{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "8710147c",
   "metadata": {},
   "source": [
    "# 59 Visualizing DoubletCalc Results\n",
    "\n",
    "This notebook illustrates how to create the output plots provided by DoubletCalc with matplotlib.\n",
    "\n",
    "## Importing Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "51b2ca78",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e189a510",
   "metadata": {},
   "source": [
    "# Reading DoubletCalc Results CSV File"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7d53f77c",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\ale93371\\AppData\\Local\\Temp\\ipykernel_15364\\1359617900.py:1: ParserWarning: Falling back to the 'python' engine because the 'c' engine does not support skipfooter; you can avoid this warning by specifying engine='python'.\n",
      "  data = pd.read_csv('data/export_output.csv',\n"
     ]
    },
    {
     "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>iS</th>\n",
       "      <th>aquifer permeability (mD)</th>\n",
       "      <th>aquifer gross thickness (m)</th>\n",
       "      <th>aquifer net to gross (-)</th>\n",
       "      <th>aquifer top at injector (m TVD)</th>\n",
       "      <th>aquifer top at producer (m TVD)</th>\n",
       "      <th>aquifer water salinity (ppm)</th>\n",
       "      <th>aquifer kH net (Dm)</th>\n",
       "      <th>mass flow (kg/s)</th>\n",
       "      <th>delta T (°C)</th>\n",
       "      <th>heat capacity (kJ/(kg*K))</th>\n",
       "      <th>av. production density (kg/m³)</th>\n",
       "      <th>required pump power (kW)</th>\n",
       "      <th>pump volume flow (m³/h)</th>\n",
       "      <th>geothermal power (MW)</th>\n",
       "      <th>COP (kW/kW)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>254.29453</td>\n",
       "      <td>98.67665</td>\n",
       "      <td>0.809259</td>\n",
       "      <td>2458.3457</td>\n",
       "      <td>2457.9678</td>\n",
       "      <td>0.119523</td>\n",
       "      <td>20.306683</td>\n",
       "      <td>40.136295</td>\n",
       "      <td>49.975120</td>\n",
       "      <td>3664.4312</td>\n",
       "      <td>1057.3365</td>\n",
       "      <td>248.91680</td>\n",
       "      <td>136.65536</td>\n",
       "      <td>7.350175</td>\n",
       "      <td>29.528645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>232.21005</td>\n",
       "      <td>101.61317</td>\n",
       "      <td>0.787313</td>\n",
       "      <td>2643.6982</td>\n",
       "      <td>2521.1965</td>\n",
       "      <td>0.123078</td>\n",
       "      <td>18.577118</td>\n",
       "      <td>37.513557</td>\n",
       "      <td>51.644176</td>\n",
       "      <td>3651.1710</td>\n",
       "      <td>1058.8849</td>\n",
       "      <td>232.31094</td>\n",
       "      <td>127.53875</td>\n",
       "      <td>7.073621</td>\n",
       "      <td>30.448938</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>347.02588</td>\n",
       "      <td>110.62248</td>\n",
       "      <td>0.783280</td>\n",
       "      <td>2322.7173</td>\n",
       "      <td>2336.0005</td>\n",
       "      <td>0.102066</td>\n",
       "      <td>30.069246</td>\n",
       "      <td>51.665833</td>\n",
       "      <td>47.223145</td>\n",
       "      <td>3733.5127</td>\n",
       "      <td>1046.2684</td>\n",
       "      <td>323.81015</td>\n",
       "      <td>177.77185</td>\n",
       "      <td>9.109110</td>\n",
       "      <td>28.131021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>416.37143</td>\n",
       "      <td>110.71101</td>\n",
       "      <td>0.793836</td>\n",
       "      <td>2409.1120</td>\n",
       "      <td>2465.4832</td>\n",
       "      <td>0.126697</td>\n",
       "      <td>36.593388</td>\n",
       "      <td>57.302696</td>\n",
       "      <td>51.169163</td>\n",
       "      <td>3636.7332</td>\n",
       "      <td>1062.0903</td>\n",
       "      <td>353.78850</td>\n",
       "      <td>194.22997</td>\n",
       "      <td>10.663378</td>\n",
       "      <td>30.140543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>385.43112</td>\n",
       "      <td>106.67485</td>\n",
       "      <td>0.803228</td>\n",
       "      <td>2553.3394</td>\n",
       "      <td>2534.5093</td>\n",
       "      <td>0.123331</td>\n",
       "      <td>33.025370</td>\n",
       "      <td>54.664562</td>\n",
       "      <td>53.064050</td>\n",
       "      <td>3650.8708</td>\n",
       "      <td>1058.3341</td>\n",
       "      <td>338.69850</td>\n",
       "      <td>185.94554</td>\n",
       "      <td>10.590165</td>\n",
       "      <td>31.267237</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>996</td>\n",
       "      <td>208.79338</td>\n",
       "      <td>107.78278</td>\n",
       "      <td>0.796793</td>\n",
       "      <td>2371.8330</td>\n",
       "      <td>2634.3254</td>\n",
       "      <td>0.116407</td>\n",
       "      <td>17.931303</td>\n",
       "      <td>38.144660</td>\n",
       "      <td>55.109097</td>\n",
       "      <td>3679.4836</td>\n",
       "      <td>1051.8035</td>\n",
       "      <td>237.80956</td>\n",
       "      <td>130.55750</td>\n",
       "      <td>7.734708</td>\n",
