Notice we add the jacobian of the warping function here.

def log_likelihood(self):
        """
        Notice we add the jacobian of the warping function here.
        """
        ll = GP.log_likelihood(self)
        jacobian = self.warping_function.fgrad_y(self.Y_untransformed)
        return ll + np.log(jacobian).sum()