def split_after(
        self, split_point: Union[pd.Timestamp, float, int]
    ) -> tuple[Self, Self]:
        """
        Splits the series in two, after a provided `split_point`.

        Parameters
        ----------
        split_point
            A timestamp, float or integer. If float, represents the proportion of the series to include in the
            first TimeSeries (must be between 0.0 and 1.0). If integer, represents the index position after
            which the split is performed. A pd.Timestamp can be provided for TimeSeries that are indexed by a
            pd.DatetimeIndex. In such cases, the timestamp will be contained in the first TimeSeries, but not
            in the second one. The timestamp itself does not have to appear in the original TimeSeries index.

        Returns
        -------
        Tuple[TimeSeries, TimeSeries]
            A tuple of two time series. The first time series contains the first samples up to the `split_point`,
            and the second contains the remaining ones.
        """
        return self._split_at(split_point, after=True)

        Splits the series in two, after a provided `split_point`.

        Parameters
        ----------
        split_point
            A timestamp, float or integer. If float, represents the proportion of the series to include in the
            first TimeSeries (must be between 0.0 and 1.0). If integer, represents the index position after
            which the split is performed. A pd.Timestamp can be provided for TimeSeries that are indexed by a
            pd.DatetimeIndex. In such cases, the timestamp will be contained in the first TimeSeries, but not
            in the second one. The timestamp itself does not have to appear in the original TimeSeries index.

        Returns
        -------
        Tuple[TimeSeries, TimeSeries]
            A tuple of two time series. The first time series contains the first samples up to the `split_point`,
            and the second contains the remaining ones.
        
darts/timeseries.py