SPATZ/new_sensor.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "# Preprocess\n",
    "import os\n",
    "import shutil\n",
    "\n",
    "from spatz.utils.preprocess import preprocess_file\n",
    "\n",
    "\n",
    "PATH = 'data/simulations/'\n",
    "\n",
    "# Delete the old folder of preprocessed files.\n",
    "if os.path.isdir(PATH + 'temp/'):\n",
    "    shutil.rmtree(PATH + 'temp/')\n",
    "\n",
    "# Create the folder again.\n",
    "os.mkdir(PATH + 'temp/')\n",
    "\n",
    "# Preprocess the files.\n",
    "for file in os.listdir(PATH):\n",
    "    if not os.path.isdir(PATH + file) and '.txt' in file:\n",
    "        df = preprocess_file(PATH + file)\n",
    "        df.to_csv(PATH + 'temp/' + file.replace('.txt', '.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from spatz.simulation import Simulation, UniformTimeSteps\n",
    "\n",
    "# Construct a time model.\n",
    "timesteps = UniformTimeSteps(0.1, mu=0, sigma=0, delay_only=True)\n",
    "\n",
    "# Construct a simulation instance with the time model.\n",
    "simulation = Simulation(timesteps)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed 65160 lines in 1.0s.\n",
      "Used 65160 lines due to step size\n"
     ]
    }
   ],
   "source": [
    "#Setup Sensors / observers\n",
    "\n",
    "from spatz.sensors.antenna.tx_gain import AntennaTxGain\n",
    "\n",
    "altitude = simulation.add_observer(['altitude'])\n",
    "latitude = simulation.add_observer(['latitude'])\n",
    "longitude = simulation.add_observer(['longitude'])\n",
    "\n",
    "x = simulation.add_observer(['x'])\n",
    "y = simulation.add_observer(['y'])\n",
    "z = simulation.add_observer(['z'])\n",
    "p = simulation.add_observer(['pitch_l'])\n",
    "\n",
    "antenna_tx_gain_sensor = simulation.add_sensor(AntennaTxGain)\n",
    "\n",
    "simulation.load(PATH + 'temp/' + '13_5DrougeOnly.csv')\n",
    "logger = simulation.get_logger()\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████▉| 299.9999999999997/300.0 [00:32<00:00,  9.19it/s] \n"
     ]
    }
   ],
   "source": [
    "# Run simulation\n",
    "for step, t, dt in simulation.run(verbose=True):\n",
    "    # Get the sensor data for the current time\n",
    "    gain = antenna_tx_gain_sensor()\n",
    "    \n",
    "    \n",
    "    # Get the correct altitude data.\n",
    "    altitude()\n",
    "    latitude()\n",
    "    longitude()\n",
    "\n",
    "    x()\n",
    "    y()\n",
    "    z()\n",
    "    p()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</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/tx_gain/out</th>\n",
       "      <th>general/altitude</th>\n",
       "      <th>general/latitude</th>\n",
       "      <th>general/longitude</th>\n",
       "      <th>general/x</th>\n",
       "      <th>general/y</th>\n",
       "      <th>general/z</th>\n",
       "      <th>general/pitch_l</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.1</td>\n",
       "      <td>-0.658078</td>\n",
       "      <td>319.189854</td>\n",
       "      <td>1.184825</td>\n",
       "      <td>0.367914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.033017</td>\n",
       "      <td>0.189854</td>\n",
       "      <td>1.396263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2</td>\n",
       "      <td>-0.658078</td>\n",
       "      <td>319.754649</td>\n",
