Note
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Expected Degree SequenceΒΆ
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 ( 0)
29 ( 0)
30 ( 0)
31 ( 0)
32 ( 0)
33 ( 2) **
34 ( 2) **
35 ( 1) *
36 ( 4) ****
37 ( 3) ***
38 ( 7) *******
39 ( 7) *******
40 (12) ************
41 (17) *****************
42 (12) ************
43 (15) ***************
44 (24) ************************
45 (30) ******************************
46 (24) ************************
47 (21) *********************
48 (24) ************************
49 (30) ******************************
50 (29) *****************************
51 (28) ****************************
52 (26) **************************
53 (21) *********************
54 (21) *********************
55 (22) **********************
56 (20) ********************
57 (17) *****************
58 (16) ****************
59 (12) ************
60 (12) ************
61 ( 9) *********
62 ( 7) *******
63 ( 7) *******
64 ( 7) *******
65 ( 5) *****
66 ( 1) *
67 ( 2) **
68 ( 0)
69 ( 3) ***
import networkx as nx
from networkx.generators.degree_seq import expected_degree_graph
# 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 = 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 0.077 seconds)