randomForestRegressor.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as patches\n",
    "from time import process_time\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import mean_absolute_error as MAE\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "\n",
    "import psutil\n",
    "\n",
    "# def MAPE2(actual_values, predicted_values):\n",
    "#     mape = np.mean(np.abs(np.where(np.logical_and(actual_values != 0, predicted_values != 0), (actual_values - predicted_values) / (actual_values + 1e-10), (actual_values - predicted_values) / 100)))\n",
    "#     return mape\n",
    "\n",
    "def MAPE(actual_values, predicted_values):\n",
    "    mape_sum = 0.0\n",
    "    count = 0\n",
    "\n",
    "    for actual, predicted in zip(actual_values, predicted_values):\n",
    "        if actual != 0 and predicted != 0:\n",
    "            mape_sum += abs((actual - predicted) / actual)\n",
    "        else:\n",
    "            mape_sum += abs(actual - predicted) / 100\n",
    "        count += 1\n",
    "\n",
    "    if count == 0:\n",
    "        return 0  # Handle the case when there are no valid entries to avoid division by zero.\n",
    "\n",
    "    return (mape_sum / count)[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-122.0</td>\n",
       "      <td>-37.0</td>\n",
       "      <td>-59.0</td>\n",
       "      <td>-24.0</td>\n",
       "      <td>49019.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-166.0</td>\n",
       "      <td>-62.0</td>\n",
       "      <td>-139.0</td>\n",
       "      <td>-43.0</td>\n",
       "      <td>1040.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>99.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>66507.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-159.0</td>\n",
       "      <td>-77.0</td>\n",
       "      <td>-112.0</td>\n",
       "      <td>-62.0</td>\n",
       "      <td>1041.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-63.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>-3.0</td>\n",
       "      <td>66.0</td>\n",
       "      <td>68350.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       0     1      2     3        4\n",
       "0 -122.0 -37.0  -59.0 -24.0  49019.0\n",
       "1 -166.0 -62.0 -139.0 -43.0   1040.0\n",
       "2   99.0  30.0  115.0  68.0  66507.0\n",
       "3 -159.0 -77.0 -112.0 -62.0   1041.0\n",
       "4  -63.0  50.0   -3.0  66.0  68350.0"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1M = pd.DataFrame(np.loadtxt('./intersect.filter.csv', delimiter=','))\n",
    "df1M.head() # show the first 5 rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(999999, 4)"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = np.loadtxt('./intersect.filter.csv', delimiter=',')\n",
    "Rectangles = data[:,0:4]\n",
    "Rectangles.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "univ_xmin = -180\n",
    "univ_xmax = 180\n",
    "univ_ymin = -90\n",
    "univ_ymax = 90\n",
    "Surface_univ=(univ_xmax-univ_xmin)*(univ_ymax-univ_ymin)\n",
    "\n",
    "s=0\n",
    "rectanglesCoverageRatio = []\n",
    "for i in Rectangles:\n",
    "    s = abs((i[3]-i[1])*(i[2]-i[0])/Surface_univ)\n",
    "    rectanglesCoverageRatio.append(s)\n",
    "rectanglesCoverageRatio = np.array(rectanglesCoverageRatio)\n",
    "\n",
    "\n",
    "# Plot 1000 rectangles from x1, y1 to x2, y2\n",
    "ax = plt.subplot()\n",
    "for rect, color in zip(Rectangles[0:1000], rectanglesCoverageRatio[0:1000]):\n",
    "    x1, y1, x2, y2 = rect\n",
    "    rectangle = patches.Rectangle((x1, y1), x2 - x1, y2 - y1, linewidth=1, edgecolor='b', facecolor='none', alpha=color)\n",
    "    ax.add_patch(rectangle)\n",
    "# The next code show the real rectangles forms with the color of the CoverageRatio\n",
    "# plt.xlim(min(rect[0] for rect in Rectangles), max(rect[0] for rect in Rectangles))\n",
    "# plt.ylim(min(rect[1] for rect in Rectangles), max(rect[1] for rect in Rectangles))\n",
    "plt.xlim(-200, 200)\n",
    "plt.ylim(-100, 100)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max : 1683002.0\n",
      "Min : 2.0\n",
      "Mean : 172835.6677046677\n",
      "Median : 65194.0\n"
     ]
    }
   ],
   "source": [
    "# Prepare data for the models the input is X and the output is Y\n",
    "Y = data[:,4:5]\n",
    "rectanglesCoverageRatio = rectanglesCoverageRatio.reshape(rectanglesCoverageRatio.shape[0],1)\n",
    "X = data[:,0:4]\n",
    "# X = np.append(data[:,0:4], rectanglesCoverageRatio, axis=1)\n",
    "\n",
    "\n",
    "# Split the data into 80% train and 20% test\n",
    "X_train, X_test_all, y_train, y_test_all = train_test_split(X, Y, test_size=0.2, random_state=3)\n",
    "\n",
    "\n",
    "# Taking just 100k first data\n",
    "sample_size = 800000\n",
    "# X_train = X_train[:sample_size,:]\n",
    "# y_train = y_train[:sample_size]\n",
    "\n",
    "Y.shape # (999999, 1)\n",
    "X.shape # (999999, 5)\n",
    "\n",
    "\n",
    "# columns = ['x_min','y_min','x_max','y_max','Density']\n",
    "columns = ['x_min','y_min','x_max','y_max']\n",
    "Data_Set = pd.DataFrame(data=X,columns=columns)\n",
    "column = ['number_of_objets']\n",
    "Target = pd.DataFrame(data=Y,columns=column)\n",
    "\n",
    "# Split the data into 80% train and 20% test\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X_sample, Y_sample, test_size=0.2, random_state=3)\n",
    "\n",
    "# Max, min, mean and median\n",
    "print(\"Max :\", np.max(Y))\n",
    "print(\"Min :\", np.min(Y))\n",
    "print(\"Mean :\", np.mean(Y))\n",
    "print(\"Median :\", np.median(Y))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "###### Random Forest Regressor ######\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/nadir/anaconda3/lib/python3.11/site-packages/sklearn/base.py:1151: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
      "  return fit_method(estimator, *args, **kwargs)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Elapsed time during the learning phase in seconds ( 30  etimators): 98.76383421599985\n",
      "R^2: 0.9994480920929664\n",
      "Mean Absolute Error of 20% of all: 2552.67\n",
      "Mean Absolute Percentage Error of 20% of all: 2.20%\n",
      "I/O Operations (mean of 10 times) - Reads: 3.5e-06, Writes: 0.000451\n",
      "Elapsed time during one estimation in seconds (mean of 10 times): 2.2582893289000595e-05\n",
      "Elapsed time during one estimation in microseconds (mean of 10 times): 22.582893289000594\n"
     ]
    }
   ],
   "source": [
    "# Random Forest Regressor\n",
    "print(\"###### Random Forest Regressor ######\")\n",
    "\n",
    "# Finding best parametres\n",
    "# t1_start = process_time()\n",
    "# param_grid = {'n_estimators': [10, 15, 20, 30, 40, 50, 60, 70, 80, 90, 100]}\n",
    "# param_grid = {'n_estimators': [30]}\n",
    "# randomForestRegressor = RandomForestRegressor(random_state=3)\n",
    "# gridSearchCV = GridSearchCV(randomForestRegressor, param_grid, cv=5, scoring='neg_median_absolute_error')\n",
    "# gridSearchCV.fit(X_train, y_train)\n",
    "# bestEstimatorsNumber = gridSearchCV.best_params_['n_estimators']\n",
    "# t1_stop = process_time()\n",
    "# print(\"Best number of estimators:\", bestEstimatorsNumber)\n",
    "# print(\"Elapsed time during the GridSearchCV:\", t1_stop-t1_start)\n",
    "bestEstimatorsNumber = 30\n",
    "\n",
    "# Create the regressor: randomForestRegressor\n",
    "randomForestRegressor = RandomForestRegressor(n_estimators=bestEstimatorsNumber, random_state=3)\n",
    "\n",
    "# Fit the regressor to the training data\n",
    "t1_start = process_time()\n",
    "randomForestRegressor.fit(X_train, y_train)\n",
    "t1_stop = process_time()\n",
    "print(\"Elapsed time during the learning phase in seconds (\",bestEstimatorsNumber,\" etimators):\", t1_stop-t1_start)\n",
    "\n",
    "# Predict on the test data: y_pred\n",
    "y_pred = randomForestRegressor.predict(X_test_all)\n",
    "\n",
    "# Compute and print R^2 and RMSE\n",
    "print(\"R^2: {}\".format(randomForestRegressor.score(X_test_all, y_test_all)))\n",
    "# print(\"Mean Absolute Error: {}\".format(MAE(y_test, y_pred)))\n",
    "# print(f\"Mean Absolute Percentage Error: {MAPE(y_test, y_pred):.2%}\")\n",
    "print(f\"Mean Absolute Error of 20% of all: {MAE(y_test_all, randomForestRegressor.predict(X_test_all)):.2f}\")\n",
    "print(f\"Mean Absolute Percentage Error of 20% of all: {MAPE(y_test_all, randomForestRegressor.predict(X_test_all)):.2%}\")\n",
    "\n",
    "import pickle\n",
    "filename = f'./LearnedModels/RF/RF_withoutCoverageRatio_{sample_size}_{(t1_stop-t1_start):.2f}s_{MAPE(y_test_all, randomForestRegressor.predict(X_test_all)):.2%}_{MAE(y_test_all, randomForestRegressor.predict(X_test_all)):.2f}.sav'\n",
    "pickle.dump(randomForestRegressor, open(filename, 'wb'))\n",
    "\n",
    "# Time to predict calculated 10 times and the average is calculated\n",
    "total_duration = 0\n",
    "total_read = 0\n",
    "total_write = 0\n",
    "for i in range(10):\n",
    "    io_before = psutil.disk_io_counters()\n",
    "    t1_start = process_time()\n",
    "    y_pred_tmp = randomForestRegressor.predict(X_test_all)\n",
    "    t1_stop = process_time()\n",
    "    io_after = psutil.disk_io_counters()\n",
    "    total_duration += (t1_stop-t1_start)\n",
    "    total_read += io_after.read_count - io_before.read_count\n",
    "    total_write += io_after.write_count - io_before.write_count\n",
    "\n",
