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 ( 3) ***
35 ( 2) **
36 ( 3) ***
37 ( 4) ****
38 ( 5) *****
39 ( 8) ********
40 (11) ***********
41 (15) ***************
42 (19) *******************
43 (17) *****************
44 (19) *******************
45 (24) ************************
46 (19) *******************
47 (23) ***********************
48 (20) ********************
49 (27) ***************************
50 (30) ******************************
51 (41) *****************************************
52 (26) **************************
53 (29) *****************************
54 (26) **************************
55 (25) *************************
56 (22) **********************
57 (13) *************
58 (10) **********
59 (18) ******************
60 ( 7) *******
61 ( 8) ********
62 ( 9) *********
63 ( 5) *****
64 ( 6) ******
65 ( 3) ***
66 ( 0)
67 ( 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 0.014 seconds)

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