bjkim1
21ebb16fb7
- SPipe_server_2026-10-30.zip 내용을 풀어서 등록 (압축 파일은 올리지 않음) - README에 데모 v2 서버 업데이트 순서 추가, 저장소에 없는 문서 목차 정리 - 패치내역을 docs/로 이동, _worklog.md 추가 - 임시 파일(backend/temp.*)과 API 키가 든 파일은 제외
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
from __future__ import annotations
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import networkx as nx
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import pytest
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from blocksys.partition import partition
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K_VALUES = [4, 6, 8]
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@pytest.mark.parametrize("k", K_VALUES)
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def test_node_preservation(weighted_graph, cfg, k):
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labels = partition(weighted_graph, k, cfg)
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assert set(labels.keys()) == set(weighted_graph.nodes)
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@pytest.mark.parametrize("k", K_VALUES)
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def test_block_connectivity(weighted_graph, cfg, k):
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labels = partition(weighted_graph, k, cfg)
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blocks: dict[int, list] = {}
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for n, label in labels.items():
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blocks.setdefault(label, []).append(n)
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for label, nodes in blocks.items():
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sub = weighted_graph.subgraph(nodes)
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assert nx.is_connected(sub), f"block {label} is not a single connected component"
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def test_reproducibility(weighted_graph, cfg):
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labels1 = partition(weighted_graph, 6, cfg)
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labels2 = partition(weighted_graph, 6, cfg)
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assert labels1 == labels2
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def test_k_too_large_raises(weighted_graph, cfg):
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with pytest.raises(ValueError):
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partition(weighted_graph, weighted_graph.number_of_nodes() + 1, cfg)
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def test_louvain_method(weighted_graph, cfg):
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cfg.partition.method = "louvain"
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try:
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labels = partition(weighted_graph, 6, cfg)
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assert set(labels.keys()) == set(weighted_graph.nodes)
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finally:
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cfg.partition.method = "spectral"
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