diff --git a/tutorials/3-flowerMD-coarse-graining.ipynb b/tutorials/3-flowerMD-coarse-graining.ipynb
index 354f84f7..476a31a6 100644
--- a/tutorials/3-flowerMD-coarse-graining.ipynb
+++ b/tutorials/3-flowerMD-coarse-graining.ipynb
@@ -49,9 +49,9 @@
"name": "stderr",
"output_type": "stream",
"text": [
- "/home/chris/miniforge3/envs/flowermd-dev/lib/python3.11/site-packages/mdtraj/formats/__init__.py:6: DeprecationWarning: 'xdrlib' is deprecated and slated for removal in Python 3.13\n",
+ "/home/chris/mambaforge/envs/flowermd-dev/lib/python3.11/site-packages/mdtraj/formats/__init__.py:6: DeprecationWarning: 'xdrlib' is deprecated and slated for removal in Python 3.13\n",
" from .xtc import XTCTrajectoryFile\n",
- "/home/chris/miniforge3/envs/flowermd-dev/lib/python3.11/site-packages/mbuild/recipes/__init__.py:13: DeprecationWarning: SelectableGroups dict interface is deprecated. Use select.\n",
+ "/home/chris/mambaforge/envs/flowermd-dev/lib/python3.11/site-packages/mbuild/recipes/__init__.py:13: DeprecationWarning: SelectableGroups dict interface is deprecated. Use select.\n",
" entry_points = metadata.entry_points()[\"mbuild.plugins\"]\n"
]
}
@@ -84,7 +84,7 @@
"metadata": {},
"outputs": [],
"source": [
- "pps_mol = PPS(num_mols=300, lengths=6)"
+ "pps_mol = PPS(num_mols=150, lengths=12)"
]
},
{
@@ -103,11 +103,10 @@
"outputs": [
{
"data": {
- "application/3dmoljs_load.v0": "
\n
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n jupyter labextension install jupyterlab_3dmol
\n
\n",
+ "application/3dmoljs_load.v0": "\n
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n
\n",
"text/html": [
- "\n",
- "
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n",
- " jupyter labextension install jupyterlab_3dmol
\n",
+ "
\n",
+ "
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n",
"
\n",
""
]
@@ -160,7 +159,7 @@
{
"data": {
"text/plain": [
- "
"
+ ""
]
},
"execution_count": 4,
@@ -216,11 +215,10 @@
"outputs": [
{
"data": {
- "application/3dmoljs_load.v0": "\n
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n jupyter labextension install jupyterlab_3dmol
\n
\n",
+ "application/3dmoljs_load.v0": "\n
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n
\n",
"text/html": [
- "\n",
- "
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n",
- " jupyter labextension install jupyterlab_3dmol
\n",
+ "
\n",
+ "
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n",
"
\n",
""
]
@@ -273,7 +271,7 @@
{
"data": {
"text/plain": [
- "
"
+ ""
]
},
"execution_count": 6,
@@ -301,11 +299,10 @@
"outputs": [
{
"data": {
- "application/3dmoljs_load.v0": "\n
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n jupyter labextension install jupyterlab_3dmol
\n
\n",
+ "application/3dmoljs_load.v0": "\n
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n
\n",
"text/html": [
- "\n",
- "
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n",
- " jupyter labextension install jupyterlab_3dmol
\n",
+ "
\n",
+ "
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n",
"
\n",
""
]
@@ -360,7 +357,7 @@
{
"data": {
"text/plain": [
- "
"
+ ""
]
},
"execution_count": 7,
@@ -409,16 +406,38 @@
"ff = BeadSpring(\n",
" r_cut=2.5,\n",
" beads={\n",
- " \"A\": dict(epsilon=1.0, sigma=1.0),\n",
+ " \"A\": dict(epsilon=1, sigma=0.2),\n",
" },\n",
" bonds={\n",
- " \"A-A\": dict(r0=1.1, k=300),\n",
+ " \"A-A\": dict(r0=0.64, k=500),\n",
" },\n",
- " angles={\"A-A-A\": dict(t0=2.0, k=200)},\n",
- " dihedrals={\"A-A-A-A\": dict(phi0=0.0, k=100, d=-1, n=1)},\n",
+ " angles={\"A-A-A\": dict(t0=2.8, k=50)},\n",
")"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "80c9aea7-10ed-433e-880d-69c6b8e4723e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[,\n",
+ " ,\n",
+ " ]"
+ ]
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "ff.hoomd_forces"
+ ]
+ },
{
"cell_type": "markdown",
"id": "efa1192f-e43f-4011-861e-281b89665072",
@@ -437,7 +456,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"id": "2446bbd4-1c3f-41b6-9b78-1b1252d76699",
"metadata": {},
"outputs": [],
@@ -447,17 +466,16 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"id": "ad2374d7-443b-4e3f-b184-d740fdfbb172",
"metadata": {},
"outputs": [
{
"data": {
- "application/3dmoljs_load.v0": "\n
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n jupyter labextension install jupyterlab_3dmol
\n
\n",
+ "application/3dmoljs_load.v0": "\n
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n
\n",
"text/html": [
- "\n",
- "
You appear to be running in JupyterLab (or JavaScript failed to load for some other reason). You need to install the 3dmol extension:
\n",
- " jupyter labextension install jupyterlab_3dmol
\n",
+ "
\n",
+ "
3Dmol.js failed to load for some reason. Please check your browser console for error messages.
