Python复杂网络结构可视化——matplotlib+networkx
画一个多层感知机
import matplotlib.pyplot as plt import networkx as nx left, right, bottom, top, layer_sizes = .1, .9, .1, .9, [4, 7, 7, 2] # 网络离上下左右的距离 # layter_sizes可以自己调整 import random G = nx.Graph() v_spacing = (top - bottom)/float(max(layer_sizes)) h_spacing = (right - left)/float(len(layer_sizes) - 1) node_count = 0 for i, v in enumerate(layer_sizes): layer_top = v_spacing*(v-1)/2. + (top + bottom)/2. for j in range(v): G.add_node(node_count, pos=(left + i*h_spacing, layer_top - j*v_spacing)) node_count += 1 # 这上面的数字调整我想了好半天，汗 for x, (left_nodes, right_nodes) in enumerate(zip(layer_sizes[:-1], layer_sizes[1:])): for i in range(left_nodes): for j in range(right_nodes): G.add_edge(i+sum(layer_sizes[:x]), j+sum(layer_sizes[:x+1])) # 慢慢研究吧 pos=nx.get_node_attributes(G,'pos') # 把每个节点中的位置pos信息导出来 nx.draw(G, pos, node_color=range(node_count), with_labels=True, node_size=200, edge_color=[random.random() for i in range(len(G.edges))], width=3, cmap=plt.cm.Dark2, # matplotlib的调色板，可以搜搜，很多颜色呢 edge_cmap=plt.cm.Blues ) plt.show()
还有很多其他的
https://zhuanlan.zhihu.com/p/36700425
https://networkx.org/documentation/stable/auto_examples/index.html
