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Done Cadenus ciphers, but not automated breaking
[cipher-training.git] / 2014-challenge8.ipynb
1 {
2 "metadata": {
3 "name": "",
4 "signature": "sha256:552bea7734ea4d4e21f21be2dca0f09009e1c1eb9a767ab8c6c8097144b76db4"
5 },
6 "nbformat": 3,
7 "nbformat_minor": 0,
8 "worksheets": [
9 {
10 "cells": [
11 {
12 "cell_type": "code",
13 "collapsed": false,
14 "input": [
15 "import matplotlib.pyplot as plt\n",
16 "import pandas as pd\n",
17 "import collections\n",
18 "import string\n",
19 "%matplotlib inline\n",
20 "\n",
21 "from cipherbreak import *\n",
22 "\n",
23 "c8a = open('2014/8a.ciphertext').read()\n",
24 "c8b = open('2014/8b.ciphertext').read().strip()"
25 ],
26 "language": "python",
27 "metadata": {},
28 "outputs": [],
29 "prompt_number": 1
30 },
31 {
32 "cell_type": "code",
33 "collapsed": false,
34 "input": [
35 "freqs = pd.Series(english_counts)\n",
36 "freqs.plot(kind='bar')"
37 ],
38 "language": "python",
39 "metadata": {},
40 "outputs": [
41 {
42 "metadata": {},
43 "output_type": "pyout",
44 "prompt_number": 2,
45 "text": [
46 "<matplotlib.axes.AxesSubplot at 0x7f2de7d75e10>"
47 ]
48 },
49 {
50 "metadata": {},
51 "output_type": "display_data",
52 "png": 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aiBBCtJ9eeHdM5EH0Ut2+l+Yi0pH3Gnze599O9FtMQgghvMlpgiilVwRah+yluYSqCTUu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\nTkSuQmCC\n",
53 "text": [
54 "<matplotlib.figure.Figure at 0x7f2e1c1ae978>"
55 ]
56 }
57 ],
58 "prompt_number": 2
59 },
60 {
61 "cell_type": "code",
62 "collapsed": false,
63 "input": [
64 "freqs_8a = pd.Series(collections.Counter([l.lower() for l in c8a if l in string.ascii_letters]))\n",
65 "freqs_8a.plot(kind='bar')"
66 ],
67 "language": "python",
68 "metadata": {},
69 "outputs": [
70 {
71 "metadata": {},
72 "output_type": "pyout",
73 "prompt_number": 3,
74 "text": [
75 "<matplotlib.axes.AxesSubplot at 0x7f2de514fba8>"
76 ]
77 },
78 {
79 "metadata": {},
80 "output_type": "display_data",
81 "png": 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fluiz+DlwH+7N91jcm94DmQrHA0le+3FvlvPAp4AvAm9KifM6YAn3qamw1WLl\n4GSHJs5b+zzwfwOPNTJ0h4H/ynnuJ+I+Nh3G+Ut5H0nB+Ymdg01fodg74uOB30juX0m6fTEKp+G8\n5cO4F/51Kf0aOc+zt7yUvGjkPL635Hi34OyYot/2baQs35ujO5X+A4154yUtTl68kHHpwwm4Pcdv\n4a78uRZ3LGJHyXEaPfd/jpvw7s/o/zqc//5Q4JPAx8l/Hb8DN1n/FPg6zoq5Bjcxp3EDcDnuTeQh\nwL/h3sBfkqF5A/BK3JvJ+3E7cPfj3pC+w8o979ckz9vhVODPgT/KqUeIqeFi3Bu3mGzeTvi3CWeA\ns3A7eD/L6XvakGWvzNFcCDwq5bFhBztHwtoetxBVsAe3x2PFKhLxOAv36eRU3Pa/OrldNc6kRsWC\nxy1E1Tw/v4uoKcfijnFdT7YNI4QQQgghhBBCCCGEEEIIIYQQQgghxITz/ykaLXLziWAXAAAAAElF\nTkSuQmCC\n",
82 "text": [
83 "<matplotlib.figure.Figure at 0x7f2de5155a58>"
84 ]
85 }
86 ],
87 "prompt_number": 3
88 },
89 {
90 "cell_type": "code",
91 "collapsed": false,
92 "input": [
93 "c8as = sanitise(c8a)\n",
94 "c8as"
95 ],
96 "language": "python",
97 "metadata": {},
98 "outputs": [
99 {
100 "metadata": {},
101 "output_type": "pyout",
102 "prompt_number": 4,
103 "text": [
104 "'nyvlggsyglchxfeuytqcesqxpziufiggrbjhpayncruyfpsxufiupskyrectmmcncruyregxigrlglbtiblmecebzsvrlpuxpbibjajrljreobajrlufigjehbezywtmgjyxfqxictsgrdgtbjafyoocwtmjblctwwucqmgofrlfmrfrlfwlbtijlwuypmchjqxicrfchumtsmzjbimyvhcuvyrugxjcwpdtpuisrlfdhbaencyqumufeogrhcrjmytqsmsxjmrcsxjrmttiswzvjrfpecjitnidgemdssaitasvjhuyofgxpsxgmvvqfvrxiyxxmymbxfjpufigbeufeuuiiyzfavbaofbxicmsamqfisqwpgrtribbmtskhcwuuimcxufinbitrvpwxsmnbljppytuixgpmlifbgpmtfpeugsodvpkxicsnyrjeswcvokioreoyvnchggkirishiuyrerlfdpjeluasorvpjwzqxfkwgpsnyhsmrfkiblaigpfuiociersflwvpiuusufmoewpliufeuuiemrprwflhdpmuggbjmodsskeugsoygsmwtrlfzecypnyreyftrvbgxblhuusufeuuivqiblsoavjrmdyplcchcrfpeugsonvprsdmpplxiyxdfeolimemwcrufimczfjsgasnkmukiorxicjeylbtitfsxlmobiwcppnmoexigwqjeogenqyscxiyxufizummjvfgrtreucxictpuisqyqnpzumufmoyjfuqplxiqfvrajrlmsglrlfwajjpomxhsitqxiyxxcoomabzsvrmuyreuixgpmnyugxpsxpdfvqmocwtdssjsoeiomyhfxpasncyqumufeqjeomjpsvpurumiynppgxjrmorlfkiblxjkixcrpuoomaufeurlfgvigkicwuqidsvjrcdmqnsrjaeugsoqescioavznxfbytgrhygbbioswdgticvtmafaeoqxbpxisrugrhrlsmyhfxichbrecywfdssmxicvjlxfpgfnxtuidyrdpedixigwnycccxicfscelrlsmyhfaffewcffcrmmslgrhdssgrufiggkirehymoqxufigbemcxtlsuqgscajryqypmrlfzitrlbpvz'"
105 ]
106 }
107 ],
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109 },
110 {
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113 "input": [
114 "key_a, score = vigenere_frequency_break(c8as)\n",
115 "key_a, score"
116 ],
117 "language": "python",
118 "metadata": {},
119 "outputs": [
120 {
121 "metadata": {},
122 "output_type": "pyout",
123 "prompt_number": 5,
124 "text": [
125 "('bye', -1461.9840974270046)"
126 ]
127 }
128 ],
129 "prompt_number": 5
130 },
131 {
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135 "' '.join(segment(vigenere_decipher(c8as, key_a)))"
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137 "language": "python",
138 "metadata": {},
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140 {
141 "metadata": {},
142 "output_type": "pyout",
143 "prompt_number": 6,
144 "text": [
145 "'mark i cracked what appears to be the final document about the trojan deployment and i think i have an idea about how to deal with it and with the flag day associates the principal weakness of any system like the one they have installed is the need to provide large quantities of power the fda came up with an ingenious solution but it is very vulnerable special forces could take it out for us but that would tell the fda that we have cracked their ciphers so instead i suggest we let them destroy trojan for us we will need cooperation from the omani government an armed fighter jet and the flight control systems from a drone meanwhile we need to ensure two things one that we do not send critical information across the ba balm and abstrait and two that we use an on critical key generation protocol on that channel given the level of commitment the fda have shown in developing this plan i am sure that they will reinstate the powersupply within a few months but with luck they will not guess that we know about it and we will put it out of business for long enough to come up with a plan of our own to exploit it in the meantime we now know that their highest security communications are encrypted using a caden us cipher so we can start hunting through the database for other intercepts we can crack this maybe the breakthrough we have been looking for in the fight against the fda lets not screw it up all the best harry'"
146 ]
147 }
148 ],
149 "prompt_number": 6
150 },
151 {
152 "cell_type": "code",
153 "collapsed": false,
154 "input": [
155 "len(c8b) / 8"
156 ],
157 "language": "python",
158 "metadata": {},
159 "outputs": [
160 {
161 "metadata": {},
162 "output_type": "pyout",
163 "prompt_number": 7,
164 "text": [
165 "875.0"
166 ]
167 }
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175 "[c for c in chunks(c8b, 5)]"
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1036 " '10011',\n",
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1173 " '01011',\n",
1174 " '10001',\n",
1175 " '01110',\n",
1176 " '10011',\n",
1177 " '01101',\n",
1178 " '10011',\n",
1179 " '10011',\n",
1180 " '10011',\n",
1181 " '00110',\n",
1182 " '01000',\n",
1183 " '10011',\n",
1184 " '01101',\n",
1185 " ...]"
