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chore: import upstream snapshot with attribution
2026-07-13 12:37:31 +08:00

67 lines
2.2 KiB
Python

# Copyright (c) 2024 Microsoft Corporation.
# Licensed under the MIT License
"""NetworkX-based stable LCC utility, kept for side-by-side test comparisons.
This was originally at graphrag.index.utils.stable_lcc and has been moved here
because production code no longer uses it (superseded by the DataFrame-based
graphrag.graphs.stable_lcc).
"""
import html
from typing import Any, cast
import networkx as nx
def _largest_connected_component(graph: nx.Graph) -> nx.Graph:
"""Return the largest connected component of the graph (NX-based)."""
graph = graph.copy()
lcc_nodes = max(nx.connected_components(graph), key=len)
return graph.subgraph(lcc_nodes).copy()
def stable_largest_connected_component(graph: nx.Graph) -> nx.Graph:
"""Return the largest connected component of the graph, with nodes and edges sorted in a stable way."""
graph = graph.copy()
graph = cast("nx.Graph", _largest_connected_component(graph))
graph = normalize_node_names(graph)
return _stabilize_graph(graph)
def _stabilize_graph(graph: nx.Graph) -> nx.Graph:
"""Ensure an undirected graph with the same relationships will always be read the same way."""
fixed_graph = nx.DiGraph() if graph.is_directed() else nx.Graph()
sorted_nodes = graph.nodes(data=True)
sorted_nodes = sorted(sorted_nodes, key=lambda x: x[0])
fixed_graph.add_nodes_from(sorted_nodes)
edges = list(graph.edges(data=True))
if not graph.is_directed():
def _sort_source_target(edge):
source, target, edge_data = edge
if source > target:
temp = source
source = target
target = temp
return source, target, edge_data
edges = [_sort_source_target(edge) for edge in edges]
def _get_edge_key(source: Any, target: Any) -> str:
return f"{source} -> {target}"
edges = sorted(edges, key=lambda x: _get_edge_key(x[0], x[1]))
fixed_graph.add_edges_from(edges)
return fixed_graph
def normalize_node_names(graph: nx.Graph | nx.DiGraph) -> nx.Graph | nx.DiGraph:
"""Normalize node names."""
node_mapping = {node: html.unescape(node.upper().strip()) for node in graph.nodes()} # type: ignore
return nx.relabel_nodes(graph, node_mapping)