Mercurial > repos > shellac > sam_consensus_v3
comparison env/lib/python3.9/site-packages/networkx/algorithms/approximation/tests/test_approx_clust_coeff.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
---|---|
date | Mon, 22 Mar 2021 18:12:50 +0000 |
parents | |
children |
comparison
equal
deleted
inserted
replaced
-1:000000000000 | 0:4f3585e2f14b |
---|---|
1 import networkx as nx | |
2 from networkx.algorithms.approximation import average_clustering | |
3 | |
4 # This approximation has to be be exact in regular graphs | |
5 # with no triangles or with all possible triangles. | |
6 | |
7 | |
8 def test_petersen(): | |
9 # Actual coefficient is 0 | |
10 G = nx.petersen_graph() | |
11 assert average_clustering(G, trials=int(len(G) / 2)) == nx.average_clustering(G) | |
12 | |
13 | |
14 def test_petersen_seed(): | |
15 # Actual coefficient is 0 | |
16 G = nx.petersen_graph() | |
17 assert average_clustering( | |
18 G, trials=int(len(G) / 2), seed=1 | |
19 ) == nx.average_clustering(G) | |
20 | |
21 | |
22 def test_tetrahedral(): | |
23 # Actual coefficient is 1 | |
24 G = nx.tetrahedral_graph() | |
25 assert average_clustering(G, trials=int(len(G) / 2)) == nx.average_clustering(G) | |
26 | |
27 | |
28 def test_dodecahedral(): | |
29 # Actual coefficient is 0 | |
30 G = nx.dodecahedral_graph() | |
31 assert average_clustering(G, trials=int(len(G) / 2)) == nx.average_clustering(G) | |
32 | |
33 | |
34 def test_empty(): | |
35 G = nx.empty_graph(5) | |
36 assert average_clustering(G, trials=int(len(G) / 2)) == 0 | |
37 | |
38 | |
39 def test_complete(): | |
40 G = nx.complete_graph(5) | |
41 assert average_clustering(G, trials=int(len(G) / 2)) == 1 | |
42 G = nx.complete_graph(7) | |
43 assert average_clustering(G, trials=int(len(G) / 2)) == 1 |