{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9c79795e-1a6b-4cfa-a431-c62475d84484",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cn</th>\n",
       "      <th>theta_mean</th>\n",
       "      <th>theta_std</th>\n",
       "      <th>local_density</th>\n",
       "      <th>density_2A</th>\n",
       "      <th>density_3A</th>\n",
       "      <th>density_5A</th>\n",
       "      <th>height</th>\n",
       "      <th>curvature</th>\n",
       "      <th>planarity</th>\n",
       "      <th>...</th>\n",
       "      <th>local_rings_4</th>\n",
       "      <th>local_rings_5</th>\n",
       "      <th>local_rings_6</th>\n",
       "      <th>local_rings_7</th>\n",
       "      <th>local_hexagons</th>\n",
       "      <th>rings_per_atom</th>\n",
       "      <th>smallest_ring</th>\n",
       "      <th>filename</th>\n",
       "      <th>id</th>\n",
       "      <th>ΔG(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>115.565384</td>\n",
       "      <td>1.707292</td>\n",
       "      <td>28.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.320549</td>\n",
       "      <td>0.011338</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POSCAR_001_relaxed</td>\n",
       "      <td>1</td>\n",
       "      <td>0.869249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>114.585619</td>\n",
       "      <td>9.408976</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.336314</td>\n",
       "      <td>0.008966</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.137931</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_002_relaxed</td>\n",
       "      <td>2</td>\n",
       "      <td>0.430614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>116.300221</td>\n",
       "      <td>7.520467</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.295069</td>\n",
       "      <td>0.008167</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.172414</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_003_relaxed</td>\n",
       "      <td>3</td>\n",
       "      <td>0.541070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>111.062209</td>\n",
       "      <td>4.915973</td>\n",
       "      <td>30.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.420566</td>\n",
       "      <td>0.013560</td>\n",
       "      <td>1.262177e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POSCAR_004_relaxed</td>\n",
       "      <td>4</td>\n",
       "      <td>0.328253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.0</td>\n",
       "      <td>114.849125</td>\n",
       "      <td>9.807015</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.272271</td>\n",
       "      <td>0.007583</td>\n",
       "      <td>1.262177e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.172414</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_005_relaxed</td>\n",
       "      <td>5</td>\n",
       "      <td>0.455718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1315</th>\n",
       "      <td>3.0</td>\n",
       "      <td>119.329625</td>\n",
       "      <td>6.038542</td>\n",
       "      <td>29.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.120160</td>\n",
       "      <td>0.003407</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.206897</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_995_relaxed</td>\n",
       "      <td>995</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>3.0</td>\n",
       "      <td>97.291226</td>\n",
       "      <td>31.677428</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.349768</td>\n",
       "      <td>0.004020</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.137931</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POSCAR_996_relaxed</td>\n",
       "      <td>996</td>\n",
       "      <td>-0.153311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>3.0</td>\n",
       "      <td>113.747866</td>\n",
       "      <td>8.663664</td>\n",
       "      <td>29.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.367615</td>\n",
       "      <td>0.021534</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.137931</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_997_relaxed</td>\n",
       "      <td>997</td>\n",
       "      <td>0.432398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1318</th>\n",
       "      <td>3.0</td>\n",
       "      <td>113.388649</td>\n",
       "      <td>2.041873</td>\n",
       "      <td>28.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.387738</td>\n",
       "      <td>0.010256</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.178571</td>\n",
       "      <td>6.0</td>\n",
       "      <td>POSCAR_998_relaxed</td>\n",
       "      <td>998</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>3.0</td>\n",
       "      <td>110.387013</td>\n",
       "      <td>6.244154</td>\n",
       "      <td>28.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.462149</td>\n",
       "      <td>0.003764</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.107143</td>\n",
       "      <td>7.0</td>\n",
       "      <td>POSCAR_999_relaxed</td>\n",
       "      <td>999</td>\n",
       "      <td>0.212444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1320 rows × 32 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       cn  theta_mean  theta_std  local_density  density_2A  density_3A  \\\n",
       "0     3.0  115.565384   1.707292           28.0         4.0        13.0   \n",
       "1     3.0  114.585619   9.408976           29.0         4.0        11.0   \n",
       "2     3.0  116.300221   7.520467           29.0         4.0        12.0   \n",
       "3     3.0  111.062209   4.915973           30.0         4.0        12.0   \n",
       "4     3.0  114.849125   9.807015           29.0         4.0        11.0   \n",
       "...   ...         ...        ...            ...         ...         ...   \n",
       "1315  3.0  119.329625   6.038542           29.0         3.0        11.0   \n",
       "1316  3.0   97.291226  31.677428           29.0         4.0        11.0   \n",
       "1317  3.0  113.747866   8.663664           29.0         4.0        12.0   \n",
       "1318  3.0  113.388649   2.041873           28.0         4.0        13.0   \n",
       "1319  3.0  110.387013   6.244154           28.0         4.0        12.0   \n",
       "\n",
       "      density_5A    height  curvature     planarity  ...  local_rings_4  \\\n",
       "0           28.0  0.320549   0.011338  0.000000e+00  ...            0.0   \n",
       "1           29.0  0.336314   0.008966  0.000000e+00  ...            0.0   \n",
       "2           29.0  0.295069   0.008167  0.000000e+00  ...            0.0   \n",
       "3           30.0  0.420566   0.013560  1.262177e-29  ...            0.0   \n",
       "4           29.0  0.272271   0.007583  1.262177e-29  ...            0.0   \n",
       "...          ...       ...        ...           ...  ...            ...   \n",
       "1315        29.0  0.120160   0.003407  0.000000e+00  ...            0.0   \n",
       "1316        29.0  0.349768   0.004020  0.000000e+00  ...            0.0   \n",
       "1317        29.0  0.367615   0.021534  0.000000e+00  ...            0.0   \n",
       "1318        28.0  0.387738   0.010256  0.000000e+00  ...            0.0   \n",
       "1319        28.0  0.462149   0.003764  0.000000e+00  ...            0.0   \n",
       "\n",
       "      local_rings_5  local_rings_6  local_rings_7  local_hexagons  \\\n",
       "0               0.0            3.0            0.0             3.0   \n",
       "1               1.0            2.0            1.0             2.0   \n",
       "2               2.0            1.0            2.0             1.0   \n",
       "3               0.0            3.0            2.0             3.0   \n",
       "4               3.0            1.0            1.0             1.0   \n",
       "...             ...            ...            ...             ...   \n",
       "1315            4.0            2.0            0.0             2.0   \n",
       "1316            0.0            3.0            1.0             3.0   \n",
       "1317            1.0            3.0            0.0             3.0   \n",
       "1318            2.0            3.0            0.0             3.0   \n",
       "1319            0.0            3.0            0.0             3.0   \n",
       "\n",
       "      rings_per_atom  smallest_ring            filename   id    ΔG(eV)  \n",
       "0           0.107143            7.0  POSCAR_001_relaxed    1  0.869249  \n",
       "1           0.137931            6.0  POSCAR_002_relaxed    2  0.430614  \n",
       "2           0.172414            6.0  POSCAR_003_relaxed    3  0.541070  \n",
       "3           0.166667            7.0  POSCAR_004_relaxed    4  0.328253  \n",
       "4           0.172414            6.0  POSCAR_005_relaxed    5  0.455718  \n",
       "...              ...            ...                 ...  ...       ...  \n",
       "1315        0.206897            6.0  POSCAR_995_relaxed  995       NaN  \n",
       "1316        0.137931            7.0  POSCAR_996_relaxed  996 -0.153311  \n",
       "1317        0.137931            6.0  POSCAR_997_relaxed  997  0.432398  \n",
       "1318        0.178571            6.0  POSCAR_998_relaxed  998       NaN  \n",
       "1319        0.107143            7.0  POSCAR_999_relaxed  999  0.212444  \n",
       "\n",
       "[1320 rows x 32 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv('HER_sites_full.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "a90c303a-b098-4de8-9efc-f78aaf6257ca",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>cn</th>\n",
       "      <th>theta_mean</th>\n",
       "      <th>theta_std</th>\n",
       "      <th>local_density</th>\n",
       "      <th>density_2A</th>\n",
       "      <th>density_3A</th>\n",
       "      <th>density_5A</th>\n",
       "      <th>height</th>\n",
       "      <th>curvature</th>\n",
       "      <th>planarity</th>\n",
       "      <th>...</th>\n",
       "      <th>local_rings_3</th>\n",
       "      <th>local_rings_4</th>\n",
       "      <th>local_rings_5</th>\n",
       "      <th>local_rings_6</th>\n",
       "      <th>local_rings_7</th>\n",
       "      <th>local_hexagons</th>\n",
       "      <th>rings_per_atom</th>\n",
       "      <th>smallest_ring</th>\n",
       "      <th>id</th>\n",
       "      <th>ΔG(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1.320000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>1320.0</td>\n",
       "      <td>1320.0</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1119.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.980303</td>\n",
       "      <td>108.737033</td>\n",
       "      <td>8.876499</td>\n",
       "      <td>28.903788</td>\n",
       "      <td>3.887121</td>\n",
       "      <td>11.386364</td>\n",
       "      <td>28.903788</td>\n",
       "      <td>0.314286</td>\n",
       "      <td>0.016659</td>\n",
       "      <td>4.500491e-30</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.540909</td>\n",
       "      <td>2.103788</td>\n",
       "      <td>0.602273</td>\n",
       "      <td>2.103788</td>\n",
       "      <td>0.146232</td>\n",
       "      <td>6.140909</td>\n",
       "      <td>660.500000</td>\n",
       "      <td>0.608037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.139009</td>\n",
       "      <td>18.925454</td>\n",
       "      <td>8.762212</td>\n",
       "      <td>1.504802</td>\n",
       "      <td>0.316565</td>\n",
       "      <td>1.020248</td>\n",
       "      <td>1.504802</td>\n",
       "      <td>0.097584</td>\n",
       "      <td>0.010286</td>\n",
       "      <td>6.342533e-30</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.004082</td>\n",
       "      <td>0.939723</td>\n",
       "      <td>0.713879</td>\n",
       "      <td>0.939723</td>\n",
       "      <td>0.027922</td>\n",
       "      <td>0.348060</td>\n",
       "      <td>381.195488</td>\n",
       "      <td>0.562586</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>6.159180</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-2.729075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>112.435307</td>\n",
       "      <td>3.458283</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.296806</td>\n",
       "      <td>0.009100</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.750000</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>330.750000</td>\n",
       "      <td>0.447479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>114.646638</td>\n",
       "      <td>6.530295</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.328163</td>\n",
       "      <td>0.015182</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>660.500000</td>\n",
       "      <td>0.708844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>115.924282</td>\n",
       "      <td>9.932608</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0.362932</td>\n",
       "      <td>0.022499</td>\n",
       "      <td>1.262177e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>990.250000</td>\n",
       "      <td>0.911836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>137.895186</td>\n",
       "      <td>51.414121</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.545782</td>\n",
       "      <td>0.052059</td>\n",
       "      <td>5.048710e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1.594346</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                cn   theta_mean    theta_std  local_density   density_2A  \\\n",
       "count  1320.000000  1320.000000  1320.000000    1320.000000  1320.000000   \n",
       "mean      2.980303   108.737033     8.876499      28.903788     3.887121   \n",
       "std       0.139009    18.925454     8.762212       1.504802     0.316565   \n",
       "min       2.000000     6.159180     0.000000      24.000000     3.000000   \n",
       "25%       3.000000   112.435307     3.458283      28.000000     4.000000   \n",
       "50%       3.000000   114.646638     6.530295      29.000000     4.000000   \n",
       "75%       3.000000   115.924282     9.932608      30.000000     4.000000   \n",
       "max       3.000000   137.895186    51.414121      34.000000     4.000000   \n",
       "\n",
       "        density_3A   density_5A       height    curvature     planarity  ...  \\\n",
       "count  1320.000000  1320.000000  1320.000000  1320.000000  1.320000e+03  ...   \n",
       "mean     11.386364    28.903788     0.314286     0.016659  4.500491e-30  ...   \n",
       "std       1.020248     1.504802     0.097584     0.010286  6.342533e-30  ...   \n",
       "min       7.000000    24.000000     0.000000     0.000000  0.000000e+00  ...   \n",
       "25%      11.000000    28.000000     0.296806     0.009100  0.000000e+00  ...   \n",
       "50%      11.000000    29.000000     0.328163     0.015182  0.000000e+00  ...   \n",
       "75%      12.000000    30.000000     0.362932     0.022499  1.262177e-29  ...   \n",
       "max      13.000000    34.000000     0.545782     0.052059  5.048710e-29  ...   \n",
       "\n",
       "       local_rings_3  local_rings_4  local_rings_5  local_rings_6  \\\n",
       "count         1320.0         1320.0    1320.000000    1320.000000   \n",
       "mean             0.0            0.0       1.540909       2.103788   \n",
       "std              0.0            0.0       1.004082       0.939723   \n",
       "min              0.0            0.0       0.000000       0.000000   \n",
       "25%              0.0            0.0       1.000000       1.750000   \n",
       "50%              0.0            0.0       1.000000       2.000000   \n",
       "75%              0.0            0.0       2.000000       3.000000   \n",
       "max              0.0            0.0       5.000000       5.000000   \n",
       "\n",
       "       local_rings_7  local_hexagons  rings_per_atom  smallest_ring  \\\n",
       "count    1320.000000     1320.000000     1320.000000    1320.000000   \n",
       "mean        0.602273        2.103788        0.146232       6.140909   \n",
       "std         0.713879        0.939723        0.027922       0.348060   \n",
       "min         0.000000        0.000000        0.071429       6.000000   \n",
       "25%         0.000000        1.750000        0.133333       6.000000   \n",
       "50%         0.000000        2.000000        0.142857       6.000000   \n",
       "75%         1.000000        3.000000        0.166667       6.000000   \n",
       "max         3.000000        5.000000        0.235294       7.000000   \n",
       "\n",
       "                id       ΔG(eV)  \n",
