如何使用 networkx 和 matplotlib 绘制权重标签？答案

【问题标题】：How to draw weight labels with networkx and matplotlib?如何使用 networkx 和 matplotlib 绘制权重标签？
【发布时间】：2019-09-17 00:17:39
【问题描述】：

我正在研究图表，所以我正在尝试使用 networkx 和 matplotlib 在 python 中给定字典绘制图表，这是我的代码：

import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
    "A":["B","C"],
    "B":["D","E"],
    "C":["E","F"],
    "D":["B","G"],
    "E":["B","C"],
    "F":["C","G"],
    "G":["D","F"]
}
x=10
for vertex, edges in graph.items():
    G.add_node("%s" % vertex)
    x+=2
    for edge in edges:
        G.add_node("%s" % edge)
        G.add_edge("%s" % vertex, "%s" % edge, weight = x)
        print("'%s' it connects with '%s'" % (vertex,edge))
nx.draw(G,with_labels=True)

plt.show()

我已经尝试过功能 draw_networkx_edge_labels 但似乎我需要一个我没有的位置，因为我动态添加节点，所以我需要一种方法来绘制适合我的边缘标签当前的实现。

【问题讨论】：

标签： python-3.x matplotlib networkx graph-theory

【解决方案1】：

在添加完所有节点后绘制图形，以便根据它们计算位置并使用nx.draw_networkx_edge_labels(...)：

import networkx as nx
import matplotlib.pyplot as plt
G = nx.Graph()
graph = {
    "A":["B","C"],
    "B":["D","E"],
    "C":["E","F"],
    "D":["B","G"],
    "E":["B","C"],
    "F":["C","G"],
    "G":["D","F"]
}
x=10
for vertex, edges in graph.items():
    G.add_node("%s" % vertex)
    x+=2
    for edge in edges:
        G.add_node("%s" % edge)
        G.add_edge("%s" % vertex, "%s" % edge, weight = x)
        print("'%s' it connects with '%s'" % (vertex,edge))
# ---- END OF UNCHANGED CODE ----

# Create positions of all nodes and save them
pos = nx.spring_layout(G)

# Draw the graph according to node positions
nx.draw(G, pos, with_labels=True)

# Create edge labels
labels = {e: str(e) for e in G.edges}

# Draw edge labels according to node positions
nx.draw_networkx_edge_labels(G, pos, edge_labels=labels)

plt.show()

【讨论】：