\n",
"
\n",
""
]
@@ -510,10 +528,10 @@
{
"data": {
"text/plain": [
- "
"
+ ""
]
},
- "execution_count": 10,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -535,12 +553,12 @@
"id": "65066489-f1d3-4008-97f9-560f8e75862c",
"metadata": {},
"source": [
- "similar to initializing an atomisitc simulation, we pass in the `hoomd_snapshot` generated by the system along with the force objects generated by the `BeadSpring` class to start a simulation."
+ "Similar to initializing an atomisitc simulation, we pass in the `hoomd_snapshot` generated by the system along with the force objects generated by the `BeadSpring` class to start a simulation."
]
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 12,
"id": "d903bc9b-55d5-41a1-aea7-a745be2b3025",
"metadata": {},
"outputs": [
@@ -553,12 +571,12 @@
}
],
"source": [
- "cg_sim = Simulation.from_system(system=cg_system, forcefield=ff.hoomd_forces)"
+ "cg_sim = Simulation(initial_state=cg_system.hoomd_snapshot, forcefield=ff.hoomd_forces, gsd_write_freq=int(2e5/10))"
]
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 13,
"id": "48ad9618-ee2e-4bff-a170-27491dd16922",
"metadata": {},
"outputs": [
@@ -568,7 +586,7 @@
"['A']"
]
},
- "execution_count": 12,
+ "execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
@@ -579,45 +597,56 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 14,
"id": "d739db63-10ab-4b92-9241-f2da68485988",
"metadata": {},
- "outputs": [],
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 10500 of 200000; TPS: 5018.28; ETA: 0.6 minutes\n",
+ "Step 21000 of 200000; TPS: 5141.77; ETA: 0.6 minutes\n",
+ "Step 31500 of 200000; TPS: 5151.59; ETA: 0.5 minutes\n",
+ "Step 42000 of 200000; TPS: 5129.96; ETA: 0.5 minutes\n",
+ "Step 52500 of 200000; TPS: 5114.8; ETA: 0.5 minutes\n",
+ "Step 63000 of 200000; TPS: 5107.63; ETA: 0.4 minutes\n",
+ "Step 73500 of 200000; TPS: 5102.79; ETA: 0.4 minutes\n",
+ "Step 84000 of 200000; TPS: 5094.64; ETA: 0.4 minutes\n",
+ "Step 94500 of 200000; TPS: 5089.08; ETA: 0.3 minutes\n",
+ "Step 105000 of 200000; TPS: 5082.07; ETA: 0.3 minutes\n",
+ "Step 115500 of 200000; TPS: 5078.93; ETA: 0.3 minutes\n",
+ "Step 126000 of 200000; TPS: 5072.38; ETA: 0.2 minutes\n",
+ "Step 136500 of 200000; TPS: 5068.13; ETA: 0.2 minutes\n",
+ "Step 147000 of 200000; TPS: 5062.82; ETA: 0.2 minutes\n",
+ "Step 157500 of 200000; TPS: 5057.28; ETA: 0.1 minutes\n",
+ "Step 168000 of 200000; TPS: 5054.44; ETA: 0.1 minutes\n",
+ "Step 178500 of 200000; TPS: 5051.86; ETA: 0.1 minutes\n",
+ "Step 189000 of 200000; TPS: 5050.5; ETA: 0.0 minutes\n",
+ "Step 199500 of 200000; TPS: 5048.61; ETA: 0.0 minutes\n"
+ ]
+ }
+ ],
"source": [
- "cg_sim.run_NVT(n_steps=1e3, kT=1.0, tau_kt=1.0)"
+ "cg_sim.run_NVT(n_steps=2e5, kT=3.0, tau_kt=1.0)"
]
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"id": "4d51cf2d-4643-4e59-b92c-da891a23bf0a",
"metadata": {},
"outputs": [],
"source": [
- "import hoomd\n",
- "for writer in cg_sim.operations.writers:\n",
- " if isinstance(writer, hoomd.write.GSD):\n",
- " writer.flush()"
+ "cg_sim.flush_writers()"
]
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "8ace1a8d-5391-41e7-9d52-a751c89fd0db",
"metadata": {},
- "outputs": [
- {
- "data": {
- "image/png": "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",
- "text/plain": [
- ""
- ]
- },
- "execution_count": 15,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
+ "outputs": [],
"source": [
"from cmeutils.visualize import FresnelGSD\n",
"\n",
@@ -631,6 +660,26 @@
"id": "fda6aa17-ed54-4ec6-9464-0fbf3f405644",
"metadata": {},
"outputs": [],
+ "source": [
+ "sim_visualizer.height = 20"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "3d0fc580-1a15-4d15-aa08-be51faba4a14",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "sim_visualizer.view()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "493a5090-0d59-4e14-a1cb-2e95f27e6c96",
+ "metadata": {},
+ "outputs": [],
"source": []
}
],
@@ -650,7 +699,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.7"
+ "version": "3.11.0"
}
},
"nbformat": 4,