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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 ( 0)
32 ( 0)
33 ( 0)
34 ( 0)
35 ( 1) *
36 ( 1) *
37 ( 2) **
38 ( 7) *******
39 (12) ************
40 ( 8) ********
41 (16) ****************
42 (15) ***************
43 (17) *****************
44 (13) *************
45 (23) ***********************
46 (22) **********************
47 (16) ****************
48 (30) ******************************
49 (29) *****************************
50 (33) *********************************
51 (26) **************************
52 (30) ******************************
53 (32) ********************************
54 (31) *******************************
55 (19) *******************
56 (23) ***********************
57 (14) **************
58 (16) ****************
59 (13) *************
60 ( 9) *********
61 (10) **********
62 (11) ***********
63 ( 8) ********
64 ( 5) *****
65 ( 0)
66 ( 3) ***
67 ( 3) ***
68 ( 0)
69 ( 0)
70 ( 0)
71 ( 1) *
72 ( 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 0.068 seconds)