{
 "cells": [
  {
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   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from src.preprocessing.synthetic_data import SIR, SI\n",
    "from src.preprocessing.transform_data import transform_general_to_SIR, state_based_data\n",
    "\n",
    "from src.plotter import Plotter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plotter = Plotter()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 52932 characters]",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# https://maa.org/press/periodicals/loci/joma/the-sir-model-for-spread-of-disease-the-differential-equation-model\n",
    "synth_sir_data = SIR(plotter, N=7900000, I_0=10, alpha=1/3, beta=1/2, simulation_time=150, time_points=500)\n",
    "synth_sir_data.generate()\n",
    "synth_sir_data.plot('reference_params_synth')\n",
    "synth_sir_data.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 47268 characters]",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
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   ],
   "source": [
    "synth_sir_data = SI(plotter, N=7900000, I_0=10, alpha=1/14, beta=0.25, simulation_time=150, time_points=500)\n",
    "synth_sir_data.generate()\n",
    "synth_sir_data.plot('SI_synth')\n",
    "synth_sir_data.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "[encoded data, 43956 characters]",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "[encoded data, 43956 characters]",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
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     "metadata": {},
     "output_type": "display_data"
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    {
     "data": {
      "image/png": "[encoded data, 43956 characters]",
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     "metadata": {},
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    {
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     "metadata": {},
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   "source": [
    "for sample_size in [1, 3, 5, 10]:\n",
    "    transform_general_to_SIR(plotter, plot_name=f'RKI_SIR_{sample_size}', plot_title='RKI Data (SIR)', plot_size=(6,6), sample_rate=sample_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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    {
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      "/home/rothenbeck/Covid_19_DINN/src/plotter.py:46: RuntimeWarning: More than 20 figures have been opened. Figures created through the pyplot interface (`matplotlib.pyplot.figure`) are retained until explicitly closed and may consume too much memory. (To control this warning, see the rcParam `figure.max_open_warning`). Consider using `matplotlib.pyplot.close()`.\n",
      "  fig = plt.figure(figsize=shape)\n"
     ]
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   ],
   "source": [
    "states = ['Bremen', \n",
    "          'Sachsen', \n",
    "          'Schleswig Holstein', \n",
    "          'Niedersachsen', \n",
    "          'Mecklenburg-Vorpommern', \n",
    "          'Hamburg', \n",
    "          'Rheinland-Pfalz',\n",
    "          'Brandenburg',\n",
    "          'Nordrhein-Westfalen',\n",
    "          'Berlin',\n",
    "          'Thüringen',\n",
    "          'Hessen',\n",
    "          'Saarland',\n",
    "          'Bayern',\n",
    "          'Baden-Württemberg']\n",
    "\n",
    "for state in states:\n",
    "    state_based_data(plotter, state, model='SI')\n",
    "    state_based_data(plotter, state)\n"
   ]
  }
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