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 ( 0)
30 ( 0)
31 ( 1) *
32 ( 0)
33 ( 1) *
34 ( 3) ***
35 ( 3) ***
36 ( 2) **
37 ( 7) *******
38 ( 7) *******
39 ( 3) ***
40 (10) **********
41 (10) **********
42 (11) ***********
43 (15) ***************
44 (10) **********
45 (38) **************************************
46 (28) ****************************
47 (28) ****************************
48 (28) ****************************
49 (21) *********************
50 (40) ****************************************
51 (29) *****************************
52 (23) ***********************
53 (26) **************************
54 (31) *******************************
55 (25) *************************
56 (15) ***************
57 (20) ********************
58 (17) *****************
59 (10) **********
60 (11) ***********
61 ( 9) *********
62 ( 6) ******
63 ( 4) ****
64 ( 1) *
65 ( 2) **
66 ( 2) **
67 ( 2) **
68 ( 0)
69 ( 0)
70 ( 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)

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