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": 13,
   "metadata": {},
   "outputs": [],
   "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",
    "\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": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████▉| 299.9999999999997/300.0 [00:04<00:00, 70.82it/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()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "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>time</th>\n",
       "      <th>Generic Antenna TX/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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.0</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "      <td>&lt;NA&gt;</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.1</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.2</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.3</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.4</td>\n",
       "      <td>0</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",
       "    </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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2996</th>\n",
       "      <td>299.6</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2997</th>\n",
       "      <td>299.7</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2998</th>\n",
       "      <td>299.8</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2999</th>\n",
       "      <td>299.9</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11999</th>\n",
       "      <td>300.0</td>\n",
       "      <td>0</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",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3001 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        time Generic Antenna TX/out general/altitude general/latitude  \\\n",
       "0        0.0                   <NA>             <NA>             <NA>   \n",
       "1        0.1                      0       319.189854         1.184825   \n",
       "2        0.2                      0       319.754649         1.184825   \n",
       "3        0.3                      0       320.689767         1.184825   \n",
       "4        0.4                      0        321.98961         1.184825   \n",
       "...      ...                    ...              ...              ...   \n",
       "2996   299.6                      0       954.385196         1.186267   \n",
       "2997   299.7                      0       950.544731         1.186267   \n",
       "2998   299.8                      0       946.704266         1.186267   \n",
       "2999   299.9                      0         942.8638         1.186267   \n",
       "11999  300.0                      0       939.023335         1.186267   \n",
       "\n",
       "      general/longitude general/x    general/y   general/z  \n",
       "0                  <NA>      <NA>         <NA>        <NA>  \n",
       "1              0.367914       0.0     0.033017    0.189854  \n",
       "2              0.367914       0.0     0.131239    0.754649  \n",
       "3              0.367914       0.0     0.293862    1.689767  \n",
       "4              0.367914       0.0     0.519914     2.98961  \n",
       "...                 ...       ...          ...         ...  \n",
       "2996           0.367917  7.639079  9218.178485  628.737611  \n",
       "2997           0.367917  7.639903  9218.177327  624.897143  \n",
       "2998           0.367917  7.640726  9218.176168  621.056675  \n",
       "2999           0.367917   7.64155  9218.175009  617.216207  \n",
       "11999          0.367917  7.642373   9218.17385   613.37574  \n",
       "\n",
