ml_xtb.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "5b6dc368-b741-4ce2-aba6-10c38a72fa8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import time, datetime\n",
    "import sys\n",
    "import subprocess as sp\n",
    "import os\n",
    "from pathlib import Path\n",
    "from sys import exit\n",
    "#FIXME For copying file it is better to use implemented python function\n",
    "import shutil\n",
    "# Conversion of Hartree to kcal per mol\n",
    "au2kcal = 627.509474\n",
    "# Conversion eV to Joule\n",
    "ev2jl = 1.6021766339999E-19\n",
    "# Conversion of Hartree to electronvolt\n",
    "from pyscf.data.nist import HARTREE2EV as au2ev\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "44f6e8d1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas.util  # Assuming 'util' is an alias for pandas.util\n",
    "import pandas as pd\n",
    "# Read the CSV file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "b471a64a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>smiles_key</th>\n",
       "      <th>SMILES</th>\n",
       "      <th>HOMO</th>\n",
       "      <th>LUMO</th>\n",
       "      <th>Gap</th>\n",
       "      <th>HOMO(eV)</th>\n",
       "      <th>LUMO(eV)</th>\n",
       "      <th>Gap(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdb 6</td>\n",
       "      <td>C=O</td>\n",
       "      <td>-0.2670</td>\n",
       "      <td>-0.0406</td>\n",
       "      <td>0.2263</td>\n",
       "      <td>-7.265440</td>\n",
       "      <td>-1.104782</td>\n",
       "      <td>6.157937</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdb 11</td>\n",
       "      <td>CC=O</td>\n",
       "      <td>-0.2540</td>\n",
       "      <td>-0.0198</td>\n",
       "      <td>0.2342</td>\n",
       "      <td>-6.911692</td>\n",
       "      <td>-0.538785</td>\n",
       "      <td>6.372907</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdb 18</td>\n",
       "      <td>CC(C)=O</td>\n",
       "      <td>-0.2431</td>\n",
       "      <td>-0.0087</td>\n",
       "      <td>0.2344</td>\n",
       "      <td>-6.615088</td>\n",
       "      <td>-0.236739</td>\n",
       "      <td>6.378349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>gdb 23</td>\n",
       "      <td>C#CC#C</td>\n",
       "      <td>-0.2599</td>\n",
       "      <td>-0.0214</td>\n",
       "      <td>0.2386</td>\n",
       "      <td>-7.072239</td>\n",
       "      <td>-0.582324</td>\n",
       "      <td>6.492637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>gdb 24</td>\n",
       "      <td>C#CC#N</td>\n",
       "      <td>-0.3102</td>\n",
       "      <td>-0.0543</td>\n",
       "      <td>0.2559</td>\n",
       "      <td>-8.440972</td>\n",
       "      <td>-1.477578</td>\n",
       "      <td>6.963394</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>gdb 25</td>\n",
       "      <td>N#CC#N</td>\n",
       "      <td>-0.3696</td>\n",
       "      <td>-0.0926</td>\n",
       "      <td>0.2770</td>\n",
       "      <td>-10.057328</td>\n",
       "      <td>-2.519774</td>\n",
       "      <td>7.537554</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>gdb 26</td>\n",
       "      <td>O=CC#C</td>\n",
       "      <td>-0.2777</td>\n",
       "      <td>-0.0735</td>\n",
       "      <td>0.2042</td>\n",
       "      <td>-7.556602</td>\n",
       "      <td>-2.000037</td>\n",
       "      <td>5.556565</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gdb 27</td>\n",
       "      <td>O=CC#N</td>\n",
       "      <td>-0.3166</td>\n",
       "      <td>-0.1100</td>\n",
       "      <td>0.2066</td>\n",
       "      <td>-8.615125</td>\n",
       "      <td>-2.993252</td>\n",
       "      <td>5.621872</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>gdb 28</td>\n",
