Python：具有不同颜色节点的网络 Spring 布局

Question

我从给定节点创建最短路径的弹簧布局网络。在这种情况下firm1。我想为每个分离度使用不同的颜色。例如，连接firm1 和其他公司的所有第一条边，比如firm2 和firm3，我想更改firm2 和firm3 的节点颜色（两者颜色相同）。然后所有从firm2 和firm3 连接的公司，比如说firm4 和firm5 我想改变他们的节点颜色。但我不知道如何更改从firm1 开始的每个分离度的节点颜色。这是我的代码：

import networkx as nx
import matplotlib.pyplot as plt
import pandas as pd

graph = nx.Graph()
with open('C:\\file.txt') as f: #Here, I load a text file with two columns indicating the connections between each firm
    for line in f:
        tic_1, tic_2 = line.split()
        graph.add_edge(tic_1, tic_2)

paths_from_1 = nx.shortest_path(graph, "firm1") #I get the shortest path starting from firm1

x = pd.DataFrame(paths_from_1.values()) #I convert the dictionary of the shortest path into a dataframe


tic_0=x[0].tolist() #there are 7 columns in my dataframe x and I convert each columns into a list. tic_0 is a list of `firm1` string
tic_1=x[1].tolist() #tic_1 is list of all the firms directly connected to firm1
tic_2=x[2].tolist() #tic_2 are the firms indirectly connected to firm1 via the firms in tic_1
tic_3=x[3].tolist() #and so on...
tic_4=x[4].tolist()
tic_5=x[5].tolist()
tic_6=x[6].tolist()

l = len(tic_0)
graph = nx.Graph()

for i in range(len(tic_0)):
        graph.add_edge(tic_0[i], tic_1[i]) 
        graph.add_edge(tic_1[i], tic_2[i])
        graph.add_edge(tic_2[i], tic_3[i])
        graph.add_edge(tic_3[i], tic_4[i])
        graph.add_edge(tic_4[i], tic_5[i])
        graph.add_edge(tic_5[i], tic_6[i])

pos = nx.spring_layout(graph_short, iterations=200, k=)
nx.draw(graph_short, pos, font_size='6',)
plt.savefig("network.png")
plt.show()

如何为每个分离度设置不同的颜色节点？换句话说，tic_1 中的所有公司都应该有一个蓝色的节点，tic_2 中的所有公司都有一个黄色的节点颜色，等等。

Answer 1

执行此操作的通用方法是从源节点运行最短路径长度算法来分配颜色。这是一个例子：

import matplotlib.pyplot as plt
import networkx as nx

G = nx.balanced_tree(2,5)
length = nx.shortest_path_length(G, source=0)
nodelist,hops = zip(*length.items())
positions = nx.graphviz_layout(G, prog='twopi', root=0)
nx.draw(G, positions, nodelist = nodelist, node_color=hops, cmap=plt.cm.Blues)
plt.axis('equal')
plt.show()

你可以使用

positions = nx.spring_layout(G)

相反。我使用了 graphviz circo 布局，因为它在绘制我使用的平衡树方面做得更好。