    "print(f\"I/O Operations (mean of 10 times) - Reads: {total_read/10/len(y_pred_tmp)}, Writes: {total_write/10/len(y_pred_tmp)}\")\n",
    "print(\"Elapsed time during one estimation in seconds (mean of 10 times):\", (total_duration/10)/len(y_pred_tmp))\n",
    "print(\"Elapsed time during one estimation in microseconds (mean of 10 times):\", (total_duration/10)/len(y_pred_tmp)*1000000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x4000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "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>Real number of objects</th>\n",
       "      <th>Predicted number of objects (Random Forest)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49019.0</td>\n",
       "      <td>5.143310e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1040.0</td>\n",
       "      <td>1.040000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>66507.0</td>\n",
       "      <td>6.662913e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1041.0</td>\n",
       "      <td>1.040933e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>68350.0</td>\n",
       "      <td>6.786710e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>24214.0</td>\n",
       "      <td>2.391233e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>29535.0</td>\n",
       "      <td>2.928080e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>167357.0</td>\n",
       "      <td>1.658615e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>78617.0</td>\n",
       "      <td>8.119010e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>702271.0</td>\n",
       "      <td>6.969141e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>592196.0</td>\n",
       "      <td>5.911387e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>37161.0</td>\n",
       "      <td>3.715487e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>25215.0</td>\n",
       "      <td>2.515000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>25207.0</td>\n",
       "      <td>2.524510e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>164863.0</td>\n",
       "      <td>1.648920e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>645116.0</td>\n",
       "      <td>6.447128e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17166.0</td>\n",
       "      <td>1.703097e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>223861.0</td>\n",
       "      <td>2.244764e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>27533.0</td>\n",
       "      <td>2.759613e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>30214.0</td>\n",
       "      <td>3.028167e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21558.0</td>\n",
       "      <td>2.162137e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>463926.0</td>\n",
       "      <td>4.661083e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>33090.0</td>\n",
       "      <td>3.376497e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>7126.0</td>\n",
       "      <td>7.020033e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>1045.0</td>\n",
       "      <td>1.045000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>9118.0</td>\n",
       "      <td>9.118367e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>103604.0</td>\n",
       "      <td>1.033700e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>765875.0</td>\n",
       "      <td>7.604207e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>568039.0</td>\n",
       "      <td>5.689818e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>72433.0</td>\n",
       "      <td>7.044910e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>396120.0</td>\n",
       "      <td>3.923655e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>58514.0</td>\n",
       "      <td>6.052387e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>29335.0</td>\n",
       "      <td>2.953527e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>25039.0</td>\n",
       "      <td>2.492620e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>234332.0</td>\n",
       "      <td>2.345972e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>40721.0</td>\n",
       "      <td>4.060183e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>4126.0</td>\n",
       "      <td>4.032900e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>57084.0</td>\n",
       "      <td>5.708550e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2080.0</td>\n",
       "      <td>2.077600e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>296698.0</td>\n",
       "      <td>3.057552e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>37120.0</td>\n",
       "      <td>3.700903e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>66198.0</td>\n",
