add euclidean and manhattan similarity

usc-isi-i2 · Jun 3, 2020 · 4490f7a · 4490f7a
1 parent 1885a45
commit 4490f7a
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Showing 2 changed files with 17 additions and 2 deletions.
diff --git a/rltk/similarity/__init__.py b/rltk/similarity/__init__.py
@@ -1,5 +1,6 @@
-# distance
-from rltk.similarity.distance import euclidean_distance, manhattan_distance
+# common distance
+from rltk.similarity.distance import euclidean_distance, euclidean_similarity, \
+    manhattan_distance, manhattan_similarity
 
 # normal
 from rltk.similarity.equal import string_equal, number_equal

diff --git a/rltk/similarity/distance.py b/rltk/similarity/distance.py
@@ -27,6 +27,13 @@ def euclidean_distance(vec1, vec2, weights=None):
     return euclidean(vec1, vec2, weights)
 
 
+def euclidean_similarity(vec1, vec2, weights=None):
+    """
+    Computed as 1 / (1 + euclidean_distance)
+    """
+    return 1.0 / (1.0 + float(euclidean_distance(vec1, vec2, weights)))
+
+
 def manhattan_distance(vec1, vec2, weights=None):
     """
     Manhattan distance.
@@ -47,3 +54,10 @@ def manhattan_distance(vec1, vec2, weights=None):
         raise ValueError('vec1 and vec2 should have same length')
 
     return cityblock(vec1, vec2, weights)
+
+
+def manhattan_similarity(vec1, vec2, weights=None):
+    """
+    Computed as 1 / (1 + manhattan_distance)
+    """
+    return 1.0 / (1.0 + manhattan_distance(vec1, vec2, weights))