       "      <td>1.184825</td>\n",
       "      <td>0.367914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.131239</td>\n",
       "      <td>0.754649</td>\n",
       "      <td>1.396263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.3</td>\n",
       "      <td>-0.658077</td>\n",
       "      <td>320.689767</td>\n",
       "      <td>1.184825</td>\n",
       "      <td>0.367914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.293862</td>\n",
       "      <td>1.689767</td>\n",
       "      <td>1.396263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.4</td>\n",
       "      <td>-0.658076</td>\n",
       "      <td>321.98961</td>\n",
       "      <td>1.184825</td>\n",
       "      <td>0.367914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.519914</td>\n",
       "      <td>2.98961</td>\n",
       "      <td>1.396263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.5</td>\n",
       "      <td>-0.658075</td>\n",
       "      <td>323.649225</td>\n",
       "      <td>1.184825</td>\n",
       "      <td>0.367914</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.808532</td>\n",
       "      <td>4.649225</td>\n",
       "      <td>1.396263</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2995</th>\n",
       "      <td>299.6</td>\n",
       "      <td>0.209598</td>\n",
       "      <td>954.385196</td>\n",
       "      <td>1.186267</td>\n",
       "      <td>0.367917</td>\n",
       "      <td>7.639079</td>\n",
       "      <td>9218.178485</td>\n",
       "      <td>628.737611</td>\n",
       "      <td>0.000023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2996</th>\n",
       "      <td>299.7</td>\n",
       "      <td>0.209596</td>\n",
       "      <td>950.544731</td>\n",
       "      <td>1.186267</td>\n",
       "      <td>0.367917</td>\n",
       "      <td>7.639903</td>\n",
       "      <td>9218.177327</td>\n",
       "      <td>624.897143</td>\n",
       "      <td>0.000023</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2997</th>\n",
       "      <td>299.8</td>\n",
       "      <td>0.209595</td>\n",
       "      <td>946.704266</td>\n",
       "      <td>1.186267</td>\n",
       "      <td>0.367917</td>\n",
       "      <td>7.640726</td>\n",
       "      <td>9218.176168</td>\n",
       "      <td>621.056675</td>\n",
       "      <td>0.000023</td>\n",
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       "    <tr>\n",
       "      <th>2998</th>\n",
       "      <td>299.9</td>\n",
       "      <td>0.209593</td>\n",
       "      <td>942.8638</td>\n",
       "      <td>1.186267</td>\n",
       "      <td>0.367917</td>\n",
       "      <td>7.64155</td>\n",
       "      <td>9218.175009</td>\n",
       "      <td>617.216207</td>\n",
       "      <td>0.000023</td>\n",
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       "    <tr>\n",
       "      <th>2999</th>\n",
       "      <td>300.0</td>\n",
       "      <td>0.209592</td>\n",
       "      <td>939.023335</td>\n",
       "      <td>1.186267</td>\n",
       "      <td>0.367917</td>\n",
       "      <td>7.642373</td>\n",
       "      <td>9218.17385</td>\n",
       "      <td>613.37574</td>\n",
       "      <td>0.000023</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3000 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       time antenna/tx_gain/out general/altitude general/latitude  \\\n",