1186 ]
1187 }
1188 ],
1189 "prompt_number": 8
1190 },
1191 {
1192 "cell_type": "code",
1193 "collapsed": false,
1194 "input": [
1195 "[(int(c, 2)) for c in chunks(c8b, 5)]"
1196 ],
1197 "language": "python",
1198 "metadata": {},
1199 "outputs": [
1200 {
1201 "metadata": {},
1202 "output_type": "pyout",
1203 "prompt_number": 9,
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1206 " 5,\n",
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1698 " 17,\n",
1699 " 22,\n",
1700 " 13,\n",
1701 " 8,\n",
1702 " 17,\n",
1703 " 4,\n",
1704 " 4,\n",
1705 " 4,\n",
1706 " 0,\n",
1707 " 4,\n",
1708 " 18,\n",
1709 " 4,\n",
1710 " 4,\n",
1711 " 4,\n",
1712 " 8,\n",
1713 " 3,\n",
1714 " 8,\n",
1715 " 18,\n",
1716 " 14,\n",
1717 " 6,\n",
1718 " 2,\n",
1719 " 4,\n",
1720 " 14,\n",
1721 " 12,\n",
1722 " 13,\n",
1723 " 17,\n",
1724 " 19,\n",
1725 " 4,\n",
1726 " 9,\n",
1727 " 7,\n",
1728 " 0,\n",
1729 " 6,\n",
1730 " 0,\n",
1731 " 1,\n",
1732 " 18,\n",
1733 " 4,\n",
1734 " 13,\n",
1735 " 8,\n",
1736 " 19,\n",
1737 " 11,\n",
1738 " 22,\n",
1739 " 19,\n",
1740 " 17,\n",
1741 " 13,\n",
1742 " 1,\n",
1743 " 12,\n",
1744 " 8,\n",
1745 " 4,\n",
1746 " 11,\n",
1747 " 18,\n",
1748 " 0,\n",
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1751 " 19,\n",
1752 " 4,\n",
1753 " 18,\n",
1754 " 17,\n",
1755 " 13,\n",
1756 " 6,\n",
1757 " 18,\n",
1758 " 13,\n",
1759 " 7,\n",
1760 " 4,\n",
1761 " 1,\n",
1762 " 8,\n",
1763 " 14,\n",
1764 " 18,\n",
1765 " 3,\n",
1766 " 8,\n",
1767 " 4,\n",
1768 " 13,\n",
1769 " 0,\n",
1770 " 5,\n",
1771 " 11,\n",
1772 " 4,\n",
1773 " 8,\n",
1774 " 18,\n",
1775 " 0,\n",
1776 " 7,\n",
1777 " 14,\n",
1778 " 2,\n",
1779 " 8,\n",
1780 " 5,\n",
1781 " 4,\n",
1782 " 21,\n",
1783 " 12,\n",
1784 " 5,\n",
1785 " 0,\n",
1786 " 19,\n",
1787 " 0,\n",
1788 " 13,\n",
1789 " 0,\n",
1790 " 19,\n",
1791 " 17,\n",
1792 " 13,\n",
1793 " 8,\n",
1794 " 0,\n",
1795 " 6,\n",
1796 " 13,\n",
1797 " 7,\n",
1798 " 0,\n",
1799 " 19,\n",
1800 " 13,\n",
1801 " 12,\n",
1802 " 8,\n",
1803 " 1,\n",
1804 " 13,\n",
1805 " 8,\n",
1806 " 20,\n",
1807 " 5,\n",
1808 " 4,\n",
1809 " 13,\n",
1810 " 17,\n",
1811 " 19,\n",
1812 " 14,\n",
1813 " 19,\n",
1814 " 19,\n",
1815 " 17,\n",
1816 " 13,\n",
1817 " 24,\n",
1818 " 15,\n",
1819 " 0,\n",
1820 " 8,\n",
1821 " 3,\n",
1822 " 24,\n",
1823 " 8,\n",
1824 " 4,\n",
1825 " 6,\n",
1826 " 3,\n",
1827 " 13,\n",
1828 " 12,\n",
1829 " 4,\n",
1830 " 17,\n",
1831 " 7,\n",
1832 " 7,\n",
1833 " 8,\n",
1834 " 14,\n",
1835 " 19,\n",
1836 " 17,\n",
1837 " 4,\n",
1838 " 19,\n",
1839 " 2,\n",
1840 " 4,\n",
1841 " 18,\n",
1842 " 18,\n",
1843 " 4,\n",
1844 " 8,\n",
1845 " 11,\n",
1846 " 3,\n",
1847 " 17,\n",
1848 " 1,\n",
1849 " 2,\n",
1850 " 4,\n",
1851 " 15,\n",
1852 " 17,\n",
1853 " 8,\n",
1854 " 6,\n",
1855 " 0,\n",
1856 " 4,\n",
1857 " 18,\n",
1858 " 14,\n",
1859 " 0,\n",
1860 " 3,\n",
1861 " 11,\n",
1862 " 19,\n",
1863 " 0,\n",
1864 " 7,\n",
1865 " 8,\n",
1866 " 4,\n",
1867 " 21,\n",
1868 " 4,\n",
1869 " 1,\n",
1870 " 17,\n",
1871 " 2,\n",
1872 " 4,\n",
1873 " 13,\n",
1874 " 11,\n",
1875 " 4,\n",
1876 " 21,\n",
1877 " 0,\n",
1878 " 18,\n",
1879 " 0,\n",
1880 " 3,\n",
1881 " 13,\n",
1882 " 13,\n",
1883 " 19,\n",
1884 " 7,\n",
1885 " 13,\n",
1886 " 4,\n",
1887 " 8,\n",
1888 " 19,\n",
1889 " 4,\n",
1890 " 8,\n",
1891 " 8,\n",
1892 " 18,\n",
1893 " 0,\n",
1894 " 7,\n",
1895 " 20,\n",
1896 " 7,\n",
1897 " 7,\n",
1898 " 20,\n",
1899 " 0,\n",
1900 " 12,\n",
1901 " 14,\n",
1902 " 13,\n",
1903 " 4,\n",
1904 " 5,\n",
1905 " 24,\n",
1906 " 7,\n",
1907 " 11,\n",
1908 " 14,\n",
1909 " 13,\n",
1910 " 22,\n",
1911 " 7,\n",
1912 " 0,\n",
1913 " 4,\n",
1914 " 4,\n",
1915 " 4,\n",
1916 " 4,\n",
1917 " 14,\n",
1918 " 18,\n",
1919 " 13,\n",
1920 " 4,\n",
1921 " 4,\n",
1922 " 24,\n",
1923 " 0,\n",
1924 " 13,\n",
1925 " 4,\n",
1926 " 8,\n",
1927 " 18,\n",
1928 " 4,\n",
1929 " 19,\n",
1930 " 14,\n",
1931 " 6,\n",
1932 " 24,\n",
1933 " 8,\n",
1934 " 19,\n",
1935 " 4,\n",