       "count  1320.000000  1119.000000  \n",
       "mean    660.500000     0.608037  \n",
       "std     381.195488     0.562586  \n",
       "min       1.000000    -2.729075  \n",
       "25%     330.750000     0.447479  \n",
       "50%     660.500000     0.708844  \n",
       "75%     990.250000     0.911836  \n",
       "max    1320.000000     1.594346  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3f2961aa-0b3c-4c7c-acad-6bd7d8c67a2d",
   "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>cn</th>\n",
       "      <th>theta_mean</th>\n",
       "      <th>theta_std</th>\n",
       "      <th>local_density</th>\n",
       "      <th>density_2A</th>\n",
       "      <th>density_3A</th>\n",
       "      <th>density_5A</th>\n",
       "      <th>height</th>\n",
       "      <th>curvature</th>\n",
       "      <th>planarity</th>\n",
       "      <th>...</th>\n",
       "      <th>local_rings_3</th>\n",
       "      <th>local_rings_4</th>\n",
       "      <th>local_rings_5</th>\n",
       "      <th>local_rings_6</th>\n",
       "      <th>local_rings_7</th>\n",
       "      <th>local_hexagons</th>\n",
       "      <th>rings_per_atom</th>\n",
       "      <th>smallest_ring</th>\n",
       "      <th>id</th>\n",
       "      <th>ΔG(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1.092000e+03</td>\n",
       "      <td>...</td>\n",
       "      <td>1092.0</td>\n",
       "      <td>1092.0</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.999084</td>\n",
       "      <td>107.739479</td>\n",
       "      <td>9.489334</td>\n",
       "      <td>28.945971</td>\n",
       "      <td>3.999084</td>\n",
       "      <td>11.484432</td>\n",
       "      <td>28.945971</td>\n",
       "      <td>0.338648</td>\n",
       "      <td>0.017366</td>\n",
       "      <td>4.476954e-30</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.472527</td>\n",
       "      <td>2.132784</td>\n",
       "      <td>0.647436</td>\n",
       "      <td>2.132784</td>\n",
       "      <td>0.146217</td>\n",
       "      <td>6.152015</td>\n",
       "      <td>615.975275</td>\n",
       "      <td>0.677213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.030261</td>\n",
       "      <td>19.389291</td>\n",
       "      <td>8.863510</td>\n",
       "      <td>1.507030</td>\n",
       "      <td>0.030261</td>\n",
       "      <td>0.894394</td>\n",
       "      <td>1.507030</td>\n",
       "      <td>0.050730</td>\n",
       "      <td>0.010356</td>\n",
       "      <td>6.118696e-30</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.972668</td>\n",
       "      <td>0.940847</td>\n",
       "      <td>0.731172</td>\n",
       "      <td>0.940847</td>\n",
       "      <td>0.027587</td>\n",
       "      <td>0.359200</td>\n",
       "      <td>371.942588</td>\n",
       "      <td>0.349938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>7.288074</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.071429</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-1.248642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>112.414642</td>\n",
       "      <td>4.056820</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.305642</td>\n",
       "      <td>0.009803</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.133333</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>297.750000</td>\n",
       "      <td>0.469529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>114.556490</td>\n",
       "      <td>7.062526</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>11.000000</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.331219</td>\n",
       "      <td>0.016236</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.142857</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>591.500000</td>\n",
       "      <td>0.717732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>115.701686</td>\n",
       "      <td>10.572719</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0.363723</td>\n",
       "      <td>0.023263</td>\n",
       "      <td>1.262177e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.166667</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>913.250000</td>\n",
       "      <td>0.914259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>125.266735</td>\n",
       "      <td>49.945876</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>13.000000</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.508755</td>\n",
       "      <td>0.052059</td>\n",
       "      <td>5.048710e-29</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.235294</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1320.000000</td>\n",
       "      <td>1.594346</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8 rows × 31 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                cn   theta_mean    theta_std  local_density   density_2A  \\\n",
       "count  1092.000000  1092.000000  1092.000000    1092.000000  1092.000000   \n",
       "mean      2.999084   107.739479     9.489334      28.945971     3.999084   \n",
       "std       0.030261    19.389291     8.863510       1.507030     0.030261   \n",
       "min       2.000000     7.288074     0.000000      25.000000     3.000000   \n",
       "25%       3.000000   112.414642     4.056820      28.000000     4.000000   \n",
       "50%       3.000000   114.556490     7.062526      29.000000     4.000000   \n",
       "75%       3.000000   115.701686    10.572719      30.000000     4.000000   \n",
       "max       3.000000   125.266735    49.945876      34.000000     4.000000   \n",
       "\n",
       "        density_3A   density_5A       height    curvature     planarity  ...  \\\n",
       "count  1092.000000  1092.000000  1092.000000  1092.000000  1.092000e+03  ...   \n",
       "mean     11.484432    28.945971     0.338648     0.017366  4.476954e-30  ...   \n",
       "std       0.894394     1.507030     0.050730     0.010356  6.118696e-30  ...   \n",
       "min       9.000000    25.000000     0.000000     0.000000  0.000000e+00  ...   \n",
       "25%      11.000000    28.000000     0.305642     0.009803  0.000000e+00  ...   \n",
       "50%      11.000000    29.000000     0.331219     0.016236  0.000000e+00  ...   \n",
       "75%      12.000000    30.000000     0.363723     0.023263  1.262177e-29  ...   \n",
       "max      13.000000    34.000000     0.508755     0.052059  5.048710e-29  ...   \n",
       "\n",
       "       local_rings_3  local_rings_4  local_rings_5  local_rings_6  \\\n",
       "count         1092.0         1092.0    1092.000000    1092.000000   \n",
       "mean             0.0            0.0       1.472527       2.132784   \n",
       "std              0.0            0.0       0.972668       0.940847   \n",
       "min              0.0            0.0       0.000000       0.000000   \n",
       "25%              0.0            0.0       1.000000       2.000000   \n",
       "50%              0.0            0.0       1.000000       2.000000   \n",
       "75%              0.0            0.0       2.000000       3.000000   \n",
       "max              0.0            0.0       5.000000       5.000000   \n",
       "\n",
       "       local_rings_7  local_hexagons  rings_per_atom  smallest_ring  \\\n",
       "count    1092.000000     1092.000000     1092.000000    1092.000000   \n",
       "mean        0.647436        2.132784        0.146217       6.152015   \n",
       "std         0.731172        0.940847        0.027587       0.359200   \n",
       "min         0.000000        0.000000        0.071429       6.000000   \n",
       "25%         0.000000        2.000000        0.133333       6.000000   \n",
       "50%         1.000000        2.000000        0.142857       6.000000   \n",
       "75%         1.000000        3.000000        0.166667       6.000000   \n",
       "max         3.000000        5.000000        0.235294       7.000000   \n",
       "\n",
       "                id       ΔG(eV)  \n",
       "count  1092.000000  1092.000000  \n",
       "mean    615.975275     0.677213  \n",
       "std     371.942588     0.349938  \n",
       "min       1.000000    -1.248642  \n",
       "25%     297.750000     0.469529  \n",
       "50%     591.500000     0.717732  \n",
       "75%     913.250000     0.914259  \n",
       "max    1320.000000     1.594346  \n",
       "\n",
       "[8 rows x 31 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove rows where deltaG < -1.5 (keep deltaG >= -1.5)\n",
    "df = df[df['ΔG(eV)'] >= -1.5]\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6be7e002-1429-45e4-991a-288c06673cea",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "════════════════════════════════════════════════════════════\n",
      "  ANALYSIS  :  POSCAR_014_relaxed\n",
      "════════════════════════════════════════════════════════════\n",
      "\n",
      "  H  atom index : 895\n",
      "  Nearest C     : 484\n",
      "\n",
      "  Ring features\n",
      "  ────────────────────────────────────────\n",
      "  local_rings_3_8        6\n",
      "  local_rings_3          0\n",
      "  local_rings_4          0\n",
      "  local_rings_5          2\n",
      "  local_rings_6          3\n",
      "  local_rings_7          1\n",
      "  local_rings_8          0\n",
      "  local_hexagons         3\n",
      "  rings_per_atom         0.2069\n",
      "  smallest_ring          5\n",
      "  local_atoms_count      29\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1350x1200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  ✓  Saved → ring_statistics_POSCAR_014_relaxed.png\n",
      "\n",
      "  ──────────────────────────────────────────────────────\n",
      "  FILE      : POSCAR_014_relaxed\n",
      "  Nearest C : atom #484\n",
      "  Shell N   : 29  (r < 5.0 Å)\n",
      "  Surface z : 19.943 Å\n",
      "  Ads-C z   : 19.458 Å  Δz = -0.48 Å\n",
      "  ──────────────────────────────────────────────────────\n",
      "  ✓  Saved → density_POSCAR_014_relaxed_r5.0.png\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2400x1050 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "════════════════════════════════════════════════════════════\n",
      "  Done.\n",
      "════════════════════════════════════════════════════════════\n",
      "\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "╔══════════════════════════════════════════════════════════════════════╗\n",
    "║         LOCAL RING STATISTICS & DENSITY ENVIRONMENT ANALYSIS        ║\n",
    "║         Amorphous Carbon Surface — H* Adsorption Site Analysis      ║\n",
    "╚══════════════════════════════════════════════════════════════════════╝\n",
    "\"\"\"\n",
    "\n",
    "import glob\n",
    "import warnings\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as ticker\n",
    "from matplotlib.patches import Circle, FancyArrowPatch\n",
    "from matplotlib.colors import LinearSegmentedColormap\n",
    "from matplotlib.gridspec import GridSpec\n",
    "from ase.io import read\n",
    "from matscipy.rings import ring_statistics\n",
    "\n",
    "warnings.filterwarnings(\"ignore\")\n",
    "\n",
    "# ── Palette ────────────────────────────────────────────────────────────────── #\n",
    "DARK_BG    = \"white\"\n",
    "PANEL_BG   = \"white\"\n",
    "BORDER     = \"black\"\n",
    "TEXT_PRI   = \"black\"\n",
    "TEXT_SEC   = \"black\"\n",
    "ACCENT_G   = \"#3fb950\"   # green  — adsorption site\n",
    "ACCENT_P   = \"#bc8cff\"   # purple — density shell\n",
    "ACCENT_Y   = \"#f0c43f\"   # gold   — H* adsorbate\n",
    "ACCENT_B   = \"#58a6ff\"   # blue   — ring bars / general atoms\n",
    "RED        = \"#ff7b72\"\n",
    "TEAL       = \"#39d0d8\"\n",
    "\n",
    "RING_COLORS = {\n",
    "    3: \"#ff6b6b\",   # 3-ring  — red (strained)\n",
    "    4: \"#ff9f43\",   # 4-ring  — orange\n",
    "    5: \"#feca57\",   # 5-ring  — yellow\n",
    "    6: \"#48dbfb\",   # 6-ring  — teal (graphitic)\n",
    "    7: \"#ff6bcb\",   # 7-ring  — pink\n",
    "    8: \"#a29bfe\",   # 8-ring  — lavender\n",
    "}\n",
    "\n",
    "RING_LABELS = {\n",
    "    3: \"Triangles\",\n",
    "    4: \"Squares\",\n",
    "    5: \"Pentagons\",\n",
    "    6: \"Hexagons\",\n",
    "    7: \"Heptagons\",\n",
    "    8: \"Octagons\",\n",
    "}\n",
    "\n",
    "# Custom diverging colormap for height\n",
    "HEIGHT_CMAP = LinearSegmentedColormap.from_list(\n",
    "    \"height\", [\"#ff7b72\", \"#f0c43f\", \"#3fb950\", \"#58a6ff\"], N=256\n",
    ")\n",
    "\n",
    "# ── Global Matplotlib Style ─────────────────────────────────────────────────── #\n",
    "def apply_dark_style():\n",
    "    plt.rcParams.update({\n",
    "        \"figure.facecolor\":     DARK_BG,\n",
    "        \"axes.facecolor\":       PANEL_BG,\n",
    "        \"axes.edgecolor\":       BORDER,\n",
    "        \"axes.labelcolor\":      TEXT_PRI,\n",
    "        \"axes.titlecolor\":      TEXT_PRI,\n",
    "        \"axes.titlesize\":       20,\n",
    "        \"axes.labelsize\":       20,\n",
    "        \"axes.titlepad\":        12,\n",
    "        \"axes.grid\":            True,\n",
    "        \"grid.color\":           BORDER,\n",
    "        \"grid.linestyle\":       \"--\",\n",
    "        \"grid.linewidth\":       0.5,\n",
    "        \"grid.alpha\":           0.5,\n",
    "        \"xtick.color\":          TEXT_SEC,\n",
    "        \"ytick.color\":          TEXT_SEC,\n",
    "        \"xtick.labelsize\":      20,\n",
    "        \"ytick.labelsize\":      20,\n",
    "        \"text.color\":           TEXT_PRI,\n",
    "        \"legend.facecolor\":     PANEL_BG,\n",
    "        \"legend.edgecolor\":     BORDER,\n",
    "        \"legend.fontsize\":      15,\n",
    "        \"figure.dpi\":           150,\n",
    "        \"savefig.dpi\":          500,\n",
    "        \"savefig.facecolor\":    DARK_BG,\n",
    "        \"savefig.bbox\":         \"tight\",\n",
    "        \"font.family\":          \"serif\",\n",
    "        \"font.serif\":           \"Times New Roman\",\n",
    "        \"font.weight\":          \"bold\"\n",
    "    })\n",
    "\n",
    "apply_dark_style()\n",
    "\n",
    "\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "#  RING FEATURE EXTRACTION                                                       #\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "\n",
    "def matscipy_ring_features(atoms, nearest_c, cutoff=1.6):\n",
    "    \"\"\"\n",
    "    Compute local ring statistics within a 5 Å sphere centred on nearest_c.\n",
    "\n",
    "    Returns a flat dict with per-ring-size counts and derived descriptors.\n",
    "    \"\"\"\n",
    "    try:\n",
    "        pos      = atoms.positions\n",
    "        keep     = np.linalg.norm(pos - pos[nearest_c], axis=1) < 5.0\n",
    "        local    = atoms[keep]\n",
    "        raw      = ring_statistics(local, cutoff=cutoff, maxlength=8)\n",
    "\n",
    "        rings = [0.0] * 9\n",
    "        for i in range(3, min(9, len(raw))):\n",
    "            rings[i] = raw[i]\n",
    "\n",
    "        total         = float(np.sum(rings[3:9]))\n",
    "        rings_per_atm = total / len(local) if len(local) > 0 else 0.0\n",
    "        valid         = np.array(rings[3:9]) > 0\n",
    "        smallest      = int(np.argmax(valid) + 3) if np.any(valid) else 0\n",
    "\n",
    "        return {\n",
    "            \"local_rings_3_8\":   total,\n",
    "            \"local_rings_3\":     float(rings[3]),\n",
    "            \"local_rings_4\":     float(rings[4]),\n",
    "            \"local_rings_5\":     float(rings[5]),\n",
    "            \"local_rings_6\":     float(rings[6]),\n",
    "            \"local_rings_7\":     float(rings[7]),\n",
    "            \"local_rings_8\":     float(rings[8]),\n",
    "            \"local_hexagons\":    float(rings[6]),\n",
    "            \"rings_per_atom\":    rings_per_atm,\n",
    "            \"smallest_ring\":     float(smallest),\n",
    "            \"local_atoms_count\": float(len(local)),\n",
    "        }\n",
    "\n",
    "    except Exception as exc:\n",
    "        print(f\"  ⚠  Ring statistics error: {exc}\")\n",
    "        keys = [\n",
    "            \"local_rings_3_8\", \"local_rings_3\", \"local_rings_4\",\n",
    "            \"local_rings_5\",   \"local_rings_6\", \"local_rings_7\",\n",
    "            \"local_rings_8\",   \"local_hexagons\",\"rings_per_atom\",\n",
    "            \"smallest_ring\",   \"local_atoms_count\",\n",
    "        ]\n",
    "        return dict.fromkeys(keys, 0.0)\n",
    "\n",
    "\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "#  RING STATISTICS CHART                                                         #\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "\n",
