Built enigma machine

[cipher-training.git] / norms.py

diff --git a/norms.py b/norms.py
index 37fd3c93329aa018b31fdf7f9a944eb496c41d44..eb436c3b8163141a3ada1f1f02f8be741d6f47fb 100644 (file)
--- a/norms.py
+++ b/norms.py
@@ -13,7 +13,7 @@ def normalise(frequencies):
     >>> sorted(normalise({1: 1, 2: 2, 3: 1}).items())
     [(1, 0.25), (2, 0.5), (3, 0.25)]
     """
     >>> sorted(normalise({1: 1, 2: 2, 3: 1}).items())
     [(1, 0.25), (2, 0.5), (3, 0.25)]
     """

-    length = sum([f for f in frequencies.values()])
+    length = sum(f for f in frequencies.values())

     return collections.defaultdict(int, ((k, v / length) 
         for (k, v) in frequencies.items()))
 
     return collections.defaultdict(int, ((k, v / length) 
         for (k, v) in frequencies.items()))
 


@@ -163,13 +163,13 @@ def cosine_similarity(frequencies1, frequencies2):
     """Finds the distances between two frequency profiles, expressed as dictionaries.
     Assumes every key in frequencies1 is also in frequencies2
 
     """Finds the distances between two frequency profiles, expressed as dictionaries.
     Assumes every key in frequencies1 is also in frequencies2
 

-    >>> cosine_distance({'a':1, 'b':1, 'c':1}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS
+    >>> cosine_similarity({'a':1, 'b':1, 'c':1}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS

     1.0000000000...
     1.0000000000...

-    >>> cosine_distance({'a':2, 'b':2, 'c':2}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS
+    >>> cosine_similarity({'a':2, 'b':2, 'c':2}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS

     1.0000000000...
     1.0000000000...

-    >>> cosine_distance({'a':0, 'b':2, 'c':0}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS
+    >>> cosine_similarity({'a':0, 'b':2, 'c':0}, {'a':1, 'b':1, 'c':1}) # doctest: +ELLIPSIS

     0.5773502691...
     0.5773502691...

-    >>> cosine_distance({'a':0, 'b':1}, {'a':1, 'b':1}) # doctest: +ELLIPSIS
+    >>> cosine_similarity({'a':0, 'b':1}, {'a':1, 'b':1}) # doctest: +ELLIPSIS

     0.7071067811...
     """
     numerator = 0
     0.7071067811...
     """
     numerator = 0


@@ -178,7 +178,7 @@ def cosine_similarity(frequencies1, frequencies2):
     for k in frequencies1:
         numerator += frequencies1[k] * frequencies2[k]
         length1 += frequencies1[k]**2
     for k in frequencies1:
         numerator += frequencies1[k] * frequencies2[k]
         length1 += frequencies1[k]**2

-    for k in frequencies2.keys():
+    for k in frequencies2:

         length2 += frequencies2[k]**2
     return numerator / (length1 ** 0.5 * length2 ** 0.5)
 
         length2 += frequencies2[k]**2
     return numerator / (length1 ** 0.5 * length2 ** 0.5)