{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "18e60f6c-9dac-44d4-ac8e-6cdb51f41aca",
   "metadata": {},
   "outputs": [],
   "source": [
    "import mlatom as ml\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "749b662e-c526-48dc-989e-e15b12752834",
   "metadata": {},
   "outputs": [],
   "source": [
    "# prepare H2 geometries with bond lengths ranging from 0.5 to 5.0 Å\n",
    "xyz = np.zeros((451, 2, 3))\n",
    "xyz[:, 1, 2] = np.arange(0.5, 5.01, 0.01)\n",
    "z = np.ones((451, 2)).astype(int)\n",
    "molDB = ml.molecular_database.from_numpy(coordinates=xyz, species=z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e933df31-cf44-4150-92ae-489fdcb57383",
   "metadata": {},
   "outputs": [],
   "source": [
    "# calculate HF energies\n",
    "hf = ml.models.methods(method='HF/STO-3G', program='PySCF')\n",
    "hf.predict(molecular_database=molDB, calculate_energy=True, calculate_energy_gradients=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c3246c62-3417-49a3-a6c2-fc593e7087d8",
   "metadata": {},
   "outputs": [],
   "source": [
    "Ntrain = 100\n",
    "trainDB, testDB = molDB.split(sampling='random', number_of_splits=2, fraction_of_points_in_splits=[Ntrain/451, 1-Ntrain/451])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b7cb28f1-9347-4935-8dd6-d75038d07b0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "subtrainDB, valDB = trainDB.split(sampling='random', number_of_splits=2, fraction_of_points_in_splits=[0.9, 0.1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "2727b405-c7a8-4c71-bb1a-7e19344a3acf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(valDB)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "480148c9-afb2-4722-8c8e-ed125cea6745",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimized sigma: 0.35355339059327373\n",
      "Optimized lambda: 2.9103830456733704e-11\n",
      "Optimized validation loss: 6.572634410902242e-05\n"
     ]
    }
   ],
   "source": [
    "# setup the KREG model\n",
    "kreg = ml.models.kreg(model_file='KREG.npz', ml_program='KREG_API')\n",
    "# optimize its hyperparameters\n",
    "kreg.hyperparameters['sigma'].minval = 2**-5 # modify the default lower bound of the hyperparameter sigma\n",
    "kreg.optimize_hyperparameters(subtraining_molecular_database=subtrainDB,       \n",
    "                              validation_molecular_database=valDB,\n",
    "                              optimization_algorithm='grid',\n",
    "                              hyperparameters=['lambda', 'sigma'],\n",
    "                              training_kwargs={'property_to_learn': 'energy'},\n",
    "                              prediction_kwargs={'property_to_predict': 'estimated_energy'})\n",
    "lmbd = kreg.hyperparameters['lambda'].value ; sigma=kreg.hyperparameters['sigma'].value\n",
    "valloss = kreg.validation_loss\n",
    "print('Optimized sigma:', sigma)\n",
    "print('Optimized lambda:', lmbd)\n",
    "print('Optimized validation loss:', valloss)\n",
    "# Train the model with the optimized hyperparameters to dump it to disk.\n",
    "kreg.train(molecular_database=subtrainDB, property_to_learn='energy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "352ba71a-e44e-4413-abb3-9526f7ce079e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# predict with the energy-only KREG model\n",
    "kreg.predict(molecular_database=molDB, property_to_predict='estimated_energy', xyz_derivative_property_to_predict='estimated_gradients')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "621d6f4b-47e5-4894-851d-f5f1f9603ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "testRMSE_E = ml.stats.rmse(testDB.get_properties('energy'), testDB.get_properties('estimated_energy'))*ml.constants.Hartree2kcalpermol\n",
    "testRMSE_F = ml.stats.rmse(testDB.get_xyz_vectorial_properties('energy_gradients').flatten(), testDB.get_xyz_vectorial_properties('estimated_gradients').flatten())*ml.constants.Hartree2kcalpermol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4be3e740-1691-405d-8223-29ffe75ff8ea",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test RMSE for energies: 0.22932993920676076 Hartree\n",
      "Test RMSE for forces: 12.79063992200692 Hartree/Angstrom\n"
     ]
    }
   ],
   "source": [
    "print(f'Test RMSE for energies: {testRMSE_E} Hartree')\n",
    "print(f'Test RMSE for forces: {testRMSE_F} Hartree/Angstrom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "126b47db-e7d8-4aa2-80d8-c5a57ca2b0af",
   "metadata": {},
   "outputs": [],
   "source": [
    "values = testDB.get_properties('energy')\n",
    "estimated_values = testDB.get_properties('estimated_energy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "dc6133e5-fdb9-4c94-944d-d5379f9b3f3c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2ad5c7f5f910>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1500x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax = plt.subplots() \n",
    "fig.set_size_inches(15,12)\n",
    "diagonal_line = [min([min(values),min(estimated_values)]),max([max(values),max(estimated_values)])]\n",
    "ax.plot(diagonal_line,diagonal_line,color='C3')\n",
    "#ax.scatter(values[0:Nsubtrain],estimated_values[0:Nsubtrain],color='C0',label='subtraining points')\n",
    "#ax.scatter(values[Nsubtrain:Ntrain],estimated_values[Nsubtrain:Ntrain],color='C1',label='validation points')\n",
    "ax.scatter(values,estimated_values,color='C0',label='test points')\n",
    "ax.set_xlabel(f'Energy (Hartree)')\n",
    "ax.set_ylabel(f'Estimated energy (Hartree)')\n",
