def test_negative_scalar_index(adata, index: int, obs: bool):
    pos_index = index + (adata.n_obs if obs else adata.n_vars)

    if obs:
        adata_pos_subset = adata[pos_index]
        adata_neg_subset = adata[index]
    else:
        adata_pos_subset = adata[:, pos_index]
        adata_neg_subset = adata[:, index]

    np.testing.assert_array_equal(
        adata_pos_subset.obs_names, adata_neg_subset.obs_names
    )
    np.testing.assert_array_equal(
        adata_pos_subset.var_names, adata_neg_subset.var_names
    )
def save(self, *args, **kwargs):
        # Get all other primary domains with the same tenant
        domain_list = self.__class__.objects.filter(tenant=self.tenant, is_primary=True).exclude(pk=self.pk)
        # If we have no primary domain yet, set as primary domain by default
        self.is_primary = self.is_primary or (not domain_list.exists())
        if self.is_primary:
            # Remove primary status of existing domains for tenant
            domain_list.update(is_primary=False)
        super().save(*args, **kwargs)