pedWorks.py 文件源码

def calculate_katz_centrality(graph):
    """
    Compute the katz centrality for nodes.
    """
    # if not graph.is_directed():
    #    raise nx.NetworkXError( \
    #       "katz_centrality() not defined for undirected graphs.")
    print "\n\tCalculating Katz Centrality..."
    print "\tWarning: This might take a long time larger pedigrees."
    g = graph
    A = nx.adjacency_matrix(g)
    from scipy import linalg as LA
    max_eign = float(np.real(max(LA.eigvals(A.todense()))))
    print "\t-Max.Eigenvalue(A) ", round(max_eign, 3)
    kt = nx.katz_centrality(g, tol=1.0e-4, alpha=1/max_eign-0.01, beta=1.0, max_iter=999999)
    nx.set_node_attributes(g, 'katz', kt)
    katz_sorted = sorted(kt.items(), key=itemgetter(1), reverse=True)
    for key, value in katz_sorted[0:10]:
        print "\t   > ", key, round(value, 4)
    return g, kt