net_metrics.py 文件源码

def draw_degree_rank_plot(orig_g, mG):
    ori_degree_seq = sorted(nx.degree(orig_g).values(), reverse=True)  # degree sequence
    deg_seqs = []
    for newg in mG:
        deg_seqs.append(sorted(nx.degree(newg).values(), reverse=True))  # degree sequence
    df = pd.DataFrame(deg_seqs)

    plt.xscale('log')
    plt.yscale('log')
    plt.fill_between(df.columns, df.mean() - df.sem(), df.mean() + df.sem(), color='blue', alpha=0.2, label="se")
    h, = plt.plot(df.mean(), color='blue', aa=True, linewidth=4, ls='--', label="H*")
    orig, = plt.plot(ori_degree_seq, color='black', linewidth=4, ls='-', label="H")

    plt.title('Degree Distribution')
    plt.ylabel('Degree')
    plt.ylabel('Ordered Vertices')

    plt.tick_params(
        axis='x',  # changes apply to the x-axis
        which='both',  # both major and minor ticks are affected
        bottom='off',  # ticks along the bottom edge are off
        top='off',  # ticks along the top edge are off
        labelbottom='off')  # labels along the bottom edge are off

    plt.legend([orig, h], ['$H$', 'HRG $H^*$'], loc=3)
    # fig = plt.gcf()
    # fig.set_size_inches(5, 4, forward=True)
    plt.show()