{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "78ada340",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "\n",
    "\n",
    "# import of the predifined functions in \"functions.py\"\n",
    "from functions import calculate_power\n",
    "from functions import read_inc_power\n",
    "from functions import read_trans_power"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "fce700c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "angles_str = [\"60\", \"30\",\"00\", \"m30\", \"m60\"] # angles of incidence which were simulated (m for minus)\n",
    "\n",
    "# defining which simulation to process\n",
    "# simulation=\"Discs\" # for getting the coefficients of the original domain (discs as iterface)\n",
    "simulation='Tilted_Slits' # for getting the coefficients of the new domain (fins as iterface)\n",
    "\n",
    "freq_num=10 # number of frequencies which were simulated\n",
    "\n",
    "results_dataframes = [None] * len(angles_str) # vector for storing dataframe of the calculation for reflected power\n",
    "\n",
    "# empty dataframes for power calculation  \n",
    "df_Power_ref = pd.DataFrame()\n",
    "df_Power_inc = pd.DataFrame()\n",
    "df_Power_trans = pd.DataFrame()\n",
    "df_Power_balance = pd.DataFrame()\n",
    "df_Coefficients = pd.DataFrame()\n",
    "\n",
    "# for loop over all simulated incidence angles\n",
    "for index, angle in enumerate(angles_str):\n",
    "    \n",
    "    # calcualting power reflected from interface\n",
    "    [df,Power_ref]=calculate_power(angle,simulation,freq_num)\n",
    "    results_dataframes[index]=df  \n",
    "    df_Power_ref[angle]=np.concatenate(Power_ref)\n",
    "    \n",
    "    # reading the incoming power\n",
    "    [Power_inc,frequency]=read_inc_power(angle)\n",
    "    df_Power_inc['freq_'+angle]=frequency\n",
    "    df_Power_inc[angle]=Power_inc  \n",
    "    \n",
    "    # reading the transmitted power\n",
    "    [Power_trans]=read_trans_power(angle,simulation)\n",
    "    df_Power_trans['freq_'+angle]=frequency\n",
    "    df_Power_trans[angle]=Power_trans\n",
    "\n",
    "    # check the power balance (for soundhard interface: P_inc=P_refl+P_trans)\n",
    "    df_Power_balance['balance_'+angle]=df_Power_inc[angle]-df_Power_trans[angle]-df_Power_ref[angle]\n",
    "    df_Power_balance['Error_in_%_'+angle]=abs(df_Power_balance['balance_'+angle]/df_Power_inc[angle])*100 \n",
    "\n",
    "    # calculate transmission and reflection coefficients\n",
    "    df_Coefficients['Trans_coef_'+angle]=df_Power_trans[angle]/df_Power_inc[angle]\n",
    "    df_Coefficients['Refl_coef_'+angle]=df_Power_ref[angle]/df_Power_inc[angle]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a8ed6b1b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting Transmission Coefficients\n",
    "colors = ['red', 'blue', 'green', 'orange', 'purple']\n",
    "line_styles = ['--', '--', ':', '-.', '-.']\n",
    "for index, angle in enumerate(angles_str):\n",
    "    plt.plot(df_Power_trans['freq_'+angle], df_Coefficients['Trans_coef_'+angle],linestyle=line_styles[index], color=colors[index], label=angle+'deg')\n",
    "plt.xlabel('Frequency')\n",
    "plt.ylabel('Transmission Coefficient')\n",
    "plt.ylim(0, 1.1) \n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.title('Transmission Coefficient vs Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "ecabb1df",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting Reflection Coefficients\n",
    "colors = ['red', 'blue', 'green', 'orange', 'purple','black']\n",
    "line_styles = ['--', '--', ':', '-.', '-.']\n",
    "for index, angle in enumerate(angles_str):\n",
    "    plt.plot(df_Power_trans['freq_'+angle], df_Coefficients['Refl_coef_'+angle],linestyle=line_styles[index], color=colors[index], label=angle+' deg')\n",
    "plt.xlabel('Frequency')\n",
    "plt.ylabel('Reflection Coefficient')\n",
    "plt.ylim(0, 1.1)\n",
    "plt.grid(True)\n",
    "plt.legend()\n",
    "plt.title('Reflection Coefficient vs Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d86cd49f",
   "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>60</th>\n",
       "      <th>30</th>\n",
       "      <th>00</th>\n",
       "      <th>m30</th>\n",
       "      <th>m60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000658</td>\n",
       "      <td>1.321341e-09</td>\n",
       "      <td>0.000030</td>\n",
       "      <td>2.073327e-09</td>\n",
       "      <td>0.000658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000018</td>\n",
