def METHOD_NAME():
    detector_size = (256, 256)
    pixel_size = (0.0135 * 8, 0.0135 * 8)
    calibrated_center = (256 / 2.0, 256 / 2.0)
    dist_sample = 355.0
    energy = 640  # (  in eV)
    # HC_OVER_E to convert from Energy to wavelength (Lambda)
    hc_over_e = 12398.4
    wavelength = hc_over_e / energy  # (Angstrom )
    ub_mat = np.array(
        [
            [-0.01231028454, 0.7405370482, 0.06323870032],
            [0.4450897473, 0.04166852402, -0.9509449389],
            [-0.7449130975, 0.01265920962, -0.5692399963],
        ]
    )
    setting_angles = np.array([[40.0, 15.0, 30.0, 25.0, 10.0, 5.0], [90.0, 60.0, 0.0, 30.0, 10.0, 5.0]])
    # delta=40, theta=15, chi = 90, phi = 30, mu = 10.0, gamma=5.0
    pdict = {}
    pdict["setting_angles"] = setting_angles
    pdict["detector_size"] = detector_size
    pdict["pixel_size"] = pixel_size
    pdict["calibrated_center"] = calibrated_center
    pdict["dist_sample"] = dist_sample
    pdict["wavelength"] = wavelength
    pdict["ub"] = ub_mat
    # ensure invalid entries for frame_mode actually fail
    # todo test frame_modes 1, 2, and 3
    # test that the values are coming back as expected for frame_mode=4
    hkl = recip.process_to_q(**pdict)
    # Known HKL values for the given six angles)
    # each entry in list is (pixel_number, known hkl value)
    known_hkl = [
        (32896, np.array([-0.15471196, 0.19673939, -0.11440936])),
        (98432, np.array([0.10205953, 0.45624416, -0.27200778])),
    ]
    for pixel, kn_hkl in known_hkl:
        npt.assert_array_almost_equal(hkl[pixel], kn_hkl, decimal=8)
    # smoketest the frame_mode variable
    pass_list = recip.process_to_q.frame_mode
    pass_list.append(None)
    for passes in pass_list:
        recip.process_to_q(frame_mode=passes, **pdict)