{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true,
    "run_control": {
     "frozen": false,
     "read_only": false
    }
   },
   "outputs": [],
   "source": [
    "import gym\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[2017-02-21 10:00:03,148] Making new env: CartPole-v0\n"
     ]
    }
   ],
   "source": [
    "env = gym.make('CartPole-v0').env"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "samples = np.array([env.reset() for _ in xrange(100000)]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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J5fU9LAAfADamlE7sKPv3AvVIkqQBKPEzxNHADyLiKxGxOSImI+LEHc4lSZIa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\nDAuSJCnLsCBJkrL+PzhKA+Iyk7eeAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1235860b50>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(6,12))\n",
    "for i in xrange(4):\n",
    "    ax = fig.add_subplot(4,1,i+1)\n",
    "    ax.hist(samples[i], normed=True)\n",
    "    \n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "del samples"
   ]
  },
  {
   "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": "2.7.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}