--- a/python/ml.py	Fri Jun 20 00:20:29 2014 -0400
+++ b/python/ml.py	Fri Jun 20 17:45:32 2014 -0400
@@ -58,7 +58,7 @@
     Either the initialCentroids or k are passed'''
     pass
 
-def assignCluster(data, similarFunc, initialCentroids = [], shuffleData = True):
+def assignCluster(data, similarFunc, initialCentroids = None, shuffleData = True):
     '''k-means algorithm with similarity function
     Two instances should be in the same cluster if the sameCluster function returns true for two instances. It is supposed that the average centroid of a set of instances can be computed, using the function. 
     The number of clusters will be determined accordingly
@@ -71,10 +71,10 @@
     localdata = copy(data) # shallow copy to avoid modifying data
     if shuffleData:
         shuffle(localdata)
-    if initialCentroids:
+    if initialCentroids == None:
+        centroids = [Centroid(localdata[0])]
+    else:
         centroids = deepcopy(initialCentroids)
-    else:
-        centroids = [Centroid(localdata[0])]
     for instance in localdata[1:]:
         i = 0
         while i<len(centroids) and not similarFunc(centroids[i].instance, instance):