some small fixes

Cryptography/RotationCiphers/taste_like_english.py

@@ -0,0 +1,87 @@
+#!/usr/bin/env python
+
+__author__ = "Mari Wahl"
+__email__ = "marina.w4hl@gmail.com"
+
+'''
+This program calculate the frequency of letters in a files
+so we can use this for cryptoanalysis later.
+
+For example, the 10 most frequent words in english:
+e -> 0.104
+t -> 0.072
+a -> 0.065
+0 -> 0.059
+n -> 0.056
+i -> 0.055
+s -> 0.051
+r -> 0.049
+h -> 0.049
+d -> 0.034
+'''
+
+import chardet
+from collections import defaultdict
+
+
+# calculate the mean values from the table
+def taste_like_english(dict_mean, word):
+    mean_word = 0
+    counter = 0
+    for c in word:
+        if c in dict_mean.keys():
+            mean_word += dict_mean[c]
+            counter += 1
+    return mean_word/counter
+
+
+
+
+# count number of letters
+def count_letters(FILE):
+    dict_letters = defaultdict(int)
+    with open(FILE) as file:
+        for line in file:
+            for word in line.lower().split():
+                    for c in word:
+                        if c!='!' and c!="," and c!="-" and c!="."\
+                         and c!=";" and chardet.detect(c)['encoding'] == 'ascii':
+                            dict_letters[c] += 1
+    return dict_letters
+
+
+
+# calculate the frequency for the letters
+def calculate_mean(dict_letters):
+    dict_mean = defaultdict(float)
+    sum_all = sum(dict_letters.values())
+    for letter in sorted(dict_letters.keys()):
+        dict_mean[letter] = float(dict_letters[letter])/sum_all
+    return dict_mean
+
+
+
+
+# first, test letters with official values
+def test_values():
+    dict_letters_test = {'e':0.104, 't':0.072, 'a':0.065, 'o':0.059, \
+        'n': 0.056, 'i': 0.055, 's':0.051, 'r':0.049, 'h':0.049, 'd':0.034}
+    print('Test for "english": ', taste_like_english(dict_letters_test, 'english')) # == 0.045"
+
+
+
+# now, test with some file, creating dictionary of letters
+def test_file():
+    dict_letters = count_letters(FILE)
+    dict_mean = calculate_mean(dict_letters)
+    for key in sorted(dict_mean, key=dict_mean.get, reverse=True):
+        print(key + ' --> ' + str(dict_mean[key]))
+
+
+
+
+if __name__ == '__main__':
+    test_values()
+
+    FILE = 'Ariel_Sylvia_Plath.txt'
+    test_file()