重み無し無向グラフのクラスター係数を隣接行列から求める

cluster_coef_for_unweighted_undirected_graph.py

# -*- coding: utf-8 -*-
from __future__ import print_function
import numpy as np

# it's for unweighted and undirected graph.
# Adjency matrix of the graph
adjency_mat = np.array([[0, 1, 1, 1, 0, 0],
                        [1, 0, 1, 0, 0, 1],
                        [1, 1, 0, 1, 1, 0],
                        [1, 0, 1, 0, 1, 0],
                        [0, 0, 1, 1, 0, 1],
                        [0, 1, 0, 0, 1, 0]])

mask_mat = (adjency_mat == 1)
adj_square = np.dot(adjency_mat, adjency_mat)

# k is the vector of the degree of nodes
k = adj_square.diagonal()

adj_square[~mask_mat] = 0

# m is the vector of the number of
# the neighbourhood's connecting, multiplied by two.
m = adj_square.sum(axis=1)

# coef_list includes all local cluster coefficient.
coef_list = np.divide(m.astype(float), k*(k-1))

global_coef = coef_list.mean()

print(global_coef)
# 0.416666666667, in this case.