Exemplo n.º 1
0
def _get_direction_getter(args, mask_data):
    sh_data = nib.load(args.sh_file).get_data().astype('float64')
    sphere = HemiSphere.from_sphere(get_sphere(args.sphere))
    theta = get_theta(args.theta, args.algo)

    if args.algo in ['det', 'prob']:
        if args.algo == 'det':
            dg_class = DeterministicMaximumDirectionGetter
        else:
            dg_class = ProbabilisticDirectionGetter
        return dg_class.from_shcoeff(shcoeff=sh_data,
                                     max_angle=theta,
                                     sphere=sphere,
                                     basis_type=args.sh_basis,
                                     relative_peak_threshold=args.sf_threshold)

    # Code for type EUDX. We don't use peaks_from_model
    # because we want the peaks from the provided sh.
    sh_shape_3d = sh_data.shape[:-1]
    npeaks = 5
    peak_dirs = np.zeros((sh_shape_3d + (npeaks, 3)))
    peak_values = np.zeros((sh_shape_3d + (npeaks, )))
    peak_indices = np.full((sh_shape_3d + (npeaks, )), -1, dtype='int')
    b_matrix = get_b_matrix(find_order_from_nb_coeff(sh_data), sphere,
                            args.sh_basis)

    for idx in np.ndindex(sh_shape_3d):
        if not mask_data[idx]:
            continue

        directions, values, indices = get_maximas(sh_data[idx], sphere,
                                                  b_matrix, args.sf_threshold,
                                                  0)
        if values.shape[0] != 0:
            n = min(npeaks, values.shape[0])
            peak_dirs[idx][:n] = directions[:n]
            peak_values[idx][:n] = values[:n]
            peak_indices[idx][:n] = indices[:n]

    dg = PeaksAndMetrics()
    dg.sphere = sphere
    dg.peak_dirs = peak_dirs
    dg.peak_values = peak_values
    dg.peak_indices = peak_indices
    dg.ang_thr = theta
    dg.qa_thr = args.sf_threshold
    return dg
Exemplo n.º 2
0
def test_io_save_peaks_error():
    with InTemporaryDirectory():
        fname = 'test.pam5'

        pam = PeaksAndMetrics()

        npt.assert_raises(IOError, save_peaks, 'test.pam', pam)
        npt.assert_raises(ValueError, save_peaks, fname, pam)

        pam.affine = np.eye(4)
        pam.peak_dirs = np.random.rand(10, 10, 10, 5, 3)
        pam.peak_values = np.zeros((10, 10, 10, 5))
        pam.peak_indices = np.zeros((10, 10, 10, 5))
        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        pam.sphere = default_sphere
        pam.B = np.zeros((45, default_sphere.vertices.shape[0]))
        pam.total_weight = 0.5
        pam.ang_thr = 60
        pam.gfa = np.zeros((10, 10, 10))
        pam.qa = np.zeros((10, 10, 10, 5))
        pam.odf = np.zeros((10, 10, 10, default_sphere.vertices.shape[0]))
Exemplo n.º 3
0
def test_io_save_peaks_error():
    with InTemporaryDirectory():
        fname = 'test.pam5'

        pam = PeaksAndMetrics()

        npt.assert_raises(IOError, save_peaks, 'test.pam', pam)
        npt.assert_raises(ValueError, save_peaks, fname, pam)

        sphere = get_sphere('repulsion724')

        pam.affine = np.eye(4)
        pam.peak_dirs = np.random.rand(10, 10, 10, 5, 3)
        pam.peak_values = np.zeros((10, 10, 10, 5))
        pam.peak_indices = np.zeros((10, 10, 10, 5))
        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        pam.sphere = sphere
        pam.B = np.zeros((45, sphere.vertices.shape[0]))
        pam.total_weight = 0.5
        pam.ang_thr = 60
        pam.gfa = np.zeros((10, 10, 10))
        pam.qa = np.zeros((10, 10, 10, 5))
        pam.odf = np.zeros((10, 10, 10, sphere.vertices.shape[0]))
Exemplo n.º 4
0
def test_io_peaks():
    with InTemporaryDirectory():
        fname = 'test.pam5'

