Expected Degree SequenceΒΆ

Random graph from given degree sequence.

Out:

Degree histogram
degree (#nodes) ****
 0 ( 0)
 1 ( 0)
 2 ( 0)
 3 ( 0)
 4 ( 0)
 5 ( 0)
 6 ( 0)
 7 ( 0)
 8 ( 0)
 9 ( 0)
10 ( 0)
11 ( 0)
12 ( 0)
13 ( 0)
14 ( 0)
15 ( 0)
16 ( 0)
17 ( 0)
18 ( 0)
19 ( 0)
20 ( 0)
21 ( 0)
22 ( 0)
23 ( 0)
24 ( 0)
25 ( 0)
26 ( 0)
27 ( 0)
28 ( 0)
29 ( 0)
30 ( 0)
31 ( 0)
32 ( 1) *
33 ( 0)
34 ( 2) **
35 ( 1) *
36 ( 5) *****
37 ( 2) **
38 ( 9) *********
39 (11) ***********
40 (11) ***********
41 ( 6) ******
42 (14) **************
43 (23) ***********************
44 (23) ***********************
45 (20) ********************
46 (26) **************************
47 (22) **********************
48 (19) *******************
49 (34) **********************************
50 (37) *************************************
51 (32) ********************************
52 (21) *********************
53 (24) ************************
54 (20) ********************
55 (22) **********************
56 (24) ************************
57 (17) *****************
58 (11) ***********
59 (12) ************
60 ( 6) ******
61 (10) **********
62 ( 8) ********
63 (11) ***********
64 ( 4) ****
65 ( 3) ***
66 ( 7) *******
67 ( 2) **

# Author: Aric Hagberg (hagberg@lanl.gov)

#    Copyright (C) 2006-2019 by
#    Aric Hagberg <hagberg@lanl.gov>
#    Dan Schult <dschult@colgate.edu>
#    Pieter Swart <swart@lanl.gov>
#    All rights reserved.
#    BSD license.

import networkx as nx
from networkx.generators.degree_seq import expected_degree_graph

# make a random graph of 500 nodes with expected degrees of 50
n = 500  # n nodes
p = 0.1
w = [p * n for i in range(n)]  # w = p*n for all nodes
G = expected_degree_graph(w)  # configuration model
print("Degree histogram")
print("degree (#nodes) ****")
dh = nx.degree_histogram(G)
for i, d in enumerate(dh):
    print("%2s (%2s) %s" % (i, d, '*'*d))

Total running time of the script: ( 0 minutes 0.233 seconds)

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