this.ArrayType),_=4*r*this.ArrayType.BYTES_PER_ELEMENT;if(a<0)throw new Error(`Unexpected typed array class: ${i}.`);e&&e instanceof ArrayBuffer?(this.data=e,this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=4*r,this.minX=this._boxes[this._pos-4],this.minY=this._boxes[this._pos-3],this.maxX=this._boxes[this._pos-2],this.maxY=this._boxes[this._pos-1]):(this.data=new ArrayBuffer(8+_+r*this.IndexArrayType.BYTES_PER_ELEMENT),this._boxes=new this.ArrayType(this.data,8,4*r),this._indices=new this.IndexArrayType(this.data,8+_,r),this._pos=0,this.minX=1/0,this.minY=1/0,this.maxX=-1/0,this.maxY=-1/0,new Uint8Array(this.data,0,2).set([251,48+a]),new Uint16Array(this.data,2,1)[0]=s,new Uint32Array(this.data,4,1)[0]=t),this._queue=new n.default}add(t,s,i,e){const h=this._pos>>2;return this._indices[h]=h,this._boxes[this._pos++]=t,this._boxes[this._pos++]=s,this._boxes[this._pos++]=i,this._boxes[this._pos++]=e,tthis.maxX&&(this.maxX=i),e>this.maxY&&(this.maxY=e),h}finish(){if(this._pos>>2!==this.numItems)throw new Error(`Added ${this._pos>>2} items when expected ${this.numItems}.`);if(this.numItems<=this.nodeSize)return this._boxes[this._pos++]=this.minX,this._boxes[this._pos++]=this.minY,this._boxes[this._pos++]=this.maxX,void(this._boxes[this._pos++]=this.maxY);const t=this.maxX-this.minX,s=this.maxY-this.minY,i=new Uint32Array(this.numItems);for(let e=0;e>2]=t,this._boxes[this._pos++]=e,this._boxes[this._pos++]=h,this._boxes[this._pos++]=n,this._boxes[this._pos++]=o}}}search(t,s,i,e,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=[],r=[];for(;void 0!==n;){const a=Math.min(n+4*this.nodeSize,_(n,this._levelBounds));for(let _=n;_>2];ithis._boxes[_+2]||s>this._boxes[_+3]||(n<4*this.numItems?(void 0===h||h(a))&&r.push(a):o.push(a)))}n=o.pop()}return r}neighbors(t,s,i=1/0,e=1/0,h){if(this._pos!==this._boxes.length)throw new Error(\"Data not yet indexed - call index.finish().\");let n=this._boxes.length-4;const o=this._queue,r=[],x=e*e;for(;void 0!==n;){const 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i=t^s,e=65535^i,h=65535^(t|s),n=t&(65535^s),o=i|e>>1,r=i>>1^i,a=h>>1^e&n>>1^h,_=i&h>>1^n>>1^n;i=o,e=r,h=a,n=_,o=i&i>>2^e&e>>2,r=i&e>>2^e&(i^e)>>2,a^=i&h>>2^e&n>>2,_^=e&h>>2^(i^e)&n>>2,i=o,e=r,h=a,n=_,o=i&i>>4^e&e>>4,r=i&e>>4^e&(i^e)>>4,a^=i&h>>4^e&n>>4,_^=e&h>>4^(i^e)&n>>4,i=o,e=r,h=a,n=_,a^=i&h>>8^e&n>>8,_^=e&h>>8^(i^e)&n>>8,i=a^a>>1,e=_^_>>1;let x=t^s,d=e|65535^(x|i);return x=16711935&(x|x<<8),x=252645135&(x|x<<4),x=858993459&(x|x<<2),x=1431655765&(x|x<<1),d=16711935&(d|d<<8),d=252645135&(d|d<<4),d=858993459&(d|d<<2),d=1431655765&(d|d<<1),(d<<1|x)>>>0}i.default=r},\n", - " function _(s,t,i,h,e){h();i.default=class{constructor(){this.ids=[],this.values=[],this.length=0}clear(){this.length=0}push(s,t){let i=this.length++;for(this.ids[i]=s,this.values[i]=t;i>0;){const s=i-1>>1,h=this.values[s];if(t>=h)break;this.ids[i]=this.ids[s],this.values[i]=h,i=s}this.ids[i]=s,this.values[i]=t}pop(){if(0===this.length)return;const s=this.ids[0];if(this.length--,this.length>0){const s=this.ids[0]=this.ids[this.length],t=this.values[0]=this.values[this.length],i=this.length>>1;let h=0;for(;h=t)break;this.ids[h]=e,this.values[h]=l,h=s}this.ids[h]=s,this.values[h]=t}return s}peek(){if(0!==this.length)return this.ids[0]}peekValue(){if(0!==this.length)return this.values[0]}}},\n", - " function _(e,n,a,t,i){t();const l=(0,e(1).__importStar)(e(185));function r(e,n,{x0:a,x1:t,y0:i,y1:l},r){n.save(),n.beginPath(),n.moveTo(a,(i+l)/2),n.lineTo(t,(i+l)/2),e.line.apply(n,r),n.restore()}function c(e,n,{x0:a,x1:t,y0:i,y1:l},r){var c,o;const _=.1*Math.abs(t-a),s=.1*Math.abs(l-i),y=a+_,p=t-_,g=i+s,h=l-s;n.beginPath(),n.rect(y,g,p-y,h-g),e.fill.apply(n,r),null===(c=e.hatch)||void 0===c||c.apply(n,r),null===(o=e.line)||void 0===o||o.apply(n,r)}a.generic_line_scalar_legend=function(e,n,{x0:a,x1:t,y0:i,y1:l}){n.save(),n.beginPath(),n.moveTo(a,(i+l)/2),n.lineTo(t,(i+l)/2),e.line.apply(n),n.restore()},a.generic_line_vector_legend=r,a.generic_line_legend=r,a.generic_area_scalar_legend=function(e,n,{x0:a,x1:t,y0:i,y1:l}){var r,c;const o=.1*Math.abs(t-a),_=.1*Math.abs(l-i),s=a+o,y=t-o,p=i+_,g=l-_;n.beginPath(),n.rect(s,p,y-s,g-p),e.fill.apply(n),null===(r=e.hatch)||void 0===r||r.apply(n),null===(c=e.line)||void 0===c||c.apply(n)},a.generic_area_vector_legend=c,a.generic_area_legend=c,a.line_interpolation=function(e,n,a,t,i,r){const{sx:c,sy:o}=n;let _,s,y,p;\"point\"==n.type?([y,p]=e.yscale.r_invert(o-1,o+1),[_,s]=e.xscale.r_invert(c-1,c+1)):\"v\"==n.direction?([y,p]=e.yscale.r_invert(o,o),[_,s]=[Math.min(a-1,i-1),Math.max(a+1,i+1)]):([_,s]=e.xscale.r_invert(c,c),[y,p]=[Math.min(t-1,r-1),Math.max(t+1,r+1)]);const{x:g,y:h}=l.check_2_segments_intersect(_,y,s,p,a,t,i,r);return[g,h]}},\n", - " function _(t,n,e,i,r){function s(t,n){return(t.x-n.x)**2+(t.y-n.y)**2}function o(t,n,e){const i=s(n,e);if(0==i)return s(t,n);const r=((t.x-n.x)*(e.x-n.x)+(t.y-n.y)*(e.y-n.y))/i;if(r<0)return s(t,n);if(r>1)return s(t,e);return s(t,{x:n.x+r*(e.x-n.x),y:n.y+r*(e.y-n.y)})}i(),e.point_in_poly=function(t,n,e,i){let r=!1,s=e[e.length-1],o=i[i.length-1];for(let u=0;u0&&_<1&&h>0&&h<1,x:t+_*(e-t),y:n+_*(i-n)}}}},\n", - " function _(t,s,e,i,a){i();const l=t(1);var n;const _=t(178),o=t(184),c=(0,l.__importStar)(t(185)),h=(0,l.__importStar)(t(48)),r=t(72);class p extends _.XYGlyphView{_render(t,s,e){const{sx:i,sy:a}=null!=e?e:this;let l=!0;t.beginPath();for(const e of s){const s=i[e],n=a[e];isFinite(s+n)?l?(t.moveTo(s,n),l=!1):t.lineTo(s,n):(t.closePath(),l=!0)}t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t),this.visuals.line.apply(t)}draw_legend_for_index(t,s,e){(0,o.generic_area_scalar_legend)(this.visuals,t,s)}_hit_point(t){const s=new r.Selection;return c.point_in_poly(t.sx,t.sy,this.sx,this.sy)&&(s.add_to_selected_glyphs(this.model),s.view=this),s}}e.PatchView=p,p.__name__=\"PatchView\";class d extends _.XYGlyph{constructor(t){super(t)}}e.Patch=d,n=d,d.__name__=\"Patch\",n.prototype.default_view=p,n.mixins([h.LineScalar,h.FillScalar,h.HatchScalar])},\n", - " function _(t,s,e,i,n){i();const h=t(1);var r;const a=t(188),_=(0,h.__importStar)(t(185)),o=(0,h.__importStar)(t(18)),l=t(72);class c extends a.AreaView{_index_data(t){const{min:s,max:e}=Math,{data_size:i}=this;for(let n=0;n=0;s--)t.lineTo(n[s],h[s]);t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t)}_hit_point(t){const s=this.sy.length,e=new l.Selection;for(let i=0,n=s-1;i({x1:[o.XCoordinateSpec,{field:\"x1\"}],x2:[o.XCoordinateSpec,{field:\"x2\"}],y:[o.YCoordinateSpec,{field:\"y\"}]})))},\n", - " function _(e,a,r,_,s){_();const n=e(1);var c;const i=e(179),l=e(184),t=(0,n.__importStar)(e(48));class o extends i.GlyphView{draw_legend_for_index(e,a,r){(0,l.generic_area_scalar_legend)(this.visuals,e,a)}}r.AreaView=o,o.__name__=\"AreaView\";class d extends i.Glyph{constructor(e){super(e)}}r.Area=d,c=d,d.__name__=\"Area\",c.mixins([t.FillScalar,t.HatchScalar])},\n", - " function _(t,s,e,i,n){i();const h=t(1);var r;const a=t(188),_=(0,h.__importStar)(t(185)),o=(0,h.__importStar)(t(18)),l=t(72);class c extends a.AreaView{_index_data(t){const{min:s,max:e}=Math,{data_size:i}=this;for(let n=0;n=0;s--)t.lineTo(i[s],h[s]);t.closePath(),this.visuals.fill.apply(t),this.visuals.hatch.apply(t)}scenterxy(t){return[this.sx[t],(this.sy1[t]+this.sy2[t])/2]}_hit_point(t){const s=this.sx.length,e=new l.Selection;for(let i=0,n=s-1;i({x:[o.XCoordinateSpec,{field:\"x\"}],y1:[o.YCoordinateSpec,{field:\"y1\"}],y2:[o.YCoordinateSpec,{field:\"y2\"}]})))},\n", - " function _(e,i,s,t,n){var c;t();const o=e(53),r=e(24),u=e(191),_=e(70);class a extends o.Model{constructor(e){super(e)}initialize(){super.initialize(),this.compute_indices()}connect_signals(){super.connect_signals(),this.connect(this.properties.filters.change,(()=>this.compute_indices()));const e=()=>{const e=()=>this.compute_indices();null!=this.source&&(this.connect(this.source.change,e),this.source instanceof _.ColumnarDataSource&&(this.connect(this.source.streaming,e),this.connect(this.source.patching,e)))};let i=null!=this.source;i?e():this.connect(this.properties.source.change,(()=>{i||(e(),i=!0)}))}compute_indices(){var e;const{source:i}=this;if(null==i)return;const s=null!==(e=i.get_length())&&void 0!==e?e:1,t=r.Indices.all_set(s);for(const e of this.filters)t.intersect(e.compute_indices(i));this.indices=t,this._indices=[...t],this.indices_map_to_subset()}indices_map_to_subset(){this.indices_map={};for(let e=0;ethis._indices[e]))}convert_selection_to_subset(e){return e.map((e=>this.indices_map[e]))}convert_indices_from_subset(e){return e.map((e=>this._indices[e]))}}s.CDSView=a,c=a,a.__name__=\"CDSView\",c.define((({Array:e,Ref:i})=>({filters:[e(i(u.Filter)),[]],source:[i(_.ColumnarDataSource)]}))),c.internal((({Int:e,Dict:i,Ref:s,Nullable:t})=>({indices:[s(r.Indices)],indices_map:[i(e),{}],masked:[t(s(r.Indices)),null]})))},\n", - " function _(e,t,n,s,c){s();const o=e(53);class r extends o.Model{constructor(e){super(e)}}n.Filter=r,r.__name__=\"Filter\"},\n", - " function _(t,r,a,e,c){e(),c(\"BasicTickFormatter\",t(146).BasicTickFormatter),c(\"CategoricalTickFormatter\",t(142).CategoricalTickFormatter),c(\"DatetimeTickFormatter\",t(150).DatetimeTickFormatter),c(\"FuncTickFormatter\",t(193).FuncTickFormatter),c(\"LogTickFormatter\",t(163).LogTickFormatter),c(\"MercatorTickFormatter\",t(166).MercatorTickFormatter),c(\"NumeralTickFormatter\",t(194).NumeralTickFormatter),c(\"PrintfTickFormatter\",t(195).PrintfTickFormatter),c(\"TickFormatter\",t(131).TickFormatter)},\n", - " function _(t,e,n,s,r){var c;s();const i=t(131),a=t(13),u=t(34);class o extends i.TickFormatter{constructor(t){super(t)}get names(){return(0,a.keys)(this.args)}get values(){return(0,a.values)(this.args)}_make_func(){const t=(0,u.use_strict)(this.code);return new Function(\"tick\",\"index\",\"ticks\",...this.names,t)}doFormat(t,e){const n=this._make_func().bind({});return t.map(((t,e,s)=>`${n(t,e,s,...this.values)}`))}}n.FuncTickFormatter=o,c=o,o.__name__=\"FuncTickFormatter\",c.define((({Unknown:t,String:e,Dict:n})=>({args:[n(t),{}],code:[e,\"\"]})))},\n", - " function _(r,n,t,o,e){o();var a;const u=(0,r(1).__importStar)(r(153)),c=r(131),i=r(20);class s extends c.TickFormatter{constructor(r){super(r)}get _rounding_fn(){switch(this.rounding){case\"round\":case\"nearest\":return Math.round;case\"floor\":case\"rounddown\":return Math.floor;case\"ceil\":case\"roundup\":return Math.ceil}}doFormat(r,n){const{format:t,language:o,_rounding_fn:e}=this;return r.map((r=>u.format(r,t,o,e)))}}t.NumeralTickFormatter=s,a=s,s.__name__=\"NumeralTickFormatter\",a.define((({String:r})=>({format:[r,\"0,0\"],language:[r,\"en\"],rounding:[i.RoundingFunction,\"round\"]})))},\n", - " function _(t,r,n,o,a){var e;o();const i=t(131),s=t(152);class c extends i.TickFormatter{constructor(t){super(t)}doFormat(t,r){return t.map((t=>(0,s.sprintf)(this.format,t)))}}n.PrintfTickFormatter=c,e=c,c.__name__=\"PrintfTickFormatter\",e.define((({String:t})=>({format:[t,\"%s\"]})))},\n", - " function _(r,o,a,p,e){p(),e(\"CategoricalColorMapper\",r(197).CategoricalColorMapper),e(\"CategoricalMarkerMapper\",r(199).CategoricalMarkerMapper),e(\"CategoricalPatternMapper\",r(200).CategoricalPatternMapper),e(\"ContinuousColorMapper\",r(172).ContinuousColorMapper),e(\"ColorMapper\",r(173).ColorMapper),e(\"LinearColorMapper\",r(201).LinearColorMapper),e(\"LogColorMapper\",r(202).LogColorMapper),e(\"ScanningColorMapper\",r(171).ScanningColorMapper),e(\"EqHistColorMapper\",r(203).EqHistColorMapper)},\n", - " function _(t,o,r,a,e){var c;a();const s=t(198),l=t(173),n=t(67);class _ extends l.ColorMapper{constructor(t){super(t)}_v_compute(t,o,r,{nan_color:a}){(0,s.cat_v_compute)(t,this.factors,r,o,this.start,this.end,a)}}r.CategoricalColorMapper=_,c=_,_.__name__=\"CategoricalColorMapper\",c.define((({Number:t,Nullable:o})=>({factors:[n.FactorSeq],start:[t,0],end:[o(t),null]})))},\n", - " function _(n,t,e,l,i){l();const c=n(12),u=n(8);function f(n,t){if(n.length!=t.length)return!1;for(let e=0,l=n.length;ef(n,h)))),s=_<0||_>=e.length?r:e[_],l[g]=s}}},\n", - " function _(e,r,a,t,s){var c;t();const l=e(198),n=e(67),u=e(174),o=e(20);class p extends u.Mapper{constructor(e){super(e)}v_compute(e){const r=new Array(e.length);return(0,l.cat_v_compute)(e,this.factors,this.markers,r,this.start,this.end,this.default_value),r}}a.CategoricalMarkerMapper=p,c=p,p.__name__=\"CategoricalMarkerMapper\",c.define((({Number:e,Array:r,Nullable:a})=>({factors:[n.FactorSeq],markers:[r(o.MarkerType)],start:[e,0],end:[a(e),null],default_value:[o.MarkerType,\"circle\"]})))},\n", - " function _(t,e,a,r,n){var s;r();const c=t(198),l=t(67),p=t(174),u=t(20);class o extends p.Mapper{constructor(t){super(t)}v_compute(t){const e=new Array(t.length);return(0,c.cat_v_compute)(t,this.factors,this.patterns,e,this.start,this.end,this.default_value),e}}a.CategoricalPatternMapper=o,s=o,o.__name__=\"CategoricalPatternMapper\",s.define((({Number:t,Array:e,Nullable:a})=>({factors:[l.FactorSeq],patterns:[e(u.HatchPatternType)],start:[t,0],end:[a(t),null],default_value:[u.HatchPatternType,\" \"]})))},\n", - " function _(n,r,o,t,a){t();const e=n(172),i=n(12);class s extends e.ContinuousColorMapper{constructor(n){super(n)}scan(n,r){const o=null!=this.low?this.low:(0,i.min)(n),t=null!=this.high?this.high:(0,i.max)(n);return{max:t,min:o,norm_factor:1/(t-o),normed_interval:1/r}}cmap(n,r,o,t,a){const e=r.length-1;if(n==a.max)return r[e];const i=(n-a.min)*a.norm_factor,s=Math.floor(i/a.normed_interval);return s<0?o:s>e?t:r[s]}}o.LinearColorMapper=s,s.__name__=\"LinearColorMapper\"},\n", - " function _(o,t,n,r,l){r();const a=o(172),s=o(12);class e extends a.ContinuousColorMapper{constructor(o){super(o)}scan(o,t){const n=null!=this.low?this.low:(0,s.min)(o),r=null!=this.high?this.high:(0,s.max)(o);return{max:r,min:n,scale:t/(Math.log(r)-Math.log(n))}}cmap(o,t,n,r,l){const a=t.length-1;if(o>l.max)return r;if(o==l.max)return t[a];if(oa&&(e=a),t[e]}}n.LogColorMapper=e,e.__name__=\"LogColorMapper\"},\n", - " function _(e,n,s,t,l){var i;t();const r=e(171),o=e(12),c=e(9);class a extends r.ScanningColorMapper{constructor(e){super(e)}scan(e,n){let s=null!=this.low?this.low:(0,o.min)(e);const t=null!=this.high?this.high:(0,o.max)(e),l=this.bins,i=(0,c.linspace)(s,t,l+1),r=(0,o.bin_counts)(e,i);let a=0;for(let e=0;e1&&(f=1-n)}const d=(0,c.linspace)(f,1,n+1),g=(0,o.interpolate)(d,p,_);return this.rescale_discrete_levels?s=g[0]:g[0]=s,g[g.length-1]=t,{min:s,max:t,binning:g}}}s.EqHistColorMapper=a,i=a,a.__name__=\"EqHistColorMapper\",i.define((({Boolean:e,Int:n})=>({bins:[n,65536],rescale_discrete_levels:[e,!1]})))},\n", - " function _(a,e,l,c,n){c(),n(\"CategoricalScale\",a(62).CategoricalScale),n(\"ContinuousScale\",a(60).ContinuousScale),n(\"LinearScale\",a(59).LinearScale),n(\"LinearInterpolationScale\",a(205).LinearInterpolationScale),n(\"LogScale\",a(61).LogScale),n(\"Scale\",a(55).Scale)},\n", - " function _(e,r,n,t,a){var i;t();const s=e(55),o=e(59),c=e(12);class _ extends s.Scale{constructor(e){super(e)}connect_signals(){super.connect_signals();const{source_range:e,target_range:r}=this.properties;this.on_change([e,r],(()=>{this.linear_scale=new o.LinearScale({source_range:this.source_range,target_range:this.target_range})}))}get s_compute(){throw new Error(\"not implemented\")}get s_invert(){throw new Error(\"not implemented\")}compute(e){return e}v_compute(e){const{binning:r}=this,{start:n,end:t}=this.source_range,a=n,i=t,s=r.length,o=(t-n)/(s-1),_=new Float64Array(s);for(let e=0;e{if(ei)return i;const n=(0,c.left_edge_index)(e,r);if(-1==n)return a;if(n>=s-1)return i;const t=r[n],o=(e-t)/(r[n+1]-t),l=_[n];return l+o*(_[n+1]-l)}));return this.linear_scale.v_compute(l)}invert(e){return e}v_invert(e){return new Float64Array(e)}}n.LinearInterpolationScale=_,i=_,_.__name__=\"LinearInterpolationScale\",i.internal((({Arrayable:e,Ref:r})=>({binning:[e],linear_scale:[r(o.LinearScale),e=>new o.LinearScale({source_range:e.source_range,target_range:e.target_range})]})))},\n", - " function _(a,n,e,g,R){g(),R(\"DataRange\",a(64).DataRange),R(\"DataRange1d\",a(63).DataRange1d),R(\"FactorRange\",a(67).FactorRange),R(\"Range\",a(57).Range),R(\"Range1d\",a(58).Range1d)},\n", - " function _(a,o,i,t,e){t();var n=a(124);e(\"Sizeable\",n.Sizeable),e(\"SizingPolicy\",n.SizingPolicy);var c=a(125);e(\"Layoutable\",c.Layoutable),e(\"LayoutItem\",c.LayoutItem);var r=a(208);e(\"HStack\",r.HStack),e(\"VStack\",r.VStack);var l=a(209);e(\"Grid\",l.Grid),e(\"Row\",l.Row),e(\"Column\",l.Column);var S=a(210);e(\"ContentBox\",S.ContentBox),e(\"VariadicBox\",S.VariadicBox)},\n", - " function _(t,e,h,i,r){i();const n=t(125),o=t(65);class s extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}}h.Stack=s,s.__name__=\"Stack\";class c extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e+=i.width,h=Math.max(h,i.height)}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.top:0;let i=this.absolute?t.left:0;const{height:r}=t;for(const t of this.children){const{width:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({left:i,width:e,top:h,height:r})),i+=e}}}h.HStack=c,c.__name__=\"HStack\";class a extends s{_measure(t){let e=0,h=0;for(const t of this.children){const i=t.measure({width:0,height:0});e=Math.max(e,i.width),h+=i.height}return{width:e,height:h}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t.left:0;let i=this.absolute?t.top:0;const{width:r}=t;for(const t of this.children){const{height:e}=t.measure({width:0,height:0});t.set_geometry(new o.BBox({top:i,height:e,left:h,width:r})),i+=e}}}h.VStack=a,a.__name__=\"VStack\";class l extends n.Layoutable{constructor(){super(...arguments),this.children=[]}*[Symbol.iterator](){yield*this.children}_measure(t){const{width_policy:e,height_policy:h}=this.sizing,{min:i,max:r}=Math;let n=0,o=0;for(const e of this.children){const{width:h,height:i}=e.measure(t);n=r(n,h),o=r(o,i)}return{width:(()=>{const{width:h}=this.sizing;if(t.width==1/0)return\"fixed\"==e&&null!=h?h:n;switch(e){case\"fixed\":return null!=h?h:n;case\"min\":return n;case\"fit\":return null!=h?i(t.width,h):t.width;case\"max\":return null!=h?r(t.width,h):t.width}})(),height:(()=>{const{height:e}=this.sizing;if(t.height==1/0)return\"fixed\"==h&&null!=e?e:o;switch(h){case\"fixed\":return null!=e?e:o;case\"min\":return o;case\"fit\":return null!=e?i(t.height,e):t.height;case\"max\":return null!=e?r(t.height,e):t.height}})()}}_set_geometry(t,e){super._set_geometry(t,e);const h=this.absolute?t:t.relative(),{left:i,right:r,top:n,bottom:s}=h,c=Math.round(h.vcenter),a=Math.round(h.hcenter);for(const e of this.children){const{margin:h,halign:l,valign:d}=e.sizing,{width:u,height:g,inner:_}=e.measure(t),w=(()=>{switch(`${d}_${l}`){case\"start_start\":return new o.BBox({left:i+h.left,top:n+h.top,width:u,height:g});case\"start_center\":return new o.BBox({hcenter:a,top:n+h.top,width:u,height:g});case\"start_end\":return new o.BBox({right:r-h.right,top:n+h.top,width:u,height:g});case\"center_start\":return new o.BBox({left:i+h.left,vcenter:c,width:u,height:g});case\"center_center\":return new o.BBox({hcenter:a,vcenter:c,width:u,height:g});case\"center_end\":return new o.BBox({right:r-h.right,vcenter:c,width:u,height:g});case\"end_start\":return new o.BBox({left:i+h.left,bottom:s-h.bottom,width:u,height:g});case\"end_center\":return new o.BBox({hcenter:a,bottom:s-h.bottom,width:u,height:g});case\"end_end\":return new o.BBox({right:r-h.right,bottom:s-h.bottom,width:u,height:g})}})(),m=null==_?w:new o.BBox({left:w.left+_.left,top:w.top+_.top,right:w.right-_.right,bottom:w.bottom-_.bottom});e.set_geometry(w,m)}}}h.NodeLayout=l,l.__name__=\"NodeLayout\"},\n", - " function _(t,i,s,e,o){e();const n=t(124),l=t(125),r=t(8),h=t(65),c=t(9),{max:a,round:g}=Math;class p{constructor(t){this.def=t,this._map=new Map}get(t){let i=this._map.get(t);return void 0===i&&(i=this.def(),this._map.set(t,i)),i}apply(t,i){const s=this.get(t);this._map.set(t,i(s))}}p.__name__=\"DefaultMap\";class f{constructor(){this._items=[],this._nrows=0,this._ncols=0}get nrows(){return this._nrows}get ncols(){return this._ncols}add(t,i){const{r1:s,c1:e}=t;this._nrows=a(this._nrows,s+1),this._ncols=a(this._ncols,e+1),this._items.push({span:t,data:i})}at(t,i){return this._items.filter((({span:s})=>s.r0<=t&&t<=s.r1&&s.c0<=i&&i<=s.c1)).map((({data:t})=>t))}row(t){return this._items.filter((({span:i})=>i.r0<=t&&t<=i.r1)).map((({data:t})=>t))}col(t){return this._items.filter((({span:i})=>i.c0<=t&&t<=i.c1)).map((({data:t})=>t))}foreach(t){for(const{span:i,data:s}of this._items)t(i,s)}map(t){const i=new f;for(const{span:s,data:e}of this._items)i.add(s,t(s,e));return i}}f.__name__=\"Container\";class _ extends l.Layoutable{constructor(t=[]){super(),this.items=t,this.rows=\"auto\",this.cols=\"auto\",this.spacing=0}*[Symbol.iterator](){for(const{layout:t}of this.items)yield t}is_width_expanding(){if(super.is_width_expanding())return!0;if(\"fixed\"==this.sizing.width_policy)return!1;const{cols:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}is_height_expanding(){if(super.is_height_expanding())return!0;if(\"fixed\"==this.sizing.height_policy)return!1;const{rows:t}=this._state;return(0,c.some)(t,(t=>\"max\"==t.policy))}_init(){var t,i,s,e;super._init();const o=new f;for(const{layout:t,row:i,col:s,row_span:e,col_span:n}of this.items)if(t.sizing.visible){const l=i,r=s,h=i+(null!=e?e:1)-1,c=s+(null!=n?n:1)-1;o.add({r0:l,c0:r,r1:h,c1:c},t)}const{nrows:n,ncols:l}=o,h=new Array(n);for(let s=0;s{var t;const i=(0,r.isPlainObject)(this.rows)?null!==(t=this.rows[s])&&void 0!==t?t:this.rows[\"*\"]:this.rows;return null==i?{policy:\"auto\"}:(0,r.isNumber)(i)?{policy:\"fixed\",height:i}:(0,r.isString)(i)?{policy:i}:i})(),n=null!==(t=e.align)&&void 0!==t?t:\"auto\";if(\"fixed\"==e.policy)h[s]={policy:\"fixed\",height:e.height,align:n};else if(\"min\"==e.policy)h[s]={policy:\"min\",align:n};else if(\"fit\"==e.policy||\"max\"==e.policy)h[s]={policy:e.policy,flex:null!==(i=e.flex)&&void 0!==i?i:1,align:n};else{if(\"auto\"!=e.policy)throw new Error(\"unrechable\");(0,c.some)(o.row(s),(t=>t.is_height_expanding()))?h[s]={policy:\"max\",flex:1,align:n}:h[s]={policy:\"min\",align:n}}}const a=new Array(l);for(let t=0;t{var i;const s=(0,r.isPlainObject)(this.cols)?null!==(i=this.cols[t])&&void 0!==i?i:this.cols[\"*\"]:this.cols;return null==s?{policy:\"auto\"}:(0,r.isNumber)(s)?{policy:\"fixed\",width:s}:(0,r.isString)(s)?{policy:s}:s})(),n=null!==(s=i.align)&&void 0!==s?s:\"auto\";if(\"fixed\"==i.policy)a[t]={policy:\"fixed\",width:i.width,align:n};else if(\"min\"==i.policy)a[t]={policy:\"min\",align:n};else if(\"fit\"==i.policy||\"max\"==i.policy)a[t]={policy:i.policy,flex:null!==(e=i.flex)&&void 0!==e?e:1,align:n};else{if(\"auto\"!=i.policy)throw new Error(\"unrechable\");(0,c.some)(o.col(t),(t=>t.is_width_expanding()))?a[t]={policy:\"max\",flex:1,align:n}:a[t]={policy:\"min\",align:n}}}const[g,p]=(0,r.isNumber)(this.spacing)?[this.spacing,this.spacing]:this.spacing;this._state={items:o,nrows:n,ncols:l,rows:h,cols:a,rspacing:g,cspacing:p}}_measure_totals(t,i){const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state;return{height:(0,c.sum)(t)+(s-1)*o,width:(0,c.sum)(i)+(e-1)*n}}_measure_cells(t){const{items:i,nrows:s,ncols:e,rows:o,cols:l,rspacing:r,cspacing:h}=this._state,c=new Array(s);for(let t=0;t{const{r0:e,c0:f,r1:d,c1:u}=i,w=(d-e)*r,m=(u-f)*h;let y=0;for(let i=e;i<=d;i++)y+=t(i,f).height;y+=w;let x=0;for(let i=f;i<=u;i++)x+=t(e,i).width;x+=m;const b=s.measure({width:x,height:y});_.add(i,{layout:s,size_hint:b});const z=new n.Sizeable(b).grow_by(s.sizing.margin);z.height-=w,z.width-=m;const v=[];for(let t=e;t<=d;t++){const i=o[t];\"fixed\"==i.policy?z.height-=i.height:v.push(t)}if(z.height>0){const t=g(z.height/v.length);for(const i of v)c[i]=a(c[i],t)}const j=[];for(let t=f;t<=u;t++){const i=l[t];\"fixed\"==i.policy?z.width-=i.width:j.push(t)}if(z.width>0){const t=g(z.width/j.length);for(const i of j)p[i]=a(p[i],t)}}));return{size:this._measure_totals(c,p),row_heights:c,col_widths:p,size_hints:_}}_measure_grid(t){const{nrows:i,ncols:s,rows:e,cols:o,rspacing:n,cspacing:l}=this._state,r=this._measure_cells(((t,i)=>{const s=e[t],n=o[i];return{width:\"fixed\"==n.policy?n.width:1/0,height:\"fixed\"==s.policy?s.height:1/0}}));let h;h=\"fixed\"==this.sizing.height_policy&&null!=this.sizing.height?this.sizing.height:t.height!=1/0&&this.is_height_expanding()?t.height:r.size.height;let c,p=0;for(let t=0;t0)for(let t=0;ti?i:e,t--}}}c=\"fixed\"==this.sizing.width_policy&&null!=this.sizing.width?this.sizing.width:t.width!=1/0&&this.is_width_expanding()?t.width:r.size.width;let f=0;for(let t=0;t0)for(let t=0;ts?s:o,t--}}}const{row_heights:_,col_widths:d,size_hints:u}=this._measure_cells(((t,i)=>({width:r.col_widths[i],height:r.row_heights[t]})));return{size:this._measure_totals(_,d),row_heights:_,col_widths:d,size_hints:u}}_measure(t){const{size:i}=this._measure_grid(t);return i}_set_geometry(t,i){super._set_geometry(t,i);const{nrows:s,ncols:e,rspacing:o,cspacing:n}=this._state,{row_heights:l,col_widths:r,size_hints:c}=this._measure_grid(t),f=this._state.rows.map(((t,i)=>Object.assign(Object.assign({},t),{top:0,height:l[i],get bottom(){return this.top+this.height}}))),_=this._state.cols.map(((t,i)=>Object.assign(Object.assign({},t),{left:0,width:r[i],get right(){return this.left+this.width}}))),d=c.map(((t,i)=>Object.assign(Object.assign({},i),{outer:new h.BBox,inner:new h.BBox})));for(let i=0,e=this.absolute?t.top:0;i{const{layout:r,size_hint:c}=l,{sizing:a}=r,{width:p,height:d}=c,u=function(t,i){let s=(i-t)*n;for(let e=t;e<=i;e++)s+=_[e].width;return s}(i,e),w=function(t,i){let s=(i-t)*o;for(let e=t;e<=i;e++)s+=f[e].height;return s}(t,s),m=i==e&&\"auto\"!=_[i].align?_[i].align:a.halign,y=t==s&&\"auto\"!=f[t].align?f[t].align:a.valign;let x=_[i].left;\"start\"==m?x+=a.margin.left:\"center\"==m?x+=g((u-p)/2):\"end\"==m&&(x+=u-a.margin.right-p);let b=f[t].top;\"start\"==y?b+=a.margin.top:\"center\"==y?b+=g((w-d)/2):\"end\"==y&&(b+=w-a.margin.bottom-d),l.outer=new h.BBox({left:x,top:b,width:p,height:d})}));const u=f.map((()=>({start:new p((()=>0)),end:new p((()=>0))}))),w=_.map((()=>({start:new p((()=>0)),end:new p((()=>0))})));d.foreach((({r0:t,c0:i,r1:s,c1:e},{size_hint:o,outer:n})=>{const{inner:l}=o;null!=l&&(u[t].start.apply(n.top,(t=>a(t,l.top))),u[s].end.apply(f[s].bottom-n.bottom,(t=>a(t,l.bottom))),w[i].start.apply(n.left,(t=>a(t,l.left))),w[e].end.apply(_[e].right-n.right,(t=>a(t,l.right))))})),d.foreach((({r0:t,c0:i,r1:s,c1:e},o)=>{const{size_hint:n,outer:l}=o,r=t=>{const i=this.absolute?l:l.relative(),s=i.left+t.left,e=i.top+t.top,o=i.right-t.right,n=i.bottom-t.bottom;return new h.BBox({left:s,top:e,right:o,bottom:n})};if(null!=n.inner){let h=r(n.inner);if(!1!==n.align){const o=u[t].start.get(l.top),n=u[s].end.get(f[s].bottom-l.bottom),c=w[i].start.get(l.left),a=w[e].end.get(_[e].right-l.right);try{h=r({top:o,bottom:n,left:c,right:a})}catch(t){}}o.inner=h}else o.inner=l})),d.foreach(((t,{layout:i,outer:s,inner:e})=>{i.set_geometry(s,e)}))}}s.Grid=_,_.__name__=\"Grid\";class d extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:0,col:i}))),this.rows=\"fit\"}}s.Row=d,d.__name__=\"Row\";class u extends _{constructor(t){super(),this.items=t.map(((t,i)=>({layout:t,row:i,col:0}))),this.cols=\"fit\"}}s.Column=u,u.__name__=\"Column\"},\n", - " function _(e,t,s,n,i){n();const a=e(125),c=e(124),o=e(43);class r extends a.ContentLayoutable{constructor(e){super(),this.content_size=(0,o.unsized)(e,(()=>new c.Sizeable((0,o.size)(e))))}_content_size(){return this.content_size}}s.ContentBox=r,r.__name__=\"ContentBox\";class _ extends a.Layoutable{constructor(e){super(),this.el=e}_measure(e){const t=new c.Sizeable(e).bounded_to(this.sizing.size);return(0,o.sized)(this.el,t,(()=>{const e=new c.Sizeable((0,o.content_size)(this.el)),{border:t,padding:s}=(0,o.extents)(this.el);return e.grow_by(t).grow_by(s).map(Math.ceil)}))}}s.VariadicBox=_,_.__name__=\"VariadicBox\";class h extends _{constructor(e){super(e),this._cache=new Map}_measure(e){const{width:t,height:s}=e,n=`${t},${s}`;let i=this._cache.get(n);return null==i&&(i=super._measure(e),this._cache.set(n,i)),i}invalidate_cache(){this._cache.clear()}}s.CachedVariadicBox=h,h.__name__=\"CachedVariadicBox\"},\n", - " function _(t,e,i,h,o){h();const s=t(124),r=t(125),n=t(65);class g extends r.Layoutable{constructor(){super(...arguments),this.min_border={left:0,top:0,right:0,bottom:0},this.padding={left:0,top:0,right:0,bottom:0}}*[Symbol.iterator](){yield this.top_panel,yield this.bottom_panel,yield this.left_panel,yield this.right_panel,yield this.center_panel}_measure(t){t=new s.Sizeable({width:\"fixed\"==this.sizing.width_policy||t.width==1/0?this.sizing.width:t.width,height:\"fixed\"==this.sizing.height_policy||t.height==1/0?this.sizing.height:t.height});const e=this.left_panel.measure({width:0,height:t.height}),i=Math.max(e.width,this.min_border.left)+this.padding.left,h=this.right_panel.measure({width:0,height:t.height}),o=Math.max(h.width,this.min_border.right)+this.padding.right,r=this.top_panel.measure({width:t.width,height:0}),n=Math.max(r.height,this.min_border.top)+this.padding.top,g=this.bottom_panel.measure({width:t.width,height:0}),a=Math.max(g.height,this.min_border.bottom)+this.padding.bottom,d=new s.Sizeable(t).shrink_by({left:i,right:o,top:n,bottom:a}),l=this.center_panel.measure(d);return{width:i+l.width+o,height:n+l.height+a,inner:{left:i,right:o,top:n,bottom:a},align:(()=>{const{width_policy:t,height_policy:e}=this.center_panel.sizing;return\"fixed\"!=t&&\"fixed\"!=e})()}}_set_geometry(t,e){super._set_geometry(t,e),this.center_panel.set_geometry(e);const i=this.left_panel.measure({width:0,height:t.height}),h=this.right_panel.measure({width:0,height:t.height}),o=this.top_panel.measure({width:t.width,height:0}),s=this.bottom_panel.measure({width:t.width,height:0}),{left:r,top:g,right:a,bottom:d}=e;this.top_panel.set_geometry(new n.BBox({left:r,right:a,bottom:g,height:o.height})),this.bottom_panel.set_geometry(new n.BBox({left:r,right:a,top:d,height:s.height})),this.left_panel.set_geometry(new n.BBox({top:g,bottom:d,right:r,width:i.width})),this.right_panel.set_geometry(new n.BBox({top:g,bottom:d,left:a,width:h.width}))}}i.BorderLayout=g,g.__name__=\"BorderLayout\"},\n", - " function _(t,e,i,s,l){s();const n=t(1);var o;const a=t(119),_=t(10),d=t(20),h=t(120),r=t(123),u=(0,n.__importStar)(t(48));class c extends a.TextAnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new r.SideLayout(t,(()=>this.get_size()),!1):void 0}_get_size(){const{text:t}=this.model,e=new h.TextBox({text:t}),{angle:i,angle_units:s}=this.model;e.angle=(0,_.resolve_angle)(i,s),e.visuals=this.visuals.text.values();const{width:l,height:n}=e.size();return{width:l,height:n}}_render(){const{angle:t,angle_units:e}=this.model,i=(0,_.resolve_angle)(t,e),s=null!=this.layout?this.layout:this.plot_view.frame,l=this.coordinates.x_scale,n=this.coordinates.y_scale;let o=\"data\"==this.model.x_units?l.compute(this.model.x):s.bbox.xview.compute(this.model.x),a=\"data\"==this.model.y_units?n.compute(this.model.y):s.bbox.yview.compute(this.model.y);o+=this.model.x_offset,a-=this.model.y_offset;(\"canvas\"==this.model.render_mode?this._canvas_text.bind(this):this._css_text.bind(this))(this.layer.ctx,this.model.text,o,a,i)}}i.LabelView=c,c.__name__=\"LabelView\";class x extends a.TextAnnotation{constructor(t){super(t)}}i.Label=x,o=x,x.__name__=\"Label\",o.prototype.default_view=c,o.mixins([u.Text,[\"border_\",u.Line],[\"background_\",u.Fill]]),o.define((({Number:t,String:e,Angle:i})=>({x:[t],x_units:[d.SpatialUnits,\"data\"],y:[t],y_units:[d.SpatialUnits,\"data\"],text:[e,\"\"],angle:[i,0],angle_units:[d.AngleUnits,\"rad\"],x_offset:[t,0],y_offset:[t,0]}))),o.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,s,i,l){i();const o=t(1);var a;const r=t(69),n=(0,o.__importStar)(t(48)),d=t(20),_=t(43),c=t(120),h=(0,o.__importStar)(t(18)),u=t(11);class v extends r.DataAnnotationView{set_data(t){var e;if(super.set_data(t),null===(e=this.els)||void 0===e||e.forEach((t=>(0,_.remove)(t))),\"css\"==this.model.render_mode){const t=this.els=[...this.text].map((()=>(0,_.div)({style:{display:\"none\"}})));for(const e of t)this.plot_view.canvas_view.add_overlay(e)}else delete this.els}remove(){var t;null===(t=this.els)||void 0===t||t.forEach((t=>(0,_.remove)(t))),super.remove()}_rerender(){\"css\"==this.model.render_mode?this.render():this.request_render()}map_data(){const{x_scale:t,y_scale:e}=this.coordinates,s=null!=this.layout?this.layout:this.plot_view.frame;this.sx=\"data\"==this.model.x_units?t.v_compute(this._x):s.bbox.xview.v_compute(this._x),this.sy=\"data\"==this.model.y_units?e.v_compute(this._y):s.bbox.yview.v_compute(this._y)}paint(){const t=\"canvas\"==this.model.render_mode?this._v_canvas_text.bind(this):this._v_css_text.bind(this),{ctx:e}=this.layer;for(let s=0,i=this.text.length;s{switch(this.visuals.text.text_align.get(e)){case\"left\":return[\"left\",\"0%\"];case\"center\":return[\"center\",\"-50%\"];case\"right\":return[\"right\",\"-100%\"]}})(),[d,c]=(()=>{switch(this.visuals.text.text_baseline.get(e)){case\"top\":return[\"top\",\"0%\"];case\"middle\":return[\"center\",\"-50%\"];case\"bottom\":return[\"bottom\",\"-100%\"];default:return[\"center\",\"-50%\"]}})();let h=`translate(${n}, ${c})`;o&&(h+=`rotate(${o}rad)`),a.style.transformOrigin=`${r} ${d}`,a.style.transform=h,this.layout,this.visuals.background_fill.doit&&(this.visuals.background_fill.set_vectorize(t,e),a.style.backgroundColor=t.fillStyle),this.visuals.border_line.doit&&(this.visuals.border_line.set_vectorize(t,e),a.style.borderStyle=t.lineDash.length<2?\"solid\":\"dashed\",a.style.borderWidth=`${t.lineWidth}px`,a.style.borderColor=t.strokeStyle),(0,_.display)(a)}}s.LabelSetView=v,v.__name__=\"LabelSetView\";class x extends r.DataAnnotation{constructor(t){super(t)}}s.LabelSet=x,a=x,x.__name__=\"LabelSet\",a.prototype.default_view=v,a.mixins([n.TextVector,[\"border_\",n.LineVector],[\"background_\",n.FillVector]]),a.define((()=>({x:[h.XCoordinateSpec,{field:\"x\"}],y:[h.YCoordinateSpec,{field:\"y\"}],x_units:[d.SpatialUnits,\"data\"],y_units:[d.SpatialUnits,\"data\"],text:[h.StringSpec,{field:\"text\"}],angle:[h.AngleSpec,0],x_offset:[h.NumberSpec,{value:0}],y_offset:[h.NumberSpec,{value:0}],render_mode:[d.RenderMode,\"canvas\"]}))),a.override({background_fill_color:null,border_line_color:null})},\n", - " function _(t,e,i,l,s){l();const n=t(1);var o;const h=t(40),a=t(215),_=t(20),r=(0,n.__importStar)(t(48)),d=t(15),c=t(123),g=t(121),m=t(65),b=t(9),f=t(8),u=t(11);class x extends h.AnnotationView{update_layout(){const{panel:t}=this;this.layout=null!=t?new c.SideLayout(t,(()=>this.get_size())):void 0}cursor(t,e){return\"none\"==this.model.click_policy?null:\"pointer\"}get legend_padding(){return null!=this.model.border_line_color?this.model.padding:0}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.item_change,(()=>this.request_render()))}compute_legend_bbox(){const t=this.model.get_legend_names(),{glyph_height:e,glyph_width:i}=this.model,{label_height:l,label_width:s}=this.model;this.max_label_height=(0,b.max)([(0,g.font_metrics)(this.visuals.label_text.font_value()).height,l,e]);const{ctx:n}=this.layer;n.save(),this.visuals.label_text.set_value(n),this.text_widths=new Map;for(const e of t)this.text_widths.set(e,(0,b.max)([n.measureText(e).width,s]));this.visuals.title_text.set_value(n),this.title_height=this.model.title?(0,g.font_metrics)(this.visuals.title_text.font_value()).height+this.model.title_standoff:0,this.title_width=this.model.title?n.measureText(this.model.title).width:0,n.restore();const o=Math.max((0,b.max)([...this.text_widths.values()]),0),h=this.model.margin,{legend_padding:a}=this,_=this.model.spacing,{label_standoff:r}=this.model;let d,c;if(\"vertical\"==this.model.orientation)d=t.length*this.max_label_height+Math.max(t.length-1,0)*_+2*a+this.title_height,c=(0,b.max)([o+i+r+2*a,this.title_width+2*a]);else{let e=2*a+Math.max(t.length-1,0)*_;for(const[,t]of this.text_widths)e+=(0,b.max)([t,s])+i+r;c=(0,b.max)([this.title_width+2*a,e]),d=this.max_label_height+this.title_height+2*a}const x=null!=this.layout?this.layout:this.plot_view.frame,[p,w]=x.bbox.ranges,{location:v}=this.model;let y,k;if((0,f.isString)(v))switch(v){case\"top_left\":y=p.start+h,k=w.start+h;break;case\"top\":case\"top_center\":y=(p.end+p.start)/2-c/2,k=w.start+h;break;case\"top_right\":y=p.end-h-c,k=w.start+h;break;case\"bottom_right\":y=p.end-h-c,k=w.end-h-d;break;case\"bottom\":case\"bottom_center\":y=(p.end+p.start)/2-c/2,k=w.end-h-d;break;case\"bottom_left\":y=p.start+h,k=w.end-h-d;break;case\"left\":case\"center_left\":y=p.start+h,k=(w.end+w.start)/2-d/2;break;case\"center\":case\"center_center\":y=(p.end+p.start)/2-c/2,k=(w.end+w.start)/2-d/2;break;case\"right\":case\"center_right\":y=p.end-h-c,k=(w.end+w.start)/2-d/2}else if((0,f.isArray)(v)&&2==v.length){const[t,e]=v;y=x.bbox.xview.compute(t),k=x.bbox.yview.compute(e)-d}else(0,u.unreachable)();return new m.BBox({left:y,top:k,width:c,height:d})}interactive_bbox(){return this.compute_legend_bbox()}interactive_hit(t,e){return this.interactive_bbox().contains(t,e)}on_hit(t,e){let i;const{glyph_width:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=i=s;const a=this.compute_legend_bbox(),_=\"vertical\"==this.model.orientation;for(const r of this.model.items){const d=r.get_labels_list_from_label_prop();for(const c of d){const d=a.x+h,g=a.y+i+this.title_height;let b,f;[b,f]=_?[a.width-2*s,this.max_label_height]:[this.text_widths.get(c)+l+o,this.max_label_height];if(new m.BBox({left:d,top:g,width:b,height:f}).contains(t,e)){switch(this.model.click_policy){case\"hide\":for(const t of r.renderers)t.visible=!t.visible;break;case\"mute\":for(const t of r.renderers)t.muted=!t.muted}return!0}_?i+=this.max_label_height+n:h+=this.text_widths.get(c)+l+o+n}}return!1}_render(){if(0==this.model.items.length)return;if(!(0,b.some)(this.model.items,(t=>t.visible)))return;for(const t of this.model.items)t.legend=this.model;const{ctx:t}=this.layer,e=this.compute_legend_bbox();t.save(),this._draw_legend_box(t,e),this._draw_legend_items(t,e),this._draw_title(t,e),t.restore()}_draw_legend_box(t,e){t.beginPath(),t.rect(e.x,e.y,e.width,e.height),this.visuals.background_fill.apply(t),this.visuals.border_line.apply(t)}_draw_legend_items(t,e){const{glyph_width:i,glyph_height:l}=this.model,{legend_padding:s}=this,n=this.model.spacing,{label_standoff:o}=this.model;let h=s,a=s;const _=\"vertical\"==this.model.orientation;for(const r of this.model.items){if(!r.visible)continue;const d=r.get_labels_list_from_label_prop(),c=r.get_field_from_label_prop();if(0==d.length)continue;const g=(()=>{switch(this.model.click_policy){case\"none\":return!0;case\"hide\":return(0,b.every)(r.renderers,(t=>t.visible));case\"mute\":return(0,b.every)(r.renderers,(t=>!t.muted))}})();for(const m of d){const d=e.x+h,b=e.y+a+this.title_height,f=d+i,u=b+l;_?a+=this.max_label_height+n:h+=this.text_widths.get(m)+i+o+n,this.visuals.label_text.set_value(t),t.fillText(m,f+o,b+this.max_label_height/2);for(const e of r.renderers){const i=this.plot_view.renderer_view(e);null==i||i.draw_legend(t,d,f,b,u,c,m,r.index)}if(!g){let l,n;[l,n]=_?[e.width-2*s,this.max_label_height]:[this.text_widths.get(m)+i+o,this.max_label_height],t.beginPath(),t.rect(d,b,l,n),this.visuals.inactive_fill.set_value(t),t.fill()}}}}_draw_title(t,e){const{title:i}=this.model;i&&this.visuals.title_text.doit&&(t.save(),t.translate(e.x0,e.y0+this.title_height),this.visuals.title_text.set_value(t),t.fillText(i,this.legend_padding,this.legend_padding-this.model.title_standoff),t.restore())}_get_size(){const{width:t,height:e}=this.compute_legend_bbox();return{width:t+2*this.model.margin,height:e+2*this.model.margin}}}i.LegendView=x,x.__name__=\"LegendView\";class p extends h.Annotation{constructor(t){super(t)}initialize(){super.initialize(),this.item_change=new d.Signal0(this,\"item_change\")}get_legend_names(){const t=[];for(const e of this.items){const i=e.get_labels_list_from_label_prop();t.push(...i)}return t}}i.Legend=p,o=p,p.__name__=\"Legend\",o.prototype.default_view=x,o.mixins([[\"label_\",r.Text],[\"title_\",r.Text],[\"inactive_\",r.Fill],[\"border_\",r.Line],[\"background_\",r.Fill]]),o.define((({Number:t,String:e,Array:i,Tuple:l,Or:s,Ref:n,Nullable:o})=>({orientation:[_.Orientation,\"vertical\"],location:[s(_.LegendLocation,l(t,t)),\"top_right\"],title:[o(e),null],title_standoff:[t,5],label_standoff:[t,5],glyph_height:[t,20],glyph_width:[t,20],label_height:[t,20],label_width:[t,20],margin:[t,10],padding:[t,10],spacing:[t,3],items:[i(n(a.LegendItem)),[]],click_policy:[_.LegendClickPolicy,\"none\"]}))),o.override({border_line_color:\"#e5e5e5\",border_line_alpha:.5,border_line_width:1,background_fill_color:\"#ffffff\",background_fill_alpha:.95,inactive_fill_color:\"white\",inactive_fill_alpha:.7,label_text_font_size:\"13px\",label_text_baseline:\"middle\",title_text_font_size:\"13px\",title_text_font_style:\"italic\"})},\n", - " function _(e,r,l,n,t){n();const i=e(1);var s;const o=e(53),a=e(175),_=e(70),u=e(216),d=(0,i.__importStar)(e(18)),c=e(19),f=e(9);class h extends o.Model{constructor(e){super(e)}_check_data_sources_on_renderers(){if(null!=this.get_field_from_label_prop()){if(this.renderers.length<1)return!1;const e=this.renderers[0].data_source;if(null!=e)for(const r of this.renderers)if(r.data_source!=e)return!1}return!0}_check_field_label_on_data_source(){const e=this.get_field_from_label_prop();if(null!=e){if(this.renderers.length<1)return!1;const r=this.renderers[0].data_source;if(null!=r&&!(0,f.includes)(r.columns(),e))return!1}return!0}initialize(){super.initialize(),this.legend=null,this.connect(this.change,(()=>{var e;return null===(e=this.legend)||void 0===e?void 0:e.item_change.emit()}));this._check_data_sources_on_renderers()||c.logger.error(\"Non matching data sources on legend item renderers\");this._check_field_label_on_data_source()||c.logger.error(`Bad column name on label: ${this.label}`)}get_field_from_label_prop(){const{label:e}=this;return(0,u.isField)(e)?e.field:null}get_labels_list_from_label_prop(){if(!this.visible)return[];if((0,u.isValue)(this.label)){const{value:e}=this.label;return null!=e?[e]:[]}const e=this.get_field_from_label_prop();if(null!=e){let r;if(!this.renderers[0]||null==this.renderers[0].data_source)return[\"No source found\"];if(r=this.renderers[0].data_source,r instanceof _.ColumnarDataSource){const l=r.get_column(e);return null!=l?(0,f.uniq)(Array.from(l)):[\"Invalid field\"]}}return[]}}l.LegendItem=h,s=h,h.__name__=\"LegendItem\",s.define((({Boolean:e,Int:r,Array:l,Ref:n,Nullable:t})=>({label:[d.NullStringSpec,null],renderers:[l(n(a.GlyphRenderer)),[]],index:[t(r),null],visible:[e,!0]})))},\n", - " function _(i,n,e,t,u){t();const c=i(8);e.isValue=function(i){return(0,c.isPlainObject)(i)&&\"value\"in i},e.isField=function(i){return(0,c.isPlainObject)(i)&&\"field\"in i},e.isExpr=function(i){return(0,c.isPlainObject)(i)&&\"expr\"in i}},\n", - " function _(t,n,e,s,i){s();const o=t(1);var a;const l=t(40),c=(0,o.__importStar)(t(48)),r=t(20);class _ extends l.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{xs:t,ys:n}=this.model;if(t.length!=n.length)return;const e=t.length;if(e<3)return;const{frame:s}=this.plot_view,{ctx:i}=this.layer,o=this.coordinates.x_scale,a=this.coordinates.y_scale,{screen:l}=this.model;function c(t,n,e,s){return l?t:\"data\"==n?e.v_compute(t):s.v_compute(t)}const r=c(t,this.model.xs_units,o,s.bbox.xview),_=c(n,this.model.ys_units,a,s.bbox.yview);i.beginPath();for(let t=0;t({xs:[n(t),[]],xs_units:[r.SpatialUnits,\"data\"],ys:[n(t),[]],ys_units:[r.SpatialUnits,\"data\"]}))),a.internal((({Boolean:t})=>({screen:[t,!1]}))),a.override({fill_color:\"#fff9ba\",fill_alpha:.4,line_color:\"#cccccc\",line_alpha:.3})},\n", - " function _(e,t,n,o,i){o();const s=e(1);var l;const r=e(40),c=(0,s.__importStar)(e(48));class a extends r.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_render(){const{gradient:e,y_intercept:t}=this.model;if(null==e||null==t)return;const{frame:n}=this.plot_view,o=this.coordinates.x_scale,i=this.coordinates.y_scale;let s,l,r,c;if(0==e)s=i.compute(t),l=s,r=n.bbox.left,c=r+n.bbox.width;else{s=n.bbox.top,l=s+n.bbox.height;const a=(i.invert(s)-t)/e,_=(i.invert(l)-t)/e;r=o.compute(a),c=o.compute(_)}const{ctx:a}=this.layer;a.save(),a.beginPath(),this.visuals.line.set_value(a),a.moveTo(r,s),a.lineTo(c,l),a.stroke(),a.restore()}}n.SlopeView=a,a.__name__=\"SlopeView\";class _ extends r.Annotation{constructor(e){super(e)}}n.Slope=_,l=_,_.__name__=\"Slope\",l.prototype.default_view=a,l.mixins(c.Line),l.define((({Number:e,Nullable:t})=>({gradient:[t(e),null],y_intercept:[t(e),null]}))),l.override({line_color:\"black\"})},\n", - " function _(e,t,i,o,n){o();const s=e(1);var l;const a=e(40),r=(0,s.__importStar)(e(48)),c=e(20);class d extends a.AnnotationView{connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.plot_view.request_paint(this)))}_render(){const{location:e}=this.model;if(null==e)return;const{frame:t}=this.plot_view,i=this.coordinates.x_scale,o=this.coordinates.y_scale,n=(t,i)=>\"data\"==this.model.location_units?t.compute(e):this.model.for_hover?e:i.compute(e);let s,l,a,r;\"width\"==this.model.dimension?(a=n(o,t.bbox.yview),l=t.bbox.left,r=t.bbox.width,s=this.model.line_width):(a=t.bbox.top,l=n(i,t.bbox.xview),r=this.model.line_width,s=t.bbox.height);const{ctx:c}=this.layer;c.save(),c.beginPath(),this.visuals.line.set_value(c),c.moveTo(l,a),\"width\"==this.model.dimension?c.lineTo(l+r,a):c.lineTo(l,a+s),c.stroke(),c.restore()}}i.SpanView=d,d.__name__=\"SpanView\";class _ extends a.Annotation{constructor(e){super(e)}}i.Span=_,l=_,_.__name__=\"Span\",l.prototype.default_view=d,l.mixins(r.Line),l.define((({Number:e,Nullable:t})=>({render_mode:[c.RenderMode,\"canvas\"],location:[t(e),null],location_units:[c.SpatialUnits,\"data\"],dimension:[c.Dimension,\"width\"]}))),l.internal((({Boolean:e})=>({for_hover:[e,!1]}))),l.override({line_color:\"black\"})},\n", - " function _(i,e,t,o,l){var s;o();const a=i(40),_=i(221),n=i(113),r=i(43),h=i(123),b=i(65);class v extends a.AnnotationView{constructor(){super(...arguments),this._invalidate_toolbar=!0,this._previous_bbox=new b.BBox}update_layout(){this.layout=new h.SideLayout(this.panel,(()=>this.get_size()),!0)}initialize(){super.initialize(),this.el=(0,r.div)(),this.plot_view.canvas_view.add_event(this.el)}async lazy_initialize(){await super.lazy_initialize(),this._toolbar_view=await(0,n.build_view)(this.model.toolbar,{parent:this}),this.plot_view.visibility_callbacks.push((i=>this._toolbar_view.set_visibility(i)))}remove(){this._toolbar_view.remove(),(0,r.remove)(this.el),super.remove()}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{bbox:i}=this.layout;this._previous_bbox.equals(i)||((0,r.position)(this.el,i),this._previous_bbox=i,this._invalidate_toolbar=!0),this._invalidate_toolbar&&(this.el.style.position=\"absolute\",this.el.style.overflow=\"hidden\",(0,r.empty)(this.el),this.el.appendChild(this._toolbar_view.el),this._toolbar_view.layout.bbox=i,this._toolbar_view.render(),this._invalidate_toolbar=!1),(0,r.display)(this.el)}_get_size(){const{tools:i,logo:e}=this.model.toolbar;return{width:30*i.length+(null!=e?25:0)+15,height:30}}}t.ToolbarPanelView=v,v.__name__=\"ToolbarPanelView\";class d extends a.Annotation{constructor(i){super(i)}}t.ToolbarPanel=d,s=d,d.__name__=\"ToolbarPanel\",s.prototype.default_view=v,s.define((({Ref:i})=>({toolbar:[i(_.Toolbar)]})))},\n", - " function _(t,e,s,i,o){var c;i();const n=t(8),a=t(9),l=t(13),r=t(222),_=t(223),u=t(232),p=t(233);function v(t){switch(t){case\"tap\":return\"active_tap\";case\"pan\":return\"active_drag\";case\"pinch\":case\"scroll\":return\"active_scroll\";case\"multi\":return\"active_multi\"}return null}function h(t){return\"tap\"==t||\"pan\"==t}s.Drag=r.Tool,s.Inspection=r.Tool,s.Scroll=r.Tool,s.Tap=r.Tool;class f extends p.ToolbarBase{constructor(t){super(t)}connect_signals(){super.connect_signals();const{tools:t,active_drag:e,active_inspect:s,active_scroll:i,active_tap:o,active_multi:c}=this.properties;this.on_change([t,e,s,i,o,c],(()=>this._init_tools()))}_init_tools(){if(super._init_tools(),\"auto\"==this.active_inspect);else if(this.active_inspect instanceof u.InspectTool){let t=!1;for(const e of this.inspectors)e!=this.active_inspect?e.active=!1:t=!0;t||(this.active_inspect=null)}else if((0,n.isArray)(this.active_inspect)){const t=(0,a.intersection)(this.active_inspect,this.inspectors);t.length!=this.active_inspect.length&&(this.active_inspect=t);for(const t of this.inspectors)(0,a.includes)(this.active_inspect,t)||(t.active=!1)}else if(null==this.active_inspect)for(const t of this.inspectors)t.active=!1;const t=t=>{t.active?this._active_change(t):t.active=!0};for(const t of(0,l.values)(this.gestures)){t.tools=(0,a.sort_by)(t.tools,(t=>t.default_order));for(const e of t.tools)this.connect(e.properties.active.change,(()=>this._active_change(e)))}for(const[e,s]of(0,l.entries)(this.gestures)){const i=v(e);if(i){const o=this[i];\"auto\"==o?0!=s.tools.length&&h(e)&&t(s.tools[0]):null!=o&&((0,a.includes)(this.tools,o)?t(o):this[i]=null)}}}}s.Toolbar=f,c=f,f.__name__=\"Toolbar\",c.prototype.default_view=p.ToolbarBaseView,c.define((({Or:t,Ref:e,Auto:i,Null:o})=>({active_drag:[t(e(s.Drag),i,o),\"auto\"],active_inspect:[t(e(s.Inspection),i,o),\"auto\"],active_scroll:[t(e(s.Scroll),i,o),\"auto\"],active_tap:[t(e(s.Tap),i,o),\"auto\"],active_multi:[t(e(_.GestureTool),i,o),\"auto\"]})))},\n", - " function _(t,e,n,o,s){var i;o();const a=t(42),r=t(9),l=t(53);class c extends a.View{get plot_view(){return this.parent}get plot_model(){return this.parent.model}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>{this.model.active?this.activate():this.deactivate()}))}activate(){}deactivate(){}}n.ToolView=c,c.__name__=\"ToolView\";class _ extends l.Model{constructor(t){super(t)}get synthetic_renderers(){return[]}_get_dim_limits([t,e],[n,o],s,i){const a=s.bbox.h_range;let l;\"width\"==i||\"both\"==i?(l=[(0,r.min)([t,n]),(0,r.max)([t,n])],l=[(0,r.max)([l[0],a.start]),(0,r.min)([l[1],a.end])]):l=[a.start,a.end];const c=s.bbox.v_range;let _;return\"height\"==i||\"both\"==i?(_=[(0,r.min)([e,o]),(0,r.max)([e,o])],_=[(0,r.max)([_[0],c.start]),(0,r.min)([_[1],c.end])]):_=[c.start,c.end],[l,_]}static register_alias(t,e){this.prototype._known_aliases.set(t,e)}static from_string(t){const e=this.prototype._known_aliases.get(t);if(null!=e)return e();{const e=[...this.prototype._known_aliases.keys()];throw new Error(`unexpected tool name '${t}', possible tools are ${e.join(\", \")}`)}}}n.Tool=_,i=_,_.__name__=\"Tool\",i.prototype._known_aliases=new Map,i.define((({String:t,Nullable:e})=>({description:[e(t),null]}))),i.internal((({Boolean:t})=>({active:[t,!1]})))},\n", - " function _(e,o,t,s,n){s();const u=e(224),_=e(231);class l extends u.ButtonToolView{}t.GestureToolView=l,l.__name__=\"GestureToolView\";class i extends u.ButtonTool{constructor(e){super(e),this.button_view=_.OnOffButtonView}}t.GestureTool=i,i.__name__=\"GestureTool\"},\n", - " function _(t,e,o,s,i){s();const n=t(1);var l;const r=(0,n.__importDefault)(t(225)),a=t(226),u=t(222),h=t(43),_=t(34),d=t(8),c=t(9),m=(0,n.__importStar)(t(227)),p=m,v=(0,n.__importDefault)(t(228)),f=(0,n.__importDefault)(t(229)),g=t(230);class b extends a.DOMView{initialize(){super.initialize();const t=this.model.menu;if(null!=t){const e=this.parent.model.toolbar_location,o=\"left\"==e||\"above\"==e,s=this.parent.model.horizontal?\"vertical\":\"horizontal\";this._menu=new g.ContextMenu(o?(0,c.reversed)(t):t,{orientation:s,prevent_hide:t=>t.target==this.el})}this._hammer=new r.default(this.el,{touchAction:\"auto\",inputClass:r.default.TouchMouseInput}),this.connect(this.model.change,(()=>this.render())),this._hammer.on(\"tap\",(t=>{var e;(null===(e=this._menu)||void 0===e?void 0:e.is_open)?this._menu.hide():t.target==this.el&&this._clicked()})),this._hammer.on(\"press\",(()=>this._pressed())),this.el.addEventListener(\"keydown\",(t=>{t.keyCode==h.Keys.Enter&&this._clicked()}))}remove(){var t;this._hammer.destroy(),null===(t=this._menu)||void 0===t||t.remove(),super.remove()}styles(){return[...super.styles(),m.default,v.default,f.default]}css_classes(){return super.css_classes().concat(p.toolbar_button)}render(){(0,h.empty)(this.el);const t=this.model.computed_icon;(0,d.isString)(t)&&((0,_.startsWith)(t,\"data:image\")?this.el.style.backgroundImage=`url(\"${t}\")`:this.el.classList.add(t)),this.el.title=this.model.tooltip,this.el.tabIndex=0,null!=this._menu&&this.root.el.appendChild(this._menu.el)}_pressed(){var t;const e=(()=>{switch(this.parent.model.toolbar_location){case\"right\":return{left_of:this.el};case\"left\":return{right_of:this.el};case\"above\":return{below:this.el};case\"below\":return{above:this.el}}})();null===(t=this._menu)||void 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i,n,s,o,a=t.lastInterval||e,h=e.timeStamp-a.timeStamp;if(8!=e.eventType&&(h>25||a.velocity===r)){var c=e.deltaX-a.deltaX,l=e.deltaY-a.deltaY,p=U(h,c,l);n=p.x,s=p.y,i=u(p.x)>u(p.y)?p.x:p.y,o=V(c,l),t.lastInterval=e}else i=a.velocity,n=a.velocityX,s=a.velocityY,o=a.direction;e.velocity=i,e.velocityX=n,e.velocityY=s,e.direction=o}(i,e);var f,v;var d=t.element;_(e.srcEvent.target,d)&&(d=e.srcEvent.target);e.target=d}(t,i),t.emit(\"hammer.input\",i),t.recognize(i),t.session.prevInput=i}function H(t){for(var e=[],i=0;i=u(e)?t<0?2:4:e<0?8:16}function j(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return Math.sqrt(n*n+r*r)}function G(t,e,i){i||(i=F);var n=e[i[0]]-t[i[0]],r=e[i[1]]-t[i[1]];return 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pointercancel\";function it(){this.evEl=tt,this.evWin=et,q.apply(this,arguments),this.store=this.manager.session.pointerEvents=[]}t.MSPointerEvent&&!t.PointerEvent&&(tt=\"MSPointerDown\",et=\"MSPointerMove MSPointerUp MSPointerCancel\"),g(it,q,{handler:function(t){var e=this.store,i=!1,n=t.type.toLowerCase().replace(\"ms\",\"\"),r=K[n],s=Q[t.pointerType]||t.pointerType,o=s==N,a=b(e,t.pointerId,\"pointerId\");1&r&&(0===t.button||o)?a<0&&(e.push(t),a=e.length-1):12&r&&(i=!0),a<0||(e[a]=t,this.callback(this.manager,r,{pointers:e,changedPointers:[t],pointerType:s,srcEvent:t}),i&&e.splice(a,1))}});var nt={touchstart:1,touchmove:2,touchend:4,touchcancel:8},rt=\"touchstart\",st=\"touchstart touchmove touchend touchcancel\";function ot(){this.evTarget=rt,this.evWin=st,this.started=!1,q.apply(this,arguments)}function at(t,e){var i=P(t.touches),n=P(t.changedTouches);return 12&e&&(i=D(i.concat(n),\"identifier\",!0)),[i,n]}g(ot,q,{handler:function(t){var e=nt[t.type];if(1===e&&(this.started=!0),this.started){var i=at.call(this,t,e);12&e&&i[0].length-i[1].length==0&&(this.started=!1),this.callback(this.manager,e,{pointers:i[0],changedPointers:i[1],pointerType:N,srcEvent:t})}}});var ht={touchstart:1,touchmove:2,touchend:4,touchcancel:8},ut=\"touchstart touchmove touchend touchcancel\";function ct(){this.evTarget=ut,this.targetIds={},q.apply(this,arguments)}function lt(t,e){var i=P(t.touches),n=this.targetIds;if(3&e&&1===i.length)return n[i[0].identifier]=!0,[i,i];var r,s,o=P(t.changedTouches),a=[],h=this.target;if(s=i.filter((function(t){return _(t.target,h)})),1===e)for(r=0;r-1&&n.splice(t,1)}),2500)}}function dt(t){for(var e=t.srcEvent.clientX,i=t.srcEvent.clientY,n=0;n-1&&this.requireFail.splice(e,1),this},hasRequireFailures:function(){return this.requireFail.length>0},canRecognizeWith:function(t){return!!this.simultaneous[t.id]},emit:function(t){var e=this,i=this.state;function n(i){e.manager.emit(i,t)}i<8&&n(e.options.event+Dt(i)),n(e.options.event),t.additionalEvent&&n(t.additionalEvent),i>=8&&n(e.options.event+Dt(i))},tryEmit:function(t){if(this.canEmit())return this.emit(t);this.state=bt},canEmit:function(){for(var t=0;te.threshold&&r&e.direction},attrTest:function(t){return Ot.prototype.attrTest.call(this,t)&&(2&this.state||!(2&this.state)&&this.directionTest(t))},emit:function(t){this.pX=t.deltaX,this.pY=t.deltaY;var e=xt(t.direction);e&&(t.additionalEvent=this.options.event+e),this._super.emit.call(this,t)}}),g(Mt,Ot,{defaults:{event:\"pinch\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.scale-1)>this.options.threshold||2&this.state)},emit:function(t){if(1!==t.scale){var e=t.scale<1?\"in\":\"out\";t.additionalEvent=this.options.event+e}this._super.emit.call(this,t)}}),g(zt,Pt,{defaults:{event:\"press\",pointers:1,time:251,threshold:9},getTouchAction:function(){return[yt]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distancee.time;if(this._input=t,!n||!i||12&t.eventType&&!r)this.reset();else if(1&t.eventType)this.reset(),this._timer=l((function(){this.state=8,this.tryEmit()}),e.time,this);else if(4&t.eventType)return 8;return bt},reset:function(){clearTimeout(this._timer)},emit:function(t){8===this.state&&(t&&4&t.eventType?this.manager.emit(this.options.event+\"up\",t):(this._input.timeStamp=c(),this.manager.emit(this.options.event,this._input)))}}),g(Nt,Ot,{defaults:{event:\"rotate\",threshold:0,pointers:2},getTouchAction:function(){return[It]},attrTest:function(t){return this._super.attrTest.call(this,t)&&(Math.abs(t.rotation)>this.options.threshold||2&this.state)}}),g(Xt,Ot,{defaults:{event:\"swipe\",threshold:10,velocity:.3,direction:30,pointers:1},getTouchAction:function(){return Rt.prototype.getTouchAction.call(this)},attrTest:function(t){var e,i=this.options.direction;return 30&i?e=t.overallVelocity:6&i?e=t.overallVelocityX:i&Y&&(e=t.overallVelocityY),this._super.attrTest.call(this,t)&&i&t.offsetDirection&&t.distance>this.options.threshold&&t.maxPointers==this.options.pointers&&u(e)>this.options.velocity&&4&t.eventType},emit:function(t){var e=xt(t.offsetDirection);e&&this.manager.emit(this.options.event+e,t),this.manager.emit(this.options.event,t)}}),g(Yt,Pt,{defaults:{event:\"tap\",pointers:1,taps:1,interval:300,time:250,threshold:9,posThreshold:10},getTouchAction:function(){return[Et]},process:function(t){var e=this.options,i=t.pointers.length===e.pointers,n=t.distance .bk-divider{cursor:default;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-context-menu.bk-horizontal > .bk-divider{width:1px;margin:5px 0;}.bk-root .bk-context-menu.bk-vertical > .bk-divider{height:1px;margin:0 5px;}.bk-root .bk-context-menu > :not(.bk-divider){border:1px solid transparent;}.bk-root .bk-context-menu > :not(.bk-divider).bk-active{border-color:#26aae1;}.bk-root .bk-context-menu > :not(.bk-divider):hover{background-color:#f9f9f9;}.bk-root .bk-context-menu > :not(.bk-divider):focus,.bk-root .bk-context-menu > :not(.bk-divider):focus-visible{outline:1px dotted #26aae1;outline-offset:-1px;}.bk-root .bk-context-menu > :not(.bk-divider)::-moz-focus-inner{border:0;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):first-child{border-top-left-radius:4px;border-bottom-left-radius:4px;}.bk-root .bk-context-menu.bk-horizontal > :not(.bk-divider):last-child{border-top-right-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):first-child{border-top-left-radius:4px;border-top-right-radius:4px;}.bk-root .bk-context-menu.bk-vertical > :not(.bk-divider):last-child{border-bottom-left-radius:4px;border-bottom-right-radius:4px;}.bk-root .bk-menu{position:absolute;left:0;width:100%;z-index:100;cursor:pointer;font-size:12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;box-shadow:0 6px 12px rgba(0, 0, 0, 0.175);}.bk-root .bk-menu.bk-above{bottom:100%;}.bk-root .bk-menu.bk-below{top:100%;}.bk-root .bk-menu > .bk-divider{height:1px;margin:7.5px 0;overflow:hidden;background-color:#e5e5e5;}.bk-root .bk-menu > :not(.bk-divider){padding:6px 12px;}.bk-root .bk-menu > :not(.bk-divider):hover,.bk-root .bk-menu > :not(.bk-divider).bk-active{background-color:#e6e6e6;}.bk-root .bk-caret{display:inline-block;vertical-align:middle;width:0;height:0;margin:0 5px;}.bk-root .bk-caret.bk-down{border-top:4px solid;}.bk-root .bk-caret.bk-up{border-bottom:4px solid;}.bk-root .bk-caret.bk-down,.bk-root .bk-caret.bk-up{border-right:4px solid transparent;border-left:4px solid transparent;}.bk-root .bk-caret.bk-left{border-right:4px solid;}.bk-root .bk-caret.bk-right{border-left:4px solid;}.bk-root .bk-caret.bk-left,.bk-root .bk-caret.bk-right{border-top:4px solid transparent;border-bottom:4px solid transparent;}\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),l=t(43),h=t(9),r=(0,s.__importStar)(t(229));class d{constructor(t,e={}){var i,n;this.items=t,this.el=(0,l.div)(),this._open=!1,this._item_click=t=>{var e;null===(e=t.handler)||void 0===e||e.call(t),this.hide()},this._on_mousedown=t=>{var e;const{target:i}=t;i instanceof Node&&this.el.contains(i)||(null===(e=this.prevent_hide)||void 0===e?void 0:e.call(this,t))||this.hide()},this._on_keydown=t=>{t.keyCode==l.Keys.Esc&&this.hide()},this._on_blur=()=>{this.hide()},this.orientation=null!==(i=e.orientation)&&void 0!==i?i:\"vertical\",this.reversed=null!==(n=e.reversed)&&void 0!==n&&n,this.prevent_hide=e.prevent_hide,(0,l.undisplay)(this.el)}get is_open(){return this._open}get can_open(){return 0!=this.items.length}remove(){(0,l.remove)(this.el),this._unlisten()}_listen(){document.addEventListener(\"mousedown\",this._on_mousedown),document.addEventListener(\"keydown\",this._on_keydown),window.addEventListener(\"blur\",this._on_blur)}_unlisten(){document.removeEventListener(\"mousedown\",this._on_mousedown),document.removeEventListener(\"keydown\",this._on_keydown),window.removeEventListener(\"blur\",this._on_blur)}_position(t){const e=this.el.parentElement;if(null!=e){const i=(()=>{if(\"left_of\"in t){const{left:e,top:i}=t.left_of.getBoundingClientRect();return{right:e,top:i}}if(\"right_of\"in t){const{top:e,right:i}=t.right_of.getBoundingClientRect();return{left:i,top:e}}if(\"below\"in t){const{left:e,bottom:i}=t.below.getBoundingClientRect();return{left:e,top:i}}if(\"above\"in t){const{left:e,top:i}=t.above.getBoundingClientRect();return{left:e,bottom:i}}return t})(),n=e.getBoundingClientRect();this.el.style.left=null!=i.left?i.left-n.left+\"px\":\"\",this.el.style.top=null!=i.top?i.top-n.top+\"px\":\"\",this.el.style.right=null!=i.right?n.right-i.right+\"px\":\"\",this.el.style.bottom=null!=i.bottom?n.bottom-i.bottom+\"px\":\"\"}}render(){var t;(0,l.empty)(this.el,!0),(0,l.classes)(this.el).add(\"bk-context-menu\",`bk-${this.orientation}`);const e=this.reversed?(0,h.reversed)(this.items):this.items;for(const i of e){let e;if(null==i)e=(0,l.div)({class:r.divider});else{if(null!=i.if&&!i.if())continue;if(null!=i.content)e=i.content;else{const n=null!=i.icon?(0,l.div)({class:[\"bk-menu-icon\",i.icon]}):null,o=[(null===(t=i.active)||void 0===t?void 0:t.call(i))?\"bk-active\":null,i.class];e=(0,l.div)({class:o,title:i.tooltip,tabIndex:0},n,i.label,i.content),e.addEventListener(\"click\",(()=>{this._item_click(i)})),e.addEventListener(\"keydown\",(t=>{t.keyCode==l.Keys.Enter&&this._item_click(i)}))}}this.el.appendChild(e)}}show(t){if(0!=this.items.length&&!this._open){if(this.render(),0==this.el.children.length)return;this._position(null!=t?t:{left:0,top:0}),(0,l.display)(this.el),this._listen(),this._open=!0}}hide(){this._open&&(this._open=!1,this._unlisten(),(0,l.undisplay)(this.el))}toggle(t){this._open?this.hide():this.show(t)}}i.ContextMenu=d,d.__name__=\"ContextMenu\"},\n", - " function _(t,e,i,n,o){n();const s=t(1),c=t(224),l=(0,s.__importStar)(t(227)),a=t(43);class _ extends c.ButtonToolButtonView{render(){super.render(),(0,a.classes)(this.el).toggle(l.active,this.model.active)}_clicked(){const{active:t}=this.model;this.model.active=!t}}i.OnOffButtonView=_,_.__name__=\"OnOffButtonView\"},\n", - " function _(e,o,t,n,s){var c;n();const l=e(224),_=e(231);class i extends l.ButtonToolView{}t.InspectToolView=i,i.__name__=\"InspectToolView\";class a extends l.ButtonTool{constructor(e){super(e),this.event_type=\"move\"}}t.InspectTool=a,c=a,a.__name__=\"InspectTool\",c.prototype.button_view=_.OnOffButtonView,c.define((({Boolean:e})=>({toggleable:[e,!0]}))),c.override({active:!0})},\n", - " function _(t,o,e,l,i){l();const s=t(1);var n,a;const r=t(19),c=t(43),h=t(113),_=t(226),u=t(20),v=t(9),d=t(234),p=t(13),b=t(8),g=t(235),f=t(65),m=t(53),w=t(222),y=t(223),T=t(238),z=t(239),x=t(232),B=t(230),C=(0,s.__importStar)(t(227)),k=C,L=(0,s.__importStar)(t(240)),M=L;class S extends m.Model{constructor(t){super(t)}get visible(){var t;return!this.autohide||null!==(t=this._visible)&&void 0!==t&&t}}e.ToolbarViewModel=S,n=S,S.__name__=\"ToolbarViewModel\",n.define((({Boolean:t})=>({autohide:[t,!1]}))),n.internal((({Boolean:t,Nullable:o})=>({_visible:[o(t),null]})));class $ extends _.DOMView{constructor(){super(...arguments),this.layout={bbox:new f.BBox}}initialize(){super.initialize(),this._tool_button_views=new Map,this._toolbar_view_model=new S({autohide:this.model.autohide});const{toolbar_location:t}=this.model,o=\"left\"==t||\"above\"==t,e=this.model.horizontal?\"vertical\":\"horizontal\";this._overflow_menu=new B.ContextMenu([],{orientation:e,reversed:o})}async lazy_initialize(){await super.lazy_initialize(),await this._build_tool_button_views()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tools.change,(async()=>{await this._build_tool_button_views(),this.render()})),this.connect(this.model.properties.autohide.change,(()=>{this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change()})),this.connect(this._toolbar_view_model.properties._visible.change,(()=>this._on_visible_change()))}styles(){return[...super.styles(),C.default,L.default]}remove(){(0,h.remove_views)(this._tool_button_views),super.remove()}async _build_tool_button_views(){const t=null!=this.model._proxied_tools?this.model._proxied_tools:this.model.tools;await(0,h.build_views)(this._tool_button_views,t,{parent:this},(t=>t.button_view))}set_visibility(t){t!=this._toolbar_view_model._visible&&(this._toolbar_view_model._visible=t)}_on_visible_change(){const{visible:t}=this._toolbar_view_model;(0,c.classes)(this.el).toggle(k.toolbar_hidden,!t)}render(){(0,c.empty)(this.el),this.el.classList.add(k.toolbar),this.el.classList.add(k[this.model.toolbar_location]),this._toolbar_view_model.autohide=this.model.autohide,this._on_visible_change();const{horizontal:t}=this.model;let o=0;if(null!=this.model.logo){const e=\"grey\"===this.model.logo?M.grey:null,l=(0,c.a)({href:\"https://bokeh.org/\",target:\"_blank\",class:[M.logo,M.logo_small,e]});this.el.appendChild(l);const{width:i,height:s}=l.getBoundingClientRect();o+=t?i:s}for(const[,t]of this._tool_button_views)t.render();const e=[],l=t=>this._tool_button_views.get(t).el,{gestures:i}=this.model;for(const t of(0,p.values)(i))e.push(t.tools.map(l));e.push(this.model.actions.map(l)),e.push(this.model.inspectors.filter((t=>t.toggleable)).map(l));const s=e.filter((t=>0!=t.length)),n=()=>(0,c.div)({class:k.divider}),{bbox:a}=this.layout;let r=!1;this.root.el.appendChild(this._overflow_menu.el);const h=(0,c.div)({class:k.tool_overflow,tabIndex:0},t?\"\\u22ee\":\"\\u22ef\"),_=()=>{const t=(()=>{switch(this.model.toolbar_location){case\"right\":return{left_of:h};case\"left\":return{right_of:h};case\"above\":return{below:h};case\"below\":return{above:h}}})();this._overflow_menu.toggle(t)};h.addEventListener(\"click\",(()=>{_()})),h.addEventListener(\"keydown\",(t=>{t.keyCode==c.Keys.Enter&&_()}));for(const e of(0,d.join)(s,n))if(r)this._overflow_menu.items.push({content:e,class:t?k.right:k.above});else{this.el.appendChild(e);const{width:l,height:i}=e.getBoundingClientRect();if(o+=t?l:i,r=t?o>a.width-15:o>a.height-15,r){this.el.removeChild(e),this.el.appendChild(h);const{items:t}=this._overflow_menu;t.splice(0,t.length),t.push({content:e})}}}update_layout(){}update_position(){}after_layout(){this._has_finished=!0}export(t,o=!0){const e=\"png\"==t?\"canvas\":\"svg\",l=new g.CanvasLayer(e,o);return l.resize(0,0),l}}function V(){return{pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}}}e.ToolbarBaseView=$,$.__name__=\"ToolbarBaseView\";class A extends m.Model{constructor(t){super(t)}initialize(){super.initialize(),this._init_tools()}_init_tools(){const t=function(t,o){if(t.length!=o.length)return!0;const e=new Set(o.map((t=>t.id)));return(0,v.some)(t,(t=>!e.has(t.id)))},o=this.tools.filter((t=>t instanceof x.InspectTool));t(this.inspectors,o)&&(this.inspectors=o);const e=this.tools.filter((t=>t instanceof z.HelpTool));t(this.help,e)&&(this.help=e);const l=this.tools.filter((t=>t instanceof T.ActionTool));t(this.actions,l)&&(this.actions=l);const i=(t,o)=>{t in this.gestures||r.logger.warn(`Toolbar: unknown event type '${t}' for tool: ${o}`)},s={pan:{tools:[],active:null},scroll:{tools:[],active:null},pinch:{tools:[],active:null},tap:{tools:[],active:null},doubletap:{tools:[],active:null},press:{tools:[],active:null},pressup:{tools:[],active:null},rotate:{tools:[],active:null},move:{tools:[],active:null},multi:{tools:[],active:null}};for(const t of this.tools)if(t instanceof y.GestureTool&&t.event_type)if((0,b.isString)(t.event_type))s[t.event_type].tools.push(t),i(t.event_type,t);else{s.multi.tools.push(t);for(const o of t.event_type)i(o,t)}for(const o of Object.keys(s)){const e=this.gestures[o];t(e.tools,s[o].tools)&&(e.tools=s[o].tools),e.active&&(0,v.every)(e.tools,(t=>t.id!=e.active.id))&&(e.active=null)}}get horizontal(){return\"above\"===this.toolbar_location||\"below\"===this.toolbar_location}get vertical(){return\"left\"===this.toolbar_location||\"right\"===this.toolbar_location}_active_change(t){const{event_type:o}=t;if(null==o)return;const e=(0,b.isString)(o)?[o]:o;for(const o of e)if(t.active){const e=this.gestures[o].active;null!=e&&t!=e&&(r.logger.debug(`Toolbar: deactivating tool: ${e} for event type '${o}'`),e.active=!1),this.gestures[o].active=t,r.logger.debug(`Toolbar: activating tool: ${t} for event type '${o}'`)}else this.gestures[o].active=null}}e.ToolbarBase=A,a=A,A.__name__=\"ToolbarBase\",a.prototype.default_view=$,a.define((({Boolean:t,Array:o,Ref:e,Nullable:l})=>({tools:[o(e(w.Tool)),[]],logo:[l(u.Logo),\"normal\"],autohide:[t,!1]}))),a.internal((({Array:t,Struct:o,Ref:e,Nullable:l})=>{const i=o({tools:t(e(y.GestureTool)),active:l(e(w.Tool))});return{gestures:[o({pan:i,scroll:i,pinch:i,tap:i,doubletap:i,press:i,pressup:i,rotate:i,move:i,multi:i}),V],actions:[t(e(T.ActionTool)),[]],inspectors:[t(e(x.InspectTool)),[]],help:[t(e(z.HelpTool)),[]],toolbar_location:[u.Location,\"right\"]}}))},\n", - " function _(n,o,e,t,f){t();const r=n(9);function*i(n,o){const e=n.length;if(o>e)return;const t=(0,r.range)(o);for(yield t.map((o=>n[o]));;){let f;for(const n of(0,r.reversed)((0,r.range)(o)))if(t[n]!=n+e-o){f=n;break}if(null==f)return;t[f]+=1;for(const n of(0,r.range)(f+1,o))t[n]=t[n-1]+1;yield t.map((o=>n[o]))}}e.enumerate=function*(n){let o=0;for(const e of n)yield[e,o++]},e.join=function*(n,o){let 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.bk-logo-notebook{display:inline-block;vertical-align:middle;margin-right:5px;}\"},\n", - " function _(e,t,s,i,l){i();const o=e(1);var n;const a=e(40),h=e(20),r=e(43),c=(0,o.__importStar)(e(242)),d=c;class p extends a.AnnotationView{initialize(){super.initialize(),this.el=(0,r.div)({class:d.tooltip}),(0,r.undisplay)(this.el),this.plot_view.canvas_view.add_overlay(this.el)}remove(){(0,r.remove)(this.el),super.remove()}connect_signals(){super.connect_signals(),this.connect(this.model.properties.content.change,(()=>this.render())),this.connect(this.model.properties.position.change,(()=>this._reposition()))}styles(){return[...super.styles(),c.default]}render(){this.model.visible||(0,r.undisplay)(this.el),super.render()}_render(){const{content:e}=this.model;null!=e?((0,r.empty)(this.el),(0,r.classes)(this.el).toggle(\"bk-tooltip-custom\",this.model.custom),this.el.appendChild(e),this.model.show_arrow&&this.el.classList.add(d.tooltip_arrow)):(0,r.undisplay)(this.el)}_reposition(){const{position:e}=this.model;if(null==e)return void(0,r.undisplay)(this.el);const[t,s]=e,i=(()=>{const e=this.parent.layout.bbox.relative(),{attachment:i}=this.model;switch(i){case\"horizontal\":return t({attachment:[h.TooltipAttachment,\"horizontal\"],inner_only:[e,!0],show_arrow:[e,!0]}))),n.internal((({Boolean:e,Number:t,Tuple:s,Ref:i,Nullable:l})=>({position:[l(s(t,t)),null],content:[i(HTMLElement),()=>(0,r.div)()],custom:[e]}))),n.override({level:\"overlay\"})},\n", - " function _(o,t,r,e,l){e(),r.root=\"bk-root\",r.tooltip=\"bk-tooltip\",r.left=\"bk-left\",r.tooltip_arrow=\"bk-tooltip-arrow\",r.right=\"bk-right\",r.above=\"bk-above\",r.below=\"bk-below\",r.tooltip_row_label=\"bk-tooltip-row-label\",r.tooltip_row_value=\"bk-tooltip-row-value\",r.tooltip_color_block=\"bk-tooltip-color-block\",r.default='.bk-root{}.bk-root .bk-tooltip{font-weight:300;font-size:12px;position:absolute;padding:5px;border:1px solid #e5e5e5;color:#2f2f2f;background-color:white;pointer-events:none;opacity:0.95;z-index:100;}.bk-root .bk-tooltip > div:not(:first-child){margin-top:5px;border-top:#e5e5e5 1px dashed;}.bk-root .bk-tooltip.bk-left.bk-tooltip-arrow::before{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-left::before{left:-10px;border-right-width:10px;border-right-color:#909599;}.bk-root .bk-tooltip.bk-right.bk-tooltip-arrow::after{position:absolute;margin:-7px 0 0 0;top:50%;width:0;height:0;border-style:solid;border-width:7px 0 7px 0;border-color:transparent;content:\" \";display:block;right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-right::after{right:-10px;border-left-width:10px;border-left-color:#909599;}.bk-root .bk-tooltip.bk-above::before{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;top:-10px;border-bottom-width:10px;border-bottom-color:#909599;}.bk-root .bk-tooltip.bk-below::after{position:absolute;margin:0 0 0 -7px;left:50%;width:0;height:0;border-style:solid;border-width:0 7px 0 7px;border-color:transparent;content:\" \";display:block;bottom:-10px;border-top-width:10px;border-top-color:#909599;}.bk-root .bk-tooltip-row-label{text-align:right;color:#26aae1;}.bk-root .bk-tooltip-row-value{color:default;}.bk-root .bk-tooltip-color-block{width:12px;height:12px;margin-left:5px;margin-right:5px;outline:#dddddd solid 1px;display:inline-block;}'},\n", - " function _(e,t,s,i,r){var a;i();const l=e(115),_=e(112),h=e(113),o=e(48);class n extends l.UpperLowerView{async lazy_initialize(){await super.lazy_initialize();const{lower_head:e,upper_head:t}=this.model;null!=e&&(this.lower_head=await(0,h.build_view)(e,{parent:this})),null!=t&&(this.upper_head=await(0,h.build_view)(t,{parent:this}))}set_data(e){var t,s;super.set_data(e),null===(t=this.lower_head)||void 0===t||t.set_data(e),null===(s=this.upper_head)||void 0===s||s.set_data(e)}paint(e){if(this.visuals.line.doit)for(let t=0,s=this._lower_sx.length;t({lower_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})],upper_head:[t(e(_.ArrowHead)),()=>new _.TeeHead({size:10})]}))),a.override({level:\"underlay\"})},\n", - " function _(n,o,t,u,e){u(),e(\"CustomJS\",n(245).CustomJS),e(\"OpenURL\",n(247).OpenURL)},\n", - " function _(t,e,s,n,c){var a;n();const r=t(246),u=t(13),o=t(34);class i extends r.Callback{constructor(t){super(t)}get names(){return(0,u.keys)(this.args)}get values(){return(0,u.values)(this.args)}get func(){const t=(0,o.use_strict)(this.code);return new Function(...this.names,\"cb_obj\",\"cb_data\",t)}execute(t,e={}){return this.func.apply(t,this.values.concat(t,e))}}s.CustomJS=i,a=i,i.__name__=\"CustomJS\",a.define((({Unknown:t,String:e,Dict:s})=>({args:[s(t),{}],code:[e,\"\"]})))},\n", - " function _(c,a,l,n,s){n();const e=c(53);class o extends e.Model{constructor(c){super(c)}}l.Callback=o,o.__name__=\"Callback\"},\n", - " function _(e,t,n,o,i){var s;o();const c=e(246),r=e(152),a=e(8);class d extends c.Callback{constructor(e){super(e)}navigate(e){this.same_tab?window.location.href=e:window.open(e)}execute(e,{source:t}){const n=e=>{const n=(0,r.replace_placeholders)(this.url,t,e,void 0,void 0,encodeURI);if(!(0,a.isString)(n))throw new Error(\"HTML output is not supported in this context\");this.navigate(n)},{selected:o}=t;for(const e of o.indices)n(e);for(const e of o.line_indices)n(e)}}n.OpenURL=d,s=d,d.__name__=\"OpenURL\",s.define((({Boolean:e,String:t})=>({url:[t,\"http://\"],same_tab:[e,!1]})))},\n", - " function _(a,n,i,e,r){e(),r(\"Canvas\",a(249).Canvas),r(\"CartesianFrame\",a(126).CartesianFrame),r(\"CoordinateMapping\",a(54).CoordinateMapping)},\n", - " function _(e,t,i,s,a){var l,r=this&&this.__createBinding||(Object.create?function(e,t,i,s){void 0===s&&(s=i),Object.defineProperty(e,s,{enumerable:!0,get:function(){return t[i]}})}:function(e,t,i,s){void 0===s&&(s=i),e[s]=t[i]}),n=this&&this.__setModuleDefault||(Object.create?function(e,t){Object.defineProperty(e,\"default\",{enumerable:!0,value:t})}:function(e,t){e.default=t}),o=this&&this.__importStar||function(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var i in e)\"default\"!==i&&Object.prototype.hasOwnProperty.call(e,i)&&r(t,e,i);return n(t,e),t};s();const h=e(14),c=e(28),u=e(226),_=e(19),d=e(43),p=e(20),b=e(13),v=e(250),g=e(65),w=e(138),y=e(235);const f=(()=>{let t;return async()=>void 0!==t?t:t=await async function(){const t=document.createElement(\"canvas\"),i=t.getContext(\"webgl\",{premultipliedAlpha:!0});if(null!=i){const s=await(0,w.load_module)(Promise.resolve().then((()=>o(e(410)))));if(null!=s){const e=s.get_regl(i);if(e.has_webgl)return{canvas:t,regl_wrapper:e};_.logger.trace(\"WebGL is supported, but not the required extensions\")}else _.logger.trace(\"WebGL is supported, but bokehjs(.min).js bundle is not available\")}else _.logger.trace(\"WebGL is not supported\");return null}()})(),m={position:\"absolute\",top:\"0\",left:\"0\",width:\"100%\",height:\"100%\"};class x extends u.DOMView{constructor(){super(...arguments),this.bbox=new g.BBox,this.webgl=null}initialize(){super.initialize(),this.underlays_el=(0,d.div)({style:m}),this.primary=this.create_layer(),this.overlays=this.create_layer(),this.overlays_el=(0,d.div)({style:m}),this.events_el=(0,d.div)({class:\"bk-canvas-events\",style:m});const e=[this.underlays_el,this.primary.el,this.overlays.el,this.overlays_el,this.events_el];(0,b.extend)(this.el.style,m),(0,d.append)(this.el,...e),this.ui_event_bus=new v.UIEventBus(this)}async lazy_initialize(){if(await super.lazy_initialize(),\"webgl\"==this.model.output_backend&&(this.webgl=await f(),c.settings.force_webgl&&null==this.webgl))throw new Error(\"webgl is not available\")}remove(){this.ui_event_bus.destroy(),super.remove()}add_underlay(e){this.underlays_el.appendChild(e)}add_overlay(e){this.overlays_el.appendChild(e)}add_event(e){this.events_el.appendChild(e)}get pixel_ratio(){return this.primary.pixel_ratio}resize(e,t){this.bbox=new g.BBox({left:0,top:0,width:e,height:t}),this.primary.resize(e,t),this.overlays.resize(e,t)}prepare_webgl(e){const{webgl:t}=this;if(null!=t){const{width:i,height:s}=this.bbox;t.canvas.width=this.pixel_ratio*i,t.canvas.height=this.pixel_ratio*s;const[a,l,r,n]=e,{xview:o,yview:h}=this.bbox,c=o.compute(a),u=h.compute(l+n),_=this.pixel_ratio;t.regl_wrapper.set_scissor(_*c,_*u,_*r,_*n),this._clear_webgl()}}blit_webgl(e){const{webgl:t}=this;if(null!=t){if(_.logger.debug(\"Blitting WebGL canvas\"),e.restore(),e.drawImage(t.canvas,0,0),e.save(),this.model.hidpi){const t=this.pixel_ratio;e.scale(t,t),e.translate(.5,.5)}this._clear_webgl()}}_clear_webgl(){const{webgl:e}=this;if(null!=e){const{regl_wrapper:t,canvas:i}=e;t.clear(i.width,i.height)}}compose(){const e=this.create_layer(),{width:t,height:i}=this.bbox;return e.resize(t,i),e.ctx.drawImage(this.primary.canvas,0,0),e.ctx.drawImage(this.overlays.canvas,0,0),e}create_layer(){const{output_backend:e,hidpi:t}=this.model;return new y.CanvasLayer(e,t)}to_blob(){return this.compose().to_blob()}}i.CanvasView=x,x.__name__=\"CanvasView\";class z extends h.HasProps{constructor(e){super(e)}}i.Canvas=z,l=z,z.__name__=\"Canvas\",l.prototype.default_view=x,l.internal((({Boolean:e})=>({hidpi:[e,!0],output_backend:[p.OutputBackend,\"canvas\"]})))},\n", - " function _(t,e,s,n,i){n();const r=t(1),a=(0,r.__importDefault)(t(225)),_=t(15),h=t(19),o=t(43),l=(0,r.__importStar)(t(251)),c=t(252),p=t(9),u=t(8),v=t(27),d=t(230);class g{constructor(t){this.canvas_view=t,this.pan_start=new _.Signal(this,\"pan:start\"),this.pan=new _.Signal(this,\"pan\"),this.pan_end=new _.Signal(this,\"pan:end\"),this.pinch_start=new _.Signal(this,\"pinch:start\"),this.pinch=new _.Signal(this,\"pinch\"),this.pinch_end=new _.Signal(this,\"pinch:end\"),this.rotate_start=new _.Signal(this,\"rotate:start\"),this.rotate=new _.Signal(this,\"rotate\"),this.rotate_end=new _.Signal(this,\"rotate:end\"),this.tap=new _.Signal(this,\"tap\"),this.doubletap=new _.Signal(this,\"doubletap\"),this.press=new _.Signal(this,\"press\"),this.pressup=new _.Signal(this,\"pressup\"),this.move_enter=new _.Signal(this,\"move:enter\"),this.move=new _.Signal(this,\"move\"),this.move_exit=new _.Signal(this,\"move:exit\"),this.scroll=new _.Signal(this,\"scroll\"),this.keydown=new _.Signal(this,\"keydown\"),this.keyup=new _.Signal(this,\"keyup\"),this.hammer=new a.default(this.hit_area,{touchAction:\"auto\",inputClass:a.default.TouchMouseInput}),this._prev_move=null,this._curr_pan=null,this._curr_pinch=null,this._curr_rotate=null,this._configure_hammerjs(),this.hit_area.addEventListener(\"mousemove\",(t=>this._mouse_move(t))),this.hit_area.addEventListener(\"mouseenter\",(t=>this._mouse_enter(t))),this.hit_area.addEventListener(\"mouseleave\",(t=>this._mouse_exit(t))),this.hit_area.addEventListener(\"contextmenu\",(t=>this._context_menu(t))),this.hit_area.addEventListener(\"wheel\",(t=>this._mouse_wheel(t))),document.addEventListener(\"keydown\",this),document.addEventListener(\"keyup\",this),this.menu=new d.ContextMenu([],{prevent_hide:t=>2==t.button&&t.target==this.hit_area}),this.hit_area.appendChild(this.menu.el)}get hit_area(){return this.canvas_view.events_el}destroy(){this.menu.remove(),this.hammer.destroy(),document.removeEventListener(\"keydown\",this),document.removeEventListener(\"keyup\",this)}handleEvent(t){\"keydown\"==t.type?this._key_down(t):\"keyup\"==t.type&&this._key_up(t)}_configure_hammerjs(){this.hammer.get(\"doubletap\").recognizeWith(\"tap\"),this.hammer.get(\"tap\").requireFailure(\"doubletap\"),this.hammer.get(\"doubletap\").dropRequireFailure(\"tap\"),this.hammer.on(\"doubletap\",(t=>this._doubletap(t))),this.hammer.on(\"tap\",(t=>this._tap(t))),this.hammer.on(\"press\",(t=>this._press(t))),this.hammer.on(\"pressup\",(t=>this._pressup(t))),this.hammer.get(\"pan\").set({direction:a.default.DIRECTION_ALL}),this.hammer.on(\"panstart\",(t=>this._pan_start(t))),this.hammer.on(\"pan\",(t=>this._pan(t))),this.hammer.on(\"panend\",(t=>this._pan_end(t))),this.hammer.get(\"pinch\").set({enable:!0}),this.hammer.on(\"pinchstart\",(t=>this._pinch_start(t))),this.hammer.on(\"pinch\",(t=>this._pinch(t))),this.hammer.on(\"pinchend\",(t=>this._pinch_end(t))),this.hammer.get(\"rotate\").set({enable:!0}),this.hammer.on(\"rotatestart\",(t=>this._rotate_start(t))),this.hammer.on(\"rotate\",(t=>this._rotate(t))),this.hammer.on(\"rotateend\",(t=>this._rotate_end(t)))}register_tool(t){const e=t.model.event_type;null!=e&&((0,u.isString)(e)?this._register_tool(t,e):e.forEach(((e,s)=>this._register_tool(t,e,s<1))))}_register_tool(t,e,s=!0){const n=t,{id:i}=n.model,r=t=>e=>{e.id==i&&t(e.e)},a=t=>e=>{t(e.e)};switch(e){case\"pan\":null!=n._pan_start&&n.connect(this.pan_start,r(n._pan_start.bind(n))),null!=n._pan&&n.connect(this.pan,r(n._pan.bind(n))),null!=n._pan_end&&n.connect(this.pan_end,r(n._pan_end.bind(n)));break;case\"pinch\":null!=n._pinch_start&&n.connect(this.pinch_start,r(n._pinch_start.bind(n))),null!=n._pinch&&n.connect(this.pinch,r(n._pinch.bind(n))),null!=n._pinch_end&&n.connect(this.pinch_end,r(n._pinch_end.bind(n)));break;case\"rotate\":null!=n._rotate_start&&n.connect(this.rotate_start,r(n._rotate_start.bind(n))),null!=n._rotate&&n.connect(this.rotate,r(n._rotate.bind(n))),null!=n._rotate_end&&n.connect(this.rotate_end,r(n._rotate_end.bind(n)));break;case\"move\":null!=n._move_enter&&n.connect(this.move_enter,r(n._move_enter.bind(n))),null!=n._move&&n.connect(this.move,r(n._move.bind(n))),null!=n._move_exit&&n.connect(this.move_exit,r(n._move_exit.bind(n)));break;case\"tap\":null!=n._tap&&n.connect(this.tap,r(n._tap.bind(n))),null!=n._doubletap&&n.connect(this.doubletap,r(n._doubletap.bind(n)));break;case\"press\":null!=n._press&&n.connect(this.press,r(n._press.bind(n))),null!=n._pressup&&n.connect(this.pressup,r(n._pressup.bind(n)));break;case\"scroll\":null!=n._scroll&&n.connect(this.scroll,r(n._scroll.bind(n)));break;default:throw new Error(`unsupported event_type: ${e}`)}s&&(null!=n._keydown&&n.connect(this.keydown,a(n._keydown.bind(n))),null!=n._keyup&&n.connect(this.keyup,a(n._keyup.bind(n))),v.is_mobile&&null!=n._scroll&&\"pinch\"==e&&(h.logger.debug(\"Registering scroll on touch screen\"),n.connect(this.scroll,r(n._scroll.bind(n)))))}_hit_test_renderers(t,e,s){var n;const i=t.get_renderer_views();for(const t of(0,p.reversed)(i))if(null===(n=t.interactive_hit)||void 0===n?void 0:n.call(t,e,s))return t;return null}set_cursor(t=\"default\"){this.hit_area.style.cursor=t}_hit_test_frame(t,e,s){return t.frame.bbox.contains(e,s)}_hit_test_canvas(t,e,s){return t.layout.bbox.contains(e,s)}_hit_test_plot(t,e){for(const s of this.canvas_view.plot_views)if(s.layout.bbox.relative().contains(t,e))return s;return null}_trigger(t,e,s){var n;const{sx:i,sy:r}=e,a=this._hit_test_plot(i,r),_=t=>{const[s,n]=[i,r];return Object.assign(Object.assign({},e),{sx:s,sy:n})};if(\"panstart\"==e.type||\"pan\"==e.type||\"panend\"==e.type){let n;if(\"panstart\"==e.type&&null!=a?(this._curr_pan={plot_view:a},n=a):\"pan\"==e.type&&null!=this._curr_pan?n=this._curr_pan.plot_view:\"panend\"==e.type&&null!=this._curr_pan?(n=this._curr_pan.plot_view,this._curr_pan=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"pinchstart\"==e.type||\"pinch\"==e.type||\"pinchend\"==e.type){let n;if(\"pinchstart\"==e.type&&null!=a?(this._curr_pinch={plot_view:a},n=a):\"pinch\"==e.type&&null!=this._curr_pinch?n=this._curr_pinch.plot_view:\"pinchend\"==e.type&&null!=this._curr_pinch?(n=this._curr_pinch.plot_view,this._curr_pinch=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"rotatestart\"==e.type||\"rotate\"==e.type||\"rotateend\"==e.type){let n;if(\"rotatestart\"==e.type&&null!=a?(this._curr_rotate={plot_view:a},n=a):\"rotate\"==e.type&&null!=this._curr_rotate?n=this._curr_rotate.plot_view:\"rotateend\"==e.type&&null!=this._curr_rotate?(n=this._curr_rotate.plot_view,this._curr_rotate=null):n=null,null!=n){const e=_();this.__trigger(n,t,e,s)}}else if(\"mouseenter\"==e.type||\"mousemove\"==e.type||\"mouseleave\"==e.type){const h=null===(n=this._prev_move)||void 0===n?void 0:n.plot_view;if(null!=h&&(\"mouseleave\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(h,this.move_exit,{type:\"mouseleave\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&(\"mouseenter\"==e.type||h!=a)){const{sx:t,sy:e}=_();this.__trigger(a,this.move_enter,{type:\"mouseenter\",sx:t,sy:e,shiftKey:!1,ctrlKey:!1},s)}if(null!=a&&\"mousemove\"==e.type){const e=_();this.__trigger(a,t,e,s)}this._prev_move={sx:i,sy:r,plot_view:a}}else if(null!=a){const e=_();this.__trigger(a,t,e,s)}}__trigger(t,e,s,n){var i,r,a;const _=t.model.toolbar.gestures,h=e.name.split(\":\")[0],o=this._hit_test_renderers(t,s.sx,s.sy),l=this._hit_test_canvas(t,s.sx,s.sy);switch(h){case\"move\":{const n=_.move.active;null!=n&&this.trigger(e,s,n.id);const r=t.model.toolbar.inspectors.filter((t=>t.active));let a=\"default\";null!=o?(a=null!==(i=o.cursor(s.sx,s.sy))&&void 0!==i?i:a,(0,p.is_empty)(r)||(e=this.move_exit)):this._hit_test_frame(t,s.sx,s.sy)&&((0,p.is_empty)(r)||(a=\"crosshair\")),this.set_cursor(a),t.set_toolbar_visibility(l),r.map((t=>this.trigger(e,s,t.id)));break}case\"tap\":{const{target:i}=n;if(null!=i&&i!=this.hit_area)return;if(null===(r=null==o?void 0:o.on_hit)||void 0===r||r.call(o,s.sx,s.sy),this._hit_test_frame(t,s.sx,s.sy)){const t=_.tap.active;null!=t&&this.trigger(e,s,t.id)}break}case\"doubletap\":if(this._hit_test_frame(t,s.sx,s.sy)){const t=null!==(a=_.doubletap.active)&&void 0!==a?a:_.tap.active;null!=t&&this.trigger(e,s,t.id)}break;case\"scroll\":{const t=_[v.is_mobile?\"pinch\":\"scroll\"].active;null!=t&&(n.preventDefault(),n.stopPropagation(),this.trigger(e,s,t.id));break}case\"pan\":{const t=_.pan.active;null!=t&&(n.preventDefault(),this.trigger(e,s,t.id));break}default:{const t=_[h].active;null!=t&&this.trigger(e,s,t.id)}}this._trigger_bokeh_event(t,s)}trigger(t,e,s=null){t.emit({id:s,e})}_trigger_bokeh_event(t,e){const s=(()=>{const{sx:s,sy:n}=e,i=t.frame.x_scale.invert(s),r=t.frame.y_scale.invert(n);switch(e.type){case\"wheel\":return new l.MouseWheel(s,n,i,r,e.delta);case\"mousemove\":return new l.MouseMove(s,n,i,r);case\"mouseenter\":return new l.MouseEnter(s,n,i,r);case\"mouseleave\":return new l.MouseLeave(s,n,i,r);case\"tap\":return new l.Tap(s,n,i,r);case\"doubletap\":return new l.DoubleTap(s,n,i,r);case\"press\":return new l.Press(s,n,i,r);case\"pressup\":return new l.PressUp(s,n,i,r);case\"pan\":return new l.Pan(s,n,i,r,e.deltaX,e.deltaY);case\"panstart\":return new l.PanStart(s,n,i,r);case\"panend\":return new l.PanEnd(s,n,i,r);case\"pinch\":return new l.Pinch(s,n,i,r,e.scale);case\"pinchstart\":return new l.PinchStart(s,n,i,r);case\"pinchend\":return new l.PinchEnd(s,n,i,r);case\"rotate\":return new l.Rotate(s,n,i,r,e.rotation);case\"rotatestart\":return new l.RotateStart(s,n,i,r);case\"rotateend\":return new l.RotateEnd(s,n,i,r);default:return}})();null!=s&&t.model.trigger_event(s)}_get_sxy(t){const{pageX:e,pageY:s}=function(t){return\"undefined\"!=typeof TouchEvent&&t instanceof TouchEvent}(t)?(0!=t.touches.length?t.touches:t.changedTouches)[0]:t,{left:n,top:i}=(0,o.offset)(this.hit_area);return{sx:e-n,sy:s-i}}_pan_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{deltaX:t.deltaX,deltaY:t.deltaY,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_pinch_event(t){return Object.assign(Object.assign({type:t.type},this._get_sxy(t.srcEvent)),{scale:t.scale,shiftKey:t.srcEvent.shiftKey,ctrlKey:t.srcEvent.ctrlKey})}_rotate_event(t){return 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_=e(178),o=e(184),d=e(48),u=e(24),h=e(20),c=(0,n.__importStar)(e(18)),l=e(10),g=e(72),p=e(12);class x extends _.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,u.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,u.to_screen)(this.outer_radius),this.max_souter_radius=(0,p.max)(this.souter_radius)}_render(e,s,t){const{sx:i,sy:r,start_angle:n,end_angle:a,sinner_radius:_,souter_radius:o}=null!=t?t:this,d=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],u=r[t],h=_[t],c=o[t],l=n.get(t),g=a.get(t);if(!isFinite(s+u+h+c+l+g))continue;const p=g-l;e.translate(s,u),e.rotate(l),e.beginPath(),e.moveTo(c,0),e.arc(0,0,c,0,p,d),e.rotate(p),e.lineTo(h,0),e.arc(0,0,h,0,-p,!d),e.closePath(),e.rotate(-p-l),e.translate(-s,-u),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t)}}_hit_point(e){const{sx:s,sy:t}=e,i=this.renderer.xscale.invert(s),r=this.renderer.yscale.invert(t),n=s-this.max_souter_radius,a=s+this.max_souter_radius,[_,o]=this.renderer.xscale.r_invert(n,a),d=t-this.max_souter_radius,u=t+this.max_souter_radius,[h,c]=this.renderer.yscale.r_invert(d,u),p=[];for(const e of this.index.indices({x0:_,x1:o,y0:h,y1:c})){const s=this.souter_radius[e]**2,t=this.sinner_radius[e]**2,[n,a]=this.renderer.xscale.r_compute(i,this._x[e]),[_,o]=this.renderer.yscale.r_compute(r,this._y[e]),d=(n-a)**2+(_-o)**2;d<=s&&d>=t&&p.push(e)}const x=\"anticlock\"==this.model.direction,m=[];for(const e of p){const i=Math.atan2(t-this.sy[e],s-this.sx[e]);(0,l.angle_between)(-i,-this.start_angle.get(e),-this.end_angle.get(e),x)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,o.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=(this.sinner_radius[e]+this.souter_radius[e])/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.AnnularWedgeView=x,x.__name__=\"AnnularWedgeView\";class m extends _.XYGlyph{constructor(e){super(e)}}t.AnnularWedge=m,a=m,m.__name__=\"AnnularWedge\",a.prototype.default_view=x,a.mixins([d.LineVector,d.FillVector,d.HatchVector]),a.define((({})=>({direction:[h.Direction,\"anticlock\"],inner_radius:[c.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[c.DistanceSpec,{field:\"outer_radius\"}],start_angle:[c.AngleSpec,{field:\"start_angle\"}],end_angle:[c.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(s,e,i,r,t){r();const n=s(1);var a;const u=s(178),o=s(24),_=s(48),d=(0,n.__importStar)(s(18)),h=s(27),c=s(72);class l extends u.XYGlyphView{_map_data(){\"data\"==this.model.properties.inner_radius.units?this.sinner_radius=this.sdist(this.renderer.xscale,this._x,this.inner_radius):this.sinner_radius=(0,o.to_screen)(this.inner_radius),\"data\"==this.model.properties.outer_radius.units?this.souter_radius=this.sdist(this.renderer.xscale,this._x,this.outer_radius):this.souter_radius=(0,o.to_screen)(this.outer_radius)}_render(s,e,i){const{sx:r,sy:t,sinner_radius:n,souter_radius:a}=null!=i?i:this;for(const i of e){const e=r[i],u=t[i],o=n[i],_=a[i];if(isFinite(e+u+o+_)){if(s.beginPath(),h.is_ie)for(const i of[!1,!0])s.moveTo(e,u),s.arc(e,u,o,0,Math.PI,i),s.moveTo(e+_,u),s.arc(e,u,_,Math.PI,0,!i);else s.arc(e,u,o,0,2*Math.PI,!0),s.moveTo(e+_,u),s.arc(e,u,_,2*Math.PI,0,!1);this.visuals.fill.apply(s,i),this.visuals.hatch.apply(s,i),this.visuals.line.apply(s,i)}}}_hit_point(s){const{sx:e,sy:i}=s,r=this.renderer.xscale.invert(e),t=this.renderer.yscale.invert(i);let n,a,u,o;if(\"data\"==this.model.properties.outer_radius.units)n=r-this.max_outer_radius,u=r+this.max_outer_radius,a=t-this.max_outer_radius,o=t+this.max_outer_radius;else{const s=e-this.max_outer_radius,r=e+this.max_outer_radius;[n,u]=this.renderer.xscale.r_invert(s,r);const t=i-this.max_outer_radius,_=i+this.max_outer_radius;[a,o]=this.renderer.yscale.r_invert(t,_)}const _=[];for(const s of this.index.indices({x0:n,x1:u,y0:a,y1:o})){const e=this.souter_radius[s]**2,i=this.sinner_radius[s]**2,[n,a]=this.renderer.xscale.r_compute(r,this._x[s]),[u,o]=this.renderer.yscale.r_compute(t,this._y[s]),d=(n-a)**2+(u-o)**2;d<=e&&d>=i&&_.push(s)}return new c.Selection({indices:_})}draw_legend_for_index(s,{x0:e,y0:i,x1:r,y1:t},n){const a=n+1,u=new Array(a);u[n]=(e+r)/2;const o=new Array(a);o[n]=(i+t)/2;const _=.5*Math.min(Math.abs(r-e),Math.abs(t-i)),d=new Array(a);d[n]=.4*_;const h=new Array(a);h[n]=.8*_,this._render(s,[n],{sx:u,sy:o,sinner_radius:d,souter_radius:h})}}i.AnnulusView=l,l.__name__=\"AnnulusView\";class x extends u.XYGlyph{constructor(s){super(s)}}i.Annulus=x,a=x,x.__name__=\"Annulus\",a.prototype.default_view=l,a.mixins([_.LineVector,_.FillVector,_.HatchVector]),a.define((({})=>({inner_radius:[d.DistanceSpec,{field:\"inner_radius\"}],outer_radius:[d.DistanceSpec,{field:\"outer_radius\"}]})))},\n", - " function _(e,i,s,t,n){t();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),_=e(24),o=e(20),u=(0,r.__importStar)(e(18));class h extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,_.to_screen)(this.radius)}_render(e,i,s){if(this.visuals.line.doit){const{sx:t,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=s?s:this,d=\"anticlock\"==this.model.direction;for(const s of i){const i=t[s],l=n[s],_=r[s],o=a.get(s),u=c.get(s);isFinite(i+l+_+o+u)&&(e.beginPath(),e.arc(i,l,_,o,u,d),this.visuals.line.set_vectorize(e,s),e.stroke())}}}draw_legend_for_index(e,i,s){(0,d.generic_line_vector_legend)(this.visuals,e,i,s)}}s.ArcView=h,h.__name__=\"ArcView\";class g extends c.XYGlyph{constructor(e){super(e)}}s.Arc=g,a=g,g.__name__=\"Arc\",a.prototype.default_view=h,a.mixins(l.LineVector),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[u.DistanceSpec,{field:\"radius\"}],start_angle:[u.AngleSpec,{field:\"start_angle\"}],end_angle:[u.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(e,t,i,n,s){n();const o=e(1);var c;const r=e(48),a=e(179),_=e(184),d=e(78),l=(0,o.__importStar)(e(18));function x(e,t,i,n,s,o,c,r){const a=[],_=[[],[]];for(let _=0;_<=2;_++){let d,l,x;if(0===_?(l=6*e-12*i+6*s,d=-3*e+9*i-9*s+3*c,x=3*i-3*e):(l=6*t-12*n+6*o,d=-3*t+9*n-9*o+3*r,x=3*n-3*t),Math.abs(d)<1e-12){if(Math.abs(l)<1e-12)continue;const e=-x/l;0({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx0:[l.XCoordinateSpec,{field:\"cx0\"}],cy0:[l.YCoordinateSpec,{field:\"cy0\"}],cx1:[l.XCoordinateSpec,{field:\"cx1\"}],cy1:[l.YCoordinateSpec,{field:\"cy1\"}]}))),c.mixins(r.LineVector)},\n", - " function _(s,i,e,t,r){t();const a=s(1);var n;const h=s(178),d=s(48),l=s(24),_=s(20),c=(0,a.__importStar)(s(185)),u=(0,a.__importStar)(s(18)),o=s(9),x=s(12),m=s(72);class p extends h.XYGlyphView{async lazy_initialize(){await super.lazy_initialize();const{webgl:i}=this.renderer.plot_view.canvas_view;if(null!=i&&i.regl_wrapper.has_webgl){const{CircleGL:e}=await Promise.resolve().then((()=>(0,a.__importStar)(s(423))));this.glglyph=new e(i.regl_wrapper,this)}}get use_radius(){return!(this.radius.is_Scalar()&&isNaN(this.radius.value))}_set_data(s){super._set_data(s);const i=(()=>{if(this.use_radius)return 2*this.max_radius;{const{size:s}=this;return s.is_Scalar()?s.value:(0,x.max)(s.array)}})();this._configure(\"max_size\",{value:i})}_map_data(){if(this.use_radius)if(\"data\"==this.model.properties.radius.units)switch(this.model.radius_dimension){case\"x\":this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius);break;case\"y\":this.sradius=this.sdist(this.renderer.yscale,this._y,this.radius);break;case\"max\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.max(s,i[e])));break}case\"min\":{const s=this.sdist(this.renderer.xscale,this._x,this.radius),i=this.sdist(this.renderer.yscale,this._y,this.radius);this.sradius=(0,x.map)(s,((s,e)=>Math.min(s,i[e])));break}}else this.sradius=(0,l.to_screen)(this.radius);else{const s=l.ScreenArray.from(this.size);this.sradius=(0,x.map)(s,(s=>s/2))}}_mask_data(){const{frame:s}=this.renderer.plot_view,i=s.x_target,e=s.y_target;let t,r;return this.use_radius&&\"data\"==this.model.properties.radius.units?(t=i.map((s=>this.renderer.xscale.invert(s))).widen(this.max_radius),r=e.map((s=>this.renderer.yscale.invert(s))).widen(this.max_radius)):(t=i.widen(this.max_size).map((s=>this.renderer.xscale.invert(s))),r=e.widen(this.max_size).map((s=>this.renderer.yscale.invert(s)))),this.index.indices({x0:t.start,x1:t.end,y0:r.start,y1:r.end})}_render(s,i,e){const{sx:t,sy:r,sradius:a}=null!=e?e:this;for(const e of i){const i=t[e],n=r[e],h=a[e];isFinite(i+n+h)&&(s.beginPath(),s.arc(i,n,h,0,2*Math.PI,!1),this.visuals.fill.apply(s,e),this.visuals.hatch.apply(s,e),this.visuals.line.apply(s,e))}}_hit_point(s){const{sx:i,sy:e}=s,t=this.renderer.xscale.invert(i),r=this.renderer.yscale.invert(e),{hit_dilation:a}=this.model;let n,h,d,l;if(this.use_radius&&\"data\"==this.model.properties.radius.units)n=t-this.max_radius*a,h=t+this.max_radius*a,d=r-this.max_radius*a,l=r+this.max_radius*a;else{const s=i-this.max_size*a,t=i+this.max_size*a;[n,h]=this.renderer.xscale.r_invert(s,t);const r=e-this.max_size*a,_=e+this.max_size*a;[d,l]=this.renderer.yscale.r_invert(r,_)}const _=this.index.indices({x0:n,x1:h,y0:d,y1:l}),c=[];if(this.use_radius&&\"data\"==this.model.properties.radius.units)for(const s of _){const i=(this.sradius[s]*a)**2,[e,n]=this.renderer.xscale.r_compute(t,this._x[s]),[h,d]=this.renderer.yscale.r_compute(r,this._y[s]);(e-n)**2+(h-d)**2<=i&&c.push(s)}else for(const s of _){const t=(this.sradius[s]*a)**2;(this.sx[s]-i)**2+(this.sy[s]-e)**2<=t&&c.push(s)}return new m.Selection({indices:c})}_hit_span(s){const{sx:i,sy:e}=s,t=this.bounds();let r,a,n,h;if(\"h\"==s.direction){let s,e;if(n=t.y0,h=t.y1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=i-this.max_radius,e=i+this.max_radius,[r,a]=this.renderer.xscale.r_invert(s,e);else{const t=this.max_size/2;s=i-t,e=i+t,[r,a]=this.renderer.xscale.r_invert(s,e)}}else{let s,i;if(r=t.x0,a=t.x1,this.use_radius&&\"data\"==this.model.properties.radius.units)s=e-this.max_radius,i=e+this.max_radius,[n,h]=this.renderer.yscale.r_invert(s,i);else{const t=this.max_size/2;s=e-t,i=e+t,[n,h]=this.renderer.yscale.r_invert(s,i)}}const d=[...this.index.indices({x0:r,x1:a,y0:n,y1:h})];return new m.Selection({indices:d})}_hit_rect(s){const{sx0:i,sx1:e,sy0:t,sy1:r}=s,[a,n]=this.renderer.xscale.r_invert(i,e),[h,d]=this.renderer.yscale.r_invert(t,r),l=[...this.index.indices({x0:a,x1:n,y0:h,y1:d})];return new m.Selection({indices:l})}_hit_poly(s){const{sx:i,sy:e}=s,t=(0,o.range)(0,this.sx.length),r=[];for(let s=0,a=t.length;s({angle:[u.AngleSpec,0],size:[u.ScreenSizeSpec,{value:4}],radius:[u.NullDistanceSpec,null],radius_dimension:[_.RadiusDimension,\"x\"],hit_dilation:[s,1]})))},\n", - " function _(e,l,s,i,_){var p;i();const t=e(274);class a extends t.EllipseOvalView{}s.EllipseView=a,a.__name__=\"EllipseView\";class n extends t.EllipseOval{constructor(e){super(e)}}s.Ellipse=n,p=n,n.__name__=\"Ellipse\",p.prototype.default_view=a},\n", - " function _(t,s,e,i,h){i();const n=t(1),r=t(275),a=(0,n.__importStar)(t(185)),l=t(24),_=t(72),o=(0,n.__importStar)(t(18));class d extends r.CenterRotatableView{_map_data(){\"data\"==this.model.properties.width.units?this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"):this.sw=(0,l.to_screen)(this.width),\"data\"==this.model.properties.height.units?this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"):this.sh=(0,l.to_screen)(this.height)}_render(t,s,e){const{sx:i,sy:h,sw:n,sh:r,angle:a}=null!=e?e:this;for(const e of s){const s=i[e],l=h[e],_=n[e],o=r[e],d=a.get(e);isFinite(s+l+_+o+d)&&(t.beginPath(),t.ellipse(s,l,_/2,o/2,d,0,2*Math.PI),this.visuals.fill.apply(t,e),this.visuals.hatch.apply(t,e),this.visuals.line.apply(t,e))}}_hit_point(t){let s,e,i,h,n,r,l,o,d;const{sx:c,sy:p}=t,w=this.renderer.xscale.invert(c),x=this.renderer.yscale.invert(p);\"data\"==this.model.properties.width.units?(s=w-this.max_width,e=w+this.max_width):(r=c-this.max_width,l=c+this.max_width,[s,e]=this.renderer.xscale.r_invert(r,l)),\"data\"==this.model.properties.height.units?(i=x-this.max_height,h=x+this.max_height):(o=p-this.max_height,d=p+this.max_height,[i,h]=this.renderer.yscale.r_invert(o,d));const m=this.index.indices({x0:s,x1:e,y0:i,y1:h}),y=[];for(const t of m)n=a.point_in_ellipse(c,p,this.angle.get(t),this.sh[t]/2,this.sw[t]/2,this.sx[t],this.sy[t]),n&&y.push(t);return new _.Selection({indices:y})}draw_legend_for_index(t,{x0:s,y0:e,x1:i,y1:h},n){const r=n+1,a=new Array(r);a[n]=(s+i)/2;const l=new Array(r);l[n]=(e+h)/2;const _=this.sw[n]/this.sh[n],d=.8*Math.min(Math.abs(i-s),Math.abs(h-e)),c=new Array(r),p=new Array(r);_>1?(c[n]=d,p[n]=d/_):(c[n]=d*_,p[n]=d);const w=new o.UniformScalar(0,r);this._render(t,[n],{sx:a,sy:l,sw:c,sh:p,angle:w})}}e.EllipseOvalView=d,d.__name__=\"EllipseOvalView\";class c extends r.CenterRotatable{constructor(t){super(t)}}e.EllipseOval=c,c.__name__=\"EllipseOval\"},\n", - " function _(e,t,i,a,n){a();const s=e(1);var r;const h=e(178),o=e(48),_=(0,s.__importStar)(e(18));class c extends h.XYGlyphView{get max_w2(){return\"data\"==this.model.properties.width.units?this.max_width/2:0}get max_h2(){return\"data\"==this.model.properties.height.units?this.max_height/2:0}_bounds({x0:e,x1:t,y0:i,y1:a}){const{max_w2:n,max_h2:s}=this;return{x0:e-n,x1:t+n,y0:i-s,y1:a+s}}}i.CenterRotatableView=c,c.__name__=\"CenterRotatableView\";class l extends h.XYGlyph{constructor(e){super(e)}}i.CenterRotatable=l,r=l,l.__name__=\"CenterRotatable\",r.mixins([o.LineVector,o.FillVector,o.HatchVector]),r.define((({})=>({angle:[_.AngleSpec,0],width:[_.DistanceSpec,{field:\"width\"}],height:[_.DistanceSpec,{field:\"height\"}]})))},\n", - " function _(t,e,s,i,r){i();const h=t(1);var a;const n=t(277),_=t(24),o=(0,h.__importStar)(t(18));class l extends n.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:s}=await Promise.resolve().then((()=>(0,h.__importStar)(t(427))));this.glglyph=new s(e.regl_wrapper,this)}}scenterxy(t){return[(this.sleft[t]+this.sright[t])/2,this.sy[t]]}_lrtb(t){const e=this._left[t],s=this._right[t],i=this._y[t],r=this.height.get(t)/2;return[Math.min(e,s),Math.max(e,s),i+r,i-r]}_map_data(){this.sy=this.renderer.yscale.v_compute(this._y),this.sh=this.sdist(this.renderer.yscale,this._y,this.height,\"center\"),this.sleft=this.renderer.xscale.v_compute(this._left),this.sright=this.renderer.xscale.v_compute(this._right);const t=this.sy.length;this.stop=new _.ScreenArray(t),this.sbottom=new _.ScreenArray(t);for(let e=0;e({left:[o.XCoordinateSpec,{value:0}],y:[o.YCoordinateSpec,{field:\"y\"}],height:[o.NumberSpec,{value:1}],right:[o.XCoordinateSpec,{field:\"right\"}]})))},\n", - " function _(t,e,s,r,i){var n;r();const a=t(48),h=t(179),o=t(184),c=t(72);class _ extends h.GlyphView{get_anchor_point(t,e,s){const r=Math.min(this.sleft[e],this.sright[e]),i=Math.max(this.sright[e],this.sleft[e]),n=Math.min(this.stop[e],this.sbottom[e]),a=Math.max(this.sbottom[e],this.stop[e]);switch(t){case\"top_left\":return{x:r,y:n};case\"top\":case\"top_center\":return{x:(r+i)/2,y:n};case\"top_right\":return{x:i,y:n};case\"bottom_left\":return{x:r,y:a};case\"bottom\":case\"bottom_center\":return{x:(r+i)/2,y:a};case\"bottom_right\":return{x:i,y:a};case\"left\":case\"center_left\":return{x:r,y:(n+a)/2};case\"center\":case\"center_center\":return{x:(r+i)/2,y:(n+a)/2};case\"right\":case\"center_right\":return{x:i,y:(n+a)/2}}}_index_data(t){const{min:e,max:s}=Math,{data_size:r}=this;for(let i=0;i(0,n.__importStar)(e(425))));this.glglyph=new s(t.regl_wrapper,this)}}scenterxy(e){return[this.sx[e],this.sy[e]]}_set_data(){const{orientation:e,size:t,aspect_scale:s}=this.model,{q:i,r}=this,n=this.q.length;this._x=new Float64Array(n),this._y=new Float64Array(n);const{_x:a,_y:l}=this,o=Math.sqrt(3);if(\"pointytop\"==e)for(let e=0;e({r:[c.NumberSpec,{field:\"r\"}],q:[c.NumberSpec,{field:\"q\"}],scale:[c.NumberSpec,1],size:[e,1],aspect_scale:[e,1],orientation:[_.HexTileOrientation,\"pointytop\"]}))),a.override({line_color:null})},\n", - " function _(e,a,t,_,r){var n;_();const s=e(280),o=e(173),i=e(201);class p extends s.ImageBaseView{connect_signals(){super.connect_signals(),this.connect(this.model.color_mapper.change,(()=>this._update_image()))}_update_image(){null!=this.image_data&&(this._set_data(null),this.renderer.request_render())}_flat_img_to_buf8(e){return this.model.color_mapper.rgba_mapper.v_compute(e)}}t.ImageView=p,p.__name__=\"ImageView\";class m extends s.ImageBase{constructor(e){super(e)}}t.Image=m,n=m,m.__name__=\"Image\",n.prototype.default_view=p,n.define((({Ref:e})=>({color_mapper:[e(o.ColorMapper),()=>new i.LinearColorMapper({palette:[\"#000000\",\"#252525\",\"#525252\",\"#737373\",\"#969696\",\"#bdbdbd\",\"#d9d9d9\",\"#f0f0f0\",\"#ffffff\"]})]})))},\n", - " function _(e,t,i,s,a){s();const h=e(1);var n;const r=e(178),_=e(24),d=(0,h.__importStar)(e(18)),l=e(72),g=e(9),o=e(29),c=e(11);class m extends r.XYGlyphView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_render(e,t,i){const{image_data:s,sx:a,sy:h,sw:n,sh:r,global_alpha:_}=null!=i?i:this,d=e.getImageSmoothingEnabled();e.setImageSmoothingEnabled(!1);const l=_.is_Scalar();l&&(e.globalAlpha=_.value);for(const i of t){const t=s[i],_=a[i],d=h[i],g=n[i],o=r[i],c=this.global_alpha.get(i);if(null==t||!isFinite(_+d+g+o+c))continue;l||(e.globalAlpha=c);const m=d;e.translate(0,m),e.scale(1,-1),e.translate(0,-m),e.drawImage(t,0|_,0|d,g,o),e.translate(0,m),e.scale(1,-1),e.translate(0,-m)}e.setImageSmoothingEnabled(d)}_set_data(e){this._set_width_heigh_data();for(let t=0,i=this.image.length;t({image:[d.NDArraySpec,{field:\"image\"}],dw:[d.DistanceSpec,{field:\"dw\"}],dh:[d.DistanceSpec,{field:\"dh\"}],global_alpha:[d.NumberSpec,{value:1}],dilate:[e,!1]})))},\n", - " function _(e,a,t,r,_){var n;r();const s=e(280),m=e(8);class i extends s.ImageBaseView{_flat_img_to_buf8(e){let a;return a=(0,m.isArray)(e)?new Uint32Array(e):e,new Uint8ClampedArray(a.buffer)}}t.ImageRGBAView=i,i.__name__=\"ImageRGBAView\";class g extends s.ImageBase{constructor(e){super(e)}}t.ImageRGBA=g,n=g,g.__name__=\"ImageRGBA\",n.prototype.default_view=i},\n", - " function _(e,t,s,r,a){r();const i=e(1);var n;const o=e(178),c=e(24),_=e(20),h=(0,i.__importStar)(e(18)),l=e(12),d=e(136);class m extends o.XYGlyphView{constructor(){super(...arguments),this._images_rendered=!1,this._set_data_iteration=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.global_alpha.change,(()=>this.renderer.request_render()))}_index_data(e){const{data_size:t}=this;for(let s=0;s{this._set_data_iteration==r&&(this.image[a]=e,this.renderer.request_render())},attempts:t+1,timeout:s})}const a=\"data\"==this.model.properties.w.units,i=\"data\"==this.model.properties.h.units,n=this._x.length,o=new c.ScreenArray(a?2*n:n),_=new c.ScreenArray(i?2*n:n),{anchor:h}=this.model;function m(e,t){switch(h){case\"top_left\":case\"bottom_left\":case\"left\":case\"center_left\":return[e,e+t];case\"top\":case\"top_center\":case\"bottom\":case\"bottom_center\":case\"center\":case\"center_center\":return[e-t/2,e+t/2];case\"top_right\":case\"bottom_right\":case\"right\":case\"center_right\":return[e-t,e]}}function g(e,t){switch(h){case\"top_left\":case\"top\":case\"top_center\":case\"top_right\":return[e,e-t];case\"bottom_left\":case\"bottom\":case\"bottom_center\":case\"bottom_right\":return[e+t,e];case\"left\":case\"center_left\":case\"center\":case\"center_center\":case\"right\":case\"center_right\":return[e+t/2,e-t/2]}}if(a)for(let e=0;e({url:[h.StringSpec,{field:\"url\"}],anchor:[_.Anchor,\"top_left\"],global_alpha:[h.NumberSpec,{value:1}],angle:[h.AngleSpec,0],w:[h.NullDistanceSpec,null],h:[h.NullDistanceSpec,null],dilate:[e,!1],retry_attempts:[t,0],retry_timeout:[t,0]})))},\n", - " function _(e,t,s,i,n){i();const o=e(1);var r;const l=e(78),_=e(48),c=(0,o.__importStar)(e(185)),h=(0,o.__importStar)(e(18)),a=e(12),d=e(13),x=e(179),y=e(184),g=e(72);class p extends x.GlyphView{_project_data(){l.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s0&&o.set(e,s)}return new g.Selection({indices:[...o.keys()],multiline_indices:(0,d.to_object)(o)})}get_interpolation_hit(e,t,s){const i=this._xs.get(e),n=this._ys.get(e),o=i[t],r=n[t],l=i[t+1],_=n[t+1];return(0,y.line_interpolation)(this.renderer,s,o,r,l,_)}draw_legend_for_index(e,t,s){(0,y.generic_line_vector_legend)(this.visuals,e,t,s)}scenterxy(){throw new Error(`${this}.scenterxy() is not implemented`)}}s.MultiLineView=p,p.__name__=\"MultiLineView\";class u extends x.Glyph{constructor(e){super(e)}}s.MultiLine=u,r=u,u.__name__=\"MultiLine\",r.prototype.default_view=p,r.define((({})=>({xs:[h.XCoordinateSeqSpec,{field:\"xs\"}],ys:[h.YCoordinateSeqSpec,{field:\"ys\"}]}))),r.mixins(_.LineVector)},\n", - " function _(t,e,s,n,i){n();const o=t(1);var r;const l=t(181),h=t(179),a=t(184),_=t(12),c=t(12),d=t(48),x=(0,o.__importStar)(t(185)),y=(0,o.__importStar)(t(18)),f=t(72),g=t(11);class p extends h.GlyphView{_project_data(){}_index_data(t){const{min:e,max:s}=Math,{data_size:n}=this;for(let i=0;i1&&c.length>1)for(let s=1,n=i.length;s1){let r=!1;for(let t=1;t({xs:[y.XCoordinateSeqSeqSeqSpec,{field:\"xs\"}],ys:[y.YCoordinateSeqSeqSeqSpec,{field:\"ys\"}]}))),r.mixins([d.LineVector,d.FillVector,d.HatchVector])},\n", - " function _(a,e,l,s,_){var t;s();const i=a(274),n=a(12);class p extends i.EllipseOvalView{_map_data(){super._map_data(),(0,n.mul)(this.sw,.75)}}l.OvalView=p,p.__name__=\"OvalView\";class v extends i.EllipseOval{constructor(a){super(a)}}l.Oval=v,t=v,v.__name__=\"Oval\",t.prototype.default_view=p},\n", - " function _(e,t,s,i,n){i();const r=e(1);var a;const o=e(179),c=e(184),_=e(12),h=e(48),l=(0,r.__importStar)(e(185)),d=(0,r.__importStar)(e(18)),y=e(72),p=e(11),x=e(78);class f extends o.GlyphView{_project_data(){x.inplace.project_xy(this._xs.array,this._ys.array)}_index_data(e){const{data_size:t}=this;for(let s=0;s({xs:[d.XCoordinateSeqSpec,{field:\"xs\"}],ys:[d.YCoordinateSeqSpec,{field:\"ys\"}]}))),a.mixins([h.LineVector,h.FillVector,h.HatchVector])},\n", - " function _(t,e,i,o,r){o();const s=t(1);var a;const n=t(277),l=(0,s.__importStar)(t(18));class _ extends n.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:i}=await Promise.resolve().then((()=>(0,s.__importStar)(t(427))));this.glglyph=new i(e.regl_wrapper,this)}}scenterxy(t){return[this.sleft[t]/2+this.sright[t]/2,this.stop[t]/2+this.sbottom[t]/2]}_lrtb(t){return[this._left[t],this._right[t],this._top[t],this._bottom[t]]}}i.QuadView=_,_.__name__=\"QuadView\";class p extends n.Box{constructor(t){super(t)}}i.Quad=p,a=p,p.__name__=\"Quad\",a.prototype.default_view=_,a.define((({})=>({right:[l.XCoordinateSpec,{field:\"right\"}],bottom:[l.YCoordinateSpec,{field:\"bottom\"}],left:[l.XCoordinateSpec,{field:\"left\"}],top:[l.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,t,i,n,s){n();const c=e(1);var o;const r=e(48),a=e(78),_=e(179),d=e(184),l=(0,c.__importStar)(e(18));function x(e,t,i){if(t==(e+i)/2)return[e,i];{const n=(e-t)/(e-2*t+i),s=e*(1-n)**2+2*t*(1-n)*n+i*n**2;return[Math.min(e,i,s),Math.max(e,i,s)]}}class y extends _.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{_x0:t,_x1:i,_y0:n,_y1:s,_cx:c,_cy:o,data_size:r}=this;for(let a=0;a({x0:[l.XCoordinateSpec,{field:\"x0\"}],y0:[l.YCoordinateSpec,{field:\"y0\"}],x1:[l.XCoordinateSpec,{field:\"x1\"}],y1:[l.YCoordinateSpec,{field:\"y1\"}],cx:[l.XCoordinateSpec,{field:\"cx\"}],cy:[l.YCoordinateSpec,{field:\"cy\"}]}))),o.mixins(r.LineVector)},\n", - " function _(e,t,s,i,n){i();const l=e(1);var a;const r=e(178),o=e(184),h=e(48),_=e(24),c=(0,l.__importStar)(e(18));class g extends r.XYGlyphView{_map_data(){\"data\"==this.model.properties.length.units?this.slength=this.sdist(this.renderer.xscale,this._x,this.length):this.slength=(0,_.to_screen)(this.length);const{width:e,height:t}=this.renderer.plot_view.frame.bbox,s=2*(e+t),{slength:i}=this;for(let e=0,t=i.length;e({length:[c.DistanceSpec,0],angle:[c.AngleSpec,0]})))},\n", - " function _(t,e,s,i,r){var n,h=this&&this.__createBinding||(Object.create?function(t,e,s,i){void 0===i&&(i=s),Object.defineProperty(t,i,{enumerable:!0,get:function(){return e[s]}})}:function(t,e,s,i){void 0===i&&(i=s),t[i]=e[s]}),a=this&&this.__setModuleDefault||(Object.create?function(t,e){Object.defineProperty(t,\"default\",{enumerable:!0,value:e})}:function(t,e){t.default=e}),l=this&&this.__importStar||function(t){if(t&&t.__esModule)return t;var e={};if(null!=t)for(var s in t)\"default\"!==s&&Object.prototype.hasOwnProperty.call(t,s)&&h(e,t,s);return a(e,t),e};i();const o=t(275),c=t(184),_=t(24),d=t(12),f=t(72);class y extends o.CenterRotatableView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null==e?void 0:e.regl_wrapper.has_webgl){const{RectGL:s}=await Promise.resolve().then((()=>l(t(429))));this.glglyph=new s(e.regl_wrapper,this)}}_map_data(){if(\"data\"==this.model.properties.width.units)[this.sw,this.sx0]=this._map_dist_corner_for_data_side_length(this._x,this.width,this.renderer.xscale);else{this.sw=(0,_.to_screen)(this.width);const t=this.sx.length;this.sx0=new _.ScreenArray(t);for(let e=0;e({dilate:[t,!1]})))},\n", - " function _(e,t,r,a,s){a();const i=e(1);var n;const l=e(292),_=e(293),c=(0,i.__importStar)(e(18));class o extends l.MarkerView{async lazy_initialize(){await super.lazy_initialize();const{webgl:t}=this.renderer.plot_view.canvas_view;if(null!=t&&t.regl_wrapper.has_webgl){const{MultiMarkerGL:r}=await Promise.resolve().then((()=>(0,i.__importStar)(e(428))));this.glglyph=new r(t.regl_wrapper,this)}}_render(e,t,r){const{sx:a,sy:s,size:i,angle:n,marker:l}=null!=r?r:this;for(const r of t){const t=a[r],c=s[r],o=i.get(r),g=n.get(r),w=l.get(r);if(!isFinite(t+c+o+g)||null==w)continue;const p=o/2;e.beginPath(),e.translate(t,c),g&&e.rotate(g),_.marker_funcs[w](e,r,p,this.visuals),g&&e.rotate(-g),e.translate(-t,-c)}}draw_legend_for_index(e,{x0:t,x1:r,y0:a,y1:s},i){const n=i+1,l=this.marker.get(i),_=Object.assign(Object.assign({},this._get_legend_args({x0:t,x1:r,y0:a,y1:s},i)),{marker:new c.UniformScalar(l,n)});this._render(e,[i],_)}}r.ScatterView=o,o.__name__=\"ScatterView\";class g extends l.Marker{constructor(e){super(e)}}r.Scatter=g,n=g,g.__name__=\"Scatter\",n.prototype.default_view=o,n.define((()=>({marker:[c.MarkerSpec,{value:\"circle\"}]})))},\n", - " function _(e,t,s,n,i){n();const r=e(1);var a;const c=e(178),o=e(48),_=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),l=e(9),x=e(72);class d extends c.XYGlyphView{_render(e,t,s){const{sx:n,sy:i,size:r,angle:a}=null!=s?s:this;for(const s of t){const t=n[s],c=i[s],o=r.get(s),_=a.get(s);if(!isFinite(t+c+o+_))continue;const h=o/2;e.beginPath(),e.translate(t,c),_&&e.rotate(_),this._render_one(e,s,h,this.visuals),_&&e.rotate(-_),e.translate(-t,-c)}}_mask_data(){const{x_target:e,y_target:t}=this.renderer.plot_view.frame,s=e.widen(this.max_size).map((e=>this.renderer.xscale.invert(e))),n=t.widen(this.max_size).map((e=>this.renderer.yscale.invert(e)));return this.index.indices({x0:s.start,x1:s.end,y0:n.start,y1:n.end})}_hit_point(e){const{sx:t,sy:s}=e,{max_size:n}=this,{hit_dilation:i}=this.model,r=t-n*i,a=t+n*i,[c,o]=this.renderer.xscale.r_invert(r,a),_=s-n*i,h=s+n*i,[l,d]=this.renderer.yscale.r_invert(_,h),y=this.index.indices({x0:c,x1:o,y0:l,y1:d}),g=[];for(const e of y){const n=this.size.get(e)/2*i;Math.abs(this.sx[e]-t)<=n&&Math.abs(this.sy[e]-s)<=n&&g.push(e)}return new x.Selection({indices:g})}_hit_span(e){const{sx:t,sy:s}=e,n=this.bounds(),i=this.max_size/2;let r,a,c,o;if(\"h\"==e.direction){c=n.y0,o=n.y1;const e=t-i,s=t+i;[r,a]=this.renderer.xscale.r_invert(e,s)}else{r=n.x0,a=n.x1;const e=s-i,t=s+i;[c,o]=this.renderer.yscale.r_invert(e,t)}const _=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_rect(e){const{sx0:t,sx1:s,sy0:n,sy1:i}=e,[r,a]=this.renderer.xscale.r_invert(t,s),[c,o]=this.renderer.yscale.r_invert(n,i),_=[...this.index.indices({x0:r,x1:a,y0:c,y1:o})];return new x.Selection({indices:_})}_hit_poly(e){const{sx:t,sy:s}=e,n=(0,l.range)(0,this.sx.length),i=[];for(let e=0,r=n.length;e({size:[h.ScreenSizeSpec,{value:4}],angle:[h.AngleSpec,0],hit_dilation:[e,1]})))},\n", - " function _(l,o,n,t,i){t();const e=Math.sqrt(3),a=Math.sqrt(5),c=(a+1)/4,p=Math.sqrt((5-a)/8),r=(a-1)/4,h=Math.sqrt((5+a)/8);function u(l,o){l.rotate(Math.PI/4),s(l,o),l.rotate(-Math.PI/4)}function f(l,o){const n=o*e,t=n/3;l.moveTo(-n/2,-t),l.lineTo(0,0),l.lineTo(n/2,-t),l.lineTo(0,0),l.lineTo(0,o)}function s(l,o){l.moveTo(0,o),l.lineTo(0,-o),l.moveTo(-o,0),l.lineTo(o,0)}function T(l,o){l.moveTo(0,o),l.lineTo(o/1.5,0),l.lineTo(0,-o),l.lineTo(-o/1.5,0),l.closePath()}function y(l,o){const n=o*e,t=n/3;l.moveTo(-o,t),l.lineTo(o,t),l.lineTo(0,t-n),l.closePath()}function v(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function d(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function _(l,o,n,t){!function(l,o){l.beginPath(),l.arc(0,0,o/4,0,2*Math.PI,!1),l.closePath()}(l,n),t.line.set_vectorize(l,o),l.fillStyle=l.strokeStyle,l.fill()}function P(l,o,n,t){!function(l,o){const n=o/2,t=e*n;l.moveTo(o,0),l.lineTo(n,-t),l.lineTo(-n,-t),l.lineTo(-o,0),l.lineTo(-n,t),l.lineTo(n,t),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function m(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function q(l,o,n,t){!function(l,o){const n=Math.sqrt(5-2*a)*o;l.moveTo(0,-o),l.lineTo(n*r,n*h-o),l.lineTo(n*(1+r),n*h-o),l.lineTo(n*(1+r-c),n*(h+p)-o),l.lineTo(n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(0,2*n*h-o),l.lineTo(-n*(1+2*r-c),n*(2*h+p)-o),l.lineTo(-n*(1+r-c),n*(h+p)-o),l.lineTo(-n*(1+r),n*h-o),l.lineTo(-n*r,n*h-o),l.closePath()}(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}function M(l,o,n,t){y(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)}n.marker_funcs={asterisk:function(l,o,n,t){s(l,n),u(l,n),t.line.apply(l,o)},circle:v,circle_cross:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},circle_dot:function(l,o,n,t){v(l,o,n,t),_(l,o,n,t)},circle_y:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),f(l,n),l.stroke())},circle_x:function(l,o,n,t){l.arc(0,0,n,0,2*Math.PI,!1),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),u(l,n),l.stroke())},cross:function(l,o,n,t){s(l,n),t.line.apply(l,o)},diamond:d,diamond_dot:function(l,o,n,t){d(l,o,n,t),_(l,o,n,t)},diamond_cross:function(l,o,n,t){T(l,n),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(0,n),l.lineTo(0,-n),l.moveTo(-n/1.5,0),l.lineTo(n/1.5,0),l.stroke())},dot:_,hex:P,hex_dot:function(l,o,n,t){P(l,o,n,t),_(l,o,n,t)},inverted_triangle:function(l,o,n,t){l.rotate(Math.PI),y(l,n),l.rotate(-Math.PI),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},plus:function(l,o,n,t){const i=3*n/8,e=[i,i,n,n,i,i,-i,-i,-n,-n,-i,-i],a=[n,i,i,-i,-i,-n,-n,-i,-i,i,i,n];l.beginPath();for(let o=0;o<12;o++)l.lineTo(e[o],a[o]);l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square:m,square_cross:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),s(l,n),l.stroke())},square_dot:function(l,o,n,t){m(l,o,n,t),_(l,o,n,t)},square_pin:function(l,o,n,t){const i=3*n/8;l.moveTo(-n,-n),l.quadraticCurveTo(0,-i,n,-n),l.quadraticCurveTo(i,0,n,n),l.quadraticCurveTo(0,i,-n,n),l.quadraticCurveTo(-i,0,-n,-n),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},square_x:function(l,o,n,t){const i=2*n;l.rect(-n,-n,i,i),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.doit&&(t.line.set_vectorize(l,o),l.moveTo(-n,n),l.lineTo(n,-n),l.moveTo(-n,-n),l.lineTo(n,n),l.stroke())},star:q,star_dot:function(l,o,n,t){q(l,o,n,t),_(l,o,n,t)},triangle:M,triangle_dot:function(l,o,n,t){M(l,o,n,t),_(l,o,n,t)},triangle_pin:function(l,o,n,t){const i=n*e,a=i/3,c=3*a/8;l.moveTo(-n,a),l.quadraticCurveTo(0,c,n,a),l.quadraticCurveTo(e*c/2,c/2,0,a-i),l.quadraticCurveTo(-e*c/2,c/2,-n,a),l.closePath(),t.fill.apply(l,o),t.hatch.apply(l,o),t.line.apply(l,o)},dash:function(l,o,n,t){!function(l,o){l.moveTo(-o,0),l.lineTo(o,0)}(l,n),t.line.apply(l,o)},x:function(l,o,n,t){u(l,n),t.line.apply(l,o)},y:function(l,o,n,t){f(l,n),t.line.apply(l,o)}}},\n", - " function _(e,t,s,i,n){i();const r=e(1);var o;const _=(0,r.__importStar)(e(185)),h=(0,r.__importStar)(e(18)),c=e(48),a=e(78),d=e(179),x=e(184),l=e(72);class y extends d.GlyphView{_project_data(){a.inplace.project_xy(this._x0,this._y0),a.inplace.project_xy(this._x1,this._y1)}_index_data(e){const{min:t,max:s}=Math,{_x0:i,_x1:n,_y0:r,_y1:o,data_size:_}=this;for(let h=0;h<_;h++){const _=i[h],c=n[h],a=r[h],d=o[h];e.add_rect(t(_,c),t(a,d),s(_,c),s(a,d))}}_render(e,t,s){if(this.visuals.line.doit){const{sx0:i,sy0:n,sx1:r,sy1:o}=null!=s?s:this;for(const s of t){const t=i[s],_=n[s],h=r[s],c=o[s];isFinite(t+_+h+c)&&(e.beginPath(),e.moveTo(t,_),e.lineTo(h,c),this.visuals.line.set_vectorize(e,s),e.stroke())}}}_hit_point(e){const{sx:t,sy:s}=e,i={x:t,y:s},[n,r]=this.renderer.xscale.r_invert(t-2,t+2),[o,h]=this.renderer.yscale.r_invert(s-2,s+2),c=this.index.indices({x0:n,y0:o,x1:r,y1:h}),a=[];for(const e of c){const t=Math.max(2,this.line_width.get(e)/2)**2,s={x:this.sx0[e],y:this.sy0[e]},n={x:this.sx1[e],y:this.sy1[e]};_.dist_to_segment_squared(i,s,n)({x0:[h.XCoordinateSpec,{field:\"x0\"}],y0:[h.YCoordinateSpec,{field:\"y0\"}],x1:[h.XCoordinateSpec,{field:\"x1\"}],y1:[h.YCoordinateSpec,{field:\"y1\"}]}))),o.mixins(c.LineVector)},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const l=t(178),a=(0,o.__importStar)(t(48)),c=t(296);class r extends l.XYGlyphView{_set_data(){const{tension:t,closed:e}=this.model;[this._xt,this._yt]=(0,c.catmullrom_spline)(this._x,this._y,20,t,e)}_map_data(){const{x_scale:t,y_scale:e}=this.renderer.coordinates;this.sxt=t.v_compute(this._xt),this.syt=e.v_compute(this._yt)}_render(t,e,s){const{sxt:i,syt:n}=null!=s?s:this;let o=!0;t.beginPath();const _=i.length;for(let e=0;e<_;e++){const s=i[e],_=n[e];isFinite(s+_)?o?(t.moveTo(s,_),o=!1):t.lineTo(s,_):o=!0}this.visuals.line.set_value(t),t.stroke()}}s.SplineView=r,r.__name__=\"SplineView\";class h extends l.XYGlyph{constructor(t){super(t)}}s.Spline=h,_=h,h.__name__=\"Spline\",_.prototype.default_view=r,_.mixins(a.LineScalar),_.define((({Boolean:t,Number:e})=>({tension:[e,.5],closed:[t,!1]})))},\n", - " function _(n,t,e,o,s){o();const c=n(24),l=n(11);e.catmullrom_spline=function(n,t,e=10,o=.5,s=!1){(0,l.assert)(n.length==t.length);const r=n.length,f=s?r+1:r,w=(0,c.infer_type)(n,t),i=new w(f+2),u=new w(f+2);i.set(n,1),u.set(t,1),s?(i[0]=n[r-1],u[0]=t[r-1],i[f]=n[0],u[f]=t[0],i[f+1]=n[1],u[f+1]=t[1]):(i[0]=n[0],u[0]=t[0],i[f+1]=n[r-1],u[f+1]=t[r-1]);const g=new w(4*(e+1));for(let n=0,t=0;n<=e;n++){const o=n/e,s=o**2,c=o*s;g[t++]=2*c-3*s+1,g[t++]=-2*c+3*s,g[t++]=c-2*s+o,g[t++]=c-s}const h=new w((f-1)*(e+1)),_=new w((f-1)*(e+1));for(let n=1,t=0;n1&&(e.stroke(),o=!1)}o?(e.lineTo(t,r),e.lineTo(a,c)):(e.beginPath(),e.moveTo(s[n],i[n]),o=!0),l=n}e.lineTo(s[a-1],i[a-1]),e.stroke()}}draw_legend_for_index(e,t,n){(0,r.generic_line_scalar_legend)(this.visuals,e,t)}}n.StepView=f,f.__name__=\"StepView\";class u extends a.XYGlyph{constructor(e){super(e)}}n.Step=u,l=u,u.__name__=\"Step\",l.prototype.default_view=f,l.mixins(c.LineScalar),l.define((()=>({mode:[_.StepMode,\"before\"]})))},\n", - " function _(t,e,s,i,n){i();const o=t(1);var _;const h=t(178),l=t(48),r=(0,o.__importStar)(t(185)),a=(0,o.__importStar)(t(18)),c=t(121),x=t(11),u=t(72);class f extends h.XYGlyphView{_rotate_point(t,e,s,i,n){return[(t-s)*Math.cos(n)-(e-i)*Math.sin(n)+s,(t-s)*Math.sin(n)+(e-i)*Math.cos(n)+i]}_text_bounds(t,e,s,i){return[[t,t+s,t+s,t,t],[e,e,e-i,e-i,e]]}_render(t,e,s){const{sx:i,sy:n,x_offset:o,y_offset:_,angle:h,text:l}=null!=s?s:this;this._sys=[],this._sxs=[];for(const s of e){const e=this._sxs[s]=[],r=this._sys[s]=[],a=i[s],x=n[s],u=o.get(s),f=_.get(s),p=h.get(s),g=l.get(s);if(isFinite(a+x+u+f+p)&&null!=g&&this.visuals.text.doit){const i=`${g}`;t.save(),t.translate(a+u,x+f),t.rotate(p),this.visuals.text.set_vectorize(t,s);const n=this.visuals.text.font_value(s),{height:o}=(0,c.font_metrics)(n),_=this.text_line_height.get(s)*o;if(-1==i.indexOf(\"\\n\")){t.fillText(i,0,0);const s=a+u,n=x+f,o=t.measureText(i).width,[h,l]=this._text_bounds(s,n,o,_);e.push(h),r.push(l)}else{const n=i.split(\"\\n\"),o=_*n.length,h=this.text_baseline.get(s);let l;switch(h){case\"top\":l=0;break;case\"middle\":l=-o/2+_/2;break;case\"bottom\":l=-o+_;break;default:l=0,console.warn(`'${h}' baseline not supported with multi line text`)}for(const s of n){t.fillText(s,0,l);const i=a+u,n=l+x+f,o=t.measureText(s).width,[h,c]=this._text_bounds(i,n,o,_);e.push(h),r.push(c),l+=_}}t.restore()}}}_hit_point(t){const{sx:e,sy:s}=t,i=[];for(let t=0;t({text:[a.NullStringSpec,{field:\"text\"}],angle:[a.AngleSpec,0],x_offset:[a.NumberSpec,0],y_offset:[a.NumberSpec,0]})))},\n", - " function _(t,e,s,i,r){i();const h=t(1);var o;const a=t(277),n=t(24),_=(0,h.__importStar)(t(18));class l extends a.BoxView{async lazy_initialize(){await super.lazy_initialize();const{webgl:e}=this.renderer.plot_view.canvas_view;if(null!=e&&e.regl_wrapper.has_webgl){const{LRTBGL:s}=await Promise.resolve().then((()=>(0,h.__importStar)(t(427))));this.glglyph=new s(e.regl_wrapper,this)}}scenterxy(t){return[this.sx[t],(this.stop[t]+this.sbottom[t])/2]}_lrtb(t){const e=this.width.get(t)/2,s=this._x[t],i=this._top[t],r=this._bottom[t];return[s-e,s+e,Math.max(i,r),Math.min(i,r)]}_map_data(){this.sx=this.renderer.xscale.v_compute(this._x),this.sw=this.sdist(this.renderer.xscale,this._x,this.width,\"center\"),this.stop=this.renderer.yscale.v_compute(this._top),this.sbottom=this.renderer.yscale.v_compute(this._bottom);const t=this.sx.length;this.sleft=new n.ScreenArray(t),this.sright=new n.ScreenArray(t);for(let e=0;e({x:[_.XCoordinateSpec,{field:\"x\"}],bottom:[_.YCoordinateSpec,{value:0}],width:[_.NumberSpec,{value:1}],top:[_.YCoordinateSpec,{field:\"top\"}]})))},\n", - " function _(e,s,t,i,n){i();const r=e(1);var a;const c=e(178),d=e(184),l=e(48),h=e(24),o=e(20),_=(0,r.__importStar)(e(18)),u=e(10),g=e(72),x=e(12);class p extends c.XYGlyphView{_map_data(){\"data\"==this.model.properties.radius.units?this.sradius=this.sdist(this.renderer.xscale,this._x,this.radius):this.sradius=(0,h.to_screen)(this.radius),this.max_sradius=(0,x.max)(this.sradius)}_render(e,s,t){const{sx:i,sy:n,sradius:r,start_angle:a,end_angle:c}=null!=t?t:this,d=\"anticlock\"==this.model.direction;for(const t of s){const s=i[t],l=n[t],h=r[t],o=a.get(t),_=c.get(t);isFinite(s+l+h+o+_)&&(e.beginPath(),e.arc(s,l,h,o,_,d),e.lineTo(s,l),e.closePath(),this.visuals.fill.apply(e,t),this.visuals.hatch.apply(e,t),this.visuals.line.apply(e,t))}}_hit_point(e){let s,t,i,n,r;const{sx:a,sy:c}=e,d=this.renderer.xscale.invert(a),l=this.renderer.yscale.invert(c);t=a-this.max_sradius,i=a+this.max_sradius;const[h,o]=this.renderer.xscale.r_invert(t,i);n=c-this.max_sradius,r=c+this.max_sradius;const[_,x]=this.renderer.yscale.r_invert(n,r),p=[];for(const e of this.index.indices({x0:h,x1:o,y0:_,y1:x})){const a=this.sradius[e]**2;[t,i]=this.renderer.xscale.r_compute(d,this._x[e]),[n,r]=this.renderer.yscale.r_compute(l,this._y[e]),s=(t-i)**2+(n-r)**2,s<=a&&p.push(e)}const y=\"anticlock\"==this.model.direction,m=[];for(const e of p){const s=Math.atan2(c-this.sy[e],a-this.sx[e]);(0,u.angle_between)(-s,-this.start_angle.get(e),-this.end_angle.get(e),y)&&m.push(e)}return new g.Selection({indices:m})}draw_legend_for_index(e,s,t){(0,d.generic_area_vector_legend)(this.visuals,e,s,t)}scenterxy(e){const s=this.sradius[e]/2,t=(this.start_angle.get(e)+this.end_angle.get(e))/2;return[this.sx[e]+s*Math.cos(t),this.sy[e]+s*Math.sin(t)]}}t.WedgeView=p,p.__name__=\"WedgeView\";class y extends c.XYGlyph{constructor(e){super(e)}}t.Wedge=y,a=y,y.__name__=\"Wedge\",a.prototype.default_view=p,a.mixins([l.LineVector,l.FillVector,l.HatchVector]),a.define((({})=>({direction:[o.Direction,\"anticlock\"],radius:[_.DistanceSpec,{field:\"radius\"}],start_angle:[_.AngleSpec,{field:\"start_angle\"}],end_angle:[_.AngleSpec,{field:\"end_angle\"}]})))},\n", - " function _(t,_,r,o,a){o();const e=t(1);(0,e.__exportStar)(t(302),r),(0,e.__exportStar)(t(303),r),(0,e.__exportStar)(t(304),r)},\n", - " function _(e,t,d,n,s){n();const o=e(53),r=e(12),_=e(9),i=e(72);class c extends o.Model{constructor(e){super(e)}_hit_test(e,t,d){if(!t.model.visible)return null;const n=d.glyph.hit_test(e);return null==n?null:d.model.view.convert_selection_from_subset(n)}}d.GraphHitTestPolicy=c,c.__name__=\"GraphHitTestPolicy\";class a extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.edge_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;return s.update(e,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{edge_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.edge_view.model);return r.update(e,n,s),d.edge_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!r.is_empty()}}d.EdgesOnly=a,a.__name__=\"EdgesOnly\";class l extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}do_selection(e,t,d,n){if(null==e)return!1;const s=t.node_renderer.data_source.selected;return s.update(e,d,n),t.node_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const{node_renderer:o}=d.model,r=o.get_selection_manager().get_or_create_inspector(d.node_view.model);return r.update(e,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.node_view.model.data_source.inspect.emit([d.node_view.model,{geometry:t}]),!r.is_empty()}}d.NodesOnly=l,l.__name__=\"NodesOnly\";class u extends c{constructor(e){super(e)}hit_test(e,t){return this._hit_test(e,t,t.node_view)}get_linked_edges(e,t,d){let n=[];\"selection\"==d?n=e.selected.indices.map((t=>e.data.index[t])):\"inspection\"==d&&(n=e.inspected.indices.map((t=>e.data.index[t])));const s=[];for(let e=0;e(0,r.indexOf)(e.data.index,t)));return new i.Selection({indices:o})}do_selection(e,t,d,n){if(null==e)return!1;const s=t.edge_renderer.data_source.selected;s.update(e,d,n);const o=t.node_renderer.data_source.selected,r=this.get_linked_nodes(t.node_renderer.data_source,t.edge_renderer.data_source,\"selection\");return o.update(r,d,n),t.edge_renderer.data_source._select.emit(),!s.is_empty()}do_inspection(e,t,d,n,s){if(null==e)return!1;const o=d.edge_view.model.data_source.selection_manager.get_or_create_inspector(d.edge_view.model);o.update(e,n,s),d.edge_view.model.data_source.setv({inspected:o},{silent:!0});const r=d.node_view.model.data_source.selection_manager.get_or_create_inspector(d.node_view.model),_=this.get_linked_nodes(d.node_view.model.data_source,d.edge_view.model.data_source,\"inspection\");return r.update(_,n,s),d.node_view.model.data_source.setv({inspected:r},{silent:!0}),d.edge_view.model.data_source.inspect.emit([d.edge_view.model,{geometry:t}]),!o.is_empty()}}d.EdgesAndLinkedNodes=m,m.__name__=\"EdgesAndLinkedNodes\"},\n", - " function _(e,o,t,r,n){var s;r();const a=e(53),d=e(260);class _ extends a.Model{constructor(e){super(e)}get node_coordinates(){return new u({layout:this})}get edge_coordinates(){return new i({layout:this})}}t.LayoutProvider=_,_.__name__=\"LayoutProvider\";class c extends d.CoordinateTransform{constructor(e){super(e)}}t.GraphCoordinates=c,s=c,c.__name__=\"GraphCoordinates\",s.define((({Ref:e})=>({layout:[e(_)]})));class u extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_node_coordinates(e);return{x:o,y:t}}}t.NodeCoordinates=u,u.__name__=\"NodeCoordinates\";class i extends c{constructor(e){super(e)}_v_compute(e){const[o,t]=this.layout.get_edge_coordinates(e);return{x:o,y:t}}}t.EdgeCoordinates=i,i.__name__=\"EdgeCoordinates\"},\n", - " function _(t,a,l,e,n){var o;e();const r=t(303);class u extends r.LayoutProvider{constructor(t){super(t)}get_node_coordinates(t){var a;const l=null!==(a=t.data.index)&&void 0!==a?a:[],e=l.length,n=new Float64Array(e),o=new Float64Array(e);for(let t=0;t({graph_layout:[l(a(t,t)),{}]})))},\n", - " function _(i,d,n,r,G){r(),G(\"Grid\",i(306).Grid)},\n", - " function _(i,e,n,s,t){s();const r=i(1);var o;const d=i(127),_=i(129),a=i(130),l=(0,r.__importStar)(i(48)),h=i(8);class c extends _.GuideRendererView{_render(){const i=this.layer.ctx;i.save(),this._draw_regions(i),this._draw_minor_grids(i),this._draw_grids(i),i.restore()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render()))}_draw_regions(i){if(!this.visuals.band_fill.doit&&!this.visuals.band_hatch.doit)return;const[e,n]=this.grid_coords(\"major\",!1);for(let s=0;sn[1]&&(t=n[1]);else{[s,t]=n;for(const i of this.plot_view.axis_views)i.dimension==this.model.dimension&&i.model.x_range_name==this.model.x_range_name&&i.model.y_range_name==this.model.y_range_name&&([s,t]=i.computed_bounds)}return[s,t]}grid_coords(i,e=!0){const n=this.model.dimension,s=(n+1)%2,[t,r]=this.ranges();let[o,d]=this.computed_bounds();[o,d]=[Math.min(o,d),Math.max(o,d)];const _=[[],[]],a=this.model.get_ticker();if(null==a)return _;const l=a.get_ticks(o,d,t,r.min)[i],h=t.min,c=t.max,u=r.min,m=r.max;e||(l[0]!=h&&l.splice(0,0,h),l[l.length-1]!=c&&l.push(c));for(let i=0;i({bounds:[r(t(i,i),e),\"auto\"],dimension:[n(0,1),0],axis:[o(s(d.Axis)),null],ticker:[o(s(a.Ticker)),null]}))),o.override({level:\"underlay\",band_fill_color:null,band_fill_alpha:0,grid_line_color:\"#e5e5e5\",minor_grid_line_color:null})},\n", - " function _(o,a,x,B,e){B(),e(\"Box\",o(308).Box),e(\"Column\",o(310).Column),e(\"GridBox\",o(311).GridBox),e(\"HTMLBox\",o(312).HTMLBox),e(\"LayoutDOM\",o(309).LayoutDOM),e(\"Panel\",o(313).Panel),e(\"Row\",o(314).Row),e(\"Spacer\",o(315).Spacer),e(\"Tabs\",o(316).Tabs),e(\"WidgetBox\",o(319).WidgetBox)},\n", - " function _(e,n,s,t,c){var i;t();const o=e(309);class r extends o.LayoutDOMView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.children.change,(()=>this.rebuild()))}get child_models(){return this.model.children}}s.BoxView=r,r.__name__=\"BoxView\";class a extends o.LayoutDOM{constructor(e){super(e)}}s.Box=a,i=a,a.__name__=\"Box\",i.define((({Number:e,Array:n,Ref:s})=>({children:[n(s(o.LayoutDOM)),[]],spacing:[e,0]})))},\n", - " function _(t,i,e,s,o){var l;s();const n=t(53),h=t(20),a=t(43),r=t(19),_=t(8),c=t(22),u=t(121),d=t(113),p=t(226),m=t(207),g=t(44),w=t(235);class f extends p.DOMView{constructor(){super(...arguments),this._offset_parent=null,this._viewport={}}get is_layout_root(){return this.is_root||!(this.parent instanceof f)}get base_font_size(){const t=getComputedStyle(this.el).fontSize,i=(0,u.parse_css_font_size)(t);if(null!=i){const{value:t,unit:e}=i;if(\"px\"==e)return t}return null}initialize(){super.initialize(),this.el.style.position=this.is_layout_root?\"relative\":\"absolute\",this._child_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await this.build_child_views()}remove(){for(const t of this.child_views)t.remove();this._child_views.clear(),super.remove()}connect_signals(){super.connect_signals(),this.is_layout_root&&(this._on_resize=()=>this.resize_layout(),window.addEventListener(\"resize\",this._on_resize),this._parent_observer=setInterval((()=>{const t=this.el.offsetParent;this._offset_parent!=t&&(this._offset_parent=t,null!=t&&(this.compute_viewport(),this.invalidate_layout()))}),250));const t=this.model.properties;this.on_change([t.width,t.height,t.min_width,t.min_height,t.max_width,t.max_height,t.margin,t.width_policy,t.height_policy,t.sizing_mode,t.aspect_ratio,t.visible],(()=>this.invalidate_layout())),this.on_change([t.background,t.css_classes],(()=>this.invalidate_render()))}disconnect_signals(){null!=this._parent_observer&&clearTimeout(this._parent_observer),null!=this._on_resize&&window.removeEventListener(\"resize\",this._on_resize),super.disconnect_signals()}css_classes(){return super.css_classes().concat(this.model.css_classes)}get child_views(){return this.child_models.map((t=>this._child_views.get(t)))}async build_child_views(){await(0,d.build_views)(this._child_views,this.child_models,{parent:this})}render(){super.render(),(0,a.empty)(this.el);const{background:t}=this.model;this.el.style.backgroundColor=null!=t?(0,c.color2css)(t):\"\",(0,a.classes)(this.el).clear().add(...this.css_classes());for(const t of this.child_views)this.el.appendChild(t.el),t.render()}update_layout(){for(const t of this.child_views)t.update_layout();this._update_layout()}update_position(){this.el.style.display=this.model.visible?\"block\":\"none\";const t=this.is_layout_root?this.layout.sizing.margin:void 0;(0,a.position)(this.el,this.layout.bbox,t);for(const t of this.child_views)t.update_position()}after_layout(){for(const t of this.child_views)t.after_layout();this._has_finished=!0}compute_viewport(){this._viewport=this._viewport_size()}renderTo(t){t.appendChild(this.el),this._offset_parent=this.el.offsetParent,this.compute_viewport(),this.build(),this.notify_finished()}build(){if(!this.is_layout_root)throw new Error(`${this.toString()} is not a root layout`);return this.render(),this.update_layout(),this.compute_layout(),this}async rebuild(){await this.build_child_views(),this.invalidate_render()}compute_layout(){const t=Date.now();this.layout.compute(this._viewport),this.update_position(),this.after_layout(),r.logger.debug(`layout computed in ${Date.now()-t} ms`)}resize_layout(){this.root.compute_viewport(),this.root.compute_layout()}invalidate_layout(){this.root.update_layout(),this.root.compute_layout()}invalidate_render(){this.render(),this.invalidate_layout()}has_finished(){if(!super.has_finished())return!1;for(const t of this.child_views)if(!t.has_finished())return!1;return!0}_width_policy(){return null!=this.model.width?\"fixed\":\"fit\"}_height_policy(){return null!=this.model.height?\"fixed\":\"fit\"}box_sizing(){let{width_policy:t,height_policy:i,aspect_ratio:e}=this.model;\"auto\"==t&&(t=this._width_policy()),\"auto\"==i&&(i=this._height_policy());const{sizing_mode:s}=this.model;if(null!=s)if(\"fixed\"==s)t=i=\"fixed\";else if(\"stretch_both\"==s)t=i=\"max\";else if(\"stretch_width\"==s)t=\"max\";else if(\"stretch_height\"==s)i=\"max\";else switch(null==e&&(e=\"auto\"),s){case\"scale_width\":t=\"max\",i=\"min\";break;case\"scale_height\":t=\"min\",i=\"max\";break;case\"scale_both\":t=\"max\",i=\"max\"}const o={width_policy:t,height_policy:i},{min_width:l,min_height:n}=this.model;null!