       "      <td>1.288445e-05</td>\n",
       "      <td>0.000023</td>\n",
       "      <td>7.218280e-06</td>\n",
       "      <td>0.000056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000029</td>\n",
       "      <td>7.330492e-06</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>2.833928e-05</td>\n",
       "      <td>0.000239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000023</td>\n",
       "      <td>6.671713e-06</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>1.213028e-05</td>\n",
       "      <td>0.000105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000012</td>\n",
       "      <td>5.053273e-06</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>7.108253e-06</td>\n",
       "      <td>0.000045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000009</td>\n",
       "      <td>3.235061e-06</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>8.158917e-06</td>\n",
       "      <td>0.000050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000006</td>\n",
       "      <td>2.194230e-06</td>\n",
       "      <td>0.000005</td>\n",
       "      <td>4.512408e-06</td>\n",
       "      <td>0.000029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>1.515330e-06</td>\n",
       "      <td>0.000004</td>\n",
       "      <td>2.934551e-06</td>\n",
       "      <td>0.000029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>1.800353e-06</td>\n",
       "      <td>0.000003</td>\n",
       "      <td>2.166262e-06</td>\n",
       "      <td>0.000031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.265365e-06</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>1.961640e-06</td>\n",
       "      <td>0.000012</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "         60            30        00           m30       m60\n",
       "0  0.000658  1.321341e-09  0.000030  2.073327e-09  0.000658\n",
       "1  0.000018  1.288445e-05  0.000023  7.218280e-06  0.000056\n",
       "2  0.000029  7.330492e-06  0.000018  2.833928e-05  0.000239\n",
       "3  0.000023  6.671713e-06  0.000005  1.213028e-05  0.000105\n",
       "4  0.000012  5.053273e-06  0.000008  7.108253e-06  0.000045\n",
       "5  0.000009  3.235061e-06  0.000004  8.158917e-06  0.000050\n",
       "6  0.000006  2.194230e-06  0.000005  4.512408e-06  0.000029\n",
       "7  0.000003  1.515330e-06  0.000004  2.934551e-06  0.000029\n",
       "8  0.000003  1.800353e-06  0.000003  2.166262e-06  0.000031\n",
       "9  0.000002  1.265365e-06  0.000002  1.961640e-06  0.000012"
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       "      <th>0</th>\n",
       "      <td>118.819</td>\n",
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       "      <th>1</th>\n",
       "      <td>237.637</td>\n",
       "      <td>0.000639</td>\n",
       "      <td>274.4</td>\n",
       "      <td>0.000275</td>\n",
       "      <td>300.0</td>\n",
       "      <td>0.000198</td>\n",
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       "      <td>237.637</td>\n",
       "      <td>0.000639</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>356.456</td>\n",
       "      <td>0.000287</td>\n",
       "      <td>411.6</td>\n",
       "      <td>0.000121</td>\n",
       "      <td>400.0</td>\n",
       "      <td>0.000111</td>\n",
       "      <td>411.6</td>\n",
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       "      <th>3</th>\n",
       "      <td>475.275</td>\n",
       "      <td>0.000161</td>\n",
       "      <td>548.8</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000070</td>\n",
       "      <td>548.8</td>\n",
       "      <td>0.000068</td>\n",
       "      <td>475.275</td>\n",
       "      <td>0.000161</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>594.093</td>\n",
       "      <td>0.000104</td>\n",
       "      <td>686.0</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.000048</td>\n",
       "      <td>686.0</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>594.093</td>\n",
       "      <td>0.000104</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>712.912</td>\n",
       "      <td>0.000073</td>\n",
       "      <td>823.2</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000035</td>\n",
       "      <td>823.2</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>712.912</td>\n",
       "      <td>0.000073</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>831.731</td>\n",
       "      <td>0.000054</td>\n",
