Warning

This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

Degree Sequence

Random graph from given degree sequence.

Out:

True
Configuration model
Degree sequence [5, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1]
Degree histogram
degree #nodes
1 3
2 3
3 4
5 1

# Author: Aric Hagberg (hagberg@lanl.gov)
# Date: 2004-11-03 08:11:09 -0700 (Wed, 03 Nov 2004)
# Revision: 503

#    Copyright (C) 2004-2018 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

z = [5, 3, 3, 3, 3, 2, 2, 2, 1, 1, 1]
print(nx.is_graphical(z))

print("Configuration model")
G = nx.configuration_model(z)  # configuration model
degree_sequence = [d for n, d in G.degree()]  # degree sequence
print("Degree sequence %s" % degree_sequence)
print("Degree histogram")
hist = {}
for d in degree_sequence:
    if d in hist:
        hist[d] += 1
    else:
        hist[d] = 1
print("degree #nodes")
for d in hist:
    print('%d %d' % (d, hist[d]))

nx.draw(G)
plt.show()

Total running time of the script: ( 0 minutes 0.066 seconds)