2014/2014-challenge2.ipynb

   1 {
   2  "cells": [
   3   {
   4    "cell_type": "code",
   5    "execution_count": 3,
   6    "metadata": {
   7     "collapsed": false
   8    },
   9    "outputs": [],
  10    "source": [
  11     "import os,sys,inspect\n",
  12     "currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))\n",
  13     "parentdir = os.path.dirname(currentdir)\n",
  14     "sys.path.insert(0,parentdir) \n",
  15     "\n",
  16     "import matplotlib.pyplot as plt\n",
  17     "import pandas as pd\n",
  18     "import collections\n",
  19     "import string\n",
  20     "%matplotlib inline\n",
  21     "\n",
  22     "from cipherbreak import *\n",
  23     "\n",
  24     "c2a = open('2a.ciphertext').read()\n",
  25     "c2b = open('2b.ciphertext').read()"
  26    ]
  27   },
  28   {
  29    "cell_type": "code",
  30    "execution_count": 4,
  31    "metadata": {
  32     "collapsed": false
  33    },
  34    "outputs": [
  35     {
  36      "data": {
  37       "text/plain": [
  38        "<matplotlib.axes._subplots.AxesSubplot at 0x7f8012c71eb8>"
  39       ]
  40      },
  41      "execution_count": 4,
  42      "metadata": {},
  43      "output_type": "execute_result"
  44     },
  45     {
  46      "data": {
  47       "image/png": 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UWB3jIX01cA8wF3gwIram/LuAjZL2AqNkAYiIeEbSzcAjqVxfmoQ2M7NJVHMo6XjgoaTp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\nzAocGMzMrOD/A5ZV4vqjDJn1AAAAAElFTkSuQmCC\n",
  48       "text/plain": [
  49        "<matplotlib.figure.Figure at 0x7f8012c71898>"
  50       ]
  51      },
  52      "metadata": {},
  53      "output_type": "display_data"
  54     }
  55    ],
  56    "source": [
  57     "freqs = pd.Series(english_counts)\n",
  58     "freqs.plot(kind='bar')"
  59    ]
  60   },
  61   {
  62    "cell_type": "code",
  63    "execution_count": 5,
  64    "metadata": {
  65     "collapsed": false
  66    },
  67    "outputs": [
  68     {
  69      "data": {
  70       "text/plain": [
  71        "((5, 25, True), -761.8388033231918)"
  72       ]
  73      },
  74      "execution_count": 5,
  75      "metadata": {},
  76      "output_type": "execute_result"
  77     }
  78    ],
  79    "source": [
  80     "key_a, score = affine_break(c2a)\n",
  81     "key_a, score"
  82    ]
  83   },
  84   {
  85    "cell_type": "code",
  86    "execution_count": 6,
  87    "metadata": {
  88     "collapsed": false
  89    },
  90    "outputs": [
  91     {
  92      "name": "stdout",
  93      "output_type": "stream",
  94      "text": [
  95       "DEAR MARK, \n",
  96       "\n",
  97       "THANKS FOR THE LATEST REPORT FROM THE ON-SITE TEAM. IT SHOWS THAT THE SHIPBOARD GPS SYSTEM WAS COMPLETELY SCRAMBLED SO WE ARE NOT GOING TO BE ABLE TO TRACE HER MOVEMENTS FROM THAT. DO WE HAVE ANY ODD TRACES FROM ONSHORE RADAR THAT GIVE A HINT OF WHERE SHE MIGHT HAVE BEEN? \n",
  98       "\n",
  99       "THE COMMENT IN THE LAST MESSAGE THAT THE PIRATES COMPLETED THE SURVEY EVEN THOUGH THEY HAD MOVED SOUTH TO AVOID DETECTION SHOULD HAVE TOLD ME THAT THE SURVEY WAS NOT GEOGRAPHIC. AT FIRST I THOUGHT IT MIGHT HAVE BEEN REFERRING TO A TELECOMS SURVEY SINCE YOU MENTIONED THE LONG AERIAL, BUT ACTUALLY THE ATTACHED MESSAGE IS VERY REVEALING. STILL NOT SURE WHAT THE SURVEY WAS FOR THOUGH, AND HOW THAT IS CONNECTED TO THE MISSING SUPERSTRUCTURE. CAN YOU GET ME ANY PICTURES? \n",