       "      <td>960.4</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>800.0</td>\n",
       "      <td>0.000026</td>\n",
       "      <td>960.4</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>831.731</td>\n",
       "      <td>0.000054</td>\n",
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       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>950.549</td>\n",
       "      <td>0.000042</td>\n",
       "      <td>1097.6</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000021</td>\n",
       "      <td>1097.6</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>950.549</td>\n",
       "      <td>0.000042</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1069.370</td>\n",
       "      <td>0.000034</td>\n",
       "      <td>1234.8</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.000016</td>\n",
       "      <td>1234.8</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>1069.370</td>\n",
       "      <td>0.000034</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
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       "      <td>0.000029</td>\n",
       "      <td>1372.0</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.000013</td>\n",
       "      <td>1372.0</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>1188.190</td>\n",
       "      <td>0.000029</td>\n",
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       "    freq_60        60  freq_30        30  freq_00        00  freq_m30  \\\n",
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       "      <th>1</th>\n",
       "      <td>237.637</td>\n",
       "      <td>0.000612</td>\n",
       "      <td>274.4</td>\n",
       "      <td>0.000262</td>\n",
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       "      <td>0.000596</td>\n",
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       "      <th>2</th>\n",
       "      <td>356.456</td>\n",
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       "      <td>475.275</td>\n",
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       "      <td>548.8</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>500.0</td>\n",
       "      <td>0.000067</td>\n",
       "      <td>548.8</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>475.275</td>\n",
       "      <td>0.000056</td>\n",
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       "      <th>4</th>\n",
       "      <td>594.093</td>\n",
       "      <td>0.000089</td>\n",
       "      <td>686.0</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.000041</td>\n",
       "      <td>686.0</td>\n",
       "      <td>0.000037</td>\n",
       "      <td>594.093</td>\n",
       "      <td>0.000060</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>712.912</td>\n",
       "      <td>0.000061</td>\n",
       "      <td>823.2</td>\n",
       "      <td>0.000025</td>\n",
       "      <td>700.0</td>\n",
       "      <td>0.000031</td>\n",
       "      <td>823.2</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>712.912</td>\n",
       "      <td>0.000021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>831.731</td>\n",
       "      <td>0.000046</td>\n",
       "      <td>960.4</td>\n",
       "      <td>0.000018</td>\n",
       "      <td>800.0</td>\n",
       "      <td>0.000022</td>\n",
       "      <td>960.4</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>831.731</td>\n",
       "      <td>0.000024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>950.549</td>\n",
       "      <td>0.000036</td>\n",
       "      <td>1097.6</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.000017</td>\n",
       "      <td>1097.6</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>950.549</td>\n",
       "      <td>0.000012</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1069.370</td>\n",
       "      <td>0.000029</td>\n",
       "      <td>1234.8</td>\n",
       "      <td>0.000010</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.000014</td>\n",
       "      <td>1234.8</td>\n",
       "      <td>0.000011</td>\n",
       "      <td>1069.370</td>\n",
       "      <td>0.000003</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1188.190</td>\n",
       "      <td>0.000024</td>\n",
       "      <td>1372.0</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>1100.0</td>\n",
       "      <td>0.000012</td>\n",
       "      <td>1372.0</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>1188.190</td>\n",
       "      <td>0.000015</td>\n",