       "      <td>32.524796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>997</td>\n",
       "      <td>335.04092</td>\n",
       "      <td>107.57787</td>\n",
       "      <td>0.803419</td>\n",
       "      <td>2431.6885</td>\n",
       "      <td>2622.8328</td>\n",
       "      <td>0.123286</td>\n",
       "      <td>28.957619</td>\n",
       "      <td>51.833920</td>\n",
       "      <td>55.581284</td>\n",
       "      <td>3652.3357</td>\n",
       "      <td>1056.8402</td>\n",
       "      <td>321.61395</td>\n",
       "      <td>176.56612</td>\n",
       "      <td>10.522364</td>\n",
       "      <td>32.717373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>998</td>\n",
       "      <td>230.71222</td>\n",
       "      <td>100.96610</td>\n",
       "      <td>0.813266</td>\n",
       "      <td>2666.8223</td>\n",
       "      <td>2487.1226</td>\n",
       "      <td>0.108363</td>\n",
       "      <td>18.944315</td>\n",
       "      <td>38.278194</td>\n",
       "      <td>50.756508</td>\n",
       "      <td>3709.6392</td>\n",
       "      <td>1048.6069</td>\n",
       "      <td>239.36952</td>\n",
       "      <td>131.41393</td>\n",
       "      <td>7.207337</td>\n",
       "      <td>30.109667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>999</td>\n",
       "      <td>246.51558</td>\n",
       "      <td>102.81991</td>\n",
       "      <td>0.757966</td>\n",
       "      <td>2573.6740</td>\n",
       "      <td>2542.2840</td>\n",
       "      <td>0.130512</td>\n",
       "      <td>19.211943</td>\n",
       "      <td>38.543340</td>\n",
       "      <td>52.329730</td>\n",
       "      <td>3622.4026</td>\n",
       "      <td>1063.8132</td>\n",
       "      <td>237.58229</td>\n",
       "      <td>130.43272</td>\n",
       "      <td>7.306250</td>\n",
       "      <td>30.752502</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>1000</td>\n",
       "      <td>294.76205</td>\n",
       "      <td>105.02041</td>\n",
       "      <td>0.792474</td>\n",
       "      <td>2348.7234</td>\n",
       "      <td>2447.9807</td>\n",
       "      <td>0.122900</td>\n",
       "      <td>24.531853</td>\n",
       "      <td>45.703700</td>\n",
       "      <td>50.095210</td>\n",
       "      <td>3651.1333</td>\n",
       "      <td>1059.6786</td>\n",
       "      <td>282.81820</td>\n",
       "      <td>155.26726</td>\n",
       "      <td>8.359403</td>\n",
       "      <td>29.557512</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       iS   aquifer permeability (mD)   aquifer gross thickness (m)   \n",
       "0       1                   254.29453                      98.67665  \\\n",
       "1       2                   232.21005                     101.61317   \n",
       "2       3                   347.02588                     110.62248   \n",
       "3       4                   416.37143                     110.71101   \n",
       "4       5                   385.43112                     106.67485   \n",
       "..    ...                         ...                           ...   \n",
       "995   996                   208.79338                     107.78278   \n",
       "996   997                   335.04092                     107.57787   \n",
       "997   998                   230.71222                     100.96610   \n",
       "998   999                   246.51558                     102.81991   \n",
       "999  1000                   294.76205                     105.02041   \n",
       "\n",
       "      aquifer net to gross (-)   aquifer top at injector (m TVD)   \n",
       "0                     0.809259                         2458.3457  \\\n",
       "1                     0.787313                         2643.6982   \n",
       "2                     0.783280                         2322.7173   \n",
       "3                     0.793836                         2409.1120   \n",
       "4                     0.803228                         2553.3394   \n",
       "..                         ...                               ...   \n",
       "995                   0.796793                         2371.8330   \n",
       "996                   0.803419                         2431.6885   \n",
       "997                   0.813266                         2666.8223   \n",
       "998                   0.757966                         2573.6740   \n",
       "999                   0.792474                         2348.7234   \n",
       "\n",
       "      aquifer top at producer (m TVD)   aquifer water salinity (ppm)   \n",
       "0                           2457.9678                       0.119523  \\\n",
       "1                           2521.1965                       0.123078   \n",
       "2                           2336.0005                       0.102066   \n",
       "3                           2465.4832                       0.126697   \n",
       "4                           2534.5093                       0.123331   \n",
       "..                                ...                            ...   \n",
       "995                         2634.3254                       0.116407   \n",
       "996                         2622.8328                       0.123286   \n",