       "[3001 rows x 8 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = logger.get_dataframe()\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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njgs5RZjwfSJKysxyl0VE5DT4K0V3ZVfFQncPNQuWuRL7EOClxlejusBTpURCWi7e+ukEt34gIqolDDlUbTkFRhy7mAcAeKBZkLzF2JFmWm98OqwDJAlYeSADX+89L3dJREROgSGHqi3u9BUIAbSoo0GIxk3ucuzK35qH4I1Hy7d+eHfTScs6Q0REVHMYcqjaKsfjPMhenHsytmcEBncOs2z9cCqLM66IiGoSQw5Vi8ksLBtPcjzOvanc+uGPGVcHkVNglLssIiKHxZBD1XLsYh6uFZXC280FHev7yl2O3VK5KLB4RCfU9/dARu51TPg+EcYyk9xlERE5JIYcqpbKW1W9mgTCRcmvzf3w91Thq1Gd4a12wcHz1/DmOs64IiKqCfy1omr57XR5yHmgKcfjWEOTkPIZVwoJWJt4EZ/HnZO7JCIih8OQQ3eUX1yKoxf1AIAejQNlrsZxPNgsGLMeawkAeG9LCjYfvyxzRUREjoUhh+7o4PlcmMwC4QEeqOfnIXc5DuX57g2q7HGVeOGazBURETkOhhy6o71ncgAA3RtxryprkyQJsx9riT7Ng2EsM2Pct4dwIadQ7rKIiBwCQw7d0b6zlSGHt6pqgotSgU+GdkDruhrkFpZg9NKDyCviZp5ERPeLIYf+Uk6BEb9fNgAAotiTU2M81S74elQXhPq44dyVQoz/jlPLiYjuF0MO/aX4c+W9OM213gj0UstcjWML1rjh69Fd4K12wYG0XPzjh2OcWk5EdB8Ycugv8VZV7Wqu1WDhiI5wUUjYkJSJD2NPyV0SEZHdYsihv7TvzFUAHHRcm3o1CcK7T7YGAHyy4wzWHMqQuSIiIvvEkEO3dSnvOs7nFEGpkBDZ0F/ucpzK4C71MemhRgCAf/54HHsrwiYREVUfQw7d1oG08ltVrev6wNvNVeZqnM+rDzfD4+1CUWYWmPBdInctJyK6Sww5dFsHz5cvTNe1gZ/MlTgnhULC/GfaomsDf+QbyzD6m4PIzi+WuywiIrvBkEO3dTAtFwDQuQFvVclF7aLE5891QkSgJy7lXccLyw6hqKRM7rKIiOwCQw7d0rXCEpzOLgAAdA5nT46c/DxV+Ob5LvD3VOHYRT0mrziCMpNZ7rKIiGweQw7dUuUeSo2CPBHA9XFk1yDQE1+M7Ay1iwI7UrLxxroTXEOHiOgOGHLolg6eL79V1TWCt6psRadwP3w2rCMUErD6UAY+/PW03CUREdk0hhy6pcqQ0zmcIceWPNwyBO8MbAMA+GT7aSxPuCBzRUREtoshh25SXGrC8Ut6AOzJsUXDIutjSp8mAIBZ609gW7JO5oqIiGwTQw7dJCkjD6UmgRCNGvX83OUuh25hanQTDO0aBrMAXll5BIcqet6IiOgPDDl0k8ofzM4N/CFJkszV0K1IkoS3n2iN6BbBMJaZMXbZIZzJ5mKBREQ3YsihmxywLALIW1W2zEWpwKdDO6JDfV/or5di1NcHodNzsUAiokoMOVSF2SxwpGL6eCeuj2Pz3FVKfDWqCxpWLBb4/DcHoL9eKndZREQ24a5DTlxcHAYMGIDQ0FBIkoT169dXOS6EwOzZs1GnTh24u7sjOjoap09Xneqam5uL4cOHQ6PRwNfXF2PHjkVBQUGVNseOHUOvXr3g5uaGsLAwzJs376Za1q5di+bNm8PNzQ1t2rTB5s2b7/Z06E/OXS1AvrEM7q5KNNd6y10OVYO/pwrLxnRFkLcaKbp8vPjdIRjLTHKXRUQku7sOOYWFhWjXrh0WLFhwy+Pz5s3DJ598gsWLFyMhIQGenp6IiYlBcfEf3ejDhw9HcnIyYmNjsXHjRsTFxWH8+PGW4waDAX379kV4eDgSExMxf/58zJkzB0uWLLG02bdvH4YOHYqxY8fiyJEjGDhwIAYOHIgTJ07c7SnRDY6k5wEA2tTzgYuSHX32IszfA0tHd4GX2gX7z+Vi+pqjMJu5WCAROTlxHwCIdevWWf5sNpuFVqsV8+fPtzyXl5cn1Gq1WLlypRBCiJMnTwoA4uDBg5Y2W7ZsEZIkiUuXLgkhhFi4cKHw8/MTRqPR0mbGjBmiWbNmlj8/++yzon///lXqiYyMFC+++GK169fr9QKA0Ov11X6No3tj3TERPmOjeHfTSblLoXuw9/QV0fifm0T4jI3irQ0nhNlslrskIiKrq+7vt1X/qZ6WlgadTofo6GjLcz4+PoiMjER8fDwAID4+Hr6+vujcubOlTXR0NBQKBRISEixtevfuDZVKZWkTExOD1NRUXLt2zdLmxs+pbFP5ObdiNBphMBiqPKiqoxnl6+O0q+crbyF0T7o3DsT7z7YHACzddx6f7jgjb0FERDKyasjR6coXJQsJCanyfEhIiOWYTqdDcHBwleMuLi7w9/ev0uZW73HjZ9yuTeXxW5k7dy58fHwsj7CwsLs9RYdWXGrC75fLg1+7MB+Zq6F79Xi7UMwZ0BIA8EHsKXwXf17egoiIZOJUgy5mzpwJvV5veWRkZMhdkk1JzjSgzCwQ6KVGXV8uAmjPnu8RYVkVefZPyfjpaKbMFRER1T6rhhytVgsAyMrKqvJ8VlaW5ZhWq0V2dnaV42VlZcjNza3S5lbvceNn3K5N5fFbUavV0Gg0VR70h6MZeQCA9mE+XATQAUyNboKRUeEQAnh1TRJ2n7oid0lERLXKqiEnIiICWq0W27dvtzxnMBiQkJCAqKgoAEBUVBTy8vKQmJhoabNjxw6YzWZERkZa2sTFxaG09I/1PmJjY9GsWTP4+flZ2tz4OZVtKj+H7l5SRcjheBzHIEkS5gxohQHtQlFqEpjwXSIOp1+Tuywiolpz1yGnoKAASUlJSEpKAlA+2DgpKQnp6emQJAlTp07FO++8g59++gnHjx/HyJEjERoaioEDBwIAWrRogX79+mHcuHE4cOAA9u7di8mTJ2PIkCEIDQ0FAAwbNgwqlQpjx45FcnIyVq9ejY8//hjTp0+31DFlyhRs3boV77//PlJSUjBnzhwcOnQIkydPvv+r4qSOXswDALSv7ytrHWQ9CoWE959ph95Ng3C91ITR3xzEqSxu/0BETuJup23t3LlTALjpMWrUKCFE+TTyWbNmiZCQEKFWq0WfPn1EampqlffIyckRQ4cOFV5eXkKj0YjRo0eL/Pz8Km2OHj0qevbsKdRqtahbt6547733bqplzZo1omnTpkKlUolWrVqJTZs23dW5cAr5H3ILjCJ8xkYRPmOjyCsskbscsrJCY6kYuGCPCJ+xUXR9N1ak5xTKXRIR0T2r7u+3JIRw2hXDDAYDfHx8oNfrnX58zs7UbIz+5iAaBnpix98flLscqgF5RSV49vN4nMoqQESgJ9ZOiEKgl1rusoiI7lp1f7+danYV3d6xyvVxwnzlLYRqjK+HCt+OiURdX3ekXS3EqK8PIL+Y+1wRkeNiyCEAQHJmechpXZfr4zgyrY8bvhvbFQGeKiRnGjDu20MoLuU+V0TkmBhyCED5GjkA0LKOc9+2cwYNg7ywbExXyz5XLy0/jFKTWe6yiIisjiGHoC8qxaW86wCAlqEMOc6gdV0ffDWqM9QuCuxIyca01UkwcUNPInIwDDmE5Mvlt6rq+bnDx91V5mqotkQ2DMDnz3WCq1LCxmOXMfPHY9y5nIgcCkMO4WTFrapW7MVxOg82C8YnQzpAIQFrDl3E25tOwoknXBKRg2HIoRtCDgcdO6NH2tTBvKfbAQC+2XseH/56WuaKiIisgyGHOOiY8HSnevjX460AAJ9sP40lcWdlroiI6P4x5Di54lITzlwpAAC0qsuQ48xGdW+A12KaAQD+szkFyxMuyFwREdH9Ychxcqey8mEyC/h5uEKrcZO7HJLZpIcaY+KDjQAAb64/gfVHLslcERHRvWPIcXLJN4zHkSRJ5mrIFvwjphlGRoVDCODVtUfxS7JO7pKIiO4JQ46T48wq+jNJkjBnQCsM6lgXJrPA5BVHsOf0VbnLIiK6aww5Tq5yOwcuAkg3UigkzHuqLR5prUWJyYxx3x7CofO5cpdFRHRXGHKcmMkskKLLB8CeHLqZi1KBj4a0xwNNg3C91ITR3xzEiUt6ucsiIqo2hhwnlpFbhKISE1QuCjQI8JS7HLJBahclFo/ohK4N/JFvLMOIrxLw+2WD3GUREVULQ44TS80q78VpEuwFFyW/CnRr7iolvnq+M9qH+SKvqBQjvkzA6YrvDhGRLeMvmxOr/KFqFuItcyVk67zdXLFsTFe0rqtBTmEJhn2ZgHMV6ysREdkqhhwnlppV/iPVVMuQQ3fm4+6K78ZEornWG1fyjRj2RQIu5BTKXRYR0W0x5DixUxWDjpuGeMlcCdkLP08Vlr8QiSbBXtAZijHsiwRcvFYkd1lERLfEkOOkSsrMOFtxu6Epb1fRXQjwUmP5uEg0DPTEpbzrGPrFflzWX5e7LCKimzDkOKnzOYUoMwt4qpSo6+sudzlkZ4K93bBiXDeEB3ggI/c6hn2RgGxDsdxlERFVwZDjpE5VDDpuqvXmdg50T7Q+5UGnrq870q4WYtiXCbhaYJS7LCIiC4YcJ2UZjxPMW1V07+r6umPluG6o4+OGM9kFGPFlAq4VlshdFhERAIYcp5V6Q08O0f2oH+CBFeO6IdhbjRRdPkZ8lQB9UancZRERMeQ4q1MV08e5Rg5ZQ0SgJ1aMi0SglwrJmQaM/DoBhmIGHSKSF0OOEyouNeF8xfomTbWcPk7W0TjYG9+/EAk/D1ccvajH818fQD6DDhHJiCHHCZ3JLoAQgJ+HK4K81HKXQw6kuVaD71+IhI+7Kw6n52EUgw4RyYghxwlVzqxqEsKZVWR9rUJ9sJxBh4hsAEOOEzqdXT4ep0kwb1VRzWhdt2rQGcmgQ0QyYMhxQmcrQk5jhhyqQTcGnSMVQYeDkYmoNjHkOKFzV8sHHTcKYsihmvXnoDOKQYeIahFDjpMpNZktO0c3Yk8O1YKbenS+YtAhotrBkONkMnKLUGoScHNVoI7GTe5yyElUBh1fD1ckZTDoEFHtYMhxMmevlPfiNAz0gkLBmVVUe1rX9cH3Yxl0iKj2MOQ4mXNXygcd81YVyYFBh4hqE0OOkzlbGXKCPGWuhJzVn29dPcegQ0Q1hCHHyVhuV3FmFcmocsFAXw9XHK0IOtzUk4isjSHHybAnh2zFn4POsC/341phidxlEZEDYchxIrmFJcir+Ndyw0D25JD8WoX6YOW4bgjwLN+9fOgX+3G1wCh3WUTkIBhynEhlL05dX3e4q5QyV0NUrkUdDVaN74YgbzVSdPkYsmQ/sg3FcpdFRA7A6iHHZDJh1qxZiIiIgLu7Oxo1aoS3334bQghLGyEEZs+ejTp16sDd3R3R0dE4ffp0lffJzc3F8OHDodFo4Ovri7Fjx6KgoKBKm2PHjqFXr15wc3NDWFgY5s2bZ+3TcSiV2zlwZhXZmiYh3lg9vhu0GjecyS7A4CX7cVl/Xe6yiMjOWT3k/Pe//8WiRYvw2Wef4ffff8d///tfzJs3D59++qmlzbx58/DJJ59g8eLFSEhIgKenJ2JiYlBc/Me/3oYPH47k5GTExsZi48aNiIuLw/jx4y3HDQYD+vbti/DwcCQmJmL+/PmYM2cOlixZYu1TchiVPTkNAzkeh2xPwyAvrHkxCnV93ZF2tRDPfh6PjNwiucsiInsmrKx///5izJgxVZ4bNGiQGD58uBBCCLPZLLRarZg/f77leF5enlCr1WLlypVCCCFOnjwpAIiDBw9a2mzZskVIkiQuXbokhBBi4cKFws/PTxiNRkubGTNmiGbNmlW7Vr1eLwAIvV5/9ydqh8Z8c0CEz9govo0/L3cpRLd18VqR6D1vhwifsVF0n7tdpF0pkLskIrIx1f39tnpPTvfu3bF9+3acOnUKAHD06FHs2bMHjzzyCAAgLS0NOp0O0dHRltf4+PggMjIS8fHxAID4+Hj4+vqic+fOljbR0dFQKBRISEiwtOnduzdUKpWlTUxMDFJTU3Ht2rVb1mY0GmEwGKo8nAlnVpE9qOvrjtXjo9AwyBOX8q5j8JJ4nMkuuPMLiYj+xOoh5/XXX8eQIUPQvHlzuLq6okOHDpg6dSqGDx8OANDpdACAkJCQKq8LCQmxHNPpdAgODq5y3MXFBf7+/lXa3Oo9bvyMP5s7dy58fHwsj7CwsPs8W/tRUmZGekXXP3cfJ1un9XHD6vFRaBrihSyDEUOW7EeqLl/usojIzlg95KxZswbLly/HihUrcPjwYSxbtgz/93//h2XLlln7o+7azJkzodfrLY+MjAy5S6o1GdeKYBaAh0qJYG+13OUQ3VGQtxorx3VDizoaXC0wYugX+3Ey07l6X4no/lg95Lz22muW3pw2bdrgueeew7Rp0zB37lwAgFarBQBkZWVVeV1WVpblmFarRXZ2dpXjZWVlyM3NrdLmVu9x42f8mVqthkajqfJwFhdyylc6Dg/whCRxY06yDwFeaqwcF4m29XyQW1iCoV/sx7GLeXKXRUR2wuohp6ioCApF1bdVKpUwm80AgIiICGi1Wmzfvt1y3GAwICEhAVFRUQCAqKgo5OXlITEx0dJmx44dMJvNiIyMtLSJi4tDaekfS8HHxsaiWbNm8PPzs/Zp2b20q+W3qhoEeMhcCdHd8fVQ4fsXItGxvi/010sx/IsEJF7IlbssIrIDVg85AwYMwLvvvotNmzbh/PnzWLduHT744AM8+eSTAABJkjB16lS88847+Omnn3D8+HGMHDkSoaGhGDhwIACgRYsW6NevH8aNG4cDBw5g7969mDx5MoYMGYLQ0FAAwLBhw6BSqTB27FgkJydj9erV+PjjjzF9+nRrn5JDqOzJacDp42SHNG6u+HZsJLpG+CPfWIbnvjqAvWeuyl0WEdk6a0/rMhgMYsqUKaJ+/frCzc1NNGzYULzxxhtVpnqbzWYxa9YsERISItRqtejTp49ITU2t8j45OTli6NChwsvLS2g0GjF69GiRn59fpc3Ro0dFz549hVqtFnXr1hXvvffeXdXqTFPIR3y5X4TP2ChWHbggdylE96zIWGb5Ljf552bxS7JO7pKISAbV/f2WhLhhKWInYzAY4OPjA71e7/Djc3rP24n03CKsGt8N3RoGyF0O0T0zlpnwysoj2JacBaVCwgfPtsMT7evKXRYR1aLq/n5z7yonUFJmxsVr5WNyIni7iuyc2kWJBcM6YlCHujCZBaauTsKqA+lyl0VENoghxwlcrJg+7uaq4PRxcgguSgX+75l2GB5ZH0IAr/94HF/+dk7usojIxjDkOIELOZUzqzh9nByHQiHhnYGt8WLvhgCAdzb9jo9/PQ0nvgNPRH/CkOMEzlfOrArgrSpyLJIk4fVHmuPVh5sCAD789RTmbklh0CEiAAw5TuH81YqFAAO5Rg45HkmS8HKfJpj1WEsAwJK4c3hj/QmYzAw6RM6OIccJnK+4XRXBnhxyYGN7RuC/T7WBJAErEtIxfU0SSk1mucsiIhkx5DiBG7d0IHJkg7vUxydDOsBFIWFDUiZeWn4YxjKT3GURkUwYchxcqcmMjGvXAQANeLuKnMCAdqH4/LlOULkoEHsyC2OXHkKhsUzusohIBgw5Du7SteswmQXcXBUI8XaTuxyiWtGnRQiWPt8FHiol9py5imFfJuBaYYncZRFRLWPIcXCVM6vC/T2hUHD6ODmP7o0DsWJcN/h6uOJoRh6e/TweOn2x3GURUS1iyHFwlWvk1Ofu4+SE2of5Yu2LUdBq3HA6uwBPLdqHc1cK5C6LiGoJQ46Dy8itCDn+DDnknJqEeOOHiVGICPTEpbzreGZxPE5c0stdFhHVAoYcB5dRsWdVmJ+7zJUQyaeenwfWTohCq1ANcgpLMHTJfiScy5G7LCKqYQw5Du5ixcyqMPbkkJML9FJj5fhu6Brhj3xjGUZ+fQC/nsySuywiqkEMOQ6u8nZVPT+GHCKNmyu+HdMV0S2CYSwz48XvE/Hj4Ytyl0VENYQhx4Hpr5fCUFy+Pkg93q4iAgC4uSqxaEQnDOpQFyazwPQ1R/H1njS5yyKiGsCQ48AuVozHCfBUwVPtInM1RLbDVanA/z3TDmN6RAAA/r3xJD74JZUbexI5GIYcB5aRWz4eh704RDdTKCTMeqyFZQfzT3acwewNydzYk8iBMOQ4sMqenHocdEx0S5U7mL89sDUkCfhu/wW8vPIwiku53xWRI2DIcWCWmVUcdEz0l57rFo5Ph3aAq1LC5uM6PP/NARiKS+Uui4juE0OOA/tjZhVvVxHdyWNtQ7FsdFd4qV2w/1wuBn++H9kGbgNBZM8YchyYZSFA3q4iqpbujQOxanw3BHqp8ftlAwZxGwgiu8aQ46CEEDfcrmJPDlF1ta7rgx8ndkeDAA9cvHYdTy+OR1JGntxlEdE9YMhxULmFJSgqKR88GerLkEN0N+oHeOCHid3Rpq4Pciu2gdiVmi13WUR0lxhyHFRGRS9OiEYNN1elzNUQ2Z/KbSB6NQnE9VITXlh2iKsjE9kZhhwHddGyMSfH4xDdKy+1C74a1QVPtA9FWcXqyEvizspdFhFVE0OOg+JCgETWoXJR4MNn2+OFnuWrI/9ncwre2XgSZi4aSGTzGHIcFGdWEVmPQiHhzcda4p+PNgcAfLknDdPXJKGkzCxzZUT0VxhyHBQXAiSyvvG9G+GDZ9vBRSFhfVImxiw9yEUDiWwYQ46DusiFAIlqxKCO9fDlqM7wUCmx58xVPLs4Hjo9Fw0kskUMOQ7IbL5hjRzeriKyugebBWPNi1EI8lYjRZePJxfuRYrOIHdZRPQnDDkO6EqBESUmM5QKCXV83OQuh8ghVS4a2CjIE5f1xXhmUTz2nbkqd1lEdAOGHAdUuWeVVuMGFyX/ExPVlDB/D/xvYnd0beCPfGMZRn1zAOuPXJK7LCKqwF9AB/THzCqOxyGqab4eKnw7tiv6t62DUpPA1NVJWLDzDITgFHMiuTHkOKCLuZxZRVSb3FyV+HRIB4zrVb6WzvxtqXhz/QmUmTjFnEhODDkOqLInpx5DDlGtUSgkvNG/Jd4a0BKSBCxPSMeE7xNRVFImd2lEToshxwH9MbOKt6uIatvoHhFYNLwj1C4K/Pp7NoYu2Y+rBUa5yyJySgw5DoirHRPJq1/rOlgxLhK+Hq44elGPQQv34dyVArnLInI6DDkOpsxkRmZe+cJkXAiQSD6dwv3xv4ndEebvjvTcIjy1aB8SL1yTuywip1IjIefSpUsYMWIEAgIC4O7ujjZt2uDQoUOW40IIzJ49G3Xq1IG7uzuio6Nx+vTpKu+Rm5uL4cOHQ6PRwNfXF2PHjkVBQdV/CR07dgy9evWCm5sbwsLCMG/evJo4HbuiMxTDZBZQKRUI8eYaOURyahTkhR8n9kDbej64VlSKYV/sx5bjl+Uui8hpWD3kXLt2DT169ICrqyu2bNmCkydP4v3334efn5+lzbx58/DJJ59g8eLFSEhIgKenJ2JiYlBc/MfS6MOHD0dycjJiY2OxceNGxMXFYfz48ZbjBoMBffv2RXh4OBITEzF//nzMmTMHS5YssfYp2ZXK3cfr+rlDoZBkroaIgrzVWDW+G/7WPBjGMjNeWnEYn+8+yynmRLVBWNmMGTNEz549b3vcbDYLrVYr5s+fb3kuLy9PqNVqsXLlSiGEECdPnhQAxMGDBy1ttmzZIiRJEpcuXRJCCLFw4ULh5+cnjEZjlc9u1qxZtWvV6/UCgNDr9dV+ja1bfTBdhM/YKEZ8uV/uUojoBqVlJjFr/XERPmOjCJ+xUbz+v2OipMwkd1lEdqm6v99W78n56aef0LlzZzzzzDMIDg5Ghw4d8MUXX1iOp6WlQafTITo62vKcj48PIiMjER8fDwCIj4+Hr68vOnfubGkTHR0NhUKBhIQES5vevXtDpVJZ2sTExCA1NRXXrjnvfe/KmVWcPk5kW1yUCvzr8VaY/Vj5FPOVB9K5izlRDbN6yDl37hwWLVqEJk2aYNu2bZg4cSJeeeUVLFu2DACg0+kAACEhIVVeFxISYjmm0+kQHBxc5biLiwv8/f2rtLnVe9z4GX9mNBphMBiqPBxN5e7jnD5OZHskScKYnhH4fEQnuLsq8dvpq3hmUTwu5V2XuzQih2T1kGM2m9GxY0f85z//QYcOHTB+/HiMGzcOixcvtvZH3bW5c+fCx8fH8ggLC5O7JKvjQoBEtq9vKy3WvBiFYG81UrPyMXDBXhy7mCd3WUQOx+ohp06dOmjZsmWV51q0aIH09HQAgFarBQBkZWVVaZOVlWU5ptVqkZ2dXeV4WVkZcnNzq7S51Xvc+Bl/NnPmTOj1essjIyPjXk7RplkWAuT0cSKb1qaeD9ZP6oHmWm9cyTfi2c/jsS351r3QRHRvrB5yevTogdTU1CrPnTp1CuHh4QCAiIgIaLVabN++3XLcYDAgISEBUVFRAICoqCjk5eUhMTHR0mbHjh0wm82IjIy0tImLi0Np6R/3s2NjY9GsWbMqM7lupFarodFoqjwcibHMBJ2hfIYaFwIksn2hvu5YOyEKDzQNQnGpGRO+T8SXv53jzCsiK7F6yJk2bRr279+P//znPzhz5gxWrFiBJUuWYNKkSQDK70lPnToV77zzDn766SccP34cI0eORGhoKAYOHAigvOenX79+GDduHA4cOIC9e/di8uTJGDJkCEJDQwEAw4YNg0qlwtixY5GcnIzVq1fj448/xvTp0619SnYjM68YQgDurkoEeKru/AIikp23myu+GtUZwyPrQwjgnU2/Y/aGZG7uSWQNNTG16+effxatW7cWarVaNG/eXCxZsqTKcbPZLGbNmiVCQkKEWq0Wffr0EampqVXa5OTkiKFDhwovLy+h0WjE6NGjRX5+fpU2R48eFT179hRqtVrUrVtXvPfee3dVp6NNIY87lS3CZ2wU0e/vkrsUIrpLZrNZfBF3VjR4vXyK+aivE0R+cancZRHZpOr+fktCOG+/qMFggI+PD/R6vUPculqRkI5/rjuOvzUPxtfPd5G7HCK6B1tP6DB19REUl5rRXOuNb0Z3QR0fjrEjulF1f7+5d5UD+WNmFf8Pkche9WutxerxUQj0UiNFl48nPtuLE5f0cpdFZJcYchzIHzOrOOiYyJ61C/PF+knd0TTEC9n5Rjy9eB/3vCK6Bww5DiSDCwESOYx6fh74YWJ3y8yricsP47MdpznziuguMOQ4kItcCJDIoWgqZl6N6REBAPi/X05h2uokFJeaZK6MyD4w5DiIopIyXC0oAcA1cogciYtSgdkDWuLdJ1vDRSFhfVImhizZj+z8YrlLI7J5DDkOIiO3fDyOxs0FPu6uMldDRNY2PDIc347pCh93VyRl5GHgZ3txMtPx9t8jsiaGHAfxx3gc9uIQOarujQOx7qXuaBjoiUx9MZ5evA+/cCsIottiyHEQldPHObOKyLE1DPLCupd6oEfjABSVmPDi94lYtOssByQT3QJDjoOovF1VP4Ahh8jR+Xi4YunorhjRrXwriP9uTcHf1x6DsYwDkoluxJDjIP7oyeH0cSJn4KpU4J2BbfCvx1tBIQH/O3wRw79IQE6BUe7SiGwGQ46DqByTU49jcoicyqjuDbB0dFd4u7ng0IVreGLBXqTq8uUui8gmMOQ4ACHEHwOPOSaHyOn0bhqEdS91R3iABy5eu45BC/diR0qW3GURyY4hxwFcKypFYUn5vXjuW0XknBoHe2P9Sz0QGeGPwhITxi47hC9/O8cByeTUGHIcQGUvTohGDTdXpczVEJFc/DxV+G5sJIZ0CYMQwDubfsc/fuCAZHJeDDkOgNPHiaiSykWBuYPa4M3+LaCQgLWJFzF0yX5kG7hCMjkfhhwHkM6FAInoBpIk4YVeDfFNxYDkw+l5ePyzvTiakSd3aUS1iiHHAVSukcOQQ0Q3eqBpEDZM6oFGQZ7QGYrxzOfxWHfkotxlEdUahhwHcJFr5BDRbTQM8sL6ST3Qp3kwSsrMmLb6KP6z+XeYzByQTI6PIccBcN8qIvor3m6uWDKyMyY91AgAsCTuHEYvPQh9UanMlRHVLIYcO2cyC1zK4+0qIvprSoWE12Ka49OhHeDmqkDcqSsYuHAvzmRz4UByXAw5dk5nKEapScBVKUGrcZO7HCKycQPaheJ/E7ujrq870q4WYuCCfdj+OxcOJMfEkGPnKm9V1fV1h1IhyVwNEdmDVqE+2DC5B7o28EeBsQwvfHsIC3ae4cKB5HAYcuwcx+MQ0b0