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       "    freq_60        60  freq_30        30  freq_00        00  freq_m30  \\\n",
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       "2   356.456  0.000252    411.6  0.000114    400.0  0.000094     411.6   \n",
       "3   475.275  0.000134    548.8  0.000061    500.0  0.000067     548.8   \n",
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>balance_60</th>\n",
       "      <th>Error_in_%_60</th>\n",
       "      <th>balance_30</th>\n",
       "      <th>Error_in_%_30</th>\n",
       "      <th>balance_00</th>\n",
       "      <th>Error_in_%_00</th>\n",
       "      <th>balance_m30</th>\n",
       "      <th>Error_in_%_m30</th>\n",
       "      <th>balance_m60</th>\n",
       "      <th>Error_in_%_m60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.000030</td>\n",
       "      <td>1.186312</td>\n",
       "      <td>-2.395516e-06</td>\n",
       "      <td>0.216984</td>\n",
       "      <td>-3.468353e-06</td>\n",
       "      <td>0.772930</td>\n",
       "      <td>-1.773980e-05</td>\n",
       "      <td>1.606858</td>\n",
       "      <td>-4.651930e-05</td>\n",
       "      <td>1.822734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.000009</td>\n",
       "      <td>1.338932</td>\n",
       "      <td>1.564011e-07</td>\n",
       "      <td>0.056884</td>\n",
       "      <td>-2.289205e-06</td>\n",
       "      <td>1.154023</td>\n",
       "      <td>-5.065495e-06</td>\n",
       "      <td>1.842353</td>\n",
       "      <td>-1.327702e-05</td>\n",
       "      <td>2.078135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.000005</td>\n",
       "      <td>1.916189</td>\n",
       "      <td>3.065287e-07</td>\n",
       "      <td>0.252770</td>\n",
       "      <td>-1.550867e-06</td>\n",
       "      <td>1.399665</td>\n",
       "      <td>-3.107563e-07</td>\n",
       "      <td>0.256256</td>\n",
       "      <td>4.012850e-06</td>\n",
       "      <td>1.399570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.000004</td>\n",
       "      <td>2.355722</td>\n",
       "      <td>-4.358617e-08</td>\n",
       "      <td>0.064528</td>\n",
       "      <td>-1.710858e-06</td>\n",
       "      <td>2.435782</td>\n",
       "      <td>-2.837477e-07</td>\n",
       "      <td>0.420078</td>\n",
       "      <td>8.485206e-07</td>\n",
       "      <td>0.525495</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>3.341543</td>\n",
       "      <td>4.720634e-07</td>\n",
       "      <td>1.104483</td>\n",
       "      <td>-6.804654e-07</td>\n",
       "      <td>1.409820</td>\n",
       "      <td>-1.088620e-06</td>\n",
       "      <td>2.547035</td>\n",
       "      <td>-4.833402e-07</td>\n",
       "      <td>0.465188</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>4.446738</td>\n",
       "      <td>5.215487e-07</td>\n",
       "      <td>1.784015</td>\n",
       "      <td>-8.166981e-07</td>\n",
       "      <td>2.333414</td>\n",
       "      <td>-8.087404e-07</td>\n",
       "      <td>2.766386</td>\n",
       "      <td>2.170086e-06</td>\n",
       "      <td>2.956972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.000003</td>\n",
       "      <td>5.491210</td>\n",
       "      <td>5.251447e-07</td>\n",
       "      <td>2.484672</td>\n",
       "      <td>-7.026806e-07</td>\n",
       "      <td>2.658335</td>\n",
       "      <td>-7.734992e-07</td>\n",
       "      <td>3.659737</td>\n",
       "      <td>1.343435e-06</td>\n",
       "      <td>2.466123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.000002</td>\n",
       "      <td>5.601559</td>\n",
       "      <td>5.559471e-07</td>\n",
       "      <td>3.494633</td>\n",
       "      <td>-5.701651e-07</td>\n",
       "      <td>2.773365</td>\n",
       "      <td>-9.849212e-07</td>\n",
       "      <td>6.191125</td>\n",
       "      <td>2.704936e-07</td>\n",
       "      <td>0.642806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.000002</td>\n",
       "      <td>6.409852</td>\n",
       "      <td>4.700340e-07</td>\n",
       "      <td>3.816611</td>\n",
       "      <td>-5.342472e-07</td>\n",
       "      <td>3.260779</td>\n",
       "      <td>-8.563612e-07</td>\n",
       "      <td>6.953534</td>\n",
       "      <td>-9.799783e-08</td>\n",
       "      <td>0.287618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.000002</td>\n",
       "      <td>7.297702</td>\n",
       "      <td>5.127364e-07</td>\n",
       "      <td>5.236356</td>\n",
       "      <td>-5.393413e-07</td>\n",
