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## iof-tools / networkxMiCe / networkx-master / networkx / algorithms / tests / test_link_prediction.py @ 5cef0f13

 1 ```import math ``` ```from functools import partial ``` ```from nose.tools import * ``` ```import networkx as nx ``` ```def _test_func(G, ebunch, expected, predict_func, **kwargs): ``` ``` result = predict_func(G, ebunch, **kwargs) ``` ``` exp_dict = dict((tuple(sorted([u, v])), score) for u, v, score in expected) ``` ``` res_dict = dict((tuple(sorted([u, v])), score) for u, v, score in result) ``` ``` assert_equal(len(exp_dict), len(res_dict)) ``` ``` for p in exp_dict: ``` ``` assert_almost_equal(exp_dict[p], res_dict[p]) ``` ```class TestResourceAllocationIndex(): ``` ``` def setUp(self): ``` ``` self.func = nx.resource_allocation_index ``` ``` self.test = partial(_test_func, predict_func=self.func) ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0.75)]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` self.test(G, [(0, 2)], [(0, 2, 0.5)]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` self.test(G, [(1, 2)], [(1, 2, 0.25)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_equal_nodes(self): ``` ``` G = nx.complete_graph(4) ``` ``` self.test(G, [(0, 0)], [(0, 0, 1)]) ``` ``` def test_all_nonexistent_edges(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (2, 3)]) ``` ``` self.test(G, None, [(0, 3, 0.5), (1, 2, 0.5), (1, 3, 0)]) ``` ```class TestJaccardCoefficient(): ``` ``` def setUp(self): ``` ``` self.func = nx.jaccard_coefficient ``` ``` self.test = partial(_test_func, predict_func=self.func) ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0.6)]) ``` ``` def test_P4(self): ``` ``` G = nx.path_graph(4) ``` ``` self.test(G, [(0, 2)], [(0, 2, 0.5)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (2, 3)]) ``` ``` self.test(G, [(0, 2)], [(0, 2, 0)]) ``` ``` def test_isolated_nodes(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_all_nonexistent_edges(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (2, 3)]) ``` ``` self.test(G, None, [(0, 3, 0.5), (1, 2, 0.5), (1, 3, 0)]) ``` ```class TestAdamicAdarIndex(): ``` ``` def setUp(self): ``` ``` self.func = nx.adamic_adar_index ``` ``` self.test = partial(_test_func, predict_func=self.func) ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` self.test(G, [(0, 1)], [(0, 1, 3 / math.log(4))]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` self.test(G, [(0, 2)], [(0, 2, 1 / math.log(2))]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` self.test(G, [(1, 2)], [(1, 2, 1 / math.log(4))]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_equal_nodes(self): ``` ``` G = nx.complete_graph(4) ``` ``` self.test(G, [(0, 0)], [(0, 0, 3 / math.log(3))]) ``` ``` def test_all_nonexistent_edges(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (2, 3)]) ``` ``` self.test(G, None, [(0, 3, 1 / math.log(2)), (1, 2, 1 / math.log(2)), ``` ``` (1, 3, 0)]) ``` ```class TestPreferentialAttachment(): ``` ``` def setUp(self): ``` ``` self.func = nx.preferential_attachment ``` ``` self.test = partial(_test_func, predict_func=self.func) ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` self.test(G, [(0, 1)], [(0, 1, 16)]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` self.test(G, [(0, 1)], [(0, 1, 2)]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` self.test(G, [(0, 2)], [(0, 2, 4)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_zero_degrees(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_all_nonexistent_edges(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (2, 3)]) ``` ``` self.test(G, None, [(0, 3, 2), (1, 2, 2), (1, 3, 1)]) ``` ```class TestCNSoundarajanHopcroft(): ``` ``` def setUp(self): ``` ``` self.func = nx.cn_soundarajan_hopcroft ``` ``` self.test = partial(_test_func, predict_func=self.func, ``` ``` community='community') ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 1 ``` ``` self.test(G, [(0, 1)], [(0, 1, 5)]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 2)], [(0, 2, 1)]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` G.nodes[0]['community'] = 1 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 1 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 0 ``` ``` self.test(G, [(1, 2)], [(1, 2, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_equal_nodes(self): ``` ``` G = nx.complete_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 0)], [(0, 0, 4)]) ``` ``` def test_different_community(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[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 1 ``` ``` self.test(G, [(0, 3)], [(0, 3, 2)]) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` def test_no_community_information(self): ``` ``` G = nx.complete_graph(5) ``` ``` list(self.func(G, [(0, 1)])) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` 