Mercurial > repos > shellac > sam_consensus_v3
diff 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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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_matrix.py Mon Mar 22 18:12:50 2021 +0000 @@ -0,0 +1,79 @@ +import pytest + +np = pytest.importorskip("numpy") +sp = pytest.importorskip("scipy") +sparse = pytest.importorskip("scipy.sparse") + + +import networkx as nx +from networkx.algorithms import bipartite +from networkx.testing.utils import assert_edges_equal + + +class TestBiadjacencyMatrix: + def test_biadjacency_matrix_weight(self): + G = nx.path_graph(5) + G.add_edge(0, 1, weight=2, other=4) + X = [1, 3] + Y = [0, 2, 4] + M = bipartite.biadjacency_matrix(G, X, weight="weight") + assert M[0, 0] == 2 + M = bipartite.biadjacency_matrix(G, X, weight="other") + assert M[0, 0] == 4 + + def test_biadjacency_matrix(self): + tops = [2, 5, 10] + bots = [5, 10, 15] + for i in range(len(tops)): + G = bipartite.random_graph(tops[i], bots[i], 0.2) + top = [n for n, d in G.nodes(data=True) if d["bipartite"] == 0] + M = bipartite.biadjacency_matrix(G, top) + assert M.shape[0] == tops[i] + assert M.shape[1] == bots[i] + + def test_biadjacency_matrix_order(self): + G = nx.path_graph(5) + G.add_edge(0, 1, weight=2) + X = [3, 1] + Y = [4, 2, 0] + M = bipartite.biadjacency_matrix(G, X, Y, weight="weight") + assert M[1, 2] == 2 + + def test_null_graph(self): + with pytest.raises(nx.NetworkXError): + bipartite.biadjacency_matrix(nx.Graph(), []) + + def test_empty_graph(self): + with pytest.raises(nx.NetworkXError): + bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), []) + + def test_duplicate_row(self): + with pytest.raises(nx.NetworkXError): + bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [1, 1]) + + def test_duplicate_col(self): + with pytest.raises(nx.NetworkXError): + bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], [1, 1]) + + def test_format_keyword(self): + with pytest.raises(nx.NetworkXError): + bipartite.biadjacency_matrix(nx.Graph([(1, 0)]), [0], format="foo") + + def test_from_biadjacency_roundtrip(self): + B1 = nx.path_graph(5) + M = bipartite.biadjacency_matrix(B1, [0, 2, 4]) + B2 = bipartite.from_biadjacency_matrix(M) + assert nx.is_isomorphic(B1, B2) + + def test_from_biadjacency_weight(self): + M = sparse.csc_matrix([[1, 2], [0, 3]]) + B = bipartite.from_biadjacency_matrix(M) + assert_edges_equal(B.edges(), [(0, 2), (0, 3), (1, 3)]) + B = bipartite.from_biadjacency_matrix(M, edge_attribute="weight") + e = [(0, 2, {"weight": 1}), (0, 3, {"weight": 2}), (1, 3, {"weight": 3})] + assert_edges_equal(B.edges(data=True), e) + + def test_from_biadjacency_multigraph(self): + M = sparse.csc_matrix([[1, 2], [0, 3]]) + B = bipartite.from_biadjacency_matrix(M, create_using=nx.MultiGraph()) + assert_edges_equal(B.edges(), [(0, 2), (0, 3), (0, 3), (1, 3), (1, 3), (1, 3)])