       "997                         2487.1226                       0.108363   \n",
       "998                         2542.2840                       0.130512   \n",
       "999                         2447.9807                       0.122900   \n",
       "\n",
       "      aquifer kH net (Dm)   mass flow (kg/s)   delta T (°C)   \n",
       "0               20.306683          40.136295      49.975120  \\\n",
       "1               18.577118          37.513557      51.644176   \n",
       "2               30.069246          51.665833      47.223145   \n",
       "3               36.593388          57.302696      51.169163   \n",
       "4               33.025370          54.664562      53.064050   \n",
       "..                    ...                ...            ...   \n",
       "995             17.931303          38.144660      55.109097   \n",
       "996             28.957619          51.833920      55.581284   \n",
       "997             18.944315          38.278194      50.756508   \n",
       "998             19.211943          38.543340      52.329730   \n",
       "999             24.531853          45.703700      50.095210   \n",
       "\n",
       "      heat capacity (kJ/(kg*K))   av. production density (kg/m³)   \n",
       "0                     3664.4312                        1057.3365  \\\n",
       "1                     3651.1710                        1058.8849   \n",
       "2                     3733.5127                        1046.2684   \n",
       "3                     3636.7332                        1062.0903   \n",
       "4                     3650.8708                        1058.3341   \n",
       "..                          ...                              ...   \n",
       "995                   3679.4836                        1051.8035   \n",
       "996                   3652.3357                        1056.8402   \n",
       "997                   3709.6392                        1048.6069   \n",
       "998                   3622.4026                        1063.8132   \n",
       "999                   3651.1333                        1059.6786   \n",
       "\n",
       "      required pump power (kW)   pump volume flow (m³/h)   \n",
       "0                    248.91680                 136.65536  \\\n",
       "1                    232.31094                 127.53875   \n",
       "2                    323.81015                 177.77185   \n",
       "3                    353.78850                 194.22997   \n",
       "4                    338.69850                 185.94554   \n",
       "..                         ...                       ...   \n",
       "995                  237.80956                 130.55750   \n",
       "996                  321.61395                 176.56612   \n",
       "997                  239.36952                 131.41393   \n",
       "998                  237.58229                 130.43272   \n",
       "999                  282.81820                 155.26726   \n",
       "\n",
       "      geothermal power (MW)   COP (kW/kW)  \n",
       "0                  7.350175     29.528645  \n",
       "1                  7.073621     30.448938  \n",
       "2                  9.109110     28.131021  \n",
       "3                 10.663378     30.140543  \n",
       "4                 10.590165     31.267237  \n",
       "..                      ...           ...  \n",
       "995                7.734708     32.524796  \n",
       "996               10.522364     32.717373  \n",
       "997                7.207337     30.109667  \n",
       "998                7.306250     30.752502  \n",
       "999                8.359403     29.557512  \n",
       "\n",
       "[1000 rows x 16 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv('data/export_output.csv', \n",
    "                   skiprows = 2, \n",
    "                   delimiter = ',', \n",
    "                   encoding = \"ISO-8859-1\", \n",
    "                   skipfooter = 1)\n",
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4236036",
   "metadata": {},
   "source": [
    "## Plotting the DoubletCalc Results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d86218fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x500 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(1,3, figsize=(15,5))\n",
    "\n",
    "axes[0].plot(data[' pump volume flow (m³/h)'].sort_values(ascending=False).values, np.linspace(0.1,100,len(data)))\n",
    "axes[1].plot(data[' COP (kW/kW)'].sort_values(ascending=False).values, np.linspace(0.1,100,len(data)))\n",
    "axes[2].plot(data[' geothermal power (MW)'].sort_values(ascending=False).values, np.linspace(0.1,100,len(data)))\n",
    "\n",
    "axes[0].grid()\n",
    "axes[1].grid()\n",
    "axes[2].grid()\n",
    "\n",
    "#set label text\n",
    "axes[0].set_ylabel(\"Probability [%]\")\n",
    "axes[0].set_xlabel(\"pump volume flow (m³/h)\")\n",
    "\n",
    "axes[1].set_ylabel(\"Probability [%]\")\n",
    "axes[1].set_xlabel(\"COP (kW/kW)\")\n",
    "\n",
    "axes[2].set_ylabel(\"Probability [%]\")\n",
    "axes[2].set_xlabel(\"geothermal power (MW)\")\n",
    "\n",
    "plt.tight_layout()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}