NetworkX图形间与特征向量的中心性

Question

在尝试绘制分布时，我在特征向量和中心融合中的价值方面遇到了麻烦。当前绘制时，当中心显然没有任何负值时，它显示的负值约为0.4至0.0。但是，我能够正确地绘制学度中心性。以下是目前出现的图像。

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目前代码看起来如下，我无法弄清楚为什么这个问题持续存在：

    degr_cent = nx.degree_centrality(G)
    eigvec_cent = nx.eigenvector_centrality(G)
    betw_cent = nx.betweenness_centrality(G)

    degree_sequence = sorted((d for n,d in G.degree()), reverse=True)
    fig = plt.figure("Degree of a random graph", figsize=(8, 8))
    axgrid = fig.add_gridspec(5, 4)
    ax = fig.add_subplot()
    ax.bar(*np.unique(degree_sequence, return_counts=True))
    ax.set_title("Degree histogram")
    ax.set_xlabel("Degree")
    ax.set_ylabel("# of Nodes")
    plt.savefig('degree_distribution.png')
    plt.show()

    #degree centrality histogram
    dc_degr_histogram = nx.degree_histogram(G)
    dc_degrees = range(len(dc_degr_histogram))
    dc_degr_histogram = nx.degree_histogram(G)
    dc_degrees = range(len(dc_degr_histogram))

   
    plt.figure(figsize=(12,8))
    plt.loglog(dc_degrees, dc_degr_histogram,'go-') 
    plt.xlabel('Degree')
    plt.ylabel('Frequency')
    plt.savefig('degree_distribution.png')
    plt.show()
    eigvec_values = eigvec_cent.values()
    eigvec_sequence = sorted(eigvec_values, reverse=True)
    
    fig = plt.figure("Degree of a random graph", figsize=(8, 8))
    axgrid = fig.add_gridspec(5, 4)
    ax = fig.add_subplot()
    ax.bar(*np.unique(eigvec_sequence, return_counts=True))
    ax.set_title("Eigenvec histogram")
    ax.set_xlabel("Eigenvec")
    ax.set_ylabel("# of Nodes")
    plt.savefig('eigvec_distribution.png')
    plt.show()
    
    betw_cent_values = betw_cent.values()

    
    betw_cent_values = sorted(betw_cent_values)
    fig = plt.figure("Degree of a random graph", figsize=(8, 8))
    axgrid = fig.add_gridspec(5, 4)
    ax = fig.add_subplot()
    ax.bar(*np.unique(betw_cent_values, return_counts=True))
    ax.set_title("betweenness")
    ax.set_xlabel("betw")
    ax.set_ylabel("# of Nodes")
    plt.savefig('betweenness_distribution.png')
    plt.show()