Colouring the edges by weight in networkx (Matplotlib)

To color the edges by weight in networkx, we can take the following steps −

• Set the figure size and adjust the padding between and around the subplots.
• Initialize a graph with edges, name, or graph attributes.
• Add nodes to the current graph.
• Add edges to the current graph's nodes.
• Iterate the given graph's edges and set some weight to them.
• Draw current graphs with weights for edge color.
• To display the figure, use show() method.

Example

import random as rd
import matplotlib.pylab as plt
import networkx as nx

plt.rcParams["figure.figsize"] = [7.50, 3.50]
plt.rcParams["figure.autolayout"] = True

G = nx.DiGraph()
G.add_nodes_from([1, 2, 3, 4])
G.add_edges_from([(1, 2), (2, 3), (3, 4), (4, 1), (1, 3)])
for u, v, d in G.edges(data=True):
   d['weight'] = rd.random()
edges, weights = zip(*nx.get_edge_attributes(G, 'weight').items())
nx.draw(G, node_color='b', edge_color=weights, width=2, with_labels=True)

plt.show()

Output