    "def plot_ring_statistics(ring_feats, filename=\"\"):\n",
    "    ring_sizes = list(range(3, 9))\n",
    "    counts     = [ring_feats[f\"local_rings_{n}\"] for n in ring_sizes]\n",
    "    colors     = [RING_COLORS[n] for n in ring_sizes]\n",
    "    labels     = [RING_LABELS[n] for n in ring_sizes]\n",
    "    total      = ring_feats[\"local_rings_3_8\"]\n",
    "    n_atoms    = int(ring_feats[\"local_atoms_count\"])\n",
    "    smallest   = int(ring_feats[\"smallest_ring\"])\n",
    "\n",
    "    fig, ax = plt.subplots(figsize=(9, 8))\n",
    "    fig.suptitle(\n",
    "        \"Local Ring Statistics  ·  5 Å Neighbourhood\",\n",
    "        fontsize=16, fontweight=\"bold\", color=TEXT_PRI, y=1.01,\n",
    "    )\n",
    "\n",
    "    # Bars with individual colours\n",
    "    bars = ax.bar(\n",
    "        ring_sizes, counts,\n",
    "        color=colors, edgecolor=DARK_BG,\n",
    "        linewidth=1.2, width=0.65, zorder=3,\n",
    "    )\n",
    "\n",
    "    # Value labels on top of each bar\n",
    "    for bar, cnt in zip(bars, counts):\n",
    "        if cnt > 0:\n",
    "            ax.text(\n",
    "                bar.get_x() + bar.get_width() / 2,\n",
    "                bar.get_height() + 0.05,\n",
    "                f\"{int(cnt)}\",\n",
    "                ha=\"center\", va=\"bottom\",\n",
    "                fontsize=18, fontweight=\"bold\", color=TEXT_PRI,\n",
    "            )\n",
    "\n",
    "    # Highlight smallest ring\n",
    "    if 3 <= smallest <= 8:\n",
    "        ax.bar(\n",
    "            [smallest], [counts[smallest - 3]],\n",
    "            color=RING_COLORS[smallest], edgecolor=TEXT_PRI,\n",
    "            linewidth=2.0, width=0.65, zorder=4,\n",
    "            label=f\"Smallest ring  ({RING_LABELS[smallest]})\",\n",
    "        )\n",
    "\n",
    "    ax.set_xlabel(\"Ring size  (n-membered)\", labelpad=8, fontweight='bold', fontsize=22)\n",
    "    ax.set_ylabel(\"Count in local region\", fontweight='bold', fontsize=22)\n",
    "    ax.set_xticks(ring_sizes)\n",
    "#    ax.set_xticklabels([f\"{n}\\n{RING_LABELS[n]}\" for n in ring_sizes],\n",
    "#                       fontsize=15)\n",
    "    ax.yaxis.set_major_locator(ticker.MaxNLocator(integer=True))\n",
    "    ax.set_ylim(0, max(counts) * 1.4 if max(counts) > 0 else 5)\n",
    "\n",
    "    # Stat box (top-right)\n",
    "    stats_txt = (\n",
    "        f\"  Total rings : {int(total)}\\n\"\n",
    "        f\"  Local atoms : {n_atoms}\\n\"\n",
    "        f\"  Hexagonals  : {int(ring_feats['local_hexagons'])}\\n\"\n",
    "        f\"  Smallest    : {smallest if smallest else '—'}\"\n",
    "    )\n",
    "    ax.text(\n",
    "        0.96, 0.94, stats_txt,\n",
    "        transform=ax.transAxes,\n",
    "        va=\"top\", ha=\"right\",\n",
    "        fontsize=18, linespacing=1.7,\n",
    "        color=TEXT_PRI,\n",
    "        bbox=dict(\n",
    "            boxstyle=\"round,pad=0.6\",\n",
    "            facecolor=DARK_BG, edgecolor=BORDER, alpha=0.9,\n",
    "        ),\n",
    "    )\n",
    "\n",
    "    plt.tight_layout()\n",
    "    out = f\"ring_statistics_{filename}.png\"\n",
    "    plt.savefig(out)\n",
    "    plt.show()\n",
    "    print(f\"  ✓  Saved → {out}\")\n",
    "\n",
    "\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "#  DENSITY ENVIRONMENT MAP                                                       #\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "\n",
    "def plot_density_environment(filename, density_cutoff=5.0,\n",
    "                             save=True, surface_align=True):\n",
    "    \"\"\"\n",
    "    Two-panel figure (top view + side view) of the local atomic environment\n",
    "    around the H* adsorption site.  Uses mic=True for all distance queries.\n",
    "    \"\"\"\n",
    "    atoms = read(filename)\n",
    "\n",
    "    # ── Locate H and nearest C ──────────────────────────────────────────────\n",
    "    h_idx     = next(i for i, s in enumerate(atoms) if s.symbol == \"H\")\n",
    "    c_indices = np.where(np.array([s.symbol for s in atoms]) == \"C\")[0]\n",
    "\n",
    "    dvec_hc  = atoms.get_distances(h_idx, c_indices, mic=True, vector=True)\n",
    "    dist_hc  = np.linalg.norm(dvec_hc, axis=1)\n",
    "    nearest_c = c_indices[np.argmin(dist_hc)]\n",
    "\n",
    "    # ── Density shell (PBC-correct) ─────────────────────────────────────────\n",
    "    dvec_all  = atoms.get_distances(\n",
    "        nearest_c, np.arange(len(atoms)), mic=True, vector=True\n",
    "    )\n",
    "    dr        = np.linalg.norm(dvec_all, axis=1)\n",
    "    shell_idx = np.where(dr < density_cutoff)[0]\n",
    "    n_shell   = len(shell_idx)\n",
    "\n",
    "    # ── Surface alignment ───────────────────────────────────────────────────\n",
    "    pos = atoms.positions.copy()\n",
    "    surface_z = np.median(pos[:, 2])\n",
    "    center    = pos[nearest_c].copy()\n",
    "\n",
    "    if surface_align:\n",
    "        pos[:, 2]  -= surface_z\n",
    "        center[2]  -= surface_z\n",
    "        dz_lbl = f\"Δz = {atoms.positions[nearest_c, 2] - surface_z:+.2f} Å\"\n",
    "    else:\n",
    "        dz_lbl = \"\"\n",
    "\n",
    "    # ── Console summary ─────────────────────────────────────────────────────\n",
    "    print(f\"\\n  {'─'*54}\")\n",
    "    print(f\"  FILE      : {filename}\")\n",
    "    print(f\"  Nearest C : atom #{nearest_c}\")\n",
    "    print(f\"  Shell N   : {n_shell}  (r < {density_cutoff} Å)\")\n",
    "    print(f\"  Surface z : {surface_z:.3f} Å\")\n",
    "    print(f\"  Ads-C z   : {atoms.positions[nearest_c, 2]:.3f} Å  {dz_lbl}\")\n",
    "    print(f\"  {'─'*54}\")\n",
    "\n",
    "    # ── Figure layout ───────────────────────────────────────────────────────\n",
    "    fig = plt.figure(figsize=(16, 7))\n",
    "    gs  = GridSpec(\n",
    "        1, 2, figure=fig,\n",
    "        wspace=0.06, left=0.04, right=0.96,\n",
    "        top=0.88, bottom=0.1,\n",
    "    )\n",
    "    ax1 = fig.add_subplot(gs[0])   # top view\n",
    "    ax2 = fig.add_subplot(gs[1])   # side view\n",
    "\n",
    "    fig.suptitle(\n",
    "        f\"Density Environment  ·  {filename}  ·  r < {density_cutoff} Å\",\n",
    "        fontsize=16, fontweight=\"bold\", color=TEXT_PRI,\n",
    "    )\n",
    "\n",
    "    shell_pos = pos[shell_idx]\n",
    "    z_vals    = pos[:, 2]\n",
    "    v_min, v_max = np.percentile(z_vals, 5), np.percentile(z_vals, 95)\n",
    "\n",
    "    # ── (a) Top view ─────────────────────────────────────────────────────── #\n",
    "    # Background atoms (all)\n",
    "    sc_bg = ax1.scatter(\n",
    "        pos[:, 0], pos[:, 1],\n",
    "        c=pos[:, 2], cmap=HEIGHT_CMAP,\n",
    "        vmin=v_min, vmax=v_max,\n",
    "        s=18, alpha=0.45, linewidths=0, zorder=2,\n",
    "    )\n",
    "\n",
    "    # Density shell atoms\n",
    "    ax1.scatter(\n",
    "        shell_pos[:, 0], shell_pos[:, 1],\n",
    "        c=ACCENT_P, s=35, alpha=0.8,\n",
    "        edgecolors=DARK_BG, linewidths=0.5,\n",
    "         zorder=3,\n",
    "    )\n",
    "\n",
    "    # Adsorption-site carbon\n",
    "    ax1.scatter(\n",
    "        center[0], center[1],\n",
    "        c=ACCENT_G, s=120, marker=\"o\",\n",
    "        edgecolors=TEXT_PRI, linewidths=1.5, zorder=5,\n",
    "    )\n",
    "\n",
    "    # H* adsorbate\n",
    "    ax1.scatter(\n",
    "        pos[h_idx, 0], pos[h_idx, 1],\n",
    "        c=ACCENT_Y, s=140, marker=\"*\",\n",
    "        edgecolors=\"black\", linewidths=1.2, zorder=5,\n",
    "    )\n",
    "\n",
    "    # Cutoff circle\n",
    "    circ = Circle(\n",
    "        (center[0], center[1]), density_cutoff,\n",
    "        fill=False, linestyle=\"--\",\n",
    "        edgecolor=ACCENT_G, linewidth=1.4, alpha=0.8, zorder=4,\n",
    "    )\n",
    "    ax1.add_patch(circ)\n",
    "\n",
    "    cb = plt.colorbar(sc_bg, ax=ax1, pad=0.01, shrink=0.9)\n",
    "    cb.set_label(\"Z-height [Å]\", fontsize=16, fontweight='bold', color=TEXT_SEC, labelpad=-5)\n",
    "    cb.ax.yaxis.set_tick_params(color=TEXT_SEC)\n",
    "    plt.setp(cb.ax.yaxis.get_ticklabels(), color=TEXT_SEC, fontsize=15)\n",
    "\n",
    "    ax1.set_title(\n",
    "        f\"(a)  Top View  —  Density = {n_shell}  {dz_lbl}\",\n",
    "        fontsize=16, color=TEXT_PRI, pad=8,\n",
    "    )\n",
    "    ax1.set_xlabel(\"x  [Å]\", fontsize=16, fontweight='bold'); ax1.set_ylabel(\"y  [Å]\", fontsize=16, fontweight='bold')\n",
    "    ax1.set_aspect(\"equal\")\n",
    "    ax1.legend(loc=\"lower right\", markerscale=1.1, framealpha=0.85)\n",
    "\n",
    "    # ── (b) Side view ─────────────────────────────────────────────────────── #\n",
    "    ax2.scatter(\n",
    "        pos[:, 0], pos[:, 2],\n",
    "        c=TEXT_SEC, s=14, alpha=0.4,\n",
    "        linewidths=0, zorder=2,\n",
    "    )\n",
    "\n",
    "    ax2.scatter(\n",
    "        shell_pos[:, 0], shell_pos[:, 2],\n",
    "        c=ACCENT_P, s=32, alpha=0.85,\n",
    "        edgecolors=DARK_BG, linewidths=0.5,\n",
    "        label=f\"Local atoms = {n_shell}\", zorder=3,\n",
    "    )\n",
    "\n",
    "    ax2.scatter(\n",
    "        center[0], center[2],\n",
    "        c=ACCENT_G, s=120, marker=\"o\",\n",
    "        edgecolors=TEXT_PRI, linewidths=1.5,\n",
    "        label=\"Ads. C\", zorder=5,\n",
    "    )\n",
    "\n",
    "    ax2.scatter(\n",
    "        pos[h_idx, 0], pos[h_idx, 2],\n",
    "        c=ACCENT_Y, s=140, marker=\"*\",\n",
    "        edgecolors=\"black\", linewidths=1.2,\n",
    "        label=\"H*\", zorder=5,\n",
    "    )\n",
    "\n",
    "    # Surface reference line\n",
    "    ax2.axhline(0, color=TEAL, lw=1.2, linestyle=\":\", alpha=0.7,\n",
    "                label=\"Surface (z = 0)\")\n",
    "\n",
    "    ax2.set_title(\"(b)  Side View  (x–z plane)\", fontsize=16, color=TEXT_PRI, pad=8)\n",
    "    ax2.set_xlabel(\"x  [Å]\", fontsize=16, fontweight='bold'); ax2.set_ylabel(\"z  [Å]\", fontsize=16, fontweight='bold', labelpad=-8)\n",
    "    ax2.legend(loc=\"upper right\", markerscale=1.1, framealpha=0.85)\n",
    "\n",
    "    plt.tight_layout()\n",
    "\n",
    "    if save:\n",
    "        out = f\"density_{filename}_r{density_cutoff:.1f}.png\"\n",
    "        plt.savefig(out)\n",
    "        print(f\"  ✓  Saved → {out}\")\n",
    "\n",
    "    plt.show()\n",
    "    return n_shell\n",
    "\n",
    "\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "#  ENTRY POINT                                                                   #\n",
    "# ══════════════════════════════════════════════════════════════════════════════ #\n",
    "\n",
    "def main(filename=\"POSCAR_014_relaxed\", density_cutoff=5.0):\n",
    "    print(f\"\\n{'═'*60}\")\n",
    "    print(f\"  ANALYSIS  :  {filename}\")\n",
    "    print(f\"{'═'*60}\\n\")\n",
    "\n",
    "    atoms = read(filename)\n",
    "\n",
    "    # ── Find H and nearest C ────────────────────────────────────────────────\n",
    "    h_indices = [i for i, s in enumerate(atoms) if s.symbol == \"H\"]\n",
    "    if not h_indices:\n",
    "        print(\"  ✗  No H atoms found in structure.\")\n",
    "        return\n",
    "\n",
    "    h_idx     = h_indices[0]\n",
    "    c_indices = [i for i, s in enumerate(atoms) if s.symbol == \"C\"]\n",
    "\n",
    "    dvec = atoms.get_distances(h_idx, c_indices, mic=True, vector=True)\n",
    "    dist = np.linalg.norm(dvec, axis=1)\n",
    "    nearest_c = c_indices[np.argmin(dist)]\n",
    "\n",
    "    print(f\"  H  atom index : {h_idx}\")\n",
    "    print(f\"  Nearest C     : {nearest_c}\")\n",
    "\n",
    "    # ── Ring features ───────────────────────────────────────────────────────\n",
    "    ring_feats = matscipy_ring_features(atoms, nearest_c)\n",
    "\n",
    "    print(\"\\n  Ring features\")\n",
    "    print(f\"  {'─'*40}\")\n",
    "    for k, v in ring_feats.items():\n",
    "        print(f\"  {k:<22} {v:.4g}\")\n",
    "\n",
    "    # ── Plots ───────────────────────────────────────────────────────────────\n",
    "    plot_ring_statistics(ring_feats, filename=filename)\n",
    "    plot_density_environment(filename, density_cutoff=density_cutoff)\n",
    "\n",
    "    print(f\"\\n{'═'*60}\")\n",
    "    print(\"  Done.\")\n",
    "    print(f\"{'═'*60}\\n\")\n",
    "\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    main()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f512940b-e45d-4cfb-a4ab-aa99782f47eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['cn', 'theta_mean', 'theta_std', 'local_density', 'density_2A',\n",
      "       'density_3A', 'density_5A', 'height', 'curvature', 'planarity',\n",
      "       'bond_var', 'q6_order', 'surface_cn', 'neighbor_cn_var', 'h_bond_dist',\n",
      "       'total_rings_3_8', 'global_rings_4', 'global_rings_5', 'global_rings_6',\n",
      "       'global_rings_7', 'local_rings_3_8', 'local_rings_3', 'local_rings_4',\n",
      "       'local_rings_5', 'local_rings_6', 'local_rings_7', 'local_hexagons',\n",
      "       'rings_per_atom', 'smallest_ring', 'filename', 'id', 'ΔG(eV)'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "print(df.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1821ee97-12b0-41ef-9bbf-525a45744181",
   "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>cn</th>\n",
       "      <th>theta_mean</th>\n",
       "      <th>theta_std</th>\n",
       "      <th>local_density</th>\n",
       "      <th>height</th>\n",
       "      <th>curvature</th>\n",
       "      <th>q6_order</th>\n",
       "      <th>neighbor_cn_var</th>\n",
       "      <th>local_rings_5</th>\n",
       "      <th>local_rings_6</th>\n",
       "      <th>local_rings_7</th>\n",
       "      <th>smallest_ring</th>\n",
       "      <th>ΔG(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3.0</td>\n",
       "      <td>115.565384</td>\n",
       "      <td>1.707292</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.320549</td>\n",
       "      <td>0.011338</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.869249</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3.0</td>\n",
       "      <td>114.585619</td>\n",
       "      <td>9.408976</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.336314</td>\n",
       "      <td>0.008966</td>\n",
       "      <td>0.572803</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.430614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3.0</td>\n",
       "      <td>116.300221</td>\n",
       "      <td>7.520467</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.295069</td>\n",
       "      <td>0.008167</td>\n",
       "      <td>0.714958</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.541070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3.0</td>\n",
       "      <td>111.062209</td>\n",
       "      <td>4.915973</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.420566</td>\n",
       "      <td>0.013560</td>\n",
       "      <td>0.871863</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.328253</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.0</td>\n",
       "      <td>114.849125</td>\n",
       "      <td>9.807015</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.272271</td>\n",
       "      <td>0.007583</td>\n",
       "      <td>0.538613</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.455718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1311</th>\n",
       "      <td>3.0</td>\n",
       "      <td>88.009735</td>\n",
       "      <td>32.485552</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.300370</td>\n",
       "      <td>0.026127</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.730210</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1313</th>\n",
       "      <td>3.0</td>\n",
       "      <td>78.922273</td>\n",
       "      <td>29.053511</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.474257</td>\n",
       "      <td>0.001131</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>-0.097057</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1316</th>\n",
       "      <td>3.0</td>\n",
       "      <td>97.291226</td>\n",
       "      <td>31.677428</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.349768</td>\n",
       "      <td>0.004020</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>-0.153311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1317</th>\n",
       "      <td>3.0</td>\n",
       "      <td>113.747866</td>\n",
       "      <td>8.663664</td>\n",
       "      <td>29.0</td>\n",
