def show_anomalies(
        self,
        series: TimeSeries,
        anomalies: TimeSeries = None,
        scorer_name: str = None,
        title: str = None,
        metric: Optional[Literal["AUC_ROC", "AUC_PR"]] = None,
        component_wise: bool = False,
    ):
        """Plot the results of the scorer.

        Computes the score on the given series input. And plots the results.

        The plot will be composed of the following:
            - the series itself.
            - the anomaly score of the score.
            - the actual anomalies, if given.

        It is possible to:
            - add a title to the figure with the parameter `title`
            - give personalized name to the scorer with `scorer_name`
            - show the results of a metric for the anomaly score (AUC_ROC or AUC_PR),
            if the actual anomalies is provided.

        Parameters
        ----------
        series
            The series to visualize anomalies from.
        anomalies
            The (sequence of) ground truth binary anomaly series (`1` if it is an anomaly and `0` if not).
        scorer_name
            Name of the scorer.
        title
            Title of the figure
        metric
            Optionally, the name of the metric function to use. Must be one of "AUC_ROC" (Area Under the
            Receiver Operating Characteristic Curve) and "AUC_PR" (Average Precision from scores).
            Default: "AUC_ROC".
        component_wise
            If True, will separately plot each component in case of multivariate anomaly detection.
        """
        series = _check_input(series, name="series", num_series_expected=1)[0]
        pred_scores = self.score(series)

        if title is None:
            title = f"Anomaly results by scorer {str(self)}"

        if scorer_name is None:
            scorer_name = f"anomaly score by {str(self)}"

        if self.window_agg:
            window = 1
        else:
            window = self.window

        return show_anomalies_from_scores(
            series=series,
            anomalies=anomalies,
            pred_scores=pred_scores,
            window=window,
            names_of_scorers=scorer_name,
            title=title,
            metric=metric,
            component_wise=component_wise,
        )
Plot the results of the scorer.

        Computes the score on the given series input. And plots the results.

        The plot will be composed of the following:
            - the series itself.
            - the anomaly score of the score.
            - the actual anomalies, if given.

        It is possible to:
            - add a title to the figure with the parameter `title`
            - give personalized name to the scorer with `scorer_name`
            - show the results of a metric for the anomaly score (AUC_ROC or AUC_PR),
            if the actual anomalies is provided.

        Parameters
        ----------
        series
            The series to visualize anomalies from.
        anomalies
            The (sequence of) ground truth binary anomaly series (`1` if it is an anomaly and `0` if not).
        scorer_name
            Name of the scorer.
        title
            Title of the figure
        metric
            Optionally, the name of the metric function to use. Must be one of "AUC_ROC" (Area Under the
            Receiver Operating Characteristic Curve) and "AUC_PR" (Average Precision from scores).
            Default: "AUC_ROC".
        component_wise
            If True, will separately plot each component in case of multivariate anomaly detection.
        
darts/ad/scorers/scorers.py