First notebook for comparing sampling methods

notebooks/1_explore-sampling-methods/run-all-methods.sh

@@ -1,15 +1,15 @@
 #! /bin/bash
 
 xyz=../data/exact/caffeine_pm7_None.xyz
-for step_size in 0.02 0.01 0.005; do
+for step_size in 0.04 0.02 0.01 0.005; do
     # Do the randomized methods
     for method in 0_random-directions-same-distance.ipynb 1_random-directions-variable-distance.ipynb; do
-        papermill -p starting_geometry $xyz -p step_size $s $method - > /dev/null
+        papermill -p starting_geometry $xyz -p step_size $step_size $method last.ipynb
     done
 
     # Test with different reductions for "along axes"
     notebook=2_displace-along-axes.ipynb
     for n in 1 2 4; do
-        papermill -p starting_geometry $xyz -p perturbs_per_evaluation $n $notebook - > /dev/null
+        papermill -p starting_geometry $xyz -p perturbs_per_evaluation $n -p step_size $step_size $notebook last.ipynb
     done
 done

notebooks/2_testing-fitting-strategies/1_fit-forcefield-using-mbtr.ipynb

@@ -11,7 +11,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "id": "ebbbc7f5-3007-420f-861a-9f65f84436be",
    "metadata": {
     "tags": []
@@ -29,6 +29,7 @@
     "from dscribe.descriptors import MBTR\n",
     "from ase.vibrations import VibrationsData\n",
     "from ase.db import connect\n",
+    "from random import sample\n",
     "from pathlib import Path\n",
     "from tqdm import tqdm\n",
     "import numpy as np\n",
@@ -47,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "id": "99bd4c92-9a7b-4e88-ac45-dbf30fbfc9e0",
    "metadata": {
     "tags": [
@@ -56,8 +57,9 @@
    },
    "outputs": [],
    "source": [
-    "db_path = '../1_explore-sampling-methods/data/along-axes/caffeine_pm7_None_d=5.00e-03-N=2.db'\n",
-    "overwrite = False"
+    "db_path: str = '../1_explore-sampling-methods/data/along-axes/caffeine_pm7_None_d=5.00e-03-N=2.db'\n",
+    "overwrite: bool = False\n",
+    "max_size: int = 10000"
    ]
   },
   {
@@ -70,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "id": "a8be3c37-bf1f-4ba4-ba8f-afff6d6bed7d",
    "metadata": {
     "tags": []
@@ -94,24 +96,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "75d22086-f020-40d7-8327-1154491b9821",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "ename": "ValueError",
-     "evalue": "Already done!",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[12], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (out_dir \u001b[38;5;241m/\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mout_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.json\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mexists() \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m overwrite:\n\u001b[0;32m----> 2\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mAlready done!\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
-      "\u001b[0;31mValueError\u001b[0m: Already done!"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "if (out_dir / f'{out_name}-full.json').exists() and not overwrite:\n",
     "    raise ValueError('Already done!')"
@@ -140,6 +130,28 @@
     "print(f'Loaded {len(data)} structures')"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "0c8aae57-1863-4bad-a56b-31f7b8a6062b",
+   "metadata": {},
+   "source": [
+    "Downsample if desired"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e2dfe036-a173-41ff-817b-2e92349b9704",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "if max_size is not None and len(data) > max_size:\n",
+    "    data = sample(data, max_size)\n",
+    "    print(f'Downselected to {len(data)}')"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "cb1a8e03-b045-49a4-95fd-61636a48fbad",

notebooks/2_testing-fitting-strategies/run-all-dbs.sh

@@ -1,8 +1,8 @@
 #! /bin/bash
 
 notebook=$1
-dbs=$(find ../1_explore-sampling-methods/data/ -name "caffine_pm7_None*.db")
+dbs=$(find ../1_explore-sampling-methods/data/ -name "caffeine_pm7_None*.db")
 for db in $dbs; do
   echo $db
-  papermill -p db_path $db $notebook -
+  papermill -p db_path "$db" -p max_size 5000 $notebook last.html
 done