Prototype: Bandgap Workflow NB

other/materials_designer/specific_examples/run_bandgap_workflow.ipynb

@@ -0,0 +1,200 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": [
+    "# Bandgap Workflow Example\n",
+    " This notebook demonstrates how to build and run a bandgap workflow for a material.\n",
+    "\n",
+    "## Process Overview\n",
+    "### 1. Set up the environment and parameters.\n",
+    "### 1. Log in to get the API token\n",
+    "### 1. Load the target material.\n",
+    "### 1. Import workflow builder and related analyzers.\n",
+    "### 1. Analyze material to get parameters for the workflow configuration.\n",
+    "### 1. Create the workflow configuration.\n",
+    "### 1. Create a job with material and workflow configuration.\n",
+    "### 1. Submit the job to the server.\n",
+    "### 1. Monitor the job status and retrieve results."
+   ],
+   "id": "ed24b225263ae3c3"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 1. Set up the environment and parameters",
+   "id": "598da5f8c4f507ec"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 2. Log in to get the API token",
+   "id": "51105b005c535ca"
+  },
+  {
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2025-06-30T17:49:35.443494Z",
+     "start_time": "2025-06-30T17:49:35.381267Z"
+    }
+   },
+   "cell_type": "code",
+   "source": [
+    "from mat3ra.api import ApiClient\n",
+    "# Log in to get the API token\n",
+    "auth_config = await ApiClient().login()"
+   ],
+   "id": "23626cb27f6e7206",
+   "outputs": [
+    {
+     "ename": "ModuleNotFoundError",
+     "evalue": "No module named 'mat3ra.api'",
+     "output_type": "error",
+     "traceback": [
+      "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m",
+      "\u001B[0;31mModuleNotFoundError\u001B[0m                       Traceback (most recent call last)",
+      "Cell \u001B[0;32mIn[2], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mfrom\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mmat3ra\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mapi\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mimport\u001B[39;00m ApiClient\n\u001B[1;32m      2\u001B[0m \u001B[38;5;66;03m# Log in to get the API token\u001B[39;00m\n\u001B[1;32m      3\u001B[0m auth_config \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m ApiClient()\u001B[38;5;241m.\u001B[39mlogin()\n",
+      "\u001B[0;31mModuleNotFoundError\u001B[0m: No module named 'mat3ra.api'"
+     ]
+    }
+   ],
+   "execution_count": 2
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 3. Load the target material",
+   "id": "ba816c64f28f6a3d"
+  },
+  {
+   "metadata": {
+    "collapsed": true
+   },
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from utils.visualize import visualize_materials as visualize\n",
+    "from utils.jupyterlite import load_material_from_folder\n",
+    "\n",
+    "material = load_material_from_folder(\"/uploads\", \"MoS2_twisted_interface_60_degrees.json\")\n",
+    "visualize(material)"
+   ],
+   "id": "initial_id"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 4. Import workflow builder and related analyzers",
+   "id": "f8d7e25a7c9cc2e"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from mat3ra.wode.analyzers.electronic import KPointAnalyzer, CutoffAnalyzer, SmearingAnalyzer, BandsAnalyzer\n",
+    "\n",
+    "kpoint_analyzer = KPointAnalyzer(material=material)\n",
+    "cutoff_analyzer = CutoffAnalyzer(material=material)\n",
+    "smearing_analyzer = SmearingAnalyzer(material=material)\n",
+    "bands_analyzer = BandsAnalyzer(material=material)\n",
+    "\n",
+    "kpoints = kpoint_analyzer.get_kpoints()\n",
+    "cutoff = cutoff_analyzer.get_cutoff()\n",
+    "smearing = smearing_analyzer.get_smearing()\n",
+    "number_of_bands = bands_analyzer.get_number_of_bands()\n",
+    "\n"
+   ],
+   "id": "5ead702c417eff62"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 5. Get workflow and adjust its parameters",
+   "id": "9bdd00f870caaeeb"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from mat3ra.wode.workflow.vasp.band_structure import BandStructureWorkflow\n",
+    "from mat3ra.wode.pseudopotentials import PseudopotentialEnum\n",
+    "\n",
+    "workflow = BandStructureWorkflow()\n",
+    "workflow.set_kpoints(kpoints)\n",
+    "workflow.set_pseudopotential(PseudopotentialEnum.PAW_HSE) # elements will be set automatically based on the material"
+   ],
+   "id": "68d43f6c797f2fc4"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 6. Create the job configuration",
+   "id": "1f15e054ddb9a08c"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from mat3ra.wode.compute import ComputeConfiguration, QueueEnum\n",
+    "compute_config = ComputeConfiguration(\n",
+    "    queue = QueueEnum.OR8,\n",
+    "    nodes = 1,\n",
+    "    cores = 8,\n",
+    ")"
+   ],
+   "id": "60e880dc581dafe1"
+  },
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 7. Submit the job and monitor the status",
+   "id": "8d5740e099512107"
+  },
+  {
+   "metadata": {},
+   "cell_type": "code",
+   "outputs": [],
+   "execution_count": null,
+   "source": [
+    "from mat3ra.wode.job import create_job\n",
+    "job = create_job(workflow=workflow, material=material, compute = compute_config, auth_config=auth_config)\n",
+    "job.run()\n",
+    "job.wait_for_complete()\n",
+    "# job.check_status()\n",
+    "# job.get_current_output()\n",
+    "# AFTER Finished\n",
+    "job.get_results(PropertyEnum.BANDGAP)"
+   ],
+   "id": "53c8a2cd99e5c26d"
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}