_2_clustering.py

from sklearn.cluster import KMeans

kmeans_0 = KMeans(n_clusters=10, init='k-means++',random_state=0).fit(label_0)
sample_0 = kmeans_0.cluster_centers_

kmeans_1 = KMeans(n_clusters=10, init='k-means++',random_state=0).fit(label_1)
sample_1 = kmeans_1.cluster_centers_
#the code can be repeated for all the intermediate labels
#...
kmeans_9 = KMeans(n_clusters=10, init='k-means++',random_state=0).fit(label_9)
sample_9 = kmeans_9.cluster_centers_