       "      <td>6.588570e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>60127.0</td>\n",
       "      <td>6.249260e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>65218.0</td>\n",
       "      <td>6.536793e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45550.0</td>\n",
       "      <td>4.551060e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>1017759.0</td>\n",
       "      <td>1.012473e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2356.0</td>\n",
       "      <td>2.425167e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>122412.0</td>\n",
       "      <td>1.222254e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>42187.0</td>\n",
       "      <td>3.988427e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>144728.0</td>\n",
       "      <td>1.440374e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>45758.0</td>\n",
       "      <td>4.582147e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>43513.0</td>\n",
       "      <td>4.374847e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>14093.0</td>\n",
       "      <td>1.412400e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>118415.0</td>\n",
       "      <td>1.191100e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>251768.0</td>\n",
       "      <td>2.619229e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>218572.0</td>\n",
       "      <td>2.186068e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>33306.0</td>\n",
       "      <td>3.228823e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>146272.0</td>\n",
       "      <td>1.454991e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>46332.0</td>\n",
       "      <td>4.703900e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>176912.0</td>\n",
       "      <td>1.679264e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>69953.0</td>\n",
       "      <td>7.186720e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>220849.0</td>\n",
       "      <td>2.160229e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>84675.0</td>\n",
       "      <td>8.440980e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>307659.0</td>\n",
       "      <td>3.054818e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>1399266.0</td>\n",
       "      <td>1.401445e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>662168.0</td>\n",
       "      <td>6.636633e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>4041.0</td>\n",
       "      <td>4.041000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>66448.0</td>\n",
       "      <td>6.759773e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>167192.0</td>\n",
       "      <td>1.670509e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>374238.0</td>\n",
       "      <td>3.734345e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>1040.0</td>\n",
       "      <td>1.040000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2820.0</td>\n",
       "      <td>3.140400e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>19080.0</td>\n",
       "      <td>1.975747e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>18080.0</td>\n",
       "      <td>1.888147e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>930614.0</td>\n",
       "      <td>9.314463e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>756210.0</td>\n",
       "      <td>7.665617e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>341970.0</td>\n",
       "      <td>2.964220e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>100750.0</td>\n",
       "      <td>1.005512e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>1048.0</td>\n",
       "      <td>1.048000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>405224.0</td>\n",
       "      <td>4.068929e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>59514.0</td>\n",
       "      <td>5.978373e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>35201.0</td>\n",
       "      <td>3.520717e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>15025.0</td>\n",
       "      <td>1.503077e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2065.0</td>\n",
       "      <td>2.064833e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>24081.0</td>\n",
       "      <td>2.407917e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2041.0</td>\n",
       "      <td>2.041000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>67103.0</td>\n",
       "      <td>6.717023e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>242709.0</td>\n",
       "      <td>2.430601e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>7040.0</td>\n",
       "      <td>7.040000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>305251.0</td>\n",
       "      <td>3.045016e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>63708.0</td>\n",
