| """Portable paths and provenance safeguards; no scientific computations.""" |
|
|
| from __future__ import annotations |
|
|
| import argparse |
| import hashlib |
| import importlib.metadata |
| import json |
| import platform |
| import sys |
| from pathlib import Path |
|
|
| HERE = Path(__file__).resolve().parent |
| REPOSITORY = HERE.parents[1] |
|
|
|
|
| def add_path_arguments(parser: argparse.ArgumentParser, *, inputs: bool = True) -> None: |
| if inputs: |
| parser.add_argument("--data-dir", type=Path, default=REPOSITORY / "data/raw") |
| parser.add_argument("--features", type=Path, default=REPOSITORY / "data/features/complex_features_ligand_protein_d256_seed0.npy") |
| parser.add_argument("--feature-ids", type=Path, default=REPOSITORY / "data/features/complex_feature_ids.csv", |
| help="Required one-column CSV of producer-verified IDs in feature-row order.") |
| parser.add_argument("--descriptors", type=Path, default=REPOSITORY / "data/descriptors/moad_physical_descriptors_filtered.csv") |
| parser.add_argument("--fold-split", "--fold-file", dest="fold_split", type=Path, default=REPOSITORY / "data/splits/moad_5fold_split_seed42.csv") |
| parser.add_argument("--output-dir", type=Path, default=REPOSITORY / "outputs/acquisition") |
|
|
|
|
| def fingerprint(value: object) -> str: |
| return hashlib.sha256(json.dumps(value, sort_keys=True, separators=(",", ":"), allow_nan=False).encode()).hexdigest() |
|
|
|
|
| def environment_versions() -> dict[str, str]: |
| versions = {"python": platform.python_version(), "platform": platform.platform()} |
| for distribution in ("numpy", "pandas", "scikit-learn"): |
| versions[distribution] = importlib.metadata.version(distribution) |
| return versions |
|
|
|
|
| def previous_checkpoint_size(last_checkpoint: int, checkpoint_targets: dict[int, int]) -> int: |
| """Start the next incremental export after the last COMPLETED checkpoint.""" |
| if last_checkpoint == 0: |
| return 0 |
| if last_checkpoint not in checkpoint_targets: |
| raise ValueError(f"Unknown completed checkpoint: {last_checkpoint}") |
| return checkpoint_targets[last_checkpoint] |
|
|
|
|
| def verify_existing_run(run_root: Path, expected_fingerprint: str, *, resume: bool) -> bool: |
| """Check identity before reading state, skipping completion, or writing outputs. |
| |
| Return True only for a completed run with matching release provenance. |
| Historical outputs without this metadata are deliberately not modified. |
| """ |
| manifest_path = run_root / "run_state/run_manifest.json" |
| if not run_root.exists() or not any(run_root.iterdir()): |
| return False |
| if not resume: |
| raise FileExistsError(f"Output run already exists: {run_root}. Use a fresh --output-dir.") |
| if not manifest_path.exists(): |
| raise RuntimeError(f"Existing run lacks release provenance: {run_root}. Keep historical outputs unchanged and use a fresh --output-dir.") |
| manifest = json.loads(manifest_path.read_text()) |
| if manifest.get("configuration_fingerprint") != expected_fingerprint: |
| raise RuntimeError(f"Inputs, code, environment, or run configuration changed: {run_root}. Use a fresh --output-dir.") |
| marker = run_root / "run_state/complete.json" |
| if not marker.exists(): |
| return False |
| complete = json.loads(marker.read_text()) |
| if complete.get("configuration_fingerprint") != expected_fingerprint or complete.get("checkpoints") != 100: |
| raise RuntimeError(f"Invalid completion marker: {marker}") |
| final_paths = ( |
| "strict_score_matrices/strict_score_100pct.csv", |
| "queried_cells/cumulative/queried_100pct.csv", |
| "queried_cells/newly_queried/queried_100pct.csv", |
| ) |
| if not all((run_root / path).is_file() for path in final_paths): |
| raise RuntimeError(f"Completion marker exists but final exports are missing: {run_root}") |
| return True |
|
|
|
|
| def invocation_arguments(args: argparse.Namespace) -> dict[str, object]: |
| """Record selected jobs; paths and environment variables are not serialized.""" |
| return { |
| "methods": list(args.methods), "folds": list(args.folds), "seeds": list(args.seeds), |
| "smoke_test": bool(getattr(args, "smoke_test", False)), |
| "resume": not bool(getattr(args, "no_resume", False)), |
| } |
|
|
