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
97 lines
6.2 KiB
Python
97 lines
6.2 KiB
Python
from __future__ import annotations
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import argparse, json
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from pathlib import Path
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from .describe import describe_samples
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from .pipeline import load_samples, run_stage, scan, select_samples
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from .regression import regression_sample_ids, summarize_regression, write_regression_manifest
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from .reports import generate_markdown_report, generate_reports, read_json
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DEFAULT_INPUT = Path("data/cadfs-sample/CADFS_test")
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DEFAULT_OUTPUT = Path("cadfs_to_cdsl/output")
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def _parser() -> argparse.ArgumentParser:
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parser = argparse.ArgumentParser(description="Convert CADFS FeatureScript to CDSL and validate against STEP")
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commands = parser.add_subparsers(dest="command", required=True)
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for name in ("scan", "convert", "rebuild", "compare", "report", "pipeline", "describe", "regression-select", "regression"):
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command = commands.add_parser(name)
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command.add_argument("--input", type=Path, default=DEFAULT_INPUT)
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command.add_argument("--output", type=Path, default=DEFAULT_OUTPUT)
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if name == "regression-select":
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command.add_argument("--manifest", type=Path, default=Path("cadfs_to_cdsl/regression/manifest.json"))
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elif name == "regression":
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command.add_argument("--manifest", type=Path, default=Path("cadfs_to_cdsl/regression/manifest.json"))
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command.add_argument("--tier", choices=("engine", "conversion", "all"), default="engine")
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command.add_argument("--stage", choices=("convert", "rebuild", "compare", "pipeline"), default="rebuild")
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command.add_argument("--workers", type=int, default=1)
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command.add_argument("--compare-mode", choices=("rp", "strict"), default="rp")
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command.add_argument("--timeout-seconds", type=float, default=30.0, help="per-model OCC timeout (default: 30)")
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command.add_argument("--resume", action="store_true", help="reuse cached per-sample stage results instead of rerunning them")
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elif name == "describe":
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command.add_argument("--shard", help="input shard directory to describe, for example 0005")
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command.add_argument("--sample-id", action="append")
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command.add_argument("--offset", type=int, default=0)
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command.add_argument("--limit", type=int)
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command.add_argument("--seed", type=int)
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command.add_argument("--workers", type=int, default=1)
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command.add_argument("--mode", choices=("local", "hybrid", "vision"), default="hybrid")
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command.add_argument("--force", action="store_true")
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elif name != "scan":
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command.add_argument("--sample-id", action="append")
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command.add_argument("--offset", type=int, default=0)
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command.add_argument("--limit", type=int)
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command.add_argument("--seed", type=int)
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command.add_argument("--workers", type=int, default=1)
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command.add_argument("--compare-mode", choices=("rp", "strict"), default="rp")
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command.add_argument("--force", action="store_true")
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command.add_argument("--timeout-seconds", type=float, default=30.0, help="per-model OCC timeout (default: 30)")
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if name == "report":
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command.add_argument("--markdown", action="store_true", help="also write full_run_report.md")
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return parser
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def main(argv: list[str] | None = None) -> int:
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args = _parser().parse_args(argv)
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if args.command != "describe":
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args.output.mkdir(parents=True, exist_ok=True)
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if args.command == "scan":
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records = scan(args.input, args.output); result = {"sample_count": len(records), "output": str(args.output / "dataset_index.json")}
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elif args.command == "regression-select":
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manifest = write_regression_manifest(args.output, args.manifest)
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result = {"manifest": str(args.manifest), "selected_sample_count": manifest["selected_sample_count"], "engine_sample_count": manifest["engine_sample_count"]}
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elif args.command == "regression":
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if not 1 <= args.workers <= 8: raise ValueError("--workers must be between 1 and 8")
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if args.timeout_seconds <= 0: raise ValueError("--timeout-seconds must be positive")
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sample_ids = regression_sample_ids(args.manifest, args.tier)
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samples = select_samples(load_samples(args.input, args.output), sample_ids=sample_ids)
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records = run_stage(args.stage, samples, args.output, force=not args.resume, compare_mode=args.compare_mode, timeout_seconds=args.timeout_seconds, workers=args.workers)
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result = {"tier": args.tier, "stage": args.stage, "manifest": str(args.manifest), **summarize_regression(records)}
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elif args.command == "describe":
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records, result = describe_samples(
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args.input,
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shard=args.shard,
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sample_ids=args.sample_id,
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mode=args.mode,
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offset=args.offset,
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limit=args.limit,
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seed=args.seed,
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force=args.force,
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workers=args.workers,
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)
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elif args.command == "report":
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manifest = args.output / "manifest.jsonl"; records = [json.loads(line) for line in manifest.read_text().splitlines() if line.strip()]
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result = generate_reports(args.output, records)
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if args.markdown:
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command_text = "python -m cadfs_to_cdsl report --markdown"
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result = {**result, "markdown_report": str(generate_markdown_report(args.output, records, input_root=args.input, command=command_text))}
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else:
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if not 1 <= args.workers <= 8: raise ValueError("--workers must be between 1 and 8")
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samples = select_samples(load_samples(args.input, args.output), sample_ids=args.sample_id, offset=args.offset, limit=args.limit, seed=args.seed)
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if args.timeout_seconds <= 0: raise ValueError("--timeout-seconds must be positive")
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records = run_stage(args.command, samples, args.output, force=args.force, compare_mode=args.compare_mode, timeout_seconds=args.timeout_seconds, workers=args.workers)
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counts: dict[str, int] = {}
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for record in records: counts[record["status"]] = counts.get(record["status"], 0) + 1
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result = {"sample_count": len(records), "statuses": counts, "summary": str(args.output / "summary.json")}
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print(json.dumps(result, ensure_ascii=True, indent=2, sort_keys=True)); return 0
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