test_HigherOrderNetwork.py 文件源码

def paper_figure1():
    """

    graph data g come from Jure Leskovec(2016) Higher-order organization of complex networks Fig 1
    :return: None

    """
    g = nx.DiGraph()
    g.add_edge(1, 2)
    g.add_edge(1, 3)
    g.add_edge(1, 4)
    g.add_edge(1, 5)
    g.add_edge(1, 6)
    g.add_edge(2, 1)
    g.add_edge(2, 3)
    g.add_edge(2, 4)
    g.add_edge(2, 5)
    g.add_edge(6, 2)
    g.add_edge(6, 7)
    g.add_edge(7, 2)
    g.add_edge(7, 6)
    g.add_edge(8, 2)
    g.add_edge(8, 6)
    g.add_edge(8, 9)
    g.add_edge(8, 10)
    g.add_edge(9, 6)
    g.add_edge(9, 7)
    g.add_edge(9, 8)
    g.add_edge(9, 10)

    # W = HigherOrderNetwork.motif_m7(g)
    # cluster, condv, condc, order = HigherOrderNetwork.spectral_partitioning(W)
    # print("\n\npaper figure1's result")
    # print('condc: ', condc)
    # print('cluster\n', cluster)
    # # print(list(nx.all_neighbors(g, 2)))
    # HigherOrderNetwork.count_m1(g)
    # HigherOrderNetwork.count_m2(g)
    # HigherOrderNetwork.count_m3(g)
    # HigherOrderNetwork.count_m4(g)
    # HigherOrderNetwork.count_m5(g)
    # HigherOrderNetwork.count_m6(g)
    # HigherOrderNetwork.count_m7(g)
    # HigherOrderNetwork.count_m8(g)
    # HigherOrderNetwork.count_m9(g)
    # HigherOrderNetwork.count_m10(g)
    HigherOrderNetwork.count_motif(g)