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add alignn
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@chiang-yuan
chiang-yuan committed Jul 7, 2024
1 parent 5b01054 commit eadac93
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7 changes: 4 additions & 3 deletions .gitignore
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tests/
*.out
mlip_arena/tasks/*/*/*/

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]
*$py.class
tests/
*.out
mlip_arena/tasks/*/*/

# C extensions
*.so
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295 changes: 295 additions & 0 deletions mlip_arena/tasks/diatomics/m3gnet/run.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 6,
"id": "3200850a-b8fb-4f50-9815-16ae8da0f942",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdin",
"output_type": "stream",
"text": [
"Do you really want to delete everything in /global/homes/c/cyrusyc/.cache/matgl (y|n)? y\n"
]
},
{
"ename": "ValueError",
"evalue": "Bad serialized model or bad model name. It is possible that you have an older model cached. Please clear your cache by running `python -c \"import matgl; matgl.clear_cache()\"`",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:212\u001b[0m, in \u001b[0;36mload_model\u001b[0;34m(path, **kwargs)\u001b[0m\n\u001b[1;32m 211\u001b[0m cls_ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(mod, classname)\n\u001b[0;32m--> 212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcls_\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfpaths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:129\u001b[0m, in \u001b[0;36mIOMixIn.load\u001b[0;34m(cls, path, **kwargs)\u001b[0m\n\u001b[1;32m 128\u001b[0m d \u001b[38;5;241m=\u001b[39m {k: v \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m d\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m k\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m@\u001b[39m\u001b[38;5;124m\"\u001b[39m)}\n\u001b[0;32m--> 129\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43md\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 130\u001b[0m model\u001b[38;5;241m.\u001b[39mload_state_dict(state, strict\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m) \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n",
"\u001b[0;31mTypeError\u001b[0m: Potential.__init__() got an unexpected keyword argument 'calc_magmom'",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[6], line 18\u001b[0m\n\u001b[1;32m 15\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mpandas\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m \u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[1;32m 17\u001b[0m matgl\u001b[38;5;241m.\u001b[39mclear_cache()\n\u001b[0;32m---> 18\u001b[0m potential \u001b[38;5;241m=\u001b[39m \u001b[43mmatgl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_model\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mM3GNet-MP-2021.2.8-PES\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 19\u001b[0m calculator \u001b[38;5;241m=\u001b[39m PESCalculator(potential)\n",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:214\u001b[0m, in \u001b[0;36mload_model\u001b[0;34m(path, **kwargs)\u001b[0m\n\u001b[1;32m 212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cls_\u001b[38;5;241m.\u001b[39mload(fpaths, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 214\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 215\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBad serialized model or bad model name. It is possible that you have an older model cached. Please \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mclear your cache by running `python -c \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimport matgl; matgl.clear_cache()\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 217\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n",
"\u001b[0;31mValueError\u001b[0m: Bad serialized model or bad model name. It is possible that you have an older model cached. Please clear your cache by running `python -c \"import matgl; matgl.clear_cache()\"`"
]
}
],
"source": [
"import os\n",
"import numpy as np\n",
"\n",
"from ase import Atoms, Atom\n",
"from ase.io import read, write\n",
"from ase.data import chemical_symbols, covalent_radii, vdw_alvarez\n",
"from ase.parallel import paropen as open\n",
"\n",
"from pathlib import Path\n",
"from pymatgen.core import Element\n",
"import pandas as pd\n",
"\n",
"from tqdm.auto import tqdm\n",
"\n",
"import matgl\n",
"from matgl.ext.ase import PESCalculator\n",
"\n",
"matgl.clear_cache()\n",
"potential = matgl.load_model(\"M3GNet-MP-2021.2.8-PES\")\n",
"calculator = PESCalculator(potential)\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "90887faa-1601-4c4c-9c44-d16731471d7f",
"metadata": {
"scrolled": true,
"tags": []
},
"outputs": [
{
"ename": "ValueError",
"evalue": "Bad serialized model or bad model name. It is possible that you have an older model cached. Please clear your cache by running `python -c \"import matgl; matgl.clear_cache()\"`",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:212\u001b[0m, in \u001b[0;36mload_model\u001b[0;34m(path, **kwargs)\u001b[0m\n\u001b[1;32m 211\u001b[0m cls_ \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mgetattr\u001b[39m(mod, classname)\n\u001b[0;32m--> 212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mcls_\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfpaths\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:129\u001b[0m, in \u001b[0;36mIOMixIn.load\u001b[0;34m(cls, path, **kwargs)\u001b[0m\n\u001b[1;32m 128\u001b[0m d \u001b[38;5;241m=\u001b[39m {k: v \u001b[38;5;28;01mfor\u001b[39;00m k, v \u001b[38;5;129;01min\u001b[39;00m d\u001b[38;5;241m.\u001b[39mitems() \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m k\u001b[38;5;241m.\u001b[39mstartswith(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m@\u001b[39m\u001b[38;5;124m\"\u001b[39m)}\n\u001b[0;32m--> 129\u001b[0m model \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43md\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 130\u001b[0m model\u001b[38;5;241m.\u001b[39mload_state_dict(state, strict\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m) \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n",
"\u001b[0;31mTypeError\u001b[0m: Potential.__init__() got an unexpected keyword argument 'calc_magmom'",
"\nThe above exception was the direct cause of the following exception:\n",
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[0;32mIn[2], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m potential \u001b[38;5;241m=\u001b[39m \u001b[43mmatgl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mload_model\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mM3GNet-MP-2021.2.8-PES\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m calculator \u001b[38;5;241m=\u001b[39m PESCalculator(potential)\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m symbol \u001b[38;5;129;01min\u001b[39;00m tqdm(chemical_symbols):\n",
"File \u001b[0;32m/pscratch/sd/c/cyrusyc/.conda/mlip-arena/lib/python3.11/site-packages/matgl/utils/io.py:214\u001b[0m, in \u001b[0;36mload_model\u001b[0;34m(path, **kwargs)\u001b[0m\n\u001b[1;32m 212\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m cls_\u001b[38;5;241m.\u001b[39mload(fpaths, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m 213\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 214\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 215\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mBad serialized model or bad model name. It is possible that you have an older model cached. Please \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 216\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mclear your cache by running `python -c \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimport matgl; matgl.clear_cache()\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m`\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m 217\u001b[0m ) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01merr\u001b[39;00m\n",
