{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "05a81f03-503e-414a-877b-4f8837d37eb5",
   "metadata": {},
   "source": "## Initial imports"
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3fe257a7-2374-49d6-94a2-d648a30c3ad4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:53.725480Z",
     "iopub.status.busy": "2024-05-31T13:56:53.725182Z",
     "iopub.status.idle": "2024-05-31T13:56:55.402544Z",
     "shell.execute_reply": "2024-05-31T13:56:55.401423Z"
    }
   },
   "outputs": [],
   "source": [
    "import scm.plams as plams\n",
    "from scm.params import ResultsImporter, ParAMSJob\n",
    "from scm.plams import Settings, AMSJob, log, Molecule\n",
    "from scm.simple_active_learning import SimpleActiveLearningJob\n",
    "from pathlib import Path\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# common_ru_h.py must exist in the current working directory\n",
    "from common_ru_h import (\n",
    "    rotation,\n",
    "    dft_settings,\n",
    "    QEKPointsConfig,\n",
    "    slice_slab,\n",
    "    check_installation,\n",
    ")\n",
    "\n",
    "# register dependencies for AMSjobs, to support submitting this notebook directly to a cluster in AMS2025+\n",
    "# dependency: {}  common_ru_h.py\n",
    "# dependency: {}  initial_training_results"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c19c0f9-001b-4ced-96ce-19a0878f9806",
   "metadata": {},
   "source": "## Initialize PLAMS working directory "
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "81d242b7-b776-491d-a463-cca1b62a70c0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:55.407179Z",
     "iopub.status.busy": "2024-05-31T13:56:55.407046Z",
     "iopub.status.idle": "2024-05-31T13:56:57.512149Z",
     "shell.execute_reply": "2024-05-31T13:56:57.510816Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "Current AMS version: 2024.102\n05-31 15:56:55 m3gnet is installed: M3GNet ML Backend v[0.2.4] - build:0 [06668e0a45ce742d8f66ff23484b8a1e]\n05-31 15:56:56 qe is installed: Quantum ESPRESSO (AMSPIPE) v[7.1] - build:115 [777d72eb480fe4d632a003cc62e9c1cb]\nPLAMS working folder: /home/hellstrom/SALRuH/fix2024/plams_workdir.005\n"
    }
   ],
   "source": [
    "load_model_dir = \"initial_training_results\"\n",
    "check_installation(load_model_dir)\n",
    "plams.init()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31ab389e-ad8d-4753-b0a2-ea8d434ad794",
   "metadata": {},
   "source": "## Load the optimized bulk Ru structure from the job collection \n\nThe lattice was optimized in the previous notebook, and the structure was stored in the job collection.\n\nLet's retrieve it from the job collection and use it to construct Ru surface slabs."
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "380b978e-ee27-493e-ad72-61e59c719c6f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:57.516675Z",
     "iopub.status.busy": "2024-05-31T13:56:57.516360Z",
     "iopub.status.idle": "2024-05-31T13:56:58.509109Z",
     "shell.execute_reply": "2024-05-31T13:56:58.508277Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": "<Figure size 144x144 with 1 Axes>"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "job_collection = ParAMSJob.load_external(load_model_dir).results.get_job_collection()\n",
    "optimized_bulk = job_collection[\"hcp_lattopt_Ru_dft\"].molecule\n",
    "slab = slice_slab(\n",
    "    optimized_bulk, miller=(1, 0, 0), thickness=7.0, cell_z=15, ref_atom=0\n",
    ")\n",
    "min_z = min(at.coords[2] for at in slab)\n",
    "slab.translate((0, 0, -min_z + 2.0))\n",
    "slab = slab.supercell(3, 2, 1)\n",
    "plams.plot_molecule(slab, rotation=rotation)\n",
    "plt.title(\"Ru(10-10)\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d95bed1f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.513115Z",
     "iopub.status.busy": "2024-05-31T13:56:58.512865Z",
     "iopub.status.idle": "2024-05-31T13:56:58.517541Z",
     "shell.execute_reply": "2024-05-31T13:56:58.516789Z"
    }
   },
