Note
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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 ( 2) **
32 ( 0)
33 ( 1) *
34 ( 2) **
35 ( 4) ****
36 ( 1) *
37 ( 4) ****
38 ( 6) ******
39 ( 9) *********
40 ( 7) *******
41 (12) ************
42 (17) *****************
43 (18) ******************
44 (22) **********************
45 (14) **************
46 (30) ******************************
47 (23) ***********************
48 (31) *******************************
49 (28) ****************************
50 (30) ******************************
51 (30) ******************************
52 (17) *****************
53 (26) **************************
54 (33) *********************************
55 (22) **********************
56 (16) ****************
57 (13) *************
58 (16) ****************
59 (14) **************
60 ( 9) *********
61 (11) ***********
62 ( 8) ********
63 ( 6) ******
64 ( 1) *
65 ( 6) ******
66 ( 4) ****
67 ( 2) **
68 ( 1) *
69 ( 3) ***
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 0.031 seconds)