如何在使用python igraph创建的有向图中将权重添加到边缘标签中？

Question

我开始将python igraph与networkx结合使用，因为前者已实现了network community detection最新进展。

现在，我仅从加权的非对称邻接矩阵和节点标签字典开始。 我在networkx创建一个有向图G，然后将其转换为igraph graph, g ，并在igraph中igraph带有标记节点的结果。

import numpy as npy
import networkx as nx
import igraph as ig

# Create adjacency matrix, A, and corresponding directed graph in networkx
A=npy.matrix([[4,7,7,0,0],[3,0,6,0,0],[7,6,0,2,1],[0,0,2,0,4],[0,0,1,4,0]])
G = nx.from_numpy_matrix(A, create_using=nx.DiGraph)

# Dictionary of node labels, simply 'A', 'B', ...'E' for this example
labels_dict={0: 'A', 1: 'B', 2: 'C', 3: 'D', 4: 'E'}
labels=list(labels_dict.values())

# Convert networkx graph to igraph
nx.write_graphml(G,'graph.graphml')
g = ig.read('graph.graphml',format="graphml")

# Plot directed graph using igraph with labeled vertices, 
ig.plot(g,vertex_label =  labels)

这将创建所需的图形，但是我想知道用edges的相应权重labelling edges的最有效方法。

Answer 1

这有效：

ig.plot(g,vertex_label =  labels,vertex_label_size = 10, vertex_size = 20 
,edge_label = [edge for edge in g.es['weight']],edge_width = [.25*edge for edge 
in g.es['weight']])

圆弧可能很难看到每个边缘与哪个权重相关联，可以通过添加选项edge_curved = 0来解决。