Colouring the edges by weight in networkx (Matplotlib)

Matplotlib Python Data Visualization

Python Data Science basics with Numpy, Pandas and Matplotlib

Data Visualization using MatPlotLib & Seaborn

DATAhill Solutions Srinivas Reddy

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MatPlotLib with Python

DATAhill Solutions Srinivas Reddy

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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()