       "      <td>O=CC=O</td>\n",
       "      <td>-0.2668</td>\n",
       "      <td>-0.1113</td>\n",
       "      <td>0.1555</td>\n",
       "      <td>-7.259998</td>\n",
       "      <td>-3.028627</td>\n",
       "      <td>4.231371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>gdb 35</td>\n",
       "      <td>CCC=O</td>\n",
       "      <td>-0.2500</td>\n",
       "      <td>-0.0205</td>\n",
       "      <td>0.2295</td>\n",
       "      <td>-6.802847</td>\n",
       "      <td>-0.557833</td>\n",
       "      <td>6.245013</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  smiles_key   SMILES    HOMO    LUMO     Gap   HOMO(eV)  LUMO(eV)   Gap(eV)\n",
       "0      gdb 6      C=O -0.2670 -0.0406  0.2263  -7.265440 -1.104782  6.157937\n",
       "1     gdb 11     CC=O -0.2540 -0.0198  0.2342  -6.911692 -0.538785  6.372907\n",
       "2     gdb 18  CC(C)=O -0.2431 -0.0087  0.2344  -6.615088 -0.236739  6.378349\n",
       "3     gdb 23   C#CC#C -0.2599 -0.0214  0.2386  -7.072239 -0.582324  6.492637\n",
       "4     gdb 24   C#CC#N -0.3102 -0.0543  0.2559  -8.440972 -1.477578  6.963394\n",
       "5     gdb 25   N#CC#N -0.3696 -0.0926  0.2770 -10.057328 -2.519774  7.537554\n",
       "6     gdb 26   O=CC#C -0.2777 -0.0735  0.2042  -7.556602 -2.000037  5.556565\n",
       "7     gdb 27   O=CC#N -0.3166 -0.1100  0.2066  -8.615125 -2.993252  5.621872\n",
       "8     gdb 28   O=CC=O -0.2668 -0.1113  0.1555  -7.259998 -3.028627  4.231371\n",
       "9     gdb 35    CCC=O -0.2500 -0.0205  0.2295  -6.802847 -0.557833  6.245013"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"best_GDB9.csv\")\n",
    "df_smiles=df.iloc[0:10,:]\n",
    "\n",
    "df_smiles"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "571d44cb",
   "metadata": {},
   "source": [
    "3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2da7482a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import json\n",
    "import sys\n",
    "from tqdm import tqdm\n",
    "from sklearn.metrics import r2_score, mean_absolute_error, mean_squared_error\n",
    "from sklearn import linear_model\n",
    "from cycler import cycler\n",
    "import string\n",
    "from itertools import cycle\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7952efbe",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def label_axes(fig, labels=None, loc=None, **kwargs):\n",
    "    if labels is None:\n",
    "        labels = string.ascii_lowercase\n",
    "    labels = cycle(labels)\n",
    "    if loc is None:\n",
    "        loc = (-0.1, 1.1)\n",
    "    axes = [ax for ax in fig.axes if ax.get_label() != '<colorbar>']\n",
    "    for ax, lab in zip(axes, labels):\n",
    "        ax.annotate('(' + lab + ')', size=14, xy=loc,\n",
    "                    xycoords='axes fraction',\n",
    "                    **kwargs)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8c83ecdf",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "dataQMsym =df['HOMO(eV)']\n",
    "dataSCOP=df['LUMO(eV)']\n",
    "dataALT1=df['Gap(eV)']\n",
    "dataALS1= df['HOMO']\n",
    "dataQMsymex=df['Gap']\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0260e689",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "498964a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>smiles_key</th>\n",
       "      <th>SMILES</th>\n",
       "      <th>HOMO(eV)</th>\n",
       "      <th>HOMO_xtb(eV)</th>\n",
       "      <th>HOMO_HF(eV)</th>\n",
       "      <th>HOMO_DFT(eV)</th>\n",
       "      <th>LUMO(eV)</th>\n",
       "      <th>LUMO_xtb(eV)</th>\n",
       "      <th>LUMO_HF(eV)</th>\n",
       "      <th>LUMO_DFT(eV)</th>\n",
       "      <th>...</th>\n",
       "      <th>rmsd_conf(A)</th>\n",
       "      <th>rmsd1_conf(A)</th>\n",
       "      <th>rmsd_opt(A)</th>\n",
