79 lines
3.2 KiB
Python
79 lines
3.2 KiB
Python
import pytest
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import networkx as nx
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from networkx.algorithms.approximation.steinertree import metric_closure
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from networkx.algorithms.approximation.steinertree import steiner_tree
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from networkx.testing.utils import assert_edges_equal
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class TestSteinerTree:
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@classmethod
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def setup_class(cls):
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G = nx.Graph()
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G.add_edge(1, 2, weight=10)
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G.add_edge(2, 3, weight=10)
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G.add_edge(3, 4, weight=10)
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G.add_edge(4, 5, weight=10)
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G.add_edge(5, 6, weight=10)
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G.add_edge(2, 7, weight=1)
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G.add_edge(7, 5, weight=1)
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cls.G = G
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cls.term_nodes = [1, 2, 3, 4, 5]
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def test_connected_metric_closure(self):
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G = self.G.copy()
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G.add_node(100)
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pytest.raises(nx.NetworkXError, metric_closure, G)
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def test_metric_closure(self):
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M = metric_closure(self.G)
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mc = [(1, 2, {'distance': 10, 'path': [1, 2]}),
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(1, 3, {'distance': 20, 'path': [1, 2, 3]}),
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(1, 4, {'distance': 22, 'path': [1, 2, 7, 5, 4]}),
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(1, 5, {'distance': 12, 'path': [1, 2, 7, 5]}),
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(1, 6, {'distance': 22, 'path': [1, 2, 7, 5, 6]}),
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(1, 7, {'distance': 11, 'path': [1, 2, 7]}),
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(2, 3, {'distance': 10, 'path': [2, 3]}),
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(2, 4, {'distance': 12, 'path': [2, 7, 5, 4]}),
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(2, 5, {'distance': 2, 'path': [2, 7, 5]}),
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(2, 6, {'distance': 12, 'path': [2, 7, 5, 6]}),
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(2, 7, {'distance': 1, 'path': [2, 7]}),
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(3, 4, {'distance': 10, 'path': [3, 4]}),
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(3, 5, {'distance': 12, 'path': [3, 2, 7, 5]}),
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(3, 6, {'distance': 22, 'path': [3, 2, 7, 5, 6]}),
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(3, 7, {'distance': 11, 'path': [3, 2, 7]}),
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(4, 5, {'distance': 10, 'path': [4, 5]}),
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(4, 6, {'distance': 20, 'path': [4, 5, 6]}),
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(4, 7, {'distance': 11, 'path': [4, 5, 7]}),
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(5, 6, {'distance': 10, 'path': [5, 6]}),
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(5, 7, {'distance': 1, 'path': [5, 7]}),
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(6, 7, {'distance': 11, 'path': [6, 5, 7]})]
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assert_edges_equal(list(M.edges(data=True)), mc)
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def test_steiner_tree(self):
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S = steiner_tree(self.G, self.term_nodes)
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expected_steiner_tree = [(1, 2, {'weight': 10}),
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(2, 3, {'weight': 10}),
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(2, 7, {'weight': 1}),
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(3, 4, {'weight': 10}),
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(5, 7, {'weight': 1})]
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assert_edges_equal(list(S.edges(data=True)), expected_steiner_tree)
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def test_multigraph_steiner_tree(self):
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with pytest.raises(nx.NetworkXNotImplemented):
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G = nx.MultiGraph()
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G.add_edges_from([
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(1, 2, 0, {'weight': 1}),
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(2, 3, 0, {'weight': 999}),
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(2, 3, 1, {'weight': 1}),
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(3, 4, 0, {'weight': 1}),
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(3, 5, 0, {'weight': 1})
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])
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terminal_nodes = [2, 4, 5]
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expected_edges = [
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(2, 3, 1, {'weight': 1}), # edge with key 1 has lower weight
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(3, 4, 0, {'weight': 1}),
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(3, 5, 0, {'weight': 1})
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]
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# not implemented
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T = steiner_tree(G, terminal_nodes)
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