def predict(self, t, period=None):
        """Compute the best-fit model at ``t`` for a given period

        Parameters
        ----------
        t : float or array_like
            times at which to predict
        period : float (optional)
            The period at which to compute the model. If not specified, it
            will be computed via the optimizer provided at initialization.

        Returns
        -------
        y : np.ndarray
            predicted model values at times t
        """
        t = np.asarray(t)
        if period is None:
            period = self.best_period
        result = self._predict(t.ravel(), period=period)
        return result.reshape(t.shape)
Compute the best-fit model at ``t`` for a given period

        Parameters
        ----------
        t : float or array_like
            times at which to predict
        period : float (optional)
            The period at which to compute the model. If not specified, it
            will be computed via the optimizer provided at initialization.

        Returns
        -------
        y : np.ndarray
            predicted model values at times t