check_scorer_coverage_rate_subselection

yohou.testing.scorer.check_scorer_coverage_rate_subselection(scorer, y_truth, y_pred_interval, coverage_rates)

Check coverage parameter filters interval predictions correctly.

Only applicable for interval scorers.

Parameters

Name	Type	Description	Default
scorer	BaseScorer	Interval scorer instance	required
y_truth	DataFrame	Ground truth	required
y_pred_interval	DataFrame	Interval predictions with coverage_rate column	required
coverage_rates	list of float	Coverage rates to filter	required

Raises

Type	Description
AssertionError	If coverage filtering fails

Source Code

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def check_scorer_coverage_rate_subselection(
    scorer,
    y_truth: pl.DataFrame,
    y_pred_interval: pl.DataFrame,
    coverage_rates: list[float],
) -> None:
    """Check coverage parameter filters interval predictions correctly.

    Only applicable for interval scorers.

    Parameters
    ----------
    scorer : BaseScorer
        Interval scorer instance
    y_truth : pl.DataFrame
        Ground truth
    y_pred_interval : pl.DataFrame
        Interval predictions with coverage_rate column
    coverage_rates : list of float
        Coverage rates to filter

    Raises
    ------
    AssertionError
        If coverage filtering fails

    """
    tags = scorer.__sklearn_tags__()
    if tags.scorer_tags.prediction_type != "interval":
        # Skip for non-interval scorers
        return

    scorer_filtered = clone(scorer)
    scorer_filtered.set_params(coverage_rates=coverage_rates)

    # Always fit scorer before scoring
    scorer_filtered.fit(y_truth)

    try:
        score = scorer_filtered.score(y_truth, y_pred_interval)
        assert isinstance(score, int | float | np.number), "Coverage-filtered score should be numeric"
    except Exception as e:
        raise AssertionError(f"coverage_rates={coverage_rates} filtering failed: {e}") from e