        pam = PeaksAndMetrics()
        pam.affine = np.eye(4)
        pam.peak_dirs = np.random.rand(10, 10, 10, 5, 3)
        pam.peak_values = np.zeros((10, 10, 10, 5))
        pam.peak_indices = np.zeros((10, 10, 10, 5))
        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        pam.sphere = default_sphere
        pam.B = np.zeros((45, default_sphere.vertices.shape[0]))
        pam.total_weight = 0.5
        pam.ang_thr = 60
        pam.gfa = np.zeros((10, 10, 10))
        pam.qa = np.zeros((10, 10, 10, 5))
        pam.odf = np.zeros((10, 10, 10, default_sphere.vertices.shape[0]))

        save_peaks(fname, pam)
        pam2 = load_peaks(fname, verbose=True)
        npt.assert_array_equal(pam.peak_dirs, pam2.peak_dirs)

        pam2.affine = None

        fname2 = 'test2.pam5'
        save_peaks(fname2, pam2, np.eye(4))
        pam2_res = load_peaks(fname2, verbose=True)
        npt.assert_array_equal(pam.peak_dirs, pam2_res.peak_dirs)

        pam3 = load_peaks(fname2, verbose=False)

        for attr in [
                'peak_dirs', 'peak_values', 'peak_indices', 'gfa', 'qa',
                'shm_coeff', 'B', 'odf'
        ]:
            npt.assert_array_equal(getattr(pam3, attr), getattr(pam, attr))

        npt.assert_equal(pam3.total_weight, pam.total_weight)
        npt.assert_equal(pam3.ang_thr, pam.ang_thr)
        npt.assert_array_almost_equal(pam3.sphere.vertices,
                                      pam.sphere.vertices)

        fname3 = 'test3.pam5'
        pam4 = PeaksAndMetrics()
        npt.assert_raises(ValueError, save_peaks, fname3, pam4)

        fname4 = 'test4.pam5'
        del pam.affine
        save_peaks(fname4, pam, affine=None)

        fname5 = 'test5.pkm'
        npt.assert_raises(IOError, save_peaks, fname5, pam)

        pam.affine = np.eye(4)
        fname6 = 'test6.pam5'
        save_peaks(fname6, pam, verbose=True)

        del pam.shm_coeff
        save_peaks(fname6, pam, verbose=False)

        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        del pam.odf
        save_peaks(fname6, pam)
        pam_tmp = load_peaks(fname6, True)
        npt.assert_equal(pam_tmp.odf, None)

        fname7 = 'test7.paw'
        npt.assert_raises(IOError, load_peaks, fname7)

        del pam.shm_coeff
        save_peaks(fname6, pam, verbose=True)

        fname_shm = 'shm.nii.gz'
        fname_dirs = 'dirs.nii.gz'
        fname_values = 'values.nii.gz'
        fname_indices = 'indices.nii.gz'
        fname_gfa = 'gfa.nii.gz'

        pam.shm_coeff = np.ones((10, 10, 10, 45))
        peaks_to_niftis(pam,
                        fname_shm,
                        fname_dirs,
                        fname_values,
                        fname_indices,
                        fname_gfa,
                        reshape_dirs=False)

        os.path.isfile(fname_shm)
        os.path.isfile(fname_dirs)
        os.path.isfile(fname_values)
        os.path.isfile(fname_indices)
        os.path.isfile(fname_gfa)
Exemplo n.º 5
0
def load_peaks(fname, verbose=False):
    """ Load a PeaksAndMetrics HDF5 file (PAM5)

    Parameters
    ----------
    fname : string
        Filename of PAM5 file.
    verbose : bool
        Print summary information about the loaded file.

    Returns
    -------
    pam : PeaksAndMetrics object
    """

    if os.path.splitext(fname)[1].lower() != '.pam5':
        raise IOError('This function supports only PAM5 (HDF5) files')

    f = h5py.File(fname, 'r')

    pam = PeaksAndMetrics()

    pamh = f['pam']

    version = f.attrs['version']

    if version != '0.0.1':
        raise IOError('Incorrect PAM5 file version {0}'.format(version,))

    try:
        affine = pamh['affine'][:]
    except KeyError:
        affine = None

    peak_dirs = pamh['peak_dirs'][:]
    peak_values = pamh['peak_values'][:]
    peak_indices = pamh['peak_indices'][:]

    try:
        shm_coeff = pamh['shm_coeff'][:]
    except KeyError:
        shm_coeff = None

    sphere_vertices = pamh['sphere_vertices'][:]