       "0       0.1           -0.658078       319.189854         1.184825   \n",
       "1       0.2           -0.658078       319.754649         1.184825   \n",
       "2       0.3           -0.658077       320.689767         1.184825   \n",
       "3       0.4           -0.658076        321.98961         1.184825   \n",
       "4       0.5           -0.658075       323.649225         1.184825   \n",
       "...     ...                 ...              ...              ...   \n",
       "2995  299.6            0.209598       954.385196         1.186267   \n",
       "2996  299.7            0.209596       950.544731         1.186267   \n",
       "2997  299.8            0.209595       946.704266         1.186267   \n",
       "2998  299.9            0.209593         942.8638         1.186267   \n",
       "2999  300.0            0.209592       939.023335         1.186267   \n",
       "\n",
       "     general/longitude general/x    general/y   general/z general/pitch_l  \n",
       "0             0.367914       0.0     0.033017    0.189854        1.396263  \n",
       "1             0.367914       0.0     0.131239    0.754649        1.396263  \n",
       "2             0.367914       0.0     0.293862    1.689767        1.396263  \n",
       "3             0.367914       0.0     0.519914     2.98961        1.396263  \n",
       "4             0.367914       0.0     0.808532    4.649225        1.396263  \n",
       "...                ...       ...          ...         ...             ...  \n",
       "2995          0.367917  7.639079  9218.178485  628.737611        0.000023  \n",
       "2996          0.367917  7.639903  9218.177327  624.897143        0.000023  \n",
       "2997          0.367917  7.640726  9218.176168  621.056675        0.000023  \n",
       "2998          0.367917   7.64155  9218.175009  617.216207        0.000023  \n",
       "2999          0.367917  7.642373   9218.17385   613.37574        0.000023  \n",
       "\n",
       "[3000 rows x 9 columns]"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = logger.get_dataframe()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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/a7fbrdzcXBUVFZ2yeLO8Xq/Kyso0e/ZsORwOU9972rnHdPkv3tHuhnZ9OWSKvn1OXlBr62/60qtoQ68CR68CR6/MoV+BC1WvOq9cBKJX4WPPnj16/fXX9ac//cl/LCsrS62traqrq1Nqaqr/eG1trbKysk44ltPplNPp7Hbc4XCE7APUm7FHpjt0x2UTdeeL2/Qf63aoaHK2ctP6x8xMKIXy30OkoVeBo1eBo1fm0K/ABbtXZsbq1T4fq1atUkZGhi6//HL/sRkzZsjhcGj9+vX+Y9u3b1dVVZUKCgp68zb9zsKz8zQzP03HvO36yR8/lM/XqytWAABENdPhw+fzadWqVVq0aJFiY/8xcZKSkqIbbrhBJSUlevPNN1VZWanFixeroKDghItNBxq73aYHF0xTvMOud3Yd0VPvfGF1SQAADDimw8frr7+uqqoqfec73+n22iOPPKIrrrhCCxYs0AUXXKCsrKwul2YiwcihSfr/L5soSXrg1U/1WW2DxRUBADCwmA4fRUVFMgxD48aN6/ZafHy8SktL9eWXX6qpqUl/+tOfTrreY6D61jkjdNH4dLW2+bTk2S1qbWPzMQAAAsWzXXrBZrPpoQXTNDjRoY8PuPXI659ZXRIAAAMG4aOXMlzxWj5/qiTpyfJdenf3lxZXBADAwED46INLp2TrGzOGyzCk257bIncLO+sBAHAqhI8+uvvKScpNS9D+umNa+qet6uWGsQAARA3CRx8Ninfo8WtOV6zdpv/98ICeeXev1SUBANCvET6C4PS8wfrxnPGSpGVrP9KnNYFvMQsAQLQhfATJjeeP0kXj0+Vp8+mW1R+oubXN6pIAAOiXCB9BYrfb9J/fnK5Ml1M7Dzbqnj9/ZHVJAAD0S4SPIBqS7NSjV58uu016fvM+vbRlv9UlAQDQ7xA+gqxg9BDdOmusJOnf/rRVOw+y/ToAAF9F+AiBf71krP5p9BA1tbbru7+vVKOH9R8AAHQifIRAjN2mx689Xdkp8dp1qEk/XvN39v8AAOA4wkeIDE126omFZ8gRY9Mr22r0679+bnVJAAD0C4SPEDo9b7DuvnKyJOmBVz7VO7sOW1wRAADWI3yE2MKZeVpwxnD5DOnW1R/oQP0xq0sCAMBShI8Qs9lsuv+fp2hStktHmlp189Pvy9vus7osAAAsQ/gIg3hHjJ781gwNio/VB1V1+vfXtltdEgAAliF8hEnekET9+zemS5J+teFzrf+k1uKKAACwBuEjjC6dkqXr/2mkJOmHa/6u6jrWfwAAog/hI8yWXjZBU4elqK7Zq3995gO1+9j/AwAQXQgfYeaMjVHpdWco2RmrzXuO6jdv77a6JAAAworwYYG8IYn66eUTJUn/sW67dh1qtLgiAADCh/BhkavPytX5Y4fK0+bT7X/4kMsvAICoQfiwiM1m0wMLpinZGavKPUf1u4ovrC4JAICwIHxYaFhqgu6YO0GS9PC6z3SowWNxRQAAhB7hw2LXnp2nqcNS1OBp00Ovfmp1OQAAhBzhw2IxdpuWzet4+Nyayn16v+qoxRUBABBahI9+4Iy8wfrmjOGSpLtf+kg+Fp8CACIY4aOfuP3SCRrkjNXW/fVa+2G11eUAABAyhI9+In2QUzddMEqS9EjZZzz5FgAQsQgf/ch3zsvXkKQ4fXGkWX+o3Gd1OQAAhITp8LF//35961vf0pAhQ5SQkKCpU6dq8+bN/tcNw9Bdd92l7OxsJSQkqLCwUDt27Ahq0ZEqyRmr4ovHSJIee32HWrztFlcEAEDwmQofR48e1bnnniuHw6FXXnlFH3/8sf7zP/9TgwcP9p/z0EMP6fHHH9eTTz6pTZs2KSkpSXPmzFFLS0vQi49E183MU05KvGrcLXp6U5XV5QAAEHSmwseDDz6o3NxcrVq1Smeffbby8/NVVFSk0aNHS+qY9Xj00Uf105/+VPPmzdO0adP0u9/9TtXV1XrxxRdDUX/EiXfE6JZZYyVJ//3Xz9XaxtoPAEBkiTVz8p///GfNmTNH3/zmN1VeXq5hw4bp5ptv1o033ihJ2r17t2pqalRYWOj/npSUFM2cOVMVFRW65ppruo3p8Xjk8fxjZ0+32y1J8nq98nq9vfqhTqRzvGCPG2z/Z2qGHimL04H6Fr3wfpXmnz4s7DUMlF71B/QqcPQqcPTKHPoVuFD1ysx4NsMwAt5UIj4+XpJUUlKib37zm3rvvff0gx/8QE8++aQWLVqkd955R+eee66qq6uVnZ3t/75/+Zd/kc1m03PPPddtzHvuuUfLli3rdnz16tVKTEwM+AeJNK/vt2ltVYyyEgz9ZHq77DarKwIA4MSam5t13XXXqb6+Xi6X66Tnmpr58Pl8OvPMM/Xzn/9cknT66adr27Zt/vDRG0uXLlVJSYn/a7fbrdzcXBUVFZ2yeLO8Xq/Kyso0e/ZsORyOoI4dbOe3ePXmf/xVNcfalDDqTF0yMSOs7z+QemU1ehU4ehU4emUO/QpcqHrVeeUiEKbCR3Z2tiZNmtTl2MSJE/XHP/5RkpSVlSVJqq2t7TLzUVtbq9NOO63HMZ1Op5xOZ7fjDocjZB+gUI4dLGkOh751zgg9Wb5Lv924V5dOC/+lF2lg9Kq/oFeBo1eBo1fm0K/ABbtXZsYyteD03HPP1fbt27sc++yzzzRixAhJUn5+vrKysrR+/Xr/6263W5s2bVJBQYGZt4Kk/1swQnabVPH5Ee082GB1OQAABIWp8HHbbbdp48aN+vnPf66dO3dq9erV+tWvfqXi4mJJks1m05IlS3Tffffpz3/+s7Zu3apvf/vbysnJ0VVXXRWK+iPasNQEXTIxU5L0Pxu57RYAEBlMhY+zzjpLL7zwgp555hlNmTJFP/vZz/Too49q4cKF/nNuv/123Xrrrbrpppt01llnqbGxUa+++qp/sSrM+b/ndMwq/bFyn5o8bRZXAwBA35la8yFJV1xxha644ooTvm6z2XTvvffq3nvv7VNh6HDemKEaOSRRXxxp1ktbqnXdzDyrSwIAoE94tks/Z7fb9K3jsx//s3GPxdUAANB3hI8B4Bszhisuxq6PD7j1cXXgtzIBANAfET4GgNTEOP8+H398n6fdAgAGNsLHALHgjOGSpJe27Je3nee9AAAGLsLHAHHh+HQNSYrT4cZW/XXHIavLAQCg1wgfA4Qjxq55p3XscvrHyv0WVwMAQO8RPgaQ+Wd0hI/XP6llzw8AwIBF+BhAJue4lD80SZ42n17/pNbqcgAA6BXCxwBis9l0xbSOB/b974cHLK4GAIDeIXwMMJcfDx9vfXZIDS1ei6sBAMA8wscAMz5zkEanJ6mVSy8AgAGK8DHA2Gw2XT4tRxKXXgAAAxPhYwC6bGqWJOmvOw6ruZW7XgAAAwvhYwAanzlIuWkJ8rT59Ncdh60uBwAAUwgfA5DNZlPhxExJUtnHrPsAAAwshI8BavakjvDxxqcH1e4zLK4GAIDAET4GqLNGpskVH6svm1r1ftVRq8sBACBghI8ByhFj16wJGZK49AIAGFgIHwNY4VcuvQAAMFAQPgaw88eky26Tdh5s1P66Y1aXAwBAQAgfA1hKokOn5aZKkjZ8dsjaYgAACBDhY4C7cFzHuo/y7YQPAMDAQPgY4C4cny5J+tvOw/K2+yyuBgCAUyN8DHBTh6UoNdGhBk+btuyts7ocAABOifAxwMXYbTp/bMfsB5deAAADAeEjAlw4riN8bNhB+AAA9H+Ejwhw3pihkqRt++tVf8xrcTUAAJwc4SMCZKXEK39oknyG9N7uL60uBwCAkyJ8RIhzRqVJkio+P2JxJQAAnBzhI0KcM2qIJGkj4QMA0M8RPiJEwfHw8fEBt+qaWy2uBgCAEzMVPu655x7ZbLYufyZMmOB/vaWlRcXFxRoyZIiSk5O1YMEC1dbyxNVwyHDFa1R6kgxDepd1HwCAfsz0zMfkyZN14MAB/5+3337b/9ptt92mtWvXas2aNSovL1d1dbXmz58f1IJxYp2zH6z7AAD0Z7GmvyE2VllZWd2O19fXa+XKlVq9erVmzZolSVq1apUmTpyojRs36pxzzul7tTipgtFD9PSmKlXsInwAAPov0+Fjx44dysnJUXx8vAoKCrR8+XLl5eWpsrJSXq9XhYWF/nMnTJigvLw8VVRUnDB8eDweeTwe/9dut1uS5PV65fUGd8+KzvGCPW5/MSPXJUn6tKZBB+ubNDgxrtdjRXqvgoleBY5eBY5emUO/AheqXpkZz2YYhhHoya+88ooaGxs1fvx4HThwQMuWLdP+/fu1bds2rV27VosXL+4SJCTp7LPP1sUXX6wHH3ywxzHvueceLVu2rNvx1atXKzExMeAfBB2Wb4lRzTGbbhjfrmlpAf+rBQCgT5qbm3Xdddepvr5eLpfrpOeamvmYO3eu/5+nTZummTNnasSIEXr++eeVkJDQq2KXLl2qkpIS/9dut1u5ubkqKio6ZfFmeb1elZWVafbs2XI4HEEdu794x/uRntu8X/b00bpszrhejxMNvQoWehU4ehU4emUO/QpcqHrVeeUiEKYvu3xVamqqxo0bp507d2r27NlqbW1VXV2dUlNT/efU1tb2uEakk9