1936 " 17,\n",
1937 " 11,\n",
1938 " 8,\n",
1939 " 7,\n",
1940 " 19,\n",
1941 " 2,\n",
1942 " 12,\n",
1943 " 8,\n",
1944 " 14,\n",
1945 " 8,\n",
1946 " 17,\n",
1947 " 0,\n",
1948 " 17,\n",
1949 " 5,\n",
1950 " 3,\n",
1951 " 14,\n",
1952 " 4,\n",
1953 " 19,\n",
1954 " 13,\n",
1955 " 8,\n",
1956 " 7,\n",
1957 " 19,\n",
1958 " 13,\n",
1959 " 4,\n",
1960 " 7,\n",
1961 " 8,\n",
1962 " 8,\n",
1963 " 10,\n",
1964 " 0,\n",
1965 " 12,\n",
1966 " 17,\n",
1967 " 3,\n",
1968 " 12,\n",
1969 " 13,\n",
1970 " 0,\n",
1971 " 3,\n",
1972 " 0,\n",
1973 " 13,\n",
1974 " 0,\n",
1975 " 14,\n",
1976 " 3,\n",
1977 " 18,\n",
1978 " 4,\n",
1979 " 18,\n",
1980 " 4,\n",
1981 " 8,\n",
1982 " 24,\n",
1983 " 2,\n",
1984 " 11,\n",
1985 " 18,\n",
1986 " 8,\n",
1987 " 0,\n",
1988 " 13,\n",
1989 " 19,\n",
1990 " 0,\n",
1991 " 14,\n",
1992 " 11,\n",
1993 " 19,\n",
1994 " 2,\n",
1995 " 8,\n",
1996 " 24,\n",
1997 " 12,\n",
1998 " 8,\n",
1999 " 3,\n",
2000 " 4,\n",
2001 " 13,\n",
2002 " 19,\n",
2003 " 19,\n",
2004 " 7,\n",
2005 " 11,\n",
2006 " 19,\n",
2007 " 13,\n",
2008 " 3,\n",
2009 " 23,\n",
2010 " 19,\n",
2011 " 19,\n",
2012 " 19,\n",
2013 " 12,\n",
2014 " 0,\n",
2015 " 18,\n",
2016 " 1,\n",
2017 " 11,\n",
2018 " 4,\n",
2019 " 0,\n",
2020 " 4,\n",
2021 " 4,\n",
2022 " 19,\n",
2023 " 11,\n",
2024 " 8,\n",
2025 " 18,\n",
2026 " 8,\n",
2027 " 17,\n",
2028 " 19,\n",
2029 " 22,\n",
2030 " 19,\n",
2031 " 20,\n",
2032 " 17,\n",
2033 " 15,\n",
2034 " 5,\n",
2035 " 0,\n",
2036 " 8,\n",
2037 " 11,\n",
2038 " 19,\n",
2039 " 4,\n",
2040 " 0,\n",
2041 " 14,\n",
2042 " 4,\n",
2043 " 5,\n",
2044 " 4,\n",
2045 " 8,\n",
2046 " 18,\n",
2047 " 8,\n",
2048 " 8,\n",
2049 " 8,\n",
2050 " 24,\n",
2051 " 8,\n",
2052 " 18,\n",
2053 " 8,\n",
2054 " 10,\n",
2055 " 21,\n",
2056 " 19,\n",
2057 " 22,\n",
2058 " 8,\n",
2059 " 18,\n",
2060 " 15,\n",
2061 " 17,\n",
2062 " 1,\n",
2063 " 18,\n",
2064 " 8,\n",
2065 " 13,\n",
2066 " 4,\n",
2067 " 11,\n",
2068 " 15,\n",
2069 " 7,\n",
2070 " 17,\n",
2071 " 12,\n",
2072 " 14,\n",
2073 " 7,\n",
2074 " 8,\n",
2075 " 0,\n",
2076 " 6,\n",
2077 " 13,\n",
2078 " 11,\n",
2079 " 18,\n",
2080 " 11,\n",
2081 " 21,\n",
2082 " 8,\n",
2083 " 19,\n",
2084 " 14,\n",
2085 " 3,\n",
2086 " 0,\n",
2087 " 8,\n",
2088 " 18,\n",
2089 " 3,\n",
2090 " 15,\n",
2091 " 13,\n",
2092 " 24,\n",
2093 " 3,\n",
2094 " 3,\n",
2095 " 2,\n",
2096 " 0,\n",
2097 " 0,\n",
2098 " 14,\n",
2099 " 19,\n",
2100 " 0,\n",
2101 " 7,\n",
2102 " 2,\n",
2103 " 4,\n",
2104 " 7,\n",
2105 " 19,\n",
2106 " 20,\n",
2107 " 4,\n",
2108 " 8,\n",
2109 " 17,\n",
2110 " 17,\n",
2111 " 4,\n",
2112 " 3,\n",
2113 " 0,\n",
2114 " 4,\n",
2115 " 2,\n",
2116 " 19,\n",
2117 " 14,\n",
2118 " 18,\n",
2119 " 13,\n",
2120 " 17,\n",
2121 " 7,\n",
2122 " 21,\n",
2123 " 13,\n",
2124 " 0,\n",
2125 " 14,\n",
2126 " 3,\n",
2127 " 14,\n",
2128 " 8,\n",
2129 " 10,\n",
2130 " 14,\n",
2131 " 4,\n",
2132 " 19,\n",
2133 " 2,\n",
2134 " 8,\n",
2135 " 13,\n",
2136 " 4,\n",
2137 " 13,\n",
2138 " 4,\n",
2139 " 20,\n",
2140 " 17,\n",
2141 " 17,\n",
2142 " 8,\n",
2143 " 18,\n",
2144 " 3,\n",
2145 " 2,\n",
2146 " 14,\n",
2147 " 20,\n",
2148 " 17,\n",
2149 " 0,\n",
2150 " 6,\n",
2151 " 11,\n",
2152 " 21,\n",
2153 " 8,\n",
2154 " 12,\n",
2155 " 12,\n",
2156 " 20,\n",
2157 " 15,\n",
2158 " 15,\n",
2159 " 3,\n",
2160 " 8,\n",
2161 " 19,\n",
2162 " 4,\n",
2163 " 0,\n",
2164 " 13,\n",
2165 " 3,\n",
2166 " 8,\n",
2167 " 19,\n",
2168 " 12,\n",
2169 " 0,\n",
2170 " 0,\n",
2171 " 8,\n",
2172 " 0,\n",
2173 " 8,\n",
2174 " 4,\n",
2175 " 11,\n",
2176 " 4,\n",
2177 " 14,\n",
2178 " 13,\n",
2179 " 13,\n",
2180 " 17,\n",
2181 " 4,\n",
2182 " 4,\n",
2183 " 3,\n",
2184 " 0,\n",
2185 " 14,\n",
2186 " 3,\n",
2187 " 1,\n",
2188 " 14,\n",
2189 " 8,\n",
2190 " 20,\n",
2191 " 12,\n",
2192 " 4,\n",
2193 " 11,\n",
2194 " 17,\n",
2195 " 14,\n",
2196 " 19,\n",
2197 " 13,\n",
2198 " 19,\n",
2199 " 19,\n",
2200 " 19,\n",
2201 " 6,\n",
2202 " 8,\n",
2203 " 19,\n",
2204 " 13,\n",
2205 " ...]"
