124 lines
4.2 KiB
Python
124 lines
4.2 KiB
Python
#!/usr/bin/env python
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import pytest
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import networkx as nx
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from networkx.algorithms import bipartite
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class TestBipartiteBasic:
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def test_is_bipartite(self):
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assert bipartite.is_bipartite(nx.path_graph(4))
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assert bipartite.is_bipartite(nx.DiGraph([(1, 0)]))
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assert not bipartite.is_bipartite(nx.complete_graph(3))
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def test_bipartite_color(self):
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G = nx.path_graph(4)
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c = bipartite.color(G)
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assert c == {0: 1, 1: 0, 2: 1, 3: 0}
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def test_not_bipartite_color(self):
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with pytest.raises(nx.NetworkXError):
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c = bipartite.color(nx.complete_graph(4))
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def test_bipartite_directed(self):
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G = bipartite.random_graph(10, 10, 0.1, directed=True)
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assert bipartite.is_bipartite(G)
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def test_bipartite_sets(self):
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G = nx.path_graph(4)
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X, Y = bipartite.sets(G)
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assert X == {0, 2}
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assert Y == {1, 3}
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def test_bipartite_sets_directed(self):
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G = nx.path_graph(4)
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D = G.to_directed()
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X, Y = bipartite.sets(D)
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assert X == {0, 2}
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assert Y == {1, 3}
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def test_bipartite_sets_given_top_nodes(self):
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G = nx.path_graph(4)
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top_nodes = [0, 2]
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X, Y = bipartite.sets(G, top_nodes)
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assert X == {0, 2}
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assert Y == {1, 3}
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def test_bipartite_sets_disconnected(self):
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with pytest.raises(nx.AmbiguousSolution):
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G = nx.path_graph(4)
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G.add_edges_from([(5, 6), (6, 7)])
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X, Y = bipartite.sets(G)
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def test_is_bipartite_node_set(self):
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G = nx.path_graph(4)
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assert bipartite.is_bipartite_node_set(G, [0, 2])
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assert bipartite.is_bipartite_node_set(G, [1, 3])
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assert not bipartite.is_bipartite_node_set(G, [1, 2])
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G.add_edge(10, 20)
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assert bipartite.is_bipartite_node_set(G, [0, 2, 10])
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assert bipartite.is_bipartite_node_set(G, [0, 2, 20])
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assert bipartite.is_bipartite_node_set(G, [1, 3, 10])
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assert bipartite.is_bipartite_node_set(G, [1, 3, 20])
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def test_bipartite_density(self):
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G = nx.path_graph(5)
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X, Y = bipartite.sets(G)
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density = float(len(list(G.edges()))) / (len(X) * len(Y))
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assert bipartite.density(G, X) == density
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D = nx.DiGraph(G.edges())
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assert bipartite.density(D, X) == density / 2.0
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assert bipartite.density(nx.Graph(), {}) == 0.0
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def test_bipartite_degrees(self):
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G = nx.path_graph(5)
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X = set([1, 3])
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Y = set([0, 2, 4])
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u, d = bipartite.degrees(G, Y)
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assert dict(u) == {1: 2, 3: 2}
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assert dict(d) == {0: 1, 2: 2, 4: 1}
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def test_bipartite_weighted_degrees(self):
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G = nx.path_graph(5)
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G.add_edge(0, 1, weight=0.1, other=0.2)
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X = set([1, 3])
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Y = set([0, 2, 4])
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u, d = bipartite.degrees(G, Y, weight='weight')
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assert dict(u) == {1: 1.1, 3: 2}
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assert dict(d) == {0: 0.1, 2: 2, 4: 1}
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u, d = bipartite.degrees(G, Y, weight='other')
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assert dict(u) == {1: 1.2, 3: 2}
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assert dict(d) == {0: 0.2, 2: 2, 4: 1}
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def test_biadjacency_matrix_weight(self):
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scipy = pytest.importorskip('scipy')
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G = nx.path_graph(5)
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G.add_edge(0, 1, weight=2, other=4)
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X = [1, 3]
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Y = [0, 2, 4]
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M = bipartite.biadjacency_matrix(G, X, weight='weight')
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assert M[0, 0] == 2
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M = bipartite.biadjacency_matrix(G, X, weight='other')
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assert M[0, 0] == 4
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def test_biadjacency_matrix(self):
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scipy = pytest.importorskip('scipy')
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tops = [2, 5, 10]
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bots = [5, 10, 15]
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for i in range(len(tops)):
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G = bipartite.random_graph(tops[i], bots[i], 0.2)
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top = [n for n, d in G.nodes(data=True) if d['bipartite'] == 0]
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M = bipartite.biadjacency_matrix(G, top)
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assert M.shape[0] == tops[i]
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assert M.shape[1] == bots[i]
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def test_biadjacency_matrix_order(self):
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scipy = pytest.importorskip('scipy')
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G = nx.path_graph(5)
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G.add_edge(0, 1, weight=2)
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X = [3, 1]
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Y = [4, 2, 0]
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M = bipartite.biadjacency_matrix(G, X, Y, weight='weight')
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assert M[1, 2] == 2
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