    "plt.suptitle(f'MLP model (energies)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43fdb797-aa1f-4637-9495-a5edf9f55416",
   "metadata": {},
   "source": [
    "# Train with forces"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "e2d39c46-b0c5-4f67-9bc0-3e922d853ba0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Optimized sigma: 0.10511205190671434\n",
      "Optimized lambda: 2.9103830456733704e-11\n",
      "Optimized validation loss: 5.049311690974179e-07\n"
     ]
    }
   ],
   "source": [
    "# setup the KREG model\n",
    "kreg_engrad = ml.models.kreg(model_file='KREG_engrad.npz', ml_program='KREG_API')\n",
    "# optimize its hyperparameters\n",
    "kreg_engrad.hyperparameters['sigma'].minval = 2**-5 # modify the default lower bound of the hyperparameter sigma\n",
    "kreg_engrad.optimize_hyperparameters(subtraining_molecular_database=subtrainDB,       \n",
    "                              validation_molecular_database=valDB,\n",
    "                              optimization_algorithm='grid',\n",
    "                              hyperparameters=['lambda', 'sigma'],\n",
    "                              training_kwargs={'property_to_learn': 'energy', 'xyz_derivative_property_to_learn': 'energy_gradients'},\n",
    "                              prediction_kwargs={'property_to_predict': 'estimated_energy',\n",
    "                                                 'xyz_derivative_property_to_predict': 'estimated_gradients'})\n",
    "lmbd = kreg_engrad.hyperparameters['lambda'].value ; sigma=kreg_engrad.hyperparameters['sigma'].value\n",
    "valloss = kreg_engrad.validation_loss\n",
    "print('Optimized sigma:', sigma)\n",
    "print('Optimized lambda:', lmbd)\n",
    "print('Optimized validation loss:', valloss)\n",
    "# Train the model with the optimized hyperparameters to dump it to disk.\n",
    "kreg_engrad.train(molecular_database=subtrainDB, property_to_learn='energy', xyz_derivative_property_to_learn='energy_gradients')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "2473d71e-c3ff-4e9d-ab6a-a9ef29f8ab9a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# predict with the energy & gradients KREG model\n",
    "kreg_engrad.predict(molecular_database=molDB, property_to_predict='estimated_energy', xyz_derivative_property_to_predict='estimated_gradients')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d3c8a0b5-3a42-4a46-8eba-27f61d776c2e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test RMSE for energies: 0.09702915016394459 Hartree\n",
      "Test RMSE for forces: 9.10393802391306 Hartree/Angstrom\n"
     ]
    }
   ],
   "source": [
    "testRMSE_E = ml.stats.rmse(testDB.get_properties('energy'), testDB.get_properties('estimated_energy'))*ml.constants.Hartree2kcalpermol\n",
    "testRMSE_F = ml.stats.rmse(testDB.get_xyz_vectorial_properties('energy_gradients').flatten(), testDB.get_xyz_vectorial_properties('estimated_gradients').flatten())*ml.constants.Hartree2kcalpermol\n",
    "print(f'Test RMSE for energies: {testRMSE_E} Hartree')\n",
    "print(f'Test RMSE for forces: {testRMSE_F} Hartree/Angstrom')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "05b7a12e-c138-4cc1-ab24-aa6316a7634a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2ad68fd84af0>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1500x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "values = testDB.get_properties('energy')\n",
    "estimated_values = testDB.get_properties('estimated_energy')\n",
    "fig,ax = plt.subplots() \n",
    "fig.set_size_inches(15,12)\n",
    "diagonal_line = [min([min(values),min(estimated_values)]),max([max(values),max(estimated_values)])]\n",
    "ax.plot(diagonal_line,diagonal_line,color='C3')\n",
    "#ax.scatter(values[0:Nsubtrain],estimated_values[0:Nsubtrain],color='C0',label='subtraining points')\n",
    "#ax.scatter(values[Nsubtrain:Ntrain],estimated_values[Nsubtrain:Ntrain],color='C1',label='validation points')\n",
    "ax.scatter(values,estimated_values,color='C0',label='test points')\n",
    "ax.set_xlabel(f'Energy (Hartree)')\n",
    "ax.set_ylabel(f'Estimated energy (Hartree)')\n",
    "plt.suptitle(f'MLP model (energies)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4fcec862-b582-404d-a744-af02e0094982",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot = ml.plot.plot()\n",
    "%matplotlib inline\n",
    "#plot.savein='h2_pec.png'\n",
    "plot.plottype='linechart_without_points'\n",
    "xref = [mol.atoms[1].xyz_coordinates[2] for mol in molDB.molecules]\n",
    "yref = [mol.energy for mol in molDB.molecules]\n",
    "plot.xs.append(xref)\n",
    "plot.ys.append(yref)\n",
    "plot.labels.append('reference') ; plot.colors.append('k') ; plot.linewidths.append(2) ; plot.markers.append('')\n",
    "xlabeled = [mol.atoms[1].xyz_coordinates[2] for mol in trainDB.molecules]\n",
    "ylabeled = [mol.energy for mol in trainDB.molecules]\n",
    "plot.xs.append(xlabeled)\n",
    "plot.ys.append(ylabeled)\n",
    "plot.labels.append('labels') ; plot.colors.append('k') ; plot.linewidths.append(0) ; plot.markers.append('o')\n",
    "xest = [mol.atoms[1].xyz_coordinates[2] for mol in molDB.molecules]\n",
    "yest = [mol.estimated_energy for mol in molDB.molecules]\n",
    "plot.xs.append(xest)\n",
    "plot.ys.append(yest)\n",
    "plot.labels.append('MLP') ; plot.colors.append('r') ; plot.linewidths.append(2) ; plot.markers.append('')\n",
    "plot.xaxis_caption = '$R_{H-H}$, $\\AA$'\n",
    "plot.yaxis_caption = 'Energy, Hartree'\n",
    "plot.make_figure()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}