c7c80b8429ab70ea3b4d17451eac9cd5020e68a8,dipy/align/tests/test_imwarp.py,,test_em_2d_demons,#,929

Before Change

        optimizer.full_energy_profile, 10)
    print(energy_profile)

    if USING_VC_SSE2:
        expected_profile = \
            [2.50773393, 3.26942324, 1.81684393, 5.44878881, 40.0195918,
             31.87030788, 25.15710409, 29.82206485, 196.33114499, 213.86419995]
    elif USING_GCC_SSE2:
        expected_profile = \
            [2.50773393, 3.26942352, 1.8168445, 5.44879264, 40.01956373,
             31.65616398, 32.43115903, 35.24130742, 192.89072697, 195.456909]

    assert_array_almost_equal(energy_profile, np.array(expected_profile),
                              decimal=5)

if __name__=="__main__":

After Change

    version of EM in 2D, and this test checks that the current energy profile
    matches the saved one.
    """
    fname = get_data("t1_coronal_slice")
    nslices = 1
    b = 0.1
    m = 4

    image = np.load(fname)
    moving, static = get_warped_stacked_image(image, nslices, b, m)

    //Configure the metric
    smooth=2.0
    inner_iter=20
    q_levels=256
    double_gradient=False
    iter_type="demons"
    metric = metrics.EMMetric(
        2, smooth, inner_iter, q_levels, double_gradient, iter_type)

    //Configure and run the Optimizer
    level_iters = [40, 20, 10]
    optimizer = imwarp.SymmetricDiffeomorphicRegistration(metric, level_iters)
    optimizer.verbosity = VerbosityLevels.DEBUG
    mapping = optimizer.optimize(static, moving, None)
    m = optimizer.get_map()
    assert_equal(mapping, m)

    warped = mapping.transform(moving)
    starting_energy = np.sum((static - moving)**2)
    final_energy = np.sum((static - warped)**2)
    reduced = 1.0 - final_energy/starting_energy

    assert(reduced > 0.9)

Instances