Mercurial > repos > shellac > sam_consensus_v3
comparison env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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-1:000000000000 | 0:4f3585e2f14b |
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1 import pytest | |
2 | |
3 np = pytest.importorskip("numpy") | |
4 sp = pytest.importorskip("scipy") | |
5 sparse = pytest.importorskip("scipy.sparse") | |
6 | |
7 | |
8 import networkx as nx | |
9 from networkx.algorithms import bipartite | |
10 from networkx.testing.utils import assert_edges_equal | |
11 | |
12 | |
13 class TestBiadjacencyMatrix: | |
14 def test_biadjacency_matrix_weight(self): | |
15 G = nx.path_graph(5) | |
16 G.add_edge(0, 1, weight=2, other=4) | |
17 X = [1, 3] | |
18 Y = [0, 2, 4] | |
19 M = bipartite.biadjacency_matrix(G, X, weight="weight") | |
20 assert M[0, 0] == 2 | |
21 M = bipartite.biadjacency_matrix(G, X, weight="other") | |
22 assert M[0, 0] == 4 | |
23 | |
24 def test_biadjacency_matrix(self): | |
25 tops = [2, 5, 10] | |
26 bots = [5, 10, 15] | |
27 for i in range(len(tops)): | |
28 G = bipartite.random_graph(tops[i], bots[i], 0.2) | |
29 top = [n for n, d in G.nodes(data=True) if d["bipartite"] == 0] | |
30 M = bipartite.biadjacency_matrix(G, top) | |
31 assert M.shape[0] == tops[i] | |
32 assert M.shape[1] == bots[i] | |
33 | |
34 def test_biadjacency_matrix_order(self): | |
35 G = nx.path_graph(5) | |
36 G.add_edge(0, 1, weight=2) | |
37 X = [3, 1] | |
38 Y = [4, 2, 0] | |
39 M = bipartite.biadjacency_matrix(G, X, Y, weight="weight") | |
40 assert M[1, 2] == 2 | |
41 | |
42 def test_null_graph(self): | |
43 with pytest.raises(nx.NetworkXError): | |
44 bipartite.biadjacency_matrix(nx.Graph(), []) | |
45 | |
46 def test_empty_graph(self): | |
47 with pytest.raises(nx.NetworkXError): | |
48 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), []) | |
49 | |
50 def test_duplicate_row(self): | |
51 with pytest.raises(nx.NetworkXError): | |
52 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [1, 1]) | |
53 | |
54 def test_duplicate_col(self): | |
55 with pytest.raises(nx.NetworkXError): | |
56 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], [1, 1]) | |
57 | |
58 def test_format_keyword(self): | |
59 with pytest.raises(nx.NetworkXError): | |
60 bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], format="foo") | |
61 | |
62 def test_from_biadjacency_roundtrip(self): | |
63 B1 = nx.path_graph(5) | |
64 M = bipartite.biadjacency_matrix(B1, [0, 2, 4]) | |
65 B2 = bipartite.from_biadjacency_matrix(M) | |
66 assert nx.is_isomorphic(B1, B2) | |
67 | |
68 def test_from_biadjacency_weight(self): | |
69 M = sparse.csc_matrix([[1, 2], [0, 3]]) | |
70 B = bipartite.from_biadjacency_matrix(M) | |
71 assert_edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)]) | |
72 B = bipartite.from_biadjacency_matrix(M, edge_attribute="weight") | |
73 e = [(0, 2, {"weight": 1}), (0, 3, {"weight": 2}), (1, 3, {"weight": 3})] | |
74 assert_edges_equal(B.edges(data=True), e) | |
75 | |
76 def test_from_biadjacency_multigraph(self): | |
77 M = sparse.csc_matrix([[1, 2], [0, 3]]) | |
78 B = bipartite.from_biadjacency_matrix(M, create_using=nx.MultiGraph()) | |
79 assert_edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)]) |