add m3gnet diatomic task

mlip_arena/models/externals.py

@@ -2,6 +2,8 @@ import os
 import urllib
 from typing import Literal
 
+import matgl
+import requests
 import torch
 from alignn.ff.ff import AlignnAtomwiseCalculator, get_figshare_model_ff
 from ase import Atoms
@@ -9,6 +11,8 @@ from chgnet.model.dynamics import CHGNetCalculator
 from chgnet.model.model import CHGNet
 from fairchem.core import OCPCalculator
 from mace.calculators import MACECalculator
+from matgl.ext.ase import PESCalculator
+from sevenn.sevennet_calculator import SevenNetCalculator
 
 
 # Avoid circular import
@@ -74,6 +78,7 @@ class MACE_MP_Medium(MACECalculator):
             model_paths=model, device=device, default_dtype=default_dtype, **kwargs
         )
 
+
 class MACE_OFF_Medium(MACECalculator):
     def __init__(self, device=None, default_dtype="float32", **kwargs):
         checkpoint_url = "https://github.com/ACEsuit/mace-off/raw/main/mace_off23/MACE-OFF23_medium.model?raw=true"
@@ -133,6 +138,17 @@ class CHGNet(CHGNetCalculator):
         self.results.pop("crystal_fea", None)
 
 
+class M3GNet(PESCalculator):
+    def __init__(
+        self,
+        state_attr: torch.Tensor | None = None,
+        stress_weight: float = 1.0,
+        **kwargs,
+    ) -> None:
+        potential = matgl.load_model("M3GNet-MP-2021.2.8-PES")
+        super().__init__(potential, state_attr, stress_weight, **kwargs)
+
+
 class EquiformerV2(OCPCalculator):
     def __init__(
         self,
@@ -191,3 +207,19 @@ class ALIGNN(AlignnAtomwiseCalculator):
 
     def calculate(self, atoms, properties=None, system_changes=None):
         super().calculate(atoms, properties, system_changes)
+
+
+class SevenNet(SevenNetCalculator):
+    def __init__(self, device=None, **kwargs):
+        url = (
+            "https://github.com/MDIL-SNU/SevenNet/raw/main/pretrained_potentials"
+            "/SevenNet_0__11July2024/checkpoint_sevennet_0.pth"
+        )
+        ckpt_cache = "/tmp/sevennet_checkpoint.pth.tar"
+        response = requests.get(url, timeout=20)
+        with open(ckpt_cache, mode="wb") as file:
+            file.write(response.content)
+
+        device = device or get_freer_device()
+
+        super().__init__(ckpt_cache, device=device, **kwargs)

mlip_arena/models/registry.yaml

@@ -38,6 +38,21 @@ CHGNet:
   nvt: true
   npt: true
 
+M3GNet:
+  module: externals
+  class: M3GNet
+  family: m3gnet
+  username: cyrusyc
+  last-update: 2024-07-08T00:00:00
+  datetime: 2024-07-08T00:00:00
+  datasets:
+    - atomind/mptrj
+  gpu-tasks:
+    - homonuclear-diatomics
+  prediction: EFS
+  nvt: true
+  npt: true
+
 EquiformerV2(OC22):
   module: externals
   class: EquiformerV2
@@ -108,4 +123,25 @@ ALIGNN:
     - homonuclear-diatomics
   prediction: EFS
   nvt: true
+  npt: true
+
+SevenNet:
+  module: externals
+  class: SevenNet
+  family: sevennet
+  username: cyrusyc
+  last-update: 2024-03-25T14:30:00
+  datetime: 2024-03-25T14:30:00 # TODO: Fake datetime
+  datasets:
+    - atomind/mptrj # TODO: fake HF dataset repo
+  cpu-tasks:
+    - alexandria
+    - qmof
+  gpu-tasks:
+    - homonuclear-diatomics
+  github: https://github.com/ACEsuit/mace
+  doi: https://arxiv.org/abs/2401.00096
+  date: 2023-12-29
+  prediction: EFS
+  nvt: true
   npt: true

mlip_arena/tasks/diatomics/m3gnet/run.ipynb

@@ -1,295 +0,0 @@
-{
- "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
-}

requirements.txt

@@ -5,7 +5,7 @@ scipy
 ase==3.23.0
 torch==2.2.1
 pymatgen==2024.4.13
-bokeh==2.4.3
+bokeh
 statsmodels==0.14.2
 # py3Dmol==2.0.0.post2
 # stmol==0.0.9

serve/tasks/homonuclear-diatomics.py

@@ -23,7 +23,7 @@ The potential energy curves of homonuclear diatomics are the most fundamental in
 st.markdown("### Methods")
 container = st.container(border=True)
 valid_models = [model for model, metadata in REGISTRY.items() if Path(__file__).stem in metadata.get("gpu-tasks", [])]
-methods = container.multiselect("MLIPs", valid_models, ["MACE-MP(M)", "EquiformerV2(OC22)", "CHGNet", "eSCN(OC20)", "ALIGNN"])
+methods = container.multiselect("MLIPs", valid_models, ["EquiformerV2(OC22)", "eSCN(OC20)", "CHGNet", "M3GNet",  "MACE-MP(M)"])
 dft_methods = container.multiselect("DFT Methods", ["GPAW"], [])
 
 st.markdown("### Settings")
@@ -61,6 +61,9 @@ df.drop_duplicates(inplace=True, subset=["name", "method"])
 
 method_color_mapping = {method: color_sequence[i % len(color_sequence)] for i, method in enumerate(df["method"].unique())}
 
+# img_dir = Path('./images')
+# img_dir.mkdir(exist_ok=True)
+
 for i, symbol in enumerate(chemical_symbols[1:]):
 
     if i % ncols == 0:
@@ -162,7 +165,7 @@ for i, symbol in enumerate(chemical_symbols[1:]):
             yaxis=dict(
                 title=dict(text="Energy [eV]"),
                 side="left",
-                range=[elo, 2*(abs(elo))],
+                range=[elo, 1.5*(abs(elo))],
             )
         )
 
@@ -172,10 +175,11 @@ for i, symbol in enumerate(chemical_symbols[1:]):
             yaxis2=dict(
                 title=dict(text="Force [eV/Å]"),
                 side="right",
-                range=[flo, 1.5*abs(flo)],
+                range=[flo, 1.0*abs(flo)],
                 overlaying="y",
                 tickmode="sync",
             ),
         )
 
     cols[i % ncols].plotly_chart(fig, use_container_width=True)
+    # fig.write_image(format='svg', file=img_dir / f"{name}.svg")