return best_alphabet, best_fitness
-def column_transposition_break_mp(message, translist=transpositions,
- fitness=Pbigrams, 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, False), -709.4646722...)
- >>> 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']}, \
- fitness=Ptrigrams) # doctest: +ELLIPSIS
- (((2, 0, 5, 3, 1, 4, 6), False, False), -997.0129085...)
- """
- with Pool() as pool:
- helper_args = [(message, trans, fillcolumnwise, emptycolumnwise,
- fitness)
- for trans in translist.keys()
- for fillcolumnwise in [True, False]
- for emptycolumnwise in [True, False]]
- # Gotcha: the helper function here needs to be defined at the top level
- # (limitation of Pool.starmap)
- breaks = pool.starmap(column_transposition_break_worker,
- helper_args, chunksize)
- return max(breaks, key=lambda k: k[1])
-column_transposition_break = column_transposition_break_mp
-
-def column_transposition_break_worker(message, transposition,
- fillcolumnwise, emptycolumnwise, fitness):
- plaintext = column_transposition_decipher(message, transposition,
- fillcolumnwise=fillcolumnwise, emptycolumnwise=emptycolumnwise)
- fit = fitness(sanitise(plaintext))
- logger.debug('Column transposition break attempt using key {0} '
- 'gives fit of {1} and decrypt starting: {2}'.format(
- transposition, fit,
- sanitise(plaintext)[:50]))
- return (transposition, fillcolumnwise, emptycolumnwise), fit
-
-
-def scytale_break_mp(message, max_key_length=20,
- fitness=Pbigrams, chunksize=500):
- """Breaks a scytale cipher using a range of lengths and
- n-gram frequency analysis
-
- >>> scytale_break_mp(scytale_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."), \
- 5)) # doctest: +ELLIPSIS
- (5, -709.4646722...)
- >>> scytale_break_mp(scytale_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."), \
- 5), \
- fitness=Ptrigrams) # doctest: +ELLIPSIS
- (5, -997.0129085...)
- """
- with Pool() as pool:
- helper_args = [(message, trans, False, True, fitness)
- for trans in
- [[col for col in range(math.ceil(len(message)/rows))]
- for rows in range(1,max_key_length+1)]]
- # Gotcha: the helper function here needs to be defined at the top level
- # (limitation of Pool.starmap)
- breaks = pool.starmap(column_transposition_break_worker,
- helper_args, chunksize)
- best = max(breaks, key=lambda k: k[1])
- return math.trunc(len(message) / len(best[0][0])), best[1]
-scytale_break = scytale_break_mp
-
-
def vigenere_keyword_break_mp(message, wordlist=keywords, fitness=Pletters,
chunksize=500):
"""Breaks a vigenere cipher using a dictionary and frequency analysis.
return keyword, fit
-
def vigenere_frequency_break(message, max_key_length=20, fitness=Pletters):
"""Breaks a Vigenere cipher with frequency analysis
english_counts = collections.Counter(dict(datafile('count_1l.txt')))
normalised_english_counts = norms.normalise(english_counts)
-english_bigram_counts = collections.Counter(dict(datafile('count_2l.txt')))
-normalised_english_bigram_counts = norms.normalise(english_bigram_counts)
-
-english_trigram_counts = collections.Counter(dict(datafile('count_3l.txt')))
-normalised_english_trigram_counts = norms.normalise(english_trigram_counts)
-
with open('words.txt', 'r') as f:
keywords = [line.rstrip() for line in f]
return weighted_choice(normalised_english_counts)
-def ngrams(text, n):
- """Returns all n-grams of a text
-
- >>> ngrams(sanitise('the quick brown fox'), 2) # doctest: +NORMALIZE_WHITESPACE
- ['th', 'he', 'eq', 'qu', 'ui', 'ic', 'ck', 'kb', 'br', 'ro', 'ow', 'wn',
- 'nf', 'fo', 'ox']
- >>> ngrams(sanitise('the quick brown fox'), 4) # doctest: +NORMALIZE_WHITESPACE
- ['theq', 'hequ', 'equi', 'quic', 'uick', 'ickb', 'ckbr', 'kbro', 'brow',
- 'rown', 'ownf', 'wnfo', 'nfox']
- """
- return [text[i:i+n] for i in range(len(text)-n+1)]
-
-
class Pdist(dict):
"""A probability distribution estimated from counts in datafile.
Values are stored and returned as log probabilities.
"""
return sum(Pl[l.lower()] for l in letters)
-def Pbigrams(letters):
- """The Naive Bayes log probability of the bigrams formed from a sequence
- of letters.
- """
- return sum(P2l[p] for p in ngrams(letters, 2))
-
-def Ptrigrams(letters):
- """The Naive Bayes log probability of the trigrams formed from a sequence
- of letters.
- """
- return sum(P3l[p] for p in ngrams(letters, 3))
-
def cosine_similarity_score(text):
"""Finds the dissimilarity of a text to English, using the cosine distance
projects / cipher-training.git / commitdiff