{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 62,
   "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": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Do preprocessing\n",
    "PATH = \"data/simulations\"\n",
    "TMP = f\"{PATH}/temp\"\n",
    "FILE = \"28km\"\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": 64,
   "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": 65,
   "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": 66,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|█████████▉| 639.1000000000768/639.150194412893 [00:26<00:00, 23.94it/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": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<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/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>2393.667868</td>\n",
       "      <td>107.812383</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.774005</td>\n",
       "      <td>0.626653</td>\n",
       "      <td>0.090671</td>\n",
       "      <td>101.343943</td>\n",
       "      <td>4.212357</td>\n",
       "      <td>319.625548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.2</td>\n",
       "      <td>2393.715998</td>\n",
       "      <td>107.812557</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773925</td>\n",
       "      <td>0.626641</td>\n",
       "      <td>0.091437</td>\n",
       "      <td>101.387942</td>\n",
       "      <td>4.208309</td>\n",
       "      <td>320.876645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.3</td>\n",
       "      <td>2393.765548</td>\n",
       "      <td>107.812737</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773845</td>\n",
       "      <td>0.626628</td>\n",
       "      <td>0.092204</td>\n",
       "      <td>101.431938</td>\n",
       "      <td>4.204262</td>\n",
       "      <td>322.127741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.4</td>\n",
       "      <td>2393.816519</td>\n",
       "      <td>107.812922</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773764</td>\n",
       "      <td>0.626614</td>\n",
       "      <td>0.09297</td>\n",
       "      <td>101.475932</td>\n",
       "      <td>4.200214</td>\n",
       "      <td>323.378837</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.5</td>\n",
       "      <td>2393.868912</td>\n",
       "      <td>107.813112</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>0.171335</td>\n",
       "      <td>0.985213</td>\n",
       "      <td>0.773683</td>\n",
       "      <td>0.626601</td>\n",
       "      <td>0.093736</td>\n",
       "      <td>101.519925</td>\n",
       "      <td>4.196167</td>\n",
       "      <td>324.629934</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6386</th>\n",
       "      <td>638.7</td>\n",
       "      <td>25768.750389</td>\n",
       "      <td>128.452972</td>\n",
       "      <td>-0.019599</td>\n",
       "      <td>-0.005745</td>\n",
       "      <td>0.999791</td>\n",
       "      <td>-0.976774</td>\n",
       "      <td>0.108145</td>\n",
       "      <td>-0.184981</td>\n",
       "      <td>80.420236</td>\n",
       "      <td>4.913187</td>\n",
       "      <td>2.63791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6387</th>\n",
       "      <td>638.8</td>\n",
       "      <td>25770.724327</td>\n",
       "      <td>128.453637</td>\n",
       "      <td>-0.021452</td>\n",
       "      <td>-0.000441</td>\n",
       "      <td>0.99977</td>\n",
       "      <td>-0.976763</td>\n",
       "      <td>0.108148</td>\n",
       "      <td>-0.185037</td>\n",
       "      <td>80.555707</td>\n",
       "      <td>4.917116</td>\n",
       "      <td>2.04426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6388</th>\n",
       "      <td>638.9</td>\n",
       "      <td>25772.69835</td>\n",
       "      <td>128.454303</td>\n",
       "      <td>-0.021841</td>\n",
       "      <td>0.005372</td>\n",
       "      <td>0.999747</td>\n",
       "      <td>-0.976752</td>\n",
       "      <td>0.10815</td>\n",
       "      <td>-0.185094</td>\n",
       "      <td>80.611251</td>\n",
       "      <td>4.918726</td>\n",
       "      <td>1.45061</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6389</th>\n",
       "      <td>639.0</td>\n",
       "      <td>25774.672457</td>\n",
       "      <td>128.454968</td>\n",
       "      <td>-0.02063</td>\n",
       "      <td>0.011282</td>\n",
       "      <td>0.999724</td>\n",
       "      <td>-0.976741</td>\n",
       "      <td>0.108153</td>\n",
       "      <td>-0.18515</td>\n",
       "      <td>80.576614</td>\n",
       "      <td>4.917722</td>\n",
       "      <td>0.856961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6390</th>\n",
       "      <td>639.1</td>\n",
       "      <td>25776.64665</td>\n",
       "      <td>128.455633</td>\n",
       "      <td>-0.017799</td>\n",
       "      <td>0.016842</td>\n",
       "      <td>0.9997</td>\n",
       "      <td>-0.97673</td>\n",
       "      <td>0.108156</td>\n",
       "      <td>-0.185206</td>\n",
       "      <td>80.447889</td>\n",
       "      <td>4.913989</td>\n",