       "      <th>rmsd1_opt(A)</th>\n",
       "      <th>rdkit_time</th>\n",
       "      <th>xtb_time</th>\n",
       "      <th>crest_time</th>\n",
       "      <th>xtb_opt_time</th>\n",
       "      <th>dft_time</th>\n",
       "      <th>xtb_cal_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdb 6</td>\n",
       "      <td>C=O</td>\n",
       "      <td>-7.265440</td>\n",
       "      <td>-8.2725</td>\n",
       "      <td>-11.998064</td>\n",
       "      <td>-7.250440</td>\n",
       "      <td>-1.104782</td>\n",
       "      <td>3.7638</td>\n",
       "      <td>2.341292</td>\n",
       "      <td>-2.398907</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140728</td>\n",
       "      <td>0.140997</td>\n",
       "      <td>0.133209</td>\n",
       "      <td>0.000425</td>\n",
       "      <td>0.044391</td>\n",
       "      <td>0.066756</td>\n",
       "      <td>2.931592</td>\n",
       "      <td>0.051072</td>\n",
       "      <td>5.519239</td>\n",
       "      <td>0.001183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdb 11</td>\n",
       "      <td>CC=O</td>\n",
       "      <td>-6.911692</td>\n",
       "      <td>-7.8151</td>\n",
       "      <td>-11.446164</td>\n",
       "      <td>-6.880599</td>\n",
       "      <td>-0.538785</td>\n",
       "      <td>2.9005</td>\n",
       "      <td>2.676991</td>\n",
       "      <td>-1.962855</td>\n",
       "      <td>...</td>\n",
       "      <td>0.714581</td>\n",
       "      <td>0.714196</td>\n",
       "      <td>0.829722</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>0.003492</td>\n",
       "      <td>0.271686</td>\n",
       "      <td>4.909994</td>\n",
       "      <td>0.065792</td>\n",
       "      <td>14.023237</td>\n",
       "      <td>0.000708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdb 18</td>\n",
       "      <td>CC(C)=O</td>\n",
       "      <td>-6.615088</td>\n",
       "      <td>-7.4555</td>\n",
       "      <td>-11.083129</td>\n",
       "      <td>-6.637265</td>\n",
       "      <td>-0.236739</td>\n",
       "      <td>2.5009</td>\n",
       "      <td>2.879657</td>\n",
       "      <td>-1.667241</td>\n",
       "      <td>...</td>\n",
       "      <td>1.078982</td>\n",
       "      <td>1.079223</td>\n",
       "      <td>0.924983</td>\n",
       "      <td>0.002588</td>\n",
       "      <td>0.010362</td>\n",
       "      <td>0.344117</td>\n",
       "      <td>8.872018</td>\n",
       "      <td>0.240095</td>\n",
       "      <td>22.340856</td>\n",
       "      <td>0.000934</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  smiles_key   SMILES  HOMO(eV)  HOMO_xtb(eV)  HOMO_HF(eV)  HOMO_DFT(eV)  \\\n",
       "0      gdb 6      C=O -7.265440       -8.2725   -11.998064     -7.250440   \n",
       "1     gdb 11     CC=O -6.911692       -7.8151   -11.446164     -6.880599   \n",
       "2     gdb 18  CC(C)=O -6.615088       -7.4555   -11.083129     -6.637265   \n",
       "\n",
       "   LUMO(eV)  LUMO_xtb(eV)  LUMO_HF(eV)  LUMO_DFT(eV)  ...  rmsd_conf(A)  \\\n",
       "0 -1.104782        3.7638     2.341292     -2.398907  ...      0.140728   \n",
       "1 -0.538785        2.9005     2.676991     -1.962855  ...      0.714581   \n",
       "2 -0.236739        2.5009     2.879657     -1.667241  ...      1.078982   \n",
       "\n",
       "   rmsd1_conf(A)  rmsd_opt(A)  rmsd1_opt(A)  rdkit_time  xtb_time  crest_time  \\\n",
       "0       0.140997     0.133209      0.000425    0.044391  0.066756    2.931592   \n",
       "1       0.714196     0.829722      0.001953    0.003492  0.271686    4.909994   \n",
       "2       1.079223     0.924983      0.002588    0.010362  0.344117    8.872018   \n",
       "\n",
       "   xtb_opt_time   dft_time  xtb_cal_time  \n",
