from sklearn.cluster import KMeans
import numpy as np
X = np.array([[25,79,79],[34,51,51],[22,53,53],[27,78,78],[33,59,59],[33,74,74],[31,73,73]
            ,[22,57,57],[35,69,69],[34,75,75],[67,51,51],[54,32,32],[57,40,40],[43,47,47]
            ,[50,53,53],[57,36,57],[59,35,59],[52,58,52],[65,59,65],[47,50,47],[49,25,49]
            ,[48,20,48],[35,14,35],[33,12,33],[44,20,44],[45,5,45],[38,29,38],[43,27,43]
            ,[51,8,51],[46,7,46]])

centro=np.array([[10,50,75],[11,60,55],[2,30,31]])
kmeans = KMeans(n_clusters=3, init=centro).fit(X)
#kmeans = KMeans(n_clusters=2, random_state=0).fit(X)
print (kmeans.labels_)

print (kmeans.predict([[12,3,5],[0,0,0]]))

print (kmeans.cluster_centers_)