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dwhswensondwhswenson
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Updates for Python 3
1 parent 295aa4f commit cfe9555

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-113
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5 files changed

+61
-113
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‎0_jupyter_intro.ipynb‎

Lines changed: 3 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -15,6 +15,7 @@
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},
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"outputs": [],
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"source": [
18+
"from __future__ import print_function\n",
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"import openpathsampling as paths"
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]
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},
@@ -135,7 +136,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
138-
"print message"
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"print(message)"
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]
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},
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{
@@ -200,7 +201,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.13"
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"version": "2.7.14"
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}
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},
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"nbformat": 4,

‎1_tps_sampling_tutorial.ipynb‎

Lines changed: 19 additions & 50 deletions
Original file line numberDiff line numberDiff line change
@@ -25,12 +25,11 @@
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{
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"cell_type": "code",
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"execution_count": null,
28-
"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib inline\n",
32+
"from __future__ import print_function\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"\n",
@@ -70,9 +69,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# this cell is all OpenMM specific\n",
@@ -104,9 +101,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"openmm_properties = {}\n",
@@ -146,9 +141,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"md_topology = md.Topology.from_openmm(engine.simulation.topology)"
@@ -164,13 +157,11 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"for atom_number in md_topology.select(\"backbone\"):\n",
173-
" print atom_number, md_topology.atom(atom_number)"
164+
" print(atom_number, md_topology.atom(atom_number))"
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]
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},
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{
@@ -183,9 +174,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# ACE0-C, ALA1-N, ALA1-CA, ALA1-C: 4,6,8,14\n",
@@ -195,9 +184,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# YOUR TURN: Define `psi`, similarly to `phi` above.\n",
@@ -223,9 +210,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"deg = 180.0/np.pi # for conversion between radians and degrees\n",
@@ -241,9 +226,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"# YOUR TURN: define the `alpha_R` state"
@@ -270,9 +253,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"network = paths.TPSNetwork(initial_states=C_7eq, final_states=alpha_R)\n",
@@ -293,9 +274,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"init_traj_storage = paths.Storage(\"initial_trajectory.nc\", 'r')\n",
@@ -305,9 +284,7 @@
305284
{
306285
"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"plt.plot(phi(init_traj), psi(init_traj))\n",
@@ -325,9 +302,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"initial_conditions = scheme.initial_conditions_from_trajectories(init_traj)"
@@ -345,9 +320,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
323+
"metadata": {},
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"outputs": [],
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"source": [
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"storage = paths.Storage(\"tps_simulation_results.nc\", \"w\", template=init_traj[0])\n",
@@ -359,9 +332,7 @@
359332
{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
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"metadata": {},
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"outputs": [],
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"source": [
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"sampler.run(40)"
@@ -370,9 +341,7 @@
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"collapsed": true
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},
344+
"metadata": {},
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"outputs": [],
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"source": [
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"storage.close()"
@@ -395,7 +364,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
398-
"version": "2.7.13"
367+
"version": "2.7.14"
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}
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},
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"nbformat": 4,

