#

Note

This documents the development version of NetworkX. Documentation for the current release can be found here.

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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 ( 1) *
31 ( 0)
32 ( 0)
33 ( 1) *
34 ( 0)
35 ( 3) ***
36 ( 4) ****
37 ( 2) **
38 ( 6) ******
39 ( 2) **
40 (10) **********
41 (12) ************
42 (13) *************
43 (23) ***********************
44 (15) ***************
45 (21) *********************
46 (28) ****************************
47 (35) ***********************************
48 (30) ******************************
49 (40) ****************************************
50 (22) **********************
51 (30) ******************************
52 (33) *********************************
53 (20) ********************
54 (24) ************************
55 (21) *********************
56 (19) *******************
57 (12) ************
58 (21) *********************
59 (10) **********
60 ( 6) ******
61 (11) ***********
62 ( 7) *******
63 ( 3) ***
64 ( 4) ****
65 ( 5) *****
66 ( 2) **
67 ( 0)
68 ( 2) **
69 ( 0)
70 ( 1) *
71 ( 0)
72 ( 0)
73 ( 0)
74 ( 0)
75 ( 1) *

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 0.053 seconds)

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