code: def predict(self, t, period=None):
          
          t = np.asarray(t)
          if period is None:
              period = self.best_period
          result = self._predict(t.ravel(), period=period)
          return result.reshape(t.shape)
docs: 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