# 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()