   "outputs": [],
   "source": [
    "min_z = min(at.coords[2] for at in slab)\n",
    "for i, at in enumerate(slab, 1):\n",
    "    at.properties = Settings()  # remove details about supercell generation\n",
    "    if at.coords[2] == min_z:\n",
    "        at.properties.region = \"very_cold\"\n",
    "    else:\n",
    "        at.properties.region = \"thermostatted\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a9c41a6a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.520962Z",
     "iopub.status.busy": "2024-05-31T13:56:58.520838Z",
     "iopub.status.idle": "2024-05-31T13:56:58.524450Z",
     "shell.execute_reply": "2024-05-31T13:56:58.523589Z"
    }
   },
   "outputs": [],
   "source": [
    "h_atom = plams.Molecule()\n",
    "h_atom.add_atom(plams.Atom(symbol=\"H\", coords=(0.0, 0.0, 0.0)))\n",
    "h_atom.atoms[0].properties.region = \"hydrogen\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "d7ebe364",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.529558Z",
     "iopub.status.busy": "2024-05-31T13:56:58.529136Z",
     "iopub.status.idle": "2024-05-31T13:56:58.534351Z",
     "shell.execute_reply": "2024-05-31T13:56:58.533341Z"
    }
   },
   "outputs": [],
   "source": [
    "main_system_name = \"\"  # must be empty string\n",
    "projectile_name = \"projectile\"\n",
    "molecules_dict = {main_system_name: slab, projectile_name: h_atom}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e530e5d7",
   "metadata": {},
   "source": "## Set up the MD settings\n\nBefore starting the active learning, let's set up a molecule gun simulation using the initially trained potential.\n\nThis is just to see that that simulation settings are somewhat reasonable."
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "72e5fa7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.538881Z",
     "iopub.status.busy": "2024-05-31T13:56:58.538602Z",
     "iopub.status.idle": "2024-05-31T13:56:58.550147Z",
     "shell.execute_reply": "2024-05-31T13:56:58.549076Z"
    }
   },
   "outputs": [],
   "source": [
    "s = Settings()\n",
    "s.input.ams.Task = \"MolecularDynamics\"\n",
    "md_s = s.input.ams.MolecularDynamics\n",
    "md_s.NSteps = 5000  # will be increased later for active learning\n",
    "md_s.Trajectory.SamplingFreq = 10  # for testing purposes to check the trajectory\n",
    "md_s.InitialVelocities.Temperature = 100\n",
    "md_s.Thermostat = [\n",
    "    Settings(\n",
    "        Region=\"thermostatted\",\n",
    "        Type=\"NHC\",\n",
    "        Temperature=[300],\n",
    "        Tau=100.0,\n",
    "    ),\n",
    "    Settings(\n",
    "        Region=\"very_cold\",\n",
    "        Type=\"NHC\",\n",
    "        Temperature=[2.0],\n",
    "        Tau=10.0,\n",
    "    ),\n",
    "]\n",
    "md_s.RemoveMolecules.Frequency = 1\n",
    "md_s.RemoveMolecules.Formula = \"*\"\n",
    "md_s.RemoveMolecules.SinkBox.FractionalCoordsBox = \"0 1 0 1 0.90 0.99\"\n",
    "md_s.AddMolecules.System = projectile_name\n",
    "md_s.AddMolecules.Frequency = 1000\n",
    "md_s.AddMolecules.StartStep = 100\n",
    "# insert H atoms 4.5 angstrom above the surface\n",
    "max_z = max(at.coords[2] for at in slab)\n",
    "projectile_insertion_z = (4.5 + max_z) / slab.lattice[2][2]\n",
    "md_s.AddMolecules.FractionalCoordsBox = (\n",
    "    f\"0 1 0 1 {projectile_insertion_z} {projectile_insertion_z + 0.01}\"\n",
    ")\n",
    "md_s.AddMolecules.VelocityDirection = (\n",
    "    \"0 0 -1\"  # shoot down towards slab (decrease z coordinate)\n",
    ")\n",
    "md_s.AddMolecules.DeviationAngle = 0.0\n",
    "md_s.AddMolecules.Velocity = 0.03"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "33a2e72c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.554272Z",
     "iopub.status.busy": "2024-05-31T13:56:58.553977Z",
     "iopub.status.idle": "2024-05-31T13:56:58.616389Z",
     "shell.execute_reply": "2024-05-31T13:56:58.615454Z"
    }
   },
   "outputs": [],
   "source": [
