NetworkX-根據權重畫圖

 load_data = sio.loadmat(load_path)

    #閾值處理
      mat=np.array(load_data['R'])
      mat[mat<0]=0
      mat[mat<0.45]=0

    #寫入txt文件
     # np.savetxt(thr_path, mat);

      #計算degree
      g = nx.Graph()
      for i in range(len(mat)):
          for j in range(len(mat)):
              if(mat[i,j]>0):  #刪除邊的權重小於等於0的邊
                g.add_edge(i, j,weight=mat[i,j])

      # nx.draw(g)
      # nx.draw(g,with_labels=True)  # 將標號標出來
      # plt.show()

      # 按權重划分為重權值得邊和輕權值的邊
      elarge = [(u, v) for (u, v, d) in g.edges(data=True) if d['weight'] > 0.5]
      esmall = [(u, v) for (u, v, d) in g.edges(data=True) if d['weight'] <= 0.5]
      # 節點位置
      pos = nx.spring_layout(g)  # positions for all nodes
      # 首先畫出節點位置
      # nodes
      nx.draw_networkx_nodes(g, pos, node_color='b',node_size=300,alpha=0.4)
      # 根據權重，實線為權值大的邊，虛線為權值小的邊
      # edges
      nx.draw_networkx_edges(g, pos, edgelist=elarge,
                             width=3)
      nx.draw_networkx_edges(g, pos, edgelist=esmall,
                             width=1, alpha=0.5, edge_color='g', style='dashed')

      # labels標簽定義
      nx.draw_networkx_labels(g, pos, font_size=13, font_family='sans-serif')

      plt.axis('off')
      plt.savefig("weighted_graph.png")  # save as png
      plt.show()

Result:

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