{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "dbb672ce",
   "metadata": {},
   "source": [
    "======================== Import Packages =========================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "68957f4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys, os, pdb\n",
    "import numpy as np\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "from astropy.table import Table, join\n",
    "from lifelines import KaplanMeierFitter\n",
    "from lifelines.statistics import logrank_test\n",
    "import csv"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10b6a675",
   "metadata": {},
   "source": [
    "========================== Define Fuctions =========================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a26c3ef9",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calc_KME(region, mdust, ddet):\n",
    "\n",
    "   \"\"\"\n",
    "    PURPOSE:    Calculate the KME\n",
    "\n",
    "    INPUT:      region = region name (str)\n",
    "                mdust = dust mass; non-detections are 3-sigma upper limits (array of floats)\n",
    "                ddet = detection flag; 1=detected, 0=undetected (array of floats)\n",
    "\n",
    "    OUTPUT:     KME output for plotting\n",
    "\n",
    "    \"\"\"\n",
    "   \n",
    "   dfrac = float(len(ddet[ddet==1]) )/ len(ddet)\n",
    "   kmf = KaplanMeierFitter()\n",
    "   kmf.fit(mdust, ddet)\n",
    "   \n",
    "   k = kmf.survival_function_\n",
    "   x = np.array(k.index)\n",
    "   y = dfrac * np.array(k.values[:,0])\n",
    "   \n",
    "   kc = kmf.confidence_interval_\n",
    "   yu = dfrac * kc.values[:,0]\n",
    "   yl = dfrac * kc.values[:,1]\n",
    "   \n",
    "   print('\\n>>> ' + region)\n",
    "   print('     median = {0:.2f} '.format(dfrac * kmf.median_survival_time_))\n",
    "   print('     mean   = {0:.2f} '.format(np.trapz(y, x=x)))\n",
    "   \n",
    "   return x, y, yu, yl"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4297228",
   "metadata": {},
   "source": [
    "============================= Code =================================="
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "31500f7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### LOAD IN TABLES \n",
    "TL = Table.read('../output/data_lup.txt', format='ascii.ipac')\n",
    "TT = Table.read('../output/data_tau.txt', format='ascii.ipac')\n",
    "TU = Table.read('../output/data_usc.txt', format='ascii.ipac')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "57c793c6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      ">>> lup\n",
      "     median = 4.14 \n",
      "     mean   = 14.03 \n",
      "\n",
      ">>> usc\n",
      "     median = 0.43 \n",
      "     mean   = 3.34 \n",
      "\n",
      ">>> tau\n",
      "     median = 5.85 \n",
      "     mean   = 14.99 \n"
     ]
    }
   ],
   "source": [
    "### GET KME \n",
    "x_lup, y_lup, yl_lup, yu_lup = calc_KME('lup', TL['MDust'], TL['Det'])\n",
    "x_usc, y_usc, yl_usc, yu_usc = calc_KME('usc', TU['MDust'], TU['Det'])\n",
    "x_tau, y_tau, yl_tau, yu_tau = calc_KME('tau', TT['MDust'], TT['Det'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c835d610",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### PLOT KME DISTRIBUTIONS\n",
    "plt.close('all')\n",
    "mpl.rc('xtick',labelsize=15) \n",
    "mpl.rc('ytick',labelsize=15)\n",
    "mpl.rc('xtick.major',size=5,pad=7,width=1)\n",
    "mpl.rc('ytick.major',size=5,pad=7,width=1)\n",
    "mpl.rc('axes',linewidth=1)\n",
    "mpl.rc('lines',markersize=5)    \n",
    "fig = plt.figure(figsize = (8,6))\n",
    "ax = fig.add_subplot(111)\n",
    "ax.set_xscale('log')\n",
    "ax.set_xlim(0.03,200)\n",
    "ax.set_ylim(0.0,1.0)\n",
    "ax.set_ylabel(r'$\\mathregular{P \\geq M_{dust}}$',fontsize=17)\n",
    "ax.set_xlabel(r'$\\mathregular{M_{dust}}$'+' '+r'$\\mathregular{[M_{\\oplus}]}$',fontsize=17)\n",
    "ax.fill_between(x_lup,yl_lup,yu_lup,facecolor='dodgerblue',alpha=0.3,lw=0,label='Lupus')\n",
    "ax.fill_between(x_tau,yl_tau,yu_tau,facecolor='purple',alpha=0.3,lw=0,label='Taurus')\n",
    "ax.fill_between(x_usc,yl_usc,yu_usc,facecolor='green',alpha=0.3,lw=0,label='Upper Sco')\n",
    "ax.legend(loc=1, prop={'size': 16})\n",
    "fig.savefig('../output/figure_08.png',bbox_inches='tight',dpi=100)"
   ]
  }
 ],
 "metadata": {
  "jupytext": {
   "cell_metadata_filter": "-all",
   "main_language": "python",
   "notebook_metadata_filter": "-all"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