       "      <td>0.263311</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6391 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       time antenna/pathloss/distance antenna/pathloss/out  \\\n",
       "0       0.1               2393.667868           107.812383   \n",
       "1       0.2               2393.715998           107.812557   \n",
       "2       0.3               2393.765548           107.812737   \n",
       "3       0.4               2393.816519           107.812922   \n",
       "4       0.5               2393.868912           107.813112   \n",
       "...     ...                       ...                  ...   \n",
       "6386  638.7              25768.750389           128.452972   \n",
       "6387  638.8              25770.724327           128.453637   \n",
       "6388  638.9               25772.69835           128.454303   \n",
       "6389  639.0              25774.672457           128.454968   \n",
       "6390  639.1               25776.64665           128.455633   \n",
       "\n",
       "     antenna/tx_gain/rocket_x antenna/tx_gain/rocket_y  \\\n",
       "0                        -0.0                 0.171335   \n",
       "1                        -0.0                 0.171335   \n",
       "2                        -0.0                 0.171335   \n",
       "3                        -0.0                 0.171335   \n",
       "4                        -0.0                 0.171335   \n",
       "...                       ...                      ...   \n",
       "6386                -0.019599                -0.005745   \n",
       "6387                -0.021452                -0.000441   \n",
       "6388                -0.021841                 0.005372   \n",
       "6389                 -0.02063                 0.011282   \n",
       "6390                -0.017799                 0.016842   \n",
       "\n",
       "     antenna/tx_gain/rocket_z antenna/tx_gain/pos_x antenna/tx_gain/pos_y  \\\n",
       "0                    0.985213              0.774005              0.626653   \n",
       "1                    0.985213              0.773925              0.626641   \n",
       "2                    0.985213              0.773845              0.626628   \n",
       "3                    0.985213              0.773764              0.626614   \n",
       "4                    0.985213              0.773683              0.626601   \n",
       "...                       ...                   ...                   ...   \n",
       "6386                 0.999791             -0.976774              0.108145   \n",
       "6387                  0.99977             -0.976763              0.108148   \n",
       "6388                 0.999747             -0.976752               0.10815   \n",
       "6389                 0.999724             -0.976741              0.108153   \n",
       "6390                   0.9997              -0.97673              0.108156   \n",
       "\n",
       "     antenna/tx_gain/pos_z antenna/tx_gain/theta antenna/tx_gain/out  \\\n",
       "0                 0.090671            101.343943            4.212357   \n",
       "1                 0.091437            101.387942            4.208309   \n",
       "2                 0.092204            101.431938            4.204262   \n",
       "3                  0.09297            101.475932            4.200214   \n",
       "4                 0.093736            101.519925            4.196167   \n",
       "...                    ...                   ...                 ...   \n",
       "6386             -0.184981             80.420236            4.913187   \n",
       "6387             -0.185037             80.555707            4.917116   \n",
       "6388             -0.185094             80.611251            4.918726   \n",
       "6389              -0.18515             80.576614            4.917722   \n",
       "6390             -0.185206             80.447889            4.913989   \n",
       "\n",
       "     general/altitude  \n",
       "0          319.625548  \n",
       "1          320.876645  \n",
       "2          322.127741  \n",
       "3          323.378837  \n",
       "4          324.629934  \n",
       "...               ...  \n",
       "6386          2.63791  \n",
       "6387          2.04426  \n",
       "6388          1.45061  \n",
       "6389         0.856961  \n",
       "6390         0.263311  \n",
       "\n",
       "[6391 rows x 12 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "130.43368058102035\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": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "32368.96280616025\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/distance'][1:], label='Dist to GS')\n",
    "plt.ylabel(\"Frespace pathloss [dB]\")\n",
    "plt.xlabel(\"Time [s]\")\n",
    "\n",
    "print(np.max(df['antenna/pathloss/distance'][1:]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-7.360621740783089\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": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-107.75182721480577\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
}