       "0      0.051072   5.519239      0.001183  \n",
       "1      0.065792  14.023237      0.000708  \n",
       "2      0.240095  22.340856      0.000934  \n",
       "\n",
       "[3 rows x 28 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataAll = pd.read_csv(\"rdkit_dataset_Gdb9_6-7-1.csv\")\n",
    "dataAll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3531aed1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ENERGY homo\n",
      "-10.963824158737829 0.9920592765563014\n",
      "3.6818355913273333 1.3828985442626935\n",
      "ENERGY lumo\n",
      "-109.78977722400795 -13.803404365651112\n",
      "3.6818355913273333 1.3828985442626935\n",
      "ENERGY gap\n",
      "-2093.9776614836383 -182.73870071035597\n",
      "4.599729385151 1.389963596021948\n"
     ]
    }
   ],
   "source": [
    "r2_homo_xtb = r2_score(dataAll['HOMO(eV)'], dataAll['HOMO_xtb(eV)'])\n",
    "r2_homo_dft = r2_score(dataAll['HOMO(eV)'], dataAll['HOMO_DFT(eV)'])\n",
    "MAE_homo_xtb = mean_absolute_error(dataAll['LUMO(eV)'], dataAll['LUMO_xtb(eV)'])\n",
    "MAE_homo_dft = mean_absolute_error(dataAll['LUMO(eV)'], dataAll['LUMO_DFT(eV)'])\n",
    "r2_lumo_xtb = r2_score(dataAll['LUMO(eV)'], dataAll['LUMO_xtb(eV)'])\n",
    "r2_lumo_dft = r2_score(dataAll['LUMO(eV)'], dataAll['LUMO_DFT(eV)'])\n",
    "MAE_lumo_xtb = mean_absolute_error(dataAll['LUMO(eV)'], dataAll['LUMO_xtb(eV)'])\n",
    "MAE_lumo_dft = mean_absolute_error(dataAll['LUMO(eV)'], dataAll['LUMO_DFT(eV)'])\n",
    "r2_gap_xtb = r2_score(dataAll['GAP(eV)'], dataAll['GAP_xtb(eV)'])\n",
    "r2_gap_dft = r2_score(dataAll['GAP(eV)'], dataAll['GAP_DFT(eV)'])\n",
    "MAE_gap_xtb = mean_absolute_error(dataAll['GAP(eV)'], dataAll['GAP_xtb(eV)'])\n",
    "MAE_gap_dft = mean_absolute_error(dataAll['GAP(eV)'], dataAll['GAP_DFT(eV)'])\n",
    "\n",
    "print('ENERGY homo')\n",
    "print(r2_homo_xtb, r2_homo_dft)\n",
    "print(MAE_homo_xtb, MAE_homo_dft)\n",
    "print('ENERGY lumo')\n",
    "print(r2_lumo_xtb,r2_lumo_dft)\n",
    "print(MAE_lumo_xtb, MAE_lumo_dft)\n",
    "print('ENERGY gap')\n",
    "print(r2_gap_xtb, r2_gap_dft)\n",
    "print(MAE_gap_xtb,MAE_gap_dft)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "9f680658",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2100x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(num=1, figsize=[7, 4], dpi=300, clear=True)\n",
    "ax = fig.add_subplot(1, 2, 1)\n",
    "ax.set_axisbelow(True)\n",
    "\n",
    "plt.plot(dataAll['HOMO(eV)'], dataAll['HOMO_xtb(eV)'], 'x', color='red', markersize=0.1, label='XTB HOMO')\n",
    "plt.plot(dataAll['HOMO(eV)'], dataAll['HOMO_DFT(eV)'], '^', color='blue', markersize=0.1, label='xtb LUMO')\n",
    "plt.plot(dataAll['HOMO(eV)'], dataAll['HOMO_DFT(eV)'], '.', color='green', markersize=0.1, label='XTB GAP')\n",
    "\n",
    "x = np.linspace(0, 9, 100)\n",
    "plt.plot(x, x, 'k--')\n",
    "plt.grid(True)\n",
    "plt.legend(loc='upper left')\n",
    "plt.xlabel('energy ref (eV)')\n",
    "plt.ylabel('energy xtb (eV)')\n",
    "plt.title('real vs. xtb comparison')\n",
    "plt.xlim(0, 9)\n",
    "plt.ylim(0, 9)\n",
    "plt.annotate('R2 homo xtb: %0.2f\\n' % r2_homo_xtb +\n",
    "                 'R2 lumo xtb: %0.2f\\n' % r2_lumo_xtb +\n",
    "                 'R2 gap xtb: %0.2f\\n' % r2_gap_xtb +\n",
    "                 'MAE homo xtb: %0.2f\\n' % MAE_homo_xtb +\n",
    "                 'MAE lumo xtb: %0.2f\\n' % MAE_lumo_xtb +\n",
    "                 'MAE gap xtb: %0.2f' % MAE_gap_xtb,\n",
    "                 (8.5, 0.5),\n",
    "                 bbox=dict(facecolor='white', alpha=0.5),\n",
    "                 ha='right')\n",