       "      <td>6.423123e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>141452.0</td>\n",
       "      <td>1.400636e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>1062.0</td>\n",
       "      <td>1.061933e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>11040.0</td>\n",
       "      <td>1.105677e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>16126.0</td>\n",
       "      <td>1.612250e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>16121.0</td>\n",
       "      <td>1.612107e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>20612.0</td>\n",
       "      <td>2.085870e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>40249.0</td>\n",
       "      <td>4.024420e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>312721.0</td>\n",
       "      <td>3.135241e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>109433.0</td>\n",
       "      <td>1.100154e+05</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Real number of objects  Predicted number of objects (Random Forest)\n",
       "0                  49019.0                                 5.143310e+04\n",
       "1                   1040.0                                 1.040000e+03\n",
       "2                  66507.0                                 6.662913e+04\n",
       "3                   1041.0                                 1.040933e+03\n",
       "4                  68350.0                                 6.786710e+04\n",
       "5                  24214.0                                 2.391233e+04\n",
       "6                  29535.0                                 2.928080e+04\n",
       "7                 167357.0                                 1.658615e+05\n",
       "8                  78617.0                                 8.119010e+04\n",
       "9                 702271.0                                 6.969141e+05\n",
       "10                592196.0                                 5.911387e+05\n",
       "11                 37161.0                                 3.715487e+04\n",
       "12                 25215.0                                 2.515000e+04\n",
       "13                 25207.0                                 2.524510e+04\n",
       "14                164863.0                                 1.648920e+05\n",
       "15                645116.0                                 6.447128e+05\n",
       "16                 17166.0                                 1.703097e+04\n",
       "17                223861.0                                 2.244764e+05\n",
       "18                 27533.0                                 2.759613e+04\n",
       "19                 30214.0                                 3.028167e+04\n",
       "20                 21558.0                                 2.162137e+04\n",
       "21                463926.0                                 4.661083e+05\n",
       "22                 33090.0                                 3.376497e+04\n",
       "23                  7126.0                                 7.020033e+03\n",
       "24                  1045.0                                 1.045000e+03\n",
       "25                  9118.0                                 9.118367e+03\n",
       "26                103604.0                                 1.033700e+05\n",
       "27                765875.0                                 7.604207e+05\n",
       "28                568039.0                                 5.689818e+05\n",
       "29                 72433.0                                 7.044910e+04\n",
       "30                396120.0                                 3.923655e+05\n",
       "31                 58514.0                                 6.052387e+04\n",
       "32                 29335.0                                 2.953527e+04\n",
       "33                 25039.0                                 2.492620e+04\n",
       "34                234332.0                                 2.345972e+05\n",
       "35                 40721.0                                 4.060183e+04\n",
       "36                  4126.0                                 4.032900e+03\n",
       "37                 57084.0                                 5.708550e+04\n",
       "38                  2080.0                                 2.077600e+03\n",
       "39                296698.0                                 3.057552e+05\n",
       "40                 37120.0                                 3.700903e+04\n",
       "41                 66198.0                                 6.588570e+04\n",
       "42                 60127.0                                 6.249260e+04\n",
       "43                 65218.0                                 6.536793e+04\n",
