import collections
import logging
from itertools import zip_longest, cycle, chain
-from counts import *
-
+from language_models import *
logger = logging.getLogger(__name__)
logger.addHandler(logging.FileHandler('cipher.log'))
#logger.setLevel(logging.DEBUG)
-english_counts = collections.defaultdict(int)
-with open('count_1l.txt', 'r') as f:
- for line in f:
- (letter, count) = line.split("\t")
- english_counts[letter] = int(count)
-normalised_english_counts = norms.normalise(english_counts)
-
-choices, weights = zip(*weighted_choices)
-cumdist = list(itertools.accumulate(weights))
-x = random.random() * cumdist[-1]
-choices[bisect.bisect(cumdist, x)]
-
-
modular_division_table = [[0]*26 for x in range(26)]
for a in range(26):
for b in range(26):
emptycolumnwise=False):
"""Enciphers using the column transposition cipher.
Message is padded to allow all rows to be the same length.
-
- >>> column_transposition_encipher('hellothere', 'clever')
- 'hleolteher'
- >>> column_transposition_encipher('hellothere', 'cleverly', fillvalue='!')
- 'hleolthre!e!'
- >>> column_transposition_encipher('hellothere', 'clever', columnwise=True)
- 'htleehoelr'
"""
+ # >>> column_transposition_encipher('hellothere', 'clever')
+ # 'hleolteher'
+ # >>> column_transposition_encipher('hellothere', 'cleverly', fillvalue='!')
+ # 'hleolthre!e!'
+ # >>> column_transposition_encipher('hellothere', 'clever', columnwise=True)
+ # 'htleehoelr'
+ # """
transpositions = transpositions_of(keyword)
message += pad(len(message), len(transpositions), fillvalue)
if fillcolumnwise:
columnwise=False):
"""Deciphers using the column transposition cipher.
Message is padded to allow all rows to be the same length.
-
- >>> column_transposition_decipher('hleolteher', 'clever')
- 'hellothere'
- >>> column_transposition_decipher('hleolthre!e!', 'cleverly', fillvalue='?')
- 'hellothere!!'
- >>> column_transposition_decipher('htleehoelr', 'clever', columnwise=True)
- 'hellothere'
"""
+ # >>> column_transposition_decipher('hleolteher', 'clever')
+ # 'hellothere'
+ # >>> column_transposition_decipher('hleolthre!e!', 'cleverly', fillvalue='?')
+ # 'hellothere!!'
+ # >>> column_transposition_decipher('htleehoelr', 'clever', columnwise=True)
+ # 'hellothere'
+ # """
transpositions = transpositions_of(keyword)
if columnwise:
columns = chunks(message, int(len(message) / len(transpositions)))
import matplotlib.pyplot as plt
-from counts import *
from cipher import *
+from language_models import *
# To time a run:
#
# timeit.timeit('keyword_break(c5a)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break', number=1)
# timeit.repeat('keyword_break_mp(c5a, chunksize=500)', setup='gc.enable() ; from __main__ import c5a ; from cipher import keyword_break_mp', repeat=5, number=1)
-with open('words.txt', 'r') as f:
- keywords = [line.rstrip() for line in f]
-
transpositions = collections.defaultdict(list)
for word in keywords:
transpositions[transpositions_of(word)] += [word]
chunksize=500):
"""Breaks a column transposition cipher using a dictionary and
n-gram frequency analysis
-
- >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
- "It is a truth universally acknowledged, that a single man in \
- possession of a good fortune, must be in want of a wife. However \
- little known the feelings or views of such a man may be on his \
- first entering a neighbourhood, this truth is so well fixed in the \
- minds of the surrounding families, that he is considered the \
- rightful property of some one or other of their daughters."), \
- 'encipher'), \
- translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
- (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
- (6, 1, 0, 4, 5, 3, 2): ['keyword']}) # doctest: +ELLIPSIS
- (((2, 0, 5, 3, 1, 4, 6), False), 0.0628106372...)
