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 ( 0)
33 ( 1) *
34 ( 1) *
35 ( 3) ***
36 ( 6) ******
37 ( 2) **
38 ( 6) ******
39 ( 5) *****
40 (12) ************
41 (10) **********
42 (17) *****************
43 (22) **********************
44 (12) ************
45 (24) ************************
46 (20) ********************
47 (29) *****************************
48 (27) ***************************
49 (29) *****************************
50 (32) ********************************
51 (29) *****************************
52 (30) ******************************
53 (26) **************************
54 (30) ******************************
55 (17) *****************
56 (19) *******************
57 (18) ******************
58 (10) **********
59 ( 6) ******
60 (15) ***************
61 ( 4) ****
62 (15) ***************
63 ( 7) *******
64 ( 4) ****
65 ( 3) ***
66 ( 2) **
67 ( 3) ***
68 ( 0)
69 ( 3) ***
70 ( 0)
71 ( 0)
72 ( 0)
73 ( 0)
74 ( 0)
75 ( 0)
76 ( 0)
77 ( 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 0.040 seconds)

Gallery generated by Sphinx-Gallery