{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "# Handle all includes\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "\n",
    "import os\n",
    "import shutil\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "from spatz.utils.preprocess import preprocess_file\n",
    "from spatz.simulation import Simulation, UniformTimeSteps\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Do preprocessing\n",
    "PATH = \"data/simulations\"\n",
    "TMP = f\"{PATH}/temp\"\n",
    "FILE = \"40km\"\n",
    "\n",
    "if os.path.isdir(TMP):\n",
    "    shutil.rmtree(TMP)\n",
    "os.mkdir(TMP)\n",
    "\n",
    "df = preprocess_file(f\"{PATH}/{FILE}.txt\")\n",
    "df.to_csv(f\"{TMP}/{FILE}.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create simulation objects\n",
    "timesteps = UniformTimeSteps(0.1, mu=0, sigma=0, delay_only=True)\n",
    "simulation = Simulation(timesteps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed 65160 lines in 0.3s.\n",
      "Used 65160 lines due to step size\n"
     ]
    }
   ],
   "source": [
    "from spatz.sensors.antenna.pathloss import AntennaPathloss\n",
    "from spatz.sensors.antenna.tx_gain import AntennaTxGain\n",
    "from spatz.sensors.antenna.constants import STAHR_LORA_FREQ, STAHR_GS_OFFSET\n",
    "\n",
    "alt = simulation.add_observer(['altitude'])\n",
    "fspl_gs = simulation.add_sensor(AntennaPathloss,frequency=STAHR_LORA_FREQ,rx_antenna_offset=STAHR_GS_OFFSET)\n",
    "\n",
    "tx_gain = simulation.add_sensor(AntennaTxGain,gain_pattern_path=f\"data/gain_pattern/farfield_tx_aisler_v1.txt\",rx_antenna_offset = STAHR_GS_OFFSET)\n",
    "\n",
    "simulation.load(f\"{TMP}/{FILE}.csv\")\n",
    "logger = simulation.get_logger()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████▉| 197.89999999999304/197.96503111341 [00:06<00:00, 29.46it/s]\n"
     ]
    }
   ],
   "source": [
    "# Run simulation\n",
    "for step, t, dt in simulation.run(verbose=True):\n",
    "    fspl_gs()\n",
    "    tx_gain()\n",
    "    alt()\n",
    "\n",
    "df = logger.get_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "        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>time</th>\n",
       "      <th>antenna/pathloss/pad_distance</th>\n",
       "      <th>antenna/pathloss/gs_distance</th>\n",
       "      <th>antenna/pathloss/out</th>\n",
       "      <th>antenna/tx_gain/rocket_x</th>\n",
       "      <th>antenna/tx_gain/rocket_y</th>\n",
       "      <th>antenna/tx_gain/rocket_z</th>\n",
       "      <th>antenna/tx_gain/pos_x</th>\n",
       "      <th>antenna/tx_gain/pos_y</th>\n",
       "      <th>antenna/tx_gain/pos_z</th>\n",
       "      <th>antenna/tx_gain/theta</th>\n",
       "      <th>antenna/tx_gain/out</th>\n",
       "      <th>general/altitude</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.1</td>\n",
       "      <td>2393.642403</td>\n",
       "      <td>2393.642403</td>\n",
       "      <td>107.81229</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.774045</td>\n",
       "      <td>0.62666</td>\n",
       "      <td>0.090286</td>\n",
       "      <td>101.321859</td>\n",
       "      <td>4.214389</td>\n",
       "      <td>318.993506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2</td>\n",
       "      <td>2393.635673</td>\n",
       "      <td>2393.635673</td>\n",
       "      <td>107.812266</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.774038</td>\n",
       "      <td>0.626662</td>\n",
       "      <td>0.090333</td>\n",
       "      <td>101.324573</td>\n",
       "      <td>4.214139</td>\n",
       "      <td>319.087226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.3</td>\n",
       "      <td>2393.630009</td>\n",
       "      <td>2393.630009</td>\n",
       "      <td>107.812245</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.77402</td>\n",
       "      <td>0.626663</td>\n",
       "      <td>0.090481</td>\n",
       "      <td>101.333096</td>\n",
       "      <td>4.213355</td>\n",
       "      <td>319.413466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.4</td>\n",
       "      <td>2393.633015</td>\n",
       "      <td>2393.633015</td>\n",
       "      <td>107.812256</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773985</td>\n",
       "      <td>0.626662</td>\n",
       "      <td>0.090782</td>\n",
       "      <td>101.350431</td>\n",
       "      <td>4.21176</td>\n",
       "      <td>320.094623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.5</td>\n",
       "      <td>2393.648731</td>\n",
       "      <td>2393.648731</td>\n",
       "      <td>107.812313</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773932</td>\n",
       "      <td>0.626658</td>\n",
       "      <td>0.091262</td>\n",
       "      <td>101.37803</td>\n",
       "      <td>4.209221</td>\n",
       "      <td>321.195802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1974</th>\n",
       "      <td>197.5</td>\n",
       "      <td>36965.892649</td>\n",
       "      <td>36965.892649</td>\n",
       "      <td>131.587129</td>\n",
       "      <td>0.005339</td>\n",
       "      <td>0.199508</td>\n",
       "      <td>-0.979882</td>\n",
       "      <td>-0.965728</td>\n",
       "      <td>0.038192</td>\n",
       "      <td>-0.256731</td>\n",
       "      <td>104.716086</td>\n",
       "      <td>3.878095</td>\n",
       "      <td>201.53925</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1975</th>\n",
       "      <td>197.6</td>\n",
       "      <td>36977.682744</td>\n",
       "      <td>36977.682744</td>\n",
       "      <td>131.589899</td>\n",
       "      <td>0.005338</td>\n",
       "      <td>0.199181</td>\n",
       "      <td>-0.979948</td>\n",
       "      <td>-0.965398</td>\n",
       "      <td>0.038184</td>\n",
       "      <td>-0.257971</td>\n",
       "      <td>104.788403</td>\n",