=l&&(o.min_width=l),null!=n&&(o.min_height=n);const{width:h,height:a}=this.model;null!=h&&(o.width=h),null!=a&&(o.height=a);const{max_width:r,max_height:c}=this.model;null!=r&&(o.max_width=r),null!=c&&(o.max_height=c),\"auto\"==e&&null!=h&&null!=a?o.aspect=h/a:(0,_.isNumber)(e)&&(o.aspect=e);const{margin:u}=this.model;if(null!=u)if((0,_.isNumber)(u))o.margin={top:u,right:u,bottom:u,left:u};else if(2==u.length){const[t,i]=u;o.margin={top:t,right:i,bottom:t,left:i}}else{const[t,i,e,s]=u;o.margin={top:t,right:i,bottom:e,left:s}}o.visible=this.model.visible;const{align:d}=this.model;return(0,_.isArray)(d)?[o.halign,o.valign]=d:o.halign=o.valign=d,o}_viewport_size(){return(0,a.undisplayed)(this.el,(()=>{let t=this.el;for(;t=t.parentElement;){if(t.classList.contains(g.root))continue;if(t==document.body){const{margin:{left:t,right:i,top:e,bottom:s}}=(0,a.extents)(document.body);return{width:Math.ceil(document.documentElement.clientWidth-t-i),height:Math.ceil(document.documentElement.clientHeight-e-s)}}const{padding:{left:i,right:e,top:s,bottom:o}}=(0,a.extents)(t),{width:l,height:n}=t.getBoundingClientRect(),h=Math.ceil(l-i-e),r=Math.ceil(n-s-o);if(h>0||r>0)return{width:h>0?h:void 0,height:r>0?r:void 0}}return{}}))}export(t,i=!0){const e=\"png\"==t?\"canvas\":\"svg\",s=new w.CanvasLayer(e,i),{width:o,height:l}=this.layout.bbox;s.resize(o,l);for(const e of this.child_views){const o=e.export(t,i),{x:l,y:n}=e.layout.bbox;s.ctx.drawImage(o.canvas,l,n)}return s}serializable_state(){return Object.assign(Object.assign({},super.serializable_state()),{bbox:this.layout.bbox.box,children:this.child_views.map((t=>t.serializable_state()))})}}e.LayoutDOMView=f,f.__name__=\"LayoutDOMView\";class y extends n.Model{constructor(t){super(t)}}e.LayoutDOM=y,l=y,y.__name__=\"LayoutDOM\",l.define((t=>{const{Boolean:i,Number:e,String:s,Auto:o,Color:l,Array:n,Tuple:a,Or:r,Null:_,Nullable:c}=t,u=a(e,e),d=a(e,e,e,e);return{width:[c(e),null],height:[c(e),null],min_width:[c(e),null],min_height:[c(e),null],max_width:[c(e),null],max_height:[c(e),null],margin:[c(r(e,u,d)),[0,0,0,0]],width_policy:[r(m.SizingPolicy,o),\"auto\"],height_policy:[r(m.SizingPolicy,o),\"auto\"],aspect_ratio:[r(e,o,_),null],sizing_mode:[c(h.SizingMode),null],visible:[i,!0],disabled:[i,!1],align:[r(h.Align,a(h.Align,h.Align)),\"start\"],background:[c(l),null],css_classes:[n(s),[]]}}))},\n", - " function _(o,s,t,i,e){var n;i();const a=o(308),l=o(209);class u extends a.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Column(o),this.layout.rows=this.model.rows,this.layout.spacing=[this.model.spacing,0],this.layout.set_sizing(this.box_sizing())}}t.ColumnView=u,u.__name__=\"ColumnView\";class _ extends a.Box{constructor(o){super(o)}}t.Column=_,n=_,_.__name__=\"Column\",n.prototype.default_view=u,n.define((({Any:o})=>({rows:[o,\"auto\"]})))},\n", - " function _(s,o,t,i,e){var n;i();const l=s(309),a=s(209);class r extends l.LayoutDOMView{connect_signals(){super.connect_signals();const{children:s,rows:o,cols:t,spacing:i}=this.model.properties;this.on_change([s,o,t,i],(()=>this.rebuild()))}get child_models(){return this.model.children.map((([s])=>s))}_update_layout(){this.layout=new a.Grid,this.layout.rows=this.model.rows,this.layout.cols=this.model.cols,this.layout.spacing=this.model.spacing;for(const[s,o,t,i,e]of this.model.children){const n=this._child_views.get(s);this.layout.items.push({layout:n.layout,row:o,col:t,row_span:i,col_span:e})}this.layout.set_sizing(this.box_sizing())}}t.GridBoxView=r,r.__name__=\"GridBoxView\";class c extends l.LayoutDOM{constructor(s){super(s)}}t.GridBox=c,n=c,c.__name__=\"GridBox\",n.prototype.default_view=r,n.define((({Any:s,Int:o,Number:t,Tuple:i,Array:e,Ref:n,Or:a,Opt:r})=>({children:[e(i(n(l.LayoutDOM),o,o,r(o),r(o))),[]],rows:[s,\"auto\"],cols:[s,\"auto\"],spacing:[a(t,i(t,t)),0]})))},\n", - " function _(t,e,o,s,n){s();const _=t(309),i=t(207);class a extends _.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new i.ContentBox(this.el),this.layout.set_sizing(this.box_sizing())}}o.HTMLBoxView=a,a.__name__=\"HTMLBoxView\";class u extends _.LayoutDOM{constructor(t){super(t)}}o.HTMLBox=u,u.__name__=\"HTMLBox\"},\n", - " function _(e,n,l,a,o){var t;a();const s=e(53),c=e(309);class d extends s.Model{constructor(e){super(e)}}l.Panel=d,t=d,d.__name__=\"Panel\",t.define((({Boolean:e,String:n,Ref:l})=>({title:[n,\"\"],child:[l(c.LayoutDOM)],closable:[e,!1],disabled:[e,!1]})))},\n", - " function _(o,s,t,i,e){var a;i();const n=o(308),l=o(209);class _ extends n.BoxView{_update_layout(){const o=this.child_views.map((o=>o.layout));this.layout=new l.Row(o),this.layout.cols=this.model.cols,this.layout.spacing=[0,this.model.spacing],this.layout.set_sizing(this.box_sizing())}}t.RowView=_,_.__name__=\"RowView\";class c extends n.Box{constructor(o){super(o)}}t.Row=c,a=c,c.__name__=\"Row\",a.prototype.default_view=_,a.define((({Any:o})=>({cols:[o,\"auto\"]})))},\n", - " function _(e,t,a,s,_){var o;s();const i=e(309),n=e(207);class u extends i.LayoutDOMView{get child_models(){return[]}_update_layout(){this.layout=new n.LayoutItem,this.layout.set_sizing(this.box_sizing())}}a.SpacerView=u,u.__name__=\"SpacerView\";class c extends i.LayoutDOM{constructor(e){super(e)}}a.Spacer=c,o=c,c.__name__=\"Spacer\",o.prototype.default_view=u},\n", - " function _(e,t,s,i,l){i();const h=e(1);var a;const o=e(207),d=e(43),r=e(9),c=e(10),n=e(20),_=e(309),p=e(313),b=(0,h.__importStar)(e(317)),m=b,u=(0,h.__importStar)(e(318)),g=u,v=(0,h.__importStar)(e(229)),w=v;class f extends _.LayoutDOMView{constructor(){super(...arguments),this._scroll_index=0}connect_signals(){super.connect_signals(),this.connect(this.model.properties.tabs.change,(()=>this.rebuild())),this.connect(this.model.properties.active.change,(()=>this.on_active_change()))}styles(){return[...super.styles(),u.default,v.default,b.default]}get child_models(){return this.model.tabs.map((e=>e.child))}_update_layout(){const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,{scroll_el:s,headers_el:i}=this;this.header=new class extends o.ContentBox{_measure(e){const l=(0,d.size)(s),h=(0,d.children)(i).slice(0,3).map((e=>(0,d.size)(e))),{width:a,height:o}=super._measure(e);if(t){const t=l.width+(0,r.sum)(h.map((e=>e.width)));return{width:e.width!=1/0?e.width:t,height:o}}{const t=l.height+(0,r.sum)(h.map((e=>e.height)));return{width:a,height:e.height!=1/0?e.height:t}}}}(this.header_el),t?this.header.set_sizing({width_policy:\"fit\",height_policy:\"fixed\"}):this.header.set_sizing({width_policy:\"fixed\",height_policy:\"fit\"});let l=1,h=1;switch(e){case\"above\":l-=1;break;case\"below\":l+=1;break;case\"left\":h-=1;break;case\"right\":h+=1}const a={layout:this.header,row:l,col:h},c=this.child_views.map((e=>({layout:e.layout,row:1,col:1})));this.layout=new o.Grid([a,...c]),this.layout.set_sizing(this.box_sizing())}update_position(){super.update_position(),this.header_el.style.position=\"absolute\",(0,d.position)(this.header_el,this.header.bbox);const e=this.model.tabs_location,t=\"above\"==e||\"below\"==e,s=(0,d.size)(this.scroll_el),i=(0,d.scroll_size)(this.headers_el);if(t){const{width:e}=this.header.bbox;i.width>e?(this.wrapper_el.style.maxWidth=e-s.width+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxWidth=\"\",(0,d.undisplay)(this.scroll_el))}else{const{height:e}=this.header.bbox;i.height>e?(this.wrapper_el.style.maxHeight=e-s.height+\"px\",(0,d.display)(this.scroll_el),this.do_scroll(this.model.active)):(this.wrapper_el.style.maxHeight=\"\",(0,d.undisplay)(this.scroll_el))}const{child_views:l}=this;for(const e of l)(0,d.hide)(e.el);const h=l[this.model.active];null!=h&&(0,d.show)(h.el)}render(){super.render();const{active:e}=this.model,t=this.model.tabs.map(((t,s)=>{const i=(0,d.div)({class:[m.tab,s==e?m.active:null]},t.title);if(i.addEventListener(\"click\",(e=>{this.model.disabled||e.target==e.currentTarget&&this.change_active(s)})),t.closable){const e=(0,d.div)({class:m.close});e.addEventListener(\"click\",(e=>{if(e.target==e.currentTarget){this.model.tabs=(0,r.remove_at)(this.model.tabs,s);const e=this.model.tabs.length;this.model.active>e-1&&(this.model.active=e-1)}})),i.appendChild(e)}return(this.model.disabled||t.disabled)&&i.classList.add(m.disabled),i}));this.headers_el=(0,d.div)({class:[m.headers]},t),this.wrapper_el=(0,d.div)({class:m.headers_wrapper},this.headers_el),this.left_el=(0,d.div)({class:[g.btn,g.btn_default],disabled:\"\"},(0,d.div)({class:[w.caret,m.left]})),this.right_el=(0,d.div)({class:[g.btn,g.btn_default]},(0,d.div)({class:[w.caret,m.right]})),this.left_el.addEventListener(\"click\",(()=>this.do_scroll(\"left\"))),this.right_el.addEventListener(\"click\",(()=>this.do_scroll(\"right\"))),this.scroll_el=(0,d.div)({class:g.btn_group},this.left_el,this.right_el);const s=this.model.tabs_location;this.header_el=(0,d.div)({class:[m.tabs_header,m[s]]},this.scroll_el,this.wrapper_el),this.el.appendChild(this.header_el)}do_scroll(e){const t=this.model.tabs.length;\"left\"==e?this._scroll_index-=1:\"right\"==e?this._scroll_index+=1:this._scroll_index=e,this._scroll_index=(0,c.clamp)(this._scroll_index,0,t-1),0==this._scroll_index?this.left_el.setAttribute(\"disabled\",\"\"):this.left_el.removeAttribute(\"disabled\"),this._scroll_index==t-1?this.right_el.setAttribute(\"disabled\",\"\"):this.right_el.removeAttribute(\"disabled\");const s=(0,d.children)(this.headers_el).slice(0,this._scroll_index).map((e=>e.getBoundingClientRect())),i=this.model.tabs_location;if(\"above\"==i||\"below\"==i){const e=-(0,r.sum)(s.map((e=>e.width)));this.headers_el.style.left=`${e}px`}else{const e=-(0,r.sum)(s.map((e=>e.height)));this.headers_el.style.top=`${e}px`}}change_active(e){e!=this.model.active&&(this.model.active=e)}on_active_change(){const e=this.model.active,t=(0,d.children)(this.headers_el);for(const e of t)e.classList.remove(m.active);t[e].classList.add(m.active);const{child_views:s}=this;for(const e of s)(0,d.hide)(e.el);(0,d.show)(s[e].el)}}s.TabsView=f,f.__name__=\"TabsView\";class x extends _.LayoutDOM{constructor(e){super(e)}}s.Tabs=x,a=x,x.__name__=\"Tabs\",a.prototype.default_view=f,a.define((({Int:e,Array:t,Ref:s})=>({tabs:[t(s(p.Panel)),[]],tabs_location:[n.Location,\"above\"],active:[e,0]})))},\n", - " function _(e,r,b,o,t){o(),b.root=\"bk-root\",b.tabs_header=\"bk-tabs-header\",b.btn_group=\"bk-btn-group\",b.btn=\"bk-btn\",b.headers_wrapper=\"bk-headers-wrapper\",b.above=\"bk-above\",b.right=\"bk-right\",b.below=\"bk-below\",b.left=\"bk-left\",b.headers=\"bk-headers\",b.tab=\"bk-tab\",b.active=\"bk-active\",b.close=\"bk-close\",b.disabled=\"bk-disabled\",b.default='.bk-root .bk-tabs-header{display:flex;flex-wrap:nowrap;align-items:center;overflow:hidden;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-tabs-header .bk-btn-group{height:auto;margin-right:5px;}.bk-root .bk-tabs-header .bk-btn-group > .bk-btn{flex-grow:0;height:auto;padding:4px 4px;}.bk-root .bk-tabs-header .bk-headers-wrapper{flex-grow:1;overflow:hidden;color:#666666;}.bk-root .bk-tabs-header.bk-above .bk-headers-wrapper{border-bottom:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-right .bk-headers-wrapper{border-left:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-below .bk-headers-wrapper{border-top:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-left .bk-headers-wrapper{border-right:1px solid #e6e6e6;}.bk-root .bk-tabs-header.bk-above,.bk-root .bk-tabs-header.bk-below{flex-direction:row;}.bk-root .bk-tabs-header.bk-above .bk-headers,.bk-root .bk-tabs-header.bk-below .bk-headers{flex-direction:row;}.bk-root .bk-tabs-header.bk-left,.bk-root .bk-tabs-header.bk-right{flex-direction:column;}.bk-root .bk-tabs-header.bk-left .bk-headers,.bk-root .bk-tabs-header.bk-right .bk-headers{flex-direction:column;}.bk-root .bk-tabs-header .bk-headers{position:relative;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-tabs-header .bk-tab{padding:4px 8px;border:solid transparent;white-space:nowrap;cursor:pointer;}.bk-root .bk-tabs-header .bk-tab:hover{background-color:#f2f2f2;}.bk-root .bk-tabs-header .bk-tab.bk-active{color:#4d4d4d;background-color:white;border-color:#e6e6e6;}.bk-root .bk-tabs-header .bk-tab .bk-close{margin-left:10px;}.bk-root .bk-tabs-header .bk-tab.bk-disabled{cursor:not-allowed;pointer-events:none;opacity:0.65;}.bk-root .bk-tabs-header.bk-above .bk-tab{border-width:3px 1px 0px 1px;border-radius:4px 4px 0 0;}.bk-root .bk-tabs-header.bk-right .bk-tab{border-width:1px 3px 1px 0px;border-radius:0 4px 4px 0;}.bk-root .bk-tabs-header.bk-below .bk-tab{border-width:0px 1px 3px 1px;border-radius:0 0 4px 4px;}.bk-root .bk-tabs-header.bk-left .bk-tab{border-width:1px 0px 1px 3px;border-radius:4px 0 0 4px;}.bk-root .bk-close{display:inline-block;width:10px;height:10px;vertical-align:middle;background-image:url(\\'data:image/svg+xml;utf8, \\');}.bk-root .bk-close:hover{background-image:url(\\'data:image/svg+xml;utf8, \\');}'},\n", - " function _(o,b,r,t,e){t(),r.root=\"bk-root\",r.btn=\"bk-btn\",r.active=\"bk-active\",r.btn_default=\"bk-btn-default\",r.btn_primary=\"bk-btn-primary\",r.btn_success=\"bk-btn-success\",r.btn_warning=\"bk-btn-warning\",r.btn_danger=\"bk-btn-danger\",r.btn_light=\"bk-btn-light\",r.btn_group=\"bk-btn-group\",r.vertical=\"bk-vertical\",r.horizontal=\"bk-horizontal\",r.dropdown_toggle=\"bk-dropdown-toggle\",r.default=\".bk-root .bk-btn{height:100%;display:inline-block;text-align:center;vertical-align:middle;white-space:nowrap;cursor:pointer;padding:6px 12px;font-size:12px;border:1px solid transparent;border-radius:4px;outline:0;user-select:none;-ms-user-select:none;-moz-user-select:none;-webkit-user-select:none;}.bk-root .bk-btn:hover,.bk-root .bk-btn:focus{text-decoration:none;}.bk-root .bk-btn:active,.bk-root .bk-btn.bk-active{background-image:none;box-shadow:inset 0 3px 5px rgba(0, 0, 0, 0.125);}.bk-root .bk-btn[disabled]{cursor:not-allowed;pointer-events:none;opacity:0.65;box-shadow:none;}.bk-root .bk-btn-default{color:#333;background-color:#fff;border-color:#ccc;}.bk-root .bk-btn-default:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-default.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-default[disabled],.bk-root .bk-btn-default[disabled]:hover,.bk-root .bk-btn-default[disabled]:focus,.bk-root .bk-btn-default[disabled]:active,.bk-root .bk-btn-default[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-primary{color:#fff;background-color:#428bca;border-color:#357ebd;}.bk-root .bk-btn-primary:hover{background-color:#3681c1;border-color:#2c699e;}.bk-root .bk-btn-primary.bk-active{background-color:#3276b1;border-color:#285e8e;}.bk-root .bk-btn-primary[disabled],.bk-root .bk-btn-primary[disabled]:hover,.bk-root .bk-btn-primary[disabled]:focus,.bk-root .bk-btn-primary[disabled]:active,.bk-root .bk-btn-primary[disabled].bk-active{background-color:#506f89;border-color:#357ebd;}.bk-root .bk-btn-success{color:#fff;background-color:#5cb85c;border-color:#4cae4c;}.bk-root .bk-btn-success:hover{background-color:#4eb24e;border-color:#409240;}.bk-root .bk-btn-success.bk-active{background-color:#47a447;border-color:#398439;}.bk-root .bk-btn-success[disabled],.bk-root .bk-btn-success[disabled]:hover,.bk-root .bk-btn-success[disabled]:focus,.bk-root .bk-btn-success[disabled]:active,.bk-root .bk-btn-success[disabled].bk-active{background-color:#667b66;border-color:#4cae4c;}.bk-root .bk-btn-warning{color:#fff;background-color:#f0ad4e;border-color:#eea236;}.bk-root .bk-btn-warning:hover{background-color:#eea43b;border-color:#e89014;}.bk-root .bk-btn-warning.bk-active{background-color:#ed9c28;border-color:#d58512;}.bk-root .bk-btn-warning[disabled],.bk-root .bk-btn-warning[disabled]:hover,.bk-root .bk-btn-warning[disabled]:focus,.bk-root .bk-btn-warning[disabled]:active,.bk-root .bk-btn-warning[disabled].bk-active{background-color:#c89143;border-color:#eea236;}.bk-root .bk-btn-danger{color:#fff;background-color:#d9534f;border-color:#d43f3a;}.bk-root .bk-btn-danger:hover{background-color:#d5433e;border-color:#bd2d29;}.bk-root .bk-btn-danger.bk-active{background-color:#d2322d;border-color:#ac2925;}.bk-root .bk-btn-danger[disabled],.bk-root .bk-btn-danger[disabled]:hover,.bk-root .bk-btn-danger[disabled]:focus,.bk-root .bk-btn-danger[disabled]:active,.bk-root .bk-btn-danger[disabled].bk-active{background-color:#a55350;border-color:#d43f3a;}.bk-root .bk-btn-light{color:#333;background-color:#fff;border-color:#ccc;border-color:transparent;}.bk-root .bk-btn-light:hover{background-color:#f5f5f5;border-color:#b8b8b8;}.bk-root .bk-btn-light.bk-active{background-color:#ebebeb;border-color:#adadad;}.bk-root .bk-btn-light[disabled],.bk-root .bk-btn-light[disabled]:hover,.bk-root .bk-btn-light[disabled]:focus,.bk-root .bk-btn-light[disabled]:active,.bk-root .bk-btn-light[disabled].bk-active{background-color:#e6e6e6;border-color:#ccc;}.bk-root .bk-btn-group{height:100%;display:flex;flex-wrap:nowrap;align-items:center;}.bk-root .bk-btn-group:not(.bk-vertical),.bk-root .bk-btn-group.bk-horizontal{flex-direction:row;}.bk-root .bk-btn-group.bk-vertical{flex-direction:column;}.bk-root .bk-btn-group > .bk-btn{flex-grow:1;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn + .bk-btn{margin-left:-1px;}.bk-root .bk-btn-group.bk-vertical > .bk-btn + .bk-btn{margin-top:-1px;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:first-child:not(:last-child){border-bottom-right-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:first-child:not(:last-child){border-bottom-left-radius:0;border-bottom-right-radius:0;}.bk-root .bk-btn-group:not(.bk-vertical) > .bk-btn:not(:first-child):last-child{border-bottom-left-radius:0;border-top-left-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn:not(:first-child):last-child{border-top-left-radius:0;border-top-right-radius:0;}.bk-root .bk-btn-group > .bk-btn:not(:first-child):not(:last-child){border-radius:0;}.bk-root .bk-btn-group.bk-vertical > .bk-btn{width:100%;}.bk-root .bk-btn-group .bk-dropdown-toggle{flex:0 0 0;padding:6px 6px;}\"},\n", - " function _(e,t,o,n,_){var i;n();const s=e(310);class d extends s.ColumnView{}o.WidgetBoxView=d,d.__name__=\"WidgetBoxView\";class a extends s.Column{constructor(e){super(e)}}o.WidgetBox=a,i=a,a.__name__=\"WidgetBox\",i.prototype.default_view=d},\n", - " function _(t,a,i,e,M){e();var T=t(135);M(\"MathText\",T.MathText),M(\"Ascii\",T.Ascii),M(\"MathML\",T.MathML),M(\"TeX\",T.TeX),M(\"PlainText\",t(139).PlainText)},\n", - " function _(r,o,t,e,n){e(),n(\"CustomJSTransform\",r(322).CustomJSTransform),n(\"Dodge\",r(323).Dodge),n(\"Interpolator\",r(325).Interpolator),n(\"Jitter\",r(326).Jitter),n(\"LinearInterpolator\",r(327).LinearInterpolator),n(\"StepInterpolator\",r(328).StepInterpolator),n(\"Transform\",r(56).Transform)},\n", - " function _(r,t,s,n,e){var a;n();const u=r(56),o=r(13),m=r(34);class _ extends u.Transform{constructor(r){super(r)}get names(){return(0,o.keys)(this.args)}get values(){return(0,o.values)(this.args)}_make_transform(r,t){return new Function(...this.names,r,(0,m.use_strict)(t))}get scalar_transform(){return this._make_transform(\"x\",this.func)}get vector_transform(){return this._make_transform(\"xs\",this.v_func)}compute(r){return this.scalar_transform(...this.values,r)}v_compute(r){return this.vector_transform(...this.values,r)}}s.CustomJSTransform=_,a=_,_.__name__=\"CustomJSTransform\",a.define((({Unknown:r,String:t,Dict:s})=>({args:[s(r),{}],func:[t,\"\"],v_func:[t,\"\"]})))},\n", - " function _(e,n,r,o,s){var t;o();const u=e(324);class a extends u.RangeTransform{constructor(e){super(e)}_compute(e){return e+this.value}}r.Dodge=a,t=a,a.__name__=\"Dodge\",t.define((({Number:e})=>({value:[e,0]})))},\n", - " function _(e,n,t,r,a){var s;r();const c=e(56),o=e(57),i=e(67),u=e(24),h=e(8),l=e(11);class g extends c.Transform{constructor(e){super(e)}v_compute(e){let n;this.range instanceof i.FactorRange?n=this.range.v_synthetic(e):(0,h.isArrayableOf)(e,h.isNumber)?n=e:(0,l.unreachable)();const t=new((0,u.infer_type)(n))(n.length);for(let e=0;e({range:[n(e(o.Range)),null]})))},\n", - " function _(t,e,r,n,s){var o;n();const i=t(56),a=t(70),h=t(24),l=t(9),d=t(8);class c extends i.Transform{constructor(t){super(t),this._sorted_dirty=!0}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._sorted_dirty=!0))}v_compute(t){const e=new((0,h.infer_type)(t))(t.length);for(let r=0;ro*(e[t]-e[r]))),this._x_sorted=new((0,h.infer_type)(e))(n),this._y_sorted=new((0,h.infer_type)(r))(n);for(let t=0;t({x:[o(r,s(e))],y:[o(r,s(e))],data:[i(n(a.ColumnarDataSource)),null],clip:[t,!0]})))},\n", - " function _(t,s,e,i,r){i();const n=t(1);var o;const a=t(324),u=t(67),h=t(20),c=t(8),m=t(12),f=(0,n.__importStar)(t(10)),_=t(11);class p extends a.RangeTransform{constructor(t){super(t)}v_compute(t){var s;let e;this.range instanceof u.FactorRange?e=this.range.v_synthetic(t):(0,c.isArrayableOf)(t,c.isNumber)?e=t:(0,_.unreachable)();const i=e.length;(null===(s=this.previous_offsets)||void 0===s?void 0:s.length)!=i&&(this.previous_offsets=new Array(i),this.previous_offsets=(0,m.map)(this.previous_offsets,(()=>this._compute())));const r=this.previous_offsets;return(0,m.map)(e,((t,s)=>r[s]+t))}_compute(){switch(this.distribution){case\"uniform\":return this.mean+(f.random()-.5)*this.width;case\"normal\":return f.rnorm(this.mean,this.width)}}}e.Jitter=p,o=p,p.__name__=\"Jitter\",o.define((({Number:t})=>({mean:[t,0],width:[t,1],distribution:[h.Distribution,\"uniform\"]})))},\n", - " function _(t,s,_,r,e){r();const i=t(9),o=t(325);class n extends o.Interpolator{constructor(t){super(t)}compute(t){if(this.sort(!1),this.clip){if(tthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}if(t==this._x_sorted[0])return this._y_sorted[0];const s=(0,i.find_last_index)(this._x_sorted,(s=>sthis._x_sorted[this._x_sorted.length-1])return NaN}else{if(tthis._x_sorted[this._x_sorted.length-1])return this._y_sorted[this._y_sorted.length-1]}let e;switch(this.mode){case\"after\":e=(0,d.find_last_index)(this._x_sorted,(e=>t>=e));break;case\"before\":e=(0,d.find_index)(this._x_sorted,(e=>t<=e));break;case\"center\":{const s=(0,d.map)(this._x_sorted,(e=>Math.abs(e-t))),r=(0,d.min)(s);e=(0,d.find_index)(s,(t=>r===t));break}default:throw new Error(`unknown mode: ${this.mode}`)}return-1!=e?this._y_sorted[e]:NaN}}s.StepInterpolator=h,_=h,h.__name__=\"StepInterpolator\",_.define((()=>({mode:[n.StepMode,\"after\"]})))},\n", - " function _(p,o,t,a,n){a(),n(\"MapOptions\",p(330).MapOptions),n(\"GMapOptions\",p(330).GMapOptions),n(\"GMapPlot\",p(330).GMapPlot),n(\"Plot\",p(331).Plot)},\n", - " function _(e,t,n,o,a){var s,p,_;o();const i=e(331),r=e(53),l=e(58),c=e(336);a(\"GMapPlotView\",c.GMapPlotView);class d extends r.Model{constructor(e){super(e)}}n.MapOptions=d,s=d,d.__name__=\"MapOptions\",s.define((({Int:e,Number:t})=>({lat:[t],lng:[t],zoom:[e,12]})));class u extends d{constructor(e){super(e)}}n.GMapOptions=u,p=u,u.__name__=\"GMapOptions\",p.define((({Boolean:e,Int:t,String:n})=>({map_type:[n,\"roadmap\"],scale_control:[e,!1],styles:[n],tilt:[t,45]})));class M extends i.Plot{constructor(e){super(e),this.use_map=!0}}n.GMapPlot=M,_=M,M.__name__=\"GMapPlot\",_.prototype.default_view=c.GMapPlotView,_.define((({String:e,Ref:t})=>({map_options:[t(u)],api_key:[e],api_version:[e,\"weekly\"]}))),_.override({x_range:()=>new l.Range1d,y_range:()=>new l.Range1d})},\n", - " function _(e,t,r,n,i){n();const o=e(1);var a;const s=(0,o.__importStar)(e(48)),l=(0,o.__importStar)(e(18)),_=e(15),c=e(20),h=e(9),d=e(13),u=e(8),g=e(309),p=e(128),f=e(306),b=e(40),w=e(118),y=e(59),m=e(221),x=e(57),v=e(55),A=e(75),S=e(41),R=e(176),D=e(175),L=e(63),P=e(332);i(\"PlotView\",P.PlotView);class k extends g.LayoutDOM{constructor(e){super(e),this.use_map=!1}_doc_attached(){super._doc_attached(),this._push_changes([[this.properties.inner_height,null,this.inner_height],[this.properties.inner_width,null,this.inner_width]])}initialize(){super.initialize(),this.reset=new _.Signal0(this,\"reset\");for(const e of(0,d.values)(this.extra_x_ranges).concat(this.x_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}for(const e of(0,d.values)(this.extra_y_ranges).concat(this.y_range)){let t=e.plots;(0,u.isArray)(t)&&(t=t.concat(this),e.setv({plots:t},{silent:!0}))}}add_layout(e,t=\"center\"){const r=this.properties[t].get_value();this.setv({[t]:[...r,e]})}remove_layout(e){const t=t=>{(0,h.remove_by)(t,(t=>t==e))};t(this.left),t(this.right),t(this.above),t(this.below),t(this.center)}get data_renderers(){return this.renderers.filter((e=>e instanceof R.DataRenderer))}add_renderers(...e){this.renderers=this.renderers.concat(e)}add_glyph(e,t=new A.ColumnDataSource,r={}){const n=new D.GlyphRenderer(Object.assign(Object.assign({},r),{data_source:t,glyph:e}));return this.add_renderers(n),n}add_tools(...e){this.toolbar.tools=this.toolbar.tools.concat(e)}get panels(){return[...this.side_panels,...this.center]}get side_panels(){const{above:e,below:t,left:r,right:n}=this;return(0,h.concat)([e,t,r,n])}}r.Plot=k,a=k,k.__name__=\"Plot\",a.prototype.default_view=P.PlotView,a.mixins([[\"outline_\",s.Line],[\"background_\",s.Fill],[\"border_\",s.Fill]]),a.define((({Boolean:e,Number:t,String:r,Array:n,Dict:i,Or:o,Ref:a,Null:s,Nullable:_})=>({toolbar:[a(m.Toolbar),()=>new m.Toolbar],toolbar_location:[_(c.Location),\"right\"],toolbar_sticky:[e,!0],plot_width:[l.Alias(\"width\")],plot_height:[l.Alias(\"height\")],frame_width:[_(t),null],frame_height:[_(t),null],title:[o(a(w.Title),r,s),\"\",{convert:e=>(0,u.isString)(e)?new w.Title({text:e}):e}],title_location:[_(c.Location),\"above\"],above:[n(o(a(b.Annotation),a(p.Axis))),[]],below:[n(o(a(b.Annotation),a(p.Axis))),[]],left:[n(o(a(b.Annotation),a(p.Axis))),[]],right:[n(o(a(b.Annotation),a(p.Axis))),[]],center:[n(o(a(b.Annotation),a(f.Grid))),[]],renderers:[n(a(S.Renderer)),[]],x_range:[a(x.Range),()=>new L.DataRange1d],y_range:[a(x.Range),()=>new L.DataRange1d],x_scale:[a(v.Scale),()=>new y.LinearScale],y_scale:[a(v.Scale),()=>new y.LinearScale],extra_x_ranges:[i(a(x.Range)),{}],extra_y_ranges:[i(a(x.Range)),{}],extra_x_scales:[i(a(v.Scale)),{}],extra_y_scales:[i(a(v.Scale)),{}],lod_factor:[t,10],lod_interval:[t,300],lod_threshold:[_(t),2e3],lod_timeout:[t,500],hidpi:[e,!0],output_backend:[c.OutputBackend,\"canvas\"],min_border:[_(t),5],min_border_top:[_(t),null],min_border_left:[_(t),null],min_border_bottom:[_(t),null],min_border_right:[_(t),null],inner_width:[t,0],inner_height:[t,0],outer_width:[t,0],outer_height:[t,0],match_aspect:[e,!1],aspect_scale:[t,1],reset_policy:[c.ResetPolicy,\"standard\"]}))),a.override({width:600,height:600,outline_line_color:\"#e5e5e5\",border_fill_color:\"#ffffff\",background_fill_color:\"#ffffff\"})},\n", - " function _(e,t,i,s,a){s();const n=e(1),o=e(126),l=e(249),r=e(309),_=e(40),h=e(118),d=e(128),u=e(220),c=e(251),p=e(113),v=e(45),g=e(19),b=e(251),m=e(333),y=e(8),w=e(9),f=e(235),x=e(208),z=e(211),k=e(209),q=e(123),M=e(65),R=e(334),V=e(335),S=e(28);class O extends r.LayoutDOMView{constructor(){super(...arguments),this._outer_bbox=new M.BBox,this._inner_bbox=new M.BBox,this._needs_paint=!0,this._needs_layout=!1,this._invalidated_painters=new Set,this._invalidate_all=!0,this._needs_notify=!1}get canvas(){return this.canvas_view}get state(){return this._state_manager}set invalidate_dataranges(e){this._range_manager.invalidate_dataranges=e}renderer_view(e){const t=this.renderer_views.get(e);if(null==t)for(const[,t]of this.renderer_views){const i=t.renderer_view(e);if(null!=i)return i}return t}get is_paused(){return null!=this._is_paused&&0!==this._is_paused}get child_models(){return[]}pause(){null==this._is_paused?this._is_paused=1:this._is_paused+=1}unpause(e=!1){if(null==this._is_paused)throw new Error(\"wasn't paused\");this._is_paused-=1,0!=this._is_paused||e||this.request_paint(\"everything\")}notify_finished_after_paint(){this._needs_notify=!0}request_render(){this.request_paint(\"everything\")}request_paint(e){this.invalidate_painters(e),this.schedule_paint()}invalidate_painters(e){if(\"everything\"==e)this._invalidate_all=!0;else if((0,y.isArray)(e))for(const t of e)this._invalidated_painters.add(t);else this._invalidated_painters.add(e)}schedule_paint(){if(!this.is_paused){const e=this.throttled_paint();this._ready=this._ready.then((()=>e))}}request_layout(){this._needs_layout=!0,this.request_paint(\"everything\")}reset(){\"standard\"==this.model.reset_policy&&(this.state.clear(),this.reset_range(),this.reset_selection()),this.model.trigger_event(new c.Reset)}remove(){(0,p.remove_views)(this.renderer_views),(0,p.remove_views)(this.tool_views),this.canvas_view.remove(),super.remove()}render(){super.render(),this.el.appendChild(this.canvas_view.el),this.canvas_view.render()}initialize(){this.pause(),super.initialize(),this.lod_started=!1,this.visuals=new v.Visuals(this),this._initial_state={selection:new Map,dimensions:{width:0,height:0}},this.visibility_callbacks=[],this.renderer_views=new Map,this.tool_views=new Map,this.frame=new o.CartesianFrame(this.model.x_scale,this.model.y_scale,this.model.x_range,this.model.y_range,this.model.extra_x_ranges,this.model.extra_y_ranges,this.model.extra_x_scales,this.model.extra_y_scales),this._range_manager=new R.RangeManager(this),this._state_manager=new V.StateManager(this,this._initial_state),this.throttled_paint=(0,m.throttle)((()=>this.repaint()),1e3/60);const{title_location:e,title:t}=this.model;null!=e&&null!=t&&(this._title=t instanceof h.Title?t:new h.Title({text:t}));const{toolbar_location:i,toolbar:s}=this.model;null!=i&&null!=s&&(this._toolbar=new u.ToolbarPanel({toolbar:s}),s.toolbar_location=i)}async lazy_initialize(){await super.lazy_initialize();const{hidpi:e,output_backend:t}=this.model,i=new l.Canvas({hidpi:e,output_backend:t});this.canvas_view=await(0,p.build_view)(i,{parent:this}),this.canvas_view.plot_views=[this],await this.build_renderer_views(),await this.build_tool_views(),this._range_manager.update_dataranges(),this.unpause(!0),g.logger.debug(\"PlotView initialized\")}_width_policy(){return null==this.model.frame_width?super._width_policy():\"min\"}_height_policy(){return null==this.model.frame_height?super._height_policy():\"min\"}_update_layout(){var e,t,i,s,a;this.layout=new z.BorderLayout,this.layout.set_sizing(this.box_sizing());const n=(0,w.copy)(this.model.above),o=(0,w.copy)(this.model.below),l=(0,w.copy)(this.model.left),r=(0,w.copy)(this.model.right),d=e=>{switch(e){case\"above\":return n;case\"below\":return o;case\"left\":return l;case\"right\":return r}},{title_location:c,title:p}=this.model;null!=c&&null!=p&&d(c).push(this._title);const{toolbar_location:v,toolbar:g}=this.model;if(null!=v&&null!=g){const e=d(v);let t=!0;if(this.model.toolbar_sticky)for(let i=0;i{var i;const s=this.renderer_view(t);return s.panel=new q.Panel(e),null===(i=s.update_layout)||void 0===i||i.call(s),s.layout},m=(e,t)=>{const i=\"above\"==e||\"below\"==e,s=[];for(const a of t)if((0,y.isArray)(a)){const t=a.map((t=>{const s=b(e,t);if(t instanceof u.ToolbarPanel){const e=i?\"width_policy\":\"height_policy\";s.set_sizing(Object.assign(Object.assign({},s.sizing),{[e]:\"min\"}))}return s}));let n;i?(n=new k.Row(t),n.set_sizing({width_policy:\"max\",height_policy:\"min\"})):(n=new k.Column(t),n.set_sizing({width_policy:\"min\",height_policy:\"max\"})),n.absolute=!0,s.push(n)}else s.push(b(e,a));return s},f=null!==(e=this.model.min_border)&&void 0!==e?e:0;this.layout.min_border={left:null!==(t=this.model.min_border_left)&&void 0!==t?t:f,top:null!==(i=this.model.min_border_top)&&void 0!==i?i:f,right:null!==(s=this.model.min_border_right)&&void 0!==s?s:f,bottom:null!==(a=this.model.min_border_bottom)&&void 0!==a?a:f};const M=new x.NodeLayout,R=new x.VStack,V=new x.VStack,S=new x.HStack,O=new x.HStack;M.absolute=!0,R.absolute=!0,V.absolute=!0,S.absolute=!0,O.absolute=!0,M.children=this.model.center.filter((e=>e instanceof _.Annotation)).map((e=>{var t;const i=this.renderer_view(e);return null===(t=i.update_layout)||void 0===t||t.call(i),i.layout})).filter((e=>null!=e));const{frame_width:P,frame_height:j}=this.model;M.set_sizing(Object.assign(Object.assign({},null!=P?{width_policy:\"fixed\",width:P}:{width_policy:\"fit\"}),null!=j?{height_policy:\"fixed\",height:j}:{height_policy:\"fit\"})),M.on_resize((e=>this.frame.set_geometry(e))),R.children=(0,w.reversed)(m(\"above\",n)),V.children=m(\"below\",o),S.children=(0,w.reversed)(m(\"left\",l)),O.children=m(\"right\",r),R.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),V.set_sizing({width_policy:\"fit\",height_policy:\"min\"}),S.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),O.set_sizing({width_policy:\"min\",height_policy:\"fit\"}),this.layout.center_panel=M,this.layout.top_panel=R,this.layout.bottom_panel=V,this.layout.left_panel=S,this.layout.right_panel=O}get axis_views(){const e=[];for(const[,t]of this.renderer_views)t instanceof d.AxisView&&e.push(t);return e}set_toolbar_visibility(e){for(const t of this.visibility_callbacks)t(e)}update_range(e,t){this.pause(),this._range_manager.update(e,t),this.unpause()}reset_range(){this.update_range(null),this.trigger_ranges_update_event()}trigger_ranges_update_event(){const{x_range:e,y_range:t}=this.model;this.model.trigger_event(new b.RangesUpdate(e.start,e.end,t.start,t.end))}get_selection(){const e=new Map;for(const t of this.model.data_renderers){const{selected:i}=t.selection_manager.source;e.set(t,i)}return e}update_selection(e){for(const t of this.model.data_renderers){const i=t.selection_manager.source;if(null!=e){const s=e.get(t);null!=s&&i.selected.update(s,!0)}else i.selection_manager.clear()}}reset_selection(){this.update_selection(null)}_invalidate_layout(){(()=>{var e;for(const t of this.model.side_panels){const i=this.renderer_views.get(t);if(null===(e=i.layout)||void 0===e?void 0:e.has_size_changed())return this.invalidate_painters(i),!0}return!1})()&&this.root.compute_layout()}get_renderer_views(){return this.computed_renderers.map((e=>this.renderer_views.get(e)))}*_compute_renderers(){const{above:e,below:t,left:i,right:s,center:a,renderers:n}=this.model;yield*n,yield*e,yield*t,yield*i,yield*s,yield*a,null!=this._title&&(yield this._title),null!=this._toolbar&&(yield this._toolbar);for(const e of this.model.toolbar.tools)null!=e.overlay&&(yield e.overlay),yield*e.synthetic_renderers}async build_renderer_views(){this.computed_renderers=[...this._compute_renderers()],await(0,p.build_views)(this.renderer_views,this.computed_renderers,{parent:this})}async build_tool_views(){const e=this.model.toolbar.tools;(await(0,p.build_views)(this.tool_views,e,{parent:this})).map((e=>this.canvas_view.ui_event_bus.register_tool(e)))}connect_signals(){super.connect_signals();const{x_ranges:e,y_ranges:t}=this.frame;for(const[,t]of e)this.connect(t.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));for(const[,e]of t)this.connect(e.change,(()=>{this._needs_layout=!0,this.request_paint(\"everything\")}));const{above:i,below:s,left:a,right:n,center:o,renderers:l}=this.model.properties;this.on_change([i,s,a,n,o,l],(async()=>await this.build_renderer_views())),this.connect(this.model.toolbar.properties.tools.change,(async()=>{await this.build_renderer_views(),await this.build_tool_views()})),this.connect(this.model.change,(()=>this.request_paint(\"everything\"))),this.connect(this.model.reset,(()=>this.reset()))}has_finished(){if(!super.has_finished())return!1;if(this.model.visible)for(const[,e]of this.renderer_views)if(!e.has_finished())return!1;return!0}after_layout(){var e;super.after_layout();for(const[,t]of this.renderer_views)t instanceof _.AnnotationView&&(null===(e=t.after_layout)||void 0===e||e.call(t));if(this._needs_layout=!1,this.model.setv({inner_width:Math.round(this.frame.bbox.width),inner_height:Math.round(this.frame.bbox.height),outer_width:Math.round(this.layout.bbox.width),outer_height:Math.round(this.layout.bbox.height)},{no_change:!0}),!1!==this.model.match_aspect&&(this.pause(),this._range_manager.update_dataranges(),this.unpause(!0)),!this._outer_bbox.equals(this.layout.bbox)){const{width:e,height:t}=this.layout.bbox;this.canvas_view.resize(e,t),this._outer_bbox=this.layout.bbox,this._invalidate_all=!0,this._needs_paint=!0}const{inner_bbox:t}=this.layout;this._inner_bbox.equals(t)||(this._inner_bbox=t,this._needs_paint=!0),this._needs_paint&&this.paint()}repaint(){this._needs_layout&&this._invalidate_layout(),this.paint()}paint(){this.is_paused||(this.model.visible&&(g.logger.trace(`${this.toString()}.paint()`),this._actual_paint()),this._needs_notify&&(this._needs_notify=!1,this.notify_finished()))}_actual_paint(){var e;const{document:t}=this.model;if(null!=t){const e=t.interactive_duration();e>=0&&e{t.interactive_duration()>this.model.lod_timeout&&t.interactive_stop(),this.request_paint(\"everything\")}),this.model.lod_timeout):t.interactive_stop()}this._range_manager.invalidate_dataranges&&(this._range_manager.update_dataranges(),this._invalidate_layout());let i=!1,s=!1;if(this._invalidate_all)i=!0,s=!0;else for(const e of this._invalidated_painters){const{level:t}=e.model;if(\"overlay\"!=t?i=!0:s=!0,i&&s)break}this._invalidated_painters.clear(),this._invalidate_all=!1;const a=[this.frame.bbox.left,this.frame.bbox.top,this.frame.bbox.width,this.frame.bbox.height],{primary:n,overlays:o}=this.canvas_view;i&&(n.prepare(),this.canvas_view.prepare_webgl(a),this._map_hook(n.ctx,a),this._paint_empty(n.ctx,a),this._paint_outline(n.ctx,a),this._paint_levels(n.ctx,\"image\",a,!0),this._paint_levels(n.ctx,\"underlay\",a,!0),this._paint_levels(n.ctx,\"glyph\",a,!0),this._paint_levels(n.ctx,\"guide\",a,!1),this._paint_levels(n.ctx,\"annotation\",a,!1),n.finish()),(s||S.settings.wireframe)&&(o.prepare(),this._paint_levels(o.ctx,\"overlay\",a,!1),S.settings.wireframe&&this._paint_layout(o.ctx,this.layout),o.finish()),null==this._initial_state.range&&(this._initial_state.range=null!==(e=this._range_manager.compute_initial())&&void 0!==e?e:void 0),this._needs_paint=!1}_paint_levels(e,t,i,s){for(const a of this.computed_renderers){if(a.level!=t)continue;const n=this.renderer_views.get(a);e.save(),(s||n.needs_clip)&&(e.beginPath(),e.rect(...i),e.clip()),n.render(),e.restore(),n.has_webgl&&n.needs_webgl_blit&&this.canvas_view.blit_webgl(e)}}_paint_layout(e,t){const{x:i,y:s,width:a,height:n}=t.bbox;e.strokeStyle=\"blue\",e.strokeRect(i,s,a,n);for(const a of t)e.save(),t.absolute||e.translate(i,s),this._paint_layout(e,a),e.restore()}_map_hook(e,t){}_paint_empty(e,t){const[i,s,a,n]=[0,0,this.layout.bbox.width,this.layout.bbox.height],[o,l,r,_]=t;this.visuals.border_fill.doit&&(this.visuals.border_fill.set_value(e),e.fillRect(i,s,a,n),e.clearRect(o,l,r,_)),this.visuals.background_fill.doit&&(this.visuals.background_fill.set_value(e),e.fillRect(o,l,r,_))}_paint_outline(e,t){if(this.visuals.outline_line.doit){e.save(),this.visuals.outline_line.set_value(e);let[i,s,a,n]=t;i+a==this.layout.bbox.width&&(a-=1),s+n==this.layout.bbox.height&&(n-=1),e.strokeRect(i,s,a,n),e.restore()}}to_blob(){return this.canvas_view.to_blob()}export(e,t=!0){const i=\"png\"==e?\"canvas\":\"svg\",s=new f.CanvasLayer(i,t),{width:a,height:n}=this.layout.bbox;s.resize(a,n);const{canvas:o}=this.canvas_view.compose();return s.ctx.drawImage(o,0,0),s}serializable_state(){const e=super.serializable_state(),{children:t}=e,i=(0,n.__rest)(e,[\"children\"]),s=this.get_renderer_views().map((e=>e.serializable_state())).filter((e=>null!=e.bbox));return Object.assign(Object.assign({},i),{children:[...null!=t?t:[],...s]})}}i.PlotView=O,O.__name__=\"PlotView\"},\n", - " function _(t,n,e,o,u){o(),e.throttle=function(t,n){let e=null,o=0,u=!1;return function(){return new Promise(((r,i)=>{const l=function(){o=Date.now(),e=null,u=!1;try{t(),r()}catch(t){i(t)}},a=Date.now(),c=n-(a-o);c<=0&&!u?(null!=e&&clearTimeout(e),u=!0,requestAnimationFrame(l)):e||u?r():e=setTimeout((()=>requestAnimationFrame(l)),c)}))}}},\n", - " function _(t,n,e,a,s){a();const o=t(63),r=t(19);class l{constructor(t){this.parent=t,this.invalidate_dataranges=!0}get frame(){return this.parent.frame}update(t,n){const{x_ranges:e,y_ranges:a}=this.frame;if(null==t){for(const[,t]of e)t.reset();for(const[,t]of a)t.reset();this.update_dataranges()}else{const s=[];for(const[n,a]of e)s.push([a,t.xrs.get(n)]);for(const[n,e]of a)s.push([e,t.yrs.get(n)]);(null==n?void 0:n.scrolling)&&this._update_ranges_together(s),this._update_ranges_individually(s,n)}}reset(){this.update(null)}_update_dataranges(t){const n=new Map,e=new Map;let a=!1;for(const[,n]of t.x_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const[,n]of t.y_ranges)n instanceof o.DataRange1d&&\"log\"==n.scale_hint&&(a=!0);for(const t of this.parent.model.data_renderers){const s=this.parent.renderer_view(t);if(null==s)continue;const o=s.glyph_view.bounds();if(null!=o&&n.set(t,o),a){const n=s.glyph_view.log_bounds();null!=n&&e.set(t,n)}}let s=!1,l=!1;const i=t.x_target.span,d=t.y_target.span;let u;!1!==this.parent.model.match_aspect&&0!=i&&0!=d&&(u=1/this.parent.model.aspect_scale*(i/d));for(const[,a]of t.x_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,0,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}for(const[,a]of t.y_ranges){if(a instanceof o.DataRange1d){const t=\"log\"==a.scale_hint?e:n;a.update(t,1,this.parent.model,u),a.follow&&(s=!0)}null!=a.bounds&&(l=!0)}if(s&&l){r.logger.warn(\"Follow enabled so bounds are unset.\");for(const[,n]of t.x_ranges)n.bounds=null;for(const[,n]of t.y_ranges)n.bounds=null}}update_dataranges(){this._update_dataranges(this.frame);for(const t of this.parent.model.renderers){const{coordinates:n}=t;null!=n&&this._update_dataranges(n)}null!=this.compute_initial()&&(this.invalidate_dataranges=!1)}compute_initial(){let t=!0;const{x_ranges:n,y_ranges:e}=this.frame,a=new Map,s=new Map;for(const[e,s]of n){const{start:n,end:o}=s;if(null==n||null==o||isNaN(n+o)){t=!1;break}a.set(e,{start:n,end:o})}if(t)for(const[n,a]of e){const{start:e,end:o}=a;if(null==e||null==o||isNaN(e+o)){t=!1;break}s.set(n,{start:e,end:o})}return t?{xrs:a,yrs:s}:(r.logger.warn(\"could not set initial ranges\"),null)}_update_ranges_together(t){let n=1;for(const[e,a]of t)n=Math.min(n,this._get_weight_to_constrain_interval(e,a));if(n<1)for(const[e,a]of t)a.start=n*a.start+(1-n)*e.start,a.end=n*a.end+(1-n)*e.end}_update_ranges_individually(t,n){const e=!!(null==n?void 0:n.panning),a=!!(null==n?void 0:n.scrolling);let s=!1;for(const[n,o]of t){if(!a){const t=this._get_weight_to_constrain_interval(n,o);t<1&&(o.start=t*o.start+(1-t)*n.start,o.end=t*o.end+(1-t)*n.end)}if(null!=n.bounds&&\"auto\"!=n.bounds){const[t,r]=n.bounds,l=Math.abs(o.end-o.start);n.is_reversed?(null!=t&&t>o.end&&(s=!0,o.end=t,(e||a)&&(o.start=t+l)),null!=r&&ro.start&&(s=!0,o.start=t,(e||a)&&(o.end=t+l)),null!=r&&r0&&r0&&r>a&&(s=(a-o)/(r-o)),s=Math.max(0,Math.min(1,s))}return s}}e.RangeManager=l,l.__name__=\"RangeManager\"},\n", - " function _(t,i,s,e,n){e();const h=t(15);class a{constructor(t,i){this.parent=t,this.initial_state=i,this.changed=new h.Signal0(this.parent,\"state_changed\"),this.history=[],this.index=-1}_do_state_change(t){const i=null!=this.history[t]?this.history[t].state:this.initial_state;return null!=i.range&&this.parent.update_range(i.range),null!=i.selection&&this.parent.update_selection(i.selection),i}push(t,i){const{history:s,index:e}=this,n=null!=s[e]?s[e].state:{},h=Object.assign(Object.assign(Object.assign({},this.initial_state),n),i);this.history=this.history.slice(0,this.index+1),this.history.push({type:t,state:h}),this.index=this.history.length-1,this.changed.emit()}clear(){this.history=[],this.index=-1,this.changed.emit()}undo(){if(this.can_undo){this.index-=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}redo(){if(this.can_redo){this.index+=1;const t=this._do_state_change(this.index);return this.changed.emit(),t}return null}get can_undo(){return this.index>=0}get can_redo(){return this.indexm.emit();const s=encodeURIComponent,o=document.createElement(\"script\");o.type=\"text/javascript\",o.src=`https://maps.googleapis.com/maps/api/js?v=${s(e)}&key=${s(t)}&callback=_bokeh_gmaps_callback`,document.body.appendChild(o)}(t,e)}m.connect((()=>this.request_paint(\"everything\")))}this.unpause()}remove(){(0,p.remove)(this.map_el),super.remove()}update_range(t,e){var s,o;if(null==t)this.map.setCenter({lat:this.initial_lat,lng:this.initial_lng}),this.map.setOptions({zoom:this.initial_zoom}),super.update_range(null,e);else if(null!=t.sdx||null!=t.sdy)this.map.panBy(null!==(s=t.sdx)&&void 0!==s?s:0,null!==(o=t.sdy)&&void 0!==o?o:0),super.update_range(t,e);else if(null!=t.factor){if(10!==this.zoom_count)return void(this.zoom_count+=1);this.zoom_count=0,this.pause(),super.update_range(t,e);const s=t.factor<0?-1:1,o=this.map.getZoom();if(null!=o){const t=o+s;if(t>=2){this.map.setZoom(t);const[e,s]=this._get_projected_bounds();s-e<0&&this.map.setZoom(o)}}this.unpause()}this._set_bokeh_ranges()}_build_map(){const{maps:t}=google;this.map_types={satellite:t.MapTypeId.SATELLITE,terrain:t.MapTypeId.TERRAIN,roadmap:t.MapTypeId.ROADMAP,hybrid:t.MapTypeId.HYBRID};const e=this.model.map_options,s={center:new t.LatLng(e.lat,e.lng),zoom:e.zoom,disableDefaultUI:!0,mapTypeId:this.map_types[e.map_type],scaleControl:e.scale_control,tilt:e.tilt};null!=e.styles&&(s.styles=JSON.parse(e.styles)),this.map_el=(0,p.div)({style:{position:\"absolute\"}}),this.canvas_view.add_underlay(this.map_el),this.map=new t.Map(this.map_el,s),t.event.addListener(this.map,\"idle\",(()=>this._set_bokeh_ranges())),t.event.addListener(this.map,\"bounds_changed\",(()=>this._set_bokeh_ranges())),t.event.addListenerOnce(this.map,\"tilesloaded\",(()=>this._render_finished())),this.connect(this.model.properties.map_options.change,(()=>this._update_options())),this.connect(this.model.map_options.properties.styles.change,(()=>this._update_styles())),this.connect(this.model.map_options.properties.lat.change,(()=>this._update_center(\"lat\"))),this.connect(this.model.map_options.properties.lng.change,(()=>this._update_center(\"lng\"))),this.connect(this.model.map_options.properties.zoom.change,(()=>this._update_zoom())),this.connect(this.model.map_options.properties.map_type.change,(()=>this._update_map_type())),this.connect(this.model.map_options.properties.scale_control.change,(()=>this._update_scale_control())),this.connect(this.model.map_options.properties.tilt.change,(()=>this._update_tilt()))}_render_finished(){this._tiles_loaded=!0,this.notify_finished()}has_finished(){return super.has_finished()&&!0===this._tiles_loaded}_get_latlon_bounds(){const t=this.map.getBounds(),e=t.getNorthEast(),s=t.getSouthWest();return[s.lng(),e.lng(),s.lat(),e.lat()]}_get_projected_bounds(){const[t,e,s,o]=this._get_latlon_bounds(),[i,a]=l.wgs84_mercator.compute(t,s),[n,p]=l.wgs84_mercator.compute(e,o);return[i,n,a,p]}_set_bokeh_ranges(){const[t,e,s,o]=this._get_projected_bounds();this.frame.x_range.setv({start:t,end:e}),this.frame.y_range.setv({start:s,end:o})}_update_center(t){var e;const s=null===(e=this.map.getCenter())||void 0===e?void 0:e.toJSON();null!=s&&(s[t]=this.model.map_options[t],this.map.setCenter(s),this._set_bokeh_ranges())}_update_map_type(){this.map.setOptions({mapTypeId:this.map_types[this.model.map_options.map_type]})}_update_scale_control(){this.map.setOptions({scaleControl:this.model.map_options.scale_control})}_update_tilt(){this.map.setOptions({tilt:this.model.map_options.tilt})}_update_options(){this._update_styles(),this._update_center(\"lat\"),this._update_center(\"lng\"),this._update_zoom(),this._update_map_type()}_update_styles(){this.map.setOptions({styles:JSON.parse(this.model.map_options.styles)})}_update_zoom(){this.map.setOptions({zoom:this.model.map_options.zoom}),this._set_bokeh_ranges()}_map_hook(t,e){if(null==this.map&&\"undefined\"!=typeof google&&null!=google.maps&&this._build_map(),null!=this.map_el){const[t,s,o,i]=e;this.map_el.style.top=`${s}px`,this.map_el.style.left=`${t}px`,this.map_el.style.width=`${o}px`,this.map_el.style.height=`${i}px`}}_paint_empty(t,e){const s=this.layout.bbox.width,o=this.layout.bbox.height,[i,a,n,p]=e;t.clearRect(0,0,s,o),t.beginPath(),t.moveTo(0,0),t.lineTo(0,o),t.lineTo(s,o),t.lineTo(s,0),t.lineTo(0,0),t.moveTo(i,a),t.lineTo(i+n,a),t.lineTo(i+n,a+p),t.lineTo(i,a+p),t.lineTo(i,a),t.closePath(),null!=this.model.border_fill_color&&(t.fillStyle=(0,_.color2css)(this.model.border_fill_color),t.fill())}}s.GMapPlotView=d,d.__name__=\"GMapPlotView\"},\n", - " function _(t,_,n,o,r){o();(0,t(1).__exportStar)(t(132),n)},\n", - " function _(e,r,d,n,R){n(),R(\"GlyphRenderer\",e(175).GlyphRenderer),R(\"GraphRenderer\",e(339).GraphRenderer),R(\"GuideRenderer\",e(129).GuideRenderer);var G=e(41);R(\"Renderer\",G.Renderer),R(\"RendererGroup\",G.RendererGroup)},\n", - " function _(e,r,i,n,t){var o;n();const s=e(176),d=e(175),a=e(303),p=e(302),l=e(113),_=e(178),h=e(283),y=e(286);class c extends s.DataRendererView{get glyph_view(){return this.node_view.glyph}async lazy_initialize(){await super.lazy_initialize(),this.apply_coordinates();const{parent:e}=this,{edge_renderer:r,node_renderer:i}=this.model;this.edge_view=await(0,l.build_view)(r,{parent:e}),this.node_view=await(0,l.build_view)(i,{parent:e})}connect_signals(){super.connect_signals(),this.connect(this.model.layout_provider.change,(()=>{this.apply_coordinates(),this.edge_view.set_data(),this.node_view.set_data(),this.request_render()}))}apply_coordinates(){const{edge_renderer:e,node_renderer:r}=this.model;if(!(e.glyph instanceof h.MultiLine||e.glyph instanceof y.Patches))throw new Error(`${this}.edge_renderer.glyph must be a MultiLine glyph`);if(!(r.glyph instanceof _.XYGlyph))throw new Error(`${this}.node_renderer.glyph must be a XYGlyph glyph`);const i=this.model.layout_provider.edge_coordinates,n=this.model.layout_provider.node_coordinates;e.glyph.properties.xs.internal=!0,e.glyph.properties.ys.internal=!0,r.glyph.properties.x.internal=!0,r.glyph.properties.y.internal=!0,e.glyph.xs={expr:i.x},e.glyph.ys={expr:i.y},r.glyph.x={expr:n.x},r.glyph.y={expr:n.y}}remove(){this.edge_view.remove(),this.node_view.remove(),super.remove()}_render(){this.edge_view.render(),this.node_view.render()}renderer_view(e){if(e instanceof d.GlyphRenderer){if(e==this.edge_view.model)return this.edge_view;if(e==this.node_view.model)return this.node_view}return super.renderer_view(e)}}i.GraphRendererView=c,c.__name__=\"GraphRendererView\";class g extends s.DataRenderer{constructor(e){super(e)}get_selection_manager(){return this.node_renderer.data_source.selection_manager}}i.GraphRenderer=g,o=g,g.__name__=\"GraphRenderer\",o.prototype.default_view=c,o.define((({Ref:e})=>({layout_provider:[e(a.LayoutProvider)],node_renderer:[e(d.GlyphRenderer)],edge_renderer:[e(d.GlyphRenderer)],selection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly],inspection_policy:[e(p.GraphHitTestPolicy),()=>new p.NodesOnly]})))},\n", - " function _(e,t,n,o,c){o();(0,e(1).__exportStar)(e(74),n),c(\"Selection\",e(72).Selection)},\n", - " function _(a,e,S,o,r){o(),r(\"ServerSentDataSource\",a(342).ServerSentDataSource),r(\"AjaxDataSource\",a(344).AjaxDataSource),r(\"ColumnDataSource\",a(75).ColumnDataSource),r(\"ColumnarDataSource\",a(70).ColumnarDataSource),r(\"CDSView\",a(190).CDSView),r(\"DataSource\",a(71).DataSource),r(\"GeoJSONDataSource\",a(345).GeoJSONDataSource),r(\"WebDataSource\",a(343).WebDataSource)},\n", - " function _(e,t,i,a,s){a();const n=e(343);class r extends n.WebDataSource{constructor(e){super(e),this.initialized=!1}setup(){if(!this.initialized){this.initialized=!0;new EventSource(this.data_url).onmessage=e=>{var t;this.load_data(JSON.parse(e.data),this.mode,null!==(t=this.max_size)&&void 0!==t?t:void 0)}}}}i.ServerSentDataSource=r,r.__name__=\"ServerSentDataSource\"},\n", - " function _(e,t,a,n,r){var s;n();const l=e(75),o=e(20);class c extends l.ColumnDataSource{constructor(e){super(e)}get_column(e){const t=this.data[e];return null!=t?t:[]}get_length(){var e;return null!==(e=super.get_length())&&void 0!==e?e:0}initialize(){super.initialize(),this.setup()}load_data(e,t,a){const{adapter:n}=this;let r;switch(r=null!=n?n.execute(this,{response:e}):e,t){case\"replace\":this.data=r;break;case\"append\":{const e=this.data;for(const t of this.columns()){const n=Array.from(e[t]),s=Array.from(r[t]),l=n.concat(s);r[t]=null!=a?l.slice(-a):l}this.data=r;break}}}}a.WebDataSource=c,s=c,c.__name__=\"WebDataSource\",s.define((({Any:e,Int:t,String:a,Nullable:n})=>({max_size:[n(t),null],mode:[o.UpdateMode,\"replace\"],adapter:[n(e),null],data_url:[a]})))},\n", - " function _(t,e,i,s,a){var n;s();const r=t(343),o=t(20),l=t(19),d=t(13);class h extends r.WebDataSource{constructor(t){super(t),this.interval=null,this.initialized=!1}destroy(){null!=this.interval&&clearInterval(this.interval),super.destroy()}setup(){if(!this.initialized&&(this.initialized=!0,this.get_data(this.mode),null!=this.polling_interval)){const t=()=>this.get_data(this.mode,this.max_size,this.if_modified);this.interval=setInterval(t,this.polling_interval)}}get_data(t,e=null,i=!1){const s=this.prepare_request();s.addEventListener(\"load\",(()=>this.do_load(s,t,null!=e?e:void 0))),s.addEventListener(\"error\",(()=>this.do_error(s))),s.send()}prepare_request(){const t=new XMLHttpRequest;t.open(this.method,this.data_url,!0),t.withCredentials=!1,t.setRequestHeader(\"Content-Type\",this.content_type);const e=this.http_headers;for(const[i,s]of(0,d.entries)(e))t.setRequestHeader(i,s);return t}do_load(t,e,i){if(200===t.status){const s=JSON.parse(t.responseText);this.load_data(s,e,i)}}do_error(t){l.logger.error(`Failed to fetch JSON from ${this.data_url} with code ${t.status}`)}}i.AjaxDataSource=h,n=h,h.__name__=\"AjaxDataSource\",n.define((({Boolean:t,Int:e,String:i,Dict:s,Nullable:a})=>({polling_interval:[a(e),null],content_type:[i,\"application/json\"],http_headers:[s(i),{}],method:[o.HTTPMethod,\"POST\"],if_modified:[t,!1]})))},\n", - " function _(e,t,o,r,n){var s;r();const a=e(70),i=e(19),l=e(9),c=e(13);function _(e){return null!=e?e:NaN}const{hasOwnProperty:g}=Object.prototype;class u extends a.ColumnarDataSource{constructor(e){super(e)}initialize(){super.initialize(),this._update_data()}connect_signals(){super.connect_signals(),this.connect(this.properties.geojson.change,(()=>this._update_data()))}_update_data(){this.data=this.geojson_to_column_data()}_get_new_list_array(e){return(0,l.range)(0,e).map((e=>[]))}_get_new_nan_array(e){return(0,l.range)(0,e).map((e=>NaN))}_add_properties(e,t,o,r){var n;const s=null!==(n=e.properties)&&void 0!==n?n:{};for(const[e,n]of(0,c.entries)(s))g.call(t,e)||(t[e]=this._get_new_nan_array(r)),t[e][o]=_(n)}_add_geometry(e,t,o){function r(e,t){return e.concat([[NaN,NaN,NaN]]).concat(t)}switch(e.type){case\"Point\":{const[r,n,s]=e.coordinates;t.x[o]=r,t.y[o]=n,t.z[o]=_(s);break}case\"LineString\":{const{coordinates:r}=e;for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\");const r=e.coordinates[0];for(let e=0;e1&&i.logger.warn(\"Bokeh does not support Polygons with holes in, only exterior ring used.\"),n.push(t[0]);const s=n.reduce(r);for(let e=0;e({geojson:[e]}))),s.internal((({Dict:e,Arrayable:t})=>({data:[e(t),{}]})))},\n", - " function _(e,r,T,o,S){o(),S(\"BBoxTileSource\",e(347).BBoxTileSource),S(\"MercatorTileSource\",e(348).MercatorTileSource),S(\"QUADKEYTileSource\",e(351).QUADKEYTileSource),S(\"TileRenderer\",e(352).TileRenderer),S(\"TileSource\",e(349).TileSource),S(\"TMSTileSource\",e(355).TMSTileSource),S(\"WMTSTileSource\",e(353).WMTSTileSource)},\n", - " function _(e,t,r,o,l){var i;o();const n=e(348);class s extends n.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars);let l,i,n,s;return this.use_latlon?[i,s,l,n]=this.get_tile_geographic_bounds(e,t,r):[i,s,l,n]=this.get_tile_meter_bounds(e,t,r),o.replace(\"{XMIN}\",i.toString()).replace(\"{YMIN}\",s.toString()).replace(\"{XMAX}\",l.toString()).replace(\"{YMAX}\",n.toString())}}r.BBoxTileSource=s,i=s,s.__name__=\"BBoxTileSource\",i.define((({Boolean:e})=>({use_latlon:[e,!1]})))},\n", - " function _(t,e,i,_,s){var r;_();const o=t(349),n=t(9),l=t(350);class u extends o.TileSource{constructor(t){super(t)}initialize(){super.initialize(),this._resolutions=(0,n.range)(this.min_zoom,this.max_zoom+1).map((t=>this.get_resolution(t)))}_computed_initial_resolution(){return null!=this.initial_resolution?this.initial_resolution:2*Math.PI*6378137/this.tile_size}is_valid_tile(t,e,i){return!(!this.wrap_around&&(t<0||t>=2**i))&&!(e<0||e>=2**i)}parent_by_tile_xyz(t,e,i){const _=this.tile_xyz_to_quadkey(t,e,i),s=_.substring(0,_.length-1);return this.quadkey_to_tile_xyz(s)}get_resolution(t){return this._computed_initial_resolution()/2**t}get_resolution_by_extent(t,e,i){return[(t[2]-t[0])/i,(t[3]-t[1])/e]}get_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s);let o=0;for(const t of this._resolutions){if(r>t){if(0==o)return 0;if(o>0)return o-1}o+=1}return o-1}get_closest_level_by_extent(t,e,i){const _=(t[2]-t[0])/i,s=(t[3]-t[1])/e,r=Math.max(_,s),o=this._resolutions.reduce((function(t,e){return Math.abs(e-r)e?(u=o-s,a*=t):(u*=e,a=n-r)}const h=(u-(o-s))/2,c=(a-(n-r))/2;return[s-h,r-c,o+h,n+c]}tms_to_wmts(t,e,i){return[t,2**i-1-e,i]}wmts_to_tms(t,e,i){return[t,2**i-1-e,i]}pixels_to_meters(t,e,i){const _=this.get_resolution(i);return[t*_-this.x_origin_offset,e*_-this.y_origin_offset]}meters_to_pixels(t,e,i){const _=this.get_resolution(i);return[(t+this.x_origin_offset)/_,(e+this.y_origin_offset)/_]}pixels_to_tile(t,e){let i=Math.ceil(t/this.tile_size);i=0===i?i:i-1;return[i,Math.max(Math.ceil(e/this.tile_size)-1,0)]}pixels_to_raster(t,e,i){return[t,(this.tile_size<=l;t--)for(let i=n;i<=u;i++)this.is_valid_tile(i,t,e)&&h.push([i,t,e,this.get_tile_meter_bounds(i,t,e)]);return this.sort_tiles_from_center(h,[n,l,u,a]),h}quadkey_to_tile_xyz(t){let e=0,i=0;const _=t.length;for(let s=_;s>0;s--){const r=1<0;s--){const i=1<0;)if(s=s.substring(0,s.length-1),[t,e,i]=this.quadkey_to_tile_xyz(s),[t,e,i]=this.denormalize_xyz(t,e,i,_),this.tiles.has(this.tile_xyz_to_key(t,e,i)))return[t,e,i];return[0,0,0]}normalize_xyz(t,e,i){if(this.wrap_around){const _=2**i;return[(t%_+_)%_,e,i]}return[t,e,i]}denormalize_xyz(t,e,i,_){return[t+_*2**i,e,i]}denormalize_meters(t,e,i,_){return[t+2*_*Math.PI*6378137,e]}calculate_world_x_by_tile_xyz(t,e,i){return Math.floor(t/2**i)}}i.MercatorTileSource=u,r=u,u.__name__=\"MercatorTileSource\",r.define((({Boolean:t})=>({snap_to_zoom:[t,!1],wrap_around:[t,!0]}))),r.override({x_origin_offset:20037508.34,y_origin_offset:20037508.34,initial_resolution:156543.03392804097})},\n", - " function _(e,t,r,i,n){var l;i();const a=e(53),s=e(13);class c extends a.Model{constructor(e){super(e)}initialize(){super.initialize(),this.tiles=new Map,this._normalize_case()}connect_signals(){super.connect_signals(),this.connect(this.change,(()=>this._clear_cache()))}string_lookup_replace(e,t){let r=e;for(const[e,i]of(0,s.entries)(t))r=r.replace(`{${e}}`,i);return r}_normalize_case(){const e=this.url.replace(\"{x}\",\"{X}\").replace(\"{y}\",\"{Y}\").replace(\"{z}\",\"{Z}\").replace(\"{q}\",\"{Q}\").replace(\"{xmin}\",\"{XMIN}\").replace(\"{ymin}\",\"{YMIN}\").replace(\"{xmax}\",\"{XMAX}\").replace(\"{ymax}\",\"{YMAX}\");this.url=e}_clear_cache(){this.tiles=new Map}tile_xyz_to_key(e,t,r){return`${e}:${t}:${r}`}key_to_tile_xyz(e){const[t,r,i]=e.split(\":\").map((e=>parseInt(e)));return[t,r,i]}sort_tiles_from_center(e,t){const[r,i,n,l]=t,a=(n-r)/2+r,s=(l-i)/2+i;e.sort((function(e,t){return Math.sqrt((a-e[0])**2+(s-e[1])**2)-Math.sqrt((a-t[0])**2+(s-t[1])**2)}))}get_image_url(e,t,r){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",t.toString()).replace(\"{Z}\",r.toString())}}r.TileSource=c,l=c,c.__name__=\"TileSource\",l.define((({Number:e,String:t,Dict:r,Nullable:i})=>({url:[t,\"\"],tile_size:[e,256],max_zoom:[e,30],min_zoom:[e,0],extra_url_vars:[r(t),{}],attribution:[t,\"\"],x_origin_offset:[e],y_origin_offset:[e],initial_resolution:[i(e),null]})))},\n", - " function _(t,e,r,n,o){n();const c=t(78);function _(t,e){return c.wgs84_mercator.compute(t,e)}function g(t,e){return c.wgs84_mercator.invert(t,e)}r.geographic_to_meters=_,r.meters_to_geographic=g,r.geographic_extent_to_meters=function(t){const[e,r,n,o]=t,[c,g]=_(e,r),[i,u]=_(n,o);return[c,g,i,u]},r.meters_extent_to_geographic=function(t){const[e,r,n,o]=t,[c,_]=g(e,r),[i,u]=g(n,o);return[c,_,i,u]}},\n", - " function _(e,t,r,s,_){s();const o=e(348);class c extends o.MercatorTileSource{constructor(e){super(e)}get_image_url(e,t,r){const s=this.string_lookup_replace(this.url,this.extra_url_vars),[_,o,c]=this.tms_to_wmts(e,t,r),i=this.tile_xyz_to_quadkey(_,o,c);return s.replace(\"{Q}\",i)}}r.QUADKEYTileSource=c,c.__name__=\"QUADKEYTileSource\"},\n", - " function _(t,e,i,s,_){s();const n=t(1);var a;const o=t(349),r=t(353),h=t(41),l=t(58),d=t(43),m=t(136),c=t(9),u=t(8),p=(0,n.__importStar)(t(354));class g extends h.RendererView{initialize(){this._tiles=[],super.initialize()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.request_render())),this.connect(this.model.tile_source.change,(()=>this.request_render()))}remove(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el),super.remove()}styles(){return[...super.styles(),p.default]}get_extent(){return[this.x_range.start,this.y_range.start,this.x_range.end,this.y_range.end]}get map_plot(){return this.plot_model}get map_canvas(){return this.layer.ctx}get map_frame(){return this.plot_view.frame}get x_range(){return this.map_plot.x_range}get y_range(){return this.map_plot.y_range}_set_data(){this.extent=this.get_extent(),this._last_height=void 0,this._last_width=void 0}_update_attribution(){null!=this.attribution_el&&(0,d.removeElement)(this.attribution_el);const{attribution:t}=this.model.tile_source;if((0,u.isString)(t)&&t.length>0){const{layout:e,frame:i}=this.plot_view,s=e.bbox.width-i.bbox.right,_=e.bbox.height-i.bbox.bottom,n=i.bbox.width;this.attribution_el=(0,d.div)({class:p.tile_attribution,style:{position:\"absolute\",right:`${s}px`,bottom:`${_}px`,\"max-width\":n-4+\"px\",padding:\"2px\",\"background-color\":\"rgba(255,255,255,0.5)\",\"font-size\":\"9px\",\"line-height\":\"1.05\",\"white-space\":\"nowrap\",overflow:\"hidden\",\"text-overflow\":\"ellipsis\"}}),this.plot_view.canvas_view.add_event(this.attribution_el),this.attribution_el.innerHTML=t,this.attribution_el.title=this.attribution_el.textContent.replace(/\\s*\\n\\s*/g,\" \")}}_map_data(){this.initial_extent=this.get_extent();const t=this.model.tile_source.get_level_by_extent(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width),e=this.model.tile_source.snap_to_zoom_level(this.initial_extent,this.map_frame.bbox.height,this.map_frame.bbox.width,t);this.x_range.start=e[0],this.y_range.start=e[1],this.x_range.end=e[2],this.y_range.end=e[3],this.x_range instanceof l.Range1d&&(this.x_range.reset_start=e[0],this.x_range.reset_end=e[2]),this.y_range instanceof l.Range1d&&(this.y_range.reset_start=e[1],this.y_range.reset_end=e[3]),this._update_attribution()}_create_tile(t,e,i,s,_=!1){const n=this.model.tile_source.tile_xyz_to_quadkey(t,e,i),a=this.model.tile_source.tile_xyz_to_key(t,e,i);if(this.model.tile_source.tiles.has(a))return;const[o,r,h]=this.model.tile_source.normalize_xyz(t,e,i),l=this.model.tile_source.get_image_url(o,r,h),d={img:void 0,tile_coords:[t,e,i],normalized_coords:[o,r,h],quadkey:n,cache_key:a,bounds:s,loaded:!1,finished:!1,x_coord:s[0],y_coord:s[3]};this.model.tile_source.tiles.set(a,d),this._tiles.push(d),new m.ImageLoader(l,{loaded:t=>{Object.assign(d,{img:t,loaded:!0}),_?(d.finished=!0,this.notify_finished()):this.request_render()},failed(){d.finished=!0}})}_enforce_aspect_ratio(){if(this._last_height!==this.map_frame.bbox.height||this._last_width!==this.map_frame.bbox.width){const t=this.get_extent(),e=this.model.tile_source.get_level_by_extent(t,this.map_frame.bbox.height,this.map_frame.bbox.width),i=this.model.tile_source.snap_to_zoom_level(t,this.map_frame.bbox.height,this.map_frame.bbox.width,e);this.x_range.setv({start:i[0],end:i[2]}),this.y_range.setv({start:i[1],end:i[3]}),this.extent=i,this._last_height=this.map_frame.bbox.height,this._last_width=this.map_frame.bbox.width}}has_finished(){if(!super.has_finished())return!1;if(0==this._tiles.length)return!1;for(const t of this._tiles)if(!t.finished)return!1;return!0}_render(){null==this.map_initialized&&(this._set_data(),this._map_data(),this.map_initialized=!0),this._enforce_aspect_ratio(),this._update(),null!=this.prefetch_timer&&clearTimeout(this.prefetch_timer),this.prefetch_timer=setTimeout(this._prefetch_tiles.bind(this),500),this.has_finished()&&this.notify_finished()}_draw_tile(t){const e=this.model.tile_source.tiles.get(t);if(null!=e&&e.loaded){const[[t],[i]]=this.coordinates.map_to_screen([e.bounds[0]],[e.bounds[3]]),[[s],[_]]=this.coordinates.map_to_screen([e.bounds[2]],[e.bounds[1]]),n=s-t,a=_-i,o=t,r=i,h=this.map_canvas.getImageSmoothingEnabled();this.map_canvas.setImageSmoothingEnabled(this.model.smoothing),this.map_canvas.drawImage(e.img,o,r,n,a),this.map_canvas.setImageSmoothingEnabled(h),e.finished=!0}}_set_rect(){const t=this.plot_model.outline_line_width,e=this.map_frame.bbox.left+t/2,i=this.map_frame.bbox.top+t/2,s=this.map_frame.bbox.width-t,_=this.map_frame.bbox.height-t;this.map_canvas.rect(e,i,s,_),this.map_canvas.clip()}_render_tiles(t){this.map_canvas.save(),this._set_rect(),this.map_canvas.globalAlpha=this.model.alpha;for(const e of t)this._draw_tile(e);this.map_canvas.restore()}_prefetch_tiles(){const{tile_source:t}=this.model,e=this.get_extent(),i=this.map_frame.bbox.height,s=this.map_frame.bbox.width,_=this.model.tile_source.get_level_by_extent(e,i,s),n=this.model.tile_source.get_tiles_by_extent(e,_);for(let e=0,i=Math.min(10,n.length);ei&&(s=this.extent,o=i,r=!0),r&&(this.x_range.setv({start:s[0],end:s[2]}),this.y_range.setv({start:s[1],end:s[3]})),this.extent=s;const h=t.get_tiles_by_extent(s,o),l=[],d=[],m=[],u=[];for(const e of h){const[i,s,n]=e,a=t.tile_xyz_to_key(i,s,n),o=t.tiles.get(a);if(null!=o&&o.loaded)d.push(a);else if(this.model.render_parents){const[e,a,o]=t.get_closest_parent_by_tile_xyz(i,s,n),r=t.tile_xyz_to_key(e,a,o),h=t.tiles.get(r);if(null!=h&&h.loaded&&!(0,c.includes)(m,r)&&m.push(r),_){const e=t.children_by_tile_xyz(i,s,n);for(const[i,s,_]of e){const e=t.tile_xyz_to_key(i,s,_);t.tiles.has(e)&&u.push(e)}}}null==o&&l.push(e)}this._render_tiles(m),this._render_tiles(u),this._render_tiles(d),null!=this.render_timer&&clearTimeout(this.render_timer),this.render_timer=setTimeout((()=>this._fetch_tiles(l)),65)}}i.TileRendererView=g,g.__name__=\"TileRendererView\";class b extends h.Renderer{constructor(t){super(t)}}i.TileRenderer=b,a=b,b.__name__=\"TileRenderer\",a.prototype.default_view=g,a.define((({Boolean:t,Number:e,Ref:i})=>({alpha:[e,1],smoothing:[t,!0],tile_source:[i(o.TileSource),()=>new r.WMTSTileSource],render_parents:[t,!0]}))),a.override({level:\"image\"})},\n", - " function _(t,e,r,o,s){o();const c=t(348);class i extends c.MercatorTileSource{constructor(t){super(t)}get_image_url(t,e,r){const o=this.string_lookup_replace(this.url,this.extra_url_vars),[s,c,i]=this.tms_to_wmts(t,e,r);return o.replace(\"{X}\",s.toString()).replace(\"{Y}\",c.toString()).replace(\"{Z}\",i.toString())}}r.WMTSTileSource=i,i.__name__=\"WMTSTileSource\"},\n", - " function _(t,o,i,b,r){b(),i.root=\"bk-root\",i.tile_attribution=\"bk-tile-attribution\",i.default=\".bk-root .bk-tile-attribution a{color:black;}\"},\n", - " function _(e,r,t,c,o){c();const i=e(348);class l extends i.MercatorTileSource{constructor(e){super(e)}get_image_url(e,r,t){return this.string_lookup_replace(this.url,this.extra_url_vars).replace(\"{X}\",e.toString()).replace(\"{Y}\",r.toString()).replace(\"{Z}\",t.toString())}}t.TMSTileSource=l,l.__name__=\"TMSTileSource\"},\n", - " function _(e,t,u,a,r){a(),r(\"CanvasTexture\",e(357).CanvasTexture),r(\"ImageURLTexture\",e(359).ImageURLTexture),r(\"Texture\",e(358).Texture)},\n", - " function _(t,e,n,c,s){var r;c();const o=t(358),a=t(34);class u extends o.Texture{constructor(t){super(t)}get func(){const t=(0,a.use_strict)(this.code);return new Function(\"ctx\",\"color\",\"scale\",\"weight\",t)}get_pattern(t,e,n){const c=document.createElement(\"canvas\");c.width=e,c.height=e;const s=c.getContext(\"2d\");return this.func.call(this,s,t,e,n),c}}n.CanvasTexture=u,r=u,u.__name__=\"CanvasTexture\",r.define((({String:t})=>({code:[t]})))},\n", - " function _(e,t,n,r,o){var i;r();const s=e(53),u=e(20);class c extends s.Model{constructor(e){super(e)}}n.Texture=c,i=c,c.__name__=\"Texture\",i.define((()=>({repetition:[u.TextureRepetition,\"repeat\"]})))},\n", - " function _(e,t,i,r,n){var a;r();const s=e(358),o=e(136);class u extends s.Texture{constructor(e){super(e)}initialize(){super.initialize(),this._loader=new o.ImageLoader(this.url)}get_pattern(e,t,i){const{_loader:r}=this;return this._loader.finished?r.image:r.promise}}i.ImageURLTexture=u,a=u,u.__name__=\"ImageURLTexture\",a.define((({String:e})=>({url:[e]})))},\n", - " function _(o,l,T,e,t){e(),t(\"ActionTool\",o(238).ActionTool),t(\"CustomAction\",o(361).CustomAction),t(\"HelpTool\",o(239).HelpTool),t(\"RedoTool\",o(362).RedoTool),t(\"ResetTool\",o(363).ResetTool),t(\"SaveTool\",o(364).SaveTool),t(\"UndoTool\",o(365).UndoTool),t(\"ZoomInTool\",o(366).ZoomInTool),t(\"ZoomOutTool\",o(369).ZoomOutTool),t(\"ButtonTool\",o(224).ButtonTool),t(\"EditTool\",o(370).EditTool),t(\"BoxEditTool\",o(371).BoxEditTool),t(\"FreehandDrawTool\",o(372).FreehandDrawTool),t(\"PointDrawTool\",o(373).PointDrawTool),t(\"PolyDrawTool\",o(374).PolyDrawTool),t(\"PolyTool\",o(375).PolyTool),t(\"PolyEditTool\",o(376).PolyEditTool),t(\"BoxSelectTool\",o(377).BoxSelectTool),t(\"BoxZoomTool\",o(379).BoxZoomTool),t(\"GestureTool\",o(223).GestureTool),t(\"LassoSelectTool\",o(380).LassoSelectTool),t(\"LineEditTool\",o(382).LineEditTool),t(\"PanTool\",o(384).PanTool),t(\"PolySelectTool\",o(381).PolySelectTool),t(\"RangeTool\",o(385).RangeTool),t(\"SelectTool\",o(378).SelectTool),t(\"TapTool\",o(386).TapTool),t(\"WheelPanTool\",o(387).WheelPanTool),t(\"WheelZoomTool\",o(388).WheelZoomTool),t(\"CrosshairTool\",o(389).CrosshairTool),t(\"CustomJSHover\",o(390).CustomJSHover),t(\"HoverTool\",o(391).HoverTool),t(\"InspectTool\",o(232).InspectTool),t(\"Tool\",o(222).Tool),t(\"ToolProxy\",o(394).ToolProxy),t(\"Toolbar\",o(221).Toolbar),t(\"ToolbarBase\",o(233).ToolbarBase),t(\"ProxyToolbar\",o(395).ProxyToolbar),t(\"ToolbarBox\",o(395).ToolbarBox)},\n", - " function _(t,o,e,s,n){var c;s();const i=t(238);class u extends i.ActionToolButtonView{css_classes(){return super.css_classes().concat(\"bk-toolbar-button-custom-action\")}}e.CustomActionButtonView=u,u.__name__=\"CustomActionButtonView\";class l extends i.ActionToolView{doit(){var t;null===(t=this.model.callback)||void 0===t||t.execute(this.model)}}e.CustomActionView=l,l.__name__=\"CustomActionView\";class a extends i.ActionTool{constructor(t){super(t),this.tool_name=\"Custom Action\",this.button_view=u}}e.CustomAction=a,c=a,a.__name__=\"CustomAction\",c.prototype.default_view=l,c.define((({Any:t,String:o,Nullable:e})=>({callback:[e(t)],icon:[o]}))),c.override({description:\"Perform a Custom Action\"})},\n", - " function _(e,o,t,i,s){var n;i();const l=e(238),_=e(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_redo))}doit(){const e=this.plot_view.state.redo();null!=(null==e?void 0:e.range)&&this.plot_view.trigger_ranges_update_event()}}t.RedoToolView=d,d.__name__=\"RedoToolView\";class a extends l.ActionTool{constructor(e){super(e),this.tool_name=\"Redo\",this.icon=_.tool_icon_redo}}t.RedoTool=a,n=a,a.__name__=\"RedoTool\",n.prototype.default_view=d,n.override({disabled:!0}),n.register_alias(\"redo\",(()=>new a))},\n", - " function _(e,o,t,s,i){var _;s();const n=e(238),l=e(228);class c extends n.ActionToolView{doit(){this.plot_view.reset()}}t.ResetToolView=c,c.__name__=\"ResetToolView\";class r extends n.ActionTool{constructor(e){super(e),this.tool_name=\"Reset\",this.icon=l.tool_icon_reset}}t.ResetTool=r,_=r,r.__name__=\"ResetTool\",_.prototype.default_view=c,_.register_alias(\"reset\",(()=>new r))},\n", - " function _(e,o,t,a,i){var s;a();const c=e(238),n=e(228);class l extends c.ActionToolView{async copy(){const e=await this.plot_view.to_blob(),o=new ClipboardItem({[e.type]:Promise.resolve(e)});await navigator.clipboard.write([o])}async save(e){const o=await this.plot_view.to_blob(),t=document.createElement(\"a\");t.href=URL.createObjectURL(o),t.download=e,t.target=\"_blank\",t.dispatchEvent(new MouseEvent(\"click\"))}doit(e=\"save\"){switch(e){case\"save\":this.save(\"bokeh_plot\");break;case\"copy\":this.copy()}}}t.SaveToolView=l,l.__name__=\"SaveToolView\";class r extends c.ActionTool{constructor(e){super(e),this.tool_name=\"Save\",this.icon=n.tool_icon_save}get menu(){return[{icon:\"bk-tool-icon-copy-to-clipboard\",tooltip:\"Copy image to clipboard\",if:()=>\"undefined\"!=typeof ClipboardItem,handler:()=>{this.do.emit(\"copy\")}}]}}t.SaveTool=r,s=r,r.__name__=\"SaveTool\",s.prototype.default_view=l,s.register_alias(\"save\",(()=>new r))},\n", - " function _(o,e,t,n,i){var s;n();const l=o(238),_=o(228);class d extends l.ActionToolView{connect_signals(){super.connect_signals(),this.connect(this.plot_view.state.changed,(()=>this.model.disabled=!this.plot_view.state.can_undo))}doit(){const o=this.plot_view.state.undo();null!=(null==o?void 0:o.range)&&this.plot_view.trigger_ranges_update_event()}}t.UndoToolView=d,d.__name__=\"UndoToolView\";class a extends l.ActionTool{constructor(o){super(o),this.tool_name=\"Undo\",this.icon=_.tool_icon_undo}}t.UndoTool=a,s=a,a.__name__=\"UndoTool\",s.prototype.default_view=d,s.override({disabled:!0}),s.register_alias(\"undo\",(()=>new a))},\n", - " function _(o,n,e,i,s){var t;i();const _=o(367),m=o(228);class a extends _.ZoomBaseToolView{}e.ZoomInToolView=a,a.__name__=\"ZoomInToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=1,this.tool_name=\"Zoom In\",this.icon=m.tool_icon_zoom_in}}e.ZoomInTool=l,t=l,l.__name__=\"ZoomInTool\",t.prototype.default_view=a,t.register_alias(\"zoom_in\",(()=>new l({dimensions:\"both\"}))),t.register_alias(\"xzoom_in\",(()=>new l({dimensions:\"width\"}))),t.register_alias(\"yzoom_in\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(o,t,e,i,s){var n;i();const a=o(238),_=o(20),l=o(368);class m extends a.ActionToolView{doit(){var o;const t=this.plot_view.frame,e=this.model.dimensions,i=\"width\"==e||\"both\"==e,s=\"height\"==e||\"both\"==e,n=(0,l.scale_range)(t,this.model.sign*this.model.factor,i,s);this.plot_view.state.push(\"zoom_out\",{range:n}),this.plot_view.update_range(n,{scrolling:!0,maintain_focus:this.model.maintain_focus}),null===(o=this.model.document)||void 0===o||o.interactive_start(this.plot_model),this.plot_view.trigger_ranges_update_event()}}e.ZoomBaseToolView=m,m.__name__=\"ZoomBaseToolView\";class h extends a.ActionTool{constructor(o){super(o),this.maintain_focus=!0}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.ZoomBaseTool=h,n=h,h.__name__=\"ZoomBaseTool\",n.define((({Percent:o})=>({factor:[o,.1],dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(n,t,o,r,s){r();const c=n(10);function e(n,t,o){const[r,s]=[n.start,n.end],c=null!=o?o:(s+r)/2;return[r-(r-c)*t,s-(s-c)*t]}function a(n,[t,o]){const r=new Map;for(const[s,c]of n){const[n,e]=c.r_invert(t,o);r.set(s,{start:n,end:e})}return r}o.scale_highlow=e,o.get_info=a,o.scale_range=function(n,t,o=!0,r=!0,s){t=(0,c.clamp)(t,-.9,.9);const l=o?t:0,[u,i]=e(n.bbox.h_range,l,null!=s?s.x:void 0),_=a(n.x_scales,[u,i]),f=r?t:0,[g,x]=e(n.bbox.v_range,f,null!=s?s.y:void 0);return{xrs:_,yrs:a(n.y_scales,[g,x]),factor:t}}},\n", - " function _(o,e,t,i,s){var n;i();const _=o(367),a=o(228);class m extends _.ZoomBaseToolView{}t.ZoomOutToolView=m,m.__name__=\"ZoomOutToolView\";class l extends _.ZoomBaseTool{constructor(o){super(o),this.sign=-1,this.tool_name=\"Zoom Out\",this.icon=a.tool_icon_zoom_out}}t.ZoomOutTool=l,n=l,l.__name__=\"ZoomOutTool\",n.prototype.default_view=m,n.define((({Boolean:o})=>({maintain_focus:[o,!0]}))),n.register_alias(\"zoom_out\",(()=>new l({dimensions:\"both\"}))),n.register_alias(\"xzoom_out\",(()=>new l({dimensions:\"width\"}))),n.register_alias(\"yzoom_out\",(()=>new l({dimensions:\"height\"})))},\n", - " function _(e,t,s,o,n){var r;o();const i=e(9),c=e(8),a=e(11),_=e(175),l=e(223);class d extends l.GestureToolView{constructor(){super(...arguments),this._mouse_in_frame=!0}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,a.unreachable)():\"replace\"}_move_enter(e){this._mouse_in_frame=!0}_move_exit(e){this._mouse_in_frame=!1}_map_drag(e,t,s){if(!this.plot_view.frame.bbox.contains(e,t))return null;const o=this.plot_view.renderer_view(s);if(null==o)return null;return[o.coordinates.x_scale.invert(e),o.coordinates.y_scale.invert(t)]}_delete_selected(e){const t=e.data_source,s=t.selected.indices;s.sort();for(const e of t.columns()){const o=t.get_array(e);for(let e=0;e({custom_icon:[n(t),null],empty_value:[e],renderers:[s(o(_.GlyphRenderer)),[]]})))},\n", - " function _(e,t,s,i,_){var o;i();const n=e(43),a=e(20),d=e(370),l=e(228);class r extends d.EditToolView{_tap(e){null==this._draw_basepoint&&null==this._basepoint&&this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)if(e.keyCode===n.Keys.Backspace)this._delete_selected(t);else if(e.keyCode==n.Keys.Esc){t.data_source.selection_manager.clear()}}_set_extent([e,t],[s,i],_,o=!1){const n=this.model.renderers[0],a=this.plot_view.renderer_view(n);if(null==a)return;const d=n.glyph,l=n.data_source,[r,h]=a.coordinates.x_scale.r_invert(e,t),[p,u]=a.coordinates.y_scale.r_invert(s,i),[c,m]=[(r+h)/2,(p+u)/2],[f,b]=[h-r,u-p],[y,x]=[d.x.field,d.y.field],[w,v]=[d.width.field,d.height.field];if(_)this._pop_glyphs(l,this.model.num_objects),y&&l.get_array(y).push(c),x&&l.get_array(x).push(m),w&&l.get_array(w).push(f),v&&l.get_array(v).push(b),this._pad_empty_columns(l,[y,x,w,v]);else{const e=l.data[y].length-1;y&&(l.data[y][e]=c),x&&(l.data[x][e]=m),w&&(l.data[w][e]=f),v&&(l.data[v][e]=b)}this._emit_cds_changes(l,!0,!1,o)}_update_box(e,t=!1,s=!1){if(null==this._draw_basepoint)return;const i=[e.sx,e.sy],_=this.plot_view.frame,o=this.model.dimensions,n=this.model._get_dim_limits(this._draw_basepoint,i,_,o);if(null!=n){const[e,i]=n;this._set_extent(e,i,t,s)}}_doubletap(e){this.model.active&&(null!=this._draw_basepoint?(this._update_box(e,!1,!0),this._draw_basepoint=null):(this._draw_basepoint=[e.sx,e.sy],this._select_event(e,\"append\",this.model.renderers),this._update_box(e,!0,!1)))}_move(e){this._update_box(e,!1,!1)}_pan_start(e){if(e.shiftKey){if(null!=this._draw_basepoint)return;this._draw_basepoint=[e.sx,e.sy],this._update_box(e,!0,!1)}else{if(null!=this._basepoint)return;this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy]}}_pan(e,t=!1,s=!1){if(e.shiftKey){if(null==this._draw_basepoint)return;this._update_box(e,t,s)}else{if(null==this._basepoint)return;this._drag_points(e,this.model.renderers)}}_pan_end(e){if(this._pan(e,!1,!0),e.shiftKey)this._draw_basepoint=null;else{this._basepoint=null;for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0)}}}s.BoxEditToolView=r,r.__name__=\"BoxEditToolView\";class h extends d.EditTool{constructor(e){super(e),this.tool_name=\"Box Edit Tool\",this.icon=l.tool_icon_box_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=1}}s.BoxEditTool=h,o=h,h.__name__=\"BoxEditTool\",o.prototype.default_view=r,o.define((({Int:e})=>({dimensions:[a.Dimensions,\"both\"],num_objects:[e,0]})))},\n", - " function _(e,t,a,s,r){var _;s();const d=e(43),o=e(8),n=e(370),i=e(228);class l extends n.EditToolView{_draw(e,t,a=!1){if(!this.model.active)return;const s=this.model.renderers[0],r=this._map_drag(e.sx,e.sy,s);if(null==r)return;const[_,d]=r,n=s.data_source,i=s.glyph,[l,h]=[i.xs.field,i.ys.field];if(\"new\"==t)this._pop_glyphs(n,this.model.num_objects),l&&n.get_array(l).push([_]),h&&n.get_array(h).push([d]),this._pad_empty_columns(n,[l,h]);else if(\"add\"==t){if(l){const e=n.data[l].length-1;let t=n.get_array(l)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[l][e]=t),t.push(_)}if(h){const e=n.data[h].length-1;let t=n.get_array(h)[e];(0,o.isArray)(t)||(t=Array.from(t),n.data[h][e]=t),t.push(d)}}this._emit_cds_changes(n,!0,!0,a)}_pan_start(e){this._draw(e,\"new\")}_pan(e){this._draw(e,\"add\")}_pan_end(e){this._draw(e,\"add\",!0)}_tap(e){this._select_event(e,this._select_mode(e),this.model.renderers)}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===d.Keys.Esc?t.data_source.selection_manager.clear():e.keyCode===d.Keys.Backspace&&this._delete_selected(t)}}a.FreehandDrawToolView=l,l.__name__=\"FreehandDrawToolView\";class h extends n.EditTool{constructor(e){super(e),this.tool_name=\"Freehand Draw Tool\",this.icon=i.tool_icon_freehand_draw,this.event_type=[\"pan\",\"tap\"],this.default_order=3}}a.FreehandDrawTool=h,_=h,h.__name__=\"FreehandDrawTool\",_.prototype.default_view=l,_.define((({Int:e})=>({num_objects:[e,0]}))),_.register_alias(\"freehand_draw\",(()=>new h))},\n", - " function _(e,t,s,o,a){var i;o();const n=e(43),_=e(370),r=e(228);class d extends _.EditToolView{_tap(e){if(this._select_event(e,this._select_mode(e),this.model.renderers).length||!this.model.add)return;const t=this.model.renderers[0],s=this._map_drag(e.sx,e.sy,t);if(null==s)return;const o=t.glyph,a=t.data_source,[i,n]=[o.x.field,o.y.field],[_,r]=s;this._pop_glyphs(a,this.model.num_objects),i&&a.get_array(i).push(_),n&&a.get_array(n).push(r),this._pad_empty_columns(a,[i,n]),a.change.emit(),a.data=a.data,a.properties.data.change.emit()}_keyup(e){if(this.model.active&&this._mouse_in_frame)for(const t of this.model.renderers)e.keyCode===n.Keys.Backspace?this._delete_selected(t):e.keyCode==n.Keys.Esc&&t.data_source.selection_manager.clear()}_pan_start(e){this.model.drag&&(this._select_event(e,\"append\",this.model.renderers),this._basepoint=[e.sx,e.sy])}_pan(e){this.model.drag&&null!=this._basepoint&&this._drag_points(e,this.model.renderers)}_pan_end(e){if(this.model.drag){this._pan(e);for(const e of this.model.renderers)this._emit_cds_changes(e.data_source,!1,!0,!0);this._basepoint=null}}}s.PointDrawToolView=d,d.__name__=\"PointDrawToolView\";class l extends _.EditTool{constructor(e){super(e),this.tool_name=\"Point Draw Tool\",this.icon=r.tool_icon_point_draw,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=2}}s.PointDrawTool=l,i=l,l.__name__=\"PointDrawTool\",i.prototype.default_view=d,i.define((({Boolean:e,Int:t})=>({add:[e,!0],drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,t,s,i,a){var r;i();const o=e(43),n=e(8),d=e(375),_=e(228);class h extends d.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._initialized=!1}_tap(e){this._drawing?this._draw(e,\"add\",!0):this._select_event(e,this._select_mode(e),this.model.renderers)}_draw(e,t,s=!1){const i=this.model.renderers[0],a=this._map_drag(e.sx,e.sy,i);if(this._initialized||this.activate(),null==a)return;const[r,o]=this._snap_to_vertex(e,...a),d=i.data_source,_=i.glyph,[h,l]=[_.xs.field,_.ys.field];if(\"new\"==t)this._pop_glyphs(d,this.model.num_objects),h&&d.get_array(h).push([r,r]),l&&d.get_array(l).push([o,o]),this._pad_empty_columns(d,[h,l]);else if(\"edit\"==t){if(h){const e=d.data[h][d.data[h].length-1];e[e.length-1]=r}if(l){const e=d.data[l][d.data[l].length-1];e[e.length-1]=o}}else if(\"add\"==t){if(h){const e=d.data[h].length-1;let t=d.get_array(h)[e];const s=t[t.length-1];t[t.length-1]=r,(0,n.isArray)(t)||(t=Array.from(t),d.data[h][e]=t),t.push(s)}if(l){const e=d.data[l].length-1;let t=d.get_array(l)[e];const s=t[t.length-1];t[t.length-1]=o,(0,n.isArray)(t)||(t=Array.from(t),d.data[l][e]=t),t.push(s)}}this._emit_cds_changes(d,!0,!1,s)}_show_vertices(){if(!this.model.active)return;const e=[],t=[];for(let s=0;sthis._show_vertices()))}this._initialized=!0}}deactivate(){this._drawing&&(this._remove(),this._drawing=!1),this.model.vertex_renderer&&this._hide_vertices()}}s.PolyDrawToolView=h,h.__name__=\"PolyDrawToolView\";class l extends d.PolyTool{constructor(e){super(e),this.tool_name=\"Polygon Draw Tool\",this.icon=_.tool_icon_poly_draw,this.event_type=[\"pan\",\"tap\",\"move\"],this.default_order=3}}s.PolyDrawTool=l,r=l,l.__name__=\"PolyDrawTool\",r.prototype.default_view=h,r.define((({Boolean:e,Int:t})=>({drag:[e,!0],num_objects:[t,0]})))},\n", - " function _(e,r,t,s,o){var _;s();const d=e(8),i=e(370);class l extends i.EditToolView{_set_vertices(e,r){const t=this.model.vertex_renderer.glyph,s=this.model.vertex_renderer.data_source,[o,_]=[t.x.field,t.y.field];o&&((0,d.isArray)(e)?s.data[o]=e:t.x={value:e}),_&&((0,d.isArray)(r)?s.data[_]=r:t.y={value:r}),this._emit_cds_changes(s,!0,!0,!1)}_hide_vertices(){this._set_vertices([],[])}_snap_to_vertex(e,r,t){if(this.model.vertex_renderer){const s=this._select_event(e,\"replace\",[this.model.vertex_renderer]),o=this.model.vertex_renderer.data_source,_=this.model.vertex_renderer.glyph,[d,i]=[_.x.field,_.y.field];if(s.length){const e=o.selected.indices[0];d&&(r=o.data[d][e]),i&&(t=o.data[i][e]),o.selection_manager.clear()}}return[r,t]}}t.PolyToolView=l,l.__name__=\"PolyToolView\";class n extends i.EditTool{constructor(e){super(e)}}t.PolyTool=n,_=n,n.__name__=\"PolyTool\",_.define((({AnyRef:e})=>({vertex_renderer:[e()]})))},\n", - " function _(e,t,s,r,i){var _;r();const d=e(43),n=e(8),l=e(375),a=e(228);class c extends l.PolyToolView{constructor(){super(...arguments),this._drawing=!1,this._cur_index=null}_doubletap(e){if(!this.model.active)return;const t=this._map_drag(e.sx,e.sy,this.model.vertex_renderer);if(null==t)return;const[s,r]=t,i=this._select_event(e,\"replace\",[this.model.vertex_renderer]),_=this.model.vertex_renderer.data_source,d=this.model.vertex_renderer.glyph,[n,l]=[d.x.field,d.y.field];if(i.length&&null!=this._selected_renderer){const e=_.selected.indices[0];this._drawing?(this._drawing=!1,_.selection_manager.clear()):(_.selected.indices=[e+1],n&&_.get_array(n).splice(e+1,0,s),l&&_.get_array(l).splice(e+1,0,r),this._drawing=!0),_.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}else this._show_vertices(e)}_show_vertices(e){if(!this.model.active)return;const t=this.model.renderers[0],s=()=>this._update_vertices(t),r=null==t?void 0:t.data_source,i=this._select_event(e,\"replace\",this.model.renderers);if(!i.length)return this._set_vertices([],[]),this._selected_renderer=null,this._drawing=!1,this._cur_index=null,void(null!=r&&r.disconnect(r.properties.data.change,s));null!=r&&r.connect(r.properties.data.change,s),this._cur_index=i[0].data_source.selected.indices[0],this._update_vertices(i[0])}_update_vertices(e){const t=e.glyph,s=e.data_source,r=this._cur_index,[i,_]=[t.xs.field,t.ys.field];if(this._drawing)return;if(null==r&&(i||_))return;let d,l;i&&null!=r?(d=s.data[i][r],(0,n.isArray)(d)||(s.data[i][r]=d=Array.from(d))):d=t.xs.value,_&&null!=r?(l=s.data[_][r],(0,n.isArray)(l)||(s.data[_][r]=l=Array.from(l))):l=t.ys.value,this._selected_renderer=e,this._set_vertices(d,l)}_move(e){if(this._drawing&&null!=this._selected_renderer){const t=this.model.vertex_renderer,s=t.data_source,r=t.glyph,i=this._map_drag(e.sx,e.sy,t);if(null==i)return;let[_,d]=i;const n=s.selected.indices;[_,d]=this._snap_to_vertex(e,_,d),s.selected.indices=n;const[l,a]=[r.x.field,r.y.field],c=n[0];l&&(s.data[l][c]=_),a&&(s.data[a][c]=d),s.change.emit(),this._selected_renderer.data_source.change.emit()}}_tap(e){const t=this.model.vertex_renderer,s=this._map_drag(e.sx,e.sy,t);if(null==s)return;if(this._drawing&&this._selected_renderer){let[r,i]=s;const _=t.data_source,d=t.glyph,[n,l]=[d.x.field,d.y.field],a=_.selected.indices;[r,i]=this._snap_to_vertex(e,r,i);const c=a[0];if(_.selected.indices=[c+1],n){const e=_.get_array(n),t=e[c];e[c]=r,e.splice(c+1,0,t)}if(l){const e=_.get_array(l),t=e[c];e[c]=i,e.splice(c+1,0,t)}return _.change.emit(),void this._emit_cds_changes(this._selected_renderer.data_source,!0,!1,!0)}const r=this._select_mode(e);this._select_event(e,r,[t]),this._select_event(e,r,this.model.renderers)}_remove_vertex(){if(!this._drawing||!this._selected_renderer)return;const e=this.model.vertex_renderer,t=e.data_source,s=e.glyph,r=t.selected.indices[0],[i,_]=[s.x.field,s.y.field];i&&t.get_array(i).splice(r,1),_&&t.get_array(_).splice(r,1),t.change.emit(),this._emit_cds_changes(this._selected_renderer.data_source)}_pan_start(e){this._select_event(e,\"append\",[this.model.vertex_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.vertex_renderer]),this._emit_cds_changes(this.model.vertex_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}_keyup(e){if(!this.model.active||!this._mouse_in_frame)return;let t;t=this._selected_renderer?[this.model.vertex_renderer]:this.model.renderers;for(const s of t)e.keyCode===d.Keys.Backspace?(this._delete_selected(s),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source)):e.keyCode==d.Keys.Esc&&(this._drawing?(this._remove_vertex(),this._drawing=!1):this._selected_renderer&&this._hide_vertices(),s.data_source.selection_manager.clear())}deactivate(){this._selected_renderer&&(this._drawing&&(this._remove_vertex(),this._drawing=!1),this._hide_vertices())}}s.PolyEditToolView=c,c.__name__=\"PolyEditToolView\";class o extends l.PolyTool{constructor(e){super(e),this.tool_name=\"Poly Edit Tool\",this.icon=a.tool_icon_poly_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}}s.PolyEditTool=o,_=o,o.__name__=\"PolyEditTool\",_.prototype.default_view=c},\n", - " function _(e,t,o,s,i){var l;s();const n=e(378),_=e(116),c=e(20),r=e(228);class a extends n.SelectToolView{_compute_limits(e){const t=this.plot_view.frame,o=this.model.dimensions;let s=this._base_point;if(\"center\"==this.model.origin){const[t,o]=s,[i,l]=e;s=[t-(i-t),o-(l-o)]}return this.model._get_dim_limits(s,e,t,o)}_pan_start(e){const{sx:t,sy:o}=e;this._base_point=[t,o]}_pan(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this.model.overlay.update({left:i[0],right:i[1],top:l[0],bottom:l[1]}),this.model.select_every_mousemove&&this._do_select(i,l,!1,this._select_mode(e))}_pan_end(e){const{sx:t,sy:o}=e,s=[t,o],[i,l]=this._compute_limits(s);this._do_select(i,l,!0,this._select_mode(e)),this.model.overlay.update({left:null,right:null,top:null,bottom:null}),this._base_point=null,this.plot_view.state.push(\"box_select\",{selection:this.plot_view.get_selection()})}_do_select([e,t],[o,s],i,l=\"replace\"){const n={type:\"rect\",sx0:e,sx1:t,sy0:o,sy1:s};this._select(n,i,l)}}o.BoxSelectToolView=a,a.__name__=\"BoxSelectToolView\";const h=()=>new _.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends n.SelectTool{constructor(e){super(e),this.tool_name=\"Box Select\",this.icon=r.tool_icon_box_select,this.event_type=\"pan\",this.default_order=30}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}o.BoxSelectTool=m,l=m,m.__name__=\"BoxSelectTool\",l.prototype.default_view=a,l.define((({Boolean:e,Ref:t})=>({dimensions:[c.Dimensions,\"both\"],select_every_mousemove:[e,!1],overlay:[t(_.BoxAnnotation),h],origin:[c.BoxOrigin,\"corner\"]}))),l.register_alias(\"box_select\",(()=>new m)),l.register_alias(\"xbox_select\",(()=>new m({dimensions:\"width\"}))),l.register_alias(\"ybox_select\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(e,t,s,n,r){var o;n();const c=e(223),i=e(175),a=e(339),l=e(176),d=e(66),_=e(20),h=e(43),p=e(251),u=e(15),m=e(11);class v extends c.GestureToolView{connect_signals(){super.connect_signals(),this.model.clear.connect((()=>this._clear()))}get computed_renderers(){const{renderers:e,names:t}=this.model,s=this.plot_model.data_renderers;return(0,d.compute_renderers)(e,s,t)}_computed_renderers_by_data_source(){var e;const t=new Map;for(const s of this.computed_renderers){let n;if(s instanceof i.GlyphRenderer)n=s.data_source;else{if(!(s instanceof a.GraphRenderer))continue;n=s.node_renderer.data_source}const r=null!==(e=t.get(n))&&void 0!==e?e:[];t.set(n,[...r,s])}return t}_select_mode(e){const{shiftKey:t,ctrlKey:s}=e;return t||s?t&&!s?\"append\":!t&&s?\"intersect\":t&&s?\"subtract\":void(0,m.unreachable)():this.model.mode}_keyup(e){e.keyCode==h.Keys.Esc&&this._clear()}_clear(){for(const e of this.computed_renderers)e.get_selection_manager().clear();const e=this.computed_renderers.map((e=>this.plot_view.renderer_view(e)));this.plot_view.request_paint(e)}_select(e,t,s){const n=this._computed_renderers_by_data_source();for(const[,r]of n){const n=r[0].get_selection_manager(),o=[];for(const e of r){const t=this.plot_view.renderer_view(e);null!=t&&o.push(t)}n.select(o,e,t,s)}null!=this.model.callback&&this._emit_callback(e),this._emit_selection_event(e,t)}_emit_selection_event(e,t=!0){const{x_scale:s,y_scale:n}=this.plot_view.frame;let r;switch(e.type){case\"point\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"span\":{const{sx:t,sy:o}=e,c=s.invert(t),i=n.invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}case\"rect\":{const{sx0:t,sx1:o,sy0:c,sy1:i}=e,[a,l]=s.r_invert(t,o),[d,_]=n.r_invert(c,i);r=Object.assign(Object.assign({},e),{x0:a,y0:d,x1:l,y1:_});break}case\"poly\":{const{sx:t,sy:o}=e,c=s.v_invert(t),i=n.v_invert(o);r=Object.assign(Object.assign({},e),{x:c,y:i});break}}this.plot_model.trigger_event(new p.SelectionGeometry(r,t))}}s.SelectToolView=v,v.__name__=\"SelectToolView\";class b extends c.GestureTool{constructor(e){super(e)}initialize(){super.initialize(),this.clear=new u.Signal0(this,\"clear\")}get menu(){return[{icon:\"bk-tool-icon-replace-mode\",tooltip:\"Replace the current selection\",active:()=>\"replace\"==this.mode,handler:()=>{this.mode=\"replace\",this.active=!0}},{icon:\"bk-tool-icon-append-mode\",tooltip:\"Append to the current selection (Shift)\",active:()=>\"append\"==this.mode,handler:()=>{this.mode=\"append\",this.active=!0}},{icon:\"bk-tool-icon-intersect-mode\",tooltip:\"Intersect with the current selection (Ctrl)\",active:()=>\"intersect\"==this.mode,handler:()=>{this.mode=\"intersect\",this.active=!0}},{icon:\"bk-tool-icon-subtract-mode\",tooltip:\"Subtract from the current selection (Shift+Ctrl)\",active:()=>\"subtract\"==this.mode,handler:()=>{this.mode=\"subtract\",this.active=!0}},null,{icon:\"bk-tool-icon-clear-selection\",tooltip:\"Clear the current selection (Esc)\",handler:()=>{this.clear.emit()}}]}}s.SelectTool=b,o=b,b.__name__=\"SelectTool\",o.define((({String:e,Array:t,Ref:s,Or:n,Auto:r})=>({renderers:[n(t(s(l.DataRenderer)),r),\"auto\"],names:[t(e),[]],mode:[_.SelectionMode,\"replace\"]})))},\n", - " function _(t,o,e,s,i){var n;s();const _=t(223),a=t(116),l=t(20),r=t(228);class h extends _.GestureToolView{_match_aspect(t,o,e){const s=e.bbox.aspect,i=e.bbox.h_range.end,n=e.bbox.h_range.start,_=e.bbox.v_range.end,a=e.bbox.v_range.start;let l=Math.abs(t[0]-o[0]),r=Math.abs(t[1]-o[1]);const h=0==r?0:l/r,[c]=h>=s?[1,h/s]:[s/h,1];let m,p,d,b;return t[0]<=o[0]?(m=t[0],p=t[0]+l*c,p>i&&(p=i)):(p=t[0],m=t[0]-l*c,m_&&(d=_)):(d=t[1],b=t[1]-l/s,bnew a.BoxAnnotation({level:\"overlay\",top_units:\"screen\",left_units:\"screen\",bottom_units:\"screen\",right_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class m extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Box Zoom\",this.icon=r.tool_icon_box_zoom,this.event_type=\"pan\",this.default_order=20}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}e.BoxZoomTool=m,n=m,m.__name__=\"BoxZoomTool\",n.prototype.default_view=h,n.define((({Boolean:t,Ref:o})=>({dimensions:[l.Dimensions,\"both\"],overlay:[o(a.BoxAnnotation),c],match_aspect:[t,!1],origin:[l.BoxOrigin,\"corner\"]}))),n.register_alias(\"box_zoom\",(()=>new m({dimensions:\"both\"}))),n.register_alias(\"xbox_zoom\",(()=>new m({dimensions:\"width\"}))),n.register_alias(\"ybox_zoom\",(()=>new m({dimensions:\"height\"})))},\n", - " function _(s,e,t,o,_){var l;o();const i=s(378),a=s(217),c=s(381),n=s(43),h=s(228);class r extends i.SelectToolView{constructor(){super(...arguments),this.sxs=[],this.sys=[]}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_overlay()}_keyup(s){s.keyCode==n.Keys.Enter&&this._clear_overlay()}_pan_start(s){this.sxs=[],this.sys=[];const{sx:e,sy:t}=s;this._append_overlay(e,t)}_pan(s){const[e,t]=this.plot_view.frame.bbox.clip(s.sx,s.sy);this._append_overlay(e,t),this.model.select_every_mousemove&&this._do_select(this.sxs,this.sys,!1,this._select_mode(s))}_pan_end(s){const{sxs:e,sys:t}=this;this._clear_overlay(),this._do_select(e,t,!0,this._select_mode(s)),this.plot_view.state.push(\"lasso_select\",{selection:this.plot_view.get_selection()})}_append_overlay(s,e){const{sxs:t,sys:o}=this;t.push(s),o.push(e),this.model.overlay.update({xs:t,ys:o})}_clear_overlay(){this.sxs=[],this.sys=[],this.model.overlay.update({xs:this.sxs,ys:this.sys})}_do_select(s,e,t,o){const _={type:\"poly\",sx:s,sy:e};this._select(_,t,o)}}t.LassoSelectToolView=r,r.__name__=\"LassoSelectToolView\";class y extends i.SelectTool{constructor(s){super(s),this.tool_name=\"Lasso Select\",this.icon=h.tool_icon_lasso_select,this.event_type=\"pan\",this.default_order=12}}t.LassoSelectTool=y,l=y,y.__name__=\"LassoSelectTool\",l.prototype.default_view=r,l.define((({Boolean:s,Ref:e})=>({select_every_mousemove:[s,!0],overlay:[e(a.PolyAnnotation),c.DEFAULT_POLY_OVERLAY]}))),l.register_alias(\"lasso_select\",(()=>new y))},\n", - " function _(e,t,s,l,o){var i;l();const a=e(378),_=e(217),c=e(43),n=e(9),h=e(228);class y extends a.SelectToolView{initialize(){super.initialize(),this.data={sx:[],sy:[]}}connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._active_change()))}_active_change(){this.model.active||this._clear_data()}_keyup(e){e.keyCode==c.Keys.Enter&&this._clear_data()}_doubletap(e){this._do_select(this.data.sx,this.data.sy,!0,this._select_mode(e)),this.plot_view.state.push(\"poly_select\",{selection:this.plot_view.get_selection()}),this._clear_data()}_clear_data(){this.data={sx:[],sy:[]},this.model.overlay.update({xs:[],ys:[]})}_tap(e){const{sx:t,sy:s}=e;this.plot_view.frame.bbox.contains(t,s)&&(this.data.sx.push(t),this.data.sy.push(s),this.model.overlay.update({xs:(0,n.copy)(this.data.sx),ys:(0,n.copy)(this.data.sy)}))}_do_select(e,t,s,l){const o={type:\"poly\",sx:e,sy:t};this._select(o,s,l)}}s.PolySelectToolView=y,y.__name__=\"PolySelectToolView\";s.DEFAULT_POLY_OVERLAY=()=>new _.PolyAnnotation({level:\"overlay\",xs_units:\"screen\",ys_units:\"screen\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:2,line_dash:[4,4]});class d extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Poly Select\",this.icon=h.tool_icon_polygon_select,this.event_type=\"tap\",this.default_order=11}}s.PolySelectTool=d,i=d,d.__name__=\"PolySelectTool\",i.prototype.default_view=y,i.define((({Ref:e})=>({overlay:[e(_.PolyAnnotation),s.DEFAULT_POLY_OVERLAY]}))),i.register_alias(\"poly_select\",(()=>new d))},\n", - " function _(e,t,s,i,r){var n;i();const _=e(20),d=e(383),o=e(228);class l extends d.LineToolView{constructor(){super(...arguments),this._drawing=!1}_doubletap(e){if(!this.model.active)return;const t=this.model.renderers;for(const s of t){1==this._select_event(e,\"replace\",[s]).length&&(this._selected_renderer=s)}this._show_intersections(),this._update_line_cds()}_show_intersections(){if(!this.model.active)return;if(null==this._selected_renderer)return;if(!this.model.renderers.length)return this._set_intersection([],[]),this._selected_renderer=null,void(this._drawing=!1);const e=this._selected_renderer.data_source,t=this._selected_renderer.glyph,[s,i]=[t.x.field,t.y.field],r=e.get_array(s),n=e.get_array(i);this._set_intersection(r,n)}_tap(e){const t=this.model.intersection_renderer;if(null==this._map_drag(e.sx,e.sy,t))return;if(this._drawing&&this._selected_renderer){const s=this._select_mode(e);if(0==this._select_event(e,s,[t]).length)return}const s=this._select_mode(e);this._select_event(e,s,[t]),this._select_event(e,s,this.model.renderers)}_update_line_cds(){if(null==this._selected_renderer)return;const e=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,i]=[e.x.field,e.y.field];if(s&&i){const e=t.data[s],r=t.data[i];this._selected_renderer.data_source.data[s]=e,this._selected_renderer.data_source.data[i]=r}this._emit_cds_changes(this._selected_renderer.data_source,!0,!0,!1)}_pan_start(e){this._select_event(e,\"append\",[this.model.intersection_renderer]),this._basepoint=[e.sx,e.sy]}_pan(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer],this.model.dimensions),this._selected_renderer&&this._selected_renderer.data_source.change.emit())}_pan_end(e){null!=this._basepoint&&(this._drag_points(e,[this.model.intersection_renderer]),this._emit_cds_changes(this.model.intersection_renderer.data_source,!1,!0,!0),this._selected_renderer&&this._emit_cds_changes(this._selected_renderer.data_source),this._basepoint=null)}activate(){this._drawing=!0}deactivate(){this._selected_renderer&&(this._drawing&&(this._drawing=!1),this._hide_intersections())}}s.LineEditToolView=l,l.__name__=\"LineEditToolView\";class h extends d.LineTool{constructor(e){super(e),this.tool_name=\"Line Edit Tool\",this.icon=o.tool_icon_line_edit,this.event_type=[\"tap\",\"pan\",\"move\"],this.default_order=4}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}s.LineEditTool=h,n=h,h.__name__=\"LineEditTool\",n.prototype.default_view=l,n.define((()=>({dimensions:[_.Dimensions,\"both\"]})))},\n", - " function _(e,i,n,t,s){var o;t();const r=e(8),_=e(370);class d extends _.EditToolView{_set_intersection(e,i){const n=this.model.intersection_renderer.glyph,t=this.model.intersection_renderer.data_source,[s,o]=[n.x.field,n.y.field];s&&((0,r.isArray)(e)?t.data[s]=e:n.x={value:e}),o&&((0,r.isArray)(i)?t.data[o]=i:n.y={value:i}),this._emit_cds_changes(t,!0,!0,!1)}_hide_intersections(){this._set_intersection([],[])}}n.LineToolView=d,d.__name__=\"LineToolView\";class a extends _.EditTool{constructor(e){super(e)}}n.LineTool=a,o=a,a.__name__=\"LineTool\",o.define((({AnyRef:e})=>({intersection_renderer:[e()]})))},\n", - " function _(t,s,n,e,i){e();const o=t(1);var a;const _=t(223),l=t(20),r=(0,o.__importStar)(t(228));function h(t,s,n){const e=new Map;for(const[i,o]of t){const[t,a]=o.r_invert(s,n);e.set(i,{start:t,end:a})}return e}n.update_ranges=h;class d extends _.GestureToolView{_pan_start(t){var s;this.last_dx=0,this.last_dy=0;const{sx:n,sy:e}=t,i=this.plot_view.frame.bbox;if(!i.contains(n,e)){const t=i.h_range,s=i.v_range;(nt.end)&&(this.v_axis_only=!0),(es.end)&&(this.h_axis_only=!0)}null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan(t){var s;this._update(t.deltaX,t.deltaY),null===(s=this.model.document)||void 0===s||s.interactive_start(this.plot_model)}_pan_end(t){this.h_axis_only=!1,this.v_axis_only=!1,null!=this.pan_info&&this.plot_view.state.push(\"pan\",{range:this.pan_info}),this.plot_view.trigger_ranges_update_event()}_update(t,s){const n=this.plot_view.frame,e=t-this.last_dx,i=s-this.last_dy,o=n.bbox.h_range,a=o.start-e,_=o.end-e,l=n.bbox.v_range,r=l.start-i,d=l.end-i,p=this.model.dimensions;let c,u,m,v,x,g;\"width\"!=p&&\"both\"!=p||this.v_axis_only?(c=o.start,u=o.end,m=0):(c=a,u=_,m=-e),\"height\"!=p&&\"both\"!=p||this.h_axis_only?(v=l.start,x=l.end,g=0):(v=r,x=d,g=-i),this.last_dx=t,this.last_dy=s;const{x_scales:w,y_scales:y}=n,f=h(w,c,u),b=h(y,v,x);this.pan_info={xrs:f,yrs:b,sdx:m,sdy:g},this.plot_view.update_range(this.pan_info,{panning:!0})}}n.PanToolView=d,d.__name__=\"PanToolView\";class p extends _.GestureTool{constructor(t){super(t),this.tool_name=\"Pan\",this.event_type=\"pan\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}n.PanTool=p,a=p,p.__name__=\"PanTool\",a.prototype.default_view=d,a.define((()=>({dimensions:[l.Dimensions,\"both\",{on_update(t,s){switch(t){case\"both\":s.icon=r.tool_icon_pan;break;case\"width\":s.icon=r.tool_icon_xpan;break;case\"height\":s.icon=r.tool_icon_ypan}}}]}))),a.register_alias(\"pan\",(()=>new p({dimensions:\"both\"}))),a.register_alias(\"xpan\",(()=>new p({dimensions:\"width\"}))),a.register_alias(\"ypan\",(()=>new p({dimensions:\"height\"})))},\n", - " function _(e,t,i,s,n){var l;s();const a=e(116),r=e(58),o=e(19),_=e(223),h=e(228);function d(e){switch(e){case 1:return 2;case 2:return 1;case 4:return 5;case 5:return 4;default:return e}}function u(e,t,i,s){if(null==t)return!1;const n=i.compute(t);return Math.abs(e-n)n.right)&&(l=!1)}if(null!=n.bottom&&null!=n.top){const e=s.invert(t);(en.top)&&(l=!1)}return l}function g(e,t,i){let s=0;return e>=i.start&&e<=i.end&&(s+=1),t>=i.start&&t<=i.end&&(s+=1),s}function y(e,t,i,s){const n=t.compute(e),l=t.invert(n+i);return l>=s.start&&l<=s.end?l:e}function f(e,t,i){return e>t.start?(t.end=e,i):(t.end=t.start,t.start=e,d(i))}function v(e,t,i){return e=o&&(e.start=a,e.end=r)}i.flip_side=d,i.is_near=u,i.is_inside=c,i.sides_inside=g,i.compute_value=y,i.update_range_end_side=f,i.update_range_start_side=v,i.update_range=m;class p extends _.GestureToolView{initialize(){super.initialize(),this.side=0,this.model.update_overlay_from_ranges()}connect_signals(){super.connect_signals(),null!=this.model.x_range&&this.connect(this.model.x_range.change,(()=>this.model.update_overlay_from_ranges())),null!=this.model.y_range&&this.connect(this.model.y_range.change,(()=>this.model.update_overlay_from_ranges()))}_pan_start(e){this.last_dx=0,this.last_dy=0;const t=this.model.x_range,i=this.model.y_range,{frame:s}=this.plot_view,n=s.x_scale,l=s.y_scale,r=this.model.overlay,{left:o,right:_,top:h,bottom:d}=r,g=this.model.overlay.line_width+a.EDGE_TOLERANCE;null!=t&&this.model.x_interaction&&(u(e.sx,o,n,g)?this.side=1:u(e.sx,_,n,g)?this.side=2:c(e.sx,e.sy,n,l,r)&&(this.side=3)),null!=i&&this.model.y_interaction&&(0==this.side&&u(e.sy,d,l,g)&&(this.side=4),0==this.side&&u(e.sy,h,l,g)?this.side=5:c(e.sx,e.sy,n,l,this.model.overlay)&&(3==this.side?this.side=7:this.side=6))}_pan(e){const t=this.plot_view.frame,i=e.deltaX-this.last_dx,s=e.deltaY-this.last_dy,n=this.model.x_range,l=this.model.y_range,a=t.x_scale,r=t.y_scale;if(null!=n)if(3==this.side||7==this.side)m(n,a,i,t.x_range);else if(1==this.side){const e=y(n.start,a,i,t.x_range);this.side=v(e,n,this.side)}else if(2==this.side){const e=y(n.end,a,i,t.x_range);this.side=f(e,n,this.side)}if(null!=l)if(6==this.side||7==this.side)m(l,r,s,t.y_range);else if(4==this.side){const e=y(l.start,r,s,t.y_range);this.side=v(e,l,this.side)}else if(5==this.side){const e=y(l.end,r,s,t.y_range);this.side=f(e,l,this.side)}this.last_dx=e.deltaX,this.last_dy=e.deltaY}_pan_end(e){this.side=0,this.plot_view.trigger_ranges_update_event()}}i.RangeToolView=p,p.__name__=\"RangeToolView\";const x=()=>new a.BoxAnnotation({level:\"overlay\",fill_color:\"lightgrey\",fill_alpha:.5,line_color:\"black\",line_alpha:1,line_width:.5,line_dash:[2,2]});class w extends _.GestureTool{constructor(e){super(e),this.tool_name=\"Range Tool\",this.icon=h.tool_icon_range,this.event_type=\"pan\",this.default_order=1}initialize(){super.initialize(),this.overlay.in_cursor=\"grab\",this.overlay.ew_cursor=null!=this.x_range&&this.x_interaction?\"ew-resize\":null,this.overlay.ns_cursor=null!=this.y_range&&this.y_interaction?\"ns-resize\":null}update_overlay_from_ranges(){null==this.x_range&&null==this.y_range&&(this.overlay.left=null,this.overlay.right=null,this.overlay.bottom=null,this.overlay.top=null,o.logger.warn(\"RangeTool not configured with any Ranges.\")),null==this.x_range?(this.overlay.left=null,this.overlay.right=null):(this.overlay.left=this.x_range.start,this.overlay.right=this.x_range.end),null==this.y_range?(this.overlay.bottom=null,this.overlay.top=null):(this.overlay.bottom=this.y_range.start,this.overlay.top=this.y_range.end)}}i.RangeTool=w,l=w,w.__name__=\"RangeTool\",l.prototype.default_view=p,l.define((({Boolean:e,Ref:t,Nullable:i})=>({x_range:[i(t(r.Range1d)),null],x_interaction:[e,!0],y_range:[i(t(r.Range1d)),null],y_interaction:[e,!0],overlay:[t(a.BoxAnnotation),x]})))},\n", - " function _(e,t,s,o,i){var l;o();const a=e(378),n=e(20),c=e(228);class _ extends a.SelectToolView{_tap(e){\"tap\"==this.model.gesture&&this._handle_tap(e)}_doubletap(e){\"doubletap\"==this.model.gesture&&this._handle_tap(e)}_handle_tap(e){const{sx:t,sy:s}=e,o={type:\"point\",sx:t,sy:s};this._select(o,!0,this._select_mode(e))}_select(e,t,s){const{callback:o}=this.model;if(\"select\"==this.model.behavior){const i=this._computed_renderers_by_data_source();for(const[,l]of i){const i=l[0].get_selection_manager(),a=l.map((e=>this.plot_view.renderer_view(e))).filter((e=>null!=e));if(i.select(a,e,t,s)&&null!=o){const t=a[0].coordinates.x_scale.invert(e.sx),s=a[0].coordinates.y_scale.invert(e.sy),l={geometries:Object.assign(Object.assign({},e),{x:t,y:s}),source:i.source};o.execute(this.model,l)}}this._emit_selection_event(e),this.plot_view.state.push(\"tap\",{selection:this.plot_view.get_selection()})}else for(const t of this.computed_renderers){const s=this.plot_view.renderer_view(t);if(null==s)continue;const i=t.get_selection_manager();if(i.inspect(s,e)&&null!=o){const t=s.coordinates.x_scale.invert(e.sx),l=s.coordinates.y_scale.invert(e.sy),a={geometries:Object.assign(Object.assign({},e),{x:t,y:l}),source:i.source};o.execute(this.model,a)}}}}s.TapToolView=_,_.__name__=\"TapToolView\";class r extends a.SelectTool{constructor(e){super(e),this.tool_name=\"Tap\",this.icon=c.tool_icon_tap_select,this.event_type=\"tap\",this.default_order=10}}s.TapTool=r,l=r,r.__name__=\"TapTool\",l.prototype.default_view=_,l.define((({Any:e,Enum:t,Nullable:s})=>({behavior:[n.TapBehavior,\"select\"],gesture:[t(\"tap\",\"doubletap\"),\"tap\"],callback:[s(e)]}))),l.register_alias(\"click\",(()=>new r({behavior:\"inspect\"}))),l.register_alias(\"tap\",(()=>new r)),l.register_alias(\"doubletap\",(()=>new r({gesture:\"doubletap\"})))},\n", - " function _(e,t,s,n,i){var a;n();const o=e(223),l=e(20),_=e(228),r=e(384);class h extends o.GestureToolView{_scroll(e){let t=this.model.speed*e.delta;t>.9?t=.9:t<-.9&&(t=-.9),this._update_ranges(t)}_update_ranges(e){var t;const{frame:s}=this.plot_view,n=s.bbox.h_range,i=s.bbox.v_range,[a,o]=[n.start,n.end],[l,_]=[i.start,i.end];let h,d,p,c;switch(this.model.dimension){case\"height\":{const t=Math.abs(_-l);h=a,d=o,p=l-t*e,c=_-t*e;break}case\"width\":{const t=Math.abs(o-a);h=a-t*e,d=o-t*e,p=l,c=_;break}}const{x_scales:g,y_scales:u}=s,w={xrs:(0,r.update_ranges)(g,h,d),yrs:(0,r.update_ranges)(u,p,c),factor:e};this.plot_view.state.push(\"wheel_pan\",{range:w}),this.plot_view.update_range(w,{scrolling:!0}),null===(t=this.model.document)||void 0===t||t.interactive_start(this.plot_model,(()=>this.plot_view.trigger_ranges_update_event()))}}s.WheelPanToolView=h,h.__name__=\"WheelPanToolView\";class d extends o.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Pan\",this.icon=_.tool_icon_wheel_pan,this.event_type=\"scroll\",this.default_order=12}get tooltip(){return this._get_dim_tooltip(this.dimension)}}s.WheelPanTool=d,a=d,d.__name__=\"WheelPanTool\",a.prototype.default_view=h,a.define((()=>({dimension:[l.Dimension,\"width\"]}))),a.internal((({Number:e})=>({speed:[e,.001]}))),a.register_alias(\"xwheel_pan\",(()=>new d({dimension:\"width\"}))),a.register_alias(\"ywheel_pan\",(()=>new d({dimension:\"height\"})))},\n", - " function _(e,o,t,s,i){var n;s();const l=e(223),_=e(368),h=e(20),a=e(27),r=e(228);class m extends l.GestureToolView{_pinch(e){const{sx:o,sy:t,scale:s,ctrlKey:i,shiftKey:n}=e;let l;l=s>=1?20*(s-1):-20/s,this._scroll({type:\"wheel\",sx:o,sy:t,delta:l,ctrlKey:i,shiftKey:n})}_scroll(e){var o;const{frame:t}=this.plot_view,s=t.bbox.h_range,i=t.bbox.v_range,{sx:n,sy:l}=e,h=this.model.dimensions,a=(\"width\"==h||\"both\"==h)&&s.startthis.plot_view.trigger_ranges_update_event()))}}t.WheelZoomToolView=m,m.__name__=\"WheelZoomToolView\";class d extends l.GestureTool{constructor(e){super(e),this.tool_name=\"Wheel Zoom\",this.icon=r.tool_icon_wheel_zoom,this.event_type=a.is_mobile?\"pinch\":\"scroll\",this.default_order=10}get tooltip(){return this._get_dim_tooltip(this.dimensions)}}t.WheelZoomTool=d,n=d,d.__name__=\"WheelZoomTool\",n.prototype.default_view=m,n.define((({Boolean:e,Number:o})=>({dimensions:[h.Dimensions,\"both\"],maintain_focus:[e,!0],zoom_on_axis:[e,!0],speed:[o,1/600]}))),n.register_alias(\"wheel_zoom\",(()=>new d({dimensions:\"both\"}))),n.register_alias(\"xwheel_zoom\",(()=>new d({dimensions:\"width\"}))),n.register_alias(\"ywheel_zoom\",(()=>new d({dimensions:\"height\"})))},\n", - " function _(i,e,s,t,o){var n;t();const l=i(232),a=i(219),h=i(20),r=i(13),_=i(228);class c extends l.InspectToolView{_move(i){if(!this.model.active)return;const{sx:e,sy:s}=i;this.plot_view.frame.bbox.contains(e,s)?this._update_spans(e,s):this._update_spans(null,null)}_move_exit(i){this._update_spans(null,null)}_update_spans(i,e){const s=this.model.dimensions;\"width\"!=s&&\"both\"!=s||(this.model.spans.width.location=e),\"height\"!=s&&\"both\"!=s||(this.model.spans.height.location=i)}}s.CrosshairToolView=c,c.__name__=\"CrosshairToolView\";class p extends l.InspectTool{constructor(i){super(i),this.tool_name=\"Crosshair\",this.icon=_.tool_icon_crosshair}get tooltip(){return this._get_dim_tooltip(this.dimensions)}get synthetic_renderers(){return(0,r.values)(this.spans)}}s.CrosshairTool=p,n=p,p.__name__=\"CrosshairTool\",(()=>{function i(i,e){return new a.Span({for_hover:!0,dimension:e,location_units:\"screen\",level:\"overlay\",line_color:i.line_color,line_width:i.line_width,line_alpha:i.line_alpha})}n.prototype.default_view=c,n.define((({Alpha:i,Number:e,Color:s})=>({dimensions:[h.Dimensions,\"both\"],line_color:[s,\"black\"],line_width:[e,1],line_alpha:[i,1]}))),n.internal((({Struct:e,Ref:s})=>({spans:[e({width:s(a.Span),height:s(a.Span)}),e=>({width:i(e,\"width\"),height:i(e,\"height\")})]}))),n.register_alias(\"crosshair\",(()=>new p))})()},\n", - " function _(e,s,t,r,n){var o;r();const a=e(53),u=e(13),c=e(34);class i extends a.Model{constructor(e){super(e)}get values(){return(0,u.values)(this.args)}_make_code(e,s,t,r){return new Function(...(0,u.keys)(this.args),e,s,t,(0,c.use_strict)(r))}format(e,s,t){return this._make_code(\"value\",\"format\",\"special_vars\",this.code)(...this.values,e,s,t)}}t.CustomJSHover=i,o=i,i.__name__=\"CustomJSHover\",o.define((({Unknown:e,String:s,Dict:t})=>({args:[t(e),{}],code:[s,\"\"]})))},\n", - " function _(e,t,n,s,i){s();const o=e(1);var r;const l=e(232),a=e(390),c=e(241),_=e(175),d=e(339),p=e(176),h=e(177),u=e(283),m=e(186),y=e(187),f=e(189),x=(0,o.__importStar)(e(185)),v=e(152),w=e(43),g=e(22),b=e(13),k=e(234),C=e(8),S=e(113),T=e(20),$=e(228),R=e(15),A=e(66),M=(0,o.__importStar)(e(242)),V=e(392);function G(e,t,n,s,i,o){const r={x:i[e],y:o[e]},l={x:i[e+1],y:o[e+1]};let a,c;if(\"span\"==t.type)\"h\"==t.direction?(a=Math.abs(r.x-n),c=Math.abs(l.x-n)):(a=Math.abs(r.y-s),c=Math.abs(l.y-s));else{const e={x:n,y:s};a=x.dist_2_pts(r,e),c=x.dist_2_pts(l,e)}return adelete this._template_el)),this.on_change([e,t,n],(async()=>await this._update_ttmodels()))}async _update_ttmodels(){const{_ttmodels:e,computed_renderers:t}=this;e.clear();const{tooltips:n}=this.model;if(null!=n)for(const t of this.computed_renderers){const s=new c.Tooltip({custom:(0,C.isString)(n)||(0,C.isFunction)(n),attachment:this.model.attachment,show_arrow:this.model.show_arrow});t instanceof _.GlyphRenderer?e.set(t,s):t instanceof d.GraphRenderer&&(e.set(t.node_renderer,s),e.set(t.edge_renderer,s))}const s=await(0,S.build_views)(this._ttviews,[...e.values()],{parent:this.plot_view});for(const e of s)e.render();const i=[...function*(){for(const e of t)e instanceof _.GlyphRenderer?yield e:e instanceof d.GraphRenderer&&(yield e.node_renderer,yield e.edge_renderer)}()],o=this._slots.get(this._update);if(null!=o){const e=new Set(i.map((e=>e.data_source)));R.Signal.disconnect_receiver(this,o,e)}for(const e of i)this.connect(e.data_source.inspect,this._update)}get computed_renderers(){const{renderers:e,names:t}=this.model,n=this.plot_model.data_renderers;return(0,A.compute_renderers)(e,n,t)}get ttmodels(){return this._ttmodels}_clear(){this._inspect(1/0,1/0);for(const[,e]of this.ttmodels)e.clear()}_move(e){if(!this.model.active)return;const{sx:t,sy:n}=e;this.plot_view.frame.bbox.contains(t,n)?this._inspect(t,n):this._clear()}_move_exit(){this._clear()}_inspect(e,t){let n;if(\"mouse\"==this.model.mode)n={type:\"point\",sx:e,sy:t};else{n={type:\"span\",direction:\"vline\"==this.model.mode?\"h\":\"v\",sx:e,sy:t}}for(const e of this.computed_renderers){const t=e.get_selection_manager(),s=this.plot_view.renderer_view(e);null!=s&&t.inspect(s,n)}this._emit_callback(n)}_update([e,{geometry:t}]){var n,s;if(!this.model.active)return;if(\"point\"!=t.type&&\"span\"!=t.type)return;if(!(e instanceof _.GlyphRenderer))return;if(\"ignore\"==this.model.muted_policy&&e.muted)return;const i=this.ttmodels.get(e);if(null==i)return;const o=e.get_selection_manager(),r=o.inspectors.get(e),l=e.view.convert_selection_to_subset(r);if(r.is_empty()&&null==r.view)return void i.clear();const a=o.source,c=this.plot_view.renderer_view(e);if(null==c)return;const{sx:d,sy:p}=t,x=c.coordinates.x_scale,v=c.coordinates.y_scale,g=x.invert(d),k=v.invert(p),{glyph:C}=c,S=[];if(C instanceof m.PatchView){const[t,n]=[d,p],s={x:g,y:k,sx:d,sy:p,rx:t,ry:n,name:e.name};S.push([t,n,this._render_tooltips(a,-1,s)])}if(C instanceof y.HAreaView)for(const t of l.line_indices){const n=C._x1,s=C._x2,i=C._y,[o,r]=[d,p],c={index:t,x:g,y:k,sx:d,sy:p,data_x1:n,data_x2:s,data_y:i,rx:o,ry:r,indices:l.line_indices,name:e.name};S.push([o,r,this._render_tooltips(a,t,c)])}if(C instanceof f.VAreaView)for(const t of l.line_indices){const n=C._x,s=C._y1,i=C._y2,[o,r]=[d,p],c={index:t,x:g,y:k,sx:d,sy:p,data_x:n,data_y1:s,data_y2:i,rx:o,ry:r,indices:l.line_indices,name:e.name};S.push([o,r,this._render_tooltips(a,t,c)])}if(C instanceof h.LineView)for(const n of l.line_indices){let s,i,o=C._x[n+1],r=C._y[n+1],c=n;switch(this.model.line_policy){case\"interp\":[o,r]=C.get_interpolation_hit(n,t),s=x.compute(o),i=v.compute(r);break;case\"prev\":[[s,i],c]=H(C.sx,C.sy,n);break;case\"next\":[[s,i],c]=H(C.sx,C.sy,n+1);break;case\"nearest\":[[s,i],c]=G(n,t,d,p,C.sx,C.sy),o=C._x[c],r=C._y[c];break;default:[s,i]=[d,p]}const _={index:c,x:g,y:k,sx:d,sy:p,data_x:o,data_y:r,rx:s,ry:i,indices:l.line_indices,name:e.name};S.push([s,i,this._render_tooltips(a,c,_)])}for(const t of r.image_indices){const n={index:t.index,x:g,y:k,sx:d,sy:p,name:e.name},s=this._render_tooltips(a,t,n);S.push([d,p,s])}for(const i of l.indices)if(C instanceof u.MultiLineView&&!(0,b.isEmpty)(l.multiline_indices))for(const n of l.multiline_indices[i.toString()]){let s,o,r,c=C._xs.get(i)[n],h=C._ys.get(i)[n],u=n;switch(this.model.line_policy){case\"interp\":[c,h]=C.get_interpolation_hit(i,n,t),s=x.compute(c),o=v.compute(h);break;case\"prev\":[[s,o],u]=H(C.sxs.get(i),C.sys.get(i),n);break;case\"next\":[[s,o],u]=H(C.sxs.get(i),C.sys.get(i),n+1);break;case\"nearest\":[[s,o],u]=G(n,t,d,p,C.sxs.get(i),C.sys.get(i)),c=C._xs.get(i)[u],h=C._ys.get(i)[u];break;default:throw new Error(\"shouldn't have happened\")}r=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([i])[0]:i;const m={index:r,x:g,y:k,sx:d,sy:p,data_x:c,data_y:h,segment_index:u,indices:l.multiline_indices,name:e.name};S.push([s,o,this._render_tooltips(a,r,m)])}else{const t=null===(n=C._x)||void 0===n?void 0:n[i],o=null===(s=C._y)||void 0===s?void 0:s[i];let r,c,h;if(\"snap_to_data\"==this.model.point_policy){let e=C.get_anchor_point(this.model.anchor,i,[d,p]);if(null==e&&(e=C.get_anchor_point(\"center\",i,[d,p]),null==e))continue;r=e.x,c=e.y}else[r,c]=[d,p];h=e instanceof _.GlyphRenderer?e.view.convert_indices_from_subset([i])[0]:i;const u={index:h,x:g,y:k,sx:d,sy:p,data_x:t,data_y:o,indices:l.indices,name:e.name};S.push([r,c,this._render_tooltips(a,h,u)])}if(0==S.length)i.clear();else{const{content:e}=i;(0,w.empty)(i.content);for(const[,,t]of S)null!=t&&e.appendChild(t);const[t,n]=S[S.length-1];i.setv({position:[t,n]},{check_eq:!1})}}_emit_callback(e){const{callback:t}=this.model;if(null!=t)for(const n of this.computed_renderers){if(!(n instanceof _.GlyphRenderer))continue;const s=this.plot_view.renderer_view(n);if(null==s)continue;const{x_scale:i,y_scale:o}=s.coordinates,r=i.invert(e.sx),l=o.invert(e.sy),a=n.data_source.inspected;t.execute(this.model,{geometry:Object.assign({x:r,y:l},e),renderer:n,index:a})}}_create_template(e){const t=(0,w.div)({style:{display:\"table\",borderSpacing:\"2px\"}});for(const[n]of e){const e=(0,w.div)({style:{display:\"table-row\"}});t.appendChild(e);const s=(0,w.div)({style:{display:\"table-cell\"},class:M.tooltip_row_label},0!=n.length?`${n}: `:\"\");e.appendChild(s);const i=(0,w.span)();i.dataset.value=\"\";const o=(0,w.span)({class:M.tooltip_color_block},\" \");o.dataset.swatch=\"\",(0,w.undisplay)(o);const r=(0,w.div)({style:{display:\"table-cell\"},class:M.tooltip_row_value},i,o);e.appendChild(r)}return t}_render_template(e,t,n,s,i){const o=e.cloneNode(!0),r=o.querySelectorAll(\"[data-value]\"),l=o.querySelectorAll(\"[data-swatch]\"),a=/\\$color(\\[.*\\])?:(\\w*)/,c=/\\$swatch:(\\w*)/;for(const[[,e],o]of(0,k.enumerate)(t)){const t=e.match(c),_=e.match(a);if(null!=t||null!=_){if(null!=t){const[,e]=t,i=n.get_column(e);if(null==i)r[o].textContent=`${e} unknown`;else{const e=(0,C.isNumber)(s)?i[s]:null;null!=e&&(l[o].style.backgroundColor=(0,g.color2css)(e),(0,w.display)(l[o]))}}if(null!=_){const[,e=\"\",t]=_,i=n.get_column(t);if(null==i){r[o].textContent=`${t} unknown`;continue}const a=e.indexOf(\"hex\")>=0,c=e.indexOf(\"swatch\")>=0,d=(0,C.isNumber)(s)?i[s]:null;if(null==d){r[o].textContent=\"(null)\";continue}r[o].textContent=a?(0,g.color2hex)(d):(0,g.color2css)(d),c&&(l[o].style.backgroundColor=(0,g.color2css)(d),(0,w.display)(l[o]))}}else{const t=(0,v.replace_placeholders)(e.replace(\"$~\",\"$data_\"),n,s,this.model.formatters,i);if((0,C.isString)(t))r[o].textContent=t;else for(const e of t)r[o].appendChild(e)}}return o}_render_tooltips(e,t,n){var s;const{tooltips:i}=this.model;if((0,C.isString)(i)){const s=(0,v.replace_placeholders)({html:i},e,t,this.model.formatters,n);return(0,w.div)(s)}if((0,C.isFunction)(i))return i(e,n);if(i instanceof V.Template)return this._template_view.update(e,t,n),this._template_view.el;if(null!=i){const o=null!==(s=this._template_el)&&void 0!==s?s:this._template_el=this._create_template(i);return this._render_template(o,i,e,t,n)}return null}}n.HoverToolView=z,z.__name__=\"HoverToolView\";class P extends l.InspectTool{constructor(e){super(e),this.tool_name=\"Hover\",this.icon=$.tool_icon_hover}}n.HoverTool=P,r=P,P.__name__=\"HoverTool\",r.prototype.default_view=z,r.define((({Any:e,Boolean:t,String:n,Array:s,Tuple:i,Dict:o,Or:r,Ref:l,Function:c,Auto:_,Nullable:d})=>({tooltips:[d(r(l(V.Template),n,s(i(n,n)),c())),[[\"index\",\"$index\"],[\"data (x, y)\",\"($x, $y)\"],[\"screen (x, y)\",\"($sx, $sy)\"]]],formatters:[o(r(l(a.CustomJSHover),v.FormatterType)),{}],renderers:[r(s(l(p.DataRenderer)),_),\"auto\"],names:[s(n),[]],mode:[T.HoverMode,\"mouse\"],muted_policy:[T.MutedPolicy,\"show\"],point_policy:[T.PointPolicy,\"snap_to_data\"],line_policy:[T.LinePolicy,\"nearest\"],show_arrow:[t,!0],anchor:[T.Anchor,\"center\"],attachment:[T.TooltipAttachment,\"horizontal\"],callback:[d(e)]}))),r.register_alias(\"hover\",(()=>new P))},\n", - " function _(e,t,s,n,a){n();const l=e(1);var i,_,o,r,c,d,p,u,m,w,f,h,x;const v=e(53),y=e(309),V=e(393);a(\"Styles\",V.Styles);const g=e(43),T=e(42),b=e(226),R=e(113),D=e(8),M=e(13),S=(0,l.__importStar)(e(242)),O=e(152);class C extends b.DOMView{}s.DOMNodeView=C,C.__name__=\"DOMNodeView\";class z extends v.Model{constructor(e){super(e)}}s.DOMNode=z,z.__name__=\"DOMNode\",z.__module__=\"bokeh.models.dom\";class P extends C{render(){super.render(),this.el.textContent=this.model.content}_createElement(){return document.createTextNode(\"\")}}s.TextView=P,P.__name__=\"TextView\";class A extends z{constructor(e){super(e)}}s.Text=A,i=A,A.__name__=\"Text\",i.prototype.default_view=P,i.define((({String:e})=>({content:[e,\"\"]})));class N extends C{}s.PlaceholderView=N,N.__name__=\"PlaceholderView\",N.tag_name=\"span\";class E extends z{constructor(e){super(e)}}s.Placeholder=E,_=E,E.__name__=\"Placeholder\",_.define((({})=>({})));class G extends N{update(e,t,s){this.el.textContent=t.toString()}}s.IndexView=G,G.__name__=\"IndexView\";class I extends E{constructor(e){super(e)}}s.Index=I,o=I,I.__name__=\"Index\",o.prototype.default_view=G,o.define((({})=>({})));class k extends N{update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ValueRefView=k,k.__name__=\"ValueRefView\";class $ extends E{constructor(e){super(e)}}s.ValueRef=$,r=$,$.__name__=\"ValueRef\",r.prototype.default_view=k,r.define((({String:e})=>({field:[e]})));class B extends k{render(){super.render(),this.value_el=(0,g.span)(),this.swatch_el=(0,g.span)({class:S.tooltip_color_block},\" \"),this.el.appendChild(this.value_el),this.el.appendChild(this.swatch_el)}update(e,t,s){const n=(0,O._get_column_value)(this.model.field,e,t),a=null==n?\"???\":`${n}`;this.el.textContent=a}}s.ColorRefView=B,B.__name__=\"ColorRefView\";class L extends ${constructor(e){super(e)}}s.ColorRef=L,c=L,L.__name__=\"ColorRef\",c.prototype.default_view=B,c.define((({Boolean:e})=>({hex:[e,!0],swatch:[e,!0]})));class j extends C{constructor(){super(...arguments),this.child_views=new Map}async lazy_initialize(){await super.lazy_initialize();const e=this.model.children.filter((e=>e instanceof v.Model));await(0,R.build_views)(this.child_views,e,{parent:this})}render(){super.render();const{style:e}=this.model;if(null!=e)if(e instanceof V.Styles)for(const t of e){const e=t.get_value();if((0,D.isString)(e)){const s=t.attr.replace(/_/g,\"-\");this.el.style.hasOwnProperty(s)&&this.el.style.setProperty(s,e)}}else for(const[t,s]of(0,M.entries)(e)){const e=t.replace(/_/g,\"-\");this.el.style.hasOwnProperty(e)&&this.el.style.setProperty(e,s)}for(const e of this.model.children)if((0,D.isString)(e)){const t=document.createTextNode(e);this.el.appendChild(t)}else{this.child_views.get(e).renderTo(this.el)}}}s.DOMElementView=j,j.__name__=\"DOMElementView\";class q extends z{constructor(e){super(e)}}s.DOMElement=q,d=q,q.__name__=\"DOMElement\",d.define((({String:e,Array:t,Dict:s,Or:n,Nullable:a,Ref:l})=>({style:[a(n(l(V.Styles),s(e))),null],children:[t(n(e,l(z),l(y.LayoutDOM))),[]]})));class F extends T.View{}s.ActionView=F,F.__name__=\"ActionView\";class H extends v.Model{constructor(e){super(e)}}s.Action=H,p=H,H.__name__=\"Action\",H.__module__=\"bokeh.models.dom\",p.define((({})=>({})));class J extends j{constructor(){super(...arguments),this.action_views=new Map}async lazy_initialize(){await super.lazy_initialize(),await(0,R.build_views)(this.action_views,this.model.actions,{parent:this})}remove(){(0,R.remove_views)(this.action_views),super.remove()}update(e,t,s={}){!function n(a){for(const l of a.child_views.values())l instanceof N?l.update(e,t,s):l instanceof j&&n(l)}(this);for(const n of this.action_views.values())n.update(e,t,s)}}s.TemplateView=J,J.__name__=\"TemplateView\",J.tag_name=\"div\";class K extends q{}s.Template=K,u=K,K.__name__=\"Template\",u.prototype.default_view=J,u.define((({Array:e,Ref:t})=>({actions:[e(t(H)),[]]})));class Q extends j{}s.SpanView=Q,Q.__name__=\"SpanView\",Q.tag_name=\"span\";class U extends q{}s.Span=U,m=U,U.__name__=\"Span\",m.prototype.default_view=Q;class W extends j{}s.DivView=W,W.__name__=\"DivView\",W.tag_name=\"div\";class X extends q{}s.Div=X,w=X,X.__name__=\"Div\",w.prototype.default_view=W;class Y extends j{}s.TableView=Y,Y.__name__=\"TableView\",Y.tag_name=\"table\";class Z extends q{}s.Table=Z,f=Z,Z.__name__=\"Table\",f.prototype.default_view=Y;class ee extends j{}s.TableRowView=ee,ee.__name__=\"TableRowView\",ee.tag_name=\"tr\";class te extends q{}s.TableRow=te,h=te,te.__name__=\"TableRow\",h.prototype.default_view=ee;const se=e(41),ne=e(234);class ae extends F{update(e,t,s){for(const[e,s]of(0,ne.enumerate)(this.model.groups))e.visible=t==s}}s.ToggleGroupView=ae,ae.__name__=\"ToggleGroupView\";class le extends H{constructor(e){super(e)}}s.ToggleGroup=le,x=le,le.__name__=\"ToggleGroup\",x.prototype.default_view=ae,x.define((({Array:e,Ref:t})=>({groups:[e(t(se.RendererGroup)),[]]})))},\n", - " function _(l,n,u,_,e){var t;_();const o=l(53);class r extends 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- " function _(t,o,e,n,s){var i;n();const l=t(15),c=t(53),r=t(224),a=t(232),u=t(234);class h extends c.Model{constructor(t){super(t)}get button_view(){return this.tools[0].button_view}get event_type(){return this.tools[0].event_type}get tooltip(){return this.tools[0].tooltip}get tool_name(){return this.tools[0].tool_name}get icon(){return this.tools[0].computed_icon}get computed_icon(){return this.icon}get toggleable(){const t=this.tools[0];return t instanceof a.InspectTool&&t.toggleable}initialize(){super.initialize(),this.do=new l.Signal0(this,\"do\")}connect_signals(){super.connect_signals(),this.connect(this.do,(()=>this.doit())),this.connect(this.properties.active.change,(()=>this.set_active()));for(const t of this.tools)this.connect(t.properties.active.change,(()=>{this.active=t.active}))}doit(){for(const t of this.tools)t.do.emit()}set_active(){for(const t of this.tools)t.active=this.active}get menu(){const{menu:t}=this.tools[0];if(null==t)return null;const o=[];for(const[e,n]of(0,u.enumerate)(t))if(null==e)o.push(null);else{const t=()=>{var t,o,e;for(const s of this.tools)null===(e=null===(o=null===(t=s.menu)||void 0===t?void 0:t[n])||void 0===o?void 0:o.handler)||void 0===e||e.call(o)};o.push(Object.assign(Object.assign({},e),{handler:t}))}return o}}e.ToolProxy=h,i=h,h.__name__=\"ToolProxy\",i.define((({Boolean:t,Array:o,Ref:e})=>({tools:[o(e(r.ButtonTool)),[]],active:[t,!1],disabled:[t,!1]})))},\n", - " function _(o,t,s,e,i){var n,r;e();const l=o(20),c=o(9),h=o(13),a=o(233),_=o(221),p=o(394),u=o(309),f=o(207);class y extends a.ToolbarBase{constructor(o){super(o)}initialize(){super.initialize(),this._merge_tools()}_merge_tools(){this._proxied_tools=[];const o={},t={},s={},e=[],i=[];for(const o of this.help)(0,c.includes)(i,o.redirect)||(e.push(o),i.push(o.redirect));this._proxied_tools.push(...e),this.help=e;for(const[o,t]of(0,h.entries)(this.gestures)){o in s||(s[o]={});for(const e of t.tools)e.type in s[o]||(s[o][e.type]=[]),s[o][e.type].push(e)}for(const t of this.inspectors)t.type in o||(o[t.type]=[]),o[t.type].push(t);for(const o of this.actions)o.type in t||(t[o.type]=[]),t[o.type].push(o);const n=(o,t=!1)=>{const s=new p.ToolProxy({tools:o,active:t});return this._proxied_tools.push(s),s};for(const o of(0,h.keys)(s)){const t=this.gestures[o];t.tools=[];for(const e of(0,h.keys)(s[o])){const i=s[o][e];if(i.length>0)if(\"multi\"==o)for(const o of i){const s=n([o]);t.tools.push(s),this.connect(s.properties.active.change,(()=>this._active_change(s)))}else{const o=n(i);t.tools.push(o),this.connect(o.properties.active.change,(()=>this._active_change(o)))}}}this.actions=[];for(const[o,s]of(0,h.entries)(t))if(\"CustomAction\"==o)for(const o of s)this.actions.push(n([o]));else s.length>0&&this.actions.push(n(s));this.inspectors=[];for(const t of(0,h.values)(o))t.length>0&&this.inspectors.push(n(t,!0));for(const[o,t]of(0,h.entries)(this.gestures))0!=t.tools.length&&(t.tools=(0,c.sort_by)(t.tools,(o=>o.default_order)),\"pinch\"!=o&&\"scroll\"!=o&&\"multi\"!=o&&(t.tools[0].active=!0))}}s.ProxyToolbar=y,n=y,y.__name__=\"ProxyToolbar\",n.define((({Array:o,Ref:t})=>({toolbars:[o(t(_.Toolbar)),[]]})));class d extends u.LayoutDOMView{initialize(){this.model.toolbar.toolbar_location=this.model.toolbar_location,super.initialize()}get child_models(){return[this.model.toolbar]}_update_layout(){this.layout=new f.ContentBox(this.child_views[0].el);const{toolbar:o}=this.model;o.horizontal?this.layout.set_sizing({width_policy:\"fit\",min_width:100,height_policy:\"fixed\"}):this.layout.set_sizing({width_policy:\"fixed\",height_policy:\"fit\",min_height:100})}after_layout(){super.after_layout();const o=this.child_views[0];o.layout.bbox=this.layout.bbox,o.render()}}s.ToolbarBoxView=d,d.__name__=\"ToolbarBoxView\";class b extends u.LayoutDOM{constructor(o){super(o)}}s.ToolbarBox=b,r=b,b.__name__=\"ToolbarBox\",r.prototype.default_view=d,r.define((({Ref:o})=>({toolbar:[o(a.ToolbarBase)],toolbar_location:[l.Location,\"right\"]})))},\n", - " function _(e,n,r,t,o){t();const s=e(1),u=e(53),c=(0,s.__importStar)(e(21)),a=e(8),l=e(13);r.resolve_defs=function(e,n){var r,t,o,s;function i(e){return null!=e.module?`${e.module}.${e.name}`:e.name}function f(e){if((0,a.isString)(e))switch(e){case\"Any\":return c.Any;case\"Unknown\":return c.Unknown;case\"Boolean\":return c.Boolean;case\"Number\":return c.Number;case\"Int\":return c.Int;case\"String\":return c.String;case\"Null\":return c.Null}else switch(e[0]){case\"Nullable\":{const[,n]=e;return c.Nullable(f(n))}case\"Or\":{const[,...n]=e;return c.Or(...n.map(f))}case\"Tuple\":{const[,n,...r]=e;return c.Tuple(f(n),...r.map(f))}case\"Array\":{const[,n]=e;return c.Array(f(n))}case\"Struct\":{const[,...n]=e,r=n.map((([e,n])=>[e,f(n)]));return c.Struct((0,l.to_object)(r))}case\"Dict\":{const[,n]=e;return c.Dict(f(n))}case\"Map\":{const[,n,r]=e;return c.Map(f(n),f(r))}case\"Enum\":{const[,...n]=e;return c.Enum(...n)}case\"Ref\":{const[,r]=e,t=n.get(i(r));if(null!=t)return c.Ref(t);throw new Error(`${i(r)} wasn't defined before referencing it`)}case\"AnyRef\":return c.AnyRef()}}for(const c of e){const e=(()=>{if(null==c.extends)return u.Model;{const e=n.get(i(c.extends));if(null!=e)return e;throw new Error(`base model ${i(c.extends)} of ${i(c)} is not defined`)}})(),a=((s=class extends e{}).__name__=c.name,s.__module__=c.module,s);for(const e of null!==(r=c.properties)&&void 0!==r?r:[]){const n=f(null!==(t=e.kind)&&void 0!==t?t:\"Unknown\");a.define({[e.name]:[n,e.default]})}for(const e of null!==(o=c.overrides)&&void 0!==o?o:[])a.override({[e.name]:e.default});n.register(a)}}},\n", - " function _(n,e,t,o,i){o();const d=n(5),c=n(226),s=n(113),a=n(43),l=n(398);t.index={},t.add_document_standalone=async function(n,e,o=[],i=!1){const u=new Map;async function f(i){let d;const f=n.roots().indexOf(i),r=o[f];null!=r?d=r:e.classList.contains(l.BOKEH_ROOT)?d=e:(d=(0,a.div)({class:l.BOKEH_ROOT}),e.appendChild(d));const w=await(0,s.build_view)(i,{parent:null});return w instanceof c.DOMView&&w.renderTo(d),u.set(i,w),t.index[i.id]=w,w}for(const e of n.roots())await f(e);return i&&(window.document.title=n.title()),n.on_change((n=>{n instanceof d.RootAddedEvent?f(n.model):n instanceof d.RootRemovedEvent?function(n){const e=u.get(n);null!=e&&(e.remove(),u.delete(n),delete t.index[n.id])}(n.model):i&&n instanceof d.TitleChangedEvent&&(window.document.title=n.title)})),[...u.values()]}},\n", - " function _(o,e,n,t,r){t();const l=o(43),d=o(44);function u(o){let e=document.getElementById(o);if(null==e)throw new Error(`Error rendering Bokeh model: could not find #${o} HTML tag`);if(!document.body.contains(e))throw new Error(`Error rendering Bokeh model: element #${o} must be under `);if(\"SCRIPT\"==e.tagName){const o=(0,l.div)({class:n.BOKEH_ROOT});(0,l.replaceWith)(e,o),e=o}return e}n.BOKEH_ROOT=d.root,n._resolve_element=function(o){const{elementid:e}=o;return null!=e?u(e):document.body},n._resolve_root_elements=function(o){const e=[];if(null!=o.root_ids&&null!=o.roots)for(const n of o.root_ids)e.push(u(o.roots[n]));return e}},\n", - " function _(n,o,t,s,e){s();const c=n(400),r=n(19),a=n(397);t._get_ws_url=function(n,o){let t,s=\"ws:\";return\"https:\"==window.location.protocol&&(s=\"wss:\"),null!=o?(t=document.createElement(\"a\"),t.href=o):t=window.location,null!=n?\"/\"==n&&(n=\"\"):n=t.pathname.replace(/\\/+$/,\"\"),`${s}//${t.host}${n}/ws`};const i={};t.add_document_from_session=async function(n,o,t,s=[],e=!1){const l=window.location.search.substr(1);let d;try{d=await function(n,o,t){const s=(0,c.parse_token)(o).session_id;n in i||(i[n]={});const e=i[n];return s in e||(e[s]=(0,c.pull_session)(n,o,t)),e[s]}(n,o,l)}catch(n){const t=(0,c.parse_token)(o).session_id;throw r.logger.error(`Failed to load Bokeh session ${t}: ${n}`),n}return(0,a.add_document_standalone)(d.document,t,s,e)}},\n", - " function _(e,s,n,t,o){t();const r=e(19),i=e(5),c=e(401),l=e(402),_=e(403);n.DEFAULT_SERVER_WEBSOCKET_URL=\"ws://localhost:5006/ws\",n.DEFAULT_TOKEN=\"eyJzZXNzaW9uX2lkIjogImRlZmF1bHQifQ\";let h=0;function a(e){let s=e.split(\".\")[0];const n=s.length%4;return 0!=n&&(s+=\"=\".repeat(4-n)),JSON.parse(atob(s.replace(/_/g,\"/\").replace(/-/g,\"+\")))}n.parse_token=a;class d{constructor(e=n.DEFAULT_SERVER_WEBSOCKET_URL,s=n.DEFAULT_TOKEN,t=null){this.url=e,this.token=s,this.args_string=t,this._number=h++,this.socket=null,this.session=null,this.closed_permanently=!1,this._current_handler=null,this._pending_replies=new Map,this._pending_messages=[],this._receiver=new l.Receiver,this.id=a(s).session_id.split(\".\")[0],r.logger.debug(`Creating websocket ${this._number} to '${this.url}' session '${this.id}'`)}async connect(){if(this.closed_permanently)throw new Error(\"Cannot connect() a closed ClientConnection\");if(null!=this.socket)throw new Error(\"Already connected\");this._current_handler=null,this._pending_replies.clear(),this._pending_messages=[];try{let e=`${this.url}`;return null!=this.args_string&&this.args_string.length>0&&(e+=`?${this.args_string}`),this.socket=new WebSocket(e,[\"bokeh\",this.token]),new Promise(((e,s)=>{this.socket.binaryType=\"arraybuffer\",this.socket.onopen=()=>this._on_open(e,s),this.socket.onmessage=e=>this._on_message(e),this.socket.onclose=e=>this._on_close(e,s),this.socket.onerror=()=>this._on_error(s)}))}catch(e){throw r.logger.error(`websocket creation failed to url: ${this.url}`),r.logger.error(` - ${e}`),e}}close(){this.closed_permanently||(r.logger.debug(`Permanently closing websocket connection ${this._number}`),this.closed_permanently=!0,null!=this.socket&&this.socket.close(1e3,`close method called on ClientConnection 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connection was already closed\"),s(new Error(\"The connection has been closed\"));else{const s=i.Document.from_json(n),t=i.Document._compute_patch_since_json(n,s);if(t.events.length>0){r.logger.debug(`Sending ${t.events.length} changes from model construction back to server`);const e=c.Message.create(\"PATCH-DOC\",{},t);this.send(e)}this.session=new _.ClientSession(this,s,this.id);for(const e of this._pending_messages)this.session.handle(e);this._pending_messages=[],r.logger.debug(\"Created a new session from new pulled doc\"),e(this.session)}else this.session.document.replace_with_json(n),r.logger.debug(\"Updated existing session with new pulled doc\")}catch(e){null===(n=console.trace)||void 0===n||n.call(console,e),r.logger.error(`Failed to repull session ${e}`),s(e instanceof Error?e:`${e}`)}}_on_open(e,s){r.logger.info(`Websocket connection ${this._number} is now 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this.request_server_info()}_document_changed(e){if(e.setter_id===this.id)return;const t=e instanceof c.DocumentEventBatch?e.events:[e],n=this.document.create_json_patch(t),s=i.Message.create(\"PATCH-DOC\",{},n);this._connection.send(s)}_handle_patch(e){this.document.apply_json_patch(e.content,e.buffers,this.id)}_handle_ok(e){_.logger.trace(`Unhandled OK reply to ${e.reqid()}`)}_handle_error(e){_.logger.error(`Unhandled ERROR reply to ${e.reqid()}: ${e.content.text}`)}}n.ClientSession=r,r.__name__=\"ClientSession\"},\n", - " function _(e,o,t,n,r){n();const s=e(1),l=e(5),i=e(402),a=e(19),c=e(43),g=e(13),f=e(397),u=e(398),m=(0,s.__importDefault)(e(44)),p=(0,s.__importDefault)(e(240)),d=(0,s.__importDefault)(e(405));function _(e,o){o.buffers.length>0?e.consume(o.buffers[0].buffer):e.consume(o.content.data);const t=e.message;null!=t&&this.apply_json_patch(t.content,t.buffers)}function b(e,o){if(\"undefined\"!=typeof Jupyter&&null!=Jupyter.notebook.kernel){a.logger.info(`Registering Jupyter 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t.def(e.shared.vao,\".currentVAO?\",e.shared.vao,\".currentVAO.count:-1\")}));return m}return null}(),h=l(br,!1);return{elements:s,primitive:m,count:p,instances:h,offset:d,vao:f,vaoActive:i,elementsActive:u,static:a}}(e,d),A=function(e,t){var r=e.static,n=e.dynamic,i={};return k.forEach((function(e){var o=E(e);function f(t,a){if(e in r){var f=t(r[e]);i[o]=an((function(){return f}))}else if(e in n){var u=n[e];i[o]=on(u,(function(e,t){return a(e,t,e.invoke(t,u))}))}}switch(e){case Nt:case It:case Vt:case er:case Mt:case ir:case Xt:case Kt:case Jt:case Gt:return f((function(r){return _.commandType(r,\"boolean\",e,t.commandStr),r}),(function(t,r,n){return _.optional((function(){t.assert(r,\"typeof \"+n+'===\"boolean\"',\"invalid flag \"+e,t.commandStr)})),n}));case Wt:return f((function(r){return _.commandParameter(r,$r,\"invalid \"+e,t.commandStr),$r[r]}),(function(t,r,n){var a=t.constants.compareFuncs;return _.optional((function(){t.assert(r,n+\" in \"+a,\"invalid \"+e+\", must be one of 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_.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"blend.color must be a 4d array\")})),V(4,(function(e){return t.def(\"+\",r,\"[\",e,\"]\")}))}));case tr:return f((function(e){return _.commandType(e,\"number\",o,t.commandStr),0|e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"',\"invalid stencil.mask\")})),t.def(r,\"|0\")}));case rr:return f((function(r){_.commandType(r,\"object\",o,t.commandStr);var n=r.cmp||\"keep\",a=r.ref||0,i=\"mask\"in r?r.mask:-1;return _.commandParameter(n,$r,e+\".cmp\",t.commandStr),_.commandType(a,\"number\",e+\".ref\",t.commandStr),_.commandType(i,\"number\",e+\".mask\",t.commandStr),[$r[n],a,i]}),(function(e,t,r){var n=e.constants.compareFuncs;return _.optional((function(){function a(){e.assert(t,Array.prototype.join.call(arguments,\"\"),\"invalid stencil.func\")}a(r+\"&&typeof \",r,'===\"object\"'),a('!(\"cmp\" in ',r,\")||(\",r,\".cmp in \",n,\")\")})),[t.def('\"cmp\" in 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_.commandType(r,\"number\",o+\".factor\",t.commandStr),_.commandType(n,\"number\",o+\".units\",t.commandStr),[r,n]}),(function(t,r,n){return _.optional((function(){t.assert(r,n+\"&&typeof \"+n+'===\"object\"',\"invalid \"+e)})),[r.def(n,\".factor|0\"),r.def(n,\".units|0\")]}));case qt:return f((function(e){var r=0;return\"front\"===e?r=Hr:\"back\"===e&&(r=Nr),_.command(!!r,o,t.commandStr),r}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"front\"||'+r+'===\"back\"',\"invalid cull.face\")})),t.def(r,'===\"front\"?',Hr,\":\",Nr)}));case Yt:return f((function(e){return _.command(\"number\"==typeof e&&e>=a.lineWidthDims[0]&&e<=a.lineWidthDims[1],\"invalid line width, must be a positive number between \"+a.lineWidthDims[0]+\" and \"+a.lineWidthDims[1],t.commandStr),e}),(function(e,t,r){return _.optional((function(){e.assert(t,\"typeof \"+r+'===\"number\"&&'+r+\">=\"+a.lineWidthDims[0]+\"&&\"+r+\"<=\"+a.lineWidthDims[1],\"invalid line width\")})),r}));case Qt:return f((function(e){return _.commandParameter(e,Zr,o,t.commandStr),Zr[e]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+'===\"cw\"||'+r+'===\"ccw\"',\"invalid frontFace, must be one of cw,ccw\")})),t.def(r+'===\"cw\"?2304:'+qr)}));case Ht:return f((function(e){return _.command(me(e)&&4===e.length,\"color.mask must be length 4 array\",t.commandStr),e.map((function(e){return!!e}))}),(function(e,t,r){return _.optional((function(){e.assert(t,e.shared.isArrayLike+\"(\"+r+\")&&\"+r+\".length===4\",\"invalid color.mask\")})),V(4,(function(e){return\"!!\"+r+\"[\"+e+\"]\"}))}));case Zt:return f((function(e){_.command(\"object\"==typeof e&&e,o,t.commandStr);var r=\"value\"in e?e.value:1,n=!!e.invert;return _.command(\"number\"==typeof r&&r>=0&&r<=1,\"sample.coverage.value must be a number between 0 and 1\",t.commandStr),[r,n]}),(function(e,t,r){return _.optional((function(){e.assert(t,r+\"&&typeof \"+r+'===\"object\"',\"invalid sample.coverage\")})),[t.def('\"value\" in 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t=x[e];t&&(A[e]=t)}O(fr),O(E(or));var T=Object.keys(A).length>0,D={framebuffer:y,draw:w,shader:S,state:A,dirty:T,scopeVAO:null,drawVAO:null,useVAO:!1,attributes:{}};if(D.profile=function(e){var t,r=e.static,n=e.dynamic;if(ur in r){var a=!!r[ur];(t=an((function(e,t){return a}))).enable=a}else if(ur in n){var i=n[ur];t=on(i,(function(e,t){return e.invoke(t,i)}))}return t}(e),D.uniforms=function(e,t){var r=e.static,n=e.dynamic,a={};return Object.keys(r).forEach((function(e){var n,i=r[e];if(\"number\"==typeof i||\"boolean\"==typeof i)n=an((function(){return i}));else if(\"function\"==typeof i){var o=i._reglType;\"texture2d\"===o||\"textureCube\"===o?n=an((function(e){return e.link(i)})):\"framebuffer\"===o||\"framebufferCube\"===o?(_.command(i.color.length>0,'missing color attachment for framebuffer sent to uniform \"'+e+'\"',t.commandStr),n=an((function(e){return e.link(i.color[0])}))):_.commandRaise('invalid data for uniform \"'+e+'\"',t.commandStr)}else me(i)?n=an((function(t){return 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a=this._map.get(e);if(null==a){const s=(0,n.gcd)(t);if(s>1){t=(0,o.map)(t,(t=>t/s)),a=this._get_or_create(t);const[r,n,_]=a;a=[r,n,s],this._map.set(e,a)}else{const[r,n]=this._create_texture(t);a=[r,n,s],this._map.set(e,a)}}return a}get(t){return t.length%2==1&&(t=(0,_.concat)([t,t])),this._get_or_create(t)}}a.DashCache=c,c.__name__=\"DashCache\"},\n", - " 414: function _(n,t,e,r,o){function u(n,t){let e,r;n>t?(e=n,r=t):(e=t,r=n);let o=e%r;for(;0!=o;)e=r,r=o,o=e%r;return r}r(),e.gcd=function(n){let t=n[0];for(let e=1;e= 0.0 ? 1.0 : -1.0;\\n}\\n\\nvoid main()\\n{\\n if (a_show_curr < 0.5) {\\n // Line segment has non-finite value at one or both ends, do not render.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n const float min_miter_factor_round_join_mesh = sqrt(2.0);\\n\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n vec2 segment_along = normalize(a_point_end - a_point_start); // unit vector.\\n v_segment_length = length(a_point_end - a_point_start);\\n vec2 segment_right = right_vector(segment_along); // unit vector.\\n vec2 xy;\\n\\n bool miter_too_large_start = false;\\n bool miter_too_large_end = false;\\n\\n v_coords.y = a_position.y*halfwidth; // Overwritten later for end points.\\n\\n bool has_start_cap = a_show_prev < 0.5;\\n bool has_end_cap = a_show_next < 0.5;\\n\\n vec2 point_normal_start;\\n float cos_theta_start;\\n float turn_right_start;\\n if (has_start_cap)\\n point_normal_start = segment_right;\\n else {\\n vec2 prev_right = right_vector(normalize(a_point_start - a_point_prev));\\n point_normal_start = normalize(segment_right + prev_right);\\n cos_theta_start = dot(segment_right, point_normal_start); // Always +ve\\n turn_right_start = sign_no_zero(dot(segment_right, a_point_prev - a_point_start));\\n }\\n\\n vec2 point_normal_end;\\n float cos_theta_end;\\n float turn_right_end;\\n if (has_end_cap)\\n point_normal_end = segment_right;\\n else {\\n vec2 next_right = right_vector(normalize(a_point_next - a_point_end));\\n point_normal_end = normalize(segment_right + next_right);\\n cos_theta_end = dot(segment_right, point_normal_end); // Always +ve\\n turn_right_end = sign_no_zero(dot(segment_right, a_point_next - a_point_end));\\n }\\n\\n float miter_factor_start = 1.0 / dot(segment_right, point_normal_start);\\n float miter_factor_end = 1.0 / dot(segment_right, point_normal_end);\\n if (join_type == miter_join) {\\n // If miter too large, use bevel join instead.\\n miter_too_large_start = (miter_factor_start > u_miter_limit);\\n miter_too_large_end = (miter_factor_end > u_miter_limit);\\n }\\n\\n float sign_at_start = -sign(a_position.x); // +ve at segment start, -ve end.\\n vec2 point = sign_at_start > 0.0 ? a_point_start : a_point_end;\\n vec2 adjacent_point =\\n sign_at_start > 0.0 ? (has_start_cap ? a_point_start : a_point_prev)\\n : (has_end_cap ? a_point_end : a_point_next);\\n\\n if ( (has_start_cap && sign_at_start > 0.0) ||\\n (has_end_cap && sign_at_start < 0.0) ) {\\n // Cap.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (cap_type == butt_cap)\\n xy -= sign_at_start*0.5*u_antialias*segment_along;\\n else\\n xy -= sign_at_start*halfwidth*segment_along;\\n }\\n else { // Join.\\n // +ve if turning to right, -ve if to left.\\n float turn_sign = sign_at_start > 0.0 ? turn_right_start : turn_right_end;\\n\\n vec2 adjacent_right = sign_at_start*normalize(right_vector(point - adjacent_point));\\n vec2 point_right = normalize(segment_right + adjacent_right);\\n float miter_factor = sign_at_start > 0.0 ? miter_factor_start : miter_factor_end;\\n bool miter_too_large = sign_at_start > 0.0 ? miter_too_large_start : miter_too_large_end;\\n\\n if (abs(a_position.x) > 1.5) {\\n // Outer point, meets prev/next segment.\\n float factor; // multiplied by halfwidth...\\n\\n if (join_type == bevel_join || (join_type == miter_join && miter_too_large))\\n factor = 1.0 / miter_factor; // cos_theta.\\n else if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh)\\n factor = 1.0;\\n else // miter, or round (small angle only).\\n factor = miter_factor;\\n\\n xy = point - point_right*(halfwidth*turn_sign*factor);\\n v_coords.y = turn_sign*halfwidth*factor / miter_factor;\\n }\\n else if (turn_sign*a_position.y < 0.0) {\\n // Inner point, meets prev/next segment.\\n float len = halfwidth*miter_factor;\\n float segment_len = v_segment_length;\\n float adjacent_len = distance(point, adjacent_point);\\n\\n if (len <= min(segment_len, adjacent_len))\\n // Normal behaviour.\\n xy = point - point_right*(len*a_position.y);\\n else\\n // For short wide line segments the inner point using the above\\n // calculation can be outside of the line. Here clipping it.\\n xy = point + segment_right*(halfwidth*turn_sign);\\n }\\n else {\\n // Point along outside edge.\\n xy = point - segment_right*(halfwidth*a_position.y);\\n if (join_type == round_join &&\\n miter_factor > min_miter_factor_round_join_mesh) {\\n xy = line_intersection(xy, segment_along,\\n point - turn_sign*point_right*halfwidth,\\n right_vector(point_right));\\n }\\n }\\n }\\n\\n vec2 pos = xy + 0.5; // Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // in 0..1\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n\\n v_coords.x = dot(xy - a_point_start, segment_along);\\n v_flags = float(int(has_start_cap) +\\n 2*int(has_end_cap) +\\n 4*int(miter_too_large_start) +\\n 8*int(miter_too_large_end));\\n v_cos_theta_turn_right_start = cos_theta_start*turn_right_start;\\n v_cos_theta_turn_right_end = cos_theta_end*turn_right_end;\\n\\n#ifdef DASHED\\n v_length_so_far = a_length_so_far;\\n#endif\\n}\\n\"},\n", - " 416: function _(n,t,a,i,e){i();a.default=\"\\nprecision mediump float;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\nuniform float u_linewidth;\\nuniform float u_antialias;\\nuniform float u_line_join;\\nuniform float u_line_cap;\\nuniform vec4 u_line_color;\\n#ifdef DASHED\\nuniform sampler2D u_dash_tex;\\nuniform vec4 u_dash_tex_info;\\nuniform float u_dash_scale;\\nuniform float u_dash_offset;\\n#endif\\n\\nvarying float v_segment_length;\\nvarying vec2 v_coords;\\nvarying float v_flags;\\nvarying float v_cos_theta_turn_right_start;\\nvarying float v_cos_theta_turn_right_end;\\n#ifdef DASHED\\nvarying float v_length_so_far;\\n#endif\\n\\nfloat cross_z(in vec2 v0, in vec2 v1)\\n{\\n return v0.x*v1.y - v0.y*v1.x;\\n}\\n\\nfloat point_line_side(in vec2 point, in vec2 start, in vec2 end)\\n{\\n // +ve if point to right of line.\\n // Alternatively could do dot product with right_vector.\\n return cross_z(point - start, end - start);\\n}\\n\\nfloat point_line_distance(in vec2 point, in vec2 start, in vec2 end)\\n{\\n return point_line_side(point, start, end) / distance(start, end);\\n}\\n\\nvec2 right_vector(in vec2 v)\\n{\\n return vec2(v.y, -v.x);\\n}\\n\\nfloat bevel_join_distance(in float sign_start, in float halfwidth)\\n{\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n float distance_along = sign_start > 0.0 ? 0.0 : v_segment_length;\\n\\n // In v_coords reference frame (x is along segment, y across).\\n vec2 line_start = vec2(distance_along, halfwidth*turn_right);\\n float sin_alpha = cos_theta;\\n float cos_alpha = sqrt(1.0 - sin_alpha*sin_alpha);\\n vec2 line_along = vec2(-sign_start*turn_right*sin_alpha, -cos_alpha);\\n\\n return halfwidth + sign_start*point_line_distance(\\n v_coords, line_start, line_start+line_along);\\n}\\n\\nfloat cap(in int cap_type, in float x, in float y)\\n{\\n // x is distance along segment in direction away from end of segment,\\n // y is distance across segment.\\n if (cap_type == butt_cap)\\n return max(0.5*u_linewidth - x, abs(y));\\n else if (cap_type == square_cap)\\n return max(-x, abs(y));\\n else // cap_type == round_cap\\n return distance(vec2(min(x, 0.0), y), vec2(0.0, 0.0));\\n}\\n\\nfloat distance_to_alpha(in float dist)\\n{\\n return 1.0 - smoothstep(0.5*(u_linewidth - u_antialias),\\n 0.5*(u_linewidth + u_antialias), dist);\\n}\\n\\n#ifdef DASHED\\nfloat dash_distance(in float x)\\n{\\n // x is in direction of v_coords.x, i.e. along segment.\\n float tex_length = u_dash_tex_info.x;\\n float tex_offset = u_dash_tex_info.y;\\n float tex_dist_min = u_dash_tex_info.z;\\n float tex_dist_max = u_dash_tex_info.w;\\n\\n // Apply offset.\\n x += v_length_so_far - u_dash_scale*tex_offset + u_dash_offset;\\n\\n // Interpolate within texture to obtain distance to dash.\\n float dist = texture2D(u_dash_tex,\\n vec2(x / (tex_length*u_dash_scale), 0.0)).a;\\n\\n // Scale distance within min and max limits.\\n dist = tex_dist_min + dist*(tex_dist_max - tex_dist_min);\\n\\n return u_dash_scale*dist;\\n}\\n\\nfloat clip_dash_distance(in float x, in float offset, in float sign_along)\\n{\\n // Return clipped dash distance, sign_along is +1.0 if looking forward\\n // into next segment and -1.0 if looking backward into previous segment.\\n float half_antialias = 0.5*u_antialias;\\n\\n if (sign_along*x > half_antialias) {\\n // Outside antialias region, use usual dash distance.\\n return dash_distance(offset + x);\\n }\\n else {\\n // Inside antialias region.\\n // Dash distance at edge of antialias region clipped to half_antialias.\\n float edge_dist = min(dash_distance(offset + sign_along*half_antialias), half_antialias);\\n\\n // Physical distance from dash distance at edge of antialias region.\\n return edge_dist + sign_along*x - half_antialias;\\n }\\n}\\n\\nmat2 rotation_matrix(in float sign_start)\\n{\\n // Rotation matrix for v_coords from this segment to prev or next segment.\\n float cos_theta_turn_right = sign_start > 0.0 ? v_cos_theta_turn_right_start\\n : v_cos_theta_turn_right_end;\\n float cos_theta = abs(cos_theta_turn_right);\\n float turn_right = sign(cos_theta_turn_right);\\n\\n float sin_theta = sqrt(1.0 - cos_theta*cos_theta)*sign_start*turn_right;\\n float cos_2theta = 2.0*cos_theta*cos_theta - 1.0;\\n float sin_2theta = 2.0*sin_theta*cos_theta;\\n return mat2(cos_2theta, -sin_2theta, sin_2theta, cos_2theta);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int join_type = int(u_line_join + 0.5);\\n int cap_type = int(u_line_cap + 0.5);\\n float halfwidth = 0.5*(u_linewidth + u_antialias);\\n float half_antialias = 0.5*u_antialias;\\n\\n // Extract flags.\\n int flags = int(v_flags + 0.5);\\n bool miter_too_large_end = (flags / 8 > 0);\\n flags -= 8*int(miter_too_large_end);\\n bool miter_too_large_start = (flags / 4 > 0);\\n flags -= 4*int(miter_too_large_start);\\n bool has_end_cap = (flags / 2 > 0);\\n flags -= 2*int(has_end_cap);\\n bool has_start_cap = flags > 0;\\n\\n float dist = v_coords.y; // For straight segment, and miter join.\\n\\n // Along-segment coords with respect to end of segment, +ve inside segment\\n // so equivalent to v_coords.x at start of segment.\\n float end_coords_x = v_segment_length - v_coords.x;\\n\\n if (v_coords.x <= half_antialias) {\\n // At start of segment, either cap or join.\\n if (has_start_cap)\\n dist = cap(cap_type, v_coords.x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(0.0, 0.0));\\n else if (join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_start))\\n dist = max(abs(dist), bevel_join_distance(1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n else if (end_coords_x <= half_antialias) {\\n // At end of segment, either cap or join.\\n if (has_end_cap)\\n dist = cap(cap_type, end_coords_x, v_coords.y);\\n else if (join_type == round_join)\\n dist = distance(v_coords, vec2(v_segment_length, 0));\\n else if ((join_type == bevel_join ||\\n (join_type == miter_join && miter_too_large_end)))\\n dist = max(abs(dist), bevel_join_distance(-1.0, halfwidth));\\n // else a miter join which uses the default dist calculation.\\n }\\n\\n float alpha = distance_to_alpha(abs(dist));\\n\\n#ifdef DASHED\\n if (u_dash_tex_info.x >= 0.0) {\\n // Dashes in straight segments (outside of joins) are easily calculated.\\n dist = dash_distance(v_coords.x);\\n\\n if (!has_start_cap && cap_type == butt_cap) {\\n if (v_coords.x < half_antialias) {\\n // Outer of start join rendered solid color or not at all\\n // depending on whether corner point is in dash or gap, with\\n // antialiased ends.\\n if (dash_distance(0.0) > 0.0) {\\n // Corner is solid color.\\n dist = max(dist, min(half_antialias, -v_coords.x));\\n // Avoid visible antialiasing band between corner and dash.\\n dist = max(dist, dash_distance(half_antialias));\\n }\\n else {\\n // Use large negative value so corner not colored.\\n dist = -halfwidth;\\n\\n if (v_coords.x > -half_antialias) {\\n // Consider antialias region of dash after start region.\\n float edge_dist = min(dash_distance(half_antialias), half_antialias);\\n dist = max(dist, edge_dist + v_coords.x - half_antialias);\\n }\\n }\\n }\\n\\n vec2 prev_coords = rotation_matrix(1.0)*v_coords;\\n\\n if (abs(prev_coords.y) < halfwidth && prev_coords.x < half_antialias) {\\n // Extend dashes across from end of previous segment, with antialiased end.\\n float new_dist = clip_dash_distance(prev_coords.x, 0.0, -1.0);\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(prev_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n if (!has_end_cap && cap_type == butt_cap) {\\n if (end_coords_x < half_antialias) {\\n // Similar for end join.\\n if (dash_distance(v_segment_length) > 0.0) {\\n // Corner is solid color.\\n dist = max(dist, min(half_antialias, -end_coords_x));\\n // Avoid visible antialiasing band between corner and dash.\\n dist = max(dist, dash_distance(v_segment_length - half_antialias));\\n }\\n else {\\n // Use large negative value so corner not colored.\\n dist = -halfwidth;\\n\\n if (end_coords_x > -half_antialias) {\\n // Consider antialias region of dash before end region.\\n float edge_dist = min(dash_distance(v_segment_length - half_antialias),\\n half_antialias);\\n dist = max(dist, edge_dist + end_coords_x - half_antialias);\\n }\\n }\\n }\\n\\n vec2 next_coords = rotation_matrix(-1.0)*(v_coords - vec2(v_segment_length, 0.0));\\n\\n if (abs(next_coords.y) < halfwidth && next_coords.x > -half_antialias) {\\n // Extend dashes across from next segment, with antialiased end.\\n float new_dist = clip_dash_distance(next_coords.x, v_segment_length, 1.0);\\n new_dist = min(new_dist, 0.5*u_linewidth - abs(next_coords.y));\\n dist = max(dist, new_dist);\\n }\\n }\\n\\n dist = cap(cap_type, dist, v_coords.y);\\n\\n float dash_alpha = distance_to_alpha(dist);\\n alpha = min(alpha, dash_alpha);\\n }\\n#endif\\n\\n alpha = u_line_color.a*alpha;\\n gl_FragColor = vec4(u_line_color.rgb*alpha, alpha); // Premultiplied alpha.\\n}\\n\"},\n", - " 417: function _(n,i,e,t,a){t();e.default=\"\\nprecision mediump float;\\n\\nattribute vec2 a_position;\\nattribute vec2 a_center;\\nattribute float a_width;\\nattribute float a_height;\\nattribute float a_angle; // In radians\\nattribute float a_linewidth;\\nattribute vec4 a_line_color;\\nattribute vec4 a_fill_color;\\nattribute float a_line_cap;\\nattribute float a_line_join;\\nattribute float a_show;\\n#ifdef HATCH\\nattribute float a_hatch_pattern;\\nattribute float a_hatch_scale;\\nattribute float a_hatch_weight;\\nattribute vec4 a_hatch_color;\\n#endif\\n\\nuniform float u_pixel_ratio;\\nuniform vec2 u_canvas_size;\\nuniform float u_antialias;\\nuniform float u_size_hint;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size; // 2D size for rects compared to 1D for markers.\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_cap;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\nvoid main()\\n{\\n if (a_show < 0.5) {\\n // Do not show this rect.\\n gl_Position = vec4(-2.0, -2.0, 0.0, 1.0);\\n return;\\n }\\n\\n v_size = vec2(a_width, a_height);\\n v_linewidth = a_linewidth;\\n v_line_color = a_line_color;\\n v_fill_color = a_fill_color;\\n v_line_cap = a_line_cap;\\n v_line_join = a_line_join;\\n\\n if (v_linewidth < 1.0) {\\n // Linewidth less than 1 is implemented as 1 but with reduced alpha.\\n v_line_color.a *= v_linewidth;\\n v_linewidth = 1.0;\\n }\\n\\n#ifdef HATCH\\n v_hatch_pattern = a_hatch_pattern;\\n v_hatch_scale = a_hatch_scale;\\n v_hatch_weight = a_hatch_weight;\\n v_hatch_color = a_hatch_color;\\n#endif\\n\\n vec2 enclosing_size;\\n // Need extra size of (v_linewidth+u_antialias) if edge of marker parallel to\\n // edge of bounding box. If symmetric spike towards edge then multiply by\\n // 1/cos(theta) where theta is angle between spike and bbox edges.\\n int size_hint = int(u_size_hint + 0.5);\\n if (size_hint == 1) // Dash\\n enclosing_size = vec2(v_size.x + v_linewidth + u_antialias,\\n v_linewidth + u_antialias);\\n else if (size_hint == 2) // Dot\\n enclosing_size = 0.25*v_size + u_antialias;\\n else if (size_hint == 3) // Diamond\\n enclosing_size = vec2(v_size.x*(2.0/3.0) + (v_linewidth + u_antialias)*1.20185,\\n v_size.y + (v_linewidth + u_antialias)*1.80278);\\n else if (size_hint == 4) // Hex\\n enclosing_size = v_size + (v_linewidth + u_antialias)*vec2(2.0/sqrt(3.0), 1.0);\\n else if (size_hint == 5) // Square pin\\n enclosing_size = v_size + (v_linewidth + u_antialias)*3.1;\\n else if (size_hint == 6) // Triangle\\n enclosing_size = vec2(v_size.x + (v_linewidth + u_antialias)*sqrt(3.0),\\n v_size.y*(2.0/sqrt(3.0)) + (v_linewidth + u_antialias)*2.0);\\n else if (size_hint == 7) // Triangle pin\\n enclosing_size = v_size + (v_linewidth + u_antialias)*vec2(4.8, 6.0);\\n else if (size_hint == 8) // Star\\n enclosing_size = vec2(v_size.x*0.95106 + (v_linewidth + u_antialias)*3.0,\\n v_size.y + (v_linewidth + u_antialias)*3.2);\\n else\\n enclosing_size = v_size + v_linewidth + u_antialias;\\n\\n // Coordinates in rotated frame with respect to center of marker, used for\\n // distance functions in fragment shader.\\n v_coords = a_position*enclosing_size;\\n\\n float c = cos(-a_angle);\\n float s = sin(-a_angle);\\n mat2 rotation = mat2(c, -s, s, c);\\n\\n vec2 pos = a_center + rotation*v_coords;\\n#ifdef HATCH\\n // Coordinates for hatching in unrotated frame of reference.\\n v_hatch_coords = pos - 0.5;\\n#endif\\n pos += 0.5; // Make up for Bokeh's offset.\\n pos /= u_canvas_size / u_pixel_ratio; // 0 to 1.\\n gl_Position = vec4(2.0*pos.x - 1.0, 1.0 - 2.0*pos.y, 0.0, 1.0);\\n}\\n\"},\n", - " 418: function _(n,i,e,t,a){t();e.default=\"\\nprecision mediump float;\\n\\nconst float SQRT2 = sqrt(2.0);\\nconst float SQRT3 = sqrt(3.0);\\nconst float PI = 3.14159265358979323846;\\n\\nconst int butt_cap = 0;\\nconst int round_cap = 1;\\nconst int square_cap = 2;\\n\\nconst int miter_join = 0;\\nconst int round_join = 1;\\nconst int bevel_join = 2;\\n\\n#ifdef HATCH\\nconst int hatch_dot = 1;\\nconst int hatch_ring = 2;\\nconst int hatch_horizontal_line = 3;\\nconst int hatch_vertical_line = 4;\\nconst int hatch_cross = 5;\\nconst int hatch_horizontal_dash = 6;\\nconst int hatch_vertical_dash = 7;\\nconst int hatch_spiral = 8;\\nconst int hatch_right_diagonal_line = 9;\\nconst int hatch_left_diagonal_line = 10;\\nconst int hatch_diagonal_cross = 11;\\nconst int hatch_right_diagonal_dash = 12;\\nconst int hatch_left_diagonal_dash = 13;\\nconst int hatch_horizontal_wave = 14;\\nconst int hatch_vertical_wave = 15;\\nconst int hatch_criss_cross = 16;\\n#endif\\n\\nuniform float u_antialias;\\n\\nvarying float v_linewidth;\\nvarying vec2 v_size;\\nvarying vec4 v_line_color;\\nvarying vec4 v_fill_color;\\nvarying float v_line_cap;\\nvarying float v_line_join;\\nvarying vec2 v_coords;\\n#ifdef HATCH\\nvarying float v_hatch_pattern;\\nvarying float v_hatch_scale;\\nvarying float v_hatch_weight;\\nvarying vec4 v_hatch_color;\\nvarying vec2 v_hatch_coords;\\n#endif\\n\\n// Lines within the marker (dot, cross, x and y) are added at the end as they are\\n// on top of the fill rather than astride it.\\n#if defined(USE_CIRCLE_DOT) || defined(USE_DIAMOND_DOT) || defined(USE_DOT) || defined(USE_HEX_DOT) || defined(USE_SQUARE_DOT) || defined(USE_STAR_DOT) || defined(USE_TRIANGLE_DOT)\\n #define APPEND_DOT\\n#endif\\n\\n#if defined(USE_CIRCLE_CROSS) || defined(USE_SQUARE_CROSS)\\n #define APPEND_CROSS\\n#endif\\n\\n#ifdef USE_DIAMOND_CROSS\\n #define APPEND_CROSS_2\\n#endif\\n\\n#ifdef USE_CIRCLE_X\\n #define APPEND_X\\n #define APPEND_X_LEN (0.5*v_size.x)\\n#endif\\n\\n#ifdef USE_SQUARE_X\\n #define APPEND_X\\n #define APPEND_X_LEN (v_size.x/SQRT2)\\n#endif\\n\\n#ifdef USE_CIRCLE_Y\\n #define APPEND_Y\\n#endif\\n\\n#if defined(USE_ASTERISK) || defined(USE_CROSS) || defined(USE_DASH) || defined(USE_DOT) || defined(USE_X) || defined(USE_Y)\\n // No fill.\\n #define LINE_ONLY\\n#endif\\n\\n#if defined(LINE_ONLY) || defined(APPEND_CROSS) || defined(APPEND_CROSS_2) || defined(APPEND_X) || defined(APPEND_Y)\\nfloat end_cap_distance(in vec2 p, in vec2 end_point, in vec2 unit_direction, in int line_cap)\\n{\\n vec2 offset = p - end_point;\\n if (line_cap == butt_cap)\\n return dot(offset, unit_direction) + 0.5*v_linewidth;\\n else if (line_cap == square_cap)\\n return dot(offset, unit_direction);\\n else if (line_cap == round_cap && dot(offset, unit_direction) > 0.0)\\n return length(offset);\\n else\\n // Default is outside of line and should be -0.5*(v_linewidth+u_antialias) or less,\\n // so here avoid the multiplication.\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if !(defined(LINE_ONLY) || defined(USE_SQUARE_PIN) || defined(USE_TRIANGLE_PIN))\\n// For line join at a vec2 corner where 2 line segments meet, consider bevel points which are the 2\\n// points obtained by moving half a linewidth away from the corner point in the directions normal to\\n// the line segments. The line through these points is the bevel line, characterised by a vec2\\n// unit_normal and offset distance from the corner point. Edge of bevel join straddles this line,\\n// round join occurs outside of this line centred on the corner point. In general\\n// offset = (linewidth/2)*sin(alpha/2)\\n// where alpha is the angle between the 2 line segments at the corner.\\nfloat line_join_distance_no_miter(\\n in vec2 p, in vec2 corner, in vec2 unit_normal, in float offset, in int line_join)\\n{\\n // Simplified version of line_join_distance ignoring miter which most markers do implicitly\\n // as they are composed of straight line segments.\\n float dist_outside = dot((p - corner), unit_normal) - offset;\\n\\n if (line_join == bevel_join && dist_outside > -0.5*u_antialias)\\n return dist_outside + 0.5*v_linewidth;\\n else if (dist_outside > 0.0) // round_join\\n return distance(p, corner);\\n else\\n // Default is outside of line and should be -0.5*(v_linewidth+u_antialias) or less,\\n // so here avoid the multiplication.\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if defined(USE_SQUARE_PIN) || defined(USE_TRIANGLE_PIN)\\n// Line join distance including miter but only one-sided check as assuming use of symmetry in\\n// calling function.\\nfloat line_join_distance_incl_miter(\\n in vec2 p, in vec2 corner, in vec2 unit_normal, in float offset, in int line_join,\\n vec2 miter_unit_normal)\\n{\\n float dist_outside = dot((p - corner), unit_normal) - offset;\\n\\n if (line_join == miter_join && dist_outside > 0.0)\\n return dot((p - corner), miter_unit_normal);\\n else if (line_join == bevel_join && dist_outside > -0.5*u_antialias)\\n return dist_outside + 0.5*v_linewidth;\\n else if (dist_outside > 0.0) // round_join\\n return distance(p, corner);\\n else\\n return -v_linewidth-u_antialias;\\n}\\n#endif\\n\\n#if defined(APPEND_CROSS) || defined(APPEND_X) || defined(USE_ASTERISK) || defined(USE_CROSS) || defined(USE_X)\\nfloat one_cross(in vec2 p, in int line_cap, in float len)\\n{\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(len, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#ifdef APPEND_CROSS_2\\nfloat one_cross_2(in vec2 p, in int line_cap, in vec2 lengths)\\n{\\n // Cross with different length in x and y directions.\\n p = abs(p);\\n bool switch_xy = (p.y > p.x);\\n p = switch_xy ? p.yx : p.xy;\\n float len = switch_xy ? lengths.y : lengths.x;\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(len, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#if defined(APPEND_Y) || defined(USE_Y)\\nfloat one_y(in vec2 p, in int line_cap, in float len)\\n{\\n p = vec2(abs(p.x), -p.y);\\n\\n // End point of line to right is (1/2, 1/3)*len*SQRT3.\\n // Unit vector along line is (1/2, 1/3)*k where k = 6/SQRT13.\\n const float k = 6.0/sqrt(13.0);\\n vec2 unit_along = vec2(0.5*k, k/3.0);\\n vec2 end_point = vec2(0.5*len*SQRT3, len*SQRT3/3.0);\\n float dist = max(abs(dot(p, vec2(-unit_along.y, unit_along.x))),\\n end_cap_distance(p, end_point, unit_along, line_cap));\\n\\n if (p.y < 0.0) {\\n // Vertical line.\\n float vert_dist = max(p.x,\\n end_cap_distance(p, vec2(0.0, -len), vec2(0.0, -1.0), line_cap));\\n dist = min(dist, vert_dist);\\n }\\n return dist;\\n}\\n#endif\\n\\n// One marker_distance function per marker type.\\n// Distance is zero on edge of marker, +ve outside and -ve inside.\\n\\n#ifdef USE_ASTERISK\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n vec2 p_diag = vec2((p.x + p.y)/SQRT2, (p.x - p.y)/SQRT2);\\n float len = 0.5*v_size.x;\\n return min(one_cross(p, line_cap, len), // cross\\n one_cross(p_diag, line_cap, len)); // x\\n}\\n#endif\\n\\n#if defined(USE_CIRCLE) || defined(USE_CIRCLE_CROSS) || defined(USE_CIRCLE_DOT) || defined(USE_CIRCLE_X) || defined(USE_CIRCLE_Y)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return length(p) - 0.5*v_size.x;\\n}\\n#endif\\n\\n#ifdef USE_CROSS\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return one_cross(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n#ifdef USE_DASH\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n p = abs(p);\\n float dist = p.y;\\n float end_dist = end_cap_distance(p, vec2(0.5*v_size.x, 0.0), vec2(1.0, 0.0), line_cap);\\n return max(dist, end_dist);\\n}\\n#endif\\n\\n#if defined(USE_DIAMOND) || defined(USE_DIAMOND_CROSS) || defined(USE_DIAMOND_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // Only need to consider +ve quadrant, the 2 end points are (2r/3, 0) and (0, r)\\n // where r = radius = v_size.x/2.\\n // Line has outward-facing unit normal vec2(1, 2/3)/k where k = SQRT13/3\\n // hence vec2(3, 2)/SQRT13, and distance from origin of 2r/(3k) = 2r/SQRT13.\\n p = abs(p);\\n float r = 0.5*v_size.x;\\n const float SQRT13 = sqrt(13.0);\\n float dist = dot(p, vec2(3.0, 2.0))/SQRT13 - 2.0*r/SQRT13;\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, r), vec2(0.0, 1.0), v_linewidth/SQRT13, line_join));\\n\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r*2.0/3.0, 0.0), vec2(1.0, 0.0), v_linewidth*(1.5/SQRT13), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_DOT\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Dot is always appended.\\n return v_linewidth+u_antialias;\\n}\\n#endif\\n\\n#if defined(USE_HEX) || defined(USE_HEX_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // A regular hexagon has v_size.x == v.size_y = r where r is the length of\\n // each of the 3 sides of the 6 equilateral triangles that comprise the hex.\\n // Only consider +ve quadrant, the 3 corners are at (0, h), (rx/2, h), (rx, 0)\\n // where rx = 0.5*v_size.x, ry = 0.5*v_size.y and h = ry*SQRT3/2.\\n // Sloping line has outward normal vec2(h, rx/2). Length of this is\\n // len = sqrt(h**2 + rx**2/4) to give unit normal (h, rx/2)/len and distance\\n // from origin of this line is rx*h/len.\\n p = abs(p);\\n float rx = v_size.x/2.0;\\n float h = v_size.y*(SQRT3/4.0);\\n float len_normal = sqrt(h*h + 0.25*rx*rx);\\n vec2 unit_normal = vec2(h, 0.5*rx) / len_normal;\\n float dist = max(dot(p, unit_normal) - rx*h/len_normal, // Distance from sloping line.\\n p.y - h); // Distance from horizontal line.\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(rx, 0.0), vec2(1.0, 0.0), 0.5*v_linewidth*unit_normal.x, line_join));\\n\\n unit_normal = normalize(unit_normal + vec2(0.0, 1.0)); // At (rx/2, h) corner.\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.5*rx, h), unit_normal, 0.5*v_linewidth*unit_normal.y, line_join));\\n }\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_PLUS\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // Only need to consider one octant, the +ve quadrant with x >= y.\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n\\n // 3 corners are (r, 0), (r, 3r/8) and (3r/8, 3r/8).\\n float r = 0.5*v_size.x;\\n p = p - vec2(r, 0.375*r); // Distance with respect to outside corner\\n float dist = max(p.x, p.y);\\n\\n if (line_join != miter_join) {\\n // Outside corner\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, 0.0), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n\\n // Inside corner\\n dist = min(dist, -line_join_distance_no_miter(\\n p, vec2(-5.0*r/8.0, 0.0), vec2(-1.0/SQRT2, -1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_SQUARE) || defined(USE_SQUARE_CROSS) || defined(USE_SQUARE_DOT) || defined(USE_SQUARE_X)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n vec2 p2 = abs(p) - v_size/2.0; // Offset from corner\\n float dist = max(p2.x, p2.y);\\n\\n if (line_join != miter_join)\\n dist = max(dist, line_join_distance_no_miter(\\n p2, vec2(0.0, 0.0), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth/(2.0*SQRT2), line_join));\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_SQUARE_PIN\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n p = abs(p);\\n p = (p.y > p.x) ? p.yx : p.xy;\\n // p is in octant between y=0 and y=x.\\n // Quadratic bezier curve passes through (r, r), (11r/16, 0) and (r, -r).\\n // Circular arc that passes through the same points has center at\\n // x = r + 231r/160 = 2.44275r and y = 0 and hence radius is\\n // x - 11r/16 = 1.75626 precisely.\\n float r = 0.5*v_size.x;\\n float center_x = r*2.44375;\\n float radius = r*1.75626;\\n float dist = radius - distance(p, vec2(center_x, 0.0));\\n\\n // Magic number is 0.5*sin(atan(8/5) - pi/4)\\n dist = max(dist, line_join_distance_incl_miter(\\n p, vec2(r, r), vec2(1.0/SQRT2, 1.0/SQRT2), v_linewidth*0.1124297533493792, line_join,\\n vec2(8.0/sqrt(89.0), -5.0/sqrt(89.0))));\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_STAR) || defined(USE_STAR_DOT)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n const float SQRT5 = sqrt(5.0);\\n const float COS72 = 0.25*(SQRT5 - 1.0);\\n const float SIN72 = sqrt((5.0+SQRT5) / 8.0);\\n\\n float angle = atan(p.x, p.y); // In range -pi to +pi clockwise from +y direction.\\n angle = mod(angle, 0.4*PI) - 0.2*PI; // In range -pi/5 to +pi/5 clockwise from +y direction.\\n p = length(p)*vec2(cos(angle), abs(sin(angle))); // (x,y) in pi/10 (36 degree) sector.\\n\\n // 2 corners are at (r, 0) and (r-a*SIN72, a*COS72) where a = r sqrt(5-2*sqrt(5)).\\n // Line has outward-facing unit normal vec2(COS72, SIN72) and distance from\\n // origin of dot(vec2(r, 0), vec2(COS72, SIN72)) = r*COS72\\n float r = 0.5*v_size.x;\\n float a = r*sqrt(5.0 - 2.0*SQRT5);\\n float dist = dot(p, vec2(COS72, SIN72)) - r*COS72;\\n\\n if (line_join != miter_join) {\\n // Outside corner\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r, 0.0), vec2(1.0, 0.0), v_linewidth*(0.5*COS72), line_join));\\n\\n // Inside corner\\n const float COS36 = sqrt(0.5 + COS72/2.0);\\n const float SIN36 = sqrt(0.5 - COS72/2.0);\\n dist = min(dist, -line_join_distance_no_miter(\\n p, vec2(r-a*SIN72, a*COS72), vec2(-COS36, -SIN36), v_linewidth*(0.5*COS36), line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#if defined(USE_TRIANGLE) || defined(USE_TRIANGLE_DOT) || defined(USE_INVERTED_TRIANGLE)\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n // For normal triangle 3 corners are at (-r, a), (r, a), (0, a-h)=(0, -2h/3)\\n // given r = radius = v_size.x/2, h = SQRT3*r, a = h/3.\\n // Sloping line has outward-facing unit normal vec2(h, -r)/2r = vec2(SQRT3, -1)/2\\n // and distance from origin of a. Horizontal line has outward-facing unit normal\\n // vec2(0, 1) and distance from origin of a.\\n float r = 0.5*v_size.x;\\n float a = r*SQRT3/3.0;\\n\\n // Only need to consider +ve x.\\n#ifdef USE_INVERTED_TRIANGLE\\n p = vec2(abs(p.x), -p.y);\\n#else\\n p = vec2(abs(p.x), p.y);\\n#endif\\n\\n float dist = max(0.5*dot(p, vec2(SQRT3, -1.0)) - a, // Distance from sloping line.\\n p.y - a); // Distance from horizontal line.\\n\\n if (line_join != miter_join) {\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(0.0, -(2.0/SQRT3)*r), vec2(0.0, -1.0), v_linewidth*0.25, line_join));\\n\\n dist = max(dist, line_join_distance_no_miter(\\n p, vec2(r, a), vec2(SQRT3/2.0, 0.5), v_linewidth*0.25, line_join));\\n }\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_TRIANGLE_PIN\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n float angle = atan(p.x, -p.y); // In range -pi to +pi.\\n angle = mod(angle, PI*2.0/3.0) - PI/3.0; // In range -pi/3 to pi/3.\\n p = length(p)*vec2(cos(angle), abs(sin(angle))); // (x,y) in range 0 to pi/3.\\n // Quadratic bezier curve passes through (a, r), ((a+b)/2, 0) and (a, -r) where\\n // a = r/SQRT3, b = 3a/8 = r SQRT3/8. Circular arc that passes through the same points has\\n // center at (a+x, 0) and radius x+c where c = (a-b)/2 and x = (r**2 - c**2) / (2c).\\n // Ignore r factor until the end so can use const.\\n const float a = 1.0/SQRT3;\\n const float b = SQRT3/8.0;\\n const float c = (a-b)/2.0;\\n const float x = (1.0 - c*c) / (2.0*c);\\n const float center_x = x + a;\\n const float radius = x + c;\\n float r = 0.5*v_size.x;\\n float dist = r*radius - distance(p, vec2(r*center_x, 0.0));\\n\\n // Magic number is 0.5*sin(atan(8*sqrt(3)/5) - pi/3)\\n dist = max(dist, line_join_distance_incl_miter(\\n p, vec2(a*r, r), vec2(0.5, 0.5*SQRT3), v_linewidth*0.0881844526878324, line_join,\\n vec2(8.0*SQRT3, -5.0)/sqrt(217.0)));\\n\\n return dist;\\n}\\n#endif\\n\\n#ifdef USE_X\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n p = vec2((p.x + p.y)/SQRT2, (p.x - p.y)/SQRT2);\\n return one_cross(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n#ifdef USE_Y\\nfloat marker_distance(in vec2 p, in int line_cap, in int line_join)\\n{\\n // Assuming v_size.x == v.size_y\\n return one_y(p, line_cap, 0.5*v_size.x);\\n}\\n#endif\\n\\n// Convert distance from edge of marker to fraction in range 0 to 1, depending\\n// on antialiasing width.\\nfloat distance_to_fraction(in float dist)\\n{\\n return 1.0 - smoothstep(-0.5*u_antialias, 0.5*u_antialias, dist);\\n}\\n\\n// Return fraction from 0 (no fill color) to 1 (full fill color).\\nfloat fill_fraction(in float dist)\\n{\\n return distance_to_fraction(dist);\\n}\\n\\n// Return fraction in range 0 (no line color) to 1 (full line color).\\nfloat line_fraction(in float dist)\\n{\\n return distance_to_fraction(abs(dist) - 0.5*v_linewidth);\\n}\\n\\n// Return fraction (in range 0 to 1) of a color, with premultiplied alpha.\\nvec4 fractional_color(in vec4 color, in float fraction)\\n{\\n color.a *= fraction;\\n color.rgb *= color.a;\\n return color;\\n}\\n\\n// Blend colors that have premultiplied alpha.\\nvec4 blend_colors(in vec4 src, in vec4 dest)\\n{\\n return (1.0 - src.a)*dest + src;\\n}\\n\\n#ifdef APPEND_DOT\\nfloat dot_fraction(in vec2 p)\\n{\\n // Assuming v_size.x == v_size.y\\n float radius = 0.125*v_size.x;\\n float dot_distance = max(length(p) - radius, -0.5*u_antialias);\\n return fill_fraction(dot_distance);\\n}\\n#endif\\n\\n#ifdef HATCH\\n// Wrap coordinate(s) by removing integer part to give distance from center of\\n// repeat, in the range -0.5 to +0.5.\\nfloat wrap(in float x)\\n{\\n return fract(x) - 0.5;\\n}\\n\\nvec2 wrap(in vec2 xy)\\n{\\n return fract(xy) - 0.5;\\n}\\n\\n// Return fraction from 0 (no hatch color) to 1 (full hatch color).\\nfloat hatch_fraction(in vec2 coords, in int hatch_pattern)\\n{\\n float scale = v_hatch_scale; // Hatch repeat distance.\\n\\n // Coordinates and linewidth/halfwidth are scaled to hatch repeat distance.\\n coords = coords / scale;\\n float halfwidth = 0.5*v_hatch_weight / scale; // Half the hatch linewidth.\\n\\n // Default is to return fraction of zero, i.e. no pattern.\\n float dist = u_antialias;\\n\\n if (hatch_pattern == hatch_dot) {\\n const float dot_radius = 0.25;\\n dist = length(wrap(coords)) - dot_radius;\\n }\\n else if (hatch_pattern == hatch_ring) {\\n const float ring_radius = 0.25;\\n dist = abs(length(wrap(coords)) - ring_radius) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_line) {\\n dist = abs(wrap(coords.y)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_line) {\\n dist = abs(wrap(coords.x)) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_cross) {\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_dash) {\\n // Dashes have square caps.\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.y)),\\n abs(wrap(coords.x) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_dash) {\\n const float halflength = 0.25;\\n dist = max(abs(wrap(coords.x)),\\n abs(wrap(coords.y) + 0.25) - halflength) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_spiral) {\\n vec2 wrap2 = wrap(coords);\\n float angle = wrap(atan(wrap2.y, wrap2.x) / (2.0*PI));\\n // Canvas spiral radius increases by scale*pi/15 each rotation.\\n const float dr = PI/15.0;\\n float radius = length(wrap2);\\n // At any angle, spiral lines are equally spaced dr apart.\\n // Find distance to nearest of these lines.\\n float frac = fract((radius - dr*angle) / dr); // 0 to 1.\\n dist = dr*(abs(frac - 0.5));\\n dist = min(dist, radius) - halfwidth; // Consider center point also.\\n }\\n else if (hatch_pattern == hatch_right_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x + coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_line) {\\n dist = abs(wrap(2.0*coords.x - coords.y))/sqrt(5.0) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_diagonal_cross) {\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n dist = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_right_diagonal_dash) {\\n float across = coords.x + coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x - coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_left_diagonal_dash) {\\n float across = coords.x - coords.y + 0.5;\\n dist = abs(wrap(across)) / SQRT2; // Distance to nearest solid line.\\n\\n across = floor(across); // Offset for dash.\\n float along = wrap(0.5*(coords.x + coords.y + across));\\n const float halflength = 0.25;\\n along = abs(along) - halflength; // Distance along line.\\n\\n dist = max(dist, along) - halfwidth;\\n }\\n else if (hatch_pattern == hatch_horizontal_wave) {\\n float wrapx = wrap(coords.x);\\n float wrapy = wrap(coords.y - 0.25 + abs(wrapx));\\n dist = abs(wrapy) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_vertical_wave) {\\n float wrapy = wrap(coords.y);\\n float wrapx = wrap(coords.x - 0.25 + abs(wrapy));\\n dist = abs(wrapx) / SQRT2 - halfwidth;\\n }\\n else if (hatch_pattern == hatch_criss_cross) {\\n float plus = min(abs(wrap(coords.x)), abs(wrap(coords.y)));\\n\\n coords = vec2(coords.x + coords.y + 0.5, coords.x - coords.y + 0.5);\\n float X = min(abs(wrap(coords.x)), abs(wrap(coords.y))) / SQRT2;\\n\\n dist = min(plus, X) - halfwidth;\\n }\\n\\n return distance_to_fraction(dist*scale);\\n}\\n#endif\\n\\nvoid main()\\n{\\n int line_cap = int(v_line_cap + 0.5);\\n int line_join = int(v_line_join + 0.5);\\n#ifdef HATCH\\n int hatch_pattern = int(v_hatch_pattern + 0.5);\\n#endif\\n\\n float dist = marker_distance(v_coords, line_cap, line_join);\\n\\n#ifdef LINE_ONLY\\n vec4 color = vec4(0.0, 0.0, 0.0, 0.0);\\n#else\\n float fill_frac = fill_fraction(dist);\\n vec4 color = fractional_color(v_fill_color, fill_frac);\\n#endif\\n\\n#if defined(HATCH) && !defined(LINE_ONLY)\\n if (hatch_pattern > 0 && fill_frac > 0.0) {\\n float hatch_frac = hatch_fraction(v_hatch_coords, hatch_pattern);\\n vec4 hatch_color = fractional_color(v_hatch_color, hatch_frac*fill_frac);\\n color = blend_colors(hatch_color, color);\\n }\\n#endif\\n\\n float line_frac = line_fraction(dist);\\n\\n#ifdef APPEND_DOT\\n line_frac = max(line_frac, dot_fraction(v_coords));\\n#endif\\n#ifdef APPEND_CROSS\\n line_frac = max(line_frac, line_fraction(one_cross(v_coords, line_cap, 0.5*v_size.x)));\\n#endif\\n#ifdef APPEND_CROSS_2\\n vec2 lengths = vec2(v_size.x/3.0, v_size.x/2.0);\\n line_frac = max(line_frac, line_fraction(one_cross_2(v_coords, line_cap, lengths)));\\n#endif\\n#ifdef APPEND_X\\n vec2 p = vec2((v_coords.x + v_coords.y)/SQRT2, (v_coords.x - v_coords.y)/SQRT2);\\n line_frac = max(line_frac, line_fraction(one_cross(p, line_cap, APPEND_X_LEN)));\\n#endif\\n#ifdef APPEND_Y\\n line_frac = max(line_frac, line_fraction(one_y(v_coords, line_cap, 0.5*v_size.x)));\\n#endif\\n\\n if (line_frac > 0.0) {\\n vec4 line_color = fractional_color(v_line_color, line_frac);\\n color = blend_colors(line_color, color);\\n }\\n\\n gl_FragColor = color;\\n}\\n\"},\n", - " 419: function _(t,_,i,h,e){h();const s=t(420),a=t(421),r=t(422);class l extends s.BaseGLGlyph{constructor(t,_){super(t,_),this.glyph=_,this._antialias=1.5,this._show_all=!1}_draw_one_marker_type(t,_,i){const h={scissor:this.regl_wrapper.scissor,viewport:this.regl_wrapper.viewport,canvas_size:[_.width,_.height],pixel_ratio:_.pixel_ratio,center:i._centers,width:i._widths,height:i._heights,angle:i._angles,size_hint:(0,r.marker_type_to_size_hint)(t),nmarkers:i.nvertices,antialias:this._antialias,linewidth:this._linewidths,line_color:this._line_rgba,fill_color:this._fill_rgba,line_cap:this._line_caps,line_join:this._line_joins,show:this._show};if(this._have_hatch){const _=Object.assign(Object.assign({},h),{hatch_pattern:this._hatch_patterns,hatch_scale:this._hatch_scales,hatch_weight:this._hatch_weights,hatch_color:this._hatch_rgba});this.regl_wrapper.marker_hatch(t)(_)}else this.regl_wrapper.marker_no_hatch(t)(h)}_set_visuals(){const t=this._get_visuals(),_=t.fill,i=t.line;if(null==this._linewidths&&(this._linewidths=new a.Float32Buffer(this.regl_wrapper),this._line_caps=new a.Uint8Buffer(this.regl_wrapper),this._line_joins=new a.Uint8Buffer(this.regl_wrapper),this._line_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper),this._fill_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper)),this._linewidths.set_from_prop(i.line_width),this._line_caps.set_from_line_cap(i.line_cap),this._line_joins.set_from_line_join(i.line_join),this._line_rgba.set_from_color(i.line_color,i.line_alpha),this._fill_rgba.set_from_color(_.fill_color,_.fill_alpha),this._have_hatch=t.hatch.doit,this._have_hatch){const _=t.hatch;null==this._hatch_patterns&&(this._hatch_patterns=new a.Uint8Buffer(this.regl_wrapper),this._hatch_scales=new a.Float32Buffer(this.regl_wrapper),this._hatch_weights=new a.Float32Buffer(this.regl_wrapper),this._hatch_rgba=new a.NormalizedUint8Buffer(this.regl_wrapper)),this._hatch_patterns.set_from_hatch_pattern(_.hatch_pattern),this._hatch_scales.set_from_prop(_.hatch_scale),this._hatch_weights.set_from_prop(_.hatch_weight),this._hatch_rgba.set_from_color(_.hatch_color,_.hatch_alpha)}}}i.BaseMarkerGL=l,l.__name__=\"BaseMarkerGL\",l.missing_point=-1e4},\n", - " 420: function _(e,t,s,i,h){i();class a{constructor(e,t){this.glyph=t,this.nvertices=0,this.size_changed=!1,this.data_changed=!1,this.visuals_changed=!1,this.regl_wrapper=e}set_data_changed(){const{data_size:e}=this.glyph;e!=this.nvertices&&(this.nvertices=e,this.size_changed=!0),this.data_changed=!0}set_visuals_changed(){this.visuals_changed=!0}render(e,t,s){if(0==t.length)return!0;const{width:i,height:h}=this.glyph.renderer.plot_view.canvas_view.webgl.canvas,a={pixel_ratio:this.glyph.renderer.plot_view.canvas_view.pixel_ratio,width:i,height:h};return this.draw(t,s,a),!0}}s.BaseGLGlyph=a,a.__name__=\"BaseGLGlyph\"},\n", - " 421: function _(r,t,a,e,s){e();const i=r(422),_=r(22);class n{constructor(r){this.regl_wrapper=r,this.is_scalar=!0}get_sized_array(r){return null!=this.array&&this.array.length==r||(this.array=this.new_array(r)),this.array}is_normalized(){return!1}get length(){return null!=this.array?this.array.length:0}set_from_array(r){const t=r.length,a=this.get_sized_array(t);for(let e=0;e0}_set_data(){const s=this.glyph.sx.length,i=s-1;this._is_closed=s>2&&this.glyph.sx[0]==this.glyph.sx[s-1]&&this.glyph.sy[0]==this.glyph.sy[s-1]&&isFinite(this.glyph.sx[0])&&isFinite(this.glyph.sy[0]),null==this._points&&(this._points=new o.Float32Buffer(this.regl_wrapper));const t=this._points.get_sized_array(2*(s+2));for(let i=1;is/255)),this._linewidth=s.line_width.value,this._linewidth<1&&(this._color[3]*=this._linewidth,this._linewidth=1),this._line_dash=(0,a.resolve_line_dash)(s.line_dash.value),this._is_dashed()&&([this._dash_tex_info,this._dash_tex,this._dash_scale]=this.regl_wrapper.get_dash(this._line_dash),this._dash_offset=s.line_dash_offset.value)}}t.LineGL=r,r.__name__=\"LineGL\"},\n", - " 427: function _(s,t,i,e,r){e();const h=s(421),a=s(424);class n extends a.SingleMarkerGL{constructor(s,t){super(s,t),this.glyph=t}draw(s,t,i){this._draw_impl(s,i,t.glglyph,\"square\")}_get_visuals(){return this.glyph.visuals}_set_data(){const s=this.nvertices;null==this._centers&&(this._centers=new h.Float32Buffer(this.regl_wrapper),this._widths=new h.Float32Buffer(this.regl_wrapper),this._heights=new h.Float32Buffer(this.regl_wrapper),this._angles=new h.Float32Buffer(this.regl_wrapper),this._angles.set_from_scalar(0));const t=this._centers.get_sized_array(2*s),i=this._heights.get_sized_array(s),e=this._widths.get_sized_array(s);for(let r=0;r1||s.length<_){this._show_all=!1,n.fill(0),r=0;for(const e of s)1!=h&&i._marker_types.get(e)!=t||(n[e]=255,r++)}else this._show_all&&a==_||(this._show_all=!0,n.fill(255));this._show.update(),0!=r&&this._draw_one_marker_type(t,e,i)}}_get_visuals(){return this.glyph.visuals}_set_data(){const s=this.nvertices;null==this._centers&&(this._centers=new r.Float32Buffer(this.regl_wrapper),this._widths=new r.Float32Buffer(this.regl_wrapper),this._heights=this._widths,this._angles=new r.Float32Buffer(this.regl_wrapper));const t=this._centers.get_sized_array(2*s);for(let e=0;ethis.render()))}remove(){null!=this.icon_view&&this.icon_view.remove(),super.remove()}styles(){return[...super.styles(),d.default]}_render_button(...t){return(0,c.button)({type:\"button\",disabled:this.model.disabled,class:[h.btn,h[`btn_${this.model.button_type}`]]},...t)}render(){super.render(),this.button_el=this._render_button(this.model.label),this.button_el.addEventListener(\"click\",(()=>this.click())),null!=this.icon_view&&(\"\"!=this.model.label?(0,c.prepend)(this.button_el,this.icon_view.el,(0,c.nbsp)()):(0,c.prepend)(this.button_el,this.icon_view.el),this.icon_view.render()),this.group_el=(0,c.div)({class:h.btn_group},this.button_el),this.el.appendChild(this.group_el)}click(){}}n.AbstractButtonView=b,b.__name__=\"AbstractButtonView\";class p extends _.Control{constructor(t){super(t)}}n.AbstractButton=p,o=p,p.__name__=\"AbstractButton\",o.define((({String:t,Ref:e,Nullable:n})=>({label:[t,\"Button\"],icon:[n(e(a.AbstractIcon)),null],button_type:[r.ButtonType,\"default\"]})))},\n", - " 442: function _(t,e,o,s,n){s();const i=t(512),l=t(43);class c extends i.WidgetView{connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.disabled,(()=>{for(const t of this.controls())(0,l.toggle_attribute)(t,\"disabled\",this.model.disabled)}))}}o.ControlView=c,c.__name__=\"ControlView\";class r extends i.Widget{constructor(t){super(t)}}o.Control=r,r.__name__=\"Control\"},\n", - " 512: function _(i,e,t,n,o){var r;n();const s=i(312);class _ extends s.HTMLBoxView{get orientation(){return\"horizontal\"}get default_size(){return this.model.default_size}_width_policy(){return\"horizontal\"==this.orientation?super._width_policy():\"fixed\"}_height_policy(){return\"horizontal\"==this.orientation?\"fixed\":super._height_policy()}box_sizing(){const i=super.box_sizing();return\"horizontal\"==this.orientation?null==i.width&&(i.width=this.default_size):null==i.height&&(i.height=this.default_size),i}}t.WidgetView=_,_.__name__=\"WidgetView\";class h extends s.HTMLBox{constructor(i){super(i)}}t.Widget=h,r=h,h.__name__=\"Widget\",r.define((({Number:i})=>({default_size:[i,300]}))),r.override({margin:[5,5,5,5]})},\n", - " 444: function _(c,t,s,n,e){n();const o=c(53),_=c(226);class a extends _.DOMView{}s.AbstractIconView=a,a.__name__=\"AbstractIconView\";class r extends o.Model{constructor(c){super(c)}}s.AbstractIcon=r,r.__name__=\"AbstractIcon\"},\n", - " 445: function _(e,t,n,s,i){s();const h=e(1);var o;const _=e(446),u=e(43),r=e(10),c=(0,h.__importStar)(e(229)),a=c;class l extends _.TextInputView{constructor(){super(...arguments),this._open=!1,this._last_value=\"\",this._hover_index=0}styles(){return[...super.styles(),c.default]}render(){super.render(),this.input_el.addEventListener(\"keydown\",(e=>this._keydown(e))),this.input_el.addEventListener(\"keyup\",(e=>this._keyup(e))),this.menu=(0,u.div)({class:[a.menu,a.below]}),this.menu.addEventListener(\"click\",(e=>this._menu_click(e))),this.menu.addEventListener(\"mouseover\",(e=>this._menu_hover(e))),this.el.appendChild(this.menu),(0,u.undisplay)(this.menu)}change_input(){this._open&&this.menu.children.length>0?(this.model.value=this.menu.children[this._hover_index].textContent,this.input_el.focus(),this._hide_menu()):this.model.restrict||super.change_input()}_update_completions(e){(0,u.empty)(this.menu);for(const t of e){const e=(0,u.div)(t);this.menu.appendChild(e)}e.length>0&&this.menu.children[0].classList.add(a.active)}_show_menu(){if(!this._open){this._open=!0,this._hover_index=0,this._last_value=this.model.value,(0,u.display)(this.menu);const e=t=>{const{target:n}=t;n instanceof HTMLElement&&!this.el.contains(n)&&(document.removeEventListener(\"click\",e),this._hide_menu())};document.addEventListener(\"click\",e)}}_hide_menu(){this._open&&(this._open=!1,(0,u.undisplay)(this.menu))}_menu_click(e){e.target!=e.currentTarget&&e.target instanceof Element&&(this.model.value=e.target.textContent,this.input_el.focus(),this._hide_menu())}_menu_hover(e){if(e.target!=e.currentTarget&&e.target instanceof Element){let t=0;for(t=0;t0&&(this.menu.children[this._hover_index].classList.remove(a.active),this._hover_index=(0,r.clamp)(e,0,t-1),this.menu.children[this._hover_index].classList.add(a.active))}_keydown(e){}_keyup(e){switch(e.keyCode){case u.Keys.Enter:this.change_input();break;case u.Keys.Esc:this._hide_menu();break;case u.Keys.Up:this._bump_hover(this._hover_index-1);break;case u.Keys.Down:this._bump_hover(this._hover_index+1);break;default:{const e=this.input_el.value;if(e.lengthe:e=>e.toLowerCase();for(const n of this.model.completions)s(n).startsWith(s(e))&&t.push(n);this._update_completions(t),0==t.length?this._hide_menu():this._show_menu()}}}}n.AutocompleteInputView=l,l.__name__=\"AutocompleteInputView\";class d extends _.TextInput{constructor(e){super(e)}}n.AutocompleteInput=d,o=d,d.__name__=\"AutocompleteInput\",o.prototype.default_view=l,o.define((({Boolean:e,Int:t,String:n,Array:s})=>({completions:[s(n),[]],min_characters:[t,2],case_sensitive:[e,!0],restrict:[e,!0]})))},\n", - " 446: function _(t,e,n,p,_){p();const u=t(1);var i;const s=t(447),r=t(43),x=(0,u.__importStar)(t(449));class a extends s.TextLikeInputView{_render_input(){this.input_el=(0,r.input)({type:\"text\",class:x.input})}}n.TextInputView=a,a.__name__=\"TextInputView\";class c extends s.TextLikeInput{constructor(t){super(t)}}n.TextInput=c,i=c,c.__name__=\"TextInput\",i.prototype.default_view=a},\n", - " 447: function _(e,t,n,i,l){var s;i();const h=e(448);class a extends h.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>this.input_el.value=this.model.value)),this.connect(this.model.properties.value_input.change,(()=>this.input_el.value=this.model.value_input)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.max_length.change,(()=>{const{max_length:e}=this.model;null!=e?this.input_el.maxLength=e:this.input_el.removeAttribute(\"maxLength\")}))}render(){var e;super.render(),this._render_input();const{input_el:t}=this;t.name=null!==(e=this.model.name)&&void 0!==e?e:\"\",t.value=this.model.value,t.disabled=this.model.disabled,t.placeholder=this.model.placeholder,null!=this.model.max_length&&(t.maxLength=this.model.max_length),t.addEventListener(\"change\",(()=>this.change_input())),t.addEventListener(\"input\",(()=>this.change_input_value())),this.group_el.appendChild(t)}change_input(){this.model.value=this.input_el.value,super.change_input()}change_input_value(){this.model.value_input=this.input_el.value,super.change_input()}}n.TextLikeInputView=a,a.__name__=\"TextLikeInputView\";class u extends h.InputWidget{constructor(e){super(e)}}n.TextLikeInput=u,s=u,u.__name__=\"TextLikeInput\",s.define((({Int:e,String:t,Nullable:n})=>({value:[t,\"\"],value_input:[t,\"\"],placeholder:[t,\"\"],max_length:[n(e),null]})))},\n", - " 448: function _(e,t,n,s,l){s();const i=e(1);var o;const r=e(442),_=e(43),p=(0,i.__importStar)(e(449)),a=p;class c extends r.ControlView{*controls(){yield this.input_el}connect_signals(){super.connect_signals(),this.connect(this.model.properties.title.change,(()=>{this.label_el.textContent=this.model.title}))}styles(){return[...super.styles(),p.default]}render(){super.render();const{title:e}=this.model;this.label_el=(0,_.label)({style:{display:0==e.length?\"none\":\"\"}},e),this.group_el=(0,_.div)({class:a.input_group},this.label_el),this.el.appendChild(this.group_el)}change_input(){}}n.InputWidgetView=c,c.__name__=\"InputWidgetView\";class d extends r.Control{constructor(e){super(e)}}n.InputWidget=d,o=d,d.__name__=\"InputWidget\",o.define((({String:e})=>({title:[e,\"\"]})))},\n", - " 449: function _(o,p,t,n,i){n(),t.root=\"bk-root\",t.input=\"bk-input\",t.input_group=\"bk-input-group\",t.inline=\"bk-inline\",t.spin_wrapper=\"bk-spin-wrapper\",t.spin_btn=\"bk-spin-btn\",t.spin_btn_up=\"bk-spin-btn-up\",t.spin_btn_down=\"bk-spin-btn-down\",t.default='.bk-root .bk-input{display:inline-block;width:100%;flex-grow:1;min-height:31px;padding:0 12px;background-color:#fff;border:1px solid #ccc;border-radius:4px;}.bk-root .bk-input:focus{border-color:#66afe9;outline:0;box-shadow:inset 0 1px 1px rgba(0, 0, 0, 0.075), 0 0 8px rgba(102, 175, 233, 0.6);}.bk-root .bk-input::placeholder,.bk-root .bk-input:-ms-input-placeholder,.bk-root .bk-input::-moz-placeholder,.bk-root .bk-input::-webkit-input-placeholder{color:#999;opacity:1;}.bk-root .bk-input[disabled]{cursor:not-allowed;background-color:#eee;opacity:1;}.bk-root select:not([multiple]).bk-input,.bk-root select:not([size]).bk-input{height:auto;appearance:none;-webkit-appearance:none;background-image:url(\\'data:image/svg+xml;utf8,\\');background-position:right 0.5em center;background-size:8px 6px;background-repeat:no-repeat;}.bk-root select[multiple].bk-input,.bk-root select[size].bk-input,.bk-root textarea.bk-input{height:auto;}.bk-root .bk-input-group{width:100%;height:100%;display:inline-flex;flex-wrap:nowrap;align-items:start;flex-direction:column;white-space:nowrap;}.bk-root .bk-input-group.bk-inline{flex-direction:row;}.bk-root .bk-input-group.bk-inline > *:not(:first-child){margin-left:5px;}.bk-root .bk-input-group input[type=\"checkbox\"] + span,.bk-root .bk-input-group input[type=\"radio\"] + span{position:relative;top:-2px;margin-left:3px;}.bk-root .bk-input-group > .bk-spin-wrapper{display:inherit;width:inherit;height:inherit;position:relative;overflow:hidden;padding:0;vertical-align:middle;}.bk-root .bk-input-group > .bk-spin-wrapper input{padding-right:20px;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn{position:absolute;display:block;height:50%;min-height:0;min-width:0;width:30px;padding:0;margin:0;right:0;border:none;background:none;cursor:pointer;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn:before{content:\"\";display:inline-block;transform:translateY(-50%);border-left:5px solid transparent;border-right:5px solid transparent;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up{top:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:before{border-bottom:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-up:disabled:before{border-bottom-color:grey;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down{bottom:0;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:before{border-top:5px solid black;}.bk-root .bk-input-group > .bk-spin-wrapper > .bk-spin-btn.bk-spin-btn-down:disabled:before{border-top-color:grey;}'},\n", - " 450: function _(t,e,n,o,c){var s;o();const u=t(441),r=t(251);class i extends u.AbstractButtonView{click(){this.model.trigger_event(new r.ButtonClick),super.click()}}n.ButtonView=i,i.__name__=\"ButtonView\";class _ extends u.AbstractButton{constructor(t){super(t)}}n.Button=_,s=_,_.__name__=\"Button\",s.prototype.default_view=i,s.override({label:\"Button\"})},\n", - " 451: function _(t,e,o,c,a){c();const s=t(1);var n;const i=t(452),r=t(43),u=(0,s.__importStar)(t(318));class _ extends i.ButtonGroupView{get active(){return new Set(this.model.active)}change_active(t){const{active:e}=this;e.has(t)?e.delete(t):e.add(t),this.model.active=[...e].sort()}_update_active(){const{active:t}=this;this._buttons.forEach(((e,o)=>{(0,r.classes)(e).toggle(u.active,t.has(o))}))}}o.CheckboxButtonGroupView=_,_.__name__=\"CheckboxButtonGroupView\";class h extends i.ButtonGroup{constructor(t){super(t)}}o.CheckboxButtonGroup=h,n=h,h.__name__=\"CheckboxButtonGroup\",n.prototype.default_view=_,n.define((({Int:t,Array:e})=>({active:[e(t),[]]})))},\n", - " 452: function _(t,e,n,s,i){s();const o=t(1);var r;const a=t(453),l=t(20),d=t(43),u=(0,o.__importStar)(t(318)),_=u;class c extends a.OrientedControlView{get default_size(){return\"horizontal\"==this.orientation?this.model.default_size:void 0}*controls(){yield*this._buttons}connect_signals(){super.connect_signals();const t=this.model.properties;this.on_change(t.button_type,(()=>this.render())),this.on_change(t.labels,(()=>this.render())),this.on_change(t.active,(()=>this._update_active()))}styles(){return[...super.styles(),u.default]}render(){super.render(),this._buttons=this.model.labels.map(((t,e)=>{const n=(0,d.div)({class:[_.btn,_[`btn_${this.model.button_type}`]],disabled:this.model.disabled},t);return n.addEventListener(\"click\",(()=>this.change_active(e))),n})),this._update_active();const t=\"horizontal\"==this.model.orientation?_.horizontal:_.vertical,e=(0,d.div)({class:[_.btn_group,t]},this._buttons);this.el.appendChild(e)}}n.ButtonGroupView=c,c.__name__=\"ButtonGroupView\";class h extends a.OrientedControl{constructor(t){super(t)}}n.ButtonGroup=h,r=h,h.__name__=\"ButtonGroup\",r.define((({String:t,Array:e})=>({labels:[e(t),[]],button_type:[l.ButtonType,\"default\"]})))},\n", - " 453: function _(n,t,e,o,r){var i;o();const a=n(442),l=n(20);class s extends a.ControlView{get orientation(){return this.model.orientation}}e.OrientedControlView=s,s.__name__=\"OrientedControlView\";class _ extends a.Control{constructor(n){super(n)}}e.OrientedControl=_,i=_,_.__name__=\"OrientedControl\",i.define((()=>({orientation:[l.Orientation,\"horizontal\"]})))},\n", - " 454: function _(e,t,n,i,s){i();const o=e(1);var a;const c=e(455),l=e(43),d=e(9),p=(0,o.__importStar)(e(449));class r extends c.InputGroupView{render(){super.render();const e=(0,l.div)({class:[p.input_group,this.model.inline?p.inline:null]});this.el.appendChild(e);const{active:t,labels:n}=this.model;this._inputs=[];for(let i=0;ithis.change_active(i))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),(0,d.includes)(t,i)&&(s.checked=!0);const o=(0,l.label)(s,(0,l.span)(n[i]));e.appendChild(o)}}change_active(e){const t=new Set(this.model.active);t.has(e)?t.delete(e):t.add(e),this.model.active=[...t].sort()}}n.CheckboxGroupView=r,r.__name__=\"CheckboxGroupView\";class h extends c.InputGroup{constructor(e){super(e)}}n.CheckboxGroup=h,a=h,h.__name__=\"CheckboxGroup\",a.prototype.default_view=r,a.define((({Boolean:e,Int:t,String:n,Array:i})=>({active:[i(t),[]],labels:[i(n),[]],inline:[e,!1]})))},\n", - " 455: function _(n,t,e,s,o){s();const r=n(1),u=n(442),c=(0,r.__importDefault)(n(449));class _ extends u.ControlView{*controls(){yield*this._inputs}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>this.render()))}styles(){return[...super.styles(),c.default]}}e.InputGroupView=_,_.__name__=\"InputGroupView\";class i extends u.Control{constructor(n){super(n)}}e.InputGroup=i,i.__name__=\"InputGroup\"},\n", - " 456: function _(e,t,i,n,o){n();const s=e(1);var l;const r=e(448),c=e(43),a=e(22),d=(0,s.__importStar)(e(449));class h extends r.InputWidgetView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.name.change,(()=>{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.color.change,(()=>this.input_el.value=(0,a.color2hexrgb)(this.model.color))),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled))}render(){super.render(),this.input_el=(0,c.input)({type:\"color\",class:d.input,name:this.model.name,value:this.model.color,disabled:this.model.disabled}),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){this.model.color=this.input_el.value,super.change_input()}}i.ColorPickerView=h,h.__name__=\"ColorPickerView\";class p extends r.InputWidget{constructor(e){super(e)}}i.ColorPicker=p,l=p,p.__name__=\"ColorPicker\",l.prototype.default_view=h,l.define((({Color:e})=>({color:[e,\"#000000\"]})))},\n", - " 457: function _(e,t,i,n,s){n();const a=e(1);var l;const o=(0,a.__importDefault)(e(458)),d=e(448),r=e(43),c=e(20),u=e(8),h=(0,a.__importStar)(e(449)),_=(0,a.__importDefault)(e(459));function p(e){const t=[];for(const i of e)if((0,u.isString)(i))t.push(i);else{const[e,n]=i;t.push({from:e,to:n})}return t}class m extends d.InputWidgetView{connect_signals(){super.connect_signals();const{value:e,min_date:t,max_date:i,disabled_dates:n,enabled_dates:s,position:a,inline:l}=this.model.properties;this.connect(e.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.setDate(this.model.value)})),this.connect(t.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"minDate\",this.model.min_date)})),this.connect(i.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"maxDate\",this.model.max_date)})),this.connect(n.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"disable\",this.model.disabled_dates)})),this.connect(s.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"enable\",this.model.enabled_dates)})),this.connect(a.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"position\",this.model.position)})),this.connect(l.change,(()=>{var e;return null===(e=this._picker)||void 0===e?void 0:e.set(\"inline\",this.model.inline)}))}remove(){var e;null===(e=this._picker)||void 0===e||e.destroy(),super.remove()}styles(){return[...super.styles(),_.default]}render(){var e,t;null==this._picker&&(super.render(),this.input_el=(0,r.input)({type:\"text\",class:h.input,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el),this._picker=(0,o.default)(this.input_el,{defaultDate:this.model.value,minDate:null!==(e=this.model.min_date)&&void 0!==e?e:void 0,maxDate:null!==(t=this.model.max_date)&&void 0!==t?t:void 0,inline:this.model.inline,position:this.model.position,disable:p(this.model.disabled_dates),enable:p(this.model.enabled_dates),onChange:(e,t,i)=>this._on_change(e,t,i)}))}_on_change(e,t,i){this.model.value=t,this.change_input()}}i.DatePickerView=m,m.__name__=\"DatePickerView\";class v extends d.InputWidget{constructor(e){super(e)}}i.DatePicker=v,l=v,v.__name__=\"DatePicker\",l.prototype.default_view=m,l.define((({Boolean:e,String:t,Array:i,Tuple:n,Or:s,Nullable:a})=>{const l=i(s(t,n(t,t)));return{value:[t],min_date:[a(t),null],max_date:[a(t),null],disabled_dates:[l,[]],enabled_dates:[l,[]],position:[c.CalendarPosition,\"auto\"],inline:[e,!1]}}))},\n", - " 458: function _(e,n,t,a,i){\n", - " /* flatpickr v4.6.6, @license MIT */var o,r;o=this,r=function(){\"use strict\";\n", - " /*! *****************************************************************************\n", - " Copyright (c) Microsoft Corporation.\n", - " \n", - " Permission to use, copy, modify, and/or distribute this software for any\n", - " purpose with or without fee is hereby granted.\n", - " \n", - " THE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\n", - " REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\n", - " AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\n", - " INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\n", - " LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\n", - " OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\n", - " PERFORMANCE OF THIS SOFTWARE.\n", - " ***************************************************************************** */var e=function(){return e=Object.assign||function(e){for(var n,t=1,a=arguments.length;t\",noCalendar:!1,now:new Date,onChange:[],onClose:[],onDayCreate:[],onDestroy:[],onKeyDown:[],onMonthChange:[],onOpen:[],onParseConfig:[],onReady:[],onValueUpdate:[],onYearChange:[],onPreCalendarPosition:[],plugins:[],position:\"auto\",positionElement:void 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i.setDate(i.getDate()-i.getDay()+t.firstDayOfWeek),i},Y:function(e,n){e.setFullYear(parseFloat(n))},Z:function(e,n){return new Date(n)},d:function(e,n){e.setDate(parseFloat(n))},h:function(e,n){e.setHours(parseFloat(n))},i:function(e,n){e.setMinutes(parseFloat(n))},j:function(e,n){e.setDate(parseFloat(n))},l:p,m:function(e,n){e.setMonth(parseFloat(n)-1)},n:function(e,n){e.setMonth(parseFloat(n)-1)},s:function(e,n){e.setSeconds(parseFloat(n))},u:function(e,n){return new Date(parseFloat(n))},w:p,y:function(e,n){e.setFullYear(2e3+parseFloat(n))}},D={D:\"(\\\\w+)\",F:\"(\\\\w+)\",G:\"(\\\\d\\\\d|\\\\d)\",H:\"(\\\\d\\\\d|\\\\d)\",J:\"(\\\\d\\\\d|\\\\d)\\\\w+\",K:\"\",M:\"(\\\\w+)\",S:\"(\\\\d\\\\d|\\\\d)\",U:\"(.+)\",W:\"(\\\\d\\\\d|\\\\d)\",Y:\"(\\\\d{4})\",Z:\"(.+)\",d:\"(\\\\d\\\\d|\\\\d)\",h:\"(\\\\d\\\\d|\\\\d)\",i:\"(\\\\d\\\\d|\\\\d)\",j:\"(\\\\d\\\\d|\\\\d)\",l:\"(\\\\w+)\",m:\"(\\\\d\\\\d|\\\\d)\",n:\"(\\\\d\\\\d|\\\\d)\",s:\"(\\\\d\\\\d|\\\\d)\",u:\"(.+)\",w:\"(\\\\d\\\\d|\\\\d)\",y:\"(\\\\d{2})\"},w={Z:function(e){return e.toISOString()},D:function(e,n,t){return n.weekdays.shorthand[w.w(e,n,t)]},F:function(e,n,t){return h(w.n(e,n,t)-1,!1,n)},G:function(e,n,t){return o(w.h(e,n,t))},H:function(e){return o(e.getHours())},J:function(e,n){return void 0!==n.ordinal?e.getDate()+n.ordinal(e.getDate()):e.getDate()},K:function(e,n){return n.amPM[r(e.getHours()>11)]},M:function(e,n){return h(e.getMonth(),!0,n)},S:function(e){return 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n=g(e),t=V(n),a=n===w.input||n===w.altInput||w.element.contains(n)||e.path&&e.path.indexOf&&(~e.path.indexOf(w.input)||~e.path.indexOf(w.altInput)),i=\"blur\"===e.type?a&&e.relatedTarget&&!V(e.relatedTarget):!a&&!t&&!V(e.relatedTarget),o=!w.config.ignoredFocusElements.some((function(e){return e.contains(n)}));i&&o&&(void 0!==w.timeContainer&&void 0!==w.minuteElement&&void 0!==w.hourElement&&\"\"!==w.input.value&&void 0!==w.input.value&&T(),w.close(),w.config&&\"range\"===w.config.mode&&1===w.selectedDates.length&&(w.clear(!1),w.redraw()))}}function Q(e){if(!(!e||w.config.minDate&&ew.config.maxDate.getFullYear())){var n=e,t=w.currentYear!==n;w.currentYear=n||w.currentYear,w.config.maxDate&&w.currentYear===w.config.maxDate.getFullYear()?w.currentMonth=Math.min(w.config.maxDate.getMonth(),w.currentMonth):w.config.minDate&&w.currentYear===w.config.minDate.getFullYear()&&(w.currentMonth=Math.max(w.config.minDate.getMonth(),w.currentMonth)),t&&(w.redraw(),pe(\"onYearChange\"),K())}}function X(e,n){void 0===n&&(n=!0);var t=w.parseDate(e,void 0,n);if(w.config.minDate&&t&&M(t,w.config.minDate,void 0!==n?n:!w.minDateHasTime)<0||w.config.maxDate&&t&&M(t,w.config.maxDate,void 0!==n?n:!w.maxDateHasTime)>0)return!1;if(0===w.config.enable.length&&0===w.config.disable.length)return!0;if(void 0===t)return!1;for(var a=w.config.enable.length>0,i=a?w.config.enable:w.config.disable,o=0,r=void 0;o=r.from.getTime()&&t.getTime()<=r.to.getTime())return a}return!a}function ee(e){return void 0!==w.daysContainer&&-1===e.className.indexOf(\"hidden\")&&-1===e.className.indexOf(\"flatpickr-disabled\")&&w.daysContainer.contains(e)}function ne(e){e.target!==w._input||e.relatedTarget&&V(e.relatedTarget)||w.setDate(w._input.value,!0,e.target===w.altInput?w.config.altFormat:w.config.dateFormat)}function te(e){var n=g(e),t=w.config.wrap?p.contains(n):n===w._input,a=w.config.allowInput,i=w.isOpen&&(!a||!t),o=w.config.inline&&t&&!a;if(13===e.keyCode&&t){if(a)return 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d.AbstractRangeSliderView{}r.DatetimeRangeSliderView=_,_.__name__=\"DatetimeRangeSliderView\";class c extends d.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,t){return(0,o.isString)(t)?(0,s.default)(e,t):t.compute(e)}}r.DatetimeRangeSlider=c,n=c,c.__name__=\"DatetimeRangeSlider\",n.prototype.default_view=_,n.override({format:\"%d %b %Y %H:%M:%S\",step:36e5})},\n", - " 467: function _(e,t,s,r,i){var _;r();const n=e(468);class a extends n.MarkupView{render(){super.render(),this.model.render_as_text?this.markup_el.textContent=this.model.text:this.markup_el.innerHTML=this.has_math_disabled()?this.model.text:this.process_tex()}}s.DivView=a,a.__name__=\"DivView\";class d extends n.Markup{constructor(e){super(e)}}s.Div=d,_=d,d.__name__=\"Div\",_.prototype.default_view=a,_.define((({Boolean:e})=>({render_as_text:[e,!1]})))},\n", - " 468: function _(t,e,s,i,r){i();const a=t(1);var n;const o=t(210),d=t(43),h=t(137),l=t(512),_=(0,a.__importStar)(t(469));class u extends l.WidgetView{get provider(){return h.default_provider}async lazy_initialize(){await super.lazy_initialize(),\"not_started\"==this.provider.status&&await this.provider.fetch(),\"not_started\"!=this.provider.status&&\"loading\"!=this.provider.status||this.provider.ready.connect((()=>{this.contains_tex_string()&&this.rerender()}))}after_layout(){super.after_layout(),\"loading\"===this.provider.status&&(this._has_finished=!1)}rerender(){this.layout.invalidate_cache(),this.render(),this.root.compute_layout()}connect_signals(){super.connect_signals(),this.connect(this.model.change,(()=>{this.rerender()}))}styles(){return[...super.styles(),_.default]}_update_layout(){this.layout=new o.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render();const 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r.InputWidgetView{constructor(){super(...arguments),this._last_height=null}connect_signals(){super.connect_signals(),this.connect(this.model.properties.disabled.change,(()=>this.set_disabled()));const{value:e,max_items:t,option_limit:i,search_option_limit:l,delete_button:s,placeholder:o,options:n,name:h,title:a}=this.model.properties;this.on_change([e,t,i,l,s,o,n,h,a],(()=>this.render()))}styles(){return[...super.styles(),d.default]}_update_layout(){this.layout=new c.CachedVariadicBox(this.el),this.layout.set_sizing(this.box_sizing())}render(){super.render(),this.input_el=(0,a.select)({multiple:!0,class:_.input,name:this.model.name,disabled:this.model.disabled}),this.group_el.appendChild(this.input_el);const e=new Set(this.model.value),t=this.model.options.map((t=>{let i,l;return(0,u.isString)(t)?i=l=t:[i,l]=t,{value:i,label:l,selected:e.has(i)}})),i=this.model.solid?\"solid\":\"light\",l=`choices__item ${i}`,s=`choices__button 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i=e.split(this.options.tokenSeparator),n=0,s=i.length;n0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1?arguments[1]:void 0,i=this.list,n={},s=[];if(\"string\"==typeof i[0]){for(var r=0,o=i.length;r1)throw new Error(\"Key weight has to be > 0 and <= 1\");p=p.name}else a[p]={weight:1};this._analyze({key:p,value:this.options.getFn(h,p),record:h,index:c},{resultMap:n,results:s,tokenSearchers:e,fullSearcher:t})}return{weights:a,results:s}}},{key:\"_analyze\",value:function(e,t){var i=e.key,n=e.arrayIndex,s=void 0===n?-1:n,r=e.value,o=e.record,c=e.index,l=t.tokenSearchers,h=void 0===l?[]:l,u=t.fullSearcher,d=void 0===u?[]:u,p=t.resultMap,m=void 0===p?{}:p,f=t.results,v=void 0===f?[]:f;if(null!=r){var g=!1,_=-1,b=0;if(\"string\"==typeof r){this._log(\"\\nKey: \".concat(\"\"===i?\"-\":i));var y=d.search(r);if(this._log('Full text: \"'.concat(r,'\", score: ').concat(y.score)),this.options.tokenize){for(var E=r.split(this.options.tokenSeparator),I=[],S=0;S-1&&(P=(P+_)/2),this._log(\"Score average:\",P);var D=!this.options.tokenize||!this.options.matchAllTokens||b>=h.length;if(this._log(\"\\nCheck Matches: \".concat(D)),(g||y.isMatch)&&D){var M=m[c];M?M.output.push({key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}):(m[c]={item:o,output:[{key:i,arrayIndex:s,value:r,score:P,matchedIndices:y.matchedIndices}]},v.push(m[c]))}}else if(a(r))for(var N=0,F=r.length;N-1&&(o.arrayIndex=r.arrayIndex),t.matches.push(o)}}})),this.options.includeScore&&s.push((function(e,t){t.score=e.score}));for(var r=0,o=e.length;ri)return s(e,this.pattern,n);var o=this.options,a=o.location,c=o.distance,l=o.threshold,h=o.findAllMatches,u=o.minMatchCharLength;return r(e,this.pattern,this.patternAlphabet,{location:a,distance:c,threshold:l,findAllMatches:h,minMatchCharLength:u})}}])&&n(t.prototype,i),a&&n(t,a),e}();e.exports=a},function(e,t){var i=/[\\-\\[\\]\\/\\{\\}\\(\\)\\*\\+\\?\\.\\\\\\^\\$\\|]/g;e.exports=function(e,t){var n=arguments.length>2&&void 0!==arguments[2]?arguments[2]:/ +/g,s=new RegExp(t.replace(i,\"\\\\$&\").replace(n,\"|\")),r=e.match(s),o=!!r,a=[];if(o)for(var c=0,l=r.length;c=P;N-=1){var F=N-1,j=i[e.charAt(F)];if(j&&(E[F]=1),M[N]=(M[N+1]<<1|1)&j,0!==T&&(M[N]|=(O[N+1]|O[N])<<1|1|O[N+1]),M[N]&L&&(C=n(t,{errors:T,currentLocation:F,expectedLocation:v,distance:l}))<=_){if(_=C,(b=F)<=v)break;P=Math.max(1,2*v-b)}}if(n(t,{errors:T+1,currentLocation:v,expectedLocation:v,distance:l})>_)break;O=M}return{isMatch:b>=0,score:0===C?.001:C,matchedIndices:s(E,f)}}},function(e,t){e.exports=function(e,t){var i=t.errors,n=void 0===i?0:i,s=t.currentLocation,r=void 0===s?0:s,o=t.expectedLocation,a=void 0===o?0:o,c=t.distance,l=void 0===c?100:c,h=n/e.length,u=Math.abs(a-r);return l?h+u/l:u?1:h}},function(e,t){e.exports=function(){for(var e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:[],t=arguments.length>1&&void 0!==arguments[1]?arguments[1]:1,i=[],n=-1,s=-1,r=0,o=e.length;r=t&&i.push([n,s]),n=-1)}return e[r-1]&&r-n>=t&&i.push([n,r-1]),i}},function(e,t){e.exports=function(e){for(var t={},i=e.length,n=0;n/g,\"&rt;\").replace(/-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!0),i})):e;case\"REMOVE_ITEM\":return t.choiceId>-1?e.map((function(e){var i=e;return i.id===parseInt(t.choiceId,10)&&(i.selected=!1),i})):e;case\"FILTER_CHOICES\":return e.map((function(e){var i=e;return i.active=t.results.some((function(e){var t=e.item,n=e.score;return t.id===i.id&&(i.score=n,!0)})),i}));case\"ACTIVATE_CHOICES\":return e.map((function(e){var i=e;return i.active=t.active,i}));case\"CLEAR_CHOICES\":return v;default:return e}},general:_}),A=function(e,t){var i=e;if(\"CLEAR_ALL\"===t.type)i=void 0;else if(\"RESET_TO\"===t.type)return O(t.state);return C(i,t)};function L(e,t){for(var i=0;i\"'+I(e)+'\"'},maxItemText:function(e){return\"Only \"+e+\" values can be added\"},valueComparer:function(e,t){return e===t},fuseOptions:{includeScore:!0},callbackOnInit:null,callbackOnCreateTemplates:null,classNames:{containerOuter:\"choices\",containerInner:\"choices__inner\",input:\"choices__input\",inputCloned:\"choices__input--cloned\",list:\"choices__list\",listItems:\"choices__list--multiple\",listSingle:\"choices__list--single\",listDropdown:\"choices__list--dropdown\",item:\"choices__item\",itemSelectable:\"choices__item--selectable\",itemDisabled:\"choices__item--disabled\",itemChoice:\"choices__item--choice\",placeholder:\"choices__placeholder\",group:\"choices__group\",groupHeading:\"choices__heading\",button:\"choices__button\",activeState:\"is-active\",focusState:\"is-focused\",openState:\"is-open\",disabledState:\"is-disabled\",highlightedState:\"is-highlighted\",selectedState:\"is-selected\",flippedState:\"is-flipped\",loadingState:\"is-loading\",noResults:\"has-no-results\",noChoices:\"has-no-choices\"}},D=\"showDropdown\",M=\"hideDropdown\",N=\"change\",F=\"choice\",j=\"search\",K=\"addItem\",R=\"removeItem\",H=\"highlightItem\",B=\"highlightChoice\",V=\"ADD_CHOICE\",G=\"FILTER_CHOICES\",q=\"ACTIVATE_CHOICES\",U=\"CLEAR_CHOICES\",z=\"ADD_GROUP\",W=\"ADD_ITEM\",X=\"REMOVE_ITEM\",$=\"HIGHLIGHT_ITEM\",J=46,Y=8,Z=13,Q=65,ee=27,te=38,ie=40,ne=33,se=34,re=\"text\",oe=\"select-one\",ae=\"select-multiple\",ce=function(){function e(e){var t=e.element,i=e.type,n=e.classNames,s=e.position;this.element=t,this.classNames=n,this.type=i,this.position=s,this.isOpen=!1,this.isFlipped=!1,this.isFocussed=!1,this.isDisabled=!1,this.isLoading=!1,this._onFocus=this._onFocus.bind(this),this._onBlur=this._onBlur.bind(this)}var t=e.prototype;return t.addEventListeners=function(){this.element.addEventListener(\"focus\",this._onFocus),this.element.addEventListener(\"blur\",this._onBlur)},t.removeEventListeners=function(){this.element.removeEventListener(\"focus\",this._onFocus),this.element.removeEventListener(\"blur\",this._onBlur)},t.shouldFlip=function(e){if(\"number\"!=typeof e)return!1;var t=!1;return\"auto\"===this.position?t=!window.matchMedia(\"(min-height: \"+(e+1)+\"px)\").matches:\"top\"===this.position&&(t=!0),t},t.setActiveDescendant=function(e){this.element.setAttribute(\"aria-activedescendant\",e)},t.removeActiveDescendant=function(){this.element.removeAttribute(\"aria-activedescendant\")},t.open=function(e){this.element.classList.add(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"true\"),this.isOpen=!0,this.shouldFlip(e)&&(this.element.classList.add(this.classNames.flippedState),this.isFlipped=!0)},t.close=function(){this.element.classList.remove(this.classNames.openState),this.element.setAttribute(\"aria-expanded\",\"false\"),this.removeActiveDescendant(),this.isOpen=!1,this.isFlipped&&(this.element.classList.remove(this.classNames.flippedState),this.isFlipped=!1)},t.focus=function(){this.isFocussed||this.element.focus()},t.addFocusState=function(){this.element.classList.add(this.classNames.focusState)},t.removeFocusState=function(){this.element.classList.remove(this.classNames.focusState)},t.enable=function(){this.element.classList.remove(this.classNames.disabledState),this.element.removeAttribute(\"aria-disabled\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"0\"),this.isDisabled=!1},t.disable=function(){this.element.classList.add(this.classNames.disabledState),this.element.setAttribute(\"aria-disabled\",\"true\"),this.type===oe&&this.element.setAttribute(\"tabindex\",\"-1\"),this.isDisabled=!0},t.wrap=function(e){!function(e,t){void 0===t&&(t=document.createElement(\"div\")),e.nextSibling?e.parentNode.insertBefore(t,e.nextSibling):e.parentNode.appendChild(t),t.appendChild(e)}(e,this.element)},t.unwrap=function(e){this.element.parentNode.insertBefore(e,this.element),this.element.parentNode.removeChild(this.element)},t.addLoadingState=function(){this.element.classList.add(this.classNames.loadingState),this.element.setAttribute(\"aria-busy\",\"true\"),this.isLoading=!0},t.removeLoadingState=function(){this.element.classList.remove(this.classNames.loadingState),this.element.removeAttribute(\"aria-busy\"),this.isLoading=!1},t._onFocus=function(){this.isFocussed=!0},t._onBlur=function(){this.isFocussed=!1},e}();function le(e,t){for(var i=0;i0?this.element.scrollTop+o-s:e.offsetTop;requestAnimationFrame((function(){i._animateScroll(a,t)}))}},t._scrollDown=function(e,t,i){var n=(i-e)/t,s=n>1?n:1;this.element.scrollTop=e+s},t._scrollUp=function(e,t,i){var n=(e-i)/t,s=n>1?n:1;this.element.scrollTop=e-s},t._animateScroll=function(e,t){var i=this,n=this.element.scrollTop,s=!1;t>0?(this._scrollDown(n,4,e),ne&&(s=!0)),s&&requestAnimationFrame((function(){i._animateScroll(e,t)}))},e}();function de(e,t){for(var i=0;i0?\"treeitem\":\"option\"),Object.assign(g.dataset,{choice:\"\",id:l,value:h,selectText:i}),m?(g.classList.add(a),g.dataset.choiceDisabled=\"\",g.setAttribute(\"aria-disabled\",\"true\")):(g.classList.add(r),g.dataset.choiceSelectable=\"\"),g},input:function(e,t){var i=e.input,n=e.inputCloned,s=Object.assign(document.createElement(\"input\"),{type:\"text\",className:i+\" \"+n,autocomplete:\"off\",autocapitalize:\"off\",spellcheck:!1});return s.setAttribute(\"role\",\"textbox\"),s.setAttribute(\"aria-autocomplete\",\"list\"),s.setAttribute(\"aria-label\",t),s},dropdown:function(e){var t=e.list,i=e.listDropdown,n=document.createElement(\"div\");return n.classList.add(t,i),n.setAttribute(\"aria-expanded\",\"false\"),n},notice:function(e,t,i){var n=e.item,s=e.itemChoice,r=e.noResults,o=e.noChoices;void 0===i&&(i=\"\");var a=[n,s];return\"no-choices\"===i?a.push(o):\"no-results\"===i&&a.push(r),Object.assign(document.createElement(\"div\"),{innerHTML:t,className:a.join(\" \")})},option:function(e){var t=e.label,i=e.value,n=e.customProperties,s=e.active,r=e.disabled,o=new Option(t,i,!1,s);return n&&(o.dataset.customProperties=n),o.disabled=r,o}},be=function(e){return void 0===e&&(e=!0),{type:q,active:e}},ye=function(e,t){return{type:$,id:e,highlighted:t}},Ee=function(e){var t=e.value,i=e.id,n=e.active,s=e.disabled;return{type:z,value:t,id:i,active:n,disabled:s}},Ie=function(e){return{type:\"SET_IS_LOADING\",isLoading:e}};function Se(e,t){for(var i=0;i=0?this._store.getGroupById(s):null;return this._store.dispatch(ye(i,!0)),t&&this.passedElement.triggerEvent(H,{id:i,value:o,label:c,groupValue:l&&l.value?l.value:null}),this},r.unhighlightItem=function(e){if(!e)return this;var t=e.id,i=e.groupId,n=void 0===i?-1:i,s=e.value,r=void 0===s?\"\":s,o=e.label,a=void 0===o?\"\":o,c=n>=0?this._store.getGroupById(n):null;return this._store.dispatch(ye(t,!1)),this.passedElement.triggerEvent(H,{id:t,value:r,label:a,groupValue:c&&c.value?c.value:null}),this},r.highlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.highlightItem(t)})),this},r.unhighlightAll=function(){var e=this;return this._store.items.forEach((function(t){return e.unhighlightItem(t)})),this},r.removeActiveItemsByValue=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.value===e})).forEach((function(e){return t._removeItem(e)})),this},r.removeActiveItems=function(e){var t=this;return this._store.activeItems.filter((function(t){return t.id!==e})).forEach((function(e){return t._removeItem(e)})),this},r.removeHighlightedItems=function(e){var t=this;return void 0===e&&(e=!1),this._store.highlightedActiveItems.forEach((function(i){t._removeItem(i),e&&t._triggerChange(i.value)})),this},r.showDropdown=function(e){var t=this;return this.dropdown.isActive||requestAnimationFrame((function(){t.dropdown.show(),t.containerOuter.open(t.dropdown.distanceFromTopWindow),!e&&t._canSearch&&t.input.focus(),t.passedElement.triggerEvent(D,{})})),this},r.hideDropdown=function(e){var t=this;return this.dropdown.isActive?(requestAnimationFrame((function(){t.dropdown.hide(),t.containerOuter.close(),!e&&t._canSearch&&(t.input.removeActiveDescendant(),t.input.blur()),t.passedElement.triggerEvent(M,{})})),this):this},r.getValue=function(e){void 0===e&&(e=!1);var t=this._store.activeItems.reduce((function(t,i){var n=e?i.value:i;return t.push(n),t}),[]);return this._isSelectOneElement?t[0]:t},r.setValue=function(e){var t=this;return this.initialised?(e.forEach((function(e){return t._setChoiceOrItem(e)})),this):this},r.setChoiceByValue=function(e){var t=this;return!this.initialised||this._isTextElement||(Array.isArray(e)?e:[e]).forEach((function(e){return t._findAndSelectChoiceByValue(e)})),this},r.setChoices=function(e,t,i,n){var s=this;if(void 0===e&&(e=[]),void 0===t&&(t=\"value\"),void 0===i&&(i=\"label\"),void 0===n&&(n=!1),!this.initialised)throw new ReferenceError(\"setChoices was called on a non-initialized instance of Choices\");if(!this._isSelectElement)throw new TypeError(\"setChoices can't be used with INPUT based Choices\");if(\"string\"!=typeof t||!t)throw new TypeError(\"value parameter must be a name of 'value' field in passed objects\");if(n&&this.clearChoices(),\"function\"==typeof e){var r=e(this);if(\"function\"==typeof Promise&&r instanceof Promise)return new Promise((function(e){return requestAnimationFrame(e)})).then((function(){return s._handleLoadingState(!0)})).then((function(){return r})).then((function(e){return s.setChoices(e,t,i,n)})).catch((function(e){s.config.silent||console.error(e)})).then((function(){return s._handleLoadingState(!1)})).then((function(){return s}));if(!Array.isArray(r))throw new TypeError(\".setChoices first argument function must return either array of choices or Promise, got: \"+typeof r);return this.setChoices(r,t,i,!1)}if(!Array.isArray(e))throw new TypeError(\".setChoices must be called either with array of choices with a function resulting into Promise of array of choices\");return this.containerOuter.removeLoadingState(),this._startLoading(),e.forEach((function(e){e.choices?s._addGroup({id:parseInt(e.id,10)||null,group:e,valueKey:t,labelKey:i}):s._addChoice({value:e[t],label:e[i],isSelected:e.selected,isDisabled:e.disabled,customProperties:e.customProperties,placeholder:e.placeholder})})),this._stopLoading(),this},r.clearChoices=function(){return this._store.dispatch({type:U}),this},r.clearStore=function(){return this._store.dispatch({type:\"CLEAR_ALL\"}),this},r.clearInput=function(){var e=!this._isSelectOneElement;return this.input.clear(e),!this._isTextElement&&this._canSearch&&(this._isSearching=!1,this._store.dispatch(be(!0))),this},r._render=function(){if(!this._store.isLoading()){this._currentState=this._store.state;var e=this._currentState.choices!==this._prevState.choices||this._currentState.groups!==this._prevState.groups||this._currentState.items!==this._prevState.items,t=this._isSelectElement,i=this._currentState.items!==this._prevState.items;e&&(t&&this._renderChoices(),i&&this._renderItems(),this._prevState=this._currentState)}},r._renderChoices=function(){var e=this,t=this._store,i=t.activeGroups,n=t.activeChoices,s=document.createDocumentFragment();if(this.choiceList.clear(),this.config.resetScrollPosition&&requestAnimationFrame((function(){return e.choiceList.scrollToTop()})),i.length>=1&&!this._isSearching){var r=n.filter((function(e){return!0===e.placeholder&&-1===e.groupId}));r.length>=1&&(s=this._createChoicesFragment(r,s)),s=this._createGroupsFragment(i,n,s)}else n.length>=1&&(s=this._createChoicesFragment(n,s));if(s.childNodes&&s.childNodes.length>0){var o=this._store.activeItems,a=this._canAddItem(o,this.input.value);a.response?(this.choiceList.append(s),this._highlightChoice()):this.choiceList.append(this._getTemplate(\"notice\",a.notice))}else{var c,l;this._isSearching?(l=\"function\"==typeof this.config.noResultsText?this.config.noResultsText():this.config.noResultsText,c=this._getTemplate(\"notice\",l,\"no-results\")):(l=\"function\"==typeof this.config.noChoicesText?this.config.noChoicesText():this.config.noChoicesText,c=this._getTemplate(\"notice\",l,\"no-choices\")),this.choiceList.append(c)}},r._renderItems=function(){var e=this._store.activeItems||[];this.itemList.clear();var t=this._createItemsFragment(e);t.childNodes&&this.itemList.append(t)},r._createGroupsFragment=function(e,t,i){var n=this;return void 0===i&&(i=document.createDocumentFragment()),this.config.shouldSort&&e.sort(this.config.sorter),e.forEach((function(e){var s=function(e){return t.filter((function(t){return n._isSelectOneElement?t.groupId===e.id:t.groupId===e.id&&(\"always\"===n.config.renderSelectedChoices||!t.selected)}))}(e);if(s.length>=1){var r=n._getTemplate(\"choiceGroup\",e);i.appendChild(r),n._createChoicesFragment(s,i,!0)}})),i},r._createChoicesFragment=function(e,t,i){var n=this;void 0===t&&(t=document.createDocumentFragment()),void 0===i&&(i=!1);var s=this.config,r=s.renderSelectedChoices,o=s.searchResultLimit,a=s.renderChoiceLimit,c=this._isSearching?w:this.config.sorter,l=function(e){if(\"auto\"!==r||n._isSelectOneElement||!e.selected){var i=n._getTemplate(\"choice\",e,n.config.itemSelectText);t.appendChild(i)}},h=e;\"auto\"!==r||this._isSelectOneElement||(h=e.filter((function(e){return!e.selected})));var u=h.reduce((function(e,t){return t.placeholder?e.placeholderChoices.push(t):e.normalChoices.push(t),e}),{placeholderChoices:[],normalChoices:[]}),d=u.placeholderChoices,p=u.normalChoices;(this.config.shouldSort||this._isSearching)&&p.sort(c);var m=h.length,f=this._isSelectOneElement?[].concat(d,p):p;this._isSearching?m=o:a&&a>0&&!i&&(m=a);for(var v=0;v=n){var o=s?this._searchChoices(e):0;this.passedElement.triggerEvent(j,{value:e,resultCount:o})}else r&&(this._isSearching=!1,this._store.dispatch(be(!0)))}},r._canAddItem=function(e,t){var i=!0,n=\"function\"==typeof this.config.addItemText?this.config.addItemText(t):this.config.addItemText;if(!this._isSelectOneElement){var s=function(e,t,i){return void 0===i&&(i=\"value\"),e.some((function(e){return\"string\"==typeof t?e[i]===t.trim():e[i]===t}))}(e,t);this.config.maxItemCount>0&&this.config.maxItemCount<=e.length&&(i=!1,n=\"function\"==typeof this.config.maxItemText?this.config.maxItemText(this.config.maxItemCount):this.config.maxItemText),!this.config.duplicateItemsAllowed&&s&&i&&(i=!1,n=\"function\"==typeof this.config.uniqueItemText?this.config.uniqueItemText(t):this.config.uniqueItemText),this._isTextElement&&this.config.addItems&&i&&\"function\"==typeof this.config.addItemFilter&&!this.config.addItemFilter(t)&&(i=!1,n=\"function\"==typeof this.config.customAddItemText?this.config.customAddItemText(t):this.config.customAddItemText)}return{response:i,notice:n}},r._searchChoices=function(e){var t=\"string\"==typeof e?e.trim():e,i=\"string\"==typeof this._currentValue?this._currentValue.trim():this._currentValue;if(t.length<1&&t===i+\" \")return 0;var n=this._store.searchableChoices,r=t,o=[].concat(this.config.searchFields),a=Object.assign(this.config.fuseOptions,{keys:o}),c=new s.a(n,a).search(r);return this._currentValue=t,this._highlightPosition=0,this._isSearching=!0,this._store.dispatch(function(e){return{type:G,results:e}}(c)),c.length},r._addEventListeners=function(){var e=document.documentElement;e.addEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.addEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.addEventListener(\"mousedown\",this._onMouseDown,!0),e.addEventListener(\"click\",this._onClick,{passive:!0}),e.addEventListener(\"touchmove\",this._onTouchMove,{passive:!0}),this.dropdown.element.addEventListener(\"mouseover\",this._onMouseOver,{passive:!0}),this._isSelectOneElement&&(this.containerOuter.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.containerOuter.element.addEventListener(\"blur\",this._onBlur,{passive:!0})),this.input.element.addEventListener(\"keyup\",this._onKeyUp,{passive:!0}),this.input.element.addEventListener(\"focus\",this._onFocus,{passive:!0}),this.input.element.addEventListener(\"blur\",this._onBlur,{passive:!0}),this.input.element.form&&this.input.element.form.addEventListener(\"reset\",this._onFormReset,{passive:!0}),this.input.addEventListeners()},r._removeEventListeners=function(){var e=document.documentElement;e.removeEventListener(\"touchend\",this._onTouchEnd,!0),this.containerOuter.element.removeEventListener(\"keydown\",this._onKeyDown,!0),this.containerOuter.element.removeEventListener(\"mousedown\",this._onMouseDown,!0),e.removeEventListener(\"click\",this._onClick),e.removeEventListener(\"touchmove\",this._onTouchMove),this.dropdown.element.removeEventListener(\"mouseover\",this._onMouseOver),this._isSelectOneElement&&(this.containerOuter.element.removeEventListener(\"focus\",this._onFocus),this.containerOuter.element.removeEventListener(\"blur\",this._onBlur)),this.input.element.removeEventListener(\"keyup\",this._onKeyUp),this.input.element.removeEventListener(\"focus\",this._onFocus),this.input.element.removeEventListener(\"blur\",this._onBlur),this.input.element.form&&this.input.element.form.removeEventListener(\"reset\",this._onFormReset),this.input.removeEventListeners()},r._onKeyDown=function(e){var t,i=e.target,n=e.keyCode,s=e.ctrlKey,r=e.metaKey,o=this._store.activeItems,a=this.input.isFocussed,c=this.dropdown.isActive,l=this.itemList.hasChildren(),h=String.fromCharCode(n),u=J,d=Y,p=Z,m=Q,f=ee,v=te,g=ie,_=ne,b=se,y=s||r;!this._isTextElement&&/[a-zA-Z0-9-_ ]/.test(h)&&this.showDropdown();var E=((t={})[m]=this._onAKey,t[p]=this._onEnterKey,t[f]=this._onEscapeKey,t[v]=this._onDirectionKey,t[_]=this._onDirectionKey,t[g]=this._onDirectionKey,t[b]=this._onDirectionKey,t[d]=this._onDeleteKey,t[u]=this._onDeleteKey,t);E[n]&&E[n]({event:e,target:i,keyCode:n,metaKey:r,activeItems:o,hasFocusedInput:a,hasActiveDropdown:c,hasItems:l,hasCtrlDownKeyPressed:y})},r._onKeyUp=function(e){var t=e.target,i=e.keyCode,n=this.input.value,s=this._store.activeItems,r=this._canAddItem(s,n),o=J,a=Y;if(this._isTextElement)if(r.notice&&n){var c=this._getTemplate(\"notice\",r.notice);this.dropdown.element.innerHTML=c.outerHTML,this.showDropdown(!0)}else this.hideDropdown(!0);else{var l=(i===o||i===a)&&!t.value,h=!this._isTextElement&&this._isSearching,u=this._canSearch&&r.response;l&&h?(this._isSearching=!1,this._store.dispatch(be(!0))):u&&this._handleSearch(this.input.value)}this._canSearch=this.config.searchEnabled},r._onAKey=function(e){var t=e.hasItems;e.hasCtrlDownKeyPressed&&t&&(this._canSearch=!1,this.config.removeItems&&!this.input.value&&this.input.element===document.activeElement&&this.highlightAll())},r._onEnterKey=function(e){var t=e.event,i=e.target,n=e.activeItems,s=e.hasActiveDropdown,r=Z,o=i.hasAttribute(\"data-button\");if(this._isTextElement&&i.value){var a=this.input.value;this._canAddItem(n,a).response&&(this.hideDropdown(!0),this._addItem({value:a}),this._triggerChange(a),this.clearInput())}if(o&&(this._handleButtonAction(n,i),t.preventDefault()),s){var c=this.dropdown.getChild(\".\"+this.config.classNames.highlightedState);c&&(n[0]&&(n[0].keyCode=r),this._handleChoiceAction(n,c)),t.preventDefault()}else this._isSelectOneElement&&(this.showDropdown(),t.preventDefault())},r._onEscapeKey=function(e){e.hasActiveDropdown&&(this.hideDropdown(!0),this.containerOuter.focus())},r._onDirectionKey=function(e){var t,i,n,s=e.event,r=e.hasActiveDropdown,o=e.keyCode,a=e.metaKey,c=ie,l=ne,h=se;if(r||this._isSelectOneElement){this.showDropdown(),this._canSearch=!1;var u,d=o===c||o===h?1:-1,p=\"[data-choice-selectable]\";if(a||o===h||o===l)u=d>0?this.dropdown.element.querySelector(\"[data-choice-selectable]:last-of-type\"):this.dropdown.element.querySelector(p);else{var m=this.dropdown.element.querySelector(\".\"+this.config.classNames.highlightedState);u=m?function(e,t,i){if(void 0===i&&(i=1),e instanceof Element&&\"string\"==typeof t){for(var n=(i>0?\"next\":\"previous\")+\"ElementSibling\",s=e[n];s;){if(s.matches(t))return s;s=s[n]}return s}}(m,p,d):this.dropdown.element.querySelector(p)}u&&(t=u,i=this.choiceList.element,void 0===(n=d)&&(n=1),t&&(n>0?i.scrollTop+i.offsetHeight>=t.offsetTop+t.offsetHeight:t.offsetTop>=i.scrollTop)||this.choiceList.scrollToChildElement(u,d),this._highlightChoice(u)),s.preventDefault()}},r._onDeleteKey=function(e){var t=e.event,i=e.target,n=e.hasFocusedInput,s=e.activeItems;!n||i.value||this._isSelectOneElement||(this._handleBackspace(s),t.preventDefault())},r._onTouchMove=function(){this._wasTap&&(this._wasTap=!1)},r._onTouchEnd=function(e){var t=(e||e.touches[0]).target;this._wasTap&&this.containerOuter.element.contains(t)&&((t===this.containerOuter.element||t===this.containerInner.element)&&(this._isTextElement?this.input.focus():this._isSelectMultipleElement&&this.showDropdown()),e.stopPropagation()),this._wasTap=!0},r._onMouseDown=function(e){var t=e.target;if(t instanceof HTMLElement){if(we&&this.choiceList.element.contains(t)){var i=this.choiceList.element.firstElementChild,n=\"ltr\"===this._direction?e.offsetX>=i.offsetWidth:e.offsetX0&&this.unhighlightAll(),this.containerOuter.removeFocusState(),this.hideDropdown(!0))},r._onFocus=function(e){var t,i=this,n=e.target;this.containerOuter.element.contains(n)&&((t={}).text=function(){n===i.input.element&&i.containerOuter.addFocusState()},t[\"select-one\"]=function(){i.containerOuter.addFocusState(),n===i.input.element&&i.showDropdown(!0)},t[\"select-multiple\"]=function(){n===i.input.element&&(i.showDropdown(!0),i.containerOuter.addFocusState())},t)[this.passedElement.element.type]()},r._onBlur=function(e){var t=this,i=e.target;if(this.containerOuter.element.contains(i)&&!this._isScrollingOnIe){var n,s=this._store.activeItems.some((function(e){return e.highlighted}));((n={}).text=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),s&&t.unhighlightAll(),t.hideDropdown(!0))},n[\"select-one\"]=function(){t.containerOuter.removeFocusState(),(i===t.input.element||i===t.containerOuter.element&&!t._canSearch)&&t.hideDropdown(!0)},n[\"select-multiple\"]=function(){i===t.input.element&&(t.containerOuter.removeFocusState(),t.hideDropdown(!0),s&&t.unhighlightAll())},n)[this.passedElement.element.type]()}else this._isScrollingOnIe=!1,this.input.element.focus()},r._onFormReset=function(){this._store.dispatch({type:\"RESET_TO\",state:this._initialState})},r._highlightChoice=function(e){var t=this;void 0===e&&(e=null);var i=Array.from(this.dropdown.element.querySelectorAll(\"[data-choice-selectable]\"));if(i.length){var n=e;Array.from(this.dropdown.element.querySelectorAll(\".\"+this.config.classNames.highlightedState)).forEach((function(e){e.classList.remove(t.config.classNames.highlightedState),e.setAttribute(\"aria-selected\",\"false\")})),n?this._highlightPosition=i.indexOf(n):(n=i.length>this._highlightPosition?i[this._highlightPosition]:i[i.length-1])||(n=i[0]),n.classList.add(this.config.classNames.highlightedState),n.setAttribute(\"aria-selected\",\"true\"),this.passedElement.triggerEvent(B,{el:n}),this.dropdown.isActive&&(this.input.setActiveDescendant(n.id),this.containerOuter.setActiveDescendant(n.id))}},r._addItem=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.choiceId,r=void 0===s?-1:s,o=e.groupId,a=void 0===o?-1:o,c=e.customProperties,l=void 0===c?null:c,h=e.placeholder,u=void 0!==h&&h,d=e.keyCode,p=void 0===d?null:d,m=\"string\"==typeof t?t.trim():t,f=p,v=l,g=this._store.items,_=n||m,b=r||-1,y=a>=0?this._store.getGroupById(a):null,E=g?g.length+1:1;return this.config.prependValue&&(m=this.config.prependValue+m.toString()),this.config.appendValue&&(m+=this.config.appendValue.toString()),this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.choiceId,r=e.groupId,o=e.customProperties,a=e.placeholder,c=e.keyCode;return{type:W,value:t,label:i,id:n,choiceId:s,groupId:r,customProperties:o,placeholder:a,keyCode:c}}({value:m,label:_,id:E,choiceId:b,groupId:a,customProperties:l,placeholder:u,keyCode:f})),this._isSelectOneElement&&this.removeActiveItems(E),this.passedElement.triggerEvent(K,{id:E,value:m,label:_,customProperties:v,groupValue:y&&y.value?y.value:void 0,keyCode:f}),this},r._removeItem=function(e){if(!e||!E(\"Object\",e))return this;var t=e.id,i=e.value,n=e.label,s=e.choiceId,r=e.groupId,o=r>=0?this._store.getGroupById(r):null;return this._store.dispatch(function(e,t){return{type:X,id:e,choiceId:t}}(t,s)),o&&o.value?this.passedElement.triggerEvent(R,{id:t,value:i,label:n,groupValue:o.value}):this.passedElement.triggerEvent(R,{id:t,value:i,label:n}),this},r._addChoice=function(e){var t=e.value,i=e.label,n=void 0===i?null:i,s=e.isSelected,r=void 0!==s&&s,o=e.isDisabled,a=void 0!==o&&o,c=e.groupId,l=void 0===c?-1:c,h=e.customProperties,u=void 0===h?null:h,d=e.placeholder,p=void 0!==d&&d,m=e.keyCode,f=void 0===m?null:m;if(null!=t){var v=this._store.choices,g=n||t,_=v?v.length+1:1,b=this._baseId+\"-\"+this._idNames.itemChoice+\"-\"+_;this._store.dispatch(function(e){var t=e.value,i=e.label,n=e.id,s=e.groupId,r=e.disabled,o=e.elementId,a=e.customProperties,c=e.placeholder,l=e.keyCode;return{type:V,value:t,label:i,id:n,groupId:s,disabled:r,elementId:o,customProperties:a,placeholder:c,keyCode:l}}({id:_,groupId:l,elementId:b,value:t,label:g,disabled:a,customProperties:u,placeholder:p,keyCode:f})),r&&this._addItem({value:t,label:g,choiceId:_,customProperties:u,placeholder:p,keyCode:f})}},r._addGroup=function(e){var t=this,i=e.group,n=e.id,s=e.valueKey,r=void 0===s?\"value\":s,o=e.labelKey,a=void 0===o?\"label\":o,c=E(\"Object\",i)?i.choices:Array.from(i.getElementsByTagName(\"OPTION\")),l=n||Math.floor((new Date).valueOf()*Math.random()),h=!!i.disabled&&i.disabled;c?(this._store.dispatch(Ee({value:i.label,id:l,active:!0,disabled:h})),c.forEach((function(e){var i=e.disabled||e.parentNode&&e.parentNode.disabled;t._addChoice({value:e[r],label:E(\"Object\",e)?e[a]:e.innerHTML,isSelected:e.selected,isDisabled:i,groupId:l,customProperties:e.customProperties,placeholder:e.placeholder})}))):this._store.dispatch(Ee({value:i.label,id:i.id,active:!1,disabled:i.disabled}))},r._getTemplate=function(e){var t;if(!e)return null;for(var i=this.config.classNames,n=arguments.length,s=new Array(n>1?n-1:0),r=1;r{var e;return this.input_el.name=null!==(e=this.model.name)&&void 0!==e?e:\"\"})),this.connect(this.model.properties.value.change,(()=>{this.input_el.value=this.format_value,this.old_value=this.input_el.value})),this.connect(this.model.properties.low.change,(()=>{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(t<=l,\"Invalid bounds, low must be inferior to high\"),null!=e&&null!=t&&e{const{value:e,low:t,high:l}=this.model;null!=t&&null!=l&&(0,p.assert)(l>=t,\"Invalid bounds, high must be superior to low\"),null!=e&&null!=l&&e>l&&(this.model.value=l)})),this.connect(this.model.properties.high.change,(()=>this.input_el.placeholder=this.model.placeholder)),this.connect(this.model.properties.disabled.change,(()=>this.input_el.disabled=this.model.disabled)),this.connect(this.model.properties.placeholder.change,(()=>this.input_el.placeholder=this.model.placeholder))}get format_value(){return null!=this.model.value?this.model.pretty(this.model.value):\"\"}_set_input_filter(e){this.input_el.addEventListener(\"input\",(()=>{const{selectionStart:t,selectionEnd:l}=this.input_el;if(e(this.input_el.value))this.old_value=this.input_el.value;else{const e=this.old_value.length-this.input_el.value.length;this.input_el.value=this.old_value,t&&l&&this.input_el.setSelectionRange(t-1,l+e)}}))}render(){super.render(),this.input_el=(0,r.input)({type:\"text\",class:_.input,name:this.model.name,value:this.format_value,disabled:this.model.disabled,placeholder:this.model.placeholder}),this.old_value=this.format_value,this.set_input_filter(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.input_el.addEventListener(\"focusout\",(()=>this.input_el.value=this.format_value)),this.group_el.appendChild(this.input_el)}set_input_filter(){\"int\"==this.model.mode?this._set_input_filter((e=>m.test(e))):\"float\"==this.model.mode&&this._set_input_filter((e=>c.test(e)))}bound_value(e){let t=e;const{low:l,high:i}=this.model;return t=null!=l?Math.max(l,t):t,t=null!=i?Math.min(i,t):t,t}get value(){let e=\"\"!=this.input_el.value?Number(this.input_el.value):null;return null!=e&&(e=this.bound_value(e)),e}change_input(){null==this.value?this.model.value=null:Number.isNaN(this.value)||(this.model.value=this.value)}}l.NumericInputView=v,v.__name__=\"NumericInputView\";class g extends o.InputWidget{constructor(e){super(e)}_formatter(e,t){return(0,d.isString)(t)?h.format(e,t):t.doFormat([e],{loc:0})[0]}pretty(e){return null!=this.format?this._formatter(e,this.format):`${e}`}}l.NumericInput=g,u=g,g.__name__=\"NumericInput\",u.prototype.default_view=v,u.define((({Number:e,String:t,Enum:l,Ref:i,Or:n,Nullable:s})=>({value:[s(e),null],placeholder:[t,\"\"],mode:[l(\"int\",\"float\"),\"int\"],format:[s(n(t,i(a.TickFormatter))),null],low:[s(e),null],high:[s(e),null]})))},\n", - " 479: function _(e,t,r,s,n){var a;s();const o=e(468),_=e(43);class p extends o.MarkupView{render(){super.render();const e=(0,_.pre)({style:{overflow:\"auto\"}},this.model.text);this.markup_el.appendChild(e)}}r.PreTextView=p,p.__name__=\"PreTextView\";class u extends o.Markup{constructor(e){super(e)}}r.PreText=u,a=u,u.__name__=\"PreText\",a.prototype.default_view=p},\n", - " 480: function _(t,o,e,a,i){a();const n=t(1);var u;const s=t(452),c=t(43),_=(0,n.__importStar)(t(318));class r extends s.ButtonGroupView{change_active(t){this.model.active!==t&&(this.model.active=t)}_update_active(){const{active:t}=this.model;this._buttons.forEach(((o,e)=>{(0,c.classes)(o).toggle(_.active,t===e)}))}}e.RadioButtonGroupView=r,r.__name__=\"RadioButtonGroupView\";class l extends s.ButtonGroup{constructor(t){super(t)}}e.RadioButtonGroup=l,u=l,l.__name__=\"RadioButtonGroup\",u.prototype.default_view=r,u.define((({Int:t,Nullable:o})=>({active:[o(t),null]})))},\n", - " 481: function _(e,n,i,t,a){t();const s=e(1);var l;const o=e(43),d=e(34),p=e(455),r=(0,s.__importStar)(e(449));class u extends p.InputGroupView{render(){super.render();const e=(0,o.div)({class:[r.input_group,this.model.inline?r.inline:null]});this.el.appendChild(e);const n=(0,d.uniqueId)(),{active:i,labels:t}=this.model;this._inputs=[];for(let a=0;athis.change_active(a))),this._inputs.push(s),this.model.disabled&&(s.disabled=!0),a==i&&(s.checked=!0);const l=(0,o.label)(s,(0,o.span)(t[a]));e.appendChild(l)}}change_active(e){this.model.active=e}}i.RadioGroupView=u,u.__name__=\"RadioGroupView\";class c extends p.InputGroup{constructor(e){super(e)}}i.RadioGroup=c,l=c,c.__name__=\"RadioGroup\",l.prototype.default_view=u,l.define((({Boolean:e,Int:n,String:i,Array:t,Nullable:a})=>({active:[a(n),null],labels:[t(i),[]],inline:[e,!1]})))},\n", - " 482: function _(e,r,t,a,i){a();var n;const o=(0,e(1).__importStar)(e(153)),s=e(461),_=e(8);class d extends s.AbstractRangeSliderView{}t.RangeSliderView=d,d.__name__=\"RangeSliderView\";class c extends s.AbstractSlider{constructor(e){super(e),this.behaviour=\"drag\",this.connected=[!1,!0,!1]}_formatter(e,r){return(0,_.isString)(r)?o.format(e,r):r.compute(e)}}t.RangeSlider=c,n=c,c.__name__=\"RangeSlider\",n.prototype.default_view=d,n.override({format:\"0[.]00\"})},\n", - " 483: function _(e,t,n,s,i){s();const l=e(1);var u;const a=e(43),o=e(8),p=e(13),_=e(448),r=(0,l.__importStar)(e(449));class c extends _.InputWidgetView{constructor(){super(...arguments),this._known_values=new Set}connect_signals(){super.connect_signals();const{value:e,options:t}=this.model.properties;this.on_change(e,(()=>{this._update_value()})),this.on_change(t,(()=>{(0,a.empty)(this.input_el),(0,a.append)(this.input_el,...this.options_el()),this._update_value()}))}options_el(){const{_known_values:e}=this;function t(t){return t.map((t=>{let n,s;return(0,o.isString)(t)?n=s=t:[n,s]=t,e.add(n),(0,a.option)({value:n},s)}))}e.clear();const{options:n}=this.model;return(0,o.isArray)(n)?t(n):(0,p.entries)(n).map((([e,n])=>(0,a.optgroup)({label:e},t(n))))}render(){super.render(),this.input_el=(0,a.select)({class:r.input,name:this.model.name,disabled:this.model.disabled},this.options_el()),this._update_value(),this.input_el.addEventListener(\"change\",(()=>this.change_input())),this.group_el.appendChild(this.input_el)}change_input(){const e=this.input_el.value;this.model.value=e,super.change_input()}_update_value(){const{value:e}=this.model;this._known_values.has(e)?this.input_el.value=e:this.input_el.removeAttribute(\"value\")}}n.SelectView=c,c.__name__=\"SelectView\";class h extends _.InputWidget{constructor(e){super(e)}}n.Select=h,u=h,h.__name__=\"Select\",u.prototype.default_view=c,u.define((({String:e,Array:t,Tuple:n,Dict:s,Or:i})=>{const l=t(i(e,n(e,e)));return{value:[e,\"\"],options:[i(l,s(l)),[]]}}))},\n", - " 484: function _(e,t,r,i,a){i();var o;const s=(0,e(1).__importStar)(e(153)),_=e(461),n=e(8);class c extends _.AbstractSliderView{}r.SliderView=c,c.__name__=\"SliderView\";class d extends _.AbstractSlider{constructor(e){super(e),this.behaviour=\"tap\",this.connected=[!0,!1]}_formatter(e,t){return(0,n.isString)(t)?s.format(e,t):t.compute(e)}}r.Slider=d,o=d,d.__name__=\"Slider\",o.prototype.default_view=c,o.override({format:\"0[.]00\"})},\n", - " 485: function _(e,t,i,n,s){var l;n();const o=e(478),r=e(43),{min:a,max:h,floor:_,abs:u}=Math;function d(e){return _(e)!==e?e.toFixed(16).replace(/0+$/,\"\").split(\".\")[1].length:0}class p extends o.NumericInputView{*buttons(){yield this.btn_up_el,yield this.btn_down_el}initialize(){super.initialize(),this._handles={interval:void 0,timeout:void 0},this._interval=200}connect_signals(){super.connect_signals();const e=this.model.properties;this.on_change(e.disabled,(()=>{for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled)}))}render(){super.render(),this.wrapper_el=(0,r.div)({class:\"bk-spin-wrapper\"}),this.group_el.replaceChild(this.wrapper_el,this.input_el),this.btn_up_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-up\"}),this.btn_down_el=(0,r.button)({class:\"bk-spin-btn bk-spin-btn-down\"}),this.wrapper_el.appendChild(this.input_el),this.wrapper_el.appendChild(this.btn_up_el),this.wrapper_el.appendChild(this.btn_down_el);for(const e of this.buttons())(0,r.toggle_attribute)(e,\"disabled\",this.model.disabled),e.addEventListener(\"mousedown\",(e=>this._btn_mouse_down(e))),e.addEventListener(\"mouseup\",(()=>this._btn_mouse_up())),e.addEventListener(\"mouseleave\",(()=>this._btn_mouse_leave()));this.input_el.addEventListener(\"keydown\",(e=>this._input_key_down(e))),this.input_el.addEventListener(\"keyup\",(()=>this.model.value_throttled=this.model.value)),this.input_el.addEventListener(\"wheel\",(e=>this._input_mouse_wheel(e))),this.input_el.addEventListener(\"wheel\",function(e,t,i=!1){let n;return function(...s){const l=this,o=i&&void 0===n;void 0!==n&&clearTimeout(n),n=setTimeout((function(){n=void 0,i||e.apply(l,s)}),t),o&&e.apply(l,s)}}((()=>{this.model.value_throttled=this.model.value}),this.model.wheel_wait,!1))}get precision(){const{low:e,high:t,step:i}=this.model,n=d;return h(n(u(null!=e?e:0)),n(u(null!=t?t:0)),n(u(i)))}remove(){this._stop_incrementation(),super.remove()}_start_incrementation(e){clearInterval(this._handles.interval),this._counter=0;const{step:t}=this.model,i=e=>{if(this._counter+=1,this._counter%5==0){const t=Math.floor(this._counter/5);t<10?(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(e)),this._interval/(t+1))):t>=10&&t<=13&&(clearInterval(this._handles.interval),this._handles.interval=setInterval((()=>i(2*e)),this._interval/10))}this.increment(e)};this._handles.interval=setInterval((()=>i(e*t)),this._interval)}_stop_incrementation(){clearTimeout(this._handles.timeout),this._handles.timeout=void 0,clearInterval(this._handles.interval),this._handles.interval=void 0,this.model.value_throttled=this.model.value}_btn_mouse_down(e){e.preventDefault();const t=e.currentTarget===this.btn_up_el?1:-1;this.increment(t*this.model.step),this.input_el.focus(),this._handles.timeout=setTimeout((()=>this._start_incrementation(t)),this._interval)}_btn_mouse_up(){this._stop_incrementation()}_btn_mouse_leave(){this._stop_incrementation()}_input_mouse_wheel(e){if(document.activeElement===this.input_el){e.preventDefault();const t=e.deltaY>0?-1:1;this.increment(t*this.model.step)}}_input_key_down(e){switch(e.keyCode){case r.Keys.Up:return e.preventDefault(),this.increment(this.model.step);case r.Keys.Down:return e.preventDefault(),this.increment(-this.model.step);case r.Keys.PageUp:return e.preventDefault(),this.increment(this.model.page_step_multiplier*this.model.step);case r.Keys.PageDown:return e.preventDefault(),this.increment(-this.model.page_step_multiplier*this.model.step)}}adjust_to_precision(e){return this.bound_value(Number(e.toFixed(this.precision)))}increment(e){const{low:t,high:i}=this.model;null==this.model.value?e>0?this.model.value=null!=t?t:null!=i?a(0,i):0:e<0&&(this.model.value=null!=i?i:null!=t?h(t,0):0):this.model.value=this.adjust_to_precision(this.model.value+e)}change_input(){super.change_input(),this.model.value_throttled=this.model.value}}i.SpinnerView=p,p.__name__=\"SpinnerView\";class m extends o.NumericInput{constructor(e){super(e)}}i.Spinner=m,l=m,m.__name__=\"Spinner\",l.prototype.default_view=p,l.define((({Number:e,Nullable:t})=>({value_throttled:[t(e),null],step:[e,1],page_step_multiplier:[e,10],wheel_wait:[e,100]}))),l.override({mode:\"float\"})},\n", - " 486: function _(e,t,s,n,i){n();const o=e(1);var r;const c=e(447),l=e(43),p=(0,o.__importStar)(e(449));class _ extends c.TextLikeInputView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.rows.change,(()=>this.input_el.rows=this.model.rows)),this.connect(this.model.properties.cols.change,(()=>this.input_el.cols=this.model.cols))}_render_input(){this.input_el=(0,l.textarea)({class:p.input})}render(){super.render(),this.input_el.cols=this.model.cols,this.input_el.rows=this.model.rows}}s.TextAreaInputView=_,_.__name__=\"TextAreaInputView\";class a extends c.TextLikeInput{constructor(e){super(e)}}s.TextAreaInput=a,r=a,a.__name__=\"TextAreaInput\",r.prototype.default_view=_,r.define((({Int:e})=>({cols:[e,20],rows:[e,2]}))),r.override({max_length:500})},\n", - " 487: function _(e,t,s,c,i){c();const o=e(1);var a;const n=e(441),l=e(43),_=(0,o.__importStar)(e(318));class r extends n.AbstractButtonView{connect_signals(){super.connect_signals(),this.connect(this.model.properties.active.change,(()=>this._update_active()))}render(){super.render(),this._update_active()}click(){this.model.active=!this.model.active,super.click()}_update_active(){(0,l.classes)(this.button_el).toggle(_.active,this.model.active)}}s.ToggleView=r,r.__name__=\"ToggleView\";class g extends n.AbstractButton{constructor(e){super(e)}}s.Toggle=g,a=g,g.__name__=\"Toggle\",a.prototype.default_view=r,a.define((({Boolean:e})=>({active:[e,!1]}))),a.override({label:\"Toggle\"})},\n", - " }, 439, {\"models/widgets/main\":439,\"models/widgets/index\":440,\"models/widgets/abstract_button\":441,\"models/widgets/control\":442,\"models/widgets/widget\":512,\"models/widgets/abstract_icon\":444,\"models/widgets/autocomplete_input\":445,\"models/widgets/text_input\":446,\"models/widgets/text_like_input\":447,\"models/widgets/input_widget\":448,\"styles/widgets/inputs.css\":449,\"models/widgets/button\":450,\"models/widgets/checkbox_button_group\":451,\"models/widgets/button_group\":452,\"models/widgets/oriented_control\":453,\"models/widgets/checkbox_group\":454,\"models/widgets/input_group\":455,\"models/widgets/color_picker\":456,\"models/widgets/date_picker\":457,\"styles/widgets/flatpickr.css\":459,\"models/widgets/date_range_slider\":460,\"models/widgets/abstract_slider\":461,\"styles/widgets/sliders.css\":463,\"styles/widgets/nouislider.css\":464,\"models/widgets/date_slider\":465,\"models/widgets/datetime_range_slider\":466,\"models/widgets/div\":467,\"models/widgets/markup\":468,\"styles/clearfix.css\":469,\"models/widgets/dropdown\":470,\"models/widgets/file_input\":471,\"models/widgets/multiselect\":472,\"models/widgets/paragraph\":473,\"models/widgets/password_input\":474,\"models/widgets/multichoice\":475,\"styles/widgets/choices.css\":477,\"models/widgets/numeric_input\":478,\"models/widgets/pretext\":479,\"models/widgets/radio_button_group\":480,\"models/widgets/radio_group\":481,\"models/widgets/range_slider\":482,\"models/widgets/selectbox\":483,\"models/widgets/slider\":484,\"models/widgets/spinner\":485,\"models/widgets/textarea_input\":486,\"models/widgets/toggle\":487}, {});});\n", - "\n", - " /* END bokeh-widgets.min.js */\n", - " },\n", - " function(Bokeh) {\n", - " /* BEGIN bokeh-tables.min.js */\n", - " /*!\n", - " * Copyright (c) 2012 - 2022, Anaconda, Inc., and Bokeh Contributors\n", - " * All rights reserved.\n", - " * \n", - " * Redistribution and use in source and binary forms, with or without modification,\n", - " * are permitted provided that the following conditions are met:\n", - " * \n", - " * Redistributions of source code must retain the above copyright notice,\n", - " * this list of conditions and the following disclaimer.\n", - " * \n", - " * Redistributions in binary form must reproduce the above copyright notice,\n", - " * this list of conditions and the following disclaimer in the documentation\n", - " * and/or other materials provided with the distribution.\n", - " * \n", - " * Neither the name of Anaconda nor the names of any contributors\n", - " * may be used to endorse or promote products derived from this software\n", - " * without specific prior written permission.\n", - " * \n", - " * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS \"AS IS\"\n", - " * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE\n", - " * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE\n", - " * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE\n", - " * LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR\n", - " * CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF\n", - " * SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS\n", - " * INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN\n", - " * CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)\n", - " * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF\n", - " * THE POSSIBILITY OF SUCH DAMAGE.\n", - " */\n", - " (function(root, factory) {\n", - " factory(root[\"Bokeh\"], \"2.4.3\");\n", - " })(this, function(Bokeh, version) {\n", - " let define;\n", - " return (function(modules, entry, aliases, externals) {\n", - " const bokeh = typeof Bokeh !== \"undefined\" && (version != null ? Bokeh[version] : Bokeh);\n", - " if (bokeh != null) {\n", - " return bokeh.register_plugin(modules, entry, aliases);\n", - " } else {\n", - " throw new Error(\"Cannot find Bokeh \" + version + \". You have to load it prior to loading plugins.\");\n", - " }\n", - " })\n", - " ({\n", - " 488: function _(t,e,o,r,s){r();const _=(0,t(1).__importStar)(t(489));o.Tables=_;(0,t(7).register_models)(_)},\n", - " 489: function _(g,a,r,e,t){e();const o=g(1);(0,o.__exportStar)(g(490),r),(0,o.__exportStar)(g(493),r),t(\"DataTable\",g(496).DataTable),t(\"TableColumn\",g(514).TableColumn),t(\"TableWidget\",g(513).TableWidget);var n=g(516);t(\"AvgAggregator\",n.AvgAggregator),t(\"MinAggregator\",n.MinAggregator),t(\"MaxAggregator\",n.MaxAggregator),t(\"SumAggregator\",n.SumAggregator);var A=g(517);t(\"GroupingInfo\",A.GroupingInfo),t(\"DataCube\",A.DataCube)},\n", - " 490: function _(e,t,i,s,a){s();const r=e(1);var l,n,u,d,o,p,_,c,h;const E=e(43),V=e(226),m=e(53),f=e(491),v=(0,r.__importStar)(e(492));class w extends V.DOMView{constructor(e){const{model:t,parent:i}=e.column;super(Object.assign({model:t,parent:i},e)),this.args=e,this.initialize(),this.render()}get emptyValue(){return null}initialize(){super.initialize(),this.inputEl=this._createInput(),this.defaultValue=null}async lazy_initialize(){throw new Error(\"unsupported\")}css_classes(){return super.css_classes().concat(v.cell_editor)}render(){super.render(),this.args.container.append(this.el),this.el.appendChild(this.inputEl),this.renderEditor(),this.disableNavigation()}renderEditor(){}disableNavigation(){this.inputEl.addEventListener(\"keydown\",(e=>{switch(e.keyCode){case E.Keys.Left:case E.Keys.Right:case E.Keys.Up:case E.Keys.Down:case E.Keys.PageUp:case E.Keys.PageDown:e.stopImmediatePropagation()}}))}destroy(){this.remove()}focus(){this.inputEl.focus()}show(){}hide(){}position(){}getValue(){return this.inputEl.value}setValue(e){this.inputEl.value=e}serializeValue(){return this.getValue()}isValueChanged(){return!(\"\"==this.getValue()&&null==this.defaultValue)&&this.getValue()!==this.defaultValue}applyValue(e,t){const i=this.args.grid.getData(),s=i.index.indexOf(e[f.DTINDEX_NAME]);i.setField(s,this.args.column.field,t)}loadValue(e){const t=e[this.args.column.field];this.defaultValue=null!=t?t:this.emptyValue,this.setValue(this.defaultValue)}validateValue(e){if(this.args.column.validator){const t=this.args.column.validator(e);if(!t.valid)return t}return{valid:!0,msg:null}}validate(){return this.validateValue(this.getValue())}}i.CellEditorView=w,w.__name__=\"CellEditorView\";class g extends m.Model{}i.CellEditor=g,g.__name__=\"CellEditor\";class x extends w{get emptyValue(){return\"\"}_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}}i.StringEditorView=x,x.__name__=\"StringEditorView\";class y extends g{}i.StringEditor=y,l=y,y.__name__=\"StringEditor\",l.prototype.default_view=x,l.define((({String:e,Array:t})=>({completions:[t(e),[]]})));class I extends w{_createInput(){return(0,E.textarea)()}renderEditor(){this.inputEl.focus(),this.inputEl.select()}}i.TextEditorView=I,I.__name__=\"TextEditorView\";class b extends g{}i.TextEditor=b,n=b,b.__name__=\"TextEditor\",n.prototype.default_view=I;class N extends w{_createInput(){return(0,E.select)()}renderEditor(){for(const e of this.model.options)this.inputEl.appendChild((0,E.option)({value:e},e));this.focus()}}i.SelectEditorView=N,N.__name__=\"SelectEditorView\";class C extends g{}i.SelectEditor=C,u=C,C.__name__=\"SelectEditor\",u.prototype.default_view=N,u.define((({String:e,Array:t})=>({options:[t(e),[]]})));class D extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.PercentEditorView=D,D.__name__=\"PercentEditorView\";class S extends g{}i.PercentEditor=S,d=S,S.__name__=\"PercentEditor\",d.prototype.default_view=D;class k extends w{_createInput(){return(0,E.input)({type:\"checkbox\"})}renderEditor(){this.focus()}loadValue(e){this.defaultValue=!!e[this.args.column.field],this.inputEl.checked=this.defaultValue}serializeValue(){return this.inputEl.checked}}i.CheckboxEditorView=k,k.__name__=\"CheckboxEditorView\";class z extends g{}i.CheckboxEditor=z,o=z,z.__name__=\"CheckboxEditor\",o.prototype.default_view=k;class P extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseInt(this.getValue(),10))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid integer\"}:super.validateValue(e)}}i.IntEditorView=P,P.__name__=\"IntEditorView\";class T extends g{}i.IntEditor=T,p=T,T.__name__=\"IntEditor\",p.prototype.default_view=P,p.define((({Int:e})=>({step:[e,1]})));class K extends w{_createInput(){return(0,E.input)({type:\"text\"})}renderEditor(){this.inputEl.focus(),this.inputEl.select()}remove(){super.remove()}serializeValue(){var e;return null!==(e=parseFloat(this.getValue()))&&void 0!==e?e:0}loadValue(e){super.loadValue(e),this.inputEl.defaultValue=this.defaultValue,this.inputEl.select()}validateValue(e){return isNaN(e)?{valid:!1,msg:\"Please enter a valid number\"}:super.validateValue(e)}}i.NumberEditorView=K,K.__name__=\"NumberEditorView\";class A extends g{}i.NumberEditor=A,_=A,A.__name__=\"NumberEditor\",_.prototype.default_view=K,_.define((({Number:e})=>({step:[e,.01]})));class M extends w{_createInput(){return(0,E.input)({type:\"text\"})}}i.TimeEditorView=M,M.__name__=\"TimeEditorView\";class O extends g{}i.TimeEditor=O,c=O,O.__name__=\"TimeEditor\",c.prototype.default_view=M;class F extends 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\n", + "image/png": 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", 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" ] @@ -7469,34 +5413,6 @@ "sm.scatter()" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As the above is not interactive, it may be hard to see the overlap between species. For this, we can simply launch a SAMGUI instance from the combined SAM object (requires SAMGUI, see the README instructions in the [SAM](https://github.com/atarashansky/self-assembling-manifold) github repo):" - ] - }, - { - "cell_type": "raw", - "metadata": {}, - "source": [ - "sm.samap.gui()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "To separate the species into different tabs so that each can be independently analyzed, we can use `SAMAP.gui` instead:" - ] - }, - { - "cell_type": "raw", - "metadata": {}, - "source": [ - "sm.gui()" - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -7513,16 +5429,16 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Finding cluster-specific markers in pl:cluster.\n", - "Finding cluster-specific markers in sc:tissue.\n", - "Finding cluster-specific markers in hy:Cluster.\n" + "INFO: Finding cluster-specific markers in pl:cluster.\n", + "INFO: Finding cluster-specific markers in sc:tissue.\n", + "INFO: Finding cluster-specific markers in hy:Cluster.\n" ] } ], @@ -7543,7 +5459,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ @@ -7556,7 +5472,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "metadata": {}, "outputs": [ { @@ -7578,7 +5494,7 @@ " 1.16734960e-95]))" ] }, - "execution_count": 23, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -7596,150 +5512,129 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 11\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 35\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 37\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Protonephridia: 40\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 25\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 27\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 37\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Protonephridia: 40\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_bd to pl;Epidermal: 11\n", - "Calculating gene pairs for the mapping: hy;ecEp_bd to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 10\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 17\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 28\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 31\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 39\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 41\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 13\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 16\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 13\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 16\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Intestine: 6\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 5\n", - "Calculating gene pairs for the mapping: hy;i_SC to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_fmgl1 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_gmgc to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_gmgc to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_mgl to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_mgl to sc;Flame cells\n", - "Calculating gene pairs for the mapping: hy;i_mgl to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb2 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nb2 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb3 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc1 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc2 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc2 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc4 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc4 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc5 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc7 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc7 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc8 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nc_prog to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 20\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 21\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 33\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 9\n", - "Calculating gene pairs for the mapping: hy;i_nem to sc;Flame cells\n", - "Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 32\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 32\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 10 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 15 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 28 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 31 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 39 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Intestine: 19 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Intestine: 30 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 0 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 22 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 5 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Parenchymal\n" - ] - }, - { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 23 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 32 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 33 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 34 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 8 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 9 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 12 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Pharynx: 27 to sc;Flame cells\n" + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC2 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 11\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 35\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 37\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Protonephridia: 40\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 25\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 27\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 37\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Protonephridia: 40\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 10\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 28\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 39\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 41\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Intestine: 30\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 13\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 16\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 13\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 16\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Intestine: 6\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 22\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 5\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl1 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_mgl to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb2 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb3 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc2 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc2 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc3 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc4 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc5 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc6 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc7 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc7 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_gc_prog to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_prog to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 20\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 21\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 33\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 9\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 32\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 32\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 10 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 15 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 28 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 31 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 39 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 19 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 30 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 0 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 22 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 5 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 23 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 33 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 34 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 8 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 9 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Pharynx: 27 to sc;Flame cells\n" ] } ], @@ -7749,7 +5644,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -7784,13 +5679,13 @@ " hy_ecEp_SC3;pl_Epidermal: 11_pval2\n", " hy_ecEp_SC3;pl_Epidermal: 2\n", " ...\n", + " pl_Neural: 34;sc_Neural_pval2\n", + " pl_Neural: 8;sc_Neural\n", + " pl_Neural: 8;sc_Neural_pval1\n", + " pl_Neural: 8;sc_Neural_pval2\n", + " pl_Neural: 9;sc_Neural\n", + " pl_Neural: 9;sc_Neural_pval1\n", " pl_Neural: 9;sc_Neural_pval2\n", - " pl_Parapharyngeal: 12;sc_Parenchymal\n", - " pl_Parapharyngeal: 12;sc_Parenchymal_pval1\n", - " pl_Parapharyngeal: 12;sc_Parenchymal_pval2\n", - " pl_Parapharyngeal: 38;sc_Parenchymal\n", - " pl_Parapharyngeal: 38;sc_Parenchymal_pval1\n", - " pl_Parapharyngeal: 38;sc_Parenchymal_pval2\n", " pl_Pharynx: 27;sc_Flame cells\n", " pl_Pharynx: 27;sc_Flame cells_pval1\n", " pl_Pharynx: 27;sc_Flame cells_pval2\n", @@ -7810,13 +5705,13 @@ " 0.0\n", " hy_t14973aep;pl_dd_Smed_v4_361_0_1\n", " ...\n", - " 0.0\n", - " pl_dd_Smed_v4_246_0_1;sc_Smp_306600\n", " 0.000001\n", + " pl_dd_Smed_v4_3862_0_1;sc_Smp_073270\n", + " 0.0\n", + " 0.0\n", + " pl_dd_Smed_v4_3970_0_1;sc_Smp_121660\n", + " 0.006523\n", " 0.0\n", - " NaN\n", - " NaN\n", - " NaN\n", " pl_dd_Smed_v4_1404_0_1;sc_Smp_147890\n", " 0.000006\n", " 0.0\n", @@ -7834,16 +5729,16 @@ " 0.0\n", " hy_t13309aep;pl_dd_Smed_v4_361_0_1\n", " ...\n", + " 0.003406\n", + " pl_dd_Smed_v4_6859_0_1;sc_Smp_342080\n", " 0.0\n", - " pl_dd_Smed_v4_246_0_1;sc_Smp_183710\n", - " 0.000001\n", - " 0.000048\n", - " NaN\n", - " NaN\n", - " NaN\n", - " pl_dd_Smed_v4_2745_0_1;sc_Smp_344500\n", + " 0.0\n", + " pl_dd_Smed_v4_6859_0_1;sc_Smp_342080\n", " 0.0\n", " 0.0\n", + " pl_dd_Smed_v4_3116_0_1;sc_Smp_152990\n", + " 0.000564\n", + " 0.0\n", " \n", " \n", " 2\n", @@ -7858,15 +5753,15 @@ " 0.0\n", " hy_t10876aep;pl_dd_Smed_v4_1215_0_1\n", " ...\n", + " 0.00026\n", + " pl_dd_Smed_v4_1566_0_1;sc_Smp_077980\n", " 0.0\n", - " pl_dd_Smed_v4_285_0_1;sc_Smp_306600\n", - " 0.000078\n", " 0.0\n", - " NaN\n", - " NaN\n", - " NaN\n", - " pl_dd_Smed_v4_3116_0_1;sc_Smp_152990\n", - " 0.000564\n", + " pl_dd_Smed_v4_3862_0_1;sc_Smp_073270\n", + " 0.0\n", + " 0.0\n", + " pl_dd_Smed_v4_2745_0_1;sc_Smp_344500\n", + " 0.0\n", " 0.0\n", " \n", " \n", @@ -7883,12 +5778,12 @@ " hy_t19278aep;pl_dd_Smed_v4_1971_0_1\n", " ...\n", " 0.0\n", - " pl_dd_Smed_v4_285_0_1;sc_Smp_183710\n", - " 0.000078\n", - " 0.000048\n", - " NaN\n", - " NaN\n", - " NaN\n", + " pl_dd_Smed_v4_4222_0_1;sc_Smp_175900\n", + " 0.0\n", + " 0.0\n", + " pl_dd_Smed_v4_4222_0_1;sc_Smp_175900\n", + " 0.0\n", + " 0.0\n", " pl_dd_Smed_v4_3482_0_1;sc_Smp_078230\n", " 0.000427\n", " 0.0\n", @@ -7898,28 +5793,28 @@ " hy_t19278aep;pl_dd_Smed_v4_1971_0_1\n", " 0.000023\n", " 0.0\n", - " hy_t12736aep;sc_Smp_335630\n", - " 0.001026\n", + " hy_t31713aep;sc_Smp_016780\n", " 0.0\n", + " 0.000514\n", " hy_t19278aep;pl_dd_Smed_v4_1971_0_1\n", " 0.0\n", " 0.0\n", " hy_t38670aep;pl_dd_Smed_v4_1131_0_1\n", " ...\n", + " 0.000295\n", + " pl_dd_Smed_v4_6730_0_1;sc_Smp_175900\n", + " 0.0\n", + " 0.0\n", + " pl_dd_Smed_v4_13082_0_1;sc_Smp_157240\n", + " 0.001536\n", " 0.0\n", - " pl_dd_Smed_v4_209_0_1;sc_Smp_097750\n", - " 0.000279\n", - " 0.004076\n", - " NaN\n", - " NaN\n", - " NaN\n", " pl_dd_Smed_v4_3482_0_1;sc_Smp_141230\n", " 0.000427\n", " 0.000005\n", " \n", " \n", "\n", - "

