Expected Degree Sequence¶

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 ( 1) *
34 ( 1) *
35 ( 1) *
36 ( 4) ****
37 ( 9) *********
38 ( 7) *******
39 ( 5) *****
40 (13) *************
41 (10) **********
42 (17) *****************
43 (19) *******************
44 (14) **************
45 (19) *******************
46 (32) ********************************
47 (26) **************************
48 (28) ****************************
49 (30) ******************************
50 (31) *******************************
51 (25) *************************
52 (31) *******************************
53 (28) ****************************
54 (18) ******************
55 (22) **********************
56 (21) *********************
57 (17) *****************
58 (13) *************
59 (17) *****************
60 (12) ************
61 ( 9) *********
62 ( 7) *******
63 ( 2) **
64 ( 3) ***
65 ( 3) ***
66 ( 2) **
67 ( 0)
68 ( 1) *
69 ( 1) *

import networkx as nx

# 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 = nx.expected_degree_graph(w)  # configuration model
print("Degree histogram")
print("degree (#nodes) ****")
dh = nx.degree_histogram(G)
for i, d in enumerate(dh):
    print(f"{i:2} ({d:2}) {'*'*d}")

Total running time of the script: ( 0 minutes 0.034 seconds)

Gallery generated by Sphinx-Gallery