modified: .DS_Store

modified: checkpoints_final/task1_final/task1_final_model.pkl new file: checkpoints_final/task1_final/task1_tmd_adapter.pkl new file: scripts_4/README.md new file: scripts_4/__init__.py new file: scripts_4/__pycache__/adapter.cpython-314.pyc new file: scripts_4/adapter.py new file: scripts_4/predict_tmd_single.py new file: scripts_4/train_tmd_adapter.py
2026-05-06 20:57:43 +08:00
parent f3766c74d6
commit 79f3de05f7
9 changed files with 390 additions and 0 deletions
--- a/scripts_4/predict_tmd_single.py
+++ b/scripts_4/predict_tmd_single.py
@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+import argparse
+import importlib.util
+import pickle
+from pathlib import Path
+import sys
+
+PROJECT_ROOT = Path(__file__).resolve().parents[1]
+
+try:
+    from .adapter import load_adapter
+except ImportError:
+    from adapter import load_adapter
+
+
+def _load_module(module_name: str, file_path: Path):
+    spec = importlib.util.spec_from_file_location(module_name, file_path)
+    if spec is None or spec.loader is None:
+        raise ImportError(f"Cannot load module from {file_path}")
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[module_name] = module
+    spec.loader.exec_module(module)
+    return module
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Predict TMD RMS using baseline model + frequency adapter.")
+    parser.add_argument("--file", type=str, required=True)
+    parser.add_argument("--checkpoint", type=str, default="checkpoints_final/task1_final/task1_final_model.pkl")
+    parser.add_argument("--adapter", type=str, default="checkpoints_final/task1_final/task1_tmd_adapter.pkl")
+    parser.add_argument("--data-dir", type=str, default="downloads/TMD")
+    return parser.parse_args()
+
+
+def main() -> None:
+    args = parse_args()
+    config_module = _load_module("config", PROJECT_ROOT / "scripts" / "config.py")
+    dataset_module = _load_module("task1_dataset", PROJECT_ROOT / "scripts" / "dataset.py")
+    make_experiment_config = getattr(config_module, "make_experiment_config")
+    build_record_from_file = getattr(dataset_module, "build_record_from_file")
+
+    config = make_experiment_config()
+    config.data.data_dir = args.data_dir
+    config.data.__post_init__()
+
+    ckpt_path = (PROJECT_ROOT / args.checkpoint).resolve()
+    adapter_path = (PROJECT_ROOT / args.adapter).resolve()
+    with ckpt_path.open("rb") as handle:
+        payload = pickle.load(handle)
+    model = payload["model"]
+    adapter, extra = load_adapter(adapter_path)
+
+    file_path = Path(args.file).resolve()
+    record = build_record_from_file(file_path, config.data)
+
+    pred_tr = max(float(model.predict([record.features.tolist()])[0]), config.data.normalization_eps)
+    pred_base = pred_tr * record.x_rms
+    pred_tmd = adapter.predict(pred_base, record.frequency_hz)
+
+    true_rms = float(record.y_rms)
+    base_err = abs(pred_base - true_rms) / max(abs(true_rms), 1e-12) * 100.0
+    tmd_err = abs(pred_tmd - true_rms) / max(abs(true_rms), 1e-12) * 100.0
+
+    print(f"Checkpoint: {ckpt_path}")
+    print(f"Adapter: {adapter_path}")
+    print(f"Adapter extra: {extra}")
+    print(f"Input file: {file_path}")
+    print(f"Frequency (Hz): {record.frequency_hz:.6f}")
+    print(f"x_rms: {record.x_rms:.6f}")
+    print(f"True y_rms: {true_rms:.6f}")
+    print(f"Base pred y_rms: {pred_base:.6f} | error={base_err:.4f}%")
+    print(f"Adapted pred y_rms: {pred_tmd:.6f} | error={tmd_err:.4f}%")
+    print(f"Applied scale k(f): {adapter.scale_at(record.frequency_hz):.6f}")
+
+
+if __name__ == "__main__":
+    main()