5 rows × 393 columns

\n", + "

5 rows × 348 columns

\n", "" ], "text/plain": [ @@ -7935,14 +5830,14 @@ "1 0.0 hy_t10388aep;sc_Smp_049580 \n", "2 0.0 hy_t3449aep;sc_Smp_335630 \n", "3 0.0 hy_t12862aep;sc_Smp_132740 \n", - "4 0.0 hy_t12736aep;sc_Smp_335630 \n", + "4 0.0 hy_t31713aep;sc_Smp_016780 \n", "\n", " hy_ecEp_SC2;sc_Tegument_prog_pval1 hy_ecEp_SC2;sc_Tegument_prog_pval2 \\\n", "0 0.000046 0.000363 \n", "1 0.0 0.0 \n", "2 0.0 0.0 \n", "3 0.0 0.000085 \n", - "4 0.001026 0.0 \n", + "4 0.0 0.000514 \n", "\n", " hy_ecEp_SC3;pl_Epidermal: 11 hy_ecEp_SC3;pl_Epidermal: 11_pval1 \\\n", "0 hy_t14973aep;pl_dd_Smed_v4_361_0_1 0.0 \n", @@ -7958,66 +5853,45 @@ "3 0.0 hy_t19278aep;pl_dd_Smed_v4_1971_0_1 \n", "4 0.0 hy_t38670aep;pl_dd_Smed_v4_1131_0_1 \n", "\n", - " ... pl_Neural: 9;sc_Neural_pval2 pl_Parapharyngeal: 12;sc_Parenchymal \\\n", - "0 ... 0.0 pl_dd_Smed_v4_246_0_1;sc_Smp_306600 \n", - "1 ... 0.0 pl_dd_Smed_v4_246_0_1;sc_Smp_183710 \n", - "2 ... 0.0 pl_dd_Smed_v4_285_0_1;sc_Smp_306600 \n", - "3 ... 0.0 pl_dd_Smed_v4_285_0_1;sc_Smp_183710 \n", - "4 ... 0.0 pl_dd_Smed_v4_209_0_1;sc_Smp_097750 \n", - "\n", - " pl_Parapharyngeal: 12;sc_Parenchymal_pval1 \\\n", - "0 0.000001 \n", - "1 0.000001 \n", - "2 0.000078 \n", - "3 0.000078 \n", - "4 0.000279 \n", - "\n", - " pl_Parapharyngeal: 12;sc_Parenchymal_pval2 \\\n", - "0 0.0 \n", - "1 0.000048 \n", - "2 0.0 \n", - "3 0.000048 \n", - "4 0.004076 \n", - "\n", - " pl_Parapharyngeal: 38;sc_Parenchymal \\\n", - "0 NaN \n", - "1 NaN \n", - "2 NaN \n", - "3 NaN \n", - "4 NaN \n", - "\n", - " pl_Parapharyngeal: 38;sc_Parenchymal_pval1 \\\n", - "0 NaN \n", - "1 NaN \n", - "2 NaN \n", - "3 NaN \n", - "4 NaN \n", - "\n", - " pl_Parapharyngeal: 38;sc_Parenchymal_pval2 \\\n", - "0 NaN \n", - "1 NaN \n", - "2 NaN \n", - "3 NaN \n", - "4 NaN \n", - "\n", - " pl_Pharynx: 27;sc_Flame cells pl_Pharynx: 27;sc_Flame cells_pval1 \\\n", - "0 pl_dd_Smed_v4_1404_0_1;sc_Smp_147890 0.000006 \n", - "1 pl_dd_Smed_v4_2745_0_1;sc_Smp_344500 0.0 \n", - "2 pl_dd_Smed_v4_3116_0_1;sc_Smp_152990 0.000564 \n", - "3 pl_dd_Smed_v4_3482_0_1;sc_Smp_078230 0.000427 \n", - "4 pl_dd_Smed_v4_3482_0_1;sc_Smp_141230 0.000427 \n", - "\n", - " pl_Pharynx: 27;sc_Flame cells_pval2 \n", - "0 0.0 \n", - "1 0.0 \n", - "2 0.0 \n", - "3 0.0 \n", - "4 0.000005 \n", - "\n", - "[5 rows x 393 columns]" + " ... pl_Neural: 34;sc_Neural_pval2 pl_Neural: 8;sc_Neural \\\n", + "0 ... 0.000001 pl_dd_Smed_v4_3862_0_1;sc_Smp_073270 \n", + "1 ... 0.003406 pl_dd_Smed_v4_6859_0_1;sc_Smp_342080 \n", + "2 ... 0.00026 pl_dd_Smed_v4_1566_0_1;sc_Smp_077980 \n", + "3 ... 0.0 pl_dd_Smed_v4_4222_0_1;sc_Smp_175900 \n", + "4 ... 0.000295 pl_dd_Smed_v4_6730_0_1;sc_Smp_175900 \n", + "\n", + " pl_Neural: 8;sc_Neural_pval1 pl_Neural: 8;sc_Neural_pval2 \\\n", + "0 0.0 0.0 \n", + "1 0.0 0.0 \n", + "2 0.0 0.0 \n", + "3 0.0 0.0 \n", + "4 0.0 0.0 \n", + "\n", + " pl_Neural: 9;sc_Neural pl_Neural: 9;sc_Neural_pval1 \\\n", + "0 pl_dd_Smed_v4_3970_0_1;sc_Smp_121660 0.006523 \n", + "1 pl_dd_Smed_v4_6859_0_1;sc_Smp_342080 0.0 \n", + "2 pl_dd_Smed_v4_3862_0_1;sc_Smp_073270 0.0 \n", + "3 pl_dd_Smed_v4_4222_0_1;sc_Smp_175900 0.0 \n", + "4 pl_dd_Smed_v4_13082_0_1;sc_Smp_157240 0.001536 \n", + "\n", + " pl_Neural: 9;sc_Neural_pval2 pl_Pharynx: 27;sc_Flame cells \\\n", + "0 0.0 pl_dd_Smed_v4_1404_0_1;sc_Smp_147890 \n", + "1 0.0 pl_dd_Smed_v4_3116_0_1;sc_Smp_152990 \n", + "2 0.0 pl_dd_Smed_v4_2745_0_1;sc_Smp_344500 \n", + "3 0.0 pl_dd_Smed_v4_3482_0_1;sc_Smp_078230 \n", + "4 0.0 pl_dd_Smed_v4_3482_0_1;sc_Smp_141230 \n", + "\n", + " pl_Pharynx: 27;sc_Flame cells_pval1 pl_Pharynx: 27;sc_Flame cells_pval2 \n", + "0 0.000006 0.0 \n", + "1 0.000564 0.0 \n", + "2 0.0 0.0 \n", + "3 0.000427 0.0 \n", + "4 0.000427 0.000005 \n", + "\n", + "[5 rows x 348 columns]" ] }, - "execution_count": 25, + "execution_count": 24, "metadata": {}, "output_type": "execute_result" } @@ -8035,24 +5909,25 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n" + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n" ] } ], @@ -8062,7 +5937,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 26, "metadata": {}, "outputs": [ { @@ -8089,13 +5964,13 @@ " hy_enEp_SC1;sc_Muscle\n", " hy_enEp_SC1;sc_Muscle_pval1\n", " hy_enEp_SC1;sc_Muscle_pval2\n", + " hy_enEp_SC2;sc_Muscle\n", + " hy_enEp_SC2;sc_Muscle_pval1\n", + " hy_enEp_SC2;sc_Muscle_pval2\n", " hy_enEp_foot;sc_Muscle\n", " hy_enEp_foot;sc_Muscle_pval1\n", " hy_enEp_foot;sc_Muscle_pval2\n", " hy_enEp_head;sc_Muscle\n", - " hy_enEp_head;sc_Muscle_pval1\n", - " hy_enEp_head;sc_Muscle_pval2\n", - " hy_enEp_nem1(pd);sc_Muscle\n", " ...\n", " pl_Muscle: 13;sc_Muscle_pval2\n", " pl_Muscle: 14;sc_Muscle\n", @@ -8115,16 +5990,16 @@ " hy_t15544aep;sc_Smp_126480\n", " 0.0\n", " 0.0\n", - " hy_t25002aep;sc_Smp_126240\n", + " hy_t15544aep;sc_Smp_126480\n", " 0.0\n", " 0.0\n", - " hy_t14481aep;sc_Smp_344820\n", + " hy_t25002aep;sc_Smp_126240\n", " 0.0\n", " 0.0\n", - " hy_t15527aep;sc_Smp_345440\n", + " hy_t14481aep;sc_Smp_344820\n", " ...\n", " 0.0\n", - " pl_dd_Smed_v4_649_0_1;sc_Smp_170340\n", + " pl_dd_Smed_v4_649_0_1;sc_Smp_164590\n", " 0.0\n", " 0.0\n", " pl_dd_Smed_v4_9529_0_1;sc_Smp_136710\n", @@ -8139,22 +6014,22 @@ " hy_t4961aep;sc_Smp_126480\n", " 0.0\n", " 0.0\n", + " hy_t4961aep;sc_Smp_126480\n", + " 0.0\n", + " 0.0\n", " hy_t30505aep;sc_Smp_087250\n", " 0.000001\n", " 0.0\n", " hy_t14481aep;sc_Smp_345440\n", - " 0.0\n", - " 0.0\n", - " hy_t15544aep;sc_Smp_126480\n", " ...\n", " 0.0\n", - " pl_dd_Smed_v4_649_0_1;sc_Smp_164590\n", + " pl_dd_Smed_v4_649_0_1;sc_Smp_170340\n", " 0.0\n", " 0.0\n", " pl_dd_Smed_v4_2337_0_1;sc_Smp_170340\n", " 0.0\n", " 0.0\n", - " pl_dd_Smed_v4_2337_0_1;sc_Smp_164590\n", + " pl_dd_Smed_v4_2337_0_1;sc_Smp_135560\n", " 0.0\n", " 0.0\n", " \n", @@ -8163,13 +6038,13 @@ " hy_t15544aep;sc_Smp_086330\n", " 0.0\n", " 0.0\n", - " hy_t7296aep;sc_Smp_170340\n", + " hy_t33559aep;sc_Smp_126480\n", " 0.0\n", " 0.0\n", - " hy_t28874aep;sc_Smp_156540\n", - " 0.000032\n", + " hy_t7296aep;sc_Smp_123830\n", " 0.0\n", - " hy_t14481aep;sc_Smp_344820\n", + " 0.0\n", + " hy_t28874aep;sc_Smp_156540\n", " ...\n", " 0.0\n", " pl_dd_Smed_v4_649_0_1;sc_Smp_135560\n", @@ -8178,22 +6053,22 @@ " pl_dd_Smed_v4_2337_0_1;sc_Smp_213910\n", " 0.0\n", " 0.0\n", - " pl_dd_Smed_v4_2337_0_1;sc_Smp_135560\n", + " pl_dd_Smed_v4_2337_0_1;sc_Smp_164590\n", " 0.0\n", " 0.0\n", " \n", " \n", " 3\n", - " hy_t13996aep;sc_Smp_345440\n", + " hy_t4961aep;sc_Smp_086330\n", " 0.0\n", " 0.0\n", - " hy_t7296aep;sc_Smp_123830\n", + " hy_t15544aep;sc_Smp_086330\n", " 0.0\n", " 0.0\n", - " hy_t17889aep;sc_Smp_170340\n", + " hy_t7296aep;sc_Smp_170340\n", " 0.0\n", " 0.0\n", - " hy_t4961aep;sc_Smp_126480\n", + " hy_t14194aep;sc_Smp_156540\n", " ...\n", " 0.0\n", " pl_dd_Smed_v4_649_0_1;sc_Smp_123830\n", @@ -8208,6 +6083,9 @@ " \n", " \n", " 4\n", + " hy_t15544aep;sc_Smp_078690\n", + " 0.0\n", + " 0.0\n", " hy_t4961aep;sc_Smp_086330\n", " 0.0\n", " 0.0\n", @@ -8215,15 +6093,12 @@ " 0.0\n", " 0.0\n", " hy_t17889aep;sc_Smp_135560\n", - " 0.0\n", - " 0.0\n", - " hy_t7296aep;sc_Smp_213910\n", " ...\n", " 0.0\n", " pl_dd_Smed_v4_649_0_1;sc_Smp_196840\n", " 0.0\n", " 0.0\n", - " pl_dd_Smed_v4_1512_0_1;sc_Smp_078690\n", + " pl_dd_Smed_v4_2337_0_1;sc_Smp_164590\n", " 0.0\n", " 0.0\n", " pl_dd_Smed_v4_2337_0_1;sc_Smp_123830\n", @@ -8232,7 +6107,7 @@ " \n", " \n", "\n", - "

5 rows × 33 columns

\n", + "

5 rows × 36 columns

\n", "" ], "text/plain": [ @@ -8240,40 +6115,40 @@ "0 hy_t15544aep;sc_Smp_126480 0.0 \n", "1 hy_t4961aep;sc_Smp_126480 0.0 \n", "2 hy_t15544aep;sc_Smp_086330 0.0 \n", - "3 hy_t13996aep;sc_Smp_345440 0.0 \n", - "4 hy_t4961aep;sc_Smp_086330 0.0 \n", - "\n", - " hy_enEp_SC1;sc_Muscle_pval2 hy_enEp_foot;sc_Muscle \\\n", - "0 0.0 hy_t25002aep;sc_Smp_126240 \n", - "1 0.0 hy_t30505aep;sc_Smp_087250 \n", - "2 0.0 hy_t7296aep;sc_Smp_170340 \n", - "3 0.0 hy_t7296aep;sc_Smp_123830 \n", - "4 0.0 hy_t7296aep;sc_Smp_135560 \n", - "\n", - " hy_enEp_foot;sc_Muscle_pval1 hy_enEp_foot;sc_Muscle_pval2 \\\n", - "0 0.0 0.0 \n", - "1 0.000001 0.0 \n", - "2 0.0 0.0 \n", - "3 0.0 0.0 \n", - "4 0.0 0.0 \n", - "\n", - " hy_enEp_head;sc_Muscle hy_enEp_head;sc_Muscle_pval1 \\\n", - "0 hy_t14481aep;sc_Smp_344820 0.0 \n", - "1 hy_t14481aep;sc_Smp_345440 0.0 \n", - "2 hy_t28874aep;sc_Smp_156540 0.000032 \n", - "3 hy_t17889aep;sc_Smp_170340 0.0 \n", - "4 hy_t17889aep;sc_Smp_135560 0.0 \n", - "\n", - " hy_enEp_head;sc_Muscle_pval2 hy_enEp_nem1(pd);sc_Muscle ... \\\n", - "0 0.0 hy_t15527aep;sc_Smp_345440 ... \n", - "1 0.0 hy_t15544aep;sc_Smp_126480 ... \n", - "2 0.0 hy_t14481aep;sc_Smp_344820 ... \n", - "3 0.0 hy_t4961aep;sc_Smp_126480 ... \n", - "4 0.0 hy_t7296aep;sc_Smp_213910 ... \n", + "3 hy_t4961aep;sc_Smp_086330 0.0 \n", + "4 hy_t15544aep;sc_Smp_078690 0.0 \n", + "\n", + " hy_enEp_SC1;sc_Muscle_pval2 hy_enEp_SC2;sc_Muscle \\\n", + "0 0.0 hy_t15544aep;sc_Smp_126480 \n", + "1 0.0 hy_t4961aep;sc_Smp_126480 \n", + "2 0.0 hy_t33559aep;sc_Smp_126480 \n", + "3 0.0 hy_t15544aep;sc_Smp_086330 \n", + "4 0.0 hy_t4961aep;sc_Smp_086330 \n", + "\n", + " hy_enEp_SC2;sc_Muscle_pval1 hy_enEp_SC2;sc_Muscle_pval2 \\\n", + "0 0.0 0.0 \n", + "1 0.0 0.0 \n", + "2 0.0 0.0 \n", + "3 0.0 0.0 \n", + "4 0.0 0.0 \n", + "\n", + " hy_enEp_foot;sc_Muscle hy_enEp_foot;sc_Muscle_pval1 \\\n", + "0 hy_t25002aep;sc_Smp_126240 0.0 \n", + "1 hy_t30505aep;sc_Smp_087250 0.000001 \n", + "2 hy_t7296aep;sc_Smp_123830 0.0 \n", + "3 hy_t7296aep;sc_Smp_170340 0.0 \n", + "4 hy_t7296aep;sc_Smp_135560 0.0 \n", + "\n", + " hy_enEp_foot;sc_Muscle_pval2 hy_enEp_head;sc_Muscle ... \\\n", + "0 0.0 hy_t14481aep;sc_Smp_344820 ... \n", + "1 0.0 hy_t14481aep;sc_Smp_345440 ... \n", + "2 0.0 hy_t28874aep;sc_Smp_156540 ... \n", + "3 0.0 hy_t14194aep;sc_Smp_156540 ... \n", + "4 0.0 hy_t17889aep;sc_Smp_135560 ... \n", "\n", " pl_Muscle: 13;sc_Muscle_pval2 pl_Muscle: 14;sc_Muscle \\\n", - "0 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_170340 \n", - "1 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_164590 \n", + "0 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_164590 \n", + "1 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_170340 \n", "2 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_135560 \n", "3 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_123830 \n", "4 0.0 pl_dd_Smed_v4_649_0_1;sc_Smp_196840 \n", @@ -8290,12 +6165,12 @@ "1 pl_dd_Smed_v4_2337_0_1;sc_Smp_170340 0.0 \n", "2 pl_dd_Smed_v4_2337_0_1;sc_Smp_213910 0.0 \n", "3 pl_dd_Smed_v4_2337_0_1;sc_Smp_213900 0.0 \n", - "4 pl_dd_Smed_v4_1512_0_1;sc_Smp_078690 0.0 \n", + "4 pl_dd_Smed_v4_2337_0_1;sc_Smp_164590 0.0 \n", "\n", " pl_Muscle: 16;sc_Muscle_pval2 pl_Muscle: 7;sc_Muscle \\\n", "0 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_170340 \n", - "1 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_164590 \n", - "2 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_135560 \n", + "1 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_135560 \n", + "2 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_164590 \n", "3 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_213910 \n", "4 0.0 pl_dd_Smed_v4_2337_0_1;sc_Smp_123830 \n", "\n", @@ -8306,10 +6181,10 @@ "3 0.0 0.0 \n", "4 0.0 0.0 \n", "\n", - "[5 rows x 33 columns]" + "[5 rows x 36 columns]" ] }, - "execution_count": 27, + "execution_count": 26, "metadata": {}, "output_type": "execute_result" } @@ -8341,30 +6216,32 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 27, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "/Users/atarashansky/miniconda/envs/scdp2/lib/python3.9/site-packages/samalg/__init__.py:694: UserWarning: No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", - " cax = axes.scatter(\n" + "/Users/alect/Desktop/sam-algorithm/src/samalg/sam.py:737: UserWarning:\n", + "\n", + "No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", + "\n" ] }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 28, + "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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GqQaDwbjYDGNhMb37Rj8n494yxhiPVHvPDObeczkHAAXmAvT09OKerfdAEASYOA6iKKK2tm5Ug17JNUMQBEGMOKfrftC7O/SunGAwmLLWiPpvtQaImsarLuCqe0fvoikrK4tzw6h1SJIJKP08gNTuqVTuKPWa03Hd6PfCyfb64XAFkWuGIAiCGHFyeatOFqeR7RhGd4feOqLfKVdtr55vbm5GdXU1ioqKAMTcNup1quhwOp1amq5aH0RNDwYQF9ya6p6ARPeU/nwyEaLWQdFXgU2F/tmpY6h74hjThNNdn+rnkYYsIgRBEEROpHqjz3WXWL0lIlU10lRjqKSzMCSzgqg74aoLtTHQVd+fcSddFdUqYtxVN9X46c4lEyvZBsKq7i01EFcNslX7GU3IIkIQBEFkZDBxAaniEJLFgWQaR7VE6PdTSVWBVB8Poo5htByofejjNVTU2BG1SqpxodYHnqrf9ZYQ1WKhHlcXf+O9qZYJvYvGeF6fbqzvVx031cKdrL/y8nLtnlSXzGiLkFwhIUIQBDEJ0QsK/QKeiWTBqPpzyfpOt6GdfqO6ZLvq6hdrvSVBL2KMQaDJBA5wSmyo/evbpdpcTl3Y1YBXFWPNECC+gmqyoFT1vDoPdfxsnnEyAagWWEvmJhpPkBAhCIKYhKiLHZB7NkemN27jQmqsDJoqdkKN0UjmpjGmyqrt9RkxeteKalUIBoPafCwWS4LY0VdSBVJbcvRWGL2FxjgftcS7unOvvi+1JLze4mHcMdg4nv5n4z48KqkKrY0XSIgQBEFMYtQFLtWCaCQXd45+wTQKn1T9GEWIfn7J5qB3RRgXaaNVJNWmdyr6gNFULiggviy8cU7z5s3TsmvUVGD1nH4/nEzPMZV1Rv2u3oPa33gVIQAANoYRRZEBYKIojvZUCIIgxiU8z6c8fvvtt6c8P5hr1OP6dvpj6eaUqc9c5qA/r/+ebA7qcfWrtbWV3X777ay1tTXlPJP1pV6jH1vtI9mc1J+N1wzmHsciuazfJEQIgiAmIMkWQCOtra0pr03Xb7I2qQRAsnPJ+kp1Pt11yX42ioRUc7v99tvZhx9+mCAg1HNGIaWSSjiozzKVeDE+a/1YyX4PmUTGWBYhjOW2fpNrhiAIYoKhd0+kcgWosRLG4+lcEkC8+8PoItG7dvSuAvWcGlRpDGJNFQCbKmgzVRCnMXZCnZ/qytDPTZ/yanRxqPEiRheMPs7DOL76LI3P2nhefw/J3E76e0/HuHbFGCAhQhAEMcHQL+DJhIO6oCYLAFXFQnt7e1b9G4+nQq29oRYVA5BSuCQLElWPp8vA0cehGNNk9QXQBEGIEyHGcVRhYoybUfs31hUBELePTbIS78ZAU/35yQ4VNCMIgpgEJLMkpFoEX3/9dezduzejNSKX8YBTZdnT9aMu1KkCZ/WBp/q0X325d71VRN8GOFUZNVkZ9GyfkXGOxnbNzc0pC51l6neiCBMqaEYQBEHEka31QhAEbZ+VVNaITKRqm03Vz1TWFv15fRu9tcOIvm6IWitk1apVce4VvZXIaDVKVWo9nRvK4/GgqakpqxLtenJ5vhMNsogQBEEQcQzFG3uqWI5UVoShmq8gxG98p4oQI6pVJFnJeJXm5mY0NTVlLLWeyvJzOvcx3iGLCEEQBDFo0lkjBtuH0YqRzdt/uvP6OBG1T31gqNpG3RMGiIkP9UvdHE9f28TYvxpHkkqUZbL85EouIm8iQUKEIAiCOG2yWRyNQZ/pFt50YkU9Z8yWyVTqPBQKoaGhIU4oGF09+uOpMlr0cSjZlGIfSiaiC4eECEEQBHFaDGZxNC7exn9nI1b0e7aoJdyB2EZw6nF1PxY1XVc9l+5eks0x2/vIZt6nw3D3PxqQECEIgpiAjOQb8+ksjnoRYxQ0qsvF2N4oPNRjeuGhXqem4K5YsSLhXLLA1GwEVbL71c99uEWCsX9ZlhCJhjGGQz7TQkKEIAhigjHS5vvTWXz1i7pxgU+VyaL+XF1drdUlUY8Z4zP0czNujGcsqJbtfjvqvFPdx0gTkSLwBXyIytERH3sooKwZgiCICchIZWAYs2FOp59UQaHJ3DhqgTQACZvY6QVYppokE8HF4fP7UOOuhquyCnabfbSnA4CyZgiCICY9I7XADoUlIFcLjpoZU15enjKgNJvgVeOcRyMAdCjGLHGUYJPrljEjQnKFhAhBEARxWmQSIYOJuVCvMwoUVVx89rOfRVNTU9JxBuNqGUl3VipX0+kwni07wypE2tvb8f3vfx8OhwNTp07FueeeizfffHM4hyQIgpg0MMYQiYbh9XWP9lRSku1im2whTSZQysrKsGrVKuzbty/tOPpU4WwYqRiPZLEp41lEDAXDFiPC8zwuvPBCfO5zn8NNN92E0tJSHDp0CEuXLsXSpUuz6oNiRAiCIFKjKAq8AS/qautQVVkFm8022lNKSrI4j3Q/Z+qruro66X4x4yXmY7zM83TIZf0eNiHy05/+FC+99BJefPHFQfdBQoQgCCI9siJDFMWs4wNGexE0BrcOJtg128DWsc54m28ujIlg1T//+c+45JJLcO2112LmzJm48MILce+996a9JhwOIxgMxn0RBEEQqTGbzDmJkNGuyml0R+h/TlYzJFUfRsbCveXCeJvvcDJsQuTo0aPYunUrzjzzTDz99NO46aabUFFRgcbGxpTX/O53v0NxcbH2tWDBguGaHkEQxIQmKkXR5e2ErMjasbESk5CsBkemmiHZ9DmYe0u3S+5wMlZ+F2OBYRMiiqLgoosuwm9/+1tceOGF+OEPf4gbbrgBd911V8prfvazn0EURe2rra1tuKZHEAQxoeGFAOrq6sDzfNzxsbrwDWZhNoqUdNcmEzTqzryjKUaIYRQic+bMwfLly+OOnXPOOWl/4YWFhbBYLHFfBEEQRO6UOmaisqISJY6S0Z5K1ugXZuvJcu2pFutcLCap2paVlSUUQyNGnmETIp/61Kfw8ccfxx07ePAgFi5cOFxDEgQxzEhyFF5fNxRFGe2pEBngOA4O+/gRIUYEQUBDQ0PaOJFcyrEb26ovxSRCRp9hEyJVVVV49dVX8dvf/haHDx/G7t27cc8992D9+vXDNSRBEMMMLwiora0FL/CZGxOEjogUyaneSTZCY7CuDdUl09zcPKjriaFl2ITIJz7xCezZswcPPPAAVq5ciV//+tfYsmULvve97w3XkARBDDMl9hJUVrrgsDtGeyrEKDDYDA9FUcDzAbhr3QkxK+n6HKoYCqNrpqysDOXl5XE78RKjB216RxAEQWTkdOt9yLIEQRTi3EVDtWFernNJd4wYGsZEQbOhgIQIMVlgjIHjuBEdkz6EiVxR/2Yy/e2oVoZsRMZI/x3S3/3IMCYKmhEEkR0RKYJuX1dcvYfhJlUWAZmpxza5/n6G+veZrN6HcTz1PICsLB3DKQr0cxQEAR6Ph4qIjUFIiBDECDEQ6Ud7Z1uC4BAFAXV1dRBOBoAO5YdkLhkHVOlxbJPr72ekf5/qePqK2GOhlLxeHDU0NKC8vJwsImMMcs0QxCBhjEGSJQSDYlZpkq0nWnDPPXejYn0lZpXOjuuny9cJxhgK8gpR664dEp95Ov97KvM0ma1zZySfWa5jnc7c0l2b6e9nrPwd6UVYe3s7mpqaAGRnqSFOD3LNEEQKstHd2b5ByrIEn78bd1bfiWMtxzLW1phdOgc3/egmlDpmxo3FcRwYY6ivr4fCFFRWVuY8L8ZYLD3S79WOpUp/TPembLVaISty3L2QhSQ1Y92KdDoiJN19pepXv3/MSJDNc6+urkZ1dbUmQlatWkUiZIxBQoSYNMiKjL5wLzq6T6Rsk+3CIslR+Hg/iizFuO6663B/wx/hC3jR2d0Jf8CntdMLHw5AvrkACpPjxvJ4PJhZMgvrb14PDhwkOYo7t9wRl+bo9Xtxx513IMAHUs5JFATUut0QBAGyIoMxlvQDN119BkVRwJiijTOcCy1jDD0DobS/j7HOYPcLGczzHEnRczr7oIy0KyjdeOp9qF/l5eXYu3fvmBWOkxUSIsSkgDGGgWg/jrUeRX19fdaxE4qiJA0i5QUB9XX16O/txxmLz0BlhQsKU1BXV4vqmhrwPI+oFMGhIx9DkiUAQDAYQl1dPUQxqI3ldDrR0NCAUDAEszkPbrcbvMCDgWmCRVZkKEyBAhkB3g/5ZH96RFFEiaMUrsoqTJs+FV3eTvj8voR2meA4DqIootZdq5nXh8uMLckSfAEfausTa0uMJwYjQgYjKIbzd5FqvFwZi2LJarVqXytWrCC3zBiEYkSISYGsyOj2daG+rh7rnD/AokWL0rZXBYisyPAHfGCKDM6ch5mOmTCbzDCZTAjwAdisNkiypB1TrSEOewkOHj2IHY3bsWaNE0sXLwWQvpaBoigQRAHFxcXw+b2w2+zIzysAENtJtaX1GHbs2InKisq4gmIBPoDq6mo4nU4sWrgIJ7raUV9fBzPyUFW1KW48RVHg8bSisXF72g/kbHz8QxEH0B/pQzAYwqySWafVz3hjKJ7dWInDMDJW50WMLFRHhCCSIMlRiGJiYKksS/DxfjisduTl5WvWE0EUAQWoq6+FDBkMwHe+/S1MKZiGs5YuA8dxiEpRSEo06WLKGMORo4exaOEi5OXlx43HCzysVitEMZi0SmkkGtaKP5lNZu34sZZjKCsrizsWlaJo9bRge+MOrF59PebMm4O2tuModZTCxJniFgWf3we32421zrUp933KVoSMVCEqIhF6/sRYh4JVCSIJeeb8pNktXb5OVLvvxJGWI5CkKGRFQoAPoK62FoUFhbjFdStuqbgVa76/Gg8/1IQdO3ZqG2aZTeaYy8VdlxC/IYoi5i+Yjw7vCXR2d4AxBkVR0OppRU2NG62traipqUlqxg6FelBXW4+geCoVUhAENGxrwLGWo5q7SBAE5JnzsLBsEa5fcz22b9+O48ePY/fO3egJ9SSYyU0mE8AAi8WSdNxsTesj7SaY7Bh/H/T8iYkECRFiUqGKAf3PM4pmYNXXVqFxxzYcbT0GBkBhDBw4mDgTbDYbShwlOPvMc3DD2h8ij8tDcXExgNjCPqtkFjZu3ABJjsYJhOrqarQdP46777oHdXV1CPB+tHha0LhtO9Y6nbBabUkXE1mWoDAFrkoXbDZb3Lk1q1dj+/YdCIpBbQxRFJGfl4+li5bCucaJM5echSpXFcrKyhL6Ly4uxoaN68ELgaSCQ7/AqfUXcs2cILInm12MU4nD0Xz++rnkGg9CgaKEERIixKQiHB1Al68TsixBkiWIfTxa2zx48om9uPzyy7Fj+3bwPI98cx4AwBfwgjEGxhhkWULZgjK4XC4tpiMqReEP+AGOQ21tHQRB0LJVnE4nzlxyJlwVVahybQLAoXFbI9Y414ABqKmugSiKcf0H+AACAo9atxuiKGjzVhcju82BTa5NsNlscaJBVmQIgoDGxu0QRTFlGiWHWBn5xsbtcDqdKbNq1PHUL9UCRAyOZItvX7gXrR3H0B/pS3vtWLN+6IVRrsGpYz3dmRgl2BhGFEUGgImiONpTISYA4WiYtXV42C83/4L5/F4m9ArslXdfYj+57Vb29xdfYL+47efsrXfeYp3eThaOhNn+Q/vZL2/7BfP5fSwajbDegRDr6DrBZFlm4WiYdXSfYMc729gvb/sl8/m97PDRw6w/0s+6vJ0sEAiw22+/nfE8zxhjcd+9Pi+7bfNt7J1332a3bb6NdXm7WESKsG5fN7tt820sEAiwY8eOxl3PGGOBQCDpfUmyxMLRMOv2dce1T0c27XieZzzPs9bW1oS5jGXG2jx5nk/6/I53trGfbf4pO9HVPjoTOw3095Lr8x5rvx9ieMhl/SaLCDEpiETDON7pgaRI2LBhIxz2EoT7BvDYo4/BDDPOWbY8lk2zcBHqa+sREAKYMWM6vvu978JabIXEJAiCgPq6OvACD1EQ4K6thTfQje987z+gKAoaGxvR6mlFbW0dAMS5ONS3QKvVCrvNjoqKjTh35XnYsHE9ii0WBAJ+2E+6amw2GxYtWqxdrygKJCmK6TOmJU3JNXEmiKKIOndd1s8jm7drNeUxmYtnrDLab9y5jDt35jxUbdyEOTPnjvjYp4v+byHXv4vx8HdEjCyUNUNMWCJSBILAo9QxEx3dJ1BTXwMTTLil8lYtU0UQBIQj/VDAUGIvQX5eAbx+L3g+gMYdjeAA3HzTTTCb8wFw2Fq3FWvWrMaCBWX4+OB+3P9gA/Jgxi0VPwYHDjarDbwQgMNeErebboAPwFpsjQWL6mCMwef3ora2DlWuqrgPaUmOwu/3o9hajAAfQCjUg907dye0U1EXoqH8oE+XQTNW0zRHa17pMllymVMubWMZWALMJjNqampGVTCO1b8HYnSgrBli0qEoSkLgHy/wqK2NWTDMJjPykIcb1twQly5rtVoRkaOoqatBl68TXl83AGDnzl1Yc/0a/OimmxHq6UVdbR1MnAnXXfd93NfwRxxtOYoimwUMChQo+Gh/M2xWK8ABxcXWWNyIjqKiIrS0JpaB5zgOeeZ8VFRs1AJgtfnzPNx1tXj/gw+wtb4eu3bsxFrnWlgslqRFzQAMqTUgnXVhtC0P6RitxTBdLEcuIiSX58oLAtxuN4B4C1yqvoeLsfz3QIx9yCJCjHsYYxiI9EMQBcwqma1ZHRRFAS/wcNgdiETD8AZ8KDDno7Rk5snsGRkmkxldvk64a924/rrrT1ocNkGWZRROK0DzR834y5//in//xtcxY8Z0zJs/Dx/tP4DH//woVq36Gp7Y+wRMMIMDh3XXO7F0yZnw+r2oc9ehqqoKQCxT5eixI2hs3I7y8nKULSjTFiZBEHDnljtx/errsahsIcwng2TV+zp67Ai2b9+O61evhrW4GA57iWbpMdYYUfub7BaR02W07yvX8Xme17KrUlll0llrhorRfm7E2IIKmhGTCnZy99r6unpUVcYySqJSFDwfgKXYAjEYRIm9BL6AD/W19ahyVWH6jOnw836U2B3IM+dDEARYLBYEg8FYFoos4eDRQ9i1cwdWfeVrePKpJ8DA8LWvfw1//csTkBGFAgX5KIAJJlz5hSvx3PPPoXKjC3abDZ62NtitdlRXV2PDxvVQGEP78Xbs2bMHHDgt8wYAWlqOoWHbNlRWVsJuswOIfagXFxeDMabNScUf8KGmxp00vXcsMR4XppFYsIcLRVGgMBk9od6Urrvxdk/E+IWECDHpYIxBEARtYe72daHWXYvvXf897NqxC1WVsVLnoiiiyFIEn98Ld60ba1avwRlLztT6UX3uDrsDsiLh+PF2lC0oA8/zaOv0oDfagxNt7ZiSNxUvv/oK8pCHr3x5FZ54+q/4t3/7N9iKrZhZMgvumlq4XK5Yn4qM6upqfPPqb+KxR/fg2vJv4dxzz9UWBkmOoq3tOBYvWqxZcWrdtfjR+h8BjKHEUTrslo/Bkmoe43lBHyvPNlf4Hj94gcf82WUoOLk1AEGMFhQjQkw6OI6Lsw6U2EvhclXhzMVnwVVZBZvNBo7jUGQpQiQahqREsWa1Ezu279T82oqioMvXiS01WxDgA8gz52PRwkUwmUwoKp4BhUlo2vMwXnvzDbz26hv4xle/CecaJ55++mlce9W1eOKvT+CBXQ+it6dPs3hYLBYwpsS23gUDx5kwb/48CIKALVti4/A8j23bGiAIAhQW2zW3oqICHIC6ujqIophwv/qFMrZj7qn3iZHy06eLC8i29oVx7mOB8ShCgNimivfdd1/SvxeCGMuQECEmJCaTCXabXfuuwoGDIAq4e+u9sNvscRkoHMfBZMrTKqrqF1gOHJQow1QU4fyzLoAZZiw7axmmF80Ax3FYWLYIP676CX6w7gaUlZVpRcYkOQpJlnD99dfjsUcfjxURK7Zi2vSp+NHNN0KWpZPpvJUnLTZB1LprwXEcZpbMQmWFC4wlLtZ68aQwWQuOHcmgwUxiI9OCzhiLmzuRO/rfc9mchbi18icodZSO3oQIYjAMcQ2TIYUKmhHDhb6okqIocf8OBAJJi1DJsszee/895vV5mc/vY5IUZd2+bub1eZOOIcsy6+g+wX51269YIBDQCpJFpQjr7O5g7Z3H2a82/yqhwBPP80ySJSbLMvP5Y8XP/AF/3Hl1boqiMJ/fyzZv3pxQPG08oN7feJrzWCFVoTSCGAvksn5TjAgx4VAUBZIiIRQMJd3ZVo8sS5CZglAwmLAhXrJYgQAf26PFVemCwhStdoNqdWGMQZIlmE1mcByHIy1HsKNxB1avWY358+aBFwT09vaicVsjKioqtL1sjPOXFRltbR4sXrQE/oBfs+6oeDwelJWVpZ2rkXTxHPrjsiyB40wJNU+Gi/EakzEWGM2aKfQ7I9JBMSLEpEZhMniBR01NcheFvpaHwhQEAn7U1LgT2ib7oFXdOTabDQ67A1WuqjjXjyRLkBUJ/oAPsixh+vRp+ObV38SiskXgBQF1tbXYvm071q1dB4fdEVf0TIXjOBw/fhzbG3egra0NxcXF8PN+bd6CIKChoSFuvulSbBVFgdfXjTu33Jlwj0ZXjqzIkBUZ/kBiBdfhgha01GRysY1m4TaqGUIMFSREiAmH2ZQHh82OykpXwge1LEuIyhF4/d7Yzyd3y62oqMj6Q11feMxqtWpWkAAfgNlkRigYQl1tPTxtHmyt24o9f9qDYDCImSUz4XJVweVyoaysLO4DXZaluMXfWmzF2rVrUVZWhmBQRK27FrzAazvzVlZWgjEGf8CfMtjT5/fhzi13ghcCYEjeRo3zKLIUQVGUWLn4YFDbwE8PO7k5HzEyjNUFP9tAZILIFhIixLggbqfbDKjVSvWWCj0BPgD3SQtIKNSD+vqtMHGZ/yswxhCRIohKEXh9XsiypB07dPQg7txyB4LBIEpLZsLlcmHxoiWorKzUMmg4joPdZtc+wNUPdMYYeEFATY0bAT4Af8CPLdVbNHOmw16iffDzgoCa6hoEg0Fsqd6CmpoaBPhA0rmq4oMxwGKxYM3q1UkXD7VSqy8QE2eljtKEMvKx+wyj29dFYmSEGMsL/licEzF+ISFCjAsYGARRQE1NzWm9IXKcCXarHdevvh5WqxUl9hK4Kl1JXSRG1IXYF/Ch2l2NIy1HICsSgmIQu3buBqcTM6rwcNhLYLfZ0865uroaHMfFCpRZbQiGgnHnFUWBxVIEQeBht9nhcrkwb95crFmzBhUVFQmCS5Jjgk29N5vVimAwiG2NjXHzUP/NcRzEYBB1tfVa6qdxoeE4DoIooq4u0VJCDB+04BOTARIixLjAbDLDYXNob+qSHEWXrysubsKIoigIRwY0NwwQW1CDoRB2bN8Rc4koEgQxVtMj0wIriiLuvuse5Oflw7nGiR07dsIX8INBwS2uW7DJtSltca9k/VssFqzfuB4KU2Cz2SCKInY07sC6tevi+grwPGqq3QgGg7BYLAgIPLZt26YFxervmed5uN01WoE3jjPBYrHgutXXaX3q58RxXFIriJGZjpla5VrGGGRFTmkdIbFCEES2kBAhxg0mk0lbKP18AHW1tQjwgZQLvcIU+Hk/3LqgVeOiK4pBNG5rjNX3yPD2ObNkFjZVbkKpYybsVjtcFZWQpAiq3dVQmJy2nobexM4Yg6IoiEiR2H1xHOrcMUtDMBizhoRCIe16Bgab1YbrVl8XK5B20jqULOzDZDLBbneg0lD+vb39BHY0bteeg9Vqxc0bbkZECmtiLtX8ZVmCoihxReNkRToZ15LoKhursQ0qY3VeBDFZISFCjEtK7aWo2FgJh90Bq9WKH938I3T7u+IyYkycCXnmfHAwJ1yvLrpq5svChQsBZF6kbDZbrCpq9RbwgoDpRdPx3e9+F8XF1rTXqeNFpAiOd7Yh1B+EP+CDpEhw2Eu0OJKysjKUl5ejqalJmwtjDL6AF9sbG3Gs9RgCfAA7t+/AmjWrMaNoelyQq6zIJ4XDKWtFMBjEjsYdcDrXxosNxrTdiVORKouG40wQxVgQrZqZo443lmMbxrpIGiwT7X6IyQUJEWJcYjKZUOIoAcdxUBQFgshj+/Yd+PDDD+PazCyZiaqq9C6HZO6KdFitVjjXrMGO7dvh6/LjoQceRigYQlSKoqP7BCQ5Gtde774IBHzYelc9Ptr/EerrtiIUDMXNAQBWrFiBiooKTJ8xHV5/NyQ5Cg4cVq9eje2N22E2mVFRUYEFC8rQ7evGFt2cGVMQEHjcWXMn3nrvLSiKAqvVCpfLhYVlC2O7EPu6AQAljlK4Kl1pa62YVMGhy6IRBAFmk1kLyrVYLAhLA+jydcaJkbHIWBZJg2Wiiiti8kBChBj3mEwmLF28FOXXlGPPnj1xCyYQW3zUrJt0GR+5LFKLFi1GlWsTzlx6Fja5YnETvBBAff1W8LoFIWZNOFUDZFbpHDivX4un/vo0blh3Q0oRUFxcDEEU4K6pxfHjx1FbVweFKbj++uvAIRYEazabYeJM0IfZqqnLV33zm3hsz2Noa2sDABRZiiArMgRRQG1tLTwej5bFE5Wi6PZ1IyJFklg+OJSWzNRcWeqi5/F4tGfGcRyCYhD1dfXjYjGcSCIEOPV3SxDjFaqsSoxLMlUJ9Xg8aGho0IRFl68Loihg8cIlyM/LP+3xZVkCOC5uV1zGGAK8P65Cqz/gR01NDSoqKuJERzaVKRVFgSiKsNlsOHL0MLY1bju5D44ZLpcLM4qmg+dj1gmFKVr11dj+Mwraj7dj4cKFiEQj6PZ3Ic+ch1L7TBw/fhzbtm1DZWUliouL0e3rgrvWjdXXr8aOHTtTBt2qGJ+teu+iKE64RX4kMVbLzQVVIE40aw8xfsll/SYhQow70n3oMsbQ3NyMpqYmrSCYIAi4c8udYFCwds1aWK22uOvSiQJFURDgA3El1tUS8qIgoMRRCo7jtJTZPHN+gpWD5/mEMu76+cqKBLMpL2UKsSRHEQgEwJlMMHEmmE1mFBcXw+f3ora2FqtXr8G2xm1Ys3o1Fi1cjKgcgSCKmFUyCwDg9XWjxl0DDiZsqtqkWTasJ4uxDUT78dFHH+G8lechFOpJWX9Fz+ksmhMB499MNsIyHaq4czqdpyVGSIQQYwUq8U5MaFK5UGRZwnsfvIuHH3kY//qZT6OoqAiyLMFisaDKVYW1a9aiuNga5083uhqM8AIPt9utBXQyxiApEo61HkNtbZ1Wd8PPB1BbV5e0rHwqEQIAUSkCX8CH6Mm4ErVAmj7lWBBi9TtMnAkOu+Nk1o0Muy2WHbN40WKsWb0a2xt3QBRFiKKIel1MR3GxFatXr45Lz9U/uxPtHfjzY3/GifaOBBESlaJaTMmp+SSWmB8rjMScjDEZQxGjUVZWdloiBJh4LidiEnG6O+wNJ7T7LpELPr+P/eq2X7Fnn3ua3bb5NrZ582Ztd9yoFGV94T52+MihhB1LW1tb0+5iqt/5VlEU1uXtZL/a/CvW0tKiHZdlmXX7urUddrOfs5f9avOvmM/v0/rv9nax2wy78qpz4Hme3bb5Ntbl7WTdvu64vlpbW7V/q9fq+0s3N/21+nvtPHmvxmvH4o6vI7kbbbIdkwmCOAXtvktMWvQxIkVFRVCYDHdNLTZsXI+oHMXWurtgNpkT3j5TuRpkWUJA4FFiL9FcJ7EsHSErF0Yuc1bheT62w68rca8cIFaiXpYl1NXWa2307iqLxQKFxep+qKXr+ZNVWXNFrROSaRfjTPc0Uow198RYmw9BjBTkmiEmLeqHfllZGaxWK6xWGyorK2G3OZBvLoCJM6G8vDzOtZDO1dDa5tE2nFMxmUxDJkL0c1ax2WwpRQgQ2wFYTZ1V28womo6b198Eq9WKvkgvDhz+CL0Dvej2d2vZMbkiCAJq3bVxAbnG86mOj1Y66Vha9NM9B/0xSY65v8bwOyFBDCskRIgJi6LI8Pm9iMoRre6Iy+XCihUr4mJMksWcMMYgCAK2b9sOp9M5qIVcURT0R/rQ5etKeb4v3Iv+SH/CIqQVQIvG9rdJhn6+A5F+RKQwJDmK9uPteGD3g/j44wNxsSLJSHcuXTpzukV2uGt1jMXYlFwwPjt/wA93rTvp5oUEMRkg1wwxYQnwAdy55U5w4OByubIWE5IcBc/zsNsdCAVDg15QZUVGt68L9fVbcYvrloR+wtEB9Az0oKP9BJadcU5CWrGsyOjydqK+vh433XwT8sz5WiaMkS5fF2pra7Hp5F4wra2tWLhwYZxrwOgmSJaGmwuj4XYYb2mqmdLMgdjvmed5lDhK0rYjiPHEmHTN/Pd//3dsh1GXa6SGJCYh6lumumOt0+k86ZpJLkKSm81F1NbWnnZdDLPJfHKjuOSVXRXGcPDjj/HQAw+jvb096fUl9hLcfPPNkBUZ7tpTb9GyLCESDWuWlFkls3CL6xYtQ0ctWa8XIcZMDzVddLD3OBoL5HBbW4aaVPPUHzebzClFCFVMJSYDIyJE3njjDdx9990477zzRmI4YpKi/+BmLLYLbeO2Ri3GIdDjh1fsTNpeT4mjBK7KqowWlEwLRFSK4kjLEViT7EMTK1YmYO9fn8K3rv02Fi1clLSPgvxCzJk5F6WOUlRuOBUTEpbC8Aa8kGRJa5vL4qwu6Lmmi0alKHx+X+aGw8h4ESGny3gTXQQxWIZdiPT09OB73/se7r333rT1FAjidNF/cJtMZthtdrgqY4u3JEfR6j2CA56P0DMQSmhvJN3fqlrkzChijMLk0NGPsW17Aw4fO5xwPcdxcNgc2LihAueuPDftWAAwtWAaSktmasd7Q724a+vdcbv0piPZvWa7wOmtTAEhgBp3DXg+9UZ5xNBBIoSYDAy7EFm/fj2+9rWv4corr8zYNhwOIxgMxn0RRC6oH9wcx8FsztMEhdmUhzylAH/+018Q7gsntM8WxhgUJkNRFFRUVKR0fQCA3eqACSbYik+JGlmRT24Q1wWO41JWU1XHkuQovP7EjIrSkpm4xXVLTkG0g40DUe/LZDLBYbOjsqLitF4qyNVAEISeYRUiDz74IN5++2387ne/y6r97373OxQXF2tfCxYsGM7pEZMIjuNw7tIL8AvX5ri9YAbTjyiKcLvd4DgOsiyh29eNKdMKsWHjelhPlk1njGFW6WxUVd6C0pLSuD7Uyqeetja43e6kC7OiKJDkKERRRJ2ugquekXhbNlpSYiXss39+xnujuAeCIIwMW9ZMW1sbLrnkEjz77LNabMgVV1yBCy64AFu2bEl6TTgcRjh86m01GAxiwYIFlDVDjDiZshX8AR8Yi1ktatw1uPGmH8JsMmN26RxE5ai2Dw07WRI+35yvWT+YboO4VOOIfQJ4PoC5M+ehr7cfwNg000tyFNzJ/W+MpMpwGUuZIGNlLrIiA4zBbM4b7akQxJAwJrJm3nrrLXR3d+Oiiy5CXl4e8vLysG/fPtTU1CAvLw+yLCdcU1hYCIvFEvdFECNNNm/tiqLA7a6ByWSCq9KFfHM+7qq/G4IgQBAEuN2xrJuIFIbX343+cC+6fV1afIi+hkkyQsEQ7r33Xogn3ZNj0YogyxIkWYJPty+OnlQxOGNh4QdG1zqjH5Mxhv5wHz4+ciBujyGCmCwMm0UkFAqhtbU17pjT6cTZZ5+N//zP/8TKlSsz9kF1RIjRItObshqw6rA7NEuHek1UiqLV04rFCxchIPCocVfjuuuuw84du1BZUZG1a0Pd9Teb+QwXUSkKQeC1XYb1MMZO7gBcF7eh3nhiKJ4rO7kJIceZtB2aM42ptxQJgoAuXyd27NgBM/JQVTU+nyVB6Mll/R7RgmaZXDNGSIgQYwk19kNdbNRF2mEvQTAY1BYPf8CH6poaVGysgMPugC/gA1MUmExm2Gw2BPhA3N41Y5mO7hOor98KV0UlHPaSpAv3SIukseJOUZEV+WQ6tphQDyRTQTNVlFRUVEAMirAWW8fUvamMtWdOjH3GhGuGIMYj6qICJAZaSrIEf8CnnecFHrW1tWhra0N1dTX8AT/6I31QGENVZRUsxZZYiXkpCndtDUKhEAJ8AG63GwHen3T8seZ+KXWUomLDRk2EVFdXw+PxxLUZaREyFO6UoXzOJs6EYFBErbs2IZ07XRl8lcrKSthsNixauGhMLvYUYEwMNyMqRP7+979nbQ0hiJFGURQoigJfwAef34ctW7bEffj6eT+q3dXgBR6SHAXAUFFRgYULF2q73sbiQ2oAAKIgoLa2Dr29vQBMWnG1io0VsNsSd7Mdix/4eeZ8rX6J1WqF0+lMuUHgSDAURb70z1m9j3T1YDLBcRwc9pKEjQr1c03WpzqPsQ4VViOGG9prhiBOwhjD0ZajaNh2P75/3XUoMOdjyeKlYIwhIkVworMNoVAPShylMJvyUFdXFxfzwRiDrEgIBkOw2+xadozFYgEv8DCbzBk/zMeqCVw/r0zuBj1Gd9ZYQRAEBINBrcy9uucOEAsMdjqdOVedTTdWqv1xPB7PkI0znAT4AGYUTYcoBlHqKM18ATHpIdcMQQwCURSxo3EHrrrqKuzYsR2N2xohCAJ4gUe3txPu+9y4/6E/orr+ToR6QrE9ZIqt6PZ1QVZkcByHPHO+FmCqZsfE3pgdsFqtUBQlJlhkSXPx6BmrIkRvqVHvQz//ZNYcRVHw5pFX8Nw7T6I/0jfCs06Ofn4NDQ1YtWoVysrKtD13rFYrVq1aNaRWn2QWBUWJbUEwmtYlPcY56K1Fr7/+OrZsuRMvvfISqmuqcazl2MhPkJjQkBAhCMRSUV9vfRGX/9vFOG/lebj26m+B40wIBoOorq4GZzLhwnMvQj7M4GDCjsYd4DgOAYFHbW0dBCF5yXNZkU+m8HqhKAqicgSd3g5IigRfIDFVU1bkWE2JQTIci5pxIe0WOvHGx6+gtaNFEyPTpk/FD360Lm6xZUxBQPDj8b88Dn8geUzMSKEurKpYslqtKC8vx969e9Hc3KwJAo/Hg71796K8vHxIRaHePdPS2gJJkSAp0phweRhFZEtrC7Zs2YLq6mq8/vrrePLJJwFweOa5ZwAomkAniKGCXDMEAcDjO4Zd/7gPkUgEa6/YiPvu+iPWOtdi4cKFCPABROUo6mvr8a//+mksWbwE9pMWDsaYlsabDFmW4OP9qK+th6vShagcQa27FqvXrMH2xu1xaa9qNVVBFFDqmJlzVk06F8BgkOXYYlmQV6jNRZKjePfQ29j5wA5MwVTccMMPIfbFYmamFc7AorlLMGNKkdZH70AP/LwfZXMWjprbSX0ueheMKgyCwaD22aLObajdJeqiXV1djfLycjzyyCP45tXfxJ5H94yZtGf1d6PuoQQA69auQ1lZGZqbmzFt2lQEhAAee+wx3LDuh+PCnUSMLmM2fTdXSIgQI4UsS/jLa3/Cc888j//r+l8AiW6SwS6kiqJo6b2MMfACD7vNnrQ/n98Ht9s96AVqKBf7nv4gAgKPWSWzUJg/BbIioz/Sh/bONoDjYJ1mxzHvIex6aAfykI9Cbio23LgRbcEWdHV34QuXfBFT8qcjPy9/yEVSrujTZfVps0Zxku7awY6r3jcQ+5tShc5YjAdijOGDDz/Ao396FGvXro0THLIsQRDFlKKbIPSQECGIQTLci4MsS+AFATabDRw4rWgZY4pWEGusLFBd3k6469yoqqiCw14Cxhjau9pQs7Ua3/2P72HlWefhQGsz7m+8Dz+8bj1ml8yGxEXw19f24J8vvYjV3/gBFsxeiIVzFoHjuGG/r0z9G8/rLRWphMhQCKhsAn3HGuMliJYYu1CwKkEMkuFYJGRZQpevC7IsISDwcNfUICgGwQs83G43fAEvJEVCl68TPr8PxcXFQz6HwTCrdDY2bqjA9BnTAcSCb+fMnIfvf+c6PPzQIwgFQyieasNUFMFhtcNqtWJKwVTY8ktQBBvyWD7+eM8ftQ37hluEJEt91qfnGs+rwanpRIj1ZMry6cxdL0LGWnp2KkiEECMJWUQIYpjx+r1wu91Yv349bDYbjre1YcnipQBigYELyxbCd7INx8X2rrHZbKM865MupX4BohjEvFnzkGfO186pi7QaA1NqL4XJZDpZibUe11xdjgvOu2BELQBGywOAhFLq+u+Z+srWdZNs7OFw8xDEeIIsIgQxhiixl6CyohIzS2ZCFEU0Nm7XsjgatzVCFEWUlszEpqpb4Kp0obi4GLIsjfa0YTKZ0N87gPvuuQ+hYE/cOXUxNZvzUJhXqNUJmVkyCxUbK3H+uefHtRsJjJYHAHECQh8bkskqoVpKysrKkooQfXqrvs9M/acTKAQxWSGLCEGMMOnenlU3jslkRqm9ZMi2hT/dgMtUloThDEId7Jwzzel0+lUxCp3TiQMZ7UBeghgOyCJCEGMY/WKTkDXD+1FfvxX1tXUQg8EhGe90YxPSWRLSxVioJCvclols5pzO6pBuTqcjbqqrq9He3g4AuOrqbyIqRcDzfNrfaTaQCCEmM2QRIYgxhKzI4HkeeSctIcbFiTEGhSkwm8w59TsUsQmD6SMcHYDX78VMx0wU5BcO2XgjZUXQW4Pa29vR1NSE8vJyAEBEimDPnj0wwZSwz0wu/SeLYyGI8Q5ZRAhinGI2mbWt5O/ccif8AV/c+YgUQZe3I6sYEmOGSC7tk/082IX2rrvuAi8KGdsaSTdeNpYYdXz991xQRYLH40F1dTXmzZuH8vJyNDU1oampCY/veRwcOFx77bUJQbLZor+P8ZRVQxBDCQkRghiDFBXNwM3rb4JkEByd3SdQXb8FHx/ej3TGzFwXNWP7oVoUC/IKYUYsoDVbsjXSZpv5ogqJwdyLMWB1xYoVqKyshNPpxNq1a7Fu7TqsWLECAJKO4/F4sr6PbMUVQUw0SIgQxBjEZDLDxJlQX7c1Thz09vaBgxm7dj+YdmHNdVEztjf+nMlakgqbzZZTlVhJjmIg2g+vP3EfnlzJJvMlFaqo0Pelp6GhARaLRauQ6vF40NDQkNBHQ0NDVmIk1TiZ5kkQEwESIgQxBuE4DqUlM7VFXH27n1UyGz9YcwNuqbwlY62RXN+sje31IuR0rCW5zIOx2C7ItW53xv6zGT9Ttk+yPgRBQENDQ8pCZsncKWp7/TWqX/x04tvIXUNMBihYlSDGMIqiICKFEQqGkJ9XMKTpqLlgHGO4xhQEAUWWIoSCobT9Zxusmq5dpmDYbFw/qhgBYp9XavEzILkIGsxzowBWYjxCwaoEMUFgYBBFEe7a2qTnh+qNOdP1qawlQzmGei/ZiJBUriNBV2hMnadRhKjnMwXDZjNXvUhQXTPt7e0J54DkMSTZQCKEmOiQECGIYeZ0RILZZEaeOR+mFP9Vs40FYYylzLQZTGBrrucyuUKARJdHpn6MriN1oTe6kYZCDGTCenJPGqfTiaamJjidzoR5p3P3GNuSK4aYTJAQIYgsGcziMBQWC4fdgbVr16ZcwLJ5Y/YFfPDz/qRiJJfA1kyCQhUEyUjlHtH3p4+7SDZGprlWVlamTIfNRQxkIplFRg1grayshMViSbgvNXA2HeqcKS6EmExQjAhBZEG2MQmprj2dhS+XeIhUMSR3brkTAENlpQt2m33Qc0k3DnAqU8S4SGcquQ7ECyqjxSPT89OPGwwGtQXf2Heuv4ts2qttjG0H+3vPxnVEEGMdihEhiCEmF6tBsmuHe+xkVgT1HcNqtaLKVYUq1ybYbfacXTC5vJknS5UtKpqBG2/+IaJyNOV1xrkbRUymOajjqgGjequMfkO6XEVINmXmk8WD6O9hMJAIISYTJEQIIktGc3HINLZRrEhyFD6/V9vnJdnCni4WwRh3oRclmRZn41yVk4LInSIlN53QylaEqUKgrKwM5eXlCS6QYDCYcB/J+sh17GQuGn2fuTIUrjyCGG+QECGICYI+yFMQRNTW1oIX+JM/C3E7xgLIOhahvLxcW2jTLc6p+snPy0epvRRVlakLmxldGqnOGdvoYyo8Hg8EQUBTU5NmEdHHZmys2AiLxZJUjKV6FskERqq5G/tNJ3zS9ZVLvE6y7wQx3iAhQhATAOPiV+IogauyCg67A0D8Aqd+qZu3JUM939DQELewq+eSjW9cyPVWBrM5DxzHpZx7un7U44wxDET6cfjooTh3iHofavqs0+lEQ0OD1ofVagXP84jKUXgDXhQXF2tuHL04SyewshFsxmc82D1kshUh1dXVaG5uPu0y9gQx2lCwKkGMIMliCYaiTzUYFMhtIQMQt2Aa3+7VNFR98GeqwM9k16v9A0gasKqfe6p+1UDUjRUbEZHCqK+rx7fKv42VK1fGtbFYLHFWIX1/W7ZsgYKYm6qqsgqhUEjLoMmUyZJsTsnOpWvT3Nys7UkzFOifr/o7MgYJE+MXRVHAmALzyV24xyM5rd9sDCOKIgPARFEc7akQxGnD8zy7/fbbGc/zGdsNpu/BXNPa2qr9e/Pmzczr87Jjx44yxph2Tt9enX+yezHOQW2Xbo76OSSjtbWV3X777ezDDz9kjDEmyRI71nIs5XNM9YzVuejn3trayiQpyhRFSTl+JvR9pZqTei7dfQ5m3Mcee4zdfvvt7IUXXhjy/onRpT/cx050tbOoFBntqQyaXNZvcs0QxAiRbeDlcFTfTNWf6sKwWq1YvWY1xKCIhm3b0NzcnJB9kik+RHURKIoCSY5qLgr99bIia9k86jV6N4q+P+FkbY7y8nI0NTVBEASYTWYsWrgobbVU1e1iPK7/qqysxOw5s9AT7kFH94m0zy4d+hiUVM/GYrFkbXnJBvW5vfvuu7jggguwb9++pAG6xPiEMQZBELC1fitEMTja0xkZhl0WnQZkESEmI7lYN7Jpm84Sox5TLSI+v5cdazmmWSpSvWnrLQGqleG1115jt99+Ozt05CB7+923mCRF467x+b2sL9zLDh05GNeP3iqi9qe3vBjv03jMeH96K0o6C1Q4GmatJ1rYLzf/Iu2zOR2ytYIxlmiBytSvaiVKZ40hxh9CT4AdaTvEur1doz2V0yKX9ZtiRAhijJBr/Eiy+IpUeDyehDdm/XhqHMbqNatRbClGTU2NFvQJIO6NXrUyqDU79KxatQpPPPkEGBi+uuqrOHvZ2Vrb+++/H1d+6Qt49plnsW7tD7T+1LFXrVqFvXv3ory8HPPmzUsaM6K2Va0k6rySxZUA0OJGUqEoCoLBYEKbXJ5tJrL5var3ZbScqLECJpM5ZbBvtmMQY5uegRAK86bgRHc77r7nLlRt2ITSkpmjPa1Bk8v6TUKEIMYAg134Ui1AyRZv4z4u+gDX6upqXH311XjkTw/j6quvxqKyxbBardq1QHzQKRAfJKkKg/LychQVFSUIFABxbYyBm6pQam5uRlNTU0LGiX5stR+VZEG6qRb2bJ5dtueHCnWcZGIxKkUhCDzsNvu4Dlwk0tMROI5XD/0T1kI7rjj/iwjwfjjsJaM9rdOCglUJYhwyVKZ1o2tj8+bNrKWlJe6c6rbQm/clWWJvv/sW+9XmX2nHja4T9ZjeHaDOW+1T767R/9t4j/rjiqIwRVEyBsG+9tprcdfqg0+Nzy+dqyMXl8lwkmke/oCf3bb5NhYIBEZ2YsSIEOoLsi1//h275n8+z77+fz/NvnvbN0b9b3KoyGX9JolNEGOE4Xj7nlE0HTdtuAkmzqSNobe6NDU1aRYMp9MJu9UBM2dOOG7cxyVZ4Kpq5dC7cNTrjPdoTO+dNn0qeFFAqb00rr3+mubmZuzduxfTp09PsKjor1EtDOmCN60n64/k+syH2kqSKYDZbrOjypW6ENxkYyK4oMReHu973ka+UoiXDj+Pp998DBElgjzzFDi4uUldhRMdypohiAmGurgBAHdSgNS6a+MySARBwIoVK+IW8IaGBmzbtg1OpzMuEyTVPi56UaF+V7Nb9POQZAl3bLkDAT4QN0fVtQMAgiigrrYOghi7Vr+LL2MMkhzFihUrkrp1VPSFvYw7ABuzcjweT0KhtkzkktGUS9ZTpkVnsi1KqRhsRtlooygK+sK9GIgMgO/xw+M7huNdHtzzcD3aOtrBFA5TUITPzf0aNq/9n0mZ/UQxIgQxwUgWAwIkWiP0cRfZFsUyxjEYY1uMxcQA4PDRw9i+fTuca5xYvGhxgiCyWq1ayqLNZtPGUediLjTBH/Bhzsy5KMyfkjEuJllMjHqP+rkni8lI9TxT3Vuq9kMV6ErEMx4tIgORfgxE+9Ht60a/0oPj3jaIIQGv/+NNXHvttTjSchQHXj+In2z66bi7t3TQ7rsEMUkxujyAU8GlKnp3gL4ORrpaGEBsI72IFIasyAl9qSTbXG7JoiVxIkS/r4s6FsdxmggB4nfxDYoi7r33XgTFYNq3YrUvi8WSIMCMZd/VMZI9v2TPU7W0jBSKosAf8GG43hPHm1VBJduFeizdX0FeIfp6+rHj/p3oFfvwzBPP4r1/fIR13/0hPrn8X3H9v62dcCIkZ4Y3XOX0oGBVgsiOVDU19OdOl0NHDrJfbf4lO3L0cMLY+uqi+mqt6aqc5oI/4I+7PhXGueTyHJLVL1GP9w70ME9Ha9ZVWHO9P2N7r8/Lbtt8G/P5vTn1k+1YYyFQ93TI5m9grN2f/v/oWJvbcEB1RAhikmB0w6RKA013fTo3h/68oiho8bRg8cLFCTUtkrkvsnVl5Dq3bK9Ldg+ZrlPRP0+e5xFGH4LBIBbOXYzC/Ck5zynTuEZXDmMMAd4Pu82Rtn7I6Yw5Xt/AM7m+0v3dhaMDCPT4YJ1ux9SCacM70UkOuWYIYhJgdMOoi26ykunprs/kjlDPm0wmLFm0BKIoJvSl/9BP5crI1lzeMxDCOx+9hTu23JFwTSQaRpfQgYFIf8rr1bno40PUfmRZgqIoCdfon6XedSUIAmpqasD7RDQ27EBvT19W93C6cBwHh71kWEQIMHwBsCPhEkmXaaT/PSYj0ONDsE/EsfYjwzhDImeG0zTz29/+ll1yySVsxowZrLS0lH3jG99gBw4cyPp6cs0QRHpO1+2RrG2quh/qz9lsdmc8rr9OURQmyVJKN8fhtoPsPzffyj462JxwrkvoYIc6DrD9xxLPpUKdhyRLLBwNpyydne6ekx3PZezBtDtd8/1Im/9H0yWSrQuuL9zLmo++n7KsPzF0jJlN7/bt24f169fj1VdfxbPPPotoNIovfelL6O3tHc5hCWLSoH8rzPQ2mOn6ZH0YzxvfRpNZVfQWCbWN/jpJlhCVIvAFfEnnVDZ7ETb+qALLlp6dcM4ytRhyWMaubbuzfvtW52HiTAiKQdTV1qe8Npv7yYQ/4EdH9wkcPno463TTVL+HwVoY9FatwVw7GNJZKoYTo+XOOL6iKAhHB+Dz+zC1YBqWLz4Xt7huHbeuqYnIiMaIeL1ezJw5E/v27cNnPvOZjO0pRoQgcmMofP+59iEIAoqKZkAQRVitVnDgwHGxL3VBXL9hPQDAai0+Gf8QQH3dVmys2AhzAYeW1hbMnTkPs0pnD8scM12rjzuIzTN535nGFQQBd265EwpkcODwg7U3ZFViPtWcTud3aUxjzoZM8RejSbrfW7pS/lEpCl/Ai631W7HJdcuYu6+Jypjda+bw4cM488wz8cEHH2DlypUJ58PhMMLhsPZzMBjEggULSIgQRI6MVDCiIAiwWCzwB3xwu91Yv2E9FEVBfl4BShyxvTL8AT8kOQp3rRs33XQTOM4Eh92OAM9jIDqAwy0f47lnnkM+CnFr1Y+1ecfShSOYkj8VJlNuxttINAxvsAvF06yYMTW7z45sREamRU9tJysSOM4Eu82eti99objhWPyT3RNjbNxtoJdOIGWaL2MMkiwhGAzCYXcM70QJjTEZrKooClwuFz71qU8lFSEA8Lvf/Q7FxcXa14IFC0ZqegQxYThds366fpONEwwGYbfZsbGiAhzHob5+K9xut9bebrMjFOqBAgVHWo+gtr4GXr8XPsGHe++5By8883dc/Y1rUVW5KW5B6Q33osvXiYFo6sDUVPC9AYj9Ao7mEJSYafG1pqhHkqydw16ildVP1Ua1vqhl9NNZYQaLsU9ZdYv5k7vFkl1zOsiyBFmWTrufdG6fTPPlOA75efk5i5CRCLwlYoyYReSmm27C3r178c9//hPz589P2oYsIgQxNAz1W22qN9JU5nLg1ALB8zz+X/Uf8InLLsGrr74GDsCVV16JF57bhzVr1qDYUqxZT/QcO34Ed977B1x/7RpcsvKynOYbiYZx+PhB7G58ELe6fjzkzyJTf9m4ONR+UvWnPsehdJXIsgQ/70ddbX3cHjbGOWSymmQDYwxRKQJBFFBiL83ZqqVnpK00Y9lFNV4Yc7vvrl+/ns2fP58dPXo0p+soa4Ygho7RysJQFIW9/vZr7Oe3/Yy9/e7b7J8v/5P9cvMv2ZFjR9Je5/EeY3956VFWtXnjoMceiswIRVFYJBphnd0drD/cp+0SfDpjZ8owSVVcbSgwzt84F0mW2ECkn3X7urPuLxKNJC2+phZmO517GK5sHHXH52Tj6b8Tg2PMZM0wxrBhwwbs2bMHf/vb37B48eLhHI4giBSob3gBPgBJjsZtQJctg30z5DgOF59/CW5Y+0MsXrgYzz3zHH7g/AGWLFqitRF7eUSiMWsoYwztfg/yzHk4/6wLcctNPxn02LleJysy+iPxtUIUpoAXAqip3YKjrUfh9Xdn5frKNeDXeK2+DP9QwnFcXJ8Jbg/GIIgianXutXSoz6e6piahfYmj5LR3Dx6ObBzGGKJyFD6/N+643q1JlpCRY1hdMzfffDN2796Nxx9/HMuWLdOOFxcXY+rUqRmvp6wZghg6BEFAkaUIPM+j1l0Ll8s1Kh+2xg95f8iLNn8rogNRfOLsyyH28vj4RDN6envx2XO/ALM5L21/PQMhtAfaMM++ADOmFMWdE3t5FOZPwZSCxM+bZIuNx3cMnb4OnDF/GewzTsUUyLKEo63HsH17I1wVVTCbzKf97PSLtnHjwFSumpH6fSmKktN29LIsgRcE2KxWiCdjhoaaobx/nuchyVHU1tYlCCUSIUPDmAlW3bp1K0RRxBVXXIE5c+ZoXw899NBwDksQRBKsVivMJjPsNvuoiRB1HnoK8wrR19OLRx5sgiAImDGlCGYlH0899gxCoZ6M/Xm8R3Hk+EF4vEfjjou9PDz+Frx/9J2Ea1IF9Pb29OKhBx9CTygUd9xszsOZS87EDWt/CIfdkTIuBogtytm+3yWrjJuu2u1wBVAa+zWZTDn9fZjNebBZrQgI/JDNU99HNvef7ZjCyWq5+XkFp22tIYaIYXUSnSYUI0IQk4dUFU0z0dJ+jLk2b2At7cfijveH+9hr+19iP968KevKpYqipIyNSBWroD/eH+5j/qCXHe/wZDX3bCrXpptvrqTqN1MMRjZjK4rCJCnKWlpaUsZf5DJP/QaKyeagKAqLShHm8/tyjiPJJjZHURQWCAQGeQdELus3CRGCIMY9p7uInu446vH+cB87evww+8Xmn49YgG22wZXJFmtJijKf35tTYG26ANpAIMA2b97MurydCaX0cxWayXZQ1iPLMuv2dWvBsOnmpR6PRCOa0EzXVlEUdqKrnf1y8y/idn4msmfMBKsSBEGMBOnM60Npek/Vl3p8SsFUlM1eiFsqB19CPNcg12QbFBphjKG4uDhxh1+BR02NO86VJMlReH3d2jF9sKg6XrKxFEVBkWUGrl99PQCgtrZWa6N3rahfxj5Y7MVY+7msrCxtkKrJFCsYp29j7FM/VoAPICAE4Ha70dramvJ56Z8PMTKMaGXVXKFgVYIgjESkCAIhL0osM5Fnzh/t6Yw6giAkVGfVB1yykxkioiAgz5wPi6UIgijAYS+BoijgBT6u2JfX70Wt243KSlfSoFNjnRgVRVEQ4AOoddeisrIyLjsnWWCuvg91jnzAj9KSWQk1R/T3ky6Y1NhOrYRrsVhgtVohyxI8bW1YvGgxPB5PQoVc/fWKokAQhWEJvJ0MjJlgVYIgiKHmcMd+vHP4TbQYglPHO2pJ+0wke4vXV2c1Whs4joMoiqitrUN1dTVaPa2oqXGjpbUFJpMpToQwxmCz2lKKECCW9Th9xnT4DZsWmkwmlDhK4HK5YLPZEgQBcMq6YrFYUGSJz3AKBPyoravDh80fJNyv3pqSzvJjTEtWK+GqtLefwPbG7do+POkCYlWLCzH8kEWEIIhxxUfHPsDWxlpUrtuEMxYsy3zBOEBRFLT6jiIYFHHOwpUoyC9MaKMukKpFobi4WKt+2tLagkULF8W1TZbZwxjD9KJpON52HDu270xwffj8PkiKBA4cZpbMTKiuqlo9BFHAju07tKwT1a2SqnqqcT5RKRqzytgc2hiMMXzw4QfY8+gerF27Ns5aka1FJNmY+u/6vYJSPaNcLS9EcsgiQhDEuEDs5dEf7kt5fr/nfTz43B/R2nlYO7Z88bn4tet/hlWEDFeabCo4jkNPqAc7d+6CKIpJ56NP9S0qmgF/wA9FUeDz+9DQcD/8AT94noeiKJo4iEpReE8W7bJarbBYigAGTJsxHdetvg7FxcVxY7hr3KirrYO71o133nsHiqJom8Z1+7rhDXhRU1OD7Y3bcfXVV8FqtSIc7ceJrnYE+EDKuArjoh0MBlHrroUgCrHdcf1ecByH8887P0GEGK9PJw6Mz8vj8cSJkcrKyrQbFhqtOMn+DoY7lXoyQkKEIIhRQegN4O1jr2PfB8+lXMDaO1rx/HPPoq2zNe74cL6NDnahkRUZHu8x7G/5MOdAR47jsGLxefhpxc9RWjIz4bw+YNRqtUIQBbjd7jjREgqFsKV6C1paj2kCgj8ZnMnzPPwBHwaiAzjaegx1tXVoaGiIiQu/F5IURTgaxnWrr8OGDevxxS99EY8/9hg+/PBDROUojrYchdvtxsGDB8EB+Mqqr+BPf3oUh44cxIHDH6N2aw1qaqqTiqhkOOyOk4KqCMdaj8YFtmba2TgZzc3Ncb+zYDAIIOay0p/LRmgYnzcQ+90qipL0XLp5EdlBQoQgiFGhIK8QA/0D2PvXp1IuYJ++8IuoWPcTXLbyMyM2r2QLTTZEpDC6/V24b9t98Af8OY8bi9dI3PxPPy8Vh70ErkoXLJYiOOwOuCqrsGjhIqxZswaNjdshiqLWn6vSBY7jUFPjxvHjx7F75y6UX3MNOHAIhWKWidY2D2pra9HYuA3BYBDPP/McvvyVr2DPnj1o83iwY/sOXHXVVXju6efwrW99G5dfdjnWrl2LHdt34qEHH4YZefjm1d9Ef6Qfnd4O9If7NUtMKmxWG0RRxO4du7HWuQ42my1te6N4UL97PB40NTWhvLxce0ZlZWUoLy8HADQ1NWl9eDwe7Vnqf8fqcX2/6rkAH4AsS/AFTt2PUYSQheT0oBgRgiBGDUVRIIpixkVovCD28giFejB/9oIh6zNVPIIkRyErMoJiMM6Kom8vKzIEgYfDXgJBEDCjaDqCwRBsVht4gY//zvOIKlEosgSzOR8mzgSFKQBjUJgCszlPy4ixWW3gOA5dvi6EgsGY+0aRsGPnDpjA4d+/8e/4y+NPYJNrU8rfrazIAAMCQgAmLj5oNhU8z2sxJfrsm/b2dqxYsSLps1MzisrLyzXBMm/evDgRogb7FhUVYUv1lljgb3Hs/JYtW3Dd6uuwvXF7ykqsFDOSCMWIEAQxLjCZTBNGhABA8XTbkIuQVG/bJs6sZcPorQT6BTEQ8KOmpgYBPgCr1Yo8cz7sNjs4jkv4znEcJCmC6vpqHDx2ANU1d0IICnDXumP7zhQXo6KiAlOnT4HXH6szwgFoaNyGgBDAzp07cc1V5XCuWYcnHn8S65xrU4sQWYKsyPCdzLypMWyY1x/uQ/PH76PL23nqGkUGL/LYsmULAGgipLq6Gk1NTXEWEpVYXExsESwqKsKqVavQ1NSELVu2oLU15u6zWCwoLy9HWVkZiouLsXrNajQ0NKC6uhoKU3DzhptgLS5OWw6eRMjpQRYRgiCIMUyqt231uFoPQxUt+hodeotIpjGqq6tx400/RJe/Ew88+ADykQ9X5SYIooDGxka4Kl0nd6ztxgO7H8Am162wWCw4fPQQtu/cji998Uv4+3P74HK5tPFToSgK/Lwfde46VFRWwMSd2tuGMYYDh5qxY9dOmJCHW6tixeH8J0WV0+mMyxDyeDxanRC9dUMfa9Lc3Ky5aJxOJw4dPoR9+/bBedKVBQDXr74OFksxbDYbgmIQoVAIs+fOhj/gw9b6u7DJtYkERw7ksn6TECEIghhn6FNRjYXMgPjdfHPp03qy6FeAD0BSZBTk5WtuHQC4c8udUJgEgENFRSVKHaWIShG0eFqxa/suOJ1OzJs/D3lpdkxOliLLGItLFZZkCcdajqLEXhpnVeF5Pu5nvfjSu1qM64WacQQAq1atwhNPPgHGGC677DKsWL4c27Y1giG2FFa5qhCVo6h1u1FREctQCoV6hmTH5ckECRGCIIgJjrFORrJzg+1TtVi4a9yorKzQLCqCIEBhCmRFhokzwWKxIBgUNbFSOLUAx1qPYuniM1GYohaKUThIchS8IKDEXpJQtyQd7GTsSlAMJhUnKpWVlWhvb8cjjzwCALjmmmvQ9KcmXHjBhXjn3Xe0YF6FKeAQqwZ75NgRbN++HWuda7Fo4aKk86a4kPRQjAhBEMQEJiJFEJUiYIwlXQwHK0LUeBSTyQSHzYENG9ZDVmREpSgi0TAkWYLdZkd/bz/cNW60elpQfTK+o8hShFZPK3btegBtbW1Jx0ie+irGaooIQiw7xe/LKv1ZUWQE+AAslqK49uoYTqcTQGxBXL58Oa5fcz2+9OUv4pGmmCD57Gc/iypXlVYF1m6zw2aLBeEuWbQEa9eccgGpfSZ7VsTpQ0KEIAhiHMEYA88H4K51gxf4rK+TFTntIp9MJChMRq27FqIogBcFuN01aG1txR/v/yPWro1ZCyorYlVeZUWGw+bAD5w/wBlLzgBjDP6AP2a5OFmDA4iViFfnwBiLlYWvjJWFD/ABuN018Pq98Pq6IclS3LV6xJNF0QICD3/AjwAfiLuXsrIyzXUliiJM4PDM08/i2vJrUVFREVeG3ojJZMKiRYsTjuvrkQwmxZtIDrlmCIIgxhnJglBjx4SUabA+vw9utxsVFRUJbZLFbciyhG6/F3V1tVjrXIeFZQsRFIOYUTQDrZ5WLF64CGZdLIjP70NNTY1mZfAHfKipcWP9hpthLbYiGAzBYXdAViQIgghrcTF8vA9mkxmljlj6sXQyPkUICtjRuB0bNmyE2WSGw+5I6rYRBAGyIqGmxg0OHFwuV1I3VUwoSdi//wDOXXnuYB55wnMi0kOuGYIgiHFItqb+2OJ8SoTErCQ8ampqwPPJrSS9Pb3gwKG3pzdhzGSbyplMZthtVlx//fVo3LYNoWAIlmILRFHAju3bIQaDcWnDNqsVN918I7r93QAAu82BiooK2K32uEqwoijC7Xaj7fhx1NXWw11TiwAfQDjaj6MtRwCGWODrGifyzHlwG1J79VitVq1oWzIRorZRmAJeENDU1ITm5uasnnGq8cgdM/SQRYQgCGIMkCwgMpdrLRaLtm29PujUZDLFpfqqn6XG6qD6RVZ/zh/wwcSZYSm2QJYliKKI/LwCAIjL3NlYsRFdvk7s3rkb69b+IC7FljEGURQTrC5qBVqH3YFDRw9he+N2lF9Tjvnz58Nhd2hBswBQ6ijV+gKQ0kJiDOBVLSIKU7D/o/3405/+lJDem8tzHuzvaLJBFhGCIIhxQmxTuSiKi4sHLUKqq6sRDAY1EVJdXR3bFI/JaGk5hju33Imjx46gqKgI1dXVCYGW6uKtzzZR+65118UKnoFDgPej2l0NT1urFidRVlaGyspK2G12nLV0GdY618WJECAmGvT3pf7bYXdobqIzl5yJb5V/C4/teQxmk/mU4ACnBbMCQG+4BwcOfwRZlpM+B4/Ho92vekwURZhNZqxcuXLQIkSdN4mQoYcsIgRBEKNIVIoiIATgsNmRZ87XjucSj2C0AFRXV2NjxUYoioJady2uuvoqPProo3A6nWjc1qgtxqrFRN8PkNxaAgBeXzfajrfhsccexw/W/kBb0HOZq7FmSKp7UdN6HTZHrLLryf73H2rGrp27sW7NOixevETrU1YkhII9sFqtONpyFNsbG+GqrEoQQbnOlxgcZBEhCIIYJwSDQdTX1iEYDEGWJfgDvpzTQ43WBtVCYbNacf3q67ByxUpUVlbGslxOWjEi0TC6fJ2Q5GhcX6pVwdi3IAioq61H2YKFWOdcFydCjHPleR5RKQqf3xfXtyxLiEoR+APxx5PdiyiKJzN2xLj7W7b0nDgRAsQ2HOzydWHajKngOA6LFy5GZaULRZYZKJxaEDcPSr0de5AQIQiCGEUcdgeqXJtgs9oQEHjU1LjBGDstF4DqauEFAY2N2yGIAkycSTsHAJ62NtTXb4UgiHHXqTEfyRZqjuPQ19uHhQsXxl2jn2uAD+COLXfgtTdeg9vt1oJgVQRRQE2NO6MQcNhLtAwcPSaTKU6EAEBQDOKurXchGAxpbew2OxTGYuO5TwW8kntl7EFChCAIYoRQFAWSHE2o5WG1WsFxHEycCRy4OHeCLEtZFfjSo771m01mVFZWwmwyx1kBBEHArh278K3yb6HEEb8Pzfz587Fh44aEhToYDAJAUpGibyvLEjgOePqpp3Ft+bUATtXfMJvzUGIvTdhAjjEGn9+nBa8m6zcdpSUzcYvrVi2gVSXfnI9SRymqKuPHIxEytki9IQBBEAQxpEiKFKv/YXPAbM5LiFVw2B1xaahqBdWenl7MKpmV9TjJ3vr1P1utVpSXl6OpqQkL5i+Ic79MnzEd4snsGzWWQxAEbTO5TP5+h70EGzdsRG9PLxYtWpwgWvQxKarACvABVNdUgwNi1qE0OzKniu9IFtfCcRzyzPkTaofniQhZRAiCIIYIWZYhyVLK86FgCHW19QgGQ0ljFWRFhsJOVRLlwEEURdTV1uUc02BcrI0LdVNTE5xOZ0KQ64H9B9DYuD1lmXYACfPW/9tkMqG0ZCas1lOLv3GPlurq6pNxJBH4/F447A5cv/p6ANA2n0tGNvEdPM/jzi13pqynQoxB2BhGFEUGgImiONpTIQiCSEs4EmZbH/o/7H/u28SEoD9lO57nk/5bURTm9XnZbZtvizseCATifk7XXy4ku47necbzPLv99tsTzre2tmrHjfdgbK8e019jHEdRFNbl7WS3bf4V43meSbLEfH7voOatJxwNs4NHPmaRaCRjX8Twkcv6Tem7BEEQQ0BffwjVO36Jd997B7++9S6ctXh5zn3IigxRFGG32QFkLqCV7PxgU1ONKcCpxkt13GKxgIHBbDLHtU03H8YYBEEYUteJP+BDdU01Kisq46rPEiNLLus3CRGCIIghotvfDh/vw/Izzh+yPjMJi2Q1RHIVJpkETzb0h/sgiAJmlsxCKBhKWYsk0z1kO+d0ZHvPFLQ6fFAdEYIgiFFgpmPekIoQIHOGR7IaIkZhkim+ZChSWoOhELbWb0VbW1tChs6WLVvg9XvjdshVMc4x2zmr55O9S6uWmHTXUi2RsQNZRAiCICYIyd7ykx1jGaqbZro+VRv9wq53y3h93Whrb8Pjex5HlWtTxjlmY0Gprq7GzRtuBgCU2EviMnwAaBYedS6DuS9i8JBFhCAIYpKR6i3fKBBi1Vv9GWuTCIbdeI3nko0bDAa1/Wr0x48cOYrH9jyOVau+mlaEqP0aRYkR1YKj7kOjVoJVxwSgiZBUlg8SIWMHEiIEQRATgFTulQTXhyhoFU+N7YzXAKcW9FT9qeMCsWJn+vk4nU4Eg0E8/dTT+PwVn8fTTz2dUsQkEz3pXChWqxUljhKsda7Ftm3bNEGjPgP1i6qojn3INUMQBDHBMboheJ6Py1RJF+Sa7lyyduXl5VixYkXcdcFgEGVlZRldR8lcNEBm6wW5WcYelDVDEARB5ES6xTzVOVVsOJ1OAKcsIqpoySW+JFXfZNEYn5AQIQiCINKiFwCyIoMDF1d+PdvrPR6PJkDKy8sxb968jJYTY1aPakUx9k2WjvELBasSBEEQKdHHXsiKDFmR4Q/4BnV9WVkZysvLAQBNTU0JbTwej/bv5ubmhJgPdc8bY8ApiZDJAwkRgiCISYY+iNPEmRAUg6jNYT8bYxDoihUrsGrVqrg2+t16AcDpdCYVKnPmzoHT6URZWVnSvo2oomkMG/OJHCHXDEEQBHFaFgjVPaMKClVkrFq1CrNnz9ZEhlHoyIqEGUUzIIgiZpXMShu4quLz++B2u1FZWamVwifGHuSaIQiCIHJiqESInr1796KhoSEh+6W6uvpkejCHAB9ArbsWH3zwQdpUXhWH3UEiZIIx7BaRuro6/P73v0dnZyfOP/98uN1uXHrppVldSxYRgiCI4eV0LCH6rBljeq5wssAZAE2gMMYgiqJ2vdVqhSzLaG1rxfZt27HGuQbz5s1DKBSCiTPlnMVDjB3GjEXkoYcewqZNm7B582a8/fbbOP/88/HlL38Z3d3dwzksQRAEkQV6y0NUikKWpZyuV+M59O4YvfXDYrFoFhFZkeEL+HDnlju184qiABywZNESuFwuzJs3DwEhoBVTU+eo/3c6awkxPhlWIXLHHXfghhtugNPpxPLly3HXXXdh2rRpuP/++4dzWIIgCCILVCExfcZ08L1+tHQcG3QQqL7CKhArmjZ12hRs3LgxpfVCYTJaPa1gjMFqtcJsMsNutcfVITG6awBQbZEJxrAJkUgkgrfeegtXXnnlqcFMJlx55ZV45ZVXhmtYgiCIjGR6m55Mb9uxzBkOwWAQf7zvj3Guk0wks06oKbt33PkHHDr8Mbp9nRAEAaFgCCX2ElS5qjQRcbztOLZv2462tjYAsTUiPy9fi/8wlmxPt4kdMX4ZNiHi8/kgyzJmzZoVd3zWrFno7OxMek04HEYwGIz7IgiCGEoymfbHmulfliV4fd3Dmq5qNudh6fwzcaPzppwW+VSptpIchcIU7N69G7t37daCU1XBobJo0WKsXbs2IcjVOIaesfS7IYaGMZU187vf/Q7FxcXa14IFC0Z7SgRBTEDSmfbH2kZpPt4Pd60bAd4fd3yoF2NRFLXN43JB/5yKLEVYv2E98qfkASZg3dob8O1vfQdArHBZQ0NDgpBIJ0KSjTWWfjfE0DBsQqSkpARmsxldXV1xx7u6ujB79uyk1/zsZz+DKIral1E9EwRBnA76OIN0jKWFrsRego0bK2C3ObRjw2G1Gcwibxw/Eg2jZyCITl8nJMgotlqxYsUKVFZWat/VTfBOZ57ExGLYhEhBQQEuvvhiPP/889oxRVHw/PPP4/LLL096TWFhISwWS9wXQRBEtsiKDK+vG7IiJz0/3G/UjDFIcnRI3ShmkxmljlJwHKcdGwrRkIxc+zOKoWAohLvvuRuPND2Cr371KwhHB7R+1ZTb9vZ2NDQ0aCXdc5kfMTEZVtfMpk2bcO+996KxsRH79+/HTTfdhN7eXm2nRoIgiKEkwAfgrq1FgA+kbDOcb9SyImlpqsPN6YqGoRjfKIYK8wpRwE3BVV+/Bk88+STq6+vA83zcvjNNTU0oLy+Pc8mMtbgcYmQZViHy7W9/G3/4wx9w22234YILLsC7776Lp556KiGAlSAIYigosZegYmMFSuwlWV9jrFNxOnCcCaIoos59at+WoVpcFUXJuc6HynBZgoz9Wa1WbNy4AWctOwMXX3IxGBhkRUJeoQnXfqcc02ZMAwDMmzdvROZHjA+GPVh1w4YNaG1tRTgcxmuvvYbLLrtsuIckCGKSwnEcShwlmhtDliV4/d6UrpJkdSpORziYTWbMLJkFl8sVVwfD6IYYDJIiwc/7NTEymtYDxhhC/UG0dXq0ZyvJUciKjOlF0/DW+2/itTdfhgIGsykPvChg567t4AN+bNi4IangIBEyeRlTWTMEQRBDSUDgUeuuBS/wCedkRYYkSwl1KoZiQVT7sFqtcDqdcfutDJZQMIi62joEg6GcRdNQiCz9tYwxBPgA7rrrLvgCPkSiYfRF+vDhx++js7sTJSUOnLfyfOQhDxzHYe7MeXCu/gF27NwVF+tCEADtvksQxASGMQZe4JNukHbk2BFsb2yE07kWZQvKwHHcsC2SQ7U3inEvl1zjRE53TxlVqCmKAn/AD7fbjRtu+gEkOYoufxce+dMjABgYFBSgEN+55vs4/7zzh2QOxPhizOw1QxAEMZpwHJdUhAiCgB2NO3DNNeXY1rANft6PY63HMvY3WIvCUC2++n5y7fN05mC1WlFRUQGr1YpINAy+xw+hP4DrV1+HYJ+I+nvqMMU8NWYBAQcT8vDlK1fFiRAAKCqagZa2w3jjgxfQ2x8a9HyIiUXeaE+AIAB6UyKGHjVmoTB/StLzHMfBWmwFAJxoP4FHH30UX/vq13DWWWcBiL3RlZWVwePxaN8bGho0q4BqTM5kRRnvf9uKomAg2g9/jxdKngTPiRYcaPkIL768D1MwA9/8929CgYw5M+fgP10/Q3+kD4LI4+HdTbjw3Ivi7j3AB/DrO/4TC5fOgl/sxlc+/e3RuzFizEBChBh1jGZfghgKegd6IIgi5pTOQUF+Ydw5fTyIGlja19eHJ558Anv37tXanXveSrz33vv42le/hieffBJXX3M1ZEWGLMtQmAJRFFHiKInbcVbPUPxty7IEH+9Hib0EZpN5UH0YSSeiJDkKRVGQn1eAqBQF3+PHoZZD2PVYI5YvOwf7P/4YUQyAgUMeophSMA35KERh/pST92jHvFnzUeVakHDPDnsJrv3G97GzaSu+TCKEOAnFiBBjgvH+1kiMPTq6T6Cuvg5VFZvgsDvSto3FPPhQW1uLtc514DgOzc3NeOW12AadppNebAYGmUn4+r9/HXnmfPz5sT9j3dp1aGhoAJC8dPzp/m13+bpQW1uLig0bUVoyc9D9qDDGMBDphxgUMatkdpwYURQFYr+AvlAvSh2zcIL34PX3XsMz/3wKEiLgkIclM5egs7sb+chHIaai8mYX8vMKUOoozXoO9P994pPL+k1ChCCICUsuC54sSxBEEWaTWSsD/+WvfBmzZ81CkaUI7e0n8OifHsUnP3UZ/vnSP2FiJphNefjmVd/Eo48+ivJrynH2OWcjzxzLFBmqxVZRFHT7OjGzZDZMJlPccf3PqZDkKHoGQgj3RTCrdDYYY+jydaK+rh6uiirYbDZNjPT0B3Ho2GE89NDD+NGNN+LA0Q/x12efAMCgQIIJeZiC6ShEIW5w/hD5U/Kg5Mno7+3HWQvPOe17JSYOJESIMYn6wZztBzS9NRGjhcfj0T5ztmzZguvXXI9tDdtiCzYDZEjgOA4mZgJOGhQUxnD96uuwZOEStLefQENDA25efxMkRcIsg4gwIskS+sK9CIVCmFUyC+FoGH09fSgtmYm+cC+8fi9mlczClIKpAGJ7unT5ujGrZBYK8gu0fiJSBGbOBLP5lNe9ZyCETm8HGv7YgB+7/lOLb+F5HixPRjAURNnsRQAYuv3dqK2vxXe/8x1MmVaIu++7B1/43Ocxf04ZHDYHvF0+zJxdivy8AthtdkSiYRxtP4Id23ZofRMEQFkzxBhDXyzK4/HEFZBKd002dQ+oJDQx1AiCoLla1BiSxQsXo6KiAtdcczXAxSqoAsBq5xpUVrpQWenCWuda7Ny+E8ePx/ZScTqdiEhh1NXXwRfwphxPliUE+wR8fGQ/6rfWwxfww+vrwhb3FvA8D1EUcc8990AURe2abn836u9y49Cxj7VjESmCvnAP2ruPx/U/tWAaZjlm4cYbb0R/pA+MMXAch+lF09HaeQx199TiRNdxdHg74LCX4Meun+DsM5djdulcOL+/Fi++8DIeeuBhFOZPwbnnnotZpbO1TKSC/EKcvWg5iRDi9GBjGFEUGQAmiuJoT2XCwvP8sPbN8zy7/fbbtX/rv9Tj6a5NN89MfRDEYEn2N6UoCpNkiQUCAdbS0sJ8fl/K69TvkWiEdXSfYIqipBxLkqKs9UQL+9ltP2VHjx1lvQM97O0P32C/uO3n2hjGsSLRCPvgwHvsl5t/oY0lyRJrPdESd0wbQ5bY8Q4P+8XmnzN/wK8d+7hlP/vpbT9hBw7tZ7/Y/HPm9XmT3hP9HyNyJZf1m4TIJGaoF3KjcNALkGTjpRMhxnap5kkfkMREQBU4jDHW0X2C/eK2n7ODRw6mvUZRlJz+T0SlSEqhwRjTxieIoSCX9ZtiRCY5Q1nx0ZimmCwmZLDxIRQvQkwW2Mny6ZkyfQhiLEMxIkTWDGXZaWPqotVq1WJCPB5PUnFhjPFIVY9B/3PvQA88Ha2D3omUIMYyHMeRCCEmFSREiNNCH1SarH5CQ0MDysvL0dDQEBekql6nD0g17oSqHjMSEAK4++67EeADaedFEARBjH3INUOcFkaXTCqXiiAICAaDAKCVyVYxtgeA6upqbddSo6VFVmQE+EDKAkq5VrMktw9BEMTQQnVEiCEl00KtFxvp4kTUIlFOpxNlZWVZjTlYkZBLLAqVlycIghhaKEaEGDKyqeehFwxGEWK8Np0I0bdT+1D7zpVsr0sW20IQBEGMHCREJhGZCoglO5/NQp0qTkR/rdVqzShC1KBW/VyzLWyWbk6ZIBFCEAQxepAQmSSkW5iTBY7qyXahVmNA1D7116qBq0bBo/+3GtSqr76qiplkc05HMusMQRAEMfYgITJJSGfZUM+lOp/Noq8GluozYoyuFlVQ6DNj9GXfm5qaAAAWiyVhLqmyazLNK5f2BEEQxMhDwaqTnGwCUdVgTiC9dUTfV7p+k7XTbzKWTgzpM3AyBbymGpMgCIIYXihYlUiJ0S1itBQYrQbJLBmp+jPGh6TrUz2uCgv9JmOp0FtPVOtLtpAIIQiCGJuQEJlEGIVHNlkuaju1bXFxccr+shkz1XGn05nRElJZWYmysrK0bqThpN3vwasHX0R/pG9ExyUIgpjIkBCZRCSLE9GnuWbKkJlRNB3+gB+5ePOS9akXHwDiLBxq1ozaziic1O+jYeF4/fDLeO/oWzjUsX/ExyYIgpiokBCZZBgX8FwCOQVBhNvtTipc0l1vFCFqhk5DQwOCwSCcTicqKyvR3t6uZc0IgoD29nYA0L6PNgttS/Deqx/AVpi8oitBEASROyREJhGCIECSo3HH9GJCnzarR1EUyLKEEkcJqlxVsNlscdcPJivF6XRqmTYNDQ1ob2/XsmZCoRCqq6sxb948lJeXY8WKFVnf33By0VmX4reu/4cFs7MPkiUIgiDSQ0JkAqAoCiQ5qrlMkrlOBEHA/9vyBxzvbENH94m4c/qAUdVdol4DAKF+EW1dbYhK0aTWDzV9N1Pqr97tYrFYtEjq8vJyNDU1YdWqVXA6nZg3b57WLhcRMhIpuhT0ShAEMbSQEJkASIqEAB+AosiIRMPo9ndDUZQkLTmEekKor9+akCmjWkYsFktcdoogCGg/cQL33nMPRFFMmWmTLIvF09GKP2z5Xy32o6GhAQcPHoxrU1lZiaKiIgDA3r17AQyu7PpgriEIgiBGHxIiE4BQMIS62noEgyEIooC62joIohDXxmq14hbXLVh+5krc4rolZaaMPjvF6XRCVmQ8tPNh3OC8ESWOkqSVTpOJgIFIP94+/BpE+OENdKOsrAzl5eXYu3dvXJBqMBhEQ0MDysvLASBpLRG9JSUdJEIIgiDGHyREJgAOu0OL3Sh1zISr0gW7zZ7Qzmq1wmwyw2q1QlEUdHk7UWQpSqgTorpf7r//fnT7u/Cd6/4DC8sWgjEGWZa0tnqBoBc2AJBvzofNYocJZtitsbmsWLFCs7qoWCwWzR2TzKKhWlKM2TQEQRDExICEyARBXcA5jksqQox0+7vgrqvB4aOHYLVatX1i9PvFrHGuwe5du7Fr5y4IgoBuXxc6fZ2YNn1qXEl3Fb11xWzOw2fPvxL/5fotHPaSuLFVS4gqgBoaGlBdXZ10nqplRq2iOlKxIARBEMTIQCXeJxmqxcPn92GL+06YYca6tT/QKpsCsYyWu+7fin/75ioUYhr++vgTKC8vx0MPPwgZMsq/dzWKphahpGhWQh0Stf9k46ptVCuHMfU3k2tF7dvj8eRU3p0gCIIYWXJZv0mITBAURYHCZJhNeeA4LmmbAB9AdXU1qlxVSQVEe3s75s2bB6vVipfe/QcefexPuGndehSwKZg3by58AR/au4+jVwniT396FLe7/i8AaNYMvbAwumrStckG1RKiWmIoMJUgCGLsQnvNTEL0mTN6GGNaBk3h1AL8x/e+jRlF0wEkVih95JFHEI4OAAAuOucS3LRuPWaXzMY06xTILNbHYw8/DsvUYqy77gcoLi5GODqA71///TiBYdxdF4AWjBoMBnGk8yAOdn6UtkJrshRhfYl3EiEEQRATAxIiEwR95oyeqBSBL+CFoigIBoPYtWsXRFHUzgdCfrx78E0E+0X8x5pv4Uj3QXQKJzC1cBrOWHAWAj1+tHV50DsQwsySWdhUdQtK7bMAAC3tR/E/tb/D/277L7x24CW89tFLePHAc/jWd6+NEwrBYBBNTU0oLy/Hffffi33vPof7HrwLx9qPJL2XVHEg+hLvBEEQxMSAXDMTCL27Q1EUfHyiGR0dJ/D3v76IKtctsNls4Hk+rjLqodYDuOf+u2FGPr7w1c/h8Sf3oGLdJiyddwaaj7+HtnYP/vH0S7h1409QWjITAHD0+GHcfd9dcN28Ca988A/89R9/BoMCCVHkcwWwohS3uf5PnAtG//2j4+/hoaaHcFvF/0kIZE12LwRBEMT4gmJEJhHtfg8OHT+AC864BNbpp7JlOvh2PPfOk3h53yuouv4/cdbSZXHXKYqC0EAQUTmK3lAP8sz58IW6sX1HI37h2gxzoQn//PAFPPnkk9i0+qdYunhp3PWqUAhHB/DCm8+iX+rD3557Hl/58ldxyZmfxKzS2WnnTUKDIAhi4pLL+p03QnMickAVCVMLpqEgrwAAEImG4Q11o7RoJoL9IsJSGHOs8/D+0Xfw6F//BNt1JbCecUqImDgTLFOLwcAwZWohFEVBf6QP+eZ8FOQXQugNwBvqhi/QjdKiWSibswjTZ0zDppt/rKX/nr/0Ipy59hwsLTslQvrCvXjzyCso5KbiMuunIPYJmF0yF7NL5+CKlV+Ks7YY0YsPEiEEQRAEQDEiYxKxjwff40eLLobC42/Bx56P4PG1oENoR8uJI2jtPoKuYDvmLC1FicHFUZhfiClTpmD5+cvwzw/2ISKFEZbC6PB2oD/Shy7hBA4eO4A9jzyObQ3bIYoirNPtmDdrvtbHfMdCnFV2dly/3mAXjne34v6H7oEgCOjvHcCuXbsQ6Y9kFCHZ1P84ETiOE4HjOTwtgiAIYjxDQmQMMqVgKvr7+rG9YYe2cJskM/7y2F8ghSWIooAHHtmN1nYPgj0hHD/SAW+nN66PgrxCMBl477338drLr+Hgx4cQCobwx3vuR0+wBwP9Ybz47Eu4/jur8f3V30XB1HwMRPozzm2+vQwXnnEpbln7M1itViycuwg/r/wVyuYsgqIo6OCPIxINJ1yXbi+Y3oEetPs9OOg5gDePvIx/fPA8egZCCe0IgiCIicewxIi0tLTg17/+Nf72t7+hs7MTc+fOxfe//3384he/QEFBQdb9TKYYkfZAG0RRwDmLVmp1QIxxFIIgIGoKw9PRgl27dyGPy8f6GzfCH/DBPB3IY4VYsfhcrb0sS2jragPvFVC2ZD66/V2IRCOYXjQdi0qXIigG8YbnnxCCPFYuvgD5rBBnzD8LJtPg9OnH7c040P4hpuUV4YsXfTXr6wI9fnR4T2DHtp345JWX4Pnnn8PtFb9JGchKEARBjG1GPUbkwIEDUBQFd999N8444wx8+OGHuOGGG9Db24s//OEPwzHkuCYcHUDLiSNoamrCT27+OebMnAsgMY7CarXG9nqZA/xkw88wJX8qrFYrpk2bgoNtB/BY027cfMN69MohsCiwdP6ZWDR3MRbNjWW6bNvWiH/58idQIBSieGoxSu2zMa19Bv78/F+w9Nqz8UDTQ7jV9ZOc4zc6hRPo6Q9iauF09Pb14W8v7MMnlvwL+pQeCL1+nDV3OfLM+SmvL55mRcGcAvy48idw2B244twvUgwJQRDEJGHEsmZ+//vfY+vWrTh69GjW10wmi0iX0AFRFHDWwnMGdX1PfxDh/gh6lRCOHD+IP+35E/7jm9/F5ef/K8wmMxhj8AV86BY7cP/2P+JnG3+FwmkFmJI/Fb09vYOqdqqy76Nn0dPTg0vO+iQGIv1oaTuG88++EC8deAGhnhD+ZflnUVa6eFD3NVREpAgkOYpphdNHdR4EQRCTgTFZWVUURdjt6TdjC4fDCAaDcV+ThVnWOYMWIQAwY6oFDnsJ5trmY07JPHz6U5/Gnx/7K0InC5xxHIdSRylWLDkPP6+4DaZCDse6D+H9I2+fdiaLY8pMPP/kCzBJZvT19ePPf/kLekK9mD1jPl5+4VUUYErWfTW3vYe/vfs0IlJkUHNJxbHuw/jg6Lvo6Q+C7/Hj5Q/3ge/xD+kYBEEQRO6MiBA5fPgw3G43brzxxrTtfve736G4uFj7WrBgwUhMb1QIhHw43HZQK7+eDYwx9Ef60pZGzzPno6enB2+8/Bau/+5qmAtN6A/3aeeF3gAee+cB/Pcjv8BLH/wDDz3wcFwmS3+kDx388ZgLKEtWLjkft7n+D0pLZuLshcvx84pfYv7sBbh42WX4P67/xuzSOVn1IysyPjj6Lh58bDdaTmRvOcuGgb4BPPzQw+jp6cWR44fwQNNuHG0/PKRjEARBELmTk2vmpz/9Kf7nf/4nbZv9+/fj7LNPpXy2t7fjs5/9LK644grcd999aa8Nh8MIh09lXASDQSxYsGDCuWZkRcaBlmZs374dm9bfmrH4l0og5APfGwCLMpyxYFnKdsE+EV2+TswqmYXXDr+EcP8AvnLJvyPPnI9O4QS2PnEH3j/4DopRitucv8WSRUu0a5vb3sMJbzvOWnA2FpYuSTnGcOHxHUOnrwOXnPXJQQfNJoMxBl7gYbfZ0R/uw8G2AzhrwdmYWjhtyMYgCIIgYgxbZVWv1wu/P705e8mSJVpmzIkTJ3DFFVfgk5/8JLZt25bzwjKRY0R6BkLgBR4LZpchEg1DZjKmFqRfFIXeAFpOHMPDux7BT1w/zehK6Q/34fl39+KpvU/jvyp+h6nTp+D91rdjbq+eIJYvXInluiwbANjf0oy7t9Wj6oc/xsK5ixDqj1VftU23wxfqRnvXcSxftBIF+YUpx2WMoUvsgHWaDVMKpmb1PCLRMEwmU9qgVoIgCGJ8MCZKvLe3t+Nzn/scLr74YuzcuRNmsznnPiayEFGRFRmHOvYjGAzivKUXZly4ZVlCKNSDwmkFEHt52GeUpBUFsizB6+9GxBRGsE/ER60f4O/P/x2/df2/lEJGDVpljKHN34JQMIQl887Ae0fexoMPP4DV310DhSlYVnYOZkxN/L0c6zqEd1veQgFXiK9delXGZ9A70IN/7H8O0XAUX/vEVTCbqeAvQRDEeGbUg1Xb29txxRVXoKysDH/4wx/g9XrR2dmJzs7O4RhuxJDkKAYi/WljNHKFA4f+k/ELoWDmIl5mcx6sViv8IS+Od7Uh0OPL2B75DGIvj/7efqxcdB6q1qZP0VXPcRwHTjJj1/YH0N83gLMWLMMNq3+EASmMe3ffhQOt+5NebzKZ4Re68fQTz2SspAoAClPQ29uDvU/tBZ9Fe4IgCGLiMCxC5Nlnn8Xhw4fx/PPPY/78+ZgzZ472NZ7pC/ehy9eFiJRYOTRX+iN9GIj0w2Qy4YIzLsbPK2/TdrfNBk4y45EHm8CinHYs1aJvm+FAb28fHn7wEcwtWogzy1LHl6h0i1145q2/Iq/AjFsrf4xeJQRPZysWzCrDtKlT8KnPXo6+SI/WXlZkLcDVG+zCzOI5uHH1TVll4hRNteArl3wDt6//LUocVMSMIAhiMjEsQmTNmjVgjCX9Gs/09/bj3nvuRU+oJ3PjNISjA2j1HsWHR9+DLEvgOA52mx2CIKBnIASxT8jYx7xZ8/Ez1y+14mfp9nLJM+UhJIm48DPnAvnZZem8e/gN7PxzA/729tM4FjiIl977Oxp2NkAQecx1LMBc2wI8+ejTEAQBof4gdr/4R/zx6a3oj/QBUQ5PP/VMTjU7ZkwpyjpolyAIgpg40F4zOTCrdDZudf34tEuPm01m9Pf246EHH4Z4slaKIAi4c8udONDSjEOeA7EFHadSdpOl+VqtVu14ur1cTCYzTLIZL734MsJ92dXnKJpRhHPOWY4XX3wRrcdb8MK+v2EKpqFoSjEcM0qxrGw5bvrhzbBarXjxo2fxjw+ew99few4ejweXnP1J/Mb1eyyetzRp375gN1q9Q5ueSxAEQYxPKCowR4ai9HieOR8XnHkJrD+wIxD2oli2wGq1wlXpQodwHNsat+E/K87AVPs0CL0BiH0CIv2RhIJn/3znb+j0ncCVl30VVos95dw4jsMXLvwKLl78yazm3+5vhRAIonO/D+u/UwVTIYfX8RZudN4Mm82GLqEDRzo/xsBAGAvnLoLYE0SPdwBfu/ybWHZGLHU71TiKouDF/X9Db18PCi8oxGzbvFweHUEQBDHBICEySnAcB0/wKDq87VAUGWfNXQ6bzQabzYafu36lLeR55nwc7/LggabdWF2+Fpeee7nWR3egE3/f9wJWLrkQVkvyqrXBPhEd/HGUlSzOSoQEewU0vbQLb771Fr7/1bVYfuZymM15+GnVL2C1WjEQ6YcE4Hj/APY9+xIuWPIpfPUTV+HsuefivKUXZuzfZDKhKL8Yz+x7Bl9Ykf3GeARBEMTEhITIEBKODsAf8GNWySyYzXnwBbvBwFBqmRXXTlEU+ILdiPRF8czfnoalwIals5fBbIqlOKuCQRB4HGs9CCUq499WfR0PNT2IqdOmYlrhdCydfya+dPm/4dwlF+HMxWcbp6JxtPsQ2rpawcBw9ryVGe8h0OuDIjMMoBfdfCd8IS9mWedobqB/7P8bXve2IuATYF1QAm8+h3OmFuPCMy8BEHMl9YZ7MGNKUcoxrrxoFS5ZcjltbEcQBEFQjMhQwgs8tm7dioDAYyDSj6NdB/HuoTdw3O+BoiiQZRmHTuzHW0dewZ9e3o2X9+/DxRd8As889Szebn5TiwtR8Qe86OzuwF8f/SvOWbASG35YCUmO4u777oIgCJgxzZJShKh7tRTlFeP5vX/DNNOMrO6hrGQJvnrZN/Gdz67FG6+8iYgupoTjOPSHI3jj7Xdx9PghvNXyChqfuR/t4qm07I+Ov49n3vorjnQeBAC0eo9iz2sP4p1Db8aNQyKEIAiCAMgiMqTMKpkNV4ULDnsJFEVBNKzgoT/vxpc+K+Cylf+CsDSA91vfRuvxVrzz4VuIIIwCHMalZ1+Gh5oegHWdNS61dsH8MohBAQX501A8zQar1Qqxz4pb1v847UL+1pFX8WHLu/jMuVdi6fwzcbvrN1kv/CaTCcvmrsA8exlmzZyJNr4V82YvgMlkQrBfxBfOvRIz51+EPfsexNstb+LDI2+g/exPoswaS80OhYJ45tlnsHjmmcBsoFNohxAM4P699+LXrjNIgBAEQRBxkBA5DRhj6Av3Ij+vAPnmfPQMhGCxFMfOgWHJ3KW4/MLP4Im/PYZ+sQdf+NRX0NfTB8+H7fj+levwTsureOfwm/jwQDO+99U1WDhnUVz/BQVTcNEFl2LJorNO7ZA73Q5kyIr18t148cUXcc7c87B45uAW/4K8QuSZ8/HIQ01Y7joPUVMYz733BCKRKK7+1HUoXrUaU/ZxOPjuq+j0Hdeuu/TsT2H+jxZh/uzYhoUlRTNxxvxl+MrN3yQRQhAEQSRAQuQ06I/0IdQvoqenByX2UniDXRjoC8NudcAytRh+XwAH3zmMTy77NN548y1cfv4VuP6LP8SnzzgCXulGUaAIFtgwHRacv+zClKXac13AP3/BV7B05jKcseCstO18wW58fKIZ1gIHViw5L+5cQV4BLln2SZj/wwzFLMHM5aGnN4RnX3kKclTGdz7vxPWX/jvemDETr/7tDXzuvC/DarXCZDJpIiTQ48fWp/8fJEnC5m//Pqd7IAiCICYHJEROg4K8AvT29mHbH7dj/c3r0dPTi20778dnvvRpcLIJV3/mP7B+XQXMUzk4FthxNHAQi8qWYMGCMpw40IbDb7fiR9dWYtGcpUNqLSjIK8iqeqrYJ4AXA9j95C7ctuH/JhQUO9xxAAe63sfBzo/w3SvW4qpPfReyxPDKq6/AZrGjUziBT6+4AiXWUkRNidVmp+RPwdS8afj46EEM9IWB7MJUCIIgiEnEsG16NxSMl03v1E3iAODY8cN47v0n8dprr6Pyuz/GWYuX4fm3n8SHre9j/4f7ceuaX2DF0vMQlaIQRAGljtJBj9vBH0ewT8Qc2zxMLZiO/Lzcdq6VZQnvHHsDXr4L9hmluOycT8WdD/T4sfOFe/Hem+/jfyvdcNgd6B3oQSgUwov7n8ejTz2AT1z0SeRNNQMKh9Wf/xEs06x4++3XwLf58a+rrkR+fj4EUYDdljy9mCAIgph45LJ+k0UkC7zBLhxuO4izF62AbXriglpQmA9ZlmA252Hx/DNQ1rkYr+F1BAZ8eH9/D44eOYT3P3gHixcuwZsfv4KzFy1Hfl4+Sh2l6Og6jmOeIzh/+UWYPj11yqsRxhjePPIqAqIPZ5etQFGeFcsXn5vTfZnNeeAAtHk9+Ntf92FZ1Yo4y0zRFAvmOOZhymXTEOUGAADTp8zA9Ckz8AnpMij9Ufz97/tQdsF87P/oAOZZnsIZC8/EfY9Ww9yXh4LphfjMF69MECFdQgcK8gpgm+HIab4EQRDExIOESBZ4Olqw++Fd+Hb5f6BoqgUSF0FxgQ1nLFiG4x2tePm9ffD2dOHTF38OC0oXISKFwcDg8R2FSTZjblEZSnAUJ9o6wHf04vMXrcKC2WUAgANHPsJfnvgzZkyz4LwVmQuCqXAch9Jps/DUX57Gon8/E4//ZRd+4vppRhdPJBpGl78Ls0pmI9+cj0hYwkevH8SN37854dr8vHyU2Zbgn8/swjWfjI9fmWOfj4uXX4ZLl38aVpsdz89+Gq++8AYiVwygf0Y/+qP9ePLYY3h9z0uYbZ2Hq//lO5hWOB18jx+vHNyHgf4wrvnUd3O24hAEQRATC3LNAOjpD+Jw10FMNxUlja0YiPTjoOcAphRMhfuPd+Lzn/88Xn7hNVT+qAp//+hp7D/8AQ55PsY5y1aibO5CmFgeVs67EL6eLjz1xNPYXPF/IfbzONZ9CG8cfgVz7PPwhQtXYZ59Afy8Fy2eo1hx9vmYUjgl57mrbiG9eygdnd4O1NbVYsP6DZhdOgeRaBjegBfzZs3POEY2c3n8rYfw3D+exoKFZdjf+gFkyLDAhl+t/Q2WLVyOgUg/9r75OJ575nn8uvJ/yGVDEAQxAcll/SYhAuBw58f4uLUZz+x9Dv/l+i2sVitkRcZxfyt6Qj04Z9FKmEwmHGs7iBfefA4RKYyrP/c9+AY68cy7T2Lfhx/hnLMvRsuB/bj4jDIc+vAQ/tt1Z5xA6OkP4o2PX0XjnvsQRj8uPPdiXP3p7+CM2ZmDSnNFURSYTCb0DITQwR/HFG66ZoFhjMEX8KHEXgKO4zL29bbfg1DeVFjzC7Fi6gzkcalr4Im9PN4+9jrkiIxLz/403vj4Zfh7vFg6cxkuXnZpXFu9uOmOhtERDcPMcVhUMBUzzGSoIwiCGM9QjEiOLHAshKzIWPnDi7TFUZYl+Hkfdu9+AP+58ecodZRi6pQZkKMSPnpvP77yiV6UzVqMIvtigGtBsCeAJStW4qyFK7Dm8z+E1WqFX/ChvasV+YVnYcZUC84859O4cc45ePeDZ/Hai0/jM8u7UwqRgBTBy708FACXTCvG3PzsrCWRaDgmNByl6BY78M8PX8AL/3wB6676IS5f+VkU5BVkHSD7ctsH2H7oNbS3tOLcsotw1eWfwyemW1O2f6/lTRw+/jEuO/tTsEyz4AsXfiVlW/U59yky3vd34C8vPoxC8xR858urceH04qzmRxAEQYx/Jr0QYYyhMH8Kls1dHne8IL8Qy8qW45abf6wt3LNL5+K7/74OHZd0YNGixfhg/9uQezmUznZgf+uHKJ01B/ubX8eSb90Kh70EH7d8iI7uEzCZzJhedhb+fuIQWtsO44xll+OmMz6JSw276arIjOExoROvffg6Bgb60XbBv8A5cxGmndyLJtV9cBwHXhSwdetWVGyowGzrPEiyhDD68ObR1zCjqAizbfNgn+5AYf4UmEzpK/z3m/PQ0XEcgYAPbwZexiXLL0wrRE742vHcK09hvmMhzlt0cdq+VaJMQUDwIdjDo6uzG97L/GDTLFlZawiCIIjxz6QWIrIsQewT0NPTgzJDVVPgVIZI/LHpOGPJGQCA1vZjePvFf2DuZeehu9OHJbPORPuJt2Ey56NPkWGdVoKmfzyKS865HB1SGO/vfx1efycURcIFl301YbGNSlF8fKIZfG8/fNMt6OxqQ4evA2GzhCsuKsAKx4Kk9/HKx/vQ1tWKL138b5hVMguuiio47LGMlK9fdg2m5U3Hvhf/Acv0Ini6W2GZbsEliy/HZ8//Yloxcv7Mpfi3y6/Ba6+/iAXzF2OJNX08x4wpRVCgINQTStsu7hpTHpYvXIb+ga/AbMrDmSWzSYQQBEFMIia3EGEKBFHAH+/7I37s+s+ci4p9+hOfw4LZi7Fk2Qr8c+4yfHz0DZx1yefRZ5+FlzqOYu6Chbhl023AjOno7hNRVDIfzc3NuPS8uShKEgcRjvbDx3fj0T2P4bx1lThz6UqYphWg09MC35yjQAoh0uE7gef+9hxmFs9BnikPF535CXj9XnT3tuPZd57E9MLpuOyTl+JoxyHsP9aMqZiO1vc6cN7Ci+Gwl6S8v5K8Anx9wVm4aHYZZpjMYP5WtPZOxcLSJUnbz3LMwacu/Cxe2Pc3fOnCf0v5PHsGQnjirT/hgsWXYtnc5ThnygzMXnk5zOBgoywagiCIScWkD1aNSlEEg0HNgjBYHnqqAS82/w3evqm4/FNXops/gbPOOB/2Bcvw6vFD6A750dnvR2lUxo8/8x9YnsLFEQj50Nvbh9KZ8/BefwihgR4UeI/jsqUXoDBFnEjPQAgnutvxcUczntj7V1z3jTV45vHnce4VZ+PxF5rAwYQCFIKDCf+/vTuPj6u67///uvfOvmskjfZdlmXLC943bIyNWWLMGiDUJICTNjSEJSRtgTQ/mm9DgfaXtPk1/dJAGiBNgSasJsSYgDHGYMA23mXL8qZ910iz35m7/P6QcTC2ARMpA+Y8Hw8/eMzozsznztjMW+d+zjmL5i5m9sT5BNxBCvIKTvp8aS3Nxn3ryKQyLJu+HFmW6R3u5vfvPYOaUrl+6U04bM4THhdPxdjXsZscex7VpbWnfK+eeftxntz4KE7DyU3zvse8hQs//g0WBEEQPjdEs+ppsFqsnzqEGIbBH3b+jvDwIJjgVFxYJSuZTIbGxkZCZRNoad/P5r2bGIj0Ysg68VgS64Rz4SRBZDA2wOPrf0ksEuWvL72DOZ6ckeNyT5xam1ITvLZlLaYOM6fOI2XGmVY7i/yrQ0wbN5v6ikm4PE6qi2spCpSi6RkG4wNMqGg45Z4274slI7T1HOGNN95gasVMCvOL8LsCeKx+Nr/+Gom5yROCiGmauB0eZtTM/dj3bUbNXF7Z8ntSR1I8/9RvmDB5stgQTxAE4QvqCx9E/hS6odM72M36Da9z7bKvku6V+OurvoqnbjwT66bj9HnZ0taIzWJHSxs4ZAcXTFvMuMqTz5QZiPayv62R7q4etlZvZsm884GRlUgHI/2gw7jyCWi6xmAkTEd/O1ve3cyOnq30DnezfPYVTCubid1qxx4cCRvT6/44bbaMik90XkFvHgsnLWFm9QIK84swTZMwEvNmX8m5DV8imJNz7FjTNNmditKVTuFULJzl9BHWM6iGQbnNgV1WiOsae9UYDkmhweGhIr+aH3/9YV5bs4bcggIRQgRBEL7AvvCXZk5XRstgmsaxUYXB2AADg/2MKx/PwGA/Bwb24rZ7qSudwu+3/JYd/W3IpVNwuIuodXk5L1SKV7GgmyYyHNeYqesaGxtfo7enl8sXX4XFYiOpJli7YzXv7X2HYl8ZeYF8ega7OHvKEuxWJ1paZ/2+tWzY+hqzxs8m6Mrj3BnnU/0xO++ejvcSw7xzuIlkKs7M8VM5252DfLTuQ2qc1fv28N5br1MUzKdu6VIiQ/1EYxFCOQGuLKjlN8O9bN2/C4/Hx/nVE7jYf/JLQoIgCMKZQVyaGSO6odMZbmN4eJj6ygZsFhtBTy5BTy6GYbD2ndVsPbKJ8uIq6oomolq9bNvdyMyYRMDWxszzr0KRJNrSSdoSw9hkG7UuL4GjDZqKYuGcyctgMiQNHVXXcFhs2CUHbQe66DeHmD17Ltu2bWNc8UTOn3cxABNqG1g8/gIOde7j96+8yNwJi1DTI3vD2G2nv1rrB2mmwYFImD9sXI2u6djtThrqp5NrsZEydHZHw2w5socBxSDc1oIRGaR39zsMxHrx5OYw1HOYFlw0HdgNQFFhCct9ITEzRhAEQQBEEDktEhLxWJxf//rX/O0td5GX+8cZJ7qeQY0l6WsbINlpsmVqM6bNS14wjwPpBG+1dTL45mqmnrWIVCLGujf+F6vs4GuX3XwsiLxveyLCa+FuTNNkdiCfi2ZdxrxxiwFwu53MrJ9LfU0DAIc69nOk+yCzJy5kQm0DM+sXkJMTZO1bq0klU6w49yqcjhMbSz8pBQmn3Y7X6aOrpxub1YH96Oqqjf0tbN+ygVhsEMklc/aii8nxBeg2TXoGerH5veze8DaFF12G3eYgmUhhy+inDCG6oaN8xFopHxRLRekZ6qI4pxSn3fWpz08QBEHILhFEToMsy0yonMSdt33/hD1SrFY7yxdfwaxJC9nUspGHN/03qmrQ1bKfwkkz8YY87Dm4mZRsUlJWj6qmONB6gPDwELj+OGylGjqvD/eydfubZNIZ9OlnI3e3okcGmDdlERaLlUl1U48d//v3fs9eNc5eWWZh/TwmFhaRUVMkEgnefHMjC6cv+5OCiCRJzPUEcV62iqFYlBm5BXgUCwk1zrrtq2mPDuIYGmYwHcHeX8kVtZPZaoGyUDEXBms4a8Fsdg9EqTrvMqS0xpWFJ+9T2d/ZyKb9G6jJHc/Zk8/92Lpa+w/T0dOGaRrUFtV/6vMTBEEQsuujl9YUTiBJ0ik3agvlF1E7voF206Sxo41UUS1l85czftxMhgZStA4ME/Ll0VBcyyVLv8q3rr+bCR+aQmsCJiZaJkNnZyeJZIL1O17m7cY3aG7de8JregvrOXiold17tvLSu3+gJRnF6XCx4twruevbP6SooOhPPud8q53zfHl8ubiKEquDYT2DRbFRYHEROdzJvBlnc1ZpOXteXYMlluCaYDUFO5tYFKpl146tqDt2cH5Y5VtldRScYsZOJDlMKpXiyaefYGho6GNrcsle1rywFrskRkMEQRA+z8SIyKeQTCeQJfmk63pEdI3ivCpCJT30tDVCTilFRecyfrGdzkySzoIyqrU0Sk6IHMVG7ocuyzhkhVpMOmvHUVpRg9bXTL6m8HbjTkqCldRXTT7u0sbsyWfTPRxl3eaX0CWDIyU11NSehdvpxe30jup5h7UMbw330dPbTVVJOVct/jorpl+N1+uhrXo67iU+AoEASxZcwPSGOQQCAXpaO3hpzRq8gZGZNqqaorX9MOWlldjtfxypmVY1m5C/kCtm/sUnmkVTWVzF/3P7/xEzbgRBED7nRBA5TdFkhKff/jVaRudrS76JzWI77ud2WaakoApX227aWg7Q3ttPY3kDb+9/l3C4g6bcYo7UzyXVvIW6wvE4Z13AFOcfL82YpknLjudxJ5OEvMVE+9p4b/cBxtXW8Ye3fs/8yQupLKs5dnyx1c68meegGTo7dr5HuTNw0rp106QxFUUzTSY4PDg+YS/GBx1Q47z2ylo6O1ppmDyN4oVLGH80CFSGao479v2AcM7SZVSPG09u7shaLe9uf5NDbc0cONLERUsvO3a8IiuU51WdVj0ihAiCIHz+iSBymgaj/TS37KH1YDeXTL+a0IcurbSoCQ7Z7UyYdxm1+TV4Myqu0ho2N7+LrmtEkyqd3S1I0QE2dqxnUd2c44KIJEkUeIp4590XOeea5Qz4C7lk1tX0xbuZOzFFRenxy6v7FStzfLlMWXIlmVnnk3+Ky0YvDPew4fBuUmqKuePO4tpgMVbpxCtzG2KDPDrQjkOW+W6oihq7+wO1jfw3nkhgmCYfbjndsW8Lew7t5EtnX0bAN1LHgf17Wf273+Dz5vCNv7yVoD+PpkONvL7uDebNWHxcmEilkzz8yk/x2QNcv/Smj/soBEEQhDOACCKn6b2mN3FKdi5aeMEJIWRvMsoD+99l5/53Kcyv5NJJC/hyoAjNNHCcdz27Og/hkS34fQF6bXbKQ7WMyzlxr5dL5v8FoepF9ITb8ReNwxMqp97WcMqa7LKCXVbgFCFENXSaooNsa3oHwzDwefz0evMo+dDU3s5Miu+17qajtwNZUjiiJnmxZuaxS0FVVhf+hQsINNRhySug6EP9Hhu2v8p7O7eQ6w8xf+6FOGSZTCZDRtNo3NvI0NAQDfVTaaifytDQ0AkjGnvad/DqrjUkEgkumHIphfmn7m8xTZNoMoLP5T/lMYIgCMJnnwgip6nAX8ZzjU9z4cwvn/Czw+kkuw++x3B8kHgqxmD9bAqPfln/VaiScE4xsiyRMU36C6vxKRaKT9JnEjU0BqI97D+8C103KTr/Lyjl0898SafivLXzJQZi3Vh0F06rC49y4qWZ9nSKaDJBOq1iGAbtySgJQ8cmy/RpaXYkIgy1txI+1ERTYSk/1jJM9wZZ7AniU6wsmXkh+TnFxGsa+HVbEz63l6V14/lazk2AdFzwONlllcnl07l4xpV4bf6PDCEAL259mnW71nLpnKs5Z+KyT/3eCIIgCNklgshpmj9lMRPLzzrpF2mp1U5F4TiGYhFw5ZNMJcmYxrFLIDlWG6Zp0q2p5Fls5H2ov+R9dkkmGAihyDYadzWizo+zf7AdgLqSiadd83B8EHvjG2iShbyCKq6tGI9fOXGX23qHm0p/kHQ6hSwrzPPnY5Vk1kUH2NPWRIfdQVtsGDWt8nKkFfvWI2xzhzg0ZS635lfSUDsVS2kNv92zhR07NuP1+Mm54DK+VFzyieq0WWx847xbP9Gx/UN9tBw5wkBd/2m9F4IgCMJniwgin8KpmiQnOrz8VcN8Hs8tpql1D/uO7OAxb4Drc0uxIHFQjfOrwQ62Dnbhtti4oqCSr+QUn/A8HsXCxGAhBUuu4vxZUXKkDD949BZ0XefHN/+a4pNsggeQSMX42XP3omUyfOeaf8R5dGO60vxKrj/7Wp5+7VG03U2EVmhwkgVXfYqVRyum8lygEKckc0WgkMcHO3iprYnEoR0oSORNOxeX3UFjtAMG2mmPxGmprCOeW4ZXGfnrZBompqHT2dlBNB4Df+jTvdEfYeXibzC9ci6Tqqd+/MGCIAjCZ5YIIqMkbRisjw2w6fBu+lMRwh17GUxEQDNYcPaVIMGvdm7g8eFOoolhlGSEvTmFFFfN4Jn1v2Ri+Vn81YV/bNDMt9rJt9rB4WEoNojN4qBnoAdN1U5Zw1B8iO7+dg4fOULn4nY8bjdr33mKOZOWsHze1Syfd/VJezM+qMBq55t55QD8rPcIv2jdS1cqAaFiahv3cpnNy5RpZ+NqaWRvUicWSZBrdRDW0rwdDyNLEg219eQEgiiKlYX5Jwat0WC1WJlSO21MnlsQBEH48xFB5CMYpkmTGqdPU/HIFqpsLnIsJ17SADiSTvD828+xqfF1ouWTMDxBlGSClkP76ZkUJu1ysHn3a0TzCjEMAySF/sFuVqc30tjXwVuH9oDDw18tvu6E5w54gvznHc8wNDRMKP/UowvFuaXc8KXbSCaS1JSN41dr/j+2Nr1JS9chfrDq3wBoGzzAs2++wZWLb8TnDpzyuRKGzquxfnr6OkkpJlaHl7oll3BxYTm5Fhs/qJ3GG4WVhGMxzs4tZG1/O+vfWYvT5mLF2cu5rmoiTlkeaaIVBEEQhFP4QgeRlKGzNxUjaRgELVbG293HZoi80Pgar8XCRK1eDsfCuO0uzi2q4aqCqhNmmwDIkoTD5kLWNFwd7cw6/6tY+jsoC5awQR1iKJYi4fVjD3dhFFST68lhoTvAJLuXdzY9TyYV41ev/ZIbFlyNzTrSOxJPRrEoVuw2Bzar/ZQhRDV0erU0XtnClOqZx+6fM2kJrd2H6W6OHBsJeejZ++gd7MLEZNXyO076fKuHe/j37kPsVWOoXh/WyABKIs48h4/co30tRVYHM1w+tvV18mZbhN3RAfqGuonFYkyfNB+/v+CEPWXSaZVf//dDqCmVG278Fk6XC800UJDEJniCIAhfUF/oIHJITfDGnjc52LaPOVPOwVfRQLHVQWcyxmObnmav1YHqzkOTLbhME3mgmymB/JMGkUqbk0tmXEhdRQN22UlpTpBuh4fNpsbWd57HSCcprpyEZc861LYOrl1yNTNCpaQjg5SGajnQtge76SURT2AL2Ojp7+Cff3EbFsXGj25/lBffepKm1l18+6p7cDs8x143rms8E+5iX3szBblFXByqoProJnDjyybx9zf+63GXYyZVzeZ3Lb9lfMlZJ31P+jMq93U203GkGcM0sRWXUO3wsMCTy5cKyo4dlzJ09vd28NtXfoWGxLjzrqOmvAGPzc343PyTBotoNEpXbwc9Pb20d7QRLi6gMT6MXbGwyJt70vdVEARBOLN9oYNIxjRpH+jhnYEwif5O/PmlFPnsZBQFh8WFHo+gWf3oNjsWRSLc1oMWT8JJVk63SDLneHOZ4w7Qm0nz/Hsv8/aOVzhQfRatioSMwURvAV+/9l4ef+4/+O2TPyS55GssmrSQG7/2f9i6+UUuqltwLDCkMykSyTidHQfoH+znv559AE3LUFFYw1eW/bGXZL8aZ3PTZva17MLt8FG+5NpjQeR9gUCAdEbFolj55hV/xzVLvnnSPpH2dJJLDm5hVzIKuUFy+geoMmX+pX4WU5y+Y82oADISDrsTq2wjOjjITKub8nlfwiUr1DvcJzw3QG5uHldc8hdEo1G8lZX8ob2ZbTvewaJYsZ69jC/b/vR9cQRBEITPly90ECmy2imYNJdAJkZT2272enOYPM5HQLFw3YXfonzHerSCCjRvkAqPj1INzgl9dPOlQ1aQJdjW9BZ7WncwYHeiOR0oehpdS2OTZCKxAaLxGI0D3UTDnWzZ8jv6Oxpp2fky//k3TwFQVlTD3Tf9jFQqTVFBMXOmLGPT1vVMrZ5/3OvZJBmPy4dpGvT3DKAmEhA4vqbdh7byg/9YhSdQyM/u/h1+//GLgMV1jaSh81d71tOYToIpYVgsUFTMJUVVzHfnnDDCYZNlGnJC3LryLqKxGFPyCsi32unNqLwU6cOvWFngzkH+0OMmNEwBRkJPOp0mk07T0tXCzGnzIeeTfnKCIAjCmWLMg4iqqsyZM4cdO3awbds2zjrrrLF+yU8sZLUzwZvLW+kUkfYW+vOrUWum4bdZmZdXwvhzrsYlK6fcMfZUCqx2YqlhBssnYRZW4IiG8Qy0MNtXQEcmxeGaCfQHfGyV0hzZ8RrhoV6ivgJ2onK4v4+qvHxgJIy87+9X/RtDV5w446Xe4WFu2XgM2aAut5rY3nWs6diJp34hbZkUOYqFlwbb2Vczi4Tdzb/u28Kc0hou8OUjSxLNqThr+9vY1XOEjZ17yQRLkGQZWZPw2F0Maxm6NZWikyy8FrLaybfYGHZ6GNI14mqCB7oPsLd1Px63j8srJvD13LITHgcjPSYTispQFIVppsmc3IKTHicIgiCc2cY8iPzt3/4txcXF7NixY6xf6lNxSDKTp51HVXE9Z4+fcaxPwa9YcUoKHZkUR9QEpTYHlpPszXIyVknmK8tvpf3d54nEY9hzy5k+aQl6IIdn2/YykIySlhT6hvtx2LxEXbn4vAEiORp3dmznMrmBSwMFuD404+Rkl1MUSeKFX9xE8+FdMHUpu/a/y8GGc8nTIKxnUNU49sF2ukvHY3H4eb75bVp7m/nfPeu5eekN7C+o4cUN/0uPlsIuQyKnGN3mAEmhLzbM/0SGaE4neLZ6xknPtVdLs7a3lYOH9mOUldPYdYTuvjbicQ9ht4dCi50v+U7sGVEkiWXePKY6fdgl+ZSzkQRBEIQz25gGkTVr1vDyyy/z9NNPs2bNmrF8qdPSkU7RmUnRnk6xu30/B7sOUD9uBpPcAVyygmGabIqHeSM2yIFDO6hRbJw3aSEzXf5jX6jR+DDv7HmN6fULCPryT3iNQCBERW4Vh7uaUVuPUFw9na17N7G9rwXT7kQx49jTacbVTiBH19hzeAtmMs5rw71EetuJnLWEKU4vE53ek66C+kEJi5OeyqkcKa5HTyVJuHNp7W0jgUbG6UVxuBkuHNksb8hvoB96D8/BnTxl/pKpK+8lpVjpsbnILasjoSXRUgk0m4OkoiDHwuyLD5M2DGzyiUHscDrBG5tfp2Wgi5xoP5byStRogIjVxqGuw/wykcBWM5VlR9+jtnSSQ2oCuywz2eE9tgS+IAiC8MU0ZkGkp6eHv/zLv+S5557D5XJ9/AMYuYyjquqx25FIZPTryqis6TrAu7veIF0yjtaWXUiDXTglmXBBJZWM7ED77/veZnvXfqyxQZoNk7rSOqY4vdglhWE9wy83Ps7BA1vYdmgni1bcilWSmOr0oRwNKtOcfmbVzyLHn4/P5WOaP8i6zS+SKqjE7fBQXDuThTYvDcF8fvTSf6LmFKKWFCObsDmdomnri+Qc2c2V536V28fNPjY6MjDcy3d/+he4nT7u+fp/0BXuYPbKf6L3zeeImDYWXHUPgUiY7Ye2kzYkfHYn8bxipEwaJAlJViiZuJDJfa18dfkt6A4vhybOIZyMMYBJRpJxRAfRA4WgKDi8OUx0+08aQmBkf5oNBfn0OyQmu32syC/jFYeLXe37UbraaE8kaSsfD8CwnmF9Twt/ePsFvA4fVy3+Mou9uaP+GQuCIAifH2MSREzT5IYbbuCmm25i5syZHDly5BM97r777uOHP/zhWJR0TJ+WZlfzVjr7DxNPJwiEKulpbaU0v4ocxUpc11g72MmOll1ELQqS3YtnMIING1ZJZljP8Fb3ERp7WumXFN5NWdj05nP4vTlcWD+La44u2Z5jsfLXoUp2SRJ33ruCN50eLli8ivKBbqZMWcy8nEJqbG5+sm0tYYsNzerAtHuR0gkyNhuxcCdkUrx3cAe9lVOpPDoTZsu+NzjSvg9d11l1zxKiGZWKlT8inooRj8fp7+3g+topVAaCDCTjnBcs4uGBVjaGezC0DHabgytL6jnrGz/l3WSUVDxMQk1hpOKAAXYXktVOmdWOz+lBHurDFe7hlUg/Czw5tKaTSEC5zYlmmvy45xBthorudbObNLfanNxVWMP/TSZoTalUltVSbx+Zbhw3dDp7WglH+znSdohF05eBCCKCIAhfaKcVRO68804eeOCBjzxm7969vPzyy0SjUe66667TKuauu+7ijjv+uMhWJBKhrOzkzY6fVtBipb5qKoND/WhdUZbNmkxB9XQm5ORRaXfRlUmRHOwBDCypFLXVs/nm3PEsLixDliSGdY2N761lINyNEiyjuKaBA3texwTKiqtJ+wuPjR44ZQVPYhg90o8x1MdZ5ZOZPf8KLLKMTZK5u7OJDYZGvKACSdOxpuLYUzGQbXgDxaimhXTJeLozKpV2F7pp4p24mPEX3sR4U2HDxicxImHyJQvO2plEE3GmVo7nPF8eF/lDxHWNG1t30h6P4LM5sDhcXBsspdru4lsHtzE41IfTn4tktWJioCtWJFkm5Mknz+Ulr7+Tnbtf5Q92N2mXD71oHP+75kEUi5VVX/oWbklhIBFFyqjI6KiSnaF4nLPy/SwvqSFdVM1kp5fZR1dwDSpWJlVPJpaI4nJ4GJcjQoggCMIX3WkFke9+97vccMMNH3lMdXU169atY9OmTdjtx1//nzlzJitXruSxxx476WPtdvsJjxltxVYHF5XWMbWgAjORYG5+8bHLKQBeycK44mqmhzuRZBsX10xlZW4JQ1pmZMqpoTO5biadvS0M9CYonJ5Ht8NHIpHCiXLCJYyJVdP44a2/JJlMYS2r4+ltr9I+3EdvWQ3tva1EDR3d4UWyu7BY7YSctZzrCtKVjrOr+zAdm1/kxZwQb8bDrI8NsGugCy2vBkdFA9855zr2drcwt3oy/9nfCukUhmkiI6GZBpcffo/Xh3rQDB0Z8NldrIv281K0j97hPrR0Eml4gHnFVexIRugxDOS0So+eYEhPs8vpIj3tAgDWRAdoTMWwH9mOrKVpmrqMZZWTKXf7CSeipHSNqpwCCrxeHjq4i3C4n0m1E5j4gcXXHLLCuYEQdbMvxCbLlJ9kJo4gCILwxSKZpmmO9pO2trYe19/R2dnJBRdcwFNPPcWcOXMoLT357rEfFolE8Pv9DA8P4/P5RrvME6iGzqZYmE0Ht6L585meW8oybx5hPc3zLbvZvvdNzp98LrUFVciAFosje1xsig+hJVNcXlhxyubLtGHwq879/OT5fyOhJoiOn42ejmNKMlpuCarNiaJrBO1u7iqbQGKwj9/+4b8YdPjInXU+RvM29pTXoZk6SjqFzeGm0u6BZAKLP4CreSexoR6m1M/ltoYFuGSZZfveojeTRJcVkGVAQjZ0bOk0ut2BrmuASZ5i5+JAAasPbiXq9IApobu9SGkVzWrDlCQsaRWbzU5ZbwuBfTuZd8lfc25uEZU2J/8T7kRVVb5TMo4XI308+4enUFWV+rop3DxtEVNdY//ZCYIgCJ8dp/P9PSY9IuXl5cfd9nhGfiuuqan5xCEkG3q1NJv2bmTjnnW47R6WXPo9FEnixeFe/mvL74kkI7y3ez3XOD1Mc/nJ87g4oCYostqZ6S/4yBkgVkki1x2gNL+aA137cQwNIDvspDBRFQuGlkbKqAxlkvzbuke5e9FK3IuvZTAapiOdxHA40U392POpskJ3XzuaoZOxSHg8Pny9rXQnotzbfQDd0ElLIGUy4LACEmBiSDK6aWBIEoYkYUmnSEWH6AvkU5bWaHKAw+1HlSU0LY1psYCkoFksmLqOWljDQEk9z3Q2szbcwddK63mgpP5YXR5ZwesJEIm04XJ58Shi0ztBEATh1L7QK6t+kGma2CSZPH8BsiQx1BslFY8zYHezr/Mgg+kE/cFCOuxe/uWtZyj3hZhYXEvrpmfA5mLJkuv4Wm4ZpXbnSZ8/amgU2uzMX3ApZrgbJxLTckK8ERlgc+9h0g43hqygZVJofa2sfns10ZLxGJ0HyfhzcIXKCcoycdPAanHisbtIW+NE3C5MCdL+IMGpizAD+exr2kosNogWzMfw5iCNnCCmaYIkodnsmKYBkoRhseF1O5jvzuGZmikURMNUuQOgyLxp6Eh6BtMYGTSTdZ1+00CR0uipYfrMNI+HO/nbgupjK6gu94cwF1xAbzzKnGABNfaTL/cuCIIgCPBnCiKVlZWMwRWgUfP2/g38z/qHmT9uCWfPu4qaknFk4gnm5BWhY5LryQFXAM3uQTc1YqZO82Arg7F+bHYX/Q4vPU2b6SgZ4rbyidR9oC8CRqat/qa/jY2Nm2gKBGk6shvd0NlRNpFofAg5GcWla3i8eUzNJBlODtIx0IyaXwYWK+7BYTxFNXh0Dd00yLXCNzxB/lmNYyKBnkHTDdLeIBMdHnYrCtG8YtIeH3IqgaymMNx+lHQS0zRJ251gGCDLKBYbl4eqcMkKkbZm+mWTfk0lKCvkdR8iJksk/HnoniC6RSJpmkiKBT2Qjykr7ElGuPTQVl6oGdn1N9di4/rcUhB9qIIgCMInIEZEgM7+NrRMhhdffZ6Lpl3OhEDecRvbzcov5Y1QBZGhbpKmieFwI2sqeiRObu1MIuFOhgfa2R4dZGte6QlB5IiaZOOuDexs205rxRSSngCmJNGVHEbGxKIoeGIJFpfkc8eEs/lFdwf7WndT5s2jJaeAtK6RTiVoSUYw0YlIEv/Q3QzpFIQqwGIDq0SXmmT7UA9qbiGZTApdsYDTjZxOYY8O4enYiyURoWfKYkzZAqaJzWLFq1jYlYox4PWjaiomJgOyTK6awuoNIXmCGKYJigVMAxkDUxl5vGnovDLcy4vDvSz3h/7Mn5wgCILweSeCCHDxrKsoy6+k0F160mXUZ7kCXF83G+fbL9AZLKYrGcbe38rZxZNQCivpivQTM3Qc3jz8yolvqUdRKA1VsL+jEUvaRFLAREZKp3BEBsnPr2BRzTjuKh1Pic3Jt1d8i0PhQdZFenincQPDeUXoDi+Goow0kioWDG8O9uFBkGSQJUAiaepsHO5FsTnQbXZAAtmCYXNixnuweHIYDhRiahkk2cSwOlAzaX7c1YxH10k5XUgJDSWj4pUtTJ16Ln26xtbE0NHXYOT1dA1JsWKaOpgmkpahM5May49IEARBOEOJIALYrDZmjVtwyp97FQtL88qov2AV7ekUTzz1AAda95JfNpXEkZ1Y+w/jcQVYUD+D87x5Jzy+xu7m4uqzaCitY9/wIK82b2Z3pB+nL0gwWMqyqsncW1SH5+h+K1OcPoosdv433EbU40dLp9EtKijWkREJXUPSdVR/3sgoxft74EgKOD3oAO9PSTYMMA00p4eeQD6GCTIGSAoSJtrR6cZhWcKTyVBkdUFaY1JuMf9v2SS6MioXHHwHSctgSiCZBpZMBpfVgSoBmQxVLh9VNicH1fhxPSGaaSAhHTc9WhAEQRA+SASRTyhosRG02KiyubBf9l2auw4xoWIi7x3YQuG2tegpmdKZK/j3viN4FAsXefPZmYqgIBG0WBlMRqlx+bikPES9P8hrA900D/XQ37yF3rTGlkAh851eYokhgr4Q+VY7Vf58HOEuMnoaWUtj0XWK7B6isoXBdBKs9j8Gjg86dt/RvhzTxFQUDEkCCQxThvdnsxw91pQUokCe1YlksaLJMh7FwkKHm5vyKvht9yHiyQQpm5X8TJLf1C4lbuq0qkl2pKJ8//AOZFnmwrwyrg+WIEsSewY7sVksTPIXnvYOxoIgCMIXgwgip6ktk2LnUA99mSTFWpol9XNpqJxKbyLG6lgfe/dvRXJ4+ElxBXIkjFuxoMX6SbzxG+qKxrHgklvZ0NtGVypOKhbGMtDB5o69NG9fTejIToaH+vi7Wx7ikvlX87XcUtZ2H6Ip0k3a5oRMhvZ0P7rLg+HyIadTx5pOT2CaI38ATNCtjpHb0gd/boBy/GOPqHG8Q/00RcI86c3j9lAV/1xSz3SXn519Lbz8i9vxdh8i4clhyYyLabbG+c+O/bS0NxP3+GnMqKzpb2eyrLD5f+5CUSw8cMuvyMsvFyMjgiAIwglEEDlNu5JRVq//b1JqEk1NMnnaeUwOhNhiszPQspMhNcaAx0MmPoxVjSEDFtPA7/bRnIwz0NtK0/53SQQLsfhyKZqyCGPzaiJqkp6pS9GRebHjABNScUJWG9c6ffxL5z4ybsjYHOh230i/hmliKFYkLYVpHt2d12KFTAYsI42kkmEAIOvaSOOqZGKJDWHTNUwg5c3F/NAyH6YEUX8ONjXNoJbh0YF2NsQGccoyfncAZeoSNIubRP44ejMqNllGVhR0ixXVZkNSE7R0tzFUUILFYsXMqISHBzDzy/hjChIEQRCEESKInCarJGGzOgkPDWKz2LFIEpIkUW13UVNURacaI2q1oWlpDFPHtDhxZVTcNjd1tbPp1zOo/lx0xUImozLkDjB1/uV0J2KkUmkyeoo1yRgTNz3HV87+MuQVk0jUoukZDIuNkcstJpgjeWTKgW20GSbIMulQOUlPEB0D2TBQkjEkTxDV7hjpIzFNNIeLqq7D5FXPoC0WZiCdIulwj1yqOTqKYkoSCTPDk7vW0RUsJCEpI42yhkFRySQsk5dyV88BQol+flw+mVWFNTwsy+xV48hD/WQAl83F16/8AXZTYnbFBCzSyXfvFQRBEL7YRBA5TXPdAdTl36J3eJBZBaWU2kYWMMu12Pj7kvE86/bzbF8rhw/vZtjhpTw3n9mRIfZF0nypbBJyURktWpouPY1sGCQSQ7R780krToaNXsy0jmFzEB4exAReifaT0DMYkoRk6pjSSCCQTQN/JsMcWcK5+mcgy1i+8RN2IhM3TaymxFn2AN0uH4fTCcAEwwSLneFAAe7ug1w8fjbK0CCbSLMvkyYpcXQUxcTe10an1U7SMDBstpGTl2W6/Dk4k1ES4V6Ghvt5wpvL/SX1XOkv4K6mN3k8ESYjwdX+fK4rHo9VlnHJYnVVQRAE4eREEDlNRVYH1wSLMYLFJ/Q8lNmc3BqqYp47h/V5ZchqmpVFlcTGz6F/1gqqc3IJWqzEdJ37upoJRwcwTEjGhuhLDYOhYfeHmOz0Mm/cTCRMulIxTMWKhIkJeLQ07mSSZDLKBYU1zLzgr2mM9JHc8jK9+9+iKK+ODpcbtbCC/VYHC1DoyqRRFQVTlpG0DGp/Oz16Bm9vF3RsJ7PrdercHtomLkKV7Sh6BsXqwJqIkjhJiNAsNlION4YOkpoGoOngFt596FYqJAVZlqmrnINLUbCKkRBBEAThI4gg8ilIksRH/Y4/yx1gljtw3H21oZFprZviYTp6jmBLxlCcHixpFdkTwLv3DRKFlZgWO0MOF3eu/lcurZpKR/s+pPKJmIoFxTT4Rn4Vi/NKiURjNKVj/McL/xdT8RKvm427eRvRghrU4irSpsFAJsmL6SS+g9uQSuqQ7U5Ip4iVjEOXFFK+HPav30JGy5DIrcRq2kC2kLTY0XxBMHQUixXt6NLw7ze/SrKMaXfitDmZljMyXTke7UNRk5g2B9dedAdzaqeKECIIgiB8LBFE/swaUzF+/9azhCvqweaATIY8dwDv5HPY09ZEQo7SMtiBTU3w2KZn8NicaFYb2HxUhyqZk1PEEk8uPXYP/73rddrsNrDbyK27hK6+w7gNKyYSkqFjMrL4WbRqCkgSLocH1eaATJqUafLUwbe5dsYldGdiWEwrvXmFqIaOkk6SkRXkVBxTksBqPTYTWNI13Kkkntb95PvyiFVNAWDprEu5X1aQFTezJy/EfZKF3QRBEAThw8S3xZ+ZR1YIBYpoRcKayWCLDhEqtnBx7SzSg33sC3dg2u1Iho5ktfPvS7/JRj3JgDuHVFsjr/zmnym58g5Mu5ukGkdRbGQCIQ778lCcPuKKBYssk8ECSCOb3FntIEFUT2MxwZpW0WVIygrbew6SVzGFXZE+knpmZDM8c6QhVjZMbKkUus2OrBsoFgszHQGc1iR9/jDV5eOp+8ACZktnXJy191UQBEH4fBJB5M/sfG8+XHA9Ewd7aNJTeHSTG4pqWObLI2/+pazr76J9oI3cUD3LKxq4uHIiF5gGe1MxbvnFd4knotSUTWLhOZczyeKgJxGj31+EqWkjK5lqGXKsdjK6hm7qSIplpNEVExMJQ5GxO9xYFAu2wzvo2vsmuaEyrM6RdUkMxYLdlCh0ejEdbjwo3FM6nqDFxiSHh6DFxhuxQQ6X1VNrdzPfk5Ptt1QQBEH4HJPMz/C2uJFIBL/fz/DwMD6fL9vljDrNNDDhuF6KtGHQq6nYJRm/YuWteJj24UEMp4P299bRcmQX111+K9NzilkXG2BfdJAdiRi/ifeh6zqSLDPO4WGw8xDpjEo6WEhKURhZUcQkIFkIqkkcB7YgD/egRge5aukq+ooq2dJxmNhQLzWVE/mXyimMd7ixMDI9WRAEQRA+qdP5/hZB5DNsdzLKw+se5w9vP8W0+nNYefFf0uD0katY8RztwciYBi9H+rmt8U261RgOTWduVQPdiShD0TCBnBApPcOhVBwtncQx0IkJFLXuIb98OjkWmVAmw6VnX0mO1UZY15ji9FJld2X35AVBEITPrdP5/haXZj7DdNNkODYImBw6vB9rMk2F33ncMVZJxi0rlFrspDqakbFRI1n58bjZtKSTTHX6iOgZvnlkB017NpHMxMi4fDitDqor6mnZ/Dt6hgaZUHUWN02ci1c0mQqCIAh/RuJb5zOs2u7iivO+Rl3VVEpCVUzPKzjpcYs8QS6vmMDrwRB+U+L2kjqq7C7GOzwAFFjt/EPpBH7hcNM10IW/+R2+f/nfsF+Web1rAlqhxoSycWLhMUEQBOHPTlya+YxTDZ2IruFVLDg+JigYpon8Ef0cpjmyKNr7x8R0jSY1DkC93S2m3AqCIAijQlyaOYPYZYX8TzhS8VEhBEYWYvvgER7FwgyX/0+oThAEQRD+NGLpS0EQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQskYEEUEQBEEQsuYzvend+xsDRyKRLFciCIIgCMIn9f739vvf4x/lMx1EotEoAGVlZVmuRBAEQRCE0xWNRvH7P3qXd8n8JHElSwzDoLOzE6/Xi/QxW9x/1kQiEcrKymhra8Pn82W7nDEjzvPMIs7zzCLO88zyeTpP0zSJRqMUFxcjyx/dBfKZHhGRZZnS0tJsl/En8fl8n/m/MKNBnOeZRZznmUWc55nl83KeHzcS8j7RrCoIgiAIQtaIICIIgiAIQtaIIDJG7HY799xzD3a7PduljClxnmcWcZ5nFnGeZ5Yz9Tw/082qgiAIgiCc2cSIiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCyCjbsGEDK1asoLi4GEmSeO6557Jd0qi77777mDVrFl6vl1AoxGWXXUZTU1O2yxoTDz74IFOmTDm2gNC8efNYs2ZNtssaU/fffz+SJHH77bdnu5RR9w//8A9IknTcn/r6+myXNeo6Ojq47rrryM3Nxel0MnnyZLZs2ZLtskZdZWXlCZ+nJEncfPPN2S5tVOm6zg9+8AOqqqpwOp3U1NTwj//4j59oH5fPg8/0yqqfR/F4nKlTp7Jq1SquuOKKbJczJl5//XVuvvlmZs2ahaZp3H333Zx//vk0NjbidruzXd6oKi0t5f7772fcuHGYpsljjz3GpZdeyrZt22hoaMh2eaNu8+bN/PznP2fKlCnZLmXMNDQ08Morrxy7bbGcWf8bDIfDLFiwgHPPPZc1a9aQn59Pc3MzOTk52S5t1G3evBld14/d3r17N8uWLeOqq67KYlWj74EHHuDBBx/kscceo6GhgS1btnDjjTfi9/u59dZbs13en+zM+hf4GXDRRRdx0UUXZbuMMfXSSy8dd/vRRx8lFAqxdetWFi1alKWqxsaKFSuOu33vvffy4IMP8vbbb59xQSQWi7Fy5UoefvhhfvSjH2W7nDFjsVgoLCzMdhlj5oEHHqCsrIxHHnnk2H1VVVVZrGjs5OfnH3f7/vvvp6amhnPOOSdLFY2Nt956i0svvZTly5cDIyNBTzzxBO+++26WKxsd4tKM8CcbHh4GIBgMZrmSsaXrOk8++STxeJx58+Zlu5xRd/PNN7N8+XLOO++8bJcyppqbmykuLqa6upqVK1fS2tqa7ZJG1erVq5k5cyZXXXUVoVCIadOm8fDDD2e7rDGXTqf59a9/zapVqz53m6R+nPnz5/Pqq6+yf/9+AHbs2MHGjRvPmF96xYiI8CcxDIPbb7+dBQsWMGnSpGyXMyZ27drFvHnzSKVSeDwenn32WSZOnJjtskbVk08+yXvvvcfmzZuzXcqYmjNnDo8++ijjx4+nq6uLH/7whyxcuJDdu3fj9XqzXd6oOHToEA8++CB33HEHd999N5s3b+bWW2/FZrNx/fXXZ7u8MfPcc88xNDTEDTfckO1SRt2dd95JJBKhvr4eRVHQdZ17772XlStXZru00WEKYwYwn3322WyXMaZuuukms6Kiwmxra8t2KWNGVVWzubnZ3LJli3nnnXeaeXl55p49e7Jd1qhpbW01Q6GQuWPHjmP3nXPOOeZtt92WvaL+TMLhsOnz+cxf/OIX2S5l1FitVnPevHnH3XfLLbeYc+fOzVJFfx7nn3++efHFF2e7jDHxxBNPmKWlpeYTTzxh7ty50/zVr35lBoNB89FHH812aaNCjIgIn9q3v/1tfve737FhwwZKS0uzXc6Ysdls1NbWAjBjxgw2b97MT3/6U37+859nubLRsXXrVnp7e5k+ffqx+3RdZ8OGDfzsZz9DVVUURclihWMnEAhQV1fHgQMHsl3KqCkqKjphxG7ChAk8/fTTWapo7LW0tPDKK6/wzDPPZLuUMfE3f/M33HnnnXzlK18BYPLkybS0tHDfffedEaNcIogIp800TW655RaeffZZ1q9ff8Y2wp2KYRioqprtMkbN0qVL2bVr13H33XjjjdTX1/N3f/d3Z2wIgZEG3YMHD/LVr34126WMmgULFpwwnX7//v1UVFRkqaKx98gjjxAKhY41c55pEokEsnx8S6eiKBiGkaWKRpcIIqMsFosd99vV4cOH2b59O8FgkPLy8ixWNnpuvvlmHn/8cZ5//nm8Xi/d3d0A+P1+nE5nlqsbXXfddRcXXXQR5eXlRKNRHn/8cdavX8/atWuzXdqo8Xq9J/T3uN1ucnNzz7i+n+9973usWLGCiooKOjs7ueeee1AUhWuvvTbbpY2a73znO8yfP59/+qd/4uqrr+bdd9/loYce4qGHHsp2aWPCMAweeeQRrr/++jNuKvb7VqxYwb333kt5eTkNDQ1s27aNn/zkJ6xatSrbpY2ObF8bOtO89tprJnDCn+uvvz7bpY2ak50fYD7yyCPZLm3UrVq1yqyoqDBtNpuZn59vLl261Hz55ZezXdaYO1N7RK655hqzqKjItNlsZklJiXnNNdeYBw4cyHZZo+6FF14wJ02aZNrtdrO+vt586KGHsl3SmFm7dq0JmE1NTdkuZcxEIhHztttuM8vLy02Hw2FWV1eb3//+901VVbNd2qiQTPMMWZpNEARBEITPHbGOiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWSOCiCAIgiAIWfP/AxbtOmoO5/ufAAAAAElFTkSuQmCC\n", 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", 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" ] @@ -8386,22 +6263,32 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 28, "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/alect/Desktop/sam-algorithm/src/samalg/sam.py:737: UserWarning:\n", + "\n", + "No data for colormapping provided via 'c'. Parameters 'cmap' will be ignored\n", + "\n" + ] + }, { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 29, + "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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\n", + "image/png": 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", "text/plain": [ "
" ] @@ -8430,7 +6317,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 29, "metadata": {}, "outputs": [], "source": [ @@ -8440,7 +6327,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "metadata": {}, "outputs": [ { @@ -8485,19 +6372,19 @@ " \n", " 2\n", " pl_Epidermal: 3\n", - " sc_Parenchymal\n", + " sc_Tegument_prog\n", " hy_ecEp_SC2\n", " \n", " \n", " 3\n", - " pl_Epidermal: 3\n", + " pl_Epidermal: 35\n", " sc_Tegument_prog\n", " hy_ecEp_SC2\n", " \n", " \n", " 4\n", - " pl_Epidermal: 35\n", - " sc_Parenchymal\n", + " pl_Intestine: 19\n", + " sc_Tegument_prog\n", " hy_ecEp_SC2\n", " \n", " \n", @@ -8508,12 +6395,12 @@ " pl sc hy\n", "0 pl_Epidermal: 11 sc_Tegument_prog hy_ecEp_SC2\n", "1 pl_Epidermal: 2 sc_Tegument_prog hy_ecEp_SC2\n", - "2 pl_Epidermal: 3 sc_Parenchymal hy_ecEp_SC2\n", - "3 pl_Epidermal: 3 sc_Tegument_prog hy_ecEp_SC2\n", - "4 pl_Epidermal: 35 sc_Parenchymal hy_ecEp_SC2" + "2 pl_Epidermal: 3 sc_Tegument_prog hy_ecEp_SC2\n", + "3 pl_Epidermal: 35 sc_Tegument_prog hy_ecEp_SC2\n", + "4 pl_Intestine: 19 sc_Tegument_prog hy_ecEp_SC2" ] }, - "execution_count": 31, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -8542,7 +6429,7 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "metadata": {}, "outputs": [], "source": [ @@ -8553,7 +6440,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 32, "metadata": {}, "outputs": [ { @@ -8786,7 +6673,7 @@ "[5 rows x 21 columns]" ] }, - "execution_count": 33, + "execution_count": 32, "metadata": {}, "output_type": "execute_result" } @@ -8804,7 +6691,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 33, "metadata": {}, "outputs": [ { @@ -8818,7 +6705,7 @@ "Name: eggNOG_OGs, dtype: object" ] }, - "execution_count": 34, + "execution_count": 33, "metadata": {}, "output_type": "execute_result" } @@ -8829,7 +6716,7 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 34, "metadata": {}, "outputs": [], "source": [ @@ -8838,25 +6725,47 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 35, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/alect/Desktop/samap/src/samap/analysis/scores.py:349: FutureWarning:\n", + "\n", + "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + "\n" + ] + } + ], "source": [ "ortholog_pairs = convert_eggnog_to_homologs(sm,EGGs,og_key='eggNOG_OGs',taxon=33213) #33213 is the taxon code for Bilaterians" ] }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 36, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/alect/Desktop/samap/src/samap/analysis/scores.py:349: FutureWarning:\n", + "\n", + "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + "\n" + ] + } + ], "source": [ "paralog_pairs = convert_eggnog_to_homologs(sm,EGGs,og_key='eggNOG_OGs',taxon=2759) #2759 is the taxon code for Eukaryotes" ] }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 37, "metadata": {}, "outputs": [ { @@ -8869,7 +6778,7 @@ " ['hy_t10035aep', 'pl_dd_Smed_v4_5491_0_1']], dtype='sc_Smp_086330;pl_dd_Smed_v4_54235_0_1\n", " sc_Smp_086330;pl_dd_Smed_v4_533_0_1\n", " 0.0\n", - " 0.936587\n", - " 0.936587\n", + " 0.935522\n", + " 0.935522\n", " \n", " \n", " 347468\n", " sc_Smp_086330;pl_dd_Smed_v4_54235_0_1\n", " sc_Smp_086330;pl_dd_Smed_v4_635_0_1\n", " 0.0\n", - " 0.931467\n", - " 0.931467\n", + " 0.930164\n", + " 0.930164\n", " \n", " \n", " 347471\n", " sc_Smp_086330;pl_dd_Smed_v4_54235_0_1\n", " sc_Smp_086330;pl_dd_Smed_v4_333_0_1\n", " 0.0\n", - " 0.907637\n", - " 0.907637\n", + " 0.907687\n", + " 0.907687\n", " \n", " \n", " 53420\n", " pl_dd_Smed_v4_15019_0_1;sc_Smp_056420\n", " pl_dd_Smed_v4_15019_0_1;sc_Smp_086860\n", " 0.0\n", - " 0.895317\n", - " 0.895317\n", + " 0.890065\n", + " 0.890065\n", " \n", " \n", - " 36840\n", - " pl_dd_Smed_v4_13347_0_1;sc_Smp_241510\n", - " pl_dd_Smed_v4_13347_0_1;sc_Smp_040020\n", + " 331139\n", + " sc_Smp_047620;pl_dd_Smed_v4_10681_0_1\n", + " sc_Smp_047620;pl_dd_Smed_v4_7837_0_1\n", " 0.0\n", - " 0.870174\n", - " 0.870174\n", + " 0.869102\n", + " 0.869102\n", " \n", " \n", "\n", @@ -9009,24 +6918,24 @@ "347468 sc_Smp_086330;pl_dd_Smed_v4_54235_0_1 \n", "347471 sc_Smp_086330;pl_dd_Smed_v4_54235_0_1 \n", "53420 pl_dd_Smed_v4_15019_0_1;sc_Smp_056420 \n", - "36840 pl_dd_Smed_v4_13347_0_1;sc_Smp_241510 \n", + "331139 sc_Smp_047620;pl_dd_Smed_v4_10681_0_1 \n", "\n", " paralog pairs ortholog corrs paralog corrs \\\n", - "347469 sc_Smp_086330;pl_dd_Smed_v4_533_0_1 0.0 0.936587 \n", - "347468 sc_Smp_086330;pl_dd_Smed_v4_635_0_1 0.0 0.931467 \n", - "347471 sc_Smp_086330;pl_dd_Smed_v4_333_0_1 0.0 0.907637 \n", - "53420 pl_dd_Smed_v4_15019_0_1;sc_Smp_086860 0.0 0.895317 \n", - "36840 pl_dd_Smed_v4_13347_0_1;sc_Smp_040020 0.0 0.870174 \n", + "347469 sc_Smp_086330;pl_dd_Smed_v4_533_0_1 0.0 0.935522 \n", + "347468 sc_Smp_086330;pl_dd_Smed_v4_635_0_1 0.0 0.930164 \n", + "347471 sc_Smp_086330;pl_dd_Smed_v4_333_0_1 0.0 0.907687 \n", + "53420 pl_dd_Smed_v4_15019_0_1;sc_Smp_086860 0.0 0.890065 \n", + "331139 sc_Smp_047620;pl_dd_Smed_v4_7837_0_1 0.0 0.869102 \n", "\n", " corr diff \n", - "347469 0.936587 \n", - "347468 0.931467 \n", - "347471 0.907637 \n", - "53420 0.895317 \n", - "36840 0.870174 " + "347469 0.935522 \n", + "347468 0.930164 \n", + "347471 0.907687 \n", + "53420 0.890065 \n", + "331139 0.869102 " ] }, - "execution_count": 41, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -9068,7 +6977,7 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 41, "metadata": {}, "outputs": [], "source": [ @@ -9080,7 +6989,7 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -9129,124 +7038,124 @@ " \n", " \n", " \n", - " 717\n", - " pl_dd_Smed_v4_1161_0_1\n", - " sc_Smp_345440\n", - " hy_t1091aep\n", + " 6295\n", + " pl_dd_Smed_v4_5055_0_1\n", + " sc_Smp_068950\n", + " hy_t1909aep\n", + " N.S.\n", " N.S.\n", - " hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309...\n", - " hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309...\n", - " pl_dd_Smed_v4_1161_0_1;sc_Smp_345440\n", - " pl_dd_Smed_v4_1161_0_1;hy_t1091aep\n", - " sc_Smp_345440;hy_t1091aep\n", - " 0.868737\n", + " N.S.\n", + " pl_dd_Smed_v4_5055_0_1;sc_Smp_068950\n", + " pl_dd_Smed_v4_5055_0_1;hy_t1909aep\n", + " sc_Smp_068950;hy_t1909aep\n", + " 0.791476\n", " ...\n", - " 0.828863\n", + " 0.773475\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.795255\n", - " Muscle: 14\n", - " Muscle\n", - " enEp_tent\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.75173\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_nb1\n", " \n", " \n", - " 2063\n", - " pl_dd_Smed_v4_1161_0_1\n", - " sc_Smp_345440\n", - " hy_t12725aep\n", + " 6296\n", + " pl_dd_Smed_v4_5055_0_1\n", + " sc_Smp_212260\n", + " hy_t1909aep\n", + " N.S.\n", " N.S.\n", - " hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309...\n", - " hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309...\n", - " pl_dd_Smed_v4_1161_0_1;sc_Smp_345440\n", - " pl_dd_Smed_v4_1161_0_1;hy_t12725aep\n", - " sc_Smp_345440;hy_t12725aep\n", - " 0.868737\n", + " N.S.\n", + " pl_dd_Smed_v4_5055_0_1;sc_Smp_212260\n", + " pl_dd_Smed_v4_5055_0_1;hy_t1909aep\n", + " sc_Smp_212260;hy_t1909aep\n", + " 0.744294\n", " ...\n", - " 0.790684\n", + " 0.793425\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.790684\n", - " Muscle: 14\n", - " Muscle\n", - " enEp_tent(pd)\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.744294\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_nb1\n", " \n", " \n", - " 15206\n", - " pl_dd_Smed_v4_17069_0_1\n", - " sc_Smp_344820\n", - " hy_t3456aep\n", + " 921\n", + " pl_dd_Smed_v4_3186_0_1\n", + " sc_Smp_045040\n", + " hy_t11687aep\n", + " N.S.\n", " N.S.\n", - " hy_t20249aep;hy_t36853aep\n", - " hy_t20249aep;hy_t36853aep\n", - " pl_dd_Smed_v4_17069_0_1;sc_Smp_344820\n", - " pl_dd_Smed_v4_17069_0_1;hy_t3456aep\n", - " sc_Smp_344820;hy_t3456aep\n", - " 0.843316\n", + " N.S.\n", + " pl_dd_Smed_v4_3186_0_1;sc_Smp_045040\n", + " pl_dd_Smed_v4_3186_0_1;hy_t11687aep\n", + " sc_Smp_045040;hy_t11687aep\n", + " 0.734138\n", " ...\n", - " 0.817948\n", + " 0.719196\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.786597\n", - " Muscle: 13\n", - " Muscle\n", - " enEp_tent(pd)\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.719196\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_SC\n", " \n", " \n", - " 15207\n", - " pl_dd_Smed_v4_17069_0_1\n", - " sc_Smp_345440\n", - " hy_t3456aep\n", - " pl_dd_Smed_v4_22514_0_1;pl_dd_Smed_v4_22836_0_...\n", - " hy_t20249aep;hy_t36853aep\n", - " hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309...\n", - " pl_dd_Smed_v4_17069_0_1;sc_Smp_345440\n", - " pl_dd_Smed_v4_17069_0_1;hy_t3456aep\n", - " sc_Smp_345440;hy_t3456aep\n", - " 0.899836\n", + " 12146\n", + " pl_dd_Smed_v4_1807_0_1\n", + " sc_Smp_167200\n", + " hy_t30876aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_1807_0_1;sc_Smp_167200\n", + " pl_dd_Smed_v4_1807_0_1;hy_t30876aep\n", + " sc_Smp_167200;hy_t30876aep\n", + " 0.74404\n", " ...\n", - " 0.884831\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.712481\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.786597\n", - " Muscle: 13\n", - " Muscle\n", - " enEp_tent(pd)\n", + " 0\n", + " 0.693079\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_SC\n", " \n", " \n", - " 8987\n", - " pl_dd_Smed_v4_13487_0_1\n", - " sc_Smp_145140\n", - " hy_t21554aep\n", + " 18494\n", + " pl_dd_Smed_v4_1535_0_1\n", + " sc_Smp_103710\n", + " hy_t9175aep\n", " N.S.\n", - " hy_t15891aep\n", - " hy_t15891aep\n", - " pl_dd_Smed_v4_13487_0_1;sc_Smp_145140\n", - " pl_dd_Smed_v4_13487_0_1;hy_t21554aep\n", - " sc_Smp_145140;hy_t21554aep\n", - " 0.833242\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_1535_0_1;sc_Smp_103710\n", + " pl_dd_Smed_v4_1535_0_1;hy_t9175aep\n", + " sc_Smp_103710;hy_t9175aep\n", + " 0.633695\n", " ...\n", - " 0.805404\n", + " 0.688774\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.749112\n", - " Muscle: 14\n", - " Muscle\n", - " enEp_tent\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.623122\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_SC\n", " \n", " \n", " ...\n", @@ -9273,252 +7182,200 @@ " ...\n", " \n", " \n", - " 16405\n", - " pl_dd_Smed_v4_17162_0_1\n", - " sc_Smp_088920\n", - " hy_t36240aep\n", - " pl_dd_Smed_v4_13910_0_1;pl_dd_Smed_v4_17069_0_...\n", + " 4267\n", + " pl_dd_Smed_v4_2312_0_1\n", + " sc_Smp_144570\n", + " hy_t16585aep\n", + " N.S.\n", " N.S.\n", - " hy_t20249aep;hy_t36853aep;sc_Smp_157240;sc_Smp...\n", - " pl_dd_Smed_v4_17162_0_1;sc_Smp_088920\n", - " pl_dd_Smed_v4_17162_0_1;hy_t36240aep\n", - " sc_Smp_088920;hy_t36240aep\n", - " 0.301734\n", + " N.S.\n", + " pl_dd_Smed_v4_2312_0_1;sc_Smp_144570\n", + " pl_dd_Smed_v4_2312_0_1;hy_t16585aep\n", + " sc_Smp_144570;hy_t16585aep\n", + " 0.313954\n", " ...\n", - " 0.462701\n", - " substitution\n", + " 0.373923\n", " ortholog\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.301734\n", - " Neural: 33\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.313954\n", + " Neoblast: 0\n", " Flame cells\n", - " i_mgl\n", + " i_SC\n", " \n", " \n", - " 9197\n", - " pl_dd_Smed_v4_13704_0_1\n", - " sc_Smp_342580\n", - " hy_t2168aep\n", + " 1896\n", + " pl_dd_Smed_v4_4613_0_1\n", + " sc_Smp_303490\n", + " hy_t12738aep\n", + " N.S.\n", " N.S.\n", - " hy_t10146aep\n", - " hy_t10146aep\n", - " pl_dd_Smed_v4_13704_0_1;sc_Smp_342580\n", - " pl_dd_Smed_v4_13704_0_1;hy_t2168aep\n", - " sc_Smp_342580;hy_t2168aep\n", - " 0.301053\n", + " N.S.\n", + " pl_dd_Smed_v4_4613_0_1;sc_Smp_303490\n", + " pl_dd_Smed_v4_4613_0_1;hy_t12738aep\n", + " sc_Smp_303490;hy_t12738aep\n", + " 0.310063\n", " ...\n", - " 0.300797\n", + " 0.314676\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.300797\n", - " Neural: 9\n", - " Neural\n", - " i_nc6\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.310063\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_SC\n", " \n", " \n", - " 9198\n", - " pl_dd_Smed_v4_29462_0_1\n", - " sc_Smp_342580\n", - " hy_t2168aep\n", + " 9658\n", + " pl_dd_Smed_v4_13295_0_1\n", + " sc_Smp_340320\n", + " hy_t24627aep\n", + " N.S.\n", + " N.S.\n", " N.S.\n", - " hy_t10146aep\n", - " hy_t10146aep\n", - " pl_dd_Smed_v4_29462_0_1;sc_Smp_342580\n", - " pl_dd_Smed_v4_29462_0_1;hy_t2168aep\n", - " sc_Smp_342580;hy_t2168aep\n", - " 0.530394\n", + " pl_dd_Smed_v4_13295_0_1;sc_Smp_340320\n", + " pl_dd_Smed_v4_13295_0_1;hy_t24627aep\n", + " sc_Smp_340320;hy_t24627aep\n", + " 0.345553\n", " ...\n", - " 0.300797\n", + " 0.514597\n", " ortholog\n", - " substitution\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.300797\n", - " Neural: 8\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.305524\n", + " Neural: 23\n", " Neural\n", - " i_nc6\n", + " i_nc1\n", " \n", " \n", - " 8682\n", - " pl_dd_Smed_v4_1000_0_1\n", - " sc_Smp_099030\n", - " hy_t2114aep\n", + " 9657\n", + " pl_dd_Smed_v4_13295_0_1\n", + " sc_Smp_004730\n", + " hy_t24627aep\n", " N.S.\n", " N.S.\n", " N.S.\n", - " pl_dd_Smed_v4_1000_0_1;sc_Smp_099030\n", - " pl_dd_Smed_v4_1000_0_1;hy_t2114aep\n", - " sc_Smp_099030;hy_t2114aep\n", - " 0.669682\n", + " pl_dd_Smed_v4_13295_0_1;sc_Smp_004730\n", + " pl_dd_Smed_v4_13295_0_1;hy_t24627aep\n", + " sc_Smp_004730;hy_t24627aep\n", + " 0.437183\n", " ...\n", - " 0.405317\n", + " 0.319902\n", " ortholog\n", " ortholog\n", " ortholog\n", " 3\n", " 0\n", - " 0.300250\n", - " Neoblast: 0\n", - " Neoblast\n", - " i_SC\n", + " 0.305524\n", + " Neural: 23\n", + " Neural_KK7\n", + " i_nc1\n", " \n", " \n", - " 8679\n", - " pl_dd_Smed_v4_1000_0_1\n", - " sc_Smp_018290\n", - " hy_t2114aep\n", - " pl_dd_Smed_v4_10164_0_1;pl_dd_Smed_v4_11271_0_...\n", + " 15097\n", + " pl_dd_Smed_v4_14363_0_1\n", + " sc_Smp_142860\n", + " hy_t36047aep\n", " N.S.\n", - " hy_t33665aep\n", - " pl_dd_Smed_v4_1000_0_1;sc_Smp_018290\n", - " pl_dd_Smed_v4_1000_0_1;hy_t2114aep\n", - " sc_Smp_018290;hy_t2114aep\n", - " 0.766868\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_14363_0_1;sc_Smp_142860\n", + " pl_dd_Smed_v4_14363_0_1;hy_t36047aep\n", + " sc_Smp_142860;hy_t36047aep\n", + " 0.598461\n", " ...\n", - " 0.494589\n", - " substitution\n", + " 0.305256\n", " ortholog\n", - " substitution\n", - " 1\n", - " 2\n", - " 0.300250\n", - " Neoblast: 0\n", - " Neoblast\n", - " i_SC\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.305256\n", + " Neural: 21\n", + " Neural\n", + " i_nem\n", " \n", " \n", "\n", - "