2206 ]
2207 }
2208 ],
2209 "prompt_number": 9
2210 },
2211 {
2212 "cell_type": "code",
2213 "collapsed": false,
2214 "input": [
2215 "min([(int(c, 2)) for c in chunks(c8b, 5)])"
2216 ],
2217 "language": "python",
2218 "metadata": {},
2219 "outputs": [
2220 {
2221 "metadata": {},
2222 "output_type": "pyout",
2223 "prompt_number": 10,
2224 "text": [
2225 "0"
2226 ]
2227 }
2228 ],
2229 "prompt_number": 10
2230 },
2231 {
2232 "cell_type": "code",
2233 "collapsed": false,
2234 "input": [
2235 "max([chr(int(c, 2) + ord('a')) for c in chunks(c8b, 5)])"
2236 ],
2237 "language": "python",
2238 "metadata": {},
2239 "outputs": [
2240 {
2241 "metadata": {},
2242 "output_type": "pyout",
2243 "prompt_number": 11,
2244 "text": [
2245 "'y'"
2246 ]
2247 }
2248 ],
2249 "prompt_number": 11
2250 },
2251 {
2252 "cell_type": "code",
2253 "collapsed": false,
2254 "input": [
2255 "def cadenus_letter(n, doubled='v'):\n",
2256 " letter = chr(n + ord('a'))\n",
2257 " if letter > doubled:\n",
2258 " letter = chr(n + ord('a') + 1)\n",
2259 " return letter"
2260 ],
2261 "language": "python",
2262 "metadata": {},
2263 "outputs": [],
2264 "prompt_number": 12
2265 },
2266 {
2267 "cell_type": "code",
2268 "collapsed": false,
2269 "input": [
2270 "c8bl = ''.join([cadenus_letter(int(c, 2)) for c in chunks(c8b, 5)])\n",
2271 "c8bl"
2272 ],
2273 "language": "python",
2274 "metadata": {},
2275 "outputs": [
2276 {
2277 "metadata": {},
2278 "output_type": "pyout",
2279 "prompt_number": 13,
2280 "text": [
2281 "'afcaeuottacthrioletcserthshtrahkzorpfrgeoadppjnglternefeofiortsddoeeumscruernfetlaafstxientrvoonerhuahravereetsvsielhlostdoalozaesmnndignnrhohhtsnaoilncnssicreanneeiiierxtanesrvogieizxssdgpvoiaisaoaeoaedrnitrnyeigrpsshadhdtoipaateyennesagrobtlesrnroirzpbgedcllixalaleenigrrnxzrlimlpstoleftrdmuarieeeiiaolnexsaohrtlstobetnslvfivdovtpoaeeisciohipseveedtexfarnhebleaotohtttepnckaonhxetmvzprreonnasgdedoeeeoaamtcicttifnadresrtserosetrhcictpsaaehldhsfysoaotctbbsoeirnsadlztrrunrceptthreuhnktaceceelrxnireeeaeseeeidisogceomnrtejhagabsenitlxtrnbmielsaretesrngsnhebiosdienafleisahocifevmfatanatrniagnhatnmibniufenrtottrnzpaidziegdnmerhhiotretcesseildrbceprigaesoadltahievebrcenlevasadnnthneiteiisahuhhuamonefzhlonxhaeeeeosneezaneisetogziterlihtcmioirarfdoetnihtnehiikamrdmnadanaodseseizclsiantaoltcizmidentthltndytttmasbleaeetlisirtxturpfailteaoefeisiiizisikvtxisprbsinelphrmohiagnlslvitodaisdpnzddcaaotahcehtueirredaectosnrhvnaodoikoetcineneurrisdcouraglvimmuppditeanditmaaiaieleonnreedaodboiumelrotntttgitnrlrienniklzsogstcifzpipvidvssmnceiasiitsnneatitomrhbnhnidprlrepoznalsnvsdosanesitfaenltgodatteeaisicrootmsmfhauenirsghznxeintegodiileedtarnosrcaaendtcuttfdrbehtmfitoordruiaozaanoeeldoinhusgiteaoriecevemntratmtfpeucutahamtnexonicdeemrpaolitoafesoosspfnlneeootachllirssysofpdftfrnpraeeazlonahautntcntcbaxloneftoatecvoxdlxvnneedtiioigtegmtaheeatefaaeprrcrosheerrpalediengidrreouhvesuroztnsosinuiuiofprda'"
2282 ]
2283 }
2284 ],
2285 "prompt_number": 13
2286 },
2287 {
2288 "cell_type": "code",
2289 "collapsed": false,
2290 "input": [
2291 "min(c8bl), max(c8bl)"
2292 ],
2293 "language": "python",
2294 "metadata": {},
2295 "outputs": [
2296 {
2297 "metadata": {},
2298 "output_type": "pyout",
2299 "prompt_number": 14,
2300 "text": [
2301 "('a', 'z')"
2302 ]
2303 }
2304 ],
2305 "prompt_number": 14
2306 },
2307 {
2308 "cell_type": "code",
2309 "collapsed": false,
2310 "input": [
2311 "len(c8bl), len(c8bl) / 25"
2312 ],
2313 "language": "python",
2314 "metadata": {},
2315 "outputs": [
2316 {
2317 "metadata": {},
2318 "output_type": "pyout",
2319 "prompt_number": 15,
2320 "text": [
2321 "(1400, 56.0)"
2322 ]
2323 }
2324 ],
2325 "prompt_number": 15
2326 },
2327 {
2328 "cell_type": "code",
2329 "collapsed": false,
2330 "input": [
2331 "freqs_8b = pd.Series(collections.Counter([l.lower() for l in c8bl if l in string.ascii_letters]))\n",
2332 "freqs_8b.plot(kind='bar')"
2333 ],
2334 "language": "python",
2335 "metadata": {},
2336 "outputs": [
2337 {
2338 "metadata": {},
2339 "output_type": "pyout",
2340 "prompt_number": 16,
2341 "text": [
2342 "<matplotlib.axes.AxesSubplot at 0x7f2de5006ba8>"
2343 ]
2344 },
2345 {
2346 "metadata": {},
2347 "output_type": "display_data",
2348 "png": 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2349 "text": [
2350 "<matplotlib.figure.Figure at 0x7f2de5006198>"
2351 ]
2352 }
2353 ],
2354 "prompt_number": 16
2355 },
2356 {
2357 "cell_type": "code",
2358 "collapsed": false,
2359 "input": [
2360 "freqs = pd.Series(english_counts)\n",
2361 "freqs.plot(kind='bar')"
2362 ],
2363 "language": "python",
2364 "metadata": {},
2365 "outputs": [
2366 {
2367 "metadata": {},
2368 "output_type": "pyout",
2369 "prompt_number": 17,
2370 "text": [
2371 "<matplotlib.axes.AxesSubplot at 0x7f2de80f8a90>"
2372 ]
2373 },
2374 {
2375 "metadata": {},
2376 "output_type": "display_data",
2377 "png": 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aiBBCtJ9eeHdM5EH0Ut2+l+Yi0pH3Gnze599O9FtMQgghvMlpgiilVwRah+yluYSqCTUu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\nTkSuQmCC\n",
2378 "text": [
2379 "<matplotlib.figure.Figure at 0x7f2de4f43eb8>"
2380 ]
2381 }
2382 ],
2383 "prompt_number": 17
2384 },
2385 {
2386 "cell_type": "code",
2387 "collapsed": false,
2388 "input": [