       "      <td>0.367615</td>\n",
       "      <td>0.021534</td>\n",
       "      <td>0.630537</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.432398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1319</th>\n",
       "      <td>3.0</td>\n",
       "      <td>110.387013</td>\n",
       "      <td>6.244154</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.462149</td>\n",
       "      <td>0.003764</td>\n",
       "      <td>0.797768</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>0.212444</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1092 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       cn  theta_mean  theta_std  local_density    height  curvature  \\\n",
       "0     3.0  115.565384   1.707292           28.0  0.320549   0.011338   \n",
       "1     3.0  114.585619   9.408976           29.0  0.336314   0.008966   \n",
       "2     3.0  116.300221   7.520467           29.0  0.295069   0.008167   \n",
       "3     3.0  111.062209   4.915973           30.0  0.420566   0.013560   \n",
       "4     3.0  114.849125   9.807015           29.0  0.272271   0.007583   \n",
       "...   ...         ...        ...            ...       ...        ...   \n",
       "1311  3.0   88.009735  32.485552           30.0  0.300370   0.026127   \n",
       "1313  3.0   78.922273  29.053511           28.0  0.474257   0.001131   \n",
       "1316  3.0   97.291226  31.677428           29.0  0.349768   0.004020   \n",
       "1317  3.0  113.747866   8.663664           29.0  0.367615   0.021534   \n",
       "1319  3.0  110.387013   6.244154           28.0  0.462149   0.003764   \n",
       "\n",
       "      q6_order  neighbor_cn_var  local_rings_5  local_rings_6  local_rings_7  \\\n",
       "0     0.950000              0.0            0.0            3.0            0.0   \n",
       "1     0.572803              0.0            1.0            2.0            1.0   \n",
       "2     0.714958              0.0            2.0            1.0            2.0   \n",
       "3     0.871863              0.0            0.0            3.0            2.0   \n",
       "4     0.538613              0.0            3.0            1.0            1.0   \n",
       "...        ...              ...            ...            ...            ...   \n",
       "1311  0.950000              0.0            2.0            1.0            2.0   \n",
       "1313  0.950000              0.0            2.0            2.0            1.0   \n",
       "1316  0.950000              0.0            0.0            3.0            1.0   \n",
       "1317  0.630537              0.0            1.0            3.0            0.0   \n",
       "1319  0.797768              0.0            0.0            3.0            0.0   \n",
       "\n",
       "      smallest_ring    ΔG(eV)  \n",
       "0               7.0  0.869249  \n",
       "1               6.0  0.430614  \n",
       "2               6.0  0.541070  \n",
       "3               7.0  0.328253  \n",
       "4               6.0  0.455718  \n",
       "...             ...       ...  \n",
       "1311            6.0  0.730210  \n",
       "1313            6.0 -0.097057  \n",
       "1316            7.0 -0.153311  \n",
       "1317            6.0  0.432398  \n",
       "1319            7.0  0.212444  \n",
       "\n",
       "[1092 rows x 13 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = df.drop(['id', 'filename', 'total_rings_3_8','global_rings_4', 'global_rings_5', 'global_rings_6', 'bond_var', 'global_rings_7', 'surface_cn', 'local_hexagons', 'density_2A','density_3A', 'density_5A', 'surface_cn', 'h_bond_dist', 'local_rings_3',  'local_rings_4','local_hexagons', 'rings_per_atom', 'planarity', 'local_rings_3_8'], axis=1)\n",
    "df1 = df.dropna(subset=['ΔG(eV)'])\n",
    "df2 = df1.drop(['ΔG(eV)'], axis=1)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "2ef79e1d-b63d-469d-82f1-309a077597ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='cn', ylabel='ΔG(eV)'>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 960x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df1.plot.scatter('cn', 'ΔG(eV)') "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4c091218-c02f-455f-a097-9c9269af5b66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import pandas as pd\n",
    "\n",
    "mpl.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "mpl.rcParams[\"font.size\"] = 14\n",
    "\n",
    "rename_map = {\n",
    "    \"cn\": \"Coordination Number (CN)\",\n",
    "    \"theta_mean\": \"Mean Angle\",\n",
    "    \"theta_std\": \"Angle std\",\n",
    "    \"local_density\": \"Local Density\",\n",
    "    \"height\": \"Nearest C mean height\",\n",
    "    \"q6_order\": \"Hexagonal order\",\n",
    "    \"neighbor_cn_var\": \"Neighbor CN variation\",\n",
    "    \"local_rings_6\": \"6-membered rings\",\n",
    "    \"local_rings_5\": \"5-membered rings\",\n",
    "    \"local_rings_7\": \"7-membered rings\",\n",
    "    \"curvature\": \"Curvature\",\n",
    "    \"smallest_ring\": \"Smallest ring\",\n",
    "}\n",
    "\n",
    "df_renamed = df2.rename(columns=rename_map)\n",
    "corr_matrix = df_renamed.corr(numeric_only=True)\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "fig.patch.set_facecolor(\"white\")\n",
    "\n",
    "sns.heatmap(\n",
    "    corr_matrix,\n",
    "    annot=True,\n",
    "    fmt=\".2f\",\n",
    "    cmap=\"coolwarm\",\n",
    "    vmin=-1, vmax=1,\n",
    "    center=0,\n",
    "    square=True,\n",
    "    linewidths=0.4,\n",
    "    annot_kws={\"size\": 10, \"family\": \"Times New Roman\"},\n",
    "    ax=ax,\n",
    ")\n",
    "\n",
    "ax.set_title(\"Correlation Matrix\", fontsize=14, fontweight=\"bold\", pad=14)\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha=\"right\", fontsize=12)\n",
    "ax.set_yticklabels(ax.get_yticklabels(), rotation=0, fontsize=12)\n",
    "\n",
    "cbar = ax.collections[0].colorbar\n",
    "cbar.ax.tick_params(labelsize=11)\n",
    "for label in cbar.ax.get_yticklabels():\n",
    "    label.set_fontfamily(\"Times New Roman\")\n",
    "cbar.set_label(\"Pearson Correlation Coefficient\", fontsize=16, fontfamily=\"Times New Roman\")  # ← added\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"correlation_viridis.png\", dpi=500, bbox_inches=\"tight\",\n",
    "            facecolor=fig.get_facecolor())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cf1368f4-a29e-4c43-bc4c-b19e6deb131a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib as mpl\n",
    "\n",
    "mpl.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "mpl.rcParams[\"font.weight\"] = \"bold\"        # makes tick labels bold\n",
    "mpl.rcParams[\"axes.labelweight\"] = \"bold\"   # makes axis labels bold\n",
    "\n",
    "target = \"ΔG(eV)\"\n",
    "corr = df1.corr(numeric_only=True)[target].drop(target).sort_values()\n",
    "\n",
    "rename_map = {\n",
    "    \"cn\": \"Coordination Number (CN)\",\n",
    "    \"theta_mean\": \"Mean Angle\",\n",
    "    \"theta_std\": \"Angle std\",\n",
    "    \"local_density\": \"Local Density\",\n",
    "    \"height\": \"Nearest C mean height\",\n",
    "    \"q6_order\": \"Hexagonal order\",\n",
    "    \"neighbor_cn_var\": \"Neighbor CN variation\",\n",
    "    \"local_rings_6\": \"6-membered rings\",\n",
    "    \"local_rings_5\": \"5-membered rings\",\n",
    "    \"local_rings_7\": \"7-membered rings\",\n",
    "    \"curvature\": \"Curvature\",\n",
    "    \"smallest_ring\": \"Smallest ring\",\n",
    "}\n",
    "corr.index = [rename_map.get(name, name) for name in corr.index]\n",
    "\n",
    "colors = [\"#D85A30\" if v < 0 else \"#1D9E75\" for v in corr.values]\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "fig.patch.set_facecolor(\"white\")\n",
    "ax.set_facecolor(\"white\")\n",
    "bars = ax.barh(corr.index, corr.values, color=colors, edgecolor=\"none\",\n",
    "               height=0.65, zorder=3)\n",
    "ax.axvline(0, color=\"#888780\", linewidth=0.8, linestyle=\"--\", zorder=2)\n",
    "ax.set_xlim(-1.1, 1.1)\n",
    "ax.xaxis.set_tick_params(labelsize=15, colors=\"black\")\n",
    "ax.yaxis.set_tick_params(labelsize=15, colors=\"black\")\n",
    "ax.set_xlabel(\"Pearson correlation coefficient\", fontsize=16, color=\"black\", labelpad=8, fontweight=\"bold\")\n",
    "\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(True)\n",
    "    spine.set_color(\"black\")\n",
    "    spine.set_linewidth(0.8)\n",
    "\n",
    "ax.xaxis.set_ticks_position(\"bottom\")\n",
    "\n",
    "for bar, val in zip(bars, corr.values):\n",
    "    pad = 0.025\n",
    "    ha = \"left\" if val >= 0 else \"right\"\n",
    "    x = val + pad if val >= 0 else val - pad\n",
    "    color = \"#0F6E56\" if val >= 0 else \"#993C1D\"\n",
    "    ax.text(x, bar.get_y() + bar.get_height() / 2,\n",
    "            f\"{val:.2f}\", va=\"center\", ha=ha, fontsize=14,\n",
    "            color=color, fontweight=\"700\")\n",
    "\n",
    "neg_patch = mpatches.Patch(color=\"#D85A30\", label=\"Negative correlation\")\n",
    "pos_patch = mpatches.Patch(color=\"#1D9E75\", label=\"Positive correlation\")\n",
    "ax.legend(handles=[neg_patch, pos_patch], frameon=False,\n",
    "          fontsize=13, loc=\"lower right\",\n",
    "          prop={\"family\": \"Times New Roman\", \"weight\": \"bold\", \"size\": 13})  # bold legend\n",
    "\n",
    "ax.set_title(f\"Feature correlation with {target}\",\n",
    "             fontsize=13, fontweight=\"700\", color=\"#2C2C2A\",\n",
    "             loc=\"left\", pad=14)\n",
    "ax.grid(False)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"target_correlation_bar.png\", dpi=500, bbox_inches=\"tight\",\n",
    "            facecolor=fig.get_facecolor())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "900befc7-49fb-4b67-96d5-db9fa76da2ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as mpl\n",
    "import pandas as pd\n",
    "import pingouin as pg\n",
    "\n",
    "mpl.rcParams[\"font.family\"] = \"Times New Roman\"\n",
    "mpl.rcParams[\"font.size\"] = 14\n",
    "\n",
    "rename_map = {\n",
    "    \"cn\": \"Coordination Number (CN)\",\n",
    "    \"theta_mean\": \"Mean Angle\",\n",
    "    \"theta_std\": \"Angle std\",\n",
    "    \"local_density\": \"Local Density\",\n",
    "    \"height\": \"Nearest C mean height\",\n",
    "    \"q6_order\": \"Hexagonal order\",\n",
    "    \"neighbor_cn_var\": \"Neighbor CN variation\",\n",
    "    \"local_rings_6\": \"6-membered rings\",\n",
    "    \"local_rings_5\": \"5-membered rings\",\n",
    "    \"local_rings_7\": \"7-membered rings\",\n",
    "    \"curvature\": \"Curvature\",\n",
    "    \"smallest_ring\": \"Smallest ring\",\n",
    "}\n",
    "\n",
    "df_renamed = df2.rename(columns=rename_map)\n",
    "cols = list(rename_map.values())\n",
    "\n",
    "# Build partial correlation matrix\n",
    "pcorr_matrix = pd.DataFrame(index=cols, columns=cols, dtype=float)\n",
    "for i, x in enumerate(cols):\n",
    "    for j, y in enumerate(cols):\n",
    "        if i == j:\n",
    "            pcorr_matrix.loc[x, y] = 1.0\n",
    "        else:\n",
    "            covariates = [c for c in cols if c not in (x, y)]\n",
    "            result = pg.partial_corr(data=df_renamed, x=x, y=y, covar=covariates)\n",
    "            pcorr_matrix.loc[x, y] = result[\"r\"].values[0]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(10, 8))\n",
    "fig.patch.set_facecolor(\"white\")\n",
    "sns.heatmap(\n",
    "    pcorr_matrix,\n",
    "    annot=True,\n",
    "    fmt=\".2f\",\n",
    "    cmap=\"coolwarm\",\n",
    "    vmin=-1, vmax=1,\n",
    "    center=0,\n",
    "    square=True,\n",
    "    linewidths=0.4,\n",
    "    annot_kws={\"size\": 10, \"family\": \"Times New Roman\"},\n",
    "    ax=ax,\n",
    ")\n",
    "ax.set_title(\"Partial Correlation Matrix\", fontsize=14, fontweight=\"bold\", pad=14)\n",
    "ax.set_xticklabels(ax.get_xticklabels(), rotation=45, ha=\"right\", fontsize=12)\n",
    "ax.set_yticklabels(ax.get_yticklabels(), rotation=0, fontsize=12)\n",
    "cbar = ax.collections[0].colorbar\n",
    "cbar.ax.tick_params(labelsize=11)\n",
    "for label in cbar.ax.get_yticklabels():\n",
    "    label.set_fontfamily(\"Times New Roman\")\n",
    "cbar.set_label(\"Partial Correlation Coefficient\", fontsize=16, fontfamily=\"Times New Roman\")\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"partial_correlation.png\", dpi=500, bbox_inches=\"tight\",\n",
    "            facecolor=fig.get_facecolor())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "d2ba2c93-0262-423f-a981-de0b328f7878",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pingouin as pg\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import matplotlib as mpl\n",
    "\n",
    "mpl.rcParams[\"font.family\"]    = \"Times New Roman\"\n",
    "mpl.rcParams[\"font.weight\"]    = \"bold\"\n",
    "mpl.rcParams[\"axes.labelweight\"] = \"bold\"\n",
    "\n",
    "target   = \"ΔG(eV)\"\n",
    "POS_COL  = \"#0F7B6C\"   # teal\n",
    "NEG_COL  = \"#B5192B\"   # crimson\n",
    "POS_LABEL_COL = \"#084D43\"\n",
    "NEG_LABEL_COL = \"#7A0D1B\"\n",
    "\n",
    "rename_map = {\n",
    "    \"cn\": \"Coordination Number (CN)\",\n",
    "    \"theta_mean\": \"Mean Angle\",\n",
    "    \"theta_std\": \"Angle std\",\n",
    "    \"local_density\": \"Local Density\",\n",
    "    \"height\": \"Nearest C mean height\",\n",
    "    \"q6_order\": \"Hexagonal order\",\n",
    "    \"neighbor_cn_var\": \"Neighbor CN variation\",\n",
    "    \"local_rings_6\": \"6-membered rings\",\n",
    "    \"local_rings_5\": \"5-membered rings\",\n",
    "    \"local_rings_7\": \"7-membered rings\",\n",
    "    \"curvature\": \"Curvature\",\n",
    "    \"smallest_ring\": \"Smallest ring\",\n",
    "}\n",
    "\n",
    "# ── Compute partial correlations ───────────────────────────────────\n",
    "features = [c for c in df1.select_dtypes(\"number\").columns if c != target]\n",
    "data     = df1[[target] + features].dropna()\n",
    "\n",
    "records = []\n",
    "for feat in features:\n",
    "    covariates = [f for f in features if f != feat]\n",
    "    result = pg.partial_corr(data=data, x=feat, y=target, covar=covariates)\n",
    "    records.append({\"feature\": feat, \"r\": result[\"r\"].values[0]})\n",
    "\n",
    "pcorr = (\n",
    "    pd.DataFrame(records)\n",
    "    .set_index(\"feature\")\n",
    "    .sort_values(\"r\")\n",
    ")\n",
    "pcorr.index = [rename_map.get(n, n) for n in pcorr.index]\n",
    "\n",
    "# ── Plot ───────────────────────────────────────────────────────────\n",
    "colors = [NEG_COL if v < 0 else POS_COL for v in pcorr[\"r\"]]\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 6))\n",
    "fig.patch.set_facecolor(\"white\")\n",
    "ax.set_facecolor(\"white\")\n",
    "\n",
    "bars = ax.barh(pcorr.index, pcorr[\"r\"], color=colors, edgecolor=\"none\",\n",
    "               height=0.65, zorder=3)\n",
    "\n",
    "ax.axvline(0, color=\"#888780\", linewidth=0.8, linestyle=\"--\", zorder=2)\n",
    "ax.set_xlim(-1.1, 1.1)\n",
    "ax.xaxis.set_tick_params(labelsize=15, colors=\"black\")\n",
    "ax.yaxis.set_tick_params(labelsize=15, colors=\"black\")\n",
    "ax.set_xlabel(\"Partial correlation coefficient\", fontsize=16, color=\"black\",\n",
    "               labelpad=8, fontweight=\"bold\")\n",
    "\n",
    "for spine in ax.spines.values():\n",
    "    spine.set_visible(True)\n",
    "    spine.set_color(\"black\")\n",
    "    spine.set_linewidth(0.8)\n",
    "\n",
    "ax.xaxis.set_ticks_position(\"bottom\")\n",
    "\n",
    "for bar, val in zip(bars, pcorr[\"r\"]):\n",
    "    pad = 0.025\n",
    "    ha  = \"left\"  if val >= 0 else \"right\"\n",
    "    x   = val + pad if val >= 0 else val - pad\n",
    "    col = POS_LABEL_COL if val >= 0 else NEG_LABEL_COL\n",
    "    ax.text(x, bar.get_y() + bar.get_height() / 2,\n",
    "            f\"{val:.2f}\", va=\"center\", ha=ha, fontsize=14,\n",
    "            color=col, fontweight=\"700\")\n",
    "\n",
    "neg_patch = mpatches.Patch(color=NEG_COL, label=\"Negative correlation\")\n",
    "pos_patch = mpatches.Patch(color=POS_COL, label=\"Positive correlation\")\n",
    "ax.legend(handles=[neg_patch, pos_patch], frameon=False,\n",
    "          loc=\"lower right\",\n",
    "          prop={\"family\": \"Times New Roman\", \"weight\": \"bold\", \"size\": 13})\n",
    "\n",
    "ax.set_title(f\"Partial feature correlation with {target}\\n(controlling for all other features)\",\n",
    "             fontsize=13, fontweight=\"700\", color=\"#2C2C2A\", loc=\"left\", pad=14)\n",
    "\n",
    "ax.grid(False)\n",
    "plt.tight_layout()\n",