       "      <td>3.870429</td>\n",
       "      <td>157.943233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1976</th>\n",
       "      <td>197.7</td>\n",
       "      <td>36989.474675</td>\n",
       "      <td>36989.474675</td>\n",
       "      <td>131.592668</td>\n",
       "      <td>0.005337</td>\n",
       "      <td>0.198854</td>\n",
       "      <td>-0.980015</td>\n",
       "      <td>-0.965067</td>\n",
       "      <td>0.038177</td>\n",
       "      <td>-0.259205</td>\n",
       "      <td>104.860455</td>\n",
       "      <td>3.862792</td>\n",
       "      <td>114.487215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1977</th>\n",
       "      <td>197.8</td>\n",
       "      <td>37001.267964</td>\n",
       "      <td>37001.267964</td>\n",
       "      <td>131.595437</td>\n",
       "      <td>0.005336</td>\n",
       "      <td>0.198527</td>\n",
       "      <td>-0.980081</td>\n",
       "      <td>-0.964737</td>\n",
       "      <td>0.038169</td>\n",
       "      <td>-0.260435</td>\n",
       "      <td>104.932242</td>\n",
       "      <td>3.855182</td>\n",
       "      <td>71.171197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1978</th>\n",
       "      <td>197.9</td>\n",
       "      <td>37013.062286</td>\n",
       "      <td>37013.062286</td>\n",
       "      <td>131.598205</td>\n",
       "      <td>0.005335</td>\n",
       "      <td>0.198199</td>\n",
       "      <td>-0.980147</td>\n",
       "      <td>-0.964406</td>\n",
       "      <td>0.038162</td>\n",
       "      <td>-0.261659</td>\n",
       "      <td>105.003766</td>\n",
       "      <td>3.847586</td>\n",
       "      <td>27.99477</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1979 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       time antenna/pathloss/pad_distance antenna/pathloss/gs_distance  \\\n",
       "0       0.1                   2393.642403                  2393.642403   \n",
       "1       0.2                   2393.635673                  2393.635673   \n",
       "2       0.3                   2393.630009                  2393.630009   \n",
       "3       0.4                   2393.633015                  2393.633015   \n",
       "4       0.5                   2393.648731                  2393.648731   \n",
       "...     ...                           ...                          ...   \n",
       "1974  197.5                  36965.892649                 36965.892649   \n",
       "1975  197.6                  36977.682744                 36977.682744   \n",
       "1976  197.7                  36989.474675                 36989.474675   \n",
       "1977  197.8                  37001.267964                 37001.267964   \n",
       "1978  197.9                  37013.062286                 37013.062286   \n",
       "\n",
       "     antenna/pathloss/out antenna/tx_gain/rocket_x antenna/tx_gain/rocket_y  \\\n",
       "0               107.81229                      0.0                 0.171335   \n",
       "1              107.812266                      0.0                 0.171335   \n",
       "2              107.812245                     -0.0                 0.171335   \n",
       "3              107.812256                     -0.0                 0.171335   \n",
       "4              107.812313                     -0.0                 0.171335   \n",
       "...                   ...                      ...                      ...   \n",
       "1974           131.587129                 0.005339                 0.199508   \n",
       "1975           131.589899                 0.005338                 0.199181   \n",
       "1976           131.592668                 0.005337                 0.198854   \n",
       "1977           131.595437                 0.005336                 0.198527   \n",
       "1978           131.598205                 0.005335                 0.198199   \n",
       "\n",
       "     antenna/tx_gain/rocket_z antenna/tx_gain/pos_x antenna/tx_gain/pos_y  \\\n",
       "0                    0.985213              0.774045               0.62666   \n",
       "1                    0.985213              0.774038              0.626662   \n",
       "2                    0.985213               0.77402              0.626663   \n",
       "3                    0.985213              0.773985              0.626662   \n",
       "4                    0.985213              0.773932              0.626658   \n",
       "...                       ...                   ...                   ...   \n",
       "1974                -0.979882             -0.965728              0.038192   \n",
       "1975                -0.979948             -0.965398              0.038184   \n",
       "1976                -0.980015             -0.965067              0.038177   \n",
       "1977                -0.980081             -0.964737              0.038169   \n",
       "1978                -0.980147             -0.964406              0.038162   \n",
       "\n",
       "     antenna/tx_gain/pos_z antenna/tx_gain/theta antenna/tx_gain/out  \\\n",
       "0                 0.090286            101.321859            4.214389   \n",
       "1                 0.090333            101.324573            4.214139   \n",
       "2                 0.090481            101.333096            4.213355   \n",
       "3                 0.090782            101.350431             4.21176   \n",
       "4                 0.091262             101.37803            4.209221   \n",
       "...                    ...                   ...                 ...   \n",
       "1974             -0.256731            104.716086            3.878095   \n",
       "1975             -0.257971            104.788403            3.870429   \n",
       "1976             -0.259205            104.860455            3.862792   \n",
