{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from network.gibbs import *\n",
    "from network.network import pp_network, can_antenna_be_turned_on\n",
    "from collections import defaultdict\n",
    "from random import Random\n",
    "from numpy import matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mc = defaultdict(dict)\n",
    "random = Random(66)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "prec_network = 0\n",
    "\n",
    "for i, network in zip(range(10**5), get_random_networks(2, random)):\n",
    "    if network not in mc[prec_network]:\n",
    "        mc[prec_network][network] = 0\n",
    "    mc[prec_network][network] += 1\n",
    "    prec_network = network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "defaultdict(dict,\n",
       "            {0: {0: 964, 1: 3671, 2: 1844, 4: 1759, 6: 1835, 8: 938, 9: 3387},\n",
       "             1: {0: 891, 1: 3646, 2: 1832, 4: 1839, 6: 1729, 8: 938, 9: 3663},\n",
       "             2: {0: 1810, 2: 3548, 4: 3517, 6: 3611, 8: 1811},\n",
       "             4: {0: 1779, 2: 3519, 4: 3490, 6: 3486, 8: 1796},\n",
       "             6: {0: 1885, 2: 3554, 4: 3465, 6: 3475, 8: 1757},\n",
       "             8: {0: 3633, 1: 3553, 8: 3654, 9: 3572},\n",
       "             9: {0: 3436, 1: 3668, 8: 3518, 9: 3527}})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def get_prob(from_, to):\n",
    "    return mc[from_][to]/ sum(mc[from_].values())\n",
    "\n",
    "def get_matrix(mc):\n",
    "    n = len(mc)\n",
    "    mat = [[] for i in range(n)]\n",
    "    for i, from_ in enumerate(mc):\n",
    "        for j in enumerate(mc):\n",
    "            pass\n",
    "            "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "for key in mc:\n",
    "    print(key)\n",
    "    print( pp_network(key, 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "□-□\n",
      "■-□\n",
      "\n",
      "1 True\n"
     ]
    }
   ],
   "source": [
    "ant = 1\n",
    "print(get_prob(0, 2))\n",
    "print(ant, can_antenna_be_turned_on(ant, 4, 2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "0.5**4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "m = matrix([[1, 2], [3, 4]])\n",
    "v = matrix([[1, 3]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from numpy import std"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "42.73458667121028"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "std([1432, 1376, 1461, 1436, 1436, 1363, 1496])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
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