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* Use graspologic-native hierarchical leiden * Re-implement largest_connected_component * Copy in modularity * Use graspologic-native directly in pyproject * Remove directed graph tests (we don't use this) * Semver * Remove graspologic dep
46 lines
1.7 KiB
Python
46 lines
1.7 KiB
Python
# Copyright (c) 2024 Microsoft Corporation.
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# Licensed under the MIT License
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import unittest
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import networkx as nx
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from graphrag.index.utils.stable_lcc import stable_largest_connected_component
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class TestStableLCC(unittest.TestCase):
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def test_undirected_graph_run_twice_produces_same_graph(self):
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graph_in_1 = self._create_strongly_connected_graph()
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graph_out_1 = stable_largest_connected_component(graph_in_1)
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graph_in_2 = self._create_strongly_connected_graph_with_edges_flipped()
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graph_out_2 = stable_largest_connected_component(graph_in_2)
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# Make sure they're the same
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assert "".join(nx.generate_graphml(graph_out_1)) == "".join(
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nx.generate_graphml(graph_out_2)
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)
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def _create_strongly_connected_graph(self, digraph=False):
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graph = nx.Graph() if not digraph else nx.DiGraph()
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graph.add_node("1", node_name=1)
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graph.add_node("2", node_name=2)
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graph.add_node("3", node_name=3)
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graph.add_node("4", node_name=4)
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graph.add_edge("4", "5", degree=4)
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graph.add_edge("3", "4", degree=3)
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graph.add_edge("2", "3", degree=2)
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graph.add_edge("1", "2", degree=1)
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return graph
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def _create_strongly_connected_graph_with_edges_flipped(self, digraph=False):
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graph = nx.Graph() if not digraph else nx.DiGraph()
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graph.add_node("1", node_name=1)
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graph.add_node("2", node_name=2)
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graph.add_node("3", node_name=3)
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graph.add_node("4", node_name=4)
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graph.add_edge("5", "4", degree=4)
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graph.add_edge("4", "3", degree=3)
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graph.add_edge("3", "2", degree=2)
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graph.add_edge("2", "1", degree=1)
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return graph
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