       "1977             -0.260435            104.932242            3.855182   \n",
       "1978             -0.261659            105.003766            3.847586   \n",
       "\n",
       "     general/altitude  \n",
       "0          318.993506  \n",
       "1          319.087226  \n",
       "2          319.413466  \n",
       "3          320.094623  \n",
       "4          321.195802  \n",
       "...               ...  \n",
       "1974        201.53925  \n",
       "1975       157.943233  \n",
       "1976       114.487215  \n",
       "1977        71.171197  \n",
       "1978         27.99477  \n",
       "\n",
       "[1979 rows x 13 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"general/altitude\"].max()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "132.97536657811125\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.plot(df['time'][1:], df['antenna/pathloss/out'][1:], label='FSPL')\n",
    "plt.ylabel(\"Frespace pathloss [dB]\")\n",
    "plt.xlabel(\"Time [s]\")\n",
    "\n",
    "print(np.max(df['antenna/pathloss/out'][1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "43372.36295531341\n"
     ]
    },
    {
     "data": {
      "image/png": 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CsFrNjilyzVQ0iUipcTY9lbUfPkzT5QMJ4yTHLaFs6/QVrUbOpXK14r3nlNjPt1wA7R4eg9vwrcTVeIxMw4e6BfuJWvkYO9+6jX1bVpkdUeSaqGgSkVJh228/Xti7lPoTAGtD+lB+5HqaduhlcjK5nMDgisQMepecIZtYE9qPXMODJrlbqD27J+sn3E/K8YNmR3Q5Fovlovu3ifOoaBKREi03J5s1n/yDpsv7E8ZJTlhC2dF1BtFDp+LnH2R2PLFDhcrVaDf4E049spqNAZ1wsxi0SVuA/2fRxE35J1nn0s2OWKINHDgQi8WCxWLB09OT0NBQunbtytSpU7H+5XBnYmIiPXr0sKtfewqsQ4cOYbFYiI+Pv8b0RSUlJTFs2DDq1q2Lj48PoaGhtG/fnsmTJ5OVlWVrt2XLFu666y4qV66Mj48P4eHh9O3bl5SUFKfkuFYqmkSkxDp+YAeH3rmFdkkXbgK6tuLdBI1YR5P2PU1OJteiangDWo2cw+47ZrPboxF+lhxijn5O5vgo1s+dqJPFr6B79+4kJiZy6NAhFixYQMeOHRk2bBh33HEH+fn5tnZhYWF4e5fM8/oOHDhAixYtWLx4MW+++SabN28mLi6O5557jnnz5rF06VIATp48SefOnalQoQKLFi1i165dTJs2japVq5KZmWnqGFQ0iUiJtOHnTwn6sjP18/eQTjk2xUwk+qkvdcNYF9CwdWcavLCajW0ncMISSiXO0Cb+3+wZ2559W/64egdlkLe3N2FhYVSrVo2WLVvywgsv8OOPP7JgwQKmT59ua/fnvUe5ubk89dRTVKlSBR8fH2rVqsXYsWMBCA8PB+Cee+7BYrHYHv9VRMSFcwVbtGiBxWLhtttuAy7c923MmDFUr14db29vmjdvzsKFC684hn/84x94eHiwYcMG7rvvPho1akTt2rXp1asXv/zyC3feeScAq1atIj09nS+++IIWLVoQERFBx44def/99215zKKiSURKlOzzmaz74AFab3wOf8t5dnk24fyjK2nZ7WGzo4kTWdzcaHX7I1R8Pp41tZ8my/CmYf4uas++g7UfDSD9dHLxhzAMyM0058cwrjt+p06diIqKYvbs2Zdc/+mnn/Lzzz/z3XffkZCQwNdff20rjtavXw/AtGnTSExMtD3+q3XrLty3cenSpSQmJtpe64MPPuDdd99l/PjxbN26lW7dunHXXXexd+/eS/Zz+vRpFi9ezJAhQyhXrtwl21gsFuDC3rL8/HzmzJmD4YT3yZk045iIlBhJR/eR8WU/2ubvocCwsK7mINr0H4uHp5fZ0aSYePv40a7/a6Qcf5Sd346k9dllRJ+ey5mPlrEucgSt7xlWfPe0y8uCt6oXT99X88IJ8Lp08eCIhg0bsnXr1kuuO3bsGPXq1ePmm2/GYrFQq1Yt27pKlSoBEBwcTFhY2GX7L2xXsWLFIu3Gjx/P888/z/333w/A22+/za+//sqECROYNGnSRf3s27cPwzBo0KBBkeUhISFkZ2cDMGTIEN5++23atWvHCy+8wAMPPMCTTz5J27Zt6dSpE/379yc0NNSet6XYaE+TiJQIO1b9gteUjtTP30Ma/uzsPI2YQe+qYCojKleLoPXI2ezoOoNDbjUpz1nabn+VfWPbsWfTSrPjlViGYdj20PzVAw88QHx8PA0aNODpp59m8eLFTnnNjIwMTpw4Qfv27Yssb9++Pbt27XKor3Xr1hEfH0+TJk3IycmxLX/jjTdISkrik08+oUmTJnzyySc0bNiQbdu2OWUM16rE7Gl66623GDVqFMOGDWPChAkAZGdnM3LkSL799ltycnLo1q0bH3/8cZFK88iRIwwePJhff/0Vf39/BgwYwNixY/H407T9K1asYMSIEezYsYMaNWrw4osvMnDgwCKvP2nSJN555x2SkpKIiorio48+om3btjdi6CJlmmG1svbbN2id8B4eFiv73Wvj+9A3NI1oaHY0MUGT9j3Ja9OFNd+Po0nCJOrn78H6Yy/Wru5N44fHExBUwXkv5ul3YY+PGTz9nNLNrl27LnueT1RUFPv372fRokUsXbqU++67jy5duvD999875bUdUbduXSwWCwkJCUWW165dGwBfX9+LnlOxYkXuvfde7r33Xt58801atGjB+PHj+fLLL29I5kspEXua1q9fz6effkqzZs2KLH/mmWf4+eefmTVrFitXruTEiRP07t3btr6goICePXuSm5vL6tWr+fLLL5k+fTqjR4+2tTl48CA9e/akY8eOxMfHM3z4cB577DEWLVpkazNz5kxGjBjByy+/zKZNm4iKiqJbt26mX9oo4urycnNY/9FDtNszHg+LlQ2BXak64jeqqmAq0zy9vGn3wEvkDF7HhsCuuFkMok/9wPn3W7F50ZfOm1XcYrlwiMyMn8vsHXLE8uXL2bZtG3369Llsm8DAQPr27cvnn3/OzJkz+eGHH0hNTQXA09OTgqtcsejldWFP75/bBQYGUrVqVVatKjpJ6apVq2jcuPEl+6lYsSJdu3Zl4sSJ13QFnJeXF3Xq1NHVc+fOnePBBx/k888/p3z58rbl6enpTJkyhffee49OnTrRqlUrpk2bxurVq1mzZg0AixcvZufOnfz3v/+lefPm9OjRg9dee41JkyaRm5sLwCeffEJERATvvvsujRo1YujQofztb3/j/ffft73We++9x+OPP84jjzxC48aN+eSTT/Dz82Pq1Kk39s0QKUPSz5wi4d1Y2p75hQLDwpr6/6TV8O/wLRdgdjQpIULCatJ6xPds7/wVxyxVqEwqLeKeZsv420k6cukTjl1VTk4OSUlJHD9+nE2bNvHmm2/Sq1cv7rjjDvr373/J50yaNIlvvvmG3bt3s2fPHmbNmkVYWBjBwcHAhSvoli1bRlJSEmfOnLlkH5UrV8bX15eFCxeSnJxMevqFObWeffZZ3n77bWbOnElCQgL/+te/iI+PZ9iwYZcdw8cff0x+fj6tW7dm5syZ7Nq1i4SEBP773/+ye/du3P937tq8efN46KGHmDdvHnv27CEhIYHx48czf/58evUydzJb0w/PDRkyhJ49e9KlSxdef/112/KNGzeSl5dHly5dbMsaNmxIzZo1iYuLo127dsTFxdG0adMih+u6devG4MGD2bFjBy1atCAuLq5IH4Vthg8fDly4JHPjxo2MGjXKtt7NzY0uXboQFxd32dw5OTlFjr9mZGQAkJeXR15e3rW9GZdQ2Jcz+yxpNEbX4MgYEw/vxphxP5HWY2QaPiTc/D6tbruX/IICKMFz9Wg7mqNBu9vJbtaB1TNfpfXxr2ieFUfWlPbE1RtC897/tOu8t7y8PAzDwGq12q7IKnxc0hmGwcKFC6lSpQoeHh6UL1+eZs2aMWHCBAYMGIDFYikyjsIx+vv7M378ePbu3Yu7uztt2rRh3rx5tjbvvPMO//znP/n888+pVq0aBw4cuOi13dzcmDBhAq+//jqjR4/mlltuYfny5QwdOpS0tDRGjhxJSkoKjRs3Zu7cudSpU+ey72lERAQbN25k7NixjBo1imPHjuHt7U3jxo0ZOXIkgwcPxmq10rBhQ3x9fRk5ciRHjx7F29ubevXq8dlnn/Hggw/a+ndkOxa+J3l5ebbirJAjv+sWw8Tr+b799lveeOMN1q9fj4+PD7fddhvNmzdnwoQJzJgxg0ceeaRIYQLQtm1bOnbsyNtvv80TTzzB4cOHixxqy8rKoly5csyfP58ePXpQv359HnnkkSJF0fz58+nZsydZWVmcOXOGatWqsXr1amJiYmxtnnvuOVauXMnatWsvmf2VV17h1VdfvWj5jBkz8PNzzrFqEVeUfXIfXY5OoKIlg2SjPCvCR+JToabZsaSUyD5znEaHp9PMuHBuTALhxNcYiE9I7Ss+z8PDg7CwMGrUqGE75CRlR25uLkePHiUpKanIZKBwoW544IEHSE9PJzAw8Ir9mLan6ejRowwbNowlS5bg4+NjVoxrNmrUKEaMGGF7nJGRQY0aNYiNjb3qm+6IvLw8lixZQteuXfH09HRavyWJxuga7BnjthWzaHx0LD6WPPa518av/0x6Vy09N9rVdiwZrAWPsubnSTTe8S4NOETdI6+yLvd+mvR787KHd7Ozszl69Cj+/v54e3tz9uxZAgICLnvlWWlnGIbG+CfZ2dn4+vrSoUOHi2qOwiNF9jCtaNq4cSMpKSm0bNnStqygoIDffvuNiRMnsmjRInJzc0lLS7MdfwVITk62zRURFhZmm3jrz+sL1xX+Wbjsz20CAwPx9fXF3d0dd3f3S7a50twV3t7el5yq3tPTs1g+aIqr35JEY3QNlxvj+h8/psWmf+NhsbLFty11/zGr1M7uXZa3Y4ng6Um7e0dy6pb72PD1MFqfXUZM8jcc/2A5R7q8S2T7Oy96SkFBARaLBTc3N9sXbOFjV1R4uEpjvKBwu1/q99qR33PT3snOnTuzbds24uPjbT+tW7fmwQcftP3d09OTZcuW2Z6TkJDAkSNHbIfRYmJi2LZtW5Gr3JYsWUJgYKDtDP6YmJgifRS2KezDy8uLVq1aFWljtVpZtmxZkcN1InLt1sx4jTabR+FhsbI+KJbGz8wrtQWTlBwhYTVoPXI2Wzp8SjIVqWYkE7nkIdZ9+BAZaafNjicuyLQ9TQEBAURGRhZZVq5cOSpWrGhbPmjQIEaMGEGFChUIDAzkqaeeIiYmhnbt2gEQGxtL48aNefjhhxk3bhxJSUm8+OKLDBkyxLYX6Mknn2TixIk899xzPProoyxfvpzvvvuOX375xfa6I0aMYMCAAbRu3Zq2bdsyYcIEMjMzeeSRR27QuyHimgyrlTVTRhBzfBoAa0Lvp+0THxffDM9SJkV1up+zrWJZ+9UzRJ+eS9vUn0mZsIoD7d+gedcHzI4nLsT0q+eu5P3338fNzY0+ffoUmdyykLu7O/PmzWPw4MHExMRQrlw5BgwYwJgxY2xtIiIi+OWXX3jmmWf44IMPqF69Ol988QXdunWztenbty8nT55k9OjRJCUl2W48aPZ07SKlmWG1su7jx4g59QMAcRFDaPfw61hc9FCBmCsgqALRT33JzrgFBCweQQ3jBJVXDWbj1u8If2gi5YJCAErcvczkxnDWdi9RRdOKFSuKPPbx8WHSpEmXvI9NoVq1ajF//vwr9nvbbbexefPmK7YZOnQoQ4cOtTuriFyetaCA9R8/SvTpuVgNC+sjXyLm3pFmx5IyoHFMD7KjbiHuP6Noc+K/tDr7K2cmt2N7q9GUq3MzWVlZlzwfVVxbVlYW4Nj5S5dSooomESn9rAUFbP54INFn5mE1LGxs8TrRd+s/JHLj+Pj5E/P3j9gbfx9uPz9FnYKDtN74LJuznifReidWqxWr1Up2drZLnySdm5tb5sdoGAZZWVmkpKQQHBx80RxNjlLRJCJOY7Va2TK5P23TF1FgWNjc6i3a3PWk2bGkjKrX/BbyGq9lzYxXaXnwU5rvGseR/GSO1rsPw90HX19fl74c//z58xrj/wQHB1/xinh7qWgSEacoyM+nwo7PaZu/inzDjS1t36F1z8fMjiVlnKeXN+0GvsnhhPs4//1gGu6dTvUDM9nu2xqvHq9SvXYTsyMWi7y8PH777Tc6dOhQcqeOuE72jtHT0/O69zAVUtEkItfNWlDAlk8HcWv+KvIMd7a1e5dWPXT1qZQctRo0x/qvP1g7axxNd71P1LnfyfmuG5vqDKZNv5fsuhVLaeLu7k5+fj4+Pj4uWzSZMUbXPNApIjeMYbWy7pO/E5124ca78W3G0VIFk5RAbu7uRN8/itP9V7DB0hRvSx4xBz7k8FvR7I3/3ex4UgqoaBKR67Lmi+G0OzkLgDnlH6d5twEmJxK5srCa9TjW7J+sbfY66ZSjTsEBas+5kzWTnyTrXLrZ8aQEU9EkItdszfQXiDnxJQBxDUfhGXGzyYlE7GNxs9DyzifJH7yODQGdcbcYtEv+hvTxrdj66/dmx5MSSkWTiFyTtd+Opd2hC3Oorak7nNZ9NA+TlD4VQ6tfuBXLrV+QSCWqcJJmKwex4b0+nE4+ZnY8KWFUNImIwzbOn0KbXW8DEFfjcdo99KrJiUSuT1THewkcuYE1of0oMCy0zliK++Ro1s35CON/N4YVUdEkIg7ZseoXmq59DjeLwdqQ3rR7ZJzZkUScolxAMO0Gf8KBu39iv3ttgjlH2y0vsuPtjhzbt93seFICqGgSEbsd2L6WmosH4WXJZ1O5W2j95Oe6l5y4nHotOlDz+TWsqTOM84YXkTnxhPznNuK+/De5OdlmxxMT6dNOROySeDgB/+/vJ8Bynp2ekTQeOhN3D031Jq7J08ubdg+PIXXACrZ5t8DHkkfMwYkkvt2K7b//aHY8MYmKJhG5qrRTSeR+2ZvKpHLIrSbVBs/Fx7ec2bFEil212k2IfH4561uMJZVAalmPEbmsP5vG30XS0X1mx5MbTEWTiFxRTnYWiZ/eQy3rMZKpiM8jcwiqUMnsWCI3jMXNjTa9/oH7sM2srfQ3CgwLLc+tJPCLm3TIroxR0SQil2VYrWz7uD+N8naSgR/n+35HWI26ZscSMUVQ+RCih0zh0N8WssuzCX6WHGIOTiT5rRZsWznb7HhyA6hoEpHLWvvVi7TOWEK+4cbhTh8T3qi12ZFETFenaTsajvqD9S3GcopgahgnaPrrI2we14PDCfFmx3NZ6aknST9zytQMKppE5JI2LZhmm7xyY5MXaNrhHpMTiZQchYfsvIZvYk3lvuQbbrTIWk21GR1Z+9EATiUdNTuiy9i/bQ3rPnwIrw8as3P2W6ZmUdEkIhfZu/k3Gq15DoA1le8j+r5nTU4kUjIFBlek3T8+4/gDv7LZ7yY8LFaiT8/Fd3Jr4qY9r3vZXaPcnGw2zPuMXW/EUOeHbrRN/RlfSy7lTm42NZeuFxaRIpKP7Sf4x/74WnLZ4tOGNk9MNjuSSIlXq0Fzaj23gJ1xC/BYNpr6+XuIOfwJKeO/Y1vjf9Ci11N4efuYHbPESz62nwMLJ1Lv2GxakwZAnuHO1sAO+LZ/kqZtY03Np6JJRGyys86RMe0+6nGGQ241qT34O83FJOKAxjE9sLaNZcPCqVTdMI6qRgqVd75O0s5POdzkSVrcNVTF018YVis7Vs8jN+4zmp1bRajlwm1rUqjA/pr3Uq/7EFpVrWVyygv0aSgiwP+ulPvsMdoU7OMMAXg9PIuAoApmxxIpddzc3Wnd83FyOj/ImjkTqJPwGWGcJGzHayTt+ITDTQbT4q4hZb54Sk05zp7Fn1PlwCwirf+7ObIFdng1JafFIJp2foAYL29zQ/6FiiYRAWDdrHeITltAgWHhWOdJNI1oaHYkkVLN28ePdv1eIDvradb8+AF1bcXTGFJ2TORA7YdodOcwgsqHmB31hrEWFLBj1U/krZtG5Nk/aGcpACDT8GF7SHcqdx5Kk8ZtTE55eSqaRIRdaxfRcufbYIH19YbRrkMvsyOJuAwfP3/a9fs32VnDWDN3AnX3fE5lUql84EMyJ3zGmtC7qNljJFVd+D8qJw4lcPjXqdQ6MpumRsqFhRbY61GP1Ab9aBz7CNGlYM+2iiaRMu7kiUNUWvAEnpYCNgZ0JPqBl82OJOKSfPz8affAi+Rkj2Ddgi+otO0LIqyHaZfyHQXTZxFfrh206E/kbX/Dw9PL7LjXLe1UEgnLvyJw7xwa5e2k6v+WZ+DHrpDuhHR4nHrNbjI1o6NUNImUYTnZWZyeej8NSeOgWziN/v4lFjfNRCJSnLx9/Gh7z9MYvYay7fe5GHETaZa9keZZcbAqjpOrXmBftV5U7/gYNeo2NTuuQ9JPJ7Pnjx/wTPiJJpnriP7f4TerYWGnTxTnG/eladf+RPv5m5z02qhoEinD4j8fTHT+LjIoh9dDM/DzDzI7kkiZYXFzo+mtveHW3hxOiCfx18+on/QzlThDpePT4b/T2e9em5M1elDt5n4ltoBKPJzA4dXfE3BwEQ1yttHmf1e/YYF97nU4FXEXtTsOILJahLlBnUBFk0gZteHnT4k+PRerYeHgbR8QVbuJ2ZFEyqxaDZpTq8HH5Oa8x6Zfv8Uj/r80Pr+ROgUHqHNoEhyaxEG3cJIrt6dc467Ua90VH5P21qSfTmb/+gXk7f2VqqnrqGGcoErhSgsccAsnpWpnqrR/kLqNWuFKd6tU0SRSBh3du4VGG0aDBdbVeJR2He81O5KIAF7ePrTsPhC6D+TMyUT2/vYtPnt/pvH5zURYDxGRdAiSviZ7mSc7vBuRUbE5PuGtqdrkZkKr13F6nuzzmRzdvZHUPXG4JW6mUsYOahYcpaXFsLUpMCwkeEeSUSuWGjH3Urt2I2o7PUnJoKJJpIzJzjpH7rcDKGfJZodXU9oMHGd2JBG5hPKVqtC2zzPAM6SdSmLf2p+x7l1OeNoaKltSaZK7FRK3QuJXEAdp+JPsUZ2McuHkBUeQl57P9pVZ+IdUxy8wBE9vHzy9fPD09qEgP5+87CxysrPIPZ/BudNJ5KSdID8jCdKP43f2ICE5RwiznqTenwokACxwyK0GyRWj8arXkdptutO4jEyboKJJpIzZMuUfRBccJJVAKg/8r2b8FikFgkPCaN3zceBxDKuVwwmbSd75O8bxjYSkb6NW/mGCLecIzt8N6buh8JZ3f3x+fS9sgTMEcNSnAVkhUfiEt6F65M2Eh9Ug/DrHVBrp01KkDNnwy+dEn/4Rq2HheKcPaFo13OxIIuIgi5sbtRq1olajVrZl2VnnOHJgB2eO7CQ3JQH3MwexnE2kvOUcgQVn8Dcy8SQfz/9dzQYXrmjLxoscizfpbsGc86xAtncI+X6huIXUxb96Y0IjIqlQqSrldVUtoKJJpMw4um8bjda9CBZYW30gMbf2NjuSiDiJj58/tSOjITIagLy8PObPn0/z22/H09PT1q4gP5/cnPO4e3ji6emFn5sbfkB5k3KXNiqaRMqA7POZ5H7zMOUs2ezUeUwiZZa7hwe+HgFmxyi1tL9NpAyInzqMOgUHOUMgIQP+4xKzDYuI3GgqmkRc3NYVP9Du5CwAjnR4l8ouMMGciIgZVDSJuLDUlONUXTECgLUhvYnqdJ/JiURESi8VTSIuyrBaOTz9MUJI47BbDaIe/cjsSCIipZqKJhEXtX72BFpkrSbXcCf/7s9Mu+WCiIirUNEk4oKO7t1C5La3ANhU7ynqNLvJ5EQiIqWfiiYRF5OXm0P2zEH4WXLY7t2ctv1Gmx1JRMQlqGgScTEbvvoX9fL3kk45Kj08FTd3d7MjiYi4BBVNIi5k7+bfaHN0OgD72r5WLHc9FxEpq1Q0ibiInOwsPH8egofFysaAjrS6fZDZkUREXIqKJhEXsemrfxFuPcJpgqjdf7LZcUREXI6KJhEXsGfTCtoe/wqAwzFvUL5SFZMTiYi4HhVNIqVc9vlMvOcNwd1isCGwCy27PWx2JBERl6SiSaSUi//yWWpZj3GKYOr2n2R2HBERl6WiSaQU271+KW0SZwBw9KY3CA4JMzmRiIjrUtEkUkpln8/Eb8HTuFsM1gfF0iL2IbMjiYi4NBVNIqXU5v++QE3rcU5SnvoDPjY7joiIy1PRJFIKHdi+ltbH/gPAsZhXCapQyeREIiKuT0WTSClTkJ9P/tyheFoK2OzXnhbdBpgdSUSkTFDRJFLKrJ/1NvXz93DW8KXag7paTkTkRlHRJFKKJB3ZS7PdHwCws8kIKleLMDmRiEjZoaJJpJQwrFaSvhmKnyWHXZ6NadNnpNmRRETKFBVNIqXEpoXTaH5+DbmGO369J+Lm7m52JBGRMsXDnkZbt251uOPGjRvj4WFX9yJyFempJ6m1bgwAG2s+SkyjViYnEhEpe+yqapo3b47FYsEwDLs6dXNzY8+ePdSuXfu6wonIBbu//ifRpHHYrTotHxxjdhwRkTLJ7l1Ba9eupVKlq88FYxgGkZGR1xVKRP7fnk0raXPqR7DAuS7v4O3jZ3YkEZEyya6i6dZbb6Vu3boEBwfb1WmHDh3w9fW9nlwiwoU5mSzzR+JmMdgQ2JXWN91udiQRkTLLrqLp119/dajT+fPnX1MYESlqw+z3ic7fy1nDl/AH3jM7johImaar50RKqNPJx2i4830AdjR8mpCwmiYnEhEp2xwqmvbu3csPP/zAwYMHAfjll1/o0KEDbdq04Y033rD7RHERuboD3/yTIDLZ716b1n/7p9lxRETKPLtPBJ8zZw733Xcfbm5uWCwWPvvsM/7+979z2223ERgYyCuvvIKHhwfPP/98ceYVKRN2r11Mm7QFAOR1fwcPTy+TE4mIiN17mt544w2ee+45srOzmTx5Mk8++SRjx45lwYIFzJs3j0mTJjF9+vRijCpSNuTn5eK16FkA1pXvScM2XUxOJCIi4EDRlJCQwKOPPorFYmHAgAHk5ubSpcv/f5jHxsZy+PDhYgkpUpZsmPU2ta2HSMOfeg+8a3YcERH5H7uLpszMTAICAi48yc0NX19f/Pz+f74YX19fcnJynJ9QpAw5nXyMJgmTAEhoMoLylaqYnEhERArZXTRZLBYsFstlH4vI