Note
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Expected Degree Sequence#
Random graph from given degree sequence.
Out:
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 ( 1) *
29 ( 0)
30 ( 0)
31 ( 0)
32 ( 0)
33 ( 2) **
34 ( 1) *
35 ( 2) **
36 ( 5) *****
37 ( 7) *******
38 (10) **********
39 ( 5) *****
40 ( 7) *******
41 ( 8) ********
42 (22) **********************
43 (11) ***********
44 (15) ***************
45 (24) ************************
46 (31) *******************************
47 (25) *************************
48 (26) **************************
49 (34) **********************************
50 (25) *************************
51 (37) *************************************
52 (22) **********************
53 (21) *********************
54 (26) **************************
55 (24) ************************
56 (19) *******************
57 (14) **************
58 (12) ************
59 (17) *****************
60 (13) *************
61 (11) ***********
62 ( 7) *******
63 ( 3) ***
64 ( 2) **
65 ( 1) *
66 ( 4) ****
67 ( 2) **
68 ( 0)
69 ( 1) *
70 ( 2) **
71 ( 0)
72 ( 0)
73 ( 0)
74 ( 0)
75 ( 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 0.073 seconds)