‎2_tps_analysis_tutorial.ipynb‎

Lines changed: 9 additions & 8 deletions
Original file line numberDiff line numberDiff line change
@@ -29,6 +29,7 @@
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"outputs": [],
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"source": [
3131
"%matplotlib inline\n",
32+
"from __future__ import print_function\n",
3233
"import openpathsampling as paths\n",
3334
"import numpy as np\n",
3435
"import os\n",
@@ -231,11 +232,11 @@
231232
},
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"outputs": [],
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"source": [
234-
"print \"File size: {0} for {1} steps, {2} snapshots\".format(\n",
235+
"print(\"File size: {0} for {1} steps, {2} snapshots\".format(\n",
235236
" flexible.file_size_str,\n",
236237
" len(flexible.steps),\n",
237238
" len(flexible.snapshots)\n",
238-
")"
239+
"))"
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]
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},
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{
@@ -311,7 +312,7 @@
311312
" )\n",
312313
")\n",
313314
"\n",
314-
"print \"Decorrelated trajectories:\", len(full_tree.generator.decorrelated_trajectories)"
315+
"print(\"Decorrelated trajectories:\", len(full_tree.generator.decorrelated_trajectories))"
315316
]
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},
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{
@@ -345,8 +346,8 @@
345346
"source": [
346347
"path_lengths = [len(step.active[0].trajectory) for step in flexible.steps]\n",
347348
"plt.hist(path_lengths, bins=40, alpha=0.5);\n",
348-
"print \"Maximum:\", max(path_lengths), \"(\"+str(max(path_lengths)*engine.snapshot_timestep)+\")\"\n",
349-
"print \"Average:\", \"{0:.2f}\".format(np.mean(path_lengths)), \"(\"+(np.mean(path_lengths)*engine.snapshot_timestep).format(\"%.3f\")+\")\""
349+
"print(\"Maximum:\", max(path_lengths), \"(\"+str(max(path_lengths)*engine.snapshot_timestep)+\")\")\n",
350+
"print(\"Average:\", \"{0:.2f}\".format(np.mean(path_lengths)), \"(\"+(np.mean(path_lengths)*engine.snapshot_timestep).format(\"%.3f\")+\")\")"
350351
]
351352
},
352353
{
@@ -395,7 +396,7 @@
395396
"cell_type": "markdown",
396397
"metadata": {},
397398
"source": [
398-
"The next step is will take the longest (perhaps 10-15 minutes):"
399+
"The next step is will take the longest (perhaps up to 20 minutes):"
399400
]
400401
},
401402
{
@@ -470,7 +471,7 @@
470471
"ax = plotter.plot(xlim=(-np.pi, 0), ylim=(-np.pi/2, np.pi), cmap=\"Blues\")\n",
471472
"plotter.plot_trajectory(trajA, '-r', lw=1)\n",
472473
"plotter.plot_trajectory(trajB, '-k', lw=1)\n",
473-
"#plt.savefig(\"AD_tps_pathdensity.pdf\")"
474+
"#plt.savefig(\"AD_tps_pathdensity.pdf\") # uncomment this line to save as PDF"
474475
]
475476
},
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{
@@ -527,7 +528,7 @@
527528
"name": "python",
528529
"nbconvert_exporter": "python",
529530
"pygments_lexer": "ipython2",
530-
"version": "2.7.13"
531+
"version": "2.7.14"
531532
}
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},
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"nbformat": 4,

‎3_committor_analysis_tutorial.ipynb‎

Lines changed: 9 additions & 5 deletions
Original file line numberDiff line numberDiff line change
@@ -71,11 +71,11 @@
7171
},
7272
"outputs": [],
7373
"source": [
74-
"print \"File size: {0} for {1} steps, {2} snapshots\".format(\n",
74+
"print(\"File size: {0} for {1} steps, {2} snapshots\".format(\n",
7575
" simulation_storage.file_size_str,\n",
7676
" len(simulation_storage.steps),\n",
7777
" len(simulation_storage.snapshots)\n",
78-
")"
78+
"))"
7979
]
8080
},
8181
{
@@ -130,6 +130,7 @@
130130
},
131131
"outputs": [],
132132
"source": [
133+
"%time\n",
133134
"phi_hash = lambda x : float(phi(x))\n",
134135
"analyzer.to_pandas(label_function=phi_hash)"
135136
]
@@ -151,7 +152,7 @@
151152
"source": [
152153
"hist1D, phi_bins = analyzer.committor_histogram(phi_hash, alpha_R, bins=10)\n",
153154
"bin_widths = [phi_bins[i+1]-phi_bins[i] for i in range(len(phi_bins)-1)]\n",
154-
"plt.bar(left=phi_bins[:-1], height=hist1D, width=bin_widths)\n",
155+
"plt.bar(x=phi_bins[:-1], height=hist1D, width=bin_widths)\n",
155156
"plt.xlabel(\"$\\phi$\")\n",
156157
"plt.ylabel(\"$p_B$\");"
157158
]
@@ -204,6 +205,7 @@
204205
},
205206
"outputs": [],
206207
"source": [
208+
"%time\n",
207209
"ramachandran_hash = lambda x : (float(phi(x)), float(psi(x)))\n",
208210
"hist2D, bins_phi, bins_psi = analyzer.committor_histogram(ramachandran_hash, alpha_R, bins=20)"
209211
]
@@ -282,7 +284,9 @@
282284
"cell_type": "markdown",
283285
"metadata": {},
284286
"source": [
285-
"Try a few different values of `psi_star_min` and `psi_star_max`. Do you ever get a distribution that is peaked around $p_B = 0.5$?"
287+
"Try a few different values of `psi_star_min` and `psi_star_max`. \n",
288+
"\n",
289+
"* Do you ever get a distribution that is peaked around $p_B = 0.5$?"
286290
]
287291
},
288292
{
@@ -352,7 +356,7 @@
352356
"name": "python",
353357
"nbconvert_exporter": "python",
354358
"pygments_lexer": "ipython2",
355-
"version": "2.7.13"
359+
"version": "2.7.14"
356360
}
357361
},
358362
"nbformat": 4,

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