def fit(
        self,
        y: np.ndarray,
        X: Optional[np.ndarray] = None,
    ):
        r"""Fit the SeasonalExponentialSmoothing model.

        Fit an SeasonalExponentialSmoothing to a time series (numpy array) `y`
        and optionally exogenous variables (numpy array) `X`.

        Parameters
        ----------
        y : numpy.array
            Clean time series of shape (t, ).
        X : array-like
            Optional exogenous of shape (t, n_x).

        Returns
        -------
        self :
            SeasonalExponentialSmoothing fitted model.
        """
        y = _ensure_float(y)
        mod = _seasonal_exponential_smoothing(
            y=y,
            season_length=self.season_length,
            alpha=self.alpha,
            fitted=True,
            h=self.season_length,
        )
        self.model_ = dict(mod)
        self._store_cs(y=y, X=X)
        return self
Fit the SeasonalExponentialSmoothing model.

        Fit an SeasonalExponentialSmoothing to a time series (numpy array) `y`
        and optionally exogenous variables (numpy array) `X`.

        Parameters
        ----------
        y : numpy.array
            Clean time series of shape (t, ).
        X : array-like
            Optional exogenous of shape (t, n_x).

        Returns
        -------
        self :
            SeasonalExponentialSmoothing fitted model.
        
python/statsforecast/models.py