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 ( 3) ***
34 ( 3) ***
35 ( 2) **
36 ( 2) **
37 ( 4) ****
38 (10) **********
39 ( 9) *********
40 ( 5) *****
41 (10) **********
42 (11) ***********
43 ( 9) *********
44 (24) ************************
45 (19) *******************
46 (22) **********************
47 (25) *************************
48 (39) ***************************************
49 (19) *******************
50 (38) **************************************
51 (24) ************************
52 (28) ****************************
53 (27) ***************************
54 (26) **************************
55 (29) *****************************
56 (27) ***************************
57 (23) ***********************
58 (11) ***********
59 (14) **************
60 (10) **********
61 ( 7) *******
62 ( 7) *******
63 ( 3) ***
64 ( 4) ****
65 ( 0)
66 ( 4) ****
67 ( 0)
68 ( 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 0.026 seconds)

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