{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "WARNING:\n",
    "\n",
    "\"fitting_parameters.h5\" need to be in the directory you are working on\n",
    "or there will be an error for importing mr_forecast in the next cell.\n",
    "\n",
    "If you don't want the file in this directory,\n",
    "change the mr_forecast.py line 16\n",
    "\n",
    "hyper_file = 'fitting_parameters.h5' \n",
    "\n",
    "->\n",
    "\n",
    "hyper_file = [directory of fitting parameter file]+'fitting_parameters.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import mr_forecast as mr\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "================================\n",
    "\n",
    "predict the mean and std of radius given those of the mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Terran 97.0 %, Neptunian 3.0 %, Jovian 0.0 %, Star 0.0 %\n"
     ]
    }
   ],
   "source": [
    "Rmedian, Rplus, Rminus = mr.Mstat2R(mean=1.0, std=0.1, unit='Earth', sample_size=100, classify='Yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "R = 1.00 (+ 0.12 - 0.10) REarth\n"
     ]
    }
   ],
   "source": [
    "print 'R = %.2f (+ %.2f - %.2f) REarth' % (Rmedian, Rplus, Rminus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "================================\n",
    "\n",
    "predict a vector of radius given a vector of mass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Terran 100.0 %, Neptunian 0.0 %, Jovian 0.0 %, Star 0.0 %\n"
     ]
    }
   ],
   "source": [
    "M1 = np.loadtxt('demo_mass.dat')\n",
    "R1 = mr.Mpost2R(M1, unit='Earth', classify='Yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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F+gxFimVQoao2JZ5BVpa5ZsreJlG077nR91m0GPtZVomnUCMXhKKRCyQkTbOQ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\nHhERCer/A6IO23M4mdSJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d400f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.log10(M1), np.log10(R1), 'bx')\n",
    "plt.xlabel(r'$log_{10}\\ M/M_{\\oplus}$')\n",
    "plt.ylabel(r'$log_{10}\\ R/R_{\\oplus}$')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "================================\n",
    "\n",
    "predict the mean and std of mass given those of the radius"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Terran 69.0 %, Neptunian 31.0 %, Jovian 0.0 %, Star 0.0 %\n"
     ]
    }
   ],
   "source": [
    "Mmedian, Mplus, Mminus = mr.Rstat2M(mean=0.1, std=0.01, unit='Jupiter', sample_size=100, grid_size=1e3, classify='Yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "M = 0.005 (+ 0.004 - 0.002) MEarth\n"
     ]
    }
   ],
   "source": [
    "print 'M = %.3f (+ %.3f - %.3f) MEarth' % (Mmedian, Mplus, Mminus)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "================================\n",
    "\n",
    "predict a vector of mass given a vector of radius"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Terran 72.0 %, Neptunian 28.0 %, Jovian 0.0 %, Star 0.0 %\n"
     ]
    }
   ],
   "source": [
    "R2 = np.loadtxt('demo_radius.dat')\n",
    "M2 = mr.Rpost2M(R2, unit='Earth', grid_size=1e3, classify='Yes')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x10d2bb690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(np.log10(M2))\n",
    "plt.xlabel(r'$log_{10}\\ M/M_{\\odot}$')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}