2389 "rows = chunks(c8bl, len(c8bl) // 25)\n",
2390 "rows"
2391 ],
2392 "language": "python",
2393 "metadata": {},
2394 "outputs": [
2395 {
2396 "metadata": {},
2397 "output_type": "pyout",
2398 "prompt_number": 18,
2399 "text": [
2400 "['afcaeuottacthrioletcserthshtrahkzorpfrgeoadppjnglternefe',\n",
2401 " 'ofiortsddoeeumscruernfetlaafstxientrvoonerhuahravereetsv',\n",
2402 " 'sielhlostdoalozaesmnndignnrhohhtsnaoilncnssicreanneeiiie',\n",
2403 " 'rxtanesrvogieizxssdgpvoiaisaoaeoaedrnitrnyeigrpsshadhdto',\n",
2404 " 'ipaateyennesagrobtlesrnroirzpbgedcllixalaleenigrrnxzrlim',\n",
2405 " 'lpstoleftrdmuarieeeiiaolnexsaohrtlstobetnslvfivdovtpoaee',\n",
2406 " 'isciohipseveedtexfarnhebleaotohtttepnckaonhxetmvzprreonn',\n",
2407 " 'asgdedoeeeoaamtcicttifnadresrtserosetrhcictpsaaehldhsfys',\n",
2408 " 'oaotctbbsoeirnsadlztrrunrceptthreuhnktaceceelrxnireeeaes',\n",
2409 " 'eeeidisogceomnrtejhagabsenitlxtrnbmielsaretesrngsnhebios',\n",
2410 " 'dienafleisahocifevmfatanatrniagnhatnmibniufenrtottrnzpai',\n",
2411 " 'dziegdnmerhhiotretcesseildrbceprigaesoadltahievebrcenlev',\n",
2412 " 'asadnnthneiteiisahuhhuamonefzhlonxhaeeeeosneezaneisetogz',\n",
2413 " 'iterlihtcmioirarfdoetnihtnehiikamrdmnadanaodseseizclsian',\n",
2414 " 'taoltcizmidentthltndytttmasbleaeetlisirtxturpfailteaoefe',\n",
2415 " 'isiiizisikvtxisprbsinelphrmohiagnlslvitodaisdpnzddcaaota',\n",
2416 " 'hcehtueirredaectosnrhvnaodoikoetcineneurrisdcouraglvimmu',\n",
2417 " 'ppditeanditmaaiaieleonnreedaodboiumelrotntttgitnrlrienni',\n",
2418 " 'klzsogstcifzpipvidvssmnceiasiitsnneatitomrhbnhnidprlrepo',\n",
2419 " 'znalsnvsdosanesitfaenltgodatteeaisicrootmsmfhauenirsghzn',\n",
2420 " 'xeintegodiileedtarnosrcaaendtcuttfdrbehtmfitoordruiaozaa',\n",
2421 " 'noeeldoinhusgiteaoriecevemntratmtfpeucutahamtnexonicdeem',\n",
2422 " 'rpaolitoafesoosspfnlneeootachllirssysofpdftfrnpraeeazlon',\n",
2423 " 'ahautntcntcbaxloneftoatecvoxdlxvnneedtiioigtegmtaheeatef',\n",
2424 " 'aaeprrcrosheerrpalediengidrreouhvesuroztnsosinuiuiofprda']"
2425 ]
2426 }
2427 ],
2428 "prompt_number": 18
2429 },
2430 {
2431 "cell_type": "code",
2432 "collapsed": false,
2433 "input": [
2434 "chunks(''.join([l if l in 'phase' else '.' for l in c8bl]), 56)"
2435 ],
2436 "language": "python",
2437 "metadata": {},
2438 "outputs": [
2439 {
2440 "metadata": {},
2441 "output_type": "pyout",
2442 "prompt_number": 19,
2443 "text": [
2444 "['a..ae....a..h....e..se..hsh..ah....p...e.a.pp.....e..e.e',\n",
2445 " '......s...ee..s...e...e..aa.s...e.......e.h.ah.a.e.ee.s.',\n",
2446 " 's.e.h..s...a...aes.........h.hh.s.a......ss...ea..ee...e',\n",
2447 " '...a.es.....e...ss..p...a.sa.ae.ae........e...pssha.h...',\n",
2448 " '.paa.e.e..esa......es.......p..e......a.a.ee............',\n",
2449 " '.ps...e......a..eee..a...e.sa.h...s...e..s.........p.aee',\n",
2450 " '.s...h.pse.ee..e..a..he..ea...h...ep...a..h.e....p..e...',\n",
2451 " 'as..e..eee.aa..........a..es..se..se..h....psaaeh..hs..s',\n",
2452 " '.a......s.e...sa..........ep..h.e.h...a.e.ee......eeeaes',\n",
2453 " 'eee...s...e.....e.ha.a.se...........e.sa.e.es...s.he...s',\n",
2454 " '..e.a..e.sah....e...a.a.a....a..ha.........e.........pa.',\n",
2455 " '...e....e.hh....e..esse......ep...aes.a...ah.e.e...e..e.',\n",
2456 " 'asa....h.e..e..sah.hh.a...e..h....haeeee.s.ee.a.e.se....',\n",
2457 " '..e...h.......a....e...h..eh...a.....a.a.a..sese....s.a.',\n",
2458 " '.a.........e...h.........as..eaee...s.......p.a...ea.e.e',\n",
2459 " '.s.....s......sp..s..e.ph...h.a...s......a.s.p.....aa..a',\n",
2460 " 'h.eh..e...e.ae...s..h..a......e....e.e....s.....a.......',\n",
2461 " 'pp...ea.....aa.a.e.e....ee.a.......e................e...',\n",
2462 " '...s..s.....p.p....ss...e.as...s..ea......h..h...p...ep.',\n",
2463 " '..a.s..s..sa.es...ae......a..eea.s.......s..ha.e...s.h..',\n",
2464 " '.e...e......ee..a...s..aae...........eh............a..aa',\n",
2465 " '..ee.....h.s...ea...e.e.e....a....pe....aha...e......ee.',\n",
2466 " '.pa.....a.es..ssp....ee...a.h....ss.s..p......p.aeea....',\n",
2467 " 'aha.........a....e...a.e..........ee........e...aheea.e.',\n",
2468 " 'aaep.....shee..pa.e..e......e..h.es......s.s........p..a']"
2469 ]
2470 }
2471 ],
2472 "prompt_number": 19
2473 },
2474 {
2475 "cell_type": "code",
2476 "collapsed": false,
2477 "input": [
2478 "columns = [''.join(c) for c in zip(*rows)]\n",
2479 "columns"
2480 ],
2481 "language": "python",
2482 "metadata": {},
2483 "outputs": [
2484 {
2485 "metadata": {},
2486 "output_type": "pyout",
2487 "prompt_number": 20,
2488 "text": [
2489 "['aosriliaoeddaitihpkzxnraa',\n",
2490 " 'ffixppssaeizstascplneopha',\n",
2491 " 'cietascgoeeiaeoiedzaieaae',\n",
2492 " 'aolaatidtinedrlihislneoup',\n",
2493 " 'erhntooecdagnltittostlltr',\n",
2494 " 'utleelhdtifdniczuegnedinr',\n",
2495 " 'ososyeiobslnthiieasvgottc',\n",
2496 " 'tdsrefpeboemhtzsintsoiocr',\n",
2497 " 'tdtvntsesgiencmirdcddnano',\n",
2498 " 'aodonreeocsremikriioihfts',\n",
2499 " 'ceogedvoeeahiidvetfsiuech',\n",
2500 " 'teaismeaiohhtoetdmzalssbe',\n",
2501 " 'huleauearmoieinxaapnegoae',\n",
2502 " 'rmoigadmnncoirtieaieeioxr',\n",
2503 " 'iszzrrttsritiatscipsdtslr',\n",
2504 " 'ocaxoiecatfrsrhptavitesop',\n",
2505 " 'lresbexideeeaflroiitaapna',\n",
2506 " 'eusstefcljvthdtbsedfrofel',\n",
