noNPI_Plots.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "6a9a08e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import os\n",
    "import pandas as pd\n",
    "import re\n",
    "from plotfx import *\n",
    "import pickle\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "from matplotlib.ticker import FuncFormatter\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1313150a",
   "metadata": {},
   "source": [
    "## High Community Transmission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "53c6aaa3",
   "metadata": {},
   "outputs": [],
   "source": [
    "outfile = 'allbeta_noNPI_vax_hicom'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e83f9135",
   "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>rep</th>\n",
       "      <th>p_vax</th>\n",
       "      <th>tstep</th>\n",
       "      <th>ext_inf_ct</th>\n",
       "      <th>test_freq</th>\n",
       "      <th>ia_nodes</th>\n",
       "      <th>is_nodes</th>\n",
       "      <th>test_pos_schd</th>\n",
       "      <th>test_pos_symp</th>\n",
       "      <th>q_schd</th>\n",
       "      <th>...</th>\n",
       "      <th>cum_list_inf</th>\n",
       "      <th>n_cum_inf</th>\n",
       "      <th>all_test</th>\n",
       "      <th>n_test_pos</th>\n",
       "      <th>cum_list_test</th>\n",
       "      <th>n_cum_pos</th>\n",
       "      <th>all_quar</th>\n",
       "      <th>n_quar</th>\n",
       "      <th>cum_list_quar</th>\n",
       "      <th>n_cum_quar</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[684]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>...</td>\n",
       "      <td>{684}</td>\n",
       "      <td>1</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>[684]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>...</td>\n",
       "      <td>{684}</td>\n",
       "      <td>1</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>[690, 159]</td>\n",
       "      <td>[684]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>...</td>\n",
       "      <td>{690, 684, 159}</td>\n",
       "      <td>3</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>[690, 159]</td>\n",
       "      <td>[684, 661]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>...</td>\n",
       "      <td>{690, 684, 661, 159}</td>\n",
       "      <td>4</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>128</td>\n",
       "      <td>0</td>\n",
       "      <td>[159]</td>\n",
       "      <td>[684, 661]</td>\n",
       "      <td>[]</td>\n",
       "      <td>[684]</td>\n",
       "      <td>[]</td>\n",
       "      <td>...</td>\n",
       "      <td>{690, 684, 661, 159}</td>\n",
       "      <td>4</td>\n",
       "      <td>[684]</td>\n",
       "      <td>1</td>\n",
       "      <td>{684}</td>\n",
       "      <td>1</td>\n",
       "      <td>[]</td>\n",
       "      <td>0</td>\n",
       "      <td>{}</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   rep  p_vax  tstep  ext_inf_ct  test_freq    ia_nodes    is_nodes  \\\n",
       "0    1    0.0      0         128          0          []       [684]   \n",
       "1    1    0.0      1         128          0          []       [684]   \n",
       "2    1    0.0      2         128          0  [690, 159]       [684]   \n",
       "3    1    0.0      3         128          0  [690, 159]  [684, 661]   \n",
       "4    1    0.0      4         128          0       [159]  [684, 661]   \n",
       "\n",
       "  test_pos_schd test_pos_symp q_schd  ...          cum_list_inf  n_cum_inf  \\\n",
       "0            []            []     []  ...                 {684}          1   \n",
       "1            []            []     []  ...                 {684}          1   \n",
       "2            []            []     []  ...       {690, 684, 159}          3   \n",
       "3            []            []     []  ...  {690, 684, 661, 159}          4   \n",
       "4            []         [684]     []  ...  {690, 684, 661, 159}          4   \n",
       "\n",
       "   all_test n_test_pos  cum_list_test n_cum_pos  all_quar n_quar  \\\n",
       "0        []          0             {}         0        []      0   \n",
       "1        []          0             {}         0        []      0   \n",
       "2        []          0             {}         0        []      0   \n",
       "3        []          0             {}         0        []      0   \n",
       "4     [684]          1          {684}         1        []      0   \n",
       "\n",
       "   cum_list_quar n_cum_quar  \n",
       "0             {}          0  \n",
       "1             {}          0  \n",
       "2             {}          0  \n",
       "3             {}          0  \n",
       "4             {}          0  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pickle.load(open(outfile + \".pkl\", \"rb\" ))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e82e0c8b",
   "metadata": {},
   "source": [
    "### Plot Infections Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5db126fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "annotate = [\"0%\\nImmune\", \"20%\\nImmune\", \"40%\\nImmune\", \"60%\\nImmune\", \"80%\\nImmune\"]\n",
    "title = 'Every {freq} Days'\n",
    "titles = [title.format(freq = f) for f in [3,7,14,28]] + ['Symptomatic Only']\n",
    "titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "db35cfcc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the number needed to hit 10% of student population infected\n",
    "n10 = 0.1*692"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b8851b5",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c33a304b",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if t10<=112:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 70, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 40, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('InfTime_R15_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('InfTime_R15_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae9e4b03",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "18387bbb",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==6) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 6, 120, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 120, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 60, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('InfTime_R30_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('InfTime_R30_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87ef09be",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f59abb06",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==9) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if t10<=112:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 175, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 100, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('InfTime_R45_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('InfTime_R45_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a58f3a0d",
