for j in range(0, len(cluster)):
if phi[j]==0:
cluster1.append(cluster[j])
indexes1.append(j+1)
elif phi[j]==1:
cluster2.append(cluster[j])
indexes2.append(j+1)
elif phi[j]==2:
cluster3.append(cluster[j])
indexes3.append(j+1)
print '\n Indexes are :'
print '******************************'
print 'Cluster 1:', indexes1
print '******************************'
print 'Cluster 2:', indexes2
print '******************************'
print 'Cluster 3:', indexes3
print '******************************'
""" Plotting the data """
title="Clustering using Llyods algorithm with C initially with points indexed {1,2,3}"
HC.lloyds_plot(cluster,phi,c,title)
x = phi[i]
means_cost += (((c[x][0] - cluster[i][0])**2 +
(c[x][1] - cluster[i][1])**2)**0.5)**2
#means_cost=means_cost/ float(len(cluster))
print '3-means cost is :', means_cost
print '\n Indexes are :'
print '******************************'
print 'Cluster 1:', indexes1
print '******************************'
print 'Cluster 2:', indexes2
print '******************************'
print 'Cluster 3:', indexes3
print '******************************'
""" Plotting the data """
title = "Clustering using Gonzalez algorithm "
HC.lloyds_plot(cluster, phi, c, title)
"""
print '\n Subsets are :'
print '******************************'
print 'Subset 1:', subset1
print '******************************'
print 'Subset 2:', subset2
print '******************************'
print 'Subset 3:', subset3
print '******************************'
"""
