def tracking(pam_files, stopping_files, seeding_files):
# define inputs
tracking_method = 'eudx' #"deterministic"
stopping_thr = 0.1 # dropped from 0.2
# define outputs
import os
out_tractogram = os.path.abspath('tractogram.trk')
# import and run tractography algorithm
from dipy.workflows.tracking import LocalFiberTrackingPAMFlow
track_local = LocalFiberTrackingPAMFlow()
track_local.run(pam_files, stopping_files, seeding_files,
stopping_thr=stopping_thr,
seed_density=1,
tracking_method=tracking_method,
pmf_threshold=0.1,
max_angle=30.,
out_dir='',
out_tractogram=out_tractogram)
return out_tractogram
def test_local_fiber_tracking_workflow():
with TemporaryDirectory() as out_dir:
data_path, bval_path, bvec_path = get_fnames('small_64D')
vol_img = nib.load(data_path)
volume = vol_img.get_data()
mask = np.ones_like(volume[:, :, :, 0])
mask_img = nib.Nifti1Image(mask.astype(np.uint8), vol_img.affine)
mask_path = join(out_dir, 'tmp_mask.nii.gz')
nib.save(mask_img, mask_path)
reconst_csd_flow = ReconstCSDFlow()
reconst_csd_flow.run(data_path, bval_path, bvec_path, mask_path,
out_dir=out_dir, extract_pam_values=True)
pam_path = reconst_csd_flow.last_generated_outputs['out_pam']
gfa_path = reconst_csd_flow.last_generated_outputs['out_gfa']
# Create seeding mask by thresholding the gfa
mask_flow = MaskFlow()
mask_flow.run(gfa_path, 0.8, out_dir=out_dir)
seeds_path = mask_flow.last_generated_outputs['out_mask']
mask_path = mask_flow.last_generated_outputs['out_mask']
# Put identity in gfa path to prevent impossible to use
# local tracking because of affine containing shearing.
gfa_img = nib.load(gfa_path)
save_nifti(gfa_path, gfa_img.get_data(), np.eye(4), gfa_img.header)
# Test tracking with pam no sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
assert_equal(lf_track_pam.get_short_name(), 'track_local')
lf_track_pam.run(pam_path, gfa_path, seeds_path)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with binary tissue classifier
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, mask_path, seeds_path,
use_binary_mask=True)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="eudx")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and deterministic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="deterministic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and probabilistic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="probabilistic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and closest peaks getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="closestpeaks")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test that tracking returns seeds
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="deterministic",
save_seeds=True)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_true(tractogram_has_seeds(tractogram_path))
assert_true(seeds_are_same_space_as_streamlines(tractogram_path))
def test_local_fiber_tracking_workflow():
with TemporaryDirectory() as out_dir:
data_path, bval_path, bvec_path = get_fnames('small_64D')
vol_img = nib.load(data_path)
volume = vol_img.get_data()
mask = np.ones_like(volume[:, :, :, 0])
mask_img = nib.Nifti1Image(mask.astype(np.uint8), vol_img.affine)
mask_path = join(out_dir, 'tmp_mask.nii.gz')
nib.save(mask_img, mask_path)
reconst_csd_flow = ReconstCSDFlow()
reconst_csd_flow.run(data_path, bval_path, bvec_path, mask_path,
out_dir=out_dir, extract_pam_values=True)
pam_path = reconst_csd_flow.last_generated_outputs['out_pam']
gfa_path = reconst_csd_flow.last_generated_outputs['out_gfa']
# Create seeding mask by thresholding the gfa
mask_flow = MaskFlow()
mask_flow.run(gfa_path, 0.8, out_dir=out_dir)
seeds_path = mask_flow.last_generated_outputs['out_mask']
# Put identity in gfa path to prevent impossible to use
# local tracking because of affine containing shearing.
gfa_img = nib.load(gfa_path)
save_nifti(gfa_path, gfa_img.get_data(), np.eye(4), gfa_img.header)
# Test tracking with pam no sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
assert_equal(lf_track_pam.get_short_name(), 'track_local')
lf_track_pam.run(pam_path, gfa_path, seeds_path)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="eudx")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and deterministic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="deterministic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and probabilistic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="probabilistic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and closestpeaks getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, gfa_path, seeds_path,
tracking_method="closestpeaks")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
def test_local_fiber_tracking_workflow():
with TemporaryDirectory() as out_dir:
data_path, bval_path, bvec_path = get_fnames('small_64D')
volume, affine = load_nifti(data_path)
mask = np.ones_like(volume[:, :, :, 0], dtype=np.uint8)
mask_path = join(out_dir, 'tmp_mask.nii.gz')
save_nifti(mask_path, mask, affine)
reconst_csd_flow = ReconstCSDFlow()
reconst_csd_flow.run(data_path,
bval_path,
bvec_path,
mask_path,
out_dir=out_dir,
extract_pam_values=True)
pam_path = reconst_csd_flow.last_generated_outputs['out_pam']
gfa_path = reconst_csd_flow.last_generated_outputs['out_gfa']
# Create seeding mask by thresholding the gfa
mask_flow = MaskFlow()
mask_flow.run(gfa_path, 0.8, out_dir=out_dir)
seeds_path = mask_flow.last_generated_outputs['out_mask']
mask_path = mask_flow.last_generated_outputs['out_mask']
gfa_img, gfa_affine = load_nifti(gfa_path)
save_nifti(gfa_path, gfa_img, gfa_affine)
# Test tracking with pam no sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
assert_equal(lf_track_pam.get_short_name(), 'track_local')
lf_track_pam.run(pam_path, gfa_path, seeds_path)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with binary stopping criterion
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path, mask_path, seeds_path, use_binary_mask=True)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path,
gfa_path,
seeds_path,
tracking_method="eudx")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and deterministic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path,
gfa_path,
seeds_path,
tracking_method="deterministic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and probabilistic getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path,
gfa_path,
seeds_path,
tracking_method="probabilistic")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test tracking with pam with sh and closest peaks getter
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path,
gfa_path,
seeds_path,
tracking_method="closestpeaks")
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_false(is_tractogram_empty(tractogram_path))
# Test that tracking returns seeds
lf_track_pam = LocalFiberTrackingPAMFlow()
lf_track_pam._force_overwrite = True
lf_track_pam.run(pam_path,
gfa_path,
seeds_path,
tracking_method="deterministic",
save_seeds=True)
tractogram_path = \
lf_track_pam.last_generated_outputs['out_tractogram']
assert_true(tractogram_has_seeds(tractogram_path))
assert_true(seeds_are_same_space_as_streamlines(tractogram_path))