__author__ = 'Placinta'
from Models import Models
encrypted_string = "Esp qtcde nzyqpcpynp zy esp ezatn zq Lcetqtntlw Tyepwwtrpynp hld spwo le Olcexzfes Nzwwprp ty estd jplc".upper(
)
new_string = ''
count = len(encrypted_string)
possibilities = []
corp = Models()
corp.createWordUniGramModel()
for i in range(1, 37):
character_list = []
new_string = ""
for j in range(0, count):
if encrypted_string[j] == ' ':
character_list.append(' ')
else:
character_list.append(
chr((ord(encrypted_string[j]) - 0x41 + i) % 26 + 0x41))
new_string = "".join(character_list).lower()
possibilities.append(new_string)
#print "{0}:".format(i)
max_prob = -10000
max_string = ''
for string in possibilities:
probability = corp.getWordProbability(string)
if probability > max_prob:
max_prob = probability
max_string = string
class Unshred:
def __init__(self, verbose = False):
self.encrypted_string = (
"de| | f|Cl|nf|ed|au| i|ti| |ma|ha|or|nn|ou| S|on|nd|on" "\n"
"ry| |is|th|is| b|eo|as| | |f |wh| o|ic| t|, | |he|h " "\n"
"ab| |la|pr|od|ge|ob| m|an| |s |is|el|ti|ng|il|d |ua|c " "\n"
"he| |ea|of|ho| m| t|et|ha| | t|od|ds|e |ki| c|t |ng|br" "\n"
"wo|m,|to|yo|hi|ve|u | t|ob| |pr|d |s |us| s|ul|le|ol|e " "\n"
' t|ca| t|wi| M|d |th|"A|ma|l |he| p|at|ap|it|he|ti|le|er' "\n"
'ry|d |un|Th|" |io|eo|n,|is| |bl|f |pu|Co|ic| o|he|at|mm' "\n"
"hi| | |in| | | t| | | | |ye| |ar| |s | | |. ")
self.rows = 8
self.columns = 19
self.matrix = [ [ 0 for i in range(self.columns) ] for j in range(self.rows) ]
self.combination = Combination(self.rows, self.columns)
self.used_column_indices = []
self.verbose = verbose
def iterate_lines(self, foo): return iter(foo.splitlines())
def parseIntoMatrix(self):
i = 0
for line in self.iterate_lines(self.encrypted_string):
row_values = line.split('|')
for j, value in enumerate(row_values):
if value != '':
self.matrix[i][j] = value
i += 1
def initModels(self):
self.corp = Models()
self.corp.createLetterModel()
self.corp.createWordUniGramModel()
def computeCombinationProbability(self, phrases):
sum = 0
for phrase in phrases:
sum += self.corp.getLetterProbabilities(phrase)
sum += self.corp.getWordProbabilities(phrase)
if self.verbose:
print '{0:15f} |{1:s}|'.format(sum, phrases[0])
#print sum, phrases
return sum
def getBestCombination(self):
max_prob = -100000
max_combination = ''
max_index = 0
for index, pair in enumerate(self.matrix[0]):
# Don't check columns we already added
if index in self.used_column_indices:
continue
temp_combination = copy.deepcopy(self.combination)
# Get column values for index
new_column_values = [self.matrix[i][index] for i in range(self.rows)]
temp_combination.appendColumn(new_column_values)
phrases_to_check = temp_combination.returnPhrases()
# Compute probabilities
probability = self.computeCombinationProbability(phrases_to_check)
if probability > max_prob:
max_prob = probability
max_combination = temp_combination
max_index = index
if self.verbose:
print '->{0:13f} |{1:s}|'.format(max_prob, max_combination.returnFirstPhrase())
self.used_column_indices.append(max_index)
return max_prob, max_combination
def unshred(self):
# Find uppercase
for index, pair in enumerate(self.matrix[0]):
if pair[0].isupper():
self.combination.appendColumn([self.matrix[i][index] for i in range(self.rows)])
self.used_column_indices.append(index)
break
# Find next best combinations and append them
for i in range(1, 19):
prob, combination = self.getBestCombination()
#print prob, combination
self.combination = combination
def displayResult(self):
print '\n The unencrypted message is:\n'
self.combination.display()
def execute(self):
self.parseIntoMatrix()
self.initModels()
self.unshred()
self.displayResult()
return
