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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
Updated on: 09-Jun-2021
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