       "44                 45550.0                                 4.551060e+04\n",
       "45               1017759.0                                 1.012473e+06\n",
       "46                  2356.0                                 2.425167e+03\n",
       "47                122412.0                                 1.222254e+05\n",
       "48                 42187.0                                 3.988427e+04\n",
       "49                144728.0                                 1.440374e+05\n",
       "50                 45758.0                                 4.582147e+04\n",
       "51                 43513.0                                 4.374847e+04\n",
       "52                 14093.0                                 1.412400e+04\n",
       "53                118415.0                                 1.191100e+05\n",
       "54                251768.0                                 2.619229e+05\n",
       "55                218572.0                                 2.186068e+05\n",
       "56                 33306.0                                 3.228823e+04\n",
       "57                146272.0                                 1.454991e+05\n",
       "58                 46332.0                                 4.703900e+04\n",
       "59                176912.0                                 1.679264e+05\n",
       "60                 69953.0                                 7.186720e+04\n",
       "61                220849.0                                 2.160229e+05\n",
       "62                 84675.0                                 8.440980e+04\n",
       "63                307659.0                                 3.054818e+05\n",
       "64               1399266.0                                 1.401445e+06\n",
       "65                662168.0                                 6.636633e+05\n",
       "66                  4041.0                                 4.041000e+03\n",
       "67                 66448.0                                 6.759773e+04\n",
       "68                167192.0                                 1.670509e+05\n",
       "69                374238.0                                 3.734345e+05\n",
       "70                  1040.0                                 1.040000e+03\n",
       "71                  2820.0                                 3.140400e+03\n",
       "72                 19080.0                                 1.975747e+04\n",
       "73                 18080.0                                 1.888147e+04\n",
       "74                930614.0                                 9.314463e+05\n",
       "75                756210.0                                 7.665617e+05\n",
       "76                341970.0                                 2.964220e+05\n",
       "77                100750.0                                 1.005512e+05\n",
       "78                  1048.0                                 1.048000e+03\n",
       "79                405224.0                                 4.068929e+05\n",
       "80                 59514.0                                 5.978373e+04\n",
       "81                 35201.0                                 3.520717e+04\n",
       "82                 15025.0                                 1.503077e+04\n",
       "83                  2065.0                                 2.064833e+03\n",
       "84                 24081.0                                 2.407917e+04\n",
       "85                  2041.0                                 2.041000e+03\n",
       "86                 67103.0                                 6.717023e+04\n",
       "87                242709.0                                 2.430601e+05\n",
       "88                  7040.0                                 7.040000e+03\n",
       "89                305251.0                                 3.045016e+05\n",
       "90                 63708.0                                 6.423123e+04\n",
       "91                141452.0                                 1.400636e+05\n",
       "92                  1062.0                                 1.061933e+03\n",
       "93                 11040.0                                 1.105677e+04\n",
       "94                 16126.0                                 1.612250e+04\n",
       "95                 16121.0                                 1.612107e+04\n",
       "96                 20612.0                                 2.085870e+04\n",
       "97                 40249.0                                 4.024420e+04\n",
       "98                312721.0                                 3.135241e+05\n",
