def METHOD_NAME(self):
    data_dict = self.load_image(FILES[1])
    affine = data_dict["image"].affine
    data_dict["image"].meta["original_affine"] = data_dict["image"].affine = (
        torch.tensor([[0, 0, 1, 0], [0, 1, 0, 0], [-1, 0, 0, 0], [0, 0, 0, 1]], dtype=torch.float64) @ affine
    )
    t = Compose(
        [
            Spacingd(keys="image", pixdim=(1, 2, 3), diagonal=False, padding_mode="border"),
            Orientationd(keys="image", axcodes="LPI"),
        ]
    )
    res_dict = t(data_dict)
    np.testing.assert_allclose(
        res_dict["image"].affine,
        np.array(
            [
                [-3.0, 0.0, 0.0, 56.4005909],
                [0.0, -2.0, 0.0, 52.02241516],
                [0.0, 0.0, -1.0, 35.29789734],
                [0.0, 0.0, 0.0, 1.0],
            ]
        ),
    )