2507 " 'temdleatzhmcuonsnlvanrnfe',\n",
2508 " 'crngeirttafehedireseoiltd',\n",
2509 " 'snnpsinirgashtynhosnsenoi',\n",
2510 " 'efdvrahfratsuntevnmlrceae',\n",
2511 " 'reionoenubaeaitlnnntceetn',\n",
2512 " 'ttgirlbansnimhtparcgavoeg',\n",
2513 " 'hlnaonldrealotmhoeeoaeoci',\n",
2514 " 'saniieercntdnnardeidemtvd',\n",
2515 " 'harsrxaeeirreesmodaannaor',\n",
2516 " 'tfhazsosptnbfhboiastdtcxr',\n",
2517 " 'rsoopatrtliczilhkoittrhde',\n",
2518 " 'athaboottxaehieiodiecallo',\n",
2519 " 'hxheghhshtgplkaaebteutlxu',\n",
2520 " 'kitoerterrnroaegtosatmivh',\n",
2521 " 'zesadttrenhinmencinittrnv',\n",
2522 " 'onnecltoubagxrtliunsffsne',\n",
2523 " 'rtadlseshmtahdlsnmeidpses',\n",
2524 " 'prorltpenineamileeacreyeu',\n",
2525 " 'fviniontkemsensvnltrbusdr',\n",
2526 " 'rolixbcrtlioeaiierioecoto',\n",
2527 " 'gontaekhasbaedrtuotohufiz',\n",
2528 " 'encrltaccandeatortotttpit',\n",
2529 " 'oennanoierilonxdrnmmmadon',\n",
2530 " 'arsylsncceutsataitrsfhfis',\n",
2531 " 'dhseelhtetfanouisthmiatgo',\n",
2532 " 'puiievxpeeehedrsdtbftmfts',\n",
2533 " 'pacgnfeslsniespdcgnhotrei',\n",
2534 " 'jhrriitarrrezefpoihaonngn',\n",
2535 " 'nrepgvmaxntvasanutnurepmu',\n",
2536 " 'gaasrdvengoeneizrniedxrti',\n",
2537 " 'lvnsrozhistbeildardnroaau',\n",
2538 " 'tenhnvplrntriztdglpiunehi',\n",
2539 " 'ereaxtrdehrcsceclrrriieeo',\n",
2540 " 'reedzprheeneelaavilsacaef',\n",
2541 " 'neihroesebzntsoaiergodzap',\n",
2542 " 'etidlaofaiploieomnehzeltr',\n",
2543 " 'fsitienyeoaegaftmnpzaeoed',\n",
2544 " 'eveomensssivzneauionamnfa']"
2545 ]
2546 }
2547 ],
2548 "prompt_number": 20
2549 },
2550 {
2551 "cell_type": "code",
2552 "collapsed": false,
2553 "input": [
2554 "letter_positions = {letter: [(r, c) for r, row in enumerate(rows) for c, char in enumerate(row) if char == letter] for letter in 'phaseeight'}\n",
2555 "letter_positions"
2556 ],
2557 "language": "python",
2558 "metadata": {},
2559 "outputs": [
2560 {
2561 "metadata": {},
2562 "output_type": "pyout",
2563 "prompt_number": 21,
2564 "text": [
2565 "{'h': [(0, 12),\n",
2566 " (0, 24),\n",
2567 " (0, 26),\n",
2568 " (0, 30),\n",
2569 " (1, 42),\n",
2570 " (1, 45),\n",
2571 " (2, 4),\n",
2572 " (2, 27),\n",
2573 " (2, 29),\n",
2574 " (2, 30),\n",
2575 " (3, 49),\n",
2576 " (3, 52),\n",
2577 " (5, 30),\n",
2578 " (6, 5),\n",
2579 " (6, 21),\n",
2580 " (6, 30),\n",
2581 " (6, 42),\n",
2582 " (7, 38),\n",
2583 " (7, 48),\n",
2584 " (7, 51),\n",
2585 " (8, 30),\n",
2586 " (8, 34),\n",
2587 " (9, 18),\n",
2588 " (9, 50),\n",
2589 " (10, 11),\n",
2590 " (10, 32),\n",
2591 " (11, 10),\n",
2592 " (11, 11),\n",
2593 " (11, 43),\n",
2594 " (12, 7),\n",
2595 " (12, 17),\n",
2596 " (12, 19),\n",
2597 " (12, 20),\n",
2598 " (12, 29),\n",
2599 " (12, 34),\n",
2600 " (13, 6),\n",
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2603 " (14, 15),\n",
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2606 " (16, 0),\n",
2607 " (16, 3),\n",
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2610 " (18, 45),\n",
2611 " (19, 44),\n",
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2613 " (20, 38),\n",
2614 " (21, 9),\n",
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2617 " (23, 1),\n",
2618 " (23, 49),\n",
2619 " (24, 10),\n",
2620 " (24, 31)],\n",
2621 " 'e': [(0, 4),\n",
2622 " (0, 17),\n",
2623 " (0, 21),\n",
2624 " (0, 39),\n",
2625 " (0, 50),\n",
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2715 " (12, 9),\n",
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2720 " (12, 38),\n",
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2722 " (12, 43),\n",
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2726 " (13, 2),\n",
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2733 " (14, 31),\n",
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2738 " (15, 21),\n",
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2740 " (16, 6),\n",
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2742 " (16, 13),\n",
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2746 " (17, 5),\n",
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2752 " (17, 52),\n",
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2754 " (18, 34),\n",
2755 " (18, 53),\n",
2756 " (19, 13),\n",
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2767 " (21, 2),\n",
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2792 " (24, 12),\n",
2793 " (24, 18),\n",
2794 " (24, 21),\n",
2795 " (24, 28),\n",
2796 " (24, 33)],\n",
2797 " 'a': [(0, 0),\n",
2798 " (0, 3),\n",
2799 " (0, 9),\n",
2800 " (0, 29),\n",
2801 " (0, 41),\n",
2802 " (1, 25),\n",
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2804 " (1, 44),\n",
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2806 " (2, 11),\n",
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2820 " (4, 40),\n",
2821 " (5, 13),\n",
2822 " (5, 21),\n",
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2825 " (6, 18),\n",
2826 " (6, 26),\n",
2827 " (6, 39),\n",
2828 " (7, 0),\n",
2829 " (7, 11),\n",
2830 " (7, 12),\n",
2831 " (7, 23),\n",
2832 " (7, 45),\n",
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2834 " (8, 1),\n",
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2838 " (9, 19),\n",
2839 " (9, 21),\n",
2840 " (9, 39),\n",
2841 " (10, 4),\n",