 100       "\n",
 101       "HARRY \n",
 102       "\n"
 103      ]
 104     }
 105    ],
 106    "source": [
 107     "print(affine_decipher(c2a, key_a[0], key_a[1]))"
 108    ]
 109   },
 110   {
 111    "cell_type": "code",
 112    "execution_count": 7,
 113    "metadata": {
 114     "collapsed": false
 115    },
 116    "outputs": [
 117     {
 118      "data": {
 119       "text/plain": [
 120        "(('flag', <KeywordWrapAlphabet.from_largest: 3>), -367.81492429457404)"
 121       ]
 122      },
 123      "execution_count": 7,
 124      "metadata": {},
 125      "output_type": "execute_result"
 126     }
 127    ],
 128    "source": [
 129     "key_b, score = keyword_break_mp(c2b)\n",
 130     "key_b, score"
 131    ]
 132   },
 133   {
 134    "cell_type": "code",
 135    "execution_count": 8,
 136    "metadata": {
 137     "collapsed": false
 138    },
 139    "outputs": [
 140     {
 141      "name": "stdout",
 142      "output_type": "stream",
 143      "text": [
 144       "calm weather allowed us to complete the hull survey and establish its integrity no major remedial works were required and the pumps and extra bulkheads were installed out in deep waters over the next five days we are now testing the system for reliability and safety before moving on to phase three of the operation operation trojan remains on target\n"
 145      ]
 146     }
 147    ],
 148    "source": [
 149     "print(' '.join(segment(sanitise(keyword_decipher(c2b, key_b[0], key_b[1])))))"
 150    ]
 151   },
 152   {
 153    "cell_type": "code",
 154    "execution_count": 9,
 155    "metadata": {
 156     "collapsed": false
 157    },
 158    "outputs": [
 159     {
 160      "data": {
 161       "text/plain": [
 162        "<matplotlib.axes._subplots.AxesSubplot at 0x7f800850a358>"
 163       ]
 164      },
 165      "execution_count": 9,
 166      "metadata": {},
 167      "output_type": "execute_result"
 168     },
 169     {
 170      "data": {
 171       "image/png": 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4L8A/n67o8oxVzlJuq9c1S5lFrWuWMota1yxlFrWuWcpsZF2zlJmt3FoC+4XA/QPzD3TL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\nRU5ErkJggg==\n",
 172       "text/plain": [
 173        "<matplotlib.figure.Figure at 0x7f800b778a58>"
 174       ]
 175      },
 176      "metadata": {},
 177      "output_type": "display_data"
 178     }
 179    ],
 180    "source": [
 181     "freqs_2b = pd.Series(collections.Counter([l.lower() for l in c2b if l in string.ascii_letters]))\n",
 182     "freqs_2b.plot(kind='bar')"
 183    ]
 184   },
 185   {
 186    "cell_type": "code",
 187    "execution_count": null,
 188    "metadata": {
 189     "collapsed": false
 190    },
 191    "outputs": [],
 192    "source": []
 193   }
 194  ],
 195  "metadata": {
 196   "kernelspec": {
 197    "display_name": "Python 3",
 198    "language": "python",
 199    "name": "python3"
 200   },
 201   "language_info": {
 202    "codemirror_mode": {
 203     "name": "ipython",
 204     "version": 3
 205    },
 206    "file_extension": ".py",
 207    "mimetype": "text/x-python",
 208    "name": "python",
 209    "nbconvert_exporter": "python",
 210    "pygments_lexer": "ipython3",
 211    "version": "3.4.3"
 212   }
 213  },
 214  "nbformat": 4,
 215  "nbformat_minor": 0
 216 }