I9FLj+xciMTyyfCfz+dtS8fLKIygqKZO7NCKrYcixcxnXysfj1ONCgER0l1QuCrz7ZBu8M7A1XBQSNh67jKcXxVvG+RHZO4YcO1fZk1OfPTlEdI9GdAvHinHdEOCpwsnLBjz+6R4cSMuVuyyi+8aQY+f+uF3FNXKI6N51jfDHhsk90LKOBjmFJRj2xX58t/8Cx+mQXWPIsXOWLR14u4qI7lM9Pw/8b2J3PNa2DsrMArPWn8CM/x1DcSk3+CT7xJBjx4pKypCdbwQANAjwlLkaInIE7iolPh3aAa8/0hwKCVhz6CIGfx6PTI7TITvEkGPHKntxfD1c4ePhKnM1ROQoJEnChAcaYdmYrvD1cMXRi3oM+HQP4s/myF0a0V1hyLFj56+Wh5xw9uIQUQ3o1SQIP0/uaRmnM+KrBHz52zmO0yG7wZBjxy7kFAIAwjmziohqSJh/+TidJzvUhcks8M6m3zFlVRKul3CcDtk+hhw7dqHidlWDAIYcIqo57iolPni2HeYMaAkXhYSfjmbiyYV7kZ5TJHdpRH+JIceOVfbk1OftKiKqYZIk4fkeEVj+QiQCvVRI0eVjwGd7sCs1W+7SiG6LIceOXchhTw4R1a7IhgHY+HIvtA/zhf56KUYvPch9r8hmMeTYKWOZyTKlsz5DDhHVIq2PG1a/2A1Du4ZZ9r2a8H0i8otL5S6NqAqGHDt18dp1mAXgoVIiyEstdzlE5GTULkrMHdQWcwe1gUqpwLbkLAxcsBdnrxTIXRqRBUOOnaoc8Bce4AlJkmSuhoic1dCu9bH6xW7Qatxw9kohnvhsL35J1sldFhEAhhy7dZ7Tx4nIRnSo74efX+6Jrg38UWAsw/jvEvF/21JhMnOcDsmLIcdOVQ46Dg9kyCEi+QV5q7F8XCSe794AAPDZzjMY9fUB5BQY5S2MnBpDjp36YyFATh8nItvgqlRgzuOt8PGQ9nB3VWLPmat47NM9OJx+Te7SyEnVeMh57733IEkSpk6danmuuLgYkyZNQkBAALy8vPDUU08hKyuryuvS09PRv39/eHh4IDg4GK+99hrKysqqtNm1axc6duwItVqNxo0bY+nSpTV9OjaD08eJyFY90b4uNkzugYaBnrisL8bgz+Pxbfx5TjOnWlejIefgwYP4/PPP0bZt2yrPT5s2DT///DPWrl2L3bt3IzMzE4MGDbIcN5lM6N+/P0pKSrBv3z4sW7YMS5cuxezZsy1t0tLS0L9/fzz00ENISkrC1KlT8cILL2Dbtm01eUo2wWQWyLhWHnI4fZyIbFHTEG9smNwDj7bRotQkMHtDMqauTkJRSdmdX0xkJZKooWhdUFCAjh07YuHChXjnnXfQvn17fPTRR9Dr9QgKCsKKFSvw9NNPAwBSUlLQokULxMfHo1u3btiyZQsee+wxZGZmIiQkBACwePFizJgxA1euXIFKpcKMGTOwadMmnDhxwvKZQ4YMQV5eHrZu3VqtGg0GA3x8fKDX66HRaKx/EWpIRm4Res3bCZVSgd/f7gelgrOriMg2CSHw1Z40zN2SApNZoGmIFxaN6IRGQV5yl0Z2rLq/3zXWkzNp0iT0798f0dHRVZ5PTExEaWlpleebN2+O+vXrIz4+HgAQHx+PNm3aWAIOAMTExMBgMCA5OdnS5s/vHRMTY3kPR5ZesWdVmL87Aw4R2TRJkvBCr4ZYOa4bgrzVOJVVgCc+24stxy/LXRo5gRoJOatWrcLhw4cxd+7cm47pdDqoVCr4+vpWeT4kJAQ6nc7S5saAU3m88thftTEYDLh+/fot6zIajTAYDFUe9sgyfZx7VhGRnega4Y9Nr/RE14jyaeYTlx/Gu5tOotRklrs0cmBWDzkZGRmYMmUKli9fDjc3N2u//X2ZO3cufHx8LI+wsDC5S7onlunjHI9DRHYk2NsNK16IxIu9GwIAvvgtDcO/SEC2oVjmyshRWT3kJCYmIjs7Gx07doSLiwtcXFywe/dufPLJJ3BxcUFISAhKSkqQl5dX5XVZWVnQarUAAK1We9Nsq8o/36mNRqOBu7v7LWubOXMm9Hq95ZGRkWGNU651F7gQIBHZKRelAjMfbYHFIzrCS+2CA+dz8egne7D/XI7cpZEDsnrI6dOnD44fP46kpCTLo3Pnzhg+fLjlf7u6umL79u2W16SmpiI9PR1RUVEAgKioKBw/fhzZ2dmWNrGxsdBoNGjZsqWlzY3vUdmm8j1uRa1WQ6PRVHnYows3bOlARGSP+rWug58m90CzEG9cLTBi+JcJ+Hz3WU4zJ6tysfYbent7o3Xr1lWe8/T0REBAgOX5sWPHYvr06fD394dGo8HLL7+MqKgodOvWDQDQt29ftGzZEs899xzmzZsHnU6HN998E5MmTYJaXb4Z5YQJE/DZZ5/hH//4B8aMGYMdO3ZgzZo12LRpk7VPyaaYzQJpV8t7ciICGXKIyH41DPLCuknd8ca6E1h35BLmbknB4fRrmP9MO2jcXOUujxyALCsef/jhh3jsscfw1FNPoXfv3tBqtfjxxx8tx5VKJTZu3AilUomoqCiMGDECI0eOxL///W9Lm4iICGzatAmxsbFo164d3n//fXz55ZeIiYmR45RqzWVDMYxlZrgqJdTzu/VtOSIie+GhcsEHz7bD2wNbw1UpYVtyFh7/dA+SM/Vyl0YOoMbWybEH9rhOzp7TVzHiqwQ0CvLE9lcflLscIiKrScrIw6Tlh3Ep7zpULgrMGdAKQ7uGQZK4VAZVJfs6OVQz0q4WAAAiArmQFhE5lvZhvtj0Sk/0aR6MkjIz/rnuOKauTkKhkask071hyLEzZ6+Uj8dpGMTxOETkeHw9VPhiZGe8/khzKBUSNiRlYsBne5Cis891zUheDDl2hoOOicjRKRQSJjzQCKvGd4NW44ZzVwoxcMFerDlkn8t+kHwYcuxMZchpyJBDRA6uS4PyVZJ7Nw1CcakZ//jhGF5dc5SbfFK1MeTYEWOZCRcrdh+P4O0qInICAV5qLH2+C/7etykUEvC/wxfxxGd7cSY7X+7SyA4w5NiR9JwimAXgpXZBkJda7nKIiGqFQiFh8t+aYPkL5Zt8ns4uwIBP92LdkYtyl0Y2jiHHjpy7YTwOp1QSkbOJahSAza/0Qo/GAbheasK01Ufx+v+OobjUJHdpZKMYcuwIBx0TkbML8lbj2zGRmBrdBJIErDqYgYEL9uLclQK5SyMbxJBjR9I4fZyICEqFhKnRTfHdmEgEeqmQosvHgE/34OejmXKXRjaGIceOsCeHiOgPPZsEYtMrvRAZ4Y/CEhNeXnkEb64/zttXZMGQY0fOVax23JCrHRMRAQBCNG5Y/kIkJj3UCADw/f50DFywF2eyefuKGHLshv56Ka4WlAAAGgR6yFwNEZHtcFEq8FpMc3w7pmuV21c/JHL2lbNjyLET5ytuVQV7q+Ht5ipzNUREtqd306Aqs6/+vvYopq9OQgH3vnJaDDl2guNxiIjuLFjjhm/HRFoWD/zxyCUM+HQPkjP1cpdGMmDIsROV0yM5s4qI6K8pKxYPXP1iFOr4uCHtaiGeXLAPy/adhxBC7vKoFjHk2Ilz7MkhIrorXRr4Y/MrvRDdIgQlJjPe+ikZE75PhL6oVO7SqJYw5NiJPzbm5MwqIqLq8vNU4YuRnTD7sZZwVUrYlpyFRz/5DYkXcuUujWoBQ44dEEL8MSaHt6uIiO6KJEkY0zMCP07sgQYBHriUdx3Pfr4fC3edgdnM21eOjCHHDlzWF6OoxAQXhYQwP04fJyK6F23q+eDnl3viifahMJkF5m1NxahvDuBKvlHu0qiGMOTYgcpFrcIDPKBy4X8yIqJ75e3mio8Gt8e8p9rCzVWB305fxSMf/4Y9p6/KXRrVAP5i2oHTFSGnSbC3zJUQEdk/SZLwbJcw/Dy5J5qFeONqgRHPfZ2A+dtSUGoyy10eWRFDjh2o7MlpHMxBx0RE1tIkxBsbJvfA0K71IQSwYOdZPLM4Huk5RXKXRlbCkGMHzjLkEBHVCDdXJeYOaoMFwzrC280FSRl5ePST37D+yCW5SyMrYMixA2euMOQQEdWk/m3rYMuUXugc7ocCYxmmrk7C9NVJyC/mmjr2jCHHxuUUGJFbWAJJAhoFMeQQEdWUen4eWDW+G6ZGN7FsCdH/kz1IysiTuzS6Rww5Nq5yPE5dX3e4q5QyV0NE5NhclApMjW6KNS9Goa6vO9Jzi/D0on1cU8dOMeTYON6qIiKqfZ0b+GPzlF7o37YOyirW1BnxVQJ0+mK5S6O7wJBj4ywzq3irioioVvm4u+KzoR0w7+m28FApse9sDh75OA6/JOvkLo2qiSHHxlWGnCYhDDlERLVNkiQ82zkMG1/uidZ1NbhWVIrx3yVi1voTKC41yV0e3QFDjo3jGjlERPJrGOSF/03sjnG9IgAA3+2/gMc/24MUnUHmyuivMOTYsPziUlyuuP/bOIirHRMRyUntosQb/Vvi2zFdEeilxqmsAjz+2V4s23ceQnBQsi1iyLFhZ6+U7zwe5K2Gj4erzNUQEREA9G4ahK1Te+GhZkEoKTPjrZ+S8cKyQ7hawI0+bQ1Djg3joGMiItsU6KXG1893wVsDWkKlVGB7Sjb6fRSHnSnZcpdGN2DIsWEcj0NEZLskScLoHhHYMLlHxUafJRi99CBmbziB6yUclGwLGHJsGEMOEZHta1FHgw2Te2B0jwYAgG/jL2DAZ3tw4pJe3sKIIceWncnOBwA0YcghIrJpbq5KvDWgFb4d0xXB3mqcyS7Akwv3YvHuszBxpWTZMOTYqOJSE9JziwCwJ4eIyF6UD0rujZhWISg1Cby3JQXDv9yPS3nX5S7NKTHk2Kgz2QUwC8DXwxVB3mq5yyEiomry91Rh8YhO+O9TbeChUmL/uVz0+ygOPx3NlLs0p8OQY6NSdeW3qpqFeEOSJJmrISKiuyFJEgZ3qY/Nr/RC+zBf5BeX4ZWVRzBtdRIMxaVyl+c0GHJs1KmsipCj5SKARET2qkGgJ9ZOiMIrfZpAIQHrjlzCIx/9hgNpuXKX5hSsHnLmzp2LLl26wNvbG8HBwRg4cCBSU1OrtCkuLsakSZMQEBAALy8vPPXUU8jKyqrSJj09Hf3794eHhweCg4Px2muvoaysrEqbXbt2oWPHjlCr1WjcuDGWLl1q7dORTYqOIYeIyBG4KhWY/nBTrJ3QHfX9PXAp7zqGLInH/G0pKDWZ5S7PoVk95OzevRuTJk3C/v37ERsbi9LSUvTt2xeFhYWWNtOmTcPPP/+MtWvXYvfu3cjMzMSgQYMsx00mE/r374+SkhLs27cPy5Ytw9KlSzF79mxLm7S0NPTv3x8PPfQQkpKSMHXqVLzwwgvYtm2btU9JFpW3q5oz5BAROYRO4X7YPKUXnulUD2YBLNh5Fk8t2oezVwrkLs1hSaKGN9y4cuUKgoODsXv3bvTu3Rt6vR5BQUFYsWIFnn76aQBASkoKWrRogfj4eHTr1g1btmzBY489hszMTISEhAAAFi9ejBkzZuDKlStQqVSYMWMGNm3ahBMnTlg+a8iQIcjLy8PWrVurVZvBYICPjw/0ej00Go31T/4e6YtK0e7fvwAAjs/pC283bulARORINh+/jJk/Hof+eincXBV449EWGNEtnGMwq6m6v981PiZHry9fDMnf3x8AkJiYiNLSUkRHR1vaNG/eHPXr10d8fDwAID4+Hm3atLEEHACIiYmBwWBAcnKypc2N71HZpvI97FlqxXicur7uDDhERA7o0TZ1sG1qb/RsHIjiUjNmbUjGyK8PQFexKTNZR42GHLPZjKlTp6JHjx5o3bo1AECn00GlUsHX17dK25CQEOh0OkubGwNO5fHKY3/VxmAw4Pr1W69HYDQaYTAYqjxsUaquvC6OxyEiclxaHzd8O6Yr5gxoCbWLAr+dvooYTjW3qhoNOZMmTcKJEyewatWqmvyYaps7dy58fHwsj7CwMLlLuiUOOiYicg4KhYTne0Rg0yu90K6eD/TXS/HKyiOYvOIw8opK5C7P7tVYyJk8eTI2btyInTt3ol69epbntVotSkpKkJeXV6V9VlYWtFqtpc2fZ1tV/vlObTQaDdzd3W9Z08yZM6HX6y2PjIyM+zrHmsJBx0REzqVxsBd+mNgdU6ObQKmQsPHYZfT9MA67Urmr+f2wesgRQmDy5MlYt24dduzYgYiIiCrHO3XqBFdXV2zfvt3yXGpqKtLT0xEVFQUAiIqKwvHjx5Gd/cd/3NjYWGg0GrRs2dLS5sb3qGxT+R63olarodFoqjxsjRDCMiaHPTlERM7DVanA1OimWPdSdzQK8kR2vhHPf3MQb6w7jqKSsju/Ad3E6iFn0qRJ+P7777FixQp4e3tDp9NBp9NZxsn4+Phg7NixmD59Onbu3InExESMHj0aUVFR6NatGwCgb9++aNmyJZ577jkcPXoU27Ztw5tvvolJkyZBrS7f4mDChAk4d+4c/vGPfyAlJQULFy7EmjVrMG3aNGufUq26rC9GfnEZXBQSGgZyzyoiImfTtp4vNr3SC893bwAAWJ6Qjkc//g2JF67JW5gdsvoU8ttNf/vmm2/w/PPPAyhfDPDVV1/FypUrYTQaERMTg4ULF1puRQHAhQsXMHHiROzatQuenp4YNWoU3nvvPbi4uFja7Nq1C9OmTcPJkydRr149zJo1y/IZ1WGLU8h3pmRj9NKDaBrihV+mPSB3OUREJKO9Z67i72uP4rK+GAoJmPhgI0zp0xQqF+fesKC6v981vk6OLbPFkLNw1xnM25qKAe1C8enQDnKXQ0REMtNfL8Wcn5Kx7sglAECrUA0+HNweTUOcd0iDzayTQ3cnObN8+nirUNsIXUREJC8fd1d8OLg9Fg7vCD8PVyRnGvDYp3vwRdw5mM1O209RLQw5NuYkQw4REd1C5QKCDzULQkmZGe9u/h1Dv9iPjNwiuUuzWQw5NiS/uBRpV8v3+GoV6iNzNUREZGuCNW74+vkumDuoDTxUSiSk5eKRj3/DmkMZcOLRJ7fFkGNDfr9cPnW8jo8b/D1VMldDRES2SJIkDO1aH1um9ELncD8UGMvwjx+O4YVlh5Bt4LYQN2LIsSHJmeX7fPFWFRER3Ul4gCdWvxiFGf2aQ6VUYHtKNh7+MA4bki6xV6cCQ44NqRx03JK3qoiIqBqUCgkTH2yEja/0RJu65dtCTFmVhAnfJ+JqgVHu8mTHkGNDOLOKiIjuRdMQb/z4UndMf7gpXBQStiVnoe+Hcdh8/LLcpcmKIcdGGMtMOF2xnQNDDhER3S1XpQKv9GmCDZN7oLnWG7mFJXhp+WFMXnEY1wqdc7NPhhwbcTqrAGVmAR93V9T1vfUGo0RERHfSKtQHP03uiZf/1tiy2efDH8Yh9mTWnV/sYBhybMSJS38MOr7d1hhERETVoXJR4NW+zfDjxO5oEuyFqwVGjPv2EKavToK+qFTu8moNQ46NSMrIA1C+MRsREZE1tAvzxc8v98SEBxpBIQE/HrmEvh/txs7UbLlLqxUMOTaiMuS0D/OVtQ4iInIsbq5KvP5Ic6yd0B0NAz2RZTBi9DcHMeOHY8gvduxeHYYcG1BoLMOpikHHHer7ylsMERE5pE7hftj0Si+M6REBSQJWH8pAv49+w94zV+UurcYw5NiA45f0MIvylY5DNG5yl0NERA7KXaXE7AEtsWpcN9T398ClvOsY/mUC3lx/HIXGMrnLszqGHBtQeauqHcfjEBFRLYhsGIAtU3rhuW7hAIDv96ej38dx2OdgvToMOTbgaOV4HN6qIiKiWuKpdsHbA1tj+QuRqOvrjozc6xj2ZQL+ue64w4zVYcixARx0TEREcunROBDbpvW29OqsSEhHzIdx2H3qisyV3T+GHJll5l3HZX0xlAoJbepyzyoiIqp9XhW9Oisrxupk6osx6usDeG3tUbteV4chR2YHz+cCKF8E0FPtInM1RETkzKIaBWDr1D9mYK1NvIiHP9yNX+10tWSGHJklpJWHnK4N/GWuhIiICPBQuWD2gJZY+2IUGgZ6IjvfiBe+PYSpq47Y3R5YDDkyO1gRcrpEMOQQEZHt6NzAH5un9MKLDzSEQgLWJ2Xi4Q93Y4sd7WzOkCOjnAIjTmcXAAC6sCeHiIhsjJurEjMfaYEfX+pRsQdWCSYuP4xJyw/jaoFR7vLuiCFHRgfPXwMANAn2gr+nSuZqiIiIbq19mC82vvLHzuabjl/Gwx/sxoakSxBCyF3ebTHkyKhyKe1uDQNkroSIiOivqV2UeLVvM2yY1AMt6mhwragUU1YlYfx3icg2FMtd3i0x5MhoT0XI6dkkUOZKiIiIqqd1XR9smNQD06KbwlUpIfZkFqI/2I0fEi/aXK8OQ45MLl4rQtrVQigVEqIasSeHiIjsh8pFgSnRTfDzyz3Rpq4PDMVl+Pvaoxiz9CAu66/LXZ4FQ45M9pwu78VpV88HGjdXmashIiK6e821Gqx7qTv+0a8ZVEoFdqZeQd8P4rDyQLpN9Oow5Mjkt9OVt6qCZK6EiIjo3rkoFXjpwcbYPKUnOtT3Rb6xDDN/PI5hXyTgQk6hrLUx5MjAWGay7AnyYDOGHCIisn+Ng73xw4TueLN/C7i5KhB/LgcxH8VZVvaXA0OODOLP5qDAWIYgbzXa1/OVuxwiIiKrUCokvNCrIbZN7Y2ohgEI9XGXdV9GbpYkg9iKPUAebhkChUKSuRoiIiLrCg/wxIpxkbiSb4Sbq1K2OtiTU8vMZmEJOX1bhshcDRERUc2QJAnBGjdZa2DIqWVHMq4hO98IL7ULp44TERHVIIacWva/w5cAAH1bhUDtIl8XHhERkaNjyKlFxaUmbDyaCQB4umM9mashIiJybAw5tejX37NgKC5DqI8b96siIiKqYQw5tei7+AsAgCc71uWsKiIiohrGkFNLjmbkISEtFy4KCSO6hctdDhERkcNjyKklX/x2DgDweLtQ1PFxl7kaIiIix8eQUwuOX9Rj0/HLAICxvSJkroaIiMg52H3IWbBgARo0aAA3NzdERkbiwIEDcpdUhRACb/10AkIAA9uHolWofMtbExERORO7DjmrV6/G9OnT8dZbb+Hw4cNo164dYmJikJ2dLXdpFkv3ncfh9Dx4qJR4/ZEWcpdDRETkNOw65HzwwQcYN24cRo8ejZYtW2Lx4sXw8PDA119/LXdpAICNxzLxzqbfAQD/iGkGrY+8y1sTERE5E7vdoLOkpASJiYmYOXOm5TmFQoHo6GjEx8ff8jVGoxFGo9HyZ4PBYP26ysxYtu884s/lYEdKeY/S053qYVT3Blb/LCIiIro9u+3JuXr1KkwmE0JCqm5yGRISAp1Od8vXzJ07Fz4+PpZHWFiY1etyVUpYuOsMdqRkQ5KAsT0j8N+n2kKSuC4OERFRbbLbnpx7MXPmTEyfPt3yZ4PBYPWgI0kSxvaMgFKhQHSLYDQJ8bbq+xMREVH12G3ICQwMhFKpRFZWVpXns7KyoNVqb/katVoNtVpd47VN/luTGv8MIiIi+mt2e7tKpVKhU6dO2L59u+U5s9mM7du3IyoqSsbKiIiIyBbYbU8OAEyfPh2jRo1C586d0bVrV3z00UcoLCzE6NGj5S6NiIiIZGbXIWfw4MG4cuUKZs+eDZ1Oh/bt22Pr1q03DUYmIiIi5yMJIYTcRcjFYDDAx8cHer0eGo1G7nKIiIioGqr7+223Y3KIiIiI/gpDDhERETkkhhwiIiJySAw5RERE5JAYcoiIiMghMeQQERGRQ2LIISIiIofEkENEREQOiSGHiIiIHJJdb+twvyoXezYYDDJXQkRERNVV+bt9p00bnDrk5OfnAwDCwsJkroSIiIjuVn5+Pnx8fG573Kn3rjKbzcjMzIS3tzckSbLa+xoMBoSFhSEjI4N7Yt0Br1X18VrdHV6v6uO1qj5eq+qryWslhEB+fj5CQ0OhUNx+5I1T9+QoFArUq1evxt5fo9HwL0E18VpVH6/V3eH1qj5eq+rjtaq+mrpWf9WDU4kDj4mIiMghMeQQERGRQ2LIqQFqtRpvvfUW1Gq13KXYPF6r6uO1uju8XtXHa1V9vFbVZwvXyqkHHhMREZHjYk8OEREROSSGHCIiInJIDDlERETkkBhyiIiIyCEx5FjZggUL0KBBA7i5uSEyMhIHDhyQuyTZzZkzB5IkVXk0b97ccry4uBiTJk1CQEAAvLy88NRTTyErK0vGimtXXFwcBgwYgNDQUEiShPXr11c5LoTA7NmzUadOHbi7uyM6OhqnT5+u0iY3NxfDhw+HRqOBr68vxo4di4KCglo8i9pxp2v1/PPP3/Rd69evX5U2znKt5s6diy5dusDb2xvBwcEYOHAgUlNTq7Spzt+99PR09O/fHx4eHggODsZrr72GsrKy2jyVGleda/Xggw/e9N2aMGFClTbOcK0WLVqEtm3bWhb4i4qKwpYtWyzHbe07xZBjRatXr8b06dPx1ltv4fDhw2jXrh1iYmKQnZ0td2mya9WqFS5fvmx57Nmzx3Js2rRp+Pnnn7F27Vrs3r0bmZmZGDRokIzV1q7CwkK0a9cOCxYsuOXxefPm4ZNPPsHixYuRkJAAT09PxMTEoLi42NJm+PDhSE5ORmxsLDZu3Ii4uDiMHz++tk6h1tzpWgFAv379qnzXVq5cWeW4s1yr3bt3Y9KkSdi/fz9iY2NRWlqKvn37orCw0NLmTn/3TCYT+vfvj5KSEuzbtw/Lli3D0qVLMXv2bDlOqcZU51oBwLhx46p8t+bNm2c55izXql69enjvvfeQmJiIQ4cO4W9/+xueeOIJJCcnA7DB75Qgq+natauYNGmS5c8mk0mEhoaKuXPnyliV/N566y3Rrl27Wx7Ly8sTrq6uYu3atZbnfv/9dwFAxMfH11KFtgOAWLduneXPZrNZaLVaMX/+fMtzeXl5Qq1Wi5UrVwohhDh58qQAIA4ePGhps2XLFiFJkrh06VKt1V7b/nythBBi1KhR4oknnrjta5z1WgkhRHZ2tgAgdu/eLYSo3t+9zZs3C4VCIXQ6naXNokWLhEajEUajsXZPoBb9+VoJIcQDDzwgpkyZctvXOOu1EkIIPz8/8eWXX9rkd4o9OVZSUlKCxMREREdHW55TKBSIjo5GfHy8jJXZhtOnTyM0NBQNGzbE8OHDkZ6eDgBITExEaWlplevWvHlz1K9fn9cNQFpaGnQ6XZXr4+Pjg8jISMv1iY+Ph6+vLzp37mxpEx0dDYVCgYSEhFqvWW67du1CcHAwmjVrhokTJyInJ8dyzJmvlV6vBwD4+/sDqN7fvfj4eLRp0wYhISGWNjExMTAYDJZ/uTuiP1+rSsuXL0dgYCBat26NmTNnoqioyHLMGa+VyWTCqlWrUFhYiKioKJv8Tjn1Bp3WdPXqVZhMpir/4QAgJCQEKSkpMlVlGyIjI7F06VI0a9YMly9fxr/+9S/06tULJ06cgE6ng0qlgq+vb5XXhISEQKfTyVOwDam8Brf6XlUe0+l0CA4OrnLcxcUF/v7+TncN+/Xrh0GDBiEiIgJnz57FP//5TzzyyCOIj4+HUql02mtlNpsxdepU9OjRA61btwaAav3d0+l0t/zuVR5zRLe6VgAwbNgwhIeHIzQ0FMeOHcOMGTOQmpqKH3/8EYBzXavjx48jKioKxcXF8PLywrp169CyZUskJSXZ3HeKIYdq3COPPGL5323btkVkZCTCw8OxZs0auLu7y1gZOZohQ4ZY/nebNm3Qtm1bNGrUCLt27UKfPn1krExekyZNwokTJ6qMhaNbu921unHcVps2bVCnTh306dMHZ8+eRaNGjWq7TFk1a9YMSUlJ0Ov1+OGHHzBq1Cjs3r1b7rJuiberrCQwMBBKpfKmUeRZWVnQarUyVWWbfH190bRpU5w5cwZarRYlJSXIy8ur0obXrVzlNfir75VWq71pcHtZWRlyc3Od/ho2bNgQgYGBOHPmDADnvFaTJ0/Gxo0bsXPnTtSrV8/yfHX+7mm12lt+9yqPOZrbXatbiYyMBIAq3y1nuVYqlQqNGzdGp06dMHfuXLRr1w4ff/yxTX6nGHKsRKVSoVOnTti+fbvlObPZjO3btyMqKkrGymxPQUEBzp49