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 ( 1) *
31 ( 0)
32 ( 0)
33 ( 1) *
34 ( 2) **
35 ( 3) ***
36 ( 2) **
37 ( 8) ********
38 ( 4) ****
39 ( 7) *******
40 (10) **********
41 ( 9) *********
42 (12) ************
43 (19) *******************
44 (12) ************
45 (30) ******************************
46 (27) ***************************
47 (38) **************************************
48 (30) ******************************
49 (33) *********************************
50 (35) ***********************************
51 (22) **********************
52 (31) *******************************
53 (25) *************************
54 (23) ***********************
55 (20) ********************
56 (24) ************************
57 (13) *************
58 (15) ***************
59 ( 8) ********
60 ( 8) ********
61 ( 5) *****
62 ( 3) ***
63 ( 7) *******
64 ( 2) **
65 ( 6) ******
66 ( 1) *
67 ( 4) ****

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 0.029 seconds)

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