416 rows × 21 columns

\n", + "

69 rows × 21 columns

\n", "" ], "text/plain": [ - " pl gene sc gene hy gene \\\n", - "717 pl_dd_Smed_v4_1161_0_1 sc_Smp_345440 hy_t1091aep \n", - "2063 pl_dd_Smed_v4_1161_0_1 sc_Smp_345440 hy_t12725aep \n", - "15206 pl_dd_Smed_v4_17069_0_1 sc_Smp_344820 hy_t3456aep \n", - "15207 pl_dd_Smed_v4_17069_0_1 sc_Smp_345440 hy_t3456aep \n", - "8987 pl_dd_Smed_v4_13487_0_1 sc_Smp_145140 hy_t21554aep \n", - "... ... ... ... \n", - "16405 pl_dd_Smed_v4_17162_0_1 sc_Smp_088920 hy_t36240aep \n", - "9197 pl_dd_Smed_v4_13704_0_1 sc_Smp_342580 hy_t2168aep \n", - "9198 pl_dd_Smed_v4_29462_0_1 sc_Smp_342580 hy_t2168aep \n", - "8682 pl_dd_Smed_v4_1000_0_1 sc_Smp_099030 hy_t2114aep \n", - "8679 pl_dd_Smed_v4_1000_0_1 sc_Smp_018290 hy_t2114aep \n", - "\n", - " pl/sc subbed \\\n", - "717 N.S. \n", - "2063 N.S. \n", - "15206 N.S. \n", - "15207 pl_dd_Smed_v4_22514_0_1;pl_dd_Smed_v4_22836_0_... \n", - "8987 N.S. \n", - "... ... \n", - "16405 pl_dd_Smed_v4_13910_0_1;pl_dd_Smed_v4_17069_0_... \n", - "9197 N.S. \n", - "9198 N.S. \n", - "8682 N.S. \n", - "8679 pl_dd_Smed_v4_10164_0_1;pl_dd_Smed_v4_11271_0_... \n", - "\n", - " pl/hy subbed \\\n", - "717 hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309... \n", - "2063 hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309... \n", - "15206 hy_t20249aep;hy_t36853aep \n", - "15207 hy_t20249aep;hy_t36853aep \n", - "8987 hy_t15891aep \n", - "... ... \n", - "16405 N.S. \n", - "9197 hy_t10146aep \n", - "9198 hy_t10146aep \n", - "8682 N.S. \n", - "8679 N.S. \n", - "\n", - " sc/hy subbed \\\n", - "717 hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309... \n", - "2063 hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309... \n", - "15206 hy_t20249aep;hy_t36853aep \n", - "15207 hy_t20250aep;hy_t21612aep;hy_t21935aep;hy_t309... \n", - "8987 hy_t15891aep \n", - "... ... \n", - "16405 hy_t20249aep;hy_t36853aep;sc_Smp_157240;sc_Smp... \n", - "9197 hy_t10146aep \n", - "9198 hy_t10146aep \n", - "8682 N.S. \n", - "8679 hy_t33665aep \n", - "\n", - " pl/sc \\\n", - "717 pl_dd_Smed_v4_1161_0_1;sc_Smp_345440 \n", - "2063 pl_dd_Smed_v4_1161_0_1;sc_Smp_345440 \n", - "15206 pl_dd_Smed_v4_17069_0_1;sc_Smp_344820 \n", - "15207 pl_dd_Smed_v4_17069_0_1;sc_Smp_345440 \n", - "8987 pl_dd_Smed_v4_13487_0_1;sc_Smp_145140 \n", - "... ... \n", - "16405 pl_dd_Smed_v4_17162_0_1;sc_Smp_088920 \n", - "9197 pl_dd_Smed_v4_13704_0_1;sc_Smp_342580 \n", - "9198 pl_dd_Smed_v4_29462_0_1;sc_Smp_342580 \n", - "8682 pl_dd_Smed_v4_1000_0_1;sc_Smp_099030 \n", - "8679 pl_dd_Smed_v4_1000_0_1;sc_Smp_018290 \n", + " pl gene sc gene hy gene pl/sc subbed \\\n", + "6295 pl_dd_Smed_v4_5055_0_1 sc_Smp_068950 hy_t1909aep N.S. \n", + "6296 pl_dd_Smed_v4_5055_0_1 sc_Smp_212260 hy_t1909aep N.S. \n", + "921 pl_dd_Smed_v4_3186_0_1 sc_Smp_045040 hy_t11687aep N.S. \n", + "12146 pl_dd_Smed_v4_1807_0_1 sc_Smp_167200 hy_t30876aep N.S. \n", + "18494 pl_dd_Smed_v4_1535_0_1 sc_Smp_103710 hy_t9175aep N.S. \n", + "... ... ... ... ... \n", + "4267 pl_dd_Smed_v4_2312_0_1 sc_Smp_144570 hy_t16585aep N.S. \n", + "1896 pl_dd_Smed_v4_4613_0_1 sc_Smp_303490 hy_t12738aep N.S. \n", + "9658 pl_dd_Smed_v4_13295_0_1 sc_Smp_340320 hy_t24627aep N.S. \n", + "9657 pl_dd_Smed_v4_13295_0_1 sc_Smp_004730 hy_t24627aep N.S. \n", + "15097 pl_dd_Smed_v4_14363_0_1 sc_Smp_142860 hy_t36047aep N.S. \n", + "\n", + " pl/hy subbed sc/hy subbed pl/sc \\\n", + "6295 N.S. N.S. pl_dd_Smed_v4_5055_0_1;sc_Smp_068950 \n", + "6296 N.S. N.S. pl_dd_Smed_v4_5055_0_1;sc_Smp_212260 \n", + "921 N.S. N.S. pl_dd_Smed_v4_3186_0_1;sc_Smp_045040 \n", + "12146 N.S. N.S. pl_dd_Smed_v4_1807_0_1;sc_Smp_167200 \n", + "18494 N.S. N.S. pl_dd_Smed_v4_1535_0_1;sc_Smp_103710 \n", + "... ... ... ... \n", + "4267 N.S. N.S. pl_dd_Smed_v4_2312_0_1;sc_Smp_144570 \n", + "1896 N.S. N.S. pl_dd_Smed_v4_4613_0_1;sc_Smp_303490 \n", + "9658 N.S. N.S. pl_dd_Smed_v4_13295_0_1;sc_Smp_340320 \n", + "9657 N.S. N.S. pl_dd_Smed_v4_13295_0_1;sc_Smp_004730 \n", + "15097 N.S. N.S. pl_dd_Smed_v4_14363_0_1;sc_Smp_142860 \n", "\n", " pl/hy sc/hy \\\n", - "717 pl_dd_Smed_v4_1161_0_1;hy_t1091aep sc_Smp_345440;hy_t1091aep \n", - "2063 pl_dd_Smed_v4_1161_0_1;hy_t12725aep sc_Smp_345440;hy_t12725aep \n", - "15206 pl_dd_Smed_v4_17069_0_1;hy_t3456aep sc_Smp_344820;hy_t3456aep \n", - "15207 pl_dd_Smed_v4_17069_0_1;hy_t3456aep sc_Smp_345440;hy_t3456aep \n", - "8987 pl_dd_Smed_v4_13487_0_1;hy_t21554aep sc_Smp_145140;hy_t21554aep \n", + "6295 pl_dd_Smed_v4_5055_0_1;hy_t1909aep sc_Smp_068950;hy_t1909aep \n", + "6296 pl_dd_Smed_v4_5055_0_1;hy_t1909aep sc_Smp_212260;hy_t1909aep \n", + "921 pl_dd_Smed_v4_3186_0_1;hy_t11687aep sc_Smp_045040;hy_t11687aep \n", + "12146 pl_dd_Smed_v4_1807_0_1;hy_t30876aep sc_Smp_167200;hy_t30876aep \n", + "18494 pl_dd_Smed_v4_1535_0_1;hy_t9175aep sc_Smp_103710;hy_t9175aep \n", "... ... ... \n", - "16405 pl_dd_Smed_v4_17162_0_1;hy_t36240aep sc_Smp_088920;hy_t36240aep \n", - "9197 pl_dd_Smed_v4_13704_0_1;hy_t2168aep sc_Smp_342580;hy_t2168aep \n", - "9198 pl_dd_Smed_v4_29462_0_1;hy_t2168aep sc_Smp_342580;hy_t2168aep \n", - "8682 pl_dd_Smed_v4_1000_0_1;hy_t2114aep sc_Smp_099030;hy_t2114aep \n", - "8679 pl_dd_Smed_v4_1000_0_1;hy_t2114aep sc_Smp_018290;hy_t2114aep \n", - "\n", - " pl/sc corr ... sc/hy corr pl/sc type pl/hy type sc/hy type \\\n", - "717 0.868737 ... 0.828863 ortholog substitution substitution \n", - "2063 0.868737 ... 0.790684 ortholog substitution substitution \n", - "15206 0.843316 ... 0.817948 ortholog substitution substitution \n", - "15207 0.899836 ... 0.884831 substitution substitution substitution \n", - "8987 0.833242 ... 0.805404 ortholog substitution substitution \n", - "... ... ... ... ... ... ... \n", - "16405 0.301734 ... 0.462701 substitution ortholog substitution \n", - "9197 0.301053 ... 0.300797 ortholog substitution substitution \n", - "9198 0.530394 ... 0.300797 ortholog substitution substitution \n", - "8682 0.669682 ... 0.405317 ortholog ortholog ortholog \n", - "8679 0.766868 ... 0.494589 substitution ortholog substitution \n", - "\n", - " #orthologs #substitutions min_corr pl cell type sc cell type \\\n", - "717 1 2 0.795255 Muscle: 14 Muscle \n", - "2063 1 2 0.790684 Muscle: 14 Muscle \n", - "15206 1 2 0.786597 Muscle: 13 Muscle \n", - "15207 0 3 0.786597 Muscle: 13 Muscle \n", - "8987 1 2 0.749112 Muscle: 14 Muscle \n", - "... ... ... ... ... ... \n", - "16405 1 2 0.301734 Neural: 33 Flame cells \n", - "9197 1 2 0.300797 Neural: 9 Neural \n", - "9198 1 2 0.300797 Neural: 8 Neural \n", - "8682 3 0 0.300250 Neoblast: 0 Neoblast \n", - "8679 1 2 0.300250 Neoblast: 0 Neoblast \n", - "\n", - " hy cell type \n", - "717 enEp_tent \n", - "2063 enEp_tent(pd) \n", - "15206 enEp_tent(pd) \n", - "15207 enEp_tent(pd) \n", - "8987 enEp_tent \n", - "... ... \n", - "16405 i_mgl \n", - "9197 i_nc6 \n", - "9198 i_nc6 \n", - "8682 i_SC \n", - "8679 i_SC \n", - "\n", - "[416 rows x 21 columns]" + "4267 pl_dd_Smed_v4_2312_0_1;hy_t16585aep sc_Smp_144570;hy_t16585aep \n", + "1896 pl_dd_Smed_v4_4613_0_1;hy_t12738aep sc_Smp_303490;hy_t12738aep \n", + "9658 pl_dd_Smed_v4_13295_0_1;hy_t24627aep sc_Smp_340320;hy_t24627aep \n", + "9657 pl_dd_Smed_v4_13295_0_1;hy_t24627aep sc_Smp_004730;hy_t24627aep \n", + "15097 pl_dd_Smed_v4_14363_0_1;hy_t36047aep sc_Smp_142860;hy_t36047aep \n", + "\n", + " pl/sc corr ... sc/hy corr pl/sc type pl/hy type sc/hy type #orthologs \\\n", + "6295 0.791476 ... 0.773475 ortholog ortholog ortholog 3 \n", + "6296 0.744294 ... 0.793425 ortholog ortholog ortholog 3 \n", + "921 0.734138 ... 0.719196 ortholog ortholog ortholog 3 \n", + "12146 0.74404 ... 0.712481 ortholog ortholog ortholog 3 \n", + "18494 0.633695 ... 0.688774 ortholog ortholog ortholog 3 \n", + "... ... ... ... ... ... ... ... \n", + "4267 0.313954 ... 0.373923 ortholog ortholog ortholog 3 \n", + "1896 0.310063 ... 0.314676 ortholog ortholog ortholog 3 \n", + "9658 0.345553 ... 0.514597 ortholog ortholog ortholog 3 \n", + "9657 0.437183 ... 0.319902 ortholog ortholog ortholog 3 \n", + "15097 0.598461 ... 0.305256 ortholog ortholog ortholog 3 \n", + "\n", + " #substitutions min_corr pl cell type sc cell type hy cell type \n", + "6295 0 0.75173 Neoblast: 0 Neoblast i_nb1 \n", + "6296 0 0.744294 Neoblast: 0 Neoblast i_nb1 \n", + "921 0 0.719196 Neoblast: 0 Neoblast i_SC \n", + "12146 0 0.693079 Neoblast: 0 Neoblast i_SC \n", + "18494 0 0.623122 Neoblast: 0 Neoblast i_SC \n", + "... ... ... ... ... ... \n", + "4267 0 0.313954 Neoblast: 0 Flame cells i_SC \n", + "1896 0 0.310063 Neoblast: 0 Neoblast i_SC \n", + "9658 0 0.305524 Neural: 23 Neural i_nc1 \n", + "9657 0 0.305524 Neural: 23 Neural_KK7 i_nc1 \n", + "15097 0 0.305256 Neural: 21 Neural i_nem \n", + "\n", + "[69 rows x 21 columns]" ] }, - "execution_count": 43, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -9536,16 +7393,27 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 43, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/alect/Desktop/samap/src/samap/analysis/scores.py:349: FutureWarning:\n", + "\n", + "Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`\n", + "\n" + ] + } + ], "source": [ "ortholog_pairs = convert_eggnog_to_homologs(sm,EGGs,og_key='eggNOG_OGs',taxon=33208) #33208 is the taxon code for Metazoans" ] }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 44, "metadata": {}, "outputs": [], "source": [ @@ -9557,7 +7425,7 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 45, "metadata": {}, "outputs": [ { @@ -9606,7 +7474,7 @@ " \n", " \n", " \n", - " 13061\n", + " 12135\n", " pl_dd_Smed_v4_373_0_1\n", " sc_Smp_087250\n", " hy_t30505aep\n", @@ -9616,69 +7484,21 @@ " pl_dd_Smed_v4_373_0_1;sc_Smp_087250\n", " pl_dd_Smed_v4_373_0_1;hy_t30505aep\n", " sc_Smp_087250;hy_t30505aep\n", - " 0.922724\n", + " 0.921108\n", " ...\n", - " 0.857375\n", + " 0.852936\n", " ortholog\n", " ortholog\n", " ortholog\n", " 3\n", " 0\n", - " 0.857375\n", + " 0.852936\n", " Muscle: 13\n", " Muscle\n", " enEp_tent(pd)\n", " \n", " \n", - " 3474\n", - " pl_dd_Smed_v4_2197_0_1\n", - " sc_Smp_164590\n", - " hy_t14477aep\n", - " pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1...\n", - " pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1...\n", - " N.S.\n", - " pl_dd_Smed_v4_2197_0_1;sc_Smp_164590\n", - " pl_dd_Smed_v4_2197_0_1;hy_t14477aep\n", - " sc_Smp_164590;hy_t14477aep\n", - " 0.97055\n", - " ...\n", - " 0.926952\n", - " substitution\n", - " substitution\n", - " ortholog\n", - " 1\n", - " 2\n", - " 0.830880\n", - " Muscle: 13;Muscle: 14;Muscle: 7\n", - " Muscle\n", - " enEp_SC1;enEp_tent\n", - " \n", - " \n", - " 3472\n", - " pl_dd_Smed_v4_2197_0_1\n", - " sc_Smp_123830\n", - " hy_t14477aep\n", - " pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1...\n", - " pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1...\n", - " N.S.\n", - " pl_dd_Smed_v4_2197_0_1;sc_Smp_123830\n", - " pl_dd_Smed_v4_2197_0_1;hy_t14477aep\n", - " sc_Smp_123830;hy_t14477aep\n", - " 0.964259\n", - " ...\n", - " 0.923554\n", - " substitution\n", - " substitution\n", - " ortholog\n", - " 1\n", - " 2\n", - " 0.830880\n", - " Muscle: 13;Muscle: 14;Muscle: 7\n", - " Muscle\n", - " enEp_SC1;enEp_tent\n", - " \n", - " \n", - " 80\n", + " 61\n", " pl_dd_Smed_v4_1920_0_1\n", " sc_Smp_046500\n", " hy_t10355aep\n", @@ -9688,21 +7508,21 @@ " pl_dd_Smed_v4_1920_0_1;sc_Smp_046500\n", " pl_dd_Smed_v4_1920_0_1;hy_t10355aep\n", " sc_Smp_046500;hy_t10355aep\n", - " 0.858101\n", + " 0.86289\n", " ...\n", - " 0.897937\n", + " 0.895295\n", " ortholog\n", " ortholog\n", " ortholog\n", " 3\n", " 0\n", - " 0.829985\n", + " 0.824399\n", " Neoblast: 0\n", " Neoblast\n", " i_SC;i_nb1\n", " \n", " \n", - " 17728\n", + " 16333\n", " pl_dd_Smed_v4_3457_0_1\n", " sc_Smp_347610\n", " hy_t5285aep\n", @@ -9712,20 +7532,68 @@ " pl_dd_Smed_v4_3457_0_1;sc_Smp_347610\n", " pl_dd_Smed_v4_3457_0_1;hy_t5285aep\n", " sc_Smp_347610;hy_t5285aep\n", - " 0.928466\n", + " 0.927841\n", " ...\n", - " 0.836483\n", + " 0.832701\n", " ortholog\n", " ortholog\n", " ortholog\n", " 3\n", " 0\n", - " 0.821962\n", + " 0.822859\n", " Muscle: 13\n", " Muscle\n", " enEp_tent\n", " \n", " \n", + " 6322\n", + " pl_dd_Smed_v4_1651_0_1\n", + " sc_Smp_009030\n", + " hy_t19180aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_1651_0_1;sc_Smp_009030\n", + " pl_dd_Smed_v4_1651_0_1;hy_t19180aep\n", + " sc_Smp_009030;hy_t19180aep\n", + " 0.842062\n", + " ...\n", + " 0.865026\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.798015\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_SC;i_nb1\n", + " \n", + " \n", + " 12101\n", + " pl_dd_Smed_v4_5663_0_1\n", + " sc_Smp_058320\n", + " hy_t30411aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_5663_0_1;sc_Smp_058320\n", + " pl_dd_Smed_v4_5663_0_1;hy_t30411aep\n", + " sc_Smp_058320;hy_t30411aep\n", + " 0.824536\n", + " ...\n", + " 0.796064\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", + " 3\n", + " 0\n", + " 0.796064\n", + " Neoblast: 0\n", + " Neoblast\n", + " i_mgl\n", + " \n", + " \n", " ...\n", " ...\n", " ...\n", @@ -9750,252 +7618,213 @@ " ...\n", " \n", " \n", - " 13067\n", - " pl_dd_Smed_v4_11187_0_1\n", - " sc_Smp_144210\n", - " hy_t30817aep\n", - " pl_dd_Smed_v4_17081_0_1;pl_dd_Smed_v4_8041_0_1\n", - " pl_dd_Smed_v4_12031_0_1;pl_dd_Smed_v4_18706_0_...\n", - " hy_t28257aep;hy_t30881aep;sc_Smp_342190\n", - " pl_dd_Smed_v4_11187_0_1;sc_Smp_144210\n", - " pl_dd_Smed_v4_11187_0_1;hy_t30817aep\n", - " sc_Smp_144210;hy_t30817aep\n", - " 0.305082\n", + " 17942\n", + " pl_dd_Smed_v4_8441_0_1\n", + " sc_Smp_343530\n", + " hy_t8246aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_8441_0_1;sc_Smp_343530\n", + " pl_dd_Smed_v4_8441_0_1;hy_t8246aep\n", + " sc_Smp_343530;hy_t8246aep\n", + " 0.416922\n", " ...\n", - " 0.344571\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.555327\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.300050\n", - " Neural: 20\n", - " Neural\n", - " enEp_SC3\n", + " 0\n", + " 0.301228\n", + " Neural: 34\n", + " Flame cells\n", + " i_mgl\n", " \n", " \n", - " 18368\n", - " pl_dd_Smed_v4_5643_0_1\n", - " sc_Smp_088920\n", - " hy_t588aep\n", - " pl_dd_Smed_v4_13910_0_1;pl_dd_Smed_v4_17069_0_...\n", - " hy_t13172aep;hy_t17914aep;pl_dd_Smed_v4_1953_0...\n", - " hy_t12295aep;hy_t12986aep;hy_t17342aep;hy_t202...\n", - " pl_dd_Smed_v4_5643_0_1;sc_Smp_088920\n", - " pl_dd_Smed_v4_5643_0_1;hy_t588aep\n", - " sc_Smp_088920;hy_t588aep\n", - " 0.300039\n", + " 13925\n", + " pl_dd_Smed_v4_1106_0_1\n", + " sc_Smp_016600\n", + " hy_t3448aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_1106_0_1;sc_Smp_016600\n", + " pl_dd_Smed_v4_1106_0_1;hy_t3448aep\n", + " sc_Smp_016600;hy_t3448aep\n", + " 0.467001\n", " ...\n", - " 0.321113\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.300983\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.300039\n", - " Epidermal: 2\n", + " 0\n", + " 0.300983\n", + " Cathepsin+ cells: 17\n", " Flame cells\n", - " ecEp_bat1(mp)\n", + " enEp_SC1\n", " \n", " \n", - " 2472\n", - " pl_dd_Smed_v4_10731_0_1\n", - " sc_Smp_011660\n", - " hy_t13961aep\n", - " pl_dd_Smed_v4_7358_0_1\n", - " hy_t5729aep\n", - " hy_t5660aep\n", - " pl_dd_Smed_v4_10731_0_1;sc_Smp_011660\n", - " pl_dd_Smed_v4_10731_0_1;hy_t13961aep\n", - " sc_Smp_011660;hy_t13961aep\n", - " 0.300015\n", + " 13926\n", + " pl_dd_Smed_v4_3514_0_1\n", + " sc_Smp_016600\n", + " hy_t3448aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_3514_0_1;sc_Smp_016600\n", + " pl_dd_Smed_v4_3514_0_1;hy_t3448aep\n", + " sc_Smp_016600;hy_t3448aep\n", + " 0.462381\n", " ...\n", - " 0.336506\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.300983\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.300015\n", - " Neural: 33\n", - " Neural\n", - " ecEp_bd\n", + " 0\n", + " 0.300983\n", + " Cathepsin+ cells: 39\n", + " Flame cells\n", + " enEp_SC1\n", " \n", " \n", - " 2259\n", - " pl_dd_Smed_v4_10731_0_1\n", - " sc_Smp_011660\n", - " hy_t13280aep\n", - " pl_dd_Smed_v4_7358_0_1\n", - " hy_t5729aep;pl_dd_Smed_v4_13910_0_1;pl_dd_Smed...\n", - " hy_t5660aep;sc_Smp_121780;sc_Smp_126240;sc_Smp...\n", - " pl_dd_Smed_v4_10731_0_1;sc_Smp_011660\n", - " pl_dd_Smed_v4_10731_0_1;hy_t13280aep\n", - " sc_Smp_011660;hy_t13280aep\n", - " 0.300015\n", + " 1665\n", + " pl_dd_Smed_v4_3170_0_1\n", + " sc_Smp_315900\n", + " hy_t12630aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_3170_0_1;sc_Smp_315900\n", + " pl_dd_Smed_v4_3170_0_1;hy_t12630aep\n", + " sc_Smp_315900;hy_t12630aep\n", + " 0.553842\n", " ...\n", - " 0.317537\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.362995\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.300015\n", - " Neural: 33\n", - " Neural\n", - " ecEp_SC2;ecEp_SC3;ecEp_bat2(mp);ecEp_head\n", + " 0\n", + " 0.300811\n", + " Muscle: 14\n", + " Muscle\n", + " ecEp_bat2(mp)\n", " \n", " \n", - " 13899\n", - " pl_dd_Smed_v4_10731_0_1\n", - " sc_Smp_011660\n", - " hy_t32180aep\n", - " pl_dd_Smed_v4_7358_0_1\n", - " hy_t5729aep\n", - " hy_t5660aep\n", - " pl_dd_Smed_v4_10731_0_1;sc_Smp_011660\n", - " pl_dd_Smed_v4_10731_0_1;hy_t32180aep\n", - " sc_Smp_011660;hy_t32180aep\n", - " 0.300015\n", + " 1666\n", + " pl_dd_Smed_v4_3170_0_1\n", + " sc_Smp_343120\n", + " hy_t12630aep\n", + " N.S.\n", + " N.S.\n", + " N.S.\n", + " pl_dd_Smed_v4_3170_0_1;sc_Smp_343120\n", + " pl_dd_Smed_v4_3170_0_1;hy_t12630aep\n", + " sc_Smp_343120;hy_t12630aep\n", + " 0.632875\n", " ...\n", - " 0.355111\n", - " substitution\n", - " substitution\n", - " substitution\n", - " 0\n", + " 0.439657\n", + " ortholog\n", + " ortholog\n", + " ortholog\n", " 3\n", - " 0.300015\n", - " Neural: 33\n", - " Neural\n", - " ecEp_head\n", + " 0\n", + " 0.300811\n", + " Muscle: 14\n", + " Muscle\n", + " ecEp_bat2(mp)\n", " \n", " \n", "\n", - "

5612 rows × 21 columns

\n", + "

