def univariate_values(self, copy: bool = True, sample: int = 0) -> np.ndarray:
        """
        Return a 1-D Numpy array of shape (time,),
        containing this univariate series' values for one `sample`.

        Parameters
        ----------
        copy
            Whether to return a copy of the values. Leave it to True unless you know what you are doing.
        sample
            For stochastic series, the sample for which to return values. Default: 0 (first sample).

        Returns
        -------
        numpy.ndarray
            The values composing the time series guaranteed to be univariate.
        """

        self._assert_univariate()
        if copy:
            return np.copy(self._xa[:, 0, sample].values)
        else:
            return self._xa[:, 0, sample].values

        Return a 1-D Numpy array of shape (time,),
        containing this univariate series' values for one `sample`.

        Parameters
        ----------
        copy
            Whether to return a copy of the values. Leave it to True unless you know what you are doing.
        sample
            For stochastic series, the sample for which to return values. Default: 0 (first sample).

        Returns
        -------
        numpy.ndarray
            The values composing the time series guaranteed to be univariate.
        
darts/timeseries.py