PplNPp7Hbc4XCE7AMUyrGtdubIIXpu8359sLc+KD9jJPcq2OhV4OhV4OiVOfQrcMHulZmx+rTPR2Njo3bt2qXs7GzNmDFDDodD69ev97++fft2VVVVqaCgoC9vAxNmjBgsSfpwf708be0WVwMAQHemZj5+9KMf6corr9SIESNUXV2tu+++WzExMbr22muVkpKiG264QSUlJUpLS5PL5dKtt96qgoIC7nQJo/yhSUpLitOXTa36qNqtM/IGW10SAABdmAof+/bt07XXXqsjR44oPT1d5513njZu3Kj09I5Huj/yyCOy2+1asGCBPB6P5syZoyeeeCIkhaNnNptNZ+QN1uuf1Or9PUcJHwCAfsdU+Hj22WdP+np8fLxKS0tVWlrap6LQNzNGdISPyj1H9f+db3U1AAB0xbNdItCZIztmOzbvOSoTd1IDABAWhI8INHVYihwxNh1q8Gjf0WNWlwMAQBeEjwgU74jR5JwUSdL7VUctrgYAgK4IHxHqtNxUSdLf99ZbWwgAAF9D+IhQ04Z3zHxs3V9nbSEAAHwN4SNCdYaPbfvdamv3WVwNAAD/QPiIUKOGJispLkbHvO3adajJ6nIAAPAjfEQou92mKcM6Zj/+vq/O2mIAAPgKwkcEm3580enWfSw6BQD0H4SPCDb1+MzHh8x8AAD6EcJHBJs+PFWS9MmBBrW2segUANA/ED4iWG5aglITHWpt9+mz2garywEAQBLhI6LZbDb/pRcWnQIA+gvCR4TzbzbGolMAQD9B+IhwU4elSpK27id8AAD6B8JHhJuc45Ik7ahtlJedTgEA/QDhI8INH5ygQc5Ytbb79Dk7nQIA+gHCR4Sz2WyakD1IkvTxAS69AACsR/iIAhOzOy69fHKA220BANYjfESBSf7w4ba4EgAACB9RoXPm4+NqtwzDsLgaAEC0I3xEgfFZg2S3SUeaWnWowWN1OQCAKEf4iALxjhjlD02SJH3MpRcAgMUIH1FiUk7HTqcsOgUAWI3wESUm+m+3ZeYDAGAtwkeUmMgdLwCAfoLwESUmZHXMfHxxuEmtbWyzDgCwDuEjSmS54jXIGas2n6EvjrDNOgDAOoSPKGGz2TQmM1mS9Fkti04BANYhfESRcRkdl14+q220uBIAQDQjfESRscdnPnYeZOYDAGCdPoWPBx54QDabTUuWLPEfa2lpUXFxsYYMGaLk5GQtWLBAtbW1fa0TQTA2k5kPAID1eh0+3nvvPf3Xf/2Xpk2b1uX4bbfdprVr12rNmjUqLy9XdXW15s+f3+dC0Xfjjs98cMcLAMBKvQofjY2NWrhwoX79619r8ODB/uP19fVauXKlHn74Yc2aNUszZszQqlWr9M4772jjxo1BKxq9wx0vAID+ILY331RcXKzLL79chYWFuu+++/zHKysr5fV6VVhY6D82YcIE5eXlqaKiQuecc063sTwejzyefzzszO3u2ATL6/XK6/X2prwT6hwv2OMOJKMzkrRlb70+2V+n/LT4E55HrwJHrwJHrwJHr8yhX4ELVa/MjGc6fDz77LN6//339d5773V7raamRnFxcUpNTe1yPDMzUzU1NT2Ot3z5ci1btqzb8XXr1ikxMdFseQEpKysLybgDQbzHLsmuv7yzRdp76ksv0dwrs+hV4OhV4OiVOfQrcMHuVXNzc8Dnmgofe/fu1Q9+8AOVlZUpPv7E/9VsxtKlS1VSUuL/2u12Kzc3V0VFRXK5XEF5j05er1dlZWWaPXu2HA5HUMceKGrf2aONr2yXLSVbl102/YTn0avA0avA0avA0Stz6FfgQtWrzisXgTAVPiorK3Xw4EGdccYZ/mPt7e3asGGDfvnLX+q1115Ta2ur6urqusx+1NbWKisrq8cxnU6nnE5nt+MOhyNkH6BQjt3fjc/ueLrtzkNNAfUgmntlFr0KHL0KHL0yh34FLti9MjOWqfBxySWXaOvWrV2OLV68WBMmTNBPfvIT5ebmyuFwaP369VqwYIEkafv27aqqqlJBQYGZt0KIfP2Ol7hYtnoBAISXqfAxaNAgTZkypcuxpKQkDRkyxH/8hhtuUElJidLS0uRyuXTrrbeqoKCgx8WmCL/OO14aPG3ac6TJv/cHAADh0qu7XU7mkUcekd1u14IFC+TxeDRnzhw98cQTwX4b9JLNZlN+epI+3Fevzw8TPgAA4dfn8PHWW291+To+Pl6lpaUqLS3t69AIkfyhHeFj92H2+gAAhB8X/KPQqKEd6z4+P8Q26wCA8CN8RKH89CRJYuYDAGAJwkcUGjW0I3x8fojwAQAIP8JHFMo/Hj6ONLWqvpmtiAEA4UX4iEJJzlhluTp2qP38MOs+AADhRfiIUp2zH6z7AACEG+EjSo1KZ90HAMAahI8oxcwHAMAqhI8oNTr9+F4fhA8AQJgRPqLUP2Y+GuXzGRZXAwCIJoSPKDV8cIIcMTa1eH2qcbdYXQ4AIIoQPqJUbIxdeWmJklh0CgAIL8JHFMs//oyX3UcIHwCA8CF8RLERQzpmPqoIHwCAMCJ8RLHO8LHnSLPFlQAAognhI4p1rvmo+pLwAQAIH8JHFPtq+DAMbrcFAIQH4SOKDR+cKLtNam5t16FGj9XlAACiBOEjisXF2pWdkiBJqmLdBwAgTAgfUY5FpwCAcCN8RDn/7bYsOgUAhAnhI8rlpXU844XwAQAIF8JHlOu842UPG40BAMKE8BHluOwCAAg3wkeUyzsePg43tqrR02ZxNQCAaED4iHKueIcGJzokcbstACA8CB9Q3pDORaes+wAAhB7hAxqRxl4fAIDwIXxAuWkdu5zurztmcSUAgGhA+ICGD+6Y+dh3lPABAAg9wgc0fHDHzMe+o1x2AQCEnqnwsWLFCk2bNk0ul0sul0sFBQV65ZVX/K+3tLSouLhYQ4YMUXJyshYsWKDa2tqgF43g+urMh2EYFlcDAIh0psLH8OHD9cADD6iyslKbN2/WrFmzNG/ePH300UeSpNtuu01r167VmjVrVF5erurqas2fPz8khSN4clLjJUnNre062uy1uBoAQKSLNXPylVde2eXr+++/XytWrNDGjRs1fPhwrVy5UqtXr9asWbMkSatWrdLEiRO1ceNGnXPOOcGrGkHljI1RpsupWrdH+442Ky0pzuqSAAARzFT4+Kr29natWbNGTU1NKigoUGVlpbxerwoLC/3nTJgwQXl5eaqoqDhh+PB4PPJ4PP6v3W63JMnr9crrDe5/hXeOF+xxI8Gw1ATVuj364lCDJmYm0SsT6FXg6FXg6JU59CtwoeqVmfFMh4+tW7eqoKBALS0tSk5O1gsvvKBJkyZpy5YtiouLU2pqapfzMzMzVVNTc8Lxli9frmXLlnU7vm7dOiUmJpotLyBlZWUhGXcgszXbJdm1fuMHMqr+se6DXgWOXgWOXgWOXplDvwIX7F41Nwd+04Lp8DF+/Hht2bJF9fX1+sMf/qBFixapvLzc7DB+S5cuVUlJif9rt9ut3NxcFRUVyeVy9Xrcnni9XpWVlWn27NlyOBxBHXug+6Rshyo37NagrJG67LKJ9MoEehU4ehU4emUO/QpcqHrVeeUiEKbDR1xcnMaMGSNJmjFjht577z099thjuvrqq9Xa2qq6urousx+1tbXKyso64XhOp1NOp7PbcYfDEbIPUCjHHqjyhiRLkqrrPV16Q68CR68CR68CR6/MoV+BC3avzIzV530+fD6fPB6PZsyYIYfDofXr1/tf2759u6qqqlRQUNDXt0GIsdcHACBcTM18LF26VHPnzlVeXp4aGhq0evVqvfXWW3rttdeUkpKiG264QSUlJUpLS5PL5dKtt96qgoIC7nQZADrDx372+gAAhJip8HHw4EF9+9vf1oEDB5SSkqJp06bptdde0+zZsyVJjzzyiOx2uxYsWCCPx6M5c+boiSeeCEnhCK6c1I7w0dTarrpmr5LjbBZXBACIVKbCx8qVK0/6enx8vEpLS1VaWtqnohB+8Y4YZQxy6mCDR/uOHtOEzNDcaQQAAM92gR/rPgAA4UD4gB9PtwUAhAPhA37MfAAAwoHwAb/s44tOq+tbLK4EABDJCB/wG3b86bbVdVx2AQCEDuEDftkpHTMfB5j5AACEEOEDfjnHw8eXTa1q8bZbXA0AIFIRPuDnSohVYlyMJKnGzewHACA0CB/ws9ls/p1Oq+sIHwCA0CB8oIvslI5Fp6z7AACECuEDXeSw6BQAEGKED3SRffx2W9Z8AABChfCBLpj5AACEGuEDXbDgFAAQaoQPdNF52eUAl10AACFC+EAXnZddmjztOtZmcTEAgIhE+EAXCXExSk10SJKOtlpcDAAgIhE+0E3nM16OemwWVwIAiESED3TT+XTbOmY+AAAhQPhAN50zH3XMfAAAQoDwgW4673hhzQcAIBQIH+gmx7/mw+JCAAARifCBbjofLsdlFwBAKBA+0E3nLqd1rZJhGBZXAwCINIQPdJPp6pj5aDNsOtrstbgaAECkIXygm7hYu9KSOjYaq3Wz8AMAEFyED/Qoc1DH7EdtA894AQAEF+EDPcpwOSVJB5n5AAAEGeEDPco6Hj647AIACDbCB3rEZRcAQKgQPtCjzOMzHzXMfAAAgsxU+Fi+fLnOOussDRo0SBkZGbrqqqu0ffv2Lue0tLSouLhYQ4YMUXJyshYsWKDa2tqgFo3Qy+SyCwAgREyFj/LychUXF2vjxo0qKyuT1+tVUVGRmpqa/OfcdtttWrt2rdasWaPy8nJVV1dr/vz5QS8coZXRednFzWUXAEBwxZo5+dVXX+3y9VNPPaWMjAxVVlbqggsuUH19vVauXKnVq1dr1qxZkqRVq1Zp4sSJ2rhxo84555zgVY6Q6pz5ONrslaetXc7YGIsrAgBEClPh4+vq6+slSWlpaZKkyspKeb1eFRYW+s+ZMGGC8vLyVFFR0WP48Hg88nj+MbXvdrslSV6vV15vcHfX7Bwv2ONGomSHFGsz1GbYVP1lk4YPTrC6pH6Lz1Xg6FXg6JU59CtwoeqVmfF6HT58Pp+WLFmic889V1OmTJEk1dTUKC4uTqmpqV3OzczMVE1NTY/jLF++XMuWLet2fN26dUpMTOxteSdVVlYWknEjTUpcjI54pBdfe1OjXFZX0//xuQocvQocvTKHfgUu2L1qbm4O+Nxeh4/i4mJt27ZNb7/9dm+HkCQtXbpUJSUl/q/dbrdyc3NVVFQklyu4v/G8Xq/Kyso0e/ZsORyOoI4dabxerx7b9oaOeKRRk8/QZVOzrC6p3+JzFTh6FTh6ZQ79ClyoetV55SIQvQoft9xyi15++WVt2LBBw4cP9x/PyspSa2ur6urqusx+1NbWKiur519eTqdTTqez23GHwxGyD1Aox44kKXGGJJsONXnpVwD4XAWOXgWOXplDvwIX7F6ZGcvU3S6GYeiWW27RCy+8oDfeeEP5+fldXp8xY4YcDofWr1/vP7Z9+3ZVVVWpoKDAzFuhH0iJ6/jfgw3cbgsACB5TMx/FxcVavXq1XnrpJQ0aNMi/jiMlJUUJCQlKSUnRDTfcoJKSEqWlpcnlcunWW29VQUEBd7oMQB0zH1JNPbfbAgCCx1T4WLFihSTpoosu6nJ81apVuv766yVJjzzyiOx2uxYsWCCPx6M5c+boiSeeCEqxCK/U4zMfNez1AQAIIlPhwzCMU54THx+v0tJSlZaW9roo9A+dMx9sNAYACCae7YIT6lzzUVPfElDwBAAgEIQPnJDr+MJlT5tP9cfYuAcAEByED5xQXIyUmtCRQHjAHAAgWAgfOKnOZ7yw6BQAECyED5xUZ/io5XZbAECQED5wUpmueEnMfAAAgofwgZPKGHR85oPwAQAIEsIHTio9ueN+20NssQ4ACBLCB04q/fjMB893AQAEC+EDJ9UZPpj5AAAEC+EDJ5XxlfDBLqcAgGAgfOCkhiZ1rPlobWeXUwBAcBA+cFJOR4xSju9yyroPAEAwED5wSp2XXg6yxToAIAgIHziljOO7nB5qZK8PAEDfET5wSunJzHwAAIKH8IFTyji+xTprPgAAwUD4wCllsNEYACCICB84pX9sNMaaDwBA3xE+cEpssQ4ACCbCB04pY1DHmo9DLDgFAAQB4QOn1HmrbYOnTcda2y2uBgAw0BE+cEqDnLGKd3R8VHjAHACgrwgfOCWbzfaVdR8sOgUA9A3hAwHpXPfBolMAQF8RPhCQDP/ttoQPAEDfED4QEC67AACChfCBgPBkWwBAsBA+EBDWfAAAgoXwgYCku1jzAQAIDsIHApKezBbrAIDgMB0+NmzYoCuvvFI5OTmy2Wx68cUXu7xuGIbuuusuZWdnKyEhQYWFhdqxY0ew6oVFOnc5PdLkUVu7z+JqAAADmenw0dTUpOnTp6u0tLTH1x966CE9/vjjevLJJ7Vp0yYlJSVpzpw5amnhLomBbEiSU3abZBjSl02tVpcDABjAYs1+w9y5czV37tweXzMMQ48++qh++tOfat68eZKk3/3ud8rMzNSLL76oa665pm/VwjIxdpuGJjt1sMGjgw0eZbjirS4JADBAmQ4fJ7N7927V1NSosLDQfywlJUUzZ85URUVFj+HD4/HI4/nHOgK32y1J8nq98nq9wSzPP16wx41EPfVqaHKcDjZ4VH20SeMzEq0qrd/hcxU4ehU4emUO/QpcqHplZrygho+amhpJUmZmZpfjmZmZ/te+bvny5Vq2bFm34+vWrVNiYmh+wZWVlYVk3EjUpVfH7JLseuOdzTq2y7Cspv6Kz1Xg6FXg6JU59Ctwwe5Vc3NzwOcGNXz0xtKlS1VSUuL/2u12Kzc3V0VFRXK5XEF9L6/Xq7KyMs2ePVsOhyOoY0eannr1dutH+rhyv7Lyx+uyi0ZZXGH/wecqcPQqcPTKHPoVuFD1qvPKRSCCGj6ysrIkSbW1tcrOzvYfr62t1Wmnndbj9zidTjmdzm7HHQ5HyD5AoRw70ny1V1kpCZKkI01e+tcDPleBo1eBo1fm0K/ABbtXZsYK6j4f+fn5ysrK0vr16/3H3G63Nm3apIKCgmC+FSzA810AAMFgeuajsbFRO3fu9H+9e/dubdmyRWlpacrLy9OSJUt03333aezYscrPz9edd96pnJwcXXXVVcGsGxbwP9+FjcYAAH1gOnxs3rxZF198sf/rzvUaixYt0lNPPaXbb79dTU1Nuummm1RXV6fzzjtPr776quLjuTVzoEs//nwXtlgHAPSF6fBx0UUXyTBOfKeDzWbTvffeq3vvvbdPhaH/+erMh2EYstlsFlcEABiIeLYLAta55qO1zSd3S5vF1QAABirCBwIW74jRoPiOyTIuvQAAeovwAVM6Zz8ONxI+AAC9Q/iAKUOTO8IHMx8AgN4ifMCUzpkPwgcAoLcIHzAlvXPmg8suAIBeInzAFGY+AAB9RfiAKZ0zHyw4BQD0FuEDpjDzAQDoK8IHTCF8AAD6ivABUzrDx5GmVrX7TrzNPgAAJ0L4gClpSXGy2aR2n6Gjza1WlwMAGIAIHzDFEWPX4MQ4SSw6BQD0DuEDpqWzyykAoA8IHzCNRacAgL4gfMA0wgcAoC8IHzCN8AEA6AvCB0wbmsyCUwBA7xE+YJp/5oPwAQDoBcIHTEtPjpfEZRcAQO8QPmAaaz4AAH1B+IBpneHjaLNX3nafxdUAAAYawgdMS01wKMZukyQdaWSLdQCAOYQPmGa32/x3vHDpBQBgFuEDvfKPO15aLK4EADDQED7QKzzfBQDQW4QP9Ap3vAAAeovwgV4Zenzm4zALTgEAJhE+0CvMfAAAeovwgV4hfAAAeovwgV7xLzjl+S4AAJNCFj5KS0s1cuRIxcfHa+bMmXr33XdD9VawwFBmPgAAvRSS8PHcc8+ppKREd999t95//31Nnz5dc+bM0cGDB0PxdrBA52WXRk+bjrW2W1wNAGAgCUn4ePjhh3XjjTdq8eLFmjRpkp588kklJibqN7/5TSjeDhYY5IyVM7bj43OYSy8AABNigz1ga2urKisrtXTpUv8xu92uwsJCVVRUdDvf4/HI4/nHLy+32y1J8nq98nq9Qa2tc7xgjxuJAulVenKc9tW16IFXPvFvtx6NfD6fqvbYtfnlj2W3s4zqZOhV4OiVOfQrcD6fT19W2zQ7RL9jAxH08HH48GG1t7crMzOzy/HMzEx9+umn3c5fvny5li1b1u34unXrlJiYGOzyJEllZWUhGTcSnaxXCT67JLv+d2tN+Arqt+xSzT6rixgg6FXg6JU59CtQGfH2oP8ubG5uDvjcoIcPs5YuXaqSkhL/1263W7m5uSoqKpLL5Qrqe3m9XpWVlWn27NlyOBxBHTvSBNKrcWc26uWtNfL5jDBX17+0+3zavXu38vPzFcN/cZ0UvQocvTKHfgWu3efTwb2fB/13YeeVi0AEPXwMHTpUMTExqq2t7XK8trZWWVlZ3c53Op1yOp3djjscjpAFhFCOHWlO1quJwwZr4rDBYa6o//F6vfrLX3bpsjnj+VydAr0KHL0yh34FrrNXwf5daGasoMfDuLg4zZgxQ+vXr/cf8/l8Wr9+vQoKCoL9dgAAYIAJyWWXkpISLVq0SGeeeabOPvtsPfroo2pqatLixYtD8XYAAGAACUn4uPrqq3Xo0CHdddddqqmp0WmnnaZXX3212yJUAAAQfUK24PSWW27RLbfcEqrhAQDAAMWSYAAAEFaEDwAAEFaEDwAAEFaEDwAAEFaEDwAAEFaEDwAAEFaEDwAAEFaEDwAAEFaEDwAAEFYh2+G0twyj4/HsZh7NGyiv16vm5ma53W6eengK9Cpw9Cpw9Cpw9Moc+hW4UPWq8/d25+/xk+l34aOhoUGSlJuba3ElAADArIaGBqWkpJz0HJsRSEQJI5/Pp+rqag0aNEg2my2oY7vdbuXm5mrv3r1yuVxBHTvS0KvA0avA0avA0Stz6FfgQtUrwzDU0NCgnJwc2e0nX9XR72Y+7Ha7hg8fHtL3cLlcfDgDRK8CR68CR68CR6/MoV+BC0WvTjXj0YkFpwAAIKwIHwAAIKyiKnw4nU7dfffdcjqdVpfS79GrwNGrwNGrwNErc+hX4PpDr/rdglMAABDZomrmAwAAWI/wAQAAworwAQAAworwAQAAwipqwkdpaalGjhyp+Ph4zZw5U++++67VJVnunnvukc1m6/JnwoQJ/tdbWlpUXFysIUOGKDk5WQsWLFBtba2FFYfPhg0bdOWVVyonJ0c2m00vvvhil9cNw9Bdd92l7OxsJSQkqLCwUDt27OhyzpdffqmFCxfK5XIpNTVVN9xwgxobG8P4U4TPqfp1/fXXd/usXXrppV3OiYZ+LV++XGeddZYGDRqkjIwMXXXVVdq+fXuXcwL5e1dVVaXLL79ciYmJysjI0I9//GO1tbWF80cJuUB6ddFFF3X7XH3ve9/rck409EqSVqxYoWnTpvk3DisoKNArr7zif72/fa6iInw899xzKikp0d133633339f06dP15w5c3Tw4EGrS7Pc5MmTdeDAAf+ft99+2//abbfdprVr12rNmjUqLy9XdXW15s+fb2G14dPU1KTp06ertLS0x9cfeughPf7443ryySe1adMmJSUlac6cOWppafGfs3DhQn300UcqKyvTyy+/rA0bNuimm24K148QVqfqlyRdeumlXT5rzzzzTJfXo6Ff5eXlKi4u1saNG1VWViav16uioiI1NTX5zznV37v29nZdfvnlam1t1TvvvKPf/va3euqpp3TXXXdZ8SOFTCC9kqQbb7yxy+fqoYce8r8WLb2SpOHDh+uBBx5QZWWlNm/erFmzZmnevHn66KOPJPXDz5URBc4++2yjuLjY/3V7e7uRk5NjLF++3MKqrHf33Xcb06dP7/G1uro6w+FwGGvWrPEf++STTwxJRkVFRZgq7B8kGS+88IL/a5/PZ2RlZRn//u//7j9WV1dnOJ1O45lnnjEMwzA+/vhjQ5Lx3nvv+c955ZVXDJvNZuzfvz9stVvh6/0yDMNYtGiRMW/evBN+T7T26+DBg4Yko7y83DCMwP7e/eUvfzHsdrtRU1PjP2fFihWGy+UyPB5PeH+AMPp6rwzDMC688ELjBz/4wQm/J1p71Wnw4MHGf//3f/fLz1XEz3y0traqsrJShYWF/mN2u12FhYWqqKiwsLL+YceOHcrJydGoUaO0cOFCVVVVSZIqKyvl9