do classification using kmeans
then plot the centra
'''
# from sklearn.cluster import KMeans
# km = KMeans(n_clusters=3)
# km.fit(avg_filt)
# centras = km.cluster_centers_
xlabel = [int(x) for x in times_label]
# class_percentage = {}
# for i in xrange(km.n_clusters):
# class_percentage[i] = 0
# for i in km.labels_:
# class_percentage[i]+=1
# for i in xrange(km.n_clusters):
# print class_percentage[i]*1.0/len(km.labels_)
# for idx, data in enumerate(centras):
# painter.plotLine(xlabel,data,str(idx))
for data in avg_filt:
painter.plotLine(xlabel,data,None,'r*')
painter.showplot(xlabel)
#painter.showLegend()
painter.newFigure()
painter.plotLine(xlabel, time_counts,"number of new urls","r")
def cumulativeSum(vlist,start = 0):
for v in vlist:
start+= v
yield start
painter.plotBar(xlabel,[len(t) for t in time_urls.values()],None,"Hourly URLs","Communicative URLs")
painter.showplot(xlabel)
print "finish!"