    "plt.gca().set_aspect('equal', adjustable='box')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "29182ae7-c357-4eda-a35f-8259e54336e9",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_1370478/2693584063.py:11: UserWarning: No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "  plt.legend(loc='upper left')\n",
      "/tmp/ipykernel_1370478/2693584063.py:12: UserWarning: No artists with labels found to put in legend.  Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n",
      "  plt.legend(loc='upper left')\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "\n",
    "\n",
    "\n",
    "    # get metrics\n",
    "  \n",
    "\n",
    "   \n",
    "\n",
    "ax = fig.add_subplot(1, 2, 2)\n",
    "ax.set_axisbelow(True)\n",
    "\n",
    "plt.plot(x, x, 'k--')\n",
    "plt.grid(True)\n",
    "plt.legend(loc='upper left')\n",
    "plt.legend(loc='upper left')\n",
    "plt.xlabel('energy ref (eV)')\n",
    "plt.ylabel('energy dft (eV)')\n",
    "plt.title('real vs. dft comparison')\n",
    "plt.xlim(0, 9)\n",
    "plt.ylim(0, 9)\n",
    "plt.annotate('R2 homo xtb: %0.2f\\n' % r2_homo_dft +\n",
    "                 'R2 lumo xtb: %0.2f\\n' % r2_lumo_dft +\n",
    "                 'R2 gap xtb: %0.2f\\n' % r2_gap_xtb +\n",
    "                 'MAE homo xtb: %0.2f\\n' % MAE_homo_dft +\n",
    "                 'MAE lumo xtb: %0.2f\\n' % MAE_lumo_dft +\n",
    "                 'MAE gap xtb: %0.2f' % MAE_gap_dft,\n",
    "                 (8.5, 0.5),\n",
    "                 bbox=dict(facecolor='white', alpha=0.5),\n",
    "                 ha='right')\n",
    "plt.gca().set_aspect('equal', adjustable='box')\n",
    "plt.tight_layout()\n",
    "plt.savefig('mopssam_calib_nrg_' + '.png')\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b23cc512",
   "metadata": {},
   "outputs": [],
   "source": [
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(np.array(dataAll['HOMO_xtb(eV)']).reshape(-1, 1), np.array(dataAll['HOMO(eV)']).reshape(-1, 1))\n",
    "dataAll['xTB_Lin'] = [x[0] for x in regr.predict(np.array(dataAll['HOMO_xtb(eV)']).reshape(-1, 1))]\n",
    "regr = linear_model.LinearRegression()\n",
    "regr.fit(np.array(dataAll['HOMO_DFT(eV)']).reshape(-1, 1), np.array(dataAll['HOMO(eV)']).reshape(-1, 1))\n",
    "dataAll['DFT_Lin'] = [x[0] for x in regr.predict(np.array(dataAll['HOMO_DFT(eV)']).reshape(-1, 1))]\n",
    "# dataAll.info()\n",
    "dataAll.to_csv('all_data_' + '.csv', index=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "527dad52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>smiles_key</th>\n",
       "      <th>SMILES</th>\n",
       "      <th>HOMO(eV)</th>\n",
       "      <th>HOMO_xtb(eV)</th>\n",
       "      <th>HOMO_HF(eV)</th>\n",
       "      <th>HOMO_DFT(eV)</th>\n",
       "      <th>LUMO(eV)</th>\n",
       "      <th>LUMO_xtb(eV)</th>\n",
       "      <th>LUMO_HF(eV)</th>\n",
       "      <th>LUMO_DFT(eV)</th>\n",
       "      <th>...</th>\n",
       "      <th>rmsd_opt(A)</th>\n",
       "      <th>rmsd1_opt(A)</th>\n",
       "      <th>rdkit_time</th>\n",
       "      <th>xtb_time</th>\n",
       "      <th>crest_time</th>\n",
       "      <th>xtb_opt_time</th>\n",
       "      <th>dft_time</th>\n",
       "      <th>xtb_cal_time</th>\n",
       "      <th>xTB_Lin</th>\n",
       "      <th>DFT_Lin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdb 6</td>\n",
       "      <td>C=O</td>\n",
       "      <td>-7.265440</td>\n",
       "      <td>-8.2725</td>\n",
       "      <td>-11.998064</td>\n",
       "      <td>-7.250440</td>\n",
       "      <td>-1.104782</td>\n",
       "      <td>3.7638</td>\n",
       "      <td>2.341292</td>\n",
       "      <td>-2.398907</td>\n",
       "      <td>...</td>\n",
       "      <td>0.133209</td>\n",
       "      <td>0.000425</td>\n",
       "      <td>0.044391</td>\n",
       "      <td>0.066756</td>\n",
