In [1]:

    

from message import Message

with open('test.txt','r') as source:
    sample = source.read()
    
my_message = Message(sample)
my_message = my_message.filter()


    

In [2]:

    

counts = my_message.triplet_frequencies()


    

In [3]:

    

np.sum(counts)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-3-00841a469aef> in <module>()
----> 1 np.sum(counts)

NameError: name 'np' is not defined

In [4]:

    

import numpy as np


    

In [5]:

    

my_message.text


    

    
Out[5]:





'     '

In [6]:

    

a = [1,62,3,5,7,4,5,8,3,92]
b = np.argsort(a)
b[0:5]


    

    
Out[6]:





array([0, 2, 8, 5, 3], dtype=int64)

In [7]:

    

len('   ')


    

    
Out[7]:





3

In [74]:

    

import numpy as np

def best_keys(key_list, encrypted_message, natural_sample, number_returned = 10):
    metric_list = []
    for key in key_list:
        decryption_attempt = encrypted_message.substitute(key)
        metric = metric_function(decryption_attempt, natural_sample)
        metric.append(metric)
    ranking = np.argsort(metric_list)
    return key_list[ranking[0]:ranking[number_returned]]
    
def metric_function(decryption_attempt, natural_sample):
    decryption_attempt.triplet_frequencies()
    difference = abs(natural_sample.rates - decryption_attempt.rates)
    difference = np.absolute(difference) + 1e-10
    metric = -np.sum(1/difference)
    return metric

def metric_function2(decryption_attempt, natural_sample):
    decryption_attempt.triplet_frequencies()
    difference = abs(natural_sample.rates - decryption_attempt.rates)
    difference = np.absolute(difference)
    metric = -np.sum(difference)
    return metric


    

In [63]:

    

from message import Message

with open('sample.txt','r') as source:
    message1 = source.read()
with open('sample2.txt','r') as source:
    message2 = source.read()

message1 = Message(message1)
message2 = Message(message2)
    
message1 = message1.filter()
message2 = message2.filter()

message1.triplet_frequencies()
message2.triplet_frequencies()


    

In [71]:

    

metric_function(message1,message2)


    

    
Out[71]:





142123910345989.09

In [72]:

    

with open('test.txt','r') as source:
    message = source.read()

random_message = Message(message)


    

In [73]:

    

metric_function(random_message, message1)


    

    
Out[73]:





148620541785872.06

In [75]:

    

print metric_function(message1,message2)
print metric_function(random_message, message1)
print metric_function2(message1,message2)
print metric_function2(random_message, message1)


    

    




1.42123910346e+14
1.48620541786e+14
0.213559561829
1.98049264461

In [26]:

    

1 + 1e-3


    

    
Out[26]:





1.001

In [34]:

    

a = np.array([[1,2],[3,4]],dtype=np.float64)


    

In [35]:

    

1/a


    

    
Out[35]:





array([[ 1.        ,  0.5       ],
       [ 0.33333333,  0.25      ]])

In [33]:

    

type(a[0])


    

    
Out[33]:





numpy.float64

In [36]:

    

np.sum(a)


    

    
Out[36]:





10.0

In [ ]:

    

a = np.argsort(np.arange(5))


    

In [ ]:

    

a.size


    

In [ ]: