Train the model in a Cannon-like fashion using the grid points as labels
        and the intensities as normalised rest-frame fluxes.

def train_global(self, label_vector_description=None, N=None, limits=None,
        pivot=True, **kwargs):
        """
        Train the model in a Cannon-like fashion using the grid points as labels
        and the intensities as normalised rest-frame fluxes.
        """

        lv = self._cannon_label_vector if label_vector_description is None else\
            self._interpret_label_vector(label_vector_description)
        lv_array, grid_indices, offsets = _build_label_vector_array(
            self.grid_points, lv, N, limits, pivot=pivot)
        return self._train(lv_array, grid_indices, offsets, lv, **kwargs)