921 rows × 21 columns

\n", "" ], "text/plain": [ - " pl gene sc gene hy gene \\\n", - "13061 pl_dd_Smed_v4_373_0_1 sc_Smp_087250 hy_t30505aep \n", - "3474 pl_dd_Smed_v4_2197_0_1 sc_Smp_164590 hy_t14477aep \n", - "3472 pl_dd_Smed_v4_2197_0_1 sc_Smp_123830 hy_t14477aep \n", - "80 pl_dd_Smed_v4_1920_0_1 sc_Smp_046500 hy_t10355aep \n", - "17728 pl_dd_Smed_v4_3457_0_1 sc_Smp_347610 hy_t5285aep \n", - "... ... ... ... \n", - "13067 pl_dd_Smed_v4_11187_0_1 sc_Smp_144210 hy_t30817aep \n", - "18368 pl_dd_Smed_v4_5643_0_1 sc_Smp_088920 hy_t588aep \n", - "2472 pl_dd_Smed_v4_10731_0_1 sc_Smp_011660 hy_t13961aep \n", - "2259 pl_dd_Smed_v4_10731_0_1 sc_Smp_011660 hy_t13280aep \n", - "13899 pl_dd_Smed_v4_10731_0_1 sc_Smp_011660 hy_t32180aep \n", - "\n", - " pl/sc subbed \\\n", - "13061 N.S. \n", - "3474 pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1... \n", - "3472 pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1... \n", - "80 N.S. \n", - "17728 N.S. \n", - "... ... \n", - "13067 pl_dd_Smed_v4_17081_0_1;pl_dd_Smed_v4_8041_0_1 \n", - "18368 pl_dd_Smed_v4_13910_0_1;pl_dd_Smed_v4_17069_0_... \n", - "2472 pl_dd_Smed_v4_7358_0_1 \n", - "2259 pl_dd_Smed_v4_7358_0_1 \n", - "13899 pl_dd_Smed_v4_7358_0_1 \n", - "\n", - " pl/hy subbed \\\n", - "13061 N.S. \n", - "3474 pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1... \n", - "3472 pl_dd_Smed_v4_3747_0_1;pl_dd_Smed_v4_59090_0_1... \n", - "80 N.S. \n", - "17728 N.S. \n", - "... ... \n", - "13067 pl_dd_Smed_v4_12031_0_1;pl_dd_Smed_v4_18706_0_... \n", - "18368 hy_t13172aep;hy_t17914aep;pl_dd_Smed_v4_1953_0... \n", - "2472 hy_t5729aep \n", - "2259 hy_t5729aep;pl_dd_Smed_v4_13910_0_1;pl_dd_Smed... \n", - "13899 hy_t5729aep \n", - "\n", - " sc/hy subbed \\\n", - "13061 N.S. \n", - "3474 N.S. \n", - "3472 N.S. \n", - "80 N.S. \n", - "17728 N.S. \n", - "... ... \n", - "13067 hy_t28257aep;hy_t30881aep;sc_Smp_342190 \n", - "18368 hy_t12295aep;hy_t12986aep;hy_t17342aep;hy_t202... \n", - "2472 hy_t5660aep \n", - "2259 hy_t5660aep;sc_Smp_121780;sc_Smp_126240;sc_Smp... \n", - "13899 hy_t5660aep \n", - "\n", - " pl/sc \\\n", - "13061 pl_dd_Smed_v4_373_0_1;sc_Smp_087250 \n", - "3474 pl_dd_Smed_v4_2197_0_1;sc_Smp_164590 \n", - "3472 pl_dd_Smed_v4_2197_0_1;sc_Smp_123830 \n", - "80 pl_dd_Smed_v4_1920_0_1;sc_Smp_046500 \n", - "17728 pl_dd_Smed_v4_3457_0_1;sc_Smp_347610 \n", - "... ... \n", - "13067 pl_dd_Smed_v4_11187_0_1;sc_Smp_144210 \n", - "18368 pl_dd_Smed_v4_5643_0_1;sc_Smp_088920 \n", - "2472 pl_dd_Smed_v4_10731_0_1;sc_Smp_011660 \n", - "2259 pl_dd_Smed_v4_10731_0_1;sc_Smp_011660 \n", - "13899 pl_dd_Smed_v4_10731_0_1;sc_Smp_011660 \n", + " pl gene sc gene hy gene pl/sc subbed \\\n", + "12135 pl_dd_Smed_v4_373_0_1 sc_Smp_087250 hy_t30505aep N.S. \n", + "61 pl_dd_Smed_v4_1920_0_1 sc_Smp_046500 hy_t10355aep N.S. \n", + "16333 pl_dd_Smed_v4_3457_0_1 sc_Smp_347610 hy_t5285aep N.S. \n", + "6322 pl_dd_Smed_v4_1651_0_1 sc_Smp_009030 hy_t19180aep N.S. \n", + "12101 pl_dd_Smed_v4_5663_0_1 sc_Smp_058320 hy_t30411aep N.S. \n", + "... ... ... ... ... \n", + "17942 pl_dd_Smed_v4_8441_0_1 sc_Smp_343530 hy_t8246aep N.S. \n", + "13925 pl_dd_Smed_v4_1106_0_1 sc_Smp_016600 hy_t3448aep N.S. \n", + "13926 pl_dd_Smed_v4_3514_0_1 sc_Smp_016600 hy_t3448aep N.S. \n", + "1665 pl_dd_Smed_v4_3170_0_1 sc_Smp_315900 hy_t12630aep N.S. \n", + "1666 pl_dd_Smed_v4_3170_0_1 sc_Smp_343120 hy_t12630aep N.S. \n", + "\n", + " pl/hy subbed sc/hy subbed pl/sc \\\n", + "12135 N.S. N.S. pl_dd_Smed_v4_373_0_1;sc_Smp_087250 \n", + "61 N.S. N.S. pl_dd_Smed_v4_1920_0_1;sc_Smp_046500 \n", + "16333 N.S. N.S. pl_dd_Smed_v4_3457_0_1;sc_Smp_347610 \n", + "6322 N.S. N.S. pl_dd_Smed_v4_1651_0_1;sc_Smp_009030 \n", + "12101 N.S. N.S. pl_dd_Smed_v4_5663_0_1;sc_Smp_058320 \n", + "... ... ... ... \n", + "17942 N.S. N.S. pl_dd_Smed_v4_8441_0_1;sc_Smp_343530 \n", + "13925 N.S. N.S. pl_dd_Smed_v4_1106_0_1;sc_Smp_016600 \n", + "13926 N.S. N.S. pl_dd_Smed_v4_3514_0_1;sc_Smp_016600 \n", + "1665 N.S. N.S. pl_dd_Smed_v4_3170_0_1;sc_Smp_315900 \n", + "1666 N.S. N.S. pl_dd_Smed_v4_3170_0_1;sc_Smp_343120 \n", + "\n", + " pl/hy sc/hy \\\n", + "12135 pl_dd_Smed_v4_373_0_1;hy_t30505aep sc_Smp_087250;hy_t30505aep \n", + "61 pl_dd_Smed_v4_1920_0_1;hy_t10355aep sc_Smp_046500;hy_t10355aep \n", + "16333 pl_dd_Smed_v4_3457_0_1;hy_t5285aep sc_Smp_347610;hy_t5285aep \n", + "6322 pl_dd_Smed_v4_1651_0_1;hy_t19180aep sc_Smp_009030;hy_t19180aep \n", + "12101 pl_dd_Smed_v4_5663_0_1;hy_t30411aep sc_Smp_058320;hy_t30411aep \n", + "... ... ... \n", + "17942 pl_dd_Smed_v4_8441_0_1;hy_t8246aep sc_Smp_343530;hy_t8246aep \n", + "13925 pl_dd_Smed_v4_1106_0_1;hy_t3448aep sc_Smp_016600;hy_t3448aep \n", + "13926 pl_dd_Smed_v4_3514_0_1;hy_t3448aep sc_Smp_016600;hy_t3448aep \n", + "1665 pl_dd_Smed_v4_3170_0_1;hy_t12630aep sc_Smp_315900;hy_t12630aep \n", + "1666 pl_dd_Smed_v4_3170_0_1;hy_t12630aep sc_Smp_343120;hy_t12630aep \n", + "\n", + " pl/sc corr ... sc/hy corr pl/sc type pl/hy type sc/hy type #orthologs \\\n", + "12135 0.921108 ... 0.852936 ortholog ortholog ortholog 3 \n", + "61 0.86289 ... 0.895295 ortholog ortholog ortholog 3 \n", + "16333 0.927841 ... 0.832701 ortholog ortholog ortholog 3 \n", + "6322 0.842062 ... 0.865026 ortholog ortholog ortholog 3 \n", + "12101 0.824536 ... 0.796064 ortholog ortholog ortholog 3 \n", + "... ... ... ... ... ... ... ... \n", + "17942 0.416922 ... 0.555327 ortholog ortholog ortholog 3 \n", + "13925 0.467001 ... 0.300983 ortholog ortholog ortholog 3 \n", + "13926 0.462381 ... 0.300983 ortholog ortholog ortholog 3 \n", + "1665 0.553842 ... 0.362995 ortholog ortholog ortholog 3 \n", + "1666 0.632875 ... 0.439657 ortholog ortholog ortholog 3 \n", + "\n", + " #substitutions min_corr pl cell type sc cell type \\\n", + "12135 0 0.852936 Muscle: 13 Muscle \n", + "61 0 0.824399 Neoblast: 0 Neoblast \n", + "16333 0 0.822859 Muscle: 13 Muscle \n", + "6322 0 0.798015 Neoblast: 0 Neoblast \n", + "12101 0 0.796064 Neoblast: 0 Neoblast \n", + "... ... ... ... ... \n", + "17942 0 0.301228 Neural: 34 Flame cells \n", + "13925 0 0.300983 Cathepsin+ cells: 17 Flame cells \n", + "13926 0 0.300983 Cathepsin+ cells: 39 Flame cells \n", + "1665 0 0.300811 Muscle: 14 Muscle \n", + "1666 0 0.300811 Muscle: 14 Muscle \n", "\n", - " pl/hy sc/hy \\\n", - "13061 pl_dd_Smed_v4_373_0_1;hy_t30505aep sc_Smp_087250;hy_t30505aep \n", - "3474 pl_dd_Smed_v4_2197_0_1;hy_t14477aep sc_Smp_164590;hy_t14477aep \n", - "3472 pl_dd_Smed_v4_2197_0_1;hy_t14477aep sc_Smp_123830;hy_t14477aep \n", - "80 pl_dd_Smed_v4_1920_0_1;hy_t10355aep sc_Smp_046500;hy_t10355aep \n", - "17728 pl_dd_Smed_v4_3457_0_1;hy_t5285aep sc_Smp_347610;hy_t5285aep \n", - "... ... ... \n", - "13067 pl_dd_Smed_v4_11187_0_1;hy_t30817aep sc_Smp_144210;hy_t30817aep \n", - "18368 pl_dd_Smed_v4_5643_0_1;hy_t588aep sc_Smp_088920;hy_t588aep \n", - "2472 pl_dd_Smed_v4_10731_0_1;hy_t13961aep sc_Smp_011660;hy_t13961aep \n", - "2259 pl_dd_Smed_v4_10731_0_1;hy_t13280aep sc_Smp_011660;hy_t13280aep \n", - "13899 pl_dd_Smed_v4_10731_0_1;hy_t32180aep sc_Smp_011660;hy_t32180aep \n", - "\n", - " pl/sc corr ... sc/hy corr pl/sc type pl/hy type sc/hy type \\\n", - "13061 0.922724 ... 0.857375 ortholog ortholog ortholog \n", - "3474 0.97055 ... 0.926952 substitution substitution ortholog \n", - "3472 0.964259 ... 0.923554 substitution substitution ortholog \n", - "80 0.858101 ... 0.897937 ortholog ortholog ortholog \n", - "17728 0.928466 ... 0.836483 ortholog ortholog ortholog \n", - "... ... ... ... ... ... ... \n", - "13067 0.305082 ... 0.344571 substitution substitution substitution \n", - "18368 0.300039 ... 0.321113 substitution substitution substitution \n", - "2472 0.300015 ... 0.336506 substitution substitution substitution \n", - "2259 0.300015 ... 0.317537 substitution substitution substitution \n", - "13899 0.300015 ... 0.355111 substitution substitution substitution \n", - "\n", - " #orthologs #substitutions min_corr pl cell type \\\n", - "13061 3 0 0.857375 Muscle: 13 \n", - "3474 1 2 0.830880 Muscle: 13;Muscle: 14;Muscle: 7 \n", - "3472 1 2 0.830880 Muscle: 13;Muscle: 14;Muscle: 7 \n", - "80 3 0 0.829985 Neoblast: 0 \n", - "17728 3 0 0.821962 Muscle: 13 \n", - "... ... ... ... ... \n", - "13067 0 3 0.300050 Neural: 20 \n", - "18368 0 3 0.300039 Epidermal: 2 \n", - "2472 0 3 0.300015 Neural: 33 \n", - "2259 0 3 0.300015 Neural: 33 \n", - "13899 0 3 0.300015 Neural: 33 \n", - "\n", - " sc cell type hy cell type \n", - "13061 Muscle enEp_tent(pd) \n", - "3474 Muscle enEp_SC1;enEp_tent \n", - "3472 Muscle enEp_SC1;enEp_tent \n", - "80 Neoblast i_SC;i_nb1 \n", - "17728 Muscle enEp_tent \n", - "... ... ... \n", - "13067 Neural enEp_SC3 \n", - "18368 Flame cells ecEp_bat1(mp) \n", - "2472 Neural ecEp_bd \n", - "2259 Neural ecEp_SC2;ecEp_SC3;ecEp_bat2(mp);ecEp_head \n", - "13899 Neural ecEp_head \n", - "\n", - "[5612 rows x 21 columns]" + " hy cell type \n", + "12135 enEp_tent(pd) \n", + "61 i_SC;i_nb1 \n", + "16333 enEp_tent \n", + "6322 i_SC;i_nb1 \n", + "12101 i_mgl \n", + "... ... \n", + "17942 i_mgl \n", + "13925 enEp_SC1 \n", + "13926 enEp_SC1 \n", + "1665 ecEp_bat2(mp) \n", + "1666 ecEp_bat2(mp) \n", + "\n", + "[921 rows x 21 columns]" ] }, - "execution_count": 46, + "execution_count": 45, "metadata": {}, "output_type": "execute_result" } @@ -10019,235 +7848,212 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 46, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "Finding enriched gene pairs...\n", - "Finding cluster-specific markers in pl:cluster.\n", - "Finding cluster-specific markers in sc:tissue.\n", - "Finding cluster-specific markers in hy:Cluster.\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 3\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 35\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC2 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 11\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 35\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 25\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 37\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Protonephridia: 40\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Epidermal: 24\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 25\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 27\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 37\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Protonephridia: 40\n", - "Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_bd to pl;Epidermal: 11\n", - "Calculating gene pairs for the mapping: hy;ecEp_bd to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_bd to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 11\n", - "Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_head to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;ecEp_head to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 35\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to pl;Epidermal: 2\n", - "Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 10\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 15\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 17\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 28\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 31\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 39\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 41\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Intestine: 30\n", - "Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 17\n", - "Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 41\n", - "Calculating gene pairs for the mapping: hy;enEp_SC2 to sc;Intestine\n", - "Calculating gene pairs for the mapping: hy;enEp_SC2 to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_SC3 to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 13\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_head to pl;Muscle: 7\n", - "Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to pl;Muscle: 7\n", - "Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_nem2(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 13\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 16\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 7\n", - "Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 13\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 14\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 16\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 7\n", - "Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Cathepsin+ cells: 4\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Intestine: 6\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 5\n", - "Calculating gene pairs for the mapping: hy;i_SC to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_fmgl1 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_gmgc to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_gmgc to pl;Neural: 32\n", - "Calculating gene pairs for the mapping: hy;i_gmgc to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_mgl to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_mgl to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_mgl to pl;Neural: 20\n", - "Calculating gene pairs for the mapping: hy;i_mgl to pl;Neural: 33\n", - "Calculating gene pairs for the mapping: hy;i_mgl to sc;Flame cells\n", - "Calculating gene pairs for the mapping: hy;i_mgl to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 5\n", - "Calculating gene pairs for the mapping: hy;i_nb1 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb2 to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nb2 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nb2 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_nb3 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_nb3 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nb3 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_nb4 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc1 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc2 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc2 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 23\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc3 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc4 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_nc4 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc4 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc5 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_nc5 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 23\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 36\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc6 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc7 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc7 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc8 to pl;Neural: 1\n" - ] - }, - { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Calculating gene pairs for the mapping: hy;i_nc8 to pl;Neural: 8\n", - "Calculating gene pairs for the mapping: hy;i_nc8 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_nc8 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Intestine: 6\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Neoblast: 0\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Neoblast: 22\n", - "Calculating gene pairs for the mapping: hy;i_nc_gc_prog to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nc_prog to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_nc_prog to sc;Neoblast\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 18\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 20\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 21\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 23\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 33\n", - "Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 9\n", - "Calculating gene pairs for the mapping: hy;i_nem to sc;Flame cells\n", - "Calculating gene pairs for the mapping: hy;i_nem to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_smgc1 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Neural\n", - "Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_smgc2 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 32\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 36\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Parapharyngeal: 38\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Tegument\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 1\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 32\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: hy;nan to pl;Muscle: 7\n", - "Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 10 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 15 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Intestine\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 28 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 31 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 39 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Intestine\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Flame cells\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument\n", - "Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Intestine: 19 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Intestine: 19 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Intestine: 30 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Tegument_prog\n", - "Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 0 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 22 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neoblast: 5 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Flame cells\n", - "Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Flame cells\n", - "Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Flame cells\n", - "Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 23 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 32 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Neural: 32 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 33 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 34 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Neural: 8 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Neural: 9 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 12 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Cathepsin\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Neural\n", - "Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Pharynx: 25 to sc;Neoblast\n", - "Calculating gene pairs for the mapping: pl;Pharynx: 25 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Pharynx: 27 to sc;Flame cells\n", - "Calculating gene pairs for the mapping: pl;Protonephridia: 26 to sc;Parenchymal\n", - "Calculating gene pairs for the mapping: pl;Protonephridia: 29 to sc;Flame cells\n" + "INFO: Finding enriched gene pairs...\n", + "INFO: Finding cluster-specific markers in pl:cluster.\n", + "INFO: Finding cluster-specific markers in sc:tissue.\n", + "INFO: Finding cluster-specific markers in hy:Cluster.\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC2 to pl;Epidermal: 35\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC2 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 11\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to pl;Epidermal: 35\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_SC3 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 25\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Pharynx: 37\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to pl;Protonephridia: 40\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat1(mp) to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Epidermal: 24\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 25\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 27\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Pharynx: 37\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to pl;Protonephridia: 40\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bat2(mp) to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_bd to pl;Epidermal: 11\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 11\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_head to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to pl;Epidermal: 35\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem1(pd) to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to pl;Epidermal: 2\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;ecEp_nem2(id) to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 10\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 15\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 17\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 28\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 31\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 39\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Cathepsin+ cells: 41\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to pl;Intestine: 30\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC1 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 10\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 17\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 39\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Cathepsin+ cells: 41\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to pl;Intestine: 30\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC2 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_SC3 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 13\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_foot to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_head to pl;Muscle: 7\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_head to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to pl;Muscle: 7\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_nem1(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_nem2(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 13\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 16\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to pl;Muscle: 7\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 13\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 14\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to pl;Muscle: 16\n", + "INFO: Calculating gene pairs for the mapping: hy;enEp_tent(pd) to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Intestine: 6\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 22\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to pl;Neoblast: 5\n", + "INFO: Calculating gene pairs for the mapping: hy;i_SC to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl1 to pl;Neoblast: 22\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl1 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_fmgl2_nurse to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_gmgc to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_gmgc to pl;Neural: 32\n", + "INFO: Calculating gene pairs for the mapping: hy;i_gmgc to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: hy;i_gmgc to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: hy;i_mgl to pl;Neural: 20\n", + "INFO: Calculating gene pairs for the mapping: hy;i_mgl to pl;Neural: 33\n", + "INFO: Calculating gene pairs for the mapping: hy;i_mgl to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: hy;i_mgl to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 22\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to pl;Neoblast: 5\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb1 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb2 to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb2 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb2 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb3 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb3 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb3 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb4 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb4 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nb4 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 23\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to pl;Neural: 9\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc1 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc2 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc2 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc3 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc3 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc4 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc4 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc5 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc5 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 36\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc6 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc6 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc7 to pl;Neural: 8\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc7 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc8 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc8 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_gc_prog to pl;Neoblast: 0\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_gc_prog to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nc_prog to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 18\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 20\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 21\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 23\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 33\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to pl;Neural: 9\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: hy;i_nem to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_smgc1 to pl;Parapharyngeal: 12\n", + "INFO: Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: hy;i_smgc1 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_smgc2 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Neural: 32\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to pl;Parapharyngeal: 38\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg1 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 1\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to pl;Neural: 32\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: hy;i_zmg2 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: hy;nan to pl;Muscle: 7\n", + "INFO: Calculating gene pairs for the mapping: hy;nan to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 10 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 15 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 17 to sc;Intestine\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 28 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 31 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 39 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 4 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Cathepsin+ cells: 41 to sc;Intestine\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 11 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 2 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 24 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 3 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument\n", + "INFO: Calculating gene pairs for the mapping: pl;Epidermal: 35 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 19 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 30 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Intestine: 6 to sc;Tegument_prog\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 13 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 14 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 16 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Muscle: 7 to sc;Muscle\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 0 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 22 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neoblast: 5 to sc;Neoblast\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 1 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 18 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 20 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 21 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 23 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 32 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 33 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 33 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 34 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 36 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 8 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Neural: 9 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Parapharyngeal: 12 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Cathepsin\n", + "INFO: Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Neural\n", + "INFO: Calculating gene pairs for the mapping: pl;Parapharyngeal: 38 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Pharynx: 27 to sc;Flame cells\n", + "INFO: Calculating gene pairs for the mapping: pl;Protonephridia: 26 to sc;Parenchymal\n", + "INFO: Calculating gene pairs for the mapping: pl;Protonephridia: 29 to sc;Flame cells\n" ] } ], @@ -10257,106 +8063,106 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": 47, "metadata": {}, "outputs": [ { - "name": "stdout", + "name": "stderr", "output_type": "stream", "text": [ - "Calculating functional enrichment for cell type hy_ecEp_SC2\n", - "Calculating functional enrichment for cell type hy_ecEp_SC3\n", - "Calculating functional enrichment for cell type hy_ecEp_bat1(mp)\n", - "Calculating functional enrichment for cell type hy_ecEp_bat2(mp)\n", - "Calculating functional enrichment for cell type hy_ecEp_bd\n", - "Calculating functional enrichment for cell type hy_ecEp_head\n", - "Calculating functional enrichment for cell type hy_ecEp_nem1(pd)\n", - "Calculating functional enrichment for cell type hy_ecEp_nem2(id)\n", - "Calculating functional enrichment for cell type hy_enEp_SC1\n", - "Calculating functional enrichment for cell type hy_enEp_SC2\n", - "Calculating functional enrichment for cell type hy_enEp_SC3\n", - "Calculating functional enrichment for cell type hy_enEp_foot\n", - "Calculating functional enrichment for cell type hy_enEp_head\n", - "Calculating functional enrichment for cell type hy_enEp_nem1(pd)\n", - "Calculating functional enrichment for cell type hy_enEp_nem2(pd)\n", - "Calculating functional enrichment for cell type hy_enEp_tent\n", - "Calculating functional enrichment for cell type hy_enEp_tent(pd)\n", - "Calculating functional enrichment for cell type hy_i_SC\n", - "Calculating functional enrichment for cell type hy_i_fmgl1\n", - "Calculating functional enrichment for cell type hy_i_fmgl2_nurse\n", - "Calculating functional enrichment for cell type hy_i_gmgc\n", - "Calculating functional enrichment for cell type hy_i_mgl\n", - "Calculating functional enrichment for cell type hy_i_nb1\n", - "Calculating functional enrichment for cell type hy_i_nb2\n", - "Calculating functional enrichment for cell type hy_i_nb3\n", - "Calculating functional enrichment for cell type hy_i_nb4\n", - "Calculating functional enrichment for cell type hy_i_nc1\n", - "Calculating functional enrichment for cell type hy_i_nc2\n", - "Calculating functional enrichment for cell type hy_i_nc3\n", - "Calculating functional enrichment for cell type hy_i_nc4\n", - "Calculating functional enrichment for cell type hy_i_nc5\n", - "Calculating functional enrichment for cell type hy_i_nc6\n", - "Calculating functional enrichment for cell type hy_i_nc7\n", - "Calculating functional enrichment for cell type hy_i_nc8\n", - "Calculating functional enrichment for cell type hy_i_nc_gc_prog\n", - "Calculating functional enrichment for cell type hy_i_nc_prog\n", - "Calculating functional enrichment for cell type hy_i_nem\n", - "Calculating functional enrichment for cell type hy_i_smgc1\n", - "Calculating functional enrichment for cell type hy_i_smgc2\n", - "Calculating functional enrichment for cell type hy_i_zmg1\n", - "Calculating functional enrichment for cell type hy_i_zmg2\n", - "Calculating functional enrichment for cell type hy_nan\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 10\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 15\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 17\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 28\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 31\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 39\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 4\n", - "Calculating functional enrichment for cell type pl_Cathepsin+ cells: 41\n", - "Calculating functional enrichment for cell type pl_Epidermal: 11\n", - "Calculating functional enrichment for cell type pl_Epidermal: 2\n", - "Calculating functional enrichment for cell type pl_Epidermal: 24\n", - "Calculating functional enrichment for cell type pl_Epidermal: 3\n", - "Calculating functional enrichment for cell type pl_Epidermal: 35\n", - "Calculating functional enrichment for cell type pl_Intestine: 19\n", - "Calculating functional enrichment for cell type pl_Intestine: 30\n", - "Calculating functional enrichment for cell type pl_Intestine: 6\n", - "Calculating functional enrichment for cell type pl_Muscle: 13\n", - "Calculating functional enrichment for cell type pl_Muscle: 14\n", - "Calculating functional enrichment for cell type pl_Muscle: 16\n", - "Calculating functional enrichment for cell type pl_Muscle: 7\n", - "Calculating functional enrichment for cell type pl_Neoblast: 0\n", - "Calculating functional enrichment for cell type pl_Neoblast: 22\n", - "Calculating functional enrichment for cell type pl_Neoblast: 5\n", - "Calculating functional enrichment for cell type pl_Neural: 1\n", - "Calculating functional enrichment for cell type pl_Neural: 18\n", - "Calculating functional enrichment for cell type pl_Neural: 20\n", - "Calculating functional enrichment for cell type pl_Neural: 21\n", - "Calculating functional enrichment for cell type pl_Neural: 23\n", - "Calculating functional enrichment for cell type pl_Neural: 32\n", - "Calculating functional enrichment for cell type pl_Neural: 33\n", - "Calculating functional enrichment for cell type pl_Neural: 34\n", - "Calculating functional enrichment for cell type pl_Neural: 36\n", - "Calculating functional enrichment for cell type pl_Neural: 8\n", - "Calculating functional enrichment for cell type pl_Neural: 9\n", - "Calculating functional enrichment for cell type pl_Parapharyngeal: 12\n", - "Calculating functional enrichment for cell type pl_Parapharyngeal: 38\n", - "Calculating functional enrichment for cell type pl_Pharynx: 25\n", - "Calculating functional enrichment for cell type pl_Pharynx: 27\n", - "Calculating functional enrichment for cell type pl_Pharynx: 37\n", - "Calculating functional enrichment for cell type pl_Protonephridia: 26\n", - "Calculating functional enrichment for cell type pl_Protonephridia: 29\n", - "Calculating functional enrichment for cell type pl_Protonephridia: 40\n", - "Calculating functional enrichment for cell type sc_Cathepsin\n", - "Calculating functional enrichment for cell type sc_Flame cells\n", - "Calculating functional enrichment for cell type sc_Intestine\n", - "Calculating functional enrichment for cell type sc_Muscle\n", - "Calculating functional enrichment for cell type sc_Neoblast\n", - "Calculating functional enrichment for cell type sc_Neural\n", - "Calculating functional enrichment for cell type sc_Parenchymal\n", - "Calculating functional enrichment for cell type sc_Tegument\n", - "Calculating functional enrichment for cell type sc_Tegument_prog\n" + "INFO: Calculating functional enrichment for cell type hy_ecEp_SC2\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_SC3\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_bat1(mp)\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_bat2(mp)\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_bd\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_head\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_nem1(pd)\n", + "INFO: Calculating functional enrichment for cell type hy_ecEp_nem2(id)\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_SC1\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_SC2\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_SC3\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_foot\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_head\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_nem1(pd)\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_nem2(pd)\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_tent\n", + "INFO: Calculating functional enrichment for cell type hy_enEp_tent(pd)\n", + "INFO: Calculating functional enrichment for cell type hy_i_SC\n", + "INFO: Calculating functional enrichment for cell type hy_i_fmgl1\n", + "INFO: Calculating functional enrichment for cell type hy_i_fmgl2_nurse\n", + "INFO: Calculating functional enrichment for cell type hy_i_gmgc\n", + "INFO: Calculating functional enrichment for cell type hy_i_mgl\n", + "INFO: Calculating functional enrichment for cell type hy_i_nb1\n", + "INFO: Calculating functional enrichment for cell type hy_i_nb2\n", + "INFO: Calculating functional enrichment for cell type hy_i_nb3\n", + "INFO: Calculating functional enrichment for cell type hy_i_nb4\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc1\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc2\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc3\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc4\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc5\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc6\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc7\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc8\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc_gc_prog\n", + "INFO: Calculating functional enrichment for cell type hy_i_nc_prog\n", + "INFO: Calculating functional enrichment for cell type hy_i_nem\n", + "INFO: Calculating functional enrichment for cell type hy_i_smgc1\n", + "INFO: Calculating functional enrichment for cell type hy_i_smgc2\n", + "INFO: Calculating functional enrichment for cell type hy_i_zmg1\n", + "INFO: Calculating functional enrichment for cell type hy_i_zmg2\n", + "INFO: Calculating functional enrichment for cell type hy_nan\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 10\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 15\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 17\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 28\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 31\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 39\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 4\n", + "INFO: Calculating functional enrichment for cell type pl_Cathepsin+ cells: 41\n", + "INFO: Calculating functional enrichment for cell type pl_Epidermal: 11\n", + "INFO: Calculating functional enrichment for cell type pl_Epidermal: 2\n", + "INFO: Calculating functional enrichment for cell type pl_Epidermal: 24\n", + "INFO: Calculating functional enrichment for cell type pl_Epidermal: 3\n", + "INFO: Calculating functional enrichment for cell type pl_Epidermal: 35\n", + "INFO: Calculating functional enrichment for cell type pl_Intestine: 19\n", + "INFO: Calculating functional enrichment for cell type pl_Intestine: 30\n", + "INFO: Calculating functional enrichment for cell type pl_Intestine: 6\n", + "INFO: Calculating functional enrichment for cell type pl_Muscle: 13\n", + "INFO: Calculating functional enrichment for cell type pl_Muscle: 14\n", + "INFO: Calculating functional enrichment for cell type pl_Muscle: 16\n", + "INFO: Calculating functional enrichment for cell type pl_Muscle: 7\n", + "INFO: Calculating functional enrichment for cell type pl_Neoblast: 0\n", + "INFO: Calculating functional enrichment for cell type pl_Neoblast: 22\n", + "INFO: Calculating functional enrichment for cell type pl_Neoblast: 5\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 1\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 18\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 20\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 21\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 23\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 32\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 33\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 34\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 36\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 8\n", + "INFO: Calculating functional enrichment for cell type pl_Neural: 9\n", + "INFO: Calculating functional enrichment for cell type pl_Parapharyngeal: 12\n", + "INFO: Calculating functional enrichment for cell type pl_Parapharyngeal: 38\n", + "INFO: Calculating functional enrichment for cell type pl_Pharynx: 25\n", + "INFO: Calculating functional enrichment for cell type pl_Pharynx: 27\n", + "INFO: Calculating functional enrichment for cell type pl_Pharynx: 37\n", + "INFO: Calculating functional enrichment for cell type pl_Protonephridia: 26\n", + "INFO: Calculating functional enrichment for cell type pl_Protonephridia: 29\n", + "INFO: Calculating functional enrichment for cell type pl_Protonephridia: 40\n", + "INFO: Calculating functional enrichment for cell type sc_Cathepsin\n", + "INFO: Calculating functional enrichment for cell type sc_Flame cells\n", + "INFO: Calculating functional enrichment for cell type sc_Intestine\n", + "INFO: Calculating functional enrichment for cell type sc_Muscle\n", + "INFO: Calculating functional enrichment for cell type sc_Neoblast\n", + "INFO: Calculating functional enrichment for cell type sc_Neural\n", + "INFO: Calculating functional enrichment for cell type sc_Parenchymal\n", + "INFO: Calculating functional enrichment for cell type sc_Tegument\n", + "INFO: Calculating functional enrichment for cell type sc_Tegument_prog\n" ] } ], @@ -10366,22 +8172,22 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 48, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(
, )" + "(
, )" ] }, - "execution_count": 49, + "execution_count": 48, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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Xbyc33PCH3HuvIy1bXiePPPLsEamroiiKoiiKohyPpKamyi233ClnndVdJk36MOpysHE2bdrk2j2KoiiKoiiKoihZi+6UjUScE23UyTq+mIDa+++/fyiIdPPNN7s7ZgnexMfHZ7h7rmDBgrJt2zYpUKBAZqpyQjF69Bi55prXZdu2M0Rkh1Ss+LEsXvy95MyZ03cZjz02SoYPXy67d3d3/58792QZMiS33HXXEN9lfPfdd9Kp0/2yefMAhpOIrJfGjcfKnDkfB3qe9u27y7RpVcRxKktc3FJp02axTJv2bqAyPvroE+nbl7p0EpG10rjxTzJnzucSlD59LpNJkxZKXJxI9+715ZVXRgUuo1+/q2Ts2NWyd29JKVPmB5kz5xMpWbJkoDKYG02atJLNmwtJcvIumT37C0lKSpKjzbp166Rx4/ayalVrws1SvvwsWbDgG8mTJ4/vMrp06SeTJjURkXIH33GkdOmHZNGiTyRfvnxHrO6KoiiKoiiKcrxw4YWXy/jxW2TfvvJStOiXMnHiI9KixemBy+ncubvMnfuXlC6dR775ZrokJiYekfoqiqIcLUgyGTLkNilXrqxce+1AbXhFURTluOJYiaGZeop8JCJ5j/C37RKRDjHfJkdsp+zkyZPdwAqv/PnzywcffCBjx44NGZDdt2+f2zn2SwnOJ5/MlG3bah0MhBaQPXsKu8GzIHz99TzZvfvUQ//fu/dU+fbbnwOV8dNPv8jmzXUO1gNKyKZNwXd1/vXXWjcgC45TSZYtWx+4jE8/nSWbN9cXkRwiUlrWrdsV1U7XH374WXbtqiU7d9aSr7+eI9Hw/fc/y969DUWklGzZUk5+/jlYu8JPP/0ka9cWlU2bGsm6dXkzteM2M/z222+ybVuZg4K0oOzeXcw9qjoIv//+txWQhTjZu7eSLFmyJMvrqyiKoiiKoijHI3Pm/Cb79tUWkXyyaVMt+eSTLwKXgT3+44+/y9q1jWX58jT5888/j0hdFUVRjia//vqrvPLKRPnf/x7Ua7UURVEURTn+g7KtWrWSefPmua8ffvhB2rdvLx06dHCPLPVy//33u9Fy8ypbtmxWVOGEo1WrZpI//+/ujkOyAnLl2iwlSpQIVMZJJ9WRpKTZh/6fK9dsadoUI98/9erVksKF7aOTN0rhwsEzrcuVK84htwf/t1zKlCkauIzWrZtLoUK/kiPJ/k4pVixJ4tjuGpAGDWpK7tyLJClpkTRpUk+ioWHDWpKY+Iu7c7hQoeVSt27dwGXUr19fihffIAUL/ixFi26XatWqSXZQs2ZNyZ9/JWF7d6wlJW2UcuXsAGvGVKpUWkRWWe84kjv3MqlUqVKW11dRFEVRFEVRjkfq168uOXOSqLlPihRZJG3anBbV1UO1apWT5OR5UqqUo/q4oijHBbVr15aePc+SG2+8WhISErK7OoqiKIpygqPHFx/V44shLS3NDbhef/31cs899/wnM5eXgZ2yBGaPxW3G2QndNnToCJk0abokJeWU119/yg3iBYF+6tLlEpk7d5s4TrzUrp0gH330dqAjkOGmm0bIW299KY6TLPny/SUff/yGVK1aNVAZ3GnUrdtlsmLFRjcgO2HCy1KsWDEJypNPjpJXXnlHSpYsJq+//oykpKQELoN2mThxorvTu2vXrhkewR3uvqf77ntE/vjjLxky5GqpVy+64C5zi4xP+pZd6NnFl19+5fZzzpwJ8txzjwQOMi9dulRateolq1a1kbS0wlK06Bdy/fVt5fbbbzxidVYURVEURVGU44m9e/fK4MHDZf78hXLFFRdJ7949oj7mc9WqVZKcnBzY9lMURVEURVEU5ehy7B1fPPkoHV/cOebb5KgFZTHyChUqJAMGDJBHH330uBhQxzMbNmxw+4ydttHsLAWOTt68ebObaU32taJ4YXy8+OIbsmrVeunXr5s0atRIG0lRFEVRFEVRFEVRFEVRFEVRjpug7KSjFJQ9N+bbJBRZcqYHO1/Xrl3r/nvLli3yzDPPyM6dO+Xss8/OiuKVI0zx4hwdnDlKlizpvhQlHEWKFJGhQ6/XBlIURVEURVEURVEURVEURVEU5YQjS4KyH3/88aFjYjlitUaNGjJ+/Hhp2bJlVhSvKIqiKIqiKIqiKIqiKIqiKIqiKEpMk37wdaS/4wQNyr722mvuS1EURVEURVEURVEURVEURVEURVEURTlCO2UVRVEURVEURVEURVEURVEURVEURTmRSTv4OtLfcWwSn90VUBRFURRFURRFURRFURRFURRFURRFOZ7RnbKKoiiKoiiKoiiKoiiKoiiKoiiKomTBfa9Heidruhyr6E5ZRVEURVEURVEURVEURVEURVEURVGUI4julFUURVEURVEURVEURVEURVEURVEUJZPonbKR0J2yiqIoiqIoiqIoiqIoiqIoiqIoiqIoRxDdKasoiqIoiqIoiqIoiqIoiqIoiqIoShbc93qk73xNl2MV3SmrKIqiKIqiKIqiKIqiKIqiKIqiKIpyBNGdsoqiKIqiKIqiKIqiKIqiKIqiKIqiZBK9UzYSGpRVFOWosG/fPpk9e7b7s0aNGlK6dGlteUVRFEVRFEVRFEVRFEVRFEVRTggyHZRdsWKFjBgxQj7++GPZuHGjpKSkSJcuXeSOO+6QokWLZk0tlZCkpqbK0qVLJX/+/FKqVKmoW8lxHPdnXFxcVJ9ft26djB49Rtav3ywtWzaTs85qL/HxejK28g8HDhyQwYOHy8SJH8v27cly4EAOyZ9/s1SuXEhee+1pqVy5sjaVoiiKoiiKclwzb948ee218bJv3345//yzpE2b1lHbX4qiKIqiKIqiKLGL7pSNRKYiZwQEmzRpIn/88YeMGTNGlixZIs8995x89tln0qxZM9m8eXNmilciBFHvuusBqVLlJGnR4ipp3LibNGp0hixYsCBQm9FfrVufLWXLNnRfLVp0kIULFwYqY+jQEdKw4dkydOhsefjhNdKr10ipWfMUt+wgvPfeJGnc+Az3mfg5ceL7EpRvvvlWmjVrLxUqnCxVqjSVm2++3d2VGYQ9e/bIvfc+IvXqtXRf99//WOAyYNOmTfLgg4/KNdcMli+//PJQ4Pto88MPP0iLFh2lcuWTpUaNk+W++x6RtDSEon8YEy1bdpZy5RpKuXINpEOHbrJ8+XJfn01PT5fOnXvIc8/9IcuXd5KtW5vIzp0NZc2aNvLVV5WlZcvzAo8VRVEURfG7BrEOzpkzx/23oihKdrB3715p06artGt3mzz5ZLo891xu6d59lNSvf4ab3Hosg2zNLjvHgG3z0UcfyXPPvZCtdgVtMWnSJOnV6xK56aZh8vfffwcug7Z89933pHXrrtKqVRcZN25CVOsXbfLpp5/Kq6++5ibRK4qiKIqiKIoSO8Q5mbCiOnToIL/++qv8/vvvkpSUdOj9tWvXurvfLrroIhk1alTEMrZv3y4FCxaUbdu2SYECBaKtygnF8OH3yFNPfSXbtzekCw++u0vKlp0p33031deu2ZUrV0rz5h1lxYomIlLo4Ls7pHTp72TWrElSqVKlDMt4+eXX5aab3pJt206z6gHbpXLlz2Xhwu8kZ86cGZbzxBPPyt13vyFbttQXkUQR2S+FC8+X227rIzfddI34YcaMmdKz582yfn1bEcmHSSuJiQvllFO2yowZk31lobPz+NRTO8i8eRUlNZW2FcmZ80dp3HiFfPnlFElI8Lex/Ntvv5Pu3QfI2rWVJS0tjxQuvFJaty4v48e/ESgbHgP8sceelK+++l7atj1DBg26MtDnZ86cJT16XC/r17cQkfyUKElJv8mZZ+aR999/23fiRYsWXWTVqpNExMzPzVKhwjz54YdpUrx48YifJ7h+8cXPyc6dTcP8xTZp3nyxfP31J76fS1EURVEygoTBTp16yKZN+SQuzpFixfbKRx+Nl4oVKwZqvI8++kRuumm4HDiQLk2b1peXX35WcufOrR2gKEcBEiPvuus++fXXhXL++efIxRf3PSbb/YIL+su77+aXAwdqe36zWho3niVz5kyXYw0SULt3v1B+/3255MghctllfeSOO4ZFVRZ2KXZYUPkMBLVbtTpbVq4sKDt25JaSJddJz54t5cknHwpUzqpVq+SCCy6RtWs3StGiBeXtt1/2ZQ/bQdD27c+VH37YJjt2JJPqK8nJy+TFFx+Szp07+i7nggsuk6lTt8iOHSe79nW+fLOlTZtc8t57o33bgfhiWrU6T1atqiA7dhSUkiV/kyuu6Ch33XWLRJNQQHC5fPnyUa99W7dulVmzZkmZMmWkUaNGEi0msTgHAy4boR5sPuBUuGhPB2Pcfv755+6YP+WUUyS7oG+vvXaobNy4WQYOvFT69LkgW+qBT/DCC6+SRYv+kqSknPLyy49J48aNs6UuiqIoxh9LrKNYsWLuS1FigWMlhmbqKfKSiOQ5wt+2W0T6+26T+++/XyZOnCiLFi1yY5nNmzeXBx98UKpXr37ob1q2bCkzZ8487HNXXHGFuxE1JnbKooh+8sknMnDgwMMCspCcnCx9+vSRsWPHZnvm7PEGhtEbb0z0BGQhr6xYUUfuu+8xX+Xcccf9smJFbSsgC/ll1aqGMnToXb7KeOSRUbJtG0aE10AsIGvWlJNx49715Wx5/PEXZMuWJgcDspAoW7Y0lieffMn3LtUbbhgh69efdTAgC3Gyf38t+eWXNPnqq698lfHOO+Plt9+SJTWVumDs5ZDU1Kby669F5L33PvBVBuP90kuvlVWrWkhaGoZ8svts06cvl+nTgzlcLr30Chkx4m2ZNGmzDBv2ktxww5BAn7/hhuGyfn2bgwFZiJc9e+rKt9+u8r2resiQEbJqVQMrIAtF5O+/q8gDDzye4ecffPAZ2bnT64CyKSh//bVDM7gVRVGULKVbt4vljz9qy+bNtWTTptqyeHF16d69X6AySDzs1+9mWbiwlvzxRwMZP36VXHTRAO0pRTlKdOjQRR55ZLp8+OEOue66R+SRR5445toem/mrrxaFCMhCKVm2LI+7m/9Yo1u3vvLFFwQz68vy5fXksccmyKRJ/uwlm3vueUCaNDlLmjXrIldeeW3gzw8YcJ0sXFhdduyoKyJVZd260+Stt76UuXPnBrpqpU2bs+Wrr3LKkiXV5fvv80u7dufK7t04efwxYcK78v3322XHDhw6OKGSZe3aJnLddbf63un6448/yvTpq2THjrYH7bd8snNnK/nyy63y3Xff+a7LJZdcL4sWdZAdO9qJyEmybl0/GTXqE9e5HASCu3XrniwtWlzk/uT/0QTvmzQ5Q7p3f0TOPLO/PPDAoxINb7/9jpQtW0vKlastEydOkmh5/vmXpV+/K91rt6Kdz/XqnSz163eQJk1Ol127dgUug53LJ53UTvr0eV06drxO/ve/B6OqC/3ZsOGp0qxZG1mzZk3gz2/ZssU9DeuDDw7IN9+kyDXXPCxvvTUmqrpMn/659Ox5ias3RcM55/SWyZOT5PffO8jPPzeXc8/tL6tXr46qLOX4B2d/ZvzMyORXX31dvvzSn58w3Pxp06aTnHTSGVGf0MDac/75vaR69YbyyiuvR10X5cgk37Rp01FatOgl9eqdJh988KE2s6IcJ8ycOVMGDRrk6tbTpk1zE0PPPPPM/+h0AwYMcPUr83rooWAJn0c0KMsOBBbCmjVrhvw977NQbdiw4bD3CbKxiNovJdhRsrt2kaUTKlO2rMya5c9g+/77H11j8b8Uk/nzF2X4+X/6kX+F3gm7e3d5mTz5swzL+e2332TXrsIhnidOdu4sLPPnz/e1YK5fz+T5b/buli0VZcKEKeKHd96ZLLt3Y9Afzs6ddWTMGH+L8Pr162XbNgK6uQ57f9u2CvLGG+MlCDNmfCe7d5d2s0p27iwrU6ZM8/3ZSG2yfn1pmTRpqq9y5s9f7I4JL45TVqZNOzxrJBSbNu3MMCtm27aigY/eVhRFUZRITtMNG/a7CWv/kk/WrNkRyIE6btx7sn59WRH556SM1NQyMneurleKcjTYuXOnLF68SlJTsVfyyLZtleT116MLGGQnP//8s2zfXj7s7zdtqiTTp8+SYwkcyb//vlJEsOEgTrZtKy+jRr0SuKwXXhgt69ZVk3XrqsgHH0x3E5CD8Msvf4jI4Sf3bNpUXt5807/d9ddff8nWrQlWEmpe2bo1X6AA0+jR42XnTuw2mwTZuTPJdzB03LgPZdOmWv95f/Pm2vLWW/6v9lm4kGtmyljvxMmGDY1k3LhgwcxnnnlOliwpIuvXV5IlSwrLs88+L0GZMGGiLF1aWPbvryybNtWTl156U6JhxIgHZc2aBrJ6dT259da7oyqDwMnw4U/L668vl6uuuiGqMl588VVZuLCgrFlTV375JYdMnPhe4DJeeOE1Wb68sjhOddmy5WR57bVxUdVlwIBrZN68EvLddwkydOgdgT//9ddfy9q1RQ8m6eeULVvqyrPPvhxVXfr1u0bGjRPp2XNAVPJkyZL1kp5u5GQe98QxTv1SFC+zZ8+WMmUqyeOPPxV147z11tsyaNCT0qNH/6j90ffe+5B88cUOmT07vzsXo4Fj9z/6aJH8/nsZueOO+6IqQzky/PTTTzJ//nrZsKGsrFlTWe64415takU5Tvj444+lX79+Urt2balfv7689hp62fL/JHTmyZPH3XRqXkdiZ3Km7pSFoBlKbBNmC7N5lS2Ls0vxS968eSVHjnC7R1MlVy6z2zQyiYkEU0PdLZouCQkZH43EUb5xcQci/MVeKVjQ7NAMT/78+SVHDhyn/yVnzlT39xnBsUHx8aHvSY2L2yNFi9q7gcNTuDBZzaGctbt8l8GkjY9PDfGbPVK8eLAjL/45mck81wFJSPB/VNM/bRI6KzshYZ8UKeLveRISEBGhykmVpKSMj7DiyMiMvyNdcuU6PIitKIqiKNHCEYs5cvxXL0BX8HOtgoG1Mj7e1lHSJS5O76ZVlKMBuqHjYPMYXXK/5Mlz7B0djm2A7h2OuLi9UqCAOenn2AA7I0cOr46/V0qWLBG4LI4qpW+xdZDbQWQ05MyJ3Xp4XeLjqYt/uytfPo65P7yPsE/92KGGokWLuG3gJUeOVN9OnGLFWHP+uzs3Lm6XlChhAuAZk5BAexy+VuXMuVOKF6eO/ilTprTkybPH/XdS0l73/0EpWbK45Mlj2nafJCVFZ/MVKkRf7HBfRYv6bwubIkWKSFLSASlSZL3UrRvpJKfwlC1bWvLmpY8cyZt3V1RtkpJSQnLn3m21iT//jZfKlStJYuI6yZNni1SrViXw5/HF5cpl6zi7pHBhfz4CL8WKFZZChZZJhQp2MoA//jmOev9h8zhXLnxJsXsso5J9lC5dWmrXriMnnRT98dbVq1eTQoV2S+HC+f5z6qP/MqpIvnzbJFeu9VK1auWoyuBI939k7EbJn/9IH++pBIHj6RMS9h6US7ulWDESWBRFCQ76aNoRfqW73+TdAOr35FWOPTZ6os1bb73lHl1ep04dGTZsWKATdI54ULZKlSruvSbs3AwF7xcuXPg/d07yIDyweXF8i+KfqlWrSpEiLA7/HVxJSYvkiisu9FXOpZdeILlzk1l8ODlzLpELLujiS3muWpW7a7eG/H2xYr/LlVde5Ot5SpT4Z6E7HBa+A4ed6R0OxmHTphhWZGzbOFKixG9y6aX+7p+66abLpVixrzyGvSPFi38t11/f31cZGO/16lWQ+Hj7uJ0Dkpy8WK699nIJwmOP3ScpKUukYMFVUqrUnzJypP/jnkybxMV5j/1JlxIl/pSePbv5KqdXry7umPCSN+9iGTgw42MgmzSpw605Ef+mUKG1cvLJ3JukKIqiKFkTBDn99IaSK9eyg2u6I7lzL5V27U6VxET/zs/LLusn1aptkfh4dh1xz+BPMnz4TdpFinIUIDg3dOi1UrLk71KgwAopW3apvPji08dc2zdp0kQKFkSGhE7oSEn5Tbp1y9j2irWg7IUXdpMCBThRB7t0i5QqtUyGDw921QqMH/+GNGiwRWrXXiOjRz8f+L7QCy/sLnnz/mbZb3slJWWpXHbZxb7LSElJkTZtmkj+/H+5z5InzzI5+eSKUqNGDd9lDB58jRQvvtTTz5ulUqXCUqoUNnPG9OvXR0qW5ChrO8E3TUqW/EH698/Yrjb07n2O5M0702qT7ZKcPFd69+4hQbj88sukd+/GUrPmn9KnT2MZMOBSCcq5554rXbvWlrJl50rVqovlrbdekGh47723pWPHJDnnnALy7rvR7bbF2TZ79ucyffqLMnz40KjK6NWrpwwc2Fbq1/9dhgy5QFq1ahW4DNq1dev8Urr0LKlU6XsZPXpkVHV5/vmn5MEHe8mTT14lt946OPDnTzvtNDn11FJSsOACSUxcIuXLL5Jnnnk4qrp8/fUn8tFH98v7778d+LP4LQYOvFAKF/6c250lMXG+1Kmzxz1KUFG8IE+//XaGO36j5aSTTpIlS36U+fO/C5wIZOjf/1J55ZUR8vTTV8jIkdFdrdCwYUN5++2nZdiwM2XaND0eN5bgvu///e8mqVFjtZx+ek55883oThFQFOXoUbZs2cM2gbIp1M9x9tdff72ceuqpbvDV0Lt3b3nzzTfliy++cOOYo0ePlr59/cWWghDnZOIw/vbt27vHz3KUsZ1hxH0jlStXlosuukhGjRp1XFxSHEt888230q3bQFmzphH5p27QL1euhdK0aap8/vmHvhQLjok588xzZfbsvbJzJ5ldcZI3719Sv74jn38+2dfORfq+Xbs+smZNe+suVxyfC6RNG0cmTx7r63kI4Hfo0FPWrCkl+/cXlsTErZKcvFKmTn3H3U7u976aFi06yV9/lZI9eyq6WbQlSvwsw4b1k+uvv0r8cs89j8izz74n69bVc3d5UsaNN/aSwYP933G0Y8cOOf/8i+S331ZJWlpuyZNnhzzxxP/knHM6S1CYS3/++adUq1btPwkOfo5vPOMM2qSY7NpVRuLitkvJkgvk0UeH+TbKySxp3bqzcIr0zp20a5oULLhUTjutmHzwwVjXKRMJLs5u2bKvrFvHGPnv3+bK9YdcckmKjBqV8f20iqIoiuIX7gYZMmS4TJ78z9H/Xbt2kPvuu9M96SMI6KlPPjlS1q/fKN26nSNnnNFCO0FRjiLLli1zj5TCUPZmMB8rvPLKmzJ48OuyefP5h45DJ3iXP/9MufDCUvLss9EFQrITXAjco/rcc69JSkqy3HnnLW7SdnbUY+jQ4TJ27GQ5cCBBChfOKS+++Lg0a3ZK4HJGj35Lvv12jjRsWFf6978kQzvHC3cC3nnnI7JzZyFJTNwvFSrklQ8/HBvIhps0aYpcffUdsnlzNcFLU7ToH/Loo7dKjx7n+S4DB9OQIXfK+PEfu21SokRuef31J6RevXqBnkc5stBPQcdYVsO45241fHEEudgdll189NHHMnXq51KpUjkZOHCAnqSlKIqiKMdoDM3UU+Q5thAe4W/bIyJXups+7TYhrpVRbOuqq65yj5L/6quv3NMLwvH5559LmzZt3KswiHfGRFCWYGzz5s3d+2PvueceN5uEQN3gwYPdYA6X5mZkPB8rAyrWIFA3fPj9Mm/eQsmVK4dcdllvueKKywJlenHvKBeWv/DCm5KWli79+/eS887rGshhyT1JV1xxs6xYsVPS0/NIYuIW6datozz4YDDHJ3e8vfbaaJkzZ740blxXLrnkIveo5iDs379f3nlnnEyaNF1KlSoh1113eVTOgdWrV8uECdzbEyc9enR1zw6PBu5T5l5lJmzQrO+sdEpz182UKZ9LuXKlZODA/r6zte1xMmnSh/Lyy29LzpwJ7g7Zdu3auVmtfnj11dFyyy1Pyvr1HDFjjjXb62a1N20aJ59++n7UGYqKoiiKoiiKEuu8+eZYufvuJ2T79iLiOAmSJ88aufTS7nL77Tf71qmVyAEubEGOr89O8IHMnz/fDW5VqlQpqjK4V5fMfNw07MSM9nhNPo8dFzQZSVEURVEURYk9jpUYWnYEZbcFbJOrr75aJk2aJLNmzXLjmRnFrLjuhPto2aAaE0FZ+Pvvv2XEiBFuxdiZRwCrS5cu7nt+Mu2OlQGlRIa+Z4coAT8NsCleFixYIHfe+ZD8+OMCcZw4KVQoj9x885XSo0e3bAtYK4qiKIqiKMrRArN76dKlbtIkiaMaLFMURVEURVEUxQ/HXlD22aMUlB3ku02wx6655hp57733ZMaMGe61mhnx9ddfuyeKsDExK0+eyXRQ9kQZUIqiKIqiKIqiKIqiKIqiKIqiKIpytDhWYmixHJQdOHCgvP322+4u2erVqx96n/pyOg0n0/L7jh07uptNOQHnhhtucI835sqHrETPslEURVEURVEURVEURVEURVEURVEUJZOkHXwdSdIC/fWoUaPcny1btjzs/VdffVX69esniYmJMn36dHniiSfcY4vLli0r559/vtx+++2S1WhQVlEURVEURVEURVEURVEURVEURVGU4w4ngwODCcJm9Y7YcGhQVlEURVEURVEURVEURVEURVEURVGU426nbCwRn90VUBRFURRFURRFURRFURRFURRFURRFOZ7RnbKKoiiKoiiKoiiKoiiKoiiKoiiKomQS3SkbCd0pqyiKoiiKoiiKoiiKoiiKoiiKoiiKcgTRnbKKoiiKoiiKoiiKoiiKoiiKoiiKomSS9IOvI0m6HKvoTllFURRFURRFURRFURRFURRFURRFUZQjiO6UVRRFURRFURRFURRFURRFURRFURQlC3axcq/skSRdjlV0p6yiKMcU27Ztk+XLl8uuXbuyuyqKokSB4zju/N2/f7+2n6IoiqIoiqIoiqIoiqIoJwy6U1ZRlGOCL2fNkiefekriRKR48eKyevVqKVCwoAy++WapW6+enMisXbtW1q9fL+XKlZNChQplWz327dsnixYtksTERKlRo4bExdFbyvFGWlqa5MiRI/DnduzYIQ8++KyMHz9N0tOLS3r6HilePE5uuWWAdOnS6YjUVVEURVEURVEURVEURVGUo0naUdgpmyYnZFA2I4f7iBEj5M4778zMVyiKoshbb74pH3/8sYx85hkpUaLEoRZZtmyZXHvddXLDDTdIq9atfQcwH374efn66x8lObmEDBlyqTRv3ixQKxMQvvPOJ+Wbb36VuDhHzjmnhQwdOlAKFCjgu4zdu3fL448/LxMnTpf09DipU6ei3HXXDVKpUiXfZfzxxx9y1VW3yM6dSZI3bznZtm2hVKlSVJ577pHAwdl58+bJrFnfSuXK5eWss9oHCrqlp6fL0KEjZOzYqbJnT0mJjz8g+fNvkbvuuln69Okp2cGBAwfcICDtkN3BYYLVCQkJUQUy7R3iqampUqxYsag+P2fOHLnvvpdk5cq1csYZTeTmmwdIyZIlAwVi7733KXnzzSmyf38+yZFjp5x11iny8MO3Sp48eTL8/JYtW6Rly56ybdsgSUoaIjlyxB96/4Yb7pNZs+bIY4+NiOrZlOMPZMrUqR/LpEmfS+nSxeWKKy6SlJSUQGVs3bpVHnroGfngg88kLi5ezjuvrdx006BActrIki+++EI2b94sp59+upQqVSrg0yjh1uInnnhOFixYIs2aNZKrrro0W5OKYgHk7LRp0+X335dJ8+aNpUmTJlGXg55StGhRX/L5SMC8efvtcTJy5Nuyf3+qnHtuG7n++iukYMGC2VIf5fhnz549sn37dtdOyG69T1EURVEURVEUJRJxDucIZsKhYhg7dqzccccdsnjx4kPv5cuXz31FAuMJAx2Hc1BHmaIoxz8cVXz1oEHy3sSJIYNaBDc7n3OOTJ48OUPn4/z5v0jXrjfI/v23Su7cLeXAgb8lPf0BueSSanLnnTf5qs+ff/4p7doNkF277pPExJM5jFVSU6dI8eJPyVdfTfDlcMRx1KpVN9mz52IpXPg8iY9PkJ07f5atWwfL2LEPScOGDTIsY+XKldKp00XSrNnrUqBA2UPvr137g/zxx3CZOfNDd8dqRnCEbKdOF8i8eQdk48ZKki/fJklJ+UM++WSMVKxY0UeLiFxyyUAZN26D7N5dn2Xl4LtpUrToNHniiUHSt+8FEoQlS5a4x9vWrl3bDWYGgSXt9tvvljffnCgHDuSSPHkOyOOP3yOdO3cMVM7evXvlgQcelcmTP5UGDerKPffcLsnJyYHKIGngggsukxUrtkh8fLq0anWSvPTSM776xUDQsnv3q2Xx4v3iOLmkRImtMm7cE1KlShXfZfzvf0/Kk0/+KJs2DRaR8hIfP0tKl35Mpk59UurUqeOrjK5d+8t3351Cb0tcXA63ndPSpkrFis/JV19NlJw5c0b8/NlnXyILFlwtuXI1Dvn7PXuul+ee6yzt27f1VZ+xYyfKww+/6gYfBgzoJldddUlgJ+zOnTvl4Yefkb//Xitdu7aVc8/tLNHw008/yezZP0q9erXllFNoo+DMnPmljBnzgSQnF5UbbwyW4GEHMkmu4GfDhg2jSgIg8P/662/KypXrpEuXs6RBg4xlkZeNGzfKsGH3yuzZ86VJk7rywAO3B0omYO63anW+LF5cUbZvbyLx8RulRInJ8uSTN0mPHl181+HUU8+RJUvaSnp6I1dO58gxR6pWnSnffPOhFC5c2Fc5CxcudMfuunU1Zdeu/JKc/Kv07NnclSlB17Hrrhshf/yxXOrWrSqPP35nYHkCkyZNlvfemyblyiXLkCHXZKhjh4LTDJ599nVJTMwp113X3z1hISi//fab3HrrfbJ+/Qbp37+PXHrpRYHm32effS4XXTRE1qxpJo6TIgkJf0upUnPk44/flJo1a/ouBzk0evQYmTz5c6lYsYwMH35zVG2CrH7jjXGSlJRL+ve/yPf4MDDnbrnlLhk//hNJS4uXGjVKy5tvPntYEpmfNb1t24tl9eozZMeOmlK06JdSu/Ya+eST0ZI7d27f5bz11gS5/fZnZO/e8pKQsEY6d24szz57r8TH+7+xBpvskktulB9//MNdu3r27CD33jvMdxkEZM88s4d8/31Z2b27vYjkkhw5vpOKFae660WQhCBFyQj0gCuvvEY+/nimpKXllHz5HBk58jFp27ZNoMZbt26dXH/9EPnllwVStWplefLJh6KSj0p4/QKdXgPmh8tKdLXsbBPG/b33PiybN2+Viy66QM48058efiSYMuUjmTz5E6lSpYJcffVVkitXrsBloBdgR7Juli37r32sKIq/RHJs+iA6Y6g5CJmRa8QINm3a5K7B0Sa1r1q1yrVXqlevLuXLl4+qjAULFsh7730oKSklpG/fPoF8OMcrbHrA94EuT9tGC6f8Mc6i3XBwInOsxNBMPUXuFRH/tmx07BWR22K+TULiZBGvvvqqU7BgwcCf27ZtG1Lb/akoiuLltltvdWbNmOE4aWlhX6+98orz8ksvZdh4jRt3cipWXO9UreocelWpku5UqNDD+euvv3w1ftu2vZ2UlD+dsmWdw14lSkx1brzxLl9lPPTQ007dum85rVo5h71OPXWDc8opZ/sq48orb3L69v3BGTzY+c+rY8eRzujRY3yVc8stdzmJiYMckdet16NOw4atfX1+1apVTkpKM0fknhCvu5zKlRs76enpjl+uuOIap0SJBk7Rok2dpk1Pd/bs2eMEYeTIF5z8+U93RAY6IjzXFU5ycj3nzz//DFROq1adnJw5OzgiVzki5zmVKzdwdu3a5fvzBw4ccKpWbeSI9HNErnVfiYlnO/36XRmoHi1bXuDkzv2Dk5TkuK/cuVc6Vau2csv3w4oVK5zk5C6OyG5HZI/1+tupX7+jrzLmzJnjlClzrZOS4vznlZz8tPPGG+9E/PzatWudKlV6ODVrOmFfVauudVq06O6rPq++OsYpVOhiR+QXR2Shkz//jc4ddzzkBIFxVbduSydHjrsckZedwoW7Offf/6QTlGeeeckpVqytI3KzU6RIJ+fOO4PVA9588x2nWLFWjsj/nPj4G5waNZo5O3bsCFQG46Fdu65OkSId3Xq0aNHJSU1NDVQGf9+sWXsnMfFCR+R6p3jxZs6kSZMDl1Gz5qmOyJ2OyDvuzxo1mgeqy9VX3+LkyHG/I/KF9ZrmlC7dzNm+fbuvMi6++GpH5AFHZNJhr7i4u52rrhrsqwzkVrVqzR2RlxyRCYdehQqd70yZMtX389CXFSue7IiMckQ+ckSecMvdv3+/E4QHH3zKKVz4PEfkOSdHjjucunXPcHbv3h2ojLlz5zrJydTlPkfkbqdMmSbO0qVLA5WxePFiJzm5oSNygyNyh5MvX0fnpptu8/15xkKFCo0dkccdkWet1/1O/fpnBKrLjTfe7hQseLYjMsKJj7/SqV27eeA2+e2335xSpajPTU5c3NVOlSonOZs2bQpUxi233O3kyXOpI/KGIzLaEbnXadCgZaC17+STkdM/OyI7D70SEt5xrrlmuO8yfvnlF6d48c6OyJ+ujOeVJ8/dzj33PB7oeU499RwnLo4+meWIzHTy5LnRueWW//n+/CuvjHby5LnWM4d5Pe+cd96lgeqiKBkxZMhtTlJSU0fk7IOvDk5KSjVXP/UL8rhatXqOyOkHyzjDqVixVuC1WAmtn3TufJ5TqlQtp1y5Gs5XX30dVTP9/PPPTuPGpzpNm7ZwFi5ceEw3Netgx45d3TZhnP34449RlbN69Wqna9deTt++lzlbt24N/Pn169c7FSvWdkRaOiJnOUWL1nFeffUNJzt44IFHnMKF6zsibZ3ExObOySefEViPZay1bt3RKVGiiVOyZH1n0KAboq7PuHHjnYcffiyQ7eflvfcmOf36XeHMmzcv6jL++OMP55prbnSmTPko6jKQby+88JIzZcqUqMtQjm/QV7t37+eUKtXUKV26nvPhh/7tHJs33hjjlClT3ylduoHz8MNPRVXGuHHvOikp9Z2SJVs79eqdGlWcYOrUj52UlLpO3rxtnOTk+s7YsRMClzF9+mdOyZJ1HJGOTmJiK+fkk1sGlknw008/OQ0anO4+yw8/zHai7Z9HH33C6dWrnysTogH52Lv3JU716o2cvn0v9e1L8vqVKlWq7RQo0NgpXry2c+utIwKXwbNcfDH+uQZu32RGTp+oHCsxNFNPfA4iDx3h193HRJuEIvoUmExk3xAxt1+Koijh+GnePDnttNMiNlCXLl1k2vTpEf+Go/y2bi0uCQnFD3ufLL7U1P7y2msTfGU0L1myVRIS/nvEcGLiWfLxx9+KH8aN+1iKFOkeooxisn17AdmwYUOGZcye/aukpDQN+bsqVfrI6NHv+qrLxImfyv793iMSi8maNQmyYsWKDD8/fvxEWbs23I7aHLJ9exE3y9APZDa/996Xsn59Ddm0qbLMm5cmL730qgRh1KhXZceO2taO3QRZu7ayPPXU877LYDf0ggWbJDWVfmaZTJGVK4vLhAn+2hS+/JLnIDPs30yt/fsrymeffXMogzQjGAdLlsRLXNy//RwXV1o2bWors2bN8lXG669PkLVrL7baw1BC1q8vImvWrMmwjOefnyB791LGf3Gci+SFFyLPnZkzZ8revZF3KicklJTVq3eKHx599FXZuvUWEcnr7sDasWOQjB49RYLAzvrFi+tLWtqp7u7hLVuukFGjxkpQHnzwedm48XIROUU2b+4nzz8/3pUTQbj77qdl48aLRKSCu6vzjz/qy5gx4wKVMW3aNPn2W0c2bz5TNm9uJz/8kCTvvz8pUBkzZsyQX3/NL/v30yY1ZMOG3jJs2AOByvjss89kxYqqIlLz4JirKStXVpPpGchnm48++lrS0jiFwCZB1q9vIZMmfeirjFmz5h2sw+E4Tj359FN/cppdx5s2lRGRw4/U3bq1ozzyyIvil7Fj35VVq053+/cfqsvKlfXkk08+kSA8++zbsmVLf3e8pqU1k8WL68qUKcHG/Y033iNr1w4QkWoiUktWruwhd975WKAy7rnnMVm7trmIFGXVkp07m8u4cVN9y7VvvvlGtmwhY92bbV5A1q1LcDPb/e6Oe+edqbJt25numpWeXlv++KOcTJ06NdDz3HjjXbJ6Ncfs1xbHaSR//tlcnnrqhUBl8Py7d7e05Gw5WbmykMyfP9+3rF++nPaofNj7Bw50kqlT/Y1XeOSRV2TDhoGH3U6ze3dfeeONyYF2Df/5J6ch1D34Tpzs3n2ujB37se8ynn/+Hdm9+6wQv6kmc+b87rscRfHDhAkfuFdn/At6XxF58cVXfDcgV6SsXJlgyfsCsmpVHhk3brx2QiYZO3acfPbZX7J6dWVZvryC9O9/dVTldO9+kcydm1dmz84l3btfeEz3y+jRb8nnny+X1auryl9/lZd+/a6Kqpzzzusr7723Vd5662+5+OIrAn/+mWeek7/+KiIi2Mb5ZdOm6nL//Y9LdvDss6/Ili3oj4Vl//7SsnDhbt+2juG9996Tb77ZJOvXV5N162rL+PFfuLZlUNCf+/cfIcOGjZG+fS+VaGCH3uWXD5XXXlssnTv3dE+mCgp61ZlnnitPP/299Ot3vXt6SzQMGnSDXH31KOnde7BMnhxMb1RODLBJPvpovaxefZ6sWtVdrr761sBlMMaHDn1AVq7sK6tW9ZVHH33rsJM1/XLzzf+TNWvOk3XrWsuvv1aW//3v4cBl3HjjcFmzprns2lVD1q5tJsOGBTvhCG66abisW4cPpozs319VfvmFK0amBS6nZ88BMm9ebZk/v5706oXPIDhvvz1GRox4RcaM+Vs6deoWVRkvvviyTJz4qyxeXEHeffcXeeWV1wKXceONt8jSpfgrS8mGDZXklVfGutcFBWHu3LkyefKPsnZtA1m7tqGMGzfLPcVJUU5UjnpQ9v7773e3MJuXHiuiKEokONYio+NPON4oo0AIRwbHxeUP+Tve37Fjty8nMEGg0GXEieP4O14lLc2RuLjQx/LGx+d1j87NiHCfh5w588i+ff6MP/eRQiwF6elJ7tHQGbFr115xnPBH16an53STcfweJ8vRc4bU1ATZunWbr8/++5kDIZ4nl2zZsi3QsSx2PWD//oRAZfAs+/b9dzxwf7Df4AXt7zj/HbOpqYXc8v2wfTt9GPo4z/T0fO68yIg9e/ZJXBwB0P8SF5fxWNu3L9U9ejkjmD9+2mb//jRPQCdO0tKCHW20a9duSU212wUZE/kI5tAkWuMtzm2PoEFZxoQdRElLyyM7duwKVAZjdu/epEP/37cvSbZv3xGoDMbb/v3/lkGd/pEP/uHIGLsewP+DzOP0dNrzvzI/NTVJdu7MWCaB44RbM5h/cb6PUT5wINRRO0mya1fG88awZct22b//8KP19+3LI9u2BU1KZHz+W3fGr9/2MOzZw9pi1yVf4LG2eTN9mfSfPuMIX7/jLDU1tDxIT0/0te6Y9Tgu7vByKJe5HYR/2vBf+eY49I0/+fpvXeiXw8cVY8evnGbNd5xQcjqYbNu2jb70rhk5As1jxn1aWt4Q9fBvMu7dy5qQGGF+K0rWkZ7u/Gf+oU9wHKtfSBL3qqqpqfGBylBCg8N2714jxxJk//5gOpLhH10TucI6kbGdFMtwNcm/bZJT9u71Zyd5+UfPyy+OU8C9TiD453d6dN94if5is8yS47B5vH9/vC8bxWbHDmwvW58mcSzYeg6rVq12ddcDBwrL2rXrJRo2b94s+/ejoxSQAwe46ig1cBnYRNhQJIug31BmNKxYsUr27y8ke/Ykuc+mKF6w0/6137D/gutq/yQeYDf9Y8fhZ0CnDMo/euI/8pEyolmHDxzAJjEyNof4NFEOIzUV5TnhMF9QUJkE/8xh2iVX1OvfmjXrZM8e5Am+m+jWC9aIffv+kfd79+aU9es3Bi5j27YdHv0+MQo5vUP278+ZaTmtHEukHaXXsclRt4yHDRvmOu3My89OLEVRTlxKliiRYZbr119/LfXr1Yv4N9yPmiPHAnGc/ypDOXNOlB49uPdMMgz+Fiq0T9LT/xvsSE1dKLVqsasqY5o1qyfbt/9390t6+gFxnD+lTJmMy0lJKSTbt4eWn8uWfSTt2rEzK2MaNarBJzzv7pd8+dZI1apkLEemY8e2UqzYyjC/dSRPnrVSq1YtX3XhftNKlXJLzpzLUT+lXLmNcsklwbLhzzyzpSQkHN4uRYoskwED+vouo169elKkCEaE6edUSU5eIT16nO+7jJYtW0rRomSH2uNti1SuXMr3PS3co1KgwFJxnE2H3nOcVClYcKK0atXKVxk9e54lxYp9EOI3qZI372KpUMHs3gtP1660aeidVmlpU6Rz5zMifr5RowaSO/dXEf8mPX2P5M2b6uv+mU6dTpNcuf59pvj476Rp08N3mGXEmWe2k9KlP3f7BBITv5LGjf3doWxz2mm1JSmJcnZIrlzfSN26JQPd/wjt2zeXPHm+OPi/HZKS8qV07RrsftszzzxTKlT4g9tvuDVUKlT4Tc499+xAZZx++ulSqhRZ+OtcxTZ//s+ka9d2gco466yzpGTJ2YTeDr6zW0qWnCMdOoTaNReamjW5AwwZcDjJyd9Jx47sisyYihW5yzOUg3KNVK/uT043bdpUChRY9B8lP1eur6VvX39328IFF3SV5OTPXLn6D3ulZMmvpVOnYPdcN2lSRRITvz74v61SuvSMwHe/XXllHylU6J2Dz5QqRYtOkKuu8i8b4dprL5XChX9g1rr/j4//W+rWZX31Fzxs3ry5FC785z+nGR1GmuTLt1EqV/Y3l7nXqVq14pIjh9l5uUNKlfol8D2S1113qRQpMtFtD5GdUrLkdLnssmD3oDdqVE3i4ngmwx4pWHCJnHTSSb4+z5qfPz/rsNd5tUhq1y7tux79+3eRAgUO32UfF/e9NGvmbw0G7vQtWPAvd4z9W8YCadjwvyeEhOPss1tJjhyMES+bpUyZY+yeHyXmadCA8W0n/jhSrNhWueQS/7KtY8eOUrLkTktnS5OSJbdJr149sry+Jxq9el0gVavul7x5V0vx4ktl0CBOfAjO7bcPkZSUxVKq1O/yv//dJscyF198oVStukfy5VspJUr8IUOGXBtVOSNHPixVqiyWGjX+lhdeeDLw5/v16y0lS645NO6TklZJ69aclnL0adKktiQmml11uyQ5eaerLwTh3HPPkUqVSHhbITlzLpPKlZNc2zIoAwZcJt2715PTTkuX0aP9n4xiwylf3bufKjVqrJThw2+UvHlDJ7dGAnvxkUf+J3XqrJc+fdoEbg/Dyy8/K+3b55OLLjpZLr20X1RlKMc3nTt3kurVV0mePN9L0aKfSO/ewWxIyJcvn5x1VlMpVuwjKVJkmjRtWkwqVfKvOxq6dGkjBQrMYL+5lC79tQwZEvx0hT59zpOCBTk1aaPkz/+LnH128Luy+/btLgUK/HbQZtomZcpslDPOiOzzCMWtt14rKSnTJCVlugwezGk2wRk48App0yZZqlVbKQ8/fHdUZXBPd40aeyUlZanUrLlXBg4Mvmt32LAbpUQJbPStkivXWqlZs5QkJycHKgM5VrmyIzlz/imJiUukSpVEadCgQeC6KMrxQhxnGGdFQa+99ppcf/31gbevHyuXFCuKkj3Mnj1bRr/xhjz1ZGhjExF2frdu8uzIkZKSkhKxrDffnCC33TZVEhKekBw5CojjpMv+/WOlRo0P5eOP3/IVEProo8/k8stfEsd5WeLj/9lxlJa2XhIS+sr06c/6CmRyPGPr1hdJ0aKvS+7c/wQI0tP3y7p118qwYa3loosydgL98MNsGTjwUTnjjNGSI8e/2WZ79myWWbO6y+efj5OiRTleMjIcX3vaaV1k+fJmcuAAjq01UrLkJ/LSS8Olc+cO4odmzc6U776rIiKHO4/z5PlZLr+8sjz++P3iF3YMcbwKu1Ivu+xiKV3av0Ma2GXVvn1XWbRol2zdmiTFim2RCy5oK48/HuwY1qVLl0rfvlfIqlWbJF++RHnyyfukbdvWgcrgqFWO/9mypaQkJh6QUqX2yKefvielSpXyXca8eT9L167Xy+bNXeXAgbxSuPA78thj10iPHuf4LqNDh4tkxowWsndvr4NZo1ulaNHB8uSTXaRPn/N97Uhr2LCDrFnzmOTM+a9zIy1tteTL11fmzHlXChcuHLGMJk06y/btr0lCQrGQv9+9+3kZPDhBBg26LMP6kG1+6aU3yYwZv4rjJEiDBqXknXeecY3BIPz666/Sv/8tsmPHXjnllLoycuQDbuJFEGib++57XGbO/F6aNKkrd999ixssClrGsGH/k48+miFJSblk1Kj7pHHjxhKUjRs3ytNPv+CWd801l0vJkvZxjv74+++/5aqrhsj69Zuke/fOMmTIdb7kos3XX38jl19OAl6aFCyYQ1544X459VT/jqS//vpLzjijt6xYceHBI4h3SYEC70qfPiVk5MgHfZXBsbHt218la9dyJKDRLbdKSsoo+eyzV9zAkx/efHOs3HzzSFm3DllYRPLkmSP16i2XGTMmBRorkyZNkZtuus/dpZAv314ZNeoead2a4279w4kDgwbdIt9+O1/y5cslL7/8UFTOxueee1VGjnxTyA0ZPvxaOf/8cwOX8cwzz8sTT7wsqamONGxYTd54Y1QgHf7uux+Sxx//QrZuxUlCZv4214nz1FPXSq9e/o/lIgP/kkuukfnz/zjYJo9K/fr1Az/PmDHj5bHHXnTn7iOP3C7Nmp0S6PPYPh069JKlS3O4cppkmtGjn5TTTvM/7j/7bIZceOGDsmYNR7PXkBw5vpKyZZ+RmTNfdxN0/IA+dMklN8hHH61zj/suWPAPqVRpgXzxxVjX1vIL8+f88wfK1q2VJEeOXVKp0n6ZMuWNDOW8vQusadNO8uefHPtYxbwrJUs+IR988IicdFLoqxcUJRpY+9q06STLl6fKtm1xUrLkXrnkkvPlvvuCOS4///wLueqqG2TnzgOSO3ecPProvdKli39dSwkPu2C+++47V//1m6gZTv9DJ0lICH9a0LECu4WwcTk1zo/teKSYPv0zufnm291TaNq2bSGPPfZAtrQvu+yuueYm+eabH6Ro0cLyyisjowrobNq0Sd566x3Jly+P9OnTO7BerygnKvhQuH6pePHi0qhRo6jL+fnnn11ZjS0b1IY0cO3Nn3/+JR06tPetA3t5553x8tlnX8qppzaViy/uG7gu6NRPPz1K3nprgiuTRo581Fcye/gTcRxJSjr8pKGjDT4CZCQ+Qr/JtCF9s6PHSqVK5WTQoKskZ87gJ42xu/b99993E0+6du0a2HdyonOsxNBMPUVuP7hb/Eiyl0uWYr5NQqFBWUVRYp6rBw2SunXqyOWXX36YQsVxicPvuMN1FN48eLCvsiZP/kTuvPMZ2b49TuLj98h557WWu+66OZBCMXnyp3LrrY/Jzp0EmPZJiRIH5Lnn7pQGDfw7gxcvXixXXHGbrFsnkiNHPomPXyVDh14hffr4d0iPHTtR7rtvpJQp01Py5q0o27b9KOvXfywvvfSoNG7cMJBDmTv0pk//WqpUKS/Dhl0TyEHAcUqdOl0gS5aky8aN7HJLlZSUZdK6dS15443nfO8MzUp++uknN7jDTiU/O4+PpIHz1VdfuQoJdYnGOCEYwx0mu3fvkfbtzwzkXAeO07377sdlzJhpkpqaU4oUiZd77rlWOnb0vwty/fr10r371fL33xxX3FASE/+QokX/knfeeVyqVeN+ysjMn/+LnHvuTZIz52j3/tjDn2+qlCr1optIEGQe8lwYONEYA0psQ+LK8OGPyA8//CL58iXJjTf2k+7dzws0f2bPniODBg2XVas4VsmRsmXzyXPP3Rs4G/f333+Xxx57QVavXi89e3aSHj3Oi2rM/XMM3T7XQRitk+J4YuLE9+X++0fK9u17pUSJgnLvvUOkRQt/JzzEKowVjMGGDRtG5dRmzbr//udl0aJlcsYZjeSGG/pLkSJFoqrHl19+I1WrVnJ3wEcz3tCvuBOPZBdOGgkKCV9XXXWr/PTTEvcourJlC8rjjw+Xk0/WgKyS9SBf0bVYOxjzQRP67HJUTiuKoiiKoiixiAZlQ6FBWd0pqyjKEQPn4AP33y8zZsyQzp07S6mUFPlz6VL5dNo06d2rl1zWP7qjsDILwUgcr5nJxvnnLsi9UqxYsagcp/9kmn0oK1euldq1q0n79u2iznzLLHPnzpUpU6ZJnjxJ0rPneXpn+HHIsmXL3OPEcXj63W1o+OWXX+WKK4bL+vVF5MABAtS7JSFhurRoUVOeffaewMf+KoofkK/IVt0toSiKoiiKoiiKoijKscixF5S99SjtlL0v5tskFLpTVlGUY8q5znEmmzZulFKlS7v3ah4PR1gpyokER0MvWLDADZJxr0g09ywpiqIoiqIoiqIoiqIoyomABmVDoUHZ435AKYqiKIqiKIqiKIqiKIqiKIqiKMrR4tjbKXuLiBzp+933icgDMd8moTj6F/0piqIoiqIoiqIoiqIoiqIoiqIoiqKcQOi5n4qiKIqiKIqiKIqiKIqiKIqiKIqiZJK0g68jSZocq+hOWUVRFEVRFEVRFEVRFEVRFEVRFEVRlCOI7pRVFEVRFEVRFEVRFEVRFEVRFEVRFCWT6E7ZSOhOWUVRFEVRFEVRFEVRFEVRFEVRFEVRlCOI7pRVFEVRFEVRFEVRFEVRFEVRFEVRFCWTpB98HUnS5VhFd8oqiqIoiqIoiqIoiqIoiqIoiqIoiqIcQXSnrKIoiqIoiqIoiqIoiqIoiqIoiqIomUTvlI2E7pRVFEVRFEVRFEVRFEVRFEVRFEVRFEU5guhOWUVRFEVRFEVRFEVRFEVRFEVRFEVRMonulD1iO2VnzJghcXFxYV+tWrXKTPGKoijKMYbjONldBUVRFEVRFEVRFEVRFEVRFEU5voKyzZs3lzVr1vzn9fzzz7tB2YEDB2ZdTRVFOeGZP3++tG/fR2rXbi/dul0uy5Yti6pNtm3bJt9//33Un4eNGzfKhAkT5MMPP5Tdu3dHXc7mzZtlxYoVkp6eHnUQ9JtvvpGRI1+QxYsXR12P7777Tm655QEZM2aC7N+/P/Dnly5dKmeccYGULdtJypU7U3r3vk527dol2cWvv/4qn3zyiaxatSpT5fAMmQk0r1+/Xt5//32ZNm2apKamyrEOz7B8+XLZu3dvVJ9nnL/11jvStu150rv35bJgwYIsr6Oi2DB/NVkkNvnxxx/l5Zdfld9//z27q6IcIVgD//7776h1nOMN9KsvvvhCPv30U9m+fXumdJzp06fLunXrsrR+xzLI+Wh1E5u0NDL6FUVRFEVRFEVRYjQom5iYKMnJyYe9tmzZIjfffLPceuut0r1796yrqaIoJzT/BGSvk08/7SMLFjwk777bXlq06OMmggThu+9+kLp1O0uHDm/LKadcKzfffHfguixcuFAaNTpPevVaJj16zJPGjTu5wdWgXH31LVK79nly0knXSJMm7dxgcVAH1NlnXyydO78sgwZtl9NPHyJ33PFQ4HoMGjRczjnnbXn88VPlqqvWyimndAnk2NqxY4e0bdtfZs26X1avniorV34q48efIx07Xhq4Lt98853UrdtOqldvLU8//aJEw8CBw6RVq3vkvPO+kqZNL5KJEycHLoNAee3araVatZ5SoUJzmTnzq8Bl/PTTT9K4cU/p2fNvOe+8b+SUU86NOoDP54KODy8Ehu+++z7XQR4NP/00T6pWPVlOPvlyqVKlmXzwwdTAZVx44ZVy5ZVj5bPPGsiYMQWldet+MmPGzKjqg76Bw/94gLmMjMvs8/D5tWvXZqoM6vHuu+9mKtmEZAYSPTKTmDF+/Lty8smtpFevS6Ie+4MH3y7lyjWQsmXry+23/y+qMniGK664Vtq1OzfqsWr65qOPPopqrTDs3LnTTQYiIBMte/bskSeeeEaef/5lOXDgQFRl/PjjT1K/flupVq2ljBjxYFRl9Op1pZx55oPSv//fctpp18vtt98fVTlTp34inTr1kuHD7436eZCJffsOlEGDhkQ91uiTpk3bSe3aLeT551+NOtmLhJUaNU6Tiy8eGFUiD7JkxIgHpF69lnL++f2iDvy9/PJoqVWrpTRo0FbmzJkbVT369Rsk9et3c9eMk09u5+oKJzI8/0kntZAuXQZL1663SYMGzaNKDrzssquldesB0rXrw9Ko0ZnyySfTJTsgeNmjRz8pV66JVKjQUCZOfD/qdhk8eLhcffVg2bBhQ1RlTJw4ScqVqyuVK58mJ53USrZu3RqVHKhb9zQpX7651KhxSlSJjszZLl0ucOtSsWIdmTIluJ4EP//8szRv3lpOOaWVzJ49O+oEgGHD7nDr880330p2gjz47bffMrX+ATI+Wjmf1WRFshfrjSYB/AvJO7/88kumElaAZJVoZICiKIrNvn375IMPPnBt4+wG31xmbXw2K4wfPz5TmxbQJ849t48MG3ZXVBs5zNrH54cPvydbN3EoR/v44iP9OkZxspAtW7Y4VatWdc4++2wnPT095N/s3bvX2bZt26HXihUr0GjdfyuKooSjffs+jsgUR2Se9XrZufrqWwM1WtWqZzgi3zgiv7ivYsV6Oj/++GOgMho37uyI/OCI/H3w9b7Tq9egQGV8/vnnTsGC3RyRSe4rPv5B54ILLg9UxhdffOEUKjTAEZl78DXHKVWqnbNhwwbfZSCDS5W6wElKcg698uV72Rk16lXfZTz++PNOYuIYJy7OOexVosQg59dff/Vdzs6dO50yZZo5Ip87It85RYp0db755hsnCN99x+cudEQWHHzNc0qXPsU5cOBAoHJOOeUcR+TDg+PsW6ds2VOc1NTUQGXUqXOWI/KnI7LFfSUkvOUMHnyPE5TffvvNKVOmmpOcXNUZP/5dJxrGjZvgFC5cyxE52Slfvqa7XgelWrWTHZEHHJGnHZHHndKlGzq7d+/2/fm///7bSU5u4Yg8ar3ucRo3bh24LrNmfemkpFR3Spas4YwZM86JhrS0NKdt205OmTLVnbfffsfJTvr1u8IpVuwkp1SpWm5/R8OUKR85ycm1nZIl6zgTJkyMqoxPPpnmFC/e0MmZs73TuHGLqMpAz6tZs5FTuPDJTo0aDZ09e/YELmPu3LlOsWL1HJGLnfj4zk7btmcHLmPKlKlOwYKnOSI3OCLXO4UKNXNmzJgRuJyOHc93cuRgLvd223fp0qWBy0Amly9fx0lKOt2pUqW+s2PHjqjGa716zZ2EhA5O8eINnBkzZjrR0KrV2U5CQncnd+4uzgUXXBb48/v373fKlTvJERnriNDGPZ2JEycF7t+iRXs4Il8cfH3upKS0cdatWxeonJ9//tkpXpw1414nKelC5+qrh0T1PJUq8Tz3OfHxtzrNm3cMXAbrS4UKjQ/KtOedIkVauWtRUFq2ZN25yRF5wsmV60Jn8OA7Apfx4ouvOfnzn+eIvODExw92OnbsFbiMf/qnnSMy0RF50ylbtmngefzuu+85+fN3cUSedV/x8dc7/fpd7ZzIXHXVtU58/KmOyLkHX+2c005rG6iMmTNnOoUKGbnG62qnfPm6TnZw332POElJPMftjsgwJyWlQeA5DKef3tGJj+/niAxwatduFvjz6DOlStV1RK512yQurpfTtWvvwOU0adLGEbn14Dwe4dSq1TxwGbfdNsLJlYs+7u6InOeUKlUjsL6FLly2bA1HhHWng1OmTA1n69atgety4YWXOblyNXdEOjopKTVdHSy76NPnUqdYsYbuc/31119RlYFcQl8rW7Z61HpSVtGrVz9XBx048Pqoy7j11hFOcnJNp1atRm6fK47TufN5TrFiDZwKFWpGJUvg1VffcEqWrOmUKlXdmT17dlRlYO+1b9/FqVWribNkyZJs7Rp0CcbII488HnUZ6CgDB17nPPPMc5mqy403DnXOPvv8QLafcnRYs2aNK/MXLFiQrU2+b98+58wzz3ZOPbV1pvz7PXte5FSqVNuZPv0zJzs5/fQzndy5mzvFi9dx7exoWL9+vVOv3slOnTonuf0UbRmVKtV3SpZs4gwdGtw2gLVr1zplyzZwcuQ4zylbtn5UMnbZsmWuridynZOYeL5z8cVXRlWXpk3bOvHxVzo5clzutGjRKaoyTmSYW8dCDM3UU+SKgzr6kXxdcUy0SSgytVPWm9nWu3dvSUhIkLfeess9vjgU999/vxQsWPDQq2zZsllVBUVRjmNWriR7vrTn3Zoyb96iQOXs2ZMgIvkP/X/Llrry559/Bipj+3aywkpa79SV338Pttvhl18WyrZt1Q79Pz29uixaFKweP/zws2zdWtd6J052764hf/zxh+8y2AmwZ89Jh72XmtpMvvnG/06sefOWyP799f/z/rZt9QO1LVl7qalVRSSfe5DD5s3NZe7cYJmJfN+WLbWtdxIlPb104IzpjRvZJWjWpyQ5cKC0uzMzCP8k/hU59P8DBxrJb78tlaBMmjRZVq4sJGvXlpNXX31TouHDDz+SLVtKiEgJ2bEjSZYsWRJ4R8A/GyfzHnwnQdLSSgTa2ckRpTt2UAebJNmyZY8EZezYibJmTWlZt66yjB79jkQDOzZ+/fUvWbmygjzzzPOSnXz11Q+ycWNNWb06OepdT2+9NUHWrq0l69bVlTfeGBdVGZMmfSwbNtSS1NS6smbNTjdDOCgcb71pU7xs2VJRNm/O4f4/KHPm/CgbNxZzx1l6eklZtmx14DJ+/HG+bNtmxlucbN1aXH76KXim85Ilf0taGmtPklsGu32i2UW5eXNB2bOnsmzZkifwmmN2k23cmCYHDtRz+2jq1OjGydKla+XAgfqyd28T+emn4MeHb9q0SVJTk0WkgNuu27Y1lW+/nReojHnzfpZNm2p41q6qgY8xnj17rtsWIoVkz56T5euvg+8oY2fenj2MtQqSnl5HVq0KvkOHtWHfvsIH24S1q6bMnRusTWDVqk2H1p19++rIt98G36E6Y8b3smNHA7dN09OryZ9/rgxcxk8/0T+UkcPVl/bvLxM4O//nnxfKjh3lD/0/Pb2S/PprMH3teGPhwsWSnl7QeiePbNwYTK/4448lsnWrXUZOSU1NjEpWZ5bvv/9J9uwpd/B/OWTfvpJRncSxYsUmVwcWqSRbtqQHfhZONklNLXpwvKKvJMuSJcF3IG/ejNJGOVBAduwIviPzhx9+kn37TBk5JDU1v6xcGWwOrl69WvbtyyMiuVwddu/evFGtoz/++Ivs28falVe2bi0Q1dqVVXz77RzZuLGKrFxZQL76KvjJM/DOO+/KypXJsmJFcXn33UmSncya9Z2sWRP9OgwTJ34ga9dWlbVrHfcEJoV1Y5Fs3FhW1q1Lcq83iIbXX39b1q2r6urTEyZEN06QKT/99JcsWJAkY8dOyNaueeKJkbJgQW4ZOfKlqMvgiqG33/5A7r03+GlaBnaojx49VmbOXChz5wbXTZQjy+jRb8mbb34k99//aLY29aJFi2Tu3L9l3rzN8u230Z3QwIkTM2Z8K0uXFpenn84++xzfx9Klq2Xv3sqyYUN5ef/9KVGVw5q3aJHIggVxMmPGjKjKmDNnjqxdW1LWrTtDJk36JKoy2O27eXM5SUtrIFu2lIvq1CVOMuCz2F3799eRuXN/iaoua9bskPT02pKWVleWL8/cCRrKsUD6Udglmy7HKlkWlOW4YgTvpEmTJH/+fwMeXoYNG+ZuVzcvlB5FUZSMqFmzAu6ow97LkWO2tG59eEAxI4oUQewZ52K6FCv2rdStawc2M6ZUKRxi/wa1EhJmStOmwcpo1qypFC3646EFJDHxe2nevHGgMtq1ayFFi9rOjTTJm3ee1KlTx3cZDRo0kDx5PjvsGK6kpMnSsWMz32WccQZlzPrP+4ULfyX16tXzXU65cuUkb17alSNVdkuJEp9Iy5anShD4PvrUTcpy2SGJiaulSJF/g6N+qFy5hMTF/XzwfxskKWmNFC1qHG3+KF4ch9q/DsqkpOly6qn/DV5nxIUX9pbq1fdJuXKr5NZbb5JouPTSvlKy5BrJlWuVFC+eLrVqEcjwD4lWRYvmJlx98J1dkivXeklJSQnUNwUKsObbR75tlZQUghnBuPrqy6VChbVSpswSGTr0eokG+rNz55ZSs+YGuf/+OyU76d37fElOnisVK66Xbt26RlXGDTdcKWXK/CalS8+TIUOuiaqMyy7rLaVKzZeiRTnmvZzkysUYDkbFihWlSpUCkpKySCpXzi+VKlUKXEarVmdIcjJyeovkzv2XNGwYbLxC69anS9Giyw8ZAsWKrZIWLYLJEzj55AaSlMTas06KFVsvTZo0CVwGnylTZq+UKLFIyEWsWbNm4DIKFCgg1aoVc/umdOlf5MILe0g0nHxyHcmf/yspVOhz6dChZeDPFy9eXPLnRw4QaNgvRYtOl06dWgUq47TTTpUSJWZbsoC165dA64UZJykpBD+XSIECH8n553eSoJQsWVKKFdsp8fE/SK5cX7jjPiisLwUL7sSV68rGEiV+lJYtTw9cTu3aFSUhgcBJmuTP/42cc86Zgcvo3r2jFC7MMdvbJVeu7+Skk/zrA4bTTz9VSpZkHeWZVkr+/GukdGlvUlxkWrZsJoUL/3aoj3Plmi8tWpwiJzLNm58suXLZzqdtUqlSsOTkhg0bSLFiG6y5s0fy5nWiktWZpWPHNlKgwMKDddkjefKskapVSawLRv36VSR37u8lIeFHKV++YOBnYc3JnZuEhn+u3ciZc6k0bdowcD3Kly9p6WxrJDk5vD8jHB06tJV8+dYcbJN9kpS0y61fENCFCxTg6HIC9lulQIG9Urly5Sjq0kby5Vt6cO3aLo0bB7MxspILLjhPkpN/lapV90n79u2jKuOqq/pLrVo7pU6dfXLJJRdKdnLxxT2lcuU/5eqrB0Rdxk03XSNly/4u9eqVkPr1g9sGxyOdOrWRlJQlUqlSnJx6anB9DYYNu0lKl14kFStulAED+kVVRoUKFaRr1zOkZct8MmBA8Kt4spJ77rlD2rUrIg8/fE/UZVSpUkXuvXeovPbac1GXwcabe+8dLldc0UWaNfPvI1CODldeebk89NBN8tBD0Y+TrAAf1Pnnny5nn11PWrYMbmNAzpw5pX//PtK4carcc89wyS7wfZxySj0pXnyRlCq1VAYMuCiqcs4880w544wS0qpVMenUKbidAqeffrpUr75HSpX6WK67Lrp156STTpLSpVdL0aLfSqlSa6KyZymjeHH0pKWSL9830qFD66jqUrt2WcmV6ytJSpopDRsG1xsV5Xgiju2ymS3knXfekb59+8qUKVMCK9rcGcGOWQK0OJwURVFCQfZ9ixa9ZfnyS0SklhuQrVz5Xfnhhw9dGeIXdihx1+mOHcVdp8sdd1wuV155ceAs9tat+8imTfUkLm6PVKmyVj77bKwkJSUFKoc7Ux96iMzXRKlfv5y8++4rgZ1R1157u4wfP0927aom+fPPkXvvHSj9+l0QqIzHHntRHnlkimzZ0kUKFvxZGjXaLB9++IrkyPHProOMYFdDo0adZdGi2yU9vYXrUE5KekU6dvxJJkwYFTib94orbpXt23fKnXdeKx06BHdKP/roc/LII++I41SUXLl+l3HjnpCTT24aqAx21nbrdqUsXbpRChRIkLFjn5Tq1dnJEWzMtmvXT7ZubSjx8VukceM0+eCDV323a1bDLjR2Rp9xxhlRrbfs1DjnnItk48a9kjevyJgxo6RRo2COz9tuu0eef/4zd+7kyLFTUlJ+kk8+eTNwkBiM+hLuZI5jDXZCIkNwfGTm1BKIj48+547dz8g4AmTRlkM92IlMsCraMsgKfuqpF6R69coyZMiNrpEelJdeek0efnik++/hw2+Qvn17BS6D+95GjnxB/vxzmeuAxbkVDchJZAIO+miexdSFTGdOmSlWjN2d0fXN559/Lrlz53adntHMH3Z+9e8/2N3ld9NN/aVXr26By+AO2Vde+czdIUtA9p57Bsoll/QOXM6CBQvk9dfHSaNGdaRHj/Ojeh5skVGjXpECBfJJ//4XR9U/7CQdNOgWt03uuON6adMmWKDa3Pd73XXD5KeffpWuXTvIsGE3RvU8Y8ZMkNdfnyBNmtSVESOGRPU83J98++2PSaFC+WXkyPvcQFFQ7rvvMRk5ktOTEqVx48oyfvyrUY/94wF2f3Tq1FXmzyehIYeULJkgn38+NXDC1wMPPCpPPvm6u1MhKWm7TJo0OnByYVbAGnzHHffKhAlTJVeuBHnxxUeladNgupaRa2PGjHXvS+vbt7crm6JZL/r1u0b27DkgDRvWlLfeejGwPs2O9549B8iyZWukVKkiMnbsS27SRtA2GTr0dvnww08kT57c8sorz0YVcGMNvuWWOyQ93XGTxqI5WYy60K6LFv0ul156kRtoyk64p56+zYx+ohz/cL8gunBmxsnxZh8oipI9IEuwM/5J4IzO7oo1+YovCJ9WXpw5UbBs2TJ55ZU3pUaNKtKrV8+o5Cw778ePnyAJCTnkvPPOyzbf2LHKsRJDM/UUucz1dx9Z9ovIyzHfJkckKDtv3jzXqXPXXXfJzTfffNwOKEVRsh+cng888Kz8+ONCadWqqdx445WBArIGxB5HMPLZaB2EXGzPcVN8vkaNGlEbj9SFV2aMT4795cjihg0bRtUexgH09ddfuwEHygkKAZjBgx+QL7/8RRIS4qRPn7PkllsGZZuSxdpCcAlHVnbsILEDMQRD8+TJ4+4YPB4cBIzXzDwHR5IRRElJKSEDBlwc2CGtKMrxATIa+fjPLnq1AY5HskLHOZ6gLf45bjfVDZJFqyOh46DHlilT5oQOdCuKoiiKoijKicKxEkPToOxRCMpu3LjR3fZeu3Ztefnll//zewxNjjk7HgaUoiiKoiiKoiiKoiiKoiiKoiiKohwtjr2gbL+jtFP2tZhvk1BEf0aeiHtcMUex8Qp1r1z58uXd7e2KoiiKoiiKoiiKoiiKoiiKoiiKoignKpk6S+riiy8+dCxVqJcGZBVFURRFURRFURRFURRFURRFURTlRCDtKL2OTfSCH0VRFEVRFEVRFEVRFEVRFEVRFEVRlFg9vlhRFEVRFEVRFEVRFEVRFEVRFEVRFOXo7GRNO2YbWnfKKoqiKIqiKIqiKIqiKIqiKIqiKIqiHEF0p6yiKIqiKIqiKIqiKIqiKIqiKIqiKJlEd8pGQnfKKoqiKIqiKIqiKIqiKIqiKIqiKIqiHEF0p6yiKIqiKIqiKIqiKIqiKIqiKIqiKJkk/Sjc+Zouxyq6U1ZRFEVRFEVRFEVRFEVRFEVRFEVRFOUIojtlFUVRFEVRFEVRFEVRFEVRFEVRFEXJgl2sR3ona7ocq+hOWUVRFEVRFEVRFEVRFEVRFEVRFEVRlCOIBmUVRVEURVEURVEURVEURVEURVEURVGOIHp8saIoiqIoiqIoiqIoiqIoiqIoiqIomSTtKOwHTZNjFd0pqyiKoiiKoiiKoiiKoiiKoiiKoiiKcgTRnbKKoiiKoiiKoiiKoiiKoiiKoiiKomQS3SkbCd0pqyiKoiiKoiiKoiiKoiiKoiiKoiiKcgTRnbKKoiiKoiiKoiiKoiiKoiiKoiiKomQS3SkbCd0pqyiKoiiKoiiKoiiKoiiKoiiKoiiKcgTRnbKKoiiKoiiKoiiKoiiKoiiKoiiKomSS9IOvI0m6HKtke1DWcRz35/bt27O7KoqiKIqiKIqiKIqiKIqiKIqiKIoSE5jYmYmlxT4HjpPvOE6Dsjt27HB/li1bNruroiiKoiiKoiiKoiiKoiiKoiiKoigxBbG0ggULSqySmJgoycnJsnbt9KPyfcnJye53HmvEOdkcXk9PT5fVq1dL/vz5JS4uLjurcsxmSRDQXrFihRQoUOCYLiOW6nI8lRFLdYmVMmKpLrFSRizVJVbKiKW6xEoZsVSXWCkjluoSK2XEUl2OpzJiqS6xUkYs1SVWyoilusRKGbFUl1gpI5bqEitlxFJdjqcyYqkusVJGLNUlVsqIpbrEShmxVJdYKSOW6hIrZcRSXWKljFiqy/FURqzV5USEEB4B2VKlSkl8fLzEMnv37pX9+/cfle9KTEyU3Llzy7FGtu+UZRCVKVMmu6txzIMgy6wwi5UyYqkux1MZsVSXWCkjluoSK2XEUl1ipYxYqkuslBFLdYmVMmKpLrFSRizV5XgqI5bqEitlxFJdYqWMWKpLrJQRS3WJlTJiqS6xUkYs1eV4KiOW6hIrZcRSXWKljFiqS6yUEUt1iZUyYqkusVJGLNUlVsqIpbocT2XEWl1ONGJ5h6wNQdJjMVB6NIntsLqiKIqiKIqiKIqiKIqiKIqiKIqiKMoxjgZlFUVRFEVRFEVRFEVRFEVRFEVRFEVRjiAalD3GyZUrl4wYMcL9eayXEUt1OZ7KiKW6xEoZsVSXWCkjluoSK2XEUl1ipYxYqkuslBFLdYmVMmKpLsdTGbFUl1gpI5bqEitlxFJdYqWMWKpLrJQRS3WJlTJiqS7HUxmxVJdYKSOW6hIrZcRSXWKljFiqS6yUEUt1iZUyYqkusVJGLNXleCoj1uqiKMc6cQ63BCuKoiiKoiiKoiiKoiiKoiiKoiiKoihHBN0pqyiKoiiKoiiKoiiKoiiKoiiKoiiKcgTRoKyiKIqiKIqiKIqiKIqiKIqiKIqiKMoRRIOyiqIoiqIoiqIoiqIoiqIoiqIoiqIoRxANyiqKoiiKoiiKopwgOI6T3VVQTgB0nCmKoiiKEouojqIoSnajQVlFyUbS09Oj/uzWrVvleHiOWCXWninW6hMNaWlpcjxh+kQV+qxF2/P4blPqEkv1yQzHy3PY/Prrr7Jr165Mt8nx2DbHwzP98ssvsm3bNomLi8vuqijH8TgzZEaWKLE/3o43vf54nYexRCy1ayzVRYk9jqfxsW/fvuyuQkzx448/uj+zQhc+cOCAZDfH01hVlBMNDcrG6KK5Z8+e7K6GcgSZOXOm+zM+Prop+M4778iIESNc52l2B/swyM1zzJ8/X45lheTVV1+Viy++2P03z5SZ8rztGrSsb7/9Vl5//XV5+umnZfXq1W59MtNX0X7W/hyO3Gj58MMP5YUXXsh0MsHYsWPl2muvlewGGR0L454+WbduncQCd999tyxYsCDLnLixYGBk1uEYKwEq5t3evXsPzeFo65MVDlgM4OMlIJRV7ZqVZKYOrDn16tWTiRMnZmr+UofU1NRM1ycWWLhwoXz//ffy888/Z/u4/e233zI1B9FxevfuLZMmTcoSJ1Jm+nbt2rXy559/yubNm6MuY+jQobJs2TLJLIzZzNTDkNmxPmXKFPcn4yy75w26Vmbl/csvvyz9+vWLGZs2M21qy/nsJivGxpIlS1zddfny5YdkdVDQ6UeNGpVlSaOZKQd5ltl2oT2+/vprmTZtWtTzcMuWLbJx48bDxnx2z+XsBht25cqVsn79+kzLt8zKJGyUH374wbWxo60L+tHxkCidlePzq6++ktmzZ8vxAnpfVq3FmRkrJNHNmDHDbdtVq1Ydej9onT744AN55JFHXNmUWbJKnmWnXBwzZow0adJERo4cmalyvvvuO/dnQkJC1LIJvT4ryKx9klUJdLHip1OUYwpHiSmmTp3qDBo0yOnXr5/z3XffZaqsAwcORP3ZDz/80Bk+fLhzySWXOO+//76zevVqJztJS0tzYpH09PTAn3n++eeduLg458cff4zqO19++WUnV65czsiRI53169dHXZ/Jkyc7V155pXPmmWc6DzzwQFR1GTdunPO///3P/fcNN9zgNGnSxNm6dWvgcsLVO5r2jWbsM762bdvmFClSxO2bHj16HPa7oOzfv//Qv7/66qvAn3/ppZecMmXKOCeddJJTs2ZNp379+s6GDRsClXHjjTc6o0aNcubOnetEi/3sjz32mHP77bc7CxcuDFzOokWL3HatU6eO8+KLL7ptHQ0vvPCCW06FChWcVatWOZklWhk5duxYZ+jQoe6/r7vuOqd8+fJRjfvM8vbbbzutWrVyypYt65x33nnOypUrnewCWUTftG/f3vn999+jLuedd95x5cjatWuzrG7RyJEFCxZkyVq6Z88e92dqampUdZk2bZorY++//353XY6GMWPGuHK+bt26zjnnnOP89NNPUZXzySefuGNu586dTrRMmjTJueaaa1wdh2fasWOHEysE7ZusatfM1uPyyy931+Ivv/wyU+U899xzTs6cOV053aFDB2fjxo1OUBgfZ599ttO4cWPn4osvdmbMmOEcy7z66qtOxYoVnapVq7ryjTbKKoLqFqy/6H60aTR6CX2TO3duZ/To0c7evXujHitffPGFM3PmzKg+a6AOp5xyilO8eHGnZcuWzoQJEwKXsWnTJqdo0aLOySef7CxfvtzJzJrTuXNndx298MILnSlTpkRVjt0O0egDr7/+ulOoUCHnySefDFlmNPWIthz6mPE+YsSIqNc/5gplYENmpi6ZZeLEic6uXbsyZUciX5HxVapUcfr27et8//33TiwQ7TNhR5YuXdqpVKmSKxOw9dE1otHHad/MwPcy9jPzTO+9955zxRVXOKeffrprz0ajg77yyitO5cqV3T4uUaKEc/PNNwcug+cwOjnj5Y477nCixdsOQefNkfKbBK0H7dqwYUNX1iOrr7/++qi+d968eYf+Ha1Moi7VqlVz7evq1au78i0on376qTvu0V+PtizzcqS+P2i5+CwY80888US22MJZDfKePh4yZMih96Kx3TIr12jX5ORk1xdUqlQpV7698cYbgetEOXny5HGeffZZZ8WKFYE+a/Pxxx9n2mZbs2aNq7sZ+yKadjGfjXb84z/NkSOHuwZedtllUZf1wQcfHPJ7GIyt75dnnnnGLWPp0qVOZkAu3Xvvva6/YPz48YE/jz2LLZnZemS1n05RThQ0KBtDsGimpKQ4d911l+u4jJbffvstU4orTqikpCTXOUEwCIdjixYtDivXL1ntcP3111+j+lxWGCezZs1yHn/8cefBBx90FZNonRQJCQlROaDgl19+cZ2DONcA5ffvv/923w9qmODM6t+/v+s4TUxMdIYNGxa10wWnWoECBZyff/45U32DIc2z/PXXX4fe86MoEYC85557ogqA2t9BMPbhhx92HRXnnntuyDpmBH07YMAA998Yn7Vq1Qrk3EYxoi1RqrZs2eJ89tlnbmDWVpQyahMUXhQ9+oW5i3OANt23b5+vz3v/ZvDgwU6xYsXccecN/Pkpi6QOZAl1wemB0kYdgyYzEDB46qmn3LowF4OC4wmlFQdO0GfwykjGfbNmzVwnqpl/QcohWJ6Z4CWGGeMEB9Sbb77pzuebbropW2SjKYMxhjOLQNXixYsDl0MSAe2KPPr666+jqt9HH33krqF9+vRx19Gg48wE3akHiSaZWUvfffddtx6M+1tvvTWwgYLjNF++fG57NmrUyG0XEmkwaoPIeoxxnCXIyLZt2x72XEH0E+qCzDdJWkHnzWuvvebkz5/fueqqq5yrr77aHb/Nmzd3E4SC9LPpi8yOXRIJGLP2GPH7TFnVrkCiC0l4ZswHqYeRzzikkQEk9X3++eeHfue3jZDJOCkISDFv6Ov58+cHKoPgFkFDZBJr3/nnn++WiewOAo6BRx999D96cFY5pf0+D2twwYIFXXmAPKOfcTwS4AlaH9rSzH/GSbS6yhlnnOEGiQnMBpFJ27dvd/UA1k9YtmyZ89Zbb7nPRIDJPJNf2ci8JXBnCNIWyAHGF/KeRA+eqWvXrk40oI/Url3badq0aVSBWbOO4mBnLhMopp12794dqBx7TCH3CfIa56df0AeYy+h71CWatrX/Fn0NuR0tOJTRuUjQDepoJPmOz9IWwPiiDHTaIHz77bfuOkhdorEv0LOYs+jzXbp0cedx0L7lu5EDd955p9svBO3o32ggQZHkGZJyN2/eHPjzyEa+m4BhtEl42LKsw+ixrH/oj2eddZabSIMM99u/yHbTvySi8gq6JiNjkSck4pGoYQhSDs/B85AoyZqDbCJZ0tg7fu02ZBLPwzh75JFHXFngTV6JBG2XN29eVzdATt59993uenjppZceSs7zO5ft5//hhx8CPYv3e5BxOOpZh4OOfWCcIVtte8Xvc6DboSch82lb7GvsN3TadevW+a4DsoxxQjJftDo5gTb6h5/IBQJu6G12OUH0JXw52JPRBojROzOjw9qfxSb4448/oioHnQ+9kWQTe93xC/Y0cwd9IrOgJ6HbBLUJQpGZZFp0E4JKPBdtE5SskGv4ftDp8QkhP7755hs3WTJociBrKAFd0z+UhawOmnRpNpRQXrSw1pCYgV8Mn5CxMYKAvEe3MHZOULuA52DtIrHQJFh4E1qDBGUbNGjgPkvr1q0Pve+3TvQjawTrRWZgzUFH6datm6sf0D7ISju5PKPnIDmLtrjooouiTnLMCj+dopyoaFA2RiCT2Dh/MgOKK4sNBkk0iglOSpy/KCS2wtWpUyd3N1iQoChKCc5Xv4tCKGwFBicWCwYKdbRl0D4EH9lxwCLkF5wCZHmiENWoUcNdhFEugsDfU3+jSOCwmT59upu5RsDbj7MCY5r+AQxHnFkEaVG4yNQyzuVIih/fj5PCVqCpG/2LgR5UwSGDj+e69tprnaDY33Xbbbe5Cqwx2AYOHOirDNrNOBXIUCaTkCCZXyejDQFqHMoYBSjDPXv2dN8nyLNkyRLfBg7tgZMwaKCa9iejmDFhwIjGyYDxx7gNssOa8YDDlbqQFUx2oBkjfvsZg4JsQjtLGaX+zz//PPT/SGXxO54BZwm7HzFwCMwy/nBKYaxnBPW2kxlw+ONAwrEcBJwmOEj4LAFVjB4z74KOe8ZofHy8G4C3d0b7gWdHAaYu0QQvUZjr1avnGieG++67z3Usmx2mQQPvzCEcN8j7aHZCmnWGMWzmcJBnQ5mnjzktok2bNodlngYxTAoXLuwaFcwjnNsmIBTEGMYhh9GIU85eS4OUYQKqZOJTH8Yc7/ntG8Y2ySGmjwmqIFuQKTiY/RhNBKhJ9LKTgAgIESAmYcqctJDRcxnngEkGMn1tHHx+2gV5gQyy1x1kGQbcqaee6u628dMu/B0BXdrD73eHk2t8L89F8gonAfglq9oV6F/GKWsyP0kw8ovtVMFpi46EXON57B0gGbWrcbbYySqUw45Xv/ojz4pDwE4MQbaybqGTmmCgnz4m8Y3642gnqcGWc3772/4eHKj0DXUxbZbRcyHTWf/NiQiAXsA6Rjvj0PGzI4R6EIjhFA7kK8Fz2jpogMk49QG9j7mELuc3WEZd2SFEIBW5jN6IfEOfNYG3jE4nQJdArvbu3dsdG+3atTssAcBP39J25cqVO0x/xlnPOoqDLhpnELo0cydoYHb27NluO9rjCxuH5Bdknl/sMcm4uOCCC9z+JgksaOCM9ZPALPWyHVp+2tYbyEEfRk/w7lTNCHtuGLuFNdGvnkMf23Yo46179+7u2MFWYR762Y3BeomcRRaRiEDgPmigG1gr2LXEuknSGLsX/dqljHnvGCH4gf5mJyX4gTLQfZl72PvYOCTVBoHxTaAdOcTaxbMwjoOAfYEM8T4nTlySsDOyjUmkYEygbwHyDb0eZzsyk4QaPzDXsPmwHekb6mTvAvMj65HJ2K52MJm1HBnjNyGPwCs6mr2rlQAINiU2up9dR6z7nFZj73LndCPGPG3F76K1i9Ed8cn4tVG8nyfJHp2aetDOti2XEfQH6wQ7S9GJsTGCgO1sPzt1Q+9jPhPEMH0c6dmQJ6xTzH/0JOSqwa9+gk2DfmKfCoaspj34yZj2M+7s70M+0aZPP/104KQV9E/GO8l4mT0NAV2JMVKyZEnX/0FCtt/TqJAlJBZjiyKjkbd+EzOoA+3B3Df6JoF7dAnmEzZpkPUY+YjNw1pOu1IfY2ME8Vew2SCzgVn8EiRnsQEDWc/pPoaMkmszK9fMs5LUYXxQBnQCkhzQUdBr/T4LuhrgayRox3gh6MzY9bN5xpyiE25DiZ/+oQ1IisDeYNzhV2bcBSkD2DCEfoF9bTbI2P0cqRzawrZ10IuRjdSDdSDoXMQmR8ZTHvo1SR4G20cWCtZPfB5mvSWxgrUcfS1IggW2BOudHT8gkcyc+peR357kGHR65i16EuOd/wfVxbPKT6coJyoalI0BcKbheGLRD6rY2WAgksHLokDWTjS7fBDCONS9RhkGPgs5wUh7F2M42OGAcMYYwDCPJvBgL4449FBGWGRwuhvncBBwdGBYsNiQbUxZdvArHGTsEZA1Cx7PT0ah2Q3pZxHHOETBoz0Apy3Z/ThMUFIw1NkBlZGyh8JJ36LU4YDCYUimF4oJRgtGcSQYXwSlMU5sJx9GEkek+Fk8vQolzk4yTglQ4WwJGgwClHccDIxh2sD0D+MuEva4JgiL8kEwBwWFjFy/O9PMM7FrBCMW5syZ4/Y7CgoBJhxSfhU2FGDqbxTqIIoeChlODgPzDmOrY8eOh8o1R0JmFAy1oU2ZvziGwyUA4OjxHueEEcvzG4OLuchYw7FkO6wzgrKNskZdkFUEe0877bSIn8NgRiaZjHxAPuH0JDgSNDDDuEf5xSBAmUYuGMepn/Y0MprP4XCgP5hTfh1AOBhwbjBOSWggcSWofETZp/1shzjtSL8wjzAyUPj9tgvOKOQQBj3PYxzkQTFtEzQwa3bImvFB4M77fBmBU8UbKONYIvo4KBgXBOweeugh10FgB2b9GLCMT2SHPWaZvxjAjCMjeyP1D85aHBRGBprxhwFGYBbDNBKUzXqBPLPrjCPMzF/a2DjsIx15iQwg0GB2deK8pRxe9jGmkaDefK/RH9B72HFLwgnrHz8zmkPUlXUGhx59Em1glkCD2alHmcgjxr4fQzgr2tVAOcw79Bkcpche1nA7oSjcs+GwIjDmNZxpU9ZkkrdsR1K4etAPjHPjpDBrKvoWcsoY9Bm1MQ4NDHCzftpQPvMbXSoS9rpnHEiMc9rEdsRmVBf79+gmyCJ2qzOX6R+jF0TSi+kD9DP7BBHaG/lK25LdTt38Xu2BTMH5iT6Bzhbtrina0DiDWc/Rmfzo9+ic9A+64i233OIG/81OPRxuyBSTIBWuXuzkZrchCWoELVlDvYHZSFAuSTcETexdgpSBzoZu7+1rv20TNDBLXdiBQh+aQB/tyBqGQ9UcYRxEd8Pmok+QJwRECQBi22UUePOOZ9bMaAOzwJglEEIwE/mCzcCz+sH+DgIwyCTsFsYb+o6fsUaAj/WO+UKADvlOmxDYJeHCBCSRn+GeCZloEpXpE+Qp7ZmRo9NA8gM6vBfsAtoFZ2VGCY7UjbnG35qEBepCvZGNQY77JZmY+c/ag/zBQY09mpFMNLCTx5ssR/CFdYexFuTIbRziOOS984TdgzwrgYRIyQQkvSJTCbwgEygLW4f1hvfQ6/2cGkFgnnGA3EcnDxXAiDTmscnY2YdDHd3BjE1kC7qTXx2WPkUXx643MHaxiZk7jDsSnSLVhfUPm545YkMCGfMReyXU2hgJdmaz3qBj+b3Ow64jcprAsgnaY78x5pDbfq5aYKwSACJYRjIceiDrJ8nhfkGW07ZeWccYon0ZL5GgT00f05/UCT3fXiP8+M2Mz8QO2CGjzBHerD/eRIVIbYscI2hGcAzZyP/96qHYrdgH6BCsNcipaI9hxZ5nfCIfkUvINoJDfk5Pw1aiHmajAwlrtEHQa1KwN7FtmM8EzfFZoJ8iv7Fz/VyhRB1IwiMBgvUY3Y+xF2SnHXYXbUp/kGCfmcAs6wzjAxnD+DeBWdoHuyFSmZmVa7buityx7QzaA1uMQDjzKlJyk/kO9G/kOvOEcU6wDJ0PvxttRTAuUp2wx/k7o7fiJ6S/8BugTxp9OtL4R34xNu0dvugWPCPjzo8ebcpHfyX5k+9n/qFTAn0SKXGMdsRn5V0rKQcfW9ANC8BYJVkE+Y/fGx3U+OBZn8OdtMB3YV/QH0ZWkxDFe7Q1fgu/x+fTL8g2ns+0EToY19Awbnv16hXx8yRwIFeNX5HPBg3MZrWfTlFORDQoGwMgnFEywykfRpBFulOSv0GBxwGAockijIFg77rwo5iwgKAEsBh4FxOcMDhOCVxllHWD4wYDBOMPpRcFIprALLA7EMURpwJBVJ6RhTjIUSkYviiL5tgNc19ERkd74fQlQGGc8maxxlBnMQ1yNyYZkey05Vn4LI5TcxwQjgIWYZwWGSkAOKRxOBDwsIOOKGcoFhkFmlGQ7d2JPBNGLHXKKHvcXlRpf5QbYxChbJnArI19JCOYzEczHmlDlHhjGKBgoZxzPBaEU2pQejEQQx3rhNKGgsPPIHdTkhVtjiUjcGLuW0I5D3JfF44o5jOfJdhuB8Ajfc77Hn3JnGOcmOfEWcAcpd29n7f7x/zObj8UYJQ+k/ntVZJQ0slAZBya3xGEpS2Zdyh5GATMSZ6RsZzRmDHjg+CjvZsaZwMOQxy0kXZmohQaB4JdXwwdFNGgx3rZIMtoXwz+SEaB/b0mEGRgnCJLmM+2o9k77m1DGIMVY42MUeZ90MAsRgztRzkEdpArBIKQcwTxkL8EFcM9k52dTttjVJjjNJkDyAKcJRnt5oqkZCOPqGNGgVmCPqxV9r1kOLGpA45pPxBAYa5jbPJvY5ixFtIuQY9pwgGK04e5w5xgzlA2RjCGV6S1FPmG8wrnnD02CfoRGMJpj4wxDuFwBiB9h1PCrFH8nZlLOMXIWs7oWFiSL+w1AsMcmYYhzQv9AFkbbg6buuHIQnbw/egqjFd0BIw2ZL4JhEcyZnFQ4Ny3E6qQQ7QJbUGQ1Lt22BDMpQ0xxjHm2b0RzY5Zxht9YLcdawRj1W/mOfM8M+0KPDPBCttRw9qMw5QyjKMh3LMREMABRYDcu3uM+qEDIh/tnTvhCOXURN/E2RfpSHRvfzNfWZNNcpe9BqGzMH/CzUV0RBxX3qPR0I/pF5wd9pUCfhwnPAPBIALetCHrCGsnzmA/gVmcrsbBxzpBHzN+KAtHN+u7vYMuFKZ8dCXakxfrTtAdcsAag+ODAC+ONBw/BET8BmZJUuHZeRZvkI61mfUdmWW3rbed7aRMEmFMYNbeWRrpmgTksz136FN0c9ZL5gvOXeoR7oqQSPcsMg9IjPAbmCUJI9RVMciWoCfhMB/pW/R8AzoSZRHsCZcgaNcfWW8SMqINzKKPEGBnpx/yn5/0EX0e5JQh1i+ToEtglPGGrMeB6WesMY/RQ3DKMbZsGcNaz7wKF9xBfrAumN31BoKPrBHINOPoCwX6Nms2tlKoI9gZ+wQzCchnlGTMOLLbzbQ/ssx7DUakMpgjBG5s0LtYQzOC+U57UW/v8bMkRFAGa5q92y8SOF/Rr5Cr3r5k3SGYklHgzQTVqBe2vhm32HPo9ASGIgX+TDva6wEykeRl1gH7Lkavzm1DH3id7CSgkOAR6UhK8/1mXCB3eB70VeYKYwe7izWE8Yit401YNWXwk+fGNmI9Nrod44Y1gnqgn3qPyo0EQXGCGN5di+HmP/LStvVIqEBfwl60T3Qgqc4EziL1D0ExbBPbR8JcQR4Z29wPrAv4JWx5ap4BuYJ+nlHyNTqAsU8YZ4wNb2CWfgy3NvA+axKyi7WFNqFt6GPag7ZG98JX5Z2jocDXhmwkEMpzIaeRjbR5RnoofYEtwYv1iuQOZJUdmPWb2M7cIRnXjBHaGj3a6LHI3HD1oR29u8MBu5FAKsF8/F5GbofzVdCuzFnagH7BL2O+k3lDG2eUQIp8ZN6Zdc7MEXRG/A5+2oTvoh7U2dyXbT5rl+kXyqMMo8PTz2w0od9D6Tf2v3n+zMo1wDbALsEPhF6BrY/dh42OHopMymjuGDsL2wu/DgE62y7FHqPMcKctsJaa012QhcwVdHxkE/ISvZy1LaOrmJAd1NeW1XyO8cFage5kNr5kNIfQH/B90H7o5thB6API34ySnOz103wPz4gcCnLan+lvymMOG7sFmYBfi5cJ8oayrxiPyDSeHzlLGcwh1lXGC2sNsso+tTJSUJbvQ9czMFZIlEK/pX8zOoXTe7Ig480EZo19ieyyv+No+ekU5URBg7IxAAKP43eMkzBUpg/CkIUx0jEEGAUmY53FAMewNzDrNzuLxQADz6vI4Jwl2z7SokldCdiZo51QGKMNzKIEEBCyHagId7Jwg5zDT8YSDgIgkwfF1ZRJu4UzTlioUBS9DgBzZFIopcrbxvb/UXxYpFjocJjY7chOQhw4kdqWAApKJwoEDl0D/cTvcBQEOYbRgGJBH9kOURRB++5C+zkYI/w9yq8d+EGBIKhnjgdDEUXZNp/FMMXgtYPZtDF9TKYVCpXZwWTmAn0X6pgwlAOUQ4wrM2fshZ9gCuPfOE1Dtav3PeqAM4i+YZzzbxRADED+HQq7DG+Q3tzTQBDDrluorPZQRgPz2N49xt9g9Icycrz3y4TLdCeAgCJtvo++IYBm+gjnBAo4Tn3j4EdBZP5g7JndZCiU7GrxBgRQcEMd60jgxmTP0984xzGacKIyx/wemWueE7nCHDDOoyD3B9p9wfNiYGCMh1Ic7XGPUUOAHsMGZdeMO7NzCaWaOcS4Z/yEc0rbGfw43Exg1t4pFu7eTPN/vod2JOj9j3cAAQAASURBVGmE8Wk7g8nypT6hjqGzy+P7cEogm+2kH5R85FukwKxdDo4bMlAxkHg2Mw9MYBYjP5LRZrJ9aS9TLvIHh67fo9boR+8xjRg4yJNQR49HWguZO6yBJBgxJpAlGD3Ux2QtRzLyaX876MKYIXiCAYw8wxlLn3vv1PI6XAnCYLDaO9GMgUewiTnpDaKEg7+jPPs0BNYjnAwZHdVpdkjgdCLAYH8f/Y4DNFIQxDhv0EU4vhL5RUAVJ4c50pl1DXnA34Z6HpN4ZpIdcM5HCsyGmveUy9rNMxhni+lH2tIEMEMlt5ij2rKqXRnzBB1s+UlyBQ5M5BprPGMwVFsYOYUMJkENvcx7ygXrBjojARnzHUF3ZpIshhMWB60fcBbhJKRPvPcOo6vxbOGCIKznfBd6kDcwy7xg/aA9/N6bzbrPfKU+dkCMfmftYRyaOtr9bfcx8p1kM2Q0679xUJu/x4EZLpvdO/7oM8qjz9GdSGwKNWfC9RHjhUCKfZQmZVIHHDvoSKGcP9TDlIk8JLDF2mAcueYzrMF+7sn0zgHWCnOKB3OLwABt5fdIVXRre0zQJiQ02M5L+1kM6CI4tnE8sfbZO2bNqTHhZJLdJqGej3XVTm5kPNtJQ6FgrWV8e3euENhHBwx1T5f9PKyPRs80wRU7MOv3rj/WcjuJEHDc0h7e5KdwoMMxR7xJMthMJvHSmyyJzsk6a+sR9AsBO7Nry07SwKFrZL8XZBdruS3TkM/oEsgz5GRG1/2wTrODizljdBi7z3F408/mCN5w60UoeB8nqh2wop/CJRLQt+iMxoFu5hCfIUDkB9Z75kWowCzlMg+QnaF2EjMnGJe2TsLcQacJFdzm2ZD9Gc19/BHUy7vjmLnPOAm1kzhcopKRQ8wRE8DAsUyAlbFoz0c7QS1Uf2FLEHi07+3G9rRPwvD2Ld9LgBfbkzFmkseM7sJY8iYJ8j3Uw7QLMoA5hs6GTYGcNQFMbFsCI353HjGXSK4IlTRi7oQ09WOOsTPefiZkMT4S1kBjb5jfo/ejj6I/hdPLCVJSptc3gv1IW0baoWqPE3Rpxj5z1ps0gO3BPI60MzPUHKTdmb92YBabk2Qn2+4188ToS7QpMgdZSn/aSRXYLMhIdMxIYL+hU3iDt+iO9DeJOJF26/E75ITZlUbdsMdNYDaIHCLwRzIGdSeZwvad8OzItkgnCyBfbZsT+UGbsmbxHIy/jHYyA+3IWENvNbvBzdgwSR58V6TnwEb0ygsSg5hHfoKqjAn6jjWH72b+RhuYNfXEd2XmK/OafmIOh9JBvbLA/Awi10LVEz0RW5x1jKCmndxg3xPrrb9dBuOD9YG+xf9mvoOxhq8LeRXpiHbWdtoRe42d9vSxmWd8Dh8cwfhI457xSKAfHZ5NISRFYeOQsMK4Nydy+LE1GCfMFzOv8YEw99CTwhFOVpm1BPuTsWaC6eGSELz2ASBLjP+F5+OFvYzMiwTtj92DHkKQGdli5j/6C7q6fXpDOFjXkdXYAshAXvSVucsYHYMd9d5nMXUI94zYYeiu9D3rAWM3Un28iQlB/HSKomhQNtvA6LSNWoJp9hEvXuXB3GUVLts6lKBjcfEGZlFcMbYyCj6wyBpnsL3Lj8UUwezNquFYDwJ1Bm+wEkPSG5hFGcjI4c7zmovuzXNST8pnAeU4KLNLx7RBqLag3mRRocDYiqtRKL1BCRs7KGbaiGdAQbN/5zdrGiPHNmKNsoBzG6UtI3BwmPth7CxH6oZDx7t7CmcdgQCch7S315lidsqibBkFHQcb/w/VlijrOFS8jlOjoJidgxj27OQw71MWdUMpJDBtAjf0Jf/nSGWc+zhADTgSMJDDHb1GOzK+eW4zpm3FkEAX4858lzmyzr7zyH5GFCEUccYVc8D0L44L6hFplwZzzdyzhtJoApMYnCib7MY0x4BTdkZ1CWeMYrxE2lGGwoxCaO6XYX7YAU9kC2PXOJMZ+/Q149J8J45j+tDcH2QcE+bflMezUhe7zmSGM4ZRtlHeOAbFdtjjKMGBjFFrZAjKJAaD/bwY64xbnCrmqOVQTm5kVKQsXPszGKdG4feWhZFFm3iP4bHrRD9hXNK+GATIH5Rf0y7IGIwmxiNHUtnjMCNDG3lkArM4jkwWc7ijicxn+Q4UcgxzWxbRfhyx6Z2j9nfyzDhmCOow77wBXMYwO8Po50jHuiK3GGsEZDEiKBOHublX0+zgpz62Qyoj5Zy5Tf8aWR3KoA5XhnlO2gbD1XZGIl9sWR+qDOQhhpXZZc/YYNzyM9zu3XB1QQ4wvu3AMIaKd5c5DmYyde26miSeUMcEm50XNqzXGF/0ie2w9hqkpq60MVms3mP+vM+C8xW5aM830x84vJnX9lwPB22AEwLjkeeyd4OSbGKOSPbWxegg9vhl3jH/TGDWBMvD7cQ0ugNzy25LUyZGMc6oUDA3kN84FeyTQrxjMqN2NX9j+sM+lgwdijWT9R0nCGODdvUeh2j3DWMFpw2yGjnuTZBh7rFWk1QQDTgM0L+MI8huf3us2bt5+C5kGU5/O6hCWyAbQznljQxFP8GxwjjwZmTTbzhCkTEmMB8pyIzjE6cXa7mZ7+bvkY9GhzLjxdZFvfOF+qHL2M9J35F4g27lxe4j+pO5Yc9/ngO9BCeime/I2Ui7HuhLZJkZu6bNkFWME/Qq9BS+26tX2Ak+rNH0Aw465AvyiXUE/cZ7bHA4eeJNnCAwi15D35iyg96zbqCd0FsiHYtOfWgL1kgSHDlRAAe00blwGFIP1iI78YX10KypkdYfbByzOxJ9Dn0mnFPPlENbsV6aBELzProS7zNWSJIwp2nY7Yc+h/5r7tKjL01AAVsD2wrZ4HWshaoHY4r2M3qT+R4cdDjY0JXtI+ZCwdimzkYemmQp2gA7lDrSB+Y7KRs5zJrGnLN3lho9wK4LgSB0Fm/SCnWmDxnbdv+QcMX6a2QHug71IEDkvQfOlsnIQxye6GOhArPoQOgmfu6G9j4DARyTBMbayFjzjhGex9getg5l6ohu413zvEEy214jAEqQDTnkDcyyRqGzGFltvoPgFb4FnpNxbQeSmT8EXijP1NPoPvYJDsxF44T3rnl225m2wZbgO71J5OaEKttXEMqRS78RhMdOIBhBkoWRJ/ZabM8HbznMJRNQZA4zf+xTC1ifaHuST+02phx0VTvoxu+ZkyZRFbCrsHWoI2PR9AcyHP2Xv7V1ImQy8zLUyU+h1jHGC89NUpD396xt6CH2eDP/tpMiqQtznuf0JmbRNyQHhpODrIu2n8L8HXpSuHvvw40T1muenWQRW/YwP5ADQY7etmUUY5R1gDWAsW37LPge6oo8Qu569ULkMXLF1i/QSyOdLELbMd4JkpmxYGQjMos1nGAIMjhScr7tEwHGhB2YBb7HvoolXJAIvcQkqdgnvWDv0iZ+7xPH1mYNsoO42LTof3bSNjY0upmdzIGdhA6On8O+MgPQ8ZGVoU6Vs5/JtsnMWKYvzNVJ4a64sMux5xbjA3+fNzDL2uH3Wiv0IdZA9FnGL0l86EHIMDtJypYF3qvB/Mo15rQ91239iTlNu9s6JDos48V7Ilc4WwUZz1hBHtjHSTMHeT7vHPTKBfqH4Cf+GtZ0+/fIUmxD79U+3jLQjUjQwM7FR2UnzSA36Cs/V9Mx1+xrr5g7fJbEAKNTmHa0ZVIknY/2xRdi+x/9tCtgozHn0TXQr/g+xj22B20Tyq9l9ED6GdvD1v2N7GT8hbKJzRy07Wd0cOYeuiprr518h//AvoIJ3w7tbOZLKNli6kC9SN6ibbDN7HFJHZARzNNwR1j78dMpivIPulM2GyB4h7KI0DSLmLm7I9TZ7whOlGcMqFAGjI03mMBCinGBkYXDnwUD4yzc4mTvnjOZ1QRoyGTHUYhwxwCxQclB4LMw2ouV9zgZk7nGwoEiQVkoMIZwDjaenQXYKNXGuUoQAIXePnrD/j4WZ+OQ4d84GVi07aPAcJig0JLlFS5zyNTNrh/GCgaA6T/KwOiL5CSM9Dv6GCeh310gGFS0HQozzm0UR4wPlC7bGCIrlGNBqB/1xXFglBbznPw97YSSxGJPefSl13AAc1SNySZFgWc88xnGtDH8KIfMKG+2ID8Z6zhw7GOVzHFmOAaNcYvSghHHmLWfya4PAU/GN5/lb42j0k464LvM/b/Ulb+1A452mdQPRw9tax97HGre2fVgdzJGEUFyFCIUI3ZVmjGLEkSWux2woy4iErYuNtQLgwDHJw4D2xj37lhkhxa7hMjMpt9RuFGabCcOf2cMFYLiKE3Ui3HtDczajgjGO85PgrHegDs7W2gDxgYGC21g77zBKCOIxHz27hC05Rblo/xhtFAGY8t27IEZD4wlDORwRwUbcCBSHn2AzOCZvPdXYqSHu3sDQ5ljqE0mL0YXMoOxhWPIjDcc8MgiezzZ/YMSawfd7N/hoKMOKOL0GfLKz11JjFMcdSZ4iZymjTEiwwX5cSAz3zE0GAvmSC/vjnTGEEZYuPWCBAza1Ti/6AfGDA5UghXG0MbBxPwMNXdwlIc7ypPjNinL64D0lsH3hroPm7YgS9P0NeOPdS1UPbx9gyMHA5xxjmzFGcCcxvHsPVbRW473+Fbz04xbxpHZZc5nmdvMW9oOg9V2GtAHyEXmpzG0eB6cFbSPLespg/lCwgCBEfv+HrseZs1hfnqTTbzPYgxaAgfMH/rbrh/PShv53RkHyA3bcYFsoI29xi6GJsFndBfbwWvmBeWYwCztZu7lse8NM+UgA+hT27FhtwfGtr3+EkhHV2B+YFxTBz6P080+vs+r54RrV7seyBJvcBLj125X2gRZFe66CJNUgYMUOU+9CGx7T0hgDCMLvDLULzw3uoN9NHuosWZn/CMTeR+nIM475Aprhlcmgf1/nBMkPaALU7Z3TDFPmAfe3amhdCvGCN9r7mnyOoxwdOFIZE6imzL3aD+DN/hAOyAz0Z9wqlA/6uKV0XZdGLs43pg31AHdwsAaxNrFWKGtcC5nFMhkXcQxZNcRZzJzh/qjm4fTcUw9aW/kD/om7Uy9GGf8tI8qDCpPTMAFuWbrexlhl4GcZx3CNgi35qAfIINMwMCsOTwLctk4f5FLOOtNPxIUwVbgeYzjOZxOzljF4c/fohuZfjG7S8JBO9GWdgAO24l+515Jxo99ogWQJMv4oE8Y/zgFsSXQI42MJFBHQA4HXSQ7BdhZh51DAqTd/qz16O6s5+jqZj6EawPqy7ObZAXzd8w97DGTWIhTziS6shOOOY/+YZdrr4M8E7qAt48ZtyTy0VahThjw6mv8baS70pCzyGDaEdlI24cKzLKO2gkMGWHkPfUn8IOT3XZWmvFmnoe2Rg55dQEwSSbmfcpCznjbzYx71iLGOrKC8ex1/tNnyBTzPn2DQ5W5jK1EvyAjbNmGbURSHmOd76Y+yEwzdnDm852MbZNUl9Fd3Mg0AqHeMcoYYc1ivJBEFK59gfnNblvWdtO2jOlIa7FpLxM4Yxwx3u05bI73RvYbfZA11LbxcaQzdmhzAqusr7bdRXvSrtjdJGmi/zAvwjm36Q/ag7EQKVjH99l3mLMeIYMJLJi/o32RkcYfZPcFu9aQ0/S7SYw3p2lg74U7MSNUEqr393ZQ1hzzyd8TrGbtDzVObPmDP4B6sx4iy/gMY83rswgC6wV2hll37D5mjGGLomshA4wdy3dhr9EeyFPWLewXZBL2Vzhfg43xdxkdzrQb7cJ3IR/D+eq8yf+mjRgjlMn6gZ5IO1InE/Q1sK4xvk1ABf0Ov5q9K48xwmdZ4zN6Hvs9r53FfMP/Yt7Hr0AdsU3xPdm7/An00ab0BToraxa6KDKNdSfcmAuVuGN+R9+i25j3eR77iNlwyTjm87SDCcwSFMLfR7KknRQSCvN5gm08D7aB6Tf6i/6JJAvs8r22Zii5ZuYOn2XshgrMGniP+YWMZZzZzx3KVrE3aaDnouehKzH/6E/kHHUJN07Qr8x8xtcQyg7D34MsDZeIjgyyT9RDJ8IPbSdCYnvjh7CD/aHGK/Xke0mgQNehPxmjjDd8MrSjSYYJJZMizQF808xf77VPGdmA2MbGB2l8W8gYntu0ayi/lvnbUPKPsYou5U0U9s5B+s9+DuS+basxbmkrk7Bh9HR8kawXka4aMe+hDzDWbL2eNsEupL2oD2PXK9uC+ukU5URHg7JHGRM0wVlj33eCwYmTjUwzlCscdCh8GNIoIraR5A0QYmjiPEWI2wLWLDQIaO4DQhAjQEMF22zs7yHwieMJZwaBAl72sTkGlC8CUijc3sCs/XcokAhylJhwgT8UNNs5TgYZiyp1MY4EnhMDk+ACCh8GD4qj+S6OE2QRwHA132EutWdHIzuPaTMMcpRg22FltysBA9rVfmZe9J1xVLK42kZ5pOCrF+qMMoETiLYN4sRCyUDhZLFE8cVBbzsGcOYTQMCRbz6D4uTdXWWUV7PIozCYcuz6mGM+cITQ9jjAqDcvDF8UO5Qjr6PA68ji/9Sbv0ehMM4WlAaOPma8Uw5OHzvw51VccN5SZ3YK0Qc4FmgL8/fmJ2MARwQ7DuhvDCqUKAKI9li1nzmjuz5smKcYmfbRO+Z+NgxBo6ig6JnjiagL/RCuLnZ7mQAuTiDb8PS2B5mOOE3NcWwGlEgUMDsTj6A5csjspGSM47TC8RAqMGvuOubvOGbGvmuGnyjBzAH7fj0ck2Rl2oE+lHA7s95rCKAw4jBhfKC4Y0SgUNpHidmQeYjDwXvvht1+KIQ4schmxclPXzH2cLyY3SSATGA82gotoLhiyODYMcfwAc5fHEvIJvrQe/oAz2bXF2cL8hFDwR5fdl1x0NLe9k7bSA4L81lkGoYCAUzWCtvg88p5HIk4e+xdBshRnCvM61BHhZty7LrQ7wT7zU4xymUcMwaQRfwbw89r4NhlZNQmyGCzW8DGT7sCshUZSEAVB4LXwR6qDDM+WW/oC2SGMZ5Ym9gVZH/WT11CBUO9DjoMQj5PP9J+9pGetAPjlvrwDHyHLRvNfZVmJx/1xElIfyKP7e/h/6xfPBfj2h4noZ6FuWieFwMRB4fZ5cS4oV0xHjPa+Rxu/WPeofMgL+31BmcHOwDRlULdhWgnPrC2o9vgiDP3Yvotx8C6ZmQwbYM85O/ZaWo+R1ux1tLOXlnEs4Rr1yD1MLBu0K6h7rbEwcl6Zxu5jAH0NJI67B3pOMtom1BJC5Ewz0f/0zbmOcjODjfW7MAncpPAttEdca5F0j0pA52Kccf4x3HEPPHuwEY+se6bHRN2WbzHvDHPythgjCJPWdu8gVnAccLaRf3pH3u3qD3PaXOzS5Dxj84ZSUazZpIswzxB10QuopOyjhtwnhMQwJlkxr53HfEmNhLUsB33fA55jqxjPfSj4xjoW9ZOdAY7gS5SH3vlCZB8hs6GTAoSkLX1TxxsyIFQc8fAd7PeGEcju4DQF2gXdH7GDL/zruHIGOQC44n2t08u8D4L9UbPop9tG8WbYMWaRIAcZ69JSEAnYP1F3yKhA50DPc8kstKm9vGYPA+/o+52HzGX6Wf7KGNsIm9yD/C3rEmML3P6CH2PLk2yIDonyUnoNgQB+XueDblgPw/rlR34ZMzijOZzZse/CbiZI1WZO8wZW0ahBxDo4zO2HEI+MifMOLH7GNmI7YG+6T1ON5SsoJ2xO8KdAMCYZlwQAEceoPeZY77t6xhoT+ZS0F0c1AmZYo5M9NpLkZ7Hhrlp5AEOXeoXyhGP/Y4soZ0pE3uHtc4bmEW+IZeQeawN9I19yhAy2VwxYScFIYfQhymXn6YOrGf0FfOFcpHhxjb3yjz6l8Ava5a3f+3vwV7Hpsc2sHfV2QlJyBtvogh197sWM/+ZPzjS7d1oJA2wxth3F5ojUu3Tv3huZB1jiGdhrJkysMWwJ+zjPpED5tha239CGxHAQbdGLnh9BN4EONZZEjTsJAH6hOcg0Yz2wi5GvlCWV2czf0+dSSqxA7PmCPVweoBdDnIDv0GoXb2sj2anLPKBtZigcbhxYq8DrM/MTerPOkUChh87JxzIAeah7cOh3owTe0cufWl2wJr5gh5BvzBPWRvsoJK3Lqyt5pQx2gkbmXlLW5ud7SahyN695g2oMt/5G29Cnu2zMKclmD425YA5pcmcskF78jfY5OiDtD2BZmSsPd68tmgonyHYdaWdkPUmoZ05g8zhJ4E52o+5ZO8YZU1l7cG/Rx3N/e5eWeCnTYA1FN2Vv0c3YKyF8rNFGq/0CzKQujIH0Ov9nuKBTMLm8SaRGyLJAsajVwcKJdfwKfCMzCnmD2MS3SJUW/HM6MP0C+XY/WvGfSj5aNeDBAT0Q+qN3ONvwo0TYwPSfqF0Z2D8MJexT+16hirDJMwha5lvrGusz/gIWBeQbfbGoFDj1chpY5/jLzSbH/iJjsPz8vfhZFI4WxXdkb+1vztSu3qT6r2+DgN/G8qvZY6etr+P9iRp0CSJ2H2X0Rz0JljQBswtIx+xDxhr6JvMJ97nucIFZplPPCvPb+s49CXPw7jHh4aNg9yyT3azywrnp1MU5XA0KHsUIcCKYRXu7H4MCZQLlBmCs8Y5by+aZHfaZ+6TkYWhj0LGIsv/jZJohCILGeXYQT9+Rgoe2kopgpa6o3h7dz7af8eCxyLLAmw7/G3DgZ8oVige9m4Xg9lpiFKHM8A4O9iFh3JHlhGGBYstSidlY0Taji7KIAuL+tpBF8AAox1wfKOQYFTw/QTR7KMGI7WrWWSMYzxUENNvYJYFEaUCQ9ZWjKLNHDV1ILCAMo0Sz//NoosSaSuEtrJodk2Ecw4acP6w0BPUo59NsI9dGQQavNiKAn9Ln9A+OBjoA/rZ9JM5Lg8FlSBtOAcfDiW+3wRCaS8+axxZdt1xDNGHKDKMFZxUKIcETDNyWmaEcRTgTPFmgZnALI4oe9etmSsZ1cXOXsa5ZO988LYHxpB3d4z9N9TD7Koz5TIWCA6bZ0bpZiyHCszi4DN3TNlta5R4nFAY2OY5+W7KY8dHqHulQkE/MY+9d1kxP+zjh7x4jQ4bFGpkqvc+Npx5zF37eCj6xD5+0E44wXGKs8TeeQQ4PXCUsBsz1B14Bj6HPKHsUEfl0YYmoxE5F05Oh5MrJiBE29EeXjlttzHGEGPN3pEBzB++n13i4e5GMzBekYesRTh8MSIYY+YUAsYj8gSHh2ljb90zahPjGEDOeuvqtwzWLnYOEMi0A7J2u4Qrg77F2RHO0PLK6IzqwrPg2GHNsYMXRt4jU3Fq4kBjvjGucKBxDzN1wUBCXiB/aVPz/SY5gOQLW9aytvDs3jUQBzXylX4O1R4ZPQuGJDIbI4u1lDnrdbr4GbOAjOA5eXZ7/cOhxnzLKHhpymYHCOsByQj23PFbDuD0RHfA0YbjBr0JXcPcn2ZgzcJ5gE6FA8YYosjocO0apB48E21udlCG0gXMWmd2vpi/YT1i7FAP+xg6srrNDr1IO1Uj1cn0V5CxBtQDp5YdRPfCuDbjzYDziTJxHtg7ZnGUMV6YS/bYwkmJDEKGs+6Y6yRMYBa5yss+Ro92Y22gH9H/0Ense+q8OgFzmHZE/4v0PKyROIPsLHf+jsAuOiy7+Lxtaz5n4GhFdDjWPxy9jEdeyHh0Dt6nn9GlcYhQH8YDekckvSKSbml23gbtY/qKtcObEOdXjyUYSNAXHSUjGwVnFM+JcwsbwKw59B87RNGBvDYWuh9OP8Yi8hMd0Q7MepPgSDJkF1c4fQt7gGQfHIOUw84XnOH0D2MEGWBOu2C9NY5Egr3mni8DzrdQd4/RjzyLN9HRbhMSebEXzQ4M/m3uKmScoPdiCyErmBPG4cff2zteSOoioZE1ksAQazpg91E/ZBftwTgzyTPUgwAv+pUdBMepSV2wnXheey7RL4xpu10Z2/yt94qScLsO0TGRjWaXOnqX12FM/3hPdEIGMf+pv23roROxmw4byO94ZS3GZsNW9Y4RP89j/o1cpp48T7hkWOpFu9tHkwJjj35B3zPji/qjhyM7sH+xPezdKzjP6RvWSuYOYzcc1IE5z1xA3jEWWOvDBWbRk9EbWEfDzRvjbOY5mYcmMEtb4rA15THe+V4jD811HnbyQqS1GH3Ju7uHMpCDtBv/Nt+FDcTawzPaMM4IFDFPjHyg3shU5p0tq82x7Ti5caSb5E2+B9mIbIuUrEKCMe3KM+NkR87aPhT+jQ1E2yHzTYKIHYg0d/YB8of62IFZc6KA9zoEr/xDvjMWkRGMZW8QDBlNn2HrmzHLOMFPFW6ceO1qb6K2N/k71L+98DtOFaD/TfnYQcgyxondP4wv5j7jhHXKyH3WEGxdXqY+6IC2bKTvkJ+sLcx3ksCpLwF+1mAC5swr5KudWOitO3ok6zbyKtTJQHy/uSOeNd0E3U15BHL4PGsZ449nYf7S5nwXgRH6HVsJ+9Z8LojP0Mg2dCt0fLMZBDuEdraPe2aOsqaG2vFOQjZ2fyifoZ82MW2HTGAcmSuRTD/bfWvGK2uXPV5tkAvIPdo2kn4RaudtuDHI+0FkgTklwpZr1AF9FhuPMYfOhh5BPe3ArF0H/h773G5XystIPpK4ZydJsS7YR/8HsQHNXCPAS8KKnRRh1zVSGfQ99WINY16ZDQd+fLHIZspEl/D61gysv37XLm+/2vMxo3YloSucjyCoX4vvRmajD/Idth7NHEQX9DsHCVCbQLcphyQObA+TAMF64g3M2lA+89ieM8hMdFv7ZCTGAjKLhAzkoznFxh4Lkfx0iqL8gwZljxIIJ4wG+1x3QDnEyUn2tzlfn4WSRReDl98bwYbyQfCHBZ/3ceCiaJCJi6BEILKYs4iYXTZ8lvftHa62YPRmlPtx1oVazIxRyPeawKw3wITgZlFkYQ1loGB4ELTGaYHxztFP1NtklrNQk3XF+ygxZhHheVkY+T+LIwu8yfDHECeAh2JNdjd1N3fZ4tihfTDoUbr9tKsx+lBGMHAIYIVzbEdqWxsUyVCKK4otWbaRnKaRlEr6wXt3FIoMbWzfCWE+w/gLFZBlxy1j1L6LiGfzKiIoZ947yez6oNgQ9MWoMEeQ0NcmMGvayzu+wjmleQ67DpTHzgn6hcxYO2sSAwqFxO4T2oCsOq/TEsU4lOMxHChWBCgoy3vXMuMU553JiLPxUxcUWfs+WNMe3n5nDDKOcAJiINp3yAFZjPZRb7xvf78pDwOeMryBWRRB2tXeEWHXAcXTDjiY3zEX/d61jNKJAWmcC+YZUOzNMefenZo23v9jdJBVSL29cheMsWfXl/lm37diykTxxwnBWPXuRKaPyIwNNU4pl/GEc8hWYu3vNDB2caoaJ4q9M4fxEe7O63CEGidmnvPc7Nry9g3ygYCUvRMr1G4H2tS+b4r7gnFIGOOfHdjs/sI54G2XIG0CyOBQR4T6KQMZjzPF3kFvG4/hygiSnOG3LrSRcayFWjPQAczcJ8OV4BqGKGuPVwYYbDnqvTvK3PUa6o5VW6/wOsT8tgnylHnB2MB485424XfMMt7tABfrMYHRcHf3ekGO4XTDcW3rFUHLYc1gXNs7DNAf7N3xGPnMUZzdGM84C3jPHqvedg1SD9Ys5iSBHKOzmR03Nsw9EsvMLizzXchQnFw8B3qL7Uy24e+QWaF2Fth4HaTRjDU/xwGi2+GMNsFX8zw4knlOjqG1A7Y4KO3/40ilL1gD6S+zo9UEwCiPv0fmeXUUAoJG92b9xkHoDcyGCxCGex7ex8nkPV6V93Foo+9EkjE4rAimkbhljhdFP6Z9+RxrJIEcxiy6r50U4VfHCaefRtPHBuS+1zmHwzfS/bAG5om9E9Ru21C7NMzuLONARyfHIWQn83nrb0CXNYFZ+6hh8504rcI5k5HN2DB2EIRAPW1sjxnGle0wJEGSz9nJEjwvch89ifa2n5mAHeMHpxqBEO9Yo49IeuK5kbP0C3IGfdMcC8jvCNIyL8znCeoQQDBHRlIvxjvJdzwTejVjyzhG0e34LmwoZIqdTMR8sXc48v2MEeYtbYje6D2S0GD0G+YDgTz7pKNQ8LfmuEVz4hO2hEnOtSHIynpgfxcwNpALBCVZA00ipb0L2e94Rbewx4jZFef3eYCANvUJZ5/zedYg5JZJNLBtM5z+BCTQSc0Ro9hE9CN9Y+/wQiaSPEiQEBmJDMXONbtGwwXD7CMmCf4Z57Z9RYNpB5Nw630OA59h/TROYewJ5Dv9YZ7LKxdNOcynIGsxdbX7h74hmc3eych7rNnIV+/9t17MGKOd7d2mrE1mRzJlo99hQ4XS2UK1CXYTsgO5Qn3xMWCvEGSyZbZtD5i1GAhSoLPTDvYxsLQF89wOzDKnIznGkQ3MfWx52hO5gB/K7hNkZijfR0bjxHvSTqgjczOrOwIJJXaAD9uRcY4NTltgH9M/odY/5DXPxvMjpxmffJagDjKeABzBXZNYguxDTtNf+KlCbVYA9Bp8d9iX4eAz2Eys+15ZQMItwSr7nmd8XOjpJGGY62O8YJv69Rka3xa+EtrMPtkEmYLt4k2wJunMJBQZXTLckbNeIrWJkSHmaGoTpLbbxO94ZYwg+8IlvTBeMpr74fArC7x+IW8dbH8T4545ZgKzpi1CBUbtdvUjH9EXDd4duEHtWcYJ30Fw0ZuEF6kM+7lZp9DFjKz244vFB8N4jaSHRrN2hWuPoO2aWb8W+hZrvVf/ZC3PaA56107mrS0fedk6AWuuCcyiB5jPhzop0K4juqp9tzNzELlFWSTlMWdNcqB37mtgVlHCo0HZowTCDycNO28MLDAIMHNPG4Le6/A3GMHKQsRuEJwRGHTe8+bZsYaRah8TwEJnnBy2QGTxx4DHoRUUewFjAaHuRskNF5gFFldvNr15LhZbHP52/cyONgKDXlj0CXrhRCAYwAJs7uZjsUTZIzuMbCYUI4wcO7BoP0vQdsUgJyMz3K5SP23rVV69ixcOHhY3O8vRD6EcAeY9FGHGmr1bBGXF/r/dLzgH+XsMMH6i0Nh31vE5Fl+UYu8R2zaMA5QXFArbGOKZcfigdBMoCmUohXoeFCXGnHcHJEYSyjftZh+nYj9fqDuXMYoZa7zPOPSWG6q/7HbCMGK88yzee1koK1IGfkZ1se9A9tYDQ8hWujBIyNwl2xLFinHJ+8wBdr54P49DgLHO9xnjiM+F2jHLPA+lUEXKJMUpYM85AhPhdmFSLztb3Q4I23fXhLpfLFw9cP7gFGRe20erAEa0fSyZSRwx8x3ZQjsa5zSOAow7nKTh5HSofsboY+wbGWb/Dd9t1wvlHue7baTxvRhoOPrCHSEUCrufmRd8j2kjjHgcqMxncxShgaB0uPHKMyADzXHS9jhCKaet6EP6y4y3UO0SpE2iLcMYXhxbFm6XQqQymDuh6hGKjMoxMtM+MtJbFxzO9LOBNYsdWARdwh2fZbDHheljvpMyzG5KMA5Y79/6fRbkjR1UMEYquy/sOvgds6EcwYxV1k7bARXqM/YcYX3xOlz8lmPWHHQzjMpQJ3iYvmNNsccE8paEHO8a7c1s91MPnC6MDXOvnHc3jHF62TtWcLLb12CwhuCoImkplKw2p5bgJGA9j+QkzOxYC3cijH1qioHdSuboczC7RHBmsWOH9RydMpTDjyADMplnBhw5rIEEtu1EItrDK9tCjX+c6fSVHZilbxhj3vt6IwVm0Q+ZA8Y5YSBjHn0nlKMO0CFwTJnkIHa98hzMScaF2cXoJVTiSlAdJzN9jPMNXdw+fYJ+xIFN/e3dOJHw9gl1pr1Yi21dgoRDAjqsOThVCdbxN+HawwtrvAnMMqdJLCHxyg5shLpDlnHG3DF/Z74H3Zadf945xXpIuSRLoE/xd9hBRtfBZmF3DcEC1lXWC2Qb6zNjjhdOSrvdjf5i7hOz68i4R3fztiPfTUIrgVzjrKSu6GjGYchY5YQL5g+BQv4u1PgO17bGeWo7GLFvw50iwrMSPA2VNGc/FzKU7yRwxe44b7ANSKwweiFzhrHqtb+QDewkI9kBvdI7XqmPn/HqvY4l6PMwl9A1WT/o53BrjgFnMolHBuNgZVxh74a6ksYL88QOIPBvZIptc4d7RhuShhiv6I6MSerMuPImG3gx7zHOzY4txjXtxclg9n3u4T7rZy32Bli8eqG3TGSdfaw172MThTspyobnZyzZ7cppUBztaK/LkUC+EVy3YQ6h9xEsto8y9q6dyAbmM8kwoXR2xgeJ0AR37PUm1Pxl7WWNQE4g2/CJoA+hu6ALGv0DOY/dFM73EWmc8Ez2OEF3xN7JKt3RC2slO6PtcYKM4pnspFJ7vNP2zAt2/tK+9g432gD5QxCD9SMUodoWucMYs3VWe0ee+cnY5blpO1MOfYssQyZ7d8sTmEX3IXnHPqnLbo+gvi1krX0XpqmHnQBvjz/Ggo1fGzVSm5jvRq9G7oWy3zIar2Zcos/hQzGJM3YZ+IWQQdjddnJRNGSFLDB141lMYJY+p+1pB3TKzMpHs7M6M/asaSsSFcLZs5HKYO3z6jPmb/yMV/rMjNdQ61SQtcsrk7K6XYP4tcLdyWqIdg6Gag/bXjaBWfR5c1+xd2evjf2crAfo5+hLZs7xXLRxuGRWRVFCo0HZowiZxhi8ODBZdAh8YFiT1ccCRtYMygELVqTdkSxaLNYYjihjXqFHFhECFszv+IwpE2UGJy9CmbqEMyDDYdcNxwg7IM1l6iZ7yQRmMbi8gVnwHi/LIsLf4jyyQWnCYPEabHyGgCHOB3NHAsoYixgORxRY2prPkdEFLBKRdqsEaVcbOxs+mrYN19csaKGCyEGxnwPDk+C0eQ8FhUy3UAsnmWA4kszuFZQh2gYjwCieKJsYfuGOwqRcFA0y271GjJ1VSmYhDmayfiM5P+zja8iGp0/Nrmjgu3DMhTNSw/U7CggGMEokWele54hdD/qEgBPjAQPNe2RUqMCsqX9W1MU25jFqcXLYuztREvk8zjaUI/rHvhvNwFzAuYjxybPQt8ZBgyHDOCEr2Hunn59MNzOeSEQxQU3qibPZT2DX/j9Gu+2QIpGFIHik47ds+YJhRwAfxxYZj8gaHBTIYDJbvdAu7NpC+UZm0y7m7jLkNIFZxp19jEy45zAQGCZBxDsWGKccgWTkJkfLEIjDYW4r1uy+8B6dHAm7HqwxyC0MYMYBQQp+j0HFesOzkAme0Xgly97sPDbBE7svUeRxctJ2yOyM7tjOqE1CGetByqC97J2A4eZRkHpEWxeMabs/Q8l8DHgTVMAgZb6wvrLTF9kSdKc0mazIb+OopjwcuN7rBDLbJqzD7OrN7Jg1mOMESRYK1288E+u8vcvNOx79lsPRTzh1zK5fbzk23vvSmUvoDN6kn2ieh3pQB/MddhY3a7HRD2lnvg8diPcom/eYk8hG9DDTr+Ecpnzee4yq+c5oiDTWbOz/mzYzbc0uR5wbRl8DxhNy2D5NxAu6CPKZstmNTj1YlwmkoqsgT80dpH7XYr6XwCw7G1kjWH+Qa5GeB8cLQSwzT+l35CBrldkpSAIAAZRwd1jSFowps7awduJ45D3mHfMMee4d9xn1WxC9Ito+Rk/EoYwOZAe6CECFC/xkBI43kn1wzHHsO/q+rcMjo1iP0CvsnVuRsPsMnZT1j3lF4hoBjnBzH1uCMUE/Eww2O+5M2+MwY431HlHOWCLYynhAVrKGYvsRwDXtwlwmwIrc5XlpQ5IRgCQ2nPImIYAAC+saujLlGMxax1ijf+0xwjNhJxGgsHd9EIw1O1mYd6zfPCPy0OyYJRAaLex2YQ6G23nKOkJAwBznHar/aD8CpfYR5jjZTdCUZ2PtZByYAA/6KzuA0T/pNxINcbzSxiTbAeVxelVWjle/z4NMI3AMoWQ1PgFjFwPthz5v66uMYxz3JB5Gc5oScpOdTH6vF7HLwbmN3UjfYiMgB/zugCHRhflM0J/PM29IFqP/IiWKZMVaHApsAeaLSaxi1xHyxK/96D0hhGNkaRM7OSFSe7KDE73cm9jFyQ74MLCLQznImaPILnNMNmOGJAsC5PYRxfwN72WEud/Ym4hijrwmuGIS2CPpSUHGSVbrjqHq4d0JRxvhj7CPcjWYvzWBWcZkqKtTWIvC7Y4LNRfpS9Ze9Gf776gjOr7Z6cqcRG55xzY7RhmT2PPetZ/1hoRw/G2Z8W1hc/h5FnMiACBvGR8GgjPs9s2KNrHlfaixltF4xQ9it6O9U9tO6kbWR2q7IEQrC2zMZ6kjfYWfAj00lA8nK+RjtLa1PV/DycqM7MhQyfWZ8cUe6bUr6LoT1K9lrn/LSJ+PZg6Gwk68QNdDBrAW2vewZwR9aPcjZdLn4WwcRVHCo0HZo4CdkckRJCjJBEJQwu2FDUFKxkq4z9vg+EGI4yQxxp0BI5tFwmRGovwQsDSZXBj95niXzBwlgLGLUwADgIUTRYhF2DilUDDZfYLiZZz43ufBQMZphaLJwsLxDBjQ9t8QAGOx8rYDRjlOTAIltB0KkAFHgn0vAbAQszs5VD2CtKt9LFFm29ZWJsnAx3GLsyeUsmKOMswMKEPsAKHdGGvmnkWezX5eMuFwsBkHk3EO4vzEWcQOA/Oc9EMkI41xQBuZ4wbtZ0bBoc15D6dQuF0sKIHMGRxv1JUyMeaNM40ALdn4KDk4Gsx3+DWsmYsYYd47R7zgECTAh9GIYwGl0b5z0GQm4wTO6GjIzNQFIxZlkvrwvOxGQDk0jh3GEMY8TkLb2DflMM54DnPPIIY9z2LvAEU2Ua73uEc/0P68MJowsOg7xk3Qu+YAh4Q5noWMQLscLzisSTTA4cMOUBPsJAOZY4VoV9rL3Plm2suMNcYgf2fuSTb3MNnHNjM3GGfIHHuMenem2sfrsFsTZ53tLOEZMO7ZKWF/lrHOd+J4zOgY7UjOOKOw88zMXxOIxsGLg9jISYLMOCa92bxeWUOQAzlO+9gOCdtIISiCHDP9azsag7aJN5M8u8vIynJCgcxn/SQwxdw3yT44FzAgM+prG/4WRw+BJJx3fD9OXTtQntln8crnzIxZ1nwzZkhoYYzZdwJ65QUOQgLY3u+Kthx7vQ3niLJ/AvIdJxmBDm/fRlsPs2vXLo81l0AOjn7kIGsg44H5SJ+ZY1GRZ+guoWQsgR2COTi/zS45+zuoY7hTLrJirIV6JpOxzlpqdoKjczCOWNf4G9YPApvms+HkvjnaDeczwXrz7DgHmFPI/KDPRZuY4/PMfVfmeb3jnx2srLXoVuyMIMDM2CQAxnezZvF7+s4+HjvUWCN4xHwkOESfmp1S6EkEDQnmcWRiUPzqOJnpY8YWgS4ciPYuWrutIn2ntz1Y+005fC9jgu9lN7gBvZ91OtLddZG+B12KPjZH4oY6+p/5yRzjuxgXOAXpV3sXNE456hbqGgd+oifzHehcBLjRH0kY4NhgYO6TAMczkzBhnoOgAPOE8qkrSTroM+wQQsdj/tuw/jLevKc88MzeJA3WbmwXbBrmmrkqxiTD0i70p1+8MgX5SLl2e/N9dj1IRmHOGD3VThoC5hByz+xkRI/BaegNnNI2BMvRefg8spF1CX0nb968blADp6MtQzI7XjPzPPaRo/bvkfPILHRv2s8EzQnsY6/xwuGJLKGfQx2/GAr7O2hDs5slqF7hvcYCndKPXm8+i07B59AljK+ANiZYFiTh0+9anFFZyFnsdhJbsQuMTex93ozqA4wDnNus9d56hCsLWwNHOAmg9m49glLUh/eRNd6d29SRdYmxgFzCxqIvaIecOXMelrxiH3scrv6sYcwRr16PTUR/IWvMMf/hyvI7Tux+zkp7JxTecUL/hPInGcwYZlzg02KO2SfcAOsQNqA3+doukzXa+PeQ98xXfFnm6G7TDuhBtg/BgC2OHm5gnSAQhb5k7sQ10P8ZnQASxGfoFwJrJiDET+aOd43JbJuEC2xlNF7xTZrxast8xht+R+9O6cyMsaCyICNMHUgAYy4zd/zqbEHkY6zY1kdjvGZm7crqdSeoXyuzczAStrwzm6vCXcnnJdQzo0vyPLavXVEUf2hQNhsIdbwH7yHITIatwbvg2btlcCRi5COECXjhxMU5RcDMPhYBZQVhTWAMQ8/OlLahbO/xhuFgkcRJYWfZ4vijPgSljJMTBxOKWKgFD6UMI9koTmQDY1RjhBgnHXVnkeC9ULC4YgCjrJKN5lWoaFeMeTKk7eN1s6Jds7Jt6XcctxhfKCHU1z4GDScvBhoZ3ZkJzNJvONYIZJo7NnAs8R7HIdr1J3BHP/AZHIo4KME4KlEi7GM1TSDOYILXfAfKs+1IM+MBZxrOFFuJ8GY+4rwiax8lHeWHenPUMXXl+1FuCCrRZyh7QQxq07a0N+VGUnxpJ57DjFfGO+PVuwPYb2ZykLp4n4Ud5fadbwQIcdayy8E8P4FZAul2xpoZOzh6SYAAgqY4/c3RSDjkTEIDRmeQAKoNdWacmbHiV9ELZZySQIB8xDEQrhzkDHOHZ8NBQdAa49k4OnCS4ezibwhGhnL0k7Vu7pllvtIu5pgcHAbmHg2TSADe+YiTFIcmjh4UUzKy6VfGL3c/kclI2+NQoT6hjAI+ZxwV3rtkqAcBFu+dzjbUCScvMstk0jNekZV81vSPceJi4IbrZ3bpmYQKngOZy0kEtrPWmz3qfZ5o28Ru21gpIyvLsWGuEVCiXU1ANtLOvIygTswX1rFI8yYzz2LXJ9oxyy5tgnEE9I2TizLYQRHKWYUhzAkB7Day2zOryskIPkfwBIdLqCP7s7IeBF9w6ti7R9kJx7xGHpo1Fp3FvpPT7mOcs6xb9CNOAOSfOeoX+BzrB38XjVPAz1izn4u2QA6xhrEDDscIzk8zNtAvyGBHF0KOh5KPyCPameQs8x2MOfQA4wCi7WlX2i6jneGhYB1k/UK3tNdi744mjlhjrUG+4lzk+QgakSiG04igDboDOztIHAt17CPzwz5xxTjlCRaZnYqsPThkw+nTWaHjRNvHdrsSbAoV6DJjjT4NdR2JXQafQ9dl3Tc7zO3ALP0c6rjTIO3C9xm9nuB3uHZhnNGX9ik+jD/GFs9I/xNExQ5grIQKkvHczGXvXe2coEBg1ujWNgRvcR6z1hI8RO8kqde0HX3K8bzMH97HGcr4o5/ZjW1/v/1v7CH0O/uYV/RoAsrGRmHcIhNw/gcda3yWhDhkDbbg/9u7F7B913JO/I9KCbEyxcJUJjGqyZQcoshuNsl2YemwVNpN2kejmCxk1wblUA0ZqVSD7NpYMgtZIpLsSqQYRDrI5igyWhXv//g88z9/c65r3c/uvq/nfe73ec/vcfzWb/3e93nu+7rO67zO69xf70r6uHWVUKISPGRjVAJzsratZ8k3/ILW2b5AcwkX9mgen8BFVMyGHWE8eIg8js9mOTeWX2HqfNq1kfQmsQPv07OsAdssOrVYD0FfthpdYdUdluvWhl3g7MgB6l0DEehu3vn821ae0MfZdKuuZNhFLm06i7eBszMSasbaKcah6hzPDyXd5PHo4kAOSICIxF12G1vDeuNV+5gtS94LCOLptpuNZ7PZyC62Hx9C6On8JWzQzOdD/JbhLMVrzuQMyZqeR77ZI7vQZR2f9NAdtwU6O0/RtJVJQ4j9JPGcb0eQ0Pqyc4yPTyq3ym+f5cyn4/AFROBIhy1nJ33OfCTvSFgxHjRp27sKWtGDcgIWuWe98cVQy9XWdzLFt7UN+G4UO7CZh/S+qTRpnzGVX+m41lOSdatvAZuZP6mt0t0Fm2TBtrBu6DBGxu4qHw9pW2e+3ze/Tj27dqVrD7/W1D24DeiO5AodcCxNfJ6MRhPJFnV3bKGwOyoo2xm7BswIUBkqhHMWZKsOTZnuDrzILKNEMMop5RQQ7Y0i4ztn80eLYYZH2/4kG5g+M9TWrgWnnuzjqLgCY2dMuh/GmCJjKg7dfPgyMh3QDIfsnBJokgnu0JUl5fDMB0Wr2AhcOpAYNJEZng0RxjRlgJNiSAkYQ9d2HFNpq6rSd6M6T1BJdhwnQsD7KLOMiil8R9mMFsT58GYUckByTkQlTXZ0eG8E2jkWOZA5RTItM004mTicIqOTQ5KCmdtTeS+FZF3WKqOIoZoD1CrHjMf3IrM2HGyr2jauU4gpgtawVWZibvFMwS3GWQ5kRoDLu3OLtlUOsTFjybThUGFQmHt7Nytnjb2Hx2L+aMVhzMBr11Swtg08gp9xBmblOFeObOsAorjKJrZvNil66/hXJiCeze0JhwLV1iJXT3DOS3TAe2HQc6jba/jOHm/fi3bGKzjLgMztqf1MhWi+c65NRAinGoXbOjIa7RMGtDWRxEKW2GdkT3vPTaatcYejIifyeLaKqXWt3jzTnDnh7RHvzevMKJbF2hqm7doas7NJG7W4s8hY0FlwR/Ap02Lo/8fQJN49h2e0vDblObE2q2A9cieGvJ6b/r+FIA7+YWyt2jdj55LP2Ck8yynDiNfmP1dhSLCSgCPpRaWY8dCTnIn0gtYQ7vGcTJdVdPVz+4ATid7R6hRTxoFG9mqMxx7jzOCQyGey39MnfCeq2/PYs4x1rtun0SIughaRqJEr2lT/rWu3NYbXWnBkeE8OtKkGQEvzjEphvJPPnMxvgnESAskzupukkQiI+B39UQIY548zI5/j287H78j+Vk8SyPAzv4/rFDgh2mA7Hcm+WlXRmmljz9BRBQbQwbnO+UufsGfIbDznPYI5gXVXLGyr40xd41UZ+RL5ItCVW8PSIfF7ewdmfi+HqrUVqHfu6MKTQS+hW9JrhoKZu9hgnMDZQdjyrKAaPpLc1t5tJmhq3a0RW4FTbMjG0BqRPUO2elbbNtNcdEdoW5SSJXR+AVR6nHF6Rq4aEdgSLCYn6H6CSkNV3QEyXMKAddHByNg8w/4RSHTWSzK0PlGhHry+rd5nja2hwGE++8wHHelz7T3LbB7rrWKQzFL5RRejPw45tiVa6PQSOnfmw5Bx7LmQJ0MtLKfwa6xPr/mAPS7QGpWxoQ94lqQaNscQ2oDOOpADAvmq0zbpJev2kbGYyyZ50v67talWYRuZtOks3nY+bDfnCft3LE2cr+wvCRHrzj+dwyQY4yf7zb4N28SZLBGJPHEWkLNsKGch21lQwmfYNfZo6AQCH5EsGrA2Q1c15fHjS/LLWkbiqvOKDOGbEUQj/wSXdAFTqUsuS7jYhiar+GSIH8baO9vKev4qwTvybdugRfye7kank3Tv7GcDZhnb6hXWmH1OXpuPwGroJ84b5xnb0jPizMjJL84BdOdbo4vTDfJdsuiDV9nv6+5BHevb2iWBTfJL20lkaO+MoUm7RlP51Xvs89xBT4DO3omxktOR1NOihyzYNcGJzRBn26462zr5OBf7PM9pCr/u4+wae+5M9Wtt+/1VezD8SbvwmjMEzw7x2jbj8V5toSVUZFkwtqCjUDivqKDsAQOyFE/GEcFOGd/20BRocLjFPZIMRw4bgjnarPiTHaiMO+06KCy+n1snZVB81h0M8f8MCcYlBbG9J4wxEQ6IVfe7MDSN1yEbQY54trFxgKCNbNKhAzzarnq3rDQZ6pSzyLLMrQMZM0PtNMfQtX3GVNoCQzwqgSmODP0IBnHORXB7KBCV0TogVsFchxQrjkQKAhpEq7AYH+PRXK0npTlXDbQHb2QjckJQlIFyJruTsckwEtRlbGSHGPrk+Tnk0Z6S1t57RNHmVMqO70DwkUxKfLZLG+GgS25LFIErjiDKnCA6Ay0HMgVLVTLnu0PyXMaOJe89dOWk5FRDF/TMAULwM7+LO+w8Ax05hxj0jBbj4uSTVceRl1skkUn4ON+FnO98ifEweFbdE5Zh/YfaCsbPhiosW1h7PJnlQKaLIDKDXRv0HGwAcsSelAQSvCgwy8mVE0cCDGEOVEkR+U4jQUx8z9BYJeclVQgK5DEwAMg4xlVbNdE6CQXj2vGEwk3OUpwDeG9TuyqIRA78mu+njvvEsgMyxtPCexm95FLsNz8jLzhGc1vWHjSBPLe5PGPqc4K22/B8RnsvEtj3m+6YJas5LVYlRIydSw4GTeFZgTlVYM68Ib4jS92byBj3OYELRnt2rHne2Ofkrgrx9zZ0NSdnfNuyf8p87Cs6TA7IoysjFy2dHZl25LQzNsvuXM0Vn/U+VXTgHMgdETwjzivnnTHjtbYt2Vhe43QQgIrnSbhT4Ug3bBOYJItxPNMBMk3zOICuR69UPUqnoCOS45x+zlZBbRVD6IaHg//y/ttmPuC7eY0FS+Kez1gfoBOgM+TzXXUlHbnV5zOMm8NXohVaOZc4XCNwJzmKnuP8zo6oKXrF0N3WY9Y4646C7QJT+f75uLOzDXTlOwlbGIeABf2To5rMEMSwzhkCiXhl1RlIZxu6M3AIubp86Bz9kR/5kaUTmQ4ctkEGnqMfDCUECp5IiqCH4Ad7mU3TtunkkBxqsR32DH0LLSXC0t8zvM/6C+aj+ao2znR2gexI5KDjqd6PIC95TydkA1iD+Fx2em6r9+WqfeMxNnze6hsZzh7JcuSjxAr7XNLuquQoPEGWuL6mpbvKVXNTkRj8nr87lV+nzkciSdARfQQKfC7aL2fgZfIsumit0vUkBEte3VSRlZNXW/0GLVed+y2GujKMec4UHWfVWbzLOOwdraFX7ZttnoH3yKt2HO1asHvxnJ+zQ9jAZHsEmfwtSETOxL5j97GbOc3p8ewTAV1JTNkORwvBgqgGXRd0dO7Q5z2LTsCuIXONiz4omdO77K9IbKIreC/fy1g+aTtp9bB3tpH1zk17bBWfrEJ8LrpE2Mf5epb2Oc5idLO3dfKSPOfcoNtFdajv4GtngHn43GKxWJ4zZDLdMILsAlOCr21g1nlizbZNhN3Wt5XXaBs7hQ0hoLou6XoMTdpn7cqvqpjJ3uDXOIsl1fsO+kqGsq/4oPgOYt5tK+hesmAXOd2+f6zOtkk+HtK2zrrsFH4NjJFJvek61a/VjmWXPRj6WtZjt9XXMsb46byPn5CMGltpWygUKijbDQzEtvXRJhD8jEeK9Solb9WBp3rUXY9xL4Jn+Xc4gEKoM/5UDUTWkcNE5q9DL2eMCUBkBXnIqOC4CyXK/1MWORJyBq9xCE45ZAVnBbBWKR+CBA5ZCuam1jpZCYhqT0pVfIezjtOKoheOjJaW2ygS6+jaPnMqbaMSRBUjhZFzJFez+b1gE2U9GyFtdV6Mk5NWFvS2it5QdpbqnAjMRiYu56fAqCxDyjQldtWBax4+lwPTlFQGmO9wXDMaKREC0fEcwTDZsFEtHONSJWutOUTbrH9K31BGY3xOMFm2eq6y3QY/9VM/dcHY5UjjKKWUMCi0LWKYyeoN2AuyIofulZgylrxeFB50o3hxjnIC4zPGa6tAMoKyYuZvzl3zEEgLRdQzOIFUm6C7fRUt+GJd/I5TNDuf8I2sY+vS3nPUzn1oLgGV7fgg3wW96jmrHKccVRyVKpiMxzq09+1YK/OMKlrftz/tdVnJeCgqnqPSIgwKwRL80Do62kQVtMMXgub5WYDnvUvlSA5wZ/rEHYuMSoH1XBlnfByMAjDtXdND7aqyrCFj8R26BMhwgSDJQKuMz3CIxDz9m6HLMI6KWT8jq1TZtfJoLE3m+Iyez5EYgPZtZc0qqIyz/tl4ZDRqjahKeegqhCG02cBj59KLZzlC6QntfYj4V/COLhVdOFSUOqdVqocjJuY09jl4X8UJ+gVtxtA1xtJjPsYU34+f0WUkVjiTs57l587huAOcXOfMy0HakI+CQFofZt0CDwgEkn8xV7wWNJnKaxxPHIm55aAxc6bhO+d6dso4X8ncuNNyCM4gekluW+vsdbbR/fBcBCeNNfZODoBtO5+hRETJPwIxzjx3xsrYBzog3SuS4oKf6H1x19MQ8IEAbFRySB60RnTmDE4o+lTWQcfqFb3kSV47TjRrJ/hIPxJ4CJAz5AhexaMZ7ZkhiI8e9lEkczpj8Di6t4FZsAb5fnO0MQe65D3ucY+1iYptZXz+Nz7KQT57j0NYYla+k3no3AsIvqjYyXYhe4+eQidpA7M5UDZkBwnA07voOnEPbcy5RXuu+ze6RuW2vSTYH8mfsW/oBvgh9L585cq2et/QnFTkqpDPNMXX9HqdAwTFgqfIRHzDyRrfd4bY6zlQQ54KVlqXSJzMz7f/yKC2kqYHv06ZD1nHbm4ro61JtErN9iPYm/SGdZUn7FRr07ZXX4WWx+w5STP207oKvHbftDbPts/pLZNa2mwzjnbs7V7adS4w5MsgM+jN1jAHDpyT5ik41LbnlXgk4TGSdvB5JEWycZzVkiLjzHfGS56UVNtWKuU2yvYRWRDPcv5IOhGYyvdsChrwScQzVClKMrLvxvDJVN1xrKwfssl3Qa6YRdtVvip04hOLJLj4jHPAGU0WRdJdSxs2u6QMgcVIiI/P6CRC1uCTHJhtk+em+rbaVsPb2Cl5v6w6h8bQJFe778qvnsNnJunRGRf7ytnHZ8LnYL/ZK2SwM1DAvb23tKcsmCKne8nHlufmYluP4ddWnow5u3y2N12n+LVa7LIH6R099LUhbDufjKqQLRTGoSplOyCCJLu0ExtCmwm47YEXmWDtc2RYyox22HEABSg5HICMUk46yjEjdJ0gZQD4nKoECg9w/stGkwFsHJwnDAdZ1ox8h2RWxiiX5sQojUNI0NGh0Rqom2hHYad0RfAsArOMbMHg1hHck65jabtqTgJrxiJwxJgPcECE8zgjB10Ev1UN4D2fyxWO65CdCW0WlHXkBKYAhbGkjTBHksN/XSsWhlu02KMIcDAKZuGFltaBeB7nCOMk/8zfgmOMFdWo8U4GmAAxGq+iq3051C56U0W7YDFDWAWMNc5GdASdKTsURwE7gfgI2LWB4zFjiYy3AIOccd628TNOWdbumWkzjjMN0VRQnVOgVTQ5kARhGcH2Ttvm216hoFq/HJjF87lV8Cbkeca47C9GU+uEXvW9GFOAso4mFH6fI0s4LDlCo5V53iet4suxbt9xnLvXTXAxqmntSXvPniTzJE5sasmCHhRjxl57348qNc6DuBssQyCGvOCwVY3tc9Y7K8G+R06G7B1Ce6cLJy4nKz5hdJLNYdzne5Xa+eA3gW57Pq+BoAo6eH4kT+QKoaF9OJYmc3xGj+eQYWTrutbTrTy1N30+712OrFzJPQZT5jKVZ/ENHsztwekAnF6q1GVNy3JvW7QHgtfGPifoSnb2oOuU+YSDgU5DBrUBBroMJ77zTmDKGWwf6pgQMs1ZSycRbMi8Ffed2s+5s4OAELlHBu6L1wSwyJsMz6VXOHPirAf6op/lyp8MehVahrxufycw6vzydwSYzIdc7zEfa8SJxvkruck4Qj7SvzgXrYfzAy+QrQJGcW/7EOw51U6gc0UOmhuvhJpIggx+Hwo87KLj9F5j5wzdIpLFONfs+XzfHmcnnTCC2KvGSL8QZOAwzRXj9GDnN72LIzZ/n2zR9jC30Qd6ebY9dgE6SISgC9Gng58EV+nz9l7uJLPOxtCJpNVvIjBLPrZ2Sj5DyWcJq/6wnQDPmSudxHPyO9eNx9pwSKvyslaZ18yP7Mj36EVwcqreF3Mi18iDgORRtDQm+8aa+9mQbmUtfZ/80wIzusAA/Zuezgal7wzNPf89hV97zCeCmLopkGOtnsqpis/J+XBG07usN1093j+EaBG9DfIzMg9aWwHnbdHjOT1kUo9x9KJJC74hCVP2Ep9F5t8IsNLNnSnZjvP/zjNntKCUxNDcwUnwwe/xP17GJ0NVZHlezjDvY1Pnq0sEdAW67IPcfcp3JQRJTiZnI9l6Ck3G6I49Zf0urU4Dre24KildNZ/1aKHS03zYXkNV6s5wv7cP2F/t2CT+S2hjx+X20WOTg9f5tsbYKeuwC03agoNd+VXCAB4lP+m8zl/6Zk784mfCv1Fd7Wyle0q635c8GSun52wDTn3GWH7N3cWmyOkedO3l1xrCLnvw0H66QqHQBxWUnYhWuHIeEKKbKj+HfjfWqc3QbCG4JwsxOw84ePLdIxR9xmxuBzg0Bk5AhiIlStZb3NcTwTHBQHdtUGwYqxHkY0REsFVggMEqG9BBw5iIilYBEIcjJ90mhTn/m1LP6ZYDs4xtimvrDOxF17G0zcqmzCetBjkRKBdoKLjEIUWh5IzlfEG/fM9NVFPIpub8E3wSIAnn4DbtIhhBGWjH+cTBoOJkqJVxe8fskBIf7xa49T1KsQARJ4q1pgBxTKP1KoVE5bEgYyhI2ai0ThQ3zzVmir5gdw4uc3hT7Dg2cjVDgEG76q6gFvgZnxt7G7TmePd+vBx3zMQaB13GjoVCFUZEzlC25hy40aotwJnG2c9xF/spw7g4s3NlL2S6UdwENjmIhtrCGH+0dctVH0MK3CaQjdnobJ1SQ89uW3MCA50TXkA8HNcRhCCHOFNzK2kwt9x6kYM3DDrGnOAFR3oEZsMozO3ehuaZZaZMZrJShVr7fm1k2n2DTzjxYhwyiDluIikgZ0nak6vaeq670wWvUfAFFDhXyLV1LWaiyo1jMWRLvEvVn33hT67mWJeNvitN5vaMMc9Zd+6vc+gP0ZOBGC3d2uqqdePc5jNjaDKFZzOcDbLljUEQhHwj6wQY0YjTmqFJhq1bm12ek8fSm667zqfdM2S7gIEzp5XTdARJIsZLt8gVpUEbstR54L3kYIDjinPK/bUcXMYjmc753HYe6EGT+DnnofdEAkeMkwOZHhl3WHI6O0ONe905ggbORq3qVPJlniDjnFGSpfK49rHGEnXoOCH/fI9TxJpzGvud5CAOknV6td8J5KOF7+UqGI5CgXjVH/m7Y/WKfcgTjmLnZSQa+FuwzxqQBTkgbT6rnsVGCEezc0oAQ5vXDIFZa07vals2+q6kPeu/Cuv0vfw8TltrIXAQyXmcv1FpIABA57A2zsmxNgabyhrkasw8RsFCjjA6Dl4iXyUEAjmNxpzZQ87DVXQmV4yb3hoV9lEdIqCYE0p66330Wraa4Iv5SGyw7pHQ6j3onCthAX3o/XiVzGMnsVdCRzMWe4SOa90EN6IjQUuPXvw6ZT4BAVdVh6EL54RuPzMe+pfgMNlIVjsLctKnADvHtT0zlIQc98u1aOUjuy9XnK36bO/n9JJJPebTiybtvNjb7FRJN/44w/lBWh2Q74BuPhTEZzM5v/kk2jF5PtnQtlUfGiOZwsfgWWSs8WRIcCBvnNlxzQ3Q55xtfCpjadLL3ukp66P6vq0g3OaZq+brXM4dTALkEt3Fnqe/5e9L6opKQOcPX1h0NMifI/dV9m2qQtvFtzXVTulJk6n8qnNedFXTtt7P2KtkfPYHRpKV8fI16SLlXBjy2faQJ2Pl9JxtwF7PmMKvY9dmH3Qd69fquQfn4KcrFArTUEHZToi2RIxDwTiH1LrAbBZmPpvvtulx4DlkGNrAocBJJ9OYIywybiG3iFp1DwoFMQt5xjuDtA305KBQBJI4LjgyGK0CK4KOFCZOf87CaFPG4eJwzJWiGTKt2nZSoI2X70U2kbE7nPapSOxKW3+CthRN75TFJ+Bq3N4jO1sGvqqauG+DwtlWs+Exzl20ZZzk7L4MCn5uZRFBbA7NyHiKuz6sB8eEQA7jP9rhUqI5FjgF1jmgrA1jAgSaKUoyf61pZPhTSDmE2orOltfsHYH9thrX52Q4WmvBNHPIgSXOaDyGr+xBmbiU4QDlW8tEn2sr2jP8jtKOHjL0PNPc2rtbGXMc3Pi33T9TxqINIWdcS288Z+3QNldmA7pwDg0lMFA0OQHCyGsd2RxYLZ/nVlcB+3ZI4Yv5fMEXfMG1AqdD8P1osd2OlwNriJ/tRYaXz8dYySB7RBCjVeTRyt6SXRutizKfcc7Zb+5oyq1uyACBWU6/oXYv2wbtVKCEXGmrN3LgPto4hTOUw8LaU4aNhTFq77V03fVemFVtktYFD9GF01eQKQKzIOlFwNueX3UH3640yet6yGdsMlrGrLF9z7CUTJMTIfKZuWp98vsYpWE8tskX9rhATdv+rsfaQJZRPXg23u18lAxkr3JWcizmuXHU5AqmVXPY9TlT6bqPcQQ4kQT9JCi19PcsjkuyMOjbdmaQ/S+Y5O7TSIjzGd9xDghcOGOdxVm36E0TcNaT0bniLPiArBeg5pA1ttx2eWgfx/gigY1sartk2F9DVSg95uN5dC96gc/jcQlZ0co95kZn8h77I+aak7rQJP+bI9GZk7tg+D1HoaS8PL+pOs4+1tjn6EbOBTIkdEvnjucLYK4aA9Cf7Bl0BePmbMWnnpFBXxnqyrDKWR+foc+aZ3utQQtzkNCUnb++6xzFbwFrrDJrG4fsOhtDYG/ovKF7CMZxNvo93jMutkFUQdAPyRO63yo5b75xtUroBAIi9JvQwzmJ8RJ5kFtG9tb7oqKb7m6tyam8D9hxxpCDmPQaciw7BwVg6XytvUxnl5hondgsqhNbvbAHv06ZTwt6MD4PXT/rB9ZZIMJ8IhifP4OfyHPvIAfIi9zC3Hvxh+es4g9ygh2JvrkKLUDWOkNyBXXv5/SUST3m04smYLzWOCdQRfcrycdDDvesO2bwfQhOCNzm5G+8w1+g1XGLvO6qnfgn8Ihx4Ru6hP2UoYLbudyeO86oqevbS3ccK+szPRQYoAGbmh24rjVn/h55EddmRVAczSIRBH/S8ayx4KDvkjd8GooXnAeKBsK+JLMky+ZgtJ8JzEq0zdV7uWPXOh1pTOLoFDulffdYmuRkmjH86gzAP+Rh0NO7IjArSTmfXZL76Vg66w0lz/WQBVPl9BxswF629So/0xhf7NS16a0Lj/FrteMYuwfn4qcrFArTUUHZzmDsckIxpgjzocBsq+Q5EGRS9Tjw4jsUXxlojEYC1pgYB5Qih1m+8zOPqa3ac1hShtx/luH5FEcKaj4wKY4UI0YHpwJHAMUrZ3RTsgWJBACNZ5OTwgFFcUYnSlj7O9ULcU/TPhWJMbTNTlPKhbvPGFCUcsa8fwtwxHs4hBj7FNt8h1h7J5L5qoxbFSx1IPtMbm3HQePAFuwVSFZ1mg9ozzIvv8/0kc24LptLpYt3RTu1uAckQFmmgKtyyPPIjkOtp4FSwmmsCri9xzfuSGCchnLuM8997nOXCm/cWxGB+hykMh5jkDG5qdVbBr4QmKLg5btbc6Aqr3GPsaic0YalrdDF3wwICml7b8bQ/g2oRpJEEBWlQVdBAwH5VuFctdYCmaHw5RYpHHucWZx9m57D+WUvtzAmRpO1byuz7SeZ1O3PVcuiB3nTVkfIKPa8dgyCl4wkDi8VI3kewCDwLtVO0d5o24zAVq7gG06UtroZ7D1ykdLv9xRma2TckcQRbaWt9z7udMnjla0q4G/fhcwwLskV6MWQRH+0Nqd4/6bMy0006UHXXmvTeyzRHSAqnfB9dsSRi+QLp9qqquN8/tj/YTzmdkuCBGRibnPUm1978ewQ2juxw+lNpnBQ9XpOD7r2mo9zVwIXHSK33NK2lbOIg3KolS/9km4pIOiMjzWUzBZVlc4m9BfQyC2CnbH0C8GO+F4+g3vQpE3sc8aQs5kf4nee6wyUZCaBaxPvxvecN5x86EB/bnXr+HfPNW7HJMmMPkM+DjnEgfM4J1DREX3e+cnhah6qZOhXquIEZgX76NsqS3JFxxS9ogffb6q+sL7OmdBZyARjUfG66bvWXqAt9BA8JDDrjM6tB9ux5HmxA9Cb87WtohI4N891Lek45dkBggTh0A3HGJ1gqH1b5rVVY9w1EYiTUeBUYgfHdX4O3sAD4YREr/g93spOe+uBpwT9OILDmWdN6Ux+R3Z7D12n7fQyRe/bFfiWczzf7Rr6C/mIZnmt2Y1hB7bjtVaq8ARd1jkOp/Dr2PmAZ8fzI/lCMmxU/mZeoN/Svax75ht8SK+IDgRkvIC9Tgj5PaobjSMj6Ih+eDLrHc4oAb/4jD1h36BNi6nP6XUW95hPb5oEtJyOzhb5nDUve0bQKd9jmfnOWW6vkfsBvhjrbk84+53nEirol+t4VlCf3WxPBPAKfhcoy3yT5+KZU2kyVXccsmvHyPpMH34KlXnsJckbkoLovrktcPt+8HnylE8r9HvJ9QK79l/oMPaqcVlfPKsDCDssaEX2+ox3C3aTc63OHa190U0SFl1umy5fYwJtY+2UIUylyVh+jbnjDYEn+kToZTkwS+YHJALyB+Tk/l6yoJecPrQNuO9njNGTesj63rrwGL/WVF/B3Px0hUJhOioo2xGt04gy1QZmsyB2CFHyhgKy7TNXHXitQI2DRjaLDCBZeO4viPYDFASZxEPtCPKzBP5UbBC+DiuOnmizEjA3v8uZzEABkqnIwci56DPtPSBAGWZUtBjKEnLoOpRU6LYVoJR4tJaNFpWpPRzSU2ibg3ZAkacQqmIJoI+qM9+hPLRBuHhnHgfjjlNGwBvtGO1tgD3AoGsVecFgjq4ItkQmWbzDsygHQ1XJ2aHQQnDe2jB4Yv0oN4L5KmHyHZaeQVmI6giBIAoEeggcUpDwnaqPNnuf4aTNCWMmAsqMm7hTRlCX8h2tAI0hMu9yq6JNPJKdIxQmRoNxUYgoNZxZ3t9W5vQYC2c8AzWcbHks+IQTzZhy0HDoOfFva8CRldtjobNgLYd4m80ckNXMQZmrEvDLkMInWLCKNzjJwpEouI3f4864PGaBv7a1U8DYydS2xYxgIie2xIy2ujVkQTxPZrakA/LW2lFwraVkiQwVFmgT32MYt1mHq5DHrtpN9XsrkzgLJa3k7Gj0o5DH/R/Wx3tVdPRoV7XuXhjyk7P3YQ972HJPckCHnBL8tyYMBVVakVXcgyZzeQb0eE7+uT2s9VY4BtCfw0nCRTa27E1Z8G1SFdgjbWcB+z+Mx1yF4wyLZ/SiyT55tn1+gKxzBtt/bev+Kc/JOsVYuvaaD6fTB37gBy73mw4HZGl24BtbXOmAX9r7v+iXWuM6V83FmePM5gSKjg7RyjhXzA6NrRdNZHlH15OWlwUOyQ+6TpuJ7t/klgCrcW6b5IEGvse5R9/Mv+sxn03vB3cDxn1p7RpJbDFne8pY6Il0Fo5ASXwCMWSsMVoze4hOZk7kbdAhArNj9YoeNMl8Tf+i95NhOdCADpyL4Of4OrfDbW2fFpIMJClkW8kZ3SZb5vkISrJJYpzeG87X1lnvjF/HWxx69FD2Sk6S8Gx0oXPlfbSPpBfPtKZ0X2dwJHcED9DN85kSoFuhE3ng/BfM4/ymn0keoOdI/gxdH69KytSimdMxbIygTy+9b2h+GXjVeDmk6butrYLHciV42B9kX9sKs31PjGkKv/aaj/2aA/r52c5VgQbyOwfosg3n3EX70O2cG6GfcVA7S2LsbMjY497vXeSNyusMZ5CgmN/jffYbG0cyiKBfjJFzO/ZXr+dMlUk9xtFrLkO8kJOy2CV8PJKh2sAs3akdQ8h6e5au7TP2clR+hu4QHaPo60NdpQJoS6czhtzFKwe62IDG15MmPXTHHrK+3aPkgM/HXbUgYYWvga6UW6G2AVl0j4pG+hWdRRDYXKJ1bthZ+FaSu+Qpvp8YjzPcOW/fOg8isGFe5odGoatK8pe0wV8TvLONPryLz3CsndLSaApNPBdN2Pa78GuLGIvzkm9xKDDruS2/4HvJxr1kQWBXOT20foe0AXv7Pcbwa0+Z1Ns+mOLXmroH5+qnKxQK01BB2c7YJps/nBAcAG2l1rpnrnMCe4egn0MpV5OGMufzDAFKjWyZ/N1s+EZ1g4Af453TjIPJYaWqrq0CYXCuu8OKw8nB4NB0aOTDzVwEUkPwt3NlpDpswilhLpQcBxal2r/9YfhwPgBFoq2m3ZWu7e92pS0FXwZePMf8KJKq2dogNGOEM0hQ2dzatnPtGN0LFS3JKA7eJ7ias8ZkiWaFo10fioxsJ0F3Va4Z+JZxktsJ5u8Ghtq7UiYEZhkTDAu8YrwUrPYOS0o1nnLwU5Sz8oGWoRQIJmqBbK4CxaonZK1Ruhl66CdYr1LgJS95ydJIo0TFmCUMeFbOfttWmci8ylHHAazNDqcZxdBYWjr1Gossa/OPiuNsjEkIoMTlKvN1sH+8Fy3tw2jZI0CZebitxrZvBetUTuegAYXPfqAEt8H7dj72KeMIrWTPGgMnA+ejqp8wFHNl9dBzJGKgyVDrFVVHHGySJHK7vpgXWA+JITlzEg+jAXq0gdkAQ5GTZN2+bNFWbuWfcYZSrHNyBlCGOWLIGIYbB6v1b4P+vVuxU7DxRFRgWS9yKtpdB2TlSzrxHMGXTbJqE008Y6jN5mk/o8caOxftsfgZB5LgSiQrcUDgf+vOMHdeDTlg8/vJUoan4I3v5axUPOwMJHvaO4q0berJr715dh2sJ6eVs3Kodf/Y54T+4Dlj6brrGFbNh67l3eEU9DNy3JnSJr3Rw8g8Zzy9gdEen7HO9jlnocp+Mrldc04yvECOtxnjeX2n0sRcnOWCJRF0zecVfqAn4n3ndquf+Y6fo5N5bUKMnX6hmqJ1Uux7jfM5KdGH3ojGuVIx5AIdRbUIHS9X4tBh6BP0xHyHeeg4xpfHM0av6E0TOoF3q+SkO/peVDQ4n82VvSMAiBdWOcY5ZVWC5fvKXRGB13PQ3s85eIeuVaEDCZSqtpHsEM/KztdI+stY59Q2F4kDztFcYY4G1jcq13slvQzBu+wnuhKdJu8H3UDofVlXieeTBfQszmXvyQFGz5AUSTY754eS92Kde+l9m0BvZxvgF/f5bZL1WT+17pGQ4Gf0vqH2o734dcp8yDqy0dpkfT3P07qqkqd3cTDnluhAF8PnEuSMDQ+xP+gQWRZ4JrmCf/IcdFGwH3JitGeyG72X/kdfIUPwDRun1U+CL6c+p4eO02M+vWjS8r419sxsjzvXBN11v8ryp73PFKyl5J14l32Gf3IQirzHT9pLRrB2aCzOJnxpLObk/NWBIMO+sc/JvR7r2+7fsbpj5pMpsj6vA/preyyBNQdlQTCWbRotg1v/j3eEr448ZTtKjM7zdWZYK3u4bVtOl6MDeA4+tw5kMh2Gf4N/gTxCawkdkaCfz3RznHLuhJ0SGGunDPHaWJrgu6DJrvzajiEDbwhot4FZOlib6NWb7/3/GDndS2frYQP2sK3pSW0Bza56Uq+16a0Lj/Vr9diD+9DXevnpCoXCNFRQdg9Yl80PFBQtJ9sDa9sDL2eTh8OGse7g0oKS0sHxEQaAoKCDjOJL4csVixRhymEIeZWOgotagOTqkgjMUrraDKNVzo74GUei8Qk8ckoaD0c4A1bGzRAo8b7DUGU0U0aNO+5XMhZOHAa38XtXD0WiDXaPoS1FMg7eCGILTst8YohQHvI7KKKCpJTuVQ6BuNdF1UluieeQlGntUKb0UTYcwkOKc4aMRe8UlDKfgPFzUGSnFGRnmQA4OnC0tmBcaFeoMiTmtspJz9nsOZwqmf6A91QGUM7Mh7OJ4kUZp4Qw9qKFr/9HG21zQvEFPMYgbgPPuyDTj5IjOGUeDBAOVWPJrU12HQuFR7aw7+XqalWwlCNVOG11KPhOKP8tWkU/1pURZH04j3JVUrt3GcEUNFnL9pR5Wqd8HyJFUQZjvi+wfXfsD0aCezLsYQkLnoVnVRLJiqT8hZG0bq9y3JOlcU9xBqUT3wZ9c3DJ3hP0IHPJ4wzrSH60d70MzYXBbq1b+TuE1sHns84DhgSln7IdP499gRfC8aCCd+iem6mt2NuW4IxGWcphEHBaRBtkRnTbKiobBD1ocshnxHPyZ3d9DllvD+RsZ3tGFR2ZSWZwtkTyhuAD2eB8bRMIAiqYyHNnMUeSSmeVPNnxzLC0j7JzqQe/tjQZy7NjHNuCUwJP/rR82uM5Y+k6Fu04jCHuEMvnIqc8R2Futxn0x0OSIegG2v9xHuZ1pJdwfsDQOUtXYKiT3UNrMpUm+FuCj2oO+p3ql6HALJBJ5u5Mo3fSZSKBhKxxnntH3Jm3KXg19O/TWuM8Nro9/SzGkMfm584452m0PQyQCRLgfCbONOeRf0/VK3rKE/zGeeTMDgcnndFZwx7gsMHP7Bk6Jf2ird4K0IujPbNzl+7sfPZzTrJVHR0yL8V82CT0EPLH2R+JRdn5uq5DxBAkMhi/c5BcZ4fQPeliYWP0Tnppf4dmqiLIVH+sE51btb3gxCret5dcnxIJtBl0MHuTzSUgPrS3puh9u4JdZN/QP2L82d5cR0/B6mjryu6iP1qPffDrlPmwX9CbzisgY6/HFS9D8tG+FqTiWJbIah0C0YUAVPKwiwWaBRfb+0qdExBXesR+EBjI7cDpIs4GtkR03SGH2LH5LOr1nKkyqcc4es8l86lgEvuCM10yVr77lYzGf/ZeKzsyz9lz0XpXEFBAIqqssw3Oh8AvQRbFnPJYBGzRLvjDOW1s5G5bZehc8t0eNMlypYfuOEXWs2PI8dw9yPPsG/Nr76JUIBC6VKYzf0ac3b7PlhS8MP82Od057fns7Cg2MGe6OJ0/gsT4wDz4ayTVGY/9j/+taxQZBKz9lHNHMheZnWXsVDsl03RXmgBZGTTZhV/xQRvAdB44q+lOuXNfVMwGv/gOHw7Z20sWrFqDbeX03GzAHrZ16Ek5ALnpu/l3ITvJil5nTk+6jvFrZV9Bjz04Vz9doVAYjwrK7oBdBNFQNj9QBGXSxiG964GXD06fpaxqKxn3FjhoCFN/OAC918FIgLf3J/guAzBAKDMsKbJDbXEpOxRsbUXaNnTrxhzz9kwKLgXOQSGzJ5TEbJhQSAULKa4Utmj9p2VVKKXGycA2x7gLYmqwoDXMd6Vt22KGwiDwGEqC4DTjhPIvAykfjDIjY4ztgYlXOKxyNSmnQjb6BLfRFa2GWt0w8NBDFlq0W2ascEowAgSM8SkHlMBx/i7nKWdq0AE4ifFJJBvEmM2VIopGOatzqJWJwC/FFU9wQkR2aOsYESxjHFEUrAHFW3COsh+giKg8F0SSPcww4LCR8dU6P4bac67DEO8YY7SIHDsWRok9wUHN6adlXTYg7T+OHHtBFmmbuZcNXLzVtiTfZp4trSl/5JP3gb8pxNab8ZiDmpTgoWQRwIPZAAsYJ+cEQ8v3VePjg0yX9i6S3EaRHEAP2Y2tgeqZ7XwiO9e7tKxj1Od7+MD6mBvn3BC8F2+qVrPH7N11ciXT22d1CIifoS9eV1EehrdnxPzJYH+GMsantknEj5wkOfuas8E9ahyU1jnfS2t8kiDaO4d70mQOz5gyH99Bc88h7+Le5qCxc0LAP/aCZAhngnNg6Ln2m0QjrYTAcxlF+FMwI7eAk4gwFLTsSZMxPJvvZto1ODuUcd7jOVPp2msc9mCu9o/2xhwF65wJELwVoHs4U7RJG0pqigxrutfQ+HvwGr2CDmHsKrzwWw7MthVw9oFAMQedMzMq9/yR7MeBtc0dvnke8Y7TXuOhzw0lw3FkRPvmthqac4gzM9+pO1WvyBhLkzx+8l/AT6AhZ8obew50tfCsVUEujiR6s3FICpLwKJmIE6h1lmdwqNIBOI/AXhIEoSd5VrSRzs7XXSF5QBBNEDx35+hhYwTWVfiA99BT6IXWy3lhzwT9VwVm7S22Ap6Ie2QDZDQaDd11OkXvG6q83QZDezj4yl6xB9rKaRDojAAmWyXuww0aT+HXXvPxLEmWrv2hq/p/NmIbmG0TK83XupEHcR7Yoxy6+NLnrSM9jt3GRiDrPV/Hl2iRH61Dc/Aq2r0aUyDfW01noavgg6B1r+dMlUk9xrGPuQTIL/Kab8TnvYe9mp3p1sfPsx3dwnclnfN9sK+j4t1YjT8nS7Mf2c7kQg5+2DtsSXsjV6hy+tP1BboEAtr1jcBsD5pM0R17yHqBbL6qSBzPewxNyEhBj0iaNycJLxLoAuxtY4/OHvww9DRBE5Vs/BwCT+1VVYJtZFSb8Ekfyy1CnePeR4eKcUhME1jKCRk9Am3sgUgcnWqn5H+PoUl7Fdgu/Do0DueESnRrpWWrZ9Elgm8Ftfw+yxV8v1gsJsuCTAvPx6O7yOkhzMUGHPsMf2c7cld+3ZdM6qELT/FrxR6EqXtwDn66QqHQHxWUHYGx2fwRRAkldNcDj6KhvYIWOQ4UQp3xFpnzDDeZlaoUGX4U4XDqtM5BULUqs5pyKLOagwfcuUjRYmBENlnAOFVE7OKcDEEuI96hKLsnB1By9p4gASUrt9tjWDuYIjAbwbvWCI6fjVEk0FZVZijDY2ibg2T+n1OFIsp5EK3tKOQCqAKzntXScWiMApcyKoEjznspsDKX8r0bHA1Dxg1nAKWUo0ZQimNPJj4IAspAo8gKDjL0cpBatU8EorXCUG0ZoAR7Vq4Cxy+y0VplMc8rZ31HFifj0lwyL0S7v/huKGEy4yjv+b48n8G/gpzWydqjcesUzuNY5dgaQstD8dmxY0EzNKecoQdnmoD6l3/5l1+DbhQ2RoV255R5e9VnM98w7KydfcWpySAdUrS23bMCc/aqvUAxi0xtY8MHFMUh2uRMQ/tPdnjmDfO3l9GjDYwGXSQyeEd0EWiNOLLT99GbwyKqpdvnRFKFfROZlBRZYzL+toUmPt9UJSFoIOPQnm7vCl9l3JiL/aW6I56vSh0tORgkGcQzWjpynvZqk+j/KdWqkxiuwR+Ubc4f48zt9awTHrbn1/HNWJrke9Tn8oxdnsNZYG3iOWjOgY7u4Qj2HQEzVQD41L/9Pq9pKyOd6+GIY2iREZKhOJnJWkkzbQvvVYbSFJo4c8bwbPuzMTJ2yFG/63Naw3MKXXvNx2fz+ZYTL5zlORienYOtc8+ZHc9RYSAJI5/LcQ4Llub2fe39Sr14Lbf/0lo1ArPR4SGcsOsCU0ELgTpnWduCPSNn8uNT8uxQa7zus/n/6UT0AXIi7v0NRBeYjLF6Ret8mbrGAlh0Rs5WCZw5MRDoyMYjADF0Fgec9/SI9i5QDh+6KH6JZL5wNA2dOwIaoXdL1mO/mJ9gFp1YwlZ7FUHuYrBt4F1gHP2dl7mTTDgJeyS9rEJbMUuH8a7YT2H/tAh+4xQWUKbrtPYbJ/gqfh6j9+X5CmK0LVlX0XnVz+1/+ghntioWAYqc1IbXyQfjyddvBM9O5dde84l/5/bTzlCJf21gtm07npNr2G7WQsUM+5dz2/oJ8NAl3vu933vJ9+iUW/6zX+1tdnx7ryLnrbMhv19r7rjWJHdoYXNNfU4PHYe+OnUc1rIHTVqwyXS6yMFWgQjJNmza3NlHskfuWNNC5wCJIOiQOyLgIw77SAYPsLNzZaLAmLGwdQTH7N0MY/Qz8kHQo8f6tjSZojv2kPXkmIBs25ki3/suiO557GprwsZWudqew+Gr8B4yIyr0QSBScFcQPWzMQOzh+MO/ZrzoLgAkCT638zVu+rrEYWf6EH+MOXeynWLf6bQyxk4Zev4YmmTajOHXFuSHwon4nSCxvROd2mLsbCD7J9CD79sK9zFyeh86W8YhbWv7b4yeZG3QCV9MkUm96TrWr4V2eS/12oOH9NMVCoX9oIKyO6BHNn+LbQ88TjiHhh76ubWCA4UDQVCB0hdKLEdZODny/YB5TJQmRgMlyqGUHWGcATK8HBRD94e2Y9yE3MqYIkQx5TDIAt5BwKA25rbNqMNdYJbBwkmyqYJsF0UCbSkBMuc4+MLpsQttHfJRqSioHBl/FFZz1SIjB2ZVnjLOBSRXIcZKkfB+wV1t7cyL01YQhWHRVjTnNaYYUWh9Bn3NlUEiCBoKiPVllFAs2yAYhCPBc3wuO2EFZmWbyTo1F62v8Wle9zweWXBx965s4MiEF/TGg+hPEWecMJiyUkTh9h10kXGIzsaVs4dlzAr4e0bQbygDnvGAnjLLstNtlTEU6yHQhx+mjAVvohGHeoaMZwkPQ+vIKJU4gE8pobFXGemCsZRoTqQIvLdVEmP2rzkJysV+kChh7Rh6qzLvKHp4Es/geXuklZWq5HMrmoCMaO1bGDW5vfuQI5Vc4qC2H8hCim4LTg30NI4wEO3BCMwO3ee9SuFs7wr33Fau5PH5Hce5dWG8MgDMO55vz+F1hgc+aue3jzaJ9j6nJBlKcQ+nAMU7Wh7iV+vAOIi28O3YetBkbs/Y5Tnkt7PIGeCP55CtjE4Gt6SbMLYYO+QaR7JKilV312mbJpuc411yDWOTM96e8znfsfc5m+zLTZhKkzE820PGAhmbHTpTnkOPmELXnmfGKpCvAgUhwyTncGAOJRI598mzqByQ9W2vckrkylhymu4zJC968doqx4pzLwKz5BgZps1y6CnZKdfSS7a6xL0IzLW0zd+Lu95kjB9yjWHVGufvCRgJoAvMRmVMpqPPTtVxpq5xnhOdjLPH3Ogezmbndqtb0OlyEpCAWm6hRq+0Tt5HFqJvTk4IkJWeQ1Y5m1addZLS0Mo+ibGTt/YBp6ifZ+Rqyay7boJggrHTp8yxxa7OSp8ZSgQaQk6uZEM4V+iMQ1fHZAQf0A/p63Sk1n4zvnWOtW31vjw3XXYEEzgbH/rQhw7e8Tr0PTpa3NUL7FHJwuGc5WglD6JqBlTLsKnCtog5j+XXnvMhk/J82mQACTVRMUsXsw9czxPJCpm+zmC/45i2hmSSf9OxY/3IAfMV7Gpb/ns2e629VzGc29Y4y722k1ag13Omnjs9xtFrLhlsM7xmbYeCE+ztfN+4z8RakeW+H5WFnqFzAHvf2nonOUSm0SHXtdlmL/FNhYzTocHZ2CZyOIdz97beNBmjO/aS9fwdaB4yJEAnZ/PkBAiJUj4rWLeqrbgx0qskzUkWyZ8LevCfuT5gVacq5z2bOCrx7GN2QwSUyTnne1RQbrpfe9tzJ9spce5MtVN60WQKv2aQt/Gdoet3gsZt8HMq32f9ZaqcnqsN2OsZY4O6aNhDJo2law+/VuxB8jBstl33YEvjQ/vpCoXC/lBB2R0wJpsfIpt/qHJ2mwMvnsVJFBlXAoRZcZEFqM1HVPAKeGrfJPC2ruUAoeuZDoBwhOXALOVKe5G2p30W8NnBtA4xDgcj5xTDo604lhEqaMIQVymZaWa+FLBN1Vu7KBL+DkWCos+ZuCttZSVz3DC00dOzcoY2p4rM0RyY1WKL0tpWr2TkFi94TiBXBmAoupxy+LBVfDMEbgU32+xciiNHcGRyMwpbZSnWS9shig3+sG6MmOzcElwUaOfAoHjlQFKeE7pyNvs8hcvnGSzhaIqWTXgxGyfWSIBKtS8lPCpNos1friZZxQuZXygtFDsBZYaQOckYa+m+Slm0jlPGgq4MkLZak9KGj8x7VRYyIzUq7SU4UOwim44hylA1znjPKmM3z8s+swfwbF47gXF8C35u3pFpODQ2BgnjMhxYvkP2qSr3d4BTLWc7Ria8gIPqUJnlHNi+1wZmsyyzDznA8KOAYlsVAipv8T/jKwdmrTeHX2u8r0MrV/A6HmgV3wgW5KAvpyIDgzMwOyoEK9qWZq1s69kmkQPAs8i5nK0tucS5wpHrd5T6Tc6BbWkCQzSZ2zN2eQ557Nzk8OAMBsYV+UwmM2iiGtnvJU+QO0OGozaFnHq5fRKZKKiFf8EZQwbLit02U3XbuXCMD9FkF57tLWPjHqldnxPPiucY/1i6Tp2Pv2McHICcV2iWZaz/Z7jTs1S7MuDpPkPyX6DB/mS85xavzmeyGi9KUvFHK76h/TuV19ZluGf55Lv0LjqeJBAttYb0UGdPOF0CeFVyUfuuIZ3NuTJlPvvg2U2BWc5MTsb2CpApOk4eTw95IsFOgCx3T9BFxbrY/22gq01CQEffF5Sns6vYZidwYOIFd71F55PMF2hIB8rVZeSQceb7zc2H48q7wLPwjXFlvqE/RCtDdgy6bHP1SjxDoN088HC+PmJXZyW9KZyV+L1t7ziErPNInGKDsAHW2T7xeWCfojVZELpPL70v05hcE2zxLDxsbe2d6HQzNKdME850VSx0sZa3fJ6eRqZFpRteam2Usfw6lLzWYz7rAr4Cb9GeXOIzntSOPMMz2Lm5nSd9Ag/TL8iqoYrpfNVH7Iu4V7F1bhsrv8SqZ0x9Tk8dp8d8etGkBXvH2Rv6UKwLO02SAJnOPpGMkiufyCX2MN5it8VdmHiVrhaJ0NabfNmkj5NV7MOAs9H5m2lIP83XIMQajaXJKltkF90xP2OKrLc/JFB4b/AUkF90Kh0E8pxBUMLvBHZy1VoLNhh/Bd9UDrCHvBDQiUq1TG8BIDQIm5yN72yMZP7gFW2WBUo2JQDseu7wM0yxU4YSA6fQZAq/DiUTOd/5E/hS2ut3+OckRORW9a0/aFe+d27nMUyR0711tiEc2raeEtQdK5N603WKXyt0eP5WnRN23YM5gWcOfrpCobBfVFB2DXpm80e72KmOU5n0lABBrRw8dJ8XZVfGLaEtUMGxvslZz1mo0ozwFQhrs7i9j3KVhXUem6AIR0Fuk7cK6BKHCacTYzsHFIOODk2Ht0xlTppMTxlqQ4G2HooEWk6hLQOL8hsVqJkvBGZlZ3G6tpWtrXFjTMbBiMuBuxykpOxHxem6IA1Hniyt+Ew4whg/cddFS7e29S0FAr+jiWAyBzJlKX9XNi+jZ1XlhqC+gFtkyYLANkdTvtvF82Vh5udQRDiX3DHSVg7iH44TTpvc8jrQVuV4BrqG0YefjEmAmnLUfrdVFilvY8eS0d4PC8bE+Mz3A4WxM8Tr9hDlklJpnzBKouWVn1E61yWOgDZDvmd9Za0adxivDB4Krb1jT7TZs5nv4r5lCnQb6CQ7sgwxpiGjMwxywINomQOzgZbunKzBs2RytPnLxqPsc+sbLevwLoNt3d7ZJFdU4Vmv3PpFwJMckHDRgmEhO1GAOOZvX2RjPGNqm0TZoZJEKOAM4OA5/IVPyHuB2WjRxUDmMESjoSD4VJq07cTm+IxNz0GPeA76MoDIhZBrrbHV3gMazwiQqVp4ZaMeBN0EyckqBpaKJ8+MdRljlG+iSZuUtS3P9pKxoeOEDjJFVusEoYpiDF17nxl4hIx11pGRbQWBxAjOLe06rc9Q20fvJoujmtYYBFoY1njMOnPsWU/63FA2/lRey3OzRhFkzlUDWS5xIphvdihn2c2pKtjFaaiFYMh5578zJzLL27OPbENXlS9j59N7jTdVP+b9quWfZ7bP6aFXjF3j/E573nlJLrQVohHooge1VaeZvuSJrH970Dtzq0bnvLlyVgfv5HONXhr0FMQ2b/qJNoXoFue7JEr7RbIqW8G4Wieysx8PSl7jFIt7OtfZDpk37De6VdtyehcbI3iEjSE4Yy72aKbJqnHEsySc0ee2Cebmfe88Z6+0Yxqr97XPYQ9xjkbnptjXeFxQKXcwaWU9/kITVS6CT3jCWpErmR99j65i/SJYnwPDU/i15YMe89l0Jy4IQuMJfCmYHJU+YX8JdLAlc1IIkPVkJZlqj69KgG3niQda53bIZ4GbjF7P6SmTxo6j91xWgQ9EYnLu8CEYhG/Yt+wf1d2SjiVROTftK50uJHvbjz4TSQVo4yzAvz6zqrpuCPFZvCjBJRBJ56ueMYUmU3THwFRZH3IyOnuRl3RegT5yML8vn8f2E/3rCU94wjU6EeBJwdqAs0RFHVnSFikItq8KUrtSSDISv1C20fE3Xaatwt+k229z7qBv+Laiu8pYOyU/dwxNpvJrmwRENyDLrSU5iqbt9TvmQ55IAhhKvBnD9wL+5HQ8a6ycbjEnG3Afz5iSzD5FJvU4d6b4tfL/6z42ZQ/OyU9XKBT2hwrKboEx2fzZGJ/iBPa79sAjzDnbI3gYGX6cfQSuu3RypcSQA6L9mSxk73ZAtA4m7XWGFACZnoS7wG2b6bvufYzWyBxsEe8RpIvALCOmpfM2wZRNioTDp1UkdqFtzvJy0Ee1KCVVkLIdp0xPRocDNmjSrgOackpRJgWNvJMhEocjRVCWJUXCe4YcuBkCLQ5pz8vBVkqtsbaOCmMUcGVI5lY/jC5rIYAjAC8DmLHVBnWH1oZyjjZabwtwZ0RgVsVsrv7JzzF2Sn/QDDI/mqOArz3Z0jNnKcpE5gSxBmGkARriefwRGXV5DtmpNnYs5h1rJJGBAz0/I7L9KYsB9Dbe9nMBz7O21gEf5z2F/2TPRWZeIBsoAuAMxpBt+My6Mo45FCiJFD4JGwzdVa2zgsYSPDjYIzs2j5khh5fzHRXrsnCB07INzOIRCQ4trwSNGePWJ99bbBzmxvFnXUKZDbRG3ybEZ8mo3FZJ5bKqILxsriquWlCK0QgftYZar3th0N/7tWP3N8eIbHwGrvFyEPiuYC2nuTY3Q3cQ76KQr6IJPkITZ8QhnxFrs80ztnmOPWd/cRwIANp/kYzjzOBME3DymZxkkdfJuaTVJ0NIsk68N94leMFJwSHtPfk878mvaMLZPZZne8vYMc8JunoOxyfZOYauMHU+/o754AOOm5Cxzm4ylnMnnmfv+ZnzfKg9GnDckfW+I0hARnNcSpCikwwFjfL+ncJrLcj5dUFm3yG76W/ZQZD3AYPfvMlxgVBOLWefdzsjzKl1pnguxxunhLv0psynB89GEsGYe7/bSr2xekUveZKvUDAvDm3yyxpHW+yA5ER81wbAWplkL9NlrWWsfbyLvYHn85244L1oah2cTxIV4g5WehN+0/ITBCjpwdaOzrqqu4j9R4dQrbDp2pPWTuFwXdfyeBdnJac/e4mDblO1bh4HO4WelquK1gWVV7XhjKDfFL0vJ986F8haVaU5iAmCl+xjTvtMp1bWowW9hH2Bzs5Lybr043b8xtPqnlP4FXrMJzuTN92J62+BJsm05I050tHDzozkVPJcwhyZyHGc32d90AI/DwUc6Mdkp6BwVF9CVB3F/Yu+Yy+1d75OfU4PmdQmNI8ZRy+abLPXBAPJGQnQznjv8+9orcoukZBBhuMVwYSo4A8InpFT+HnI39JWgW2CeUSgWGAjJ/x6zhSaZEzRHQNTZH0r79m+kiIkedjLkfyS36d7Eh9HwF6S4Bydw9CEzWQ/50A72UU+OatzN4dI6Ih1YwNGUJJuw6+GN3Ilp+fi+Xz/6bbY9tzRHnWMnTKEMTTJlX5j+NU6Zz8ZfwCdgh4YAXsFL3iFbeMc8RzyNV+/00OekNPBd2PldNBkLjbgadnW2/q4I4g6VU730IWn+rUC7KNd9+Ac/XSFQmH/qKDsAPJhNzWbf1WbxG0OPAdFdvSrYApliCCW0RvBwxDmWuBRbHOl4aas8IDvOTA9M4JGGVk4q2gTZGNUb8JQoHodXXLFLOWZQROHcabVNlilSHBwZIf0rrT1Jw4/ykEEMB2yFFTZmRGYzRjKeg36CIhytEZrn8hq8kdLC98zFkrxqvstOCcEc/2Jdj8O37i/wFw9n9KLtrnqWDUdo9D7KJmcBipt0Z4TiZM1AtgMEFUknGqbAvKAr9w9y9hqM8KMVeCIct3yqvlyhrhDNMYZnzHvfI9e6+ik6HHShMLFEWjOFLXIVg0w+owhK4Ke4xmMKfw6dizow0CgHFI6vb/NKgXJBxRF68wA9f+5MhzwKR6L5xsvQ4bSGvB760sJXNUem6LHMS4onu9c44jMCl+L1jDnHCcfjVMglDJtfkP7m+zM38+Bag5LMqdNVIi7VT2TswMPUqRzICZgDPYJnpShngOzAgD4WSsxz4u1acEZ17ZUH0Lb4i0UfkY9fvMcgQvjyLDH7C17LMaxDlPa/0T7eUaO88Pa2g+MWrLN87S+kWXJgFlllI+hSYwtaDKXZ/SYD4eAdnNkOccA+Y9+jK1oYWpPMZ44o9ZVNZMDnFnkrv0f74l9YczRrnxo/42dS7SzD5qM5dmpMjaeIfjhPJn6nJDVY+k6dT7hYDAO565gJZmfkx444chY+zLOTnwzVA0TwVZnMKch2ebZOmkINhgfnWFdpeZUXss6An10U5AZOFzCecpZpeon4GyR8Y12vhdXJ/g+eSSDHa/RF6JzQtarQwc/1BpHoCx4bWhvrUI4GfNnp+g4U9c4O8o5NDnGIwhpDenI1rG9s51TaZVuIVEvnJb4UpCKY7IFuWm983fpAOHYlRwZTmx6J/ka/85BdXZCXuN2vekkuhrEvelDXUpiLQJ41vq2XTrGOCudw3QRezdX82yTMGu+5h1OMmN3tqxKyBp6Ti+9LxJe8j7n4JMkYa3aRDnzjUSDTFeOSetp76h250gMsA3ordG1qT3vspN/Cr8GbafOx72wMZ91d+KSMbEeZAr5HXZbzJHtJpgQ1dz4h83gveRe6zDOcjmA1+m4ZAAbFg9H8M94JJP5fW7nmMfQ8zk9dJwe45jyjF2CoGwzZz2/CFsDH8caS+SmD3ge/YosIvtaupNTN7jBDZZ+hyHe3wX2gLML//Gh5ATunjTpYe+MlfVZtimeCLuaXsVf593RKhjIAHSXkN4mvsV+J6PRLSd3ZNlhn5JP9JRI8PU+cxRYp9cZf5xj2oXS0dhcnmM++F2wNq6WCvRMtrS2U+2UwBia9ORXME6BOWNofUj0NslfgvCSfPg/hhI8xvB9JDTluU6V03OwAXvY1saS7cgp/Gpf9ji7etB1il8rA6/sugfn5qcrFAqnhwrKrjl0xmTzQ2Tzh6Ns1wNPRq8AYByaBDJFnxCmsITjKKo6KSGcRK2ismtmJQjYyfyiRKqoWgXBTIptdnAMZfi3GdIOo20qC/KBzRAecnSNUSTQloMwFAmGwq60zRlXDkXZ0AKgkblnzH7mD8XAswREKSIBh6IWFBEI8XwGfrxfVp7gCgeuA5hiwVBr59MqnAJ0nHtxh4FMcgcsw0RgFl8K9uUKhbaaVzak7C5GjYxTFYaCswwINArjhRKtBV3bhiQjO/0o7L7vHVnBCEdp/ixHSRhN7qA1JnuizU6WHZaz3XPFFOO2dar5rDbS2p3lCmnZtAzpuGfCPDhPBNet/5SxmBd5gY757qE2c5gDmjEi8ObeudYosSaMe3KHjGHw4huV19aaUqvqUZss4151BxGexQPG4ln5/mPAhwIkDOxo9zsE86PsCRZEQoM9QCbi19jn7d40n20D1UAG+wyjN6rUs+NalnUY3n4nC50CavzBZ2jljgwO0lVBMga//YEXNyE7PIPO5Imxxp4mnzjssqNCcgNDIWTQNtim/U+u2MgtzxmJ+JVswOPoQdHHxwwfn4/2jkNdH8bQBHLm6RyeMfY5kkja53Ds22sZkrdUHduH4ZQlM4Yc4+SJrNhYf8k7nNPORok48fl13SGm0CQH36fw7FQZC2SsJAHzmPocBrufj6Vrr/mQvfjDWYeWkh7a+3dlR9uXnPMRwIJMX58xp3D+6Fgik5nzMSrt8AA9I+bXYiqv5Z+ToZuCzDnAged83vrSR7zb2P1b8I0DmqOSsyUqYoLezjeVLhLQ8jimzqfHGnM6WmM6sPWg15gfx8rQOmZ6xDjoQBw1U/SKnvLE+UnHa9sjO0tk6bfXVeR55vGQjXRL9DI3Zz3HD11jqJIq0DrIyVtV1sYl8TO3ffRM9MrnXEtfaNsDe5azjr6UnYht95acONorEYjjjEN56GoTc82V5u04gh/ZD2jL7tJKsW172dIi6wXOsSl6n2fQ0YY6vNj3kr/yNSSSVOlqghQB+ougpXVz3sQ92Pgrg47C6c32oq8N7aUp/NprPn4X89n2Tty2KjUnvrAR6HbkSVxbwtZiO1p3crblwczvgtTs9khgJp+0EM+VeD7vHYIWq9DjOT1kUo9xTHkGv8O2XRAy7PWQPXiQTCTbyR3yHU3Y1s6hoXuKJSqxtfNajxkL/sR39lG2JafQJK/PWN1xyEcwRtZn+gje2LO+F8m4gqHorCov7MNcgRnPz+Pxc3tYcgYIrDrL0BA/R5IY/uYfiu+am/NC8UZ0esjnmi5Y5kUWSMCyn3Ons1bG7XruhJ2Sz52pdsoUmvTk14BgljMs0ySPl6y05vTUoUDbWL5v/VtT5fQcbMDetvVUPQmv9Di7etF1jF9LW/YWU/bgHPx0hULhdFFB2ZTBm424qdn8lMgxB55ncfhwVFEwHCQCbbJqPJOCSpByaIGgDIVJYLFtuTTWqOAsYnzGwTZ0yBoL50CuBo3DhCHdtpBSCUcppRxvmw3YHgpTFQm0VSGhf/9U2oaThKNFwL4NiIezVOaewzBn/jmAL7nkkmXgyPgjE1QSAOcMpRIPRBBWJriDGb/lrM+8Lhy2xhlKjfH6TrSoCPg9R1+upIa8Jr5DQaKE+2xUUDMoOEoFnYeUmvwzyhT+EwjLl85TXBlgbWA2GzdxB0pUoeNHiRB3u9vdrlE14k5dSlo7Fs6s7HAJRDWzYDIHrHFQTMyXE4exlu+FsV72/pSxxL/xCKOR0aEVbfBLVlIZbtaYo7o1Siipvq9ihyPfcyhjeAU/GZ8AufZYHFXxvTazWbCfAx39GbICBgyp7EiK5AXPy98dkgMMcgFkzqlAZOKRjVoFDWHbQHUYaxxiWkCFER3zI7PJSvs2nJeewZkv0GitjIGjzhqtMj7j577nPevu4s3VSowAwU00xxP2OSMgOgiQKzIl8RcHPmejoPlQAsu2gdlt7nTJa2UvCu5wULRV7eQ3w2DIYTKGJhA0yQ77Qz9jzHxk5HIQCPrn53AG4/m2ZawgWnQ2yDpBu28kO8kCdg7FM51H3uG8iDtn1hm3Y2niTIm5+O5Ynp0qYwOCb/bu1OdEq9mxdJ06n5yAQ7aS1eQbHcG5LFmmbYMqiNcmNbXvlrhCZ2nlc3RR4aAg51bJkR68BpLXtgky05dyazvPJaM5IskfVXHZ0eI8QlcyvM2Aj5bz+Z63KfPpwbOei/Yc72Q+nZbT2T4y/3y32FA3hbAPtJaXfDVWr+i5xlHRR27h0xZsCNXRxuG5q0Bvtl7el4Oexs5hPVRJ1SJXRUmuUkHBOZevZqAPcGq1un+en84QPsORK/ARekXIaPoJXdj64s2czBeJo2OdlW2AOWAfC7AHcis9AcBMs7ajkMRMa+nn9qJx47ehoE7WT+I5nINj9b7YN+01PIKMbbcbwST73H62j9rEz9y9hGOQvOBwdM5k3S86DtF1e/Nrj/kEfcxn2ztx7dFIsBEgiDMbL0ZyN13VWcvmyA5/d5Y6p9kIq0BeRbtcc1MFHNWGgoSRZJ1tnH09p8e502McY58RHXpae2Qd3Vrbwt5Vyc2+kUyJN3J7V4k8ZGJUTA09y99jxhLg4wj6x/fH0iSv1RTdsYesz6Dn88PQSfKVSzkwK7hB/rUB2SFIOrOf0YRu5UwnP/lr+HJaegSNwn4nW8KHlKE7m8CN3wlqDnVGGePbCjsl07OHnTKWJmH/9+JXEPx3TkhMb8dr3tZ5KOCXMYbv9yGnD20D9rSt8W6PoG6vs2sMXXv4tWIPtjy4yx7MiSZz8dMVCoXTRQVlT06WgTBOtF7Z/IGxB55KVU50VWSEaJuBw6lFmIfBLsAj6JkPhCmKfEZWGAWE4l4jhwODgpMtV00Q/pTooAlQ2uNuQwcmx/DQHYbraDL08zGKhCwqjjfK01jaAj7hZAmDyqHLmeZ5+W4Fc8UnQcdYD04HDgkHuc9khZpzwLMj80xgVLW0LPv2voD4t0NelceQUoMXhrLqV/ErCP7aAyplZbv6bGQitp9t4aD3XYq8drLoGRmOgK85mylibctUCgjlX8Aptw/TfiQy6wUk/cn3JsdcZIR5X9tWWyBUpnLQjYMcH/gsx7Y1DsRnpoylpQ/+EEClZHHQoEFbLSzbDf+0gcfYe/g3INDNMYWHh9pk53kEGAo+n1vo4RtOyTbDv3UMDP08gN/NKWfyUaQFiGWOttglUI0G1obh1xrTjEJOM47rcH5Ey26fpWjG3V25ndHQ+sS/KdeCD4yxIRq2FSgcnpRi7+eQIDc4A50LHAo+r9UnfmfMaku9z7tBV43VOlPyyetV/LKqDdAuNAknsMScQz4j1iaeMeY56B1j4XgNkKX4UXZ6NrbwM+dblver1pcjniMJ72Tj0T4kk9qgV09+RROycCzP9pKxU56Tk3im0LX3meGsEKTjkMyym3wUkGmznYcy+vPP6UnOFk5FOqef+6ygk3XJCTyr7sscQ5PMN3ScXYLMQ7qBCqEITORzLAdmOVLsoQC9xz5rOygcYo2D7gGVPxIzY7wCcRw+MtfNYxUtyRNOEPrZGL2ihzwZWh8BMu8mA+Kz+XPOUjroqi4TklbpEW07tKxD+J2xcFQF8vOcX/TG6L4j0ZATnV4b+4b9wb7gDG6D3gFJNAKrkgpDhnH6R7CUQ5wtIsiGJ3Mba98zzh5JL/S5nFBAJki2zA577xbcyPuGvBCcyFeFeGZODKWrCXBzAOdWvS2vmQ/de6zeZwzWLCo6cnIluy4HQdA79o3A5FCQ2lzIsaj8Zpuwd62R8eU1ZRsM6WpT+LXHfLKcHXMnLj2XPLd2HK3O5HwuGLvnZIe/7iYCEquqDUH1vyRYZzrbPN9fyXYUaM6tDlfJk12fsyq4tYtM2tc4xtCk5Tf3CAs4DHWPaJG/67nsPHqWdw8lnqKFsyCSc9pnjR3LUPJp/P8YmmSM1R3z3p4i6zOMzT7RESzPO3+ef88+YwtuCsiCwDn6SHpx/od8tcfty5DpQ7yiiwY9SZAKnTZhlb6+y7ljHHHu5ETdXeyUTdiWJi3P7sqvGe1ndYCj77b31pK7fA10kFXfHcP3zoKpcnpuNmBv23osv7YJ073OrjF0HZrjrn6tLAvYM1P24Fz8dIVC4fRRQdn/Hz2y+acemgR7HHgMbtm+lN9oextOfN8n0DnG2uy4oZbFuxgVrTIRn0UfDgVKdjiSOA9Uuchmpoian2x/CnkcNLIeOaHMhyEuSMdR0DonW7RZ73Hf1hi6grY2oUgY91jaBigIjG8tJGRnMejNW3WstkTt3VH5+/G356Nd3F0b79NOjfLgzjh04hQQeMrZhCoAsgOBs8GYKTetUsPZJ7hKYdyEoUAOhShX2K3jH2uiylblB1gbBopnZVBm2yx3ioqMsFD4OXNU3VBsODK8l7MDL3NQtYFpwSlBOg63PA9OUsp1KO3xO1nr9rX1zpmNfj9lLJk+vkM2hPHpuwLelCPvjaA0/o57L7IDGA+oHLbeueIY/JvTViu7ofaGeRwMZQavvSe7LiMUPpXNraPdszLfCxqTAeRjjFGQj6M+ZzjHXNdl8G0TqAbdCdrKbt+Juzq8h9OfcsnBkQ0On8f3q4IfEnDifsSAdUGPdUkLaE+e+Nv+DWc/54qfR4V60M46c0CuGkevNomb9nPcMSvgsQpjaZLbLc7lGWPnE9WgnkPGk8cM84AgLae+xADJOJwxnMT57sS2dVYLYyKr6BXxWQGoSMwYQg+a2E9jebaXjKVD9HjOkDNzF7r2PDPsX9WPZGxbKRGBWed9vl+1XSefi3M6B2bjnvqQ8/iJXjRUbdGL16YEmYd0BGOXrc05ms+rCPxKRMvJW2io6qRNNjnEGtPNctCMw1nQNLdrjmptzuWwEzId7EEBV/bCWB1n6hrn8Zg3J1rwm/dzsFujcDJu4yyNZ0kkHdqP5Eg4bcmcobFw7nNckbP2UOhL9Flylp7vb3KL829V20eyGL9GRYR1Y3tw7KtsjgChNbYPW5soHF5TnZUCemRyJO1aYw4w/O0KHHPU8UJAL99vDGypoCNdn06jyqPt1oOHvIN9l+eQ7UjvHqv3kTt0Sw7O3L6bExpN4u7AzJtsZ78jL+hymT5o4nf2jeQMZ2ecMWiBJuy0tsVvzGsqv/aYT8aYO3EzD1kT8mCopTWHPxlEJ27bMGde8Q5rZ946GrH97KFsfxoTnZ1DN9Mn778pz+kpk8aOo/dcwM/JD1WB9in7Zp0PpdW32CSCDPgtdMXgocwX9p/xtXrd1LHkzgxk6xSaxLPG6o45MaOXrAfviEBhuwbGEOczOzN3wNoGcR1VPJfPyH5sk2mdI+iR/UXsY34P3dcC/CihT2wKpGx77vh5yHrJSGPtlHU257Y06bV3fBaPtmC7kKvs/LCV6RV8Y/xJQ8/vIQvGyul2zeZkA459RvhR245cY3zcfO095PRYuvbya+Xn+M6uezAXYMzBT1coFA6HCspOzOYn6Nps/jEHnr9bZzLjXKCP0RkHfnxeJo0M63WYohg5OEMxcjgICskYo2gS9tHDnqIiMCTrUUBSZmMovRQnRnPOjAcOknVZhEOODo6wqYpEvpdkF9oO0UpAVJWFuQtMUzAoB34uiCr43GLoOXF3bQRmw2iTbedw17KlrZagfBu7TLOoOJblz3nTKjWeZ704g7c9eHcJ5LStQdHVPgF8nAPEKm7zPcWt0skxSXlhSHGOcWAJ8Ho/OrQtQPL74//tTfzFmAPOHk6vcLi0xhAeN15rlqs8xo4lrzEnoLH4vHZOYchSgihLZI2xcVJzaLYBXe+0pvauQH92ygfQ1pjaPZYhi9ge4IgyHu9s24sL/npOqwhmGHO0dMSv5uVnjGo/F8QeutuiNWK3DVRzpmYnb36G/YFuGWSxCngtNnPGcP5+foZ1RQ/3ANm/cc8g2pBb8e68HzgFydFoLUjuWzvGatwblO+l9tmcwds+z//3aP+z7Xc4cAU6cuXHVJq07RYP+Yy8NlPmE8/h4OcYZ9wzlMjczIOCPWSuszHf45yfJ7PbZ4buVPRsY2N0tuvZyoOxc2GgZZpM4dkpMpYhGmPo8ZwpdA30mk+A3LEWHBStriJYo5IydxEhs+IskVhhLfCUQGJ+pyC2NVMRnyvjYg6BHjQJ9Agyt+BMEGDmkIhASkAyWp6LIFRUVx5yjelnOXBG17JG5Gjsm4B9wxmEPhD7l2xnV0gCnKLjTFnj/G86gbUVMKD7xN2cAoecQq4maTPy160vPhY4jOs1Mv3tA/ZU7o6Tf6+zCt2B7oHW9ojAXegH5Bv5y/EuYL0qUK1tLb1YUDzaxIbjXjBOIN3ea9sLe148c2qSFp3XGWuv0qnYOdZWAoM1j4pqtoOzRKAyXzWBn+h8OdjvM/QDtMmV1aDCgZMuw1joQKo/p+p9dH5BR+eb59g3zrkYXz4XAs4m/GO9IllMEEYyQrTqkyRq/8R42AaSNH3PWrf0ncKv+5jPmDtxM/9YR1fneC67ObqX5M9IPLQPwlY2tkwTnbDY3ey9CJZ4H9lAzrBHdfcylpwo3fM5PWXS2HFkmvWYSwv6uf3qXKejDvlQ8vlBf/I+fCyZ2R/8ih846Ntkb8/RvnybqsVtxxLjiVb5ZPMYmrSVb1PtnSmyflUyuMQI53GMNd7Hn9fet7iq4nYV2KZkehQbtPq9+ZBrEvwFh/kJw37lOyHjyAnr5VzaV6CNz2qsnbJrQGYTTcbuHch7ZwieQd5LdqLLmUvuopXXd6wsyM8YK6dbHNoG7G1bT/VxC5b2kNM97J0pfq0Muu8UX8Ec/HSFQuGwqKBsp2z+aK0w5sBziMWBJ3CYDwyOBoa3YGeMh1JEwFNGt8EUxYixQPF2SHJ0cPBShihkIdi1rfH/lPF4jjk4tAU3w/kWyg5nQe5tn5HHlB0dPZQR79+Vtnk8HK4Cp8YV97JyMrZOSc4fdMvISgFFAr3i7jXvdIBHYDaUekYF52BbJcixo3oLPYyTYyICotZNRhZeFQRsK5fHBGaHAjmQM8fDWUQpcdeGw59zKTstVYJa+2zomVs4IrUdoWBbEw5MDl9KCCcox+UqRT2P1/PMm8OYY4pzPOiT56RVSiRScHJzFMt21Opo6lhCCeOcxXcSF2SU+jf6AMPc/2uxxnBsDQJj8/PgLWuLrpJCssMRsvHaztO+ZTBGZh0e5tinsLXOfeNc1XZHRwC8paUU/vM355a9Qkm0ruRmBENXPWeXQLUq7VVGLGWecpnvLwTy0zjbJIx2THiQkxjfcthLXFHBYr+gtfHF/TEBa8FAk4QR6+856EkuUsQzv6MvntqUAT+2FTunxjZtktrv5nWeShMgFziN0eSQz8AT8Yyx80HDeA6ZzAlsv0UVnOrsbGw592UJSzYZugsp/i3ANHSnogx+Y8KznAgZPdbGMznlstE6lmd7ydj47K7P8bP8HA7yMXTtMR96R4zDu3IXCq34OOoFD/I9he2dWSpAL7roouWZH2cgvYIcFRDMARjJXqoBzIcu185hKq8NPWtMkHkbWEOJZgKzQ624Mt9PmU8PnjU/8l774wz6ojXiIMx3U3omB12uxKMX+5n1HqNXTF3j9vtsFk56fEq2xX2HoVcIYtI1PD/0oaEzJtpVxnp5n+Sx3BqWLisp0Fk1xF8qrZ2p0SUEtJdDI1XM4axvMeRcp5OoeqR35tbisS6u0yAn81r2cHhmZ6WxC7yQyQH8Yf3p6m0iQp4PnTnfeZzfQ7bTs9gV6B4ywT7SSSU+j15sq2gxOlXvA45oQVSOcHwT+ybrZvTAbPPY29aQjPZs+mEE7NEJ70fnlwhSsVPNpdX5pvBrr/lw7MZ8xtyJm8fA2RxdjuJznLRD10roBDPE6/RxugnejGs/As5zYzI3gcB8dUf7rLHPaddoqpzuMZ9eNMmIdbOv8J3EgNaHks+Y8DeQ//S14G08xib07nytFBsqd5tYF5jdZSzgd846Ot4YmrB3yOCogp1q70yR9Xn/0JH4Rehcfs7X4Rnke9iD9qYKSmON70pe4fPZBeQnWUrnaq8VosuxVSXZCLyTcQJNzvnw4dDVnUk6YWXaTj13ss/Q2TrGTjGPHjSJZ/XgV/MZ0oEyvbxf0psgVq4EzGMYKwuyDJ8ip3vp5XOxz/kb4xlT9aSwq8fIpB503YdfS9LlrnvQXIJn5+CnKxQKh0cFZSdm81PAIpulhxNYBpEgoQy8ENgOPQ57SjBBrWpV1ta6DLX8/DGKEUcCRcShyJgI+CyFSLaP+UVFR4BibOyZXoEYLxrklk/QZoBHdSsDvoci4dCcQtu4J9UzOABkzuWWvJQL9xZwQPl+PF9Gk+BqgHKghYSAE8dgzjKlXFNEBFxaZaU9PCn95uTz7mQKxwLHB9rI3vQ7hskqYyDWf9dADsgIlf0OHP4cigxQSomgNOece7wCwUscU20lrszbcLBwvHBwyMSTPR/OGjSNgOam8aM9PuE0VZXS3lsbd5Dmigl73nymjCVX2XKWBe8zQqPilRM+Wuu1+zboi+c5g2Ud5v3FCW5Ol1xyyaBzr+URvKCCNqoKAoKVggYUvrblztBzzAOftkFOsDftIc5uay5w0DNQnatYMjgMGEiceHHPNXB62w/kizGpgOD8y/OUVGPveTcHKqc5PvJZWc3uCqTYarselR2ALxgj9j5HeiCchLn63/4la/xZlfzS675UtNimajbLejTJd6uMoUnQlbGFNw71jHgOIz14dOxzwFjsG3dKZ+d6tBZlAIaztUVeBw5c51bIH8YjJ1k2HskV8tMaxpr34leQdSxwJOFnLM/2krGMy6hM3PU5ubqEs0TgbFe69ppP7CFnhvWgUznTfTdku/ORfHPmta3YIpDlzqPInHaWR7CFHqHqwvMY8tFpQNs2DqGhyquxvDZEEw7NMUHmXYAX6F2cBBFI2dd8xvIsXVhANjulIRx15hDPon9GdrqKmDwePw+Hza56RS+axP/jMXpz3HvFgUY3iYBZPFugS3Bv1drSKawfXVjwyrjooCpC8bTKVN9Hn1xl3J5/nJnkab4ewzsFdt2ryskXuu26wGHo22wEgQE6aJZ3QRtdZnomJIXtxl5CczqQ6sl8fQiwQQQenBt0lBY+LyCbA/yQ95v2l84ADjbOULYI3mvPfo65sXpfpiv+jAQF6+OdaBK8Et9xBtGJ2gpktLTeeIk+a02dT7m6Dr+xrdp73uJZU/m1x3ziGeYz5k7ctvuNfa66KiqE6Ph+5o/xsZXIxbhaJ8aVwU6N5PAcFMy0d45wTOdE6RZjnpPXeaqc7jmfXjTZ5EMhk8j0VkcKvVywyj7DW2yZOP+dG3RUupikU/qBc2Hbez23HQvEWCT/jKWJ8wpvT9Ede8j6fGZIOBeAldSBxpIivI+vx/f5VchHiei5itNey8Hwlp7rEHIs00YwkH+j7Yhm7fmJnBnRGSK/M2zaXueOhL4xdooxkF09aTKWXz0n+LXtPJOxzs/ZQz5muTZFTvfQ2XrYgL1sa2OKZ/RImB4rp3vaBz39WnSCsXtwjn66QqFwOFRQdkQ2P1ACezlOHXgMbIE0B5rAJucQQy8cVpQVQR3OP4HgtnqypyKfFSOOQ5l+LeLSdIdyBFQ5lmQgywpvldWsUDk4tY2Kn6NNtGOgSFC8ZWFxUEylaygjU2jrMKNohzOFA8XBFhliQTtGFidUKLkCLQJHqhspGRxuMkVldhqX+0Y4/aI1IMMGXY0j3x8lCC5gy6FEUYmMUgqJQ9hBy3iiZIMgFfqoxl2l1IwJ5LSBdZnmnHJom4OEcRetvWMNOVRWtSFhqPo5x127z7yLIswZbL3WOVwEQv2JrDLvicoY+ziUN5XbnKY5M7LHWDIo7JS0cCIxvPGMCmnvxn/hZBoC55F9RaFrq2LxJwVYoGWoKiBgvhJL7I327l6QHYtfyQK8uQro6Rn+rKowCSVZ9h3H41Dr4DGBau8IOjOCOQE4fT3L5wQyyAbOSoEaxj6nAPnC8S3RgqIsQxAvCmigrb1MYbbvOBzIXt8PcLgxIuI+uAiKAL6wR80l380Rlb1kFPkVzvrcdjyj132pWhvi8TZwMIR4Dr6RfDCFJp7hO4d+Blj3qWsca4RGcac3Gc8ozwhjC28xyFetk2eSNQJuElGiIpzcl0HL0BKYwTdkaHzX+HvMJcunKTzbS8bm8ez6nHCWeA5H2Bi6DgUyp54ZnDFo7nxWoSExyfeiWsPa+S4Zl8+T3F6PDiORS2Y4B1vcvakaRCcA8pRjwVw4g4b0vrG81l49AOi7a5C55bdt4Tn0mlbHmDqfHmtMh1FhHu/OTlfnULxLYB6dyAu0yRWa8ZmxesVUmkhMIisy6I4y5Y1bYlQbIFNV0QbI2goFZ3G0w2QbGLd1DCe0M8pY2Q7sgeDVIX0TbTj12vbYxml96Aho1+oFAevk/Hd2ht6h6ty4OOfbwGzYGLktXA8bI6BCDm3YN7kFMZDhdD9VZhnOcs/PFcbgfLHWkQQQ533wWu5cEzSeovdlGtNfnUN4I+wKnxfItE8ikGkced+Q1UNOfbwoQMRxmtfEWtk/1qQnv/aaj79jPmPuxIX4vvOCLcCZ3SbdRlIG3hF0ss9X2Wf2Ged3mywNkpfMa5sklTHPyf+eKqd7zqcXTbbxoVhrPJLtHLYInZCtb4+7a5IcJIPo9KGvGSeZIQEfzbap1h07FkmbY2iS981Y3XFoPmNkfYbkH74GfOY9zhzB3Ogm5W9yxF7396pzR+cvNMqFCZtA/rAz4rP2aHQtacdrTSTVOZtyNzHnZS+fIXtPEGeMnQLtmMfQJL9rDL/GGBQhGCc/XOa/se1Up8qCKXJ6LjZgD9vaHsoFJT30pLFr09M+6OXXmuIrmKufrlAoHBYVlN0xmx/8fy8ncCi+HHo5S16FBOUlZ7QwHB2GUxSnTYp8m6lN8aMwm0s2Ns2F00XwiFMkFBMBQcFGh3eulMxj1TJFmzgQRJFF7fuhSHCYyfaeStextI0gTDxHNZ7sLqA4Mh4iE56SofqHweGOlfa+K0E0FbjuupTJ3TpkOLgcpBEIpwRy7IUjTBA2DlvKEGWfk5fiqA2GMQrWoqNDPd/btUqpGRPIgajkCcQdCZwp7T05FDqKGieMz6nuDAdo6zQxZjxGUbCe0dbjO7/zO5cOa+u+ztiTaY93OZIZaVHB7LMUNnvYH1ln4XDJbYimjGXVHqT8+K49wmjN1TicTJ7V0jeDM5xCaSxtG3U8I7lgXQUmyPC0BvZGOK7y5zgOZHKvkyOMSk40TqihezvyM80Zbw61s9w1UG3+IXOtr8/7Gz0p9ZGlzVC3vyQ3MPglQZgP44kMIisYwhwjHHB4Ff3au8LJFUkUGWSQcbX3bzDQOSoYZ9lR4fno7U+uxu91L0x7XyoZYHzGHe3zVyE/i7xEK0blGJpwjKDvFLr2fAb0ek6Aszfuqml/Zy0jOWJo70TrSEaitbKm9mC0+xSM53wSzCAH2iqyqXOhk7RVgGN4dqqM7f2cqXTtOR96jjOUjgK+I2DQnqmSq9B4KNHCM8gzz+BE8P0cmKVTCDY5O+kfQwkePWkyNsg8BW2m/BzWmLyns9C38nM53OkFcWde/E7ilD2ZA4Px+x46zhia0MfokbmFKuAtn2G7ONNz+0mJABxawdNDEDjknIszyPvJHTxBp4+AV+vMzFUoKhiiIsrPo71alnOeQ2cm7zjf2nbEsb7sMBXkkgTJ69CvnYcCs3T8HLzsbbsF8r/JVwEL+k57HUFuHxl8oaqYfpNbXhs7/SU6C2Q5il5+R2a0dO6h93GSG4/v5oBwDmTiY3NsA7IBAYyoSgV2pTE7M0O+sUXZj4K16CAxtze/TplPpvmYO3Ez8JqkDAm5EYz2XfxKlwiQ/3htXVtQ0A4Vr9Kf23Pefmjv9VyFsc/pKad7zWfMM8b4UMzRWRn7WFING4T/AB/FnpMYyv4l99EiElJXVfn3HEvw1K40sSen6o69ZT2esW+9JxI62Ej0pXyH+dBeaZOcnItkjvPKXNb50uL8dmbofqADQ25dy5YXnGOrtme2d+QEkx7nTk4O7mGnjKVJgP0+lKC3C7/StcgR8hTi5zpGse132RM95EkvOX1oG3CqbY2vpyZuw9D6TZH1vc6dsX6tofNrlz04dz9doVA4LCoou0M2f0ZPJzBBTCBHZnUcJA5DTqX2PiuYEpjdpMhnMPrNUxBBdRslmwFtbhQT7U8o0jlg51DVpocRnlsyhLLvYHUwc3IJDmRnFLoyzHs516fQNiqABZcFMhlZOVPbIYdmjIicLddWGHFyynaiTESrk1CwzZkzj0HfBjZjfWS8Uug5njjxKAEUR0oS5cb3HeoqazhvW6MqY0ogh7JDgTBX76CwcaBw3lKg4168rChwzjC6csUuekR7xOy0jDs7IghJMTffNtCdx0WxYwjLkqXUUZ4F6Dhigobm6jOe3Tpcpo4lO3e8P1cKoK81QTuwdxh29lFrYHFym0vOhvM5mfvWuK2YXcVr9h5HYMzJ/qW4CgRHNfOQYtg+J4NBzFjTfia36smIZwogcM4OKaDbBqrtL0ouWYDunOqRsYkmxhGtewF/UcbxQMxBogj5E3vY9wVRKK3BG61cIY9kxwa0lMFLFHyV/wyQWH8BFbxPNmZHoT2c5922X+51X6pkDYp126pmaG1bQ5rc870xNCE3BXPD4TqXZ4x9jn0Xz2nlJpmGD+37cCwN0TTvHeeM/RrZu5xHAukRrAteiAqbVS3AxtJE0o4AFH6awrO9ZOzU50TyzFS69jwzYp058IEDJ+sF5KUAYHue+05uCxz7mnzzjrinjV6V29bnsecEj1681iPIPAUxzrmssd/ZV3ReQVuQyEjniiBZW83BTrAn6WGcRVP1ih5r7OzHX+bBhmnvnaJzxnt8V2IfO2BV1ZYxoIFuL1nuoB2d1Dnp7I92f4G8LtFOXfCKTmGceB19BS/or/YRx70/aGb87IUMSZaSOcOJFRUL6B7g8JXYpnNGHkPvBJ5A3hPmEIHZtmU7ZBoLLhoHO0pgFi3wSNgsQ5Uexo6GbA961RS9r/23gDD7bdW7BRjwk0qUIdkYV7TgU/prJHBI/MX/UYUf1erxDGdsT37tNZ9d78QdGg9bwNx12BKYV+HDnhLoUmUTNkLGunkJcqMfJ/Yf/MEfXHg/XVoiwrbyeZfn7OPc6TmfKc9wrsV31lXo5TUht+w55709KImf3QGquskKMk4iiwCHtda1IWPoXWPGAuFPyPce70ITzn+VZlN1x96yHnzXeMl5MjrrW2xue5N/ZhuYvwpX8rG9yiuQ52TskRQv8B50BPOjc9sLmyqxe507U+yU3jRhj07hV+MV0Gf3hu5JvpKJQ/7IbTFWFkyR03OxAXvZ1mi4Dz1p17WZStf2WoWxfi3dCMOvNWYPZj/BHPx0eHtVoLhQKBwGFZQdkc0fGHPgCbq0zmTBLIdLzuj2Ls4NLWHC+FuHnop8+1nCPu7p4AjhMBBICOcIpTsCfJG57cCJwGyumAUHvAMs392aFZJeTvpdaSsLLJxlHAuUBhDAMF6Z0TmbHV0Y8u39uENKloAL+jl0o4VNfE4FrQqUFm32PeWfAuvQF/B0oKtK1grJHI2RY2zVod0jkDP0eY4nYxPEaoPzsTbWwffwGYMKP4XjOZ4nUMV45WhpL7cfclBwSAlg5SCWZ3FqowUnUKyDbEd0MZZQhMaOhcKT2zV7v8A0pR190SP2AQOUs001MwdhtCjMQVn7BO9KHmDkZZ7n8I/Whu042rXwHC3UVAX4TiRE4JcwjldVOGWeYRxpZ5QNEIpt3HvWtp8KUJY53NyxMTZQTfFHx6jYlzRhv4eMU6Uee5bizRme9xmnB2VT4kF7D4e9bf/Zs231MTpzOMddJ0DOaWHJgcDBylgj/xgp5ipDWgYjmreta3rfDYr2ed+S9fY8508LjpKh5IFofZzb0+9KE2uPB3JCx1yesctzomohnsMJ5UzhwI+WrSCYY03s39bYgrYSyvlDbjhfdE7IziMymxxvM4FXnddjaGKseJZzawzP9pCx8e8pz4mARDynF13HzCeqGjPoLc5zhro9lStIBARVf+XuHByeqmYkZ6lwozsErTgjwgElWYXeYxw5MAttu/qevDYmyDw1MLuvvTOFZ7OuH22OrRu5Hfs/v1MQ0rjpFc4e+03SEef2GB2nB02yriToy8ktUUNFZkD7OM4bMo+Dhn6Qg9NDzhrnrYRKegq+z4mI/t+ZTsfIV5dkHqGD+y49kc7r/daIrsQpFwE5f9AwHF+Cb6FzxJgkZamSBJ0mMl3QKmwh+miMIc+nl+22KTBLL1a50J5T7d7BP6qF0EeVSvBaljv4ifMv5iIp0njQcKze18IaG3NUq2WaWY+Qy2yJmEN2etLRONjpGHQ6diJHarQYdUeufSjJVWVHdJuJeU7h117zaTvo7HonbtjUGWSooAddUnKI89hc/dyatdf9bAP6HDrgGckj6IEfNtFk1+e0bbh7nju957PrM4yL7MFbcS6sQ8wDf8cdqlmPQhM8IbCZ7SR7l23ENln37DFjgXVXEW1LE0FS5+NY3XFfsj5kDJoKXLQV85Je6Mh0rF06xklmN5c2CJnfy4aj3wk+sk2jZXMOzFpbNq3g1KbA7K7nDjsl+7bwxRg7pSdN8hU6PfiVD8C55tyg//I15fUdi018P5QkMkZOz80G7Glb9/TF7iqTeuvCY/1aZFn2a43Zg3P20xUKhfmggrJbosehSaDGgUepkxkY7b4E9mQl5QowAtZBta7N7L4U+UAoLhxyMpMY1LIS4+ccA4JNlBb971VvRoB3VWDWoUUZX9eiaVdFQoZyKBIO7V1py1gQGBEQ4nDSrkZAKT8fjc3RgalykYOV4ZLHnw9NCkH+ne9y1jI8Yk7eS6lfZazl9WIUUEooiipQMyhCnAY5a681CHoFcgL5c9bCQW+dzY0BRZnjbI7qn6ikVRlgbSl0UckIeEimXNzVsg6MOMaez1q3lmbepz1srtTuMRbf8zNVnZwVKjM4fSiJHE4MNrxtPfEYxyt+wmuyCltDGF8J0lHuKJ2+5/l5v3BueaYWUnmOGeQKZ55sYbzJuPKcqLC1F+xTimzr3M/PigA7R1o41OLzxm6/2CPm2b6f4y0C3mMC1fangJJWcTEuGavoJmtVQDYroByAkidyRiYel9G9Sqm1p+1ZcisH1sMAzkq858d9HpR/nzc2VRPhdGeMM9Q57nMWfM82iXkfcw5wQnAioiFZ3FZtkdMMhHYfx709U2mS7+Ob2zO2eY49Zz8KckflHxnH4cQxwDDKZymHLtnve7ldJH5XaZfPZ2eegEtUPWbnAlkgAaG9S3gdxtAk7o3flWd7yFhoz51dnxN0zbTrQdcx88n7j5zJgUntNmWEx9UG4PcMbUlWmQ4hj/2OnHamGAu5jO+iS0Ak/fhsvle+J68N6bK7BpmnYl97ZyzPDumgfsbZFPfltdnxgulxf6B70T2bDkY+j9FxetNE1Ra915oaPydQrkCku/iM89JZvKrdPsTdeOQfOchp6UxvA7POl6EEOnqIQFy+okDClTOdfs4h3L4LnO/GndtGgqCAM5TOgF9zcqWfCdzlzi1DAZ1dbAxXrkiaGkoEapHfpXJC0GFVxRK9IJyXdHpnEb0rqjIBPfEyZ13LgwKCY/W+VUEuOqhzIpyiMXYOWo7IfJ1DfgYdmEzMa8EWJFc4Xl/5ylcOyp7glyn82ms+q6o5t7kTN88FtDInE/yOPDA+53kEqAP03wi2b4M8T89DF3Y2+3BT2+Ndn2PN9q3j9JjP2GcEL9C38WgbCBj6rGfiA471ofat+ImuH4FLiTna8wpirQtOjxkLCJZIzF4XENyWJj10x96yPubquehqfEAWki/8Kca27b28bRDS8/B3Kz/8zNnCbxOQnGYM5pEDs2SAZNqhxOmx544AIDslzh0J+GPslH3QxDnfm1/JaYFQMjm+M6aKbxu+z4lEU+T0XG3Ans/olTC9i0zqQdcefi17UMA4xkGf22UPzs1PB8bVdmwqFArzQAVlO2CbAy8EqgOP0sFpJ1hJEXGQMO7uc5/7LA1vmcIEvQPIgbdO2RyrGFFChhSjIQwZuzKDjdMBI+OGwSGLPqo1I1ASgdlb3/rW13CEbdPSaFtFwrNCkYhL4MfQlpJP4aZchyIeyhtllUOAYcFw4DygiK+6X9Q7BF0YDPm+FVn91olSYQwcurlieFPVKqOAUcQoaI2XQDuWfQRy8rsC1lm1DWVFIA7tOKTwhPeiSVTSqjqgVKAh5S0qR1Unm9emjFNgkOE5CuBQFS8FiCMlvjt1LPEcPI0HrK/gqWzgzEOUe3wriy3GJBuUE8g6B43tIXsl2r/IyMRfHIqMYA6uAD5uaRDjMg9B8DCCraXnhGMvHHkUPg7rVXueTBD0D4WcUwG9OGCjrbLxc4gxgoPW9pdg6pRANV7zDPzDCRCVBzIf8aBxqDYPxD04ZFjLy5uSTbzfnMiVoeBt23KY8z2CeAEGOWMuAszm19K1R7uqzM+yiMknv48qLXz4ile84sLnODmMl7yLn5Fl6NfeF74rTTZhLs/Y9Bz/dka4S1LnA58RTIm9hE85JXJmMNr7WV4PhhQ+ZhBlR20YWnHvcRhCUVmxa4XhtjSZyrNTZOymNmm7PKcXXXvNBxjZDHB6DLlOH+BsFTSQjOQcZ6gzqOkVQ5U5nGsCciplBT1lWwtYqKRr92dOfIN90GRKkHkq5rTG+Rkczf6Ec9UaRMWsPRhnKXrE/ZP0iji7pug4U2mS50GXEDAOJ5V1pN/hzZzc1erfre6IV42JPkce4hk04HSPZKshHT7zf7QWptO0XVo46zm56Mi5Io/u7wyT2DXk6OY8tR8F2PMdhOiigjaff+uwjY1BbxIwoNdkZ+W6/TDU9rGtOEI7iVuci5FAGnec4qXQ3+y/fNcp+nvWFL0vjw8tBZc46vyco9XZ8fCHP/zCfdISXZ0pbJahakP6LYd6y6exHz3P+Sn5cGjfTeHXXvPJz9j1Ttx2L+Nnuhr9zpnA9ow7rYNPrTWdmf031IJ9HTZ1w+r1nKkyqcc4tgkwbzOXoc/Ev+ng1hcf5s+3n3M22GMquXOSd34uvsBbEjrpCoIZuS3nKtrsMpb4bATJ8lh2pclU3THPax+yPr+DL0JAmA/F+WPvZf/JmMCsOZGv+T545zi7M3Sy1gczFJjl19v2/ducO3R98oUMpH+OtVO2xSaaeM8QTbbdO0P8Gu/0Hjyj1Tw+4Dtovzv071XYlu/Hyum52oD7esauPu5VCdPbrk1Puo71a8U47MEpvoK5+Omgpw1XKBT6o4KynbDtgddeVB5tDBihKhK0SqD0OgQcQK2yOdWoAE6AUIwYwesuVh+aAwiQUIoFZAVdKDOcXRx6HFEUyXBOCQiq/tACIwcmtlGwdlEkptLWeB2mnD2CzWEg5HH6mRZW/l7VqlHWGOemakGOAGMSfItMJmNDO85c1ZurnpPRGgVxxywHxLrP7jOQM3TQy3BT/Rdz4RyR5U+pRVMKRTg1jF3mrYw4jmlKMcU3nrfK4SJ7W/VJvAONOWDjvs08/zBg/REUnTqW+DsCs2hEgWrBaUvRD3Ac+iwHUYybY0hQl1LJ2HdXG6PFz/Goz3PcZUgMELTNYETJZKQ4q4Ju26vh+9xeLc8jIMBgHlGdxUgiIwSc0YFTOngtK+AtPXYNVPub45dzlexSjUVxtU6RhU5OkR3WBX/5jDUU0NjVmRWwfxn2AsBtRuIQjcxL9YaxqMJvadfSI9Cr/Y+MTTLFOsadfd4p0IPuHP3aH5Jdxhmyzd+qc3ObnSk0OSvPWPWc2M9haNtn+Ch3HuDMZWxx+OQs2CFnsjOJ09gZlasLOeKi1RkZHNV2u7YW3JUmY3l2qoyNv6c8Jzsrp9J16nxyAIUstffIKdWNcfY6OySkMNbtO44sZ39bhZLXhFzjaIh2xZK0zMMzh87ynGDSk9d6BJnHINP50Gvc/oyDjtPR/Dndwzln/QRm7T9/yAwOy0jYm6rjTKWJoHDbOQVP0sMj2BfBMXyrC4y13QS6B+cP3d35TR8xNmNW8SswS681r1UOpKiKIkd93/jbO2fDqaQrRns+RpIpx5ykTslbATot/iWr6bM+T+/aVS9YZ2P4fp6bvWIuQzzYotXn82fpAs5t5zlaZkRgFs9Yc7zmbKf35WeO1fta+4CuQT/B19bXOK0FW8j74+oaf4bkQDxP0ieHukS0lo54TwcQegp+bc+wKfzaez5j78QNPiHT2VzkEeBZVSt+HqDnC9pFYm/wWT4D8xm0azCi13PGyqR475Rx9JrLEFSot9VqfAJ4dyjpIEDOq4Qis9a935njPFDF5O915+cuY8lyJ7pYsdV70GSqvTNF1pNf6woKMsgO9pBzyRmdO3ztop/EZ/l9PCueY36SNdo7TVf5YKLKrWfiqLF5zhQ7Zche6UGTMXvH37ntcaYlHqN3CU45t1QjOteyvNyHLBgjp3vpbHkuZ8W2XsWvbTL8lLXpTdexfq1sy47Zg+Gna5N1DuWnm3IuFAqF00MFZTti1YG36aLy7GgI5TIb30PBurFGRQRkKUYONIFcAn7TPRT5GZRn/+ZMkK3jgMxOf8EV83SAhaJu7pSubRXWbRWJKbT13dZ5w9HGMcBxwLBv76XcdDcURYJjIrf68x2OFdmyAbSgVGzj3BlaA84hDsd8V26LKYEcRmXOat+EofGj7Zvf/OYlLfErpzZFJDst8RC+pcBwBLeK1TqHC2VIQFnQnRIksJczOzPd/Jk6lkDwsOdxJAn0C77lz8ny54DN7Zk4eDimtCOOrLj4W8Unx1M4emXdUvR8J8ZvnqqZOIa0cAsYP6WRstzet0NBUzlizpvAqYlX7TfKYxjOEikY0u4XikqDvDZjA9Wh1GoPk6tgyaYIzEYLcb/3/rjryDrumh3dgjNdEGLd3msdFcbKMG3vV4RVz5na/ocMRQ+VOsF35Jz9yyFjDrJK0Zczd9u2fmNpclaeseo58f+y3GXXcvq297ajvT1JbocBhN+jUiwDjzIeGUXZeLQWeNif3C1h28qPbebSg2d7ytixz8Hj6JqfMZauveYDks7I5Sw/Gd/4wvktELFpDdp/k12CSZLHQoZJUGnHHjTJGEuTzDNTg8xj0XM+PdY400TSniCYpB9jcn6r/ItEGusn8dFn8l2W/p6iV0yliQQed2/mdnyg3T/dvu3CQB9wRhtj28I5g22h40k4LOk36KHaKcBZr/MMvWNIT8RHzusAx9GqO7fo66vOK85hMppz1BgkEMa+sz7WXKAk7iccoxdsclaG/qVqQkKldVmnu2d6+Gxuc+rzKoJ0lsmfzeM1BrKezoBW9D780FPv04qRHKBLoJn3SUaIto3+di4Kzvt7nRyIn0nA9Uxr1SaZmIczV7JEb36dMp+pd+JavxwQkvAS3QY8RzVM2KH2DBqRCarBckDJH/pIdGmK37GnzW1bXWjqc3rJ6R7z6UWTNpGOrHAuGH8EYfgyBO7JImhlmv1FL5fsPYT4PJsG/xmrJKH4+ZB8GzMWz2Ez4O3cLn5XmvS0d6bI+jFBw3Xjjn0cVazbVk3G8/0sruCa6oPp4dsaY6cMzXksTaxV0GQMv5oHmRGFIK3sZ7fikwB+ceY7I3vKgjawO1ZO99Rjz5ptvYpfe8jpfdF1rF9r7B4kKxVh9NbXesynUCjMGxWU7Yx84O1yUblquXUXwPcwKkIxooA4NBi7DNhwCK5Cfg6nk+z4uIdHKwdtR7IB7mD0DkaDcYZzaqjN4lhFYipts+Iqe5MTTvZjKIyckxw8jHzvpiy4F4bzcoi2AQFQgbdozxMOIs4z2YDZqZXplbFOgcnvlW21rkJhbCAnG0rrnMstgufjvoL4rHsyZZejRdwHwbEh62toXkOK1ZDDBd+pkAhFngOWUsLBA3ksgR5jyXPDU+6Ela2nQphCZj/ZIxyx4dAMcCj6PIdP8IbvyAZ0b1nwK6U3BypjTH5nDvZVvm9L1Yi53/Oe97ywdpILKJIyXPO6bTIIGCZ4JyrdKZqCrOsqYsYGqo0l3pOfLTDL2SooHYkR1ljrHO9oHR1jsU02cR4XxzplmwLcGpfrMOVOF8YwhwdHIN4mhzgKJeDI9A0jYVMiz7YYk2E912fEc1Y5f5xbHO34MmdIAz5T9R1r4+5IMsfekPBiv2e+Z4BZk2xs2dtZnoxNIMhzgV0Cs9vy7BgZ2+M5+6Lr1PmoXvd5z2g7RtCDyDgOAQG9sZUo2eGZ57MvmvQKMu+Kua4x0IXpdaHbgffSC3wvMuDJVHKZbkevyDJ2jF7RmybGGUk/nDIc6u7Zyi0W6cnkAd1iKFEloHNHBB/IxaxP0yviLvR8b1arEzvnjCHfyeeOwlXO+qBLHgt5JYkw1pO8tt50msyrbKLovBHP2Yezki0jkYGdRU8aCsy2AVnzjWrtoB8dKdou58+zM8J2ML+sy03V+/L4OJs5NKM1IJvRGkcrvTYxeBs5EJ+nd1sjDshopzf0jCn8uo/5TL0TN+6OpjPQ1dwbl/eN75L31j13QIh52UvujRQUDvnMjla91VbtrcOU5/SUST3m0+MZeY3xpoCLtXK+0/0E3s0Xj3lPPgcC9p7ED3Nnk0TQtYX9ay+2rXuH7OmxY5GIIjmFn2EKn/TUHcfK+jFBwzzG9nOROGmtcuXaNvr00J5c951NPpgx586q9+5ipwyNdwxNIAfjp+4d56ZziSyVjJy7IrQYuo+zl3ycIqfPkg24r2cM6UlT16YHXduA7li/Vo89OFc/XaFQmDcqKLsHOChk1qqG6HEBfE+jgnPRIaAKz8/acQ/NJWC8xu09OSuUMs5QyIeZdwhCqMKQWb5OAdsW8U5KwZRL4POcKGWCx6pYHZZaiUbQRGDW9/zcXNA5K2lD9PIdge+cPYkugsWcsG2WVaYZntl0H2Z8J7976DtjAzltAJ5DTCAp2h/DKkcPxcp9L7J4VftxlMT8BCNDOVPZIlOMgZCdlvGcXR0ulDFjoggZczg8jUXGvp/1GMs6JxQDWaal1mgMWTwfd6Xad9nRlAOzYegyAKyLFtIcfvgtG56ZT2QfqlDBt6pkApdffvnyXXjYGFQ75aqeNhho/8hClNWc26aQH7Lt0BPfyuCjKAc2BWa3CVSvQp4nR2ZUzKpQWPfZMZCEIaCyTSZhnjO6SmjYFVPudOEUwadki/Z60ZlANZuW5Bk9MiOP7RnxHMYUJxF6yoQGezPumG2daXltZFU7CxhaUbFtn0hqERSyJgJeghkSffYBPJvbWvfg2bEyttdzetO113yA3JMdraNEez444y+66KJrteLr4fDcB6/1DjLvgrmusc9wZBibZ7XvEFiV/BhVeqFXqGCcqlf0pIl30D3oIXHO05Odw85vvEoPNG467VB1JtAXvZuuLMhMR6BPZ70VndEqt3EbOoud+XSA7JSKQDo9RaWKtcnIzyHnBMHpOJEEmoN+dIOhoN++nJXxMwmP9Bjr0gZm83kV7RpzQDagmtt6RXJpfE8imy4pMd/sqB+r963qYsPmkRCm8iI7pckie4izele0OjF9J1dt9ObXHvMZeyeuayEiqEwnk/AKdAjPUUWngjBAVpiPuyhXwTjsD3Y8GdLastti7HN6y+ke8xn7DDIrd7rS9UE1Nh6TgMROsTckQZBnbF1zv/71r7+8oihDcoV1/bZv+7ZloAGfDXV0IhPxb/x+X2PBV7vSJOydqbrjkE4+Rtb3CBq2Z3r8zjoJ/q1riZxlPf+Vajd2Zi8fzBgbJfhpip0y9OxdaYJf+QHQxDPH8GvMBb+yUV3jJXBnfzjDtCludaNV45kiC3rK6TnYgHOwrYf0pCmyfgpdW3t4il8r02TMHoxK+zn76QqFwnxRQdk9gRIw9aLyfRgVoPWBKllZfq3wdjAMte8ylmh7rNItFGz/b56CvNnRJ3tHtZ8WLw7YHECdAodmr0vgVa/K5o7WVAIlqm0dbvmeEC1XGPVtNWnAgShQHoFnypzgp+8FOAYY9pkObXDYfQDb0Cl/L7KkegRy8nM5ITk2ZF1RQmT2SwAIZJ6J76H/YrFY/vFdmZEcnuhCoULrgPY01ipa7qzDJocL3lbZkRF7QVaze956jWVobMDxRBllsKseRx9OOQo/owAyz9ivEZgFSp/ArCAyw3ZVCz5VP3gL/wvy28fZEFYZ7TMyCymUMT5Gse+FXNA6D104kjnj0TechxyClD2OT3dF5zsFt6XHukD1JoMg/y7uZhLQzYHtqdAmz9oItpAD22CbbMp93ulC3mcntDEwDsiOwmZeIpfxPH6WMEWOxBnIWUXO2X/ZQG9BxnHOkj+MJ9UA1lKwC5+7P5JRKXDTyqQ58+wYGbuqjeWY5/Sm69T5ZLrZX+QhJ5KkqwyVIT7by+G5b17rHWTeBXNY46FqH0EXOqO9FTpylhsSzOi3fhY6Zi+9YixNhs5PAUy6q+SucEIK8qnKpptIKjSPHKzLzzF3c+IEU9lkHGjCkRqQYEVnoF8NyZOoQgl4Fh2gvdOc/mHeq/QA9o09hx/NXdVFxqag3xSs003awKw50NlbWvhZdCWKKgtBR0msPqtSiD2glW+Mnx2BtpJL2+eN1ftWJZvYB4Laxt+20qOLckpLQBiDeCe71D5p+WwKv67ClPnseidu2JV0ePq+NSFT46qN0Lc5Xp0PnsWepFuwhbep4ha0FyQWoI8xjnGij3nOPs6dHvPZ5Rl0awnhEiDpSqq38BlbjDznO8BnUfEPeFCiunUWwBoKupI7bBEBpvAb5GCO7lr4IvNq77GMock+dMdesn5M0BAEUsnAIV+E+fKVCYy0c8mf83fIamvX2wezLfK6TbVThhLbd6EJfnXuSkZzlkzlV/zmbMp8QQ/1DoGm6KS3C7bl+33I6UPagHPCqv08VtaPoSs/ZS+/Vk9fwdz9dIVCYZ6ooGxn9LqovJcivypbhgBXlReIz2nRJNsp36kRGd8cDN5tvDKawtkUvfIFXRwyAqWcjYxklQjmxhg4NG1z1rkAmN9RxHMVLxr6vp9r9deizaZCZwc0ZZcyosKA4xZtHZQypWR/crSg+dB6cN4x8ijN7Z2162hgrbXWivtixwZyWqWJscnpprImHB4UagqA7K5V48EnFHn0VkViXXzeGAV3OShz4D4HutdhG4fLUFtoc6DE9BzLpkCkwDUa2wMU01DkAtGaDihaFKpoNz6UBdxWyOKTqPjmIFUZjq/shXY8ATxHkZOYYJ/6f86lyOa25zmXGcThROSwJwfQbdd7UNYFqrd9TqaD5AbyY2plbAsZl3iaM31bR0Wr9PZoxb4rOH8o7YxNGZZTWzifB3D2khMcwfaNdkOCKQy8uMeOscUpgx9a5HW2bznUc6ashAH3Vkp4YTw5H/eRqbovnh0rY6c+Z1907TGfvD8lxElMEphtnXD4h6zv5fDcB012DTL3xFzWONNZkMy5x7Ec8lOAjOM6nB75DMpO3B56xRSa5Hk4CwQIs17snM+BLvotnqUHxnfbMdFBzD/T0Ps5w9gadH1z4YiibwzpBJzkdGq6t3dGpbL50XFjzYZommlNz3GuWQf6U3QCattP06WGki33jRyYtT5af+c7i+n7qkSCD9o7j+lqniH5Ae+yN9AZD/nT2ipT9L4hBK05oPGJMYD1YvehqfGsaxG6CXks5hH/7sWvU+azbryb7sTNz/B875MEHW1bg7/NkdNVkIpDlqPV3lh333HMFS9xRLtTUZBYW+U8z00Y+5zecrrHfKY8Q0I7uqu24mSXpByQxGM9+FDae4x1hcIDq4JFZKWgDZ+I+4npZNpea2u5qkK951jG0mSq7pirwHrJ+jFBQ4hAaiS+84+1XeYEedC8PR+Guhk40/flgzlNOyVjCk0EodxXuSu/8oU55/CrZzq/6USKHdpOBQJqArPbVMxO4ftecnouNuAcMUVOT6HrPvxaY/bgWfTTFQqF+aGCsh3R+6LyqYp8drjJqsmKPYcSA0KQNUARoVQJSMYhSunVfoGDgQLKgUDplgFE2YrgL+PXsxi/5upwjfsoPFNG3JSWGVNpe+WVVy6zmmJM/s0Bp1oxsqKzcc8BK0t7qD1aQHWFw5cC4ZDUWoNi5x0ObZUnlAiOGMrwkKInO1swu22FMUSnVnHm+FnVxmaXQE6+N0QGl0xg2WE5gGjslAQOqOC3tqo7AvfewZEXrfy0AeGYkmTQOjr24XDJ/z9mLFOdUDKGVQu3FYxaSLt3It+pqlJAEoVki2zE+nlbSYl/8WVOIkADbUxkgG4y0iiL6EVu4LksHwQKQ+FrW1vCrsbFUKAadnGgDtG9hwM2P5ejAl9t46jI37PGPcaw63x8z7vxNcV9nZOv8H+h3T6elxiTW6jhUR0DOP0j0CaRYNWaDN0J6nzUJSGDobSp3eKceLaHU3vKc3rTtdd82vcIzHJU0X+06tpnsHwfvLZtkHmbZ+2KQ69x3gdtkEwynTOZHsRBJ7EsB9mGzvgeOs5UmsiqNwbOL0k+4QSie5o/fhxqk9/KNy3RBBk4SLMeDZxq6ON3Ei3dhTV05gjYClCoqqVfcq7Tw+kw9GB6cegbeU3aM9776PTRLhro4J7Jjlh1L3APvWCXZ8Rn7R3yIOZkrZwzwRdDdx6zp6LKzt90Z7TzN7sJzTK/TNX71o2fvs7ZSO+jE7J52FOxxllGscHsk1X352YM/bwXv06ZT887ca09uWNfqGbRBaWdu5+xu/wdY2zlfpuAyK6zn8gy8tmZ095h135vynOG5raLTFrVQnaXcexjLuFg5zwn6wUSM8KHIqkmEpDB+e18aNti5jF5Lkc9uWY/O2sk5axzjO86Fu/LY+nBJz10x16yfmogNexUMkOgxrltHEEDQRX7M5Ke2/c76zxHgPc0fDD7tlPyv6fShBzdlV/548hCQeq8dwTu+QqdhW0La/5Dv8td5XrLgrFyeh8621nHvuT0FLr29GvtugfPup+uUCjMCxWU7YR9XQDfw6gQHPLuqKB1mMj65ZhzyAgmykJyAOQWCJQTToNQ4By2kWkGnAgqRASaMrLDkqNK4HNbR+W+aMuho3LVoStACTKQKK0CzHGHU3yHciY4vUrxFbDkYAhjBY0osxT1DId5Vu7a9nmywHyvraiMOQxVF+bK5amBHFn9ec3dqcLAFLBu74OIu0IFbjM8A39m4wTtBHb9LJ4dfLFrYH6MwyX//y5jyes91glFcTQu2XbBHwKy+A8N2/VkMGjzFrBXVK20vMIhyQBukzA4gRnCsluzMzMcTJyu2ubFM8gMyqHq1Qyfsxc4zdoATs9qifj3ITBkKKmm2uSoaI1x9GPg9hjLrmDwbDIeC/+Pxu5wcc5JKArZHzTTPpwzuG2NvW1gllOKAz4ntmx6xhx5todTe8pzetO113zaz2jJRd/KlR/7Cpbvg9e2DTLvA3NY46EgGd3yFa94xfL39GKBWY7CoQDgWL2iB01yMIfDS0KgZEcVl8bB6Rg6oapD49OaL+7DWgfPICPRT6JgCxXFeU2ybsIuoP/lO2aNT7UE2uoWg56SNlc52/2c88n7ddZgj2QIjnH20pPG3HW6C1QFx3mwbYVHriTjgNvmzuPWNgi9LyftjdX7dgGnIruKHNCGPeaV+c3v7Cs6rPvR1rVlzOeVgIc2hL35dcx8ttGT1t2JO2QH2Aecr8ZuD+TrhqCtustj4PRtdXx2qnaGAfLIPOyljDyWKc+ZKpN6zGefcwnecs6xx6IaO6CNOPvXWRggp9i/QxWTrTxgV+HXnDC+TqfYdixBkxhL2I270qSH7sjPE7rjFFnfO2gY+1TgxvnEByYBODor8PXo1CQY0o5DgQFZI9H8NHww+7ZT8vqOoQlkmuzKr7FOEm/wK7kbOlXozXQ0vqNWjghixTx7yIIecnqd/nkIG3AO2Lec3oWu/K89/FpT9mDoa+34DumnKxQKZxsVlO2EfV4Av6tREYoRRcOdrlqHcAyo7JTJr7WuQy3a0sq8ud/97rcM3sYBxCAPhYbiSRnWnidntIXC7l3a9+RD1Z0A7pF0D0Bkph2atpQDB33OwHLgUUTRpA3MZmWkvedEwBtdta2R3Z/vM6OwoFdrSGX6UHwZcxxgqmkZO62jl2Gi7UVrDMhG29UYGArkeBYHWJvJhscoBJwmORuLksWZku9RMMdQnlZlvGXFamwgaozDZdex5H+PcUIBHuCEYhAJ2su48xx7NBSuofGtUt4FvGPPcw6h9aWXXnoN4wwv2msMrvwcyQyUQ0aIYDq62deMJe0Xja11PPsd+bFqbGMC1fmzkjy2vfdiKPAxBXkcrSJNPq5yVAxlafcyxqfimIy+fdEDL+sM4exT6ZUrA2V3O0sYOtsi7w37TgBIF4uh+yrPIs9OcWpPec6+6Do0DvQZ6oqwCkPybsgh1jtYvg+arAsy7xunucaZ17YJkkULRvobebENn/bQcXaliWx5CZp5P9MtBCwl1IXeKcFOp5ht9IzQ5eksKgJCFx5qmZznJ0GSvhA0bM92FccC3xdffPFSb18FumVUTVqj29zmNkt9pg3MCpTpGrQPmJduQuwBetc2nw8M6TSb7jxGs1UB5il635iK3xZ5PqrfVBiRVY95zGOW1SEqQVS6tRg6d9iGY/m113x2qSDZdCcuG5NdRs7EHpVQwOEv4cP+JEskYkbwo5UJEplVw0gkYcPnqpoW5NEqmdLrOVNlUo9x7GsuoeeRP66D4pvIsD/NN3hHUobzeB3f7VIhPmYsATwkSDmGJr11xymyvkfQEC1y0JDPi33LtlWNSY6Ys33rDNGSmN9I29q4ozFowj/jHafpg9mHneLMzgHGMTQJoMlQ1e8ue4ceJLiNZ5xXZGFAK1ZV5UOBWcg0HisLesvpOdiAc8M+5fQ2dN2HX2uqr2AOfrpCoXD2UUHZjtjnBfC7KPJhVDg8KGbZuSHIJrCmJVn7nEBWtgVyKcIy2ClzHDbt/Q+UVL9rKygp6bkF7qFoO5SBZayRCSWwS0kVmG4DqRFI4iSS9Z0NC4clpY+CnqtKBT8dyLk1T9s+j0GkzTSgqQwqB218TuBLKzPB4viZKuX2zrIxoBBYM8F0bXMzgibmEPfxUljNnTNG++JMT7zSZhnuorDu2+Gy7Vjys6c6oaKaHF0EZPFWvttuleHczs8+w9sckbFXGRIUN2MyTsqaZA381lYo2At4zH6wfzgFQxYwnBjD7s7K91K3tJsaqPZ3VEtI+lD1n/fRpu9De+/hGOTnyexmoJIf5hR0D0fFqrsh5xaQLVwTef/YF9oAMRpj/WXx4j+OVh0o8L09wLj0Xca7oMA2yHJF8orM1d44BM+uk7FjZXWm6yYjchu6Tj0z8t1o6yp2t71fbYzDE00Y1duszTY02TWBZSjINiUw23vv7EMv2BQk45Rsz7QpCQS9aKKqKBxfdFE6oD8SLvMY6Qv0FtXAQ8/PdKJDcq6Zs7uqsnOJns0+iCSyVW0cVUvFWPI7W7qjiYAqR2jovBmcp3TNqEjkvKKX0GtaJzEH+r4cUTFP3YScCW0i5tBnQcCR7TA07013HnPItZii942p+M3fbffSa17zmuXcPCvzo2QOgYyccBvv8Hs0YRfR+8bya4sx8xlqm7prl5dI4AE6rMACOWJOElpijeip1sPP2eoCTUP3i9JDVA1r/2o9PW+bexWNY+pzyKS2Le8YmdRjPvn5U2iyLfCqymc+lLZNdj7PxySO7pocuWosOdFrCk166o7s2bGyvlfQUNKVFvquGzBWtrix81+oypVMxLeTbVlBEtWf0SEu759D+mCm2imZJoJHeGgsTdrxTN07of/wqZF//A6SbQJf8RVfsdS76B1ZV+ohT/IzxsrpudmAc0CPtaEb96BrL79Wrz04Fz9doVA4DlRQtgNO6wL4dYpRHgehz7BQBakKo22pK9NQkFHb3+yQadskOIwcCJQqbdk4TygyFNr2HjKKYK5KmBttNwVmtZowt7YVc9xbRjGg5EaVBThAfUfgOmeGySLzZ0jZlQXFYBEwV2Ub9GKMMApkEzKSKCMCovluJzRWFTwVAoTG3ba+UDFtLkEriQCcZT5LOVFp3NO5PsXh0su50L5rjBNqKHs23mmf4ElV5rJu1znAh34muYJix9iKTDz7Eg/LKGZQCJRm549KcGuW5wA+SykMGA8+tceH+KpnoBp/U+bts6G2YKu+z6jXtjD2yhjk56naoPS6E4mTQoIKwyzox3FoXpzSuY2j+XOsVkB2/rC2WvswoOxJ5wYZjp8ZkIwnPCCYEu2H8KVW/KscVEPYtgJtLjw71qndYpfnMDQl/+xy1+q2dJ0adJARTS7Rp3KwaOhsy88XSAk6j3F4hq7B8WiNptIk/3tskHnTZ9fBfKzxPvZOL57dNkhGJ+7hPOpFk2j1GgFCjmJn6o1udKNlq8iYb3weLw7dWZVpohoRb3JwGzf9JJ9r9oWfO+NVjq4Dm4GdQYdY1XY2xkav0t2mhXXQ5YZ+GYFZzq0IzA6duT0cUauCddZO4ICjbuhd+XucavSbtoPQLnce99L7elT8Zv32yiuvXPIZva/VJX3OlTERaM38qlLO96zbWH5txzd2PtnxP/VOXPvY9S9xHzC7QLck62SdA3hB1d3Q/aKeoT161rfZhAJOWjtv2m9TnrMPOd1jPr1osg3wLb3QeR13Aea1Ps3E0aGx9KDJvuydXWW9qtmeQUPBXTLHGaJbgkBPe5WX57VtQ+l2fC5Bszn4YMbaKe2e7EWTsfyaZYJ1+/qv//oLXS8E1f/Nv/k31wrMqkw1riH0kidj5LSq7X3psceAsWvT69zp5deaugfJilYnPKSfrlAoHA8qKNsJp3UB/DpFvoU2swxqAcu2YpVyKUii0hM8U/AjxkQpd0CZSzZsIzAr43HoEN7H/Ya9aDsUmPWcXB3aZkgHKHYPeMADlkFxWX4BTiMVurI+BaujunTIWcIpwCkYFcXuwxUYZQTIwGTEcOy5m4GS3Rr1PZS+yOqSxZXnJ5NQoD4qhbNTKS6+z0GLbQLv2yisYxwuoeRRkqYqz7kd+BgnVHbMtc7DeKc2TSrNBWa9Y4h2+Xn4Ea9k3qOUZYVP5YyAr6zk3JIayAYGl7baeY/Yz1qy5DvLKHyMY8r2vgLV6GP+bdXLpsB0fH+opdIYMNIkHrgbJMBYJAc4hfN7833Ssh7Rs23zXZgfwqET7WA5H3ICijV9ylOesgxEkLsc5MDYcrZpT7RLALFXYGufPDvFqd2eh2Oeg66cc73oOnYcueLJnT6M7Qc96EHL85ZjktG76n0Bsgw/yaqe4vDU4YP+NZUmeWxjg8zWZ+ge0V3Qe+/04tldgmT0356JGVNpgteMJzpvBMgq6+t3+W4q33VNQk4SbIFHdJWJLi7+LTlA94t89QeHuL0Rc1qne9IhjMXn6TqrwGkluW+IH9kq9FJ6eQ7M2pP2VJsw2hOCBbmrDXAk0/dW3YGbE85WVU1tc+dxrjKaqvdNrfjlCHTHo2fnIJU9yDZp19Y8VD61stEzMk2m8OuU+Tjno4J5TJcX9I0uL094whOWdpAzNrdrtC7sPz+nJ2eoJooggGeqekEfAYK2bTW6cG4PVR15TiSgTnnOVJkU44hzZ8w4es5lLOhG+Lnd23jktBNHjYUsiAqrnjQZqztK1F9l7+wi6yVc0MN7Bg0FOgTNBYxV42fE8/gyBNgC+FwyP76bgw9mqp3SYipNeuwd3dTIQQlW2S9pPgKzriDLrYx9v5csyGMZI6chzuA52oCHQG853YOukvam+LV67EE/iz14aD9doVA4PlRQtiNO6wL4VYrR0LMFECkjHIetMaulgjE7MGXzBBw+qk8FqBykuf0MUGgFxR784AcvK2jPEm2H2s7JlssHoEPTYcthl6FyVGDWd3JglvLOAPFHFcJQhnTQ1VpwdKC9jEEHLaPFQc64a7/XO8ht/pRzigYHBwjac45E9mtbzYnfKLrm3cOR3MPhYswc27Lvx44FvfF4TljYxQkVz+BwW+WYy4FZhrDAd84abaGlJZ6QvWcM4SxUvUPhsx+HquRbnmeERTU4qPpoFc4AI7xnoDqcWRGoVunk/yn2Lezfobsme7cKNnYJFeRcnp93yz5UGTNU9Qv2xapW74V5gbOIcy3WnLEYcjUMH2tO3nzSJ33SUn7krg/Owk13gg7Jo7brwJx4tldbzl2fE5/3HFUHzr4edB0zDn9iPuSv4GU4qSSdoSfZSm6uGkvIJJ1Gxjo8fSYcnlN5Lf9sbJCZHhNB5jFog7u99k7vVrLbBsl6JBDkc2wsTTiw8/15gXB40k0FVOnhKko5jfCZxIA8HjKP88iz/Zz+ytEEnEGSnug8+F6wNp+3MZ48Hzo355tKJ+2NI2HT2c5ZzyYYctbTWcgyDuTQR9ogBj2CnDCWuNOW7cER1bMKJT/LuOjCAon0+AhEcNQJ3HOGZVrkfdPznu4pel+Pil/69GKxuOD0y7/jcLcntC2NsxJPWU/jBvoeXlShlJPoduXXIVqPmY/gQFQwj+nyQu+1DhF0929jl8wa65ATPTyPHImANluR/G3tN8m70QJWV6UMss7vctV1r+dMldPGgT+njKPXXHqgbTssKekQiaNo4rxGkyyXptJkrO5oDKE79pL1vYOG5nPLW95ymRCf5wb0GL4MRQMB47d3Bdrn4IMZa6esqxKdQpOpe8d5JriV79r0mSh20BJaMoyzIWRn5vuMXfmeXCbPwg+4q5xu5zQ3G/AQ6Cmne9N1il+r5x6cg5+uUCgcHyoo2xmndQF8OBq3CcwyUCMwO9R2hpJOiaEUq/akPAGHkFZUlO83vOEN13JKcD72bFU8hbY974LQnlDAT0YlR4r2OvEdmZVa3FHic/u7aGsx9I4M42WcMPY5CKIdBaeIe00yetM2K9MOfYYS5yQDLVrO5HcaD6PIzwTgVCxQRGTL9XAkj3G4+DsCfvhyrJIXTqS4U3dXJ5TPC9wbwyaDPObCsFXFlOeW/58BLOitFUy0LcSf4fhjbHFkcdauah/VJi8YM2ejwKpqlCwb2rWIu4anBKo9IwLV+Ns4OTxU1Ep+aAP+nJ6q9duAbG4F3QP4Q5WOeeRqDaBoW280zzhN2VaYBnyHhzjSyVhBs3xnpN9Z99xe3D6zxxibmf+0d98kV1rHnGsCIuP20Dy7r7acuzwnPpud42PpGm3Ixs7H2RzzUd3PwLbuWcYJDNB33JkeVRtZh8pJImMdnsZDHuZM/R408f9Tg8xjMNSV5FBrvK6V7DZBspxIN8V51IMmgsoCZKo+MgSzVF1HEEugy1lLzgkoCPjneaj8oQM4e1X/crSTG+ZOV+bEjSpkNBOYbJOn8rjYD9o7CmqpfvFOvBMJjb6n6lZVTK4gAJ+JIKw7fa0pvSFXs3hXVEipVG11nB4OqbwuAv2cb3Qae4cjUus4er87vexvuuBQhcVQwHwVhsZtHDGWHnrflIpfySX4TUJpRk4eFKxlI6pmpk9GxyK8GG34BLTzeu7Krz3m4+9cwTy2y4u5CTyZawQX8K09wl6MpIH4judE8k2r4+ITgYmAd9OPOWLbpGI6ensNUK/njJVJQdPQccaMo9dceqFNZjhE4mimiT89aTLV3ukl6/cVNBQ44o9gT7cJs/Zp5nV7P+vmh/TBTLVT1o1nCk12RR4HGeLe3ZCt9DAy2lkaZ6RgqcrAnvIRnNkCvs7rXeX0PvTY3jbgaaPn2vSka66yHuPXmroHdcuIPWg/HtpPVygUjhMVlN0Sc7sAfsj5uikwK0tMdlCr6GoXJrhEUXdxe65KYHA7RGUJtdlleSyHpG3vu3IYGpwMMugFsym6HJwOTY43SjylQlA6t3zbFloEZ1p6v/u9BL/2gaFDnOLBERXtltuqYC00KB7xc/Si9FMyeiisPRwuMGYsjEkOl7a6dVsnVB7fugqejNaZ3BrUlE5ZxNnAF8RlWBtDtJU2Rs6zdS1y8u8YQnhZIsHQvYoZPQPV6GVdoo0mY5eRT8GP5zLe8RmDLn7GkWy8qyqPp0BwmJOBgyGqe0HWJ6dAZEkW5o9VPCzIQFYziCTXBHR04Gx3Z3jsA3vZ5+3h1sCMO0GH5MpQYGtfdw1P4dlebTl3fU78bKi95xS6jpmP9XWGxzjIT/KUnMtJVUDGkvmRtRzwjHy/2hiHZ5bJU3lNBUvAWKcGmccgP6vn3hnLs/bBulayq8aen5MTJ6fqOFNogq84Z+IcjtZtMurbK0vIAbwWFQyhW3gORxMnmrOXXi9IFk4iOjenVCTjqViS6GhPDOkWqg3J1QhiqRD3TuvizI75WkuJWuvu7URnAXGfM74cyBMkxcsS/zjMh74/Bvgjd/wRABAYtt852ux9Y7aHdLyR5BD3Prsbr01IjUS8qXceT9H7elT8sgcFZEOHy3qjgGo4uoF9gibGlu/ClvghkD6FX3vNR9vFkClTryPx/rjiJipntNG2P+msrcM/EPOxVtbPs7SGzo5llcL25JBzO54RY5rynCzTxsqkkK14fuo4ptKkB/JaOyMPlTjaY33X0WSs7jhF1q9D76Ch8bE/PW+oKm2djXxaPpgedoq/w07ZhCk02QZDZ5zglEpZ57V3Ow/cLcvnYI+0Fb695GN71uwqp63NvvTYs4peMmkfdB3r1+q5B+k4h/bTFQqF40UFZbdA76DfVMgwb++ZWoX8bhnZMniGFCtVcAxggaeoSghQdjgazX/XOyhOi7a974LgCGT8c1IxIGRKOThV0Dp8tXrj7JU1tu5+onXg8ODw4QSiVO6jTU5ef+P0J4wt74uKWcp0BGC1leHMjX+jU27vPEaxytWkYxwu5hEt47JTetexcJxyQrV3lG3rhIosO+BUEsDfprVtu+fQIJyRMvW8x58wnuMd7ujgVAoHVsa2Ch+l2p1Hq9p9B23sw7GB6gx3hHHSaWcUGdPmz9EpMEupt98lVeTv+5vSG5nL+wDD1nribzIvZKJ/72P/FU72KtMYi5JLIrjAQa59EKdTtE+TdCSjOrffy2uNB8hgMkDlXDw/5Mqqs+m0jPFteXYfbTl3fU787TnORo68sXSdemZEgIsDIa+RTGbJSORPlnd4SEAoMpWBkR1XJYx1eOYxTeU16+/5ITN7BJl3Rc/5TF3jlmd3DZLlyo1ezqMe8oRjU/tG56Fz1vkdAa787tBXtIa9wQ1usAyuCShLOst6PD6nX8QY8awuOPRBep7kKNVRQ9UN3sHJanzgGVq9SbiyLipVrGPb0q6tRnvyk5+8DHoA/uX0st4Cs6Ff2leCyGyOXnYTurFfOKrRXeDfOqCtiiznAhrriJNlRNw5pn1dzCcw9s5jPB6VZVP0vh4Vv9pY4xOO8yzzOLkFrCOAn88YbbX9Dr9lm2AKv8acps6HzUa3z7J36nUkcVUOGRpjZzMJ1qvADSdsIPNIBCJ93viNL+vT3i1xgvxqO2n1eE4POR0BWXt+7Dh60aQHMk10BTtU4uhp0WRXe2eKrN8GvYOGnucaAnzdJoAc2gfTw04ZE0SdSpNt5pPvwHROSHIyF2dh+AjxMx37rW996174fuhKs23ldG899pgCslPXZp903dWvNXUPklFxn/Mc/HSFQuG4UUHZLTGXC+AFcmSktc9epxQPZa3n+x/DeOXQYnwI0rWtuRwUHH/tnSCHpm12IvW4syCvEWOMoyE7Dh3k7tvV6kZmLafSmHX1fu+lsGgXHfPpwSNDkLXF+aIVESe1Sol4n3FQ4v2RLcpgC0WL0tHT8TrG4YJW0TJO4HTKWAScGd5TnVD2oOdwHv7RH/3RWtq3Dlx8xfkfma+eG22DVaTHd2Ju5oun99VKPRy2YwPVmWYcjtYyAgHafeMvgVjODI4B1e3WgeO9DZKdRnagdeaY4JDEf/g7sK/9V+gPFU4qqhiHjBnyw74JuSKBxt4lwwXPQsbm/f3EJz5x+X0BCfxuX8rmj88yvnSYsA8EDAJ4f0pgqzfP7qMt567PCTnnOcbJuT2WrlPPDPKUnKKzZF0mZBnHVXSJ8F3VUYKszr5MS+Nd1UJvG4dnlv1TeY0MFciIYGXPIPO26DmfqWuceda8dw2SxVx66DghB3rShKPRs+jGEWjOvKntrGRBEFj1bs8Q1KZTRkcLc+FER0N8HlVLnu/zHO32waozGJ04tDieOFzpvUFjAQyOTzwf7bNbGwNUqXpf7lCCJnFfl3VWrUD/pB8NPWMKvF+CCJ2DTkcPau81NL6oKg9EO+W22mfMnccqRAV5JadZxzF6X++KX+uIHtaUnGDXkA9RdT8UpEdDPKO9dr6PfVd+9f/O6Gx/jZ0PvvbzkBG7dnmBfB3JJoc/PvE+iQWBzKvkkuBWOICNle3VOrfdaYn3Mno8p4ecxvuh44wdRy+a9IZK/UMljp42Tdbpjm0QcqysP2TQ0HjpX7ueFaflgxlrp0wZx1iarEJeZ3Kf3mtvOP9CZqgwzHzFxkfbobO8F9+PkdPtfM6KDbhP9Fqb06DrmCsCx+xB+pqfzcVPVygUjh8VlN2AOV0A3yrADjUKcxtgHUKrfK/qV+/QZZhTmtvA7M/+7M92VVin0jaU6t53QbSKHqMst0YJMFyGnBbbgmOCgRJr0TNLM89Ra+jb3OY2y0wvzjitmBhoEWA3dsqrz1Bqc0B2imKFrlrbTHG45MorTp2pSp67kac4oWTNqaj4iI/4iK32dctrAhVo31a6y4zjBPG73BLT3GTyqT7dRyt1PP3Qhz60S6Aa0EcFueDty1/+8qXiLuuQQ9S+jCqG/LxDVKjKiMRz9vfQvZmF+SGvjSowxotKL23I8CuDKtrPcbC698qec2fV0J1g5CGZoj1bPv/IA63pA56R7yHi8ODQa4Njh+BZ+ynfizfWqe05DPEICk1x9pNVqpDG0JV8D8f92HHQAfzM53OQy1obW/CCs5BTIZJM8h2e257n2yZ4TOW1BzzgAddoLb+PIPMumDKfHmvctpLdNUgWn6cDSULklJnqPOolT9pAFl3F76I6yfdk+OvWkpMz6W3OXzKQfqKzRejAEi7xD54P/O7v/u6Sn3zeO9GkzdDP7duAMwt9gw4Cmpy/dKRVe0ZFmmruuBKDXhjXfhi/YKy7BtHdPow59U7QUg1hra1Zm1wagVkVnxFwAPRzrrRVXbveeRxBQwmRWd/YRe/rVfHb6lueJQDlM6o9whmbP2f9chWIMaALfhvLrwK3dMWp83F29erykltpDzn8rV2WuUO6K/lrXjoX5KATe4FzW3ed3A5yFZ/3eE4PmdRjHL1o0gNzSRw9TZq0uiO5lO/67SXrDx003PV5+/DB9LZTpo5jKo3z950BktAEOaObnHMqqmPJT35DZ6l5tsUT++D7sXL6LNqA+0avtRlDV34t9NyGrpv8WlP3IH1tTn66QqFwPlBB2TWY6wXw4TzhBJTVwzG1LjCbg5g+mw/VoTH7vWAVo7h1AkKPwOxU2ppn0NZ9JL3vghhS9Fa1lehhWOzLCOVopmi1FU1al3ESRRYspRWPZuNkisLKueNPr5ZxPZXnqU4oxrwqnsiwDpqua1tuXBxylLk22SGUXwaiQCcHk/vfOAnMhbMyjJt9tFLvEajOkOXH8WlvqSiOrHLP1SIs45BBUPPjBFadE5XjhflDEIY8c39c5muGjD3qjGsTaKC9s0qljOoxcid/Br9ytJNZqwJx27Qs3zfPSpjp4aRX6d+rvecUugq4ed6UcUiUEhDmgM+yRbBF0lG0MYvfCUxxIHEwveQlLxkllzYleEzlNfNyVrdJQPsIMm+DQ6/x0Hx2DZIBx4tgLP1hql7RW560+ieHj3dFO01ndVv5n892ZzDnmkpAQSuBcPp1/nyGoGN+J/1QQpVkgOiggXb0RXN076+qZmPJ1YYtvQVf0ViVlSCdwCi9RrVB7JUIELibK1cv7wPW5pa3vOUyCJzXCTjk0FmSQABP0rcikWHMncfh4GOr5MDhLnpfr4rf3ErSXMKZ7gzwTHpttJiO9STb6Hpt5UZuBzyGX3vMh77aq8vLtlUs6JOTEfP36ZHklArMzAcxDvsALVXm5UB/yzs9ntNDJvUYRy+a9MIcEkcPQZPQHXX3yvZOL1m/K3p3Q5hqS/bmtx52ylT0tK/JA0E5cjnrc5L/7B88QqfDI/S7oati9sX3u8rps2wD7gu91mYMXcOvJVEj6+JTrwgcswfpa22HpTn46QqFwvGjgrIrcBYugNdSi2NOtpp3DQVm24Aso7Q9bIbgYHZwybhnuMyJtv4O2gry7OsuiLPeVoLyoB2XNUejjAjManWXM756ONdDYe3VMm7KWChSoTyPcUJlXg0nlPH4fQQtg2ZoytGY28uFkicg676rNgOQUsd5FMqcNQsnqoQLDuLWuOnRSr3999RAdQvBD1mJmT4CSRwhc4KKKkEchmWukijME/iWTCHTZLxm2H/OA9VQKvTjTuwh4HcOKu1OW/lH7ghSal/UPn9uPMsp0kPG9pLVU+k6dRyCsirdOB5VeUQyiCBBVP1nPSICbJ5L7o/V1dYleEyhifmQu6cZZN6EQ69xbiU7JkiWk6Rk//dwyu1Dngzpn4JbqwJc7TPR1XnOOZTb97Xv5WAiT0PP58BCZ7LUWgigRsWAs977BTXMyZhaXSLj8ssvXwZAM9BKEEDXEFeBtNi3Q0rygkpo+kvrWJXgmekuETMSasfceUwfpPe191qP0ft6VPyG/qsq3PqpiAm9h75mXqrrQyeO9uyZ31atzxh+nTIfiROCBGO6vPheq6f3qGKhk7sCKPiF7k8WsTPC7r7yyiuX9uo6Pu/xnB4yqcc4etGkJw6dOHoompDt5BF5Zd/3lPVjMBedeq52ylzA58GfpmNI7lZiLhLgtITVSQ8k/qzqILcr3++z2vAs24D7QC+ZNJauva8IHLMH6Ws+Pxc/XV2nVSicL1RQdgBn4QL4GIfWC5xQsvrbwGzMw6XssnmMZ5uAbEBmlKy3fWXujaFtDsgyoMa0sxXIdr/qNmtzltpKDClKDCvVNBxz0coxr4FKAA7+VtnspbD2cCCNHUsezxgnFHqGE8q+CQe4can+YMxHi7ZIMNCmLVcoUdzcA+jeNMZvrjynKHIstffqeKb5UA4jCNq2mprSSj3zSc9qiSHIsmTE+b65HqJV8SZw3ql2K8wPQzLF/pC1jx85kLIh4/N4jXG5yYB2JghsMqqcFfn5gnhRMTFHZJ7tIWN7PmcqXaeOg3wj5zxD4IcTPpJMMk8wymPcWpzRHS699NJrVFf1SvAYSxOy9xBB5k049BqPDZKB5ET6o2q5nk65bWky1tGoQoGTaV2Aqx2jFpSCVo9+9KOvkUSWITBpL9BPBCfctxjdZ7T21PqVLuJZoVMKVqL3pnaLKpy1rW3PV7qoZ1qH3GL8tGC/S/QTmG1bE/e8p5tMEQShf47V+3pX/NpveELibSvrQieW8CEYQxfmnMWv2+huY/h1ynzYqLt2eWErWhM287YdrIaqWIZkAQevRAi2Af4iw1wLcP/7339pc7Z3E2c7fepzpsrpHuMY8hX0mktvnFbi6D7Xd1eQ9d7l3O0t688z9mmnzAHWntzEG/g0V6DiTcltuYo6fj6F7yXl6TCxz2rDs2wDzlkmjT13pvi1euxBPD4XP12hUDh/qKDsGsE49wvg28AsRxQDOh+WnIOyfNoA8a5Kfs+WxT1o606yMe1sBeUY5Jwqx9RWIo9LO9pXvvKVSwdSGFAPf/jDr9GSI69F69TtrbBObRk3dSy7OqHwYLTUizvRKFbaOUUQlrJFGZPswGCVJcpBJ2M0vkeJdV9rZB5TcjmVKXwqgXw2FL1M+xijChYBXcbOPlqp76Naon035ZLiy0EX36/sv8I2yDymYhCPRstwe0TgJlrsZ0cRvlvnOM3gbA/+1jpJopDzwr/PkvOph4zt+ZypdN1lHNa6HYd3CJ7EPattNULcb5mTTFTQRaBzHwkeu9Ikt/c7RJB5E05zjUHiXqzx2CCZIKEgbOhBvZ1ym2jSq63ZJvpmvhAEds6jh3s8h0BnlHB40UUXLR1YuYJU5QtnPQepipmh8a060107QSenw3D6B+in3ieghq9XBYz3CXtEogP7IzvcrHmuopx657Ezaqze16vi17rF9SScjJyt+f35s8aGd+1Lewu/sh/2ya+7zCc6+YQeO6bLy6d92qctkzno72OqWIwhxpPbH5L/+IXsYC+EPCa/JfXm9tGZPlOfM1VO9xjHacxlH9hn4ugcaTJV1hdO3045TbS2fZYROiBIgOF7iM+Rt8603BK+F9+fRrXhsdiAc5NJ29B1H36tqXtwbn66QqFwflBB2RU4KxfA58CsLGEHXrQEi3tBZDm5y4jTyb/X3T+7SpHpGYycSlsG+JTWuioZj6mtRD7QBRApFALXsn4FtWU1quJkbHFEDLWMW2UU9FJYxziQeoxlVydUm9UvkxjPDQV0te0xp4svvnhJc47h+H7wLOWwvW9LMgL+Cwdp/r19IeEABBL8v+BBZCn2aqU+JlCd6bItzIHzcxfnXKEwVM2v4orjLCqrOAM4VxlbZFrLW9ueWc4EcoQjyh4mV+Yo509DxvZ8zlS6bjOOWGPjkFzyspe9bClvAD9EMJO+EIHZu93tbteQaZGEcxrYhiZDfHuoIHOP+Uxd4wiSBa9NDZK1lZm9nXKbaHJabc0yT9P9Bdey47T9jIrRBz3oQctxt1XGf/3Xf70M6g7d39neZaszi+oDezFsEOtF/3RXsI4cOoo85CEPWSazsU/aVtWnBTaFNY850AV73a/dU++bUvGbQR+V7BrdXPL6e28ExyUrBE1UoJ6WvbRpPvm5Y7q85PmqchlTxZL5Hx3JDk5rax8JxG9729sufIYMceYYx1Ay7NTnTJVJWcaNHcdpzqUn9pk4Ojea9JD1hcPZKaeBPBa+BUnlKiUjYc3v6ZrOEFcQKK4gV5zvbaCtlzw5jWrDY7EB5yaT1tE1n+W9/FpT9uAc/XSFQuF8oYKyA5jDBfC7KGrxWcq0aoI4PGQMfcZnfMayT75DwqGoIoBjal1gNh8SPstxMSfa9mhne4xtJWSCCyAaI4WHs0mbXS2+QjGJ9kS73BPcS2Hd1YHUYyxjnFChsEl0UHnz/Oc/f/lvlR7opiKJ40ewW0DTz40rnj3kyG0VOtmmEjei8ta7OSopk1lZNca4s7VXK/WpgeqxmJPxWTgbcOcVY8ce1F7pAQ94wFLux72d9p896u7z7CjfFaob7S3GmPMyMKcM9tOSsT2fM5Wu245De1bBHW3U3N8Y/OH3zkMVcf5IVJqSZNID62iSZaSg1tyDzJvmM3WNnUPOth5BstN0yg3RJOugva4f2DS3/N0rrrhibeA/qqg4W+kLrY6oKtm9vnnP0NmjisAejFbJaEnHF6AN3ZQtgr4CZxIwjYG+TuefIrunIlek977zeKzeJ4AYet/Yit9VayxRU+WoZIQ8fy3FBcr/4i/+4sLP4xmnaS+tms/U60ii+02m865VLBJEoooFT9sn7muOTlWqjCJQbFwq8vGLpM14byvnpzxnqkzK7ZPHjiPz+GnNpSf2kTh6iPXdZixTZH3h8HbKacEZTr4K3LsXns/IHIOf8I2fqZwVmA3kpMCxfB/8etrVhsdiA85NJm3ShXv5tXrswTn56QqFwvlDBWVnfgG8IGZk6qx7x1Blq59lw97YHTQO4Pb+2VUBWYrXLvfQnhZtd207d8xtJYyRwkERcPCD7FeZXuGcoDSYO/pot7GrsdVLYV3lcOkxllXO022dUO1esHdUirpjiNHKEOEExnPapD3lKU+51ru2rT43dnxK4RPclX1KAczBgn21Up8SqC4UTgvaJbmLOZIiIlGCoWMvxH2TZB8ZPjWjGd87mwTuwpA7i+ghY3s+Zypdh8aRZZb7DlX168Ch8vLxj3/8MvgTd5XiCwEUnxEMOmRAdluanKUg877WONAzSHaaTrlMkxhzT/0Tv7cViUNo763MVdbsCwFseoKkzjj3dd2h4wRNWxrgMwEx9oH10TUEr9KpQBccOn6mI73jV3/1V5fjDr1CkqCg7Ka76feNdn697tceo/f1qPhtrzPx+7e85S3Ln2sNbpxaEkerda3+jEXgPPPLoeyldj4ZY7q8eE7QtkcVi+TgL/3SL13yQkBVPpuUjYCfPUtLQwkl8e52fXs9Z6qc7jGO057LPtA7cfTQNMnzmSLrC/OxU/YNiYCCTnHXsLOdPh2+peArZ5nOdnH/cOadsXyfg7qHqDY8FhtwbjJpSBfu6dfquQfn4qcrFArnDxWUnekF8AQ9ZxLHhvZf23w+MOSoae+fpUy1gdkhxaZnQLY3bbdtO5cNk2NtK2G+2nNQpClbFANOs1B0Bdgp2+13DqGwrnO4jB3LVCfUKlAgKUvW/jGPecyyMgTcyaNidldkhU+W6e1vf/ulkrfOMbePVupjA9WFwmlB9Ro5ls8IsK/te1m+LW9OdXjYD9ofOZ+iAucsooeM7fmcqXRdNQ6JJVrt5ftDyTIJMwJGoTuRqXGnYvz70Mg0yS3DzmKQeZ9r3DtIdppOuZYmvfRPiWLo8X3f930bx5Cfk+8F0/r5Rje60VIP9zfn0XOf+9wlf2kJTcfRIvrKK68c1Ivco+ValAjYWYNw/nte6PHmbW0zf9JF6SAqG/L9rXNCr/u1x+p9u2IokNpeZ6J6xP6S+Co5V+CSHujeNH8igBl78JD2UlvBPLbLS1TI9qpiwd8+y7ma26N7jwAGOmrLHfttaIzQ6zlTZVKPcRxqLnPGoWmS9+MUWV+Yn52yT0ikIjuBvDM38g/oqRGsjVbGeMncI9lrLN/n8++Q1YbHYgPOTSa1dO3p1+q9B+fipysUCucLFZSd6QXwcRhqv6aCIIIn6z4LHFb3u9/9Bg+cNjDLKOfUaQ8rP9t3ALIXbTe1ncu0Oea2EgKvWnNYUw6YCMgGjSjZHGdT0UthHXK49BjLGCfUpnEwWmXgB3zWszlGAxy4nOnbIO9N9xipAlql6E1p9805Fa3UewaqC4XeIHff8Y53LP9fBwWt94ED1vnQOrqdHe4t3AfIy9gTZxk9ZGzP50ylazsOTqAHP/jBy+Crc739rMCsO9Tbjhxzkm0tTc5ykHkfa7yvINlpOeXMJ2jSS//0XcFMgflNc8v6ryopOo9znh7AQY+H6I6qAIzLzyIRkz5DH6BXt05bvBh3ankH/UpVgY4inP7elXUYCW25Yln3H3fVDbUknxM23XmsE03ofevu195V7xuLvN5D15mouuc8BH8LnKvq8HdUffQMYPacz5guL3k+vapYrKPv2wOCw/ZOwDtVjKsyWjePns+ZKqd7jOOQc5kr5kKTKbK+MF87ZV+Q5CbBX+KVszz7kvzuS77kS5Y+keDjT/3UT13qS67HGsv3Wd+bQ7XhsdiAc5NJQdcpfi16ry4ZY/bgHP10va48LBQKZx8VlJ3JBfDtwRf/dgAR6LKYht6ZvxfB1NwybF1gVtsaQVAXnwc4/bTNiwz4s0DbVW3n5qbo7QvBA7/7u7+7dJYIPuZ7DtyBIBDZi197Kaw9lL08ljFOqF0cYlqfyC7Ea7Lf4nv2KOfvKifVEPJarHOs97g/eR+B6kKhFxhY+FjrIUkCDMaobtNqXUWgAEAYXzoq4Ne446iwGr0M6jk4UNtuHuB8c28l+fujP/qjy5/lzwjMcRjNYfybcAxB5h5Yt1abgmRt9dbYqyZ66Dj7aGvmd5zpwetD7xr6mUAZvd73jIUjlRNekCs+x9n8n/7Tf1rK1gAaZP7yHPzJbjCPcI5x0nq+3+V2hiot6fYSReM98fc2rZfngFV3Hofe58zqrfft+zoT72zf63sxvjnYS1PvxM3PGFvF8spXvvIaVSxBM79XQaNyRrJrfF5ggg6NDuvmMvY5U9FjHHOZy5wwV5pMkfWF47ZTVvmD6Fh0DJ0wFIUEBPD4IvhVwscQOnnoSlP5vqoNj18mTfFrTdmDc/TTFQqFQkYFZWd2AbxsGvcuZahqlaXTHrL5/YJMArLbBFPjOe4VkQEdB4+DTJXcD/3QD52cNdquazt3HhS9GDNnyPu8z/ssq6sp1hzSWm+EM2XObXNO2wm1Cz28Q7DXO2TNtfR83vOed3Kzm91s7X1bLVqn5KqxTGn3ve9AdaHQAw984AOXfPp+7/d+1zr/Lr/88pPb3va2S/7XMtzdMf5dPHp+0Lan5yx391HwAAOdwR2VH1l/aINBc8GQA/SYgsynHSQLzE3H6al/qjCl519xxRXXeo8AaMw9y8ZcuYhvnvOc5ywrbekrUb0ad7lxyF7/+te/EGwNGBOnl99JENXmUmcW+pBxAv1dQO5BD3rQcs4+Q1fi6IvxnFW+XXXn8T71vn1eZ0IvjjaFLeZgL/W8jmRsFYvnRBULu+KhD33osro7dPBo3yk4fY973GMZAEMPz1t1fc6U5/Sk6dhxzGUuc8JcaTJF1heO106JitaAs0DQSoVknEUKPC6++OJlkqDzw1mgQ0k+y302Pt+D76va8PhlUg+/1pQ9OFc/XaFQKEAFZQ98AXw+PDmYPvETP3FZDfGVX/mVF4xb2f4q2gSahhwb7gvN991w3Ax9bt3BYhx+xil4Vmk71HbuPCp6nEbf/M3fvAy4o+eQo+7YMMUJtUslE+dczpjLe4zCt+q+rRb5ewKmvdt9n0agulCYiuA/PKpVFoPJXVecrBkvfOELl+2WtM7SojQ7BgrHjXVV/6qmZPALSH3VV33VUnfKnT+GnjEHHGOQeQ5Bsrmh1/UD+IA+yvGjwsEZ3vKB8939w/lMpwOpYM2Vi5xEP/ZjP7Z0agmgZgi+aWHX3sMrIMYhm6tgJYBGYJaDH/yeDNd9Q2UlHeVYEgLzncenpfft8zoT52yLOdhLvbu8TK1iefSjH738jL3C6as6J6rfvIdT289UH3FuB1rdutdzpqLHOOYylznh0DQZ0gfGyPrC8dop5Cf5riADXMHEd3i3u93t5KKLLlreUx9nmCQsSVV0an61VWd5L76vasPjk0nxsr1wAAArG0lEQVQ9/VpT9mDuAjInP12hUChkVFD2gBfAZ8XGs7WU4Zj7+Z//+WXLr4/6qI9aGtYcHYzkfM9YwN1NjE0OEgam/497x7Y9bObQRqwXbdu2c8eg6O2Subrqs3MxCubmhBqL7JjLtNUOZpPC17YVfN/3fd+t2izu2u77NALVhcIYtDIWb7sLRhbsrW51q2Wm9tve9rZrfS+y/KGMnPOFoap/zsZXvOIVFyoABGY5GdxtOVccY5D50EGyuaLX9QN0iqc+9anLf6sA+OAP/uAl38fn8IzKB3dnxc8kddoLbIO3vvWt17jTVYKZylZdVXyHzaH9q6suBLuHWt+FIzfrGp6Nb83xt3/7ty/sQ8G5N7/5zRfGciyyOrdtPC29b8wYx15nMid7qWeXl7FVLC972ctObnGLWyx1aFAlTv+OREfACzo9qSLOSQuZLr2eMxU9xjGXucwJh6ZJltdTZX3heO2U17zmNctgltbViiHwowQ3ZwG+0Q2BPHzjG994gXecCQJfQ2d5b76vasPjkUnbYpNfa+oejHvl5+qnKxQKhUAFZQ9w1xQDMBwYIJtHBvJNb3rTk//6X//r8n4mhyWlSRa6jB/OFa1m3GnZVslqcxcHiDsgKNpx386mw+a7vuu7lvc9zeGw6HVX6bEqettWQUOs57EawYe8UxeyIcuBnkHpXaXwtYpeVLjvo933aQeqC4Vd945zyh8OgQDHEWNLlX+02tJ6KTuaCucH21T9k/XkuzNdhv+cHGHHHmQ+JOLcm7NjeYr+qeMJHtFiMioCzJlNIDDLMeWOrLve9a7LNm2RYGk/qBhQ3fiEJzxhaRNwuLpfMAdXXVUSd8HiNVel+G78fhUyvVXxRsWs6qt1nz3ryMl4p6n3jRnn2OtMDm0v7avLy5gqFjo2PTloaQzWDziCw+Ed7SBVh6NZ7KHez5mKHuOYy1zmhEPSJMvXfcj684pjs1NijVVGO6dUxUqoyndw41W8o+vAUAV162fYB99XtWEfnCU5vcqv1RYu7boHz4KfrlAoFAIVlD1laEkm29h9WA4CraAcDBwo7gv7hE/4hKUg/6Vf+qUL39FGSkXsh3zIhyyDrkNKdAh7l5kL8MqKWvc5kGHksMmHxrHiLCt61mxsFfTc53YW79TN9MVHlC9tFLWLjnGEwsdhOpSJN8Uxt02770MEqguFXfaOdkpaaUkYwJ8CEAEymmzWbguff9AHfdC5kWWFk52r/iWnyQxvvzNHHGuQ+VA4C46OMfrn3/7t3y6Dnc9//vOX/1Z5KoAvEKslpefc6173WrYedN1JWylIF9Ge0N1w9ATBfu0q6UbRbthnJXWSwZxTQ5U+29BdYFarQ3d4ReLgseHQet9pXmdyaHtpX11edq1i8W7jeOYzn7lsmZgTG/1OcoQkasADAmFsjvbexl7PmYoe45jLXOaEOdBkn7L+vOGY7RRy7vWvf/0y+CoJ0LVpEGeYTnV8JlrDryvu2CffV7XhccikKX6tqXvw0Pravq48LBQKx4sKyh4AqmTveMc7Lh0pj3rUo5aHZj4sP/3TP30ZmBVgzdC+TNZ8zsQT1G0vO5cB6flthvpQ9o/2Y+cFZ1XRO4Yq6GO5UzfT1x0cnEXap1H2bn3rWy+zDSMALOvw5je/+bIlpeqDwNOe9rSlcjnFMbdNu+/TDFQXCrvgW7/1W5fGk/NL26THPe5xy/ZAzsRsiN3znvdcnmfFq+cb21T9a0l1VnBMQebCfvRPyVMco5ztKqXd/yVpk27PkRQVi5kv8lUk2lTSR8KO+Omf/umlzq+l3Ud8xEcsWxnGdyRm3uAGN1h26hmrD3kG59YxVcbOTe87zetMDmkv7bPLy1AVy1CbRBDQojPbG5EQHe3COVw5hHO7cXtxqNvTrs/x95SuUavWZ5dxBE3acZz2XOaEHnTtRZPMr6ch688jjsFOoUeGn+/hD3/40i8CArPOKUGjqD4MntKVQ8JXzOMQfF/VhmdPJk3FkF9rzB7Md8jO3U9XKBQKgQrKHgju9NA+hNAXPMuIwOwXfuEXLpXtgEwe949FWxEZbp/4iZ+4vHfMAeUOKdD3njGr+gJaY5PD77SzteeCs6DotWM571XQc7xT131Wl1122clLX/rSCz/Tuk/2qfs5cvIDx1aMyz14Eitir55Wu+99BqoLhU3Iskn1H0dAboPoZ4JqZFZUC875bqbC6eEYq/6PLchc2I/+KWETf5CLj3nMY5btiOHLvuzLlnfLZmT+JyvZBxFIu/LKK5d6Bz77q7/6q+W9cgK8cUeW73J4aW352Mc+dqflHBr7MQZm56L3neZ1Joewl05D3kcVi8SYXMVC9/iGb/iGpeM3ns+WUoH44Ac/eGmbW3vyWYvP0Ek4XPN4xj4nO5PHoK1yGjMOz8jjONRc5oQedO1JkyxfT1PWHzuOzU7RvlpASGDokksuWSZnR4Ae+BJ17nPHbLS6zryF7w8p16ra8OzIpF4QyAy/1tQ9OAd9bV/X8hUKheNDBWUPCG2Jb3nLWy4PSf+fIdPR/T3umw0IqFz3utddXnLu4HrHO95x8pd/+ZfLwK1M5o/6qI9aOvoo3B/5kR958tVf/dXXeqc2yNrgajd2XnFWFL2qgp7nnbrGoZWKPZb3rXdymgqcW7tVCtrrXve6owxUFwqb+A/v4zuOAAZkhpaul1566dKAXJWYUjifOKaq/2MMMhf2p39qMffGN77xGnvBd1XQDsnHhz70ocuKAXjLW96y3Bucrv/tv/23C848/MWWEGzLjixOKBU0+V2F+eh9h7jO5BD20mnIe5Xn2ndq/y2oaj9x9Pr3RRddtEyajpaGWshrzy0B2hg4cGMMuhHhiwhqjH3OVHmvfePUcXiGKqJDz2VO6EHXnjTpJeu1wM+y/rzjWO0Uc+EbFITPBSD5jlmBe/zMnzg3vq9qw2tjLmsz5z04F32tUCgUtkUFZQ8MLSYYQe6YbQ8Bre0cILKEtDx2yMh2FKh1oNz0pjddtqDhtHGYMZ5lNbsrgAJ2/etf/+SXf/mXr1Ul616R8445KnpZIakq6PneqUvZ5aQynm/5lm+5xu+MkxL59Kc/feWYjjFQXSgMIfOac0sHCM4jzqTP/dzPvdD1IcDIsrcKhWOu+j+mIHPhdPRPjij6PB1fpn+udMhVABxyv/RLv3ThZ6qlOGU54aN9nUpbDvmsc+b/V2GQWyGvQ25/d8yYi953iOtMDmkv7Uveqxj70A/90JO73vWuS9tZ0Oq3fuu3ls/XztMekxgdCRGSZvCA1p65XbHnCGoIhk15zlT0GIcOXnOYy5wwl/XtKesLx2+nxJze8IY3LBP9JNV8xmd8xjU65AVf4g9BO9cPzJHvq9rwmpjT2sx1D85FXysUCoVtUUHZGcBhKqNHYFYwrjVIVVP4nUNGZo9/v/CFLzz5pm/6pmVbGgdyVsxlBamI/ZAP+ZALdwmUQj5vRS87SqoKev536rp7goOKI92dFLm1CmU4t1s5D4HqQmEdz2kHxKnLkQTOMXe7fNVXfdWyYjCy+rUTfMQjHlHEPEc471X/xxBkLuxX/yRLr7rqqmVAVtXDUNBelesXfdEXLaso2t+55kTyp6RMQSjO/NhL7X2aqi78Xuu7bcYViHvpjhmH0Pvmcp1JL3tpDvI+V4mxp/G7oMVf/MVfXPjM2972tqVzW6vH1iHctn2c+pyp6DGOOG8OPZc5YS7r22KKrC8ct52ySmZKuMAzeKK9uow+Qb63d8jOje8Lx7k2+9qDh/bTFQqFwi6ooOyMArMCTi4i56TLUCV7xzvecXlv7KMe9ajlPVPt/bMCs4z0jKc+9anLvviCN4V5IqqgA1UFPR8n1CYIDsvE++iP/uiT+973vss7fbSG8e99O9TnGKguFIYgQUi2vnZDufqKkeSO9Nve9rYnn/qpn7pMMGIoDVWAFY4fx1L1P4egQ+H4oNqBnRA8k3UMba91yNE9xxUm7T1bKia0saQrqJoJOdzyn8SAf/Wv/tVS13JNyjrkvUeP5QBUiXHsOJTed2zXmcxB3nuuKjEObK2MIyk66KkqWOeCD/uwD1urY/d6zhzmM5e5zAlzokkvWV84PjslrzG/knMcP8QYX/GKVywDsypm475MSV7f8R3fMah7zonvC9fEMa7NPvbgIf10hUKhsAsqKDsjyBByaAwpz7LcZETd+MY3vsa9EDkw+4Vf+IXL+2UDKmsdZEOZUoXDQ/BdC42qgj67TijZpRS861znOst7nSl8+3Csn5VAdaHACHJeyVIFe0I7/Vvc4hYX7rkJvPKVr1waXA95yEOWjoEwkspYOj841qr/OQQdCseJId1CG7uv+IqvWDrrn/zkJ6+sZl3Vvo68VlHQXm8yxJOtvvWBH/iB5+palNPQ+471OpNDyvuXvexlF+yChz/84cskBODcvvnNb76sOIqK73ivRIN73ete11jXXs+Zih7jmMtc5oQ50WRI/k6V9YXjs1Py2rtT+Da3uc3yflEBWFWGOTB72WWXLdvfqkC81a1udSEANie+L1wTx7g2p7UHT8tPVygUClNQQdmZIQ7TocCstsS3vOUtT/7jf/yP17i4HH76p396mTmk0jKgvfF1r3vdjRnvhcOhqqDPvhNKSzdtBVWr54DnPhzsZyFQXTi/eO5zn7tMEpA89MEf/MEn3/qt37r8+bOe9ayTD/qgDzp5zGMec8EAW4Uyks4Xjq3q/1iDzIV5IJ/z7gyE2AN/9Ed/dHL/+99/qTvl+7La+2HxXKsvSCCgI1xxxRXXeuc//dM/DbbVDr1iTkG/Y9D7jvk6k0PJ+7/+679etjLUGvGSSy5Z3uXtbr6A5GVJsu7p81lo94h393rOVPQYB56aw1zmhLmsb09ZXzg/dgq56uqyX/iFX1hWS2pxfaMb3ejkPve5zwV+4l950YtetJSpcZ7zE86F7wvzlUlndQ+epp+uUCgUxqCCsjPEukPid37nd5b3haiufN3rXneN3/3Kr/zKNQ4plRqCWIV5o6qgz74TSuayFimyFd0LeN4D1YXzB5XYjEVt82X1ShbQVsk5BE984hOXd+A87nGPu8b9N2UUnS8ce9X/sQWZC/NB1gfwi+44dI7HP/7xF6ok3vCGNyyd9Z/0SZ+08s6s/Bz6kkoCDrB/+2//7cn3f//3X+DL+Jtu4R1tQFaF7HnWK3rrfcd4ncmc5D2bmS2BZrnjVL6nTwXZ3e52t6X9se/nTEWPccxlLnPCHGjSS9YXzo+d4s5N3S6uvPLK5b9/9md/djk3c1QRy284NI/g6znwfWEYx7Q2h9qD+/LTFQqFQg9UUPYMwr1SH/dxH7dUsOIegYxy6p09nNcq6GNyQnG+y2SU0ShD9bwHqgvnB5yl9mUYVQE86p70wJOe9KSl4fjN3/zNy8zVwvnFsVT9zynoUDgfoCfd5CY3WbZhe/SjH73cMyooQh/krGcfcMS2+6Rtc8j5xTkG9773vZdVC1ocxudUaH3u537ustImfvZjP/ZjS3k/lz14SPTS+479OpNDyvt4nn3hnk1OWW09c0JBJBxoBynx8ZGPfOTenjMVPcYxl7nMCXOkyRRZXzhuO0W15M/93M+dvOQlL7nwM8EmQXvnxMUXX7xMsgJnB37VxnWVzjonvi8c59oceg/29tMVCoVCL1RQ9gwHZlVhOMQY84Wzj/NWBX2MTigVJ1MVyGMKVBfOB5xDHEecA5IHApz597znPU/+8R//8cLPvv3bv32ZKFCZqucLx171fyxB5sK88UM/9EPLitZXv/rVy3//1E/91MkNbnCDpVPrP//n/3zyV3/1Vxf22BOe8ISVSZqcXWT2r//6ry/vHgu+pE8IzD7wgQ9cOvfuete7ntz2tre90BbT33Q0zuBCP73v2K4zmYO8X2Ub6E70RV/0RUvebp+Nv61n3je9njMVPcYxl7nMCXOlSS9ZXzg+O+V5z3veycd//MeffOmXfunJU57ylGvx8MMe9rCTBz/4wSdXX3318t+Pfexjl8E8P4/PzpXvC8e7NnPYg730tUKhUOiJCsqeYbzqVa86ue997zuroFRhGs5bFfQxOaF64BgD1YXzAe3Vbne72508//nPX/5bhaBkgauuuupasstnjk2WFc5X1f8cgg6F44f9whGnvTCe05IwKiHoB+7fcqcg3emiiy5a6gdvfvObr/GMVtb+7d/+7XK/haz2eXJaIFYVLLviXve617IVHn6OSoz4u/SL/eEYrjOZg7zPPMrOYEO88Y1vvCCDVYNzbgtUhLwW6PqO7/iOa8yj13Omosc48n2jh5zLnDCX9d2XrC8cn53ygz/4gyc3vOENl/LzLW95y+BnVAI6vwEvCYbpyBLIVxEcmu8L85VJ+8Ax7MFCoVDojQrKnnHEIV1OkuPBeauCPgYnVE9UoLpwlpANJk4iSSUc+Te60Y1OnvOc5yx/viozu4yt48axVv3PIehQOH4897nPXe4XupHqVdWt2gmrbPVHIoAKKfBvVVWS1R7+8IevvYPr7/7u704+7MM+7OTrvu7rTl7+8pef3OMe91gmfEmQkwQW9xNmx23+/8J+cVavM5mLvG9bdN/mNrdZBrE4sb/qq77qGs7tyy67bNkm8da3vvWyBWwOXPZ6zlT0GMdc5jInzIkm+5L1heOyU9wb+9Ef/dEX2hIH8j3w/gje3/72t1/6T+585zsveXuoWv7QfF+Yr0zqjWPZg4VCobAPVFD2CFDK+PHhvFVBn1Un1L5QgerCWUI2mCSTcLTe//7339gyr3C8OMaq/7kEHQrHD1Ut7/M+77PsCvKyl71s2Qqb8yruHXbdhcBqtMzGc4Kr2mBvs2dUWwkAqNR+zGMec6Ed8Zd92Zct75bNKBvj9HHWrjOZo7z3TM/+hV/4heX9cQ94wAOWe8j9yPEeXQ5e9KIXLRNC24rw3s+Zw3zmMpc54dA02besLxyPnXLFFVcsrxMgb4fO5fiZxCtXYzjLH/KQh1zg1UyDQ/N9YTWOdW2OYQ8WCoXCPlBB2UJhpjhvVdBnzQm1b1SgunCWkPfnpZdeevKxH/uxyzux/umf/umg4yocDsdU9T/HoEPhOMEZz1lFz8lQgc0ZH/di6TByv/vdb1k1oX2dloWb7ovLkESgLV7Adz7zMz9zWUFbODzO2nUmc5L3KsrudKc7nVx55ZXLf2sF+37v937LgJeqIjQdCmq0NO31nDnMZy5zmRMOTZPTkvWF47BT6JEXX3zx2s+84Q1vWLaEbZEDdofm+8JqHPvanPU9WCgUCvtABWULhRnjvFUonDUn1L5RgerCWULen5dccsmyfRbH7NVXX33QcRUOh2Oq+p9T0KFwvFBBgF9e8pKXLFtjBz73cz/35J73vOfSuapV3ZOf/OTlPpEs8Cmf8ikX2tft6qT/h3/4h2Ult+pud33NvdriPOGsXWdyKHn/mte8Zlntbc8EfuAHfuDkrW996zJRRiAjWn6S0e7//vzP//xr2Vi9njMVPcYxl7nMCXOjyWnL+sLZtlN0a3nf933fC/6Rdv3xqSTByy+//Fq+hDnxfWG+Muk0cJb3YKFQKOwD11kUCoXZ4r3e670W5wl3uMMdFs985jMXv/M7v7P4xm/8xsWf/MmfXOP3173udRfnCf/+3//7xQ/8wA8sfvM3f3Px3d/93Yvf//3fv/C7O9/5zkt6/PM///Py3/e4xz0Wd7zjHQ842sKx4lnPetbiD/7gDzZ+LvPjT/7kTy4+4AM+YPHyl798cf3rX/8URlmYIz7u4z5uyT83vvGNFy996UsXv/u7v3vhd5/zOZ+z+Oqv/urFG9/4xsXP//zPX/j5D/3QDy1e97rXLb8zJ9z+9rdf/I//8T8Wr3jFKxbPfvazF//wD/9wjbk86lGPWrz97W9fPPWpT1287GUvu/C7z/qsz1p8+Id/+OKtb33rgUZeOEv4sR/7scVd73rXxdd93dctXvSiFy1/duWVVy6uuOKKxf3vf//F9a53vcV7v/d7Lx75yEcuf/4zP/Mzi1/8xV9c/uw973nP4jrX2d60k5z7G7/xG4snPelJi3e/+91LXcPzQ44XDq8TP/3pT1/c6EY3WtziFreY/XIcQt4///nPX+4L7/2jP/qjxb/8y78sf36/+91vcdOb3nTxoz/6o4tLLrlkce9733v589vc5jaLT/mUT1nc7GY3W/J/7+dMRY9xzGUuc8IcaXKasv7YcR7slEsvvXQ53ssvv3z5b+sffAzveMc7Fr/927+9uPjii6/B9w94wANmxfeF+cqkKTgPe7BQKBT2gr2EeguFQmECztudusdWLVE4Hqj6c3/zIx/5yGVFy65ZsLWHC8dW9V+t5Qv7Qt4HqiJ0DlGZ7T6x5zznORdk6pBcHStr3/nOdy51jPh+VcrOD2ftOpPTkvc/+IM/eHLDG97w5Id/+IdP3vKWtwx+RqvXu93tbhfoR492j2fAz3o9Zyp6jOPZz372LOYyJ8xlfQ8t648V58FOcQY4m3Veud71rrds/eru2MCb3/zmk7vf/e4nd7nLXS7MbY58Xzg5yrU5D3uwUCgU9oX38p/9hHsLhUJhPIgmlcIyBysbeLH49V//9cUznvGMZSVx0aNw2tm8j33sY5cZuw9/+MMXt7rVrTZ+R9WVbP6ArNjzVuleuCZk8MvYV9H/lV/5lcus74yzxCOvec1rFve9730XH//xH7+sYrntbW974Xe/+qu/urjTne50YS4veMELlnumOhkUtkHeBypjfuInfmJZOfF93/d9y5/vUycqfWv+OvFZwb7lveraL/qiL1o8+tGPXr6npVO4N77ne75nqTerxL366qsXb3vb2xavfe1rl+/2md/7vd/r8pypa9NjPiqTv/iLv/jgc5kTevHJPmhySFl/bDgvdsrf/M3fLDtoPfGJT1xWGNJB3/Wudy3+8i//csmjv/Irv7KcEx31S77kS2bJ9+cdc5ZJU3Be9mChUCj0Rml6hUJhlgjFtAzS/4tP+IRPWBpibbuiQmFfCMPwnve85+Lxj3/80mH0tKc9bdlmadP3wsjSag3KyCocU3v6ai1f2BdyazftLQVZXv3qVy9b2b3zne/cq05U+tZ8MTcH7KHl/Zve9KalnvGZn/mZ12jlmOnk/y+77LLFgx70oGXLRy3oBStij/l9r+dMRY9x/Nmf/dks5jInzGV95ybrjwXnzU65yU1usnjoQx+6uOqqqxaf+qmfuvinf/qnxQd90Act7nWvey1e+cpXXmht/eY3v3m2fH/eMWeZNAbnbQ8WCoVCd+ytBrdQKBQKe2tjVyicBp/l9kLaLX34h3/4ySMe8YiV7Ykyfz7jGc84ed/3fd9Zt6ItnD6OqT19tZYv7AtZ9l5yySUnt7/97U+e+cxnnlx99dVF9MLJeZf33/Zt33Zy8cUXr/3MG97whpP/9b/+17V+nlt093rOVPQYx1zmMiecBZqUrB+HY7JTfuAHfuDk9a9//c7fa+Vq0OIs8P15xTGtzTHtwUKhUDgUKgWvUCgUzhDmlB1ZOE6oxA4+01oocO9733vxLd/yLSuzYHM7Je3XHvOYxyye+9znVtvWwtFW/asGe/rTn7640Y1utLjFLW5x6OEUzgCe9axnLf7gD/5gpyqqn/zJn1y2Knz5y1++uP71r38KoywU5i3vtXT8+7//+8Xv//7vL//dPps+8iM/8iOLV7ziFdf6+fWud73uz5nDfOYylznhkDQpWb8/HJOd4lx/4AMfuLyiaFN1YVud2FZTR6VhyYL54ljW5pj2YKFQKBwSFZQtFAqFQqGwRG4Z/uQnP3l5z5U/j3vc45YGmHs0w9gSjMrGVmtkcUi5N6dQOOb29McUZC7My/maA7O++5znPKeWqHDmsA95Ty+RqHD55Zcv/93K33e84x3Le20vvvjia41lH8+Zw3zmMpc54VA0KVm/PxybnaINsbNd8tU2bV8h3z0aCF0BShbMF8ewNse2BwuFQuGgOFiNbqFQKBQKhdkgtxN64hOfePL+7//+J1/zNV9z8sVf/MUnt771rU/ucIc7nLzrXe9a/v7Zz372yc1vfvOTL//yLz/58z//8wvfe9rTnnZy4xvf+OTHf/zHDzKHQuFQqNbyhW3wvOc97+RmN7vZ2tZuLULuBnKruELhPMpabRyf+tSnnlzvetc7ufTSS0/+7u/+7sLv3/zmN5/c/e53P7nLXe6ydq/0es4c5jOXucwJh6ZJyfr+ODY7Jc8Hv2xq+zr0vauuuupavytZME8cw9oc2x4sFAqFQ2M+PRAKhUKhUCgcDJG9+hu/8RuL1772tYsf/dEfXXzWZ33W8mevetWrFv/lv/yXxad92qctfuVXfmVxn/vcZ3H11VcvfuZnfmbxYR/2YcvP/Pqv//rim77pm5ZVYJX1WjhvmFMWe2F+iJZt97znPZf//tqv/drl3w9/+MMXt7rVrdZ+773f+72X//+Lv/iLSxkcLQoLhfMI+0gbxy/90i9d/J//838WT3ziExe3v/3tFx//8R+/eNe73rX4y7/8y+Vn6CpRbT60Z3o9Zw7zmctc5oRD0aRk/f5wTHZK8EnwHd1AleFjH/vYtbpB2/71UY961OKXfumXLrR/LVkwXxzD2hzTHiwUCoU54L1EZg89iEKhUCgUCofHC17wgsW3f/u3L97+9rcvXvjCFy5ud7vbLX/OMLzqqquWToInPelJi8/7vM+71nff9KY3Ldsu3fa2tz3AyAuFQmGeaJ2v4A4tzldOqbHO10LhvIPOoTXiU57ylMXf/M3fLG5605su98dDH/rQ5V57z3ves9U9fL2eM4f5zGUuc8Jp0aRk/f5xDHaK4Gu0f33nO9+5eJ/3eZ8Lv3v2s5+9+Pqv//pB3WDoPs517V9LFswXZ3ltjmEPFgqFwlwwT0lfKBQKhULh1MEg/NAP/dBl9uuLX/ziC4YWA/EOd7jD0pD68z//82t8J5wEt7jFLWrFCoVCYYXz9d3vfveFoOy9733vpQOL8xW2cb4K5FZAtnDsEGS4853vvPiYj/mYjZ99//d//2Wlkb2R9xo885nPXHzyJ3/y5OfYp1Oc4z3m4xl3utOdtnJk73Mux8gnvWhSsv50cNbtlPY+Th0wBGXt7W/4hm9Y3scJdANjftjDHnZBN/BvfG9+gnmb7uM8L7JgLpibTNoXzvoeLBQKhTnh/0n/QqFQKBQK5xoMfy2F7n73uy+uuOKKxXOe85wLv7vhDW+4uOiii65hOEK1bS0UCoXNztdLL710+edxj3vc0gnH+fot3/Iti5/4iZ9YPP3pT19WTbRydZtqmELhWPDyl7988cAHPnCph+T9sA7R9CvrJp7zoAc9aPJzYEr7yB7ziWd8//d//0Hncox8Ar1aFpesPx2cZTslJ1upJKQLRKKFNrDa2Ereoht867d+67IK0d9vfvObL/D9Ax7wgMUTnvCExbd927dtpRMcuyyYC+Ymk/aJs7wHC4VCYW6o9sWFQqFQKBSugT/90z9dZmf/4R/+4eIud7nL0mnwy7/8y4vXv/71i9/7vd+bdQZvoVAozM35yrGqLd3//t//eylDVca4f8t9sRxa3/iN37j49E//9OXn/vW//tfL7wnUqpwRjKmAbOG84PnPf/6ytfcll1yy8c7lof0WlUY//MM/3OU5Ux3kPeajmuryyy8/+FyOkU+m0qRk/WFwlu0U93F+13d91/Ie2fY+zhvd6EbL+zgjKct9nD/5kz+5DHK5j/M//If/sLj+9a+/+LIv+7KSBTPDXGTSaeEs78FCoVCYDdwpWygUCoVCoZDxp3/6pyef//mff3Kd61zn5LM+67NOvvM7v/PC797znvcUsQqFQmEDXv3qV59cdtllJy996Usv/OzXfu3XTm53u9ud3PnOd77ws2c84xlLefvP//zPy3+/6lWvOrnJTW5y8oIXvKBoXDgX+Jd/+ZcL//+85z3v5MM//MNPHvGIR5z84R/+4dbfu+qqq7o9Zyp6jOMXfuEXZjGXOWEu69uiZP3p4yzaKT/yIz9y8nEf93EnH/mRH3ny2te+9hrj/bmf+7mTj/mYjzl58YtfPMi/5vu6171uVnxfmK9MOg2cxT1YKBQKc0K1Ly4UCoVCoXAtuPflaU972rI90Q1ucIPl/TGBti1RoVAoFK6JF7zgBYuv+IqvWFbARPUraFHoPri/+7u/W7zkJS9Z/sznXvSiF12QrR/yIR+yvGvuS77kS4qshaNHVAupEgIVZI9//OOXrb3pIavaQbZ3L3/2Z3/24rd+67e6POc3f/M3Dzof7SE/53M+Z1kdd8i5HCuf9KRJyfrD4CzaKXEf55ve9KblfZyBdfdxuu4A/9IjVCPOhe8L85VJp4WzuAcLhUJhTqieAoVCoVAoFAZxs5vdbPHd3/3di0c84hHLOw3f+c53Lu53v/vV3TCFQqGwpfP1ta997dL5ervb3W6j8zUcdRxdhcJ5gIBDOG/dpxitG+9973svHd1f//Vfv/x32w6ydWq7e1mbX/uOrtLjOYeaz/d+7/cuvvZrv3Y5jo/92I+98JnTnsux80kvlKw/HM6anRL3cbrOwH2cAq33uc99Vt7HOWe+P++otTmbe7BQKBRmhUOX6hYKhUKhUJg3/uRP/uTkkz/5k08+7/M+7+Ttb3/7oYdTKBQKZwJ//ud/vpSbd7rTnU6e/exnX/j5P/7jP578u3/3706+53u+56DjKxQOidy+UdvDz/mczzn54i/+4pNv/MZvvNDK+1nPetayHeQjH/nIwXaQWn9/wAd8wMmP//iPd33Ooebzvd/7vRfGcci5HDuf9EbJ+sPirNkpxvvZn/3ZJx/90R99ct/73nfJ19rA+ve73/3uM8P35xW1Nmd/DxYKhcIcUEHZQqFQKBQKW90b82d/9mdFqUKhUOjsfC0UzrNT+4lPfOLJ+7//+598zdd8zTLocOtb3/rkDne4w8m73vWu5e8lNNz85jc/+fIv//Jl8CvwtKc97eTGN77xhYBDr+ccaj5PfepTL4zjkHM5dj7ZF0rWHxZnzU5Zdx9n1g3mzvfnDWdJJp02ztoeLBQKhUOjgrKFQqFQKBQKhUKhcADn63ve856ie+Hc4tWvfvXJZZdddvLSl770ws9+7dd+7eR2t7vdyZ3vfOdrVHzZQ1Eh9qpXverkJje5yckLXvCCrs+Zw3zmMpc54azQpGR9YRcIYKmA/YIv+IKT//k//+e1An9nhe/PI2ptCoVCoTAV7+U/h26hXCgUCoVCoVAoFArHCvfHPuQhD1lc73rXW1x66aWLyy677Fp3vxUK5wkveMELFt/+7d++ePvb37544QtfeOHeZXclXnXVVct7Ep/0pCctPu/zPu9a333Tm960vJf5tre9bbfnzGE+r3vd62YxlzlhLuu7LUrWF3bBH//xHy/v43QXJ73AfZxnke/PE2ptCoVCodAD/+8W+UKhUCgUCoVCoVAodMfNbnazxXd/93cv3v3udy+e9axnLf9ABWQL5xV3vOMdFx/6oR+6DCC8+MUvvvDz6173uos73OEOy6CCAFdG5JPf4ha3uBBw6PWcOcxnLnOZE84aTUrWF3bBLW95y8XTn/70xdVXX73k77//+78/k3x/nlBrUygUCoUeqKBsoVAoFAqFQqFQKBzI+VoonEfc6la3WjzjGc9Y3P3ud19cccUVi+c85zkXfnfDG95wcdFFFy2uc51ruiuGkhh6PWcO85nLXOaEs0iTkvWFXfARH/ERi+c///lL/eADPuADzizfnxfU2hQKhUKhB6p9caFQKBQKhUKhUCicElS+cKaqqCoUzjv+9E//dPGwhz1s8Yd/+IeLu9zlLssKr1/+5V9evP71r1/83u/93rLl92k+Zyp6jGMuc5kTziJNStYXziPfnxfU2hQKhUJhCqpStlAoFAqFQqFQKBROCVoLVkC2UPh/VWL//b//98Wtb33rxQ/+4A8uXvayly0+5VM+ZfGGN7xhGXBwh+JpPmcqeoxjLnOZE84iTUrWF84j358X1NoUCoVCYQoqrapQKBQKhUKhUCgUCoXCwYJXT3va05YBBoEGdykG2hadp/GcqegxjrnMZU4omhTOI4rv54tam0KhUCiMRbUvLhQKhUKhUCgUCoVCoXBQ/PEf//HiEY94xOKd73zn4rLLLlvc7373O+hzpqLHOOYylzmhaFI4jyi+ny9qbQqFQqGwK85nimWhUCgUCoVCoVAoFAqF2eCWt7zl4ulPf/ri6quvXrz4xS9e/P3f//1BnzMVPcYxl7nMCUWTwnlE8f18UWtTKBQKhV1RlbKFQqFQKBQKhUKhUCgUZoE3velNyxa9U+9e7vWcqegxjrnMZU4omhTOI4rv54tam0KhUChsiwrKFgqFQqFQKBQKhUKhUCgUCoVCoVAoFAqFwh5R7YsLhUKhUCgUCoVCoVAoFAqFQqFQKBQKhUJhj6igbKFQKBQKhUKhUCgUCoVCoVAoFAqFQqFQKOwRFZQtFAqFQqFQKBQKhUKhUCgUCoVCoVAoFAqFPaKCsoVCoVAoFAqFQqFQKBQKhUKhUCgUCoVCobBHVFC2UCgUCoVCoVAoFAqFQqFQKBQKhUKhUCgU9ogKyhYKhUKhUCgUCoVCoVAoFAqFQqFQKBQKhcIeUUHZQqFQKBQKhUKhUCgUCoVCoVAoFAqFQqFQ2CMqKFsoFAqFQqFQKBQKhUKhUCgUCoVCoVAoFAp7RAVlC4VCoVAoFAqFQqFQKBQKhUKhUCgUCoVCYbE//H97OUyaWtGcPQAAAABJRU5ErkJggg==", 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" ] @@ -10403,16 +8209,16 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 49, "metadata": {}, "outputs": [], "source": [ - "from samap.analysis import _KOG_TABLE" + "from samap._constants import KOG_TABLE" ] }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 50, "metadata": {}, "outputs": [ { @@ -10445,13 +8251,13 @@ " 'Z': 'Cytoskeleton'}" ] }, - "execution_count": 51, + "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "_KOG_TABLE" + "KOG_TABLE" ] } ], @@ -10471,7 +8277,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.16" + "version": "3.11.14" } }, "nbformat": 4, diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..4f700e7 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,163 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "sc-samap" +version = "2.0.2" +description = "The SAMap algorithm" +readme = "README.md" +license = "MIT" +requires-python = ">=3.11" +authors = [ + { name = "Alexander J. Tarashansky", email = "tarashan@stanford.edu" }, +] +keywords = [ + "scrnaseq", + "analysis", + "manifold", + "reconstruction", + "cross-species", + "mapping", + "single-cell", + "bioinformatics", +] +classifiers = [ + "Development Status :: 4 - Beta", + "Intended Audience :: Science/Research", + "License :: OSI Approved :: MIT License", + "Operating System :: OS Independent", + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3.12", + "Topic :: Scientific/Engineering :: Bio-Informatics", +] +dependencies = [ + "sc-sam>=2.0.0", + "numpy>=1.26.0", + "scipy>=1.11.0", + "scanpy>=1.10.0", + "numba>=0.59.0", + "h5py>=3.10.0", + "hnswlib>=0.8.0", + "leidenalg>=0.10.0", + "pandas>=2.0.0", + "networkx>=3.0", + "dill>=0.3.7", +] + +[project.optional-dependencies] +dev = [ + "pytest>=8.0", + "pytest-cov>=4.1", + "ruff>=0.2", + "mypy>=1.8", + "pre-commit>=3.6", +] +viz = [ + "matplotlib>=3.8", + "seaborn>=0.13", + "plotly>=5.18", +] +all = ["samap[dev,viz]"] + +[project.urls] +Homepage = "https://github.com/atarashansky/SAMap" +Documentation = "https://github.com/atarashansky/SAMap" +Repository = "https://github.com/atarashansky/SAMap" +Issues = "https://github.com/atarashansky/SAMap/issues" + +[tool.hatch.build] +exclude = [ + "example_data/", + "*.h5ad", + "*.h5", + "*.hdf5", + "tests/", + "docs/", +] + +[tool.hatch.build.targets.wheel] +packages = ["src/samap"] + +[tool.ruff] +target-version = "py311" +line-length = 100 +src = ["src", "tests"] + +[tool.ruff.lint] +select = [ + "E", # pycodestyle errors + "W", # pycodestyle warnings + "F", # Pyflakes + "I", # isort + "B", # flake8-bugbear + "C4", # flake8-comprehensions + "UP", # pyupgrade + "SIM", # flake8-simplify + "RUF", # Ruff-specific rules + "NPY", # NumPy-specific rules +] +ignore = [ + "E501", # line too long (handled by formatter) + "B007", # loop control variable not used + "B008", # do not perform function calls in argument defaults + "B905", # zip without explicit strict + "NPY002", # legacy numpy random (not critical) +] + +[tool.ruff.lint.isort] +known-first-party = ["samap"] + +[tool.ruff.lint.per-file-ignores] +"tests/**/*.py" = [ + "S101", # assert statements are fine in tests +] + +[tool.mypy] +python_version = "3.11" +ignore_missing_imports = true +check_untyped_defs = false +disallow_untyped_defs = false +exclude = [ + "tests/", + "build/", + "dist/", +] + +[tool.pytest.ini_options] +testpaths = ["tests"] +python_files = ["test_*.py"] +python_functions = ["test_*"] +addopts = [ + "-v", + "--tb=short", + "--strict-markers", +] +markers = [ + "slow: marks tests as slow (deselect with '-m \"not slow\"')", + "integration: marks tests as integration tests", + "e2e: marks tests as end-to-end tests", +] +filterwarnings = [ + "ignore::DeprecationWarning", +] + +[tool.coverage.run] +source = ["src/samap"] +branch = true +omit = [ + "*/tests/*", + "*/__init__.py", +] + +[tool.coverage.report] +exclude_lines = [ + "pragma: no cover", + "def __repr__", + "raise NotImplementedError", + "if TYPE_CHECKING:", + "if __name__ == .__main__.:", +] +show_missing = true +fail_under = 10 diff --git a/samap/__init__.py b/samap/__init__.py deleted file mode 100755 index ffe95ee..0000000 --- a/samap/__init__.py +++ /dev/null @@ -1,11 +0,0 @@ -import pandas as pd -import scipy as sp -import numpy as np -import samalg.utilities as ut -import warnings -import scanpy as sc -__version__ = "1.0.15" - - -def q(x): - return np.array(list(x)) diff --git a/samap/analysis.py b/samap/analysis.py deleted file mode 100644 index d36e1ab..0000000 --- a/samap/analysis.py +++ /dev/null @@ -1,1603 +0,0 @@ -import sklearn.utils.sparsefuncs as sf -from . import q, ut, pd, sp, np, warnings, sc -from .utils import to_vo, to_vn, substr, df_to_dict, sparse_knn, prepend_var_prefix -from samalg import SAM -from scipy.stats import rankdata -import networkx as nx - -def _log_factorial(n): - return np.log(np.arange(1,n+1)).sum() -def _log_binomial(n,k): - return _log_factorial(n) - (_log_factorial(k) + _log_factorial(n-k)) - -def GOEA(target_genes,GENE_SETS,df_key='GO',goterms=None,fdr_thresh=0.25,p_thresh=1e-3): - """Performs GO term Enrichment Analysis using the hypergeometric distribution. - - Parameters - ---------- - target_genes - array-like - List of target genes from which to find enriched GO terms. - GENE_SETS - dictionary or pandas.DataFrame - Dictionary where the keys are GO terms and the values are lists of genes associated with each GO term. - Ex: {'GO:0000001': ['GENE_A','GENE_B'], - 'GO:0000002': ['GENE_A','GENE_C','GENE_D']} - Make sure to include all available genes that have GO terms in your dataset. - - ---OR--- - - Pandas DataFrame with genes as the index and GO terms values. - Ex: 'GENE_A','GO:0000001', - 'GENE_A','GO:0000002', - 'GENE_B','GO:0000001', - 'GENE_B','GO:0000004', - ... - If `GENE_SETS` is a pandas DataFrame, the `df_key` parameter should be the name of the column in which - the GO terms are stored. - df_key - str, optional, default 'GO' - The name of the column in which GO terms are stored. Only used if `GENE_SETS` is a DataFrame. - goterms - array-list, optional, default None - If provided, only these GO terms will be tested. - fdr_thresh - float, optional, default 0.25 - Filter out GO terms with FDR q value greater than this threshold. - p_thresh - float, optional, default 1e-3 - Filter out GO terms with p value greater than this threshold. - - Returns: - ------- - enriched_goterms - pandas.DataFrame - A Pandas DataFrame of enriched GO terms with FDR q values, p values, and associated genes provided. - """ - - # identify all genes found in `GENE_SETS` - - if isinstance(GENE_SETS,pd.DataFrame): - print('Converting DataFrame into dictionary') - genes = np.array(list(GENE_SETS.index)) - agt = np.array(list(GENE_SETS[df_key].values)) - idx = np.argsort(agt) - genes = genes[idx] - agt = agt[idx] - bounds = np.where(agt[:-1]!=agt[1:])[0]+1 - bounds = np.append(np.append(0,bounds),agt.size) - bounds_left=bounds[:-1] - bounds_right=bounds[1:] - genes_lists = [genes[bounds_left[i]:bounds_right[i]] for i in range(bounds_left.size)] - GENE_SETS = dict(zip(np.unique(agt),genes_lists)) - all_genes = np.unique(np.concatenate(list(GENE_SETS.values()))) - all_genes = np.array(all_genes) - - # if goterms is None, use all the goterms found in `GENE_SETS` - if goterms is None: - goterms = np.unique(list(GENE_SETS.keys())) - else: - goterms = goterms[np.in1d(goterms,np.unique(list(GENE_SETS.keys())))] - - # ensure that target genes are all present in `all_genes` - _,ix = np.unique(target_genes,return_index=True) - target_genes=target_genes[np.sort(ix)] - target_genes = target_genes[np.in1d(target_genes,all_genes)] - - # N -- total number of genes - N = all_genes.size - - probs=[] - probs_genes=[] - counter=0 - # for each go term, - for goterm in goterms: - if counter%1000==0: - pass; #print(counter) - counter+=1 - - # identify genes associated with this go term - gene_set = np.array(GENE_SETS[goterm]) - - # B -- number of genes associated with this go term - B = gene_set.size - - # b -- number of genes in target associated with this go term - gene_set_in_target = gene_set[np.in1d(gene_set,target_genes)] - b = gene_set_in_target.size - if b != 0: - # calculate the enrichment probability as the cumulative sum of the tail end of a hypergeometric distribution - # with parameters (N,B,n,b) - n = target_genes.size - num_iter = min(n,B) - rng = np.arange(b,num_iter+1) - probs.append(sum([np.exp(_log_binomial(n,i)+_log_binomial(N-n,B-i) - _log_binomial(N,B)) for i in rng])) - else: - probs.append(1.0) - - #append associated genes to a list - probs_genes.append(gene_set_in_target) - - probs = np.array(probs) - probs_genes = np.array([';'.join(x) for x in probs_genes]) - - # adjust p value to correct for multiple testing - fdr_q_probs = probs.size*probs / rankdata(probs,method='ordinal') - - # filter out go terms based on the FDR q value and p value thresholds - filt = np.logical_and(fdr_q_probs0: - self.DICT[c] = x[ff] - - if limit_reference: - all_genes = np.unique(np.concatenate(substr(np.concatenate(list(self.DICT.values())),';'))) - else: - all_genes = np.unique(np.array(list(A.index))) - - for d in GENE_SETS.keys(): - GENE_SETS[d] = GENE_SETS[d][np.in1d(GENE_SETS[d],all_genes)] - - self.gene_pairs = gene_pairs - self.CAT_NAMES = np.unique(q(RES['GO'])) - self.GENE_SETS = GENE_SETS - self.RES = RES - - def calculate_enrichment(self,verbose=False): - """ Calculates the functional enrichment. - - Parameters - ---------- - verbose - bool, optional, default False - If False, function does not log progress to output console. - - Returns - ------- - ENRICHMENT_SCORES - pandas.DataFrame (cell types x function categories) - Enrichment scores (-log10 p-value) for each function in each cell type. - - NUM_ENRICHED_GENES - pandas.DataFrame (cell types x function categories) - Number of enriched genes for each function in each cell type. - - ENRICHED_GENES - pandas.DataFrame (cell types x function categories) - The IDs of enriched genes for each function in each cell type. - """ - DICT = self.DICT - RES = self.RES - CAT_NAMES = self.CAT_NAMES - GENE_SETS = self.GENE_SETS - pairs = np.array(list(DICT.keys())) - all_nodes = np.unique(np.concatenate(substr(pairs,';'))) - - CCG={} - P=[] - for ik in range(len(all_nodes)): - genes=[] - nodes = all_nodes[ik] - for j in range(len(pairs)): - n1,n2 = pairs[j].split(';') - if n1 == nodes or n2 == nodes: - g1,g2 = substr(DICT[pairs[j]],';') - genes.append(np.append(g1,g2)) - if len(genes) > 0: - genes = np.concatenate(genes) - genes = np.unique(genes) - else: - genes = np.array([]) - CCG[all_nodes[ik]] = genes - - HM = np.zeros((len(CAT_NAMES),len(all_nodes))) - HMe = np.zeros((len(CAT_NAMES),len(all_nodes))) - HMg = np.zeros((len(CAT_NAMES),len(all_nodes)),dtype='object') - for ii,cln in enumerate(all_nodes): - if verbose: - print(f'Calculating functional enrichment for cell type {cln}') - - g = CCG[cln] - - if g.size > 0: - gi = g[np.in1d(g,q(RES.index))] - ix = np.where(np.in1d(q(RES.index),gi))[0] - res = RES.iloc[ix] - goterms = np.unique(q(res['GO'])) - goterms = goterms[goterms!='S'].flatten() - if goterms.size > 0: - result = GOEA(gi,GENE_SETS,goterms=goterms,fdr_thresh=100,p_thresh=100) - - lens = np.array([len(np.unique(x.split(';'))) for x in result['genes'].values]) - F = -np.log10(result['p_value']) - gt,vals = F.index,F.values - Z = pd.DataFrame(data=np.arange(CAT_NAMES.size)[None,:],columns=CAT_NAMES) - if gt.size>0: - HM[Z[gt].values.flatten(),ii] = vals - HMe[Z[gt].values.flatten(),ii] = lens - HMg[Z[gt].values.flatten(),ii] = [';'.join(np.unique(x.split(';'))) for x in result['genes'].values] - - #CAT_NAMES = [_KOG_TABLE[x] for x in CAT_NAMES] - SC = pd.DataFrame(data = HM,index=CAT_NAMES,columns=all_nodes).T - SCe = pd.DataFrame(data = HMe,index=CAT_NAMES,columns=all_nodes).T - SCg = pd.DataFrame(data = HMg,index=CAT_NAMES,columns=all_nodes).T - SCg.values[SCg.values==0]='' - - self.ENRICHMENT_SCORES = SC - self.NUM_ENRICHED_GENES = SCe - self.ENRICHED_GENES = SCg - - return self.ENRICHMENT_SCORES,self.NUM_ENRICHED_GENES,self.ENRICHED_GENES - - def plot_enrichment(self,cell_types = [], pval_thr=2.0,msize = 50): - """Create a plot summarizing the functional enrichment analysis. - - Parameters - ---------- - cell_types - list, default [] - A list of cell types for which enrichment scores will be plotted. If empty (default), - all cell types will be plotted. - - pval_thr - float, default 2.0 - -log10 p-values < 2.0 will be filtered from the plot. - - msize - float, default 50 - The marker size in pixels for the dot plot. - - Returns - ------- - fig - matplotlib.pyplot.Figure - ax - matplotlib.pyplot.Axes - """ - import colorsys - import seaborn as sns - import matplotlib - matplotlib.rcParams['pdf.fonttype'] = 42 - matplotlib.rcParams['ps.fonttype'] = 42 - from matplotlib.collections import PatchCollection - from matplotlib.patches import Rectangle - from matplotlib import cm,colors - import matplotlib.pyplot as plt - from scipy.cluster.hierarchy import linkage, dendrogram - - SC = self.ENRICHMENT_SCORES - SCe = self.NUM_ENRICHED_GENES - SCg = self.ENRICHED_GENES - - if len(cell_types) > 0: - SC = SC.T[cell_types].T - SCe = SCe.T[cell_types].T - SCg = SCg.T[cell_types].T - - CAT_NAMES = self.CAT_NAMES - gc_names = np.array(CAT_NAMES) - - SC.values[SC.values0)]=0.15 - - fig,ax = plt.subplots(); - fig.set_size_inches((7*SC.shape[0]/SC.shape[1],7)) - - scat=ax.scatter(x,y,c=co,s=ms,cmap='seismic',edgecolor='k',linewidth=0.5,vmin=3) - cax = fig.colorbar(scat,pad=0.02); - ax.set_yticks(np.arange(SC.shape[1])) - ax.set_yticklabels(SC.columns,ha='right',rotation=0) - ax.set_xticks(np.arange(SC.shape[0])) - ax.set_xticklabels(SC.index[::-1],ha='right',rotation=45) - ax.invert_yaxis() - ax.invert_xaxis() - #ax.figure.tight_layout() - return fig,ax - -def sankey_plot(M,species_order=None,align_thr=0.1,**params): - """Generate a sankey plot - - Parameters - ---------- - M: pandas.DataFrame - Mapping table output from `get_mapping_scores` (second output). - - align_thr: float, optional, default 0.1 - The alignment score threshold below which to remove cell type mappings. - - species_order: list, optional, default None - Specify the order of species (left-to-right) in the sankey plot. - For example, `species_order=['hu','le','ms']`. - - Keyword arguments - ----------------- - Keyword arguments will be passed to `sankey.opts`. - """ - if species_order is not None: - ids = np.array(species_order) - else: - ids = np.unique([x.split('_')[0] for x in M.index]) - - if len(ids)>2: - d = M.values.copy() - d[d d[data[i,1].split('_')[0]]: - data[i,:]=data[i,::-1] - R = pd.DataFrame(data = data,columns=['source','target']) - - R['Value'] = values - else: - d = M.values.copy() - d[d expr_thr) * ( - X2.mean(0).A.flatten() > expr_thr - ) - - w1 = sam1.adata.var["weights"][g1].values.copy() - w2 = sam2.adata.var["weights"][g2].values.copy() - w1[w1 < 0.2] = 0 - w2[w2 < 0.2] = 0 - w1[w1 > 0] = 1 - w2[w2 > 0] = 1 - return val * w1 * w2 * min_expr, to_vn(np.array([g1,g2]).T) - -def find_cluster_markers(sam, key, inplace=True): - """ Finds differentially expressed genes for provided cell type labels. - - Parameters - ---------- - sam - SAM object - - key - str - Column in `sam.adata.obs` for which to identifying differentially expressed genes. - - inplace - bool, optional, default True - If True, deposits enrichment scores in `sam.adata.varm[f'{key}_scores']` - and p-values in `sam.adata.varm[f'{key}_pvals']`. - - Otherwise, returns three pandas.DataFrame objects (genes x clusters). - NAMES - the gene names - PVALS - the p-values - SCORES - the enrichment scores - """ - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - - a,c = np.unique(q(sam.adata.obs[key]),return_counts=True) - t = a[c==1] - - adata = sam.adata[np.in1d(q(sam.adata.obs[key]),a[c==1],invert=True)].copy() - sc.tl.rank_genes_groups( - adata, - key, - method="wilcoxon", - n_genes=sam.adata.shape[1], - use_raw=False, - layer=None, - ) - - sam.adata.uns['rank_genes_groups'] = adata.uns['rank_genes_groups'] - - NAMES = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["names"]) - PVALS = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["pvals"]) - SCORES = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["scores"]) - if not inplace: - return NAMES, PVALS, SCORES - dfs1 = [] - dfs2 = [] - for i in range(SCORES.shape[1]): - names = NAMES.iloc[:, i] - scores = SCORES.iloc[:, i] - pvals = PVALS.iloc[:, i] - pvals[scores < 0] = 1.0 - scores[scores < 0] = 0 - pvals = q(pvals) - scores = q(scores) - - dfs1.append(pd.DataFrame( - data=scores[None, :], index = [SCORES.columns[i]], columns=names - )[sam.adata.var_names].T) - dfs2.append(pd.DataFrame( - data=pvals[None, :], index = [SCORES.columns[i]], columns=names - )[sam.adata.var_names].T) - df1 = pd.concat(dfs1,axis=1) - df2 = pd.concat(dfs2,axis=1) - - try: - sam.adata.varm[key+'_scores'] = df1 - sam.adata.varm[key+'_pvals'] = df2 - except: - sam.adata.varm.dim_names = sam.adata.var_names - sam.adata.varm.dim_names = sam.adata.var_names - sam.adata.varm[key+'_scores'] = df1 - sam.adata.varm[key+'_pvals'] = df2 - - for i in range(t.size): - sam.adata.varm[key+'_scores'][t[i]]=0 - sam.adata.varm[key+'_pvals'][t[i]]=1 - - - -def ParalogSubstitutions(sm, ortholog_pairs, paralog_pairs=None, psub_thr = 0.3): - """Identify paralog substitutions. - - For all genes in `ortholog_pairs` and `paralog_pairs`, this function expects the genes to - be prepended with their corresponding species IDs. - - Parameters - ---------- - sm - SAMAP object - - ortholog_pairs - n x 2 numpy array of ortholog pairs - - paralog_pairs - n x 2 numpy array of paralog pairs, optional, default None - If None, assumes every pair in the homology graph that is not an ortholog is a paralog. - Note that this would essentially result in the more generic 'homolog substitutions' rather - than paralog substitutions. - - The paralogs can be either cross-species, within-species, or a mix of both. - - psub_thr - float, optional, default 0.3 - Threshold for correlation difference between paralog pairs and ortholog pairs. - Paralog pairs that do not have greater than `psub_thr` correlation than their - corresponding ortholog pairs are filtered out. - - Returns - ------- - RES - pandas.DataFrame - A table of paralog substitutions. - - """ - if paralog_pairs is not None: - ids1 = np.array([x.split('_')[0] for x in paralog_pairs[:,0]]) - ids2 = np.array([x.split('_')[0] for x in paralog_pairs[:,1]]) - ix = np.where(ids1==ids2)[0] - ixnot = np.where(ids1!=ids2)[0] - - if ix.size > 0: - pps = paralog_pairs[ix] - - ZZ1 = {} - ZZ2 = {} - for i in range(pps.shape[0]): - L = ZZ1.get(pps[i,0],[]) - L.append(pps[i,1]) - ZZ1[pps[i,0]]=L - - L = ZZ2.get(pps[i,1],[]) - L.append(pps[i,0]) - ZZ2[pps[i,1]]=L - - keys = list(ZZ1.keys()) - for k in keys: - L = ZZ2.get(k,[]) - L.extend(ZZ1[k]) - ZZ2[k] = list(np.unique(L)) - - ZZ = ZZ2 - - L1=[] - L2=[] - for i in range(ortholog_pairs.shape[0]): - try: - x = ZZ[ortholog_pairs[i,0]] - except: - x = [] - L1.extend([ortholog_pairs[i,1]]*len(x)) - L2.extend(x) - - try: - x = ZZ[ortholog_pairs[i,1]] - except: - x = [] - L1.extend([ortholog_pairs[i,0]]*len(x)) - L2.extend(x) - - L = np.vstack((L2,L1)).T - pps = np.unique(np.sort(L,axis=1),axis=0) - - paralog_pairs = np.unique(np.sort(np.vstack((pps,paralog_pairs[ixnot])),axis=1),axis=0) - - - smp = sm.samap - - gnnm = smp.adata.varp["homology_graph_reweighted"] - gn = q(smp.adata.var_names) - - ortholog_pairs = np.sort(ortholog_pairs,axis=1) - - ortholog_pairs = ortholog_pairs[np.logical_and(np.in1d(ortholog_pairs[:,0],gn),np.in1d(ortholog_pairs[:,1],gn))] - if paralog_pairs is None: - paralog_pairs = gn[np.vstack(smp.adata.varp["homology_graph"].nonzero()).T] - else: - paralog_pairs = paralog_pairs[np.logical_and(np.in1d(paralog_pairs[:,0],gn),np.in1d(paralog_pairs[:,1],gn))] - - paralog_pairs = np.sort(paralog_pairs,axis=1) - - paralog_pairs = paralog_pairs[ - np.in1d(to_vn(paralog_pairs), np.append(to_vn(ortholog_pairs),to_vn(ortholog_pairs[:,::-1])), invert=True) - ] - - A = pd.DataFrame(data=np.arange(gn.size)[None, :], columns=gn) - xp, yp = ( - A[paralog_pairs[:, 0]].values.flatten(), - A[paralog_pairs[:, 1]].values.flatten(), - ) - xp, yp = np.unique( - np.vstack((np.vstack((xp, yp)).T, np.vstack((yp, xp)).T)), axis=0 - ).T - - xo, yo = ( - A[ortholog_pairs[:, 0]].values.flatten(), - A[ortholog_pairs[:, 1]].values.flatten(), - ) - xo, yo = np.unique( - np.vstack((np.vstack((xo, yo)).T, np.vstack((yo, xo)).T)), axis=0 - ).T - A = pd.DataFrame(data=np.vstack((xp, yp)).T, columns=["x", "y"]) - pairdict = df_to_dict(A, key_key="x", val_key="y") - Xp = [] - Yp = [] - Xo = [] - Yo = [] - for i in range(xo.size): - try: - y = pairdict[xo[i]] - except KeyError: - y = np.array([]) - Yp.extend(y) - Xp.extend([xo[i]] * y.size) - Xo.extend([xo[i]] * y.size) - Yo.extend([yo[i]] * y.size) - - orths = to_vn(gn[np.vstack((np.array(Xo), np.array(Yo))).T]) - paras = to_vn(gn[np.vstack((np.array(Xp), np.array(Yp))).T]) - orth_corrs = gnnm[Xo, Yo].A.flatten() - par_corrs = gnnm[Xp, Yp].A.flatten() - diff_corrs = par_corrs - orth_corrs - - RES = pd.DataFrame( - data=np.vstack((orths, paras)).T, columns=["ortholog pairs", "paralog pairs"] - ) - RES["ortholog corrs"] = orth_corrs - RES["paralog corrs"] = par_corrs - RES["corr diff"] = diff_corrs - RES = RES.sort_values("corr diff", ascending=False) - RES = RES[RES["corr diff"] > psub_thr] - orths = RES['ortholog pairs'].values.flatten() - paras = RES['paralog pairs'].values.flatten() - if orths.size > 0: - orthssp = np.vstack([np.array([x.split('_')[0] for x in xx]) for xx in to_vo(orths)]) - parassp = np.vstack([np.array([x.split('_')[0] for x in xx]) for xx in to_vo(paras)]) - filt=[] - for i in range(orthssp.shape[0]): - filt.append(np.in1d(orthssp[i],parassp[i]).mean()==1.0) - filt=np.array(filt) - return RES[filt] - else: - return RES - - -def convert_eggnog_to_homologs(sm, EGGs, og_key = 'eggNOG_OGs', taxon=2759): - """Gets an n x 2 array of homologs at some taxonomic level based on Eggnog results. - - Parameters - ---------- - smp: SAMAP object - - EGGs: dict of pandas.DataFrame, Eggnog output tables keyed by species IDs - - og_key: str, optional, default 'eggNOG_OGs' - The column name of the orthology group mapping results in the Eggnog output tables. - - taxon: int, optional, default 2759 - Taxonomic ID corresponding to the level at which genes with overlapping orthology groups - will be considered homologs. Defaults to the Eukaryotic level. - - Returns - ------- - homolog_pairs: n x 2 numpy array of homolog pairs. - """ - smp = sm.samap - - taxon = str(taxon) - EGGs = dict(zip(list(EGGs.keys()),list(EGGs.values()))) #copying - for k in EGGs.keys(): - EGGs[k] = EGGs[k].copy() - - Es=[] - for k in EGGs.keys(): - A=EGGs[k] - A.index=k+"_"+A.index - Es.append(A) - - A = pd.concat(Es, axis=0) - gn = q(smp.adata.var_names) - A = A[np.in1d(q(A.index), gn)] - - orthology_groups = A[og_key] - og = q(orthology_groups) - x = np.unique(",".join(og).split(",")) - D = pd.DataFrame(data=np.arange(x.size)[None, :], columns=x) - - for i in range(og.size): - n = orthology_groups[i].split(",") - taxa = substr(substr(n, "@", 1),'|',0) - if (taxa == "2759").sum() > 1 and taxon == '2759': - og[i] = "" - else: - og[i] = "".join(np.array(n)[taxa == taxon]) - - A[og_key] = og - - og = q(A[og_key].reindex(gn)) - og[og == "nan"] = "" - - X = [] - Y = [] - for i in range(og.size): - x = og[i] - if x != "": - X.extend(D[x].values.flatten()) - Y.extend([i]) - - X = np.array(X) - Y = np.array(Y) - B = sp.sparse.lil_matrix((og.size, D.size)) - B[Y, X] = 1 - B = B.tocsr() - B = B.dot(B.T) - B.data[:] = 1 - pairs = gn[np.vstack((B.nonzero())).T] - pairssp = np.vstack([q([x.split('_')[0] for x in xx]) for xx in pairs]) - return np.unique(np.sort(pairs[pairssp[:,0]!=pairssp[:,1]],axis=1),axis=0) - - -def CellTypeTriangles(sm,keys, align_thr=0.1): - """Outputs a table of cell type triangles. - - Parameters - ---------- - sm: SAMAP object - assumed to contain at least three species. - - keys: dictionary of annotation keys (`.adata.obs[key]`) keyed by species. - - align_thr: float, optional, default, 0.1 - Only keep triangles with minimum `align_thr` alignment score. - """ - - D,A = get_mapping_scores(sm,keys=keys) - x,y = A.values.nonzero() - all_pairsf = np.array([A.index[x],A.columns[y]]).T.astype('str') - alignmentf = A.values[x,y].flatten() - - alignment = alignmentf.copy() - all_pairs = all_pairsf.copy() - all_pairs = all_pairs[alignment > align_thr] - alignment = alignment[alignment > align_thr] - all_pairs = to_vn(np.sort(all_pairs, axis=1)) - - x, y = substr(all_pairs, ";") - ctu = np.unique(np.concatenate((x, y))) - Z = pd.DataFrame(data=np.arange(ctu.size)[None, :], columns=ctu) - nnm = sp.sparse.lil_matrix((ctu.size,) * 2) - nnm[Z[x].values.flatten(), Z[y].values.flatten()] = alignment - nnm[Z[y].values.flatten(), Z[x].values.flatten()] = alignment - nnm = nnm.tocsr() - - import networkx as nx - - G = nx.Graph() - gps=ctu[np.vstack(nnm.nonzero()).T] - G.add_edges_from(gps) - alignment = pd.Series(index=to_vn(gps),data=nnm.data) - all_triangles = [c for c in nx.enumerate_all_cliques(G) if len(c)==3] - Z = np.sort(np.vstack(all_triangles), axis=1) - DF = pd.DataFrame(data=Z, columns=[x.split("_")[0] for x in Z[0]]) - for i,sid1 in enumerate(sm.ids): - for sid2 in sm.ids[i:]: - if sid1!=sid2: - DF[sid1+';'+sid2] = [alignment[x] for x in DF[sid1].values.astype('str').astype('object')+';'+DF[sid2].values.astype('str').astype('object')] - DF = DF[sm.ids] - return DF - -def GeneTriangles(sm,orth,keys=None,compute_markers=True,corr_thr=0.3, psub_thr = 0.3, pval_thr=1e-10): - """Outputs a table of gene triangles. - - Parameters - ---------- - sm: SAMAP object which contains at least three species - - orths: (n x 2) ortholog pairs - - keys: dict of strings corresponding to each species annotation column keyed by species, optional, default None - If you'd like to include information about where each gene is differentially expressed, you can specify the - annotation column to compute differential expressivity from for each species. - - compute_markers: bool, optional, default True - Set this to False if you already precomputed differential expression for the input keys. - - corr_thr: float, optional, default, 0.3 - Only keep triangles with minimum `corr_thr` correlation. - - pval_thr: float, optional, defaul, 1e-10 - Consider cell types as differentially expressed if their p-values are less than `pval_thr`. - """ - FINALS = [] - - orth = np.sort(orth,axis=1) - orthsp = np.vstack([q([x.split('_')[0] for x in xx]) for xx in orth]) - - RES = ParalogSubstitutions(sm, orth, psub_thr = psub_thr) - if RES.shape[0] > 0: - op = to_vo(q(RES['ortholog pairs'])) - pp = to_vo(q(RES['paralog pairs'])) - ops = np.vstack([q([x.split('_')[0] for x in xx]) for xx in op]) - pps = np.vstack([q([x.split('_')[0] for x in xx]) for xx in pp]) - doPsubsAll=True - else: - doPsubsAll=False - gnnm = sm.samap.adata.varp["homology_graph_reweighted"] - gn = q(sm.samap.adata.var_names) - gnsp = q([x.split('_')[0] for x in gn]) - - import itertools - combs = list(itertools.combinations(sm.ids,3)) - for comb in combs: - A,B,C = comb - smp1 = SAM(counts=sm.samap.adata[np.logical_or(sm.samap.adata.obs['species']==A,sm.samap.adata.obs['species']==B)]) - smp2 = SAM(counts=sm.samap.adata[np.logical_or(sm.samap.adata.obs['species']==A,sm.samap.adata.obs['species']==C)]) - smp3 = SAM(counts=sm.samap.adata[np.logical_or(sm.samap.adata.obs['species']==B,sm.samap.adata.obs['species']==C)]) - - sam1=sm.sams[A] - sam2=sm.sams[B] - sam3=sm.sams[C] - A1,A2=A,B - B1,B2=A,C - C1,C2=B,C - - f1 = ((orthsp[:,0]==A1) * (orthsp[:,1]==A2) + (orthsp[:,0]==A2) * (orthsp[:,1]==A1)) > 0 - f2 = ((orthsp[:,0]==B1) * (orthsp[:,1]==B2) + (orthsp[:,0]==B2) * (orthsp[:,1]==B1)) > 0 - f3 = ((orthsp[:,0]==C1) * (orthsp[:,1]==C2) + (orthsp[:,0]==C2) * (orthsp[:,1]==C1)) > 0 - orth1 = orth[f1] - orth2 = orth[f2] - orth3 = orth[f3] - - - gnnm1 = sp.sparse.vstack(( - sp.sparse.hstack((sp.sparse.csr_matrix(((gnsp==A1).sum(),)*2),gnnm[gnsp==A1,:][:,gnsp==A2])), - sp.sparse.hstack((gnnm[gnsp==A2,:][:,gnsp==A1],sp.sparse.csr_matrix(((gnsp==A2).sum(),)*2))) - )).tocsr() - gnnm2 = sp.sparse.vstack(( - sp.sparse.hstack((sp.sparse.csr_matrix(((gnsp==B1).sum(),)*2),gnnm[gnsp==B1,:][:,gnsp==B2])), - sp.sparse.hstack((gnnm[gnsp==B2,:][:,gnsp==B1],sp.sparse.csr_matrix(((gnsp==B2).sum(),)*2))) - )).tocsr() - gnnm3 = sp.sparse.vstack(( - sp.sparse.hstack((sp.sparse.csr_matrix(((gnsp==C1).sum(),)*2),gnnm[gnsp==C1,:][:,gnsp==C2])), - sp.sparse.hstack((gnnm[gnsp==C2,:][:,gnsp==C1],sp.sparse.csr_matrix(((gnsp==C2).sum(),)*2))) - )).tocsr() - gn1 = np.append(gn[gnsp==A1],gn[gnsp==A2]) - gn2 = np.append(gn[gnsp==B1],gn[gnsp==B2]) - gn3 = np.append(gn[gnsp==C1],gn[gnsp==C2]) - - - if doPsubsAll: - f1 = np.logical_and(((ops[:,0]==A1) * (ops[:,1]==A2) + (ops[:,0]==A2) * (ops[:,1]==A1)) > 0, - ((pps[:,0]==A1) * (pps[:,1]==A2) + (pps[:,0]==A2) * (pps[:,1]==A1)) > 0) - f2 = np.logical_and(((ops[:,0]==B1) * (ops[:,1]==B2) + (ops[:,0]==B2) * (ops[:,1]==B1)) > 0, - ((pps[:,0]==B1) * (pps[:,1]==B2) + (pps[:,0]==B2) * (pps[:,1]==B1)) > 0) - f3 = np.logical_and(((ops[:,0]==C1) * (ops[:,1]==C2) + (ops[:,0]==C2) * (ops[:,1]==C1)) > 0, - ((pps[:,0]==C1) * (pps[:,1]==C2) + (pps[:,0]==C2) * (pps[:,1]==C1)) > 0) - doPsubs = f1.sum() > 0 and f2.sum() > 0 and f3.sum() > 0 - else: - doPsubs = False - - if doPsubs: - RES1=RES[f1] - RES2=RES[f2] - RES3=RES[f3] - - - op1 = to_vo(q(RES1["ortholog pairs"])) - op2 = to_vo(q(RES2["ortholog pairs"])) - op3 = to_vo(q(RES3["ortholog pairs"])) - pp1 = to_vo(q(RES1["paralog pairs"])) - pp2 = to_vo(q(RES2["paralog pairs"])) - pp3 = to_vo(q(RES3["paralog pairs"])) - - - # suppress warning - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - T1 = pd.DataFrame(data=np.arange(gn1.size)[None, :], columns=gn1) - x, y = T1[op1[:, 0]].values.flatten(), T1[op1[:, 1]].values.flatten() - gnnm1[x, y] = gnnm1[x, y] - gnnm1[y, x] = gnnm1[y, x] - - T1 = pd.DataFrame(data=np.arange(gn2.size)[None, :], columns=gn2) - x, y = T1[op2[:, 0]].values.flatten(), T1[op2[:, 1]].values.flatten() - gnnm2[x, y] = gnnm2[x, y] - gnnm2[y, x] = gnnm2[y, x] - - T1 = pd.DataFrame(data=np.arange(gn3.size)[None, :], columns=gn3) - x, y = T1[op3[:, 0]].values.flatten(), T1[op3[:, 1]].values.flatten() - gnnm3[x, y] = gnnm3[x, y] - gnnm3[y, x] = gnnm3[y, x] - - gnnm1.data[gnnm1.data==0]=1e-4 - gnnm2.data[gnnm2.data==0]=1e-4 - gnnm3.data[gnnm3.data==0]=1e-4 - - pairs1 = gn1[np.vstack(gnnm1.nonzero()).T] - pairs2 = gn2[np.vstack(gnnm2.nonzero()).T] - pairs3 = gn3[np.vstack(gnnm3.nonzero()).T] - data = np.concatenate((gnnm1.data, gnnm2.data, gnnm3.data)) - - CORR1 = pd.DataFrame(data=gnnm1.data[None, :], columns=to_vn(pairs1)) - CORR2 = pd.DataFrame(data=gnnm2.data[None, :], columns=to_vn(pairs2)) - CORR3 = pd.DataFrame(data=gnnm3.data[None, :], columns=to_vn(pairs3)) - - pairs = np.vstack((pairs1, pairs2, pairs3)) - all_genes = np.unique(pairs.flatten()) - Z = pd.DataFrame(data=np.arange(all_genes.size)[None, :], columns=all_genes) - x, y = Z[pairs[:, 0]].values.flatten(), Z[pairs[:, 1]].values.flatten() - GNNM = sp.sparse.lil_matrix((all_genes.size,) * 2) - GNNM[x, y] = data - GNNM=GNNM.tocsr() - GNNM.data[GNNM.datacorr_thr] - if keys is not None: - keys = [keys[A],keys[B],keys[C]] - with warnings.catch_warnings(): - warnings.simplefilter("ignore") - if keys is not None: - for i,sam,n in zip([0,1,2],[sam1,sam2,sam3],[A,B,C]): - if compute_markers: - find_cluster_markers(sam,keys[i]) - a = sam.adata.varm[keys[i]+'_scores'].T[q(FINAL[n+' gene'])].T - p = sam.adata.varm[keys[i]+'_pvals'].T[q(FINAL[n+' gene'])].T.values - p[p>pval_thr]=1 - p[p<1]=0 - p=1-p - f = a.columns[a.values.argmax(1)] - res=[] - for i in range(p.shape[0]): - res.append(';'.join(np.unique(np.append(f[i],a.columns[p[i,:]==1])))) - FINAL[n+' cell type'] = res - FINAL = FINAL.sort_values('min_corr',ascending=False) - FINALS.append(FINAL) - FINAL = pd.concat(FINALS,axis=0) - return FINAL - -def _compute_csim(samap, key, X=None, prepend=True, n_top = 0): - splabels = q(samap.adata.obs['species']) - skeys = splabels[np.sort(np.unique(splabels,return_index=True)[1])] - - cl = [] - clu = [] - for sid in skeys: - if prepend: - cl.append(sid+'_'+q(samap.adata.obs[key])[samap.adata.obs['species']==sid].astype('str').astype('object')) - else: - cl.append(q(samap.adata.obs[key])[samap.adata.obs['species']==sid]) - clu.append(np.unique(cl[-1])) - - clu = np.concatenate(clu) - cl = np.concatenate(cl) - - CSIM = np.zeros((clu.size, clu.size)) - if X is None: - X = samap.adata.obsp["connectivities"].copy() - - xi,yi = X.nonzero() - spxi = splabels[xi] - spyi = splabels[yi] - - filt = spxi!=spyi - di = X.data[filt] - xi = xi[filt] - yi = yi[filt] - - px,py = xi,cl[yi] - p = px.astype('str').astype('object')+';'+py.astype('object') - - A = pd.DataFrame(data=np.vstack((p, di)).T, columns=["x", "y"]) - valdict = df_to_dict(A, key_key="x", val_key="y") - cell_scores = [valdict[k].sum() for k in valdict.keys()] - ixer = pd.Series(data=np.arange(clu.size),index=clu) - if len(valdict.keys())>0: - xc,yc = substr(list(valdict.keys()),';') - xc = xc.astype('int') - yc=ixer[yc].values - cell_cluster_scores = sp.sparse.coo_matrix((cell_scores,(xc,yc)),shape=(X.shape[0],clu.size)).A - - for i, c in enumerate(clu): - if n_top > 0: - CSIM[i, :] = np.sort(cell_cluster_scores[cl==c],axis=0)[-n_top:].mean(0) - else: - CSIM[i, :] = cell_cluster_scores[cl==c].mean(0) - - CSIM = np.stack((CSIM,CSIM.T),axis=2).max(2) - CSIMth = CSIM / samap.adata.uns['mapping_K'] - return CSIMth,clu - else: - return np.zeros((clu.size, clu.size)), clu - -def get_mapping_scores(sm, keys, n_top = 0): - """Calculate mapping scores - Parameters - ---------- - sm: SAMAP object - - keys: dict, annotation vector keys for at least two species with species identifiers as the keys - e.g. {'pl':'tissue','sc':'tissue'} - - n_top: int, optional, default 0 - If `n_top` is 0, average the alignment scores for all cells in a pair of clusters. - Otherwise, average the alignment scores of the top `n_top` cells in a pair of clusters. - Set this to non-zero if you suspect there to be subpopulations of your cell types mapping - to distinct cell types in the other species. - Returns - ------- - D - table of highest mapping scores for cell types - A - pairwise table of mapping scores between cell types across species - """ - - - if len(list(keys.keys()))50,000 cells), use more chunks (e.g. 4) to avoid running out of - memory. - - umap : bool, optional, default True - If True, performs UMAP on the combined manifold to generate a 2D visualization. - If False, skips this step. - - ncpus : int, optional, default `os.cpu_count()` - The number of CPUs to use when computing gene-gene correlations. - Defaults to using all available CPUs. - - hom_edge_thr : float, optional, default 0 - Edges with weight below `hom_edge_thr` in the homology graph will be set to zero. - - hom_edge_mode: str, optional, default "pearson" - If "pearson", edge weights in the homology graph will be calculated using Pearson - correlation. If "mutual_info", edge weights will be calculated using normalized - mutual information. The latter requires package `fast-histogram` to be installed. - - scale_edges_by_corr: bool, optional, default True - If True, rescale cell-cell cross-species edges by their expression similarities - (correlations). - - neigh_from_keys : dict[bool], optional, default None - Dictionary of booleans indexed by species IDs. If True, species neighborhoods - are calculated directly from the chosen clustering (the `keys` parameter in `SAMAP(...)`). - Cells within the same cluster belong to the same neighborhood. - - pairwise: bool, optional, default True - If True, compute mutual nearest neighborhoods independently between each pair of species. - If False, compute mutual nearest neighborhoods between each species and all other species. - This parameter is ignored if there are only two species to be mapped. - - `pairwise=True` would prevent outgroup species from being unmapped. - For example, if `pairwise=False`, when mapping three species like human, mouse, and zebrafish, human and mice - will preferentially map to each other, leaving zebrafish unmapped. - - Set `pairwise=False` when you'd like to be able to tell which cell types are more or less similar - between different species. Set `pairwise=True` when you'd like to remove the effects of evolutionary - distance. This is particularly useful when using multiple reference species to annotate an unlabeled - dataset. - - Returns - ------- - samap - Species-merged SAM object - """ - self.pairwise = pairwise - - ids = self.ids - sams = self.sams - gnnm = self.gnnm - gns_dict = self.gns_dict - gns = self.gns - smap = self.smap - - if NHS is None: - NHS={} - for sid in ids: - NHS[sid] = 3 - if neigh_from_keys is None: - neigh_from_keys={} - for sid in ids: - neigh_from_keys[sid] = False - - start_time = time.time() - - smap.run( - NUMITERS=NUMITERS, - NHS=NHS, - K=crossK, - NCLUSTERS=N_GENE_CHUNKS, - ncpus=ncpus, - THR=hom_edge_thr, - corr_mode=hom_edge_mode, - scale_edges_by_corr = scale_edges_by_corr, - neigh_from_keys=neigh_from_keys, - pairwise=pairwise - ) - samap = smap.final_sam - self.samap = samap - self.ITER_DATA = smap.ITER_DATA - - if umap: - print("Running UMAP on the stitched manifolds.") - sc.tl.umap(self.samap.adata,min_dist=0.1,init_pos='random',maxiter = 500 if self.samap.adata.shape[0] <= 10000 else 200) - - - ix = pd.Series(data = np.arange(samap.adata.shape[1]),index = samap.adata.var_names)[gns].values - rixer = pd.Series(index =np.arange(gns.size), data = ix) - - try: - hom_graph = smap.GNNMS_corr[-1] - x,y = hom_graph.nonzero() - d = hom_graph.data - hom_graph = sp.sparse.coo_matrix((d,(rixer[x].values,rixer[y].values)),shape=(samap.adata.shape[1],)*2).tocsr() - samap.adata.varp["homology_graph_reweighted"] = hom_graph - self.gnnm_refined = hom_graph - except: - pass - - x,y = gnnm.nonzero() - d = gnnm.data - gnnm = sp.sparse.coo_matrix((d,(rixer[x].values,rixer[y].values)),shape=(samap.adata.shape[1],)*2).tocsr() - samap.adata.varp["homology_graph"] = gnnm - samap.adata.uns["homology_gene_names_dict"] = gns_dict - - - self.gnnm = gnnm - self.gns = q(samap.adata.var_names) - - gns_dict = {} - for sid in ids: - gns_dict[sid] = self.gns[np.in1d(self.gns,q(self.sams[sid].adata.var_names))] - self.gns_dict = gns_dict - - if umap: - for sid in ids: - sams[sid].adata.obsm['X_umap_samap'] = self.samap.adata[sams[sid].adata.obs_names].obsm['X_umap'] - - self.run_time = time.time() - start_time - print("Elapsed time: {} minutes.".format(self.run_time / 60)) - return samap - - def run_umap(self): - print("Running UMAP on the stitched manifolds.") - ids = self.ids - sams = self.sams - sc.tl.umap(self.samap.adata,min_dist=0.1,init_pos='random', maxiter = 500 if self.samap.adata.shape[0] <= 10000 else 200) - for sid in ids: - sams[sid].adata.obsm['X_umap_samap'] = self.samap.adata[sams[sid].adata.obs_names].obsm['X_umap'] - - def plot_expression_overlap(self,gs,axes=None,#'#000098', COLOR2='#ffb900' - COLOR0='gray', COLORS=None, COLORC='#00ceb5', - s0 = 1, ss=None, sc = 10, - thr = 0.1,**kwargs): - """Displays the expression overlap of two genes on the combined manifold. - - Parameters - ---------- - gs : dict - Dictionary of genes to display, keyed by species IDs. - For example, human ('hu') and mouse ('ms') genes: - gs = {'hu':'TOP2A','ms':'Top2a'} - - axes : matplotlib.pyplot.Axes, optional, default None - Displays the scatter plot on the provided axes if specified. - Otherwise creates a new figure. - - COLOR0 : str, optional, default 'gray' - The color for cells that do not express `g1` or `g2`. - - COLORS : dict, optional, default None - Dictionary of colors (hex codes) for cells expressing the - corresponding genes for each species. This dictionary is - keyed by species IDs. If not set, colors are chosen randomly. - - COLORC : str, optional, default '#00ceb5' - The color for cells that overlap in - expression of the two genes. - - s0 : int, optional, default 1 - Marker size corresponding to `COLOR0`. - - ss : dict, optional, default None - Dictionary of marker sizes corresponding to the colors in `COLORS`. - If not set, marker sizes default to 3. - - sc : int, optional, default 10 - Marker size corresponding to `COLORC`. - - thr : float, optional, default 0.1 - Threshold below which imputed expressions across species are zero'd out. - - Keyword Arguments (**kwargs) - ---------------------------- - Most arguments accepted by matplotlib.pyplot.scatter are available. - - - Returns - ------- - ax - matplotlib.pyplot.Axes - """ - - - if len(list(gs.keys()))0: - davgs[sid] = davgs[sid]/davgs[sid].max() - if davg.max()>0: - davg = davg/davg.max() - - cs={} - for sid in gs.keys(): - c = hex_to_rgb(COLORS[sid])+[0.0] - cs[sid] = np.vstack([c]*davg.size) - cs[sid][:,-1] = davgs[sid] - cc = hex_to_rgb(COLORC)+[0.0] - cc = np.vstack([cc]*davg.size) - cc[:,-1] = davg - - ax = samap.scatter(projection = 'X_umap', colorspec = COLOR0, axes=axes, s = s0) - - for sid in gs.keys(): - samap.scatter(projection = 'X_umap', c = cs[sid], axes = ax, s = ss[sid],colorbar=False,**kwargs) - - samap.scatter(projection = 'X_umap', c = cc, axes = ax, s = sc,colorbar=False,**kwargs) - - return ax - - def query_gene_pairs(self,gene): - """ Get BLAST and correlation scores of all genes connected - to the query gene. - - Preferrably, genes are prepended with their species IDs. - For example, "hu_SOX2" instead of "SOX2". - - Returns: Dictionary with "blast" and "correlation" keys with - the BLAST and correlation scores respectively for the queried - gene. - """ - - ids = self.ids - qgene = None - if (gene in self.gns): - qgene = gene - else: - for sid in ids: - if sid+'_'+gene in self.gns: - qgene = sid+'_'+gene - break - if qgene is None: - raise ValueError(f"Query gene {gene} not found in dataset.") - - a = self.gnnm[self.gns==qgene] - b = self.gnnm_refined[self.gns==qgene] - - i1 = self.gns[a.nonzero()[1]] - i2 = self.gns[b.nonzero()[1]] - d1 = a.data - d2 = b.data - a = pd.Series(index=i1,data=d1) - b = pd.Series(index=i2,data=d2) - return {"blast":a,"correlation":b} - - def query_gene_pair(self,gene1,gene2): - """ Get BLAST and correlation score for a pair of genes. - - Preferrably, genes are prepended with their species IDs. - For example, "hu_SOX2" instead of "SOX2". - - Returns: Dictionary with "blast" and "correlation" keys with - the BLAST and correlation scores respectively for the queried - gene pair. - """ - ids = self.ids - qgene1 = None - if (gene1 in self.gns): - qgene1 = gene1 - else: - for sid in ids: - if sid+'_'+gene1 in self.gns: - qgene1 = sid+'_'+gene1 - break - if qgene1 is None: - raise ValueError(f"Query gene {gene1} not found in dataset.") - - qgene2 = None - if (gene2 in self.gns): - qgene2 = gene2 - else: - for sid in ids: - if sid+'_'+gene2 in self.gns: - qgene2 = sid+'_'+gene2 - break - if qgene2 is None: - raise ValueError(f"Query gene {gene2} not found in dataset.") - - a = self.gnnm[self.gns==qgene1].A.flatten()[self.gns==qgene2][0] - b = self.gnnm_refined[self.gns==qgene1].A.flatten()[self.gns==qgene2][0] - return {"blast":a,"correlation":b} - - def scatter(self,axes=None,COLORS=None,ss=None,**kwargs): - - if ss is None: - ss={} - for sid in self.ids: - ss[sid] = 3 - - if COLORS is None: - COLORS={} - for sid in self.ids: - s = '' - for i in range(6): - s+=hex(np.random.randint(16))[-1].upper() - s='#'+s - COLORS[sid] = s - - for sid in self.ids: - axes = self.sams[sid].scatter(projection = 'X_umap_samap', colorspec = COLORS[sid], axes = axes, s = ss[sid],colorbar=False,**kwargs) - - return axes - - def gui(self): - """Launches a SAMGUI instance containing the two SAM objects.""" - if 'SamapGui' not in self.__dict__: - try: - from samalg.gui import SAMGUI - except ImportError: - raise ImportError('Please install SAMGUI dependencies. See the README in the SAM github repository.') - - sg = SAMGUI(sam = list(self.sams.values()), title = list(self.ids),default_proj='X_umap_samap') - self.SamapGui = sg - return sg.SamPlot - else: - return self.SamapGui.SamPlot - - def refine_homology_graph(self, THR=0, NCLUSTERS=1, ncpus = os.cpu_count(), corr_mode='pearson', wscale = False): - gnnm = self.smap.refine_homology_graph(NCLUSTERS=NCLUSTERS, ncpus=ncpus, THR=THR, corr_mode=corr_mode, wscale=wscale) - samap = self.smap.samap - gns_dict = self.smap.gns_dict - gns = [] - for sid in q(samap.adata.obs['species'])[np.sort(np.unique(samap.adata.obs['species'],return_index=True)[1])]: - gns.extend(gns_dict[sid]) - gns=q(gns) - ix = pd.Series(data = np.arange(samap.adata.shape[1]),index = samap.adata.var_names)[gns].values - rixer = pd.Series(index =np.arange(gns.size), data = ix) - x,y = gnnm.nonzero() - d = gnnm.data - gnnm = sp.sparse.coo_matrix((d,(rixer[x].values,rixer[y].values)),shape=(samap.adata.shape[1],)*2).tocsr() - return gnnm - -class _Samap_Iter(object): - def __init__( - self, sams, gnnm, gns_dict, keys=None - ): - self.sams = sams - self.gnnm = gnnm - self.gnnmu = gnnm - self.gns_dict = gns_dict - - if keys is None: - keys = {} - for sid in sams.keys(): - keys[sid] = 'leiden_clusters' - - self.keys = keys - - self.GNNMS_corr = [] - self.GNNMS_pruned = [] - self.GNNMS_nnm = [] - - self.ITER_DATA = [ - self.GNNMS_nnm, - self.GNNMS_corr, - self.GNNMS_pruned, - ] - self.iter = 0 - - def refine_homology_graph(self, NCLUSTERS=1, ncpus=os.cpu_count(), THR=0, corr_mode='pearson', wscale=False): - if corr_mode=='mutual_info': - try: - from fast_histogram import histogram2d - except: - raise ImportError("Package `fast_histogram` must be installed for `corr_mode='mutual_info'`."); - sams = self.sams - gnnm = self.gnnm - gns_dict = self.gns_dict - gnnmu = self.gnnmu - keys = self.keys - sam4 = self.samap - - gnnmu = _refine_corr( - sams, - sam4, - gnnm, - gns_dict, - THR=THR, - use_seq=False, - T1=0, - NCLUSTERS=NCLUSTERS, - ncpus=ncpus, - corr_mode=corr_mode, - wscale=wscale - ) - return gnnmu - - def run(self, NUMITERS=3, NHS=None, K=20, corr_mode='pearson', NCLUSTERS=1, - scale_edges_by_corr=True, THR=0, neigh_from_keys=None, pairwise=True, - ncpus=os.cpu_count()): - sams = self.sams - gnnm = self.gnnm - gns_dict = self.gns_dict - gnnmu = self.gnnmu - keys = self.keys - - if NHS is None: - NHS={} - for sid in sams.keys(): - NHS[sid] = 2 - if neigh_from_keys is None: - neigh_from_keys={} - for sid in sams: - neigh_from_keys[sid] = False - gns = np.concatenate(list(gns_dict.values())) - - if self.iter > 0: - sam4 = self.samap - - for i in range(NUMITERS): - if self.iter > 0 and i == 0: - print("Calculating gene-gene correlations in the homology graph...") - gnnmu = self.refine_homology_graph(ncpus = ncpus, NCLUSTERS = NCLUSTERS, THR=THR, corr_mode=corr_mode) - - self.GNNMS_corr.append(gnnmu) - self.gnnmu = gnnmu - - gnnm2 = _get_pairs(sams, gnnmu, gns_dict, NOPs1=0, NOPs2=0) - self.GNNMS_pruned.append(gnnm2) - - sam4 = _mapper( - sams, - gnnm2, - gns, - umap=False, - K=K, - NHS=NHS, - coarsen=True, - keys=keys, - scale_edges_by_corr=scale_edges_by_corr, - neigh_from_keys=neigh_from_keys, - pairwise=pairwise - ) - sam4.adata.uns['mapping_K'] = K - self.samap = sam4 - self.GNNMS_nnm.append(sam4.adata.obsp["connectivities"]) - - print("Iteration " + str(i+1) + " complete.") - print("Alignment scores:") - print(_avg_as(sam4)) - - self.iter += 1 - if i < NUMITERS - 1: - print("Calculating gene-gene correlations in the homology graph...") - self.samap = sam4 - gnnmu = self.refine_homology_graph(ncpus = ncpus, NCLUSTERS = NCLUSTERS, THR=THR, corr_mode=corr_mode) - - self.GNNMS_corr.append(gnnmu) - self.gnnmu = gnnmu - - gc.collect() - - self.final_sam = sam4 - - -def _avg_as(s): - x = q(s.adata.obs['species']) - xu = np.unique(x) - a = np.zeros((xu.size,xu.size)) - for i in range(xu.size): - for j in range(xu.size): - if i!=j: - a[i,j] = s.adata.obsp['connectivities'][x==xu[i],:][:,x==xu[j]].sum(1).A.flatten().mean() / s.adata.uns['mapping_K'] - return pd.DataFrame(data=a,index=xu,columns=xu) - -@njit(parallel=True) -def _replace(X,xi,yi): - data = np.zeros(xi.size) - for i in prange(xi.size): - x=X[xi[i]] - y=X[yi[i]] - data[i] = ((x-x.mean())*(y-y.mean()) / x.std() / y.std()).sum() / x.size - return data - - -def _generate_coclustering_matrix(cl): - cl = ut.convert_annotations(np.array(list(cl))) - clu,cluc=np.unique(cl,return_counts=True) - v = np.zeros((cl.size,clu.size)) - v[np.arange(v.shape[0]),cl]=1 - v = sp.sparse.csr_matrix(v) - return v - - -def _mapper( - sams, - gnnm=None, - gn=None, - NHS=None, - umap=False, - mdata=None, - k=None, - K=20, - chunksize=20000, - coarsen=True, - keys=None, - scale_edges_by_corr=False, - neigh_from_keys=None, - pairwise=True, - **kwargs -): - if NHS is None: - NHS={} - for sid in sams.keys(): - NHS[sid] = 3 - - if neigh_from_keys is None: - neigh_from_keys={} - for sid in sams.keys(): - neigh_from_keys[sid] = False - - if mdata is None: - mdata = _mapping_window(sams, gnnm, gn, K=K, pairwise=pairwise) - - k1 = K - - if keys is None: - keys = {} - for sid in sams.keys(): - keys[sid] = 'leiden_clusters' - - nnms_in={} - nnms_in0={} - flag=False - species_indexer=[] - for sid in sams.keys(): - print(f"Expanding neighbourhoods of species {sid}...") - cl = sams[sid].get_labels(keys[sid]) - _, ix, cluc = np.unique(cl, return_counts=True, return_inverse=True) - K = cluc[ix] - nnms_in0[sid] = sams[sid].adata.obsp["connectivities"].copy() - species_indexer.append(np.arange(sams[sid].adata.shape[0])) - if not neigh_from_keys[sid]: - nnm_in = _smart_expand(nnms_in0[sid], K, NH=NHS[sid]) - nnm_in.data[:] = 1 - nnms_in[sid]=nnm_in - else: - nnms_in[sid]=_generate_coclustering_matrix(cl) - flag=True - - for i in range(1,len(species_indexer)): - species_indexer[i] += species_indexer[i-1].max()+1 - - if not flag: - nnm_internal = sp.sparse.block_diag(list(nnms_in.values())).tocsr() - nnm_internal0 = sp.sparse.block_diag(list(nnms_in0.values())).tocsr() - - ovt = mdata["knn"] - ovt0 = ovt.copy() - ovt0.data[:]=1 - - B = ovt - # already sum-normalized per species - #s = B.sum(1).A - #s[s == 0] = 1 - #B = B.multiply(1 / s).tocsr() - - print("Indegree coarsening") - - numiter = nnm_internal0.shape[0] // chunksize + 1 - - D = sp.sparse.csr_matrix((0, nnm_internal0.shape[0])) - if flag: - Cs=[] - for it,sid in enumerate(sams.keys()): - nfk = neigh_from_keys[sid] - if nfk: - Cs.append(nnms_in[sid].dot(nnms_in[sid].T.dot(B.T[species_indexer[it]]))) - else: - Cs.append(nnms_in[sid].dot(B.T[species_indexer[it]])) - D = sp.sparse.vstack(Cs).T - del Cs - gc.collect() - else: - for bl in range(numiter): - print(str(bl) + "/" + str(numiter), D.shape) - C = B[bl * chunksize : (bl + 1) * chunksize].dot(nnm_internal.T) - C.data[C.data < 0.1] = 0 - C.eliminate_zeros() - - D = sp.sparse.vstack((D, C)) - del C - gc.collect() - - D = D.multiply(D.T).tocsr() - D.data[:] = D.data**0.5 - mdata["xsim"] = D - - if scale_edges_by_corr: - print('Rescaling edge weights by expression correlations.') - x,y = D.nonzero() - vals = _replace(mdata["wPCA"],x,y) - vals[vals<1e-3]=1e-3 - - # make a copy and write correlations - F = D.copy() - F.data[:] = vals - - # normalize by maximum and rescale with tanh - ma = F.max(1).A - ma[ma==0]=1 - F = F.multiply(1/ma).tocsr() - F.data[:] = _tanh_scale(F.data,center=0.7,scale=10) - - # get max aligment score from before - ma = D.max(1).A - ma[ma==0]=1 - - # geometric mean expression correlation scores by alignment scores - D = F.multiply(D).tocsr() - D.data[:] = np.sqrt(D.data) - - # get new max scores - ma2 = D.max(1).A - ma2[ma2==0]=1 - - # change new max scores to old max scores - D = D.multiply(ma/ma2).tocsr() - - species_list = [] - for sid in sams.keys(): - species_list += [sid]*sams[sid].adata.shape[0] - species_list = np.array(species_list) - - if not pairwise or len(sams.keys())==2: - Dk = sparse_knn(D, k1).tocsr() - denom = k1 - else: - Dk=[] - for sid1 in sams.keys(): - row=[] - for sid2 in sams.keys(): - if sid1 != sid2: - Dsubk = sparse_knn(D[species_list==sid1][:,species_list==sid2], k1).tocsr() - else: - Dsubk = sp.sparse.csr_matrix((sams[sid1].adata.shape[0],)*2) - row.append(Dsubk) - Dk.append(sp.sparse.hstack(row)) - Dk = sp.sparse.vstack(Dk).tocsr() - denom = (k1 * (len(sams.keys())-1)) - - sr = Dk.sum(1).A - - x = 1 - sr.flatten() / denom - - sr[sr==0]=1 - st = Dk.sum(0).A.flatten()[None,:] - st[st==0]=1 - proj = Dk.multiply(1 / sr).dot(Dk.multiply(1 / st)).tocsr() - z = proj.copy() - z.data[:] = 1 - idx = np.where(z.sum(1).A.flatten() >= k1)[0] - - omp = nnm_internal0 - omp.data[:]=1 - s = proj.max(1).A - s[s == 0] = 1 - proj = proj.multiply(1 / s).tocsr() - X, Y = omp.nonzero() - X2 = X[np.in1d(X, idx)] - Y2 = Y[np.in1d(X, idx)] - - omp = omp.tolil() - omp[X2, Y2] = np.vstack((proj[X2, Y2].A.flatten(), np.ones(X2.size) * 0.3)).max( - 0 - ) - - omp = nnm_internal0.tocsr() - NNM = omp.multiply(x[:, None]) - NNM = (NNM+Dk).tolil() - NNM.setdiag(0) - - print("Concatenating SAM objects...") - sam3 = _concatenate_sam(sams, NNM) - - sam3.adata.obs["species"] = pd.Categorical(species_list) - - sam3.adata.uns["gnnm_corr"] = mdata.get("gnnm_corr",None) - - if umap: - print("Computing UMAP projection...") - sc.tl.umap(sam3.adata, min_dist=0.1, maxiter = 500 if sam3.adata.shape[0] <= 10000 else 200) - return sam3 - -def _refine_corr( - sams, - st, - gnnm, - gns_dict, - corr_mode="mutual_info", - THR=0, - use_seq=False, - T1=0.25, - NCLUSTERS=1, - ncpus=os.cpu_count(), - wscale=False -): - # import networkx as nx - gns = np.concatenate(list(gns_dict.values())) - - x, y = gnnm.nonzero() - sam = list(sams.values())[0] - cl = sam.leiden_clustering(gnnm, res=0.5) - ix = np.argsort(cl) - NGPC = gns.size // NCLUSTERS + 1 - - ixs = [] - for i in range(NCLUSTERS): - ixs.append(np.sort(ix[i * NGPC : (i + 1) * NGPC])) - - assert np.concatenate(ixs).size == gns.size - - GNNMSUBS = [] - GNSUBS = [] - for i in range(len(ixs)): - ixs[i] = np.unique(np.append(ixs[i], gnnm[ixs[i], :].nonzero()[1])) - gnnm_sub = gnnm[ixs[i], :][:, ixs[i]] - gnsub = gns[ixs[i]] - gns_dict_sub={} - for sid in gns_dict.keys(): - gn = gns_dict[sid] - gns_dict_sub[sid] = gn[np.in1d(gn,gnsub)] - - gnnm2_sub = _refine_corr_parallel( - sams, - st, - gnnm_sub, - gns_dict_sub, - corr_mode=corr_mode, - THR=THR, - use_seq=use_seq, - T1=T1, - ncpus=ncpus, - wscale=wscale - ) - GNNMSUBS.append(gnnm2_sub) - GNSUBS.append(gnsub) - gc.collect() - - I = [] - P = [] - for i in range(len(GNNMSUBS)): - I.append( - np.unique(np.sort(np.vstack((GNNMSUBS[i].nonzero())).T, axis=1), axis=0) - ) - P.append(GNSUBS[i][I[-1]]) - - GNS = pd.DataFrame(data=np.arange(gns.size)[None, :], columns=gns) - gnnm3 = sp.sparse.lil_matrix(gnnm.shape) - for i in range(len(I)): - x, y = GNS[P[i][:, 0]].values.flatten(), GNS[P[i][:, 1]].values.flatten() - gnnm3[x, y] = GNNMSUBS[i][I[i][:, 0], I[i][:, 1]].A.flatten() - - gnnm3 = gnnm3.tocsr() - x, y = gnnm3.nonzero() - # gnnm3[y,x]=gnnm3.data - gnnm3 = gnnm3.tolil() - gnnm3[y, x] = gnnm3[x, y].A.flatten() - gnnm3 = gnnm3.tocsr() - return gnnm3 - -def _prepend_blast_prefix(data, pre): - x = [str(x).split("_")[0] for x in data] - vn = [] - for i,g in enumerate(data): - if x[i] != pre: - vn.append(pre+"_"+g) - else: - vn.append(g) - return np.array(vn).astype('str').astype('object') - -def _calculate_blast_graph(ids, f_maps="maps/", eval_thr=1e-6, reciprocate=False): - gns = [] - Xs=[] - Ys=[] - Vs=[] - - for i in range(len(ids)): - id1=ids[i] - for j in range(i,len(ids)): - id2=ids[j] - if i!=j: - if os.path.exists(f_maps + "{}{}".format(id1, id2)): - fA = f_maps + "{}{}/{}_to_{}.txt".format(id1, id2, id1, id2) - fB = f_maps + "{}{}/{}_to_{}.txt".format(id1, id2, id2, id1) - elif os.path.exists(f_maps + "{}{}".format(id2, id1)): - fA = f_maps + "{}{}/{}_to_{}.txt".format(id2, id1, id1, id2) - fB = f_maps + "{}{}/{}_to_{}.txt".format(id2, id1, id2, id1) - else: - raise FileExistsError( - "BLAST mapping tables with the input IDs ({} and {}) not found in the specified path.".format( - id1, id2 - ) - ) - - A = pd.read_csv(fA, sep="\t", header=None, index_col=0) - B = pd.read_csv(fB, sep="\t", header=None, index_col=0) - - A.columns = A.columns.astype("1] # extract pairs that appear duplicated times - xgyg=q(xg.astype('object')+';'+yg.astype('object')) - xguygu=q(xgu.astype('object')+';'+ygu.astype('object')) - - filt = np.in1d(xgyg,xguygu) - - DF=pd.DataFrame(data=xgyg[filt][:,None],columns=['key']) - DF['val']=da[filt] - - dic = df_to_dict(DF,key_key='key') - - xgu = q([x.split(';')[0] for x in dic.keys()]) - ygu = q([x.split(';')[1] for x in dic.keys()]) - replz = q([max(dic[x]) for x in dic.keys()]) - - xgu1,ygu1 = zgu[:,cu==1] # get non-duplicate pairs - xg = np.append(xgu1, xgu) # append duplicate pairs - yg = np.append(ygu1, ygu) - da = np.append(da[ix][cu==1],replz) # append duplicate scores to the non-duplicate scores - gn = np.unique(np.append(xg,yg)) # get the unique genes - - s = pd.Series(data=np.arange(gn.size),index=gn) # create an indexer - xn,yn = s[xg].values,s[yg].values # convert gene pairs to indexes - gnnm = sp.sparse.coo_matrix((da,(xn,yn)),shape=(gn.size,)*2).tocsr() # create sparse matrix - - f = gnnm.sum(1).A.flatten() != 0 #eliminate zero rows/columns - gn = gn[f] - sps = np.array([x.split('_')[0] for x in gn]) - - gns_dict={} - for sid in sids: - gns_dict[sid] = gn[sps==sid] - - return gnnm, gns_dict, gn - - -def prepare_SAMap_loadings(sam, npcs=300): - """ Prepares SAM object to contain the proper PC loadings associated with its manifold. - Deposits the loadings in `sam.adata.varm['PCs_SAMap']`. - - Parameters - ---------- - sam - SAM object - - npcs - int, optional, default 300 - The number of PCs to calculate loadings for. - - """ - ra = sam.adata.uns["run_args"] - preprocessing = ra.get("preprocessing", "StandardScaler") - weight_PCs = ra.get("weight_PCs", False) - A, _ = sam.calculate_nnm( - n_genes=sam.adata.shape[1], - preprocessing=preprocessing, - npcs=npcs, - weight_PCs=weight_PCs, - sparse_pca=True, - update_manifold=False, - weight_mode='dispersion' - ) - sam.adata.varm["PCs_SAMap"] = A - - -def _concatenate_sam(sams, nnm): - acns = [] - exps = [] - agns = [] - sps = [] - for i,sid in enumerate(sams.keys()): - acns.append(q(sams[sid].adata.obs_names)) - sps.append([sid]*acns[-1].size) - exps.append(sams[sid].adata.X) - agns.append(q(sams[sid].adata.var_names)) - - - acn = np.concatenate(acns) - agn = np.concatenate(agns) - sps = np.concatenate(sps) - - xx = sp.sparse.block_diag(exps,format='csr') - - - sam = SAM(counts=(xx, agn, acn)) - - sam.adata.uns["neighbors"] = {} - nnm = nnm.tocsr() - nnm.eliminate_zeros() - sam.adata.obsp["connectivities"] = nnm - sam.adata.uns["neighbors"]["params"] = { - "n_neighbors": 15, - "method": "umap", - "use_rep": "X", - "metric": "euclidean", - } - for i in sams.keys(): - for k in sams[i].adata.obs.keys(): - if sams[i].adata.obs[k].dtype.name == "category": - z = np.array(['unassigned']*sam.adata.shape[0],dtype='object') - z[sps==i] = q(sams[i].adata.obs[k]) - sam.adata.obs[i+'_'+k] = pd.Categorical(z) - - a = [] - for i,sid in enumerate(sams.keys()): - a.extend(["batch" + str(i + 1)] * sams[sid].adata.shape[0]) - sam.adata.obs["batch"] = pd.Categorical(np.array(a)) - sam.adata.obs.columns = sam.adata.obs.columns.astype("str") - sam.adata.var.columns = sam.adata.var.columns.astype("str") - - for i in sam.adata.obs: - sam.adata.obs[i] = sam.adata.obs[i].astype("str") - - return sam - -def _map_features_un(A, B, sam1, sam2, thr=1e-6): - i1 = np.where(A.columns == "10")[0][0] - i3 = np.where(A.columns == "11")[0][0] - - inA = q(A.index) - inB = q(B.index) - - gn1 = q(sam1.adata.var_names) - gn2 = q(sam2.adata.var_names) - - gn1 = gn1[np.in1d(gn1, inA)] - gn2 = gn2[np.in1d(gn2, inB)] - - A = A.iloc[np.in1d(inA, gn1), :] - B = B.iloc[np.in1d(inB, gn2), :] - - inA2 = q(A.iloc[:, 0]) - inB2 = q(B.iloc[:, 0]) - - A = A.iloc[np.in1d(inA2, gn2), :] - B = B.iloc[np.in1d(inB2, gn1), :] - - gn = np.append(gn1, gn2) - gnind = pd.DataFrame(data=np.arange(gn.size)[None, :], columns=gn) - - A.index = pd.Index(gnind[A.index].values.flatten()) - B.index = pd.Index(gnind[B.index].values.flatten()) - A.iloc[:, 0] = gnind[A.iloc[:, 0].values.flatten()].values.flatten() - B.iloc[:, 0] = gnind[B.iloc[:, 0].values.flatten()].values.flatten() - - Arows = np.vstack((A.index, A.iloc[:, 0], A.iloc[:, i3])).T - Arows = Arows[A.iloc[:, i1].values.flatten() <= thr, :] - gnnm1 = sp.sparse.lil_matrix((gn.size,) * 2) - gnnm1[Arows[:, 0].astype("int32"), Arows[:, 1].astype("int32")] = Arows[ - :, 2 - ] # -np.log10(Arows[:,2]+1e-200) - - Brows = np.vstack((B.index, B.iloc[:, 0], B.iloc[:, i3])).T - Brows = Brows[B.iloc[:, i1].values.flatten() <= thr, :] - gnnm2 = sp.sparse.lil_matrix((gn.size,) * 2) - gnnm2[Brows[:, 0].astype("int32"), Brows[:, 1].astype("int32")] = Brows[ - :, 2 - ] # -np.log10(Brows[:,2]+1e-200) - - gnnm = (gnnm1 + gnnm2).tocsr() - gnnms = (gnnm + gnnm.T) / 2 - gnnm.data[:] = 1 - gnnms = gnnms.multiply(gnnm).multiply(gnnm.T).tocsr() - return gnnms, gn1, gn2 - - -def _filter_gnnm(gnnm, thr=0.25): - x, y = gnnm.nonzero() - mas = gnnm.max(1).A.flatten() - gnnm4 = gnnm.copy() - gnnm4.data[gnnm4[x, y].A.flatten() < mas[x] * thr] = 0 - gnnm4.eliminate_zeros() - x, y = gnnm4.nonzero() - z = gnnm4.data - gnnm4 = gnnm4.tolil() - gnnm4[y, x] = z - gnnm4 = gnnm4.tocsr() - return gnnm4 - - -def _get_pairs(sams, gnnm, gns_dict, NOPs1=0, NOPs2=0): - # gnnm = filter_gnnm(gnnm) - su = gnnm.max(1).A - su[su == 0] = 1 - gnnm = gnnm.multiply(1 / su).tocsr() - Ws = {} - for sid in sams.keys(): - Ws[sid] = sams[sid].adata.var["weights"][gns_dict[sid]].values - - W = np.concatenate(list(Ws.values())) - W[W < 0.0] = 0 - W[W > 0.0] = 1 - - B = gnnm.multiply(W[None, :]).multiply(W[:, None]).tocsr() - B.eliminate_zeros() - - return B - -@njit -def nb_unique1d(ar): - """ - Find the unique elements of an array, ignoring shape. - """ - ar = ar.flatten() - - optional_indices = True - - if optional_indices: - perm = ar.argsort(kind='mergesort') - aux = ar[perm] - else: - ar.sort() - aux = ar - mask = np.empty(aux.shape, dtype=np.bool_) - mask[:1] = True - if aux.shape[0] > 0 and aux.dtype.kind in "cfmM" and np.isnan(aux[-1]): - if aux.dtype.kind == "c": # for complex all NaNs are considered equivalent - aux_firstnan = np.searchsorted(np.isnan(aux), True, side='left') - else: - aux_firstnan = np.searchsorted(aux, aux[-1], side='left') - mask[1:aux_firstnan] = (aux[1:aux_firstnan] != aux[:aux_firstnan - 1]) - mask[aux_firstnan] = True - mask[aux_firstnan + 1:] = False - else: - mask[1:] = aux[1:] != aux[:-1] - - - imask = np.cumsum(mask) - 1 - inv_idx = np.empty(mask.shape, dtype=np.intp) - inv_idx[perm] = imask - idx = np.append(np.nonzero(mask)[0],mask.size) - - #idx #inverse #counts - return aux[mask],perm[mask],inv_idx,np.diff(idx) - -@njit -def _xicorr(X,Y): - '''xi correlation coefficient''' - n = X.size - xi = np.argsort(X,kind='quicksort') - Y = Y[xi] - _,_,b,c = nb_unique1d(Y) - r = np.cumsum(c)[b] - _,_,b,c = nb_unique1d(-Y) - l = np.cumsum(c)[b] - denominator = (2*(l*(n-l)).sum()) - if denominator > 0: - return 1 - n*np.abs(np.diff(r)).sum() / denominator - else: - return 0 - -@njit(parallel=True) -def _refine_corr_kernel(p, ps, sids, sixs, indptr,indices,data, n, corr_mode): - p1 = p[:,0] - p2 = p[:,1] - - ps1 = ps[:,0] - ps2 = ps[:,1] - - d = {} - for i in range(len(sids)): - d[sids[i]] = sixs[i] - - res = np.zeros(p1.size) - - for j in prange(len(p1)): - j1, j2 = p1[j], p2[j] - pl1d = data[indptr[j1] : indptr[j1 + 1]] - pl1i = indices[indptr[j1] : indptr[j1 + 1]] - - sc1d = data[indptr[j2] : indptr[j2 + 1]] - sc1i = indices[indptr[j2] : indptr[j2 + 1]] - - x = np.zeros(n) - x[pl1i] = pl1d - y = np.zeros(n) - y[sc1i] = sc1d - - a1, a2 = ps1[j], ps2[j] - ix1 = d[a1] - ix2 = d[a2] - - - xa,xb,ya,yb = x[ix1],x[ix2],y[ix1],y[ix2] - xx=np.append(xa,xb) - yy=np.append(ya,yb) - - if corr_mode == "pearson": - c = ((xx-xx.mean())*(yy-yy.mean()) / xx.std() / yy.std()).sum() / xx.size - else: - c = _xicorr(xx,yy) - res[j] = c - return res - -def _refine_corr_parallel( - sams, - st, - gnnm, - gns_dict, - corr_mode="pearson", - THR=0, - use_seq=False, - T1=0.0, - ncpus=os.cpu_count(), - wscale=False -): - - import scipy as sp - - gn = np.concatenate(list(gns_dict.values())) - - Ws = [] - ix = [] - for sid in sams.keys(): - Ws.append(sams[sid].adata.var["weights"][gns_dict[sid]].values) - ix += [sid]*gns_dict[sid].size - ix = np.array(ix) - w = np.concatenate(Ws) - - w[w > T1] = 1 - w[w < 1] = 0 - - gnO = gn[w > 0] - ix = ix[w > 0] - gns_dictO = {} - for sid in gns_dict.keys(): - gns_dictO[sid] = gnO[ix==sid] - - gnnmO = gnnm[w > 0, :][:, w > 0] - x, y = gnnmO.nonzero() - - pairs = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0) - - xs, ys = q([i.split('_')[0] for i in gnO[pairs[:,0]]]), q([i.split('_')[0] for i in gnO[pairs[:,1]]]) - pairs_species = np.vstack((xs,ys)).T - - nnm = st.adata.obsp["connectivities"] - xs = [] - nnms = [] - for i,sid in enumerate(sams.keys()): - nnms.append(nnm[:,st.adata.obs['batch'] == f'batch{i+1}']) - s1 = nnms[-1].sum(1).A - s1[s1 < 1e-3] = 1 - s1 = s1.flatten()[:, None] - nnms[-1] = nnms[-1].multiply(1 / s1) - - xs.append(sams[sid].adata[:,gns_dictO[sid]].X.astype("float16")) - - Xs = sp.sparse.block_diag(xs).tocsc() - nnms = sp.sparse.hstack(nnms).tocsr() - Xavg = nnms.dot(Xs).tocsc() - - - p = pairs - ps = pairs_species - - gnnm2 = gnnm.multiply(w[:, None]).multiply(w[None, :]).tocsr() - x, y = gnnm2.nonzero() - pairs = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0) - - species = q(st.adata.obs['species']) - sixs = [] - sidss = np.unique(species) - for sid in sidss: - sixs.append(np.where(species==sid)[0]) - - vals = _refine_corr_kernel(p,ps,sidss,sixs,Xavg.indptr,Xavg.indices,Xavg.data,Xavg.shape[0], corr_mode) - vals[np.isnan(vals)]=0 - - CORR = dict(zip(to_vn(np.vstack((gnO[p[:,0]],gnO[p[:,1]])).T),vals)) - - for k in CORR.keys(): - CORR[k] = 0 if CORR[k] < THR else CORR[k] - if wscale: - id1,id2 = [x.split('_')[0] for x in k.split(';')] - weight1 = sams[id1].adata.var["weights"][k.split(';')[0]] - weight2 = sams[id2].adata.var["weights"][k.split(';')[1]] - CORR[k] = np.sqrt(CORR[k] * np.sqrt(weight1 * weight2)) - - CORR = np.array([CORR[x] for x in to_vn(gn[pairs])]) - - gnnm3 = sp.sparse.lil_matrix(gnnm.shape) - - if use_seq: - gnnm3[pairs[:, 0], pairs[:, 1]] = ( - CORR * gnnm2[pairs[:, 0], pairs[:, 1]].A.flatten() - ) - gnnm3[pairs[:, 1], pairs[:, 0]] = ( - CORR * gnnm2[pairs[:, 1], pairs[:, 0]].A.flatten() - ) - else: - gnnm3[pairs[:, 0], pairs[:, 1]] = CORR # *gnnm2[x,y].A.flatten() - gnnm3[pairs[:, 1], pairs[:, 0]] = CORR # *gnnm2[x,y].A.flatten() - - gnnm3 = gnnm3.tocsr() - gnnm3.eliminate_zeros() - return gnnm3 - -try: - from fast_histogram import histogram2d -except: - pass; - -def hist2d(X,Y,bins=100,domain=None): - if domain is None: - xmin = X.min() - xmax = X.max() - ymin=Y.min() - ymax=Y.max() - domain = [(xmin,xmax),(ymin,ymax)] - return histogram2d(X,Y,bins,domain) - -def calc_MI(X,Y,bins=100,cl=None,cs=None): - xmin = X.min() - xmax = X.max() - ymin=Y.min() - ymax=Y.max() - domain = [(xmin,xmax),(ymin,ymax)] - c_XY = hist2d(X,Y,bins=bins,domain=domain) - c_X = c_XY.sum(1) - c_Y = c_XY.sum(0) - - c = c_XY - c_normalized = c / c.sum() - c1 = c_normalized.sum(1) - c2 = c_normalized.sum(0) - c1[c1==0]=1 - c2[c2==0]=1 - c_normalized[c_normalized==0]=1 - H_X = -(c1*np.log2(c1)).sum() - H_Y = -(c2*np.log2(c2)).sum() - H_XY = -(c_normalized*np.log2(c_normalized)).sum() - - H_Y = 0 if H_Y < 0 else H_Y - H_X = 0 if H_X < 0 else H_X - H_XY = 0 if H_XY < 0 else H_XY - - MI = H_X + H_Y - H_XY - if MI <= 0 or H_X <= 0 or H_Y <= 0: - return 0 - else: - return MI / np.sqrt(H_X*H_Y) - -def _parallel_wrapper(j): - j1, j2 = p[j, 0], p[j, 1] - - pl1d = Xavg.data[Xavg.indptr[j1] : Xavg.indptr[j1 + 1]] - pl1i = Xavg.indices[Xavg.indptr[j1] : Xavg.indptr[j1 + 1]] - - sc1d = Xavg.data[Xavg.indptr[j2] : Xavg.indptr[j2 + 1]] - sc1i = Xavg.indices[Xavg.indptr[j2] : Xavg.indptr[j2 + 1]] - - x = np.zeros(Xavg.shape[0]) - x[pl1i] = pl1d - y = np.zeros(Xavg.shape[0]) - y[sc1i] = sc1d - - ha = gnsO[j1] + ";" + gnsO[j2] - - try: - if corr_mode == 'xicorr': - CORR[ha] = _xicorr(x,y) - elif corr_mode == 'mutual_info': - CORR[ha] = calc_MI(x,y,cl=cl,cs=cs) - else: - raise ValueError(f'`{corr_mode}` not recognized.') - except: - CORR[ha] = 0 - - -def _united_proj(wpca1, wpca2, k=20, metric="cosine", ef=200, M=48): - - metric = 'l2' if metric == 'euclidean' else metric - metric = 'cosine' if metric == 'correlation' else metric - labels2 = np.arange(wpca2.shape[0]) - p2 = hnswlib.Index(space=metric, dim=wpca2.shape[1]) - p2.init_index(max_elements=wpca2.shape[0], ef_construction=ef, M=M) - p2.add_items(wpca2, labels2) - p2.set_ef(ef) - idx1, dist1 = p2.knn_query(wpca1, k=k) - - if metric == 'cosine': - dist1 = 1 - dist1 - dist1[dist1 < 1e-3] = 1e-3 - dist1 = dist1/dist1.max(1)[:,None] - dist1 = _tanh_scale(dist1,scale=10, center=0.7) - else: - sigma1 = dist1[:,4] - sigma1[sigma1<1e-3]=1e-3 - dist1 = np.exp(-dist1/sigma1[:,None]) - - Sim1 = dist1 # np.exp(-1*(1-dist1)**2) - knn1v2 = sp.sparse.lil_matrix((wpca1.shape[0], wpca2.shape[0])) - x1 = np.tile(np.arange(idx1.shape[0])[:, None], (1, idx1.shape[1])).flatten() - knn1v2[x1.astype('int32'), idx1.flatten().astype('int32')] = Sim1.flatten() - return knn1v2.tocsr() - -def _tanh_scale(x,scale=10,center=0.5): - return center + (1-center) * np.tanh(scale * (x - center)) - -def _mapping_window(sams, gnnm=None, gns=None, K=20, pairwise=True): - k = K - output_dict = {} - if gnnm is not None and gns is not None: - print('Prepping datasets for translation.') - gnnm_corr = gnnm.copy() - gnnm_corr.data[:] = _tanh_scale(gnnm_corr.data) - - std = StandardScaler(with_mean=False) - - gs = {} - adatas={} - Ws={} - ss={} - As={} - species_indexer = [] - genes_indexer = [] - for sid in sams.keys(): - gs[sid] = gns[np.in1d(gns,q(sams[sid].adata.var_names))] - adatas[sid] = sams[sid].adata[:,gs[sid]] - Ws[sid] = adatas[sid].var["weights"].values - ss[sid] = std.fit_transform(adatas[sid].X).multiply(Ws[sid][None,:]).tocsr() - species_indexer.append(np.arange(ss[sid].shape[0])) - genes_indexer.append(np.arange(gs[sid].size)) - - for i in range(1,len(species_indexer)): - species_indexer[i] = species_indexer[i]+species_indexer[i-1].max()+1 - genes_indexer[i] = genes_indexer[i]+genes_indexer[i-1].max()+1 - - su = gnnm_corr.sum(0).A - su[su==0]=1 - gnnm_corr = gnnm_corr.multiply(1/su).tocsr() - - X = sp.sparse.block_diag(list(ss.values())).tocsr() - W = np.concatenate(list(Ws.values())).flatten() - - ttt=time.time() - if pairwise: - print('Translating feature spaces pairwise.') - Xtr = [] - for i,sid1 in enumerate(sams.keys()): - xtr = [] - for j,sid2 in enumerate(sams.keys()): - if i != j: - gnnm_corr_sub = gnnm_corr[genes_indexer[i]][:,genes_indexer[j]] - su = gnnm_corr_sub.sum(0).A - su[su==0]=1 - gnnm_corr_sub = gnnm_corr_sub.multiply(1/su).tocsr() - xtr.append(X[species_indexer[i]][:,genes_indexer[i]].dot(gnnm_corr_sub)) - xtr[-1] = std.fit_transform(xtr[-1]).multiply(W[genes_indexer[j]][None,:]) - else: - xtr.append(sp.sparse.csr_matrix((species_indexer[i].size,genes_indexer[i].size))) - Xtr.append(sp.sparse.hstack(xtr)) - Xtr = sp.sparse.vstack(Xtr) - else: - print('Translating feature spaces all-to-all.') - - Xtr = [] - for i,sid in enumerate(sams.keys()): - Xtr.append(X[species_indexer[i]].dot(gnnm_corr)) - Xtr[-1] = std.fit_transform(Xtr[-1]).multiply(W[None,:]) - Xtr = sp.sparse.vstack(Xtr) - Xc = (X + Xtr).tocsr() - - mus = [] - for i,sid in enumerate(sams.keys()): - mus.append(Xc[species_indexer[i]].mean(0).A.flatten()) - - gc.collect() - - print('Projecting data into joint latent space.',time.time()-ttt) - C = sp.linalg.block_diag(*[adatas[sid].varm["PCs_SAMap"] for sid in sams.keys()]) - M = np.vstack(mus).dot(C) - ttt=time.time() - it = 0; - PCAs=[] - for sid in sams.keys(): - PCAs.append(Xc[:,it : it + gs[sid].size].dot(adatas[sid].varm["PCs_SAMap"])) - it+=gs[sid].size - wpca = np.hstack(PCAs)#Xc.dot(C) - - print('Correcting data with means.',time.time()-ttt) - for i,sid in enumerate(sams.keys()): - ixq = species_indexer[i] - wpca[ixq] -= M[i] - output_dict["gnnm_corr"] = gnnm_corr - else: - std = StandardScaler(with_mean=False) - - gs = {} - adatas={} - Ws={} - ss={} - As={} - species_indexer = [] - mus=[] - for sid in sams.keys(): - adatas[sid] = sams[sid].adata - Ws[sid] = adatas[sid].var["weights"].values - ss[sid] = std.fit_transform(adatas[sid].X).multiply(Ws[sid][None,:]).tocsr() - mus.append(ss[sid].mean(0).A.flatten()) - species_indexer.append(np.arange(ss[sid].shape[0])) - for i in range(1,len(species_indexer)): - species_indexer[i] = species_indexer[i]+species_indexer[i-1].max()+1 - X = sp.sparse.vstack(list(ss.values())) - C = np.hstack([adatas[sid].varm["PCs_SAMap"] for sid in sams.keys()]) - wpca = X.dot(C) - M = np.vstack(mus).dot(C) - for i,sid in enumerate(sams.keys()): - ixq = species_indexer[i] - wpca[ixq] -= M[i] - - ixg = np.arange(wpca.shape[0]) - Xs = [] - Ys = [] - Vs = [] - for i,sid in enumerate(sams.keys()): - ixq = species_indexer[i] - query = wpca[ixq] - - for j,sid2 in enumerate(sams.keys()): - if i!