9ds/818EWM6z170ubXoPNzuOiIj8id0nghuGQf369W2F0rlz52jRogVubm629SJy7fZtWUXr0/PAAgWxY3VDXhGREsbuomnatGnFmUOkTDOsVnLnPXdh5u+AzrSOjjU7koiI/IXdRdOAAQOKM4dImbZp4TRa5W3nvOFF9fvGmR1HREQuwdQZwSdPnkyzZs0IDAwkMDCQmJgYFixYYFufnZ3NkCFDqFixIv7+/vTp04fk5OQifRw5coSePXvi5+dH5cqVefbZZ8nPzy/SZsWKFbRs2RJvb2/q1q17yakRJk2aRHh4OD4+PkRHR7Nu3bpiGbPIX53PPEu1dWMBiK81kLAadU1OJCIil2JX0VS+fHkqVKhg148jqlevzltvvcXGjRvZsGEDnTp1olevXuzYsQOAZ555hp9//plZs2axcuVKTpw4Qe/evW3PLygooGfPnuTm5rJ69Wq+/PJLpk+fzujRo21tDh48SM+ePenYsSPx8fEMHz6cxx57jEWLFtnazJw5kxEjRvDyyy+zadMmoqKi6NatGykpKQ6NR+RaxM98jTBOkkQIzfuOvvoTRETEFHYdnpswYYLt76dPn+b111+nW7duxMTEABAXF8eiRYt46aWXHHrxO++8s8jjN954g8mTJ7NmzRqqV6/OlClTmDFjBp06dQIunFfVqFEj1qxZQ7t27Vi8eDE7d+5k6dKlhIaG0rx5c1577TWef/55XnnlFby8vPjkk0+IiIjg3XcvzHfTqFEj/vjjD95//326desGwHvvvcfjjz/OI488AsAnn3zCL7/8wtSpU/nXv/7l0JhEHJF0dB/ND08DCxxvM4qwcgFmRxIRkcuwq2j68/lMffr0YcyYMQwdOtS27Omnn2bixIksXbqUZ5555pqCFBQUMGvWLDIzM4mJiWHjxo3k5eUVmUCzYcOG1KxZk7i4ONq1a0dcXBxNmzYlNDTU1qZbt24MHjyYHTt20KJFC+Li4or0Udhm+PDhAOTm5rJx40ZGjRplW+/m5kaXLl2Ii4u7bN6cnJwi81JlZGQAkJeXR15e3jW9B5dS2Jcz+yxpyvIYj373HGGWXHZ5NqFpl4dL9XtQlrejK9EYXYPG6Hg/9rD7RPBCixYt4u23375oeffu3a9pr8y2bduIiYkhOzsbf39/5syZQ+PGjYmPj8fLy4vg4OAi7UNDQ0lKSgIgKSmpSMFUuL5w3ZXaZGRkcP78ec6cOUNBQcEl2+zevfuyuceOHcurr7560fLFixcXmfTTWZYsWeL0PkuasjbG8yf3c//ZZVgNC1vD+rJn4UITkzlPWduOrkpjdA0a49VlZWXZ3dbhoqlixYr8+OOPjBw5ssjyH3/8kYoVKzraHQ0aNCA+Pp709HS+//57BgwYwMqVKx3u50YbNWoUI0aMsD3OyMigRo0axMbGEhgY6LTXycvLY8mSJXTt2hVPT0+n9VuSlMUxGlYr+8d3BGBDcDd69/+HyQmvX1ncjq5IY3QNGqP9Co8U2cPhounVV1/lscceY8WKFURHRwOwdu1aFi5cyOeff+5od3h5eVG37oWrhVq1asX69ev54IMP6Nu3L7m5uaSlpRXZ25ScnExYWBgAYWFhF13lVnh13Z/b/PWKu+TkZAIDA/H19cXd3R13d/dLtins41K8vb3x9va+aLmnp2ex/IIWV78lSVka46ZF/6Fl3g7OG17UuvdNlxp3WdqOrkxjdA0ao33Pt5fDUw4MHDiQVatWERgYyOzZs5k9ezaBgYH88ccfDBw40NHuLmK1WsnJyaFVq1Z4enqybNky27qEhASOHDliOwE9JiaGbdu2FbnKbcmSJQQGBtK4cWNbmz/3UdimsA8vLy9atWpVpI3VamXZsmW2NiLOlJebQ6U1bwIQX/1BQqvXMTmRiIjYw+E9TQDR0dF8/fXX1/3io0aNokePHtSsWZOzZ88yY8YMVqxYwaJFiwgKCmLQoEGMGDGCChUqEBgYyFNPPUVMTAzt2rUDIDY2lsaNG/Pwww8zbtw4kpKSePHFFxkyZIhtL9CTTz7JxIkTee6553j00UdZvnw53333Hb/88ostx4gRIxgwYACtW7embdu2TJgwgczMTNvVdCLOtGnO+0QbJ0glkMj7NMWAiEhpYVfRlJGR4dB5OmfPniUg4OqXTqekpNC/f38SExMJCgqiWbNmLFq0iK5duwLw/vvv4+bmRp8+fcjJyaFbt258/PHHtue7u7szb948Bg8eTExMDOXKlWPAgAGMGTPG1iYiIoJffvmFZ555hg8++IDq1avzxRdf2KYbAOjbty8nT55k9OjRJCUl0bx5cxYuXHjRyeEi1+ts+hnq7ZoEwN5GQ4kOcmxuMxERMY9dRVP58uVJTEykcuXKdnVarVo14uPjqV279hXbTZky5YrrfXx8mDRpEpMmTbpsm1q1ajF//vwr9nPbbbexefPmK7YZOnRokWkURIrD7h9e5yYyOOJWjZb3DDc7joiIOMCuoskwDL744gv8/f3t6tSV54UQuVa551JpeWIGWOB0uxeo6XXxhQQiIlJy2VU01axZ06Er48LCwlz+bH0RR1U6+AM+ljx2ekbSvMsDZscREREH2VU0HTp0qJhjiLi2g9vX0iHvD7CAR483sLiZeq9sERG5BvrkFrkBzi96BTeLwQb/jtRveZvZcURE5BqoaBIpZjvXLCQqez15hjshd1186x0RESkdVDSJFCPDasWy7EKhtNL7NqpFNDY5kYiIXCsVTSLFaOuK72iUt5Pzhhdnwu8yO46IiFwHFU0ixcRaUID/qrcA2FzlXrzKlTc5kYiIXA+Hi6aFCxfyxx9/2B5PmjSJ5s2b88ADD3DmzBmnhhMpzTYtmEKdgoNk4Ef9e/5tdhwREblODhdNzz77LBkZGQBs27aNkSNHcvvtt3Pw4EFGjBjh9IAipVFebg5hG98FYEf4AIIq2DebvoiIlFwO37D34MGDNG584WTWH374gTvuuIM333yTTZs2cfvttzs9oEhptOnHj4g2kjhNEM36/MvsOCIi4gQO72ny8vIiKysLgKVLlxIbGwtAhQoVbHugRMqy7KxzROz43015G/ydcgHB5gYSERGncHhP080338yIESNo374969atY+bMmQDs2bOH6tWrOz2gSGkT/8M42pFKIpVocc8zZscREREncXhP08SJE/Hw8OD7779n8uTJVKtWDYAFCxbQvXt3pwcUKU3OpqfScP8UAI5GDcPbx8/kRCIi4iwO72mqWbMm8+bNu2j5+++/75RAIqXZ9tlvE8M5jrhVo9Wdg82OIyIiTuTwnqZNmzaxbds22+Mff/yRu+++mxdeeIHc3FynhhMpTTLSTtPk8H8ASGk5HHcPh/9PIiIiJZjDRdPf//539uzZA8CBAwe4//778fPzY9asWTz33HNODyhSWuyY/RaBZHLYrQYtuj9qdhwREXEyh4umPXv20Lx5cwBmzZpFhw4dmDFjBtOnT+eHH35wdj6RUiH9zCmaHPkvAKdaaS+TiIgrcrhoMgwDq9UKXJhyoHBupho1anDq1CnnphMpJXbOHksgWRxyq0mL7o+YHUdERIqBw0VT69atef311/nPf/7DypUr6dmzJ3Bh0svQ0FCnBxQp6dJTTxJ55GsAUtuMwM3d3eREIiJSHBwumiZMmMCmTZsYOnQo//73v6lbty4A33//PTfddJPTA4qUdDtnv0mA5TwH3MJpHtvf7DgiIlJMHD7xolmzZkWuniv0zjvv4K7/YUsZk346maZHvwELpEdrL5OIiCu75rNVN27cyK5duwBo3LgxLVu2dFookdJi5+w3ibGcZ797BFFdHjI7joiIFCOHi6aUlBT69u3LypUrCQ4OBiAtLY2OHTvy7bffUqlSJWdnFCmRzpxMpNmxb8ECGdH/1F4mEREX5/A5TU899RTnzp1jx44dpKamkpqayvbt28nIyODpp58ujowiJdLuH8dRzpLNPvc6NO/ygNlxRESkmDm8p2nhwoUsXbqURo0a2ZY1btyYSZMmERsb69RwIiVV+plTRP7vXKaMts9gcXP4/x8iIlLKOPxJb7Va8fT0vGi5p6enbf4mEVe388fxBFjOc8itpvYyiYiUEQ4XTZ06dWLYsGGcOHHCtuz48eM888wzdO7c2anhREqizLNpNDz0v9m/WwzVuUwiImWEw0XTxIkTycjIIDw8nDp16lCnTh0iIiLIyMjgo48+Ko6MIiXKtp8+oDxnOWapQnPN/i0iUmY4fE5TjRo12LRpE0uXLmX37t0ANGrUiC5dujg9nEhJk30+k7p7pwKQ2HQw1T29TE4kIiI3yjXN02SxWOjatStdu3Z1dh6REm3LTxOJJo0kQojq+Xez44iIyA1kV9H04Ycf2t2hph0QV5WXm0OtXZ8DcLjR44R5+5icSEREbiS7iqb333/frs4sFouKJnFZm3/5lLac5BTBRN051Ow4IiJyg9lVNB08eLC4c4iUaAX5+VTd+jEA++oOpJ2fv8mJRETkRtOMfCJ22LxwKtWNRNLwp2mvZ8yOIyIiJnD4RPCCggKmT5/OsmXLSElJuWhCy+XLlzstnEhJYFitVNw0CYBdtR4iJiDY3EAiImIKh4umYcOGMX36dHr27ElkZCQWi6U4comUGFtX/kCU9RCZhg+Ne/3T7DgiImISh4umb7/9lu+++47bb7+9OPKIlDgecReuHt0Wdg/tKlQyOY2IiJjF4XOavLy8qFu3bnFkESlx9mxaQZPcreQZ7kTc+azZcURExEQOF00jR47kgw8+wDCM4sgjUqKcW/YuAPHBXQmtXsfkNCIiYia7Ds/17t27yOPly5ezYMECmjRpgqenZ5F1s2fPdl46ERMd3buF5ud+BwtU7v6c2XFERMRkdhVNQUFBRR7fc889xRJGpCQ5sWA8NSwG8X4xNG/Uyuw4IiJiMruKpmnTphV3DpES5VTSEZqfXgAW8L5V8zKJiMg1nNPUqVMn0tLSLlqekZFBp06dnJFJxHR7fxqPtyWP3Z6NaRTdzew4IiJSAjhcNK1YsYLc3NyLlmdnZ/P77787JZSImc6mp9LkxCwAzrcZYnIaEREpKeyep2nr1q22v+/cuZOkpCTb44KCAhYuXEi1atWcm07EBDt+/pB2ZHHYrTpRnfuZHUdEREoIu4um5s2bY7FYsFgslzwM5+vry0cffeTUcCI3Wm5ONrX3fQlASuQT1HJ3NzmRiIiUFHYXTQcPHsQwDGrXrs26deuoVOn/Z0b28vKicuXKuOsLRkq5LQun0oZUTlKeZrc/bnYcEREpQewummrVqgVw0Q16RVyFYbVSYevnAOyLeJAYHz+TE4mISEni8L3nCu3cuZMjR45cdFL4XXfddd2hRMywM24BTQoOkGV40/iOp82OIyIiJYzDRdOBAwe455572LZtGxaLxXY7FYvFAlw4KVykNMpbdeGcvG2VehJdMdTkNCIiUtI4POXAsGHDiIiIICUlBT8/P3bs2MFvv/1G69atWbFiRTFEFCl+R/duoXlWHABVuw03N4yIiJRIDhdNcXFxjBkzhpCQENzc3HBzc+Pmm29m7NixPP20DmlI6XRi0QQA4v1iqFEvytwwIiJSIjlcNBUUFBAQEABASEgIJ06cAC6cKJ6QkODcdCI3QPrpZJqe/AUAj/aazFJERC7N4XOaIiMj2bJlCxEREURHRzNu3Di8vLz47LPPqF27dnFkFClWO+d9SIwlh/3uETSJ6Wl2HBERKaEcLppefPFFMjMzARgzZgx33HEHt9xyCxUrVmTmzJlODyhSnHJzsqlzcAYAqU0fp46bwztfRUSkjHC4aOrW7f9vXlq3bl12795Namoq5cuXt11BJ1JabF00ndakcopgonoMMjuOiIiUYNc8TxPA0aNHAahRo