{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#import libraries\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.gridspec as gridspec\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Age Seroprevalence and Seroconversion Rate\n",
    "\n",
    "#read in the dataframes\n",
    "ageprev=pd.read_csv(\"ageseroprev.csv\") #age seroprevalence in the lab set all percentages are listed as whole numbers without '%' signs for ease of graphing\n",
    "ageprev.dropna()\n",
    "ageprev\n",
    "\n",
    "#set style\n",
    "sns.set(style=\"ticks\", color_codes=True)\n",
    "\n",
    "#read in SCR data with each age graph\n",
    "scrfacet=pd.read_csv(\"scrtable.csv\") #age seroprevalence in the lab set\n",
    "scrfacet\n",
    "\n",
    "#plot a facetgrid\n",
    "l=sns.FacetGrid(scrfacet, col=\"Method\", hue=\"Method\", sharex=True, sharey=True, xlim=[0,10], ylim=[0, 1.0])\n",
    "l=(l.map(plt.plot,\"Age (Years)\",\"MeanSCRAllAge\",color='black').set(xlim=(0,10), ylim=(0,1.0), \n",
    "\n",
    "#specify tick marks                                                                  \n",
    "xticks=[1,2,3,4,5,6,7,8,9], \n",
    "yticks=[0,0.1,0.3,0.5,0.7,0.9,1.0]))\n",
    "\n",
    "#scatter plot\n",
    "l=(l.map(plt.scatter,\"Age (Years)\",\"Proportion Seropositive (%)\").set(xlim=(0,10), ylim=(0,1.0), \n",
    "\n",
    "#specify tick marks                                                                       \n",
    "xticks=[1,2,3,4,5,6,7,8,9], \n",
    "yticks=[0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1.0]))\n",
    "\n",
    "#define axes\n",
    "plt.suptitle('Age Seroprevalence and Seroconversion Rate (n=2915)', fontweight='bold',  y=1.08)\n",
    "plt.ylabel=(\"Proportion Seropositive (%)\")\n",
    "\n",
    "#save graph as jpeg\n",
    "l.savefig(\"scrfacets.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#MFI HeatMap\n",
    "\n",
    "#set style\n",
    "sns.set(style=\"white\")\n",
    "\n",
    "#read in both dataframes\n",
    "#heatmap not log transformed\n",
    "heatmapnolog=pd.read_csv(\"heatmapnolog.csv\") \n",
    "#heatmap log transformed\n",
    "heatmaplog=pd.read_csv(\"heatmaplog.csv\")\n",
    "\n",
    "#define figure name\n",
    "h = plt.figure()\n",
    "\n",
    "#graph both log transformed and untransformed data to get both axes\n",
    "ax=sns.heatmap(heatmapnolog, cmap=(\"RdBu_r\"),cbar=True, xticklabels=True, yticklabels=False)\n",
    "ax=sns.heatmap(heatmaplog, cmap=(\"RdBu_r\"),cbar=True, xticklabels=True, yticklabels=False)\n",
    "\n",
    "#define axes\n",
    "ax.invert_yaxis()\n",
    "plt.xlabel(\"Antigen\")\n",
    "plt.title(\"(n=2915)\")\n",
    "plt.suptitle('Median Flouresence Intensity-Background', fontweight='bold' )\n",
    "plt.locator_params(nbins=10)\n",
    "plt.show()\n",
    "\n",
    "#save and export all lines to jpeg\n",
    "h.savefig(\"mfiheatmap.jpeg\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Seroprevalence in the Lab Dataset\n",
    "\n",
    "#read in lab seroprevalence graph data\n",
    "seroprevlab=pd.read_csv(\"seroprevlab.csv\") \n",
    "\n",
    "#setup a category plot graph\n",
    "h =sns.catplot(x='Assay Method', y='Seroprevalence (%)', data=seroprevlab, kind=\"bar\").set(xlim=(0,4), ylim=(0,100), yticks=[0,10, 20, 30,40,50,60,70,80,90,100])\n",
    "\n",
    "#define axes\n",
    "plt.suptitle('Seroprevalence in the Lab Set (n=2915)', fontweight='bold', y=1.08)\n",
    "plt.axis([-0.75, 3, 0, 100])\n",
    "plt.show()\n",
    "\n",
    "#save as a jpeg\n",
    "h.savefig(\"seroposlab.jpeg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Seroprevalence in Field Dataset\n",
    "\n",
    "#read in the dataframe\n",
    "seroposfieldeu=pd.read_csv(\"seroprevfield.csv\") \n",
    "seroposfieldeu #seropositivity across assays in the field set\n",
    "\n",
    "#graph a category plot\n",
    "s = sns.catplot(x='Assay Method', y=' Seroprevalence (%)', data=seroposfieldeu, kind=\"bar\").set(xlim=(0,4), ylim=(0,100), \n",
    "\n",
    "#define ticks and axes                                                                                                \n",
    "yticks=[0,10, 20, 30,40,50,60,70,80,90,100])\n",
    "plt.axis([-0.75, 3, 0, 100])\n",
    "plt.xticks(rotation=45)\n",
    "plt.axis([-1, 4, 0, 100])\n",
    "plt.suptitle('Seroprevalence in the Field Set (n=1914)', fontweight='bold', y=1.08)\n",
    "plt.show()\n",
    "\n",
    "#save as jpeg\n",
    "s.savefig(\"seroposfield.jpeg\")"
   ]
  }
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