Updated for challenge 9

[cipher-tools.git] / .ipynb_checkpoints / challenge6-checkpoint.ipynb

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%matplotlib inline\n",
      "import matplotlib.pyplot as plt\n",
      "\n",
      "from cipherbreak import *\n",
      "with open('2013/mona-lisa-words.txt') as f:\n",
      "    mlwords = [line.rstrip() for line in f]\n",
      "mltrans = collections.defaultdict(list)\n",
      "for word in mlwords:\n",
      "    mltrans[transpositions_of(word)] += [word]\n",
      "c6a = open('2013/6a.ciphertext').read()\n",
      "c6b = open('2013/6b.ciphertext').read()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c1a = open('2013/1a.ciphertext').read()\n",
      "c1b = open('2013/1b.ciphertext').read()\n",
      "c2a = open('2013/2a.ciphertext').read()\n",
      "c2b = open('2013/2b.ciphertext').read()\n",
      "c3a = open('2013/3a.ciphertext').read()\n",
      "c3b = open('2013/3b.ciphertext').read()\n",
      "c4a = open('2013/4a.ciphertext').read()\n",
      "c4b = open('2013/4b.ciphertext').read()\n",
      "c5a = open('2013/5a.ciphertext').read()\n",
      "c5b = open('2013/5b.ciphertext').read()\n",
      "\n",
      "p1a = caesar_decipher(c1a, 8)\n",
      "p1b = caesar_decipher(c1b, 14)\n",
      "p2a = affine_decipher(c2a, 3, 3, True)\n",
      "p2b = caesar_decipher(c2b, 6)\n",
      "p3a = affine_decipher(c3a, 7, 8, True)\n",
      "p3b = keyword_decipher(c3b, 'louvigny', 2)\n",
      "p4a = keyword_decipher(c4a, 'montal', 2)\n",
      "p4b = keyword_decipher(c4b, 'salvation', 2)\n",
      "p5a = keyword_decipher(c5a, 'alfredo', 2)\n",
      "p5b = vigenere_decipher(sanitise(c5b), 'florence')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_frequency_histogram(frequencies(sanitise(c6a)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stderr",
       "text": [
        "/home/neil/.virtualenvs/p3basic/lib/python3.3/site-packages/matplotlib/figure.py:372: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
        "  \"matplotlib is currently using a non-GUI backend, \"\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xaebe642c>"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c6af = frequencies(sanitise(c6a))\n",
      "plot_frequency_histogram(c6af, sort_key=lambda l: c6af[l])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xae9d774c>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_frequency_histogram(normalised_english_counts, sort_key=lambda l: normalised_english_counts[l])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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3HT58WJJa/g3mlltuUVlZmXbt2qWcnJw268aPH69ly5ZpwoQJGj9+vF5++WWN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\nwv8DbMnA/BWkp54AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0xaea2d2cc>"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c6bf = frequencies(sanitise(c6b))\n",
      "plot_frequency_histogram(c6bf, sort_key=lambda l: c6bf[l])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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QoEFKSEhQZGSkZsyYoY0bN4Z7NcbyF1C3B8lC3Ros14LEe+gs9Frroyeh9JrakGvbsm1q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\n",
       "text": [
