def test_odf_sh_to_sharp():
SNR = None
S0 = 1
_, fbvals, fbvecs = get_fnames('small_64D')
bvals, bvecs = read_bvals_bvecs(fbvals, fbvecs)
gtab = gradient_table(bvals, bvecs)
mevals = np.array(([0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]))
S, _ = multi_tensor(gtab,
mevals,
S0,
angles=[(10, 0), (100, 0)],
fractions=[50, 50],
snr=SNR)
sphere = default_sphere
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
qb = QballModel(gtab, sh_order=8, assume_normed=True)
qbfit = qb.fit(S)
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
odf_gt = qbfit.odf(sphere)
Z = np.linalg.norm(odf_gt)
odfs_gt = np.zeros((3, 1, 1, odf_gt.shape[0]))
odfs_gt[:, :, :] = odf_gt[:]
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
odfs_sh = sf_to_sh(odfs_gt, sphere, sh_order=8, basis_type=None)
odfs_sh /= Z
with warnings.catch_warnings():
warnings.filterwarnings("ignore",
message=descoteaux07_legacy_msg,
category=PendingDeprecationWarning)
fodf_sh = odf_sh_to_sharp(odfs_sh,
sphere,
basis=None,
ratio=3 / 15.,
sh_order=8,
lambda_=1.,
tau=0.1)
fodf = sh_to_sf(fodf_sh, sphere, sh_order=8, basis_type=None)
directions2, _, _ = peak_directions(fodf[0, 0, 0], sphere)
assert_equal(directions2.shape[0], 2)
def test_odf_sh_to_sharp():
SNR = 100
S0 = 1
_, fbvals, fbvecs = get_data('small_64D')
bvals = np.load(fbvals)
bvecs = np.load(fbvecs)
gtab = gradient_table(bvals, bvecs)
mevals = np.array(([0.0015, 0.0003, 0.0003], [0.0015, 0.0003, 0.0003]))
S, sticks = multi_tensor(gtab,
mevals,
S0,
angles=[(10, 0), (100, 0)],
fractions=[50, 50],
snr=SNR)
sphere = get_sphere('symmetric724')
qb = QballModel(gtab, sh_order=8, assume_normed=True)
qbfit = qb.fit(S)
odf_gt = qbfit.odf(sphere)
Z = np.linalg.norm(odf_gt)
odfs_gt = np.zeros((3, 1, 1, odf_gt.shape[0]))
odfs_gt[:, :, :] = odf_gt[:]
odfs_sh = sf_to_sh(odfs_gt, sphere, sh_order=8, basis_type=None)
odfs_sh /= Z
fodf_sh = odf_sh_to_sharp(odfs_sh,
sphere,
basis=None,
ratio=3 / 15.,
sh_order=8,
lambda_=1.,
tau=1.)
