def _check_univariate_scorer(
        self, anomalies: Union[TimeSeries, Sequence[TimeSeries]]
    ):
        """Checks if `anomalies` contains only univariate series when the scorer has the
        parameter 'is_univariate' set to True.

        'is_univariate' is:
            True -> when the function of the scorer `score(series)` (or, if applicable,
                `score_from_prediction(series, pred_series)`) returns a univariate
                anomaly score regardless of the input `series` (or, if applicable, `series`
                and `pred_series`).
            False -> when the scorer will return a series that has the
                same number of components as the input (can be univariate or multivariate).
        """

        def _check_univariate(s: TimeSeries):
            """Checks if `anomalies` contains only univariate series, which
            is required if any of the scorers returns a univariate score.
            """
            if self.is_univariate and not s.width == 1:
                raise_log(
                    ValueError(
                        f"Scorer {str(self)} will return a univariate anomaly score series (width=1). "
                        f"Found a multivariate `anomalies`. "
                        f"The evaluation of the accuracy cannot be computed between the two series."
                    ),
                    logger=logger,
                )

        _ = _check_input(anomalies, name="anomalies", extra_checks=_check_univariate)
Checks if `anomalies` contains only univariate series when the scorer has the
        parameter 'is_univariate' set to True.

        'is_univariate' is:
            True -> when the function of the scorer `score(series)` (or, if applicable,
                `score_from_prediction(series, pred_series)`) returns a univariate
                anomaly score regardless of the input `series` (or, if applicable, `series`
                and `pred_series`).
            False -> when the scorer will return a series that has the
                same number of components as the input (can be univariate or multivariate).
        
darts/ad/scorers/scorers.py