       "99                109433.0                                 1.100154e+05"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Compare the predicted number of objects with the real number of objects\n",
    "\n",
    "# Create a scatter plot for the real number of objects\n",
    "Y[:100]\n",
    "\n",
    "# Create a scatter plot for the predicted number of objects by Decision Tree compared to the real number of objects\n",
    "plt.figure(figsize=(20, 40))\n",
    "plt.scatter(range(100), Y[:100], c='green', label='Real number of objects')\n",
    "plt.scatter(range(100), randomForestRegressor.predict(X[:100]), c='blue', label='Predicted number of objects (Random Forest)')\n",
    "plt.xlabel('Rectangles')\n",
    "plt.ylabel('Number of object in the rectangle')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()\n",
    "\n",
    "# Show the same plot data in a table\n",
    "real_values = Y[:100].ravel()\n",
    "predicted_RF_values = randomForestRegressor.predict(X[:100]).ravel()\n",
    "df = pd.DataFrame({'Real number of objects': real_values, 'Predicted number of objects (Random Forest)': predicted_RF_values})\n",
    "# Print the table with all lines\n",
    "pd.set_option(\"display.max_rows\", None, \"display.max_columns\", None)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Median : 65194.0\n",
      "Minimal number of objects: 0, Mean absolute error of Random Forest: 2552.6685684999998, Mean absolute percentage error of Random Forest: 2.20%\n",
      "Minimal number of objects: 10, Mean absolute error of Random Forest: 2553.0383873995065, Mean absolute percentage error of Random Forest: 2.19%\n",
      "Minimal number of objects: 100, Mean absolute error of Random Forest: 2555.103250771153, Mean absolute percentage error of Random Forest: 2.18%\n",
      "Minimal number of objects: 1000, Mean absolute error of Random Forest: 2602.6245016162425, Mean absolute percentage error of Random Forest: 2.15%\n",
      "Minimal number of objects: 5000, Mean absolute error of Random Forest: 2858.8391940321435, Mean absolute percentage error of Random Forest: 1.90%\n",
      "Minimal number of objects: 40027, Mean absolute error of Random Forest: 4075.7647372807423, Mean absolute percentage error of Random Forest: 1.88%\n",
      "Minimal number of objects: 100000, Mean absolute error of Random Forest: 5177.717108515523, Mean absolute percentage error of Random Forest: 1.69%\n",
      "Minimal number of objects: 200000, Mean absolute error of Random Forest: 6327.251906553084, Mean absolute percentage error of Random Forest: 1.46%\n",
      "Minimal number of objects: 500000, Mean absolute error of Random Forest: 8497.235298500997, Mean absolute percentage error of Random Forest: 1.12%\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 2000x4000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select test data just who have number of objects > median\n",
    "median = np.median(Y)\n",
    "print(\"Median :\", median)\n",
    "y_median = y_test_all\n",
    "X_median = X_test_all\n",
    "\n",
    "\n",
    "# Create a graph changing the minimal number of objects and display the MAE and MAPE for each minimal number of objects\n",
    "# minimal_number_of_objects = 10 # 10, 100, 1000, 10000, 100000\n",
    "maeRF = []\n",
    "mapeRF = []\n",
    "minimal_number_of_objects_range = [0, 10, 100, 1000, 5000, 40027, 100000, 200000, 500000]\n",
    "for i in minimal_number_of_objects_range:\n",
    "    minimal_number_of_objects = i\n",
    "    merged_X_y = np.append(X_median, y_median, axis=1)\n",
    "    merged_X_y = merged_X_y[merged_X_y[:, 4] >= minimal_number_of_objects]\n",
    "    X_median = merged_X_y[:, 0:4]\n",
    "    y_median = merged_X_y[:, 4:5]\n",
    "    maeRF.append(MAE(y_median, randomForestRegressor.predict(X_median)))\n",
    "    mapeRF.append(MAPE(y_median, randomForestRegressor.predict(X_median)))\n",
    "    print(f\"Minimal number of objects: {minimal_number_of_objects}, Mean absolute error of Random Forest: {maeRF[-1]}, Mean absolute percentage error of Random Forest: {mapeRF[-1]:.2%}\")\n",
    "\n",
    "minimal_number_of_objects_range_str = ['0', '10', '100', '1k', '5k', 'Median', '100k', '200k', '500k',]\n",
    "plt.figure(figsize=(20, 40))\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(minimal_number_of_objects_range_str, maeRF, c='blue', label='MAE of Random Forest')\n",
    "plt.xlabel('Minimal number of objects')\n",
    "plt.ylabel('MAE')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(minimal_number_of_objects_range_str, mapeRF, c='green', label='MAPE of Random Forest')\n",
    "plt.xlabel('Minimal number of objects')\n",
    "plt.ylabel('MAPE')\n",
    "plt.legend()\n",
    "plt.grid()\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.1.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}