    "test_md_job = AMSJob(\n",
    "    settings=s\n",
    "    + ParAMSJob.load_external(load_model_dir).results.get_production_engine_settings(),\n",
    "    molecule=molecules_dict,\n",
    "    name=\"test_molecule_gun\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "921e9a23",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T13:56:58.623028Z",
     "iopub.status.busy": "2024-05-31T13:56:58.622907Z",
     "iopub.status.idle": "2024-05-31T14:01:58.029500Z",
     "shell.execute_reply": "2024-05-31T14:01:58.028374Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "[31.05|15:56:58] JOB test_molecule_gun STARTED\n[31.05|15:56:58] JOB test_molecule_gun RUNNING\n[31.05|16:01:57] JOB test_molecule_gun FINISHED\n[31.05|16:01:58] JOB test_molecule_gun SUCCESSFUL\n"
    }
   ],
   "source": [
    "test_md_job.run();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8db2457b",
   "metadata": {},
   "source": "Open the trajectory in AMSmovie to check if it is reasonable. We'd expect some combination of the following events:\n\n* H atoms adsorbing on the Ru surface\n* H atoms diffusing into the subsurface\n* H atoms desorbing from the Ru surface\n* H atoms combining into H2 molecules and desorbing from the surface\n\nThe simulation seems reasonable, so let's couple it to the active learning with on-the-fly retraining.\n\n## Active Learning for Ru/H molecule gun simulation"
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "78a2fb9f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T14:01:58.032913Z",
     "iopub.status.busy": "2024-05-31T14:01:58.032776Z",
     "iopub.status.idle": "2024-05-31T14:01:58.218638Z",
     "shell.execute_reply": "2024-05-31T14:01:58.218077Z"
    }
   },
   "outputs": [],
   "source": [
    "plams.config.jobmanager.hashing = None\n",
    "al_s = plams.Settings()\n",
    "al_s.input.ams.ActiveLearning.Steps.Type = \"Linear\"\n",
    "al_s.input.ams.ActiveLearning.Steps.Linear.Start = 1000\n",
    "al_s.input.ams.ActiveLearning.Steps.Linear.StepSize = 5000\n",
    "# H atoms at high temperature, so let's decrease the minimum allowed distance a bit\n",
    "al_s.input.ams.ActiveLearning.ReasonableSimulationCriteria.Distance.MinValue = 0.50\n",
    "al_s.input.ams.ActiveLearning.MaxReferenceCalculationsPerAttempt = 1\n",
    "al_s.input.ams.ActiveLearning.SuccessCriteria.Forces.MaxDeviationForZeroForce = 0.65\n",
    "\n",
    "ml_s = plams.Settings()\n",
    "ml_s.input.ams.MachineLearning.Backend = \"M3GNet\"\n",
    "ml_s.input.ams.MachineLearning.LoadModel = Path(load_model_dir).resolve()\n",
    "ml_s.input.ams.MachineLearning.MaxEpochs = 50\n",
    "ml_s.input.ams.MachineLearning.RunAMSAtEnd = \"No\"\n",
    "\n",
    "ref_s = dft_settings(QEKPointsConfig(3, 3, 1), conv_thr=1e-4)\n",
    "\n",
    "new_md_s = s.copy()\n",
    "new_md_s.input.ams.MolecularDynamics.NSteps = 100000\n",
    "new_md_s.input.ams.MolecularDynamics.Trajectory.SamplingFreq = 100\n",
    "\n",
    "al_job = SimpleActiveLearningJob(\n",
    "    name=\"sal\", settings=al_s + ml_s + ref_s + new_md_s, molecule=molecules_dict\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "33c24499",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-05-31T14:01:58.222070Z",
     "iopub.status.busy": "2024-05-31T14:01:58.221831Z",
     "iopub.status.idle": "2024-06-01T09:31:05.464666Z",
     "shell.execute_reply": "2024-06-01T09:31:05.464158Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": "[31.05|16:01:58] JOB sal STARTED\n[31.05|16:01:58] JOB sal RUNNING\n[01.06|11:31:05] JOB sal FINISHED\n[01.06|11:31:05] JOB sal SUCCESSFUL\n"
    },
    {
     "data": {
      "text/plain": "<scm.simple_active_learning.plams.simple_active_learning_job.SimpleActiveLearningResults at 0x1458f8214a00>"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "al_job.run()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76f7879f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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