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diff --git a/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_link_prediction.py b/.venv/lib/python3.12/site-packages/networkx/algorithms/tests/test_link_prediction.py
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+import math
+from functools import partial
+
+import pytest
+
+import networkx as nx
+
+
+def _test_func(G, ebunch, expected, predict_func, **kwargs):
+ result = predict_func(G, ebunch, **kwargs)
+ exp_dict = {tuple(sorted([u, v])): score for u, v, score in expected}
+ res_dict = {tuple(sorted([u, v])): score for u, v, score in result}
+
+ assert len(exp_dict) == len(res_dict)
+ for p in exp_dict:
+ assert exp_dict[p] == pytest.approx(res_dict[p], abs=1e-7)
+
+
+class TestResourceAllocationIndex:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.resource_allocation_index)
+ cls.test = partial(_test_func, predict_func=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ assert pytest.raises(
+ nx.NetworkXNotImplemented, self.func, graph_type([(0, 1), (1, 2)]), [(0, 2)]
+ )
+
+ def test_node_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(0, 1), (0, 2), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.jaccard_coefficient)
+ cls.test = partial(_test_func, predict_func=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ assert pytest.raises(
+ nx.NetworkXNotImplemented, self.func, graph_type([(0, 1), (1, 2)]), [(0, 2)]
+ )
+
+ def test_node_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(0, 1), (0, 2), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.adamic_adar_index)
+ cls.test = partial(_test_func, predict_func=cls.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))])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ assert pytest.raises(
+ nx.NetworkXNotImplemented, self.func, graph_type([(0, 1), (1, 2)]), [(0, 2)]
+ )
+
+ def test_node_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(0, 1), (0, 2), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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 TestCommonNeighborCentrality:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.common_neighbor_centrality)
+ cls.test = partial(_test_func, predict_func=cls.func)
+
+ def test_K5(self):
+ G = nx.complete_graph(5)
+ self.test(G, [(0, 1)], [(0, 1, 3.0)], alpha=1)
+ self.test(G, [(0, 1)], [(0, 1, 5.0)], alpha=0)
+
+ def test_P3(self):
+ G = nx.path_graph(3)
+ self.test(G, [(0, 2)], [(0, 2, 1.25)], alpha=0.5)
+
+ def test_S4(self):
+ G = nx.star_graph(4)
+ self.test(G, [(1, 2)], [(1, 2, 1.75)], alpha=0.5)
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ assert pytest.raises(
+ nx.NetworkXNotImplemented, self.func, graph_type([(0, 1), (1, 2)]), [(0, 2)]
+ )
+
+ def test_node_u_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(1, 3), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 1)])
+
+ def test_node_v_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(0, 1), (0, 2), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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)
+ assert pytest.raises(nx.NetworkXAlgorithmError, self.test, G, [(0, 0)], [])
+
+ def test_equal_nodes_with_alpha_one_raises_error(self):
+ G = nx.complete_graph(4)
+ assert pytest.raises(
+ nx.NetworkXAlgorithmError, self.test, G, [(0, 0)], [], alpha=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, 1.5), (1, 2, 1.5), (1, 3, 2 / 3)], alpha=0.5)
+
+
+class TestPreferentialAttachment:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.preferential_attachment)
+ cls.test = partial(_test_func, predict_func=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ assert pytest.raises(
+ nx.NetworkXNotImplemented, self.func, graph_type([(0, 1), (1, 2)]), [(0, 2)]
+ )
+
+ def test_node_not_found(self):
+ G = nx.Graph()
+ G.add_edges_from([(0, 1), (0, 2), (2, 3)])
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.cn_soundarajan_hopcroft)
+ cls.test = partial(_test_func, predict_func=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ G = graph_type([(0, 1), (1, 2)])
+ G.add_nodes_from([0, 1, 2], community=0)
+ assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
+
+ def test_node_not_found(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
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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)])
+
+ 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, 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:
+ @classmethod
+ def setup_class(cls):
+ cls.func = staticmethod(nx.ra_index_soundarajan_hopcroft)
+ cls.test = partial(_test_func, predict_func=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ G = graph_type([(0, 1), (1, 2)])
+ G.add_nodes_from([0, 1, 2], community=0)
+ assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
+
+ def test_node_not_found(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
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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)])
+
+ 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, 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:
+ @classmethod
+ def setup_class(cls):
+ cls.delta = 0.001
+ cls.func = staticmethod(nx.within_inter_cluster)
+ cls.test = partial(
+ _test_func, predict_func=cls.func, delta=cls.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)])
+
+ @pytest.mark.parametrize("graph_type", (nx.DiGraph, nx.MultiGraph, nx.MultiDiGraph))
+ def test_notimplemented(self, graph_type):
+ G = graph_type([(0, 1), (1, 2)])
+ G.add_nodes_from([0, 1, 2], community=0)
+ assert pytest.raises(nx.NetworkXNotImplemented, self.func, G, [(0, 2)])
+
+ def test_node_not_found(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
+ assert pytest.raises(nx.NodeNotFound, self.func, G, [(0, 4)])
+
+ 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)])
+
+ 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)])
generated by cgit v1.2.3 (git 2.47.1) at 2025-07-27 07:56:10 +0000