# Stephanie Taylor
# clustering_test2.py
# Spring 2014
import numpy as np
import analysis
import sys
def main( ):
mat = np.matrix( [[0.0,1.0],
[1.0,0.1],
[0.9,1.0],
[0.7,0.6]] )
means = np.matrix( [[0.0,0.1], [0.95,1.0]] )
N = mat.shape[0]
F = mat.shape[1]
k = means.shape[0]
(cluster_idxs,cluster_distances) = analysis.kmeans_classify( mat, means )
print "for data:"
print mat
print 'with "means":'
print means
print "the indices are :"
print cluster_idxs
print "and each point is this distance from the mean of its cluster:"
print cluster_distances
if __name__ == '__main__':
main()