"\u001b[0;31mValueError\u001b[0m: Bad serialized model or bad model name. It is possible that you have an older model cached. Please clear your cache by running `python -c \"import matgl; matgl.clear_cache()\"`"
]
}
],
"source": [
"\n",
"\n",
"for symbol in tqdm(chemical_symbols):\n",
" \n",
" s = set([symbol])\n",
" \n",
" if 'X' in s:\n",
" continue\n",
" \n",
" try:\n",
" atom = Atom(symbol)\n",
" rmin = covalent_radii[atom.number] * 0.95\n",
" rvdw = vdw_alvarez.vdw_radii[atom.number] if atom.number < len(vdw_alvarez.vdw_radii) else np.nan \n",
" rmax = 3.1 * rvdw if not np.isnan(rvdw) else 6\n",
" rstep = 0.01 #if rmin < 1 else 0.4\n",
"\n",
" a = 2 * rmax\n",
"\n",
" npts = int((rmax - rmin)/rstep)\n",
"\n",
" rs = np.linspace(rmin, rmax, npts)\n",
" e = np.zeros_like(rs)\n",
"\n",
" da = symbol + symbol\n",
"\n",
" out_dir = Path(str(da))\n",
"\n",
" os.makedirs(out_dir, exist_ok=True)\n",
"\n",
" skip = 0\n",
" \n",
" element = Element(symbol)\n",
" \n",
" try:\n",
" m = element.valence[1]\n",
" if element.valence == (0, 2):\n",
" m = 0\n",
" except:\n",
" m = 0\n",
" \n",
" \n",
" r = rs[0]\n",
" \n",
" positions = [\n",
" [a/2-r/2, a/2, a/2],\n",
" [a/2+r/2, a/2, a/2],\n",
" ]\n",
" \n",
" traj_fpath = out_dir / \"traj.extxyz\"\n",
"\n",
" if traj_fpath.exists():\n",
" traj = read(traj_fpath, index=\":\")\n",
" skip = len(traj)\n",
" atoms = traj[-1]\n",
" else:\n",
" # Create the unit cell with two atoms\n",
" atoms = Atoms(\n",
" da, \n",
" positions=positions,\n",
" # magmoms=magmoms,\n",
" cell=[a, a+0.001, a+0.002], \n",
" pbc=True\n",
" )\n",
" \n",
" print(atoms)\n",
"\n",
" calc = calculator\n",
"\n",
" atoms.calc = calc\n",
" \n",
" # cdft = CDFT(calc=calc, atoms=atoms, spinspin_regions= \n",
" # atoms.calc = cdft\n",
"\n",
" for i, r in enumerate(tqdm(np.flip(rs))):\n",
"\n",
" if i < skip:\n",
" continue\n",
"\n",
" positions = [\n",
" [a/2-r/2, a/2, a/2],\n",
" [a/2+r/2, a/2, a/2],\n",
" ]\n",
" \n",
" # atoms.set_initial_magnetic_moments(magmoms)\n",
" \n",
" atoms.set_positions(positions)\n",
"\n",
" e[i] = atoms.get_potential_energy()\n",
" \n",
" atoms.calc.results.update({\n",
" \"forces\": atoms.get_forces()\n",
" })\n",
"\n",
" write(traj_fpath, atoms, append=\"a\")\n",
" except Exception as e:\n",
" print(e)\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a0ac2c09-370b-4fdd-bf74-ea5c4ade0215",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
"model_id": "cc766db4ce844c40848791e14a71832c",
"version_major": 2,
"version_minor": 0
},
"text/plain": [
" 0%| | 0/119 [00:00<?, ?it/s]"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"\n",
"df = pd.DataFrame(columns=['name', 'method', 'R', 'E', 'F', 'S^2'])\n",
"\n",
"for symbol in tqdm(chemical_symbols):\n",
" \n",
" da = symbol + symbol\n",
" \n",
" out_dir = Path(da)\n",
" \n",
" traj_fpath = out_dir / \"traj.extxyz\"\n",
"\n",
" if traj_fpath.exists():\n",
" traj = read(traj_fpath, index=\":\")\n",
" else:\n",
" continue\n",
" \n",
" Rs, Es, Fs, S2s = [], [], [], []\n",
" for atoms in traj:\n",
" \n",
" vec = atoms.positions[1] - atoms.positions[0]\n",
" r = np.linalg.norm(vec)\n",
" e = atoms.get_potential_energy()\n",
" f = np.inner(vec/r, atoms.get_forces()[1])\n",
" # s2 = np.mean(np.power(atoms.get_magnetic_moments(), 2))\n",
" \n",
" Rs.append(r)\n",
" Es.append(e)\n",
" Fs.append(f)\n",
" # S2s.append(s2)\n",
" \n",
" data = {\n",
" 'name': da,\n",
" 'method': 'M3GNet',\n",
" 'R': Rs,\n",
" 'E': Es,\n",
" 'F': Fs,\n",
" 'S^2': S2s\n",
" }\n",
"\n",
" df = pd.concat([df, pd.DataFrame([data])], ignore_index=True)\n",
"\n",
"json_fpath = 'homonuclear-diatomics.json'\n",
"\n",
"df.to_json(json_fpath, orient='records') "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2207f50e-63a1-4199-b2e1-a11858af5108",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"df"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "mlip-arena",
"language": "python",
"name": "mlip-arena"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.8"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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