izp16qBTp05wdXWtct1SU1ORnp7O6wYgIiICWq22yvUxGAxISEiwXJ+oqCjk5eUhMTHR0mbHjh0wm82W/yN2VhcvXkROTg7q1KkDwLmulRACkydPxrp167Bjxw5ERERUOV6dv3tRUVE4fvx4lWAYGxsLjUaDli1b1s6J1II7XatbSUpKAoAq3y1nuFa3YjabYTQabfM7ZfWhzE5s1apVQq1Wi6VLl4qTJ0+K8ePHC19f3yqjyJ3Rq6++Knbt2iXS0tLE3r17RXR0tAgMDBTZ2dlCCCEmTJgg6tevL3bs2CEOHTokoqKiRFRUlMxV1578/Hxx5MgRceTIEQFAfPDBB+LIkSPiwoULQggh3nvvPeHr6ys2bNggjh07Jp544gkREREhrl+/bnmPfv36iQ4dOoiEhASxZ88e0aRJEzF06FC5TqnG/NW1ys/PF3//+99FfHy8SEtLE7/++qvo2LGjaNKkiSguLra8h7Ncq4kTJwofHx+xa9cucfnyZcujqKjI0uZOf/fKyspE69atRd++fUVSUpLYunWrCAoKEjNnzpTjlGrMna7VmTNnxL///W9x6NAhkZaWJjZs2CAaNmwoevfubXkPZ7lWr7/+uti9e7dIS0sTx44dE6+//rqQJEn88ssvQgjb+04x5FjZp59+KurXry9UKpXo2rWr2L9/v9wlyW7w4MGiTp06QqVSibp164rBgweLM2fOWI5fv35dvPTSS8LPz094eHiIJ598Uly+fFnGimvXzp07BYCbHqNGjRJClE8jnzVrlggJCRFqtVr06dNHpKamVnmPnJwcMXToUOHl5SU0Go0YPXq0yM/Pl+FsatZfXauioiLRt29fERQUJFxdXUV4eLgYN27cTf/IcJZrdavrBEB88803ljbV+bt3/vx58cgjjwh3d3cRGBgoXn31VVFaWlrLZ1Oz7nSt0tPTRe/evYW/v79Qq9WicePG4rXXXhN6vb7K+zjDtRozZowIDw8XKpVKBAUFiT59+lgCjhC2952ShBDC+v1DRERERPLimBwiIiJySAw5RERE5JAYcoiIiMghMeQQERGRQ2LIISIiIofEkENEREQOiSGHiIiIHBJDDhERETkkhhwiIiJySAw5RERE5JAYcoiIiMghMeQQERGRQ/p/l2tVZ0G6sEgAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.plot(df['time'][1:], df['general/altitude'][1:], label='general/altitude')\n",
    "plt.show()\n",
    "\n",
    "\n",
    "plt.plot(df['general/longitude'][1:],df['general/latitude'][1:])\n",
    "plt.show()\n",
    "\n",
    "\n",
    "plt.plot(df['general/x'][1:],df['general/y'][1:])\n",
    "plt.show()\n",
    "\n",
    "\n",
    "plt.plot(df['time'][1:], df['general/z'][1:], label='general/z')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    Theta [deg.]  Phi   [deg.]  Abs(Gain)[dBi   ]   Abs(Theta)[dBi   ]  Phase(Theta)[deg.]  Abs(Phi  )[dBi   ]  Phase(Phi  )[deg.]  Ax.Ratio[dB    ]    \n",
      "0    -180.000         -90.000           -7.508e+00 ...                                                                                                  \n",
      "1    -170.000         -90.000           -7.301e+00 ...                                                                                                  \n",
      "2    -160.000         -90.000           -6.016e+00 ...                                                                                                  \n",
      "3    -150.000         -90.000           -5.240e+00 ...                                                                                                  \n",
      "4    -140.000         -90.000           -5.454e+00 ...                                                                                                  \n",
      "..                                                 ...                                                                                                  \n",
      "679   130.000          90.000           -6.615e+00 ...                                                                                                  \n",
      "680   140.000          90.000           -5.454e+00 ...                                                                                                  \n",
      "681   150.000          90.000           -5.240e+00 ...                                                                                                  \n",
      "682   160.000          90.000           -6.016e+00 ...                                                                                                  \n",
      "683   170.000          90.000           -7.301e+00 ...                                                                                                  \n",
      "\n",
      "[684 rows x 1 columns]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<spatz.sensors.antenna.tx_gain.GainPattern at 0x251314da450>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from spatz.sensors.antenna.tx_gain import GainPattern\n",
    "\n",
    "GainPattern('data/gain_pattern/testpattern.txt')"
   ]
  }
 ],
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