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 ( 2) **
32 ( 0)
33 ( 1) *
34 ( 0)
35 ( 0)
36 ( 3) ***
37 ( 6) ******
38 ( 4) ****
39 ( 8) ********
40 (12) ************
41 (11) ***********
42 (21) *********************
43 (21) *********************
44 (20) ********************
45 (27) ***************************
46 (23) ***********************
47 (24) ************************
48 (25) *************************
49 (23) ***********************
50 (26) **************************
51 (39) ***************************************
52 (27) ***************************
53 (34) **********************************
54 (23) ***********************
55 (26) **************************
56 (20) ********************
57 (11) ***********
58 (10) **********
59 (11) ***********
60 (11) ***********
61 (10) **********
62 ( 7) *******
63 ( 2) **
64 ( 4) ****
65 ( 4) ****
66 ( 0)
67 ( 1) *
68 ( 1) *
69 ( 0)
70 ( 1) *
71 ( 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 0.033 seconds)

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