2842 " (10, 10),\n",
2843 " (10, 20),\n",
2844 " (10, 22),\n",
2845 " (10, 24),\n",
2846 " (10, 29),\n",
2847 " (10, 33),\n",
2848 " (10, 54),\n",
2849 " (11, 34),\n",
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2855 " (12, 22),\n",
2856 " (12, 35),\n",
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2859 " (13, 31),\n",
2860 " (13, 37),\n",
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2864 " (14, 1),\n",
2865 " (14, 25),\n",
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2872 " (15, 52),\n",
2873 " (15, 55),\n",
2874 " (16, 12),\n",
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2876 " (16, 48),\n",
2877 " (17, 6),\n",
2878 " (17, 12),\n",
2879 " (17, 13),\n",
2880 " (17, 15),\n",
2881 " (17, 27),\n",
2882 " (18, 26),\n",
2883 " (18, 35),\n",
2884 " (19, 2),\n",
2885 " (19, 11),\n",
2886 " (19, 18),\n",
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2888 " (19, 31),\n",
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2890 " (20, 16),\n",
2891 " (20, 23),\n",
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2894 " (20, 54),\n",
2895 " (20, 55),\n",
2896 " (21, 16),\n",
2897 " (21, 29),\n",
2898 " (21, 40),\n",
2899 " (21, 42),\n",
2900 " (22, 2),\n",
2901 " (22, 8),\n",
2902 " (22, 26),\n",
2903 " (22, 48),\n",
2904 " (22, 51),\n",
2905 " (23, 0),\n",
2906 " (23, 2),\n",
2907 " (23, 12),\n",
2908 " (23, 21),\n",
2909 " (23, 48),\n",
2910 " (23, 52),\n",
2911 " (24, 0),\n",
2912 " (24, 1),\n",
2913 " (24, 16),\n",
2914 " (24, 55)],\n",
2915 " 'p': [(0, 35),\n",
2916 " (0, 43),\n",
2917 " (0, 44),\n",
2918 " (3, 20),\n",
2919 " (3, 46),\n",
2920 " (4, 1),\n",
2921 " (4, 28),\n",
2922 " (5, 1),\n",
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2924 " (6, 7),\n",
2925 " (6, 35),\n",
2926 " (6, 49),\n",
2927 " (7, 43),\n",
2928 " (8, 27),\n",
2929 " (10, 53),\n",
2930 " (11, 30),\n",
2931 " (14, 44),\n",
2932 " (15, 15),\n",
2933 " (15, 23),\n",
2934 " (15, 45),\n",
2935 " (17, 0),\n",
2936 " (17, 1),\n",
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2938 " (18, 14),\n",
2939 " (18, 49),\n",
2940 " (18, 54),\n",
2941 " (21, 34),\n",
2942 " (22, 1),\n",
2943 " (22, 16),\n",
2944 " (22, 39),\n",
2945 " (22, 46),\n",
2946 " (24, 3),\n",
2947 " (24, 15),\n",
2948 " (24, 52)],\n",
2949 " 'g': [(0, 38),\n",
2950 " (0, 47),\n",
2951 " (2, 23),\n",
2952 " (3, 10),\n",
2953 " (3, 19),\n",
2954 " (3, 44),\n",
2955 " (4, 13),\n",
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2957 " (4, 46),\n",
2958 " (7, 2),\n",
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2962 " (10, 30),\n",
2963 " (11, 4),\n",
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2965 " (12, 54),\n",
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2972 " (20, 6),\n",
2973 " (21, 12),\n",
2974 " (23, 42),\n",
2975 " (23, 45),\n",
2976 " (24, 23)],\n",
2977 " 'i': [(0, 14),\n",
2978 " (1, 2),\n",
2979 " (1, 31),\n",
2980 " (2, 1),\n",
2981 " (2, 22),\n",
2982 " (2, 36),\n",
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2985 " (2, 53),\n",
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2987 " (3, 11),\n",
2988 " (3, 13),\n",
2989 " (3, 23),\n",
2990 " (3, 25),\n",
2991 " (3, 37),\n",
2992 " (3, 43),\n",
2993 " (4, 0),\n",
2994 " (4, 25),\n",
2995 " (4, 36),\n",
2996 " (4, 45),\n",
2997 " (4, 54),\n",
2998 " (5, 15),\n",
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3000 " (5, 20),\n",
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3002 " (6, 0),\n",
3003 " (6, 3),\n",
3004 " (6, 6),\n",
3005 " (7, 16),\n",
3006 " (7, 20),\n",
3007 " (7, 40),\n",
3008 " (8, 11),\n",
3009 " (8, 48),\n",
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3011 " (9, 5),\n",
3012 " (9, 26),\n",
3013 " (9, 35),\n",
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3015 " (10, 1),\n",
3016 " (10, 8),\n",
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3018 " (10, 28),\n",
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3020 " (10, 40),\n",
3021 " (10, 55),\n",
3022 " (11, 2),\n",
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3025 " (11, 32),\n",
3026 " (11, 44),\n",
3027 " (12, 10),\n",
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3029 " (12, 14),\n",
3030 " (12, 49),\n",
3031 " (13, 0),\n",
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3033 " (13, 10),\n",
3034 " (13, 12),\n",
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3039 " (13, 53),\n",
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3070 " (18, 13),\n",
3071 " (18, 16),\n",
3072 " (18, 25),\n",
3073 " (18, 28),\n",
3074 " (18, 29),\n",
3075 " (18, 37),\n",
3076 " (18, 47),\n",
3077 " (19, 15),\n",
3078 " (19, 32),\n",
3079 " (19, 34),\n",
3080 " (19, 49),\n",
3081 " (20, 2),\n",
3082 " (20, 9),\n",
3083 " (20, 10),\n",
3084 " (20, 42),\n",
3085 " (20, 50),\n",
3086 " (21, 7),\n",
3087 " (21, 13),\n",
3088 " (21, 19),\n",
3089 " (21, 50),\n",
3090 " (22, 5),\n",
3091 " (22, 31),\n",
3092 " (23, 38),\n",
3093 " (23, 39),\n",
3094 " (23, 41),\n",
3095 " (24, 20),\n",
3096 " (24, 24),\n",
3097 " (24, 44),\n",
3098 " (24, 47),\n",
3099 " (24, 49)],\n",
3100 " 't': [(0, 7),\n",
3101 " (0, 8),\n",
3102 " (0, 11),\n",
3103 " (0, 18),\n",
3104 " (0, 23),\n",
3105 " (0, 27),\n",
3106 " (0, 49),\n",