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 ``` ``` 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, 4)]) ``` ``` def test_custom_community_attribute_name(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)]) ``` ``` G.nodes[0]['cmty'] = 0 ``` ``` G.nodes[1]['cmty'] = 0 ``` ``` G.nodes[2]['cmty'] = 0 ``` ``` G.nodes[3]['cmty'] = 1 ``` ``` self.test(G, [(0, 3)], [(0, 3, 2)], 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, 2), (1, 2, 1), (1, 3, 0)]) ``` ```class TestRAIndexSoundarajanHopcroft(): ``` ``` def setUp(self): ``` ``` self.func = nx.ra_index_soundarajan_hopcroft ``` ``` self.test = partial(_test_func, predict_func=self.func, ``` ``` community='community') ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 1 ``` ``` self.test(G, [(0, 1)], [(0, 1, 0.5)]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 2)], [(0, 2, 0)]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` G.nodes[0]['community'] = 1 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 1 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 0 ``` ``` self.test(G, [(1, 2)], [(1, 2, 0.25)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_equal_nodes(self): ``` ``` G = nx.complete_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 0)], [(0, 0, 1)]) ``` ``` def test_different_community(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[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 1 ``` ``` self.test(G, [(0, 3)], [(0, 3, 0)]) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` def test_no_community_information(self): ``` ``` G = nx.complete_graph(5) ``` ``` list(self.func(G, [(0, 1)])) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` 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 ``` ``` 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, 1)]) ``` ``` def test_custom_community_attribute_name(self): ``` ``` G = nx.Graph() ``` ``` G.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3)]) ``` ``` G.nodes[0]['cmty'] = 0 ``` ``` G.nodes[1]['cmty'] = 0 ``` ``` G.nodes[2]['cmty'] = 0 ``` ``` G.nodes[3]['cmty'] = 1 ``` ``` self.test(G, [(0, 3)], [(0, 3, 0)], 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, 0.5), (1, 2, 0), (1, 3, 0)]) ``` ```class TestWithinInterCluster(): ``` ``` def setUp(self): ``` ``` self.delta = 0.001 ``` ``` self.func = nx.within_inter_cluster ``` ``` self.test = partial(_test_func, predict_func=self.func, ``` ``` delta=self.delta, community='community') ``` ``` def test_K5(self): ``` ``` G = nx.complete_graph(5) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 1 ``` ``` self.test(G, [(0, 1)], [(0, 1, 2 / (1 + self.delta))]) ``` ``` def test_P3(self): ``` ``` G = nx.path_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 2)], [(0, 2, 0)]) ``` ``` def test_S4(self): ``` ``` G = nx.star_graph(4) ``` ``` G.nodes[0]['community'] = 1 ``` ``` G.nodes[1]['community'] = 1 ``` ``` G.nodes[2]['community'] = 1 ``` ``` G.nodes[3]['community'] = 0 ``` ``` G.nodes[4]['community'] = 0 ``` ``` self.test(G, [(1, 2)], [(1, 2, 1 / self.delta)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_digraph(self): ``` ``` G = nx.DiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multigraph(self): ``` ``` G = nx.MultiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` @raises(nx.NetworkXNotImplemented) ``` ``` def test_multidigraph(self): ``` ``` G = nx.MultiDiGraph() ``` ``` G.add_edges_from([(0, 1), (1, 2)]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.func(G, [(0, 2)]) ``` ``` def test_no_common_neighbor(self): ``` ``` G = nx.Graph() ``` ``` G.add_nodes_from([0, 1]) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` self.test(G, [(0, 1)], [(0, 1, 0)]) ``` ``` def test_equal_nodes(self): ``` ``` G = nx.complete_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` self.test(G, [(0, 0)], [(0, 0, 2 / self.delta)]) ``` ``` def test_different_community(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[2]['community'] = 0 ``` ``` G.nodes[3]['community'] = 1 ``` ``` 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)]) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` def test_no_community_information(self): ``` ``` G = nx.complete_graph(5) ``` ``` list(self.func(G, [(0, 1)])) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` 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 ``` ``` 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)]) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` def test_zero_delta(self): ``` ``` G = nx.complete_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` list(self.func(G, [(0, 1)], 0)) ``` ``` @raises(nx.NetworkXAlgorithmError) ``` ``` def test_negative_delta(self): ``` ``` G = nx.complete_graph(3) ``` ``` G.nodes[0]['community'] = 0 ``` ``` G.nodes[1]['community'] = 0 ``` ``` G.nodes[2]['community'] = 0 ``` ``` list(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)]) ```