4ZTwojcSIbVSvCWzwDYG96PGG8fkxOJiEhJ5vCxiPz8fF566SWCgoIIDw8nPDycoKAgXnzxRfLy8oojo0ix2LlmIXUL9pNteNKw5zCz44iISAnn8J6mp556itmzZzNu3DhiYmKAC9MQvPLKK5w+fZrJkyc7PaRIccj9YyIAW0JuJ7pSFZPTiIhISedw0TRjxgy+/fZbevToYVvWrFkzatSoQb9+/VQ0SamQeDiBZpmrwQJhXbSXSURErs7hw3Pe3t6Eh4dftDwiIgIvLy9nZBIpdocWTsTdYrDduzm1GrUyO46IiJQCDhdNQ4cO5bXXXiMnJ8e2LCcnhzfeeIOhQ4c6NZxIccjOOkfDxDkA5LV63OQ0IiJSWjh8eG7z5s0sW7aM6tWrExV14XYTW7ZsITc3l86dO9O7d29b29mzZzsvqYiTbF00lbacJYlKNOt0v9lxRESklHC4aAoODqZPnz5FlmnKASktDKuVCtunA3Cwdj/CPK5r1g0RESlDHP7GmDZtWnHkELkhEjYso+H/phlodLvuMyciIvbTPSOkTDn3+4WrO7eW70pwSJjJaUREpDRR0SRlxqkTh4nKWAFAhY7ayyQiIo5R0SRlxt6FE/G0FLDbszF1o242O46IiJQyKpqkTMjNyabeke8AONf8UZPTiIhIaXRdRVN2drazcogUq61L/0MIaZwimGZdHjY7joiIlEIOF01Wq5XXXnuNatWq4e/vz4EDBwB46aWXmDJlikN9jR07ljZt2hAQEEDlypW5++67SUhIKNImOzubIUOGULFiRfz9/enTpw/JyclF2hw5coSePXvi5+dH5cqVefbZZ8nPzy/SZsWKFbRs2RJvb2/q1q3L9OnTL8ozadIkwsPD8fHxITo6mnXr1jk0Him5/OOnArC35n14efuYnEZEREojh4um119/nenTpzNu3Lgit02JjIzkiy++cKivlStXMmTIENasWcOSJUvIy8sjNjaWzMxMW5tnnnmGn3/+mVmzZrFy5UpOnDhRZALNgoICevbsSW5uLqtXr+bLL79k+vTpjB492tbm4MGD9OzZk44dOxIfH8/w4cN57LHHWLRoka3NzJkzGTFiBC+//DKbNm0iKiqKbt26kZKS4uhbJCXMvi2raJi3kzzDnXrdNWu9iIhcI8NBderUMZYuXWoYhmH4+/sb+/fvNwzDMHbt2mUEBwc72l0RKSkpBmCsXLnSMAzDSEtLMzw9PY1Zs2bZ2uzatcsAjLi4OMMwDGP+/PmGm5ubkZSUZGszefJkIzAw0MjJyTEMwzCee+45o0mTJkVeq2/fvka3bt1sj9u2bWsMGTLE9rigoMCoWrWqMXbsWLuyp6enG4CRnp7u4KivLDc315g7d66Rm5vr1H5LkuIe49oPHjSMlwONDePvLpb+7aHt6Bo0RtegMboGZ43Rke9vhye3PH78OHXr1r1oudVqJS8v77oKuPT0dAAqVKgAwMaNG8nLy6NLly62Ng0bNqRmzZrExcXRrl074uLiaNq0KaGhobY23bp1Y/DgwezYsYMWLVoQFxdXpI/CNsOHDwcgNzeXjRs3MmrUKNt6Nzc3unTpQlxc3CWz5uTkFLn/XkZGBgB5eXnX/T78WWFfzuyzpCnOMZ5NP0Pk6cVgAa/oQaa9j9qOrkFjdA0ao2tw1hgdeb7DRVPjxo35/fffqVWrVpHl33//PS1atHC0Oxur1crw4cNp3749kZGRACQlJeHl5UVwcHCRtqGhoSQlJdna/LlgKlxfuO5KbTIyMjh//jxnzpyhoKDgkm127959ybxjx47l1VdfvWj54sWL8fPzs3PU9luyZInT+yxpimOMBfuX0duSw0Gqsv9kPgfmz3f6azhC29E1aIyuQWN0Ddc7xqysLLvbOlw0jR49mgEDBnD8+HGsViuzZ88mISGBr776innz5jnanc2QIUPYvn07f/zxxzX3cSONGjWKESNG2B5nZGRQo0YNYmNjCQwMdNrr5OXlsWTJErp27Yqnp6fT+i1JimuMhtXKsbdfAiCxXj963tHTaX07StvRNWiMrkFjdA3OGmPhkSJ7OFw09erVi59//pkxY8ZQrlw5Ro8eTcuWLfn555/p2rWro90BMHToUObNm8dvv/1G9erVbcvDwsLIzc0lLS2tyN6m5ORkwsLCbG3+epVb4dV1f27z1yvukpOTCQwMxNfXF3d3d9zd3S/ZprCPv/L29sbb2/ui5Z6ensXyC1pc/ZYkzh7j7vVLaWg9TLbhSZMeg0vE+6ft6Bo0RtegMbqG6x2jI8+9pnmabrnlFpYsWUJKSgpZWVn88ccfxMbGOtyPYRgMHTqUOXPmsHz5ciIiIoqsb9WqFZ6enixbtsy2LCEhgSNHjhATEwNATEwM27ZtK3KV25IlSwgMDKRx48a2Nn/uo7BNYR9eXl60atWqSBur1cqyZctsbaT0OfvH5wBsK9+FoAqVTE4jIiKlncN7mtavX4/VaiU6OrrI8rVr1+Lu7k7r1q3t7mvIkCHMmDGDH3/8kYCAANs5SEFBQfj6+hIUFMSgQYMYMWIEFSpUIDAwkKeeeoqYmBjatWsHQGxsLI0bN+bhhx9m3LhxJCUl8eKLLzJkyBDbnqAnn3ySiRMn8txzz/Hoo4+yfPlyvvvuO3755RdblhEjRjBgwABat25N27ZtmTBhApmZmTzyyCOOvkVSAqSnnqRp2jKwQMDNj5sdR0REXIDDe5qGDBnC0aNHL1p+/Phxhgxx7CaokydPJj09ndtuu40qVarYfmbOnGlr8/7773PHHXfQp08fOnToQFhYGLNnz7atd3d3Z968ebi7uxMTE8NDDz1E//79GTNmjK1NREQEv/zyC0uWLCEqKop3332XL774gm7dutna9O3bl/HjxzN69GiaN29OfHw8CxcuvOjkcCkddi38FB9LHvvdI2jQsqPZcURExAU4vKdp586dtGzZ8qLlLVq0YOfOnQ71ZRjGVdv4+PgwadIkJk2adNk2tWrVYv5Vroq67bbb2Lx58xXbDB06lKFDNflhaWdYrVTZ9w0Apxo8SB033WJRRESun8PfJt7e3hedMA2QmJiIh4fDNZiI0+1cs5Ba1mNkGd407jbI7DgiIuIiHC6aYmNjGTVqlG0iSoC0tDReeOGFa756TsSZzsdduJ3PtordCAiqYHIaERFxFQ7vGho/fjwdOnSgVq1atsks4+PjCQ0N5T//+Y/TA4o44nTyMZplrAALVLz1SbPjiIiIC3G4aKpWrRpbt27l66+/ZsuWLfj6+vLII4/Qr18/l58LQkq+vYs+pZ2lgD0e9akf1d7sOCIi4kKu6SSkcuXK8cQTTzg7i8h1MaxWqh38HoC0Rg+anEZERFzNNZ+5vXPnTo4cOUJubm6R5Xfdddd1hxK5FrvWLaaxcYJMw4cmsQPNjiMiIi7G4aLpwIED3HPPPWzbtg2LxWKbNsBisQBQUFDg3IQidsqMmwbAjgqdaRsQbG4YERFxOQ5fPTds2DAiIiJISUnBz8+PHTt28Ntvv9G6dWtWrFhRDBFFru5seipN0n4FIPCmR01OIyIirsjhoikuLo4xY8YQEhKCm5sbbm5u3HzzzYwdO5ann366ODKKXNXOxdPws+Rw2K0GDVp1MjuOiIi4IIeLpoKCAgICAgAICQnhxIkTwIVZuRMSEpybTsRO5RO+BSCx9t+waAZwEREpBg6f0xQZGcmWLVuIiIggOjqacePG4eXlxWeffUbt2rWLI6PIFR3csZb6+XvIM9yp1/Uxs+OIiIiLcrhoevHFF8nMzARgzJgx3HHHHdxyyy1UrFixyI12RW6U5JVfEAFs87+JlqHVzY4jIiIuyuGiqVu3bra/161bl927d5Oamkr58uVtV9CJ3Cg52Vk0TLlws2b3Vv1NTiMiIq7suu6we/ToUQBq1KjhlDAijtq+/BtacY4UKhDZobfZcURExIU5fMZsfn4+L730EkFBQYSHhxMeHk5QUBAvvvgieXl5xZFR5LI8t34NwP5qvXD3uK7/A4iIiFyRw98yTz31FLNnz2bcuHHExMQAF6YheOWVVzh9+jSTJ092ekiRS0k8nEDk+U1ggZqd/252HBERcXEOF00zZszg22+/pUePHrZlzZo1o0aNGvTr109Fk9wwh5Z9QRWLwQ6vKJrUbmR2HBERcXEOH57z9vYmPDz8ouURERF4eXk5I5PIVVkLCgg/MgeA85EPmJxGRETKAoeLpqFDh/Laa6+Rk5NjW5aTk8Mbb7zB0KFDnRpO5HJ2rPqJKpwkAz8iuzxkdhwRESkDHD48t3nzZpYtW0b16tWJiooCYMuWLeTm5tK5c2d69/7/K5hmz57tvKQif5K7/ksAdoV0J9rP3+Q0IiJSFjhcNAUHB9OnT58iyzTlgNxIaaeSaJrxO1ig4i2DzI4jIiJlhMNF07Rp04ojh4jddi+ZQjtLPvvda1M36maz44iISBnh8DlN58+fJysry/b48OHDTJgwgcWLFzs1mMilGFYroXu/A+BU/b4mpxERkbLE4aKpV69efPXVVwCkpaXRtm1b3n33XXr16qXpBqTY7Y3/nQjrIXIMTxp21aE5ERG5cRwumjZt2sQtt9wCwPfff09YWBiHDx/mq6++4sMPP3R6QJE/O7NqCgDbgm4lqEIlk9OIiEhZ4nDRlJWVRUBAAACLFy+md+/euLm50a5dOw4fPuz0gCKFzmeepfGpC4eBfdoOMDmNiIiUNQ4XTXXr1mXu3LkcPXqURYsWERsbC0BKSgqBgYFODyhSaMfyGQRYznPCUpnGMT3NjiMiImWMw0XT6NGj+ec//0l4eDht27a13X9u8eLFtGjRwukBRQp57ZgJwOHqd+Hm7m5yGhERKWscnnLgb3/7GzfffDOJiYm2yS0BOnfuzD333OPUcCKFUo4fpEnhzXk7Pmp2HBERKYMc3tMEEBYWRkBAAEuWLOH8+fMAtGnThoYNGzo1nEih/cum4m4x2OXZhGq1m5gdR0REyiCHi6bTp0/TuXNn6tevz+23305iYiIAgwYNYuTIkU4PKGJYrVQ9dOHmvGcb3mtyGhERKascLpqeeeYZPD09OXLkCH5+frblffv2ZeHChU4NJwIX5maqZT1KtuFJw879zY4jIiJllMPnNC1evJhFixZRvXr1Isvr1aunKQekWJxZPR2A7YEdaB1c0dwwIiJSZjm8pykzM7PIHqZCqampeHt7OyWUSKGc7Cwa/G9uJq9WD5qcRkREyjKHi6ZbbrnFdhsVAIvFgtVqZdy4cXTs2NGp4UR2rpxFMOdIoQJNbu5ldhwRESnDHD48N27cODp37syGDRvIzc3lueeeY8eOHaSmprJq1ariyChlmGXLNwDsr3I7lT0c/nUVERFxGof3NEVGRrJnzx5uvvlmevXqRWZmJr1792bz5s3UqVOnODJKGXU6+RhNMtcBULWD5mYSERFzOfRf97y8PLp3784nn3zCv//97+LKJALA3mXTaGcpYI9Hfeo3amV2HBERKeMc2tPk6enJ1q1biyuLSBGV9s8G4Ey9PiYnERERuYbDcw899BBTpkwpjiwiNge2r6VOwQFyDXcadB5odhwRERHHTwTPz89n6tSpLF26lFatWlGuXLki69977z2nhZOyK+X3adQGtvvfRMuQMLPjiIiIOF40bd++nZYtWwKwZ8+eIussFotzUkmZlp+XS93kBQC4NX/A5DQiIiIX2F00HThwgIiICH799dfizCPCjt9nE0UaqQTS5FadzyQiIiWD3ec01atXj5MnT9oe9+3bl+Tk5GIJJWVbwaYZAOyp3B1PL80yLyIiJYPdRZNhGEUez58/n8zMTKcHkrItPfUkkWcvTJIa0n6guWFERET+xOGr50SK0+6l0/Gy5HPQLZw6TWPMjiMiImJjd9FksVguOtFbJ36LswXv+R6A5Nr3YHFTTS8iIiWH3SeCG4bBwIED8fa+cI5JdnY2Tz755EVTDsyePdu5CaXMOLp3Kw3yd5NvuFG3i26bIiIiJYvdRdOAAQOKPH7ooYecHkbKtqTfv6Q2sMOvNVFhNc2OIyIiUoTdRdO0adOKM4eUcVarlTqJ8wDIb6q5mUREpOTRSSNSIuQm7yKU02RQjiYd7zM7joiIyEVUNEmJEHbqDwB2VeyKj2+5q7QWERG58VQ0ienOnU2jTd4GAIJi+pucRkRE5NJUNInpEn79Gj9LDkcsVWnQsqPZcURERC5JRZOYLmD3hbmZjtXspbmZRESkxNI3lJjqxMHdNMnbhtWwUOu2R8yOIyIiclkqmsRUh3+dCkC8W2MqV69tchoREZHLU9EkpjGsVmoc/RGAA8E3m5xGRETkylQ0iWl2r19CdSOJTMMHS7XWZscRERG5IhVNYpqza74CYEfwbXh4epucRkRE5MpUNIkpsrPO0Sh1GQC+rR80OY2IiMjVqWgSU2xfPoMAy3kSqUT9NrFmxxEREbkqFU1iCq/tMwE4XP0u3NzdTU4jIiJydSqa5IY7eeIQTc5vBKBGp0EmpxEREbGPiia54fYvnYK7xWCXZxOq1W5idhwRERG7qGiSG8qwWqlyaA4AZxvea3IaERER+6lokhtqb/zv1LIeJdvwpGHn/mbHERERsZuKJrmhzqyeDsD2wA4EBlc0N4yIiIgDVDTJDZOTnUWDU4sB8GqluZlERKR0UdEkN8zOlbMI5hwpVKDJzb3MjiMiIuIQFU1y42z5FoD9VW7H3cPD5DAiIiKOMbVo+u2337jzzjupWrUqFouFuXPnFllvGAajR4+mSpUq+Pr60qVLF/bu3VukTWpqKg8++CCBgYEEBwczaNAgzp07V6TN1q1bueWWW/Dx8aFGjRqMGzfuoiyzZs2iYcOG+Pj40LRpU+bPn+/08ZZlqSnHicxcC0DVDo+anEZERMRxphZNmZmZREVFMWnSpEuuHzduHB9++CGffPIJa9eupVy5cnTr1o3s7GxbmwcffJAdO3awZMkS5s2bx2+//cYTTzxhW5+RkUFsbCy1atVi48aNvPPOO7zyyit89tlntjarV6+mX79+DBo0iM2bN3P33Xdz9913s3379uIbfBmzZ+k0PC0F7PWoR61GrcyOIyIi4jBTj5H06NGDHj16XHKdYRhMmDCBF198kV69Lpz/8tVXXxEaGsrcuXO5//772bVrFwsXLmT9+vW0bt0agI8++ojbb7+d8ePHU7VqVb7++mtyc3OZOnUqXl5eNGnShPj4eN577z1bcfXBBx/QvXt3nn32WQBee+01lixZwsSJE/nkk09uwDvh+kL2zwYgtW4fk5OIiIhcmxJ7YsnBgwdJSkqiS5cutmVBQUFER0cTFxfH/fffT1xcHMHBwbaCCaBLly64ubmxdu1a7rnnHuLi4ujQoQNeXl62Nt26dePtt9/mzJkzlC9fnri4OEaMGFHk9bt163bR4cI/y8nJIScnx/Y4IyMDgLy8PPLy8q53+DaFfTmzzxvt0M711CvYT67hTu3bHrpoLK4wxqvRGF2DxugaNEbX4KwxOvL8Els0JSUlARAaGlpkeWhoqG1dUlISlStXLrLew8ODChUqFGkTERFxUR+F68qXL09SUtIVX+dSxo4dy6uvvnrR8sWLF+Pn52fPEB2yZMkSp/d5o3jv/JZ6wEaPFqSs3XTZdqV5jPbSGF2DxugaNEbXcL1jzMrKsrttiS2aSrpRo0YV2TuVkZFBjRo1iI2NJTAw0Gmvk5eXx5IlS+jatSuenp5O6/dGyc/LJXPz0wB4tRnA7Z1vv6hNaR+jPTRG16AxugaN0TU4a4yFR4rsUWKLprCwMACSk5OpUqWKbXlycjLNmze3tUlJSSnyvPz8fFJTU23PDwsLIzk5uUibwsdXa1O4/lK8vb3x9va+aLmnp2ex/IIWV7/Fbefvc4gijVQCadap7xXHUFrH6AiN0TVojK5BY3QN1ztGR55bYudpioiIICwsjGXLltmWZWRksHbtWmJiYgCIiYkhLS2NjRs32tosX74cq9VKdHS0rc1vv/1W5JjlkiVLaNCgAeXLl7e1+fPrFLYpfB25dvmbvgZgT+XueHpdXGSKiIiUFqYWTefOnSM+Pp74+Hjgwsnf8fHxHDlyBIvFwvDhw3n99df56aef2LZtG/3796dq1arcfffdADRq1Iju3bvz+OOPs27dOlatWsXQoUO5//77qVq1KgAPPPAAXl5eDBo0iB07djBz5kw++OCDIofWhg0bxsKFC3n33XfZvXs3r7zyChs2bGDo0KE3+i1xKempJ4k8uwqAkPYDzQ0jIiJynUw9PLdhwwY6duxoe1xYyAwYMIDp06fz3HPPkZmZyRNPPEFaWho333wzCxcuxMfHx/acr7/+mqFDh9K5c2fc3Nzo06cPH374oW19UFAQixcvZsiQIbRq1YqQkBBGjx5dZC6nm266iRkzZvDiiy/ywgsvUK9ePebOnUtkZOQNeBdc1+6l04m25HHQLZw6TbXXTkRESjdTi6bbbrsNwzAuu95isTBmzBjGjBlz2TYVKlRgxowZV3ydZs2a8fvvv1+xzb333su999575cDikOA9swBIrn0PEW4l9kiwiIiIXfRNJsXi0K4NNMhPIM9wp26XQWbHERERuW4qmqRYJK34AoDt5doRElbD5DQiIiLXT0WTOF1ebg71k38BwNLyYZPTiIiIOIeKJnG67StmUYEMThFM5K2615yIiLgGFU3idJb4/wKwt8odeHh6XaW1iIhI6aCiSZzq1InDRGauBaBax8dNTiMiIuI8KprEqfYt/QIPi5Vdno2pWb+52XFEREScRkWTOI1htVL10A8AnGt0v8lpREREnEtFkzjNzrgF1LQeJ8vwplGX/mbHERERcSoVTeI02XGfAbAtpDv+geVNTiMiIuJcKprEKU4lHaHZ2Qu3qgm57R8mpxEREXE+FU3iFHsXfoynpYDdno2p07Sd2XFEREScTkWTXLeC/HwiDl24Oe+5pjqXSUREXJOKJrlu2379jjBOcYYAIruqaBIREdekokmum9vGqQAkhN2Fj285k9OIiIgUDxVNcl2OH9hB5PkNANSIHWJyGhERkeKjokmuy9EF7+NmMdji04ZqtZuYHUdERKTYqGiSa5Z+5hTNUn4CwO0m7WUSERHXpqJJrtmuXz7Cz5LDQbdaRN7cy+w4IiIixUpFk1yT/Lxcwvd9DcCpyEFY3PSrJCIirk3fdHJNtiz5D2Gc5DRBNO3xmNlxREREip2KJrkm/ps+BWBPjfs0zYCIiJQJKprEYbvWLqJBfgI5hif1eg4zO46IiMgNoaJJHJb36zsAxFfsQUhYDZPTiIiI3BgqmsQh+7b8QbPs9RQYFqrf8YLZcURERG4YFU3ikIzFbwOwOagz1Wo3MjmNiIjIjaOiSex2ePcmmp/7HYCQHqNMTiMiInJjqWgSu6UseAs3i8Fmv/aEN2ptdhwREZEbSkWT2OXInnhapi0GoFyX501OIyIicuOpaBK7nPzpZdwtBpv9bqJ+y1vNjiMiInLDqWiSq9q3ZRWtzq3AalgIuv0Vs+OIiIiYQkWTXFXmwlcB2BTUmdqR0SanERERMYeKJrmi3WsXE3V+LfmGG2F3vWp2HBEREdOoaJLLMqxWWDIagI0V76B63UiTE4mIiJhHRZNc1sZfPqdh/i6yDG9q/+01s+OIiIiYSkWTXFLWuXRqbnwLgK0Rj1Gpari5gUREREymokkuacvMMVQmlROWyjTv+2+z44iIiJhORZNc5PiBXbQ48iUASdH/xse3nMmJREREzKeiSYowrFZSZw7Gx5LHdu/mtIjtb3YkERGREkFFkxSx4aePaZqzmWzDk+B7J2Fx06+IiIgIqGiSPzmVdJT68W8CEF9nsKYYEBER+RMVTQJcOCx3/MtBBJHJPvc6tO73ktmRREREShQVTQLAuu/eJur8WnIMT9zumYyHp5fZkUREREoUFU3C/m1raL7rXQA2Nxyh+8uJiIhcgoqmMu7MyUR8Zz+MtyWPLb5tie77L7MjiYiIlEgqmsqwvNwcTnx+H1WNFI5bQqk16D+6Wk5EROQy9A1ZRlkLCoif9DBNcreSafiQd98MgkPCzI4lIiJSYqloKoMMq5X1kx+jTfoi8g039t4ygfBGrc2OJSIiUqJ5mB1Abqz8vFw2ffwI0WfmYTUsxLd6k9Zd+pkdS0REpMRT0VSGpJ85xaHPHqDt+bUUGBY2NnuZtncNNjuWiIhIqaCiqYzYvXYxQQv+QRQnyTY82dV+Am1jHzI7loiISKmhosnFJR/bz5FZL9AmfSEAxy2hZN71OS1a3mpyMhERkdJFRZMLysnOYnfcL+RvmkGzjJWEWgoAWBd8O40emUS1oAomJxQRESl9VDSVcOczz5Jz7hQnDu3CYlixFuRTkJ+PtSAPa34eeTmZZKclkZ+ehOXMIQLTdlErdx9RlpwLHVhgh1dTPLu/TtuWt5k6FhERkdJMRVMJt3vlTO7b+y/Y68CTLJBCBQ5W7EDFDk/QJKp9seUTEREpK1Q0lXAWDy+yDU8KcKfA4n7hT9zIxwOrxZ08iyfnPCqQ7R1Cnl8o7lWbUal+W2rWb0Fld3ez44uIiLgMFU0lXPPY/szPD+H222/H09PT7DgiIiJllmYEFxEREbGDiiYRERERO6hoEhEREbGDiiYRERERO6hoEhEREbGDiiYRERERO6hoEhEREbGDiiYRERERO6hoEhEREbGDiiYRERERO6hoEhEREbGDiiYRERERO6hoEhEREbGDiiYRERERO3iYHcBVGIYBQEZGhlP7zcvLIysri4yMDDw9PZ3ad0mhMboGjdE1aIyuQWO0X+H3duH3+JWoaHKSs2fPAlCjRg2Tk4iIiIijzp49S1BQ0BXbWAx7Siu5KqvVyokTJwgICMBisTit34yMDGrUqMHRo0cJDAx0Wr8licboGjRG16AxugaN0X6GYXD27FmqVq2Km9uVz1rSniYncXNzo3r16sXWf2BgoMv+4hfSGF2DxugaNEbXoDHa52p7mArpRHARERERO6hoEhEREbGDiqYSztvbm5dffhlvb2+zoxQbjdE1aIyuQWN0DRpj8dCJ4CIiIiJ20J4mERERETuoaBIRERGxg4omERERETuoaBIRERGxg4qmEm7SpEmEh4fj4+NDdHQ069atMzvSNRs7dixt2rQhICCAypUrc/fdd5OQkFCkzW233YbFYiny8+STT5qU2HGvvPLKRfkbNmxoW5+dnc2QIUOoWLEi/v7+9OnTh+TkZBMTOy48PPyiMVosFoYMGQKUzm3422+/ceedd1K1alUsFgtz584tst4wDEaPHk2VKlXw9fWlS5cu7N27t0ib1NRUHnzwQQIDAwkODmbQoEGcO3fuBo7iyq40xry8PJ5//nmaNm1KuXLlqFq1Kv379+fEiRNF+rjUtn/rrbdu8Egu72rbceDAgRfl7969e5E2pXk7Apf8t2mxWHjnnXdsbUrydrTne8Kez9EjR47Qs2dP/Pz8qFy5Ms8++yz5+fnXnU9FUwk2c+ZMRowYwcsvv8ymTZuIioqiW7dupKSkmB3tmqxcuZIhQ4awZs0alixZQl5eHrGxsWRmZhZp9/jjj5OYmGj7GTdunEmJr02TJk2K5P/jjz9s65555hl+/vlnZs2axcqVKzlx4gS9e/c2Ma3j1q9fX2R8S5YsAeDee++1tSlt2zAzM5OoqCgmTZp0yfXjxo3jww8/5JNPPmHt2rWUK1eObt26kZ2dbWvz4IMPsmPHDpYsWcK8efP47bffeOKJJ27UEK7qSmPMyspi06ZNvPTSS2zatInZs2eTkJDAXXfddVHbMWPGFNm2Tz311I2Ib5erbUeA7t27F8n/zTffFFlfmrcjUGRsiYmJTJ06FYvFQp8+fYq0K6nb0Z7viat9jhYUFNCzZ09yc3NZvXo1X375JdOnT2f06NHXH9CQEqtt27bGkCFDbI8LCgqMqlWrGmPHjjUxlfOkpKQYgLFy5UrbsltvvdUYNmyYeaGu08svv2xERUVdcl1aWprh6elpzJo1y7Zs165dBmDExcXdoITON2zYMKNOnTqG1Wo1DKP0b0PAmDNnju2x1Wo1wsLCjHfeece2LC0tzfD29ja++eYbwzAMY+fOnQZgrF+/3tZmwYIFhsViMY4fP37Dstvrr2O8lHXr1hmAcfjwYduyWrVqGe+//37xhnOSS41xwIABRq9evS77HFfcjr169TI6depUZFlp2o5//Z6w53N0/vz5hpubm5GUlGRrM3nyZCMwMNDIycm5rjza01RC5ebmsnHjRrp06WJb5ubmRpcuXYiLizMxmfOkp6cDUKFChSLLv/76a0JCQoiMjGTUqFFkZWWZEe+a7d27l6pVq1K7dm0efPBBjhw5AsDGjRvJy8srsk0bNmxIzZo1S+02zc3N5b///S+PPvpokRtVl/Zt+GcHDx4kKSmpyHYLCgoiOjratt3i4uIIDg6mdevWtjZdunTBzc2NtWvX3vDMzpCeno7FYiE4OLjI8rfeeouKFSvSokUL3nnnHacc8riRVqxYQeXKlWnQoAGDBw/m9OnTtnWuth2Tk5P55ZdfGDRo0EXrSst2/Ov3hD2fo3FxcTRt2pTQ0FBbm27dupGRkcGOHTuuK49u2FtCnTp1ioKCgiIbHSA0NJTdu3eblMp5rFYrw4cPp3379kRGRtqWP/DAA9SqVYuqVauydetWnn/+eRISEpg9e7aJae0XHR3N9OnTadCgAYmJibz66qvccsstbN++naSkJLy8vC76EgoNDSUpKcmcwNdp7ty5pKWlMXDgQNuy0r4N/6pw21zq32LhuqSkJCpXrlxkvYeHBxUqVCiV2zY7O5vnn3+efv36FbkR6tNPP03Lli2pUKECq1evZtSoUSQmJvLee++ZmNZ+3bt3p3fv3kRERLB//35eeOEFevToQVxcHO7u7i63Hb/88ksCAgIuOgWgtGzHS31P2PM5mpSUdMl/r4XrroeKJjHFkCFD2L59e5HzfYAi5w40bdqUKlWq0LlzZ/bv30+dOnVudEyH9ejRw/b3Zs2aER0dTa1atfjuu+/w9fU1MVnxmDJlCj169KBq1aq2ZaV9G5Z1eXl53HfffRiGweTJk4usGzFihO3vzZo1w8vLi7///e+MHTu2VNyu4/7777f9vWnTpjRr1ow6deqwYsUKOnfubGKy4jF16lQefPBBfHx8iiwvLdvxct8TZtLhuRIqJCQEd3f3i64ISE5OJiwszKRUzjF06FDmzZvHr7/+SvXq1a/YNjo6GoB9+/bdiGhOFxwcTP369dm3bx9hYWHk5uaSlpZWpE1p3aaHDx9m6dKlPPbYY1dsV9q3YeG2udK/xbCwsIsu0MjPzyc1NbVUbdvCgunw4cMsWbKkyF6mS4mOjiY/P59Dhw7dmIBOVrt2bUJCQmy/m66yHQF+//13EhISrvrvE0rmdrzc94Q9n6NhYWGX/PdauO56qGgqoby8vGjVqhXLli2zLbNarSxbtoyYmBgTk107wzAYOnQoc+bMYfny5URERFz1OfHx8QBUqVKlmNMVj3PnzrF//36qVKlCq1at8PT0LLJNExISOHLkSKncptOmTaNy5cr07Nnziu1K+zaMiIggLCysyHbLyMhg7dq1tu0WExNDWloaGzdutLVZvnw5VqvVVjSWdIUF0969e1m6dCkVK1a86nPi4+Nxc3O76JBWaXHs2DFOnz5t+910he1YaMqUKbRq1YqoqKirti1J2/Fq3xP2fI7GxMSwbdu2IgVw4X8CGjdufN0BpYT69ttvDW9vb2P69OnGzp07jSeeeMIIDg4uckVAaTJ48GAjKCjIWLFihZGYmGj7ycrKMgzDMPbt22eMGTPG2LBhg3Hw4EHjxx9/NGrXrm106NDB5OT2GzlypLFixQrj4MGDxqpVq4wuXboYISEhRkpKimEYhvHkk08aNWvWNJYvX25s2LDBiImJMWJiYkxO7biCggKjZs2axvPPP19keWndhmfPnjU2b95sbN682QCM9957z9i8ebPtyrG33nrLCA4ONn788Udj69atRq9evYyIiAjj/Pnztj66d+9utGjRwli7dq3xxx9/GPXq1TP69etn1pAucqUx5ubmGnfddZdRvXp1Iz4+vsi/z8KrjVavXm28//77Rnx8vLF//37jv//9r1GpUiWjf//+Jo/s/11pjGfPnjX++c9/GnFxccbBgweNpUuXGi1btjTq1atnZGdn2/oozduxUHp6uuHn52dMnjz5oueX9O14te8Jw7j652h+fr4RGRlpxMbGGvHx8cbChQuNSpUqGaNGjbrufCqaSriPPvrIqFmzpuHl5WW0bdvWWLNmjdmRrhlwyZ9p06YZhmEYR44cMTp06GBUqFDB8Pb2NurWrWs8++yzRnp6urnBHdC3b1+jSpUqhpeXl1GtWjWjb9++xr59+2zrz58/b/zjH/8wypcvb/j5+Rn33HOPkZiYaGLia7No0SIDMBISEoosL63b8Ndff73k7+aAAQMMw7gw7cBLL71khIaGGt7e3kbnzp0vGvvp06eNfv36Gf7+/kZgYKDxyCOPGGfPnjVhNJd2pTEePHjwsv8+f/31V8MwDGPjxo1GdHS0ERQUZPj4+BiNGjUy3nzzzSIFh9muNMasrCwjNjbWqFSpkuHp6WnUqlXLePzxxy/6T2hp3o6FPv30U8PX19dIS0u76PklfTte7XvCMOz7HD106JDRo0cPw9fX1wgJCTFGjhxp5OXlXXc+y/9CioiIiMgV6JwmERERETuoaBIRERGxg4omERERETuoaBIRERGxg4omERERETuoaBIRERGxg4omERERETuoaBIRERGxg4omEXFZAwcO5O67777hrzt9+nQsFgsWi4Xhw4fb9ZyBAwfanjN37txizSci18bD7AAiItfCYrFccf3LL7/MBx98gFk3PQgMDCQhIYFy5crZ1f6DDz7grbfeKrU3NhYpC1Q0iUiplJiYaPv7zJkzGT16NAkJCbZl/v7++Pv7mxENuFDUhYWF2d0+KCiIoKCgYkwkItdLh+dEpFQKCwuz/QQFBdmKlMIff3//iw7P3XbbbTz11FMMHz6c8uXLExoayueff05mZiaPPPIIAQEB1K1blwULFhR5re3bt9OjRw/8/f0JDQ3l4Ycf5tSpUw5n/vjjj6lXrx4+Pj6Ehobyt7/97XrfBhG5gVQ0iUiZ8uWXXxISEsK6det46qmnGDx4MPfeey833XQTmzZtIjY2locffpisrCwA0tLS6NSpEy1atGDDhg0sXLiQ5ORk7rvvPoded8OGDTz99NOMGTOGhIQEFi5cSIcOHYpjiCJSTHR4TkTKlKioKF588UUARo0axVtvvUVISAiPP/44AKNHj2by5Mls3bqVdu3aMXHiRFq0aMGbb75p62Pq1KnUqFGDPXv2UL9+fbte98iRI5QrV4477riDgIAAatWqRYsWLZw/QBEpNtrTJCJlSrNmzWx/d3d3p2LFijRt2tS2LDQ0FICUlBQAtmzZwq+//mo7R8rf35+GDRsCsH//frtft2vXrtSqVYvatWvz8MMP8/XXX9v2ZolI6aCiSUTKFE9PzyKPLRZLkWWFV+VZrVYAzp07x5133kl8fHyRn7179zp0eC0gIIBNmzbxzTffUKVKFUaPHk1UVBRpaWnXPygRuSF0eE5E5ApatmzJDz/8QHh4OB4e1/eR6eHhQZcuXejSpQsvv/wywcHBLF++nN69ezsprYgUJ+1pEhG5giFDhpCamkq/fv1Yv349+/fvZ9GiRTzyyCMUFBTY3c+8efP48MMPiY+P5/Dhw3z11VdYrVYaNGhQjOlFxJlUNImIXEHVqlVZtWoVBQUFxMbG0rRpU4YPH05wcDBubvZ/hAYHBzN79mw6depEo0aN+OSTT/jmm29o0qRJMaYXEWeyGGZNlysi4qKmT5/O8OHDr+l8JYvFwpw5c0y5/YuIXJn2NImIFIP09HT8/f15/vnn7Wr/5JNPmjqDuYhcnfY0iYg42dmzZ0lOTgYuHJYLCQm56nNSUlLIyMgAoEqVKnbfs05EbhwVTSIiIiJ20OE5ERERETuoaBIRERGxg4omERERETuoaBIRERGxg4omERERETuoaBIRERGxg4omERERETuoaBIRERGxw/8BOk79YmmPf4wAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.plot(df['time'][1:], df['antenna/pathloss/pad_distance'][1:], label='Dist to PAD')\n",
    "plt.plot(df['time'][1:], df['antenna/pathloss/gs_distance'][1:], label='Dist to GS')\n",
    "plt.ylabel(\"Frespace pathloss [dB]\")\n",
    "plt.xlabel(\"Time [s]\")\n",
    "plt.legend()\n",
    "\n",
    "print(np.max(df['antenna/pathloss/gs_distance'][1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-8.061355822543295\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.grid()\n",
    "plt.plot(df['time'][1:], df['antenna/tx_gain/out'][1:], label='FSPL')\n",
    "plt.ylabel(\"TX Antenna Gain [dBi]\")\n",
    "plt.xlabel(\"Time [s]\")\n",
    "\n",
    "print(np.min(df['antenna/tx_gain/out'][1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-110.36486375494266\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Calculate recieved power\n",
    "# Assumptions:  3 dB polarization loss\n",
    "#               25 dBm output power per channel\n",
    "#               16 dBi antenna rx gain\n",
    "#               -6 dB on reciever side\n",
    "\n",
    "\n",
    "df[\"antenna/power_rx\"] = 20+df[\"antenna/tx_gain/out\"] - df[\"antenna/pathloss/out\"] - 3 + 10 - 6 \n",
    "plt.grid()\n",
    "plt.plot(df['time'][1:], df['antenna/power_rx'][1:], label='FSPL')\n",
    "plt.ylabel(\"Recieved Power [dBm]\")\n",
    "plt.xlabel(\"Time [s]\")\n",
    "\n",
    "print(np.min(df['antenna/power_rx'][1:]))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}