使用边缘元数据绘制有向图（使用 Python 中的 NetworkX）

Question

I have a directed multigraph that I want to represent as a (complete) directed graph with edge meta-data such that if there are e number of edges from node A to node B (in the original multigraph) then I save e as the meta-data for the edge (A,B) in the new (not-multi) directed graph.

I can construct the graph as follows:

DG = nx.complete_graph(node_list, create_using= nx.DiGraph() )

where node_list = ['node_A', 'node_B', ....]

I can add the edges using:

DG.edges[('node_A', 'node_B')]['edge_count'] = 1

But how do I print this value (nicely) using the draw command? I tried the following

nx.draw(DG, with_labels = True)
plt.show()

But the edge values hide; what's more, I would need a nice way to show the meta-data associated with edge (A,B) and easily distinguishing it from edge (B,A).

Answer 1

You should be able to do the following:

edge_labels = nx.get_edge_attributes(G,'edge_count')

pos = nx.spring_layout(G)
nx.draw(G, pos = pos, with_labels=True)
nx.draw_networkx_edge_labels(G, pos=pos, edge_labels = edge_labels)
plt.show()

---

Here's an approach that uses curved arrows to avoid overlapping labels

import networkx as nx
import matplotlib.pyplot as plt

G = nx.DiGraph()

G.add_nodes_from(range(4))

G.add_edge(0,1,edge_count = 1)
G.add_edge(1,0,edge_count = 2)
G.add_edge(1,2,edge_count = 2)
G.add_edge(2,3,edge_count = 3)
G.add_edge(3,0,edge_count = 2)

def offset(d, pos, dist = .1):
    for (u,v),obj in d.items():
        par = dist*(pos[v] - pos[u])
        dx,dy = par[1],-par[0]
        x,y = obj.get_position()
        obj.set_position((x+dx,y+dy))

edge_labels = nx.get_edge_attributes(G,'edge_count')
pos = nx.spring_layout(G)
nx.draw(G, pos = pos, with_labels=True, connectionstyle = 'arc3,rad=0.2', node_color = 'orange')
d = nx.draw_networkx_edge_labels(G, pos=pos, edge_labels = edge_labels)
offset(d,pos)
plt.gca().set_aspect('equal')
plt.show()

Result from the above: