507 lines
18 KiB
Python
507 lines
18 KiB
Python
import math
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from functools import partial
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import pytest
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import networkx as nx
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def _test_func(G, ebunch, expected, predict_func, **kwargs):
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result = predict_func(G, ebunch, **kwargs)
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exp_dict = dict((tuple(sorted([u, v])), score) for u, v, score in expected)
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res_dict = dict((tuple(sorted([u, v])), score) for u, v, score in result)
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assert len(exp_dict) == len(res_dict)
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for p in exp_dict:
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assert nx.testing.almost_equal(exp_dict[p], res_dict[p])
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class TestResourceAllocationIndex():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.resource_allocation_index)
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cls.test = partial(_test_func, predict_func=cls.func)
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def test_K5(self):
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G = nx.complete_graph(5)
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self.test(G, [(0, 1)], [(0, 1, 0.75)])
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def test_P3(self):
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G = nx.path_graph(3)
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self.test(G, [(0, 2)], [(0, 2, 0.5)])
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def test_S4(self):
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G = nx.star_graph(4)
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self.test(G, [(1, 2)], [(1, 2, 0.25)])
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def test_notimplemented(self):
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.DiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiDiGraph([(0, 1), (1, 2)]), [(0, 2)])
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_equal_nodes(self):
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G = nx.complete_graph(4)
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self.test(G, [(0, 0)], [(0, 0, 1)])
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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self.test(G, None, [(0, 3, 0.5), (1, 2, 0.5), (1, 3, 0)])
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class TestJaccardCoefficient():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.jaccard_coefficient)
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cls.test = partial(_test_func, predict_func=cls.func)
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def test_K5(self):
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G = nx.complete_graph(5)
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self.test(G, [(0, 1)], [(0, 1, 0.6)])
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def test_P4(self):
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G = nx.path_graph(4)
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self.test(G, [(0, 2)], [(0, 2, 0.5)])
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def test_notimplemented(self):
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.DiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiDiGraph([(0, 1), (1, 2)]), [(0, 2)])
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (2, 3)])
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self.test(G, [(0, 2)], [(0, 2, 0)])
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def test_isolated_nodes(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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self.test(G, None, [(0, 3, 0.5), (1, 2, 0.5), (1, 3, 0)])
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class TestAdamicAdarIndex():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.adamic_adar_index)
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cls.test = partial(_test_func, predict_func=cls.func)
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def test_K5(self):
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G = nx.complete_graph(5)
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self.test(G, [(0, 1)], [(0, 1, 3 / math.log(4))])
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def test_P3(self):
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G = nx.path_graph(3)
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self.test(G, [(0, 2)], [(0, 2, 1 / math.log(2))])
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def test_S4(self):
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G = nx.star_graph(4)
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self.test(G, [(1, 2)], [(1, 2, 1 / math.log(4))])
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def test_notimplemented(self):
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.DiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiDiGraph([(0, 1), (1, 2)]), [(0, 2)])
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_equal_nodes(self):
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G = nx.complete_graph(4)
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self.test(G, [(0, 0)], [(0, 0, 3 / math.log(3))])
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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self.test(G, None, [(0, 3, 1 / math.log(2)), (1, 2, 1 / math.log(2)),
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(1, 3, 0)])
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class TestPreferentialAttachment():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.preferential_attachment)
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cls.test = partial(_test_func, predict_func=cls.func)
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def test_K5(self):
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G = nx.complete_graph(5)
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self.test(G, [(0, 1)], [(0, 1, 16)])
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def test_P3(self):
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G = nx.path_graph(3)
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self.test(G, [(0, 1)], [(0, 1, 2)])
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def test_S4(self):
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G = nx.star_graph(4)
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self.test(G, [(0, 2)], [(0, 2, 4)])
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def test_notimplemented(self):
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.DiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiGraph([(0, 1), (1, 2)]), [(0, 2)])
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assert pytest.raises(nx.NetworkXNotImplemented, self.func,
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nx.MultiDiGraph([(0, 1), (1, 2)]), [(0, 2)])
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def test_zero_degrees(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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self.test(G, None, [(0, 3, 2), (1, 2, 2), (1, 3, 1)])
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class TestCNSoundarajanHopcroft():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.cn_soundarajan_hopcroft)
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cls.test = partial(_test_func, predict_func=cls.func,
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community='community')
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def test_K5(self):
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G = nx.complete_graph(5)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 1
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self.test(G, [(0, 1)], [(0, 1, 5)])
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def test_P3(self):
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G = nx.path_graph(3)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 0
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self.test(G, [(0, 2)], [(0, 2, 1)])
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def test_S4(self):
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G = nx.star_graph(4)
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G.nodes[0]['community'] = 1
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 1
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 0
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self.test(G, [(1, 2)], [(1, 2, 2)])
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def test_notimplemented(self):
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G = nx.DiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiDiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_equal_nodes(self):
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G = nx.complete_graph(3)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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self.test(G, [(0, 0)], [(0, 0, 4)])
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def test_different_community(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 1
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self.test(G, [(0, 3)], [(0, 3, 2)])
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def test_no_community_information(self):
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G = nx.complete_graph(5)
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assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 1)]))
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def test_insufficient_community_information(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[3]['community'] = 0
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assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 3)]))
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def test_sufficient_community_information(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4), (3, 4), (4, 5)])
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 0
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self.test(G, [(1, 4)], [(1, 4, 4)])
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def test_custom_community_attribute_name(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['cmty'] = 0
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G.nodes[1]['cmty'] = 0
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G.nodes[2]['cmty'] = 0
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G.nodes[3]['cmty'] = 1
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self.test(G, [(0, 3)], [(0, 3, 2)], community='cmty')
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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self.test(G, None, [(0, 3, 2), (1, 2, 1), (1, 3, 0)])
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class TestRAIndexSoundarajanHopcroft():
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@classmethod
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def setup_class(cls):
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cls.func = staticmethod(nx.ra_index_soundarajan_hopcroft)
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cls.test = partial(_test_func, predict_func=cls.func,
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community='community')
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def test_K5(self):
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G = nx.complete_graph(5)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 1
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self.test(G, [(0, 1)], [(0, 1, 0.5)])
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def test_P3(self):
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G = nx.path_graph(3)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 0
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self.test(G, [(0, 2)], [(0, 2, 0)])
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def test_S4(self):
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G = nx.star_graph(4)
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G.nodes[0]['community'] = 1
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 1
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 0
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self.test(G, [(1, 2)], [(1, 2, 0.25)])
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def test_notimplemented(self):
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G = nx.DiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiDiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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self.test(G, [(0, 1)], [(0, 1, 0)])
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def test_equal_nodes(self):
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G = nx.complete_graph(3)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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self.test(G, [(0, 0)], [(0, 0, 1)])
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def test_different_community(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 1
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self.test(G, [(0, 3)], [(0, 3, 0)])
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def test_no_community_information(self):
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G = nx.complete_graph(5)
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assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 1)]))
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def test_insufficient_community_information(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[3]['community'] = 0
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assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 3)]))
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def test_sufficient_community_information(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4), (3, 4), (4, 5)])
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 0
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self.test(G, [(1, 4)], [(1, 4, 1)])
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def test_custom_community_attribute_name(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
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G.nodes[0]['cmty'] = 0
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G.nodes[1]['cmty'] = 0
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G.nodes[2]['cmty'] = 0
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G.nodes[3]['cmty'] = 1
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self.test(G, [(0, 3)], [(0, 3, 0)], community='cmty')
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def test_all_nonexistent_edges(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (2, 3)])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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self.test(G, None, [(0, 3, 0.5), (1, 2, 0), (1, 3, 0)])
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class TestWithinInterCluster():
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@classmethod
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def setup_class(cls):
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cls.delta = 0.001
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cls.func = staticmethod(nx.within_inter_cluster)
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cls.test = partial(_test_func, predict_func=cls.func,
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delta=cls.delta, community='community')
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def test_K5(self):
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G = nx.complete_graph(5)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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G.nodes[2]['community'] = 0
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 1
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self.test(G, [(0, 1)], [(0, 1, 2 / (1 + self.delta))])
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def test_P3(self):
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G = nx.path_graph(3)
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 0
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self.test(G, [(0, 2)], [(0, 2, 0)])
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def test_S4(self):
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G = nx.star_graph(4)
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G.nodes[0]['community'] = 1
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G.nodes[1]['community'] = 1
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G.nodes[2]['community'] = 1
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G.nodes[3]['community'] = 0
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G.nodes[4]['community'] = 0
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self.test(G, [(1, 2)], [(1, 2, 1 / self.delta)])
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def test_notimplemented(self):
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G = nx.DiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
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G = nx.MultiDiGraph([(0, 1), (1, 2)])
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G.add_nodes_from([0, 1, 2], community=0)
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assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
|
|
|
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def test_no_common_neighbor(self):
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G = nx.Graph()
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G.add_nodes_from([0, 1])
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G.nodes[0]['community'] = 0
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G.nodes[1]['community'] = 0
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self.test(G, [(0, 1)], [(0, 1, 0)])
|
|
|
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def test_equal_nodes(self):
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G = nx.complete_graph(3)
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G.nodes[0]['community'] = 0
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|
G.nodes[1]['community'] = 0
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|
G.nodes[2]['community'] = 0
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self.test(G, [(0, 0)], [(0, 0, 2 / self.delta)])
|
|
|
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def test_different_community(self):
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G = nx.Graph()
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G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
|
|
G.nodes[0]['community'] = 0
|
|
G.nodes[1]['community'] = 0
|
|
G.nodes[2]['community'] = 0
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|
G.nodes[3]['community'] = 1
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self.test(G, [(0, 3)], [(0, 3, 0)])
|
|
|
|
def test_no_inter_cluster_common_neighbor(self):
|
|
G = nx.complete_graph(4)
|
|
G.nodes[0]['community'] = 0
|
|
G.nodes[1]['community'] = 0
|
|
G.nodes[2]['community'] = 0
|
|
G.nodes[3]['community'] = 0
|
|
self.test(G, [(0, 3)], [(0, 3, 2 / self.delta)])
|
|
|
|
def test_no_community_information(self):
|
|
G = nx.complete_graph(5)
|
|
assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 1)]))
|
|
|
|
def test_insufficient_community_information(self):
|
|
G = nx.Graph()
|
|
G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)])
|
|
G.nodes[0]['community'] = 0
|
|
G.nodes[1]['community'] = 0
|
|
G.nodes[3]['community'] = 0
|
|
assert pytest.raises(nx.NetworkXAlgorithmError, list, self.func(G, [(0, 3)]))
|
|
|
|
def test_sufficient_community_information(self):
|
|
G = nx.Graph()
|
|
G.add_edges_from([(0, 1), (1, 2), (1, 3), (2, 4), (3, 4), (4, 5)])
|
|
G.nodes[1]['community'] = 0
|
|
G.nodes[2]['community'] = 0
|
|
G.nodes[3]['community'] = 0
|
|
G.nodes[4]['community'] = 0
|
|
self.test(G, [(1, 4)], [(1, 4, 2 / self.delta)])
|
|
|
|
def test_invalid_delta(self):
|
|
G = nx.complete_graph(3)
|
|
G.add_nodes_from([0, 1, 2], community=0)
|
|
assert pytest.raises(nx.NetworkXAlgorithmError, self.func, G, [(0, 1)], 0)
|
|
assert pytest.raises(nx.NetworkXAlgorithmError, self.func, G, [(0, 1)], -0.5)
|
|
|
|
def test_custom_community_attribute_name(self):
|
|
G = nx.complete_graph(4)
|
|
G.nodes[0]['cmty'] = 0
|
|
G.nodes[1]['cmty'] = 0
|
|
G.nodes[2]['cmty'] = 0
|
|
G.nodes[3]['cmty'] = 0
|
|
self.test(G, [(0, 3)], [(0, 3, 2 / self.delta)], community='cmty')
|
|
|
|
def test_all_nonexistent_edges(self):
|
|
G = nx.Graph()
|
|
G.add_edges_from([(0, 1), (0, 2), (2, 3)])
|
|
G.nodes[0]['community'] = 0
|
|
G.nodes[1]['community'] = 1
|
|
G.nodes[2]['community'] = 0
|
|
G.nodes[3]['community'] = 0
|
|
self.test(G, None, [(0, 3, 1 / self.delta), (1, 2, 0), (1, 3, 0)])
|