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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 ( 1) *
30 ( 0)
31 ( 2) **
32 ( 0)
33 ( 1) *
34 ( 1) *
35 ( 3) ***
36 ( 4) ****
37 ( 8) ********
38 ( 4) ****
39 (11) ***********
40 ( 9) *********
41 (13) *************
42 (18) ******************
43 (17) *****************
44 (20) ********************
45 (25) *************************
46 (25) *************************
47 (22) **********************
48 (29) *****************************
49 (26) **************************
50 (30) ******************************
51 (23) ***********************
52 (29) *****************************
53 (31) *******************************
54 (17) *****************
55 (23) ***********************
56 (24) ************************
57 (20) ********************
58 (11) ***********
59 (16) ****************
60 ( 8) ********
61 ( 9) *********
62 ( 9) *********
63 ( 4) ****
64 ( 1) *
65 ( 2) **
66 ( 1) *
67 ( 3) ***
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 0.019 seconds)