   "metadata": {},
   "source": [
    "### Plot Number of Positive Tests Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "64f94326",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e7d7fa62",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 21, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 21, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 10, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R15_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R15_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca2f11c5",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b1e34a8d",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==6) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 30, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 30, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 20, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R30_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R30_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d8af9658",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "181caa61",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==9) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 35, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 35, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 20, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R45_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R45_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "782aff8e",
   "metadata": {},
   "source": [
    "### Plot Number of Isolations Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6be6874",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "671458b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 75, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 75, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 40, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('IsoTime_R15_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('IsoTime_R15_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d879125",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9aacd75",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==6) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 110, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 110, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 60, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('IsoTime_R30_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('IsoTime_R30_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bd9c6d38",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d7ac4217",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==9) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 140, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        else:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 35, 140, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 80, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('IsoTime_R45_Allvax_hicom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('IsoTime_R45_Allvax_hicom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5b9a087a",
   "metadata": {},
   "source": [
    "## Low Community Transmission"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "44d7f4cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "outfile = 'allbeta_noNPI_vax_locom'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7d99a3c3",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pickle.load(open(outfile + \".pkl\", \"rb\" ))\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cda59558",
   "metadata": {},
   "source": [
    "### Plot Infections Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7b0b6b4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "annotate = [\"0%\\nImmune\", \"20%\\nImmune\", \"40%\\nImmune\", \"60%\\nImmune\", \"80%\\nImmune\"]\n",
    "title = 'Every {freq} Days'\n",
    "titles = [title.format(freq = f) for f in [3,7,14,28]] + ['Symptomatic Only']\n",
    "titles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "782818b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the number needed to hit 10% of student population infected\n",
    "n10 = 0.1*692"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2468a22",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75884368",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if t10<=112:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 37, 50, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 30, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "            \n",
    "plt.savefig('InfTime_R15_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('InfTime_R15_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b62263f3",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c356e9b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if t10<=112:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 37, 50, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 30, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "            \n",
    "plt.savefig('InfTime_R30_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('InfTime_R30_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ce02ea0",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "75e1a915",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_inf'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_inf'].mean().index, pltdf.groupby('tstep')['n_inf'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if t10<=112:\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 37, 50, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(175, 30, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Number Infectious', fontsize = 20)\n",
    "        if j==4:\n",
    "            axs2 = axs[i,j].twinx()\n",
    "            axs2.yaxis.set_ticks(np.arange(0,1,0.2))\n",
    "            axs2.yaxis.set_major_formatter(FuncFormatter('{0:.0%}'.format))\n",