Xq79G3ChAnKy8uL+r7t3r1bNTU1XXqTkpKimTNn+ntTUVGh1NRUnXnmmf5zCgsLZbfbtWnTprDX3B+89dZbysjI0Pjx4/X9739fR44c8b8Wrf2qr6+XJKWlpUkK7O9dRUWFpk6dqszMTP85c+bMkdvt9v9XbiT6eq86Pf300xo6dKimTJmipUuXqrm52f9atPaqvb1dzz77rJqamlRQUNAvP1f97sFywXb48GG1t7d3aagkZWZm6tNPP7Woqv5h5syZeuqppzR+/HgdOHBAy5Yt0/nnn69t27appqZGcXFxSk1N7fI9mZmZqqmpsabgfqLz5+/pM9X5Wk1NjTIyMrq8Hhsbq7S0tKjs36WXXqr58+crPz9fu3bt0r/9279p7ty5qqioUExMTFT2y+fzacmSJTr33HM1ZcoUSQro711NTU2Pn73O1yJRT72SpOuuu04jRoxQTk6OPvzwQ/3kJz/R9u3b9ac//UlS9PVq69atKigoUEtLi5KTk/XCCy9o0qRJ2rJlS7/7XEV8+MCJzZ071//P06ZN08yZMzVixAg9//zzSkhIsLAyRJprrrnG/89Tp07VtGnTNHr0aL311lu65JJLLKzMOsXFxdq2bVuXdVbo2Yl69dU1QVOnTlV2drYuueQS7dq1S6NHjw53mZYbP368tmzZovr6ev3hD3/QokWLVF5ebnVZPYr4yy5Dhw5VTExMt1W9tbW1ysrKsqiq/ik1NVXjxo3Tzp07lZWVpdbWVtXV1XU5h77J//Of7DOVlZXVbUFzW1ubvvzyy6jvnySNGjVKQ4cO1c6dOyVFX79uueUWvfzyy3rzzTc1fPhw//FA/t5lZWX1+NnrfC3SnKhXPZk5c6YkdflcRVOv4uLiNGbMGM2YMUPLly/X9OnT9dhjj/XLz1XEh4+4uDjNmDFD69ev9x/z+Xxav369CgoKLKys/2lsbNSuXbuUnZ2tGTNmyOFwdOnb9u3bVVVVFfV9y8/PV1ZWVpfeuN1ubdq0yd+bgoIC1dXVqbKy0n/OG2+8IZ/P5/8/yGi2b98+HTlyRNnZ2ZKip1+GYeiWW27RCy+8oDfeeEP5+fldXg/k711BQYG2bt3aJayVlZXJ5XJp0qRJ4flBwuBUverJli1bJKnL5yoaenUiPp9PHo+nf36ugr6EtR969tlnDafTaTz11FPGxx9/bNx0001Gampql1W90eiHP/yh8dZbbxm7d+82/va3vxmFhYXG0KFDjYMHDxqGYRjf+973jLy8POONN94wNm/ebBQUFBgFBQUWVx0eDQ0NxgcffGB88MEHhiTj4YcfNj744ANjz549hmEYxgMPPGCkpqYaL730kvHhhx8a8+bNM/Lz841jx475x7j00kuN008/3di0aZPx9ttvG2PHjjWuvfZaq36kkDpZvxoaGowf/ehHRkVFhbF7927j9ddfN8444wxj7NixRktLi3+MaOjX97//fSMlJcV46623jAMHDvj/NDc3+8851d+7trY2Y8qUKUZRUZGxZcsW49VXXzXS09ONpUuXWvEjhcyperVz507j3nvvNTZv3mzs3r3beOmll4xRo0YZF1xwgX+MaOmVYRjGHXfcYZSXlxu7d+82PvzwQ+OOO+4wbDabsW7dOsMw+t/nKirCh2EYxi9+8QsjLy/PiIuLM84++2xj48aNVpdkuauvvtrIzs424uLijGHDhhlXX321sXPnTv/rx44dM26++WZj8ODBRmJiovHP//zPxoEDByysOHzefPNNQ1K3P4sWLTIMo+N22zvvvNPIzMw0nE6ncckllxjbt2/vMsaRI0eMa6+91khOTjZcLpexePFio6GhwYKfJvRO1q/m5majqKjISE9PNxwOhzFixAjjxhtv7Bb+o6FfPfVIkrFq1Sr/OYH8vfviiy+MuXPnGgkJCcbQoUONH/7wh4bX6w3zTxNap+pVVVWVccEFFxhpaWmG0+k0xowZY/z4xz826uvru4wTDb0yDMP4zne+Y4wYMcKIi4sz0tPTjUsuucQfPAyj/32ubIZhGMGfTwEAAOhZxK/5AAAA/QvhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhBXhAwAAhNX/A8d5b8xbEQX/AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "#plt.plot(df['time'][1:], df['antenna/tx_gain/out'][1:], label='Gain')\n",
    "plt.grid()\n",
    "plt.plot(df['time'][1:], df['general/pitch_l'][1:].apply(lambda x: x*(180/np.pi)), label='Pitch')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from spatz.sensors.antenna.tx_gain import GainPattern\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed 65160 lines in 0.5s.\n",
      "Used 65160 lines due to step size\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x23fd0b78e90>]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "pattern = GainPattern(\"data/gain_pattern/farfield_2_45_GHz.txt\",1)\n",
    "\n",
    "fig, (ax1,ax2) = plt.subplots(1,2,subplot_kw={'projection': 'polar'})\n",
    "ax1.set_theta_zero_location(\"N\")\n",
    "ax2.set_theta_zero_location(\"N\")\n",
    "\n",
    "\n",
    "angles_phi, gain_phi = pattern.get_phi_cut(0) # Cut through X-Z plane (In sim actually Y-)\n",
    "ax1.plot(np.deg2rad(angles_phi), gain_phi)\n",
    "\n",
    "\n",
    "angles_theta, gain_theta = pattern.get_theta_cut(5)\n",
    "ax2.plot(np.deg2rad(angles_theta), gain_theta)\n",
    "\n",
    "\n",
    "\n"
   ]
  }
 ],
 "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
}