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- # -*- coding: utf-8 -*-
- #!/usr/bin/env python
- """
- ===========
- Erdos Renyi
- ===========
- Create an G{n,m} random graph with n nodes and m edges
- and report some properties.
- This graph is sometimes called the Erdős-Rényi graph
- but is different from G{n,p} or binomial_graph which is also
- sometimes called the Erdős-Rényi graph.
- """
- # Author: Aric Hagberg (hagberg@lanl.gov)
- # Copyright (C) 2004-2019 by
- # Aric Hagberg <hagberg@lanl.gov>
- # Dan Schult <dschult@colgate.edu>
- # Pieter Swart <swart@lanl.gov>
- # All rights reserved.
- # BSD license.
- import matplotlib.pyplot as plt
- from networkx import nx
- n = 10 # 10 nodes
- m = 20 # 20 edges
- G = nx.gnm_random_graph(n, m)
- # some properties
- print("node degree clustering")
- for v in nx.nodes(G):
- print('%s %d %f' % (v, nx.degree(G, v), nx.clustering(G, v)))
- # print the adjacency list
- for line in nx.generate_adjlist(G):
- print(line)
- nx.draw(G)
- plt.show()
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