update: use made

Author: VsevolodX

other/materials_designer/import_material_from_jarvis_db_entry.ipynb

@@ -35,17 +35,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
    "id": "9c1f4e9e",
    "metadata": {},
-   "outputs": [],
    "source": [
     "# Note: JVASP-670 is an entry for MoTe2 and JVASP-6838 is an entry for GaTe\n",
     "JARVIS_IDS = [\n",
     "    \"JVASP-670\",\n",
     "    \"JVASP-6838\",\n",
     "]"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -57,20 +57,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "ef2b38a5-de7e-419e-b605-110e9e0095f5",
    "metadata": {
     "trusted": true
    },
-   "outputs": [],
    "source": [
     "import sys\n",
+    "\n",
     "if sys.platform == \"emscripten\":\n",
     "    import micropip\n",
+    "\n",
     "    await micropip.install('mat3ra-api-examples', deps=False)\n",
-    "from utils.jupyterlite import install_packages\n",
-    "await install_packages(\"import_material_from_jarvis_db_entry.ipynb\",\"../../config.yml\")"
-   ]
+    "    from utils.jupyterlite import install_packages\n",
+    "\n",
+    "    await install_packages(\"import_material_from_jarvis_db_entry.ipynb\")"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -84,13 +87,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "b1ee775d1476f884",
    "metadata": {
     "collapsed": false,
     "trusted": true
    },
-   "outputs": [],
    "source": [
     "import pandas as pd\n",
     "from jarvis.db.figshare import data\n",
@@ -99,8 +100,10 @@
     "dft_3d = data(\"dft_3d\")\n",
     "dataframe_2d = pd.DataFrame(dft_2d)\n",
     "dataframe_3d = pd.DataFrame(dft_3d)\n",
-    "dataframe= pd.concat([dataframe_2d, dataframe_3d])"
-   ]
+    "dataframe = pd.concat([dataframe_2d, dataframe_3d])"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -112,13 +115,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "0e34472a",
    "metadata": {},
-   "outputs": [],
    "source": [
     "dataframe"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -130,18 +133,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "a771a36a",
    "metadata": {},
-   "outputs": [],
    "source": [
     "import json\n",
     "from express import ExPrESS\n",
     "\n",
     "dataframe_entries_for_jarvis_ids = dataframe[(dataframe[\"jid\"].isin(JARVIS_IDS))]\n",
     "dataframe_entries_as_json = dataframe_entries_for_jarvis_ids.to_json(orient=\"records\")\n",
     "jarvis_db_entries = json.loads(dataframe_entries_as_json)"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -153,13 +156,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "c41fb68c6d25fe48",
    "metadata": {
     "collapsed": false,
     "trusted": true
    },
-   "outputs": [],
    "source": [
     "def convert_jarvis_entry_to_esse(jarvis_db_entry):\n",
     "    jarvis_db_entry_json = json.dumps(jarvis_db_entry)\n",
@@ -173,9 +174,12 @@
     "    poscar = handler.parser.jarvis_db_entry_json_to_poscar(jarvis_db_entry_json)\n",
     "    return (esse, poscar)\n",
     "\n",
+    "\n",
     "esse_entries = list(map(lambda e: convert_jarvis_entry_to_esse(e)[0], jarvis_db_entries))\n",
     "poscars = list(map(lambda e: convert_jarvis_entry_to_esse(e)[1], jarvis_db_entries))"
-   ]
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -187,45 +191,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "860b5c1b",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "from src.utils import poscar_to_ase\n",
-    "from ase.visualize import view\n",
-    "from ase.io import write\n",
-    "from ase.build import make_supercell\n",
-    "from IPython.display import Image\n",
+    "from utils.visualize import visualize_materials\n",
+    "from mat3ra.made.tools.convert import from_poscar\n",
+    "from mat3ra.made.material import Material\n",
     "\n",
     "# Uncomment to see the JSON\n",
     "# print(json.dumps(data, indent=4))\n",
     "\n",
+    "materials = [Material(from_poscar(poscar)) for poscar in poscars]\n",
     "\n",
-    "materials = list(map(lambda p: poscar_to_ase(p), poscars))\n",
-    "\n",
-    "def visualize_material(material, index: int, number_of_repetitions: int = 3):\n",
-    "    \"\"\"\n",
-    "    Visualize the material using ASE's visualization tool\n",
-    "    Repeat the unit cell to make it easier to see.\n",
-    "\n",
-    "    Args:\n",
-    "        material: The material to visualize (Ase.Atoms object)\n",
-    "        index: The index of the material\n",
-    "        number_of_repetitions: The number of unit cell repetitions to visualize\n",
-    "    \"\"\"\n",
-    "    # Set the number of unit cell repetition for the structure to make it easier to see\n",
-    "    n = number_of_repetitions\n",
-    "    material_repeat = make_supercell(material, [[n,0,0],[0,n,0],[0,0,n]])\n",
-    "    filename = f\"material-{index}.png\"\n",
-    "    write(filename, material_repeat)\n",
-    "    img = Image(filename=filename)\n",
-    "    print(filename, \"-\", material.symbols)\n",
-    "    display(img)\n",
-    "\n",
-    "for idx, material in enumerate(materials):\n",
-    "    visualize_material(material, idx)"
-   ]
+    "visualize_materials(materials)"
+   ],
+   "outputs": [],
+   "execution_count": null
   },
   {
    "cell_type": "markdown",
@@ -237,16 +218,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
    "id": "00b187ab",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "from utils.jupyterlite import set_data\n",
+    "from utils.jupyterlite import set_materials\n",
     "\n",
-    "output_materials = esse_entries\n",
-    "set_data(\"materials\", output_materials)"
-   ]
+    "set_materials(materials)"
+   ],
+   "outputs": [],
+   "execution_count": null
   }
  ],
  "metadata": {