       "      <td>2.931592</td>\n",
       "      <td>0.051072</td>\n",
       "      <td>5.519239</td>\n",
       "      <td>0.001183</td>\n",
       "      <td>-7.268464</td>\n",
       "      <td>-7.275488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdb 11</td>\n",
       "      <td>CC=O</td>\n",
       "      <td>-6.911692</td>\n",
       "      <td>-7.8151</td>\n",
       "      <td>-11.446164</td>\n",
       "      <td>-6.880599</td>\n",
       "      <td>-0.538785</td>\n",
       "      <td>2.9005</td>\n",
       "      <td>2.676991</td>\n",
       "      <td>-1.962855</td>\n",
       "      <td>...</td>\n",
       "      <td>0.829722</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>0.003492</td>\n",
       "      <td>0.271686</td>\n",
       "      <td>4.909994</td>\n",
       "      <td>0.065792</td>\n",
       "      <td>14.023237</td>\n",
       "      <td>0.000708</td>\n",
       "      <td>-6.904822</td>\n",
       "      <td>-6.886373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdb 18</td>\n",
       "      <td>CC(C)=O</td>\n",
       "      <td>-6.615088</td>\n",
       "      <td>-7.4555</td>\n",
       "      <td>-11.083129</td>\n",
       "      <td>-6.637265</td>\n",
       "      <td>-0.236739</td>\n",
       "      <td>2.5009</td>\n",
       "      <td>2.879657</td>\n",
       "      <td>-1.667241</td>\n",
       "      <td>...</td>\n",
       "      <td>0.924983</td>\n",
       "      <td>0.002588</td>\n",
       "      <td>0.010362</td>\n",
       "      <td>0.344117</td>\n",
       "      <td>8.872018</td>\n",
       "      <td>0.240095</td>\n",
       "      <td>22.340856</td>\n",
       "      <td>0.000934</td>\n",
       "      <td>-6.618934</td>\n",
       "      <td>-6.630359</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  smiles_key   SMILES  HOMO(eV)  HOMO_xtb(eV)  HOMO_HF(eV)  HOMO_DFT(eV)  \\\n",
       "0      gdb 6      C=O -7.265440       -8.2725   -11.998064     -7.250440   \n",
       "1     gdb 11     CC=O -6.911692       -7.8151   -11.446164     -6.880599   \n",
       "2     gdb 18  CC(C)=O -6.615088       -7.4555   -11.083129     -6.637265   \n",
       "\n",
       "   LUMO(eV)  LUMO_xtb(eV)  LUMO_HF(eV)  LUMO_DFT(eV)  ...  rmsd_opt(A)  \\\n",
       "0 -1.104782        3.7638     2.341292     -2.398907  ...     0.133209   \n",
       "1 -0.538785        2.9005     2.676991     -1.962855  ...     0.829722   \n",
       "2 -0.236739        2.5009     2.879657     -1.667241  ...     0.924983   \n",
       "\n",
       "   rmsd1_opt(A)  rdkit_time  xtb_time  crest_time  xtb_opt_time   dft_time  \\\n",
       "0      0.000425    0.044391  0.066756    2.931592      0.051072   5.519239   \n",
       "1      0.001953    0.003492  0.271686    4.909994      0.065792  14.023237   \n",
       "2      0.002588    0.010362  0.344117    8.872018      0.240095  22.340856   \n",
       "\n",
       "   xtb_cal_time   xTB_Lin   DFT_Lin  \n",
       "0      0.001183 -7.268464 -7.275488  \n",
       "1      0.000708 -6.904822 -6.886373  \n",
       "2      0.000934 -6.618934 -6.630359  \n",
       "\n",
       "[3 rows x 30 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataAll"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5efde4a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>smiles_key</th>\n",
       "      <th>SMILES</th>\n",
       "      <th>HOMO(eV)</th>\n",
       "      <th>HOMO_xtb(eV)</th>\n",
       "      <th>HOMO_HF(eV)</th>\n",
       "      <th>HOMO_DFT(eV)</th>\n",
       "      <th>LUMO(eV)</th>\n",
       "      <th>LUMO_xtb(eV)</th>\n",
       "      <th>LUMO_HF(eV)</th>\n",
       "      <th>LUMO_DFT(eV)</th>\n",
       "      <th>...</th>\n",
       "      <th>rmsd_conf(A)</th>\n",
       "      <th>rmsd1_conf(A)</th>\n",
