Compressor/models/vibration/evaluate_model.py

#!/usr/bin/env python3
"""Evaluate the fixed vibration model against the sealed test directory."""
from __future__ import annotations

import argparse
import json
import sys
from pathlib import Path

sys.path.insert(0, str(Path(__file__).resolve().parents[2]))

from models.common import modeling, paths
from models.vibration import features_vibration


def main() -> None:
    parser = argparse.ArgumentParser(description="仅对封存振动测试集做最终模型评估")
    parser.add_argument("--datasets-dir", default=str(paths.VIBRATION_DATAS))
    parser.add_argument("--models-dir", default=str(paths.VIBRATION_MODELS))
    parser.add_argument("--output-dir", default=str(paths.VIBRATION_RESULTS))
    args = parser.parse_args()
    report = modeling.evaluate("vibration", features_vibration, Path(args.datasets_dir), Path(args.models_dir), Path(args.output_dir))
    summary = report["window_metrics"]
    print(f"测试集：{summary['samples']} 窗口（正常 {summary['normal_samples']}、异常 {summary['anomaly_samples']}），阈值 {report['threshold']:.6f}")
    print(f"{'类别':<6}{'查准率':>10}{'召回率':>10}{'F1':>10}{'样本数':>10}")
    for name, label in (("正常", "normal"), ("异常", "anomaly")):
        item = summary["class_metrics"][label]
        print(f"{name:<6}{item['precision']:>10.4f}{item['recall']:>10.4f}{item['f1']:>10.4f}{item['support']:>10}")
    print(
        f"准确率 {summary['accuracy']:.4f}  平衡准确率 {summary['balanced_accuracy']:.4f}  "
        f"macro-F1 {summary['macro_f1']:.4f}  加权F1 {summary['weighted_f1']:.4f}  "
        f"特异度 {summary['specificity']:.4f}  PR-AUC {summary['pr_auc']:.4f}"
    )
    print(json.dumps(report, ensure_ascii=False, indent=2))


if __name__ == "__main__":
    main()