fodf = sh_to_sf(fodf_sh, sphere, sh_order=8, basis_type=None)
directions2, _, _ = peak_directions(fodf[0, 0, 0], sphere)
assert_equal(directions2.shape[0], 2)
def test_odf_sh_to_sharp():
SNR = None
S0 = 1
_, fbvals, fbvecs = get_data('small_64D')
bvals = np.load(fbvals)
bvecs = np.load(fbvecs)
gtab = gradient_table(bvals, bvecs)
mevals = np.array(([0.0015, 0.0003, 0.0003],
[0.0015, 0.0003, 0.0003]))
S, sticks = multi_tensor(gtab, mevals, S0, angles=[(10, 0), (100, 0)],
fractions=[50, 50], snr=SNR)
sphere = get_sphere('symmetric724')
qb = QballModel(gtab, sh_order=8, assume_normed=True)
qbfit = qb.fit(S)
odf_gt = qbfit.odf(sphere)
Z = np.linalg.norm(odf_gt)
odfs_gt = np.zeros((3, 1, 1, odf_gt.shape[0]))
odfs_gt[:,:,:] = odf_gt[:]
odfs_sh = sf_to_sh(odfs_gt, sphere, sh_order=8, basis_type=None)
odfs_sh /= Z
fodf_sh = odf_sh_to_sharp(odfs_sh, sphere, basis=None, ratio=3 / 15.,
sh_order=8, lambda_=1., tau=0.1)
fodf = sh_to_sf(fodf_sh, sphere, sh_order=8, basis_type=None)
directions2, _, _ = peak_directions(fodf[0, 0, 0], sphere)
assert_equal(directions2.shape[0], 2)
def qball(gtab, data, name, sh_order=4):
qballmodel = QballModel(gtab, sh_order)
data_small = data[:, :, 39:40]
qball_fit = qballmodel.fit(data_small)
qball_odf = qball_fit.odf(default_sphere)
odf_spheres = actor.odf_slicer(qball_odf,
sphere=default_sphere,
scale=0.9,
norm=False,
colormap='plasma')
ren = window.Scene()
ren.add(odf_spheres)
print('Saving illustration as qball_odfs_{}.png'.format(
name)) #data.shape[-1] - 1))
window.record(ren,
out_path='results/qball_odfs_{}.png'.format(name),
size=(600, 600))
return qball_odf, qball_fit.shm_coeff
csamodel = CsaOdfModel(gtab, 4, smooth=0.006)
csa_fit = csamodel.fit(data_small)
sphere = get_sphere('symmetric724')
csa_odf = csa_fit.odf(sphere)
gfa_csa = gfa(csa_odf)
odfs = csa_odf.clip(0)
gfa_csa_wo_zeros = gfa(odfs)
csa_mm = minmax_normalize(odfs)
gfa_csa_mm = gfa(csa_mm)
qballmodel = QballModel(gtab, 6, smooth=0.006)
qball_fit = qballmodel.fit(data_small)
qball_odf = qball_fit.odf(sphere)
gfa_qball = gfa(qball_odf)
gfa_qball_mm = gfa(minmax_normalize(qball_odf))
print 'Saving GFAs...'
nib.save(nib.Nifti1Image(gfa_qball.astype('float32'), affine), 'gfa.nii.gz')
nib.save(nib.Nifti1Image(gfa_qball_mm.astype('float32'), affine), 'gfa_mm.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa.astype('float32'), affine), 'gfa_csa.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa_wo_zeros.astype('float32'), affine), 'gfa_csa_wo_neg.nii.gz')
nib.save(nib.Nifti1Image(gfa_csa_mm.astype('float32'), affine), 'gfa_csa_mm.nii.gz')
coeff = csa_fit._shm_coef
nib.save(nib.Nifti1Image(coeff.astype('float32'), affine), 'csa_odf_sh.nii.gz')
sphere = get_sphere('symmetric724')
odfs = sh_to_sf(coeff[20:50,55:85, 38:39], sphere, order)
if vizu :
from dipy.viz import fvtk
r = fvtk.ren()
fvtk.add(r, fvtk.sphere_funcs(odfs, sphere, colormap='jet'))
fvtk.show(r)
fvtk.clear(r)
qballmodel = QballModel(gtab, order, smooth=0.006)
print 'Computing the QBALL odf...'
qballfit = qballmodel.fit(data)
coeff = qballfit._shm_coef
#GFA = qballfit.gfa
# dipy 0.6 compatible
GFA = np.sqrt(1.0 - (coeff[:,:,:,0] ** 2 / ( np.sum(np.square(coeff), axis=3) ) ) )
GFA[np.isnan(GFA)] = 0
nib.save(nib.Nifti1Image(GFA.astype('float32'), affine), 'gfa_qball.nii.gz')
nib.save(nib.Nifti1Image(coeff.astype('float32'), affine), 'qball_odf_sh.nii.gz')
if vizu :
odfs = sh_to_sf(coeff[20:50,55:85, 38:39], sphere, order)
fvtk.add(r, fvtk.sphere_funcs(odfs, sphere, colormap='jet'))
fvtk.show(r)
fvtk.clear(r)