       "      <th>rmsd_opt(A)</th>\n",
       "      <th>rmsd1_opt(A)</th>\n",
       "      <th>rdkit_time</th>\n",
       "      <th>xtb_time</th>\n",
       "      <th>crest_time</th>\n",
       "      <th>xtb_opt_time</th>\n",
       "      <th>dft_time</th>\n",
       "      <th>xtb_cal_time</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>gdb 6</td>\n",
       "      <td>C=O</td>\n",
       "      <td>-7.265440</td>\n",
       "      <td>-8.2725</td>\n",
       "      <td>-11.998064</td>\n",
       "      <td>-7.250440</td>\n",
       "      <td>-1.104782</td>\n",
       "      <td>3.7638</td>\n",
       "      <td>2.341292</td>\n",
       "      <td>-2.398907</td>\n",
       "      <td>...</td>\n",
       "      <td>0.140728</td>\n",
       "      <td>0.140997</td>\n",
       "      <td>0.133209</td>\n",
       "      <td>0.000425</td>\n",
       "      <td>0.044391</td>\n",
       "      <td>0.066756</td>\n",
       "      <td>2.931592</td>\n",
       "      <td>0.051072</td>\n",
       "      <td>5.519239</td>\n",
       "      <td>0.001183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>gdb 11</td>\n",
       "      <td>CC=O</td>\n",
       "      <td>-6.911692</td>\n",
       "      <td>-7.8151</td>\n",
       "      <td>-11.446164</td>\n",
       "      <td>-6.880599</td>\n",
       "      <td>-0.538785</td>\n",
       "      <td>2.9005</td>\n",
       "      <td>2.676991</td>\n",
       "      <td>-1.962855</td>\n",
       "      <td>...</td>\n",
       "      <td>0.714581</td>\n",
       "      <td>0.714196</td>\n",
       "      <td>0.829722</td>\n",
       "      <td>0.001953</td>\n",
       "      <td>0.003492</td>\n",
       "      <td>0.271686</td>\n",
       "      <td>4.909994</td>\n",
       "      <td>0.065792</td>\n",
       "      <td>14.023237</td>\n",
       "      <td>0.000708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>gdb 18</td>\n",
       "      <td>CC(C)=O</td>\n",
       "      <td>-6.615088</td>\n",
       "      <td>-7.4555</td>\n",
       "      <td>-11.083129</td>\n",
       "      <td>-6.637265</td>\n",
       "      <td>-0.236739</td>\n",
       "      <td>2.5009</td>\n",
       "      <td>2.879657</td>\n",
       "      <td>-1.667241</td>\n",
       "      <td>...</td>\n",
       "      <td>1.078982</td>\n",
       "      <td>1.079223</td>\n",
       "      <td>0.924983</td>\n",
       "      <td>0.002588</td>\n",
       "      <td>0.010362</td>\n",
       "      <td>0.344117</td>\n",
       "      <td>8.872018</td>\n",
       "      <td>0.240095</td>\n",
       "      <td>22.340856</td>\n",
       "      <td>0.000934</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  smiles_key   SMILES  HOMO(eV)  HOMO_xtb(eV)  HOMO_HF(eV)  HOMO_DFT(eV)  \\\n",
       "0      gdb 6      C=O -7.265440       -8.2725   -11.998064     -7.250440   \n",
       "1     gdb 11     CC=O -6.911692       -7.8151   -11.446164     -6.880599   \n",
       "2     gdb 18  CC(C)=O -6.615088       -7.4555   -11.083129     -6.637265   \n",
       "\n",
       "   LUMO(eV)  LUMO_xtb(eV)  LUMO_HF(eV)  LUMO_DFT(eV)  ...  rmsd_conf(A)  \\\n",
       "0 -1.104782        3.7638     2.341292     -2.398907  ...      0.140728   \n",
       "1 -0.538785        2.9005     2.676991     -1.962855  ...      0.714581   \n",
       "2 -0.236739        2.5009     2.879657     -1.667241  ...      1.078982   \n",
       "\n",
       "   rmsd1_conf(A)  rmsd_opt(A)  rmsd1_opt(A)  rdkit_time  xtb_time  crest_time  \\\n",
       "0       0.140997     0.133209      0.000425    0.044391  0.066756    2.931592   \n",
       "1       0.714196     0.829722      0.001953    0.003492  0.271686    4.909994   \n",
       "2       1.079223     0.924983      0.002588    0.010362  0.344117    8.872018   \n",
       "\n",