       "      <td>4.054148</td>\n",
       "      <td>-6.513558e-07</td>\n",
       "      <td>6.652015</td>\n",
       "      <td>1.422735e-06</td>\n",
       "      <td>4.990238</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   balance_60  Error_in_%_60    balance_30  Error_in_%_30    balance_00  \\\n",
       "0    0.000030       1.186312 -2.395516e-06       0.216984 -3.468353e-06   \n",
       "1    0.000009       1.338932  1.564011e-07       0.056884 -2.289205e-06   \n",
       "2    0.000005       1.916189  3.065287e-07       0.252770 -1.550867e-06   \n",
       "3    0.000004       2.355722 -4.358617e-08       0.064528 -1.710858e-06   \n",
       "4    0.000003       3.341543  4.720634e-07       1.104483 -6.804654e-07   \n",
       "5    0.000003       4.446738  5.215487e-07       1.784015 -8.166981e-07   \n",
       "6    0.000003       5.491210  5.251447e-07       2.484672 -7.026806e-07   \n",
       "7    0.000002       5.601559  5.559471e-07       3.494633 -5.701651e-07   \n",
       "8    0.000002       6.409852  4.700340e-07       3.816611 -5.342472e-07   \n",
       "9    0.000002       7.297702  5.127364e-07       5.236356 -5.393413e-07   \n",
       "\n",
       "   Error_in_%_00   balance_m30  Error_in_%_m30   balance_m60  Error_in_%_m60  \n",
       "0       0.772930 -1.773980e-05        1.606858 -4.651930e-05        1.822734  \n",
       "1       1.154023 -5.065495e-06        1.842353 -1.327702e-05        2.078135  \n",
       "2       1.399665 -3.107563e-07        0.256256  4.012850e-06        1.399570  \n",
       "3       2.435782 -2.837477e-07        0.420078  8.485206e-07        0.525495  \n",
       "4       1.409820 -1.088620e-06        2.547035 -4.833402e-07        0.465188  \n",
       "5       2.333414 -8.087404e-07        2.766386  2.170086e-06        2.956972  \n",
       "6       2.658335 -7.734992e-07        3.659737  1.343435e-06        2.466123  \n",
       "7       2.773365 -9.849212e-07        6.191125  2.704936e-07        0.642806  \n",
       "8       3.260779 -8.563612e-07        6.953534 -9.799783e-08        0.287618  \n",
       "9       4.054148 -6.513558e-07        6.652015  1.422735e-06        4.990238  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "<div>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Trans_coef_60</th>\n",
       "      <th>Refl_coef_60</th>\n",
       "      <th>Trans_coef_30</th>\n",
       "      <th>Refl_coef_30</th>\n",
       "      <th>Trans_coef_00</th>\n",
       "      <th>Refl_coef_00</th>\n",
       "      <th>Trans_coef_m30</th>\n",
       "      <th>Refl_coef_m30</th>\n",
       "      <th>Trans_coef_m60</th>\n",
       "      <th>Refl_coef_m60</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.730330</td>\n",
       "      <td>0.257807</td>\n",
       "      <td>1.002169</td>\n",
       "      <td>0.000001</td>\n",
       "      <td>0.939777</td>\n",
       "      <td>0.067952</td>\n",
       "      <td>1.016067</td>\n",
       "      <td>0.000002</td>\n",
       "      <td>0.760413</td>\n",
       "      <td>0.257815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.958265</td>\n",
       "      <td>0.028345</td>\n",
       "      <td>0.952570</td>\n",
       "      <td>0.046862</td>\n",
       "      <td>0.897667</td>\n",
       "      <td>0.113873</td>\n",
       "      <td>0.992170</td>\n",
       "      <td>0.026253</td>\n",
       "      <td>0.932759</td>\n",
       "      <td>0.088023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.878429</td>\n",
       "      <td>0.102409</td>\n",
       "      <td>0.937023</td>\n",
       "      <td>0.060449</td>\n",
       "      <td>0.848253</td>\n",
       "      <td>0.165744</td>\n",
       "      <td>0.768871</td>\n",
       "      <td>0.233692</td>\n",
       "      <td>0.153683</td>\n",
       "      <td>0.832321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.832582</td>\n",
       "      <td>0.143861</td>\n",
       "      <td>0.901873</td>\n",
       "      <td>0.098772</td>\n",
       "      <td>0.949299</td>\n",
       "      <td>0.075059</td>\n",
       "      <td>0.824617</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.344271</td>\n",
       "      <td>0.650474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.855745</td>\n",
       "      <td>0.110839</td>\n",
       "      <td>0.870724</td>\n",
       "      <td>0.118231</td>\n",
       "      <td>0.850217</td>\n",
       "      <td>0.163881</td>\n",
       "      <td>0.859159</td>\n",
       "      <td>0.166311</td>\n",