    "plt.savefig(\"target_partial_correlation_bar.png\", dpi=500, bbox_inches=\"tight\",\n",
    "            facecolor=fig.get_facecolor())\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a746235b-7e35-460c-9cab-9c07e43c9356",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from matplotlib.colors import Normalize\n",
    "\n",
    "\n",
    "# ---------------- USER SETTINGS ----------------\n",
    "vars_of_interest = ['ΔG(eV)']\n",
    "plt.style.use('seaborn-v0_8-whitegrid')\n",
    "\n",
    "\n",
    "# ---------------- HELPERS ----------------\n",
    "def get_top_corrs_signed(var, corr_matrix, n=8):\n",
    "    return corr_matrix[var].sort_values(key=abs, ascending=False).drop(var).head(n)\n",
    "\n",
    "\n",
    "# ---------------- FIGURE ----------------\n",
    "fig, axes = plt.subplots(1, 3, figsize=(18, 6))\n",
    "plt.subplots_adjust(right=0.85, wspace=0.35)\n",
    "\n",
    "\n",
    "# ---------------- COLORMAP ----------------\n",
    "cmap = plt.get_cmap(\"coolwarm\")\n",
    "norm = Normalize(vmin=-1, vmax=1)\n",
    "\n",
    "\n",
    "# ---------------- BAR PLOTS ----------------\n",
    "for i, var in enumerate(vars_of_interest):\n",
    "    ax = axes[i]\n",
    "    top = get_top_corrs_signed(var, corr_matrix, 8)\n",
    "    y_pos = np.arange(len(top))\n",
    "\n",
    "    colors = cmap(norm(top.values))\n",
    "\n",
    "    ax.barh(\n",
    "        y_pos,\n",
    "        top.values,\n",
    "        height=0.7,\n",
    "        color=colors,\n",
    "        edgecolor='white',\n",
    "        linewidth=1.2,\n",
    "        alpha=0.9\n",
    "    )\n",
    "\n",
    "    # ---- UNIFORM LABEL STYLE ----\n",
    "    for j, (label, value) in enumerate(top.items()):\n",
    "        ax.text(\n",
    "            value, j, f'{value:.3f}',\n",
    "            ha='center', va='center',\n",
    "            fontweight='bold', fontsize=11,\n",
    "            color='white',\n",
    "            zorder=3,\n",
    "            bbox=dict(boxstyle='round,pad=0.15',\n",
    "                      facecolor='black', alpha=0.85)\n",
    "        )\n",
    "\n",
    "    ax.axvline(0, color='black', lw=2)\n",
    "    ax.set_xlim(-1.0, 1.0)\n",
    "    ax.set_xticks([-0.8, 0, 0.8])\n",
    "    ax.set_yticks(y_pos)\n",
    "    ax.set_yticklabels(top.index, fontweight='medium', fontsize=12)\n",
    "    ax.set_title(f'{var}', fontsize=14, fontweight='bold')\n",
    "    sns.despine(ax=ax, left=True)\n",
    "\n",
    "\n",
    "# ---------------- PROPER COLOR LEGEND ----------------\n",
    "cax = fig.add_axes([0.88, 0.2, 0.02, 0.6])\n",
    "\n",
    "gradient = np.linspace(-1, 1, 256).reshape(256, 1)\n",
    "cax.imshow(\n",
    "    gradient,\n",
    "    cmap=cmap,\n",
    "    origin='lower',\n",
    "    aspect='auto',\n",
    "    vmin=-1,\n",
    "    vmax=1\n",
    ")\n",
    "\n",
    "cax.set_xticks([])\n",
    "cax.set_yticks([-1, 0, 1])\n",
    "cax.set_yticklabels(['-1', '0', '+1'], fontsize=11)\n",
    "cax.set_title('r', fontsize=12, pad=8)\n",
    "\n",
    "cax.yaxis.tick_right()\n",
    "cax.tick_params(length=0)\n",
    "cax.spines['top'].set_visible(False)\n",
    "cax.spines['left'].set_visible(False)\n",
    "cax.spines['right'].set_visible(False)\n",
    "\n",
    "\n",
    "# ---------------- FINAL TOUCHES ----------------\n",
    "plt.suptitle('Signed Correlations (-1 to +1)', fontsize=16)\n",
    "plt.savefig('signed_correlations.png', dpi=500)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18e9dff7-182a-4f07-9ba6-a85167e184d5",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(df1.columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0b698ba0-0e7c-4baa-aba5-009236404c43",
   "metadata": {},
   "outputs": [],
   "source": [
    "#df1 = df1.drop(['deltaG_bin'], axis = 1)\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd  # assuming df1 exists\n",
    "\n",
    "# **EXACT SAME BINNING** as your matplotlib code\n",
    "interval = 0.50\n",
    "bins = np.arange(\n",
    "    np.floor(df1['ΔG(eV)'].min()/interval)*interval - interval/2, \n",
    "    np.ceil(df1['ΔG(eV)'].max()/interval)*interval + interval/2, \n",
    "    interval\n",
    ")\n",
    "\n",
    "# Create labels like your bins[:-1]\n",
    "bin_labels = [f\"{b:+.2f}\" for b in bins[:-1]]\n",
    "df1['deltaG_bin'] = pd.cut(df1['ΔG(eV)'], bins=bins, labels=bin_labels)\n",
    "\n",
    "print(f\"ΔG bins (0.50 eV): {len(bin_labels)} intervals\")\n",
    "print(df1['deltaG_bin'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "96103ba2-cff1-4bcf-af0e-61be781aa995",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "229ff288-0a7b-46fe-b5a2-ffb0e6e9f905",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df1.drop(['deltaG_bin'], axis = 1)\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# Your exact code (keeping binning)\n",
    "df1['deltaG_bin'] = pd.cut(df1['ΔG(eV)'], bins, labels=bin_labels)  # bins/bin_labels from above\n",
    "bin_totals = df1.groupby('deltaG_bin').size().reset_index(name='total_count')\n",
    "\n",
    "plot_data = []\n",
    "for _, row in bin_totals.iterrows():\n",
    "    bin_df = df1[df1['deltaG_bin'] == row['deltaG_bin']]\n",
    "    num_points = int(row['total_count'])\n",
    "    sampled_heights = np.random.choice(bin_df['height'], size=num_points, replace=True)\n",
    "    for h in sampled_heights:\n",
    "        plot_data.append({'deltaG_bin': row['deltaG_bin'], 'count': row['total_count'], 'height': h})\n",
    "\n",
    "plot_df = pd.DataFrame(plot_data)\n",
    "\n",
    "# **FORCE CONTINUOUS HUE**\n",
    "plt.figure(figsize=(12,12))\n",
    "sns.set_context(\"paper\")\n",
    "sns.set(style=\"darkgrid\", font_scale=1.5)\n",
    "\n",
    "# Use swarmplot directly (better continuous hue control)\n",
    "sns.swarmplot(\n",
    "    data=plot_df,\n",
    "    x=\"deltaG_bin\", \n",
    "    y=\"count\", \n",
    "    hue=\"height\",\n",
    "    palette=\"coolwarm\",  # Continuous colormap\n",
    "    size=6,              # Smaller for speed\n",
    "    legend=\"brief\"       # Compact legend\n",
    ")\n",
    "\n",
    "plt.axvline(len(bin_labels)//2 - 0.5, color='red', lw=2, ls='--', label='ΔG=0')  # Zero line\n",
    "plt.xlabel(\"ΔG (eV)\")\n",
    "plt.ylabel(\"# Sites per Bin\")\n",
    "plt.title(\"ΔG Bins: Site Counts (Continuous Height Hue)\", fontweight='bold')\n",
    "plt.xticks(rotation=90)\n",
    "plt.legend(title=\"Height (Å)\", bbox_to_anchor=(1.05, 1), loc='upper left')\n",
    "plt.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fe677e3e-1fab-46a5-bb05-dd2ad2f4a395",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1086b99-eb94-4d74-8081-ff84ccfda7da",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1.deltaG_bin"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6d58c965-812b-4d96-8f42-e601838bfc66",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Histogram + KDE (smooth curve)\n",
    "sns.histplot(data=df1, x='height', kde=True, bins=50)\n",
    "plt.title('Distribution of column_name')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "396efae1-bd90-45db-a981-d1d41f42eb71",
   "metadata": {},
   "outputs": [],
   "source": [
    "from scipy import stats\n",
    "import seaborn as sns\n",
    "\n",
    "# Q-Q plot (quantile-quantile) - checks normality\n",
    "stats.probplot(df1['ΔG(eV)'], dist=\"norm\", plot=plt)\n",
    "plt.title('Q-Q Plot: column vs Normal Distribution')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7bf33c2-de4e-4665-92fe-8fadb2d26b4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from pandas.plotting import lag_plot\n",
    "from statsmodels.graphics.tsaplots import plot_acf\n",
    "\n",
    "# Lag plot (time-delayed relationships)\n",
    "lag_plot(df1['ΔG(eV)'], lag=1)\n",
    "\n",
    "# Autocorrelation function\n",
    "plot_acf(df1['ΔG(eV)'], lags=20)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "87d1f2ad-53fa-40a5-8960-bdc8b8bb8e2e",
   "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>cn</th>\n",
       "      <th>theta_mean</th>\n",
       "      <th>theta_std</th>\n",
       "      <th>local_density</th>\n",
       "      <th>height</th>\n",
       "      <th>curvature</th>\n",
       "      <th>q6_order</th>\n",
       "      <th>neighbor_cn_var</th>\n",
       "      <th>local_rings_5</th>\n",
       "      <th>local_rings_6</th>\n",
       "      <th>local_rings_7</th>\n",
       "      <th>smallest_ring</th>\n",
       "      <th>ΔG(eV)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "      <td>1092.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.999084</td>\n",
       "      <td>107.739479</td>\n",
       "      <td>9.489334</td>\n",
       "      <td>28.945971</td>\n",
       "      <td>0.338648</td>\n",
       "      <td>0.017366</td>\n",
       "      <td>0.742716</td>\n",
       "      <td>0.002035</td>\n",
       "      <td>1.472527</td>\n",
       "      <td>2.132784</td>\n",
       "      <td>0.647436</td>\n",
       "      <td>6.152015</td>\n",
       "      <td>0.677213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.030261</td>\n",
       "      <td>19.389291</td>\n",
       "      <td>8.863510</td>\n",
       "      <td>1.507030</td>\n",
       "      <td>0.050730</td>\n",
       "      <td>0.010356</td>\n",
       "      <td>0.236610</td>\n",
       "      <td>0.021178</td>\n",
       "      <td>0.972668</td>\n",
       "      <td>0.940847</td>\n",
       "      <td>0.731172</td>\n",
       "      <td>0.359200</td>\n",
       "      <td>0.349938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>7.288074</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>25.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>-1.248642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>112.414642</td>\n",
       "      <td>4.056820</td>\n",
       "      <td>28.000000</td>\n",
       "      <td>0.305642</td>\n",
       "      <td>0.009803</td>\n",
       "      <td>0.608423</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.469529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>114.556490</td>\n",
       "      <td>7.062526</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.331219</td>\n",
       "      <td>0.016236</td>\n",
       "      <td>0.825076</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.717732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>115.701686</td>\n",
       "      <td>10.572719</td>\n",
       "      <td>30.000000</td>\n",
       "      <td>0.363723</td>\n",
       "      <td>0.023263</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>0.914259</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>125.266735</td>\n",
       "      <td>49.945876</td>\n",
       "      <td>34.000000</td>\n",
       "      <td>0.508755</td>\n",
       "      <td>0.052059</td>\n",
       "      <td>0.950000</td>\n",
       "      <td>0.222222</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.594346</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                cn   theta_mean    theta_std  local_density       height  \\\n",
       "count  1092.000000  1092.000000  1092.000000    1092.000000  1092.000000   \n",
       "mean      2.999084   107.739479     9.489334      28.945971     0.338648   \n",
       "std       0.030261    19.389291     8.863510       1.507030     0.050730   \n",
       "min       2.000000     7.288074     0.000000      25.000000     0.000000   \n",
       "25%       3.000000   112.414642     4.056820      28.000000     0.305642   \n",
       "50%       3.000000   114.556490     7.062526      29.000000     0.331219   \n",
       "75%       3.000000   115.701686    10.572719      30.000000     0.363723   \n",
       "max       3.000000   125.266735    49.945876      34.000000     0.508755   \n",
       "\n",
       "         curvature     q6_order  neighbor_cn_var  local_rings_5  \\\n",
       "count  1092.000000  1092.000000      1092.000000    1092.000000   \n",
       "mean      0.017366     0.742716         0.002035       1.472527   \n",
       "std       0.010356     0.236610         0.021178       0.972668   \n",
       "min       0.000000     0.000000         0.000000       0.000000   \n",
       "25%       0.009803     0.608423         0.000000       1.000000   \n",
       "50%       0.016236     0.825076         0.000000       1.000000   \n",
       "75%       0.023263     0.950000         0.000000       2.000000   \n",
       "max       0.052059     0.950000         0.222222       5.000000   \n",
       "\n",
       "       local_rings_6  local_rings_7  smallest_ring       ΔG(eV)  \n",
       "count    1092.000000    1092.000000    1092.000000  1092.000000  \n",
       "mean        2.132784       0.647436       6.152015     0.677213  \n",
       "std         0.940847       0.731172       0.359200     0.349938  \n",
       "min         0.000000       0.000000       6.000000    -1.248642  \n",
       "25%         2.000000       0.000000       6.000000     0.469529  \n",
       "50%         2.000000       1.000000       6.000000     0.717732  \n",
       "75%         3.000000       1.000000       6.000000     0.914259  \n",
       "max         5.000000       3.000000       7.000000     1.594346  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "80edc2c1-92c1-46a9-a472-6d2ca435607f",
   "metadata": {},
   "outputs": [],
   "source": [
    "df1 = df1.drop(['deltaG_bin'], axis = 1)\n",
    "df1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1df2b30c-980b-4c13-8c01-0c9e77de2955",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = df1.drop(['ΔG(eV)'], axis = 'columns')\n",
    "y = df1['ΔG(eV)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "191b5c21-1854-4acd-97cf-bb66c56fa09e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=0.2, random_state=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c15b3fa2-615a-41ce-bded-75ca58cde86e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# ============================================================\n",
    "# PART 1: LASSO — sparse linear regression\n",
    "# Replaces: rf = RandomForestRegressor(...)\n",
    "# ============================================================\n",
    "from sklearn.linear_model import LassoCV, Lasso\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.metrics import r2_score, mean_absolute_error\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# --- 1a. Fit LASSO with cross-validated alpha selection ---\n",
    "lasso_pipe = Pipeline([\n",
    "    (\"scaler\", StandardScaler()),          # LASSO needs scaled features\n",
    "    (\"lasso\",  LassoCV(\n",
    "        cv=5,\n",
    "        max_iter=10_000,\n",
    "        random_state=1,\n",
    "        n_alphas=200,\n",
    "    )),\n",
    "])\n",
    "\n",
    "lasso_pipe.fit(x_train, y_train)\n",
    "\n",
    "# --- 1b. Out-of-sample metrics ---\n",
    "y_pred_lasso = lasso_pipe.predict(x_test)\n",
    "r2_lasso  = r2_score(y_test, y_pred_lasso)\n",
    "mae_lasso = mean_absolute_error(y_test, y_pred_lasso)\n",
    "print(f\"LASSO  |  R² = {r2_lasso:.3f}  |  MAE = {mae_lasso:.3f} eV\")\n",
    "\n",
    "# --- 1c. Extract the interpretable formula ---\n",
    "lasso_model  = lasso_pipe.named_steps[\"lasso\"]\n",
    "scaler_model = lasso_pipe.named_steps[\"scaler\"]\n",
    "\n",
    "coef_raw = lasso_model.coef_           # coefficients in scaled space\n",
    "intercept = lasso_model.intercept_\n",
    "\n",
    "# Convert back to original-feature units for a human-readable equation\n",
    "# β_orig[i] = β_scaled[i] / σ[i]\n",
    "# intercept_orig = intercept - Σ (β_scaled[i] * μ[i] / σ[i])\n",
    "feature_names = list(x_train.columns) if hasattr(x_train, \"columns\") \\\n",
    "                else [f\"x{i}\" for i in range(x_train.shape[1])]\n",
    "\n",
    "coef_orig = coef_raw / scaler_model.scale_\n",
    "intercept_orig = intercept - np.dot(coef_raw, scaler_model.mean_ / scaler_model.scale_)\n",
    "\n",
    "# Keep only non-zero (selected) features\n",
    "nonzero_mask = coef_orig != 0\n",
    "selected = pd.DataFrame({\n",
    "    \"feature\":     np.array(feature_names)[nonzero_mask],\n",
    "    \"coefficient\": coef_orig[nonzero_mask],\n",
    "}).sort_values(\"coefficient\", key=abs, ascending=False)\n",
    "\n",
    "print(f\"\\nOptimal alpha: {lasso_model.alpha_:.5f}\")\n",
    "print(f\"Features selected: {nonzero_mask.sum()} / {len(feature_names)}\")\n",
    "print(\"\\nLASSO formula:\")\n",
    "terms = \" + \".join(f\"({row.coefficient:+.4f})·{row.feature}\"\n",
    "                   for _, row in selected.iterrows())\n",
    "print(f\"  ΔG_H = {intercept_orig:+.4f}  {terms}\")\n",
    "print(selected.to_string(index=False))\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# PART 2: SISSO-style symbolic regression via PySR\n",
