def METHOD_NAME():
    with TemporaryDirectory() as out_dir:
        S0 = 100 + 2 * np.random.standard_normal((22, 23, 30, 20))
        data_path = os.path.join(out_dir, "random_noise.nii.gz")
        save_nifti(data_path, S0, np.eye(4))
        mppca_flow = MPPCAFlow()
        mppca_flow.run(data_path, out_dir=out_dir)
        assert_true(os.path.isfile(
                mppca_flow.last_generated_outputs['out_denoised']))
        assert_false(os.path.isfile(
                mppca_flow.last_generated_outputs['out_sigma']))
        mppca_flow._force_overwrite = True
        mppca_flow.run(data_path, return_sigma=True, pca_method='svd',
                       out_dir=out_dir)
        assert_true(os.path.isfile(
                mppca_flow.last_generated_outputs['out_denoised']))
        assert_true(os.path.isfile(
                mppca_flow.last_generated_outputs['out_sigma']))
        denoised_path = mppca_flow.last_generated_outputs['out_denoised']
        denoised_data = load_nifti_data(denoised_path)
        assert_greater(denoised_data.min(), S0.min())
        assert_less(denoised_data.max(), S0.max())
        npt.assert_equal(np.round(denoised_data.mean()), 100)