File size: 6,862 Bytes
04bd3b9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 | #!/usr/bin/env python3
"""Run the CPU-only Source Atlas transfer gate without test evaluation."""
from __future__ import annotations
import argparse
import importlib.metadata
import json
import time
from pathlib import Path
from typing import Any
from mitointeract_recovery.chimera import read_manifest
from mitointeract_recovery.source_atlas import sha256_file
from mitointeract_recovery.source_atlas_gate import (
atlas_input_hashes,
build_entity_features,
read_cluster_assignments,
read_jsonl,
run_source_atlas_gate,
)
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser()
parser.add_argument("--atlas-dir", type=Path, required=True)
parser.add_argument("--clusters", type=Path, required=True)
parser.add_argument("--sample", type=Path, required=True)
parser.add_argument("--manifest", type=Path, required=True)
parser.add_argument("--output-dir", type=Path, required=True)
parser.add_argument("--alpha", type=float, default=100.0)
parser.add_argument("--outer-splits", type=int, default=5)
parser.add_argument("--bootstrap-iterations", type=int, default=2000)
parser.add_argument("--seed", type=int, default=42)
parser.add_argument("--minimum-rmse-improvement", type=float, default=0.05)
parser.add_argument("--catastrophic-fold-tolerance", type=float, default=0.10)
return parser.parse_args()
def write_jsonl(path: Path, rows: list[dict[str, Any]]) -> None:
with path.open("w") as handle:
for row in rows:
handle.write(json.dumps(row, sort_keys=True) + "\n")
def main() -> None:
args = parse_args()
if args.output_dir.exists() and any(args.output_dir.iterdir()):
raise FileExistsError(f"output directory is not empty: {args.output_dir}")
for path in (
args.atlas_dir / "records.jsonl",
args.atlas_dir / "proteins.jsonl",
args.atlas_dir / "ligands.jsonl",
args.clusters,
args.sample,
args.manifest,
):
if not path.is_file():
raise FileNotFoundError(path)
args.output_dir.mkdir(parents=True, exist_ok=True)
started = time.monotonic()
atlas_records = read_jsonl(args.atlas_dir / "records.jsonl")
proteins = read_jsonl(args.atlas_dir / "proteins.jsonl")
ligands = read_jsonl(args.atlas_dir / "ligands.jsonl")
primary_rows = read_jsonl(args.sample)
manifest = read_manifest(args.manifest)
if set(manifest) != {row["pair_id"] for row in primary_rows}:
raise ValueError("primary manifest pair set must exactly match the sample")
clusters = read_cluster_assignments(args.clusters)
protein_vectors, ligand_vectors = build_entity_features(proteins, ligands)
result = run_source_atlas_gate(
atlas_records=atlas_records,
primary_rows=primary_rows,
primary_manifest=manifest,
cluster_assignments=clusters,
protein_vectors=protein_vectors,
ligand_vectors=ligand_vectors,
alpha=args.alpha,
outer_splits=args.outer_splits,
bootstrap_iterations=args.bootstrap_iterations,
seed=args.seed,
minimum_rmse_improvement=args.minimum_rmse_improvement,
catastrophic_fold_tolerance=args.catastrophic_fold_tolerance,
)
prediction_data = result.pop("predictions")
prediction_rows = []
for index, row in enumerate(prediction_data["rows"]):
prediction_rows.append(
{
"observation_id": row["observation_id"],
"pair_id": row["pair_id"],
"protein_id": row["protein_id"],
"cluster_id": str(prediction_data["groups"][index]),
"source_partition": manifest[row["pair_id"]],
"target_pkd": float(prediction_data["targets"][index]),
"outer_fold": int(prediction_data["fold_assignments"][index]),
"kd_only_prediction": float(prediction_data["kd_only"][index]),
"multitask_prediction": float(prediction_data["multitask"][index]),
}
)
predictions_path = args.output_dir / "development-predictions.jsonl"
write_jsonl(predictions_path, prediction_rows)
report = {
"status": "development_only_no_test_evaluation",
"decision": (
"advance_to_neural_pretraining"
if result["gate"]["passed"]
else "reject_neural_pretraining_not_justified"
),
"protocol": {
"description": (
"fixed-alpha task-balanced shared-plus-task-specific Ridge transfer gate"
),
"tasks": ["Kd", "Ki", "IC50", "EC50"],
"features": {
"protein": "log length plus 20 amino-acid fractions",
"ligand": "512-bit radius-2 Morgan fingerprint plus eight descriptors",
"architecture": "shared feature block plus one task-specific feature block",
},
"alpha": args.alpha,
"outer_splits": args.outer_splits,
"grouping": "joint MMseqs2 identity 0.5 coverage 0.8 clusters",
"test_cluster_policy": (
"all Atlas and primary development rows in clusters containing any "
"benchmark test protein are excluded"
),
"test_evaluations": 0,
"seed": args.seed,
},
**result,
"inputs": atlas_input_hashes(args.atlas_dir, args.clusters, args.sample, args.manifest),
"packages": {
package: importlib.metadata.version(package)
for package in ("numpy", "rdkit", "scikit-learn", "scipy")
},
"artifacts": {
"predictions": predictions_path.name,
"predictions_sha256": sha256_file(predictions_path),
},
"elapsed_seconds": time.monotonic() - started,
}
report_path = args.output_dir / "report.json"
report_path.write_text(json.dumps(report, indent=2, sort_keys=True) + "\n")
print(
json.dumps(
{
"decision": report["decision"],
"development_rows": report["development_rows"],
"safe_atlas_records": report["safe_atlas_records"],
"kd_only_rmse": report["kd_only"]["metrics"]["rmse"],
"multitask_rmse": report["multitask"]["metrics"]["rmse"],
"rmse_improvement": report["gate"]["actual_rmse_improvement"],
"bootstrap_ci": [
report["bootstrap"]["ci_2_5"],
report["bootstrap"]["ci_97_5"],
],
"gate_passed": report["gate"]["passed"],
"test_evaluations": report["test_evaluations"],
"elapsed_seconds": report["elapsed_seconds"],
},
sort_keys=True,
)
)
if __name__ == "__main__":
main()
|