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- 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.utils import 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)])
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