我使用以下代码构建了一个图表:
G = networkx.Graph()
G.add_edges_from([list(e) for e in P + Q + R])
colors = "bgrcmyk"
color_map = [colors[i] for i in range(n/2)]
# add colors
for i in range(len(P)):
edge = list(P[i])
G[edge[0]][edge[1]]['edge_color'] = color_map[i]
for i in range(len(P)):
edge = list(Q[perms[0][i]])
G[edge[0]][edge[1]]["color"] = color_map[perms[0][i]]
for i in range(len(P)):
edge = list(R[perms[1][i]])
G[edge[0]][edge[1]]["color"] = color_map[perms[1][i]]
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然后我使用以下方式显示:
networkx.draw(G)
matplotlib.pyplot.show()
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它显示正常,但所有边缘都用黑色着色,而不是我试图在上面的代码片段中分配的颜色.有任何想法吗?
您可以在不循环绘制边缘的情况下执行此操作.对于较大的图形,它会更快.
import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
# example graph
for color in "bgrcmyk":
G.add_edge('s'+color,'t'+color, color=color)
# edge_color_attr = nx.get_edge_attributes(G,'color')
# edges = edge_color_attr.keys()
# colors = edge_color_attr.values()
edges,colors = zip(*nx.get_edge_attributes(G,'color').items())
nx.draw(G,edgelist=edges,edge_color=colors,width=10)
plt.show()
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嗯,终于找到了我需要做的事情。颜色显然需要分离,网络需要用 绘制draw_networkx。所以上面的三个for循环要替换为:
pos=networkx.spring_layout(G)
for i in range(len(P)):
networkx.draw_networkx_edges(G,pos,
edgelist=[list(P[i]), list(Q[perms[0][i]]), list(R[perms[1][i]])],edge_color=color_map[i], width="8")
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