    try:
        odf = pamh['odf'][:]
    except KeyError:
        odf = None

    pam.affine = affine
    pam.peak_dirs = peak_dirs
    pam.peak_values = peak_values
    pam.peak_indices = peak_indices
    pam.shm_coeff = shm_coeff
    pam.sphere = Sphere(xyz=sphere_vertices)
    pam.B = pamh['B'][:]
    pam.total_weight = pamh['total_weight'][:][0]
    pam.ang_thr = pamh['ang_thr'][:][0]
    pam.gfa = pamh['gfa'][:]
    pam.qa = pamh['qa'][:]
    pam.odf = odf

    f.close()

    if verbose:
        print('PAM5 version')
        print(version)
        print('Affine')
        print(pam.affine)
        print('Dirs shape')
        print(pam.peak_dirs.shape)
        print('SH shape')
        if pam.shm_coeff is not None:
            print(pam.shm_coeff.shape)
        else:
            print('None')
        print('ODF shape')
        if pam.odf is not None:
            print(pam.odf.shape)
        else:
            print('None')
        print('Total weight')
        print(pam.total_weight)
        print('Angular threshold')
        print(pam.ang_thr)
        print('Sphere vertices shape')
        print(pam.sphere.vertices.shape)

    return pam
Exemplo n.º 6
0
def test_io_peaks():
    with InTemporaryDirectory():
        fname = 'test.pam5'

        sphere = get_sphere('repulsion724')

        pam = PeaksAndMetrics()
        pam.affine = np.eye(4)
        pam.peak_dirs = np.random.rand(10, 10, 10, 5, 3)
        pam.peak_values = np.zeros((10, 10, 10, 5))
        pam.peak_indices = np.zeros((10, 10, 10, 5))
        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        pam.sphere = sphere
        pam.B = np.zeros((45, sphere.vertices.shape[0]))
        pam.total_weight = 0.5
        pam.ang_thr = 60
        pam.gfa = np.zeros((10, 10, 10))
        pam.qa = np.zeros((10, 10, 10, 5))
        pam.odf = np.zeros((10, 10, 10, sphere.vertices.shape[0]))

        save_peaks(fname, pam)
        pam2 = load_peaks(fname, verbose=True)
        npt.assert_array_equal(pam.peak_dirs, pam2.peak_dirs)

        pam2.affine = None

        fname2 = 'test2.pam5'
        save_peaks(fname2, pam2, np.eye(4))
        pam2_res = load_peaks(fname2, verbose=True)
        npt.assert_array_equal(pam.peak_dirs, pam2_res.peak_dirs)

        pam3 = load_peaks(fname2, verbose=False)

        for attr in ['peak_dirs', 'peak_values', 'peak_indices',
                     'gfa', 'qa', 'shm_coeff', 'B', 'odf']:
            npt.assert_array_equal(getattr(pam3, attr),
                                   getattr(pam, attr))

        npt.assert_equal(pam3.total_weight, pam.total_weight)
        npt.assert_equal(pam3.ang_thr, pam.ang_thr)
        npt.assert_array_almost_equal(pam3.sphere.vertices,
                                      pam.sphere.vertices)

        fname3 = 'test3.pam5'
        pam4 = PeaksAndMetrics()
        npt.assert_raises(ValueError, save_peaks, fname3, pam4)

        fname4 = 'test4.pam5'
        del pam.affine
        save_peaks(fname4, pam, affine=None)

        fname5 = 'test5.pkm'
        npt.assert_raises(IOError, save_peaks, fname5, pam)

        pam.affine = np.eye(4)
        fname6 = 'test6.pam5'
        save_peaks(fname6, pam, verbose=True)

        del pam.shm_coeff
        save_peaks(fname6, pam, verbose=False)

        pam.shm_coeff = np.zeros((10, 10, 10, 45))
        del pam.odf
        save_peaks(fname6, pam)
        pam_tmp = load_peaks(fname6, True)
        npt.assert_equal(pam_tmp.odf, None)

        fname7 = 'test7.paw'
        npt.assert_raises(IOError, load_peaks, fname7)

        del pam.shm_coeff
        save_peaks(fname6, pam, verbose=True)

        fname_shm = 'shm.nii.gz'
        fname_dirs = 'dirs.nii.gz'
        fname_values = 'values.nii.gz'
        fname_indices = 'indices.nii.gz'
        fname_gfa = 'gfa.nii.gz'

        pam.shm_coeff = np.ones((10, 10, 10, 45))
        peaks_to_niftis(pam, fname_shm, fname_dirs, fname_values,
                        fname_indices, fname_gfa, reshape_dirs=False)

        os.path.isfile(fname_shm)
        os.path.isfile(fname_dirs)
        os.path.isfile(fname_values)
        os.path.isfile(fname_indices)
        os.path.isfile(fname_gfa)
Exemplo n.º 7
0
def load_peaks(fname, verbose=False):
    """ Load a PeaksAndMetrics HDF5 file (PAM5)

    Parameters
    ----------
    fname : string
        Filename of PAM5 file.
    verbose : bool
        Print summary information about the loaded file.