       "   xtb_opt_time   dft_time  xtb_cal_time  \n",
       "0      0.051072   5.519239      0.001183  \n",
       "1      0.065792  14.023237      0.000708  \n",
       "2      0.240095  22.340856      0.000934  \n",
       "\n",
       "[3 rows x 28 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=dataAll\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "dd5254ed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "HOMO Metrics:\n",
      "R2 xtb: -12.57, MAE xtb: 0.92\n",
      "R2 lin: 1.00, MAE lin: 0.01\n",
      "R2 ML: -2435.01, MAE ML: 12.43\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2100x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.metrics import r2_score, mean_absolute_error\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "def analyze_ML(df):\n",
    "\n",
    "    \n",
    "    # Calibration ML: correction des prédictions HOMO et LUMO\n",
    "    df['HOMO_ML_calib'] = df['HOMO_xtb(eV)'] + df['HOMO_HF(eV)']  # Exemple avec correction\n",
    "    df['LUMO_ML_calib'] = df['LUMO_xtb(eV)'] + df['LUMO_HF(eV)']\n",
    "\n",
    "    # Calibration linéaire\n",
    "    lin_reg_homo = LinearRegression()\n",
    "    lin_reg_homo.fit(df[['HOMO_xtb(eV)']], df['HOMO_DFT(eV)'])\n",
    "    df['HOMO_Lin_calib'] = lin_reg_homo.predict(df[['HOMO_xtb(eV)']])\n",
    "\n",
    "    lin_reg_lumo = LinearRegression()\n",
    "    lin_reg_lumo.fit(df[['LUMO_xtb(eV)']], df['LUMO_DFT(eV)'])\n",
    "    df['LUMO_Lin_calib'] = lin_reg_lumo.predict(df[['LUMO_xtb(eV)']])\n",
    "\n",
    "    # Calcul des métriques pour les calibrations ML et linéaire\n",
    "    r2_HOMO_xtb = r2_score(df['HOMO_DFT(eV)'], df['HOMO_xtb(eV)'])\n",
    "    mae_HOMO_xtb = mean_absolute_error(df['HOMO_DFT(eV)'], df['HOMO_xtb(eV)'])\n",
    "\n",
    "    r2_HOMO_lin = r2_score(df['HOMO_DFT(eV)'], df['HOMO_Lin_calib'])\n",
    "    mae_HOMO_lin = mean_absolute_error(df['HOMO_DFT(eV)'], df['HOMO_Lin_calib'])\n",
    "\n",
    "    r2_HOMO_ML = r2_score(df['HOMO_DFT(eV)'], df['HOMO_ML_calib'])\n",
    "    mae_HOMO_ML = mean_absolute_error(df['HOMO_DFT(eV)'], df['HOMO_ML_calib'])\n",
    "\n",
    "    print('HOMO Metrics:')\n",
    "    print(f'R2 xtb: {r2_HOMO_xtb:.2f}, MAE xtb: {mae_HOMO_xtb:.2f}')\n",
    "    print(f'R2 lin: {r2_HOMO_lin:.2f}, MAE lin: {mae_HOMO_lin:.2f}')\n",
    "    print(f'R2 ML: {r2_HOMO_ML:.2f}, MAE ML: {mae_HOMO_ML:.2f}')\n",
    "\n",
    "    # Représentation graphique des résultats\n",
    "    plt.figure(figsize=[7, 4], dpi=300)\n",
    "\n",
    "    # Graphique pour HOMO\n",
    "    plt.subplot(1, 2, 1)\n",
    "    plt.scatter(df['HOMO_xtb(eV)'], df['HOMO_DFT(eV)'], color='red', label='Original')\n",
    "    plt.scatter(df['HOMO_Lin_calib'], df['HOMO_DFT(eV)'], color='blue', label='Linear Calibration')\n",
    "    plt.scatter(df['HOMO_ML_calib'], df['HOMO_DFT(eV)'], color='green', label='ML Calibration')\n",
    "    plt.plot([min(df['HOMO_DFT(eV)']), max(df['HOMO_DFT(eV)'])], [min(df['HOMO_DFT(eV)']), max(df['HOMO_DFT(eV)'])], 'k--')\n",
    "    plt.xlabel('Predicted HOMO (eV)')\n",
    "    plt.ylabel('DFT HOMO (eV)')\n",
    "    plt.title('HOMO Calibration')\n",
    "    plt.legend()\n",
    "    plt.grid(True)\n",
    "\n",
    "    # LUMO metrics and plot can be added similarly\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "\n",
    "    # Optionally save the updated DataFrame\n",
    "    df.to_csv('calibrated_data.csv', index=False)\n",
    "\n",
    "# Exécution de l'analyse avec le DataFrame en entrée\n",
    "  # Chargement du DataFrame avec les colonnes correspondantes\n",
    "analyze_ML(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "798bb6dc",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6fffa297",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}