- >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
- "It is a truth universally acknowledged, that a single man in \
- possession of a good fortune, must be in want of a wife. However \
- little known the feelings or views of such a man may be on his \
- first entering a neighbourhood, this truth is so well fixed in the \
- minds of the surrounding families, that he is considered the \
- rightful property of some one or other of their daughters."), \
- 'encipher'), \
- translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
- (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
- (6, 1, 0, 4, 5, 3, 2): ['keyword']}, \
- target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
- (((2, 0, 5, 3, 1, 4, 6), False), 0.0592259560...)
"""
+ # >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
+ # "It is a truth universally acknowledged, that a single man in \
+ # possession of a good fortune, must be in want of a wife. However \
+ # little known the feelings or views of such a man may be on his \
+ # first entering a neighbourhood, this truth is so well fixed in the \
+ # minds of the surrounding families, that he is considered the \
+ # rightful property of some one or other of their daughters."), \
+ # 'encipher'), \
+ # translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ # (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ # (6, 1, 0, 4, 5, 3, 2): ['keyword']}) # doctest: +ELLIPSIS
+ # (((2, 0, 5, 3, 1, 4, 6), False), 0.0628106372...)
+ # >>> column_transposition_break_mp(column_transposition_encipher(sanitise( \
+ # "It is a truth universally acknowledged, that a single man in \
+ # possession of a good fortune, must be in want of a wife. However \
+ # little known the feelings or views of such a man may be on his \
+ # first entering a neighbourhood, this truth is so well fixed in the \
+ # minds of the surrounding families, that he is considered the \
+ # rightful property of some one or other of their daughters."), \
+ # 'encipher'), \
+ # translist={(2, 0, 5, 3, 1, 4, 6): ['encipher'], \
+ # (5, 0, 6, 1, 3, 4, 2): ['fourteen'], \
+ # (6, 1, 0, 4, 5, 3, 2): ['keyword']}, \
+ # target_counts=normalised_english_trigram_counts) # doctest: +ELLIPSIS
+ # (((2, 0, 5, 3, 1, 4, 6), False), 0.0592259560...)
+ # """
ngram_length = len(next(iter(target_counts.keys())))
with Pool() as pool:
helper_args = [(message, trans, columnwise, metric, target_counts, ngram_length,
--- /dev/null
+import norms
+import itertools
+import random
+import bisect
+import collections
+
+english_counts = collections.defaultdict(int)
+with open('count_1l.txt', 'r') as f:
+ for line in f:
+ (letter, count) = line.split("\t")
+ english_counts[letter] = int(count)
+normalised_english_counts = norms.normalise(english_counts)
+
+english_bigram_counts = collections.defaultdict(int)
+with open('count_2l.txt', 'r') as f:
+ for line in f:
+ (bigram, count) = line.split("\t")
+ english_bigram_counts[bigram] = int(count)
+normalised_english_bigram_counts = norms.normalise(english_bigram_counts)
+
+english_trigram_counts = collections.defaultdict(int)
+with open('count_3l.txt', 'r') as f:
+ for line in f:
+ (trigram, count) = line.split("\t")
+ english_trigram_counts[trigram] = int(count)
+normalised_english_trigram_counts = norms.normalise(english_trigram_counts)
+
+with open('words.txt', 'r') as f:
+ keywords = [line.rstrip() for line in f]
+
+def weighted_choice(d):
+ """Generate a set of random items from a dictionary of item counts
+ """
+ target = random.uniform(0, sum(d.values()))
+ cuml = 0.0
+ for (l, p) in d.items():
+ cuml += p
+ if cuml > target:
+ return l
+ return None
+
+def random_english_letter():
+ """Generate a random letter based on English letter counts
+ """
+ return weighted_choice(normalised_english_counts)
projects / cipher-tools.git / commitdiff