X-Git-Url: https://git.njae.me.uk/?a=blobdiff_plain;f=cipher.py;h=f2c6775223f726de2386c4d674c829e19922dd55;hb=3dc63370f2be9afe868b79d836613aba24f1a06d;hp=b3ab488db74c3af8090aefcc2396c2d503725064;hpb=3b82269b94de43fa0150fe5b34ca39b4ba3b6ba4;p=cipher-tools.git

diff --git a/cipher.py b/cipher.py
index b3ab488..f2c6775 100644
--- a/cipher.py
+++ b/cipher.py
@@ -7,6 +7,14 @@ with open('count_1l.txt', 'r') as f:
         (letter, count) = line.split("\t")
         english_counts[letter] = int(count)
 
+modular_division = [[0]* 26 for i in range(26)]
+for i in range(26):
+    for j in range(26):
+        t = (i*j) % 26
+        # therefore,  i = t / j
+        modular_division[t][j] = i
+
+
 def sanitise(text):
     sanitised = [c.lower() for c in text if c in string.ascii_letters]
     return ''.join(sanitised)
@@ -17,6 +25,21 @@ def letter_frequencies(message):
         frequencies[letter]+=1
     return frequencies
 
+def scale_freq(frequencies):
+    total= sum(frequencies.values())
+    scaled_frequencies = collections.defaultdict(int)
+    for letter in frequencies.keys():
+        scaled_frequencies[letter] = frequencies[letter] / total
+    return scaled_frequencies
+
+def value_diff(frequencies1, frequencies2):
+    total= 0
+    for letter in frequencies1.keys():
+        total += abs(frequencies1[letter]-frequencies2[letter])
+    return total
+        
+    
+
 def caesar_cipher_letter(letter, shift):
     if letter in string.ascii_letters:
         if letter in string.ascii_lowercase:
@@ -37,3 +60,73 @@ def caesar_cipher_message(message, shift):
 
 def caesar_decipher_message(message, shift):
     return caesar_cipher_message(message, -shift)
+
+def affine_cipher_letter(letter, multiplier, shift, one_based=True):
+    if letter in string.ascii_letters:
+        if letter in string.ascii_lowercase:
+            alphastart = ord('a')
+        else:
+            alphastart = ord('A')
+        letter_number = ord(letter) - alphastart
+        if one_based: letter_number += 1  
+        enciphered_letter_number = letter_number * multiplier + shift
+        if one_based: enciphered_letter_number -=1
+        enciphered_letter = chr(enciphered_letter_number % 26 + alphastart)
+        return enciphered_letter
+    else:
+        return letter
+         
+def affine_decipher_letter(letter, multiplier, shift, one_based=True):
+    if letter in string.ascii_letters:
+        if letter in string.ascii_lowercase:
+            alphastart = ord('a')
+        else:
+            alphastart = ord('A')  
+        letter_number = ord(letter) - alphastart
+        if one_based: letter_number +=1   
+        after_unshift = letter_number - shift 
+        deciphered_letter_number = modular_division[after_unshift % 26][multiplier]
+        if one_based: deciphered_letter_number -=1
+        deciphered_letter = chr(deciphered_letter_number % 26 + alphastart)
+        return deciphered_letter
+    else:
+        return letter
+    
+def affine_cipher_message(message, multiplier, shift, one_based=True):
+    big_cipher = [affine_cipher_letter(l, multiplier, shift, one_based) for l in message]
+    return ''.join(big_cipher)    
+      
+def affine_decipher_message(message, multiplier, shift, one_based=True):
+    big_decipher = [affine_decipher_letter(l, multiplier, shift, one_based) for l in message]
+    return ''.join(big_decipher)
+
+
+def caesar_break(message):
+    best_key = 0
+    best_fit = float("inf")
+    for shift in range(26):
+        plaintxt = caesar_decipher_message(message, shift)
+        lettertxt = letter_frequencies(plaintxt)
+        total1 = scale_freq(lettertxt)
+        total2 = scale_freq(english_counts)
+        fit = value_diff(total2, total1)
+        if fit < best_fit:
+            best_key = shift
+            best_fit = fit
+    return best_key
+
+def affine_break(message):
+    best_key = (0, 0, 0)
+    best_fit = float("inf")
+    for multiplier in range(1, 26, 2):
+        for shift in range(26):
+            for one_based in [True, False]:
+                plaintxt = affine_decipher_message(message, multiplier, shift, one_based)
+                lettertxt = letter_frequencies(plaintxt)
+                total1 = scale_freq(lettertxt)
+                total2 = scale_freq(english_counts)
+                fit = value_diff(total2, total1)c
+                if fit < best_fit:
+                    best_key = (multiplier, shift, one_based)
+                    best_fit = fit
+    return best_key