3107 " (1, 5),\n",
3108 " (1, 23),\n",
3109 " (1, 29),\n",
3110 " (1, 34),\n",
3111 " (1, 53),\n",
3112 " (2, 8),\n",
3113 " (2, 31),\n",
3114 " (3, 2),\n",
3115 " (3, 38),\n",
3116 " (3, 54),\n",
3117 " (4, 4),\n",
3118 " (4, 17),\n",
3119 " (5, 3),\n",
3120 " (5, 8),\n",
3121 " (5, 32),\n",
3122 " (5, 35),\n",
3123 " (5, 39),\n",
3124 " (5, 50),\n",
3125 " (6, 14),\n",
3126 " (6, 28),\n",
3127 " (6, 31),\n",
3128 " (6, 32),\n",
3129 " (6, 33),\n",
3130 " (6, 45),\n",
3131 " (7, 14),\n",
3132 " (7, 18),\n",
3133 " (7, 19),\n",
3134 " (7, 29),\n",
3135 " (7, 36),\n",
3136 " (7, 42),\n",
3137 " (8, 3),\n",
3138 " (8, 5),\n",
3139 " (8, 19),\n",
3140 " (8, 28),\n",
3141 " (8, 29),\n",
3142 " (8, 37),\n",
3143 " (9, 15),\n",
3144 " (9, 27),\n",
3145 " (9, 30),\n",
3146 " (9, 42),\n",
3147 " (10, 21),\n",
3148 " (10, 25),\n",
3149 " (10, 34),\n",
3150 " (10, 46),\n",
3151 " (10, 48),\n",
3152 " (10, 49),\n",
3153 " (11, 14),\n",
3154 " (11, 17),\n",
3155 " (11, 41),\n",
3156 " (12, 6),\n",
3157 " (12, 11),\n",
3158 " (12, 52),\n",
3159 " (13, 1),\n",
3160 " (13, 7),\n",
3161 " (13, 20),\n",
3162 " (13, 24),\n",
3163 " (14, 0),\n",
3164 " (14, 4),\n",
3165 " (14, 13),\n",
3166 " (14, 14),\n",
3167 " (14, 17),\n",
3168 " (14, 21),\n",
3169 " (14, 22),\n",
3170 " (14, 23),\n",
3171 " (14, 33),\n",
3172 " (14, 39),\n",
3173 " (14, 41),\n",
3174 " (14, 49),\n",
3175 " (15, 11),\n",
3176 " (15, 38),\n",
3177 " (15, 54),\n",
3178 " (16, 4),\n",
3179 " (16, 15),\n",
3180 " (16, 31),\n",
3181 " (17, 4),\n",
3182 " (17, 10),\n",
3183 " (17, 39),\n",
3184 " (17, 41),\n",
3185 " (17, 42),\n",
3186 " (17, 43),\n",
3187 " (17, 46),\n",
3188 " (18, 7),\n",
3189 " (18, 30),\n",
3190 " (18, 36),\n",
3191 " (18, 38),\n",
3192 " (19, 16),\n",
3193 " (19, 22),\n",
3194 " (19, 27),\n",
3195 " (19, 28),\n",
3196 " (19, 39),\n",
3197 " (20, 4),\n",
3198 " (20, 15),\n",
3199 " (20, 28),\n",
3200 " (20, 31),\n",
3201 " (20, 32),\n",
3202 " (20, 39),\n",
3203 " (20, 43),\n",
3204 " (21, 14),\n",
3205 " (21, 27),\n",
3206 " (21, 30),\n",
3207 " (21, 32),\n",
3208 " (21, 39),\n",
3209 " (21, 44),\n",
3210 " (22, 6),\n",
3211 " (22, 25),\n",
3212 " (22, 42),\n",
3213 " (23, 4),\n",
3214 " (23, 6),\n",
3215 " (23, 9),\n",
3216 " (23, 19),\n",
3217 " (23, 22),\n",
3218 " (23, 37),\n",
3219 " (23, 43),\n",
3220 " (23, 47),\n",
3221 " (23, 53),\n",
3222 " (24, 39)],\n",
3223 " 's': [(0, 20),\n",
3224 " (0, 25),\n",
3225 " (1, 6),\n",
3226 " (1, 14),\n",
3227 " (1, 28),\n",
3228 " (1, 54),\n",
3229 " (2, 0),\n",
3230 " (2, 7),\n",
3231 " (2, 17),\n",
3232 " (2, 32),\n",
3233 " (2, 41),\n",
3234 " (2, 42),\n",
3235 " (3, 6),\n",
3236 " (3, 16),\n",
3237 " (3, 17),\n",
3238 " (3, 26),\n",
3239 " (3, 47),\n",
3240 " (3, 48),\n",
3241 " (4, 11),\n",
3242 " (4, 20),\n",
3243 " (5, 2),\n",
3244 " (5, 27),\n",
3245 " (5, 34),\n",
3246 " (5, 41),\n",
3247 " (6, 1),\n",
3248 " (6, 8),\n",
3249 " (7, 1),\n",
3250 " (7, 27),\n",
3251 " (7, 30),\n",
3252 " (7, 34),\n",
3253 " (7, 44),\n",
3254 " (7, 52),\n",
3255 " (7, 55),\n",
3256 " (8, 8),\n",
3257 " (8, 14),\n",
3258 " (8, 55),\n",
3259 " (9, 6),\n",
3260 " (9, 23),\n",
3261 " (9, 38),\n",
3262 " (9, 44),\n",
3263 " (9, 48),\n",
3264 " (9, 55),\n",
3265 " (10, 9),\n",
3266 " (11, 20),\n",
3267 " (11, 21),\n",
3268 " (11, 36),\n",
3269 " (12, 1),\n",
3270 " (12, 15),\n",
3271 " (12, 41),\n",
3272 " (12, 50),\n",
3273 " (13, 44),\n",
3274 " (13, 46),\n",
3275 " (13, 52),\n",
3276 " (14, 26),\n",
3277 " (14, 36),\n",
3278 " (15, 1),\n",
3279 " (15, 7),\n",
3280 " (15, 14),\n",
3281 " (15, 18),\n",
3282 " (15, 34),\n",
3283 " (15, 43),\n",
3284 " (16, 17),\n",
3285 " (16, 42),\n",
3286 " (18, 3),\n",
3287 " (18, 6),\n",
3288 " (18, 19),\n",
3289 " (18, 20),\n",
3290 " (18, 27),\n",
3291 " (18, 31),\n",
3292 " (19, 4),\n",
3293 " (19, 7),\n",
3294 " (19, 10),\n",
3295 " (19, 14),\n",
3296 " (19, 33),\n",
3297 " (19, 41),\n",
3298 " (19, 51),\n",
3299 " (20, 20),\n",
3300 " (21, 11),\n",
3301 " (22, 11),\n",
3302 " (22, 14),\n",
3303 " (22, 15),\n",
3304 " (22, 33),\n",
3305 " (22, 34),\n",
3306 " (22, 36),\n",
3307 " (24, 9),\n",
3308 " (24, 34),\n",
3309 " (24, 41),\n",
3310 " (24, 43)]}"
3311 ]
3312 }
3313 ],
3314 "prompt_number": 21
3315 },
3316 {
3317 "cell_type": "code",
3318 "collapsed": false,
3319 "input": [
3320 "solutions = [[p] for p in letter_positions['p']]\n",
3321 "for letter in 'has': #'haseeight':\n",
3322 " new_solutions = []\n",
3323 " for solution in solutions:\n",
3324 " used_columns = [p[1] for p in solution]\n",
3325 " for position in letter_positions[letter]:\n",
3326 " if position[1] not in used_columns:\n",
3327 " new_solutions += [solution + [position]]\n",
3328 " solutions = new_solutions\n",
3329 "len(solutions)"
3330 ],
3331 "language": "python",
3332 "metadata": {},
3333 "outputs": [
3334 {
3335 "metadata": {},
3336 "output_type": "pyout",
3337 "prompt_number": 24,
3338 "text": [
3339 "17639131"
3340 ]
3341 }
3342 ],
3343 "prompt_number": 24
3344 },
3345 {
3346 "cell_type": "code",
3347 "collapsed": false,
3348 "input": [],
3349 "language": "python",
3350 "metadata": {},
3351 "outputs": [],
3352 "prompt_number": 22
3353 }
3354 ],
3355 "metadata": {}
3356 }
3357 ]
3358 }
Teacher training using ciphers