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Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

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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.

Out:

node degree clustering
0 4 0.16666666666666666
1 4 0.3333333333333333
2 3 0.3333333333333333
3 5 0.5
4 2 1.0
5 4 0.5
6 5 0.4
7 6 0.4
8 3 1.0
9 4 0.16666666666666666

the adjacency list
0 5 3 9 2
1 7 9 5 4
2 7 6
3 7 6 8 5
4 9
5 7
6 9 8 7
7 8
8
9

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(f"{v} {nx.degree(G, v)} {nx.clustering(G, v)}")

print()
print("the adjacency list")
for line in nx.generate_adjlist(G):
    print(line)

nx.draw(G)
plt.show()