import kMeans

from numpy import*

import matplotlib

import matplotlib.pyplot as plt

k = 4

datmat = array(kMeans.loadDataSet('testSet.txt'))

centerList, clusterAssment = kMeans.biKmeans(datmat,k)

print 'The cendroids is:',centerList

fig = plt.figure()

fig.add_subplot(111)

colorList = ['b','c','g','k','r','y']

makerList = ['.','^','*','o','+']

for i in range(k):

ax = plt.scatter(datmat[nonzero(clusterAssment[:,0].A == i)[0],0],datmat[nonzero(clusterAssment[:,0].A == i)[0],1],

c = colorList[i],marker=makerList[i])

ax = plt.scatter(array(centerList[:,0]),array(centerList[:,1]),c = colorList[4],marker=makerList[3])

plt.title('Graph of k_Means ',)

plt.xlabel('x')

plt.ylabel('y')

plt.show()