        "<matplotlib.figure.Figure at 0xaea3550c>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_frequency_histogram(c6bf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xaea9556c>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot_frequency_histogram(normalised_english_counts)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0xae9bd72c>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c6a"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "'CPYYL GVVIR PDDVU BCSUP QOWPW SYBYP ODBCS PBBPR CSIOZ PTSTV HYVTW PYOZC OGCRV TTPUI BVGVS YOUGZ ZSRYS BPYLY SHSYY OUGBV BCSWP OUBOU GPUIR DSPYD LTSUB OVUOU GZPYP ZSSTZ DONSB CSLNU SJPAV EBBCS ZRPTV EYHYO SUIDL ZZVHH ORSYJ PZWDP UUOUG BVWED DBCSL WORNS IEWCS YBYPO DBCSU OGCBP HBSYZ CSJSU BTOZZ OUGAE BLVER PUYSP IPAVE BBCPB OUBCS OYYSW VYBZB ODDUV MVLVU GSBBO UGPRR SZZBV BCSVY OGOUP DTOZZ TVUPO UBCSG PDDSY LPUIO PTASG OUUOU GBVBC OUNJS TOGCB USSIB VYVDD VEBPA DPRNA PGMVA LVEJP UBBVI VOBVY ZCPDD OALBC SJPLO JPZZE YWYOZ SIALB COZYS WVYBB CSVBC SYWPW SYZJS CPFSH YVTBC SUPQO ZPBBC OZDSF SDPYS SURYL WBSIE ZOUGA OHOIV YWDPL HPOYZ BLDSR OWCSY ZBCOZ VUSOZ UBTPL ASBCS ROWCS YRDSY NJPZV HHIEB LBCPB IPLJS GVBDE RNL\\n'"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "len(sanitise(c6b))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "1573"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "c6as = sanitise(c6a)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 35
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "frequencies(ngrams(c6as, 2))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 48,
       "text": [
        "Counter({'bc': 21, 'cs': 20, 'ou': 15, 'sy': 12, 'oz': 10, 'ug': 10, 'bv': 8, 'ub': 8, 'bb': 7, 'su': 7, 'py': 6, 'pu': 6, 'vy': 6, 'jp': 6, 'dd': 6, 'zz': 6, 'ys': 6, 'yo': 6, 've': 6, 'ds': 5, 'eb': 5, 'po': 5, 'bo': 5, 'si': 5, 'yz': 5, 'vu': 5, 'vb': 5, 'co': 5, 'cp': 5, 'wp': 4, 'dp': 4, 'pz': 4, 'pl': 4, 'pd': 4, 'pb': 4, 'js': 4, 'og': 4, 'bp': 4, 'zb': 4, 'sb': 4, 'yl': 4, 'yb': 4, 'uo': 4, 'ui': 4, 'up': 4, 'hy': 3, 'wc': 3, 'pt': 3, 'pr': 3, 'sw': 3, 'bl': 3, 'zc': 3, 'rp': 3, 'zp': 3, 'zs': 3, 'zv': 3, 'od': 3, 'ow': 3, 'gb': 3, 'gc': 3, 'gv': 3, 'gp': 3, 'lb': 3, 'sr': 3, 'ss': 3, 'sp': 3, 'rn': 3, 'st': 3, 'sj': 3, 'lv': 3, 'db': 3, 'sg': 3, 'to': 3, 'ie': 3, 'tv': 3, 'yy': 3, 'yp': 3, 'al': 3, 'yv': 3, 'yw': 3, 'us': 3, 'vt': 3, 'vh': 3, 'pa': 3, 'wv': 2, 'ws': 2, 'ip': 2, 'wd': 2, 'ho': 2, 'hh': 2, 'pw': 2, 'er': 2, 'mv': 2, 'oy': 2, 'ry': 2, 'lw': 2, 'so': 2, 'qo': 2, 'by': 2, 'bs': 2, 'bt': 2, 'zd': 2, 'rs': 2, 'zo': 2, 'or': 2, 'rd': 2, 'ga': 2, 'go': 2, 'ey': 2, 'gz': 2, 'sz': 2, 'ro': 2, 'sv': 2, 'dv': 2, 'sh': 2, 'do': 2, 'sl': 2, 'dl': 2, 'io': 2, 'ts': 2, 'ir': 2, 'tp': 2, 'iv': 2, 'as': 2, 'av': 2, 'nj': 2, 'uu': 2, 'ns': 2, 'fs': 2, 'ib': 2, 'pq': 2, 'vi': 2, 'cb': 2, 'hs': 1, 'hp': 1, 'wy': 1, 'we': 1, 'wb': 1, 'wo': 1, 'hi': 1, 'lj': 1, 'lo': 1, 'du': 1, 'pi': 1, 'ph': 1, 'ed': 1, 'pf': 1, 'zj': 1, 'pg': 1, 'lp': 1, 'oa': 1, 'lt': 1, 'yn': 1, 'nl': 1, 'vv': 1, 'lz': 1, 'ze': 1, 'ao': 1, 'bi': 1, 'ap': 1, 'bd': 1, 'bz': 1, 'de': 1, 'bu': 1, 'on': 1, 'oj': 1, 'oh': 1, 'oi': 1, 'rr': 1, 'ob': 1, 'rv': 1, 'zr': 1, 'zt': 1, 'zw': 1, 'rc': 1, 'op': 1, 'dt': 1, 'gm': 1, 'ej': 1, 'gs': 1, 'zu': 1, 'la': 1, 'lg': 1, 'ld': 1, 'ov': 1, 'ly': 1, 'sf': 1, 'sd': 1, 'lh': 1, 'os': 1, 'ia': 1, 'ta': 1, 'id': 1, 'tz': 1, 'tw': 1, 'tt': 1, 'ad': 1, 'ae': 1, 'yr': 1, 'yh': 1, 'yj': 1, 'yd': 1, 'ln': 1, 'un': 1, 'na': 1, 'uy': 1, 'nu': 1, 'uv': 1, 'ez': 1, 'ur': 1, 'tb': 1, 'vw': 1, 'ew': 1, 'vs': 1, 'sc': 1, 'hb': 1, 'vd': 1, 'vg': 1, 'va': 1, 'vm': 1, 'vl': 1, 'vo': 1, 'zy': 1, 'cr': 1})"