       "      <td>0.576115</td>\n",
       "      <td>0.428537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.830757</td>\n",
       "      <td>0.124776</td>\n",
       "      <td>0.871501</td>\n",
       "      <td>0.110659</td>\n",
       "      <td>0.897418</td>\n",
       "      <td>0.125916</td>\n",
       "      <td>0.748579</td>\n",
       "      <td>0.279085</td>\n",
       "      <td>0.290505</td>\n",
       "      <td>0.679925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.843713</td>\n",
       "      <td>0.101375</td>\n",
       "      <td>0.871335</td>\n",
       "      <td>0.103818</td>\n",
       "      <td>0.847375</td>\n",
       "      <td>0.179208</td>\n",
       "      <td>0.823097</td>\n",
       "      <td>0.213500</td>\n",
       "      <td>0.449625</td>\n",
       "      <td>0.525713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.865751</td>\n",
       "      <td>0.078234</td>\n",
       "      <td>0.869801</td>\n",
       "      <td>0.095252</td>\n",
       "      <td>0.817170</td>\n",
       "      <td>0.210564</td>\n",
       "      <td>0.877448</td>\n",
       "      <td>0.184463</td>\n",
       "      <td>0.295397</td>\n",
       "      <td>0.698175</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.841859</td>\n",
       "      <td>0.094042</td>\n",
       "      <td>0.815648</td>\n",
       "      <td>0.146186</td>\n",
       "      <td>0.876480</td>\n",
       "      <td>0.156127</td>\n",
       "      <td>0.893638</td>\n",
       "      <td>0.175897</td>\n",
       "      <td>0.093388</td>\n",
       "      <td>0.909489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.851220</td>\n",
       "      <td>0.075803</td>\n",
       "      <td>0.818410</td>\n",
       "      <td>0.129226</td>\n",
       "      <td>0.883385</td>\n",
       "      <td>0.157156</td>\n",
       "      <td>0.866186</td>\n",
       "      <td>0.200334</td>\n",
       "      <td>0.530004</td>\n",
       "      <td>0.420094</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Trans_coef_60  Refl_coef_60  Trans_coef_30  Refl_coef_30  Trans_coef_00  \\\n",
       "0       0.730330      0.257807       1.002169      0.000001       0.939777   \n",
       "1       0.958265      0.028345       0.952570      0.046862       0.897667   \n",
       "2       0.878429      0.102409       0.937023      0.060449       0.848253   \n",
       "3       0.832582      0.143861       0.901873      0.098772       0.949299   \n",
       "4       0.855745      0.110839       0.870724      0.118231       0.850217   \n",
       "5       0.830757      0.124776       0.871501      0.110659       0.897418   \n",
       "6       0.843713      0.101375       0.871335      0.103818       0.847375   \n",
       "7       0.865751      0.078234       0.869801      0.095252       0.817170   \n",
       "8       0.841859      0.094042       0.815648      0.146186       0.876480   \n",
       "9       0.851220      0.075803       0.818410      0.129226       0.883385   \n",
       "\n",
       "   Refl_coef_00  Trans_coef_m30  Refl_coef_m30  Trans_coef_m60  Refl_coef_m60  \n",
       "0      0.067952        1.016067       0.000002        0.760413       0.257815  \n",
       "1      0.113873        0.992170       0.026253        0.932759       0.088023  \n",
       "2      0.165744        0.768871       0.233692        0.153683       0.832321  \n",
       "3      0.075059        0.824617       0.179584        0.344271       0.650474  \n",
       "4      0.163881        0.859159       0.166311        0.576115       0.428537  \n",
       "5      0.125916        0.748579       0.279085        0.290505       0.679925  \n",
       "6      0.179208        0.823097       0.213500        0.449625       0.525713  \n",
       "7      0.210564        0.877448       0.184463        0.295397       0.698175  \n",
       "8      0.156127        0.893638       0.175897        0.093388       0.909489  \n",
       "9      0.157156        0.866186       0.200334        0.530004       0.420094  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Display Dataframes for Verification \n",
    "\n",
    "display(df_Power_ref)\n",
    "display(df_Power_inc)\n",
    "display(df_Power_trans)\n",
    "display(df_Power_balance)\n",
    "display(df_Coefficients)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e7839fb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "12c06515",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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