    Returns
    -------
    pam : PeaksAndMetrics object
    """

    if os.path.splitext(fname)[1] != '.pam5':
        raise IOError('This function supports only PAM5 (HDF5) files')

    if TABLES_LESS_3_0:
        func_open_file = tables.openFile
    else:
        func_open_file = tables.open_file

    f = func_open_file(fname, 'r')

    pam = PeaksAndMetrics()

    pamh = f.root.pam

    version = f.root.version[0].decode()

    if version != '0.0.1':
        raise IOError('Incorrect PAM5 file version')

    try:
        affine = pamh.affine[:]
    except tables.NoSuchNodeError:
        affine = None

    peak_dirs = pamh.peak_dirs[:]
    peak_values = pamh.peak_values[:]
    peak_indices = pamh.peak_indices[:]

    try:
        shm_coeff = pamh.shm_coeff[:]
    except tables.NoSuchNodeError:
        shm_coeff = None

    sphere_vertices = pamh.sphere_vertices[:]

    try:
        odf = pamh.odf[:]
    except tables.NoSuchNodeError:
        odf = None

    pam.affine = affine
    pam.peak_dirs = peak_dirs
    pam.peak_values = peak_values
    pam.peak_indices = peak_indices
    pam.shm_coeff = shm_coeff
    pam.sphere = Sphere(xyz=sphere_vertices)
    pam.B = pamh.B[:]
    pam.total_weight = pamh.total_weight[:][0]
    pam.ang_thr = pamh.ang_thr[:][0]
    pam.gfa = pamh.gfa[:]
    pam.qa = pamh.qa[:]
    pam.odf = odf

    f.close()

    if verbose:
        print('PAM5 version')
        print(version)
        print('Affine')
        print(pam.affine)
        print('Dirs shape')
        print(pam.peak_dirs.shape)
        print('SH shape')
        if pam.shm_coeff is not None:
            print(pam.shm_coeff.shape)
        else:
            print('None')
        print('ODF shape')
        if pam.odf is not None:
            print(pam.odf.shape)
        else:
            print('None')
        print('Total weight')
        print(pam.total_weight)
        print('Angular threshold')
        print(pam.ang_thr)
        print('Sphere vertices shape')
        print(pam.sphere.vertices.shape)

    return pam
Exemplo n.º 8
0
def load_peaks(fname, verbose=False):
    """ Load a PeaksAndMetrics HDF5 file (PAM5)

    Parameters
    ----------
    fname : string
        Filename of PAM5 file.
    verbose : bool
        Print summary information about the loaded file.

    Returns
    -------
    pam : PeaksAndMetrics object
    """

    if os.path.splitext(fname)[1] != '.pam5':
        raise IOError('This function supports only PAM5 (HDF5) files')

    if TABLES_LESS_3_0:
        func_open_file = tables.openFile
    else:
        func_open_file = tables.open_file

    f = func_open_file(fname, 'r')

    pam = PeaksAndMetrics()

    pamh = f.root.pam

    version = f.root.version[0].decode()

    if version != '0.0.1':
        raise IOError('Incorrect PAM5 file version')

    try:
        affine = pamh.affine[:]
    except tables.NoSuchNodeError:
        affine = None

    peak_dirs = pamh.peak_dirs[:]
    peak_values = pamh.peak_values[:]
    peak_indices = pamh.peak_indices[:]

    try:
        shm_coeff = pamh.shm_coeff[:]
    except tables.NoSuchNodeError:
        shm_coeff = None

    sphere_vertices = pamh.sphere_vertices[:]

    try:
        odf = pamh.odf[:]
    except tables.NoSuchNodeError:
        odf = None