    "# pip install pysr   (wraps Julia SymbolicRegression.jl)\n",
    "# For a pure-Python fallback use gplearn (shown below too)\n",
    "# ============================================================\n",
    "# --- Option A: PySR (recommended — closest to actual SISSO) ---\n",
    "try:\n",
    "    from pysr import PySRRegressor\n",
    "\n",
    "    sr_model = PySRRegressor(\n",
    "        niterations=50,           # increase to 200 for publication\n",
    "        binary_operators=[\"+\", \"-\", \"*\", \"/\"],\n",
    "        unary_operators=[\"square\", \"sqrt\", \"log\", \"exp\"],\n",
    "        maxsize=12,               # max formula complexity (nodes)\n",
    "        populations=20,\n",
    "        population_size=50,\n",
    "        parsimony=0.01,           # penalises complexity → short formulas\n",
    "        model_selection=\"best\",   # picks formula on Pareto front\n",
    "        random_state=1,\n",
    "        verbosity=0,\n",
    "        temp_equation_file=True,\n",
    "    )\n",
    "\n",
    "    # PySR works on numpy arrays\n",
    "    X_tr = x_train.values if hasattr(x_train, \"values\") else np.array(x_train)\n",
    "    X_te = x_test.values  if hasattr(x_test,  \"values\") else np.array(x_test)\n",
    "\n",
    "    sr_model.fit(X_tr, y_train, variable_names=feature_names)\n",
    "\n",
    "    y_pred_sr = sr_model.predict(X_te)\n",
    "    r2_sr  = r2_score(y_test, y_pred_sr)\n",
    "    mae_sr = mean_absolute_error(y_test, y_pred_sr)\n",
    "    print(f\"\\nPySR   |  R² = {r2_sr:.3f}  |  MAE = {mae_sr:.3f} eV\")\n",
    "\n",
    "    # The best human-readable equation:\n",
    "    print(\"\\nBest symbolic formula:\")\n",
    "    print(sr_model.latex())          # LaTeX string → paste directly into paper\n",
    "    print(sr_model.sympy())          # SymPy expression for manipulation\n",
    "\n",
    "    # Pareto front: complexity vs loss tradeoff\n",
    "    print(\"\\nPareto front (complexity → accuracy):\")\n",
    "    print(sr_model.equations_[[\"complexity\", \"loss\", \"equation\"]].to_string(index=False))\n",
    "\n",
    "except ImportError:\n",
    "    print(\"PySR not installed. Run:  pip install pysr\")\n",
    "    print(\"Falling back to gplearn symbolic regression...\\n\")\n",
    "\n",
    "    # --- Option B: gplearn (pure Python, no Julia required) ---\n",
    "    from gplearn.genetic import SymbolicRegressor as GPLearnSR\n",
    "    from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "    sc = StandardScaler()\n",
    "    X_tr_sc = sc.fit_transform(x_train)\n",
    "    X_te_sc = sc.transform(x_test)\n",
    "\n",
    "    gp_model = GPLearnSR(\n",
    "        population_size=2000,\n",
    "        generations=30,\n",
    "        stopping_criteria=0.001,\n",
    "        p_crossover=0.7,\n",
    "        p_subtree_mutation=0.1,\n",
    "        p_hoist_mutation=0.05,\n",
    "        p_point_mutation=0.1,\n",
    "        max_samples=0.9,\n",
    "        verbose=1,\n",
    "        parsimony_coefficient=0.01,\n",
    "        random_state=1,\n",
    "        function_set=(\"add\", \"sub\", \"mul\", \"div\", \"sqrt\", \"log\", \"abs\"),\n",
    "        metric=\"mse\",\n",
    "        n_jobs=-1,\n",
    "    )\n",
    "    gp_model.fit(X_tr_sc, y_train)\n",
    "    y_pred_gp = gp_model.predict(X_te_sc)\n",
    "    r2_gp  = r2_score(y_test, y_pred_gp)\n",
    "    mae_gp = mean_absolute_error(y_test, y_pred_gp)\n",
    "    print(f\"\\ngplearn |  R² = {r2_gp:.3f}  |  MAE = {mae_gp:.3f} eV\")\n",
    "    print(\"\\nBest symbolic formula:\")\n",
    "    print(gp_model._program)\n",
    "\n",
    "\n",
    "# ============================================================\n",
    "# PART 3: SISSO-literal 2-feature descriptor (no extra lib)\n",
    "# Manual combinatorial search over d₁ op d₂ — exactly SISSO tier-1\n",
    "# ============================================================\n",
    "from itertools import combinations, product as iproduct\n",
    "\n",
    "def sisso_tier1(X_df, y, ops=None):\n",
    "    \"\"\"\n",
    "    Brute-force SISSO dimension-1: fit y ~ a·φ(fᵢ, fⱼ) + b\n",
    "    for all binary ops on all feature pairs. Returns top-5 by R².\n",
    "    \"\"\"\n",
    "    if ops is None:\n",
    "        ops = {\n",
    "            \"add\":  lambda a, b: a + b,\n",
    "            \"sub\":  lambda a, b: a - b,\n",
    "            \"mul\":  lambda a, b: a * b,\n",
    "            \"div\":  lambda a, b: np.where(np.abs(b) > 1e-10, a / b, np.nan),\n",
    "            \"sq_a\": lambda a, b: a**2,          # unary on first\n",
    "            \"sqrt_a\": lambda a, b: np.sqrt(np.abs(a)),\n",
    "        }\n",
    "    from sklearn.linear_model import LinearRegression\n",
    "    cols = X_df.columns.tolist()\n",
    "    results = []\n",
    "    for (i, ci), (j, cj) in iproduct(enumerate(cols), enumerate(cols)):\n",
    "        if i >= j:\n",
    "            continue\n",
    "        fi, fj = X_df[ci].values, X_df[cj].values\n",
    "        for op_name, op_fn in ops.items():\n",
    "            phi = op_fn(fi, fj)\n",
    "            if not np.isfinite(phi).all():\n",
    "                continue\n",
    "            phi = phi.reshape(-1, 1)\n",
    "            lr = LinearRegression().fit(phi, y)\n",
    "            r2 = r2_score(y, lr.predict(phi))\n",
    "            results.append({\n",
    "                \"descriptor\": f\"{op_name}({ci}, {cj})\",\n",
    "                \"coeff\": lr.coef_[0],\n",
    "                \"intercept\": lr.intercept_,\n",
    "                \"R2_train\": r2,\n",
    "            })\n",
    "    return pd.DataFrame(results).sort_values(\"R2_train\", ascending=False).head(10)\n",
    "\n",
    "print(\"\\n--- SISSO tier-1 (manual) top descriptors on train set ---\")\n",
    "top_descriptors = sisso_tier1(\n",
    "    pd.DataFrame(x_train, columns=feature_names),\n",
    "    y_train\n",
    ")\n",
    "print(top_descriptors.to_string(index=False))\n",
    "\n",
    "# Evaluate best descriptor out-of-sample\n",
    "best = top_descriptors.iloc[0]\n",
    "print(f\"\\nBest SISSO-1 descriptor: {best.descriptor}\")\n",
    "print(f\"  ΔG_H = {best.coeff:.4f} · {best.descriptor} + {best.intercept:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "1cab0f55-0b39-47f2-9afb-d8f7f640b00e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-1 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: #000;\n",
       "  --sklearn-color-text-muted: #666;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-1 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-1 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-1 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: flex;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "  align-items: start;\n",
       "  justify-content: space-between;\n",
       "  gap: 0.5em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
       "  font-size: 0.6rem;\n",
       "  font-weight: lighter;\n",
       "  color: var(--sklearn-color-text-muted);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content {\n",
       "  display: none;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  overflow: visible;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-1 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-1 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-1 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 0.5em;\n",
       "  text-align: center;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".estimator-table summary {\n",
       "    padding: .5rem;\n",
       "    font-family: monospace;\n",
       "    cursor: pointer;\n",
       "}\n",
       "\n",
       ".estimator-table details[open] {\n",
       "    padding-left: 0.1rem;\n",
       "    padding-right: 0.1rem;\n",
       "    padding-bottom: 0.3rem;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table {\n",
       "    margin-left: auto !important;\n",
       "    margin-right: auto !important;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
       "    background-color: #fff;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:nth-child(even) {\n",
       "    background-color: #f6f6f6;\n",
       "}\n",
       "\n",
       ".estimator-table .parameters-table tr:hover {\n",
       "    background-color: #e0e0e0;\n",
       "}\n",
       "\n",
       ".estimator-table table td {\n",
       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
       "}\n",
       "\n",
       ".user-set td {\n",
       "    color:rgb(255, 94, 0);\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td.value pre {\n",
       "    color:rgb(255, 94, 0) !important;\n",
       "    background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".default td {\n",
       "    color: black;\n",
       "    text-align: left;\n",
       "}\n",
       "\n",
       ".user-set td i,\n",
       ".default td i {\n",
       "    color: black;\n",
       "}\n",
       "\n",
       ".copy-paste-icon {\n",
       "    background-image: url(data:image/svg+xml;base64,PHN2ZyB4bWxucz0iaHR0cDovL3d3dy53My5vcmcvMjAwMC9zdmciIHZpZXdCb3g9IjAgMCA0NDggNTEyIj48IS0tIUZvbnQgQXdlc29tZSBGcmVlIDYuNy4yIGJ5IEBmb250YXdlc29tZSAtIGh0dHBzOi8vZm9udGF3ZXNvbWUuY29tIExpY2Vuc2UgLSBodHRwczovL2ZvbnRhd2Vzb21lLmNvbS9saWNlbnNlL2ZyZWUgQ29weXJpZ2h0IDIwMjUgRm9udGljb25zLCBJbmMuLS0+PHBhdGggZD0iTTIwOCAwTDMzMi4xIDBjMTIuNyAwIDI0LjkgNS4xIDMzLjkgMTQuMWw2Ny45IDY3LjljOSA5IDE0LjEgMjEuMiAxNC4xIDMzLjlMNDQ4IDMzNmMwIDI2LjUtMjEuNSA0OC00OCA0OGwtMTkyIDBjLTI2LjUgMC00OC0yMS41LTQ4LTQ4bDAtMjg4YzAtMjYuNSAyMS41LTQ4IDQ4LTQ4ek00OCAxMjhsODAgMCAwIDY0LTY0IDAgMCAyNTYgMTkyIDAgMC0zMiA2NCAwIDAgNDhjMCAyNi41LTIxLjUgNDgtNDggNDhMNDggNTEyYy0yNi41IDAtNDgtMjEuNS00OC00OEwwIDE3NmMwLTI2LjUgMjEuNS00OCA0OC00OHoiLz48L3N2Zz4=);\n",
       "    background-repeat: no-repeat;\n",
       "    background-size: 14px 14px;\n",
       "    background-position: 0;\n",
       "    display: inline-block;\n",
       "    width: 14px;\n",
       "    height: 14px;\n",
       "    cursor: pointer;\n",
       "}\n",
       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>RandomForestRegressor(n_estimators=150, random_state=1)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>RandomForestRegressor</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.ensemble.RandomForestRegressor.html\">?<span>Documentation for RandomForestRegressor</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
       "        <div class=\"estimator-table\">\n",
       "            <details>\n",
       "                <summary>Parameters</summary>\n",
       "                <table class=\"parameters-table\">\n",
       "                  <tbody>\n",
       "                    \n",
       "        <tr class=\"user-set\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_estimators',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">n_estimators&nbsp;</td>\n",
       "            <td class=\"value\">150</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('criterion',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">criterion&nbsp;</td>\n",
       "            <td class=\"value\">&#x27;squared_error&#x27;</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
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       "                          this.parentElement.nextElementSibling)\"\n",
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       "            <td class=\"param\">max_depth&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
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       "    \n",
       "\n",
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       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('min_samples_split',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
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       "            <td class=\"param\">min_samples_split&nbsp;</td>\n",
       "            <td class=\"value\">2</td>\n",
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       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
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       "            <td class=\"param\">min_samples_leaf&nbsp;</td>\n",
       "            <td class=\"value\">1</td>\n",
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       "    \n",
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       "            <td class=\"param\">min_weight_fraction_leaf&nbsp;</td>\n",
       "            <td class=\"value\">0.0</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('max_features',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">max_features&nbsp;</td>\n",
       "            <td class=\"value\">1.0</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('max_leaf_nodes',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">max_leaf_nodes&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('min_impurity_decrease',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">min_impurity_decrease&nbsp;</td>\n",
       "            <td class=\"value\">0.0</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('bootstrap',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">bootstrap&nbsp;</td>\n",
       "            <td class=\"value\">True</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
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       "                          this.parentElement.nextElementSibling)\"\n",
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       "            <td class=\"param\">oob_score&nbsp;</td>\n",
       "            <td class=\"value\">False</td>\n",
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       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('n_jobs',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"user-set\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('random_state',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">random_state&nbsp;</td>\n",
       "            <td class=\"value\">1</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('verbose',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">verbose&nbsp;</td>\n",
       "            <td class=\"value\">0</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('warm_start',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">warm_start&nbsp;</td>\n",
       "            <td class=\"value\">False</td>\n",
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       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('ccp_alpha',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">ccp_alpha&nbsp;</td>\n",
       "            <td class=\"value\">0.0</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('max_samples',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">max_samples&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "\n",
       "        <tr class=\"default\">\n",
       "            <td><i class=\"copy-paste-icon\"\n",
       "                 onclick=\"copyToClipboard('monotonic_cst',\n",
       "                          this.parentElement.nextElementSibling)\"\n",
       "            ></i></td>\n",
       "            <td class=\"param\">monotonic_cst&nbsp;</td>\n",
       "            <td class=\"value\">None</td>\n",
       "        </tr>\n",
       "    \n",
       "                  </tbody>\n",
       "                </table>\n",
       "            </details>\n",
       "        </div>\n",
       "    </div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
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       "</script></body>"
      ],
      "text/plain": [
       "RandomForestRegressor(n_estimators=150, random_state=1)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "rf = RandomForestRegressor(n_estimators=150, random_state=1)\n",
    "rf.fit(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7ff934dd-c6c3-4fd9-9a72-28a35eb49964",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9561592869394033"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rf.score(x_train, y_train)\n",
    "rf.score(x_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "80f73f88-fe14-426e-a681-274c86568dfe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.6140910019846333"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#rf.score(x_test, y_test)\n",
    "rf.score(x_test, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7dfca458-b247-4b2b-848d-6ab456c26cfd",
   "metadata": {},
   "outputs": [],
   "source": [
    "import plotly.graph_objects as go\n",
    "\n",
    "fig = go.Figure()\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=y_test, y=rf.predict(x_test),\n",
    "    mode='markers', name='Predictions',\n",
    "    marker=dict(size=6, opacity=0.7)\n",
