示例#1
0
def test_mapmri_odf(radial_order=6):
    gtab = get_gtab_taiwan_dsi()

    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    l1, l2, l3 = [0.0015, 0.0003, 0.0003]
    data, golden_directions = generate_signal_crossing(gtab,
                                                       l1,
                                                       l2,
                                                       l3,
                                                       angle2=90)
    mapmod = MapmriModel(gtab,
                         radial_order=radial_order,
                         laplacian_regularization=True,
                         laplacian_weighting=0.01)
    # symmetric724
    sphere2 = create_unit_sphere(5)
    mapfit = mapmod.fit(data)
    odf = mapfit.odf(sphere)

    directions, _, _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    # 5 subdivisions
    odf = mapfit.odf(sphere2)
    directions, _, _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        asmfit = mapmod.fit(data)
        odf = asmfit.odf(sphere2)
        directions, _, _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)

    # for the isotropic implementation check if the odf spherical harmonics
    # actually represent the discrete sphere function.
    mapmod = MapmriModel(gtab,
                         radial_order=radial_order,
                         laplacian_regularization=True,
                         laplacian_weighting=0.01,
                         anisotropic_scaling=False)
    mapfit = mapmod.fit(data)
    odf = mapfit.odf(sphere)
    odf_sh = mapfit.odf_sh()
    odf_from_sh = sh_to_sf(odf_sh, sphere, radial_order, basis_type=None)
    assert_almost_equal(odf, odf_from_sh, 10)
示例#2
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def test_mapmri_odf(radial_order=6):
    gtab = get_gtab_taiwan_dsi()

    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    l1, l2, l3 = [0.0015, 0.0003, 0.0003]
    data, golden_directions = generate_signal_crossing(gtab, l1, l2, l3,
                                                       angle2=90)
    mapmod = MapmriModel(gtab, radial_order=radial_order,
                         laplacian_regularization=True,
                         laplacian_weighting=0.01)
    # symmetric724
    sphere2 = create_unit_sphere(5)
    mapfit = mapmod.fit(data)
    odf = mapfit.odf(sphere)

    directions, _, _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    # 5 subdivisions
    odf = mapfit.odf(sphere2)
    directions, _, _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        asmfit = mapmod.fit(data)
        odf = asmfit.odf(sphere2)
        directions, _, _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)

    # for the isotropic implementation check if the odf spherical harmonics
    # actually represent the discrete sphere function.
    mapmod = MapmriModel(gtab, radial_order=radial_order,
                         laplacian_regularization=True,
                         laplacian_weighting=0.01,
                         anisotropic_scaling=False)
    mapfit = mapmod.fit(data)
    odf = mapfit.odf(sphere)
    odf_sh = mapfit.odf_sh()
    odf_from_sh = sh_to_sf(odf_sh, sphere, radial_order, basis_type=None)
    assert_almost_equal(odf, odf_from_sh, 10)
示例#3
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def test_shore_odf():
    gtab = get_isbi2013_2shell_gtab()

    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    sphere2 = create_unit_sphere(5)
    data, golden_directions = SticksAndBall(gtab,
                                            d=0.0015,
                                            S0=100,
                                            angles=[(0, 0), (90, 0)],
                                            fractions=[50, 50],
                                            snr=None)
    asm = ShoreModel(gtab,
                     radial_order=6,
                     zeta=700,
                     lambdaN=1e-8,
                     lambdaL=1e-8)
    # symmetric724
    asmfit = asm.fit(data)
    odf = asmfit.odf(sphere)
    odf_sh = asmfit.odf_sh()
    odf_from_sh = sh_to_sf(odf_sh, sphere, 6, basis_type=None)
    assert_almost_equal(odf, odf_from_sh, 10)

    directions, _, _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    # 5 subdivisions
    odf = asmfit.odf(sphere2)
    directions, _, _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        asmfit = asm.fit(data)
        odf = asmfit.odf(sphere2)
        directions, _, _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)
示例#4
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def test_shore_odf():
    gtab = get_isbi2013_2shell_gtab()

    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    sphere2 = create_unit_sphere(5)
    data, golden_directions = SticksAndBall(gtab, d=0.0015,
                                            S0=100, angles=[(0, 0), (90, 0)],
                                            fractions=[50, 50], snr=None)
    asm = ShoreModel(gtab, radial_order=6,
                     zeta=700, lambdaN=1e-8, lambdaL=1e-8)
    # symmetric724
    asmfit = asm.fit(data)
    odf = asmfit.odf(sphere)
    odf_sh = asmfit.odf_sh()
    odf_from_sh = sh_to_sf(odf_sh, sphere, 6, basis_type=None)
    assert_almost_equal(odf, odf_from_sh, 10)


    directions, _ , _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    # 5 subdivisions
    odf = asmfit.odf(sphere2)
    directions, _ , _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        asmfit = asm.fit(data)
        odf = asmfit.odf(sphere2)
        directions, _ , _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)
示例#5
0
def test_mapmri_odf():

    gtab = get_3shell_gtab()
    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    sphere2 = create_unit_sphere(5)
    evals = np.array(([0.0017, 0.0003, 0.0003], [0.0017, 0.0003, 0.0003]))
    data, golden_directions = MultiTensor(gtab,
                                          evals,
                                          S0=1.0,
                                          angles=[(0, 0), (90, 0)],
                                          fractions=[50, 50],
                                          snr=None)
    map_model = MapmriModel(gtab, radial_order=4)
    # symmetric724
    mapfit = map_model.fit(data)
    odf = mapfit.odf(sphere)
    directions, _, _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    # 5 subdivisions
    odf = mapfit.odf(sphere2)
    directions, _, _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(angular_similarity(directions, golden_directions), 2,
                        1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        mapfit = map_model.fit(data)
        odf = mapfit.odf(sphere2)
        directions, _, _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)
示例#6
0
def test_mapmri_odf():

    gtab = get_3shell_gtab()
    # load symmetric 724 sphere
    sphere = get_sphere('symmetric724')

    # load icosahedron sphere
    sphere2 = create_unit_sphere(5)
    evals = np.array(([0.0017, 0.0003, 0.0003],
                      [0.0017, 0.0003, 0.0003]))
    data, golden_directions = MultiTensor(
        gtab, evals, S0=1.0, angles=[(0, 0), (90, 0)], fractions=[50, 50],
        snr=None)
    map_model = MapmriModel(gtab, radial_order=4)
    # symmetric724
    mapfit = map_model.fit(data)
    odf = mapfit.odf(sphere)
    directions, _, _ = peak_directions(odf, sphere, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    # 5 subdivisions
    odf = mapfit.odf(sphere2)
    directions, _, _ = peak_directions(odf, sphere2, .35, 25)
    assert_equal(len(directions), 2)
    assert_almost_equal(
        angular_similarity(directions, golden_directions), 2, 1)

    sb_dummies = sticks_and_ball_dummies(gtab)
    for sbd in sb_dummies:
        data, golden_directions = sb_dummies[sbd]
        mapfit = map_model.fit(data)
        odf = mapfit.odf(sphere2)
        directions, _, _ = peak_directions(odf, sphere2, .35, 25)
        if len(directions) <= 3:
            assert_equal(len(directions), len(golden_directions))
        if len(directions) > 3:
            assert_equal(gfa(odf) < 0.1, True)