larsmans · July 15, 2012 13:25 · Jul 15, 2012 · Jul 15, 2012
diff --git a/hellinger.py b/hellinger.py
@@ -8,7 +8,7 @@
 from scipy.spatial.distance import euclidean
 
 
-_SQRT2 = np.sqrt(2)     # sqrt(2) with default precision np.float64)
+_SQRT2 = np.sqrt(2)     # sqrt(2) with default precision np.float64
 
 
 def hellinger1(p, q):

diff --git a/hellinger.py b/hellinger.py
@@ -0,0 +1,23 @@
+"""
+Three ways of computing the Hellinger distance between two discrete
+probability distributions using NumPy and SciPy.
+"""
+
+import numpy as np
+from scipy.linalg import norm
+from scipy.spatial.distance import euclidean
+
+
+_SQRT2 = np.sqrt(2)     # sqrt(2) with default precision np.float64)
+
+
+def hellinger1(p, q):
+    return norm(np.sqrt(p) - np.sqrt(q)) / _SQRT2
+
+
+def hellinger2(p, q):
+    return euclidean(np.sqrt(p), np.sqrt(q)) / _SQRT2
+
+
+def hellinger3(p, q):
+    return np.sqrt(np.sum((np.sqrt(p) - np.sqrt(q)) ** 2)) / _SQRT2