Expected Degree Sequence#

Random graph from given degree sequence.

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 ( 1) *
30 ( 0)
31 ( 1) *
32 ( 0)
33 ( 0)
34 ( 0)
35 ( 0)
36 ( 1) *
37 ( 6) ******
38 ( 7) *******
39 (12) ************
40 (11) ***********
41 (17) *****************
42 (11) ***********
43 (15) ***************
44 (21) *********************
45 (16) ****************
46 (26) **************************
47 (17) *****************
48 (24) ************************
49 (29) *****************************
50 (33) *********************************
51 (34) **********************************
52 (33) *********************************
53 (20) ********************
54 (28) ****************************
55 (21) *********************
56 (30) ******************************
57 (15) ***************
58 (18) ******************
59 (13) *************
60 ( 7) *******
61 ( 6) ******
62 (11) ***********
63 ( 5) *****
64 ( 2) **
65 ( 1) *
66 ( 3) ***
67 ( 1) *
68 ( 2) **
69 ( 1) *
70 ( 0)
71 ( 0)
72 ( 0)
73 ( 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 0.051 seconds)

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