    "))\n",
    "fig.add_trace(go.Scatter(\n",
    "    x=[-3.0,1.5], y=[-3.0,1.5],\n",
    "    mode='lines', name='Perfect', \n",
    "    line=dict(color='black', dash='dash')\n",
    "))\n",
    "\n",
    "fig.update_layout(\n",
    "    title='Random Forest Regression',\n",
    "    xaxis_title='Original ΔG (eV)',\n",
    "    yaxis_title='Predicted ΔG (eV)',\n",
    "    width=600, height=600,\n",
    "    showlegend=False,\n",
    "    # Modern title font (no titlefont!)\n",
    "    title_font=dict(size=16, family='Arial')\n",
    ")\n",
    "\n",
    "fig.write_html(\"rf_regression.html\")\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "82df7fd6-9b88-4b63-9614-9f889b2ab3dc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Permutation importance (test set) — top features:\n",
      "  height                          0.4623 ± 0.0672\n",
      "  theta_mean                      0.2634 ± 0.0355\n",
      "  theta_std                       0.2499 ± 0.0391\n",
      "  q6_order                        0.1126 ± 0.0277\n",
      "  curvature                       0.0643 ± 0.0099\n",
      "  local_rings_6                   0.0263 ± 0.0130\n",
      "  local_density                   0.0175 ± 0.0062\n",
      "  local_rings_7                   0.0124 ± 0.0087\n",
      "  local_rings_5                   0.0016 ± 0.0036\n",
      "  neighbor_cn_var                 0.0001 ± 0.0002\n",
      "\n",
      "Out-of-sample R² = 0.443\n",
      "\n",
      "LASSO kept 9 / 10 features\n",
      "\n",
      "Equation:\n",
      "  ΔG_H = +2.1063  (-3.8914)·height  +  (-0.0040)·theta_mean  +  (-0.0131)·theta_std  +  (+0.4526)·q6_order  +  (-0.6460)·curvature  +  (-0.0713)·local_rings_6  +  (+0.0114)·local_density  +  (-0.0845)·local_rings_7  +  (-1.0602)·neighbor_cn_var\n",
      "\n",
      "SHAP summary plot →\n"
     ]
    },
    {
     "data": {
      "image/png": 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z+4Pvzm9mC+xSI35ez7PPszNnzpkzM2fOzJyZOUPe3t60cOHCol0wViaUZPmMj4+nL774gry9vTV+ISEhxbJ87MNW0vWnuqCgIKGMMqautMrnX3/9Rb1796auXbvS6dOnKScnp8iWiZUdJVk+jx07Rr6+vuTr60tXrlwhIqK4uDjy8/Mjb29v2rVrV9EvIPvgFbaMZmdn0/Hjx2n48OHCsXrIkCE6p+drpOLDr6oxVkjJyckIDAyEUqlE8+bNAQCNGjWCTCZDTEwMNm3alG8aQUFBSEhIgI+PDywtLWFtbY26desiMTERQUFBkmkjIyOFVnTV/D7//HMAwJ49e3Dx4sWiXDz2gSvp8jlv3jwkJyejQoUKMDExkYRt2rQJT58+LbqFYx+8ki6f6vbt24f9+/cXybKwsqe0yuf27dsxatQoWFhYYMeOHWjZsiXfKWcaSrJ8pqenIygoCEqlEjVq1ICPjw8AwN3dHS1btgQArFmzBtnZ2cWwpOxDVdgymp6ejg0bNuDBgwd48OBBvvPja6TixQ1HjBXS/v37kZqaCgCws7MDABgZGcHBwQFAbkWlUCh0xo+NjUVUVJQkPgA4OjoCAG7cuIHY2Fhh/LZt24T/qulV0wLAzp07C7U8rGwpyfIZGxsLCwsLHD58GIcOHcKxY8fg5+cnxMnJycH169eLcOnYh66k60+x69evY8uWLYVfCFZmlUb5PHDgAJYvXw6ZTIYlS5bA2tq66BaIlSklWT7v37+PtLQ0AMCbN2+Qk5MjTK96pS09PV2YhjGg8GXUysoKo0aNQkBAALp165bv/PgaqXhxwxFjhRQZGSn8Nzc31whPS0vTeeGiT3wAuHTpEoDcvjhUB3ld01+7dg3v37/PP+Pso1CS5dPKygqLFi0SDtJ2dnYIDAyU3CkXH8AZK8nyKfb69WvMnz8fs2bNMiS77CNT0uXz6dOnCA4OBgD4+/vDxcXF4Dyzj0dJlk/VhT6Q23B04MABYfjdu3cAAA8PD5QrV06frLOPRGHLqJiFhUWe4XyNVPy44YixQhJXeOqv5qjExMTojC8O0xVfNY+4uDhkZGTkOX1mZibi4uLyzjT7aJRk+XRzc9Po6NDBwUE4kbS2tka9evX0yjf7OJRk+VR5//49pk+fjsmTJ+vVeTb7eJV0+dy4cSOysrIAAI8fP0ZAQAC6d++OUaNG4eTJkwblnZV9JVk+XV1d4e3tLYwPDg7GH3/8ASLCjRs34OzsnO+rwezjU9gyagi+Rip+3HDEWCFkZmZKHsvVVSm+fftWZxrisPziJyQkSMYXZH7s41HS5VNXHlR3I3v37m3wFzRY2VVa5XPhwoVo0aKF5DVKxtSVdPnMyspCRESEMH7u3LlYs2YNatSogatXr2LatGmSrwSxj1tp1J/z58+Hu7s7ACA7OxuzZs3CqFGjoFQqsXv3bv7aH5MoijJqCL5GKn7ccMRYIaSkpOg1ner93oKmoYqvPq2uzjLzmh/7eJR0+dTmwoULICJ4eHhg+PDheuWHfRxKo3yGhYUhPT0dQ4cO1Wve7ONV0uXz7t27SE9PF8aXK1cOZmZmGDNmjDBu9erVwues2cetNOpPJycnbNy4EfXq1YOzszMA4K+//sLjx48RGBjIHWMziaIoo4WZH18jFT1uOGKsEGQymV7TyeXyQqWhil8U82Mfj5Iun9ps374d9vb2WLZsmd75YR+Hki6f165dQ3h4OObMmaNfBtlHraTL599//6013M3NDba2tgByn/LQ1mcX+/iUxvE9OTkZ8+bNw7t37/D7779j0KBBQtipU6ewcOFCvfLEPg4lfc3C10jFjxuOGCsEGxsbvSqqvDoEVt210Se++rREZPD82MejpMunuv379+PBgwdYvXo1KlWqlG867ONS0uXz4MGDuH37Npo3bw4fHx/4+PhofKXFx8cH4eHh+abJyr6SLp/GxtJT8szMTOF/hQoVhP+vX7/ON01W9pV0+VQoFBg1ahQiIiLQrFkzmJubY8KECejVq5cw7cGDB/H06VM9cs8+BkVRRg3B10jFjxuOGCsEIyMj1KlTRxjW9UnJunXr6kxDn/iffvopAKBGjRowMzMTxiuVSo1pZTIZatSokXfG2UehpMun2L1797B+/XqsXr0anp6ewvhnz57x4+wMQOmWT8byU9LlU9w4BPz/L1UB0q8J2djY6M40+2iUdPk8deoU7t69CwCSG0Hjx48XPntORLhz546eS8DKuqIoo4bga6Tixw1HjBVS06ZNhf/iO4QqcrkcXl5eyMrKwsSJE9GyZUuEhIToHR+A0ImrTCaDj4+PMF789QAVb29vScXJPm4lWT5V3r17h6CgIKxYsUJy0f706VPMnTsXpqamBV4eVraUZPkcN24c9u7dK/mJ0wKAvXv3onXr1oVaJlZ2lGT59PT0lHzK/MmTJ8J/8dNIXl5ehi8IK5NKsnw+e/ZMGCc+x5TL5ZKvpfIr6UyssGXUEHyNVPy44YixQurevbvwvqy4R39VJ5dffvklzMzMcPjwYZw7dw5paWnYuHEjHj9+DCC3pV3V2i6Or/oSQZ06dSQX3/379xf+q6YXd6jZp0+fIl0+9mEr6fKZnZ2NqVOn4ubNmxg8eDA+++wzfPbZZ2jcuDH8/f1hbGyss8NC9vEpyfLp5OSE6tWrS36VK1eW5Kd69eqwtrYupqVlH5qSLJ+mpqb46quvhGmuXbsm/E9MTASQ+/RH7dq1i3w52YepJMtnzZo1hfBHjx5J8qF6ssPOzg6NGjUqykVkH7jCllGx9+/fC/91PbnO10jFixuOGCske3t7zJ49G8bGxrh48SKA3Nd0kpKSULt2bQQEBADQfNdWPDx37lzY2dkhKioKmZmZyMrKQmxsLOzs7DQ6cv3888/Rt29fALlfrAKAq1evAgB69uyJZs2aFc+Csg9SSZZPIsIPP/yAqKgoEBGUSqXwU6XHFz1MrKTrT8YMUdLlc8iQIWjSpAkA4MCBA0hNTcWDBw/w5MkTODg4cHlmEiVZPps0aSI8jXn48GGhL6OYmBhERkZCJpMhMDAQVlZWxbrM7MNSFGUUyH3NLSYmRhh++vSppCFKha+RipcR6eo5ijFmkMjISKxbtw6JiYkwMjJCs2bNMHLkSOEgmpmZiWnTpuH69evo27ev5BO7QG4luGrVKty6dQsymQzu7u4YP368xh1xlT179mD37t3CI+y9e/dGz549+WkOplVJlM9169bhl19+yTMfQUFB6NixY9EvIPuglXT9qfL8+XNJB9mqE0zGxEqyfCoUCuzZswfh4eFISUmBubk5GjZsiOHDh2v0g8QYUHLlU6lUYs+ePTh8+DCePXsGZ2dnZGRkoGHDhhgyZAg++eSTEltm9mEpTBkdMGAAXr58Ken3Dcjt+61q1arYunUrTExMJGF8jVQ8uOGIMcYYY4wxxhhjjGnFr6oxxhhjjDHGGGOMMa244YgxxhhjjDHGGGOMacUNR4wxxhhjjDHGGGNMK244YowxxhhjjDHGGGNaccMRY4wxxhhjjDHGGNOKG44YY4wxxhhjjDHGmFbccMQYY4wxxhhjjDHGtOKGI8YYY4wxxhhjjDGmFTccMcYYY4wxxhhjjDGtuOGIMcYYY4wxxhhjjGnFDUeMMcYYY4wxxhhjTCtuOGKMMcYYY4wxxhhjWnHDEWOMfQSSk5OxfPlyvHnzprSzUqSuXr1a2llg/+fRo0dYu3YtMjIyijztV69eYd68eUWeLmOMMcZKX0REBA4fPgwiKu2sMB244Ygxxsq48PBwNGjQAI6OjnBycgIAbN68GUZGRti8ebPWOEePHkWXLl3g7OwMOzs7eHh4oG/fvjh+/DiICKtXr5Y02tSsWRPGxsYwMjLS+pPJZFi4cCEuXboEuVyuczojIyPY2toiKysr3+X6888/0b9/f+Tk5OQ77Y0bNzB58mTUrl1b6zxNTEyE5ezRowc2btyIzMxM/VZwCRk9erRGvocOHVpq+VEvQ9WqVUNmZiYaNGiA8+fPF9l8fv31V/j5+aFx48ZFliYrvEePHsHPzw+2traYNGlSaWfnH+vs2bN49+5daWejzKtRo0aR1o+dOnXSSO+HH34osvwWJ4VCgSNHjpR2NnQKDw8v7Sx8cBITE9G+fXvY2Nigf//+yM7O1jltSa3f0NBQmJqaauwnjx49KlB6fn5+CAsLQ/v27fH06dOizSwrGsQYY6zMWr58OZmamtKxY8ck4zdt2kQAaNOmTRpxJk6cSACoc+fOdPfuXSIiSkpKonXr1pGTkxOVL1+eTE1N6cqVK5J4CQkJ1Lp1awIg+a1YsYKUSqVk2suXL5NcLpdMV6NGDXr8+LHey/avf/2LANCBAwf0jvPu3TsyNzeXzPfw4cN08+ZNWrZsmSRPHh4edPv2bb3TLgkhISGSvA8ZMqTU8qKrDK1fv57MzMxo3759hZ7HpEmTyNramqKjowudFitaAwcOlJTFEydOlHaW/nESEhKofPny9PDhw9LOykfhl19+KdL6cdq0aZL05syZUyT5LG5BQUGlemzIy7Zt26hly5alnY0PzqxZsyRl8ddff9U63b1798jS0rLE8pWUlES1a9eW5K0w9V1OTg4NGDCAKlWqRHfu3Cm6jLIiwU8cMcZYGbVx40ZMmjQJI0aMQLt27fSKs3btWqxYsQLOzs7Yu3cvatSoAQCwtbVFQEAArly5AplMBoVCoRHXwcEBvXr10hg/cuRIGBtLDze+vr7w8vKSjPP390eVKlX0yuetW7dw+PBhAMDSpUv1igMAdnZ2cHZ2loyztLRE7dq1MWnSJOzYsUMYHxcXh06dOiE9PV3v9ItbmzZtSjsL+RoxYgR8fX3Rp08f/PnnnwVO5/vvv8fy5csxe/Zs1K9fvwhzyIoC8esEeVIoFOjbty9evnxZ2ln5aLRq1apI0/sQ6lt1ERER/9gno2JiYjB69OjSzsYHSZ/6NiUlBV9++WWxvC6ui62tLRo1alRk6RkZGWHFihVIS0tDmzZt8Pr16yJLmxUeNxwxxlgZFBMTg7Fjx8LIyAjfffed3vEWLlwIAKhSpQosLS01wqtXr47ffvtNoyFIxcrKSmOchYWF1mnV09cWV5clS5YIJ1Jnz541qK8jU1NTnWFdu3aVNCw9fPgQO3fu1Dvt4iaTyUo7C3qZNWsWFAoF+vfvX6B+tY4dO4agoCDY2tpi/PjxxZBDVliBgYFo3LgxbGxsMH78+A/yIru4KBQKDB48GBEREaWdlY9KXnV7QXwo9a3KhQsX0KtXL603dkrbnTt30LlzZ6SkpJR2Vj5IkyZNQtu2bSGXy9G3b18MHDhQEp6amoru3bsjJiamxPNW1Pudk5MTRo0ahWfPnmksJytd3HDEGGNl0H/+8x9kZmaiRYsWqFy5sl5xXr9+jfj4eABAVFQUjh07pnU6Hx8fdOnSpcjyaqgXL15g+/btknGGPHWUFyMjI7i7u0vGXbt2rUjS/ph88cUXcHJywvPnzzFnzhyD4mZnZ2PcuHEgIvTo0UNrAyYrfW5uboiMjERycjJWrVpV2tn5x0hMTET37t3/UQ3OrOzbt28f2rVrh6SkpNLOioazZ8+iefPm3G9NITg6OiIiIgKpqanYtWsXzM3NhbCnT5+iTZs2OHXqVCnmsGj169cPQO5NpD179pRybpgKNxwxxsqc4cOHw8TERKOzvrCwMDRp0gRyuRz29vbo2bMnnjx5AgC4ffs2BgwYABcXF8jlcjRr1gyXL1/WOY/o6Gj06tUL5cuXh1wuh5+fHw4ePKh1WiLCoUOH0LdvX9SsWRMWFhZwcXFB+/btcfLkSY3pZ86cCXNzc0n+T58+jZMnT6Jdu3awsbGBi4sLxo0bp7UD56NHj+L06dMAgLZt2+q93sR3V4kI3bp1w8qVK7V2wti9e3e90y1qq1atgpGRkWTc3r178fjx42KZn667aVlZWTo7+J49e7YwjZmZmTDe2NgYSqVSSCMpKQmLFy9Gy5YtUblyZVhYWMDNzQ3jxo3DixcvDMrnzJkzIZPJNMqNKkxbmdLm1KlT6Ny5M5ycnCCXy9G2bVucO3fOoLyYmpqiQ4cOAID169fj4cOHesfduHEj7t27ByDv8puRkYGff/4ZHTp0QNWqVSGTyVC1alUMHjwYcXFxkmmbNGmidTs1b95cmKZ58+aSMPV9U5/1snfvXlSsWFFrh7rXr19HmzZtYGNjg2+++UYST6FQYPv27ejevTvc3Nwgk8lQqVIl9OjRI8+GS3En9urb3tTUFOXKlUO5cuXw6tUrSTxD6i91aWlp+XaIWlx1sLbO7Tdv3oybN2+iS5cusLW1RfXq1TF16lQkJydrzb+h9bFYaGgomjdvDmdnZ5QrVw6+vr7YvHmz0EH/8+fP0bp1axw/flwSr169esK20FdSUhK+++47eHp6wtbWFq6urujSpQv++OMPjWlPnjwJd3d3jY6hX7x4gbFjx8LV1RVyuRwtW7bE9evX9c7D6dOnUbNmTY10nz9/jtGjRwt1lqenJ9atWwcAUCqVWLNmDRo2bAhLS0u4urpi+vTpOp+CycrKwqJFi9CgQQPY2tqiQoUKaNOmDcLCwvJ8Pef48eNo27Yt7Ozs4OLigl69euHu3bt6LdeDBw8wbNgwVKpUCXK5HPXr18evv/6q93rRlyHbMCwsTGfdERYWhgoVKujsqHvp0qUYNmyY5LXqHTt2CGVu4cKFOjv7fvr0Kfr37w8HBwdUqlQJI0aM0Dj2nDx5Eh4eHlo7HtdV9lR27tyJHj16SF45OnfunJC3MWPG5LkOY2Ji4O3tLUm/VatWePfuHaZPny7Ul5988gnmz58v7Is7duwQ6hoXFxeMGDECqampOreTocdhpVKJn3/+GU2aNIGtra3kOG9kZAQLCwuhjgCA1atXw8bGRqPuunbtGvz9/WFvbw97e3sMHDgQCQkJknmpb3vx8Ts2NhatWrXSOE6o1m+9evWQnp6OLl26aKQBAOnp6ejcubPWMHWJiYmYMWMG3N3dIZfL4eXlhdWrV+v1Gl1OTg42bNgAX19f2NrawtHREYMGDdJ53tagQQO4uroCyD1/4Vej/yFKq3MlxhgrTu3atZN01vfFF19Qt27daMGCBWRnZyfpkHn9+vXUsGFDCg4Opnr16glhtra29PLlS420t2zZQqamplShQgWKj4+nO3fukIODAwGg5cuXS6ZNTU2lTp06EQAKDw+nnJwciomJEaY3NjamrVu3aszj3//+tyT/nTp1Il9fXxo9ejSZmpoK4//9739rxO3Vq5cQ/vvvv2tdP7o6Nm7QoIFG59Zubm60ceNGys7Ozne9q9IV/3Rp2bKlwR2PpqSkkL29Pe3YsYPMzMwk8b/55pt84xMRVatWTRLv1KlTknAXFxdJeFhYmM60oqOjJeUJAH377beSadLS0qhevXrk6upKcXFxwviLFy+Si4sL1atXj548eUI5OTn0448/CulUrVqVnj9/Lknr4cOHeXb+Onz4cJ3Lpl6m1JebiGj+/PkEgLy8vCghIYEuXrxIZmZmZGpqSnv37pVMm1cH60RES5cuLVCnsj4+PkK869eva53m7t275O7uTpUqVRI6MN+xY4cQz97enmJjY4Xp37x5Q97e3pLlb9asmaRM5+Tk0IgRI8jY2Jj++9//Fni9nDhxQqNcX79+nWxsbCTjExMTiYjoxYsX1LhxY7K0tKTLly8TEdHp06eF8m1hYaG14+kpU6YIaQ0dOpQyMzPp3LlzQjxzc3MhPTFD6i9dUlJSqGbNmnl2iFocdbBCoaB+/fpp7G/lypWjihUrSsb7+PhQUlKSJE8FrY+VSiX17t2bAFCPHj0oKyuLJkyYIMzr66+/lkw/ZMiQQnUWGx8fT5988gkBoC5dulBaWhrFxcWRs7MzAaDRo0eTQqGQxDlz5oxknt7e3uTp6Unjx48nd3d3YbyzszMlJCTonZfz589L0m3QoAF5enrS/PnzhQ8UqH6LFi2iVq1a0ZgxYzQ6lp4xY4ZG2omJicJ+6ePjQwkJCfT69WuqVasWASB/f39KS0vTiLdixQoyMjIiADRr1iwiIjp16hSVL18+z/qRiOjYsWMkl8vJ0tKSoqOj6cWLF+Th4UEAaOLEiZJpT506ZfAxSqUg23Dbtm065xcaGppnXvI7NhARTZ06VTLN2LFjqUqVKlSxYkUyNjaWHPOfPn0qiXvu3Dmd6auXPW3zFocb2jn2s2fPJPHd3d3Jy8uLZs2aRYMHD9Y4D+jZsycNGDCAAgMDJR/D6Nevn0baBTkOp6amSs5f1q9fTwqFgoKDg4Vx1atXp3fv3kniBQYGSvLarl07qlu3Lo0fP15yfGjTpo0kXlZWlsb5kvrxWz1cG1U51zaNuI7QFv/58+dUp04dAkAVKlSgJ0+eUFJSEg0ZMkTjXEy9vsvMzKSuXbsSABo8eDBlZWXRsmXLCAC5uLjo7ARbFUfb8rLSwQ1HjLEyadCgQZID2ciRI4Ww2bNna5xgp6SkEBHRyZMnJWGrVq2SpHvhwgWh4SYoKEgYP27cOAJApqamki9xTZ48WUhL/JWpnj17CuMdHR01vjqmnsd27doJF7niZTM1NRUuQIlyTzAsLCyEcF0X3rou+o8cOSKckKv/3NzcaOvWrZSTk6NzvRd3w9Hy5cupfv36REQaF5C2traUnJycbxp5NRwdPnxYEla/fv18G8wWL16c7wVSgwYNaOPGjcJwRkYGubq6EgCqUqWKcIGbkpIiSWvSpEmSdPK7OFAvN+JlyyuMiGj37t1C2LZt24TxXbp0Edbv27dvhfH5NRzt379fSM/T0zOvVSiIj4+X5FH9wl+lUaNGBIBsbGzo0aNHwnhHR0chbo8ePSRxLl++LEnbz89PI92JEyfS4MGDJeMMXS/379+XzGf69Onk5eUlaZQ1MjISyuqXX35JAMjExETypUJxQ1fDhg0ledq5c6dkHi9evBDCVA0jAKh9+/aSeIbWX3lR3//ULxaKqw5W/7KgtbU1RUREEBHRH3/8IQlTb0wuaH08c+ZMIfzmzZtERBQRESGZ171794TpC9NwpFAoqHHjxkLcS5cuCWHfffedMH7x4sWSeOrlTi6X0//+9z8i0mzMXL16td75UU/Xzs6Obt26RURE6enpJJPJJOHbt28X4rZo0UIY7+DgoJF2jx49hPBdu3YJ49evXy+MHzNmjCROVFSU0MhhbW0taVjas2dPnvVjXFyccIE+fPhwYfySJUuEOKqyRFTwhqOCbkNtjc76hBHp13CkfnwzNzen0NBQYb2Kzx169uwpiateDsTp5xWmIg43tOFIqVRK4puZmdGff/5JRLkN/urH9AULFghxxQ1LxsbGksacgh6HR44cKYSJj23Z2dmSBiBxPoiIfv31V0m6devWFeo99ToxJiZGEnfGjBmS8II0HDVv3lznNHmFEUn31cDAQGG8QqGQNPZrq+/GjBlDQO4xLj4+XohXrlw5AnJv4mgjbpwfNWqU1mlYyeJX1RhjZZJ6580zZswQ/qt/uWvcuHGwtrYGAI3+gNRfeZkxY4bwyL34NZeaNWsCyH3lRPzIu/iVhXnz5gn/VfMDgISEBI1Hk9XzP336dOGVqapVqwrjFQqF5BWR6Ohoyetr6l8Qy0/Hjh2xdu1amJiYaIQ9ePAAgwYNQsuWLQ16LUz1yLT6z9DXn5RKJVasWIEJEyYAyN1uYsnJydiwYYNBaaq8ffsWW7duxYABA4RxzZs3x/Hjx/Pt+HH06NGSV1B27NgheR0tPj4er169kqR98+ZNPHv2DADw5MkTbN68GYC0XAC5HYoaQlen5fmFKZVKTJ8+XRjWVraTk5MN6rdFXPbu3LmjV98bly5dEv6bm5vD1tZWY5q3b98Kj+WnpKRg5cqVQph4/amvO19fX8mrb5cuXdJ4tSU8PBxTpkwRhguyXtTX8/r16/Hdd98hKioKgYGBsLW1xYQJE2BjYwPg/9cRSqUSCxYs0GtZ1q9fL/y3t7dH+fLlhWFPT0/h/4ULFyTxDK2/8pJfx8HFVQer93k1ZswYYbt26NABTZs2FcJCQkIkXxgqSH384sULBAcHC9PVrl0bANCoUSNJXt6/f4+isGvXLly5ckUYrlevnvBf/HXBH374QfLqjfr67tGjB+rUqQNAeswANNdpXtTT9ff3F8qYpaUlHB0dhbBq1aqhf//+wrB4W759+xaJiYnC8Pnz57F//36tyyb+//PPP0vyGxQUJLyO1KhRI8lHFXx8fPJclsDAQKFzZm3lH4Dwyl1hFNU2FMsrTF/q+46/vz8GDRoEIPfVoJ49ewphv/32m+Tcorjzlhf19Js0aYIWLVoAyO2XUPVKk8q3334r/BeXwZycHDx48EAYLshxOCsrC6GhocKwqj4Acl/R9vDwEIbV61/15ZgwYYIwr/z20aLoqL2g2zA2NlayrzZr1kz4b2JigoYNG+qMe//+faxduxZA7jKqltPExARubm4Acl9dvHnzpkZc8TlEXl1HsJLDDUeMsY+OmZmZ3mHik7oXL17gzJkzwnClSpWE/3K5XPgvPsCJP0+vOtEBIJz4quT3+VRxQ456Q4Y4j+oHXzs7uzzT1SYgIABnzpyRnOyKnT17Fo0bN9a7UePdu3daf+KTD33s3r0b6enpwoVJ06ZNNU5YVq5cKWm00UfXrl1RrVo1TJs2DVWqVMGgQYPwxx9/4PTp03o1vFlbW2PEiBHC8OPHjyUnWVu2bMHIkSMlnVl6enrCy8sLQO4J4WeffQbA8HJRVK5cuSLph0ifsp0fcWMaESE2NjbfOOLyq6vsOjg4CF/wMjY2ljQUiNeftnU3efJkybC4U+czZ86gatWqqFu3rjCuKNaLvb29UGZnz56NpKQkLF++XAjXp45QX5a///5b+K9+kSMeFtdnBam/iktB62BtxBduAODn5yf8z8jIwNmzZ4XhgtTHYWFhQqOQuEzb29tj165d6NmzJ1auXCk00hSWuON/GxsbycW+eP7p6ekIDw/XmY6+x4zCKui2VP/AgYuLi/Bfve5QdY77/v17HD16VAirUKGC3vlUKBTYt2+fMFyc5b+otmFxy2vfAaDzAxn/NAUtgwU5Dr97904yrG/9q01J7aOFpd7/nSH73Z49e4T1Kd7ngPz3O/G+Ehsby/0c/QMU7ffzGGOsjBE3QkRFRUnCGjZsKBz4lUqlcEdI/GTF999/j969eyM1NRWNGzfGjRs3EBQUhEOHDknSUj9RKWge3759KwkTN1YYokmTJoiKisLOnTsxf/583Lp1SxL+6tUrDBw4UHJXtbgtWbIEo0aNktx5GzduHL7++mthOD4+Hr/99hv69Omjd7rh4eFo1apVofI2fvx4LF++XHiaY9myZejVqxeUSiVCQ0Nx/vx5yfRWVlb466+/cPXqVVSrVg0VK1bEtm3bsGTJEsl0hSkXhlAv246OjkIHmQqFQljn79690ztN9bKn/lSdNuLym1fZPX78OCIjI+Hk5AQPDw8cOnQI8+fPl3Rkqm3dderUCbVq1RIaPTdv3ox58+bB3t4eP//8M/7zn/9Ipi+K9SJu2NJm48aNGD9+PMzMzPDpp5/i7NmzCAoKQmRkpDCN+glzzZo1cfv2bQCaT7qInzhs0KCBzmXRp/76JzC0IVj9aaZ79+6hffv2AApWH4svaNQ/Jd6tWzd069bNoPzl5+rVq8J/8YUVoHkhqk9jrDaGrtOiIp6veDkB6bLqWs7Hjx9LLqgtLCz0nve9e/ckcbt37y7MJycnRyj/ujpVN0RJbMPioG3fKWvEZbAgx2EXFxfY2dkJ9aS+9W9h8lna1G9IGrLfiY87Fy9elDQGvX//Xtjv1M9dAek5QHZ2NlJSUrQ+hcxKDj9xxBhjelI/sO3Zs0d4eiYlJQWZmZnIzMxEdHS0ZLratWujUqVKGDRoEHx9fdG8eXODGjbyI76oVH8yQdsrZ7o8evQIQUFBwrCxsTEGDBiA2NhYbN++HdWrV5dMf/XqVfz1118Fy7SBTp48iZiYGIwePVoyXvU1GLGlS5eWSJ7EqlSpgi+//FIYvnjxIi5duoTw8HA0bdpU8iqRikwmQ9OmTREbG4v69esjKCgIW7ZsKclsC9TL9uXLl4WynZqaKpTt33//Xe801e+gql90ayMuv3mVXWNjY/j5+SEhIQFNmzZFQEAAFixYoHFHU52RkZHwqiOQ+4WwdevW4dWrV4iKitJoBCiK9ZJfnoDcRhxTU1N06dIFXbp0wfDhwzXu/otNmDBBaMB69eqVpOFK/CTg1KlTdS6LvvXXh0b86hKg2RBmaH385s0bSVrF3bAmfp1LvfFUvTFU/KUqQ/wT7tyLlxOQLquu5VRfXkOWQ738L126VCj/ycnJQvlXz1dBlMQ2LA757TtlkaHHYfVjiLi+zcnJEV4xs7Ozw8iRIwucr3/CPqpSVPuds7Oz5Knz9PR0Yb9T/9IoULBzCFa8uOGIMcb0pP6Oub79/GzduhW1a9fG9u3bsWXLFowfP744sgcAGndjDL1rdeTIEY1xxsbG6N+/P2JjYyV9IADQ+/PHhRUcHAwjIyPUrl1b0k9ShQoVkJaWJpk2MjJS4wmfkjBp0iTJ8LJly7Q+xaKSlpaGgQMHolOnTkhPT8fp06cl/V+UpIKW7bxkZ2dLhlV9+uRFXH7zKrsKhQLffPMNmjRpgtu3b+PEiRNo3bq1XvkaMmSIpLHxp59+wtq1azFixAiNfh6KYr3oc3c2ODgY9evXR0REBMLDw9G7d+88p2/Tpg1CQ0Mhl8tBRJg+fTrS09Px3//+F0eOHIGJiQmWLl2KTp06FemyfAjUt6G9vb1k2ND6WL1fGPHrfsUhrzvq6p+012ef+qcqyHIW5kKyJMv/h7oN89t3yqKCHIfnzJmDCRMmwNjYGNHR0di0aRMyMjIQGBiIxMRE2Nvb48CBA1pvGH2Iimq/e/PmDdLT0/WOW5BzCFa8uOGIMcb05O7uLhn+448/tE4nvhsTGhqKwYMHIyUlBV26dEHfvn2LNY/qJyrix6b1ceHCBdy4cUNrmFwux/bt21GtWjVhnPix4+ISGxuLEydO4NatW1r7Snry5InGndLSeOrIz89P8pTIvn37kJGRAW9vb41piQjdu3cX+sJYsmSJQf0G6GLIE2ZiBSnb+cnKypIM69NflLj85lV2AwICsGzZMuTk5GDmzJkafXXkxcrKCgEBAcLws2fPsHz5cskrjyrFsV7UBQYGYtq0aXj//j0CAgIkfe/kZeDAgbhz5w48PDywadMmODo6YsSIEejduzeuXLmi0Z9TSSzLP4F6Q7K4s9qC1MfizsYB6PVUoOppsIIQ99um/gqk+kWXuD+uD416/3TiZdW1nOpl+MmTJ3rPryTLf0G3YUHrb6BwZU4lr32nMHn7pyrocdjY2BgrVqzAiRMnYGlpidGjR8PR0RHbt2/HN998g5s3bxb69XdD6bP9i+r8oKD7nVKpREREhNbptO134nMImUzGr6n9A3DDEWOM6alevXqSk4qDBw9K+iEBcvtxUT2erFQqJa+KiE/CikteJ+P6mjBhgs6+dWQymfDlGrlcbnAH1wWxYMEC9OnTR/gChzpnZ2dJ59QA8Pvvv5fY01BiEydOFP4rlUqNL7+pHDp0CCdOnBCGi6ps5PXEmfqdbrFWrVpJXqnYsGGD5Is6QO7XUcRfxsqP+HUNY2NjvS5y87rgUomJicGmTZuE4YKsu3Hjxknuon711VdaG0GLY72IJSQkSF4PNWRZ7t69i5YtW2LQoEHIzMxERkYGnj9/ju3bt2v9yo2h9deH6vnz58J/CwsLoY4qaH3co0cPyfC+fftw+vRpybiEhAScOnVKGC5o33JAbllUSU5Oluy34tc+ZDIZunbtWuD5lDbxcgLSZVN/rUz1BJ6DgwMaNWokjL9x44bkVUL1PnnExzF7e3vJV9eioqLw22+/SabPysrCwIEDDV0UDQXdhgWtv4HClTkV8b4DAO3atSuSvAFFk7+iVpjj8IEDB9CjRw+Eh4cjMzMT6enpuHfvXpHdBDKUPuu3oNtQXA6A3K4DxNS/ACfe71T9y6nMnTtX40miPXv2YPfu3RrzFZ9D6PpYCytZ3HDEGCuT1A9M4r5T1MPEw+p9BInDTExMJHfxlUolunbtir179yIhIQHnz59Hhw4dhAuvN2/e4NWrV8L0oaGhCAsLQ3BwsMYJa2ZmpuRun3rDjXhY/QAvvlPj4eEheWpD/URQH6dPn8bIkSO1viqUlpYmdBY7d+5cjUeHtT2GrOvJEfVptX0FKzIyErt27ZJ8DUmbKVOmSBoCcnJyMGfOHK3Tqt9VVR8ujJ49ewodjFauXFnS75GYemeTM2bMwMGDB9GvXz/J+MzMTCgUCuHOm/pTPOrDtWrVkgw/ffoUQG7/VapP4qqoX1QNHz5cGE5JSUG7du1w/PhxJCQk4OjRo/D399fZEKbNy5cvhf9169bV+PqMNr6+vkLnsUqlUrL/qKivu3nz5iE8PBxjx46VvH6iKnfatq+rq6twMWpkZKTzdaWCrBf1cpzXEwxxcXGSOmblypU4cOAAZs6cqfEpZ3EdkZmZiQ4dOuD+/fsYN26cXp/DNrT+yo962cur7lQPL2gdrI16Q564MWzUqFHCq2YFrY/9/Pwkr/wREfz9/RESEoKYmBjs378fbdu2lXQsrP7kp2oZVB2a52XQoEHCl54A6UWZ+CMFU6dOhaOjozBc0GNGfvLajurhhkzbtm1byQWpuNFHvJwDBw6UrA/xK8HZ2dn4/vvvAeQ24I4ZM0YyP/Uvf06bNk0yPGTIEGzYsAGvX79GdHQ0OnfuLOnvKr/6VpeCbkM3NzfJcUxVf2dlZWkcz9S3t4ODg6TjbdW6VigUuH//vtZ85rXv+Pv7S/o1tLOzk5RrVd6ICN9++22eeQOk+4S4HOizTxhSrtSH85q2oMfhmJgY9O7dG1WqVEHbtm3zzb9KYfbR/OpbfeocXecHBw8e1DjeiPOm+qiEyq+//op79+6BiPD9999r3IAQz7Njx46Sm0bXrl1D165dcePGDbx69Qrr1q3DqlWrtJ7jic8hmjRpohHOSgExxlgZk5SURLVr1yYAwm/NmjVERJSZmUl9+vSRhPXv358UCgUREQUHB0vCvLy8KCUlRUhboVDQv/71L8k0qp+RkRGtW7dOmDYnJ4dcXV01puvSpQsFBgZKxnl6etLixYuFuCNHjpSEb9++XQgbNmyYJGzXrl2S5Z84caIQtmPHDq3raNOmTQSANm3aJIx7+PAhASC5XE5GRkbk5+dHR48epezsbFIoFBQVFUWtWrUiIyMj+u677zTSfPv2LbVp00ZjeVesWEFKpVIy7dmzZ0kmk0mm+/TTT+nx48eSaapWrUoAaMSIEfTu3Tud2/zvv/+mcuXKacw7JCRE2LZKpZLCwsI0phkwYAAlJyfrTNtQixcvJgC0YMECndMcO3ZMIx/m5uYUEhJCjRo1EsYZGxuTn58f3b59m4iIfvrpJ0mcWrVqSfKuUCjo008/FcJdXV1p0qRJVLNmTWrdurXOMkVElJqaSt7e3lrLtkwmo0OHDkmm11aGxBYuXCjEX7Rokd7rz9/fX4h34cIFjfBbt26RsbGxJH/GxsY0e/ZsSVwA1LBhQ/rzzz+1zicyMpIAUPv27fPMj6HrJSQkRDLNF198QVlZWVrTfvv2Lcnlco10hw8fTmPHjpWMq1u3rrDN9u7dK4xft24dvX//Xp9Va1D9lZe3b99SzZo1JfFXr14thBdnHawqd6qftbU1hYSEUHZ2Nh09elQoGw0bNqTExEQhXmHq4xcvXpCnp6fW9SaXy+ngwYOS9XPv3j3Jdv3ll18oLi6OAgMD9Vq/d+7coYoVKxIA6tmzJ2VkZNCdO3fI2dmZAFCfPn2E9aVy8eJFSb7atWsnhP3555+SsI4dO+qVDyKiX375RRLXzc1NqHOuXLlCJiYmkv0wJiaGiIjevHkj1N+qn3pd8fLlS6GcNG3alBITE+nvv/8Wylbz5s0pNTVVI0/9+vWTpFupUiWysLCg1atXa2yf5s2bU0JCghB31KhRWrcjAJo5c6YwXU5ODk2dOlUS3qpVK537srqCbEP1/Jmbm9O4ceOocePG1LVrV0leRowYoRE3ICBACK9RowalpqbSvHnzKC4ujoiITp06JUnDwsKCvv/+e8rIyKCoqCiytrYmAFStWjWKj4/XSF9cpwOgr7/+mtq2bUvdunXTWfZUFixYIITb29vTq1evaN26dXT+/Pl81+Xx48cl6dvY2NDff/9NREQPHjzQOPYfPnyYiIjS09OpcePGkrA5c+YI6Rb0ODxu3DgCQFZWVhQZGUk5OTn5LgMR0Y8//iiZ1/z584WwuXPnSsIWLlwohKWnp1OLFi0k4VOmTJHM9+zZs5J98fjx43T58mWh3iUiiouLk9RLvr6+NGbMGKpbty7VqlVLkv6zZ88kef/rr78kcS0sLMjFxYWaNWtGX331lSSunZ0drV+/Xoj7v//9jxwcHLTuc5UrV6aHDx9qXV8dO3YUprt8+bJe65gVL244YoyVOboOUKtWraLevXtrDWvTpg2tXLlSa5iDg4MkfYVCQStXrqQGDRqQlZUVOTs7U+fOnencuXMaeblw4QLVq1ePLC0tyc/Pj3bu3ElEuScCPXv2JLlcTq6urhQcHCzEmT17NpmZmUny4OrqShEREbR8+XIyNTXVOPCGhYUJ8W/evCmcQEycOFHrOtLVcNStWzfKysqi58+f0+LFi8nPz49cXFxILpdTlSpVaMCAAXTp0iWN9GrUqEFGRkY6T8jNzc3pxx9/pIsXL5KVlZXO6VQnhbt27dIaFhAQoDFvbQ1G4l+3bt0oLCxMY72Jf0ZGRuTv7593wdJTYmIiOTk50Zs3b/Kcbt68eeTk5EQODg40YMAAunPnDhHllhkvLy+ysLCgzz77jCIjI4lIszFRfFIrPsl/9uwZ+fv7k7W1NTk6OlK/fv3o7t27NGfOHEm8SpUqScoNEVFGRgb98MMP5OnpSRYWFlSxYkXq06cP3bhxQyP/+TUcqRoHrKyshJN8fRw9elTI44oVK7ROs2HDBnJ1dSVbW1vq1q2bsI7u3LlDvr6+ZGFhQZ9++ikdOXIkz3k1bdpUo+FHG33Xy/z587VuIzMzM3rw4IHWtA8ePEju7u4kl8upTZs2dPToUSLKvahu27YtWVpakru7O4WGhgpxNm7cqLMsm5mZkZOTE/n5+VFwcDBlZ2dL5mdI/aVNamqqRsOd6tevXz8iKt46WL3h6KeffqIZM2ZQrVq1yNzcnKpXr05Tp06VNBqpFKQ+VklKSqJvv/2WPDw8SCaTUeXKlWno0KF069Ytrevp7Nmz1LhxY7KwsKBPPvmEFixYoNGAnpc3b97QlClTqGbNmmRjY0P29vbUokUL2rp1q8a0p06dInd3d416YerUqXT9+nVyc3OThJmYmNDXX3+dbx5WrVqlc3v873//01kGz5w5Q/b29jrLgFhqaioFBgZS3bp1ydbWluzs7Khx48a0evVqrQ0rRLk3AYKDg6lmzZokk8nIy8uLDh06RI8ePSJ3d3caOHAghYSEUHR0tNZ1HhoaSp9//jlZW1tTuXLlqGXLlhQeHi6ZpkOHDlrzb2pqmu96UzFkG6q8f/+eJk+eTE5OTmRtbU2tWrWiY8eOaTT6yGQymjVrliRuZmYmTZw4kZydncnGxoY6d+5M169fF8LV05g5cyYtXLiQ6tWrRzKZjFxdXSkgIECj0UDsxx9/pEqVKpGVlRV99tlntHPnTuGmk7jsDRs2TBIvJyeHgoKCyNXVlaysrKhFixZ06tSpfNfh77//rnM7PH78WOd5R2hoKDVs2FBr2OTJk4X0DT0OExENHjxYZ9mXyWRUqVIlat++Pe3bt0+Is2bNGrKxsZFMW65cOdq5cyft3LlTaLRT/ezt7emnn34iIqLy5ctrnZefn59kXR04cIDq1KlDFhYW5OXlRWvXrtVYnxcuXCBfX1+SyWRUrVo1mjJlCr17945atmwpSdvb25uio6MlcWNjY6lbt25kZ2dHtra2NGzYMEpJSaGxY8dSq1at6Ntvv6Xw8HCt5z5PnjyhESNGUOXKlUkmk5GbmxtNnjyZXr16pXPbq5a7UaNGeRURVoK44Ygxxsqg4cOHE5B751Db3bD8LvoZy09eZSg7O5scHR0JAM2ePdvgtNu1a0cAqEWLFkWQ07Ln5cuXOhtn1H9Dhgwp7ewWKfWGI67DGNOPesOR+Okbpr9jx47leaOM66fCu3btmrAOIyIiSjs77P9wH0eMMVYGLVy4EFWqVEF8fHyxfz6aMXVHjhxBQkIC6tSpU6COo0NCQmBra4uzZ89q9MPBABcXF4SHh+vVb9TWrVsN+nwyY4wx3dq1a4cVK1boNW1ISEjxZqaM2rZtGwBg6NChBvUjxYoXNxwxxlgZ5OjoiN27d8PS0hIzZ84s7eywj0hOTg5++OEH2NnZYe/evbCysjI4DQ8PD2zevBlGRkZcfrUICwtD+/btUbduXdy/fx/v37+HUqlEdnY2UlNT8ejRI8yePRtA7vagIvjEOGOMMWDy5MmYOHEixowZg5cvX0KhUECpVOL9+/dISkpCbGwsunfvDkC/L84xqefPn2PdunVo0KAB1qxZU9rZYSLccMQYY2WUn58fDh8+jOvXr2Px4sWlnR32kZg1axbi4+Nx4sQJ1K5du8Dp9OjRA9u3b8fevXsRFhZWhDn88M2fPx9paWnw9/eHm5sbzMzMYGxsDFNTU8jlclSrVk34Ulzr1q01PsP8IVP/upC2rz8yxjTxvlN4iYmJWL58OYgIQ4YMgYuLC0xMTGBsbAwzMzPY2trCy8sLAwYMAJD7dTqmv8zMTAwcOBCenp6IiIgo0I0nVny44YgxxsqwVq1aITo6GocOHcL48ePz/bQ1YwWVlZWFr7/+GteuXUN0dDS8vb0LnWa/fv1w4cIFLFq0CEFBQUWQy7Khf//+AIBFixZh//79SE1NFcJSUlJw5MgR+Pv7o0aNGti0aVNpZbPIZWdn4+TJk5JxJ0+e5AtgxvKRk5OD48ePS8adOXNGozGJ5c3e3h4dO3YEAIwaNQqXLl2SnFe9fPkSW7ZswaRJk9CtWzdMnz69tLL6wXny5Anatm2L+vXr49y5c3B0dCztLDE1RsTPLzPG2Efh1KlTaNiwIcqVK4fNmzdj2LBh2LRpE4YOHVraWWMfIPUy9PLlSzx48ACff/55kc8rJycH4eHhwuP/LPeib9u2bYiMjER8fDyICDKZDDY2NvD29kbHjh3Rv39/yGSy0s5qkfH09MSdO3c0xpubm+P8+fPw8fEphVwx9s/XsWNHHD16VGO8qakpdu3ahZ49e5ZCrj5MOTk52LVrF/bv34/r16/j5cuXMDExgUwmg5OTE5o2bQp/f3+hgYnpJzo6GuXKlUP16tVLOytMB244YowxxhhjjDHGGGNa8atqjDHGGGOMMcYYY0wrbjhijDHGGGOMMcYYY1pxwxFjjDHGGGOMMcYY04objhhjjDHGGGOMMcaYVtxwxBhjjDHGGGOMMca04oYjxhhjjDHGGGOMMaYVNxwxxhhjjDHGGGOMMa244YgxxhhjjDHGGGOMacUNR4wxxhhjjDHGGGNMK244YowxxhhjjDHGGGNaccMRY4wxxhhjjDHGGNOKG44YY4wxxhhjjDHGmFbccMQYY4wxxhhjjDHGtOKGI8YYY4wxxhhjjDGm1f8D5tsBO8TJIvkAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x945 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.inspection import permutation_importance\n",
    "from sklearn.linear_model import LassoCV\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.pipeline import Pipeline\n",
    "from sklearn.metrics import r2_score\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "# ── Step 1: Fit RF ─────────────────────────────────────────────────\n",
    "rf = RandomForestRegressor(n_estimators=150, random_state=1)\n",
    "rf.fit(x_train, y_train)\n",
    "\n",
    "# ── Step 2: Permutation importance on TEST set ─────────────────────\n",
    "feature_names = list(x_train.columns) if hasattr(x_train, \"columns\") \\\n",
    "                else [f\"x{i}\" for i in range(x_train.shape[1])]\n",
    "\n",
    "perm = permutation_importance(\n",
    "    rf, x_test, y_test,\n",
    "    n_repeats=30,        # 30 shuffles per feature → stable estimate\n",
    "    random_state=1,\n",
    "    n_jobs=1,\n",
    ")\n",
    "\n",
    "importances = pd.Series(perm.importances_mean, index=feature_names)\n",
    "importance_std = pd.Series(perm.importances_std, index=feature_names)\n",
    "\n",
    "top_features = importances.sort_values(ascending=False).head(10).index.tolist()\n",
    "\n",
    "print(\"Permutation importance (test set) — top features:\")\n",
    "for feat in top_features:\n",
    "    print(f\"  {feat:<30s}  {importances[feat]:.4f} ± {importance_std[feat]:.4f}\")\n",
    "\n",
    "# ── Step 3: LASSO on top RF features ──────────────────────────────\n",
    "X_train_top = x_train[top_features]\n",
    "X_test_top  = x_test[top_features]\n",
    "\n",
    "lasso_pipe = Pipeline([\n",
    "    (\"scaler\", StandardScaler()),\n",
    "    (\"lasso\",  LassoCV(cv=5, max_iter=10_000, random_state=1)),\n",
    "])\n",
    "lasso_pipe.fit(X_train_top, y_train)\n",
    "y_pred = lasso_pipe.predict(X_test_top)\n",
    "\n",
    "print(f\"\\nOut-of-sample R² = {r2_score(y_test, y_pred):.3f}\")\n",
    "\n",
    "# ── Step 4: Equation in original units ────────────────────────────\n",
    "lasso  = lasso_pipe.named_steps[\"lasso\"]\n",
    "scaler = lasso_pipe.named_steps[\"scaler\"]\n",
    "\n",
    "coef_orig      = lasso.coef_ / scaler.scale_\n",
    "intercept_orig = lasso.intercept_ - np.dot(lasso.coef_, scaler.mean_ / scaler.scale_)\n",
    "\n",
    "nonzero = coef_orig != 0\n",
    "print(f\"\\nLASSO kept {nonzero.sum()} / {len(coef_orig)} features\")\n",
    "print(\"\\nEquation:\")\n",
    "terms = \"  +  \".join(\n",
    "    f\"({c:+.4f})·{f}\"\n",
    "    for c, f in zip(coef_orig[nonzero], np.array(top_features)[nonzero])\n",
    ")\n",
    "print(f\"  ΔG_H = {intercept_orig:+.4f}  {terms}\")\n",
    "\n",
    "# ── Step 5: SHAP attribution (optional) ───────────────────────────\n",
    "try:\n",
    "    import shap\n",
    "\n",
    "    explainer   = shap.TreeExplainer(rf)\n",
    "    shap_values = explainer.shap_values(x_test)\n",
    "\n",
    "    print(\"\\nSHAP summary plot →\")\n",
    "    shap.summary_plot(\n",
    "        shap_values, x_test,\n",
    "        feature_names=feature_names,\n",
    "        plot_type=\"bar\",        # swap to \"dot\" for beeswarm\n",
    "        show=True,\n",
    "    )\n",
    "except ImportError:\n",
    "    print(\"\\nSHAP not installed — run: pip install shap\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18a0ac60-e717-4778-ab87-6728f4a883df",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Detail performance metrics\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "from scipy.stats import pearsonr\n",
    "import numpy as np\n",
    "\n",
    "# Your test set predictions\n",
    "y_true = y_test.values.ravel()      # Actual ΔG\n",
    "y_pred = rf.predict(x_test).ravel() # Predicted ΔG\n",
    "\n",
    "# 1. RMSE (eV) - prediction error\n",
    "rmse = np.sqrt(mean_squared_error(y_true, y_pred))\n",
    "\n",
    "# 2. R² - variance explained\n",
    "r2 = r2_score(y_true, y_pred)\n",
    "\n",
    "# 3. Pearson correlation (r, p-value)\n",
    "pearson_r, p_value = pearsonr(y_true, y_pred)\n",
    "\n",
    "print(f\"RMSE: {rmse:.3f} eV\")\n",
    "print(f\"R²:   {r2:.3f}\")\n",
    "print(f\"Pearson r: {pearson_r:.3f} (p={p_value:.1e})\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97e60687-a9ad-443b-9ddb-94bfd802a6cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "# Your setup (after rf.fit)\n",
    "importances = rf.feature_importances_\n",
    "indices = np.argsort(importances)[::-1]\n",
    "top_features = x_test.columns[indices[:10]]\n",
    "top_importances = importances[indices[:10]]\n",
    "\n",
    "# DataFrame for easier handling\n",
    "feat_df = pd.DataFrame({\n",
    "    'feature': top_features,\n",
    "    'importance': top_importances\n",
    "})\n",
    "\n",
    "# Set style\n",
    "plt.style.use('default')\n",
    "sns.set_palette(\"husl\")\n",
    "\n",
    "# Create figure\n",
    "fig, ax = plt.subplots(figsize=(10, 7))\n",
    "colors = plt.cm.Blues(np.linspace(0.3, 0.9, len(top_importances)))  # Gradient blue\n",
    "\n",
    "bars = ax.barh(range(10), top_importances, color=colors, alpha=0.8, edgecolor='navy', linewidth=1.2)\n",
    "\n",
    "# Customize\n",
    "ax.set_yticks(range(10))\n",
    "ax.set_yticklabels(top_features, fontsize=11, fontweight='medium')\n",
    "ax.set_xlabel('Feature Importance', fontsize=12, fontweight='bold')\n",
    "ax.set_title('Top 10 Feature Importances (Random Forest)', fontsize=14, fontweight='bold', pad=20)\n",
    "\n",
    "# Invert y-axis and grid\n",
    "ax.invert_yaxis()\n",
    "ax.grid(axis='x', alpha=0.3, linestyle='--')\n",
    "\n",
    "# Value labels on bars\n",
    "for i, (bar, imp) in enumerate(zip(bars, top_importances)):\n",
    "    width = bar.get_width()\n",
    "    ax.text(width + 0.001, bar.get_y() + bar.get_height()/2, f'{imp:.3f}', \n",
    "            ha='left', va='center', fontsize=10, fontweight='bold')\n",
    "\n",
    "# Styling tweaks\n",
    "ax.spines['top'].set_visible(False)\n",
    "ax.spines['right'].set_visible(False)\n",
    "ax.spines['left'].set_linewidth(1.2)\n",
    "ax.spines['bottom'].set_linewidth(1.2)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig('rf_feature_importance.png', dpi=300, bbox_inches='tight', facecolor='white')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8c6c9b8f-be5d-4d1f-b41a-84717229d90d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Histogram + KDE (smooth curve)\n",
    "sns.histplot(data=df1, x='height', kde=True, bins=50)\n",
    "plt.title('Distribution of height')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f12da36f-74d0-4e7d-910d-6551dfbaa58f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.metrics import r2_score, mean_squared_error\n",
    "import numpy as np\n",
    "\n",
    "param_grid = {\n",
    "    'max_depth': [3, 4, 5, 6],\n",
    "    'min_samples_split': [2, 5, 10, 20],\n",
    "    'min_samples_leaf': [1, 2, 5],\n",
    "    'max_features': [None, 'sqrt']\n",
    "}\n",
    "\n",
    "dt = DecisionTreeRegressor(random_state=42)\n",
    "\n",
    "# Multi-metric scoring\n",
    "grid_search_rmse = GridSearchCV(\n",
    "    dt, param_grid, cv=10, \n",
    "    scoring='neg_mean_squared_error',\n",
    "    n_jobs=-1\n",
    ")\n",
    "grid_search_rmse.fit(x_train, y_train)\n",
    "\n",
    "grid_search_r2 = GridSearchCV(\n",
    "    dt, param_grid, cv=5, \n",
    "    scoring='r2',  # R² scoring\n",
    "    n_jobs=-1\n",
    ")\n",
    "grid_search_r2.fit(x_train, y_train)\n",
    "\n",
    "best_dt_rmse = grid_search_rmse.best_estimator_\n",
    "best_dt_r2 = grid_search_r2.best_estimator_\n",
    "\n",
    "# RESULTS\n",
    "print(\"🏆 OPTIMIZED DECISION TREE\")\n",
    "print(f\"RMSE-tuned - CV RMSE: {np.sqrt(-grid_search_rmse.best_score_):.3f} eV\")\n",
    "print(f\"RMSE-tuned - CV R²:   {r2_score(y_test, best_dt_rmse.predict(x_test)):.3f}\")\n",
    "print(f\"RMSE-tuned - Params:  {grid_search_rmse.best_params_}\")\n",
    "\n",
    "print(f\"\\nR²-tuned   - CV R²:   {grid_search_r2.best_score_:.3f}\")\n",
    "print(f\"R²-tuned   - CV RMSE: {np.sqrt(mean_squared_error(y_test, best_dt_r2.predict(x_test))):.3f} eV\")\n",
    "print(f\"R²-tuned   - Params:  {grid_search_r2.best_params_}\")\n",
    "\n",
    "# Test set final scores\n",
    "print(f\"\\n📊 FINAL TEST PERFORMANCE\")\n",
    "y_pred_rmse = best_dt_rmse.predict(x_test)\n",
    "y_pred_r2 = best_dt_r2.predict(x_test)\n",
    "\n",
    "print(f\"RMSE-tuned Test: RMSE={np.sqrt(mean_squared_error(y_test, y_pred_rmse)):.3f} eV, R²={r2_score(y_test, y_pred_rmse):.3f}\")\n",
    "print(f\"R²-tuned   Test: RMSE={np.sqrt(mean_squared_error(y_test, y_pred_r2)):.3f} eV, R²={r2_score(y_test, y_pred_r2):.3f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b1fe973-3375-4818-8006-a8dd3013f898",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.metrics import mean_squared_error, r2_score\n",
    "import numpy as np\n",
    "\n",
    "# RF-specific params (more flexible than DT)\n",
    "param_grid_rf = {\n",
    "    'n_estimators': [100, 200, 300],\n",
    "    'max_depth': [5, 8, 12, None], \n",
    "    'min_samples_split': [2, 5, 10],\n",
    "    'min_samples_leaf': [1, 2, 4],\n",
    "    'max_features': ['sqrt', 'log2', None],\n",
    "    'bootstrap': [True, False]\n",
    "}\n",
    "\n",
    "rf_base = RandomForestRegressor(random_state=42)\n",
    "\n",
    "# RMSE-optimized\n",
    "grid_rf_rmse = GridSearchCV(\n",
    "    rf_base, param_grid_rf, cv=5,\n",
    "    scoring='neg_mean_squared_error',\n",
    "    n_jobs=-1, verbose=1\n",
    ")\n",
    "grid_rf_rmse.fit(x_train, y_train)\n",
    "\n",
    "# R²-optimized  \n",
    "grid_rf_r2 = GridSearchCV(\n",
    "    rf_base, param_grid_rf, cv=5,\n",
    "    scoring='r2',\n",
    "    n_jobs=-1, verbose=1\n",
    ")\n",
    "grid_rf_r2.fit(x_train, y_train)\n",
    "\n",
    "# BEST MODELS\n",
    "best_rf_rmse = grid_rf_rmse.best_estimator_\n",
    "best_rf_r2 = grid_rf_r2.best_estimator_\n",
    "\n",
    "# RESULTS TABLE\n",
    "print(\"🚀 OPTIMIZED RANDOM FOREST\")\n",
    "print(\"=\"*60)\n",
    "print(f\"{'Metric':<12} {'CV Score':<10} {'Test RMSE':<10} {'Test R²':<10} {'#Trees':<8} {'MaxDepth'}\")\n",
    "print(\"-\"*60)\n",
    "\n",
    "for tuned, name in [(grid_rf_rmse, 'RMSE-tuned'), (grid_rf_r2, 'R²-tuned')]:\n",
    "    best_model = tuned.best_estimator_\n",
    "    y_pred = best_model.predict(x_test)\n",
    "    \n",
    "    cv_rmse = np.sqrt(-tuned.best_score_) if name=='RMSE-tuned' else np.sqrt(mean_squared_error(y_test, y_pred))\n",
    "    cv_r2 = tuned.best_score_ if name=='R²-tuned' else r2_score(y_test, y_pred)\n",
    "    \n",
    "    print(f\"{name:<12} {cv_rmse:.3f} eV{'':<3} {cv_r2:.3f}{'':<5} \"\n",
    "          f\"{np.sqrt(mean_squared_error(y_test, y_pred)):.3f}  \"\n",
    "          f\"{r2_score(y_test, y_pred):.3f}    {best_model.n_estimators:<6}  {best_model.max_depth}\")\n",
    "\n",
    "print(f\"\\n🏆 Best RMSE-tuned RF params: {grid_rf_rmse.best_params_}\")\n",
    "print(f\"🏆 Best R²-tuned   RF params: {grid_rf_r2.best_params_}\")\n",
    "\n",
    "# Feature importance (best RMSE model)\n",
    "print(\"\\nTop 8 features (RMSE-tuned RF):\")\n",
    "importances = best_rf_rmse.feature_importances_\n",
    "top_idx = np.argsort(importances)[::-1][:8]\n",
    "for i, idx in enumerate(top_idx):\n",
    "    print(f\"{i+1:2d}. {x_test.columns[idx]:15} {importances[idx]:.3f}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7c151a82-5f4f-41c2-a9be-c868dc492127",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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