| import sys |
| import pandas as pd |
| from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, confusion_matrix |
|
|
|
|
| def resolve_label(df: pd.DataFrame) -> pd.Series: |
| label_cols = [c for c in df.columns if c.startswith("label_")] |
| if len(label_cols) == 1: |
| return df[label_cols[0]] |
| raise ValueError(f"Expected one label column, found: {label_cols}") |
|
|
|
|
| def align_frames(preds: pd.DataFrame, truth: pd.DataFrame) -> tuple[pd.DataFrame, pd.DataFrame]: |
| if len(preds) != len(truth): |
| raise ValueError( |
| f"Row count mismatch: predictions has {len(preds)} rows, truth has {len(truth)} rows" |
| ) |
|
|
| if "scenario_id" in preds.columns and "scenario_id" in truth.columns: |
| preds = preds.sort_values("scenario_id").reset_index(drop=True) |
| truth = truth.sort_values("scenario_id").reset_index(drop=True) |
|
|
| if not preds["scenario_id"].equals(truth["scenario_id"]): |
| raise ValueError("scenario_id mismatch after alignment between predictions and truth") |
|
|
| return preds, truth |
|
|
|
|
| def score(predictions_path: str, ground_truth_path: str) -> dict: |
| preds = pd.read_csv(predictions_path) |
| truth = pd.read_csv(ground_truth_path) |
|
|
| preds, truth = align_frames(preds, truth) |
|
|
| y_pred = resolve_label(preds) |
| y_true = resolve_label(truth) |
|
|
| accuracy = accuracy_score(y_true, y_pred) |
| precision = precision_score(y_true, y_pred, zero_division=0) |
| recall = recall_score(y_true, y_pred, zero_division=0) |
| f1 = f1_score(y_true, y_pred, zero_division=0) |
|
|
| tn, fp, fn, tp = confusion_matrix(y_true, y_pred, labels=[0, 1]).ravel() |
|
|
| false_safe_rate = fn / (fn + tp) if (fn + tp) > 0 else 0.0 |
|
|
| return { |
| "accuracy": accuracy, |
| "precision": precision, |
| "recall_cascade_detection": recall, |
| "false_safe_rate": false_safe_rate, |
| "f1": f1, |
| "confusion_matrix": { |
| "tp": int(tp), |
| "fp": int(fp), |
| "tn": int(tn), |
| "fn": int(fn), |
| }, |
| } |
|
|
|
|
| if __name__ == "__main__": |
| if len(sys.argv) != 3: |
| raise SystemExit("Usage: python scorer.py <predictions.csv> <ground_truth.csv>") |
| print(score(sys.argv[1], sys.argv[2])) |