       ]
      }
     ],
     "prompt_number": 48
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "' '.join(segment(letters(c6a).translate(''.maketrans({'B':'t', 'C':'h', 'S':'e', 'O':'i', 'U':'n', 'G':'g', 'A':'b', 'V':'o', 'N':'k', 'J':'w', 'T':'m', 'I':'d', 'P':'a', 'W':'p', 'R':'c', 'Y':'r', 'L':'y', 'D':'l', 'H':'f', 'Z':'s', 'Q':'z', 'E':'u', 'F':'v', 'M':'j'}))))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 65,
       "text": [
        "'harry good call on the nazi paper trail the attached is a memo from paris high command to goering s secretary referring to the painting and clearly mentioning sara seems like they knew about the scam our friendly ss officer was planning to pull they picked up her trail the night after she went missing but you can read about that in their report still no joy on getting access to the original miss mona in the gallery and i am beginning to think we might need to rollout a black bag job you want to do it or shall i by the way i was surprised by this report the other papers we have from the nazis at this level are encrypted using bifid or playfair style ciphers this one isnt maybe the cipher clerk was off duty that day we got lucky'"
       ]
      }
     ],
     "prompt_number": 65
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "trans={'B':'t', 'C':'h', 'S':'e', 'O':'i', 'U':'n', 'G':'g', 'A':'b', 'V':'o', 'N':'k', 'J':'w', 'T':'m', 'I':'d', 'P':'a', 'W':'p', 'R':'c', 'Y':'r', 'L':'y', 'D':'l', 'H':'f', 'Z':'s', 'Q':'z', 'E':'u', 'F':'v', 'M':'j'}"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 66
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sorted(trans.keys(), key=lambda k: trans[k])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 84,
       "text": [
        "['P',\n",
        " 'A',\n",
        " 'R',\n",
        " 'I',\n",
        " 'S',\n",
        " 'H',\n",
        " 'G',\n",
        " 'C',\n",
        " 'O',\n",
        " 'M',\n",
        " 'N',\n",
        " 'D',\n",
        " 'T',\n",
        " 'U',\n",
        " 'V',\n",
        " 'W',\n",
        " 'Y',\n",
        " 'Z',\n",
        " 'B',\n",
        " 'E',\n",
        " 'F',\n",
        " 'J',\n",
        " 'L',\n",
        " 'Q']"
       ]
      }
     ],
     "prompt_number": 84
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "keyword_decipher(c6as, 'parishighcommand', 2)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 86,
       "text": [
        "'harrygoodcallonthenazipapertrailtheattachedisamemofromparishighcommandtogoeringssecretaryreferringtothepaintingandclearlymentioningsaraseemsliketheyknewaboutthescamourfriendlyssofficerwasplanningtopulltheypickeduphertrailthenightaftershewentmissingbutyoucanreadaboutthatintheirreportstillnojoyongettingaccesstotheoriginalmissmonainthegalleryandiambeginningtothinkwemightneedtorolloutablackbagjobyouwanttodoitorshallibythewayiwassurprisedbythisreporttheotherpaperswehavefromthenazisatthislevelareencryptedusingbifidorplayfairstyleciphersthisoneisntmaybethecipherclerkwasoffdutythatdaywegotlucky'"
       ]
      }
     ],
     "prompt_number": 86
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}