Chimie Théorique » scripts_chimie4psmn » DockOnSurf

#!/usr/bin/env python

# -*- coding: utf-8 -*-

import sys

import numpy as np

import sklearn

from sklearn import cluster

from sklearn.cluster import AffinityPropagation

matrice = sys.argv[1]

X = np.loadtxt(matrice) # lecture de la matrice à partir d'un fichier

if len(X.shape)==0:

    print 'Number of clusters: 1'

    print 'Cluster centers:'

    print '0'

    print 'Cluster groups:'

    print '0'

else:

    af = AffinityPropagation(affinity='precomputed').fit(X)

    cluster_centers_indices = af.cluster_centers_indices_

    labels = af.labels_

    n_clusters_ = len(cluster_centers_indices)

    print('Number of clusters: %d' % n_clusters_)

    print 'Cluster centers:' 

    print cluster_centers_indices

    def ClusterIndicesNumpy(clustNum, labels_array): #numpy 

            return np.where(labels_array == clustNum)[0]

    print 'Cluster groups:'

    for i in range(0,n_clusters_) :

        a = ClusterIndicesNumpy(i, labels)

        print a