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 0.8333333333333334
1 6 0.3333333333333333
2 5 0.5
3 1 0
4 6 0.6666666666666666
5 4 0.8333333333333334
6 6 0.4666666666666667
7 1 0
8 5 0.7
9 2 1.0

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