    pam.affine = affine
    pam.peak_dirs = peak_dirs
    pam.peak_values = peak_values
    pam.peak_indices = peak_indices
    pam.shm_coeff = shm_coeff
    pam.sphere = Sphere(xyz=sphere_vertices)
    pam.B = pamh.B[:]
    pam.total_weight = pamh.total_weight[:][0]
    pam.ang_thr = pamh.ang_thr[:][0]
    pam.gfa = pamh.gfa[:]
    pam.qa = pamh.qa[:]
    pam.odf = odf

    f.close()

    if verbose:
        print('PAM5 version')
        print(version)
        print('Affine')
        print(pam.affine)
        print('Dirs shape')
        print(pam.peak_dirs.shape)
        print('SH shape')
        if pam.shm_coeff is not None:
            print(pam.shm_coeff.shape)
        else:
            print('None')
        print('ODF shape')
        if pam.odf is not None:
            print(pam.odf.shape)
        else:
            print('None')
        print('Total weight')
        print(pam.total_weight)
        print('Angular threshold')
        print(pam.ang_thr)
        print('Sphere vertices shape')
        print(pam.sphere.vertices.shape)

    return pam
def _get_direction_getter(args):
    odf_data = nib.load(args.in_odf).get_fdata(dtype=np.float32)
    sphere = HemiSphere.from_sphere(get_sphere(args.sphere))
    theta = get_theta(args.theta, args.algo)

    non_zeros_count = np.count_nonzero(np.sum(odf_data, axis=-1))
    non_first_val_count = np.count_nonzero(np.argmax(odf_data, axis=-1))

    if args.algo in ['det', 'prob']:
        if non_first_val_count / non_zeros_count > 0.5:
            logging.warning('Input detected as peaks. Input should be'
                            'fodf for det/prob, verify input just in case.')
        if args.algo == 'det':
            dg_class = DeterministicMaximumDirectionGetter
        else:
            dg_class = ProbabilisticDirectionGetter
        return dg_class.from_shcoeff(
            shcoeff=odf_data, max_angle=theta, sphere=sphere,
            basis_type=args.sh_basis,
            relative_peak_threshold=args.sf_threshold)
    elif args.algo == 'eudx':
        # Code for type EUDX. We don't use peaks_from_model
        # because we want the peaks from the provided sh.
        odf_shape_3d = odf_data.shape[:-1]
        dg = PeaksAndMetrics()
        dg.sphere = sphere
        dg.ang_thr = theta
        dg.qa_thr = args.sf_threshold

        # Heuristic to find out if the input are peaks or fodf
        # fodf are always around 0.15 and peaks around 0.75
        if non_first_val_count / non_zeros_count > 0.5:
            logging.info('Input detected as peaks.')
            nb_peaks = odf_data.shape[-1] // 3
            slices = np.arange(0, 15+1, 3)
            peak_values = np.zeros(odf_shape_3d+(nb_peaks,))
            peak_indices = np.zeros(odf_shape_3d+(nb_peaks,))

            for idx in np.argwhere(np.sum(odf_data, axis=-1)):
                idx = tuple(idx)
                for i in range(nb_peaks):
                    peak_values[idx][i] = np.linalg.norm(
                        odf_data[idx][slices[i]:slices[i+1]], axis=-1)
                    peak_indices[idx][i] = sphere.find_closest(
                        odf_data[idx][slices[i]:slices[i+1]])

            dg.peak_dirs = odf_data
        else:
            logging.info('Input detected as fodf.')
            npeaks = 5
            peak_dirs = np.zeros((odf_shape_3d + (npeaks, 3)))
            peak_values = np.zeros((odf_shape_3d + (npeaks, )))
            peak_indices = np.full((odf_shape_3d + (npeaks, )), -1, dtype='int')
            b_matrix = get_b_matrix(
                find_order_from_nb_coeff(odf_data), sphere, args.sh_basis)

            for idx in np.argwhere(np.sum(odf_data, axis=-1)):
                idx = tuple(idx)
                directions, values, indices = get_maximas(odf_data[idx],
                                                          sphere, b_matrix,
                                                          args.sf_threshold, 0)
                if values.shape[0] != 0:
                    n = min(npeaks, values.shape[0])
                    peak_dirs[idx][:n] = directions[:n]
                    peak_values[idx][:n] = values[:n]
                    peak_indices[idx][:n] = indices[:n]

            dg.peak_dirs = peak_dirs

        dg.peak_values = peak_values
        dg.peak_indices = peak_indices

        return dg