158 lines
6.4 KiB
Python
158 lines
6.4 KiB
Python
#!/usr/bin/env python
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import pytest
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import networkx as nx
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class TestFloyd:
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@classmethod
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def setup_class(cls):
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pass
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def test_floyd_warshall_predecessor_and_distance(self):
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XG = nx.DiGraph()
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XG.add_weighted_edges_from([('s', 'u', 10), ('s', 'x', 5),
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('u', 'v', 1), ('u', 'x', 2),
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('v', 'y', 1), ('x', 'u', 3),
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('x', 'v', 5), ('x', 'y', 2),
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('y', 's', 7), ('y', 'v', 6)])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG)
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assert dist['s']['v'] == 9
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assert path['s']['v'] == 'u'
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assert (dist ==
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{'y': {'y': 0, 'x': 12, 's': 7, 'u': 15, 'v': 6},
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'x': {'y': 2, 'x': 0, 's': 9, 'u': 3, 'v': 4},
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's': {'y': 7, 'x': 5, 's': 0, 'u': 8, 'v': 9},
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'u': {'y': 2, 'x': 2, 's': 9, 'u': 0, 'v': 1},
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'v': {'y': 1, 'x': 13, 's': 8, 'u': 16, 'v': 0}})
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GG = XG.to_undirected()
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# make sure we get lower weight
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# to_undirected might choose either edge with weight 2 or weight 3
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GG['u']['x']['weight'] = 2
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path, dist = nx.floyd_warshall_predecessor_and_distance(GG)
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assert dist['s']['v'] == 8
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# skip this test, could be alternate path s-u-v
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# assert_equal(path['s']['v'],'y')
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G = nx.DiGraph() # no weights
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G.add_edges_from([('s', 'u'), ('s', 'x'),
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('u', 'v'), ('u', 'x'),
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('v', 'y'), ('x', 'u'),
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('x', 'v'), ('x', 'y'),
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('y', 's'), ('y', 'v')])
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path, dist = nx.floyd_warshall_predecessor_and_distance(G)
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assert dist['s']['v'] == 2
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# skip this test, could be alternate path s-u-v
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# assert_equal(path['s']['v'],'x')
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# alternate interface
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dist = nx.floyd_warshall(G)
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assert dist['s']['v'] == 2
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# floyd_warshall_predecessor_and_distance returns
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# dicts-of-defautdicts
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# make sure we don't get empty dictionary
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XG = nx.DiGraph()
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XG.add_weighted_edges_from([('v', 'x', 5.0), ('y', 'x', 5.0),
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('v', 'y', 6.0), ('x', 'u', 2.0)])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG)
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inf = float("inf")
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assert (dist ==
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{'v': {'v': 0, 'x': 5.0, 'y': 6.0, 'u': 7.0},
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'x': {'x': 0, 'u': 2.0, 'v': inf, 'y': inf},
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'y': {'y': 0, 'x': 5.0, 'v': inf, 'u': 7.0},
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'u': {'u': 0, 'v': inf, 'x': inf, 'y': inf}})
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assert (path ==
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{'v': {'x': 'v', 'y': 'v', 'u': 'x'},
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'x': {'u': 'x'},
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'y': {'x': 'y', 'u': 'x'}})
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def test_reconstruct_path(self):
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with pytest.raises(KeyError):
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XG = nx.DiGraph()
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XG.add_weighted_edges_from([('s', 'u', 10), ('s', 'x', 5),
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('u', 'v', 1), ('u', 'x', 2),
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('v', 'y', 1), ('x', 'u', 3),
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('x', 'v', 5), ('x', 'y', 2),
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('y', 's', 7), ('y', 'v', 6)])
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predecessors, _ = nx.floyd_warshall_predecessor_and_distance(XG)
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path = nx.reconstruct_path('s', 'v', predecessors)
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assert path == ['s', 'x', 'u', 'v']
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path = nx.reconstruct_path('s', 's', predecessors)
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assert path == []
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# this part raises the keyError
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nx.reconstruct_path('1', '2', predecessors)
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def test_cycle(self):
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path, dist = nx.floyd_warshall_predecessor_and_distance(
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nx.cycle_graph(7))
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assert dist[0][3] == 3
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assert path[0][3] == 2
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assert dist[0][4] == 3
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def test_weighted(self):
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XG3 = nx.Graph()
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XG3.add_weighted_edges_from([[0, 1, 2], [1, 2, 12], [2, 3, 1],
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[3, 4, 5], [4, 5, 1], [5, 0, 10]])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG3)
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assert dist[0][3] == 15
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assert path[0][3] == 2
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def test_weighted2(self):
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XG4 = nx.Graph()
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XG4.add_weighted_edges_from([[0, 1, 2], [1, 2, 2], [2, 3, 1],
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[3, 4, 1], [4, 5, 1], [5, 6, 1],
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[6, 7, 1], [7, 0, 1]])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG4)
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assert dist[0][2] == 4
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assert path[0][2] == 1
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def test_weight_parameter(self):
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XG4 = nx.Graph()
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XG4.add_edges_from([(0, 1, {'heavy': 2}), (1, 2, {'heavy': 2}),
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(2, 3, {'heavy': 1}), (3, 4, {'heavy': 1}),
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(4, 5, {'heavy': 1}), (5, 6, {'heavy': 1}),
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(6, 7, {'heavy': 1}), (7, 0, {'heavy': 1})])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG4,
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weight='heavy')
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assert dist[0][2] == 4
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assert path[0][2] == 1
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def test_zero_distance(self):
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XG = nx.DiGraph()
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XG.add_weighted_edges_from([('s', 'u', 10), ('s', 'x', 5),
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('u', 'v', 1), ('u', 'x', 2),
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('v', 'y', 1), ('x', 'u', 3),
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('x', 'v', 5), ('x', 'y', 2),
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('y', 's', 7), ('y', 'v', 6)])
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path, dist = nx.floyd_warshall_predecessor_and_distance(XG)
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for u in XG:
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assert dist[u][u] == 0
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GG = XG.to_undirected()
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# make sure we get lower weight
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# to_undirected might choose either edge with weight 2 or weight 3
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GG['u']['x']['weight'] = 2
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path, dist = nx.floyd_warshall_predecessor_and_distance(GG)
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for u in GG:
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dist[u][u] = 0
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def test_zero_weight(self):
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G = nx.DiGraph()
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edges = [(1, 2, -2), (2, 3, -4), (1, 5, 1),
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(5, 4, 0), (4, 3, -5), (2, 5, -7)]
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G.add_weighted_edges_from(edges)
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dist = nx.floyd_warshall(G)
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assert dist[1][3] == -14
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G = nx.MultiDiGraph()
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edges.append((2, 5, -7))
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G.add_weighted_edges_from(edges)
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dist = nx.floyd_warshall(G)
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assert dist[1][3] == -14
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