    "            axs2.set_ylabel('Percent Infectious', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        axs2.tick_params(axis = 'y', labelsize = 12)\n",
    "            \n",
    "plt.savefig('InfTime_R45_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('InfTime_R45_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3877ebed",
   "metadata": {},
   "source": [
    "### Plot Number of Positive Tests Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed5f1136",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "958b6149",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 13, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 13, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 8, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R15_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R15_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e1c9d80",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "27662d4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==6) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 18, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 18, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 10, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R30_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R30_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6c5534d1",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfa3d671",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==9) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_test_pos'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_test_pos'].mean().index, pltdf.groupby('tstep')['n_test_pos'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 28, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 28, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 15, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Positive Tests', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "plt.savefig('TestsTime_R45_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "#plt.savefig('TestsTime_R45_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbf5fe40",
   "metadata": {},
   "source": [
    "### Plot Number of Isolations Over Time for Multiple Immunity Levels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "802fe622",
   "metadata": {},
   "source": [
    "#### R0 approx. 1.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "899c3555",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==3) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 55, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 55, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 30, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('IsoTime_R15_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('IsoTime_R15_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e087e73",
   "metadata": {},
   "source": [
    "#### R0 approx. 3.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "36932c31",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==6) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 80, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 80, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 40, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('IsoTime_R30_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('IsoTime_R30_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2902133",
   "metadata": {},
   "source": [
    "#### R0 approx. 4.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d17cc394",
   "metadata": {},
   "outputs": [],
   "source": [
    "mpl.rcParams['axes.titlesize'] = 'xx-large'\n",
    "mpl.rcParams['axes.labelsize'] = 'xx-large'\n",
    "\n",
    "f, axs = plt.subplots(5, 5, figsize = (25, 25), sharex = True, sharey = True)\n",
    "#f.suptitle('Testing Frequency', fontsize = 20, y = 0.93)\n",
    "f.subplots_adjust(wspace=0, hspace=0)\n",
    "\n",
    "# Loop through rows\n",
    "for (i, p_vax) in enumerate(df.p_vax.unique()):\n",
    "    \n",
    "    # Loop through the testing values (columns)\n",
    "    for (j, tf) in enumerate(df.test_freq.unique()):\n",
    "        \n",
    "        pltdf = df.loc[(df.beta==9) & (df.p_vax == p_vax) & (df.test_freq==tf)]\n",
    "        \n",
    "        if tf==0:\n",
    "            j = 4\n",
    "        else:\n",
    "            j = j-1\n",
    "        \n",
    "        # Plot individual runs\n",
    "        for k in range(1, pltdf['rep'].max() + 1):\n",
    "            axs[i,j].plot(pltdf[pltdf.rep == k]['tstep'].values, pltdf[pltdf.rep == k]['n_quar'].values, 'lightgrey', linewidth = 0.75)\n",
    "        \n",
    "        # Plot average run and time to 10% infected\n",
    "        axs[i,j].plot(pltdf.groupby('tstep')['n_quar'].mean().index, pltdf.groupby('tstep')['n_quar'].mean().values)\n",
    "        t10 = pltdf.loc[pltdf['n_cum_inf']>=n10].groupby('rep')['tstep'].first().mean()\n",
    "        if (t10<=112) & (t10<=70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 + 7, 110, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "        if (t10<=112) & (t10>70):\n",
    "            axs[i,j].axvline(x = t10, color = 'darkred', linestyle = 'dashed')\n",
    "            axs[i,j].text(t10 - 36, 110, str(np.round(t10)) + ' Days', color = 'darkred', fontsize = 14)\n",
    "            \n",
    "        # Annotate immunity levels if last column\n",
    "        if (j)==(len(titles)-1):\n",
    "            axs[i,j].text(140, 60, annotate[i], fontsize = 20, ha='center', va='center')\n",
    "            \n",
    "        # Only set title if first row\n",
    "        if i==0:\n",
    "            axs[i,j].set_title(titles[j], fontsize = 20)\n",
    "            \n",
    "        # Only set xlabel if last row\n",
    "        if i==4:\n",
    "            axs[i,j].set_xlabel('Time (Days)', fontsize = 20)\n",
    "            \n",
    "        # Only set ylabel if first column\n",
    "        if j==0:\n",
    "            axs[i,j].set_ylabel('Isolations', fontsize = 20)\n",
    "            \n",
    "        # Adjust ticks and labels\n",
    "        axs[i,j].tick_params(axis = 'x', labelsize = 12)\n",
    "        axs[i,j].tick_params(axis = 'y', labelsize = 12)\n",
    "        \n",
    "#plt.savefig('IsoTime_R45_Allvax_locom.eps', bbox_inches='tight', transparent=True);\n",
    "plt.savefig('IsoTime_R45_Allvax_locom.jpg', bbox_inches='tight', transparent=True);"
   ]
  }
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