Test with tanimoto distance.

2 files changed, 13 insertions, 2 deletions

diff --git a/source/clusters.py b/source/clusters.py
index 7122c55d..bdfebe6e 100755
--- a/source/clusters.py
+++ b/source/clusters.py
@@ -38,6 +38,17 @@ def pearson(v1,v2):
 

   return 1.0-num/den

 

+def tanimoto(v1, v2):

+    c1, c2, shr = 0, 0, 0

+    for i in range(len(v1)):

+        if v1[i] != 0:

+            c1 += 1 # in v1

+        if v2[i] != 0:

+            c2 += 1 # in v2

+        if v1[i] != 0 and v2[i] != 0:

+            shr += 1 # in both

+    return 1.0 - (float(shr) / (c1 + c2 - shr))

+

 def kcluster(rows,distance=pearson,k=4):

   # Determine the minimum and maximum values for each point

   ranges=[(min([row[i] for row in rows]),max([row[i] for row in rows])) 

diff --git a/source/testclusters.py b/source/testclusters.py
index ea6406b1..a16d3492 100644
--- a/source/testclusters.py
+++ b/source/testclusters.py
@@ -2,14 +2,14 @@
 
 import clusters
 
-K = 8
+K = 7
 
 blognames,words,data = clusters.readfile("blogdata1.txt")
 
 coords = clusters.scaledown(data)
 
 print "Generating clusters..."
-kclust = clusters.kcluster(data, k=K)
+kclust = clusters.kcluster(data, k=K, distance=clusters.pearson)
 print
 print "Clusters:"
 for i in range(K):