likang
038d38ed98
- 新增 loft、双向切除、through-all/up-to-next 等 CADFS lowering 与 engine 支持 - 支持多种 reference plane、B-spline profile 和 circular pattern replay - 保留 transform 历史，并烘焙安全的单源平移/旋转变换 - 改进 selector 绑定、拓扑快照和 pattern 变换处理 - 建立 17 个代表样本的转换、重建与比较回归工具链 - 补充 schema、author guidance、运行时和几何回归测试
74 lines
3.6 KiB
Python
74 lines
3.6 KiB
Python
from __future__ import annotations
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import json
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import tempfile
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import unittest
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from pathlib import Path
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from cadfs_to_cdsl.regression import build_regression_manifest, regression_sample_ids
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class RegressionSelectionTests(unittest.TestCase):
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def _sample(
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self,
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root: Path,
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sample_id: str,
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*,
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operation: str,
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entity: str | None = None,
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atomic: str | None = None,
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capability: str | None = None,
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rebuilt: bool = False,
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) -> None:
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directory = root / "samples" / sample_id
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directory.mkdir(parents=True)
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history = [{"operation": operation}]
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if entity:
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history[0]["entities"] = [{"operation": entity}]
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(directory / "history.json").write_text(json.dumps(history), encoding="utf-8")
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if atomic:
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(directory / "candidate.cdsl.json").write_text(json.dumps({"features": [{"atomic_id": atomic}]}), encoding="utf-8")
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diagnostics = [] if not capability else [{"code": "unsupported_engine_capability", "capability": capability}]
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(directory / "diagnostics.json").write_text(json.dumps(diagnostics), encoding="utf-8")
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status = {"status": "rebuilt_approximate" if rebuilt else "converted_partial"}
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if rebuilt:
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status["rebuild_status"] = "rebuilt"
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(directory / "status.json").write_text(json.dumps(status), encoding="utf-8")
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def test_manifest_covers_every_observed_signal_and_keeps_engine_pool_buildable(self) -> None:
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with tempfile.TemporaryDirectory() as temporary:
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output = Path(temporary)
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self._sample(output, "00000001", operation="extrude", entity="skLineSegment", atomic="extrude_add_blind", rebuilt=True)
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self._sample(output, "00000002", operation="loft", entity="skFitSpline", capability="loft")
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self._sample(output, "00000003", operation="revolve", entity="skCircle", atomic="revolve_add", rebuilt=True)
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manifest = build_regression_manifest(output)
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self.assertEqual(manifest["selected_ids"], ["00000001", "00000002", "00000003"])
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self.assertEqual(set(manifest["coverage"]), {
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"engine_atomic:extrude_add_blind", "engine_atomic:revolve_add",
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"sketch_entity:skCircle", "sketch_entity:skFitSpline", "sketch_entity:skLineSegment",
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"source_operation:extrude", "source_operation:loft", "source_operation:revolve",
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"unsupported_capability:loft",
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})
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self.assertEqual(regression_sample_ids_from_manifest(manifest, "engine"), ["00000001", "00000003"])
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self.assertEqual(manifest["engine_baseline_atomic_ids"], ["extrude_add_blind", "revolve_add"])
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self.assertEqual(manifest["engine_diagnostic_only_atomic_ids"], [])
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def test_manifest_reader_rejects_unknown_tier(self) -> None:
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with tempfile.TemporaryDirectory() as temporary:
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root = Path(temporary)
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self._sample(root, "00000001", operation="extrude", atomic="extrude_add_blind", rebuilt=True)
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manifest_path = root / "manifest.json"
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manifest_path.write_text(json.dumps(build_regression_manifest(root)), encoding="utf-8")
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self.assertEqual(regression_sample_ids(manifest_path, "engine"), ["00000001"])
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with self.assertRaisesRegex(ValueError, "Unknown regression tier"):
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regression_sample_ids(manifest_path, "not-a-tier")
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def regression_sample_ids_from_manifest(manifest: dict, tier: str) -> list[str]:
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return sorted(
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entry["sample_id"] for entry in manifest["entries"]
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if tier == "all" or tier in entry["tiers"]
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)
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