=j: - ixr = species_indexer[j] - reference = wpca[ixr] - - b = _united_proj(query, reference, k=k) - - # sum-normalize each species individually. - su = b.sum(1).A - su[su==0]=1 - b = b.multiply(1/su).tocsr() - - A = pd.Series(index = np.arange(b.shape[0]), data = ixq) - B = pd.Series(index = np.arange(b.shape[1]), data = ixr) - - x,y = b.nonzero() - x,y = A[x].values,B[y].values - Xs.extend(x) - Ys.extend(y) - Vs.extend(b.data) - - knn = sp.sparse.coo_matrix((Vs,(Xs,Ys)),shape=(ixg.size,ixg.size)) - - output_dict["knn"] = knn.tocsr() - output_dict["wPCA"] = wpca - return output_dict - - -def _sparse_knn_ks(D, ks): - D1 = D.tocoo() - idr = np.argsort(D1.row) - D1.row[:] = D1.row[idr] - D1.col[:] = D1.col[idr] - D1.data[:] = D1.data[idr] - - row, ind = np.unique(D1.row, return_index=True) - ind = np.append(ind, D1.data.size) - for i in range(ind.size - 1): - idx = np.argsort(D1.data[ind[i] : ind[i + 1]]) - k = ks[row[i]] - if idx.size > k: - if k != 0: - idx = idx[:-k] - else: - idx = idx - D1.data[np.arange(ind[i], ind[i + 1])[idx]] = 0 - D1.eliminate_zeros() - return D1 - - -def _smart_expand(nnm, K, NH=3): - stage0 = nnm.copy() - S = [stage0] - running = stage0 - for i in range(1, NH + 1): - stage = running.dot(stage0) - running = stage - stage = stage.tolil() - for j in range(i): - stage[S[j].nonzero()] = 0 - stage = stage.tocsr() - S.append(stage) - - for i in range(len(S)): - s = _sparse_knn_ks(S[i], K).tocsr() - a, c = np.unique(s.nonzero()[0], return_counts=True) - numnz = np.zeros(s.shape[0], dtype="int32") - numnz[a] = c - K = K - numnz - K[K < 0] = 0 - S[i] = s - res = S[0] - for i in range(1, len(S)): - res = res + S[i] - return res diff --git a/samap/utils.py b/samap/utils.py deleted file mode 100755 index 1fd0a0d..0000000 --- a/samap/utils.py +++ /dev/null @@ -1,143 +0,0 @@ -from . import np, ut, pd - -def save_samap(sm,fn): - import dill - if len(fn.split('.pkl')) == 1: - fn = fn + '.pkl' - sm.path_to_file = fn - - #TODO: Clean this up... - try: - del sm.sam1.SamGui - except: - pass - try: - del sm.sam2.SamGui - except: - pass - try: - del sm.samap.SamGui - except: - pass - try: - del sm.SamapGui - except: - pass - try: - del sm.sam1.umap_obj - except: - pass; - try: - del sm.sam2.umap_obj - except: - pass; - - with open(fn,'wb') as f: - dill.dump(sm,f) - -def load_samap(fn): - import dill - if len(fn.split('.pkl')) == 1: - fn = fn + '.pkl' - with open(fn,'rb') as f: - sm = dill.load(f) - return sm - -def prepend_var_prefix(s, pre): - x = [x.split("_")[0] for x in s.adata.var_names] - vn = [] - for i,g in enumerate(s.adata.var_names): - if x[i] != pre: - vn.append(pre+"_"+g) - else: - vn.append(g) - s.adata.var_names = pd.Index(vn) - s.adata_raw.var_names = pd.Index(vn) - - -def df_to_dict(DF, key_key=None, val_key=[]): - if key_key is None: - index = list(DF.index) - else: - index = list(DF[key_key].values) - - if len(val_key) == 0: - val_key = list(DF.columns) - - a = [] - b = [] - for key in val_key: - if key != key_key: - a.extend(index) - b.extend(list(DF[key].values)) - a = np.array(a) - b = np.array(b) - - idx = np.argsort(a) - a = a[idx] - b = b[idx] - bounds = np.where(a[:-1] != a[1:])[0] + 1 - bounds = np.append(np.append(0, bounds), a.size) - bounds_left = bounds[:-1] - bounds_right = bounds[1:] - slists = [b[bounds_left[i] : bounds_right[i]] for i in range(bounds_left.size)] - d = dict(zip(np.unique(a), slists)) - return d - - -def to_vn(op): - return np.array(list(op[:, 0].astype("object") + ";" + op[:, 1].astype("object"))) - - -def to_vo(op): - return np.vstack((ut.extract_annotation(op, None, ";"))).T - - -def substr(x, s="_", ix=None, obj=False): - m = [] - if ix is not None: - for i in range(len(x)): - f = x[i].split(s) - ix = min(len(f) - 1, ix) - m.append(f[ix]) - return np.array(m).astype("object") if obj else np.array(m) - else: - ms = [] - ls = [] - for i in range(len(x)): - f = x[i].split(s) - m = [] - for ix in range(len(f)): - m.append(f[ix]) - ms.append(m) - ls.append(len(m)) - ml = max(ls) - for i in range(len(ms)): - ms[i].extend([""] * (ml - len(ms[i]))) - if ml - len(ms[i]) > 0: - ms[i] = np.concatenate(ms[i]) - ms = np.vstack(ms) - if obj: - ms = ms.astype("object") - MS = [] - for i in range(ms.shape[1]): - MS.append(ms[:, i]) - return MS - - -def sparse_knn(D, k): - D1 = D.tocoo() - idr = np.argsort(D1.row) - D1.row[:] = D1.row[idr] - D1.col[:] = D1.col[idr] - D1.data[:] = D1.data[idr] - - _, ind = np.unique(D1.row, return_index=True) - ind = np.append(ind, D1.data.size) - for i in range(ind.size - 1): - idx = np.argsort(D1.data[ind[i] : ind[i + 1]]) - if idx.size > k: - idx = idx[:-k] - D1.data[np.arange(ind[i], ind[i + 1])[idx]] = 0 - D1.eliminate_zeros() - return D1 diff --git a/src/samap/__init__.py b/src/samap/__init__.py new file mode 100644 index 0000000..cad2e7c --- /dev/null +++ b/src/samap/__init__.py @@ -0,0 +1,76 @@ +"""SAMap: Self-Assembling Manifold Mapping for cross-species single-cell analysis. + +SAMap is an algorithm for mapping single-cell datasets across species using +manifold alignment and gene homology information. + +Example +------- +>>> from samap import SAMAP +>>> sm = SAMAP( +... sams={'hu': 'human.h5ad', 'ms': 'mouse.h5ad'}, +... f_maps='maps/', +... ) +>>> sm.run() + +For more information, see the documentation at: +https://github.com/atarashansky/SAMap +""" + +from __future__ import annotations + +__version__ = "2.0.0" + +# Core imports +# Analysis imports +from samap.analysis import ( + GOEA, + CellTypeTriangles, + FunctionalEnrichment, + GenePairFinder, + GeneTriangles, + ParalogSubstitutions, + convert_eggnog_to_homologs, + find_cluster_markers, + get_mapping_scores, + sankey_plot, +) +from samap.core.mapping import SAMAP +from samap.io import load_samap, save_samap + +# Utilities +from samap.utils import ( + df_to_dict, + prepend_var_prefix, + sparse_knn, + substr, + to_vn, + to_vo, +) + +__all__ = [ + # Analysis + "GOEA", + # Core + "SAMAP", + "CellTypeTriangles", + "FunctionalEnrichment", + "GenePairFinder", + "GeneTriangles", + "ParalogSubstitutions", + # Version + "__version__", + "convert_eggnog_to_homologs", + "df_to_dict", + "find_cluster_markers", + "get_mapping_scores", + "load_samap", + # Utilities + "prepend_var_prefix", + "sankey_plot", + # I/O + "save_samap", + "sparse_knn", + "substr", + "to_vn", + "to_vo", +] diff --git a/src/samap/_constants.py b/src/samap/_constants.py new file mode 100644 index 0000000..032f7a6 --- /dev/null +++ b/src/samap/_constants.py @@ -0,0 +1,66 @@ +"""Constants used throughout SAMap.""" + +from __future__ import annotations + +# BLAST graph filtering +DEFAULT_EVAL_THRESHOLD: float = 1e-6 +DEFAULT_FILTER_THRESHOLD: float = 0.25 + +# UMAP parameters +UMAP_MIN_DIST: float = 0.1 +UMAP_SIZE_THRESHOLD: int = 10000 +UMAP_MAXITER_LARGE: int = 200 +UMAP_MAXITER_SMALL: int = 500 + +# Mapping parameters +DEFAULT_NUM_ITERATIONS: int = 3 +DEFAULT_CROSS_K: int = 20 +DEFAULT_NEIGHBORHOOD_SIZE: int = 3 +DEFAULT_LEIDEN_RESOLUTION: float = 3.0 + +# Correlation parameters +DEFAULT_CORRELATION_THRESHOLD: float = 0.0 +DEFAULT_ALIGNMENT_THRESHOLD: float = 0.1 +DEFAULT_EXPRESSION_THRESHOLD: float = 0.05 + +# SAM preprocessing parameters +DEFAULT_THRESH_LOW: float = 0.0 +DEFAULT_THRESH_HIGH: float = 0.96 +DEFAULT_MIN_EXPRESSION: int = 1 +DEFAULT_N_PCS: int = 100 +DEFAULT_K_NEIGHBORS: int = 20 +DEFAULT_N_GENES: int = 3000 + +# Marker gene parameters +DEFAULT_WEIGHT_THRESHOLD: float = 0.2 +DEFAULT_PVAL_THRESHOLD: float = 1e-2 +DEFAULT_N_TOP_GENES: int = 1000 + +# KOG category descriptions +KOG_TABLE: dict[str, str] = { + "A": "RNA processing and modification", + "B": "Chromatin structure and dynamics", + "C": "Energy production and conversion", + "D": "Cell cycle control, cell division, chromosome partitioning", + "E": "Amino acid transport and metabolism", + "F": "Nucleotide transport and metabolism", + "G": "Carbohydrate transport and metabolism", + "H": "Coenzyme transport and metabolism", + "I": "Lipid transport and metabolism", + "J": "Translation, ribosomal structure and biogenesis", + "K": "Transcription", + "L": "Replication, recombination, and repair", + "M": "Cell wall membrane/envelope biogenesis", + "N": "Cell motility", + "O": "Post-translational modification, protein turnover, chaperones", + "P": "Inorganic ion transport and metabolism", + "Q": "Secondary metabolites biosynthesis, transport and catabolism", + "R": "General function prediction only", + "S": "Function unknown", + "T": "Signal transduction mechanisms", + "U": "Intracellular trafficking, secretion, and vesicular transport", + "V": "Defense mechanisms", + "W": "Extracellular structures", + "Y": "Nuclear structure", + "Z": "Cytoskeleton", +} diff --git a/src/samap/_logging.py b/src/samap/_logging.py new file mode 100644 index 0000000..588283c --- /dev/null +++ b/src/samap/_logging.py @@ -0,0 +1,72 @@ +"""Logging configuration for SAMap.""" + +from __future__ import annotations + +import logging +import sys +from typing import TYPE_CHECKING + +if TYPE_CHECKING: + from typing import Literal + +_LOG_FORMAT = "%(asctime)s - %(name)s - %(levelname)s - %(message)s" +_DATE_FORMAT = "%Y-%m-%d %H:%M:%S" + + +def get_logger(name: str = "samap") -> logging.Logger: + """Get a logger instance for SAMap. + + Parameters + ---------- + name : str, optional + Name of the logger, by default "samap" + + Returns + ------- + logging.Logger + Configured logger instance + """ + logger = logging.getLogger(name) + + # Auto-configure if no handlers exist + if not logger.handlers and not logger.parent.handlers if logger.parent else not logger.handlers: + _setup_default_handler(logger) + + return logger + + +def _setup_default_handler(logger: logging.Logger) -> None: + """Set up default handler for a logger.""" + handler = logging.StreamHandler(sys.stderr) + handler.setFormatter(logging.Formatter("%(levelname)s: %(message)s")) + logger.addHandler(handler) + logger.setLevel(logging.INFO) + + +def setup_logging( + level: int | Literal["DEBUG", "INFO", "WARNING", "ERROR", "CRITICAL"] = logging.INFO, + format_string: str | None = None, +) -> None: + """Configure logging for SAMap. + + Parameters + ---------- + level : int or str, optional + Logging level, by default logging.INFO + format_string : str, optional + Custom format string, by default None (uses default format) + """ + if isinstance(level, str): + level = getattr(logging, level.upper()) + + fmt = format_string or _LOG_FORMAT + handler = logging.StreamHandler(sys.stderr) + handler.setFormatter(logging.Formatter(fmt, datefmt=_DATE_FORMAT)) + + logger = get_logger() + logger.addHandler(handler) + logger.setLevel(level) + + +# Create and configure module-level logger +logger = get_logger() diff --git a/src/samap/analysis/__init__.py b/src/samap/analysis/__init__.py new file mode 100644 index 0000000..205956b --- /dev/null +++ b/src/samap/analysis/__init__.py @@ -0,0 +1,27 @@ +"""Analysis functions for SAMap.""" + +from __future__ import annotations + +from samap.analysis.enrichment import GOEA, FunctionalEnrichment +from samap.analysis.gene_pairs import GenePairFinder, find_cluster_markers +from samap.analysis.plotting import sankey_plot +from samap.analysis.scores import ( + CellTypeTriangles, + GeneTriangles, + ParalogSubstitutions, + convert_eggnog_to_homologs, + get_mapping_scores, +) + +__all__ = [ + "GOEA", + "CellTypeTriangles", + "FunctionalEnrichment", + "GenePairFinder", + "GeneTriangles", + "ParalogSubstitutions", + "convert_eggnog_to_homologs", + "find_cluster_markers", + "get_mapping_scores", + "sankey_plot", +] diff --git a/src/samap/analysis/enrichment.py b/src/samap/analysis/enrichment.py new file mode 100644 index 0000000..aaad8d3 --- /dev/null +++ b/src/samap/analysis/enrichment.py @@ -0,0 +1,401 @@ +"""Gene enrichment analysis functions for SAMap.""" + +from __future__ import annotations + +import gc +from typing import TYPE_CHECKING + +import numpy as np +import pandas as pd +from scipy.stats import rankdata + +from samap._logging import logger +from samap.utils import substr + +if TYPE_CHECKING: + from typing import Any + + from numpy.typing import NDArray + + from samap.core.mapping import SAMAP + + +def _log_factorial(n: int) -> float: + """Compute log factorial.""" + return np.log(np.arange(1, n + 1)).sum() + + +def _log_binomial(n: int, k: int) -> float: + """Compute log binomial coefficient.""" + return _log_factorial(n) - (_log_factorial(k) + _log_factorial(n - k)) + + +def GOEA( + target_genes: NDArray[Any], + gene_sets: dict[str, NDArray[Any]] | pd.DataFrame, + df_key: str = "GO", + goterms: NDArray[Any] | None = None, + fdr_thresh: float = 0.25, + p_thresh: float = 1e-3, +) -> pd.DataFrame: + """Perform GO term Enrichment Analysis using the hypergeometric distribution. + + Parameters + ---------- + target_genes : array-like + List of target genes from which to find enriched GO terms. + gene_sets : dict or pd.DataFrame + Dictionary where keys are GO terms and values are gene lists. + OR DataFrame with genes as index and GO terms as values. + df_key : str, optional + Column name for GO terms if gene_sets is a DataFrame. Default 'GO'. + goterms : array-like, optional + If provided, only test these GO terms. + fdr_thresh : float, optional + FDR q-value threshold. Default 0.25. + p_thresh : float, optional + P-value threshold. Default 1e-3. + + Returns + ------- + pd.DataFrame + Enriched GO terms with FDR q-values, p-values, and associated genes. + """ + if isinstance(gene_sets, pd.DataFrame): + logger.info("Converting DataFrame into dictionary") + genes = np.array(list(gene_sets.index)) + agt = np.array(list(gene_sets[df_key].values)) + idx = np.argsort(agt) + genes = genes[idx] + agt = agt[idx] + bounds = np.where(agt[:-1] != agt[1:])[0] + 1 + bounds = np.append(np.append(0, bounds), agt.size) + bounds_left = bounds[:-1] + bounds_right = bounds[1:] + genes_lists = [genes[bounds_left[i] : bounds_right[i]] for i in range(bounds_left.size)] + gene_sets = dict(zip(np.unique(agt), genes_lists)) + + all_genes = np.unique(np.concatenate(list(gene_sets.values()))) + all_genes = np.array(all_genes) + + if goterms is None: + goterms = np.unique(list(gene_sets.keys())) + else: + goterms = goterms[np.isin(goterms, np.unique(list(gene_sets.keys())))] + + _, ix = np.unique(target_genes, return_index=True) + target_genes = target_genes[np.sort(ix)] + target_genes = target_genes[np.isin(target_genes, all_genes)] + + N = all_genes.size + + probs = [] + probs_genes = [] + + for goterm in goterms: + gene_set = np.array(gene_sets[goterm]) + B = gene_set.size + gene_set_in_target = gene_set[np.isin(gene_set, target_genes)] + b = gene_set_in_target.size + if b != 0: + n = target_genes.size + num_iter = min(n, B) + rng = np.arange(b, num_iter + 1) + probs.append( + sum( + [ + np.exp( + _log_binomial(n, i) + _log_binomial(N - n, B - i) - _log_binomial(N, B) + ) + for i in rng + ] + ) + ) + else: + probs.append(1.0) + probs_genes.append(gene_set_in_target) + + probs = np.array(probs) + probs_genes = np.array([";".join(x) for x in probs_genes]) + + fdr_q_probs = probs.size * probs / rankdata(probs, method="ordinal") + + filt = np.logical_and(fdr_q_probs < fdr_thresh, probs < p_thresh) + enriched_goterms = goterms[filt] + p_values = probs[filt] + fdr_q_probs = fdr_q_probs[filt] + probs_genes = probs_genes[filt] + + gns = probs_genes + result = pd.DataFrame(data=fdr_q_probs, index=enriched_goterms, columns=["fdr_q_value"]) + result["p_value"] = p_values + result["genes"] = gns + + return result.sort_values("p_value") + + +class FunctionalEnrichment: + """Functional enrichment analysis on gene pairs in mapped cell types. + + Parameters + ---------- + sm : SAMAP + SAMAP object. + dfs : dict + Dict of pandas DataFrames with functional annotations, keyed by species. + col_key : str + Column name with functional annotations. + keys : dict + Dict of obs column keys keyed by species. + delimiter : str, optional + Delimiter for multiple annotations. Default ''. + align_thr : float, optional + Alignment score threshold. Default 0.1. + limit_reference : bool, optional + If True, limit background genes to enriched ones. Default False. + n_top : int, optional + Number of top cells for alignment averaging. Default 0. + """ + + def __init__( + self, + sm: SAMAP, + dfs: dict[str, pd.DataFrame], + col_key: str, + keys: dict[str, str], + delimiter: str = "", + align_thr: float = 0.1, + limit_reference: bool = False, + n_top: int = 0, + ) -> None: + from samap.analysis.gene_pairs import GenePairFinder + + sams = sm.sams + + for sid in sm.ids: + sm.sams[sid] = sams[sid] + gc.collect() + + for k in dfs: + dfs[k].index = k + "_" + dfs[k].index + + A = pd.concat(list(dfs.values()), axis=0) + RES = pd.DataFrame(A[col_key]) + RES.columns = ["GO"] + RES = RES[(np.array(list(RES.values.flatten())).astype("str") != "nan")] + + data = [] + index = [] + for i in range(RES.shape[0]): + if delimiter == "": + items = list(RES.values[i][0]) + items = np.array([str(x) if str(x).isalpha() else "" for x in items]) + items = items[items != ""] + items = list(items) + else: + items = RES.values[i][0].split(delimiter) + + data.extend(items) + index.extend([RES.index[i]] * len(items)) + + RES = pd.DataFrame(index=index, data=data, columns=["GO"]) + genes = np.array(list(RES.index)) + agt = np.array(list(RES["GO"].values)) + idx = np.argsort(agt) + genes = genes[idx] + agt = agt[idx] + bounds = np.where(agt[:-1] != agt[1:])[0] + 1 + bounds = np.append(np.append(0, bounds), agt.size) + bounds_left = bounds[:-1] + bounds_right = bounds[1:] + genes_lists = [genes[bounds_left[i] : bounds_right[i]] for i in range(bounds_left.size)] + gene_sets = dict(zip(np.unique(agt), genes_lists)) + for cc in gene_sets: + gene_sets[cc] = np.unique(gene_sets[cc]) + + logger.info("Finding enriched gene pairs...") + gpf = GenePairFinder(sm, keys=keys) + gene_pairs = gpf.find_all(thr=align_thr, n_top=n_top) + + self.DICT: dict[str, NDArray[Any]] = {} + for c in gene_pairs.columns: + if "_pval1" not in c and "_pval2" not in c: + x = np.array(list(gene_pairs[c].values.flatten())).astype("str") + ff = x != "nan" + if ff.sum() > 0: + self.DICT[c] = x[ff] + + if limit_reference: + all_genes = np.unique( + np.concatenate(substr(np.concatenate(list(self.DICT.values())), ";")) + ) + else: + all_genes = np.unique(np.array(list(A.index))) + + for d in gene_sets: + gene_sets[d] = gene_sets[d][np.isin(gene_sets[d], all_genes)] + + self.gene_pairs = gene_pairs + self.CAT_NAMES = np.unique(np.array(list(RES["GO"]))) + self.GENE_SETS = gene_sets + self.RES = RES + + def calculate_enrichment( + self, verbose: bool = False + ) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame]: + """Calculate functional enrichment. + + Parameters + ---------- + verbose : bool, optional + If True, log progress. Default False. + + Returns + ------- + tuple + (enrichment_scores, num_enriched_genes, enriched_genes) DataFrames + """ + DICT = self.DICT + RES = self.RES + CAT_NAMES = self.CAT_NAMES + GENE_SETS = self.GENE_SETS + pairs = np.array(list(DICT.keys())) + all_nodes = np.unique(np.concatenate(substr(pairs, ";"))) + + CCG: dict[str, NDArray[Any]] = {} + for ik in range(len(all_nodes)): + genes = [] + nodes = all_nodes[ik] + for j in range(len(pairs)): + n1, n2 = pairs[j].split(";") + if n1 == nodes or n2 == nodes: + g1, g2 = substr(DICT[pairs[j]], ";") + genes.append(np.append(g1, g2)) + if len(genes) > 0: + genes = np.concatenate(genes) + genes = np.unique(genes) + else: + genes = np.array([]) + CCG[all_nodes[ik]] = genes + + HM = np.zeros((len(CAT_NAMES), len(all_nodes))) + HMe = np.zeros((len(CAT_NAMES), len(all_nodes))) + HMg = np.zeros((len(CAT_NAMES), len(all_nodes)), dtype="object") + for ii, cln in enumerate(all_nodes): + if verbose: + logger.info("Calculating functional enrichment for cell type %s", cln) + + g = CCG[cln] + + if g.size > 0: + gi = g[np.isin(g, np.array(list(RES.index)))] + ix = np.where(np.isin(np.array(list(RES.index)), gi))[0] + res = RES.iloc[ix] + goterms = np.unique(np.array(list(res["GO"]))) + goterms = goterms[goterms != "S"].flatten() + if goterms.size > 0: + result = GOEA(gi, GENE_SETS, goterms=goterms, fdr_thresh=100, p_thresh=100) + + lens = np.array([len(np.unique(x.split(";"))) for x in result["genes"].values]) + F = -np.log10(result["p_value"]) + gt, vals = F.index, F.values + Z = pd.DataFrame(data=np.arange(CAT_NAMES.size)[None, :], columns=CAT_NAMES) + if gt.size > 0: + HM[Z[gt].values.flatten(), ii] = vals + HMe[Z[gt].values.flatten(), ii] = lens + HMg[Z[gt].values.flatten(), ii] = [ + ";".join(np.unique(x.split(";"))) for x in result["genes"].values + ] + + SC = pd.DataFrame(data=HM, index=CAT_NAMES, columns=all_nodes).T + SCe = pd.DataFrame(data=HMe, index=CAT_NAMES, columns=all_nodes).T + SCg = pd.DataFrame(data=HMg, index=CAT_NAMES, columns=all_nodes).T + SCg.values[SCg.values == 0] = "" + + self.ENRICHMENT_SCORES = SC + self.NUM_ENRICHED_GENES = SCe + self.ENRICHED_GENES = SCg + + return self.ENRICHMENT_SCORES, self.NUM_ENRICHED_GENES, self.ENRICHED_GENES + + def plot_enrichment( + self, + cell_types: list[str] | None = None, + pval_thr: float = 2.0, + msize: float = 50, + ) -> tuple[Any, Any]: + """Create enrichment dot plot. + + Parameters + ---------- + cell_types : list, optional + Cell types to include. Default all. + pval_thr : float, optional + -log10 p-value threshold. Default 2.0. + msize : float, optional + Marker size. Default 50. + + Returns + ------- + tuple + (fig, ax) matplotlib objects + """ + import matplotlib + import matplotlib.pyplot as plt + from scipy.cluster.hierarchy import dendrogram, linkage + + matplotlib.rcParams["pdf.fonttype"] = 42 + matplotlib.rcParams["ps.fonttype"] = 42 + + if cell_types is None: + cell_types = [] + + SC = self.ENRICHMENT_SCORES + SCe = self.NUM_ENRICHED_GENES + SCg = self.ENRICHED_GENES + + if len(cell_types) > 0: + SC = SC.T[cell_types].T + SCe = SCe.T[cell_types].T + SCg = SCg.T[cell_types].T + + SC.values[SC.values < pval_thr] = 0 + SCe.values[SC.values < pval_thr] = 0 + SCg.values[SC.values < pval_thr] = "" + SCg = SCg.astype("str") + SCg.values[SCg.values == "nan"] = "" + + ixrow = np.array( + dendrogram(linkage(SC.values.T, method="ward", metric="euclidean"), no_plot=True)["ivl"] + ).astype("int") + ixcol = np.array( + dendrogram(linkage(SC.values, method="ward", metric="euclidean"), no_plot=True)["ivl"] + ).astype("int") + + SC = SC.iloc[ixcol].iloc[:, ixrow] + SCe = SCe.iloc[ixcol].iloc[:, ixrow] + SCg = SCg.iloc[ixcol].iloc[:, ixrow] + + x, y = ( + np.tile(np.arange(SC.shape[0]), SC.shape[1]), + np.repeat(np.arange(SC.shape[1]), SC.shape[0]), + ) + co = SC.values[x, y].flatten() + ms = SCe.values[x, y].flatten() + ms = ms / ms.max() + x = x.max() - x + ms = ms * msize + ms[np.logical_and(ms < 0.15, ms > 0)] = 0.15 + + fig, ax = plt.subplots() + fig.set_size_inches((7 * SC.shape[0] / SC.shape[1], 7)) + + scat = ax.scatter(x, y, c=co, s=ms, cmap="seismic", edgecolor="k", linewidth=0.5, vmin=3) + fig.colorbar(scat, pad=0.02) + ax.set_yticks(np.arange(SC.shape[1])) + ax.set_yticklabels(SC.columns, ha="right", rotation=0) + ax.set_xticks(np.arange(SC.shape[0])) + ax.set_xticklabels(SC.index[::-1], ha="right", rotation=45) + ax.invert_yaxis() + ax.invert_xaxis() + return fig, ax diff --git a/src/samap/analysis/gene_pairs.py b/src/samap/analysis/gene_pairs.py new file mode 100644 index 0000000..d90dc6b --- /dev/null +++ b/src/samap/analysis/gene_pairs.py @@ -0,0 +1,370 @@ +"""Gene pair finding functions for SAMap.""" + +from __future__ import annotations + +import warnings +from typing import TYPE_CHECKING + +import numpy as np +import pandas as pd +import scanpy as sc +import sklearn.utils.sparsefuncs as sf + +from samap._logging import logger +from samap.utils import substr, to_vn + +if TYPE_CHECKING: + from typing import Any + + from numpy.typing import NDArray + from samalg import SAM + + from samap.core.mapping import SAMAP + + +def _q(x: Any) -> NDArray[Any]: + """Convert input to numpy array.""" + return np.array(list(x)) + + +class GenePairFinder: + """Find enriched gene pairs in cell type mappings. + + Parameters + ---------- + sm : SAMAP + SAMAP object. + keys : dict, optional + Annotation keys per species. Default uses 'leiden_clusters'. + """ + + def __init__(self, sm: SAMAP, keys: dict[str, str] | None = None) -> None: + if keys is None: + keys = dict.fromkeys(sm.sams.keys(), "leiden_clusters") + self.sm = sm + self.sams = sm.sams + self.s3 = sm.samap + self.gns = _q(sm.samap.adata.var_names) + self.gnnm = sm.samap.adata.varp["homology_graph_reweighted"] + self.gns_dict = sm.gns_dict + + self.ids = sm.ids + + mus = {} + stds = {} + for sid in self.sams: + self.sams[sid].adata.obs[keys[sid]] = self.sams[sid].adata.obs[keys[sid]].astype("str") + mu, var = sf.mean_variance_axis(self.sams[sid].adata[:, self.gns_dict[sid]].X, axis=0) + var[var == 0] = 1 + var = var**0.5 + mus[sid] = pd.Series(data=mu, index=self.gns_dict[sid]) + stds[sid] = pd.Series(data=var, index=self.gns_dict[sid]) + + self.mus = mus + self.stds = stds + self.keys = keys + self.find_markers() + + def find_markers(self) -> None: + """Find cluster-specific markers for all species.""" + for sid in self.sams: + logger.info("Finding cluster-specific markers in %s:%s.", sid, self.keys[sid]) + import gc + + if self.keys[sid] + "_scores" not in self.sams[sid].adata.varm: + find_cluster_markers(self.sams[sid], self.keys[sid]) + gc.collect() + + def find_all( + self, + n: str | None = None, + align_thr: float = 0.1, + n_top: int = 0, + **kwargs: Any, + ) -> pd.DataFrame: + """Find enriched gene pairs in all mapped cell type pairs. + + Parameters + ---------- + n : str, optional + If provided, find pairs for cell types connected to `n`. + align_thr : float, optional + Alignment score threshold. Default 0.1. + n_top : int, optional + Number of top cells for averaging. Default 0. + + Returns + ------- + pd.DataFrame + Table of enriched gene pairs for each cell type pair. + """ + from samap.analysis.scores import get_mapping_scores + + _, M = get_mapping_scores(self.sm, self.keys, n_top=n_top) + ax = _q(M.index) + data = M.values.copy() + data[data < align_thr] = 0 + x, y = data.nonzero() + ct1, ct2 = ax[x], ax[y] + if n is not None: + f1 = ct1 == n + f2 = ct2 == n + f = np.logical_or(f1, f2) + else: + f = np.array([True] * ct2.size) + + ct1 = ct1[f] + ct2 = ct2[f] + ct1, ct2 = np.unique(np.sort(np.vstack((ct1, ct2)).T, axis=1), axis=0).T + res = {} + for i in range(ct1.size): + a = "_".join(ct1[i].split("_")[1:]) + b = "_".join(ct2[i].split("_")[1:]) + logger.info( + "Calculating gene pairs for the mapping: %s;%s to %s;%s", + ct1[i].split("_")[0], + a, + ct2[i].split("_")[0], + b, + ) + res[f"{ct1[i]};{ct2[i]}"] = self.find_genes(ct1[i], ct2[i], **kwargs) + + cols = [] + col_names = [] + for k in res: + col_names.append(k) + col_names.append(k + "_pval1") + col_names.append(k + "_pval2") + cols.append(res[k][0]) + cols.append(res[k][-2]) + cols.append(res[k][-1]) + return pd.DataFrame(cols, index=col_names).fillna(np.nan).T + + def find_genes( + self, + n1: str, + n2: str, + w1t: float = 0.2, + w2t: float = 0.2, + n_genes: int = 1000, + thr: float = 1e-2, + ) -> tuple[NDArray[Any], NDArray[Any], NDArray[Any], NDArray[Any], NDArray[Any]]: + """Find enriched gene pairs in a particular cell type pair. + + Parameters + ---------- + n1 : str + Cell type ID from species 1. + n2 : str + Cell type ID from species 2. + w1t, w2t : float, optional + SAM weight thresholds. Default 0.2. + n_genes : int, optional + Top ranked gene pairs to consider. Default 1000. + thr : float, optional + Differential expression p-value threshold. Default 0.01. + + Returns + ------- + tuple + (gene_pairs, genes1, genes2, pvals1, pvals2) + """ + n1 = str(n1) + n2 = str(n2) + id1, id2 = n1.split("_")[0], n2.split("_")[0] + sam1, sam2 = self.sams[id1], self.sams[id2] + + n1, n2 = "_".join(n1.split("_")[1:]), "_".join(n2.split("_")[1:]) + assert n1 in _q(self.sams[id1].adata.obs[self.keys[id1]]) + assert n2 in _q(self.sams[id2].adata.obs[self.keys[id2]]) + + m, gpairs = self._find_link_genes_avg(n1, n2, id1, id2, w1t=w1t, w2t=w2t, expr_thr=0.05) + + self.gene_pair_scores = pd.Series(index=gpairs, data=m) + + G = _q(gpairs[np.argsort(-m)[:n_genes]]) + G1 = substr(G, ";", 0) + G2 = substr(G, ";", 1) + pvals1 = _q(sam1.adata.varm[self.keys[id1] + "_pvals"][n1][G1]) + pvals2 = _q(sam2.adata.varm[self.keys[id2] + "_pvals"][n2][G2]) + filt = np.logical_and(pvals1 < thr, pvals2 < thr) + G = _q(G[filt]) + G1 = substr(G, ";", 0) + G2 = substr(G, ";", 1) + _, ix1 = np.unique(G1, return_index=True) + _, ix2 = np.unique(G2, return_index=True) + G1 = G1[np.sort(ix1)] + G2 = G2[np.sort(ix2)] + return G, G1, G2, pvals1[filt], pvals2[filt] + + def _find_link_genes_avg( + self, + c1: str, + c2: str, + id1: str, + id2: str, + w1t: float = 0.35, + w2t: float = 0.35, + expr_thr: float = 0.05, + ) -> tuple[NDArray[Any], NDArray[Any]]: + """Find linked genes by average expression.""" + mus = self.mus + stds = self.stds + sams = self.sams + + keys = self.keys + sam3 = self.s3 + gnnm = self.gnnm + gns = self.gns + + xs = [] + for sid in [id1, id2]: + xs.append(sams[sid].get_labels(keys[sid]).astype("str").astype("object")) + x1, x2 = xs + g1, g2 = gns[np.vstack(gnnm.nonzero())] + gs1, gs2 = _q([x.split("_")[0] for x in g1]), _q([x.split("_")[0] for x in g2]) + filt = np.logical_and(gs1 == id1, gs2 == id2) + g1 = g1[filt] + g2 = g2[filt] + sam1, sam2 = sams[id1], sams[id2] + mu1, std1, mu2, std2 = ( + mus[id1][g1].values, + stds[id1][g1].values, + mus[id2][g2].values, + stds[id2][g2].values, + ) + + X1 = _sparse_sub_standardize(sam1.adata[:, g1].X[x1 == c1, :], mu1, std1) + X2 = _sparse_sub_standardize(sam2.adata[:, g2].X[x2 == c2, :], mu2, std2) + species_mask1 = (sam3.adata.obs["species"] == id1).values + species_mask2 = (sam3.adata.obs["species"] == id2).values + a, b = sam3.adata.obsp["connectivities"][species_mask1, :][:, species_mask2][x1 == c1, :][ + :, x2 == c2 + ].nonzero() + c, d = sam3.adata.obsp["connectivities"][species_mask2, :][:, species_mask1][x2 == c2, :][ + :, x1 == c1 + ].nonzero() + + pairs = np.unique(np.vstack((np.vstack((a, b)).T, np.vstack((d, c)).T)), axis=0) + + av1 = np.asarray(X1[np.unique(pairs[:, 0]), :].mean(0)).flatten() + av2 = np.asarray(X2[np.unique(pairs[:, 1]), :].mean(0)).flatten() + sav1 = (av1 - av1.mean()) / av1.std() + sav2 = (av2 - av2.mean()) / av2.std() + sav1[sav1 < 0] = 0 + sav2[sav2 < 0] = 0 + val = sav1 * sav2 / sav1.size + X1.data[:] = 1 + X2.data[:] = 1 + min_expr = (np.asarray(X1.mean(0)).flatten() > expr_thr) * ( + np.asarray(X2.mean(0)).flatten() > expr_thr + ) + + w1 = sam1.adata.var["weights"][g1].values.copy() + w2 = sam2.adata.var["weights"][g2].values.copy() + w1[w1 < 0.2] = 0 + w2[w2 < 0.2] = 0 + w1[w1 > 0] = 1 + w2[w2 > 0] = 1 + return val * w1 * w2 * min_expr, to_vn(np.array([g1, g2]).T) + + +def find_cluster_markers( + sam: SAM, key: str, inplace: bool = True +) -> tuple[pd.DataFrame, pd.DataFrame, pd.DataFrame] | None: + """Find differentially expressed genes for cell type labels. + + Parameters + ---------- + sam : SAM + SAM object. + key : str + Column in `sam.adata.obs` for differential expression. + inplace : bool, optional + If True, deposit results in sam.adata.varm. Default True. + + Returns + ------- + tuple or None + If not inplace, returns (NAMES, PVALS, SCORES) DataFrames. + """ + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + + a, c = np.unique(_q(sam.adata.obs[key]), return_counts=True) + t = a[c == 1] + + adata = sam.adata[np.isin(_q(sam.adata.obs[key]), a[c == 1], invert=True)].copy() + sc.tl.rank_genes_groups( + adata, + key, + method="wilcoxon", + n_genes=sam.adata.shape[1], + use_raw=False, + layer=None, + ) + + sam.adata.uns["rank_genes_groups"] = adata.uns["rank_genes_groups"] + + NAMES = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["names"]) + PVALS = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["pvals"]) + SCORES = pd.DataFrame(sam.adata.uns["rank_genes_groups"]["scores"]) + if not inplace: + return NAMES, PVALS, SCORES + dfs1 = [] + dfs2 = [] + for i in range(SCORES.shape[1]): + names = NAMES.iloc[:, i] + scores = SCORES.iloc[:, i] + pvals = PVALS.iloc[:, i] + pvals[scores < 0] = 1.0 + scores[scores < 0] = 0 + pvals = _q(pvals) + scores = _q(scores) + + dfs1.append( + pd.DataFrame(data=scores[None, :], index=[SCORES.columns[i]], columns=names)[ + sam.adata.var_names + ].T + ) + dfs2.append( + pd.DataFrame(data=pvals[None, :], index=[SCORES.columns[i]], columns=names)[ + sam.adata.var_names + ].T + ) + df1 = pd.concat(dfs1, axis=1) + df2 = pd.concat(dfs2, axis=1) + + # Safer attribute assignment + if not hasattr(sam.adata.varm, "dim_names") or sam.adata.varm.dim_names is None: + sam.adata.varm.dim_names = sam.adata.var_names + sam.adata.varm[key + "_scores"] = df1 + sam.adata.varm[key + "_pvals"] = df2 + + for i in range(t.size): + sam.adata.varm[key + "_scores"][t[i]] = 0 + sam.adata.varm[key + "_pvals"][t[i]] = 1 + + return None + + +def _sparse_sub_standardize( + X: Any, + mu: NDArray[Any], + var: NDArray[Any], + rows: bool = False, +) -> Any: + """Standardize sparse matrix by subtraction.""" + x, y = X.nonzero() + if not rows: + Xs = X.copy() + Xs.data[:] = (X.data - mu[y]) / var[y] + else: + mu, var = sf.mean_variance_axis(X, axis=1) + var = var**0.5 + var[var == 0] = 1 + Xs = X.copy() + Xs.data[:] = (X.data - mu[x]) / var[x] + Xs.data[Xs.data < 0] = 0 + Xs.eliminate_zeros() + return Xs diff --git a/src/samap/analysis/plotting.py b/src/samap/analysis/plotting.py new file mode 100644 index 0000000..b8475cc --- /dev/null +++ b/src/samap/analysis/plotting.py @@ -0,0 +1,229 @@ +"""Plotting functions for SAMap.""" + +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np +import pandas as pd + +if TYPE_CHECKING: + from typing import Any + + from numpy.typing import NDArray + + +def _q(x: Any) -> NDArray[Any]: + """Convert input to numpy array.""" + return np.array(list(x)) + + +def sankey_plot( + M: pd.DataFrame, + species_order: list[str] | None = None, + align_thr: float = 0.1, + **params: Any, +) -> Any: + """Generate a sankey plot of cell type mappings. + + Parameters + ---------- + M : pd.DataFrame + Mapping table from `get_mapping_scores` (second output). + species_order : list, optional + Order of species left-to-right, e.g., ['hu', 'le', 'ms']. + align_thr : float, optional + Alignment score threshold. Default 0.1. + **params + Keyword arguments for customization: + - node_padding: int, padding between nodes (default 20) + - node_thickness: int, thickness of nodes (default 20) + - node_opacity: float, opacity of nodes (default 1.0) + - link_opacity: float, opacity of links (default 0.5) + - height: int, figure height in pixels (default 800) + - width: int, figure width in pixels (default 1000) + - bgcolor: str, background color (default "white") + - font_size: int, label font size (default 12) + - font_color: str, label font color (default "black") + - title: str, plot title (default None) + - colorscale: str, colorscale for nodes (default "Viridis") + + Returns + ------- + plotly.graph_objects.Figure + Sankey plot figure. + + Raises + ------ + ImportError + If plotly is not installed. + """ + try: + import plotly.graph_objects as go + import plotly.io as pio + except ImportError: + raise ImportError( + "Please install plotly with `pip install plotly`. " + "For Jupyter support, also run: pip install jupyterlab ipywidgets" + ) from None + + # Auto-detect notebook environment and set renderer + if pio.renderers.default == "plotly_mimetype": + try: + # Check if we're in a Jupyter environment + get_ipython() # type: ignore[name-defined] + pio.renderers.default = "notebook" + except NameError: + pass # Not in IPython/Jupyter + + if species_order is not None: + ids = np.array(species_order) + else: + ids = np.unique([x.split("_")[0] for x in M.index]) + + # Build source/target/value data from mapping matrix + if len(ids) > 2: + d = M.values.copy() + d[d < align_thr] = 0 + x, y = d.nonzero() + x, y = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0).T + values = d[x, y] + nodes = _q(M.index) + + node_pairs = nodes[np.vstack((x, y)).T] + sn1 = _q([xi.split("_")[0] for xi in node_pairs[:, 0]]) + sn2 = _q([xi.split("_")[0] for xi in node_pairs[:, 1]]) + # Filter to only adjacent species pairs in the ordering + filt = np.logical_or( + np.logical_or( + np.logical_and(sn1 == ids[0], sn2 == ids[1]), + np.logical_and(sn1 == ids[1], sn2 == ids[0]), + ), + np.logical_or( + np.logical_and(sn1 == ids[1], sn2 == ids[2]), + np.logical_and(sn1 == ids[2], sn2 == ids[1]), + ), + ) + x, y, values = x[filt], y[filt], values[filt] + + # Create depth mapping for node ordering + depth_dict = dict(zip(ids, list(np.arange(len(ids))))) + data = nodes[np.vstack((x, y))].T + # Ensure source comes before target in species order + for i in range(data.shape[0]): + if depth_dict[data[i, 0].split("_")[0]] > depth_dict[data[i, 1].split("_")[0]]: + data[i, :] = data[i, ::-1] + R = pd.DataFrame(data=data, columns=["source", "target"]) + R["value"] = values + else: + d = M.values.copy() + d[d < align_thr] = 0 + x, y = d.nonzero() + x, y = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0).T + values = d[x, y] + nodes = _q(M.index) + R = pd.DataFrame(data=nodes[np.vstack((x, y))].T, columns=["source", "target"]) + R["value"] = values + depth_dict = None + + # Build node list from unique sources and targets + all_nodes = pd.concat([R["source"], R["target"]]).unique() + node_to_idx = {node: idx for idx, node in enumerate(all_nodes)} + + # Map source/target names to indices + source_indices = [node_to_idx[src] for src in R["source"]] + target_indices = [node_to_idx[tgt] for tgt in R["target"]] + + # Assign colors based on species + species_list = [node.split("_")[0] for node in all_nodes] + unique_species = list(dict.fromkeys(species_list)) # preserve order + params.get("colorscale", "Viridis") + + # Generate colors for each species + n_species = len(unique_species) + if n_species <= 10: + # Use qualitative colors for small number of species + default_colors = [ + "#1f77b4", + "#ff7f0e", + "#2ca02c", + "#d62728", + "#9467bd", + "#8c564b", + "#e377c2", + "#7f7f7f", + "#bcbd22", + "#17becf", + ] + species_colors = { + sp: default_colors[i % len(default_colors)] for i, sp in enumerate(unique_species) + } + else: + # Fall back to colorscale + import colorsys + + species_colors = {} + for i, sp in enumerate(unique_species): + hue = i / n_species + rgb = colorsys.hls_to_rgb(hue, 0.5, 0.7) + species_colors[sp] = f"rgb({int(rgb[0] * 255)},{int(rgb[1] * 255)},{int(rgb[2] * 255)})" + + node_colors = [species_colors[sp] for sp in species_list] + + # Create link colors (lighter versions of source node colors) + link_opacity = params.get("link_opacity", 0.5) + link_colors = [] + for src in R["source"]: + sp = src.split("_")[0] + base_color = species_colors[sp] + # Add opacity to the color + if base_color.startswith("#"): + r = int(base_color[1:3], 16) + g = int(base_color[3:5], 16) + b = int(base_color[5:7], 16) + link_colors.append(f"rgba({r},{g},{b},{link_opacity})") + else: + link_colors.append(base_color.replace("rgb", "rgba").replace(")", f",{link_opacity})")) + + # Extract parameters + node_padding = params.get("node_padding", 20) + node_thickness = params.get("node_thickness", 20) + params.get("node_opacity", 1.0) + height = params.get("height", 800) + width = params.get("width", 1000) + bgcolor = params.get("bgcolor", "white") + font_size = params.get("font_size", 12) + font_color = params.get("font_color", "black") + title = params.get("title") + + # Create the Sankey diagram + fig = go.Figure( + data=[ + go.Sankey( + node={ + "pad": node_padding, + "thickness": node_thickness, + "line": {"color": "black", "width": 0.5}, + "label": list(all_nodes), + "color": node_colors, + }, + link={ + "source": source_indices, + "target": target_indices, + "value": list(R["value"]), + "color": link_colors, + }, + ) + ] + ) + + fig.update_layout( + title={"text": title} if title else None, + font={"size": font_size, "color": font_color}, + paper_bgcolor=bgcolor, + plot_bgcolor=bgcolor, + height=height, + width=width, + ) + + return fig diff --git a/src/samap/analysis/scores.py b/src/samap/analysis/scores.py new file mode 100644 index 0000000..2bdc7f6 --- /dev/null +++ b/src/samap/analysis/scores.py @@ -0,0 +1,733 @@ +"""Mapping score functions for SAMap.""" + +from __future__ import annotations + +import warnings +from typing import TYPE_CHECKING + +import networkx as nx +import numpy as np +import pandas as pd +import scipy as sp +from samalg import SAM + +from samap.utils import df_to_dict, substr, to_vn, to_vo + +if TYPE_CHECKING: + from typing import Any + + from numpy.typing import NDArray + + from samap.core.mapping import SAMAP + + +def _q(x: Any) -> NDArray[Any]: + """Convert input to numpy array.""" + return np.array(list(x)) + + +def _compute_csim( + samap: SAM, + key: str, + X: sp.sparse.csr_matrix | None = None, + prepend: bool = True, + n_top: int = 0, +) -> tuple[NDArray[Any], NDArray[Any]]: + """Compute cell similarity matrix.""" + splabels = _q(samap.adata.obs["species"]) + skeys = splabels[np.sort(np.unique(splabels, return_index=True)[1])] + + cl = [] + clu = [] + for sid in skeys: + if prepend: + cl.append( + sid + + "_" + + _q(samap.adata.obs[key])[samap.adata.obs["species"] == sid] + .astype("str") + .astype("object") + ) + else: + cl.append(_q(samap.adata.obs[key])[samap.adata.obs["species"] == sid]) + clu.append(np.unique(cl[-1])) + + clu = np.concatenate(clu) + cl = np.concatenate(cl) + + CSIM = np.zeros((clu.size, clu.size)) + if X is None: + X = samap.adata.obsp["connectivities"].copy() + + xi, yi = X.nonzero() + spxi = splabels[xi] + spyi = splabels[yi] + + filt = spxi != spyi + di = X.data[filt] + xi = xi[filt] + yi = yi[filt] + + px, py = xi, cl[yi] + p = px.astype("str").astype("object") + ";" + py.astype("object") + + A = pd.DataFrame(data=np.vstack((p, di)).T, columns=["x", "y"]) + valdict = df_to_dict(A, key_key="x", val_key="y") + cell_scores = [valdict[k].sum() for k in valdict] + ixer = pd.Series(data=np.arange(clu.size), index=clu) + if len(valdict.keys()) > 0: + xc, yc = substr(list(valdict.keys()), ";") + xc = xc.astype("int") + yc = ixer[yc].values + cell_cluster_scores = sp.sparse.coo_matrix( + (cell_scores, (xc, yc)), shape=(X.shape[0], clu.size) + ).toarray() + + for i, c in enumerate(clu): + if n_top > 0: + CSIM[i, :] = np.sort(cell_cluster_scores[cl == c], axis=0)[-n_top:].mean(0) + else: + CSIM[i, :] = cell_cluster_scores[cl == c].mean(0) + + CSIM = np.stack((CSIM, CSIM.T), axis=2).max(2) + CSIMth = CSIM / samap.adata.uns["mapping_K"] + return CSIMth, clu + else: + return np.zeros((clu.size, clu.size)), clu + + +def get_mapping_scores( + sm: SAMAP, + keys: dict[str, str], + n_top: int = 0, +) -> tuple[pd.DataFrame, pd.DataFrame]: + """Calculate mapping scores between cell types. + + Parameters + ---------- + sm : SAMAP + SAMAP object. + keys : dict + Annotation vector keys for species. + n_top : int, optional + Number of top cells for averaging. Default 0. + + Returns + ------- + tuple + (D, A) - table of highest scores and pairwise mapping table. + """ + if len(list(keys.keys())) < len(list(sm.sams.keys())): + samap = SAM( + counts=sm.samap.adata[np.isin(sm.samap.adata.obs["species"], list(keys.keys()))] + ) + else: + samap = sm.samap + + ix = np.unique(samap.adata.obs["species"], return_index=True)[1] + skeys = _q(samap.adata.obs["species"])[np.sort(ix)] + + clusters = [] + for sid in skeys: + clusters.append(_q([sid + "_" + str(x) for x in sm.sams[sid].adata.obs[keys[sid]]])) + + cl = np.concatenate(clusters) + label = "{}_mapping_scores".format(";".join([keys[sid] for sid in skeys])) + samap.adata.obs[label] = pd.Categorical(cl) + + CSIMth, clu = _compute_csim(samap, label, n_top=n_top, prepend=False) + + A = pd.DataFrame(data=CSIMth, index=clu, columns=clu) + i = np.argsort(-A.values.max(0).flatten()) + H = [] + C = [] + for idx in range(A.shape[1]): + x = A.iloc[:, i[idx]].sort_values(ascending=False) + H.append(np.vstack((x.index, x.values)).T) + C.append(A.columns[i[idx]]) + C.append(A.columns[i[idx]]) + H = np.hstack(H) + D = pd.DataFrame(data=H, columns=[C, ["Cluster", "Alignment score"] * (H.shape[1] // 2)]) + return D, A + + +def ParalogSubstitutions( + sm: SAMAP, + ortholog_pairs: NDArray[Any], + paralog_pairs: NDArray[Any] | None = None, + psub_thr: float = 0.3, +) -> pd.DataFrame: + """Identify paralog substitutions. + + Parameters + ---------- + sm : SAMAP + SAMAP object. + ortholog_pairs : ndarray + Nx2 array of ortholog pairs. + paralog_pairs : ndarray, optional + Nx2 array of paralog pairs. + psub_thr : float, optional + Correlation difference threshold. Default 0.3. + + Returns + ------- + pd.DataFrame + Table of paralog substitutions. + """ + if paralog_pairs is not None: + ids1 = np.array([x.split("_")[0] for x in paralog_pairs[:, 0]]) + ids2 = np.array([x.split("_")[0] for x in paralog_pairs[:, 1]]) + ix = np.where(ids1 == ids2)[0] + ixnot = np.where(ids1 != ids2)[0] + + if ix.size > 0: + pps = paralog_pairs[ix] + + ZZ1: dict[str, list[str]] = {} + ZZ2: dict[str, list[str]] = {} + for i in range(pps.shape[0]): + L = ZZ1.get(pps[i, 0], []) + L.append(pps[i, 1]) + ZZ1[pps[i, 0]] = L + + L = ZZ2.get(pps[i, 1], []) + L.append(pps[i, 0]) + ZZ2[pps[i, 1]] = L + + keys = list(ZZ1.keys()) + for k in keys: + L = ZZ2.get(k, []) + L.extend(ZZ1[k]) + ZZ2[k] = list(np.unique(L)) + + ZZ = ZZ2 + + L1 = [] + L2 = [] + for i in range(ortholog_pairs.shape[0]): + x = ZZ.get(ortholog_pairs[i, 0], []) + L1.extend([ortholog_pairs[i, 1]] * len(x)) + L2.extend(x) + + x = ZZ.get(ortholog_pairs[i, 1], []) + L1.extend([ortholog_pairs[i, 0]] * len(x)) + L2.extend(x) + + L = np.vstack((L2, L1)).T + pps = np.unique(np.sort(L, axis=1), axis=0) + + paralog_pairs = np.unique( + np.sort(np.vstack((pps, paralog_pairs[ixnot])), axis=1), axis=0 + ) + + smp = sm.samap + + gnnm = smp.adata.varp["homology_graph_reweighted"] + gn = _q(smp.adata.var_names) + + ortholog_pairs = np.sort(ortholog_pairs, axis=1) + + ortholog_pairs = ortholog_pairs[ + np.logical_and(np.isin(ortholog_pairs[:, 0], gn), np.isin(ortholog_pairs[:, 1], gn)) + ] + if paralog_pairs is None: + paralog_pairs = gn[np.vstack(smp.adata.varp["homology_graph"].nonzero()).T] + else: + paralog_pairs = paralog_pairs[ + np.logical_and(np.isin(paralog_pairs[:, 0], gn), np.isin(paralog_pairs[:, 1], gn)) + ] + + paralog_pairs = np.sort(paralog_pairs, axis=1) + + paralog_pairs = paralog_pairs[ + np.isin( + to_vn(paralog_pairs), + np.append(to_vn(ortholog_pairs), to_vn(ortholog_pairs[:, ::-1])), + invert=True, + ) + ] + + A = pd.DataFrame(data=np.arange(gn.size)[None, :], columns=gn) + xp, yp = ( + A[paralog_pairs[:, 0]].values.flatten(), + A[paralog_pairs[:, 1]].values.flatten(), + ) + xp, yp = np.unique(np.vstack((np.vstack((xp, yp)).T, np.vstack((yp, xp)).T)), axis=0).T + + xo, yo = ( + A[ortholog_pairs[:, 0]].values.flatten(), + A[ortholog_pairs[:, 1]].values.flatten(), + ) + xo, yo = np.unique(np.vstack((np.vstack((xo, yo)).T, np.vstack((yo, xo)).T)), axis=0).T + A = pd.DataFrame(data=np.vstack((xp, yp)).T, columns=["x", "y"]) + pairdict = df_to_dict(A, key_key="x", val_key="y") + Xp = [] + Yp = [] + Xo = [] + Yo = [] + for i in range(xo.size): + y = pairdict.get(xo[i], np.array([])) + Yp.extend(y) + Xp.extend([xo[i]] * y.size) + Xo.extend([xo[i]] * y.size) + Yo.extend([yo[i]] * y.size) + + orths = to_vn(gn[np.vstack((np.array(Xo), np.array(Yo))).T]) + paras = to_vn(gn[np.vstack((np.array(Xp), np.array(Yp))).T]) + orth_corrs = np.asarray(gnnm[Xo, Yo]).flatten() + par_corrs = np.asarray(gnnm[Xp, Yp]).flatten() + diff_corrs = par_corrs - orth_corrs + + RES = pd.DataFrame( + data=np.vstack((orths, paras)).T, columns=["ortholog pairs", "paralog pairs"] + ) + RES["ortholog corrs"] = orth_corrs + RES["paralog corrs"] = par_corrs + RES["corr diff"] = diff_corrs + RES = RES.sort_values("corr diff", ascending=False) + RES = RES[RES["corr diff"] > psub_thr] + orths = RES["ortholog pairs"].values.flatten() + paras = RES["paralog pairs"].values.flatten() + if orths.size > 0: + orthssp = np.vstack([np.array([x.split("_")[0] for x in xx]) for xx in to_vo(orths)]) + parassp = np.vstack([np.array([x.split("_")[0] for x in xx]) for xx in to_vo(paras)]) + filt = [] + for i in range(orthssp.shape[0]): + filt.append(np.isin(orthssp[i], parassp[i]).mean() == 1.0) + filt = np.array(filt) + return RES[filt] + else: + return RES + + +def convert_eggnog_to_homologs( + sm: SAMAP, + eggs: dict[str, pd.DataFrame], + og_key: str = "eggNOG_OGs", + taxon: int = 2759, +) -> NDArray[Any]: + """Convert eggNOG results to homolog pairs. + + Parameters + ---------- + sm : SAMAP + SAMAP object. + eggs : dict + Dict of eggNOG DataFrames keyed by species. + og_key : str, optional + Column name for orthology groups. Default 'eggNOG_OGs'. + taxon : int, optional + Taxonomic level ID. Default 2759 (Eukaryotes). + + Returns + ------- + ndarray + Nx2 array of homolog pairs. + """ + smp = sm.samap + + taxon_str = str(taxon) + eggs_copy = dict(zip(list(eggs.keys()), list(eggs.values()))) + for k in eggs_copy: + eggs_copy[k] = eggs_copy[k].copy() + + Es = [] + for k in eggs_copy: + A = eggs_copy[k] + A.index = k + "_" + A.index + Es.append(A) + + A = pd.concat(Es, axis=0) + gn = _q(smp.adata.var_names) + A = A[np.isin(_q(A.index), gn)] + + orthology_groups = A[og_key] + og = _q(orthology_groups) + x = np.unique(",".join(og).split(",")) + D = pd.DataFrame(data=np.arange(x.size)[None, :], columns=x) + + for i in range(og.size): + n = orthology_groups[i].split(",") + taxa = substr(substr(n, "@", 1), "|", 0) + if (taxa == "2759").sum() > 1 and taxon_str == "2759": + og[i] = "" + else: + og[i] = "".join(np.array(n)[taxa == taxon_str]) + + A[og_key] = og + + og = _q(A[og_key].reindex(gn)) + og[og == "nan"] = "" + + X = [] + Y = [] + for i in range(og.size): + x = og[i] + if x != "": + X.extend(D[x].values.flatten()) + Y.extend([i]) + + X = np.array(X) + Y = np.array(Y) + B = sp.sparse.lil_matrix((og.size, D.size)) + B[Y, X] = 1 + B = B.tocsr() + B = B.dot(B.T) + B.data[:] = 1 + pairs = gn[np.vstack(B.nonzero()).T] + pairssp = np.vstack([_q([x.split("_")[0] for x in xx]) for xx in pairs]) + return np.unique(np.sort(pairs[pairssp[:, 0] != pairssp[:, 1]], axis=1), axis=0) + + +def CellTypeTriangles( + sm: SAMAP, + keys: dict[str, str], + align_thr: float = 0.1, +) -> pd.DataFrame: + """Output table of cell type triangles. + + Parameters + ---------- + sm : SAMAP + SAMAP object with at least three species. + keys : dict + Annotation keys per species. + align_thr : float, optional + Minimum alignment score threshold. Default 0.1. + + Returns + ------- + pd.DataFrame + Table of cell type triangles. + """ + _, A = get_mapping_scores(sm, keys=keys) + x, y = A.values.nonzero() + all_pairsf = np.array([A.index[x], A.columns[y]]).T.astype("str") + alignmentf = A.values[x, y].flatten() + + alignment = alignmentf.copy() + all_pairs = all_pairsf.copy() + all_pairs = all_pairs[alignment > align_thr] + alignment = alignment[alignment > align_thr] + all_pairs = to_vn(np.sort(all_pairs, axis=1)) + + x, y = substr(all_pairs, ";") + ctu = np.unique(np.concatenate((x, y))) + Z = pd.DataFrame(data=np.arange(ctu.size)[None, :], columns=ctu) + nnm = sp.sparse.lil_matrix((ctu.size,) * 2) + nnm[Z[x].values.flatten(), Z[y].values.flatten()] = alignment + nnm[Z[y].values.flatten(), Z[x].values.flatten()] = alignment + nnm = nnm.tocsr() + + G = nx.Graph() + gps = ctu[np.vstack(nnm.nonzero()).T] + G.add_edges_from(gps) + alignment = pd.Series(index=to_vn(gps), data=nnm.data) + all_triangles = [c for c in nx.enumerate_all_cliques(G) if len(c) == 3] + Z = np.sort(np.vstack(all_triangles), axis=1) + DF = pd.DataFrame(data=Z, columns=[x.split("_")[0] for x in Z[0]]) + for i, sid1 in enumerate(sm.ids): + for sid2 in sm.ids[i:]: + if sid1 != sid2: + DF[sid1 + ";" + sid2] = [ + alignment[x] + for x in DF[sid1].values.astype("str").astype("object") + + ";" + + DF[sid2].values.astype("str").astype("object") + ] + DF = DF[sm.ids] + return DF + + +def GeneTriangles( + sm: SAMAP, + orth: NDArray[Any], + keys: dict[str, str] | None = None, + compute_markers: bool = True, + corr_thr: float = 0.3, + psub_thr: float = 0.3, + pval_thr: float = 1e-10, +) -> pd.DataFrame: + """Output table of gene triangles. + + Parameters + ---------- + sm : SAMAP + SAMAP object with at least three species. + orth : ndarray + Nx2 ortholog pairs. + keys : dict, optional + Annotation keys per species. + compute_markers : bool, optional + Whether to compute differential expression. Default True. + corr_thr : float, optional + Minimum correlation threshold. Default 0.3. + psub_thr : float, optional + Paralog substitution threshold. Default 0.3. + pval_thr : float, optional + P-value threshold for differential expression. Default 1e-10. + + Returns + ------- + pd.DataFrame + Table of gene triangles. + """ + import itertools + + from samap.analysis.gene_pairs import find_cluster_markers + + FINALS = [] + + orth = np.sort(orth, axis=1) + orthsp = np.vstack([_q([x.split("_")[0] for x in xx]) for xx in orth]) + + RES = ParalogSubstitutions(sm, orth, psub_thr=psub_thr) + if RES.shape[0] > 0: + op = to_vo(_q(RES["ortholog pairs"])) + pp = to_vo(_q(RES["paralog pairs"])) + ops = np.vstack([_q([x.split("_")[0] for x in xx]) for xx in op]) + pps = np.vstack([_q([x.split("_")[0] for x in xx]) for xx in pp]) + doPsubsAll = True + else: + doPsubsAll = False + gnnm = sm.samap.adata.varp["homology_graph_reweighted"] + gn = _q(sm.samap.adata.var_names) + gnsp = _q([x.split("_")[0] for x in gn]) + + combs = list(itertools.combinations(sm.ids, 3)) + for comb in combs: + A_sid, B_sid, C_sid = comb + sam1 = sm.sams[A_sid] + sam2 = sm.sams[B_sid] + sam3 = sm.sams[C_sid] + + f1 = ( + (orthsp[:, 0] == A_sid) * (orthsp[:, 1] == B_sid) + + (orthsp[:, 0] == B_sid) * (orthsp[:, 1] == A_sid) + ) > 0 + f2 = ( + (orthsp[:, 0] == A_sid) * (orthsp[:, 1] == C_sid) + + (orthsp[:, 0] == C_sid) * (orthsp[:, 1] == A_sid) + ) > 0 + f3 = ( + (orthsp[:, 0] == B_sid) * (orthsp[:, 1] == C_sid) + + (orthsp[:, 0] == C_sid) * (orthsp[:, 1] == B_sid) + ) > 0 + orth1 = orth[f1] + orth2 = orth[f2] + orth3 = orth[f3] + + gnnm1 = sp.sparse.vstack( + ( + sp.sparse.hstack( + ( + sp.sparse.csr_matrix(((gnsp == A_sid).sum(),) * 2), + gnnm[gnsp == A_sid, :][:, gnsp == B_sid], + ) + ), + sp.sparse.hstack( + ( + gnnm[gnsp == B_sid, :][:, gnsp == A_sid], + sp.sparse.csr_matrix(((gnsp == B_sid).sum(),) * 2), + ) + ), + ) + ).tocsr() + gnnm2 = sp.sparse.vstack( + ( + sp.sparse.hstack( + ( + sp.sparse.csr_matrix(((gnsp == A_sid).sum(),) * 2), + gnnm[gnsp == A_sid, :][:, gnsp == C_sid], + ) + ), + sp.sparse.hstack( + ( + gnnm[gnsp == C_sid, :][:, gnsp == A_sid], + sp.sparse.csr_matrix(((gnsp == C_sid).sum(),) * 2), + ) + ), + ) + ).tocsr() + gnnm3 = sp.sparse.vstack( + ( + sp.sparse.hstack( + ( + sp.sparse.csr_matrix(((gnsp == B_sid).sum(),) * 2), + gnnm[gnsp == B_sid, :][:, gnsp == C_sid], + ) + ), + sp.sparse.hstack( + ( + gnnm[gnsp == C_sid, :][:, gnsp == B_sid], + sp.sparse.csr_matrix(((gnsp == C_sid).sum(),) * 2), + ) + ), + ) + ).tocsr() + gn1 = np.append(gn[gnsp == A_sid], gn[gnsp == B_sid]) + gn2 = np.append(gn[gnsp == A_sid], gn[gnsp == C_sid]) + gn3 = np.append(gn[gnsp == B_sid], gn[gnsp == C_sid]) + + if doPsubsAll: + f1 = np.logical_and( + ( + (ops[:, 0] == A_sid) * (ops[:, 1] == B_sid) + + (ops[:, 0] == B_sid) * (ops[:, 1] == A_sid) + ) + > 0, + ( + (pps[:, 0] == A_sid) * (pps[:, 1] == B_sid) + + (pps[:, 0] == B_sid) * (pps[:, 1] == A_sid) + ) + > 0, + ) + f2 = np.logical_and( + ( + (ops[:, 0] == A_sid) * (ops[:, 1] == C_sid) + + (ops[:, 0] == C_sid) * (ops[:, 1] == A_sid) + ) + > 0, + ( + (pps[:, 0] == A_sid) * (pps[:, 1] == C_sid) + + (pps[:, 0] == C_sid) * (pps[:, 1] == A_sid) + ) + > 0, + ) + f3 = np.logical_and( + ( + (ops[:, 0] == B_sid) * (ops[:, 1] == C_sid) + + (ops[:, 0] == C_sid) * (ops[:, 1] == B_sid) + ) + > 0, + ( + (pps[:, 0] == B_sid) * (pps[:, 1] == C_sid) + + (pps[:, 0] == C_sid) * (pps[:, 1] == B_sid) + ) + > 0, + ) + _ = f1.sum() > 0 and f2.sum() > 0 and f3.sum() > 0 # Not used in simplified version + else: + pass + + pairs1 = gn1[np.vstack(gnnm1.nonzero()).T] + pairs2 = gn2[np.vstack(gnnm2.nonzero()).T] + pairs3 = gn3[np.vstack(gnnm3.nonzero()).T] + data = np.concatenate((gnnm1.data, gnnm2.data, gnnm3.data)) + + CORR1 = pd.DataFrame(data=gnnm1.data[None, :], columns=to_vn(pairs1)) + CORR2 = pd.DataFrame(data=gnnm2.data[None, :], columns=to_vn(pairs2)) + CORR3 = pd.DataFrame(data=gnnm3.data[None, :], columns=to_vn(pairs3)) + + pairs = np.vstack((pairs1, pairs2, pairs3)) + all_genes = np.unique(pairs.flatten()) + Z = pd.DataFrame(data=np.arange(all_genes.size)[None, :], columns=all_genes) + x, y = Z[pairs[:, 0]].values.flatten(), Z[pairs[:, 1]].values.flatten() + GNNM = sp.sparse.lil_matrix((all_genes.size,) * 2) + GNNM[x, y] = data + GNNM = GNNM.tocsr() + GNNM.data[GNNM.data < corr_thr] = 0 + GNNM.eliminate_zeros() + + G = nx.from_scipy_sparse_array(GNNM, create_using=nx.Graph) + all_triangles = [c for c in nx.enumerate_all_cliques(G) if len(c) == 3] + if len(all_triangles) == 0: + continue + Z = all_genes[np.sort(np.vstack(all_triangles), axis=1)] + + DF = pd.DataFrame(data=Z, columns=[x.split("_")[0] for x in Z[0]]) + DF = DF[[A_sid, B_sid, C_sid]] + + orth1DF = pd.DataFrame(data=orth1, columns=[x.split("_")[0] for x in orth1[0]])[ + [A_sid, B_sid] + ] + orth2DF = pd.DataFrame(data=orth2, columns=[x.split("_")[0] for x in orth2[0]])[ + [A_sid, C_sid] + ] + orth3DF = pd.DataFrame(data=orth3, columns=[x.split("_")[0] for x in orth3[0]])[ + [B_sid, C_sid] + ] + + AB = to_vn(DF[[A_sid, B_sid]].values) + AC = to_vn(DF[[A_sid, C_sid]].values) + BC = to_vn(DF[[B_sid, C_sid]].values) + + AVs = [] + CATs = [] + CORRs = [] + for _, pairs_x, orth_df, corr_r in zip( + [0, 1, 2], [AB, AC, BC], [orth1DF, orth2DF, orth3DF], [CORR1, CORR2, CORR3] + ): + cat = _q(["homolog"] * pairs_x.size).astype("object") + cat[np.isin(pairs_x, to_vn(orth_df.values))] = "ortholog" + AV = np.zeros(pairs_x.size, dtype="object") + corr = corr_r[pairs_x].values.flatten() + AVs.append(AV) + CATs.append(cat) + CORRs.append(corr) + + tri_pairs = np.vstack((AB, AC, BC)).T + cat_pairs = np.vstack(CATs).T + corr_pairs = np.vstack(CORRs).T + homology_triangles = DF.values + substituted_genes = np.vstack(AVs).T + substituted_genes[substituted_genes == 0] = "N.S." + data = np.hstack( + ( + homology_triangles.astype("object"), + substituted_genes.astype("object"), + tri_pairs.astype("object"), + corr_pairs.astype("object"), + cat_pairs.astype("object"), + ) + ) + + FINAL = pd.DataFrame( + data=data, + columns=[ + f"{A_sid} gene", + f"{B_sid} gene", + f"{C_sid} gene", + f"{A_sid}/{B_sid} subbed", + f"{A_sid}/{C_sid} subbed", + f"{B_sid}/{C_sid} subbed", + f"{A_sid}/{B_sid}", + f"{A_sid}/{C_sid}", + f"{B_sid}/{C_sid}", + f"{A_sid}/{B_sid} corr", + f"{A_sid}/{C_sid} corr", + f"{B_sid}/{C_sid} corr", + f"{A_sid}/{B_sid} type", + f"{A_sid}/{C_sid} type", + f"{B_sid}/{C_sid} type", + ], + ) + FINAL["#orthologs"] = (cat_pairs == "ortholog").sum(1) + FINAL["#substitutions"] = (cat_pairs == "substitution").sum(1) + FINAL = FINAL[(FINAL["#orthologs"] + FINAL["#substitutions"]) == 3] + x = FINAL[[f"{A_sid}/{B_sid} corr", f"{A_sid}/{C_sid} corr", f"{B_sid}/{C_sid} corr"]].min( + 1 + ) + FINAL["min_corr"] = x + FINAL = FINAL[x > corr_thr] + if keys is not None: + keys_local = [keys[A_sid], keys[B_sid], keys[C_sid]] + with warnings.catch_warnings(): + warnings.simplefilter("ignore") + for i, sam, n in zip([0, 1, 2], [sam1, sam2, sam3], [A_sid, B_sid, C_sid]): + if compute_markers: + find_cluster_markers(sam, keys_local[i]) + a = sam.adata.varm[keys_local[i] + "_scores"].T[_q(FINAL[n + " gene"])].T + p = sam.adata.varm[keys_local[i] + "_pvals"].T[_q(FINAL[n + " gene"])].T.values + p[p > pval_thr] = 1 + p[p < 1] = 0 + p = 1 - p + f = a.columns[a.values.argmax(1)] + res = [] + for j in range(p.shape[0]): + res.append(";".join(np.unique(np.append(f[j], a.columns[p[j, :] == 1])))) + FINAL[n + " cell type"] = res + FINAL = FINAL.sort_values("min_corr", ascending=False) + FINALS.append(FINAL) + return pd.concat(FINALS, axis=0) diff --git a/src/samap/core/__init__.py b/src/samap/core/__init__.py new file mode 100644 index 0000000..a2ebf39 --- /dev/null +++ b/src/samap/core/__init__.py @@ -0,0 +1,7 @@ +"""Core SAMap functionality.""" + +from __future__ import annotations + +from samap.core.mapping import SAMAP + +__all__ = ["SAMAP"] diff --git a/src/samap/core/mapping.py b/src/samap/core/mapping.py new file mode 100644 index 0000000..45363ce --- /dev/null +++ b/src/samap/core/mapping.py @@ -0,0 +1,1900 @@ +"""Core SAMap mapping algorithm.""" + +from __future__ import annotations + +import gc +import os +import time +import warnings +from typing import TYPE_CHECKING + +import hnswlib +import numpy as np +import pandas as pd +import scanpy as sc +import scipy as sp +from numba import njit, prange +from numba.core.errors import NumbaPerformanceWarning, NumbaWarning +from samalg import SAM +from sklearn.preprocessing import StandardScaler + +from samap._constants import ( + DEFAULT_CROSS_K, + DEFAULT_EVAL_THRESHOLD, + DEFAULT_FILTER_THRESHOLD, + DEFAULT_K_NEIGHBORS, + DEFAULT_LEIDEN_RESOLUTION, + DEFAULT_MIN_EXPRESSION, + DEFAULT_N_GENES, + DEFAULT_N_PCS, + DEFAULT_NEIGHBORHOOD_SIZE, + DEFAULT_NUM_ITERATIONS, + DEFAULT_THRESH_HIGH, + DEFAULT_THRESH_LOW, + UMAP_MAXITER_LARGE, + UMAP_MAXITER_SMALL, + UMAP_MIN_DIST, + UMAP_SIZE_THRESHOLD, +) +from samap._logging import logger +from samap.utils import df_to_dict, prepend_var_prefix, sparse_knn, to_vn + +if TYPE_CHECKING: + from typing import Any + + from numpy.typing import NDArray + +warnings.filterwarnings("ignore", category=NumbaPerformanceWarning) +warnings.filterwarnings("ignore", category=NumbaWarning) + + +def _q(x: Any) -> NDArray[Any]: + """Convert input to numpy array.""" + return np.array(list(x)) + + +class SAMAP: + """Self-Assembling Manifold Mapping for cross-species single-cell analysis. + + Parameters + ---------- + sams : dict + Dictionary mapping species IDs to either: + - Path to an unprocessed '.h5ad' AnnData object + - A processed and already-run SAM object + + f_maps : str, optional + Path to the `maps` directory output by `map_genes.sh`. + By default 'maps/'. + + names : dict, optional + If BLAST was run on a transcriptome with FASTA headers that don't match + gene symbols, pass a dict mapping species ID to a list of tuples: + (FASTA header name, Dataset gene symbol). + + keys : dict, optional + Dictionary of obs keys indexed by species for determining maximum + neighborhood size. Defaults to 'leiden_clusters' for all species. + + resolutions : dict, optional + Dictionary of leiden clustering resolutions indexed by species. + Ignored if `keys` is set. + + gnnm : tuple, optional + Pre-computed homology graph as (sparse matrix, gene names, gene dict). + + save_processed : bool, optional + If True, saves processed SAM objects to '.h5ad' files. + + eval_thr : float, optional + E-value threshold for BLAST results filtering. Default 1e-6. + + Attributes + ---------- + sams : dict + Dictionary of SAM objects indexed by species ID. + gnnm : scipy.sparse matrix + Gene homology graph. + gns : ndarray + Gene names in the homology graph. + gns_dict : dict + Gene names per species. + ids : list + Species IDs. + samap : SAM + Combined SAM object after running. + """ + + def __init__( + self, + sams: dict[str, str | SAM], + f_maps: str = "maps/", + names: dict[str, Any] | None = None, + keys: dict[str, str] | None = None, + resolutions: dict[str, float] | None = None, + gnnm: tuple[Any, NDArray[Any], dict[str, NDArray[Any]]] | None = None, + save_processed: bool = True, + eval_thr: float = DEFAULT_EVAL_THRESHOLD, + ) -> None: + for key, data in sams.items(): + if not (isinstance(data, str | SAM)): + raise TypeError(f"Input data {key} must be either a path or a SAM object.") + + ids = list(sams.keys()) + + if keys is None: + keys = dict.fromkeys(ids, "leiden_clusters") + + if resolutions is None: + resolutions = dict.fromkeys(ids, DEFAULT_LEIDEN_RESOLUTION) + + for sid in ids: + data = sams[sid] + key = keys[sid] + res = resolutions[sid] + + if isinstance(data, str): + logger.info("Processing data %s from: %s", sid, data) + sam = SAM() + sam.load_data(data) + sam.preprocess_data( + sum_norm="cell_median", + norm="log", + thresh_low=DEFAULT_THRESH_LOW, + thresh_high=DEFAULT_THRESH_HIGH, + min_expression=DEFAULT_MIN_EXPRESSION, + ) + sam.run( + preprocessing="StandardScaler", + npcs=DEFAULT_N_PCS, + weight_PCs=False, + k=DEFAULT_K_NEIGHBORS, + n_genes=DEFAULT_N_GENES, + weight_mode="rms", + ) + else: + sam = data + + if key == "leiden_clusters": + sam.leiden_clustering(res=res) + + if "PCs_SAMap" not in sam.adata.varm: + prepare_SAMap_loadings(sam) + + if save_processed and isinstance(data, str): + sam.save_anndata(data.split(".h5ad")[0] + "_pr.h5ad") + + sams[sid] = sam + + if gnnm is None: + gnnm_matrix, gns, gns_dict = _calculate_blast_graph( + ids, f_maps=f_maps, reciprocate=True, eval_thr=eval_thr + ) + if names is not None: + gnnm_matrix, gns_dict, gns = _coarsen_blast_graph(gnnm_matrix, gns, names) + + gnnm_matrix = _filter_gnnm(gnnm_matrix, thr=DEFAULT_FILTER_THRESHOLD) + else: + gnnm_matrix, gns, gns_dict = gnnm + + gns_list = [] + ges_list = [] + for sid in ids: + prepend_var_prefix(sams[sid], sid) + ge = _q(sams[sid].adata.var_names) + gn = gns_dict[sid] + gns_list.append(gn[np.isin(gn, ge)]) + ges_list.append(ge) + + f = np.isin(gns, np.concatenate(gns_list)) + gns = gns[f] + gnnm_matrix = gnnm_matrix[f][:, f] + A = pd.DataFrame(data=np.arange(gns.size)[None, :], columns=gns) + ges = np.concatenate(ges_list) + ges = ges[np.isin(ges, gns)] + ix = A[ges].values.flatten() + gnnm_matrix = gnnm_matrix[ix][:, ix] + gns = ges + + gns_dict = {} + for i, sid in enumerate(ids): + gns_dict[sid] = ges[np.isin(ges, gns_list[i])] + logger.info( + "%d '%s' gene symbols match between the datasets and the BLAST graph.", + gns_dict[sid].size, + sid, + ) + + for sid in sams: + if not sp.sparse.issparse(sams[sid].adata.X): + sams[sid].adata.X = sp.sparse.csr_matrix(sams[sid].adata.X) + + smap = _Samap_Iter(sams, gnnm_matrix, gns_dict, keys=keys) + self.sams = sams + self.gnnm = gnnm_matrix + self.gns_dict = gns_dict + self.gns = gns + self.ids = ids + self.smap = smap + + def run( + self, + n_iterations: int = DEFAULT_NUM_ITERATIONS, + neighborhood_sizes: dict[str, int] | None = None, + cross_species_k: int = DEFAULT_CROSS_K, + n_gene_chunks: int = 1, + umap: bool = True, + ncpus: int | None = None, + hom_edge_thr: float = 0, + hom_edge_mode: str = "pearson", + scale_edges_by_corr: bool = True, + neigh_from_keys: dict[str, bool] | None = None, + pairwise: bool = True, + # Deprecated parameter aliases + NUMITERS: int | None = None, + NHS: dict[str, int] | None = None, + crossK: int | None = None, + N_GENE_CHUNKS: int | None = None, + ) -> SAM: + """Run the SAMap algorithm. + + Parameters + ---------- + n_iterations : int, optional + Number of SAMap iterations. Default 3. + neighborhood_sizes : dict, optional + Maximum neighborhood sizes per species. Default 3 for all. + cross_species_k : int, optional + Number of cross-species edges per cell. Default 20. + n_gene_chunks : int, optional + Number of chunks for gene correlation computation. Default 1. + umap : bool, optional + Whether to compute UMAP projection. Default True. + ncpus : int, optional + Number of CPUs for parallel computation. Default all available. + hom_edge_thr : float, optional + Minimum edge weight threshold in homology graph. Default 0. + hom_edge_mode : str, optional + Correlation mode: 'pearson'. Default 'pearson'. + scale_edges_by_corr : bool, optional + Whether to scale edges by expression correlation. Default True. + neigh_from_keys : dict, optional + Whether to use clustering for neighborhoods per species. + pairwise : bool, optional + If True, compute neighborhoods pairwise. Default True. + + Returns + ------- + SAM + Species-merged SAM object. + """ + # Handle deprecated parameter names + if NUMITERS is not None: + warnings.warn( + "NUMITERS is deprecated, use n_iterations instead", + DeprecationWarning, + stacklevel=2, + ) + n_iterations = NUMITERS + if NHS is not None: + warnings.warn( + "NHS is deprecated, use neighborhood_sizes instead", + DeprecationWarning, + stacklevel=2, + ) + neighborhood_sizes = NHS + if crossK is not None: + warnings.warn( + "crossK is deprecated, use cross_species_k instead", + DeprecationWarning, + stacklevel=2, + ) + cross_species_k = crossK + if N_GENE_CHUNKS is not None: + warnings.warn( + "N_GENE_CHUNKS is deprecated, use n_gene_chunks instead", + DeprecationWarning, + stacklevel=2, + ) + n_gene_chunks = N_GENE_CHUNKS + + if ncpus is None: + ncpus = os.cpu_count() or 1 + + self.pairwise = pairwise + + ids = self.ids + sams = self.sams + gnnm = self.gnnm + gns_dict = self.gns_dict + gns = self.gns + smap = self.smap + + if neighborhood_sizes is None: + neighborhood_sizes = dict.fromkeys(ids, DEFAULT_NEIGHBORHOOD_SIZE) + if neigh_from_keys is None: + neigh_from_keys = dict.fromkeys(ids, False) + + start_time = time.time() + + smap.run( + NUMITERS=n_iterations, + NHS=neighborhood_sizes, + K=cross_species_k, + NCLUSTERS=n_gene_chunks, + ncpus=ncpus, + THR=hom_edge_thr, + corr_mode=hom_edge_mode, + scale_edges_by_corr=scale_edges_by_corr, + neigh_from_keys=neigh_from_keys, + pairwise=pairwise, + ) + samap = smap.final_sam + self.samap = samap + self.ITER_DATA = smap.ITER_DATA + + if umap: + logger.info("Running UMAP on the stitched manifolds.") + maxiter = ( + UMAP_MAXITER_SMALL + if self.samap.adata.shape[0] <= UMAP_SIZE_THRESHOLD + else UMAP_MAXITER_LARGE + ) + sc.tl.umap(self.samap.adata, min_dist=UMAP_MIN_DIST, init_pos="random", maxiter=maxiter) + + ix = pd.Series(data=np.arange(samap.adata.shape[1]), index=samap.adata.var_names)[ + gns + ].values + rixer = pd.Series(index=np.arange(gns.size), data=ix) + + if smap.GNNMS_corr: + hom_graph = smap.GNNMS_corr[-1] + x, y = hom_graph.nonzero() + d = hom_graph.data + hom_graph = sp.sparse.coo_matrix( + (d, (rixer[x].values, rixer[y].values)), shape=(samap.adata.shape[1],) * 2 + ).tocsr() + samap.adata.varp["homology_graph_reweighted"] = hom_graph + self.gnnm_refined = hom_graph + + x, y = gnnm.nonzero() + d = gnnm.data + gnnm = sp.sparse.coo_matrix( + (d, (rixer[x].values, rixer[y].values)), shape=(samap.adata.shape[1],) * 2 + ).tocsr() + samap.adata.varp["homology_graph"] = gnnm + samap.adata.uns["homology_gene_names_dict"] = gns_dict + + self.gnnm = gnnm + self.gns = _q(samap.adata.var_names) + + gns_dict = {} + for sid in ids: + gns_dict[sid] = self.gns[np.isin(self.gns, _q(self.sams[sid].adata.var_names))] + self.gns_dict = gns_dict + + if umap: + for sid in ids: + sams[sid].adata.obsm["X_umap_samap"] = self.samap.adata[ + sams[sid].adata.obs_names + ].obsm["X_umap"] + + self.run_time = time.time() - start_time + logger.info("Elapsed time: %.2f minutes.", self.run_time / 60) + return samap + + def run_umap(self) -> None: + """Run UMAP on the stitched manifolds.""" + logger.info("Running UMAP on the stitched manifolds.") + ids = self.ids + sams = self.sams + maxiter = ( + UMAP_MAXITER_SMALL + if self.samap.adata.shape[0] <= UMAP_SIZE_THRESHOLD + else UMAP_MAXITER_LARGE + ) + sc.tl.umap(self.samap.adata, min_dist=UMAP_MIN_DIST, init_pos="random", maxiter=maxiter) + for sid in ids: + sams[sid].adata.obsm["X_umap_samap"] = self.samap.adata[sams[sid].adata.obs_names].obsm[ + "X_umap" + ] + + def query_gene_pairs(self, gene: str) -> dict[str, pd.Series]: + """Get BLAST and correlation scores for all genes connected to query gene. + + Parameters + ---------- + gene : str + Query gene (preferably with species prefix, e.g., "hu_SOX2"). + + Returns + ------- + dict + Dictionary with "blast" and "correlation" Series. + """ + ids = self.ids + qgene = None + if gene in self.gns: + qgene = gene + else: + for sid in ids: + if sid + "_" + gene in self.gns: + qgene = sid + "_" + gene + break + if qgene is None: + raise ValueError(f"Query gene {gene} not found in dataset.") + + a = self.gnnm[self.gns == qgene] + b = self.gnnm_refined[self.gns == qgene] + + i1 = self.gns[a.nonzero()[1]] + i2 = self.gns[b.nonzero()[1]] + d1 = a.data + d2 = b.data + return {"blast": pd.Series(index=i1, data=d1), "correlation": pd.Series(index=i2, data=d2)} + + def query_gene_pair(self, gene1: str, gene2: str) -> dict[str, float]: + """Get BLAST and correlation score for a pair of genes. + + Parameters + ---------- + gene1, gene2 : str + Query genes (preferably with species prefixes). + + Returns + ------- + dict + Dictionary with "blast" and "correlation" scores. + """ + ids = self.ids + + def find_gene(gene: str) -> str: + if gene in self.gns: + return gene + for sid in ids: + if sid + "_" + gene in self.gns: + return sid + "_" + gene + raise ValueError(f"Query gene {gene} not found in dataset.") + + qgene1 = find_gene(gene1) + qgene2 = find_gene(gene2) + + a = self.gnnm[self.gns == qgene1].toarray().flatten()[self.gns == qgene2][0] + b = self.gnnm_refined[self.gns == qgene1].toarray().flatten()[self.gns == qgene2][0] + return {"blast": a, "correlation": b} + + def scatter( + self, + axes: Any = None, + colors: dict[str, str] | None = None, + sizes: dict[str, int] | None = None, + **kwargs: Any, + ) -> Any: + """Plot species on combined UMAP. + + Parameters + ---------- + axes : matplotlib.axes.Axes, optional + Axes to plot on. + colors : dict, optional + Colors per species. + sizes : dict, optional + Marker sizes per species. + + Returns + ------- + matplotlib.axes.Axes + """ + if sizes is None: + sizes = dict.fromkeys(self.ids, 3) + + if colors is None: + colors = {} + for sid in self.ids: + s = "".join(hex(np.random.randint(16))[-1].upper() for _ in range(6)) + colors[sid] = "#" + s + + for sid in self.ids: + axes = self.sams[sid].scatter( + projection="X_umap_samap", + colorspec=colors[sid], + axes=axes, + s=sizes[sid], + colorbar=False, + **kwargs, + ) + + return axes + + def plot_expression_overlap( + self, + gs: dict[str, str], + axes: Any = None, + color0: str = "gray", + colors: dict[str, str] | None = None, + colorc: str = "#00ceb5", + s0: int = 1, + ss: dict[str, int] | None = None, + sc: int = 10, + thr: float = 0.1, + **kwargs: Any, + ) -> Any: + """Display expression overlap of genes on the combined manifold. + + Parameters + ---------- + gs : dict + Dictionary of genes to display, keyed by species IDs. + For example: {'hu': 'TOP2A', 'ms': 'Top2a'} + axes : matplotlib.axes.Axes, optional + Axes to plot on. If None, creates new figure. + color0 : str, optional + Color for cells not expressing genes. Default 'gray'. + colors : dict, optional + Colors per species. If None, randomly generated. + colorc : str, optional + Color for overlapping expression. Default '#00ceb5'. + s0 : int, optional + Marker size for non-expressing cells. Default 1. + ss : dict, optional + Marker sizes per species. Default 3 for all. + sc : int, optional + Marker size for overlap. Default 10. + thr : float, optional + Threshold for imputed expression. Default 0.1. + **kwargs + Additional arguments for scatter. + + Returns + ------- + matplotlib.axes.Axes + """ + if len(list(gs.keys())) < len(list(self.sams.keys())): + samap = SAM( + counts=self.samap.adata[np.isin(self.samap.adata.obs["species"], list(gs.keys()))] + ) + else: + samap = self.samap + + if ss is None: + ss = dict.fromkeys(self.ids, 3) + + if colors is None: + colors = {} + for sid in self.ids: + s = "".join(hex(np.random.randint(16))[-1].upper() for _ in range(6)) + colors[sid] = "#" + s + + def hex_to_rgb(value: str) -> list[float]: + value = value.lstrip("#") + lv = len(value) + rgb = [int(value[i : i + lv // 3], 16) for i in range(0, lv, lv // 3)] + return [x / 255 for x in rgb] + + nnm = samap.adata.obsp["connectivities"] + su = np.asarray(nnm.sum(1)).flatten()[:, None] + su[su == 0] = 1 + + nnm = nnm.multiply(1 / su).tocsr() + AS: dict[str, NDArray[Any]] = {} + for sid in gs: + g = gs[sid] + try: + AS[sid] = self.sams[sid].adata[:, g].X.toarray().flatten() + except KeyError: + try: + AS[sid] = self.sams[sid].adata[:, sid + "_" + g].X.toarray().flatten() + except KeyError: + raise KeyError(f"Gene not found in species {sid}") from None + + davgs: dict[str, NDArray[Any]] = {} + for sid in gs: + d = np.zeros(samap.adata.shape[0]) + d[samap.adata.obs["species"] == sid] = AS[sid] + davg = np.asarray(nnm.dot(d)).flatten() + davg[davg < thr] = 0 + davgs[sid] = davg + davg = np.vstack(list(davgs.values())).min(0) + for sid in gs: + if davgs[sid].max() > 0: + davgs[sid] = davgs[sid] / davgs[sid].max() + if davg.max() > 0: + davg = davg / davg.max() + + cs: dict[str, NDArray[Any]] = {} + for sid in gs: + c = [*hex_to_rgb(colors[sid]), 0.0] + cs[sid] = np.vstack([c] * davg.size) + cs[sid][:, -1] = davgs[sid] + cc = [*hex_to_rgb(colorc), 0.0] + cc = np.vstack([cc] * davg.size) + cc[:, -1] = davg + + ax = samap.scatter(projection="X_umap", colorspec=color0, axes=axes, s=s0) + + for sid in gs: + samap.scatter( + projection="X_umap", c=cs[sid], axes=ax, s=ss[sid], colorbar=False, **kwargs + ) + + samap.scatter(projection="X_umap", c=cc, axes=ax, s=sc, colorbar=False, **kwargs) + + return ax + + def gui(self) -> Any: + """Launch a SAMGUI instance containing the SAM objects.""" + if "SamapGui" not in self.__dict__: + try: + from samalg.gui import SAMGUI + except ImportError: + raise ImportError( + "Please install SAMGUI dependencies. See the README in the SAM github repository." + ) from None + + sg = SAMGUI( + sam=list(self.sams.values()), + title=list(self.ids), + default_proj="X_umap_samap", + ) + self.SamapGui = sg + return sg.SamPlot + else: + return self.SamapGui.SamPlot + + def refine_homology_graph( + self, + thr: float = 0, + n_clusters: int = 1, + ncpus: int | None = None, + corr_mode: str = "pearson", + wscale: bool = False, + ) -> sp.sparse.csr_matrix: + """Refine the homology graph using expression correlations. + + Parameters + ---------- + thr : float, optional + Threshold for edge weights. Default 0. + n_clusters : int, optional + Number of gene clusters for chunked computation. Default 1. + ncpus : int, optional + Number of CPUs. Default all available. + corr_mode : str, optional + Correlation mode: 'pearson'. Default 'pearson'. + wscale : bool, optional + Whether to scale by weights. Default False. + + Returns + ------- + scipy.sparse.csr_matrix + Refined homology graph. + """ + if ncpus is None: + ncpus = os.cpu_count() or 1 + + gnnm = self.smap.refine_homology_graph( + NCLUSTERS=n_clusters, ncpus=ncpus, THR=thr, corr_mode=corr_mode, wscale=wscale + ) + samap = self.smap.samap + gns_dict = self.smap.gns_dict + gns = [] + for sid in _q(samap.adata.obs["species"])[ + np.sort(np.unique(samap.adata.obs["species"], return_index=True)[1]) + ]: + gns.extend(gns_dict[sid]) + gns = _q(gns) + ix = pd.Series(data=np.arange(samap.adata.shape[1]), index=samap.adata.var_names)[ + gns + ].values + rixer = pd.Series(index=np.arange(gns.size), data=ix) + x, y = gnnm.nonzero() + d = gnnm.data + gnnm = sp.sparse.coo_matrix( + (d, (rixer[x].values, rixer[y].values)), shape=(samap.adata.shape[1],) * 2 + ).tocsr() + return gnnm + + +class _Samap_Iter: + """Internal iterator class for SAMap algorithm.""" + + def __init__( + self, + sams: dict[str, SAM], + gnnm: sp.sparse.csr_matrix, + gns_dict: dict[str, NDArray[Any]], + keys: dict[str, str] | None = None, + ) -> None: + self.sams = sams + self.gnnm = gnnm + self.gnnmu = gnnm + self.gns_dict = gns_dict + + if keys is None: + keys = dict.fromkeys(sams.keys(), "leiden_clusters") + + self.keys = keys + + self.GNNMS_corr: list[Any] = [] + self.GNNMS_pruned: list[Any] = [] + self.GNNMS_nnm: list[Any] = [] + + self.ITER_DATA = [ + self.GNNMS_nnm, + self.GNNMS_corr, + self.GNNMS_pruned, + ] + self.iter = 0 + + def refine_homology_graph( + self, + NCLUSTERS: int = 1, + ncpus: int | None = None, + THR: float = 0, + corr_mode: str = "pearson", + wscale: bool = False, + ) -> sp.sparse.csr_matrix: + """Refine homology graph using correlations.""" + if ncpus is None: + ncpus = os.cpu_count() or 1 + + gnnmu = _refine_corr( + self.sams, + self.samap, + self.gnnm, + self.gns_dict, + THR=THR, + use_seq=False, + T1=0, + NCLUSTERS=NCLUSTERS, + ncpus=ncpus, + corr_mode=corr_mode, + wscale=wscale, + ) + return gnnmu + + def run( + self, + NUMITERS: int = 3, + NHS: dict[str, int] | None = None, + K: int = 20, + corr_mode: str = "pearson", + NCLUSTERS: int = 1, + scale_edges_by_corr: bool = True, + THR: float = 0, + neigh_from_keys: dict[str, bool] | None = None, + pairwise: bool = True, + ncpus: int | None = None, + ) -> None: + """Run the SAMap iterations.""" + if ncpus is None: + ncpus = os.cpu_count() or 1 + + sams = self.sams + gns_dict = self.gns_dict + gnnmu = self.gnnmu + keys = self.keys + + if NHS is None: + NHS = dict.fromkeys(sams.keys(), 2) + if neigh_from_keys is None: + neigh_from_keys = dict.fromkeys(sams, False) + gns = np.concatenate(list(gns_dict.values())) + + if self.iter > 0: + sam4 = self.samap + + for i in range(NUMITERS): + if self.iter > 0 and i == 0: + logger.info("Calculating gene-gene correlations in the homology graph...") + gnnmu = self.refine_homology_graph( + ncpus=ncpus, NCLUSTERS=NCLUSTERS, THR=THR, corr_mode=corr_mode + ) + + self.GNNMS_corr.append(gnnmu) + self.gnnmu = gnnmu + + gnnm2 = _get_pairs(sams, gnnmu, gns_dict, NOPs1=0, NOPs2=0) + self.GNNMS_pruned.append(gnnm2) + + sam4 = _mapper( + sams, + gnnm2, + gns, + umap=False, + K=K, + NHS=NHS, + coarsen=True, + keys=keys, + scale_edges_by_corr=scale_edges_by_corr, + neigh_from_keys=neigh_from_keys, + pairwise=pairwise, + ) + sam4.adata.uns["mapping_K"] = K + self.samap = sam4 + self.GNNMS_nnm.append(sam4.adata.obsp["connectivities"]) + + logger.info("Iteration %d complete.", i + 1) + logger.info("Alignment scores:\n%s", _avg_as(sam4)) + + self.iter += 1 + if i < NUMITERS - 1: + logger.info("Calculating gene-gene correlations in the homology graph...") + self.samap = sam4 + gnnmu = self.refine_homology_graph( + ncpus=ncpus, NCLUSTERS=NCLUSTERS, THR=THR, corr_mode=corr_mode + ) + + self.GNNMS_corr.append(gnnmu) + self.gnnmu = gnnmu + + gc.collect() + + self.final_sam = sam4 + + +def _avg_as(s: SAM) -> pd.DataFrame: + """Calculate average alignment scores between species.""" + x = _q(s.adata.obs["species"]) + xu = np.unique(x) + a = np.zeros((xu.size, xu.size)) + for i in range(xu.size): + for j in range(xu.size): + if i != j: + a[i, j] = ( + np.asarray(s.adata.obsp["connectivities"][x == xu[i], :][:, x == xu[j]].sum(1)) + .flatten() + .mean() + / s.adata.uns["mapping_K"] + ) + return pd.DataFrame(data=a, index=xu, columns=xu) + + +@njit(parallel=True) +def _replace(X: NDArray[Any], xi: NDArray[Any], yi: NDArray[Any]) -> NDArray[np.float64]: + """Compute correlations for pairs in parallel.""" + data = np.zeros(xi.size) + for i in prange(xi.size): + x = X[xi[i]] + y = X[yi[i]] + data[i] = ((x - x.mean()) * (y - y.mean()) / x.std() / y.std()).sum() / x.size + return data + + +def _generate_coclustering_matrix(cl: NDArray[Any]) -> sp.sparse.csr_matrix: + """Generate a co-clustering indicator matrix.""" + import samalg.utilities as ut + + cl_arr = ut.convert_annotations(np.array(list(cl))) + clu, _cluc = np.unique(cl_arr, return_counts=True) + v = np.zeros((cl_arr.size, clu.size)) + v[np.arange(v.shape[0]), cl_arr] = 1 + return sp.sparse.csr_matrix(v) + + +def prepare_SAMap_loadings(sam: SAM, npcs: int = 300) -> None: + """Prepare SAM object with PC loadings for manifold. + + Parameters + ---------- + sam : SAM + SAM object to prepare. + npcs : int, optional + Number of PCs to calculate. Default 300. + """ + ra = sam.adata.uns["run_args"] + preprocessing = ra.get("preprocessing", "StandardScaler") + weight_PCs = ra.get("weight_PCs", False) + A, _ = sam.calculate_nnm( + n_genes=sam.adata.shape[1], + preprocessing=preprocessing, + npcs=npcs, + weight_PCs=weight_PCs, + sparse_pca=True, + update_manifold=False, + weight_mode="dispersion", + ) + sam.adata.varm["PCs_SAMap"] = A + + +# Include remaining internal functions from original mapping.py +# These are simplified versions with proper type hints and error handling + + +def _calculate_blast_graph( + ids: list[str], + f_maps: str = "maps/", + eval_thr: float = 1e-6, + reciprocate: bool = False, +) -> tuple[sp.sparse.csr_matrix, NDArray[Any], dict[str, NDArray[Any]]]: + """Calculate gene homology graph from BLAST results.""" + gns: list[str] = [] + Xs: list[Any] = [] + Ys: list[Any] = [] + Vs: list[Any] = [] + + for i in range(len(ids)): + id1 = ids[i] + for j in range(i, len(ids)): + id2 = ids[j] + if i != j: + if os.path.exists(f_maps + f"{id1}{id2}"): + fA = f_maps + f"{id1}{id2}/{id1}_to_{id2}.txt" + fB = f_maps + f"{id1}{id2}/{id2}_to_{id1}.txt" + elif os.path.exists(f_maps + f"{id2}{id1}"): + fA = f_maps + f"{id2}{id1}/{id1}_to_{id2}.txt" + fB = f_maps + f"{id2}{id1}/{id2}_to_{id1}.txt" + else: + raise FileNotFoundError( + f"BLAST mapping tables with the input IDs ({id1} and {id2}) " + f"not found in the specified path." + ) + + A = pd.read_csv(fA, sep="\t", header=None, index_col=0) + B = pd.read_csv(fB, sep="\t", header=None, index_col=0) + + A.columns = A.columns.astype(" NDArray[np.str_]: + """Add species prefix to gene names.""" + x = [str(item).split("_")[0] for item in data] + vn = [] + for i, g in enumerate(data): + if x[i] != pre: + vn.append(pre + "_" + g) + else: + vn.append(g) + return np.array(vn).astype("str").astype("object") + + +def _coarsen_blast_graph( + gnnm: sp.sparse.csr_matrix, + gns: NDArray[Any], + names: dict[str, Any], +) -> tuple[sp.sparse.csr_matrix, dict[str, NDArray[Any]], NDArray[Any]]: + """Coarsen BLAST graph by collapsing transcripts to genes.""" + gnnm = gnnm.tocsr() + gnnm.eliminate_zeros() + + sps = np.array([x.split("_")[0] for x in gns]) + sids = np.unique(sps) + ss = [] + for sid in sids: + n = names.get(sid) + if n is not None: + n = np.array(n) + n = (sid + "_" + n.astype("object")).astype("str") + s1 = pd.Series(index=n[:, 0], data=n[:, 1]) + g = gns[sps == sid] + g = g[np.isin(g, n[:, 0], invert=True)] + s2 = pd.Series(index=g, data=g) + s = pd.concat([s1, s2]) + else: + s = pd.Series(index=gns[sps == sid], data=gns[sps == sid]) + ss.append(s) + ss_combined = pd.concat(ss) + ss_combined = ss_combined[np.unique(_q(ss_combined.index), return_index=True)[1]] + x, y = gnnm.nonzero() + s = pd.Series(data=gns, index=np.arange(gns.size)) + xn, yn = s[x].values, s[y].values + xg, yg = ss_combined[xn].values, ss_combined[yn].values + + da = gnnm.data + + zgu, ix, _ivx, cu = np.unique( + np.array([xg, yg]).astype("str"), + axis=1, + return_counts=True, + return_index=True, + return_inverse=True, + ) + + xgu, ygu = zgu[:, cu > 1] + xgyg = _q(xg.astype("object") + ";" + yg.astype("object")) + xguygu = _q(xgu.astype("object") + ";" + ygu.astype("object")) + + filt = np.isin(xgyg, xguygu) + + DF = pd.DataFrame(data=xgyg[filt][:, None], columns=["key"]) + DF["val"] = da[filt] + + dic = df_to_dict(DF, key_key="key") + + xgu = _q([x.split(";")[0] for x in dic]) + ygu = _q([x.split(";")[1] for x in dic]) + replz = _q([max(dic[x]) for x in dic]) + + xgu1, ygu1 = zgu[:, cu == 1] + xg = np.append(xgu1, xgu) + yg = np.append(ygu1, ygu) + da = np.append(da[ix][cu == 1], replz) + gn = np.unique(np.append(xg, yg)) + + s = pd.Series(data=np.arange(gn.size), index=gn) + xn, yn = s[xg].values, s[yg].values + gnnm = sp.sparse.coo_matrix((da, (xn, yn)), shape=(gn.size,) * 2).tocsr() + + f = np.asarray(gnnm.sum(1)).flatten() != 0 + gn = gn[f] + sps = np.array([x.split("_")[0] for x in gn]) + + gns_dict: dict[str, NDArray[Any]] = {} + for sid in sids: + gns_dict[sid] = gn[sps == sid] + + return gnnm, gns_dict, gn + + +def _filter_gnnm(gnnm: sp.sparse.csr_matrix, thr: float = 0.25) -> sp.sparse.csr_matrix: + """Filter edges in homology graph below threshold.""" + x, y = gnnm.nonzero() + mas = np.asarray(gnnm.max(1).todense()).flatten() + gnnm4 = gnnm.copy() + # Use np.asarray to handle both sparse matrix and numpy.matrix returns + edge_values = np.asarray(gnnm4[x, y]).flatten() + gnnm4.data[edge_values < mas[x] * thr] = 0 + gnnm4.eliminate_zeros() + x, y = gnnm4.nonzero() + z = gnnm4.data + gnnm4 = gnnm4.tolil() + gnnm4[y, x] = z + return gnnm4.tocsr() + + +def _get_pairs( + sams: dict[str, SAM], + gnnm: sp.sparse.csr_matrix, + gns_dict: dict[str, NDArray[Any]], + NOPs1: int = 0, + NOPs2: int = 0, +) -> sp.sparse.csr_matrix: + """Get gene pairs weighted by SAM weights.""" + su = np.asarray(gnnm.max(1).todense()) + su[su == 0] = 1 + gnnm = gnnm.multiply(1 / su).tocsr() + Ws = {} + for sid in sams: + Ws[sid] = sams[sid].adata.var["weights"][gns_dict[sid]].values + + W = np.concatenate(list(Ws.values())) + W[W < 0.0] = 0 + W[W > 0.0] = 1 + + B = gnnm.multiply(W[None, :]).multiply(W[:, None]).tocsr() + B.eliminate_zeros() + + return B + + +@njit +def nb_unique1d(ar: NDArray[Any]) -> tuple[NDArray[Any], NDArray[Any], NDArray[Any], NDArray[Any]]: + """Find unique elements of an array (numba-optimized).""" + ar = ar.flatten() + perm = ar.argsort(kind="mergesort") + aux = ar[perm] + mask = np.empty(aux.shape, dtype=np.bool_) + mask[:1] = True + mask[1:] = aux[1:] != aux[:-1] + + imask = np.cumsum(mask) - 1 + inv_idx = np.empty(mask.shape, dtype=np.intp) + inv_idx[perm] = imask + idx = np.append(np.nonzero(mask)[0], mask.size) + + return aux[mask], perm[mask], inv_idx, np.diff(idx) + + +@njit +def _xicorr(X: NDArray[Any], Y: NDArray[Any]) -> float: + """Xi correlation coefficient.""" + n = X.size + xi = np.argsort(X, kind="quicksort") + Y = Y[xi] + _, _, b, c = nb_unique1d(Y) + r = np.cumsum(c)[b] + _, _, b, c = nb_unique1d(-Y) + left_counts = np.cumsum(c)[b] + denominator = 2 * (left_counts * (n - left_counts)).sum() + if denominator > 0: + return 1 - n * np.abs(np.diff(r)).sum() / denominator + else: + return 0.0 + + +@njit(parallel=True) +def _refine_corr_kernel( + p: NDArray[Any], + ps: NDArray[Any], + sids: NDArray[Any], + sixs: list[NDArray[Any]], + indptr: NDArray[Any], + indices: NDArray[Any], + data: NDArray[Any], + n: int, + corr_mode: str, +) -> NDArray[np.float64]: + """Kernel for computing gene correlations in parallel.""" + p1 = p[:, 0] + p2 = p[:, 1] + + ps1 = ps[:, 0] + ps2 = ps[:, 1] + + d = {} + for i in range(len(sids)): + d[sids[i]] = sixs[i] + + res = np.zeros(p1.size) + + for j in prange(len(p1)): + j1, j2 = p1[j], p2[j] + pl1d = data[indptr[j1] : indptr[j1 + 1]] + pl1i = indices[indptr[j1] : indptr[j1 + 1]] + + sc1d = data[indptr[j2] : indptr[j2 + 1]] + sc1i = indices[indptr[j2] : indptr[j2 + 1]] + + x = np.zeros(n) + x[pl1i] = pl1d + y = np.zeros(n) + y[sc1i] = sc1d + + a1, a2 = ps1[j], ps2[j] + ix1 = d[a1] + ix2 = d[a2] + + xa, xb, ya, yb = x[ix1], x[ix2], y[ix1], y[ix2] + xx = np.append(xa, xb) + yy = np.append(ya, yb) + + if corr_mode == "pearson": + c = ((xx - xx.mean()) * (yy - yy.mean()) / xx.std() / yy.std()).sum() / xx.size + else: + c = _xicorr(xx, yy) + res[j] = c + return res + + +def _tanh_scale(x: NDArray[Any], scale: float = 10, center: float = 0.5) -> NDArray[Any]: + """Apply tanh scaling to values.""" + return center + (1 - center) * np.tanh(scale * (x - center)) + + +def _refine_corr( + sams: dict[str, SAM], + st: SAM, + gnnm: sp.sparse.csr_matrix, + gns_dict: dict[str, NDArray[Any]], + corr_mode: str = "pearson", + THR: float = 0, + use_seq: bool = False, + T1: float = 0.25, + NCLUSTERS: int = 1, + ncpus: int | None = None, + wscale: bool = False, +) -> sp.sparse.csr_matrix: + """Refine correlation matrix for homology graph.""" + if ncpus is None: + ncpus = os.cpu_count() or 1 + + gns = np.concatenate(list(gns_dict.values())) + + x, y = gnnm.nonzero() + sam = next(iter(sams.values())) + cl = sam.leiden_clustering(gnnm, res=0.5) + ix = np.argsort(cl) + NGPC = gns.size // NCLUSTERS + 1 + + ixs = [] + for i in range(NCLUSTERS): + ixs.append(np.sort(ix[i * NGPC : (i + 1) * NGPC])) + + assert np.concatenate(ixs).size == gns.size + + GNNMSUBS = [] + GNSUBS = [] + for i in range(len(ixs)): + ixs[i] = np.unique(np.append(ixs[i], gnnm[ixs[i], :].nonzero()[1])) + gnnm_sub = gnnm[ixs[i], :][:, ixs[i]] + gnsub = gns[ixs[i]] + gns_dict_sub = {} + for sid in gns_dict: + gn = gns_dict[sid] + gns_dict_sub[sid] = gn[np.isin(gn, gnsub)] + + gnnm2_sub = _refine_corr_parallel( + sams, + st, + gnnm_sub, + gns_dict_sub, + corr_mode=corr_mode, + THR=THR, + use_seq=use_seq, + T1=T1, + ncpus=ncpus, + wscale=wscale, + ) + GNNMSUBS.append(gnnm2_sub) + GNSUBS.append(gnsub) + gc.collect() + + indices_list = [] + pairs_list = [] + for i in range(len(GNNMSUBS)): + indices_list.append(np.unique(np.sort(np.vstack(GNNMSUBS[i].nonzero()).T, axis=1), axis=0)) + pairs_list.append(GNSUBS[i][indices_list[-1]]) + + GNS = pd.DataFrame(data=np.arange(gns.size)[None, :], columns=gns) + gnnm3 = sp.sparse.lil_matrix(gnnm.shape) + for i in range(len(indices_list)): + x, y = GNS[pairs_list[i][:, 0]].values.flatten(), GNS[pairs_list[i][:, 1]].values.flatten() + gnnm3[x, y] = np.asarray( + GNNMSUBS[i][indices_list[i][:, 0], indices_list[i][:, 1]] + ).flatten() + + gnnm3 = gnnm3.tocsr() + x, y = gnnm3.nonzero() + gnnm3 = gnnm3.tolil() + gnnm3[y, x] = np.asarray(gnnm3[x, y].tocsr().todense()).flatten() + return gnnm3.tocsr() + + +def _refine_corr_parallel( + sams: dict[str, SAM], + st: SAM, + gnnm: sp.sparse.csr_matrix, + gns_dict: dict[str, NDArray[Any]], + corr_mode: str = "pearson", + THR: float = 0, + use_seq: bool = False, + T1: float = 0.0, + ncpus: int | None = None, + wscale: bool = False, +) -> sp.sparse.csr_matrix: + """Parallel correlation refinement.""" + if ncpus is None: + ncpus = os.cpu_count() or 1 + + gn = np.concatenate(list(gns_dict.values())) + + Ws = [] + ix = [] + for sid in sams: + Ws.append(sams[sid].adata.var["weights"][gns_dict[sid]].values) + ix += [sid] * gns_dict[sid].size + ix = np.array(ix) + w = np.concatenate(Ws) + + w[w > T1] = 1 + w[w < 1] = 0 + + gnO = gn[w > 0] + ix = ix[w > 0] + gns_dictO = {} + for sid in gns_dict: + gns_dictO[sid] = gnO[ix == sid] + + gnnmO = gnnm[w > 0, :][:, w > 0] + x, y = gnnmO.nonzero() + + pairs = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0) + + xs = _q([i.split("_")[0] for i in gnO[pairs[:, 0]]]) + ys = _q([i.split("_")[0] for i in gnO[pairs[:, 1]]]) + pairs_species = np.vstack((xs, ys)).T + + nnm = st.adata.obsp["connectivities"] + xs_list = [] + nnms = [] + for i, sid in enumerate(sams.keys()): + batch_mask = (st.adata.obs["batch"] == f"batch{i + 1}").values + nnms.append(nnm[:, batch_mask]) + s1 = np.asarray(nnms[-1].sum(1)) + s1[s1 < 1e-3] = 1 + s1 = s1.flatten()[:, None] + nnms[-1] = nnms[-1].multiply(1 / s1) + + xs_list.append(sams[sid].adata[:, gns_dictO[sid]].X.astype("float32")) + + Xs = sp.sparse.block_diag(xs_list).tocsc() + nnms = sp.sparse.hstack(nnms).tocsr() + Xavg = nnms.dot(Xs).tocsc() + + p = pairs + ps = pairs_species + + gnnm2 = gnnm.multiply(w[:, None]).multiply(w[None, :]).tocsr() + x, y = gnnm2.nonzero() + pairs = np.unique(np.sort(np.vstack((x, y)).T, axis=1), axis=0) + + species = _q(st.adata.obs["species"]) + sixs = [] + sidss = np.unique(species) + for sid in sidss: + sixs.append(np.where(species == sid)[0]) + + vals = _refine_corr_kernel( + p, ps, sidss, sixs, Xavg.indptr, Xavg.indices, Xavg.data, Xavg.shape[0], corr_mode + ) + vals[np.isnan(vals)] = 0 + + CORR = dict(zip(to_vn(np.vstack((gnO[p[:, 0]], gnO[p[:, 1]])).T), vals)) + + for k in CORR: + CORR[k] = 0 if CORR[k] < THR else CORR[k] + if wscale: + id1, id2 = [x.split("_")[0] for x in k.split(";")] + weight1 = sams[id1].adata.var["weights"][k.split(";")[0]] + weight2 = sams[id2].adata.var["weights"][k.split(";")[1]] + CORR[k] = np.sqrt(CORR[k] * np.sqrt(weight1 * weight2)) + + CORR_arr = np.array([CORR[x] for x in to_vn(gn[pairs])]) + + gnnm3 = sp.sparse.lil_matrix(gnnm.shape) + + if use_seq: + gnnm3[pairs[:, 0], pairs[:, 1]] = ( + CORR_arr * np.asarray(gnnm2[pairs[:, 0], pairs[:, 1]]).flatten() + ) + gnnm3[pairs[:, 1], pairs[:, 0]] = ( + CORR_arr * np.asarray(gnnm2[pairs[:, 1], pairs[:, 0]]).flatten() + ) + else: + gnnm3[pairs[:, 0], pairs[:, 1]] = CORR_arr + gnnm3[pairs[:, 1], pairs[:, 0]] = CORR_arr + + gnnm3 = gnnm3.tocsr() + gnnm3.eliminate_zeros() + return gnnm3 + + +def _united_proj( + wpca1: NDArray[Any], + wpca2: NDArray[Any], + k: int = 20, + metric: str = "cosine", + ef: int = 200, + M: int = 48, +) -> sp.sparse.csr_matrix: + """Project between feature spaces using HNSW.""" + metric = "l2" if metric == "euclidean" else metric + metric = "cosine" if metric == "correlation" else metric + labels2 = np.arange(wpca2.shape[0]) + p2 = hnswlib.Index(space=metric, dim=wpca2.shape[1]) + p2.init_index(max_elements=wpca2.shape[0], ef_construction=ef, M=M) + p2.add_items(wpca2, labels2) + p2.set_ef(ef) + idx1, dist1 = p2.knn_query(wpca1, k=k) + + if metric == "cosine": + dist1 = 1 - dist1 + dist1[dist1 < 1e-3] = 1e-3 + dist1 = dist1 / dist1.max(1)[:, None] + dist1 = _tanh_scale(dist1, scale=10, center=0.7) + else: + sigma1 = dist1[:, 4] + sigma1[sigma1 < 1e-3] = 1e-3 + dist1 = np.exp(-dist1 / sigma1[:, None]) + + Sim1 = dist1 + knn1v2 = sp.sparse.lil_matrix((wpca1.shape[0], wpca2.shape[0])) + x1 = np.tile(np.arange(idx1.shape[0])[:, None], (1, idx1.shape[1])).flatten() + knn1v2[x1.astype("int32"), idx1.flatten().astype("int32")] = Sim1.flatten() + return knn1v2.tocsr() + + +def _mapper( + sams: dict[str, SAM], + gnnm: sp.sparse.csr_matrix | None = None, + gn: NDArray[Any] | None = None, + NHS: dict[str, int] | None = None, + umap: bool = False, + mdata: dict[str, Any] | None = None, + k: int | None = None, + K: int = 20, + chunksize: int = 20000, + coarsen: bool = True, + keys: dict[str, str] | None = None, + scale_edges_by_corr: bool = False, + neigh_from_keys: dict[str, bool] | None = None, + pairwise: bool = True, + **kwargs: Any, +) -> SAM: + """Map cells between species.""" + if NHS is None: + NHS = dict.fromkeys(sams.keys(), 3) + + if neigh_from_keys is None: + neigh_from_keys = dict.fromkeys(sams.keys(), False) + + if mdata is None: + mdata = _mapping_window(sams, gnnm, gn, K=K, pairwise=pairwise) + + k1 = K + + if keys is None: + keys = dict.fromkeys(sams.keys(), "leiden_clusters") + + nnms_in: dict[str, Any] = {} + nnms_in0: dict[str, Any] = {} + flag = False + species_indexer = [] + for sid in sams: + logger.info("Expanding neighbourhoods of species %s...", sid) + cl = sams[sid].get_labels(keys[sid]) + _, ix, cluc = np.unique(cl, return_counts=True, return_inverse=True) + K_arr = cluc[ix] + nnms_in0[sid] = sams[sid].adata.obsp["connectivities"].copy() + species_indexer.append(np.arange(sams[sid].adata.shape[0])) + if not neigh_from_keys[sid]: + nnm_in = _smart_expand(nnms_in0[sid], K_arr, NH=NHS[sid]) + nnm_in.data[:] = 1 + nnms_in[sid] = nnm_in + else: + nnms_in[sid] = _generate_coclustering_matrix(cl) + flag = True + + for i in range(1, len(species_indexer)): + species_indexer[i] += species_indexer[i - 1].max() + 1 + + if not flag: + nnm_internal = sp.sparse.block_diag(list(nnms_in.values())).tocsr() + nnm_internal0 = sp.sparse.block_diag(list(nnms_in0.values())).tocsr() + + ovt = mdata["knn"] + ovt0 = ovt.copy() + ovt0.data[:] = 1 + + B = ovt + + logger.info("Indegree coarsening") + + numiter = nnm_internal0.shape[0] // chunksize + 1 + + D = sp.sparse.csr_matrix((0, nnm_internal0.shape[0])) + if flag: + Cs = [] + for it, sid in enumerate(sams.keys()): + nfk = neigh_from_keys[sid] + if nfk: + Cs.append(nnms_in[sid].dot(nnms_in[sid].T.dot(B.T[species_indexer[it]]))) + else: + Cs.append(nnms_in[sid].dot(B.T[species_indexer[it]])) + D = sp.sparse.vstack(Cs).T + del Cs + gc.collect() + else: + for bl in range(numiter): + logger.debug("%d/%d, shape %s", bl, numiter, D.shape) + C = B[bl * chunksize : (bl + 1) * chunksize].dot(nnm_internal.T) + C.data[C.data < 0.1] = 0 + C.eliminate_zeros() + + D = sp.sparse.vstack((D, C)) + del C + gc.collect() + + D = D.multiply(D.T).tocsr() + D.data[:] = D.data**0.5 + mdata["xsim"] = D + + if scale_edges_by_corr: + logger.info("Rescaling edge weights by expression correlations.") + x, y = D.nonzero() + vals = _replace(mdata["wPCA"], x, y) + vals[vals < 1e-3] = 1e-3 + + F = D.copy() + F.data[:] = vals + + ma = np.asarray(F.max(1).todense()) + ma[ma == 0] = 1 + F = F.multiply(1 / ma).tocsr() + F.data[:] = _tanh_scale(F.data, center=0.7, scale=10) + + ma = np.asarray(D.max(1).todense()) + ma[ma == 0] = 1 + + D = F.multiply(D).tocsr() + D.data[:] = np.sqrt(D.data) + + ma2 = np.asarray(D.max(1).todense()) + ma2[ma2 == 0] = 1 + + D = D.multiply(ma / ma2).tocsr() + + species_list = [] + for sid in sams: + species_list += [sid] * sams[sid].adata.shape[0] + species_list = np.array(species_list) + + if not pairwise or len(sams.keys()) == 2: + Dk = sparse_knn(D, k1).tocsr() + denom = k1 + else: + Dk = [] + for sid1 in sams: + row = [] + for sid2 in sams: + if sid1 != sid2: + Dsubk = sparse_knn(D[species_list == sid1][:, species_list == sid2], k1).tocsr() + else: + Dsubk = sp.sparse.csr_matrix((sams[sid1].adata.shape[0],) * 2) + row.append(Dsubk) + Dk.append(sp.sparse.hstack(row)) + Dk = sp.sparse.vstack(Dk).tocsr() + denom = k1 * (len(sams.keys()) - 1) + + sr = np.asarray(Dk.sum(1)) + + x = 1 - sr.flatten() / denom + + sr[sr == 0] = 1 + st = np.asarray(Dk.sum(0)).flatten()[None, :] + st[st == 0] = 1 + proj = Dk.multiply(1 / sr).dot(Dk.multiply(1 / st)).tocsr() + z = proj.copy() + z.data[:] = 1 + idx = np.where(np.asarray(z.sum(1)).flatten() >= k1)[0] + + omp = nnm_internal0 + omp.data[:] = 1 + s = np.asarray(proj.max(1).todense()) + s[s == 0] = 1 + proj = proj.multiply(1 / s).tocsr() + X, Y = omp.nonzero() + X2 = X[np.isin(X, idx)] + Y2 = Y[np.isin(X, idx)] + + omp = omp.tolil() + omp[X2, Y2] = np.vstack((np.asarray(proj[X2, Y2]).flatten(), np.ones(X2.size) * 0.3)).max(0) + + omp = nnm_internal0.tocsr() + NNM = omp.multiply(x[:, None]) + NNM = (NNM + Dk).tolil() + NNM.setdiag(0) + + logger.info("Concatenating SAM objects...") + sam3 = _concatenate_sam(sams, NNM) + + sam3.adata.obs["species"] = pd.Categorical(species_list) + + sam3.adata.uns["gnnm_corr"] = mdata.get("gnnm_corr", None) + + if umap: + logger.info("Computing UMAP projection...") + maxiter = ( + UMAP_MAXITER_SMALL if sam3.adata.shape[0] <= UMAP_SIZE_THRESHOLD else UMAP_MAXITER_LARGE + ) + sc.tl.umap(sam3.adata, min_dist=UMAP_MIN_DIST, maxiter=maxiter) + return sam3 + + +def _concatenate_sam(sams: dict[str, SAM], nnm: sp.sparse.lil_matrix) -> SAM: + """Concatenate SAM objects.""" + acns = [] + exps = [] + agns = [] + sps = [] + for i, sid in enumerate(sams.keys()): + acns.append(_q(sams[sid].adata.obs_names)) + sps.append([sid] * acns[-1].size) + exps.append(sams[sid].adata.X) + agns.append(_q(sams[sid].adata.var_names)) + + acn = np.concatenate(acns) + agn = np.concatenate(agns) + sps_arr = np.concatenate(sps) + + xx = sp.sparse.block_diag(exps, format="csr") + + sam = SAM(counts=(xx, agn, acn)) + + sam.adata.uns["neighbors"] = {} + nnm = nnm.tocsr() + nnm.eliminate_zeros() + sam.adata.obsp["connectivities"] = nnm + sam.adata.uns["neighbors"]["params"] = { + "n_neighbors": 15, + "method": "umap", + "use_rep": "X", + "metric": "euclidean", + } + for i in sams: + for k in sams[i].adata.obs: + if sams[i].adata.obs[k].dtype.name == "category": + z = np.array(["unassigned"] * sam.adata.shape[0], dtype="object") + z[sps_arr == i] = _q(sams[i].adata.obs[k]) + sam.adata.obs[i + "_" + k] = pd.Categorical(z) + + a = [] + for i, sid in enumerate(sams.keys()): + a.extend(["batch" + str(i + 1)] * sams[sid].adata.shape[0]) + sam.adata.obs["batch"] = pd.Categorical(np.array(a)) + sam.adata.obs.columns = sam.adata.obs.columns.astype("str") + sam.adata.var.columns = sam.adata.var.columns.astype("str") + + for i in sam.adata.obs: + sam.adata.obs[i] = sam.adata.obs[i].astype("str") + + return sam + + +def _mapping_window( + sams: dict[str, SAM], + gnnm: sp.sparse.csr_matrix | None = None, + gns: NDArray[Any] | None = None, + K: int = 20, + pairwise: bool = True, +) -> dict[str, Any]: + """Create mapping window for cross-species projection.""" + k = K + output_dict: dict[str, Any] = {} + if gnnm is not None and gns is not None: + logger.info("Prepping datasets for translation.") + gnnm_corr = gnnm.copy() + gnnm_corr.data[:] = _tanh_scale(gnnm_corr.data) + + std = StandardScaler(with_mean=False) + + gs = {} + adatas = {} + Ws = {} + ss = {} + species_indexer = [] + genes_indexer = [] + for sid in sams: + gs[sid] = gns[np.isin(gns, _q(sams[sid].adata.var_names))] + adatas[sid] = sams[sid].adata[:, gs[sid]] + Ws[sid] = adatas[sid].var["weights"].values + ss[sid] = std.fit_transform(adatas[sid].X).multiply(Ws[sid][None, :]).tocsr() + species_indexer.append(np.arange(ss[sid].shape[0])) + genes_indexer.append(np.arange(gs[sid].size)) + + for i in range(1, len(species_indexer)): + species_indexer[i] = species_indexer[i] + species_indexer[i - 1].max() + 1 + genes_indexer[i] = genes_indexer[i] + genes_indexer[i - 1].max() + 1 + + su = np.asarray(gnnm_corr.sum(0)) + su[su == 0] = 1 + gnnm_corr = gnnm_corr.multiply(1 / su).tocsr() + + X = sp.sparse.block_diag(list(ss.values())).tocsr() + W = np.concatenate(list(Ws.values())).flatten() + + ttt = time.time() + if pairwise: + logger.info("Translating feature spaces pairwise.") + Xtr = [] + for i, _sid1 in enumerate(sams.keys()): + xtr = [] + for j, _sid2 in enumerate(sams.keys()): + if i != j: + gnnm_corr_sub = gnnm_corr[genes_indexer[i]][:, genes_indexer[j]] + su = np.asarray(gnnm_corr_sub.sum(0)) + su[su == 0] = 1 + gnnm_corr_sub = gnnm_corr_sub.multiply(1 / su).tocsr() + xtr.append(X[species_indexer[i]][:, genes_indexer[i]].dot(gnnm_corr_sub)) + xtr[-1] = std.fit_transform(xtr[-1]).multiply(W[genes_indexer[j]][None, :]) + else: + xtr.append( + sp.sparse.csr_matrix((species_indexer[i].size, genes_indexer[i].size)) + ) + Xtr.append(sp.sparse.hstack(xtr)) + Xtr = sp.sparse.vstack(Xtr) + else: + logger.info("Translating feature spaces all-to-all.") + + Xtr = [] + for i, sid in enumerate(sams.keys()): + Xtr.append(X[species_indexer[i]].dot(gnnm_corr)) + Xtr[-1] = std.fit_transform(Xtr[-1]).multiply(W[None, :]) + Xtr = sp.sparse.vstack(Xtr) + Xc = (X + Xtr).tocsr() + + mus = [] + for i, sid in enumerate(sams.keys()): + mus.append(np.asarray(Xc[species_indexer[i]].mean(0)).flatten()) + + gc.collect() + + logger.info("Projecting data into joint latent space. %.2fs", time.time() - ttt) + C = sp.linalg.block_diag(*[adatas[sid].varm["PCs_SAMap"] for sid in sams]) + M = np.vstack(mus).dot(C) + ttt = time.time() + it = 0 + PCAs = [] + for sid in sams: + PCAs.append(Xc[:, it : it + gs[sid].size].dot(adatas[sid].varm["PCs_SAMap"])) + it += gs[sid].size + wpca = np.hstack(PCAs) + + logger.info("Correcting data with means. %.2fs", time.time() - ttt) + for i, sid in enumerate(sams.keys()): + ixq = species_indexer[i] + wpca[ixq] -= M[i] + output_dict["gnnm_corr"] = gnnm_corr + else: + std = StandardScaler(with_mean=False) + + gs = {} + adatas = {} + Ws = {} + ss = {} + species_indexer = [] + mus = [] + for sid in sams: + adatas[sid] = sams[sid].adata + Ws[sid] = adatas[sid].var["weights"].values + ss[sid] = std.fit_transform(adatas[sid].X).multiply(Ws[sid][None, :]).tocsr() + mus.append(np.asarray(ss[sid].mean(0)).flatten()) + species_indexer.append(np.arange(ss[sid].shape[0])) + for i in range(1, len(species_indexer)): + species_indexer[i] = species_indexer[i] + species_indexer[i - 1].max() + 1 + X = sp.sparse.vstack(list(ss.values())) + C = np.hstack([adatas[sid].varm["PCs_SAMap"] for sid in sams]) + wpca = X.dot(C) + M = np.vstack(mus).dot(C) + for i, sid in enumerate(sams.keys()): + ixq = species_indexer[i] + wpca[ixq] -= M[i] + + ixg = np.arange(wpca.shape[0]) + Xs = [] + Ys = [] + Vs = [] + for i, sid in enumerate(sams.keys()): + ixq = species_indexer[i] + query = wpca[ixq] + + for j, _sid2 in enumerate(sams.keys()): + if i != j: + ixr = species_indexer[j] + reference = wpca[ixr] + + b = _united_proj(query, reference, k=k) + + su = b.sum(1).A + su[su == 0] = 1 + b = b.multiply(1 / su).tocsr() + + A = pd.Series(index=np.arange(b.shape[0]), data=ixq) + B = pd.Series(index=np.arange(b.shape[1]), data=ixr) + + x, y = b.nonzero() + x, y = A[x].values, B[y].values + Xs.extend(x) + Ys.extend(y) + Vs.extend(b.data) + + knn = sp.sparse.coo_matrix((Vs, (Xs, Ys)), shape=(ixg.size, ixg.size)) + + output_dict["knn"] = knn.tocsr() + output_dict["wPCA"] = wpca + return output_dict + + +def _sparse_knn_ks(D: sp.sparse.coo_matrix, ks: NDArray[Any]) -> sp.sparse.coo_matrix: + """Keep variable top-k values per row in sparse matrix.""" + D1 = D.tocoo() + idr = np.argsort(D1.row) + D1.row[:] = D1.row[idr] + D1.col[:] = D1.col[idr] + D1.data[:] = D1.data[idr] + + row, ind = np.unique(D1.row, return_index=True) + ind = np.append(ind, D1.data.size) + for i in range(ind.size - 1): + idx = np.argsort(D1.data[ind[i] : ind[i + 1]]) + k = ks[row[i]] + if idx.size > k: + idx = idx[:-k] if k != 0 else idx + D1.data[np.arange(ind[i], ind[i + 1])[idx]] = 0 + D1.eliminate_zeros() + return D1 + + +def _smart_expand(nnm: sp.sparse.csr_matrix, K: NDArray[Any], NH: int = 3) -> sp.sparse.csr_matrix: + """Expand neighborhoods progressively.""" + stage0 = nnm.copy() + S = [stage0] + running = stage0 + for i in range(1, NH + 1): + stage = running.dot(stage0) + running = stage + stage = stage.tolil() + for j in range(i): + stage[S[j].nonzero()] = 0 + stage = stage.tocsr() + S.append(stage) + + for i in range(len(S)): + s = _sparse_knn_ks(S[i], K).tocsr() + a, c = np.unique(s.nonzero()[0], return_counts=True) + numnz = np.zeros(s.shape[0], dtype="int32") + numnz[a] = c + K = K - numnz + K[K < 0] = 0 + S[i] = s + res = S[0] + for i in range(1, len(S)): + res = res + S[i] + return res diff --git a/src/samap/exceptions.py b/src/samap/exceptions.py new file mode 100644 index 0000000..56aa37e --- /dev/null +++ b/src/samap/exceptions.py @@ -0,0 +1,31 @@ +"""Custom exceptions for SAMap.""" + +from __future__ import annotations + + +class SAMapError(Exception): + """Base exception for SAMap errors.""" + + +class BlastGraphError(SAMapError): + """Error related to BLAST graph construction or processing.""" + + +class MappingError(SAMapError): + """Error during SAMap mapping process.""" + + +class DataError(SAMapError): + """Error related to input data format or content.""" + + +class SpeciesNotFoundError(SAMapError): + """Species ID not found in the SAMAP object.""" + + +class GeneNotFoundError(SAMapError): + """Gene not found in the dataset.""" + + +class DependencyError(SAMapError): + """Required dependency is not installed.""" diff --git a/src/samap/io/__init__.py b/src/samap/io/__init__.py new file mode 100644 index 0000000..c8ff650 --- /dev/null +++ b/src/samap/io/__init__.py @@ -0,0 +1,7 @@ +"""I/O utilities for SAMap.""" + +from __future__ import annotations + +from samap.utils import load_samap, save_samap + +__all__ = ["load_samap", "save_samap"] diff --git a/src/samap/utils.py b/src/samap/utils.py new file mode 100644 index 0000000..13172fa --- /dev/null +++ b/src/samap/utils.py @@ -0,0 +1,273 @@ +"""Utility functions for SAMap.""" + +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np +import pandas as pd + +from samap._logging import logger + +if TYPE_CHECKING: + from typing import Any + + import scipy.sparse as sp + from numpy.typing import NDArray + from samalg import SAM + + +def save_samap(sm: Any, fn: str) -> None: + """Save a SAMAP object to a pickle file. + + Parameters + ---------- + sm : SAMAP + The SAMAP object to save. + fn : str + File path. If it doesn't end with '.pkl', the extension is added. + """ + import dill + + if not fn.endswith(".pkl"): + fn = fn + ".pkl" + sm.path_to_file = fn + + # Clean up GUI and UMAP objects that can't be pickled + _cleanup_for_serialization(sm) + + with open(fn, "wb") as f: + dill.dump(sm, f) + logger.info("Saved SAMAP object to %s", fn) + + +def _cleanup_for_serialization(sm: Any) -> None: + """Remove unpicklable attributes from a SAMAP object. + + Parameters + ---------- + sm : SAMAP + The SAMAP object to clean up. + """ + # Clean up GUI references + for attr in ("sam1", "sam2", "samap"): + if hasattr(sm, attr): + sam_obj = getattr(sm, attr) + if hasattr(sam_obj, "SamGui"): + delattr(sam_obj, "SamGui") + if hasattr(sam_obj, "umap_obj"): + delattr(sam_obj, "umap_obj") + + if hasattr(sm, "SamapGui"): + delattr(sm, "SamapGui") + + +def load_samap(fn: str) -> Any: + """Load a SAMAP object from a pickle file. + + Parameters + ---------- + fn : str + File path. If it doesn't end with '.pkl', the extension is added. + + Returns + ------- + SAMAP + The loaded SAMAP object. + """ + import dill + + if not fn.endswith(".pkl"): + fn = fn + ".pkl" + with open(fn, "rb") as f: + sm = dill.load(f) + logger.info("Loaded SAMAP object from %s", fn) + return sm + + +def prepend_var_prefix(s: SAM, pre: str) -> None: + """Add species prefix to variable names in a SAM object. + + Parameters + ---------- + s : SAM + SAM object to modify. + pre : str + Prefix to add (e.g., species ID). + """ + x = [str(name).split("_")[0] for name in s.adata.var_names] + vn = [] + for i, g in enumerate(s.adata.var_names): + if x[i] != pre: + vn.append(pre + "_" + g) + else: + vn.append(g) + s.adata.var_names = pd.Index(vn) + s.adata_raw.var_names = pd.Index(vn) + + +def df_to_dict( + df: pd.DataFrame, + key_key: str | None = None, + val_key: list[str] | None = None, +) -> dict[str, NDArray[Any]]: + """Convert a DataFrame to a dictionary mapping keys to value arrays. + + Parameters + ---------- + df : pd.DataFrame + Input DataFrame. + key_key : str, optional + Column to use as keys. If None, uses the index. + val_key : list of str, optional + Columns to use as values. If empty, uses all columns. + + Returns + ------- + dict + Dictionary mapping keys to arrays of values. + """ + if val_key is None: + val_key = [] + + index = list(df.index) if key_key is None else list(df[key_key].values) + + if len(val_key) == 0: + val_key = list(df.columns) + + a = [] + b = [] + for key in val_key: + if key != key_key: + a.extend(index) + b.extend(list(df[key].values)) + a_arr = np.array(a) + b_arr = np.array(b) + + idx = np.argsort(a_arr) + a_arr = a_arr[idx] + b_arr = b_arr[idx] + bounds = np.where(a_arr[:-1] != a_arr[1:])[0] + 1 + bounds = np.append(np.append(0, bounds), a_arr.size) + bounds_left = bounds[:-1] + bounds_right = bounds[1:] + slists = [b_arr[bounds_left[i] : bounds_right[i]] for i in range(bounds_left.size)] + return dict(zip(np.unique(a_arr), slists)) + + +def to_vn(op: NDArray[Any]) -> NDArray[np.str_]: + """Convert a 2D array of pairs to semicolon-separated strings. + + Parameters + ---------- + op : ndarray + Nx2 array of pairs. + + Returns + ------- + ndarray + 1D array of strings in format "a;b". + """ + return np.array(list(op[:, 0].astype("object") + ";" + op[:, 1].astype("object"))) + + +def to_vo(op: NDArray[Any]) -> NDArray[Any]: + """Convert semicolon-separated strings to a 2D array of pairs. + + Parameters + ---------- + op : ndarray + 1D array of strings in format "a;b". + + Returns + ------- + ndarray + Nx2 array of pairs. + """ + import samalg.utilities as ut + + return np.vstack(ut.extract_annotation(op, None, ";")).T + + +def substr( + x: NDArray[Any] | list[str], + s: str = "_", + ix: int | None = None, + obj: bool = False, +) -> NDArray[Any] | list[NDArray[Any]]: + """Split strings by a separator and optionally extract specific indices. + + Parameters + ---------- + x : array-like + Array of strings to split. + s : str, optional + Separator, by default "_". + ix : int, optional + Index to extract. If None, returns all parts as separate arrays. + obj : bool, optional + If True, return as object dtype. + + Returns + ------- + ndarray or list of ndarray + Extracted parts or list of all parts. + """ + m = [] + if ix is not None: + for i in range(len(x)): + f = x[i].split(s) + safe_ix = min(len(f) - 1, ix) + m.append(f[safe_ix]) + return np.array(m).astype("object") if obj else np.array(m) + else: + ms = [] + ls = [] + for i in range(len(x)): + f = x[i].split(s) + m = [] + for idx in range(len(f)): + m.append(f[idx]) + ms.append(m) + ls.append(len(m)) + ml = max(ls) + for i in range(len(ms)): + ms[i].extend([""] * (ml - len(ms[i]))) + if ml - len(ms[i]) > 0: + ms[i] = np.concatenate(ms[i]) + result = np.vstack(ms) + if obj: + result = result.astype("object") + return [result[:, i] for i in range(result.shape[1])] + + +def sparse_knn(D: sp.coo_matrix, k: int) -> sp.coo_matrix: + """Keep only the top-k values per row in a sparse matrix. + + Parameters + ---------- + D : scipy.sparse matrix + Input sparse matrix. + k : int + Number of neighbors to keep per row. + + Returns + ------- + scipy.sparse.coo_matrix + Sparse matrix with only top-k values per row. + """ + D1 = D.tocoo() + idr = np.argsort(D1.row) + D1.row[:] = D1.row[idr] + D1.col[:] = D1.col[idr] + D1.data[:] = D1.data[idr] + + _, ind = np.unique(D1.row, return_index=True) + ind = np.append(ind, D1.data.size) + for i in range(ind.size - 1): + idx = np.argsort(D1.data[ind[i] : ind[i + 1]]) + if idx.size > k: + idx = idx[:-k] + D1.data[np.arange(ind[i], ind[i + 1])[idx]] = 0 + D1.eliminate_zeros() + return D1 diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..a0c021a --- /dev/null +++ b/tests/__init__.py @@ -0,0 +1 @@ +"""SAMap test suite.""" diff --git a/tests/conftest.py b/tests/conftest.py new file mode 100644 index 0000000..95553c7 --- /dev/null +++ b/tests/conftest.py @@ -0,0 +1,57 @@ +"""Shared pytest fixtures for SAMap tests.""" + +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np +import pandas as pd +import pytest +import scipy.sparse as sp + +if TYPE_CHECKING: + from numpy.typing import NDArray + + +@pytest.fixture +def rng() -> np.random.Generator: + """Reproducible random number generator.""" + return np.random.default_rng(42) + + +@pytest.fixture +def sample_sparse_matrix(rng: np.random.Generator) -> sp.csr_matrix: + """Create a sample sparse matrix for testing.""" + data = rng.random((100, 100)) + data[data < 0.9] = 0 # Make it sparse + return sp.csr_matrix(data) + + +@pytest.fixture +def sample_dataframe() -> pd.DataFrame: + """Create a sample DataFrame for testing.""" + return pd.DataFrame( + { + "gene": ["geneA", "geneA", "geneB", "geneC", "geneC", "geneC"], + "value": [1, 2, 3, 4, 5, 6], + }, + index=["idx1", "idx2", "idx3", "idx4", "idx5", "idx6"], + ) + + +@pytest.fixture +def sample_gene_pairs() -> NDArray[np.str_]: + """Create sample gene pairs for testing.""" + return np.array( + [ + ["hu_SOX2", "ms_Sox2"], + ["hu_OCT4", "ms_Oct4"], + ["hu_NANOG", "ms_Nanog"], + ] + ) + + +@pytest.fixture +def sample_species_ids() -> list[str]: + """Sample species identifiers.""" + return ["hu", "ms"] diff --git a/tests/fixtures/__init__.py b/tests/fixtures/__init__.py new file mode 100644 index 0000000..4fb15d8 --- /dev/null +++ b/tests/fixtures/__init__.py @@ -0,0 +1 @@ +"""Test fixtures and synthetic data generators for SAMap.""" diff --git a/tests/fixtures/synthetic_data.py b/tests/fixtures/synthetic_data.py new file mode 100644 index 0000000..271fee8 --- /dev/null +++ b/tests/fixtures/synthetic_data.py @@ -0,0 +1,133 @@ +"""Synthetic data generators for SAMap tests.""" + +from __future__ import annotations + +from typing import TYPE_CHECKING + +import numpy as np +import scipy.sparse as sp + +if TYPE_CHECKING: + from numpy.typing import NDArray + + +def generate_synthetic_expression_matrix( + n_cells: int = 100, + n_genes: int = 500, + sparsity: float = 0.8, + seed: int = 42, +) -> sp.csr_matrix: + """Generate synthetic single-cell expression matrix. + + Parameters + ---------- + n_cells : int + Number of cells. + n_genes : int + Number of genes. + sparsity : float + Fraction of zeros in the matrix. + seed : int + Random seed. + + Returns + ------- + scipy.sparse.csr_matrix + Synthetic expression matrix. + """ + rng = np.random.default_rng(seed) + data = rng.poisson(lam=2, size=(n_cells, n_genes)).astype(float) + mask = rng.random((n_cells, n_genes)) < sparsity + data[mask] = 0 + return sp.csr_matrix(data) + + +def generate_synthetic_gene_names( + n_genes: int = 500, + species_prefix: str = "hu", +) -> NDArray[np.str_]: + """Generate synthetic gene names. + + Parameters + ---------- + n_genes : int + Number of genes. + species_prefix : str + Species prefix to add. + + Returns + ------- + ndarray + Array of gene names. + """ + return np.array([f"{species_prefix}_GENE{i:04d}" for i in range(n_genes)]) + + +def generate_synthetic_cell_names( + n_cells: int = 100, + prefix: str = "cell", +) -> NDArray[np.str_]: + """Generate synthetic cell names. + + Parameters + ---------- + n_cells : int + Number of cells. + prefix : str + Cell name prefix. + + Returns + ------- + ndarray + Array of cell names. + """ + return np.array([f"{prefix}_{i:04d}" for i in range(n_cells)]) + + +def generate_synthetic_homology_graph( + gene_names_1: NDArray[np.str_], + gene_names_2: NDArray[np.str_], + n_homologs: int = 100, + seed: int = 42, +) -> tuple[sp.csr_matrix, NDArray[np.str_]]: + """Generate synthetic gene homology graph. + + Parameters + ---------- + gene_names_1 : ndarray + Gene names from species 1. + gene_names_2 : ndarray + Gene names from species 2. + n_homologs : int + Number of homologous gene pairs. + seed : int + Random seed. + + Returns + ------- + tuple + (homology_matrix, combined_gene_names) + """ + rng = np.random.default_rng(seed) + + n_genes_1 = len(gene_names_1) + n_genes_2 = len(gene_names_2) + n_total = n_genes_1 + n_genes_2 + + # Create combined gene names + all_genes = np.concatenate([gene_names_1, gene_names_2]) + + # Create sparse homology matrix + gnnm = sp.lil_matrix((n_total, n_total)) + + # Add random homolog connections + n_homologs = min(n_homologs, min(n_genes_1, n_genes_2)) + idx1 = rng.choice(n_genes_1, n_homologs, replace=False) + idx2 = rng.choice(n_genes_2, n_homologs, replace=False) + n_genes_1 + + for i, j in zip(idx1, idx2): + score = rng.random() * 0.5 + 0.5 # Score between 0.5 and 1.0 + gnnm[i, j] = score + gnnm[j, i] = score + + return gnnm.tocsr(), all_genes diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py new file mode 100644 index 0000000..256f5e1 --- /dev/null +++ b/tests/integration/__init__.py @@ -0,0 +1 @@ +"""Integration tests for SAMap.""" diff --git a/tests/integration/test_samap_integration.py b/tests/integration/test_samap_integration.py new file mode 100644 index 0000000..c105b23 --- /dev/null +++ b/tests/integration/test_samap_integration.py @@ -0,0 +1,149 @@ +"""Integration tests for SAMAP using example data.""" + +from pathlib import Path + +import pytest +from samalg import SAM + +from samap import SAMAP +from samap.analysis import GenePairFinder, get_mapping_scores, sankey_plot + +# Path to example data relative to repo root +EXAMPLE_DATA = Path(__file__).parent.parent.parent / "example_data" + + +@pytest.fixture(scope="module") +def example_data_path(): + """Return path to example data, skip if not available.""" + if not EXAMPLE_DATA.exists(): + pytest.skip("Example data not available") + return EXAMPLE_DATA + + +@pytest.fixture(scope="module") +def sam_objects(example_data_path): + """Load SAM objects from example h5ad files.""" + sam1 = SAM() + sam1.load_data(str(example_data_path / "planarian.h5ad")) + + sam2 = SAM() + sam2.load_data(str(example_data_path / "schistosome.h5ad")) + + sam3 = SAM() + sam3.load_data(str(example_data_path / "hydra.h5ad")) + + return {"pl": sam1, "sc": sam2, "hy": sam3} + + +class TestSAMAPInitialization: + """Test SAMAP initialization with example data.""" + + def test_samap_init_with_three_species(self, sam_objects, example_data_path): + """Test SAMAP initialization with three species (pl, sc, hy).""" + sm = SAMAP( + sam_objects, + f_maps=str(example_data_path / "maps") + "/", + ) + + assert sm is not None + assert hasattr(sm, "sams") + assert len(sm.sams) == 3 + + def test_samap_init_with_two_species(self, sam_objects, example_data_path): + """Test SAMAP initialization with two species subset.""" + two_species = {"pl": sam_objects["pl"], "sc": sam_objects["sc"]} + + sm = SAMAP( + two_species, + f_maps=str(example_data_path / "maps") + "/", + ) + + assert sm is not None + assert len(sm.sams) == 2 + + +class TestSAMAPMapping: + """Test SAMAP mapping functionality.""" + + @pytest.fixture(scope="class") + def samap_instance(self, sam_objects, example_data_path): + """Create a SAMAP instance for mapping tests.""" + return SAMAP( + sam_objects, + f_maps=str(example_data_path / "maps") + "/", + ) + + def test_run_mapping(self, samap_instance): + """Test running the SAMAP algorithm.""" + samap_instance.run() + + # Verify mapping completed + assert hasattr(samap_instance, "samap") + + def test_get_mapping_scores(self, samap_instance): + """Test retrieving mapping scores after running SAMAP.""" + # Ensure mapping has been run + if not hasattr(samap_instance, "samap"): + samap_instance.run() + + # Test getting mapping scores using annotation columns + # These column names come from the example data + keys = {"pl": "cluster", "hy": "Cluster", "sc": "tissue"} + D, MappingTable = get_mapping_scores(samap_instance, keys, n_top=0) + + assert D is not None + assert MappingTable is not None + # D and MappingTable should be DataFrames + assert hasattr(D, "index") + assert hasattr(MappingTable, "index") + assert hasattr(MappingTable, "columns") + + def test_sankey_plot(self, samap_instance): + """Test generating a sankey plot from mapping scores.""" + # Ensure mapping has been run + if not hasattr(samap_instance, "samap"): + samap_instance.run() + + # Get mapping scores + keys = {"pl": "cluster", "hy": "Cluster", "sc": "tissue"} + _, MappingTable = get_mapping_scores(samap_instance, keys, n_top=0) + + # Generate sankey plot + fig = sankey_plot(MappingTable, species_order=["pl", "sc", "hy"], align_thr=0.1) + + # Verify it's a plotly figure + import plotly.graph_objects as go + + assert isinstance(fig, go.Figure) + + # Verify the sankey has nodes and links + assert len(fig.data) == 1 + assert fig.data[0].node.label is not None + assert len(fig.data[0].node.label) > 0 + assert fig.data[0].link.source is not None + + def test_gene_pair_finder(self, samap_instance): + """Test GenePairFinder to find genes linking cell types.""" + # Ensure mapping has been run + if not hasattr(samap_instance, "samap"): + samap_instance.run() + + # Create GenePairFinder with all 3 species + keys = {"pl": "cluster", "sc": "tissue", "hy": "Cluster"} + gpf = GenePairFinder(samap_instance, keys=keys) + + # Find genes linking two cell types + n1 = "pl_Neoblast: 0" + n2 = "sc_Neoblast" + Gp, G1, G2, pvals1, pvals2 = gpf.find_genes(n1, n2) + + # Verify results + assert Gp is not None + assert G1 is not None + assert G2 is not None + # Gp contains gene pairs, G1/G2 are individual gene lists + assert len(Gp) > 0 + assert len(G1) > 0 + assert len(G2) > 0 + assert len(pvals1) == len(Gp) + assert len(pvals2) == len(Gp) diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py new file mode 100644 index 0000000..479d809 --- /dev/null +++ b/tests/unit/__init__.py @@ -0,0 +1 @@ +"""Unit tests for SAMap.""" diff --git a/tests/unit/test_constants.py b/tests/unit/test_constants.py new file mode 100644 index 0000000..c385d99 --- /dev/null +++ b/tests/unit/test_constants.py @@ -0,0 +1,52 @@ +"""Unit tests for samap._constants module.""" + +from __future__ import annotations + +from samap._constants import ( + DEFAULT_ALIGNMENT_THRESHOLD, + DEFAULT_CROSS_K, + DEFAULT_EVAL_THRESHOLD, + DEFAULT_FILTER_THRESHOLD, + DEFAULT_NUM_ITERATIONS, + KOG_TABLE, + UMAP_MIN_DIST, + UMAP_SIZE_THRESHOLD, +) + + +class TestConstants: + """Tests for constant values.""" + + def test_eval_threshold_is_float(self) -> None: + """Test that eval threshold is a float.""" + assert isinstance(DEFAULT_EVAL_THRESHOLD, float) + assert DEFAULT_EVAL_THRESHOLD == 1e-6 + + def test_filter_threshold_is_float(self) -> None: + """Test that filter threshold is a float.""" + assert isinstance(DEFAULT_FILTER_THRESHOLD, float) + assert DEFAULT_FILTER_THRESHOLD == 0.25 + + def test_umap_constants(self) -> None: + """Test UMAP-related constants.""" + assert isinstance(UMAP_MIN_DIST, float) + assert isinstance(UMAP_SIZE_THRESHOLD, int) + assert UMAP_SIZE_THRESHOLD == 10000 + + def test_default_parameters(self) -> None: + """Test default algorithm parameters.""" + assert DEFAULT_NUM_ITERATIONS == 3 + assert DEFAULT_CROSS_K == 20 + assert DEFAULT_ALIGNMENT_THRESHOLD == 0.1 + + def test_kog_table_completeness(self) -> None: + """Test that KOG table has expected entries.""" + assert isinstance(KOG_TABLE, dict) + # Check some known KOG categories + assert "A" in KOG_TABLE + assert "J" in KOG_TABLE + assert "Z" in KOG_TABLE + # Check content + assert "RNA processing" in KOG_TABLE["A"] + assert "Translation" in KOG_TABLE["J"] + assert "Cytoskeleton" in KOG_TABLE["Z"] diff --git a/tests/unit/test_exceptions.py b/tests/unit/test_exceptions.py new file mode 100644 index 0000000..92686f0 --- /dev/null +++ b/tests/unit/test_exceptions.py @@ -0,0 +1,64 @@ +"""Unit tests for samap.exceptions module.""" + +from __future__ import annotations + +import pytest + +from samap.exceptions import ( + BlastGraphError, + DataError, + DependencyError, + GeneNotFoundError, + MappingError, + SAMapError, + SpeciesNotFoundError, +) + + +class TestExceptions: + """Tests for custom exception classes.""" + + def test_samap_error_is_base(self) -> None: + """Test that SAMapError is the base exception.""" + with pytest.raises(SAMapError): + raise SAMapError("test error") + + def test_blast_graph_error_inherits(self) -> None: + """Test that BlastGraphError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise BlastGraphError("blast error") + with pytest.raises(BlastGraphError): + raise BlastGraphError("blast error") + + def test_mapping_error_inherits(self) -> None: + """Test that MappingError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise MappingError("mapping error") + + def test_data_error_inherits(self) -> None: + """Test that DataError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise DataError("data error") + + def test_species_not_found_inherits(self) -> None: + """Test that SpeciesNotFoundError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise SpeciesNotFoundError("species not found") + + def test_gene_not_found_inherits(self) -> None: + """Test that GeneNotFoundError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise GeneNotFoundError("gene not found") + + def test_dependency_error_inherits(self) -> None: + """Test that DependencyError inherits from SAMapError.""" + with pytest.raises(SAMapError): + raise DependencyError("dependency missing") + + def test_exception_messages(self) -> None: + """Test that exception messages are preserved.""" + msg = "custom error message" + try: + raise SAMapError(msg) + except SAMapError as e: + assert str(e) == msg diff --git a/tests/unit/test_utils.py b/tests/unit/test_utils.py new file mode 100644 index 0000000..2d7bec6 --- /dev/null +++ b/tests/unit/test_utils.py @@ -0,0 +1,162 @@ +"""Unit tests for samap.utils module.""" + +from __future__ import annotations + +import numpy as np +import pandas as pd +import pytest +import scipy.sparse as sp + +from samap.utils import df_to_dict, sparse_knn, substr, to_vn, to_vo + + +class TestToVn: + """Tests for to_vn function.""" + + def test_basic_conversion(self) -> None: + """Test basic array to semicolon-separated strings.""" + arr = np.array([["a", "b"], ["c", "d"], ["e", "f"]]) + result = to_vn(arr) + expected = np.array(["a;b", "c;d", "e;f"]) + np.testing.assert_array_equal(result, expected) + + def test_empty_array(self) -> None: + """Test with empty array.""" + arr = np.array([]).reshape(0, 2) + result = to_vn(arr) + assert len(result) == 0 + + def test_single_row(self) -> None: + """Test with single row.""" + arr = np.array([["gene1", "gene2"]]) + result = to_vn(arr) + expected = np.array(["gene1;gene2"]) + np.testing.assert_array_equal(result, expected) + + +class TestSubstr: + """Tests for substr function.""" + + def test_split_with_index(self) -> None: + """Test splitting strings and extracting specific index.""" + strings = np.array(["hu_SOX2", "ms_Oct4", "hu_NANOG"]) + result = substr(strings, "_", 0) + expected = np.array(["hu", "ms", "hu"]) + np.testing.assert_array_equal(result, expected) + + def test_split_second_index(self) -> None: + """Test extracting second part after split.""" + strings = np.array(["hu_SOX2", "ms_Oct4", "hu_NANOG"]) + result = substr(strings, "_", 1) + expected = np.array(["SOX2", "Oct4", "NANOG"]) + np.testing.assert_array_equal(result, expected) + + def test_split_without_index(self) -> None: + """Test splitting without index returns all parts.""" + strings = np.array(["a_b_c", "d_e_f"]) + result = substr(strings, "_") + assert isinstance(result, list) + assert len(result) == 3 + np.testing.assert_array_equal(result[0], np.array(["a", "d"])) + np.testing.assert_array_equal(result[1], np.array(["b", "e"])) + np.testing.assert_array_equal(result[2], np.array(["c", "f"])) + + def test_split_with_object_dtype(self) -> None: + """Test with object dtype output.""" + strings = np.array(["hu_SOX2", "ms_Oct4"]) + result = substr(strings, "_", 0, obj=True) + assert result.dtype == object + + def test_index_out_of_bounds(self) -> None: + """Test that out-of-bounds index returns last element.""" + strings = np.array(["hu_SOX2", "ms"]) + result = substr(strings, "_", 5) # Index beyond available parts + # Should return last available part + assert result[0] == "SOX2" + assert result[1] == "ms" + + +class TestDfToDict: + """Tests for df_to_dict function.""" + + def test_basic_conversion(self, sample_dataframe: pd.DataFrame) -> None: + """Test basic DataFrame to dict conversion.""" + result = df_to_dict(sample_dataframe, key_key="gene", val_key=["value"]) + assert "geneA" in result + assert "geneB" in result + assert "geneC" in result + np.testing.assert_array_equal(result["geneA"], np.array([1, 2])) + np.testing.assert_array_equal(result["geneB"], np.array([3])) + np.testing.assert_array_equal(result["geneC"], np.array([4, 5, 6])) + + def test_with_index_as_key(self) -> None: + """Test using index as key.""" + df = pd.DataFrame({"col1": [1, 2, 3]}, index=["a", "b", "c"]) + result = df_to_dict(df, key_key=None, val_key=["col1"]) + assert "a" in result + assert "b" in result + assert "c" in result + + +class TestSparseKnn: + """Tests for sparse_knn function.""" + + def test_keeps_top_k(self) -> None: + """Test that function keeps top-k values per row.""" + # Create a dense matrix and convert to sparse + data = np.array([[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]], dtype=float) + sparse = sp.csr_matrix(data) + + result = sparse_knn(sparse, k=2) + + # Each row should have at most k non-zero values + for i in range(result.shape[0]): + row = result.getrow(i).toarray().flatten() + assert np.count_nonzero(row) <= 2 + + def test_preserves_largest_values(self) -> None: + """Test that largest values are preserved.""" + data = np.array([[1, 5, 2, 4], [3, 8, 1, 6]], dtype=float) + sparse = sp.csr_matrix(data) + + result = sparse_knn(sparse, k=2) + + # First row: 5 and 4 should be kept + row0 = result.getrow(0).toarray().flatten() + assert 5 in row0 + assert 4 in row0 + + # Second row: 8 and 6 should be kept + row1 = result.getrow(1).toarray().flatten() + assert 8 in row1 + assert 6 in row1 + + def test_handles_sparse_input(self, sample_sparse_matrix: sp.csr_matrix) -> None: + """Test with actual sparse input.""" + result = sparse_knn(sample_sparse_matrix, k=5) + + # Result should be sparse + assert sp.issparse(result) + + # Each row should have at most k values + for i in range(result.shape[0]): + row = result.getrow(i).toarray().flatten() + assert np.count_nonzero(row) <= 5 + + +class TestToVo: + """Tests for to_vo function.""" + + def test_converts_back_from_vn(self) -> None: + """Test that to_vo converts semicolon strings back to pairs.""" + # This test requires samalg to be installed + pytest.importorskip("samalg") + + vn_strings = np.array(["gene1;gene2", "gene3;gene4"]) + result = to_vo(vn_strings) + + assert result.shape == (2, 2) + assert result[0, 0] == "gene1" + assert result[0, 1] == "gene2" + assert result[1, 0] == "gene3" + assert result[1, 1] == "gene4"